Search results for: food processing industry

Authors: Boris Nemzer, Nebiyu Abshiru, Z. B. Pietrzkowski

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Coffee cherry is one of the most ubiquitous agricultural commodities which possess nutritional and human health beneficial properties. Between the two most widely used coffee cherries Coffea arabica (Arabica) and Coffea canephora (Robusta), Coffea arabica remains superior due to its sensory properties and, therefore, remains in great demand in the global coffee market. In this study, the phytochemical contents and pharmacokinetics of Coffeeberry® Energy (CBE), a commercially available Arabica whole coffee fruit caffeine extract, are investigated. For phytochemical screening, 20 mg of CBE was dissolved in an aqueous methanol solution for analysis by mass spectrometry (MS). Quantification of caffeine and chlorogenic acids (CGAs) contents of CBE was performed using HPLC. For the bioavailability study, serum samples were collected from human subjects before and after 1, 2 and 3 h post-ingestion of 150mg CBE extract. Protein precipitation and extraction were carried out using methanol. Identification of compounds was performed using an untargeted metabolomic approach on Q-Exactive Orbitrap MS coupled to reversed-phase chromatography. Data processing was performed using Thermo Scientific Compound Discover 3.3 software. Phytochemical screening identified a total of 170 compounds, including organic acids, phenolic acids, CGAs, diterpenoids and hydroxytryptamine. Caffeine & CGAs make up more than, respectively, 70% & 9% of the total CBE composition. For serum samples, a total of 82 metabolites representing 32 caffeine- and 50 phenolic-derived metabolites were identified. Volcano plot analysis revealed 32 differential metabolites (24 caffeine- and 8 phenolic-derived) that showed an increase in serum level post-CBE dosing. Caffeine, uric acid, and trimethyluric acid isomers exhibited 4- to 10-fold increase in serum abundance post-dosing. 7-Methyluric acid, 1,7-dimethyluric acid, paraxanthine and theophylline exhibited a minimum of 1.5-fold increase in serum level. Among the phenolic-derived metabolites, iso-feruloyl quinic acid isomers (3-, 4- and 5-iFQA) showed the highest increase in serum level. These compounds were essentially absent in serum collected before dosage. More interestingly, the iFQA isomers were not originally present in the CBE extract, as our phytochemical screen did not identify these compounds. This suggests the potential formation of the isomers during the digestion and absorption processes. Pharmacokinetics parameters (Cmax, Tmax and AUC0-3h) of caffeine- and phenolic-derived metabolites were also investigated. Caffeine was rapidly absorbed, reaching a maximum concentration (Cmax) of 10.95 µg/ml in just 1 hour. Thereafter, caffeine level steadily dropped from the peak level, although it did not return to baseline within the 3-hour dosing period. The disappearance of caffeine from circulation was mirrored by the rise in the concentration of its methylxanthine metabolites. Similarly, serum concentration of iFQA isomers steadily increased, reaching maximum (Cmax: 3-iFQA, 1.54 ng/ml; 4-iFQA, 2.47 ng/ml; 5-iFQA, 2.91 ng/ml) at tmax of 1.5 hours. The isomers remained well above the baseline during the 3-hour dosing period, allowing them to remain in circulation long enough for absorption into the body. Overall, the current study provides evidence of the potential health benefits of a uniquely formulated whole coffee fruit product. Consumption of this product resulted in a distinct serum profile of bioactive compounds, as demonstrated by the more than 32 metabolites that exhibited a significant change in systemic exposure.

Keywords: phytochemicals, mass spectrometry, pharmacokinetics, differential metabolites, chlorogenic acids

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Authors: Benjamin Thomas Greer, Grace Cotulla, Mandy Johnson

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Human trafficking is one of the fastest growing international crimes and human rights violations in the world. The United States Department of State (State Department) approximates some 800,000 to 900,000 people are annually trafficked across sovereign borders, with approximately 14,000 to 17,500 of these people coming into the United States. Today’s slavery is conducted by unscrupulous individuals who are often connected to organized criminal enterprises and transnational gangs, extracting huge monetary sums. According to the International Labour Organization (ILO), human traffickers collect approximately $32 billion worldwide annually. Surpassed only by narcotics dealing, trafficking of humans is tied with illegal arms sales as the second largest criminal industry in the world and is the fastest growing field in the 21st century. Perpetrators of this heinous crime abound. They are not limited to single or “sole practitioners” of human trafficking, but rather, often include Transnational Criminal Organizations (TCO), domestic street gangs, labor contractors, and otherwise seemingly ordinary citizens. Monetary gain is being elevated over territorial disputes and street gangs are increasingly operating in a collaborative effort with TCOs to further disguise their criminal activity; to utilizing their vast networks, in an attempt to avoid detection. Traffickers rely on a network of clandestine routes to sell their commodities with impunity. As law enforcement agencies seek to retard the expansion of transnational criminal organization’s entry into human trafficking, it is imperative that they develop reliable trafficking mapping of known exploitative routes. In a recent report given to the Mexican Congress, The Procuraduría General de la República (PGR) disclosed, from 2008 to 2010 they had identified at least 47 unique criminal networking routes used to traffic victims and that Mexico’s estimated domestic victims number between 800,000 adults and 20,000 children annually. Designing a reliable mapping system is a crucial step to effective law enforcement response and deploying a successful victim support system. Creating this mapping analytic is exceedingly difficult. Traffickers are constantly changing the way they traffic and exploit their victims. They swiftly adapt to local environmental factors and react remarkably well to market demands, exploiting limitations in the prevailing laws. This article will highlight how human trafficking has become one of the fastest growing and most high profile human rights violations in the world today; compile current efforts to map and illustrate trafficking routes; and will demonstrate how the proprietary analytical mapping analysis of point-source and destination-source mapping can help local law enforcement, governmental agencies and victim services providers effectively respond to the type and nature of trafficking to their specific geographical locale. Trafficking transcends state and international borders. It demands an effective and consistent cooperation between local, state, and federal authorities. Each region of the world has different impact factors which create distinct challenges for law enforcement and victim services. Our mapping system lays the groundwork for a targeted anti-trafficking response.

Keywords: human trafficking, mapping, routes, law enforcement intelligence

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Authors: Loreta Serniene, Dalia Sekmokiene, Justina Tomkeviciute, Lina Lauciene, Vaida Andruleviciute, Ingrida Sinkeviciene, Kristina Kondrotiene, Neringa Kasetiene, Mindaugas Malakauskas

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One of the most important areas of product development and research in the dairy industry is the product enrichment with active ingredients as well as leading to increased product safety and sustainability. The most expanding field of the active ingredients is the various plants' CO₂ extracts with aromatic, antioxidant and antimicrobial properties. In this study, 15 plant extracts were evaluated based on their antioxidant, antimicrobial properties as well as sensory acceptance indicators for the development of new dairy products. In order to increase the total antioxidant capacity of the milk products, it was important to determine the content of phenolic compounds and antioxidant activity of CO₂ extract. The total phenolic content of fifteen different commercial CO₂ extracts was determined by the Folin-Ciocalteu reagent and expressed as milligrams of the Gallic acid equivalents (GAE) in gram of extract. The antioxidant activities were determined by 2.2′-azinobis-(3-ethylbenzthiazoline)-6-sulfonate (ABTS) methods. The study revealed that the antioxidant activities of investigated CO₂ extract vary from 4.478-62.035 µmole Trolox/g, while the total phenolic content was in the range of 2.021-38.906 mg GAE/g of extract. For the example, the estimated antioxidant activity of Chinese cinnamon (Cinammonum aromaticum) CO₂ extract was 62.023 ± 0.15 µmole Trolox/g and the total flavonoid content reached 17.962 ± 0.35 mg GAE/g. These two parameters suggest that cinnamon could be a promising supplement for the development of new cheese. The inhibitory effects of these essential oils were tested by using agar disc diffusion method against pathogenic bacteria, most commonly found in dairy products. The obtained results showed that essential oil of lemon myrtle (Backhousia citriodora) and cinnamon (Cinnamomum cassia) has antimicrobial activity against E. coli, S. aureus, B. cereus, P. florescens, L. monocytogenes, Br. thermosphacta, P. aeruginosa and S. typhimurium with the diameter of inhibition zones variation from 10 to 52 mm. The sensory taste acceptability of plant extracts in combination with a dairy product was evaluated by a group of sensory evaluation experts (31 individuals) by the criteria of overall taste acceptability in the scale of 0 (not acceptable) to 10 (very acceptable). Each of the tested samples included 200g grams of natural unsweetened greek yogurt without additives and 1 drop of single plant extract (essential oil). The highest average of overall taste acceptability was defined for the samples with essential oils of orange (Citrus sinensis) - average score 6.67, lemon myrtle (Backhousia citriodora) – 6.62, elderberry flower (Sambucus nigra flos.) – 6.61, lemon (Citrus limon) – 5.75 and cinnamon (Cinnamomum cassia) – 5.41, respectively. The results of this study indicate plant extracts of Cinnamomum cassia and Backhousia citriodora as a promising additive not only to increase the total antioxidant capacity of the milk products and as alternative antibacterial agent to combat pathogenic bacteria commonly found in dairy products but also as a desirable flavour for the taste pallet of the consumers with expressed need for safe, sustainable and innovative dairy products. Acknowledgment: This research was funded by the European Regional Development Fund according to the supported activity 'Research Projects Implemented by World-class Researcher Groups' under Measure No. 01.2.2-LMT-K-718.

Keywords: antioxidant properties, antimicrobial properties, cinnamon, CO₂ plant extracts, dairy products, essential oils, lemon myrtle

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Authors: Asma Omri, Iheb Sifaoui, Sofiane Sayahi, Hichem Besbes

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Future vehicle systems demand advanced capabilities, notably in-cabin life detection and driver monitoring systems, with a particular emphasis on drowsiness detection. To meet these requirements, several techniques employ artificial intelligence methods based on real-time vital sign measurements. In parallel, Frequency-Modulated Continuous-Wave (FMCW) radar technology has garnered considerable attention in the domains of healthcare and biomedical engineering for non-invasive vital sign monitoring. FMCW radar offers a multitude of advantages, including its non-intrusive nature, continuous monitoring capacity, and its ability to penetrate through clothing. In this paper, we propose a system utilizing the AWR6843AOP radar from Texas Instruments (TI) to extract precise vital sign information. The radar allows us to estimate Ballistocardiogram (BCG) signals, which capture the mechanical movements of the body, particularly the ballistic forces generated by heartbeats and respiration. These signals are rich sources of information about the cardiac cycle, rendering them suitable for heart rate estimation. The process begins with real-time subject positioning, followed by clutter removal, computation of Doppler phase differences, and the use of various filtering methods to accurately capture subtle physiological movements. To address the challenges associated with FMCW radar-based vital sign monitoring, including motion artifacts due to subjects' movement or radar micro-vibrations, Long Short-Term Memory (LSTM) networks are implemented. LSTM's adaptability to different heart rate patterns and ability to handle real-time data make it suitable for continuous monitoring applications. Several crucial steps were taken, including feature extraction (involving amplitude, time intervals, and signal morphology), sequence modeling, heart rate estimation through the analysis of detected cardiac cycles and their temporal relationships, and performance evaluation using metrics such as Root Mean Square Error (RMSE) and correlation with reference heart rate measurements. For dataset construction and LSTM training, a comprehensive data collection system was established, integrating the AWR6843AOP radar, a Heart Rate Belt, and a smart watch for ground truth measurements. Rigorous synchronization of these devices ensured data accuracy. Twenty participants engaged in various scenarios, encompassing indoor and real-world conditions within a moving vehicle equipped with the radar system. Static and dynamic subject’s conditions were considered. The heart rate estimation through LSTM outperforms traditional signal processing techniques that rely on filtering, Fast Fourier Transform (FFT), and thresholding. It delivers an average accuracy of approximately 91% with an RMSE of 1.01 beat per minute (bpm). In conclusion, this paper underscores the promising potential of FMCW radar technology integrated with artificial intelligence algorithms in the context of automotive applications. This innovation not only enhances road safety but also paves the way for its integration into the automotive ecosystem to improve driver well-being and overall vehicular safety.

Keywords: ballistocardiogram, FMCW Radar, vital sign monitoring, LSTM

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Authors: Nkechi V. Enwuru, Bullum Nkeki, Elizabeth A. Adekoya, Olumide A. Adebesin, Rebecca F. Peters, Victoria A. Aikhomu, Mendie E. U.

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Background: Probiotics are live microbial feed supplement beneficial for host. Probiotics and their postbiotic products have been used to prevent or treat various health conditions. However, the products cell viability is often low due to harsh conditions subjected during processing, handling, storage, and gastrointestinal transit. These strongly influence probiotics’ benefits; thus, viability is essential for probiotics to produce health benefits for the host. Microencapsulation is a promising technique with considerable effects on probiotic survival. The study is aimed to formulate a microencapsulated probiotic and evaluate its viability, antimicrobial efficacy, and cytotoxic activity of its postbiotic on the MCF-7 breast cancer cell line. Method: Human and animal raw milk were sampled for lactic acid bacteria. The isolated bacteria were identified using conventional and VITEK 2 systems. The identified lactic acid bacterium was encapsulated using spray-dried and extrusion methods. The free, encapsulated, and chitosan-coated encapsulated probiotics were tested for viability in simulated-gastric intestinal (SGI) fluid and different storage conditions at refrigerated (4oC) and room (25oC) temperatures. The disintegration time and weight uniformity of the spray-dried hard gelatin capsules were tested. The antimicrobial property of free and encapsulated probiotics was tested against enteric pathogenic isolates from antiretroviral therapy (ART) treated HIV-positive patients. The postbiotic of the free cells was extracted, and its cytotoxic effect on the MCF-7 breast cancer cell line was tested through an MTT assay. Result: The Lactobacillus plantarum was isolated from animal raw milk. Zero-size hard gelatin L. plantarum capsules with granules within a size range of 0.71–1.00 mm diameter was formulated. The disintegration time ranges from 2.14±0.045 to 2.91±0.293 minutes, while the average weight is 502.1mg. Simulated gastric solution significantly affected viability of both free and microcapsules. However, the encapsulated cells were more protected and viable due to impermeability in the microcapsules. Furthermore, the viability of free cells stored at 4oC and 25oC were less than 4 log CFU/g and 6 log CFU/g respectively after 12 weeks. However, the microcapsules stored at 4oC achieved the highest viability among the free and microcapsules stored at 25oC and the free cells stored at 4oC. Encapsulated cells were released in the simulated gastric fluid, viable and effective against the enteric pathogens tested. However, chitosan-coated calcium alginate encapsulated probiotics significantly inhibited Shigella flexneri, Candida albicans, and Escherichia coli. The Postbiotic Metabolites (PM) of L. plantarum produced a cytotoxic effect on the MCF-7 breast cancer cell line. The postbiotic showed significant cytotoxic activity similar to 5FU, a standard antineoplastic agent. The inhibition concentration of 50% growth (IC50) of postbiotic metabolite K3 is low and consistent with the IC50 of the positive control (Cisplatin). Conclusions: Lactobacillus plantarum postbiotic exhibited a cytotoxic effect on the MCF-7 breast cancer cell line and could be used as combined adjuvant therapy in breast cancer management. The microencapsulation technique protects the probiotics, improving their viability and delivery to the gastrointestinal tract. Chitosan enhances antibacterial efficacy; thus, chitosan-coated microencapsulated L. plantarum probiotics could be more effective and used as a combined therapy in HIV management of opportunistic enteric infection.

Keywords: probiotics, encapsulation, gastrointestinal conditions, antimicrobial effect, postbiotic, cytotoxicity effect

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Authors: Carly Cummings, Maria Soledad Peresin

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Alabama has a long history of racial injustice and unsatisfactory educational performance. In the 1870s Jim Crow laws segregated public schools and disproportionally allocated funding and resources to white institutions across the South. Despite the Supreme Court ruling to integrate schools following Brown vs. the Board of Education in 1954, Alabama’s school system continued to exhibit signs of segregation, compounded by “white flight” and the establishment of exclusive private schools, which still exist today. This discriminatory history has had a lasting impact of the state’s education system, reflected in modern school demographics and achievement data. It is well known that Alabama struggles with education performance, especially in science education. On average, minority groups scored the lowest in science proficiency. In Alabama, minority populations are concentrated in a region known as the Black Belt, which was once home to countless slave plantations and was the epicenter of the Civil Rights Movement. Today the Black Belt is characterized by a high density of woodlands and plays a significant role in Alabama’s leading economic industry-forest products. Given the economic importance of forestry and agriculture to the state, environmental science proficiency is essential to its stability; however, it is neglected in areas where it is needed most. To better understand the inequity of science education within Alabama, our study first investigates how geographic location, demographics and school funding relate to science achievement scores using ArcGIS and Pearson’s correlation coefficient. Additionally, our study explores the implementation of a relevant, problem-based, active learning lesson in schools. Relevant learning engages students by connecting material to their personal experiences. Problem-based active learning involves real-world problem-solving through hands-on experiences. Given Alabama’s significant woodland coverage, educational materials on forest products were developed with consideration of its relevance to students, especially those located in the Black Belt. Furthermore, to incorporate problem solving and active learning, the lesson centered around students using forest products to solve environmental challenges, such as water pollution- an increasing challenge within the state due to climate change. Pre and post assessment surveys were provided to teachers to measure the effectiveness of the lesson. In addition to pedagogical practices, community and mentorship programs are known to positively impact educational achievements. To this end, our work examines the results of surveys measuring educational professionals’ attitudes toward a local mentorship group within the Black Belt and its potential to address environmental and science literacy. Additionally, our study presents survey results from participants who attended an educational community event, gauging its effectiveness in increasing environmental and science proficiency. Our results demonstrate positive improvements in environmental awareness and science literacy with relevant pedagogy, mentorship, and community involvement. Implementing these practices can help provide equitable and inclusive learning environments and can better equip students with the skills and knowledge needed to bridge this historic educational gap within Alabama.

Keywords: equitable education, environmental science, environmental education, science education, racial injustice, sustainability, rural education

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Authors: Pradipta Chandra, Titas Bhattacharjee, Bhaskar Bhowmick

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The foundation of economy in India is primarily based on agriculture while this is the most neglected in the rural setting. More significantly, household women take part in agriculture with higher involvement. However, because of lower education of women they have limited access towards financial decisions, land ownership and technology but they have vital role towards the individual family level. There are limited studies on the institution-wise training barriers with the focus of gender disparity. The main purpose of this paper is to find out the factors of institution-wise training (non-formal education) barriers in technology transfer with the focus of participation of rural women in agriculture. For this study primary and secondary data were collected in the line of qualitative and quantitative approach. Qualitative data were collected by several field visits in the adjacent areas of Seva-Bharati, Seva Bharati Krishi Vigyan Kendra through semi-structured questionnaires. In the next level detailed field surveys were conducted with close-ended questionnaires scored on the seven-point Likert scale. Sample size was considered as 162. During the data collection the focus was to include women although some biasness from the end of respondents and interviewer might exist due to dissimilarity in observation, views etc. In addition to that the heterogeneity of sample is not very high although female participation is more than fifty percent. Data were analyzed using Exploratory Factor Analysis (EFA) technique with the outcome of three significant factors of training barriers in technology adoption by farmers: (a) Failure of technology transfer training (TTT) comprehension interprets that the technology takers, i.e., farmers can’t understand the technology either language barrier or way of demonstration exhibited by the experts/ trainers. (b) Failure of TTT customization, articulates that the training for individual farmer, gender crop or season-wise is not tailored. (c) Failure of TTT generalization conveys that absence of common training methods for individual trainers for specific crops is more prominent at the community level. The central finding is that the technology transfer training method can’t fulfill the need of the farmers under an economically challenged area. The impact of such study is very high in the area of dry lateritic and resource crunch area of Jangalmahal under Paschim Medinipur district, West Bengal and areas with similar socio-economy. Towards the policy level decision this research may help in framing digital agriculture for implementation of the appropriate information technology for the farming community, effective and timely investment by the government with the selection of beneficiary, formation of farmers club/ farm science club etc. The most important research implication of this study lies upon the contribution towards the knowledge diffusion mechanism of the agricultural sector in India. Farmers may overcome the barriers to achieve higher productivity through adoption of modern farm practices. Corporates will be interested in agro-sector through investment under corporate social responsibility (CSR). The research will help in framing public or industry policy and land use pattern. Consequently, a huge mass of rural farm-women will be empowered and farmer community will be benefitted.

Keywords: dry lateritic zone, institutional barriers, technology transfer in India, farm-women participation

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Authors: Mara Getachew Zenebe, Luuk Fleskens, Abdu Obieda Ahmed

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This paper seeks to advance our scientific understanding of optimizing flood utilization in regions impacted by climate change, with a focus on enhancing agricultural productivity through effective irrigation management. The study was conducted as part of a three-year (2021 to 2023) USAID-supported initiative aimed at promoting Economic Growth and Peace in the Gash Agricultural Scheme (GAS), situated in Sudan's water-stressed Eastern region. GAS is the country's largest flood-irrigated scheme, covering 100,800 hectares of cultivable land, with a potential to provide the food security needs of over a quarter of a million agro-pastoral community members. GAS relies on the Gash River, which sources its water from high-intensity rainfall events in the highlands of Ethiopia and Eritrea. However, climate change and variations in these highlands have led to increased variability in the Gash River's flow. The study conducted water balance analyses based on a ten-year dataset of the annual Gash River flow, irrigated area; as well as the evapotranspiration demand of the major sorghum crop. Data collection methods included field measurements, surveys, remote sensing, and CropWat modelling. The water balance assessment revealed that the existing three-year rotation-based irrigation system management, capping cultivated land at 33,000 hectares annually, is excessively risk-averse. While this system reduced conflicts among the agro-pastoral communities by consistently delivering on the land promised to be annually cultivated, it also increased GAS's vulnerability to flood damage due to several reasons. The irrigation efficiency over the past decade was approximately 30%, leaving significant unharnessed floodwater that caused damage to infrastructure and agricultural land. The three-year rotation resulted in inadequate infrastructural maintenance, given the destructive nature of floods. Additionally, it led to infrequent land tillage, allowing the encroachment of mesquite trees hindering major sorghum crop growth. Remote sensing data confirmed that mesquite trees have overtaken 70,000 hectares in the past two decades, rendering them unavailable for agriculture. The water balance analyses suggest shifting to a two-year rotation, covering approximately 50,000 hectares annually while maintaining risk aversion. This shift could boost GAS's annual sorghum production by two-thirds, exceeding 850,000 tons. The scheme's efficiency can be further enhanced through low-cost on-farm interventions. Currently, large irrigation plots that range from 420 to 756 hectares are irrigated with limited water distribution guidance, leading to uneven irrigation. As demonstrated through field trials, implementing internal longitudinal bunds and horizontal deflector bunds can increase adequately irrigated parts of the irrigation plots from 50% to 80% and thus nearly double the sorghum yield to 2 tons per hectare while reducing the irrigation duration from 30 days to a maximum of 17 days. Flow measurements in 2021 and 2022 confirmed that these changes sufficiently meet the sorghum crop's water requirements, even with a conservative 60% field application efficiency assumption. These insights and lessons from the GAS on enhancing agricultural resilience and sustainability in the face of climate change are relevant to flood-based livelihood systems globally.

Keywords: climate change, irrigation management and productivity, variable flood flows, water balance analysis

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Authors: Daniele Lerede, Gianvito Colucci, Matteo Nicoli, Laura Savoldi

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The European Green Deal is the first internationally agreed set of measures to contrast climate change and environmental degradation. Besides the main target of reducing emissions by at least 55% by 2030, it sets the target of accompanying European countries through an energy transition to make the European Union into a modern, resource-efficient, and competitive net-zero emissions economy by 2050, decoupling growth from the use of resources and ensuring a fair adaptation of all social categories to the transformation process. While the general purpose to allow the realization of the purposes of the Green Deal already dates back to 2019, strategies and policies keep being developed coping with recent circumstances and achievements. However, general long-term measures like the Circular Economy Action Plan, the proposals to shift from fossil natural gas to renewable and low-carbon gases, in particular biomethane and hydrogen, and to end the sale of gasoline and diesel cars by 2035, will all have significant effects on energy supply and demand evolution across the next decades. The interactions between energy supply and demand over long-term time frames are usually assessed via energy system models to derive useful insights for policymaking and to address technological choices and research and development. TEMOA-Europe is a newly developed energy system optimization model instance based on the minimization of the total cost of the system under analysis, adopting a technologically integrated, detailed, and explicit formulation and considering the evolution of the system in partial equilibrium in competitive markets with perfect foresight. TEMOA-Europe is developed on the TEMOA platform, an open-source modeling framework totally implemented in Python, therefore ensuring third-party verification even on large and complex models. TEMOA-Europe is based on a single-region representation of the European Union and EFTA countries on a time scale between 2005 and 2100, relying on a set of assumptions for socio-economic developments based on projections by the International Energy Outlook and a large technological dataset including 7 sectors: the upstream and power sectors for the production of all energy commodities and the end-use sectors, including industry, transport, residential, commercial and agriculture. TEMOA-Europe also includes an updated hydrogen module considering its production, storage, transportation, and utilization. Besides, it can rely on a wide set of innovative technologies, ranging from nuclear fusion and electricity plants equipped with CCS in the power sector to electrolysis-based steel production processes and steel in the industrial sector – with a techno-economic characterization based on public literature – to produce insightful energy scenarios and especially to cope with the very long analyzed time scale. The aim of this work is to examine in detail the scheme of measures and policies for the realization of the purposes of the Green Deal and to transform them into a set of constraints and new socio-economic development pathways. Based on them, TEMOA-Europe will be used to produce and comparatively analyze scenarios to assess the consequences of Green Deal-related measures on the future evolution of the energy mix over the whole energy system in an economic optimization environment.

Keywords: European Green Deal, energy system optimization modeling, scenario analysis, TEMOA-Europe

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Authors: Diogo José Morgado Rebelo, Francisco António Carneiro Pacheco de Andrade, Paulo Jorge Freitas de Oliveira Novais

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Not everything in AI-power consumer credit scoring turns out to be a wonder. When using AI in Creditworthiness Assessment (CWA), opacity and unfairness ‘sins’ must be considered to the task be deemed Responsible. AI software is not always 100% accurate, which can lead to misclassification. Discrimination of some groups can be exponentiated. A hetero personalized identity can be imposed on the individual(s) affected. Also, autonomous CWA sometimes lacks transparency when using black box models. However, for this intended purpose, human analysts ‘on-the-loop’ might not be the best remedy consumers are looking for in credit. This study seeks to explore the legality of implementing a Multi-Agent System (MAS) framework in consumer CWA to ensure compliance with the regulation outlined in Article 14(4) of the Proposal for an Artificial Intelligence Act (AIA), dated 21 April 2021 (as per the last corrigendum by the European Parliament on 19 April 2024), Especially with the adoption of Art. 18(8)(9) of the EU Directive 2023/2225, of 18 October, which will go into effect on 20 November 2026, there should be more emphasis on the need for hybrid oversight in AI-driven scoring to ensure fairness and transparency. In fact, the range of EU regulations on AI-based consumer credit will soon impact the AI lending industry locally and globally, as shown by the broad territorial scope of AIA’s Art. 2. Consequently, engineering the law of consumer’s CWA is imperative. Generally, the proposed MAS framework consists of several layers arranged in a specific sequence, as follows: firstly, the Data Layer gathers legitimate predictor sets from traditional sources; then, the Decision Support System Layer, whose Neural Network model is trained using k-fold Cross Validation, provides recommendations based on the feeder data; the eXplainability (XAI) multi-structure comprises Three-Step-Agents; and, lastly, the Oversight Layer has a 'Bottom Stop' for analysts to intervene in a timely manner. From the analysis, one can assure a vital component of this software is the XAY layer. It appears as a transparent curtain covering the AI’s decision-making process, enabling comprehension, reflection, and further feasible oversight. Local Interpretable Model-agnostic Explanations (LIME) might act as a pillar by offering counterfactual insights. SHapley Additive exPlanation (SHAP), another agent in the XAI layer, could address potential discrimination issues, identifying the contribution of each feature to the prediction. Alternatively, for thin or no file consumers, the Suggestion Agent can promote financial inclusion. It uses lawful alternative sources such as the share of wallet, among others, to search for more advantageous solutions to incomplete evaluation appraisals based on genetic programming. Overall, this research aspires to bring the concept of Machine-Centered Anthropocentrism to the table of EU policymaking. It acknowledges that, when put into service, credit analysts no longer exert full control over the data-driven entities programmers have given ‘birth’ to. With similar explanatory agents under supervision, AI itself can become self-accountable, prioritizing human concerns and values. AI decisions should not be vilified inherently. The issue lies in how they are integrated into decision-making and whether they align with non-discrimination principles and transparency rules.

Keywords: creditworthiness assessment, hybrid oversight, machine-centered anthropocentrism, EU policymaking

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Authors: Michelle C. S. Azevedo, Priscila M. Colavite, Carolina F. Francisconi, Ana P. Trombone, Gustavo P. Garlet

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VIP (vasoactive intestinal peptide) know as a potential protective factor in the view of its marked immunosuppressive properties. In this work, we investigated a possible association of VIP with the clinical status of experimental periapical granulomas and the association with expression markers in the lesions potentially associated with periapical lesions pathogenesis. C57BL/6WT mice were treated or not with recombinant VIP. Animals with active/progressive (N=40), inactive/stable (N=70) periapical granulomas and controls (N=50) were anesthetized and the right mandibular first molar was surgically opened, allowing exposure of dental pulp. Endodontic pathogenic bacterial strains were inoculated: Porphyromonas gingivalis, Prevotella nigrescens, Actinomyces viscosus, and Fusobacterium nucleatum subsp. polymorphum. The cavity was not sealed after bacterial inoculation. During lesion development, animals were treated or not with recombinant VIP 3 days post infection. Animals were killed after 3, 7, 14, and 21 days of infection and the jaws were dissected. The extraction of total RNA from periodontal tissues was performed and the integrity of samples was checked. qPCR reaction using TaqMan chemistry with inventoried primers were performed in ViiA7 equipment. The results, depicted as the relative levels of gene expression, were calculated in reference to GAPDH and β-actin expression. Periodontal tissues from upper molars were vested and incubated supplemented RPMI, followed by processing with 0.05% DNase. Cell viability and couting were determined by Neubauer chamber analysis. For flow cytometry analysis, after cell counting the cells were stained with the optimal dilution of each antibody; (PE)-conjugated and (FITC)-conjugated antibodies against CD4, CD25, FOXP3, IL-4, IL-17 and IFN-γ antibodies, as well their respective isotype controls. Cells were analyzed by FACScan and CellQuest software. Results are presented as the number of cells in the periodontal tissues or the number of positive cells for each marker in the CD4+FOXp3+, CD4+IL-4+, CD4+IFNg+ and CD4+IL-17+ subpopulations. The levels mRNA were measured by qPCR. The VIP expression was predominated in inactive lesions, as well part of the clusters of cytokine/Th markers identified as protective factors and a negative correlation between VIP expression and lesion evolution was observed. A quantitative analysis of IL1β, IL17, TNF, IFN, MMP2, RANKL, OPG, IL10, TGFβ, CTLA4, COL5A1, CTGF, CXCL11, FGF7, ITGA4, ITGA5, SERP1 and VTN expression was measured in experimental periapical lesions treated with VIP 7 and 14 days after lesion induction and healthy animals. After 7 days, all targets presented a significate increase in comparison to untreated animals. About migration kinetics, profile of chemokine receptors expression of TCD4+ subsets and phenotypic analysis of Tregs, Th1, Th2 and Th17 cells during the course of experimental periodontal disease evaluated by flow cytometry and depicted as the number of positive cells for each marker. CD4+IFNg+ and CD4+FOXp3+ cells migration were significate increased 7 days post VIP treatment. CD4+IL17+ cells migration were significate increased 7 and 14 days post VIP treatment, CD4+IL4+ cells migration were significate increased 14 and 21 days post VIP treatment compared to the control group. In conclusion, our experimental data support VIP involvement in determining the inactivity of periapical lesions. Financial support: FAPESP #2015/25618-2.

Keywords: chronic inflammation, cytokines, osteolytic lesions, VIP (Vasoactive Intestinal Peptide)

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Authors: Ling Ai, Ziyu Zhao, Zeyu Zhou, Xiaochen Yang, Heng Zhai, Stuart Holmes

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Optimizing the catalyst layer structure is crucial for enhancing the performance of proton exchange membrane fuel cells (PEMFCs) with low Platinum (Pt) loading. Current works focused on the utilization, durability, and site activity of Pt particles on support, and performance enhancement has been achieved by loading Pt onto porous support with different morphology, such as graphene, carbon fiber, and carbon black. Some schemes have also incorporated cost considerations to achieve lower Pt loading. However, the design of the catalyst layer (CL) structure in the membrane electrode assembly (MEA) must consider the interactions between the layers. Addressing the crucial aspects of water management, low contact resistance, and the establishment of effective three-phase boundary for MEA, multi-walled carbon nanotubes (MWCNTs) are promising CL support due to their intrinsically high hydrophobicity, high axial electrical conductivity, and potential for ordered alignment. However, the drawbacks of MWCNTs, such as strong agglomeration, wall surface chemical inertness, and unopened ends, are unfavorable for Pt nanoparticle loading, which is detrimental to MEA processing and leads to inhomogeneous CL surfaces. This further deteriorates the utilization of Pt and increases the contact resistance. Robust chemical oxidation or nitrogen doping can introduce polar functional groups onto the surface of MWCNTs, facilitating the creation of open tube ends and inducing defects in tube walls. This improves dispersibility and load capacity but reduces length and conductivity. Consequently, a trade-off exists between maintaining the intrinsic properties and the degree of functionalization of MWCNTs. In this work, MWCNTs were modified based on the operational requirements of the MEA from the viewpoint of interlayer interactions, including the search for the optimal degree of oxidation, N-doping, and micro-arrangement. MWCNT were functionalized by oxidizing, N-doping, as well as micro-alignment to achieve lower contact resistance between CL and proton exchange membrane (PEM), better hydrophobicity, and enhanced performance. Furthermore, this work expects to construct a more continuously distributed three-phase boundary by aligning MWCNT to form a locally ordered structure, which is essential for the efficient utilization of Pt active sites. Different from other chemical oxidation schemes that used HNO3:H2SO4 (1:3) mixed acid to strongly oxidize MWCNT, this scheme adopted pure HNO3 to partially oxidize MWCNT at a lower reflux temperature (80 ℃) and a shorter treatment time (0 to 10 h) to preserve the morphology and intrinsic conductivity of MWCNT. The maximum power density of 979.81 mw cm-2 was achieved by Pt loading on 6h MWCNT oxidation time (Pt-MWCNT6h). This represented a 59.53% improvement over the commercial Pt/C catalyst of 614.17 (mw cm-2). In addition, due to the stronger electrical conductivity, the charge transfer resistance of Pt-MWCNT6h in the electrochemical impedance spectroscopy (EIS) test was 0.09 Ohm cm-2, which was 48.86% lower than that of Pt/C. This study will discuss the developed catalysts and their efficacy in a working fuel cell system. This research will validate the impact of low-functionalization modification of MWCNTs on the performance of PEMFC, which simplifies the preparation challenges of CL and contributing for the widespread commercial application of PEMFCs on a larger scale.

Keywords: carbon nanotubes, electrocatalyst, membrane electrode assembly, proton exchange membrane fuel cell

Procedia PDF Downloads 77

Authors: Manon Frédout, Laëtitia Bucari, Mathias Aloui, Gaëtan Duhamel, Olivier Rovellotti, Javier Blanco

Abstract:

Ecosystems must be resilient to ensure cleaner air, better water and soil quality, and thus healthier citizens. Technology can be an excellent tool to support urban ecosystem restoration projects, especially when based on Open Source and promoting Open Data. This is the goal of the ecoTeka application: one single digital tool for tree management which allows decision-makers to improve their urban forestry practices, enabling more responsible urban planning and climate change adaptation. EcoTeka provides city councils with three main functionalities tackling three of their challenges: easier biodiversity inventories, better green space management, and more efficient planning. To answer the cities’ need for reliable tree inventories, the application has been first built with open data coming from the websites OpenStreetMap and OpenTrees, but it will also include very soon the possibility of creating new data. To achieve this, a multi-source algorithm will be elaborated, based on existing artificial intelligence Deep Forest, integrating open-source satellite images, 3D representations from LiDAR, and street views from Mapillary. This data processing will permit identifying individual trees' position, height, crown diameter, and taxonomic genus. To support urban forestry management, ecoTeka offers a dashboard for monitoring the city’s tree inventory and trigger alerts to inform about upcoming due interventions. This tool was co-constructed with the green space departments of the French cities of Alès, Marseille, and Rouen. The third functionality of the application is a decision-making tool for urban planning, promoting biodiversity and landscape connectivity metrics to drive ecosystem restoration roadmap. Based on landscape graph theory, we are currently experimenting with new methodological approaches to scale down regional ecological connectivity principles to local biodiversity conservation and urban planning policies. This methodological framework will couple graph theoretic approach and biological data, mainly biodiversity occurrences (presence/absence) data available on both international (e.g., GBIF), national (e.g., Système d’Information Nature et Paysage) and local (e.g., Atlas de la Biodiversté Communale) biodiversity data sharing platforms in order to help reasoning new decisions for ecological networks conservation and restoration in urban areas. An experiment on this subject is currently ongoing with Montpellier Mediterranee Metropole. These projects and studies have shown that only 26% of tree inventory data is currently geo-localized in France - the rest is still being done on paper or Excel sheets. It seems that technology is not yet used enough to enrich the knowledge city councils have about biodiversity in their city and that existing biodiversity open data (e.g., occurrences, telemetry, or genetic data), species distribution models, landscape graph connectivity metrics are still underexploited to make rational decisions for landscape and urban planning projects. This is the goal of ecoTeka: to support easier inventories of urban biodiversity and better management of urban spaces through rational planning and decisions relying on open databases. Future studies and projects will focus on the development of tools for reducing the artificialization of soils, selecting plant species adapted to climate change, and highlighting the need for ecosystem and biodiversity services in cities.

Keywords: digital software, ecological design of urban landscapes, sustainable urban development, urban ecological corridor, urban forestry, urban planning

Procedia PDF Downloads 73

Authors: Artur Tyliszczak, Ewa Szymanek, Maciej Marek

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Flow through granular materials is important to a vast array of industries, for instance in construction industry where granular layers are used for bulkheads and isolators, in chemical engineering and catalytic reactors where large surfaces of packed granular beds intensify chemical reactions, or in energy production systems, where granulates are promising materials for heat storage and heat transfer media. Despite the common usage of granulates and extensive research performed in this field, phenomena occurring between granular solid elements or between solids and fluid are still not fully understood. In the present work we analyze the heat exchange process between the flowing medium (gas, liquid) and solid material inside the granular layers. We consider them as a composite of isolated solid elements and inter-granular spaces in which a gas or liquid can flow. The structure of the layer is controlled by shapes of particular granular elements (e.g., spheres, cylinders, cubes, Raschig rings), its spatial distribution or effective characteristic dimension (total volume or surface area). We will analyze to what extent alteration of these parameters influences on flow characteristics (turbulent intensity, mixing efficiency, heat transfer) inside the layer and behind it. Analysis of flow inside granular layers is very complicated because the use of classical experimental techniques (LDA, PIV, fibber probes) inside the layers is practically impossible, whereas the use of probes (e.g. thermocouples, Pitot tubes) requires drilling of holes inside the solid material. Hence, measurements of the flow inside granular layers are usually performed using for instance advanced X-ray tomography. In this respect, theoretical or numerical analyses of flow inside granulates seem crucial. Application of discrete element methods in combination with the classical finite volume/finite difference approaches is problematic as a mesh generation process for complex granular material can be very arduous. A good alternative for simulation of flow in complex domains is an immersed boundary-volume penalization (IB-VP) in which the computational meshes have simple Cartesian structure and impact of solid objects on the fluid is mimicked by source terms added to the Navier-Stokes and energy equations. The present paper focuses on application of the IB-VP method combined with large eddy simulation (LES). The flow solver used in this work is a high-order code (SAILOR), which was used previously in various studies, including laminar/turbulent transition in free flows and also for flows in wavy channels, wavy pipes and over various shape obstacles. In these cases a formal order of approximation turned out to be in between 1 and 2, depending on the test case. The current research concentrates on analyses of the flows in dense granular layers with elements distributed in a deterministic regular manner and validation of the results obtained using LES-IB method and body-fitted approach. The comparisons are very promising and show very good agreement. It is found that the size, number of elements and their distribution have huge impact on the obtained results. Ordering of the granular elements (or lack of it) affects both the pressure drop and efficiency of the heat transfer as it significantly changes mixing process.

Keywords: granular layers, heat transfer, immersed boundary method, numerical simulations

Procedia PDF Downloads 138

Authors: Subhash Nerella, Ziyuan Guan, Azra Bihorac, Parisa Rashidi

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Intensive care units (ICUs) provide care to critically ill patients in severe and life-threatening conditions. However, patient monitoring in the ICU is limited by the time and resource constraints imposed on healthcare providers. Many critical care indices such as mobility are still manually assessed, which can be subjective, prone to human errors, and lack granularity. Other important aspects, such as environmental factors, are not monitored at all. For example, critically ill patients often experience circadian disruptions due to the absence of effective environmental “timekeepers” such as the light/dark cycle and the systemic effect of acute illness on chronobiologic markers. Although the occurrence of delirium is associated with circadian disruption risk factors, these factors are not routinely monitored in the ICU. Hence, there is a critical unmet need to develop systems for precise and real-time assessment through novel enabling technologies. We have developed the mobility and circadian disruption quantification system (Mobi-DiQ) by augmenting biomarker and clinical data with pervasive sensing data to generate mobility and circadian cues related to mobility, nightly disruptions, and light and noise exposure. We hypothesize that Mobi-DiQ can provide accurate mobility and circadian cues that correlate with bedside clinical mobility assessments and circadian biomarkers, ultimately important for delirium risk assessment and prevention. The collected multimodal dataset consists of depth images, Electromyography (EMG) data, patient extremity movement captured by accelerometers, ambient light levels, Sound Pressure Level (SPL), and indoor air quality measured by volatile organic compounds, and the equivalent CO₂ concentration. For delirium risk assessment, the system recognizes mobility cues (axial body movement features and body key points) and circadian cues, including nightly disruptions, ambient SPL, and light intensity, as well as other environmental factors such as indoor air quality. The Mobi-DiQ system consists of three major components: the pervasive sensing system, a data storage and analysis server, and a data annotation system. For data collection, six local pervasive sensing systems were deployed, including a local computer and sensors. A video recording tool with graphical user interface (GUI) developed in python was used to capture depth image frames for analyzing patient mobility. All sensor data is encrypted, then automatically uploaded to the Mobi-DiQ server through a secured VPN connection. Several data pipelines are developed to automate the data transfer, curation, and data preparation for annotation and model training. The data curation and post-processing are performed on the server. A custom secure annotation tool with GUI was developed to annotate depth activity data. The annotation tool is linked to the MongoDB database to record the data annotation and to provide summarization. Docker containers are also utilized to manage services and pipelines running on the server in an isolated manner. The processed clinical data and annotations are used to train and develop real-time pervasive sensing systems to augment clinical decision-making and promote targeted interventions. In the future, we intend to evaluate our system as a clinical implementation trial, as well as to refine and validate it by using other data sources, including neurological data obtained through continuous electroencephalography (EEG).

Keywords: deep learning, delirium, healthcare, pervasive sensing

Procedia PDF Downloads 93

Authors: Nursuhaili Najwa Masrol, Nur Hafizah Mohammed, Nur Nadhirah Rusyda Rosnan, Vijaya Subramaniam, Sim Choon Cheak

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Replanting in oil palm cultivation is vital to enable the introduction of planting materials and provides an opportunity to improve the road, drainage, terrace design, and planting density. Oil palm replanting is fundamentally necessary every 25 years. The adoption of the digital replanting blueprint is imperative as it can assist the Malaysia Oil Palm industry in addressing challenges such as labour shortages and limited expertise related to replanting tasks. Effective replanting planning should commence at least 6 months prior to the actual replanting process. Therefore, this study will help to plan and design the replanting blueprint with high-precision translation on the ground. With the advancement of geospatial technology, it is now feasible to engage in thoroughly researched planning, which can help maximize the potential yield. A blueprint designed before replanting is to enhance management’s ability to optimize the planting program, address manpower issues, or even increase productivity. In terrace planting blueprints, geographic tools have been utilized to design the roads, drainages, terraces, and planting points based on the ARM standards. These designs are mapped with location information and undergo statistical analysis. The geospatial approach is essential in precision agriculture and ensuring an accurate translation of design to the ground by implementing high-accuracy technologies. In this study, geospatial and remote sensing technologies played a vital role. LiDAR data was employed to determine the Digital Elevation Model (DEM), enabling the precise selection of terraces, while ortho imagery was used for validation purposes. Throughout the designing process, Geographical Information System (GIS) tools were extensively utilized. To assess the design’s reliability on the ground compared with the current conventional method, high-precision GPS instruments like EOS Arrow Gold and HIPER VR GNSS were used, with both offering accuracy levels between 0.3 cm and 0.5cm. Nearest Distance Analysis was generated to compare the design with actual planting on the ground. The analysis revealed that it could not be applied to the roads due to discrepancies between actual roads and the blueprint design, which resulted in minimal variance. In contrast, the terraces closely adhered to the GPS markings, with the most variance distance being less than 0.5 meters compared to actual terraces constructed. Considering the required slope degrees for terrace planting, which must be greater than 6 degrees, the study found that approximately 65% of the terracing was constructed at a 12-degree slope, while over 50% of the terracing was constructed at slopes exceeding the minimum degrees. Utilizing blueprint replanting promising strategies for optimizing land utilization in agriculture. This approach harnesses technology and meticulous planning to yield advantages, including increased efficiency, enhanced sustainability, and cost reduction. From this study, practical implementation of this technique can lead to tangible and significant improvements in agricultural sectors. In boosting further efficiencies, future initiatives will require more sophisticated techniques and the incorporation of precision GPS devices for upcoming blueprint replanting projects besides strategic progression aims to guarantee the precision of both blueprint design stages and its subsequent implementation on the field. Looking ahead, automating digital blueprints are necessary to reduce time, workforce, and costs in commercial production.

Keywords: replanting, geospatial, precision agriculture, blueprint

Procedia PDF Downloads 84

Authors: Ziara Carmelli G. Tan, Irene Carmelle S. Tan

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Background: Trichotillomania (TTM) and Major Depressive Disorder (MDD) are two psychiatric conditions that frequently co-occur, presenting a significant challenge for treatment due to their complex interplay. TTM involves repetitive hair-pulling, leading to noticeable hair loss and distress, while MDD is characterized by persistent low mood and loss of interest or pleasure, leading to dysfunctionality. This case report examines the intricate relationship between TTM and MDD in a young adult female, emphasizing the need for a comprehensive, multifaceted therapeutic approach to address both disorders effectively. Case Presentation: The patient is a 21-year-old female college student and youth church leader who presented with chronic hair-pulling and depressive symptoms. Her premorbid personality was marked by low self-esteem and a strong need for external validation. Despite her academic and social responsibilities and achievements, she struggled with managing her emotional distress, which was exacerbated by her family dynamics and her role within her church community. Her hair-pulling and mood symptoms were particularly triggered by self-esteem threats and feelings of inadequacy. She was diagnosed with Trichotillomania, Scalp and Major Depressive Disorder. Intervention/Management: The patient’s treatment plan was comprehensive, incorporating both pharmacological and non-pharmacological interventions. Initial pharmacologic management was Fluoxetine 20mg/day up, titrated to 40mg/day with no improvement; hence, shifted to Escitalopram 20mg/day and started with N-acetylcysteine 600mg/day with noted significant improvement in symptoms. Psychotherapeutic strategies played a crucial role in her treatment. These included supportive-expressive psychodynamic psychotherapy, which helped her explore and understand underlying emotional conflicts. Cognitive-behavioral techniques were employed to modify her maladaptive thoughts and behaviors. Grief processing was integrated to help her cope with significant losses. Family therapy was done to address conflicts and collaborate with the treatment process. Psychoeducation was provided to enhance her understanding of her condition and to empower her in her treatment journey. A suicide safety plan was developed to ensure her safety during critical periods. An interprofessional approach, which involved coordination with the Dermatology service for co-management, was also a key component of her treatment. Outcome: Over the course of 15 therapy sessions, the patient demonstrated significant improvement in both her depressive symptoms and hair-pulling behavior. Her active engagement in therapy, combined with pharmacological support, facilitated better emotional regulation and a more cohesive sense of self. Her adherence to the treatment plan, along with the collaborative efforts of the interprofessional team, contributed to her positive outcomes. Discussion: This case underscores the significance of addressing both TTM and its comorbid conditions to achieve effective treatment outcomes. The intricate interplay between TTM and MDD in the patient’s case highlights the importance of a comprehensive treatment plan that includes both pharmacological and psychotherapeutic approaches. Supportive-expressive psychodynamic psychotherapy, Cognitive-behavioral techniques, and Family therapy were particularly beneficial in addressing the complex emotional and behavioral aspects of her condition. The involvement of an interprofessional team, including dermatology co-management, was crucial in providing holistic care. Future practice should consider the benefits of such a multidisciplinary approach to managing complex cases like this, ensuring that both the psychological and physiological aspects of the disorders are adequately addressed.

Keywords: cognitive-behavioral therapy, interprofessional approach, major depressive disorder, psychodynamic psychotherapy, trichotillomania

Procedia PDF Downloads 34

Authors: Do-Won Kim, Andy Eu Jin Lim, Raja Muthusamy Kumarasamy, Vishal Vinayak, Jacky Wang Yu-Shun, Jason Liow Tsung Yang, Patrick Lo Guo Qiang

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In this study, we demonstrate 4-channel coarse wavelength division multiplexing (CWDM) optical transceiver based on silicon photonics integrated circuits (PIC) of waveguide Ge-photodiode (Ge-PD) and Mach Zehnder (MZ)-modulator. 4-channel arrayed PICs of Ge-PD and MZ-modulator are verified to operate at 25 Gbps/ch achieving 4x25 Gbps of total data rate. 4 bare dies of single-channel commercial electronics ICs (EICs) of trans-impedance amplifier (TIA) for Ge-PD and driver IC for MZ-modulator are packaged with PIC on printed circuit board (PCB) in a chip-on-board (COB) manner. Each single-channel EIC is electrically connected to the one channel of 4-channel PICs by wire bonds to trace. The PICs have 4-channel multiplexer for MZ-modulator and 4-channel demultiplexer for Ge-PD. The 4-channel multiplexer/demultiplexer have echelle gratings for4 CWDM optic signals of which center wavelengths are 1511, 1531, 1553, and 1573 nm. Its insertion loss is around 4dB with over 15dB of extinction ratio.The dimension of 4-channel Ge-PD is 3.6x1.4x0.3mm, and its responsivity is 1A/W with dark current of less than 20 nA.Its measured 3dB bandwidth is around 20GHz. The dimension of the 4-channel MZ-modulator is 3.6x4.8x0.3mm, and its 3dB bandwidth is around 11Ghz at -2V of reverse biasing voltage. It has 2.4V•cmbyVπVL of 6V for π shift to 4 mm length modulator.5x5um of Inversed tapered mode size converter with less than 2dB of coupling loss is used for the coupling of the lensed fiber which has 5um of mode field diameter.The PCB for COB packaging and signal transmission is designed to have 6 layers in the hybrid layer structure. 0.25 mm-thick Rogers Duroid RT5880 is used as the first core dielectric layer for high-speed performance over 25 Gbps. It has 0.017 mm-thick of copper layers and its dielectric constant is 2.2and dissipation factor is 0.0009 at 10 GHz. The dimension of both single ended and differential microstrip transmission lines are calculated using full-wave electromagnetic (EM) field simulator HFSS which RF industry is using most. It showed 3dB bandwidth at around 15GHz in S-parameter measurement using network analyzer. The wire bond length for transmission line and ground connection from EIC is done to have less than 300 µm to minimize the parasitic effect to the system.Single layered capacitors (SLC) of 100pF and 1000pF are connected as close as possible to the EICs for stabilizing the DC biasing voltage by decoupling. Its signal transmission performance is under measurement at 25Gbps achieving 100Gbps by 4chx25Gbps. This work can be applied for the active optical cable (AOC) and quad small form-factor pluggable (QSFP) for high-speed optical interconnections. Its demands are quite large in data centers targeting 100 Gbps, 400 Gbps, and 1 Tbps. As the demands of high-speed AOC and QSFP for the application to intra/inter data centers increase, this silicon photonics based high-speed 4 channel CWDM scheme can have advantages not only in data throughput but also cost effectiveness since it reduces fiber cost dramatically through WDM.

Keywords: active optical cable(AOC), 4-channel coarse wavelength division multiplexing (CWDM), communication system, data center, ge-photodiode, Mach Zehnder (MZ) modulator, optical interconnections, optical transceiver, photonics integrated circuits (PIC), quad small form-factor pluggable (QSFP), silicon photonics

Procedia PDF Downloads 419

Authors: Leo Byrne, Neil Watts

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In the complex and evolving landscape of global trade, maritime sanctions emerge as a critical tool wielded by the international community to curb illegal activities and alter the behavior of non-compliant states and entities. These sanctions, designed to restrict or prohibit trade by sea with sanctioned jurisdictions, entities, or individuals, face continuous challenges due to the sophisticated evasion tactics employed by countries like North Korea. As the Democratic People's Republic of Korea (DPRK) diverts significant resources to circumvent these measures, understanding the nuances of their methodologies becomes imperative for maintaining the integrity of global trade systems. The DPRK, one of the most sanctioned nations globally, has developed an intricate network to facilitate its trade in illicit goods, ensuring the flow of revenue from designated activities continues unabated. Given its geographic and economic conditions, North Korea predominantly relies on maritime routes, utilizing foreign ports to route its illicit trade. This reliance on the sea is exploited through various sophisticated methods, including the use of front companies, falsification of documentation, commingling of bulk cargos, and physical alterations to vessels. These tactics enable the DPRK to navigate through the gaps in regulatory frameworks and lax oversight, effectively undermining international sanctions regimes Maritime sanctions carry significant implications for global trade, imposing heightened risks in the maritime domain. The deceptive practices employed not only by the DPRK but also by other high-risk jurisdictions, necessitate a comprehensive understanding of UN targeted sanctions. For stakeholders in the maritime sector—including maritime authorities, vessel owners, shipping companies, flag registries, and financial institutions serving the shipping industry—awareness and compliance are paramount. Violations can lead to severe consequences, including reputational damage, sanctions, hefty fines, and even imprisonment. To mitigate risks associated with these deceptive practices, it is crucial for maritime sector stakeholders to employ rigorous due diligence and regulatory compliance screening measures. Effective sanctions compliance serves as a protective shield against legal, financial, and reputational risks, preventing exploitation by international bad actors. This requires not only a deep understanding of the sanctions landscape but also the capability to identify and manage risks through informed decision-making and proactive risk management practices. As the DPRK and other sanctioned entities continue to evolve their sanctions evasion tactics, the international community must enhance its collective efforts to demystify and counter these practices. By leveraging more stringent compliance measures, stakeholders can safeguard against the illicit use of the maritime domain, reinforcing the effectiveness of maritime sanctions as a tool for global security. This paper seeks to dissect North Korea's adaptive strategies in the face of maritime sanctions. By examining up-to-date, geographically, and temporally relevant case studies, it aims to shed light on the primary nodes through which Pyongyang evades sanctions and smuggles goods via third-party ports. The goal is to propose multi-level interaction strategies, ranging from governmental interventions to localized enforcement mechanisms, to counteract these evasion tactics.

Keywords: maritime, maritime sanctions, international sanctions, compliance, risk

Procedia PDF Downloads 71

Authors: Yimer Mohammed Assen, Abiyot Legesse Kura, Engida Esyas Dube, Asebe Regassa Debelo, Girma Kelboro Mensuro, Lete Bekele Gure

Abstract:

Climate change has posed severe threats to many cultural landscapes of UNESCO world heritage sites recently. The UNESCO State of Conservation (SOC) reports categorized flooding, temperature increment, and drought as threats to cultural landscapes. This study aimed to examine variations and trends of rainfall and temperature extreme events and their threats to the UNESCO-designated Konso Cultural Landscape in southern Ethiopia. The study used dense merged satellite-gauge station rainfall data (1981-2020) with spatial resolution of 4km by 4km and observed maximum and minimum temperature data (1987-2020). Qualitative data were also gathered from cultural leaders, local administrators, and religious leaders using structured interview checklists. The spatial patterns, coefficient of variation, standardized anomalies, trends, and magnitude of change of rainfall and temperature extreme events both at annual and seasonal levels were computed using the Mann-Kendall trend test and Sen’s slope estimator under the CDT package. The standard precipitation index (SPI) was also used to calculate drought severity, frequency, and trend maps. The data gathered from key informant interviews and focus group discussions were coded and analyzed thematically to complement statistical findings. Thematic areas that explain the impacts of extreme events on the cultural landscape were chosen for coding. The thematic analysis was conducted using Nvivo software. The findings revealed that rainfall was highly variable and unpredictable, resulting in extreme drought and flood. There were significant (P<0.05) increasing trends of heavy rainfall (R10mm and R20mm) and the total amount of rain on wet days (PRCPTOT), which might have resulted in flooding. The study also confirmed that absolute temperature extreme indices (TXx, TXn, and TNx) and the percentile-based temperature extreme indices (TX90p, TN90p, TX10p, and TN10P) showed significant (P<0.05) increasing trends which are signals for warming of the study area. The results revealed that the frequency as well as the severity of drought at 3-months (katana/hageya seasons) was more pronounced than the 12-months (annual) time scale. The highest number of droughts in 100 years is projected at a 3-months timescale across the study area. The findings also showed that frequent drought has led to loss of grasses which are used for making traditional individual houses and multipurpose communal houses (pafta), food insecurity, migration, loss of biodiversity, and commodification of stones from terrace. On the other hand, the increasing trends of rainfall extreme indices resulted in destruction of terraces, soil erosion, loss of life and damage of properties. The study shows that a persistent decline in farmland productivity, due to erratic and extreme rainfall and frequent drought occurrences, forced the local people to participate in non-farm activities and retreat from daily preservation and management of their landscape. Overall, the increasing rainfall and temperature extremes coupled with prevalence of drought are thought to have an impact on the sustainability of cultural landscape through disrupting the ecosystem services and livelihood of the community. Therefore, more localized adaptation and mitigation strategies to the changing climate are needed to maintain the sustainability of Konso cultural landscapes as a global cultural treasure and to strengthen the resilience of smallholder farmers.

Keywords: adaptation, cultural landscape, drought, extremes indices

Procedia PDF Downloads 28

Authors: Pei Yi Lin

Abstract:

Objective: The objective of this study is to use machine learning methods to build an early prediction classifier model for acute delirium to improve the quality of medical care for intensive care patients. Background: Delirium is a common acute and sudden disturbance of consciousness in critically ill patients. After the occurrence, it is easy to prolong the length of hospital stay and increase medical costs and mortality. In 2021, the incidence of delirium in the intensive care unit of internal medicine was as high as 59.78%, which indirectly prolonged the average length of hospital stay by 8.28 days, and the mortality rate is about 2.22% in the past three years. Therefore, it is expected to build a delirium prediction classifier through big data analysis and machine learning methods to detect delirium early. Method: This study is a retrospective study, using the artificial intelligence big data database to extract the characteristic factors related to delirium in intensive care unit patients and let the machine learn. The study included patients aged over 20 years old who were admitted to the intensive care unit between May 1, 2022, and December 31, 2022, excluding GCS assessment <4 points, admission to ICU for less than 24 hours, and CAM-ICU evaluation. The CAMICU delirium assessment results every 8 hours within 30 days of hospitalization are regarded as an event, and the cumulative data from ICU admission to the prediction time point are extracted to predict the possibility of delirium occurring in the next 8 hours, and collect a total of 63,754 research case data, extract 12 feature selections to train the model, including age, sex, average ICU stay hours, visual and auditory abnormalities, RASS assessment score, APACHE-II Score score, number of invasive catheters indwelling, restraint and sedative and hypnotic drugs. Through feature data cleaning, processing and KNN interpolation method supplementation, a total of 54595 research case events were extracted to provide machine learning model analysis, using the research events from May 01 to November 30, 2022, as the model training data, 80% of which is the training set for model training, and 20% for the internal verification of the verification set, and then from December 01 to December 2022 The CU research event on the 31st is an external verification set data, and finally the model inference and performance evaluation are performed, and then the model has trained again by adjusting the model parameters. Results: In this study, XG Boost, Random Forest, Logistic Regression, and Decision Tree were used to analyze and compare four machine learning models. The average accuracy rate of internal verification was highest in Random Forest (AUC=0.86), and the average accuracy rate of external verification was in Random Forest and XG Boost was the highest, AUC was 0.86, and the average accuracy of cross-validation was the highest in Random Forest (ACC=0.77). Conclusion: Clinically, medical staff usually conduct CAM-ICU assessments at the bedside of critically ill patients in clinical practice, but there is a lack of machine learning classification methods to assist ICU patients in real-time assessment, resulting in the inability to provide more objective and continuous monitoring data to assist Clinical staff can more accurately identify and predict the occurrence of delirium in patients. It is hoped that the development and construction of predictive models through machine learning can predict delirium early and immediately, make clinical decisions at the best time, and cooperate with PADIS delirium care measures to provide individualized non-drug interventional care measures to maintain patient safety, and then Improve the quality of care.

Keywords: critically ill patients, machine learning methods, delirium prediction, classifier model

Procedia PDF Downloads 79

Authors: K. Kamal

Abstract:

Structural sandwich panels with core of Advanced Composites Laminates l Honeycombs / PU-foams are used in aerospace applications and are also fabricated for use now in some civil engineering applications. An all Advanced Composites Foot Over Bridge (FOB) system, designed and developed for pedestrian traffic is one such application earlier, may be cited as an example here. During development stage of this FoB, a profile of its decks was then spurred as a single corrugate sheet core sandwiched between two Glass Fibre Reinforced Plastics(GFRP) flat laminates. Once successfully fabricated and used, these decks did prove suitable also to form other structure on assembly, such as, erecting temporary shelters. Such corrugated sheet core profile sandwiched panels were then also tried using the construction materials but any conventional method of construction only posed certain difficulties in achieving the required core profile monolithically within the sandwiched slabs and hence it was then abended. Such monolithic construction was, however, subsequently eased out on demonstration by dispensing building materials mix through a suitably designed multi-dispenser system attached to a 3D Printer. This study conducted at lab level was thus reported earlier and it did include the fabrication of a 3D printer in-house first as ‘3DcMP’ as well as on its functional operation, some required sandwich core profiles also been 3D-printed out producing panels hardware. Once a number of these sandwich panels in single corrugated sheet core monolithically printed out, panels were subjected to load test in an experimental set up as also their structural behavior was studied analytically, and subsequently, these results were correlated as reported in the literature. In achieving the required more depths and also to exhibit further the stronger and creating sandwiched decks of better structural and mechanical behavior, further more complex core configuration such as stack corrugate sheets core with a flat mid plane was felt to be the better sandwiched core. Such profile remained as an outcome that turns out merely on stacking of two separately printed out monolithic units of single corrugated sheet core developed earlier as above and bonded them together initially, maintaining a different orientation. For any required sequential understanding of the structural behavior of any such complex profile core sandwiched decks with special emphasis to study of the effect in the variation of corrugation orientation in each distinct tire in this core, it obviously calls for an analytical study first. The rectangular,simply supported decks have therefore been considered for analysis adopting the ‘Advanced Composite Technology(ACT), some numerical results along with some fruitful findings were obtained and these are all presented here in this paper. From this numerical result, it has been observed that a mid flat layer which eventually get created monolethically itself, in addition to eliminating the bonding process in development, has been found to offer more effective bending resistance by such decks subjected to UDL over them. This is understood to have resulted here since the existence of a required shear resistance layer at the mid of the core in this profile, unlike other bending elements. As an addendum to all such efforts made as covered above and was published earlier, this unique stack corrugate sheet core profile sandwiched structural decks, monolithically construction with ease at the site itself, has been printed out from a 3D Printer. On employing 3DcMP and using some innovative building construction materials, holds the future promises of such research & development works since all those several aspects of a 3D printing in construction are now included such as reduction in the required construction time, offering cost effective solutions with freedom in design of any such complex shapes thus can widely now be realized by the modern construction industry.

Keywords: advance composite technology(ACT), corrugated laminates, 3DcMP, foot over bridge (FOB), sandwiched deck units

Procedia PDF Downloads 173

Authors: Irina Alexandra Paun, Mona Mihailescu, Marian Zamfirescu, Catalin Romeo Luculescu, Adriana Maria Acasandrei, Cosmin Catalin Mustaciosu, Roxana Cristina Popescu, Maria Dinescu

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A major concern in bone tissue engineering is to develop complex 3D architectures that mimic the natural cells environment, facilitate the cells growth in a defined manner and allow the flow transport of nutrients and metabolic waste. In particular, porous structures of controlled pore size and positioning are indispensable for growing human-like bone structures. Another concern is to monitor both the structures and the seeded cells with high spatial resolution and without interfering with the cells natural environment. The present approach relies on laser-based technologies employed for fabricating porous biomimetic structures that support the growth of osteoblast-like cells and for their non-invasive 3D imaging. Specifically, the porous structures were built by two photon polymerization –direct writing (2PP_DW) of the commercially available photoresists IL-L780, using the Photonic Professional 3D lithography system. The structures consist of vertical tubes with micrometer-sized heights and diameters, in a honeycomb-like spatial arrangement. These were fabricated by irradiating the IP-L780 photoresist with focused laser pulses with wavelength centered at 780 nm, 120 fs pulse duration and 80 MHz repetition rate. The samples were precisely scanned in 3D by piezo stages. The coarse positioning was done by XY motorized stages. The scanning path was programmed through a writing language (GWL) script developed by Nanoscribe. Following laser irradiation, the unexposed regions of the photoresist were washed out by immersing the samples in the Propylene Glycol Monomethyl Ether Acetate (PGMEA). The porous structures were seeded with osteoblast like MG-63 cells and their osteogenic potential was tested in vitro. The cell-seeded structures were analyzed in 3D using the digital holographic microscopy technique (DHM). DHM is a marker free and high spatial resolution imaging tool, where the hologram acquisition is performed non-invasively i.e. without interfering with the cells natural environment. Following hologram recording, a digital algorithm provided a 3D image of the sample, as well as information about its refractive index, which is correlated with the intracellular content. The axial resolution of the images went down to the nanoscale, while the temporal scales ranged from milliseconds up to hours. The hologram did not involve sample scanning and the whole image was available in one frame recorded going over 200μm field of view. The digital holograms processing provided 3D quantitative information on the porous structures and allowed a quantitative analysis of the cellular response in respect to the porous architectures. The cellular shape and dimensions were found to be influenced by the underlying micro relief. Furthermore, the intracellular content gave evidence on the beneficial role of the porous structures in promoting osteoblast differentiation. In all, the proposed laser-based protocol emerges as a promising tool for the fabrication and non-invasive imaging of porous constructs for bone tissue engineering. Acknowledgments: This work was supported by a grant of the Romanian Authority for Scientific Research and Innovation, CNCS-UEFISCDI, project PN-II-RU-TE-2014-4-2534 (contract 97 from 01/10/2015) and by UEFISCDI PN-II-PT-PCCA no. 6/2012. A part of this work was performed in the CETAL laser facility, supported by the National Program PN 16 47 - LAPLAS IV.

Keywords: biomimetic, holography, laser, osteoblast, two photon polymerization

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Authors: Denis Jordan, Daniel Golkowski, Mathias Lukas, Katharina Merz, Caroline Mlynarcik, Max Maurer, Valentin Riedl, Stefan Foerster, Eberhard F. Kochs, Andreas Bender, Ruediger Ilg

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Introduction: So far, clinical assessments that rely on behavioral responses to differentiate coma states or even predict outcome in coma patients are unreliable, e.g. because of some patients’ motor disabilities. The present study was aimed to provide prognosis in coma patients using markers from electroencephalogram (EEG), blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) and [18F]-fluorodeoxyglucose (FDG) positron emission tomography (PET). Unsuperwised principal component analysis (PCA) was used for multimodal integration of markers. Methods: Approved by the local ethics committee of the Technical University of Munich (Germany) 20 patients (aged 18-89) with severe brain damage were acquired through intensive care units at the Klinikum rechts der Isar in Munich and at the Therapiezentrum Burgau (Germany). At the day of EEG/fMRI/PET measurement (date I) patients (<3.5 month in coma) were grouped in the minimal conscious state (MCS) or vegetative state (VS) on the basis of their clinical presentation (coma recovery scale-revised, CRS-R). Follow-up assessment (date II) was also based on CRS-R in a period of 8 to 24 month after date I. At date I, 63 channel EEG (Brain Products, Gilching, Germany) was recorded outside the scanner, and subsequently simultaneous FDG-PET/fMRI was acquired on an integrated Siemens Biograph mMR 3T scanner (Siemens Healthineers, Erlangen Germany). Power spectral densities, permutation entropy (PE) and symbolic transfer entropy (STE) were calculated in/between frontal, temporal, parietal and occipital EEG channels. PE and STE are based on symbolic time series analysis and were already introduced as robust markers separating wakefulness from unconsciousness in EEG during general anesthesia. While PE quantifies the regularity structure of the neighboring order of signal values (a surrogate of cortical information processing), STE reflects information transfer between two signals (a surrogate of directed connectivity in cortical networks). fMRI was carried out using SPM12 (Wellcome Trust Center for Neuroimaging, University of London, UK). Functional images were realigned, segmented, normalized and smoothed. PET was acquired for 45 minutes in list-mode. For absolute quantification of brain’s glucose consumption rate in FDG-PET, kinetic modelling was performed with Patlak’s plot method. BOLD signal intensity in fMRI and glucose uptake in PET was calculated in 8 distinct cortical areas. PCA was performed over all markers from EEG/fMRI/PET. Prognosis (persistent VS and deceased patients vs. recovery to MCS/awake from date I to date II) was evaluated using the area under the curve (AUC) including bootstrap confidence intervals (CI, *: p<0.05). Results: Prognosis was reliably indicated by the first component of PCA (AUC=0.99*, CI=0.92-1.00) showing a higher AUC when compared to the best single markers (EEG: AUC<0.96*, fMRI: AUC<0.86*, PET: AUC<0.60). CRS-R did not show prediction (AUC=0.51, CI=0.29-0.78). Conclusion: In a multimodal analysis of EEG/fMRI/PET in coma patients, PCA lead to a reliable prognosis. The impact of this result is evident, as clinical estimates of prognosis are inapt at time and could be supported by quantitative biomarkers from EEG, fMRI and PET. Due to the small sample size, further investigations are required, in particular allowing superwised learning instead of the basic approach of unsuperwised PCA.

Keywords: coma states and prognosis, electroencephalogram, entropy, functional magnetic resonance imaging, machine learning, positron emission tomography, principal component analysis

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Authors: Medha Iyer, Anshul Paul, Aunnesha Bhowmick, Anahita Banerjee, Sana Prasad, Anoushka Singal, Lauren Sinopoli, Pooja Bapat, Shivi Jain

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In Himachal Pradesh, India, a majority of the population lives in rural villages spread throughout its hilly regions; many of these households rely on subsistence farming as their main source of livelihood. The student-run non-profit organization affiliated with this study, Project RISHI (Rural India Social and Health Improvement), works to promote sustainable development practices in Bharog Baneri, a gram panchayat, or union, of villages in Himachal Pradesh. In 2017, an established rainwater harvesting (RWH) project group within Project RISHI had surveyed many families, finding that the most common issue regarding food and water access was a lack of accessible water sources for agricultural use in the dry season. After a prototype build in 2018, the group built 6 systems for eligible residents that demonstrated need in 2019. Subsequently, the project went through an evaluation period, including self-evaluation of project goals and post-impact surveying of system recipients. The group used the social impact assessment model to optimize the implementation of domestic RWH systems in Bharog Baneri. Assessing implementation after in-person builds produced three pillars of focus — system design, equitable recipient selection, and community involvement. After two years of remote involvement during COVID-19, the group prepared to visit Bharog Baneri to build 10 new systems in the Summer 2022. First, the group created a more durable and cost-effective design that could withstand debris and heavy rains to prevent gutter failure. The domestic system design is a rooftop RWH catchment system with two tanks attached, an overflow pipe, debris filtration, and a spigot for accessibility. The group also developed a needs-based eligibility methodology with assistance from village leaders and surveying in Bharog Baneri and set up the groundwork for a future community board. COVID-19 has strengthened remote work, telecommunications, and other organizational support systems. As sustainable development evolves to encompass these practices in a post-pandemic world, the potential for new RWH system design and implementation processes has emerged as well. This raises the question: how can a social impact assessment of rural RWH projects inform an integrated approach to post-pandemic RWH system practices? The objective of this exploratory study is to investigate and evaluate a novel remote build infrastructure that brings access to reliable and sustainable sources of water for agricultural use. To construct the remote build approach, the group identified and assigned a point of contact who was experienced with previous RWH system builds. The recipients were selected based on demonstrated need and ease of building. The contact visited each of the houses and coordinated supplier relations and transportation of the materials in accordance with the participatory approach to sustainable development. Over the course of two months, the group completed four system builds with the resulting infrastructure. The infrastructure adhered to the social impact assessment model by centering supplier relations, material transportation, and construction logistics within the community. The conclusion of this exploration is that post-pandemic rural RWH practices should be rooted in strengthening villager communication and utilizing local assets. Through this, non-profit organizations can incorporate remote build strategies into their long-term goals.

Keywords: capturing run-off from rooftops, domestic rainwater harvesting, Implementation approaches and strategies, rainwater harvesting and management in rural sectors

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Authors: Maari Sugawara

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This study investigates the constructed notion of “motherhood” and queered forms of care in contemporary Japan, focusing on rental family services. In Japan, the concept of motherhood is often equated with womanhood, reflecting a pervasive ideology that views motherhood as an essential aspect of a woman's societal role, particularly amidst economic recovery and an aging population. This study interrogates these gendered expectations by linking rental family services, particularly the role of rental mothers, to traditional caregiving roles. It critiques the gendered construction of domestic labor and aims to expand conceptions of alternative family structures and caregiving roles beyond normative frameworks. Emerging in the 1980s to provide companionship for the elderly, rental family services have evolved to meet diverse social needs, with paid actors fulfilling familial roles at various social events. Despite their growing prevalence, academic exploration of this phenomenon remains limited. This research aims to fill that gap by investigating the cultural, social, and economic factors fueling the popularity of rental family services and analyzing their implications for contemporary understandings of family dynamics and care labor in Japan. Furthermore, this study underscores the disproportionate domestic labor burden women in Japan bear, often managing time-intensive household tasks, which creates a "double burden" for those in full-time employment. Care work, including elderly and disability support, is undervalued and typically compensated at near-minimum wage levels, with women predominantly filling these low-wage roles. This gender disparity in Japan's care industry contributes to labor shortages in caregiving and childcare, highlighting broader structural inequities in the labor market. Through semi-structured qualitative interviews with fifteen rental mothers, this study investigates their experiences, motivations, role dynamics, and emotional labor. It critically examines whether the labor performed by rental family actors constitutes a subversive practice deserving of appropriate compensation. Utilizing a role-playing method, the author engages with rental mothers as if they were her own, reflecting the dynamics of compensated labor. This interaction delves into the economic and emotional aspects of constructed motherhood, facilitating a broader inquiry into the value of both productive and reproductive labor in Japan. The study also investigates the relationship between sex work and rental family services within the socio-economic landscape, recognizing the links between the welfare sector and female employment in legal sex work. Although distinct, these sectors merit joint consideration due to the commonality of male clients in both industries. This research engages with theoretical perspectives framing mobile sex work as inherently queer, directly challenging the dominance of heteronormativity. The agency exercised by sex workers complicates narratives of conformity and deviance, underscoring the need to reevaluate caregiving labor in both paid and unpaid contexts. Ultimately, this research critiques the intersection of gender, care, and labor in contemporary Japan by examining the undervaluation of traditional caregiving roles alongside the labor involved in rental family services. It challenges Japanese policies that equate womanhood with motherhood and explores the potential of viewing outsourced care as queered maternal and non-reproductive labor, advocating for the recognition of alternative family structures and non-reproductive forms of motherhood.

Keywords: motherhood, alternative family structures, carework, Japan, queer studies

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Authors: Ipsita Pujari, Abitha Thomas, Vidhu S. Babu, K. Satyamoorthy

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Orchids are esteemed as celebrities in cut flower industry globally, due to their long-lasting fragrance and freshness. Apart from splendor, the unique metabolites endowed with pharmaceutical potency have made them one of the most hunted in plant kingdom. This had led to their trafficking, resulting in habitat loss, subsequently making them occupiers of IUCN red list as RET species. Many of the orchids especially wild varieties still remain undiscovered. In view to protect and conserve the wild germplasm, researchers have been inventing novel micropropagation protocols; thereby conserving Orchids. India is overflowing with exclusive wild cultivars of Orchids, whose pharmaceutical properties remain untapped and are not marketed owing to relatively small flowers. However, their germplasm is quite pertinent to be preserved for making unusual hybrids. Dendrobium genus is the second largest among Orchids exists in India and has highest demand attributable to enduring cut flowers and significant therapeutic uses in traditional medicinal system. Though the genus is quite endemic in Western Ghat regions of the country, many species are still anonymous with their unknown curative properties. A standard breeding cycle in Orchids usually takes five to seven years (Dendrobium hybrids taking a long juvenile phase of two to five years reaching maturity and flowering stage) and this extensive life cycle has always hindered the development of Dendrobium breeding. Dendrobium is reported with essential therapeutic plant bio-chemicals and ‘Moscatilin’ is one, found exclusive to this famous Dendrobium genus. Moscatilin is reported to have anti-mutagenic and anti-cancer properties, whose positive action has very recently been demonstrated against a range of cancers. Our preliminary study here established a simple and economic small-scale propagation protocol of Dendrobium ovatum describing in vitro production of Moscatilin. Subsequently for enhancing the content of Moscatilin, an efficient experimental related to the organization of transgenic (hairy) D. ovatum root cultures through infection of Agrobacterium rhizogenes 2364 strain on MS basal medium is being reported in the present study. Hairy roots generated on almost half of the explants used (spherules, in vitro plantlets and calli) maintained through suspension cultures, after 8 weeks of co-cultivation with Agrobacterium rhizogenes. GFP assay performed with isolated hairy roots has confirmed the integrative transformation which was further positively confirmed by PCR using rolB gene specific primers. Reverse phase-high performance liquid chromatography and mass spectrometry techniques were used for quantification and accurate identification of Moscatilin respectively from transgenic systems. A noticeable ~3 fold increase in contents were observed in transformed D. ovatum root cultures as compared to the simple in vitro culture, callus culture and callus regeneration plantlets. Role of elicitors e.g., Methyl jasmonate, Salicylic acid, Yeast extract and Chitosan were tested for elevating the Moscatilin content to obtain a comprehensive optimized protocol facilitating the in vitro production of valuable Moscatilin with larger yield. This study would provide evidence towards the in vitro assembly of Moscatilin within a short time-period through not a so-expensive technology for the first time. It also serves as an appropriate basis for bioreactor scale-up resulting in commercial bioproduction of Moscatilin.

Keywords: bioproduction, Dendrobium ovatum, hairy root culture, moscatilin

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Authors: Philipp Sommer, Amgad Agoub

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The construction sector significantly impacts global CO₂ emissions, particularly through the energy usage of residential buildings. To address this, various governments, including Germany's, are focusing on reducing emissions via sustainable refurbishment initiatives. This study examines the application of machine learning (ML) to estimate energy demands dynamically in residential buildings and enhance the potential for large-scale sustainable refurbishment. A major challenge in Germany is the lack of extensive publicly labeled datasets for energy performance, as energy performance certificates, which provide critical data on building-specific energy requirements and consumption, are not available for all buildings or require on-site inspections. Conversely, England and other countries in the European Union (EU) have rich public datasets, providing a viable alternative for analysis. This research adapts insights from these English datasets to the German context by developing a comprehensive data schema and calibration dataset capable of predicting building energy demand effectively. The study proposes a minimal feature set, determined through feature importance analysis, to optimize the ML model. Findings indicate that ML significantly improves the scalability and accuracy of energy demand forecasts, supporting more effective emissions reduction strategies in the construction industry. Integrating energy performance certificates into municipal heat planning in Germany highlights the transformative impact of data-driven approaches on environmental sustainability. The goal is to identify and utilize key features from open data sources that significantly influence energy demand, creating an efficient forecasting model. Using Extreme Gradient Boosting (XGB) and data from energy performance certificates, effective features such as building type, year of construction, living space, insulation level, and building materials were incorporated. These were supplemented by data derived from descriptions of roofs, walls, windows, and floors, integrated into three datasets. The emphasis was on features accessible via remote sensing, which, along with other correlated characteristics, greatly improved the model's accuracy. The model was further validated using SHapley Additive exPlanations (SHAP) values and aggregated feature importance, which quantified the effects of individual features on the predictions. The refined model using remote sensing data showed a coefficient of determination (R²) of 0.64 and a mean absolute error (MAE) of 4.12, indicating predictions based on efficiency class 1-100 (G-A) may deviate by 4.12 points. This R² increased to 0.84 with the inclusion of more samples, with wall type emerging as the most predictive feature. After optimizing and incorporating related features like estimated primary energy consumption, the R² score for the training and test set reached 0.94, demonstrating good generalization. The study concludes that ML models significantly improve prediction accuracy over traditional methods, illustrating the potential of ML in enhancing energy efficiency analysis and planning. This supports better decision-making for energy optimization and highlights the benefits of developing and refining data schemas using open data to bolster sustainability in the building sector. The study underscores the importance of supporting open data initiatives to collect similar features and support the creation of comparable models in Germany, enhancing the outlook for environmental sustainability.

Keywords: machine learning, remote sensing, residential building, energy performance certificates, data-driven, heat planning

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Authors: Fani Sakellariadou

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The Blue Economy includes all marine-based and marine-related activities. They correspond to established, emerging as well as unborn ocean-based industries. Seabed mining is an emerging marine-based activity; its operations depend particularly on cutting-edge science and technology. The 21st century will face a crisis in resources as a consequence of the world’s population growth and the rising standard of living. The natural capital stored in the global ocean is decisive for it to provide a wide range of sustainable ecosystem services. Seabed mineral deposits were identified as having a high potential for critical elements and base metals. They have a crucial role in the fast evolution of green technologies. The major categories of marine mineral deposits are deep-sea deposits, including cobalt-rich ferromanganese crusts, polymetallic nodules, phosphorites, and deep-sea muds, as well as shallow-water deposits including marine placers. Seabed mining operations may take place within continental shelf areas of nation-states. In international waters, the International Seabed Authority (ISA) has entered into 15-year contracts for deep-seabed exploration with 21 contractors. These contracts are for polymetallic nodules (18 contracts), polymetallic sulfides (7 contracts), and cobalt-rich ferromanganese crusts (5 contracts). Exploration areas are located in the Clarion-Clipperton Zone, the Indian Ocean, the Mid Atlantic Ridge, the South Atlantic Ocean, and the Pacific Ocean. Potential environmental impacts of deep-sea mining include habitat alteration, sediment disturbance, plume discharge, toxic compounds release, light and noise generation, and air emissions. They could cause burial and smothering of benthic species, health problems for marine species, biodiversity loss, reduced photosynthetic mechanism, behavior change and masking acoustic communication for mammals and fish, heavy metals bioaccumulation up the food web, decrease of the content of dissolved oxygen, and climate change. An important concern related to deep-sea mining is our knowledge gap regarding deep-sea bio-communities. The ecological consequences that will be caused in the remote, unique, fragile, and little-understood deep-sea ecosystems and inhabitants are still largely unknown. The blue economy conceptualizes oceans as developing spaces supplying socio-economic benefits for current and future generations but also protecting, supporting, and restoring biodiversity and ecological productivity. In that sense, people should apply holistic management and make an assessment of marine mining impacts on ecosystem services, including the categories of provisioning, regulating, supporting, and cultural services. The variety in environmental parameters, the range in sea depth, the diversity in the characteristics of marine species, and the possible proximity to other existing maritime industries cause a span of marine mining impact the ability of ecosystems to support people and nature. In conclusion, the use of the untapped potential of the global ocean demands a liable and sustainable attitude. Moreover, there is a need to change our lifestyle and move beyond the philosophy of single-use. Living in a throw-away society based on a linear approach to resource consumption, humans are putting too much pressure on the natural environment. Applying modern, sustainable and eco-friendly approaches according to the principle of circular economy, a substantial amount of natural resource savings will be achieved. Acknowledgement: This work is part of the MAREE project, financially supported by the Division VI of IUPAC. This work has been partly supported by the University of Piraeus Research Center.

Keywords: blue economy, deep-sea mining, ecosystem services, environmental impacts

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Authors: A. Aceranti, L. Moretti, S. Vernocchi, M. Colorato, P. Caristia

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Irritable bowel syndrome (IBS) is the association between abdominal pain, abdominal distension and intestinal dysfunction for recurring periods. About 10% of the world's population has IBS at any given time in their life, and about 200 people per 100,000 receive an initial diagnosis of IBS each year. Persistent pain is recognized as one of the most pervasive and challenging problems facing the medical community today. Persistent pain is considered more as a complex pathophysiological, diagnostic and therapeutic situation rather than as a persistent symptom. The low efficiency of conventional drug treatments has led many doctors to become interested in the non-drug alternative treatment of IBS, especially for more severe cases. Patients and providers are often dissatisfied with the available drug remedies and often seek complementary and alternative medicine (CAM), a unique and holistic approach to treatment that is not a typical component of conventional medicine. Osteopathic treatment may be of specific interest in patients with IBS. Osteopathy is a complementary health approach that emphasizes the role of the musculoskeletal system in health and promotes optimal function of the body's tissues using a variety of manual techniques to improve body function. Osteopathy has been defined as a patient-centered health discipline based on the principles of interrelation between body structure and function, the body's innate capacity for self-healing and the adoption of a whole person health approach. mainly by practicing manual processing. Studies reported that osteopathic manual treatment (OMT) reduced IBS symptoms, such as abdominal pain, constipation, diarrhea, and improved general well-being. The focus in the treatment of IBS with osteopathy has gone beyond simple spinal alignment, to directly address the abnormal physiology of the body using a series of direct and indirect techniques. The topic of this study was chosen for different reasons: due to the large number of people involved who suffer from this disorder and for the dysfunction itself, since nowadays there is still little clarity about the best type of treatment and, above all, to its origin. The visceral component in the osteopathic field is still a world to be discovered, although it is related to a large part of patient series, it has contents that affect numerous disciplines and this makes it an enigma yet to be solved. The study originated in the didactic practice where the curiosity of a topic is marked that, even today, no one is able to explain and, above all, cure definitively. The main purpose of this study is to try to create a good basis on the osteopathic discipline for subsequent studies that can be exhaustive in the best possible way, resolving some doubts about which treatment modality can be used with more relevance. The path was decided to structure it in such a way that 3 types of osteopathic treatment are used on 3 groups of people who will be selected after completing a questionnaire, which will deem them suitable for the study. They will, in fact, be divided into three groups where: - the first group was given a visceral osteopathic treatment. - The second group was given a manual osteopathic treatment of neurological stimulation. - The third group received a placebo treatment. At the end of the treatment, questionnaires will be re-proposed respectively one week after the session and one month after the treatment from which any data will be collected that will demonstrate the effectiveness or otherwise of the treatment received. The sample of 50 patients examined underwent an oral interview to evaluate the inclusion and exclusion criteria to participate in the study. Of the 50 patients questioned, 17 people who underwent different osteopathic techniques were eligible for the study. Comparing the data related to the first assessment of tenderness and frequency of symptoms with the data related to the first follow-up shows a significant improvement in the score assigned to the different questions, especially in the neurogenic and visceral groups. We are aware of the fact that it is a study performed on a small sample of patients, and this is a penalizing factor. We remain, however, convinced that having obtained good results in terms of subjective improvement in the quality of life of the subjects, it would be very interesting to re-propose the study on a larger sample and fill the gaps.

Keywords: IBS, osteopathy, colon, intestinal inflammation

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