Search results for: analysis of empirical research

Authors: Ousmane Sarr

Abstract:

The Senegalese coasts have high productivity of fishery resources due to the frequency of intense up-welling system that occurs along its coast, caused by the maritime trade winds making its waters nutrients rich. Fishing plays a primordial role in Senegal's socioeconomic plans and food security. However, a global diagnosis of the Senegalese maritime fishing sector has highlighted the challenges this sector encounters. Among these concerns, some significant stocks, a priority target for artisanal fishing, need further assessment. If no efforts are made in this direction, most stock will be overexploited or even in decline. It is in this context that this research was initiated. This investigation aimed to apply a multi-modal approach (LBB, Catch-only-based CMSY model and its most recent version (CMSY++); JABBA, and JABBA-Select) to assess the stock of Atlantic bonito, Sarda sarda (Bloch, 1793) in the Senegalese Exclusive Economic Zone (SEEZ). Available catch, effort, and size data from Atlantic bonito over 15 years (2004-2018) were used to calculate the nominal and standardized CPUE, size-frequency distribution, and length at retentions (50 % and 95 % selectivity) of the species. These relevant results were employed as input parameters for stock assessment models mentioned above to define the stock status of this species in this region of the Atlantic Ocean. The LBB model indicated an Atlantic bonito healthy stock status with B/BMSY values ranging from 1.3 to 1.6 and B/B0 values varying from 0.47 to 0.61 of the main scenarios performed (BON_AFG_CL, BON_GN_Length, and BON_PS_Length). The results estimated by LBB are consistent with those obtained by CMSY. The CMSY model results demonstrate that the SEEZ Atlantic bonito stock is in a sound condition in the final year of the main scenarios analyzed (BON, BON-bt, BON-GN-bt, and BON-PS-bt) with sustainable relative stock biomass (B2018/BMSY = 1.13 to 1.3) and fishing pressure levels (F2018/FMSY= 0.52 to 1.43). The B/BMSY and F/FMSY results for the JABBA model ranged between 2.01 to 2.14 and 0.47 to 0.33, respectively. In contrast, The estimated B/BMSY and F/FMSY for JABBA-Select ranged from 1.91 to 1.92 and 0.52 to 0.54. The Kobe plots results of the base case scenarios ranged from 75% to 89% probability in the green area, indicating sustainable fishing pressure and an Atlantic bonito healthy stock size capable of producing high yields close to the MSY. Based on the stock assessment results, this study highlighted scientific advice for temporary management measures. This study suggests an improvement of the selectivity parameters of longlines and purse seines and a temporary prohibition of the use of sleeping nets in the fishery for the Atlantic bonito stock in the SEEZ based on the results of the length-base models. Although these actions are temporary, they can be essential to reduce or avoid intense pressure on the Atlantic bonito stock in the SEEZ. However, it is necessary to establish harvest control rules to provide coherent and solid scientific information that leads to appropriate decision-making for rational and sustainable exploitation of Atlantic bonito in the SEEZ and the Eastern Atlantic Ocean.

Keywords: multi-model approach, stock assessment, atlantic bonito, SEEZ

Procedia PDF Downloads 45

Authors: Burak Oksuzoglu, Savas Yildirim, Ferhat Kutlu

Abstract:

Opinion mining (OM) is one of the natural language processing (NLP) problems to determine the polarity of opinions, mostly represented on a positive-neutral-negative axis. The data for OM is usually collected from various social media platforms. In an era where social media has considerable control over companies’ futures, it’s worth understanding social media and taking actions accordingly. OM comes to the fore here as the scale of the discussion about companies increases, and it becomes unfeasible to gauge opinion on individual levels. Thus, the companies opt to automize this process by applying machine learning (ML) approaches to their data. For the last two decades, OM or sentiment analysis (SA) has been mainly performed by applying ML classification algorithms such as support vector machines (SVM) and Naïve Bayes to a bag of n-gram representations of textual data. With the advent of deep learning and its apparent success in NLP, traditional methods have become obsolete. Transfer learning paradigm that has been commonly used in computer vision (CV) problems started to shape NLP approaches and language models (LM) lately. This gave a sudden rise to the usage of the pretrained language model (PTM), which contains language representations that are obtained by training it on the large datasets using self-supervised learning objectives. The PTMs are further fine-tuned by a specialized downstream task dataset to produce efficient models for various NLP tasks such as OM, NER (Named-Entity Recognition), Question Answering (QA), and so forth. In this study, the traditional and modern NLP approaches have been evaluated for OM by using a sizable corpus belonging to a large private company containing about 76,000 comments in Turkish: SVM with a bag of n-grams, and two chosen pre-trained models, multilingual universal sentence encoder (MUSE) and bidirectional encoder representations from transformers (BERT). The MUSE model is a multilingual model that supports 16 languages, including Turkish, and it is based on convolutional neural networks. The BERT is a monolingual model in our case and transformers-based neural networks. It uses a masked language model and next sentence prediction tasks that allow the bidirectional training of the transformers. During the training phase of the architecture, pre-processing operations such as morphological parsing, stemming, and spelling correction was not used since the experiments showed that their contribution to the model performance was found insignificant even though Turkish is a highly agglutinative and inflective language. The results show that usage of deep learning methods with pre-trained models and fine-tuning achieve about 11% improvement over SVM for OM. The BERT model achieved around 94% prediction accuracy while the MUSE model achieved around 88% and SVM did around 83%. The MUSE multilingual model shows better results than SVM, but it still performs worse than the monolingual BERT model.

Keywords: BERT, MUSE, opinion mining, pretrained language model, SVM, Turkish

Procedia PDF Downloads 116

Authors: M. G. Shilina

Abstract:

The interstate economic interaction phenomenon is complex. ‘Economic integration’, as one of its types, can be explored through the prism of international law, the theories of the world economy, politics and international relations. The most objective study of the phenomenon requires a comprehensive multifactoral approach. In new geopolitical realities, the problems of coexistence and possible interconnection of various mechanisms of interstate economic interaction are actively discussed. Currently, the Eurasian continent states support the direction to economic integration. At the same time, the existing international economic law fragmentation in Eurasia is seen as the important problem. The Eurasian space is characterized by a various types of interstate relations: international agreements (multilateral and bilateral), and a large number of cooperation formats (from discussion platforms to organizations aimed at deep integration). For their harmonization, it is necessary to have a clear vision to the phased international economic relations regulation options. In the conditions of rapid development of international economic relations, the modeling (including prognostic) can be optimally used as the main scientific method for presenting the phenomenon. On the basis of this method, it is possible to form the current situation vision and the best options for further action. In order to determine the most objective version of the integration development, the combination of several approaches were used. The normative legal approach- the descriptive method of legal modeling- was taken as the basis for the analysis. A set of legal methods was supplemented by the international relations science prognostic methods. The key elements of the model are the international economic organizations and states' associations existing in the Eurasian space (the Eurasian Economic Union (EAEU), the European Union (EU), the Shanghai Cooperation Organization (SCO), Chinese project ‘One belt-one road’ (OBOR), the Commonwealth of Independent States (CIS), BRICS, etc.). A general term for the elements of the model is proposed - the interstate interaction mechanisms (IIM). The aim of building a model of current and future Eurasian economic integration is to show optimal options for joint economic development of the states and IIMs. The long-term goal of this development is the new economic and political space, so-called the ‘Great Eurasian Community’. The process of achievement this long-term goal consists of successive steps. Modeling the integration architecture and dividing the interaction into stages led us to the following conclusion: the SCO is able to transform Eurasia into a single economic space. Gradual implementation of the complex phased model, in which the SCO+ plays a key role, will allow building an effective economic integration for all its participants, to create an economically strong community. The model can have practical value for politicians, lawyers, economists and other participants involved in the economic integration process. A clear, systematic structure can serve as a basis for further governmental action.

Keywords: economic integration, The Eurasian Economic Union, The European Union, The Shanghai Cooperation Organization, The Silk Road Economic Belt

Procedia PDF Downloads 129

Authors: Nezmin Kayedpour, Arash E. Samani, Siavash Asiaban, Jeroen M. De Kooning, Lieven Vandevelde, Guillaume Crevecoeur

Abstract:

The growing adoption of renewable energy sources, such as wind power, in electricity generation is a significant step towards a sustainable and decarbonized future. However, the inherent intermittency and uncertainty of wind resources pose challenges to the reliable and stable operation of power grids. To address this, hydrogen storage systems have emerged as a promising and versatile technology to support grid balancing services in wind energy conversion systems. In this study, we propose a supplementary control design that enhances the performance of the hydrogen storage system by integrating wind turbine (WT) pitch and torque control systems. These control strategies aim to optimize the hydrogen production process, ensuring efficient utilization of wind energy while complying with grid requirements. The wind turbine pitch control system plays a crucial role in managing the turbine's aerodynamic performance. By adjusting the blade pitch angle, the turbine's rotational speed and power output can be regulated. Our proposed control design dynamically coordinates the pitch angle to match the wind turbine's power output with the optimal hydrogen production rate. This ensures that the electrolyzer receives a steady and optimal power supply, avoiding unnecessary strain on the system during high wind speeds and maximizing hydrogen production during low wind speeds. Moreover, the wind turbine torque control system is incorporated to facilitate efficient operation at varying wind speeds. The torque control system optimizes the energy capture from the wind while limiting mechanical stress on the turbine components. By harmonizing the torque control with hydrogen production requirements, the system maintains stable wind turbine operation, thereby enhancing the overall energy-to-hydrogen conversion efficiency. To enable grid-friendly operation, we introduce a cascaded controller that regulates the electrolyzer's electrical power-current in accordance with grid requirements. This controller ensures that the hydrogen production rate can be dynamically adjusted based on real-time grid demands, supporting grid balancing services effectively. By maintaining a close relationship between the wind turbine's power output and the electrolyzer's current, the hydrogen storage system can respond rapidly to grid fluctuations and contribute to enhanced grid stability. In this paper, we present a comprehensive analysis of the proposed supplementary control design's impact on the overall performance of the hydrogen storage system in wind energy conversion systems. Through detailed simulations and case studies, we assess the system's ability to provide grid balancing services, maximize wind energy utilization, and reduce greenhouse gas emissions.

Keywords: active power control, electrolyzer, grid balancing services, wind energy conversion systems

Procedia PDF Downloads 55

Authors: Nutcha Taneepanichskul, Helen C. Hailes, Mark Miodownik

Abstract:

Plastic waste has emerged as a critical global environmental challenge, primarily driven by the prevalent use of conventional plastics derived from petrochemical refining and manufacturing processes in modern packaging. While these plastics serve vital functions, their persistence in the environment post-disposal poses significant threats to ecosystems. Addressing this issue necessitates approaches, one of which involves the development of biodegradable plastics designed to degrade under controlled conditions, such as industrial composting facilities. It is imperative to note that compostable plastics are engineered for degradation within specific environments and are not suited for uncontrolled settings, including natural landscapes and aquatic ecosystems. The full benefits of compostable packaging are realized when subjected to industrial composting, preventing environmental contamination and waste stream pollution. Therefore, effective sorting technologies are essential to enhance composting rates for these materials and diminish the risk of contaminating recycling streams. In this study, it leverage hyperspectral imaging technology (HSI) coupled with advanced machine learning algorithms to accurately identify various types of plastics, encompassing conventional variants like Polyethylene terephthalate (PET), Polypropylene (PP), Low density polyethylene (LDPE), High density polyethylene (HDPE) and biodegradable alternatives such as Polybutylene adipate terephthalate (PBAT), Polylactic acid (PLA), and Polyhydroxyalkanoates (PHA). The dataset is partitioned into three subsets: a training dataset comprising uncontaminated conventional and biodegradable plastics, a validation dataset encompassing contaminated plastics of both types, and a testing dataset featuring real-world packaging items in both pristine and contaminated states. Five distinct machine learning algorithms, namely Partial Least Squares Discriminant Analysis (PLS-DA), Support Vector Machine (SVM), Convolutional Neural Network (CNN), Logistic Regression, and Decision Tree Algorithm, were developed and evaluated for their classification performance. Remarkably, the Logistic Regression and CNN model exhibited the most promising outcomes, achieving a perfect accuracy rate of 100% for the training and validation datasets. Notably, the testing dataset yielded an accuracy exceeding 80%. The successful implementation of this sorting technology within recycling and composting facilities holds the potential to significantly elevate recycling and composting rates. As a result, the envisioned circular economy for plastics can be established, thereby offering a viable solution to mitigate plastic pollution.

Keywords: biodegradable plastics, sorting technology, hyperspectral imaging technology, machine learning algorithms

Procedia PDF Downloads 48

Authors: Léa Caban, Lucile Soudani, Julien Berger, Armelle Nouviaire, Emilio Bastidas-Arteaga

Abstract:

Improvement of the thermal performance of buildings is a high concern for the construction industry. With the increase in environmental issues, new types of construction materials are being developed. These include bio-based insulation materials. They capture carbon dioxide, can be produced locally, and have good thermal performance. However, their behavior with respect to moisture transfer is still facing some issues. With a high porosity, the mass transfer is more important in those materials than in mineral insulation ones. Therefore, they can be more sensitive to moisture disorders such as mold growth, condensation risks or decrease of the wall energy efficiency. For this reason, the initial moisture content on the construction site is a piece of crucial knowledge. Measuring moisture content in a laboratory is a mastered task. Diverse methods exist but the easiest and the reference one is gravimetric. A material is weighed dry and wet, and its moisture content is mathematically deduced. Non-destructive methods (NDT) are promising tools to determine in an easy and fast way the moisture content in a laboratory or on construction sites. However, the quality and reliability of the measures are influenced by several factors. Classical NDT portable devices usable on-site measure the capacity or the resistivity of materials. Water’s electrical properties are very different from those of construction materials, which is why the water content can be deduced from these measurements. However, most moisture meters are made to measure wooden materials, and some of them can be adapted for construction materials with calibration curves. Anyway, these devices are almost never calibrated for insulation materials. The main objective of this study is to determine the reliability of moisture meters in the measurement of biobased insulation materials. The determination of which one of the capacitive or resistive methods is the most accurate and which device gives the best result is made. Several biobased insulation materials are tested. Recycled cotton, two types of wood fibers of different densities (53 and 158 kg/m3) and a mix of linen, cotton, and hemp. It seems important to assess the behavior of a mineral material, so glass wool is also measured. An experimental campaign is performed in a laboratory. A gravimetric measurement of the materials is carried out for every level of moisture content. These levels are set using a climatic chamber and by setting the relative humidity level for a constant temperature. The mass-based moisture contents measured are considered as references values, and the results given by moisture meters are compared to them. A complete analysis of the uncertainty measurement is also done. These results are used to analyze the reliability of moisture meters depending on the materials and their water content. This makes it possible to determine whether the moisture meters are reliable, and which one is the most accurate. It will then be used for future measurements on construction sites to assess the initial hygrothermal state of insulation materials, on both new-build and renovation projects.

Keywords: capacitance method, electrical resistance method, insulation materials, moisture transfer, non-destructive testing

Procedia PDF Downloads 82

Authors: Shahrzad Zolfagharnassab, Abdul Rashid Mohamed Shariff, Siti Khairunniza Bejo

Abstract:

Conventional methods for nutrient soil mapping are based on laboratory tests of samples that are obtained from surveys. The time and cost involved in gathering and analyzing soil samples are the reasons that researchers use Predictive Soil Mapping (PSM). PSM can be defined as the development of a numerical or statistical model of the relationship among environmental variables and soil properties, which is then applied to a geographic database to create a predictive map. Kriging is a group of geostatistical techniques to spatially interpolate point values at an unobserved location from observations of values at nearby locations. The main problem with using kriging as an interpolator is that it is excessively data-dependent and requires a large number of closely spaced data points. Hence, there is a need to minimize the number of data points without sacrificing the accuracy of the results. In this paper, an Artificial Neural Networks (ANN) scheme was used to predict macronutrient values at un-sampled points. ANN has become a popular tool for prediction as it eliminates certain difficulties in soil property prediction, such as non-linear relationships and non-normality. Back-propagation multilayer feed-forward network structures were used to predict nitrogen, phosphorous and potassium values in the soil of the study area. A limited number of samples were used in the training, validation and testing phases of ANN (pattern reconstruction structures) to classify soil properties and the trained network was used for prediction. The soil analysis results of samples collected from the soil survey of block C of Sawah Sempadan, Tanjung Karang rice irrigation project at Selangor of Malaysia were used. Soil maps were produced by the Kriging method using 236 samples (or values) that were a combination of actual values (obtained from real samples) and virtual values (neural network predicted values). For each macronutrient element, three types of maps were generated with 118 actual and 118 virtual values, 59 actual and 177 virtual values, and 30 actual and 206 virtual values, respectively. To evaluate the performance of the proposed method, for each macronutrient element, a base map using 236 actual samples and test maps using 118, 59 and 30 actual samples respectively produced by the Kriging method. A set of parameters was defined to measure the similarity of the maps that were generated with the proposed method, termed the sample reduction method. The results show that the maps that were generated through the sample reduction method were more accurate than the corresponding base maps produced through a smaller number of real samples. For example, nitrogen maps that were produced from 118, 59 and 30 real samples have 78%, 62%, 41% similarity, respectively with the base map (236 samples) and the sample reduction method increased similarity to 87%, 77%, 71%, respectively. Hence, this method can reduce the number of real samples and substitute ANN predictive samples to achieve the specified level of accuracy.

Keywords: artificial neural network, kriging, macro nutrient, pattern recognition, precision farming, soil mapping

Procedia PDF Downloads 46

Authors: Vaiddehi Bansal, Laura Hinson, Mayumi Rezwan, Erin Leasure, Mithila Iyer, Connor Roth, Poulomi Pal, Kareem Kysia

Abstract:

As digital usage becomes increasingly ubiquitous worldwide, technology-facilitated gender-based violence (GBV) has garnered increasing attention in the recent years, especially during the COVID-19 pandemic. This form of violence is defined as “action by one or more people that harms others based on their sexual or gender identity or by enforcing harmful gender norms. This action is carried out using the internet and/or mobile technology that harms others based on their sexual or gender identity or by enforcing harmful gender norms”.Common forms of technology-facilitated GBV include cyberstalking, cyberbullying, sexual harassment, image-based abuse, doxing, hacking, gendertrolling, hate speech, and impersonation. Most literature on this pervasive yet complex issue has emerged from high-income countries, and few studies comprehensively summarize its prevalence, manifestations, and implications. This rigorous scoping review examines the evidence base of this phenomenon in low and middle-income countries across Asia, summarizing trends and gaps to inform actionable recommendations. The research team developed search terms to conduct a comprehensive search of peer-reviewed and grey literature. Query results were eligible for inclusion if they were published in English between 2006-2021 and with an explicit emphasis on technology-facilitated violence, gender, and the countries of interest in the Asia region. Title, abstracts, and full-texts were independently screened by two reviewers based on inclusion criteria, and data was extracted through deductive coding. Of 2,042 articles screened, 97 met inclusion criteria. The review revealed a gap in the evidence-base in Central Asia and the Pacific Islands. Findings across South and Southeast Asia indicate that technology-facilitated GBV comprises various forms of abuse, violence, and harassment that are largely shaped by country-specific societal norms and technological landscapes. The literature confirms that women, girls, and sexual minorities, especially those with intersecting marginalized identities, are often more vulnerable to experiencing online violence. Cultural norms and patriarchal structures tend to stigmatize survivors, limiting their ability to seek social and legal support. Survivors are also less likely to report their experience due to barriers such as lack of awareness of reporting mechanisms, the perception that digital platforms will not address their complaints, and cumbersome reporting systems. The COVID-19 pandemic has further exacerbated perpetration and strained support mechanisms. Prevalence varies by the form of violence but is difficult to estimate accurately due to underreporting and disjointed, outdated, or non-existent legal definitions. Addressing technology-facilitated GBV in Asia requires collective action from multiple actors, including government authorities, technology companies, digital and feminist movements, NGOs, and researchers.

Keywords: gender-based violence, technology, online sexual harassment, image-based abuse

Procedia PDF Downloads 101

Authors: Marcel Schulze, Behrem Aslan, Silke Lux, Alexandra Philipsen

Abstract:

Objective: Patients with Attention Deficit/Hyperactivity Disorder (ADHD) often report that they are being flooded by sensory impressions. Studies investigating sensory processing show hypersensitivity for sensory inputs across the senses in children and adults with ADHD. Especially the auditory modality is affected by deficient acoustical inhibition and modulation of signals. While studying unimodal signal-processing is relevant and well-suited in a controlled laboratory environment, everyday life situations occur multimodal. A complex interplay of the senses is necessary to form a unified percept. In order to achieve this, the unimodal sensory modalities are bound together in a process called multisensory integration (MI). In the current study we investigate MI in an adult ADHD sample using the McGurk-effect – a well-known illusion where incongruent speech like phonemes lead in case of successful integration to a new perceived phoneme via late top-down attentional allocation . In ADHD neuronal dysregulation at rest e.g., aberrant within or between network functional connectivity may also account for difficulties in integrating across the senses. Therefore, the current study includes resting-state functional connectivity to investigate a possible relation of deficient network connectivity and the ability of stimulus integration. Method: Twenty-five ADHD patients (6 females, age: 30.08 (SD:9,3) years) and twenty-four healthy controls (9 females; age: 26.88 (SD: 6.3) years) were recruited. MI was examined using the McGurk effect, where - in case of successful MI - incongruent speech-like phonemes between visual and auditory modality are leading to a perception of a new phoneme. Mann-Whitney-U test was applied to assess statistical differences between groups. Echo-planar imaging-resting-state functional MRI was acquired on a 3.0 Tesla Siemens Magnetom MR scanner. A seed-to-voxel analysis was realized using the CONN toolbox. Results: Susceptibility to McGurk was significantly lowered for ADHD patients (ADHDMdn:5.83%, ControlsMdn:44.2%, U= 160.5, p=0.022, r=-0.34). When ADHD patients integrated phonemes, reaction times were significantly longer (ADHDMdn:1260ms, ControlsMdn:582ms, U=41.0, p<.000, r= -0.56). In functional connectivity medio temporal gyrus (seed) was negatively associated with primary auditory cortex, inferior frontal gyrus, precentral gyrus, and fusiform gyrus. Conclusion: MI seems to be deficient for ADHD patients for stimuli that need top-down attentional allocation. This finding is supported by stronger functional connectivity from unimodal sensory areas to polymodal, MI convergence zones for complex stimuli in ADHD patients.

Keywords: attention-deficit hyperactivity disorder, audiovisual integration, McGurk-effect, resting-state functional connectivity

Procedia PDF Downloads 103

Authors: Rahul Ranjan

Abstract:

Using gender as a category to cull out historical analysis, feminist scholars have produced plethora of literature on the sexual symbolics and carnal practices of modern European empires. At a symbolic level, the penetration and conquest of faraway lands was charged with sexual significance and intrigue. The white male’s domination and possession of dark and fertile lands in Africa, Asia and the Americas offered, in Anne McClintock’s words, ‘a fantastic magic lantern of the mind onto which Europe projected its forbidden sexual desires and fears’. The politics of rape were also symbolically a question significant to the politics of empire. To the colonized subject, rape was a fearsome factor, a language that spoke of violent and voracious nature of imperial exploitation. The colonized often looked at rape as an act which colonizers used as tool of oppression. The rape as act of violence got encoded into the legal structure under the helm of Lord Macaulay in the so called ‘Age of Reform’ in 1860 under IPC (Indian penal code). Initially Lord Macaulay formed Indian Law Commission in 1837 in which he drafted a bill and defined the ‘crime of rape as sexual intercourse by a man to a woman against her will and without her consent , except in cases involving girls under nine years of age where consent was immaterial’. The modern English law of rape formulated under the colonial era introduced twofold issues to the forefront. On the one hand it deployed ‘technical experts’ who wrote textbooks of medical jurisprudence that were used as credential citation to make case more ‘objective’, while on the other hand the presumptions about barbaric subjects, the colonized women’s body that was docile which is prone to adultery reflected in cases. The untrustworthiness of native witness also remained an imperative for British jurists to put extra emphasis making ‘objective’ and ‘presumptuous’. This sort of formulation put women down on the pedestrian of justice because it disadvantaged her doubly through British legality and their thinking about the rape. The Imperial morality that acted as vanguards of women’s chastity coincided language of science propagated in the post-enlightenment which not only annulled non-conformist ideas but also made itself a hegemonic language, was often used as a tool and language in encoding of law. The medico-legal understanding of rape in the colonial India has its clear imprints in the post-colonial legality. The onus on the part of rape’s victim was dictated for the longest time and still continues does by widely referred idea that ‘there should signs, marks of resistance on the body of the victim’ otherwise it is likely to be considered consensual. Having said so, this paper looks at the textual continuity that had prolonged the colonial construct of women’s body and the self.

Keywords: body, politics, textual construct, phallocentric

Procedia PDF Downloads 351

Authors: Javier Carroquino, Nieves García-Casarejos, Pilar Gargallo, F. Javier García-Ramos

Abstract:

The energy used in agriculture is a source of global emissions of greenhouse gases. The two main types of this energy are electricity for pumping and diesel for agricultural machinery. In order to reduce these emissions, the European project LIFE REWIND addresses the supply of this demand from renewable sources. First of all, comprehensive data on energy demand and available renewable resources have been obtained in several case studies. Secondly, a set of simulations and optimizations have been performed, in search of the best configuration and sizing, both from an economic and emission reduction point of view. For this purpose, it was used software based on genetic algorithms. Thirdly, a prototype has been designed and installed, that it is being used for the validation in a real case. Finally, throughout a year of operation, various technical and economic parameters are being measured for further analysis. The prototype is not connected to the utility grid, avoiding the cost and environmental impact of a grid extension. The system includes three kinds of photovoltaic fields. One is located on a fixed structure on the terrain. Another one is floating on an irrigation raft. The last one is mounted on a two axis solar tracker. Each has its own solar inverter. The total amount of nominal power is 44 kW. A lead acid battery with 120 kWh of capacity carries out the energy storage. Three isolated inverters support a three phase, 400 V 50 Hz micro-grid, the same characteristics of the utility grid. An advanced control subsystem has been constructed, using free hardware and software. The electricity produced feeds a set of seven pumps used for purification, elevation and pressurization of water in a drip irrigation system located in a vineyard. Since the irrigation season does not include the whole year, as well as a small oversize of the generator, there is an amount of surplus energy. With this surplus, a hydrolyser produces on site hydrogen by electrolysis of water. An off-road vehicle with fuel cell feeds on that hydrogen and carries people in the vineyard. The only emission of the process is high purity water. On the one hand, the results show the technical and economic feasibility of stand-alone renewable energy systems to feed seasonal pumping. In this way, the economic costs, the environmental impacts and the landscape impacts of grid extensions are avoided. The use of diesel gensets and their associated emissions are also avoided. On the other hand, it is shown that it is possible to replace diesel in agricultural machinery, substituting it for electricity or hydrogen of 100% renewable origin and produced on the farm itself, without any external energy input. In addition, it is expected to obtain positive effects on the rural economy and employment, which will be quantified through interviews.

Keywords: drip irrigation, greenhouse gases, hydrogen, renewable energy, vineyard

Procedia PDF Downloads 323

Authors: Nabil Omar, Farah Jibril, Oraib Amjad

Abstract:

Purpose: Trabecatine is a is a potent marine-derived antineoplastic drug which binds to the minor groove of the DNA, bending DNA towards the major groove resulting in a changed conformation that interferes with several DNA transcription factors, repair pathways and cell proliferation. Trabectedin was approved by the European Medicines Agency (EMA; London, UK) for the treatment of adult patients with advanced stage soft tissue sarcomas in whom treatment with anthracyclines and ifosfamide has failed, or for those who are not candidates for these therapies. The recommended dosing regimen is 1.5 mg/m2 IV over 24 hours every 3 weeks. The purpose of this study was to comprehensively review available data on the safety and efficacy of trabectedin used as indicated for patients at a Tertiary Cancer Center at Qatar. Methods: A medication administration report generated in the electronic health record identified all patients who received trabectedin between November 1, 2015 and November 1, 2017. This retrospective chart review evaluated the indication of trabectedin use, compliance to administration protocol and the recommended monitoring parameters, number of patients improved on the drug and continued treatment, number of patients discontinued treatment due to side-effects and the reported side effects. Progress and discharged notes were utilized to report experienced side effects during trabectedin therapy. A total of 3 patients were reviewed. Results: Total of 2 out of 3 patients who received trabectedin were receiving it for non-FDA and non-EMA, approved indications; metastatic rhabdomyosarcoma and ovarian cancer stage IV with poor prognosis. And only one patient received it as indicated for leiomyosarcoma of left ureter with metastases to liver, lungs and bone. None of the patients has continued the therapy due to development of serious side effects. One patient had stopped the medication after one cycle due to disease progression and transient hepatic toxicity, the other one had disease progression and developed 12 % reduction in LVEF after 12 cycles of trabectedin, and the third patient deceased, had disease progression on trabectedin after the 10th cycle that was received through peripheral line which resulted in developing extravasation and left arm cellulitis requiring debridement. Regarding monitoring parameters, at baseline the three patients had ECHO, and Creatine Phosphokinase (CPK) but it was not monitored during treatment as recommended. Conclusion: Utilizing this medication as indicated with performing the appropriate monitoring parameters as recommended can benefit patients who are receiving it. It is important to reinforce the intravenous administration via central intravenous line, the re-assessment of left ventricular ejection fraction (LVEF) by echocardiogram or multigated acquisition (MUGA) scan at 2- to 3-month intervals thereafter until therapy is discontinued, and CPK and LFTs levels prior to each administration of trabectedin.

Keywords: trabectedin, drug-use evaluation, safety, effectiveness, adverse drug reaction, monitoring

Procedia PDF Downloads 112

Authors: Krzysztof Gwozdzinski, Janusz Mazur

Abstract:

Bory Tucholskie (Tucholskie Forest) is one of the largest pine forest complexes in Poland. It occupies approx. 3,000 square kilometers of Sandr in the Brda and Wda basin and the Tuchola Plain and the Charzykowskie Plain. Since 2010 it has transformed into The Bory Tucholskie Biosphere Reserve, according to the UNESCO decision. The area of the Bory Tucholskie National Park (BTNP), the park area, has been designated in 1996. There is little data on the presence of heavy metals in the Park's lakes. Concentration of heavy metals in the water of 19 lakes in the BTNP was examined. The lakes were divided into two groups: subglacial channel lakes of Struga Siedmiu Jezior (the Seven Lakes Stream) and other lakes. Heavy metals (transition metals) belong to d-block of elements. The part of these metals plays an important role in the function of living organisms as metalloproteins (enzymes, hemoproteins, vitamins, etc.). However, heavy metals are also typical; heavy metals are typical anthropogenic pollutants. Water samples were collected at the deepest points of lakes during spring and during summer stagnation. The analysis of metals was performed in an atomic absorption spectrophotometer Varian Spectra A300/400 in electric atomizer (GTA 96) in graphite cuvette. In the waters of the Seven Lakes Stream (Ostrowite, Zielone, Jelen, Belczak, Glowka, Plesno, Skrzynka, Mielnica) the increase in the concentration of the manganese and iron from outflow to inflow of Charzykowskie lake was found, while the concentration of copper (approx. 4 μg dm⁻³) and cadmium ( < 0.5 μg dm⁻³) was similar in all lakes. The concentration of the lead also varied within 2.1-3.6 μg dm⁻³. The concentration of nickel was approx. 3-fold higher in Ostrowite lake than other lakes of Struga. In turn the waters of the lakes Ostrowite, Jelen and Belczak were rich in zinc. The lowest level of heavy metals was observed in Zielone lake. In the second group of lakes, i.e., Krzywce Wielkie and Krzywce Male the heavy metal concentrations were lower than in the waters of Struga but higher than in oligotrophic lakes, i.e., Nierybno, Gluche, Kociol, Gacno Wielkie, Gacno Mae, Dlugie, Zabionek, and Sosnowek. The concentration of cadmium was below 0.5 μg dm⁻³ in all the studied lakes from this group. In the group of oligotrophic lakes the highest concentrations of metals such as manganese, iron, zinc and nickel in Gacno Male and Gacno Wielkie were observed. The high level of manganese in Sosnowek and Gacno Wielkie lakes was found. The lead level was also high in Nierybno lake and nickel in Gacno Wielkie lake. The lower level of heavy metals was in oligotrophic lakes such as Kociol, Dlugie, Zabionek and α-mesotrophic lake, Krzywce Wielkie. Generally, the level of heavy metals in studied lakes situated in Bory Tucholskie National Park was lower than in other lakes of Bory Tucholskie Biosphere Reserve.

Keywords: Bory Tucholskie Biosphere Reserve, Bory Tucholskie National Park, heavy metals, lakes

Procedia PDF Downloads 98

Authors: Simran Baweja, Bhavika Kalal, Surajit Maity

Abstract:

Photoinduced tautomerization reactions have been the centre of attention among scientific community over past several decades because of their significance in various biological systems. 7-azaindole (7AI) is considered as a model system for DNA base pairing and to understand the role of such tautomerization reactions in mutations. To the best of our knowledge, extensive studies have been carried on 7-azaindole and its solvent clusters exhibiting proton/ hydrogen transfer in both solution as well as gas phase. Derivatives of above molecule, like 2,7- and 2,6-diazaindoles are proposed to have even better photophysical properties due to the presence of -aza group on the 2nd position. However, there are a few studies in the solution phase which suggest the relevance of these molecules, but there are no experimental studies reported in the gas phase yet. In our current investigation, we present the first gas phase spectroscopic data of 2,7-diazaindole (2,7-DAI) and its solvent cluster (2,7-DAI-H2O). In this, we have employed state-of-the-art laser spectroscopic methods such as fluorescence excitation (LIF), dispersed fluorescence (DF), resonant two-photon ionization time of flight mass spectrometry (2C-R2PI), photoionization efficiency spectroscopy (PIE), IR-UV double resonance spectroscopy i.e. fluorescence-dip infrared spectroscopy (FDIR) and resonant ion-dip infrared spectroscopy (IDIR) to understand the electronic structure of the molecule. The origin band corresponding to S1 ← S0 transition of the bare 2,7-DAI is found to be positioned at 33910 cm-1 whereas the origin band corresponding to S1 ← S0 transition of the 2,7-DAI-H2O is positioned at 33074 cm-1. The red shifted transition in case of solvent cluster suggests the enhanced feasibility of excited state hydrogen/ proton transfer. The ionization potential for the 2,7-DAI molecule is found to be 8.92 eV, which is significantly higher that the previously reported 7AI (8.11 eV) molecule, making it a comparatively complex molecule to study. The ionization potential is reduced by 0.14 eV in case of 2,7-DAI-H2O (8.78 eV) cluster compared to that of 2,7-DAI. Moreover, on comparison with the available literature values of 7AI, we found the origin band of 2,7-DAI and 2,7-DAI-H2O to be red shifted by -729 and -280 cm-1 respectively. The ground and excited state N-H stretching frequencies of the 27DAI molecule were determined using fluorescence-dip infrared spectra (FDIR) and resonant ion dip infrared spectroscopy (IDIR), obtained at 3523 and 3467 cm-1, respectively. The lower value of vNH in the electronic excited state of 27DAI implies the higher acidity of the group compared to the ground state. Moreover, we have done extensive computational analysis, which suggests that the energy barrier in excited state reduces significantly as we increase the number of catalytic solvent molecules (S= H2O, NH3) as well as the polarity of solvent molecules. We found that the ammonia molecule is a better candidate for hydrogen transfer compared to water because of its higher gas-phase basicity. Further studies are underway to understand the excited state dynamics and photochemistry of such N-rich chromophores.

Keywords: photoinduced tautomerization reactions, gas phse spectroscopy, ), IR-UV double resonance spectroscopy, resonant two-photon ionization time of flight mass spectrometry (2C-R2PI)

Procedia PDF Downloads 56

Authors: Aysen Caliskan, Hanzade Haykiri-Acma, Serdar Yaman

Abstract:

Co-firing of coal and biomass blends is an effective method to reduce carbon dioxide emissions released by burning coals, thanks to the carbon-neutral nature of biomass. Besides, usage of biomass that is renewable and sustainable energy resource mitigates the dependency on fossil fuels for power generation. However, most of the biomass species has negative aspects such as low calorific value, high moisture and volatile matter contents compared to coal. Torrefaction is a promising technique in order to upgrade the fuel properties of biomass through thermal treatment. That is, this technique improves the calorific value of biomass along with serious reductions in the moisture and volatile matter contents. In this context, several woody biomass materials including Rhododendron, hybrid poplar, and ash-tree were subjected to torrefaction process in a horizontal tube furnace at 200°C under nitrogen flow. In this way, the solid residue obtained from torrefaction that is also called as 'biochar' was obtained and analyzed to monitor the variations taking place in biomass properties. On the other hand, some Turkish lignites from Elbistan, Adıyaman-Gölbaşı and Çorum-Dodurga deposits were chosen as coal samples since these lignites are of great importance in lignite-fired power stations in Turkey. These lignites were blended with the obtained biochars for which the blending ratio of biochars was kept at 10 wt% and the lignites were the dominant constituents in the fuel blends. Burning tests of the lignites, biomasses, biochars, and blends were performed using a thermogravimetric analyzer up to 900°C with a heating rate of 40°C/min under dry air atmosphere. Based on these burning tests, properties relevant to burning characteristics such as the burning reactivity and burnout yields etc. could be compared to justify the effects of torrefaction and blending. Besides, some characterization techniques including X-Ray Diffraction (XRD), Fourier Transform Infrared (FTIR) spectroscopy and Scanning Electron Microscopy (SEM) were also conducted for the untreated biomass and torrefied biomass (biochar) samples, lignites and their blends to examine the co-combustion characteristics elaborately. Results of this study revealed the fact that blending of lignite with 10 wt% biochar created synergistic behaviors during co-combustion in comparison to the individual burning of the ingredient fuels in the blends. Burnout and ignition performances of each blend were compared by taking into account the lignite and biomass structures and characteristics. The blend that has the best co-combustion profile and ignition properties was selected. Even though final burnouts of the lignites were decreased due to the addition of biomass, co-combustion process acts as a reasonable and sustainable solution due to its environmentally friendly benefits such as reductions in net carbon dioxide (CO2), SOx and hazardous organic chemicals derived from volatiles.

Keywords: burnout performance, co-combustion, thermal analysis, torrefaction pretreatment

Procedia PDF Downloads 317

Authors: Baha Eddine Aissou, Aichouche Belhadj Aissa

Abstract:

Light detection and ranging (LiDAR) is an active remote sensing technology used for several applications. Airborne LiDAR is becoming an important technology for the acquisition of a highly accurate dense point cloud. A classification of airborne laser scanning (ALS) point cloud is a very important task that still remains a real challenge for many scientists. Support vector machine (SVM) is one of the most used statistical learning algorithms based on kernels. SVM is a non-parametric method, and it is recommended to be used in cases where the data distribution cannot be well modeled by a standard parametric probability density function. Using a kernel, it performs a robust non-linear classification of samples. Often, the data are rarely linearly separable. SVMs are able to map the data into a higher-dimensional space to become linearly separable, which allows performing all the computations in the original space. This is one of the main reasons that SVMs are well suited for high-dimensional classification problems. Only a few training samples, called support vectors, are required. SVM has also shown its potential to cope with uncertainty in data caused by noise and fluctuation, and it is computationally efficient as compared to several other methods. Such properties are particularly suited for remote sensing classification problems and explain their recent adoption. In this poster, the SVM classification of ALS LiDAR data is proposed. Firstly, connected component analysis is applied for clustering the point cloud. Secondly, the resulting clusters are incorporated in the SVM classifier. Radial basic function (RFB) kernel is used due to the few numbers of parameters (C and γ) that needs to be chosen, which decreases the computation time. In order to optimize the classification rates, the parameters selection is explored. It consists to find the parameters (C and γ) leading to the best overall accuracy using grid search and 5-fold cross-validation. The exploited LiDAR point cloud is provided by the German Society for Photogrammetry, Remote Sensing, and Geoinformation. The ALS data used is characterized by a low density (4-6 points/m²) and is covering an urban area located in residential parts of the city Vaihingen in southern Germany. The class ground and three other classes belonging to roof superstructures are considered, i.e., a total of 4 classes. The training and test sets are selected randomly several times. The obtained results demonstrated that a parameters selection can orient the selection in a restricted interval of (C and γ) that can be further explored but does not systematically lead to the optimal rates. The SVM classifier with hyper-parameters is compared with the most used classifiers in literature for LiDAR data, random forest, AdaBoost, and decision tree. The comparison showed the superiority of the SVM classifier using parameters selection for LiDAR data compared to other classifiers.

Keywords: classification, airborne LiDAR, parameters selection, support vector machine

Procedia PDF Downloads 128

Authors: Fernanda A. P. Peres, Thiago N. Peres, Flavio S. Fogliatto, Michel J. Anzanello

Abstract:

Batch processes are widely used in food industry and have an important role in the production of high added value products, such as chocolate. Process performance is usually described by variables that are monitored as the batch progresses. Data arising from these processes are likely to display a strong correlation-autocorrelation structure, and are usually monitored using control charts based on multiway principal components analysis (MPCA). Process control of a new batch is carried out comparing the trajectories of its relevant process variables with those in a reference set of batches that yielded products within specifications; it is clear that proper determination of the reference set is key for the success of a correct signalization of non-conforming batches in such quality control schemes. In chocolate manufacturing, misclassifications of non-conforming batches in the conching phase may lead to significant financial losses. In such context, the accuracy of process control grows in relevance. In addition to that, the main assumption in MPCA-based monitoring strategies is that all batches are synchronized in duration, both the new batch being monitored and those in the reference set. Such assumption is often not satisfied in chocolate manufacturing process. As a consequence, traditional techniques as MPCA-based charts are not suitable for process control and monitoring. To address that issue, the objective of this work is to compare the performance of three dynamic time warping (DTW) methods in the alignment and synchronization of chocolate conching process variables’ trajectories, aimed at properly determining the reference distribution for multivariate statistical process control. The power of classification of batches in two categories (conforming and non-conforming) was evaluated using the k-nearest neighbor (KNN) algorithm. Real data from a milk chocolate conching process was collected and the following variables were monitored over time: frequency of soybean lecithin dosage, rotation speed of the shovels, current of the main motor of the conche, and chocolate temperature. A set of 62 batches with durations between 495 and 1,170 minutes was considered; 53% of the batches were known to be conforming based on lab test results and experts’ evaluations. Results showed that all three DTW methods tested were able to align and synchronize the conching dataset. However, synchronized datasets obtained from these methods performed differently when inputted in the KNN classification algorithm. Kassidas, MacGregor and Taylor’s (named KMT) method was deemed the best DTW method for aligning and synchronizing a milk chocolate conching dataset, presenting 93.7% accuracy, 97.2% sensitivity and 90.3% specificity in batch classification, being considered the best option to determine the reference set for the milk chocolate dataset. Such method was recommended due to the lowest number of iterations required to achieve convergence and highest average accuracy in the testing portion using the KNN classification technique.

Keywords: batch process monitoring, chocolate conching, dynamic time warping, reference set distribution, variable duration

Procedia PDF Downloads 144

Authors: Stojan Kravanja, Andrej Ivanič, Tomaž Žula

Abstract:

This contribution focuses on structural optimization in civil engineering using mixed integer non-linear programming (MINLP). MINLP is characterized as a versatile method that can handle both continuous and discrete optimization variables simultaneously. Continuous variables are used to optimize parameters such as dimensions, stresses, masses, or costs, while discrete variables represent binary decisions to determine the presence or absence of structural elements within a structure while also calculating discrete materials and standard sections. The optimization process is divided into three main steps. First, a mechanical superstructure with a variety of different topology-, material- and dimensional alternatives. Next, a MINLP model is formulated to encapsulate the optimization problem. Finally, an optimal solution is searched in the direction of the defined objective function while respecting the structural constraints. The economic or mass objective function of the material and labor costs of a structure is subjected to the constraints known from structural analysis. These constraints include equations for the calculation of internal forces and deflections, as well as equations for the dimensioning of structural components (in accordance with the Eurocode standards). Given the complex, non-convex and highly non-linear nature of optimization problems in civil engineering, the Modified Outer-Approximation/Equality-Relaxation (OA/ER) algorithm is applied. This algorithm alternately solves subproblems of non-linear programming (NLP) and main problems of mixed-integer linear programming (MILP), in this way gradually refines the solution space up to the optimal solution. The NLP corresponds to the continuous optimization of parameters (with fixed topology, discrete materials and standard dimensions, all determined in the previous MILP), while the MILP involves a global approximation to the superstructure of alternatives, where a new topology, materials, standard dimensions are determined. The optimization of a convex problem is stopped when the MILP solution becomes better than the best NLP solution. Otherwise, it is terminated when the NLP solution can no longer be improved. While the OA/ER algorithm, like all other algorithms, does not guarantee global optimality due to the presence of non-convex functions, various modifications, including convexity tests, are implemented in OA/ER to mitigate these difficulties. The effectiveness of the proposed MINLP approach is demonstrated by its application to various structural optimization tasks, such as mass optimization of steel buildings, cost optimization of timber halls, composite floor systems, etc. Special optimization models have been developed for the optimization of these structures. The MINLP optimizations, facilitated by the user-friendly software package MIPSYN, provide insights into a mass or cost-optimal solutions, optimal structural topologies, optimal material and standard cross-section choices, confirming MINLP as a valuable method for the optimization of structures in civil engineering.

Keywords: MINLP, mixed-integer non-linear programming, optimization, structures

Procedia PDF Downloads 19

Authors: Shayan Mohajer Hamidi

Abstract:

Federated Learning (FL) has emerged as a promising paradigm for training machine learning models on distributed data without the need for centralized data aggregation. In the realm of wireless communications, FL has the potential to leverage the vast amounts of data generated by wireless devices to improve model performance and enable intelligent applications. However, the fairness aspect of FL in wireless communications remains largely unexplored. This abstract presents an idea for fair federated learning in wireless communications, addressing the challenges of imbalanced data distribution, privacy preservation, and resource allocation. Firstly, the proposed approach aims to tackle the issue of imbalanced data distribution in wireless networks. In typical FL scenarios, the distribution of data across wireless devices can be highly skewed, resulting in unfair model updates. To address this, we propose a weighted aggregation strategy that assigns higher importance to devices with fewer samples during the aggregation process. By incorporating fairness-aware weighting mechanisms, the proposed approach ensures that each participating device's contribution is proportional to its data distribution, thereby mitigating the impact of data imbalance on model performance. Secondly, privacy preservation is a critical concern in federated learning, especially in wireless communications where sensitive user data is involved. The proposed approach incorporates privacy-enhancing techniques, such as differential privacy, to protect user privacy during the model training process. By adding carefully calibrated noise to the gradient updates, the proposed approach ensures that the privacy of individual devices is preserved without compromising the overall model accuracy. Moreover, the approach considers the heterogeneity of devices in terms of computational capabilities and energy constraints, allowing devices to adaptively adjust the level of privacy preservation to strike a balance between privacy and utility. Thirdly, efficient resource allocation is crucial for federated learning in wireless communications, as devices operate under limited bandwidth, energy, and computational resources. The proposed approach leverages optimization techniques to allocate resources effectively among the participating devices, considering factors such as data quality, network conditions, and device capabilities. By intelligently distributing the computational load, communication bandwidth, and energy consumption, the proposed approach minimizes resource wastage and ensures a fair and efficient FL process in wireless networks. To evaluate the performance of the proposed fair federated learning approach, extensive simulations and experiments will be conducted. The experiments will involve a diverse set of wireless devices, ranging from smartphones to Internet of Things (IoT) devices, operating in various scenarios with different data distributions and network conditions. The evaluation metrics will include model accuracy, fairness measures, privacy preservation, and resource utilization. The expected outcomes of this research include improved model performance, fair allocation of resources, enhanced privacy preservation, and a better understanding of the challenges and solutions for fair federated learning in wireless communications. The proposed approach has the potential to revolutionize wireless communication systems by enabling intelligent applications while addressing fairness concerns and preserving user privacy.

Keywords: federated learning, wireless communications, fairness, imbalanced data, privacy preservation, resource allocation, differential privacy, optimization

Procedia PDF Downloads 50

Authors: Peggy M. Randon, Lisa Randon

Abstract:

Introduction: The post-COVID-19 era has presented unique challenges for addressing complex mental health issues, particularly due to exacerbated stress, increased social isolation, and disrupted continuity of care. This article outlines relevant health disparities and policy implications within the context of the United States while maintaining international relevance. Methods: A comprehensive literature review (including studies, reports, and policy documents) was conducted to examine concerns related to childhood-onset schizophrenia and the impact on patients and their families. Qualitative and quantitative data were synthesized to provide insights into the complex etiology of schizophrenia, the effects of the pandemic, and the challenges faced by socioeconomically disadvantaged populations. Case studies were employed to illustrate real-world examples and areas requiring policy reform. Results: Early intervention in childhood is crucial for preventing or mitigating the long-term impact of complex psychotic disorders, particularly schizophrenia. A comprehensive understanding of the genetic, environmental, and physiological factors contributing to the development of schizophrenia is essential. The COVID-19 pandemic worsened symptoms and disrupted treatment for many adolescent patients with schizophrenia, emphasizing the need for adaptive interventions and the utilization of virtual platforms. Health disparities, including stigma, financial constraints, and language or cultural barriers, further limit access to care, especially for socioeconomically disadvantaged populations. Policy implications: Current US health policies inadequately support patients with schizophrenia. The limited availability of longitudinal care, insufficient resources for families, and stigmatization represent ongoing policy challenges. Addressing these issues necessitates increased research funding, improved access to affordable treatment plans, and cultural competency training for healthcare providers. Public awareness campaigns are crucial to promote knowledge, awareness, and acceptance of mental health disorders. Conclusion: The unique challenges faced by children and families in the US affected by schizophrenia and other psychotic disorders have yet to be adequately addressed on institutional and systemic levels. The relevance of findings to an international audience is emphasized by examining the complex factors contributing to the onset of psychotic disorders and their global policy implications. The broad impact of the COVID-19 pandemic on mental health underscores the need for adaptive interventions and global responses. Addressing policy challenges, improving access to care, and reducing the stigma associated with mental health disorders are crucial steps toward enhancing the lives of adolescents and young adults with schizophrenia and their family members. The implementation of virtual platforms can help overcome barriers and ensure equitable access to support and resources for all patients, enabling them to lead healthy and fulfilling lives.

Keywords: childhood, schizophrenia, policy, United, States, health, disparities

Procedia PDF Downloads 53

Authors: Marina Shargorodsky

Abstract:

Aim: Gestational weight gain (GWG) has been related to altering future weight-gain curves and increased risks of obesity later in life. Obesity may contribute to vascular atherosclerotic changes as well as excess cardiovascular morbidity and mortality observed in these patients. Noninvasive arterial testing, such as ultrasonographic measurement of carotid IMT, is considered a surrogate for systemic atherosclerotic disease burden and is predictive of cardiovascular events in asymptomatic individuals as well as recurrent events in patients with known cardiovascular disease. Currently, there is no consistent evidence regarding the vascular impact of excessive GWG. The present study was designed to investigate the impact of GWG on early atherosclerotic changes during late pregnancy, using intima-media thickness, as well as placental vascular circulation and inflammatory lesions and pregnancy outcomes. Methods: The study group consisted of 59 pregnant women who gave birth and underwent a placental histopathological examination at the Department of Obstetrics and Gynecology, Edith Wolfson Medical Center, Israel, in 2019. According to the IOM guidelines the study group has been divided into two groups: Group 1 included 32 women with pregnancy weight gain within recommended range; Group 2 included 27 women with excessive weight gain during pregnancy. The IMT was measured from non-diseased intimal and medial wall layers of the carotid artery on both sides, visualized by high-resolution 7.5 MHz ultrasound (Apogee CX Color, ATL). Placental histology subdivided placental findings to lesions consistent with maternal vascular and fetal vascular malperfusion according to the criteria of the Society for Pediatric Pathology, subdividing placental findings to lesions consistent with maternal vascular and fetal vascular malperfusion, as well as the inflammatory response of maternal and fetal origin. Results: IMT levels differed between groups and were significantly higher in Group 1 compared to Group 2 (0.7+/-0.1 vs 0.6+/-0/1, p=0.028). Multiple linear regression analysis of IMT included variables based on their associations in univariate analyses with a backward approach. Included in the model were pre-gestational BMI, HDL cholesterol and fasting glucose. The model was significant (p=0.001) and correctly classified 64.7% of study patients. In this model, pre-pregnancy BMI remained a significant independent predictor of subclinical atherosclerosis assessed by IMT (OR 4.314, 95% CI 0.0599-0.674, p=0.044). Among placental lesions related to fetal vascular malperfusion, villous changes consistent with fetal thrombo-occlusive disease (FTOD) were significantly higher in Group 1 than in Group 2, p=0.034). In Conclusion, the present study demonstrated that excessive weight gain during pregnancy is associated with an adverse effect on early stages of subclinical atherosclerosis, placental vascular circulation and neonatal complications. The precise mechanism for these vascular changes, as well as the overall clinical impact of weight control during pregnancy on IMT, placental vascular circulation as well as pregnancy outcomes, deserves further investigation.

Keywords: obesity, pregnancy, complications, weight gain

Procedia PDF Downloads 31

Authors: Bruce Wrightsman

Abstract:

Construction and design are inexorably linked. Traditional building methodologies, including those using wood, comprise a series of material layers differentiated and separated from each other. This results in the separation of two agencies of building envelope (skin) separate from the structure. However, from a material performance position reliant on additional materials, this is not an efficient strategy for the building. The merits of traditional platform framing are well known. However, its enormous effectiveness within wood-framed construction has seldom led to serious questioning and challenges in defining what it means to build. There are several downsides of using this method, which is less widely discussed. The first and perhaps biggest downside is waste. Second, its reliance on wood assemblies forming walls, floors and roofs conventionally nailed together through simple plate surfaces is structurally inefficient. It requires additional material through plates, blocking, nailers, etc., for stability that only adds to the material waste. In contrast, when we look back at the history of wood construction in airplane and boat manufacturing industries, we will see a significant transformation in the relationship of structure with skin. The history of boat construction transformed from indigenous wood practices of birch bark canoes to copper sheathing over wood to improve performance in the late 18th century and the evolution of merged assemblies that drives the industry today. In 1911, Swiss engineer Emile Ruchonnet designed the first wood monocoque structure for an airplane called the Cigare. The wing and tail assemblies consisted of thin, lightweight, and often fabric skin stretched tightly over a wood frame. This stressed skin has evolved into semi-monocoque construction, in which the skin merges with structural fins that take additional forces. It provides even greater strength with less material. The monocoque, which translates to ‘mono or single shell,’ is a structural system that supports loads and transfers them through an external enclosure system. They have largely existed outside the domain of architecture. However, this uniting of divergent systems has been demonstrated to be lighter, utilizing less material than traditional wood building practices. This paper will examine the role monocoque systems have played in the history of wood construction through lineage of boat and airplane building industries and its design potential for wood building systems in architecture through a case-study examination of a unique wood construction approach. The innovative approach uses a wood monocoque system comprised of interlocking small wood members to create thin shell assemblies for the walls, roof and floor, increasing structural efficiency and wasting less than 2% of the wood. The goal of the analysis is to expand the work of practice and the academy in order to foster deeper, more honest discourse regarding the limitations and impact of traditional wood framing.

Keywords: wood building systems, material histories, monocoque systems, construction waste

Procedia PDF Downloads 60

Authors: Mohammadreza Nematollahi, Bahareh Mosadegh Sedghy, Alireza Tajbakhsh

Abstract:

The last two decades have witnessed substantial attention to organic and sustainable agricultural supply chains. Motivated by real-world practices, this paper aims to address two main challenges observed in organic product supply chains: decentralized decision-making process between farmers and their retailers, and competition between organic products and their conventional counterparts. To this aim, an agricultural supply chain consisting of two farmers, a conventional farmer and an organic farmer who offers an organic version of the same product, is considered. Both farmers distribute their products through a single retailer, where there exists competition between the organic and the conventional product. The retailer, as the market leader, sets the wholesale price, and afterward, the farmers set their production quantity decisions. This paper first models the demand functions of the conventional and organic products by incorporating the effect of asymmetric brand equity, which captures the fact that consumers usually pay a premium for organic due to positive perceptions regarding their health and environmental benefits. Then, profit functions with consideration of some characteristics of organic farming, including crop yield gap and organic cost factor, are modeled. Our research also considers both economies and diseconomies of scale in farming production as well as the effects of organic subsidy paid by the government to support organic farming. This paper explores the investigated supply chain in three scenarios: decentralized, centralized, and coordinated decision-making structures. In the decentralized scenario, the conventional and organic farmers and the retailer maximize their own profits individually. In this case, the interaction between the farmers is modeled under the Bertrand competition, while analyzing the interaction between the retailer and farmers under the Stackelberg game structure. In the centralized model, the optimal production strategies are obtained from the entire supply chain perspective. Analytical models are developed to derive closed-form optimal solutions. Moreover, analytical sensitivity analyses are conducted to explore the effects of main parameters like the crop yield gap, organic cost factor, organic subsidy, and percent price premium of the organic product on the farmers’ and retailer’s optimal strategies. Afterward, a coordination scenario is proposed to convince the three supply chain members to shift from the decentralized to centralized decision-making structure. The results indicate that the proposed coordination scenario provides a win-win-win situation for all three members compared to the decentralized model. Moreover, our paper demonstrates that the coordinated model respectively increases and decreases the production and price of organic produce, which in turn motivates the consumption of organic products in the market. Moreover, the proposed coordination model helps the organic farmer better handle the challenges of organic farming, including the additional cost and crop yield gap. Last but not least, our results highlight the active role of the organic subsidy paid by the government as a means of promoting sustainable organic product supply chains. Our paper shows that although the amount of organic subsidy plays a significant role in the production and sales price of organic products, the allocation method of subsidy between the organic farmer and retailer is not of that importance.

Keywords: analytical game-theoretic model, product competition, supply chain coordination, sustainable organic supply chain

Procedia PDF Downloads 87

Authors: Khodzhaberdi Allaberdiev

Abstract:

In order to understand the interactions on the interface polyamide fibers and epoxy matrix in fiber- reinforced composites were investigated industrial aramid fibers: armos, svm, terlon using individual epoxy matrix components, epoxies: diglycidyl ether of bisphenol A (DGEBA), three- and diglycidyl derivatives of m, p-amino-, m, p-oxy-, o, m,p-carboxybenzoic acids, the models: curing agent, aniline and the compound, that depict of the structure the primary addition reaction the amine to the epoxy resin, N-di (oxyethylphenoxy) aniline. The chemical structure of the surface of untreated and treated polyamide fibers analyzed using Fourier transform infrared spectroscopy (FTIR). The impregnation of fibers with epoxy matrix components and N-di (oxyethylphenoxy) aniline has been carried out by heating 150˚C (6h). The optimum fiber loading is at 65%.The result a thermal treatment is the covalent bonds formation , derived from a combined of homopolymerization and crosslinking mechanisms in the interfacial region between the epoxy resin and the surface of fibers. The reactivity of epoxy resins on interface in microcomposites (MC) also depends from processing aids treated on surface of fiber and the absorbance moisture. The influences these factors as evidenced by the conversion of epoxy groups values in impregnated with DGEBA of the terlons: industrial, dried (in vacuum) and purified samples: 5.20 %, 4.65% and 14.10%, respectively. The same tendency for svm and armos fibers is observed. The changes in surface composition of these MC were monitored by X-ray photoelectron spectroscopy (XPS). In the case of the purified fibers, functional groups of fibers act as well as a catalyst and curing agent of epoxy resin. It is found that the value of the epoxy groups conversion for reinforced formulations depends on aromatic polyamides nature and decreases in the order: armos >svm> terlon. This difference is due of the structural characteristics of fibers. The interfacial interactions also examined between polyglycidyl esters substituted benzoic acids and polyamide fibers in the MC. It is found that on interfacial interactions these systems influences as well as the structure and the isomerism of epoxides. The IR-spectrum impregnated fibers with aniline showed that the polyamide fibers appreciably with aniline do not react. FTIR results of treated fibers with N-di (oxyethylphenoxy) aniline fibers revealed dramatically changes IR-characteristic of the OH groups of the amino alcohol. These observations indicated hydrogen bondings and covalent interactions between amino alcohol and functional groups of fibers. This result also confirms appearance of the exo peak on Differential Scanning Calorimetry (DSC) curve of the MC. Finally, the theoretical evaluation non-covalent interactions between individual epoxy matrix components and fibers has been performed using the benzanilide and its derivative contaning the benzimidazole moiety as a models of terlon and svm,armos, respectively. Quantum-topological analysis also demonstrated the existence hydrogen bond between amide group of models and epoxy matrix components.All the results indicated that on the interface polyamide fibers and epoxy matrix exist not only covalent, but and non-covalent the interactions during the preparation of MC.

Keywords: epoxies, interface, modeling, polyamide fibers

Procedia PDF Downloads 248

Authors: Anna Carolina De Paula Sermarini, Rodrigo Flora Calili

Abstract:

Energy Efficiency (EE) needs investments, new technologies, greater awareness and management on the side of citizens and organizations, and more planning. However, this issue is usually remembered and discussed only in moments of energy crises, and opportunities are missed to take better advantage of the potential of EE in the various sectors of the economy. In addition, there is little concern about the subject among the less favored classes, especially in low-income communities. Accordingly, this article presents suggestions for public policies that aim to increase EE for low-income housing and communities based on international and national experiences. After reviewing the literature, eight policies were listed, and to evaluate them; a multicriteria decision model was developed using the AHP (Analytical Hierarchy Process) and TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) methods, combined with fuzzy logic. Nine experts analyzed the policies according to 9 criteria: economic impact, social impact, environmental impact, previous experience, the difficulty of implementation, possibility/ease of monitoring and evaluating the policies, expected impact, political risks, and public governance and sustainability of the sector. The results found in order of preference are (i) Incentive program for equipment replacement; (ii) Community awareness program; (iii) EE Program with a greater focus on low income; (iv) Staggered and compulsory certification of social interest buildings; (v) Programs for the expansion of smart metering, energy monitoring and digitalization; (vi) Financing program for construction and retrofitting of houses with the emphasis on EE; (vii) Income tax deduction for investment in EE projects in low-income households made by companies; (viii) White certificates of energy for low-income. First, the policy of equipment substitution has been employed in Brazil and the world and has proven effective in promoting EE. For implementation, efforts are needed from the federal and state governments, which can encourage companies to reduce prices, and provide some type of aid for the purchase of such equipment. In second place is the community awareness program, promoting socio-educational actions on EE concepts and with energy conservation tips. This policy is simple to implement and has already been used by many distribution utilities in Brazil. It can be carried out through bids defined by the government in specific areas, being executed by third sector companies with public and private resources. Third on the list is the proposal to continue the Energy Efficiency Program (which obliges electric energy companies to allocate resources for research in the area) by suggesting the return of the mandatory investment of 60% of the resources in projects for low income. It is also relatively simple to implement, requiring efforts by the federal government to make it mandatory, and on the part of the distributors, compliance is needed. The success of the suggestions depends on changes in the established rules and efforts from the interested parties. For future work, we suggest the development of pilot projects in low-income communities in Brazil and the application of other multicriteria decision support methods to compare the results obtained in this study.

Keywords: energy efficiency, low-income community, public policy, multicriteria decision making

Procedia PDF Downloads 84

Authors: Md. Nuru Miah, A. F. M. Akhter Uddin

Abstract:

Medicinal plants are grown naturally in a tropical environment in Bangladesh and used as drug and therapeutic agents in the health care system. According to Bangladesh Agricultural Research Institute (BARI), there are 722 species of medicinal plants in the country. Of them, 255 plants are utilized by the manufacturers of Ayurvedic and Unani medicines. Medicinal plants like Aloevera, Ashwagonda, shotomul,Tulsi, Vuikumra, Misridana are extensively cultivated in some selected areas as well; where Aloevera scored the highest position in production. In the early 1980, Ayurvedic and Unani companies procured 80 percent of medicinal plants from natural forests, and the rest 20 percent was imported. Now the scenario has changed; 80 percent is imported, and the rest 20 percent is collected from local products(Source: Astudy on sectorbased need assessment of Business promotion council-Herbal products and medicinal plants, page-4). Uttara Development Program Society, a leading Non- Government development organization in Bangladesh, has been implementing a value chain development project under promoting Agricultural commercialization and Enterprises of Pally Karma Sahayak Foundation (PKSF) funded by the International Fund for Agricultural Development (IFAD) in Natore Sadar Upazila from April 2017 to sustainably develop the technological interventions for products and market development. The ultimate goal of the project is to increase income, generate employment and develop this sector as a sustainable business enterprise. Altogether 10,000 farmers (Nursery owners, growers, input supplier, processors, whole sellers, and retailers) are engaged in different activities of the project. The entrepreneurs engaged in medicinal plant cultivation did not know and follow environmental and good agricultural practices. They used to adopt traditional methodology in production and processing. Locally the farmers didn’t have any positive initiative to expand their business as well as developvalue added products. A lot of diversified products could be possible to develop and marketed with the introduction of post-harvest processing technology and market linkage with the local and global buyer. Training is imparted to the nursery owners and herbal growers on production technologies, sowing method, use of organic fertilizers/compost/pesticides, harvesting procedures, and storage facilities. Different types of herbal tea like Rosella, Moringa, Tulshi, and Basak are being produced and packed locally with a good scope of its marketing in different cities of the country. The project has been able to achieve a significant impact in the development of production technologies, but still, there is room for further improvement in processing, packaging, and marketing level. The core intervention of the current project to develop some entrepreneurs for branding, packaging, promotion, and marketing while considering environment friendly practices. The present strategies will strengthen the knowledge and skills of the entrepreneurs for the production and marketing of their products, maintaining worldwide accepted compliance system for easy access to the global market.

Keywords: aloe vera, herbs and shrubs, market, interventions

Procedia PDF Downloads 65

Authors: Maria Lazari, Lorenzo Sanavia

Abstract:

Mechanics of unsaturated soils has been an active field of research in the last decades. Efficient constitutive models that take into account the partial saturation of soil are necessary to solve a number of engineering problems e.g. instability of slopes and cuts due to heavy rainfalls. A large number of constitutive models can now be found in the literature that considers fundamental issues associated with the unsaturated soil behaviour, like the volume change and shear strength behaviour with suction or saturation changes. Partially saturated soils may either expand or collapse upon wetting depending on the stress level, and it is also possible that a soil might experience a reversal in the volumetric behaviour during wetting. Shear strength of soils also changes dramatically with changes in the degree of saturation, and a related engineering problem is slope failures caused by rainfall. There are several states of the art reviews over the last years for studying the topic, usually providing a thorough discussion of the stress state, the advantages, and disadvantages of specific constitutive models as well as the latest developments in the area of unsaturated soil modelling. However, only a few studies focused on the coupling between partial saturation states and time effects on the behaviour of geomaterials. Rate dependency is experimentally observed in the mechanical response of granular materials, and a viscoplastic constitutive model is capable of reproducing creep and relaxation processes. Therefore, in this work an elasto-viscoplastic constitutive model for unsaturated soils is proposed and validated on the basis of experimental data. The model constitutes an extension of an existing elastoplastic strain-hardening constitutive model capable of capturing the behaviour of variably saturated soils, based on energy conjugated stress variables in the framework of superposed continua. The purpose was to develop a model able to deal with possible mechanical instabilities within a consistent energy framework. The model shares the same conceptual structure of the elastoplastic laws proposed to deal with bonded geomaterials subject to weathering or diagenesis and is capable of modelling several kinds of instabilities induced by the loss of hydraulic bonding contributions. The novelty of the proposed formulation is enhanced with the incorporation of density dependent stiffness and hardening coefficients in order to allow the modeling of the pycnotropy behaviour of granular materials with a single set of material constants. The model has been implemented in the commercial FE platform PLAXIS, widely used in Europe for advanced geotechnical design. The algorithmic strategies adopted for the stress-point algorithm had to be revised to take into account the different approach adopted by PLAXIS developers in the solution of the discrete non-linear equilibrium equations. An extensive comparison between models with a series of experimental data reported by different authors is presented to validate the model and illustrate the capability of the newly developed model. After the validation, the effectiveness of the viscoplastic model is displayed by numerical simulations of a partially saturated slope failure of the laboratory scale and the effect of viscosity and degree of saturation on slope’s stability is discussed.

Keywords: PLAXIS software, slope, unsaturated soils, Viscoplasticity

Procedia PDF Downloads 198

Authors: Venencia Albert, Arulselvi Subramanian, Hara Prasad Pati, Asok K. Mukhophadhyay

Abstract:

Acute traumatic coagulopathy in an endogenous dysregulation of the intrinsic coagulation system in response to the injury, associated with three-fold risk of poor outcome, and is more amenable to corrective interventions, subsequent to early identification and management. Multiple definitions for stratification of the patients' risk for early acute coagulopathy have been proposed, with considerable variations in the defining criteria, including several trauma-scoring systems based on prehospital data. We aimed to develop a clinically relevant definition for acute coagulopathy of trauma based on conventional coagulation assays and to assess its efficacy in comparison to recently established prehospital prediction models. Methodology: Retrospective data of all trauma patients (n = 490) presented to our level I trauma center, in 2014, was extracted. Receiver operating characteristic curve analysis was done to establish cut-offs for conventional coagulation assays for identification of patients with acute traumatic coagulopathy was done. Prospectively data of (n = 100) adult trauma patients was collected and cohort was stratified by the established definition and classified as "coagulopathic" or "non-coagulopathic" and correlated with the Prediction of acute coagulopathy of trauma score and Trauma-Induced Coagulopathy Clinical Score for identifying trauma coagulopathy and subsequent risk for mortality. Results: Data of 490 trauma patients (average age 31.85±9.04; 86.7% males) was extracted. 53.3% had head injury, 26.6% had fractures, 7.5% had chest and abdominal injury. Acute traumatic coagulopathy was defined as international normalized ratio ≥ 1.19; prothrombin time ≥ 15.5 s; activated partial thromboplastin time ≥ 29 s. Of the 100 adult trauma patients (average age 36.5±14.2; 94% males), 63% had early coagulopathy based on our conventional coagulation assay definition. Overall prediction of acute coagulopathy of trauma score was 118.7±58.5 and trauma-induced coagulopathy clinical score was 3(0-8). Both the scores were higher in coagulopathic than non-coagulopathic patients (prediction of acute coagulopathy of trauma score 123.2±8.3 vs. 110.9±6.8, p-value = 0.31; trauma-induced coagulopathy clinical score 4(3-8) vs. 3(0-8), p-value = 0.89), but not statistically significant. Overall mortality was 41%. Mortality rate was significantly higher in coagulopathic than non-coagulopathic patients (75.5% vs. 54.2%, p-value = 0.04). High prediction of acute coagulopathy of trauma score also significantly associated with mortality (134.2±9.95 vs. 107.8±6.82, p-value = 0.02), whereas trauma-induced coagulopathy clinical score did not vary be survivors and non-survivors. Conclusion: Early coagulopathy was seen in 63% of trauma patients, which was significantly associated with mortality. Acute traumatic coagulopathy defined by conventional coagulation assays (international normalized ratio ≥ 1.19; prothrombin time ≥ 15.5 s; activated partial thromboplastin time ≥ 29 s) demonstrated good ability to identify coagulopathy and subsequent mortality, in comparison to the prehospital parameter-based scoring systems. Prediction of acute coagulopathy of trauma score may be more suited for predicting mortality rather than early coagulopathy. In emergency trauma situations, where immediate corrective measures need to be taken, complex multivariable scoring algorithms may cause delay, whereas coagulation parameters and conventional coagulation tests will give highly specific results.

Keywords: trauma, coagulopathy, prediction, model

Procedia PDF Downloads 156

Authors: R. P. Hewawasam, A. F. Dulhunty

Abstract:

The ryanodine receptor (RyR) is an intracellular ion channel that releases Ca2+ from the sarcoplasmic reticulum and is essential for the excitation-contraction coupling and contraction in striated muscle. Human muscle specific glutathione transferase M2-2 (GSTM2-2) is a highly specific inhibitor of cardiac ryanodine receptor (RyR2) activity. Single channel-lipid bilayer studies and Ca2+ release assays performed using the C-terminal half of the GSTM2-2 and its mutants F157A and Y160A confirmed the ability of the C terminal domain of GSTM2-2 to specifically inhibit the cardiac ryanodine receptor activity. Objective of the present study is to determine the effect of C terminal domain of GSTM2-2 (GSTM2-2C) and the mutants, F157A and Y160A on the Ca2+ transients of neonatal ventricular cardiomyocytes. Primary cardiomyocytes were cultured from neonatal rats. They were treated with GSTM2-2C and the two mutants F157A and Y160A at 15µM and incubated for 2 hours. Then the cells were led with Fluo-4AM, fluorescent Ca2+ indicator, and the field stimulated (1 Hz, 3V and 2ms) cells were excited using the 488 nm argon laser. Contractility of the cells were measured and the Ca2+ transients in the stained cells were imaged using Leica SP5 confocal microscope. Peak amplitude of the Ca2+ transient, rise time and decay time from the peak were measured for each transient. In contrast to GSTM2C which significantly reduced the % shortening (42.8%) in the field stimulated cells, F157A and Y160A failed to reduce the % shortening.Analysis revealed that the average amplitude of the Ca2+ transient was significantly reduced (P<0.001) in cells treated with the wild type GSTM2-2C compared to that of untreated cells. Cells treated with the mutants F157A and Y160A didn’t change the Ca2+ transient significantly compared to the control. A significant increase in the rise time (P< 0.001) and a significant reduction in the decay time (P< 0.001) were observed in cardiomyocytes treated with GSTM2-2C compared to the control but not with F157A and Y160A. These results are consistent with the observation that GSTM2-2C reduced the Ca2+ release from the cardiac SR significantly whereas the mutants, F157A and Y160A didn’t show any effect compared to the control. GSTM2-2C has an isoform-specific effect on the cardiac ryanodine receptor activity and also it inhibits RyR2 channel activity only during diastole. Selective inhibition of RyR2 by GSTM2-2C has significant clinical potential in the treatment of cardiac arrhythmias and heart failure. Since GSTM2-2C-terminal construct has no GST enzyme activity, its introduction to the cardiomyocyte would not exert any unwanted side effects that may alter its enzymatic action. The present study further confirms that GSTM2-2C is capable of decreasing the Ca2+ release from the cardiac SR during diastole. These results raise the future possibility of using GSTM2-2C as a template for therapeutics that can depress RyR2 function when the channel is hyperactive in cardiac arrhythmias and heart failure.

Keywords: arrhythmia, cardiac muscle, cardiac ryanodine receptor, GSTM2-2

Procedia PDF Downloads 267

Authors: Wesley Preßler, Lucie Schmidt

Abstract:

Digital transformation is playing an increasingly important role in the development of smart residential quarters. In order to accompany and steer this process and ultimately make the success of the transformation efforts measurable, it is helpful to use an appropriate maturity model. However, conventional maturity models for digital transformation focus primarily on the evaluation of processes and neglect the information and power imbalances between the stakeholders, which affects the validity of the results. The Multi-Generation Smart Community (mGeSCo) research project is developing an interdisciplinary maturity model that integrates the dimensions of digital literacy, interpretive patterns, and technology acceptance to address this gap. As part of the mGeSCo project, the technological development of selected dimensions in the Smart Quarter Jena-Lobeda (Germany) is being investigated. A specific maturity model, based on Cohen's Smart Cities Wheel, evaluates the central dimensions Working, Living, Housing and Caring. To improve the reliability and relevance of the maturity assessment, the factors Digital Literacy, Interpretive Patterns and Technology Acceptance are integrated into the developed model. The digital literacy dimension examines stakeholders' skills in using digital technologies, which influence their perception and assessment of technological maturity. Digital literacy is measured by means of surveys, interviews, and participant observation, using the European Commission's Digital Literacy Framework (DigComp) as a basis. Interpretations of digital technologies provide information about how individuals perceive technologies and ascribe meaning to them. However, these are not mere assessments, prejudices, or stereotyped perceptions but collective patterns, rules, attributions of meaning and the cultural repertoire that leads to these opinions and attitudes. Understanding these interpretations helps in assessing the overarching readiness of stakeholders to digitally transform a/their neighborhood. This involves examining people's attitudes, beliefs, and values about technology adoption, as well as their perceptions of the benefits and risks associated with digital tools. These insights provide important data for a holistic view and inform the steps needed to prepare individuals in the neighborhood for a digital transformation. Technology acceptance is another crucial factor for successful digital transformation to examine the willingness of individuals to adopt and use new technologies. Surveys or questionnaires based on Davis' Technology Acceptance Model can be used to complement interpretive patterns to measure neighborhood acceptance of digital technologies. Integrating the dimensions of digital literacy, interpretive patterns and technology acceptance enables the development of a roadmap with clear prerequisites for initiating a digital transformation process in the neighborhood. During the process, maturity is measured at different points in time and compared with changes in the aforementioned dimensions to ensure sustainable transformation. Participation, co-creation, and co-production are essential concepts for a successful and inclusive digital transformation in the neighborhood context. This interdisciplinary maturity model helps to improve the assessment and monitoring of sustainable digital transformation processes in smart residential quarters. It enables a more comprehensive recording of the factors that influence the success of such processes and supports the development of targeted measures to promote digital transformation in the neighborhood context.

Keywords: digital transformation, interdisciplinary, maturity model, neighborhood

Procedia PDF Downloads 50