Search results for: consumption patterns

Authors: Omojokun G. Aju, Adedayo O. Sule

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ZigBee wireless sensor and control network is one of the most popularly deployed wireless technologies in recent years. This is because ZigBee is an open standard lightweight, low-cost, low-speed, low-power protocol that allows true operability between systems. It is built on existing IEEE 802.15.4 protocol and therefore combines the IEEE 802.15.4 features and newly added features to meet required functionalities thereby finding applications in wide variety of wireless networked systems. ZigBee‘s current focus is on embedded applications of general-purpose, inexpensive, self-organising networks which requires low to medium data rates, high number of nodes and very low power consumption such as home/industrial automation, embedded sensing, medical data collection, smart lighting, safety and security sensor networks, and monitoring systems. Although the ZigBee design specification includes security features to protect data communication confidentiality and integrity, however, when simplicity and low-cost are the goals, security is normally traded-off. A lot of researches have been carried out on ZigBee technology in which emphasis has mainly been placed on ZigBee network performance characteristics such as energy efficiency, throughput, robustness, packet delay and delivery ratio in different scenarios and applications. This paper investigate and analyse the data accuracy, network implementation difficulties and security challenges of ZigBee network applications in star-based and mesh-based topologies with emphases on its home monitoring application using the ZigBee ProBee ZE-10 development boards for the network setup. The paper also expose some factors that need to be considered when designing ZigBee network applications and suggest ways in which ZigBee network can be designed to provide more resilient to network attacks.

Keywords: home monitoring, IEEE 802.14.5, topology, wireless security, wireless sensor network (WSN), ZigBee

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Authors: Salman Ahmad, Muhammad Aown Sammar Raza, Muhammad Farrukh Saleem, Rashid Iqbal, Muhammad Saqlain Zaheer, Muhammad Usman Aslam, Imran Haider, Muhammad Adnan Nazar, Muhammad Ali

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Among the various abiotic stresses, drought stress is one of the most challenging for field crops. Wheat is one of the major staple food of the world, which is highly affected by water deficit stress in the current scenario of climate change. In order to ensure food security by depleting water resources, there is an urgent need to adopt technologies which result in sufficient crop yield with less water consumption. Mulching and partial rootzone drying (PRD) are two important management techniques used for water conservation and to mitigate the negative impacts of drought. The experiment was conducted to screen out the best-suited mulch for wheat under PRD system. Two water application techniques (I1= full irrigation I2= PRD irrigation) and four mulch treatments (M0= un-mulched, M1= black plastic mulch, M2= wheat straw mulch and M4= cotton sticks mulch) were conducted in completely randomized design with four replications. The treatment, black plastic mulch was performed the best than other mulch treatments. For irrigation levels, higher values of growth, physiological and water-related parameters were recorded in control treatment while, quality traits and enzymatic activities were higher under partial root zone drying. The current study concluded that adverse effects of drought on wheat can be significantly mitigated by using mulches but black plastic mulch was best suited for partial rootzone drying irrigation system in wheat.

Keywords: antioxidants, leaf water relations, Mulches, osmolytes, partial root zone drying, photosynthesis

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Authors: Katie Kilgour, Brendan Turner, Carly Catella, Michael Daniele, Stefano Menegatti

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In vivo, the extracellular matrix (ECM) provides biochemical and mechanical properties that are instructional to resident cells to form complex tissues with characteristics to develop and support vascular networks. In vitro, the development of vascular networks can be guided by biochemical patterning of substrates via spatial distribution and display of peptides and growth factors to prompt cell adhesion, differentiation, and proliferation. We have developed a technique utilizing peptide ligands that specifically bind vascular endothelial growth factor (VEGF), erythropoietin (EPO), or angiopoietin-1 (ANG1) to spatiotemporally distribute growth factors to cells. This allows for the controlled release of each growth factor, ultimately enhancing the formation of a vascular network. Our engineered tissue constructs (ETCs) are fabricated out of gelatin methacryloyl (GelMA), which is an ideal substrate for tailored stiffness and bio-functionality, and covalently patterned with growth factor specific peptides. These peptides mimic growth factor receptors, facilitating the non-covalent binding of the growth factors to the ETC, allowing for facile uptake by the cells. We have demonstrated in the absence of cells the binding affinity of VEGF, EPO, and ANG1 to their respective peptides and the ability for each to be patterned onto a GelMA substrate. The ability to organize growth factors on an ETC provides different functionality to develop organized vascular networks. Our results demonstrated a method to incorporate biochemical cues into ETCs that enable spatial and temporal control of growth factors. Future efforts will investigate the cellular response by evaluating gene expression, quantifying angiogenic activity, and measuring the speed of growth factor consumption.

Keywords: growth factor, hydrogel, peptide, angiogenesis, vascular, patterning

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Authors: Sajjad Shojaeidoust, Mohsen Ghanbarzadeh, Abdolhamid Habibi

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Exercise-induced bronchospasm (EIB) is a transitory condition of airflow obstruction that is associated with physical activities. It is noted that high ventilation can lead to an increase in the heat and reduce in the moisture in airways resistance of trachea. Also causes of pathophysiological mechanism are EIB. Accordingly, studying some parameters of pulmonary function (FVC, FEV1) among active people seems quintessential. The aim of this study was to analyze bronchospasm following the implementation of a program of maximum aerobic exercise in active men at Chamran University of Ahwaz. Method: In this quasi-experimental study, the population consisted of all students at Chamran University. Among from 55 participants, of which, 15 were randomly selected as the experimental group. In this study, the size of the maximum oxygen consumption was initially measured, and then, based on the maximum oxygen consumed, the active individuals were identified. After five minutes’ warm-up, Strand treadmill exercise test was taken (one session) and pulmonary parameters were measured at both pre- and post-tests (spirometer). After data normalization using KS and non-normality of the data, the Wilcoxon test was used to analyze the data. The significance level for all statistical surveys was considered p≤0/05. Results: The results showed that the ventilation factors and bronchospasm (FVC, FEV1) in the pre-test and post-test resulted in no significant difference among the active people (p≥0/05). Discussion and conclusion: Based on the results observed in this study, it appears that pulmonary indices in active individuals increased after aerobic test. The increase in this indicator in active people is due to increased volume and elasticity of the lungs as well. In other words, pulmonary index is affected by rib muscles. It is considered that progress over respiratory muscle strength and endurance has raised FEV1 in the active cases.

Keywords: aerobic active maximum, bronchospasm, pulmonary function, spirometer

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Authors: Daniel Gidey, Kunwar Siddarth Dadhwal

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By evaluating India's aid systems and ongoing development initiatives, this conference paper offers light on India's role as a source of developmental assistance in Africa. This research attempts to provide insights into the developing landscape of foreign aid and development cooperation by focusing on understanding India's motivations and strategy. In recent years, India's connection with Africa has grown significantly, driven by economic, political, and strategic reasons. This conference paper covers India's many forms of aid, including financial, capacity building efforts, technical assistance, and infrastructure development projects, via a thorough investigation. The article seeks to establish India's priorities and highlight the possible impacts of its development assistance in Africa by examining the industries and locations of concentration. Using secondary data sources, the investigation delves into the underlying goals of India's aid policy in Africa. It investigates whether India's development assistance is consistent with its broader geopolitical aims, such as access to resources, competing with regional rivals, or strengthening diplomatic ties. Furthermore, the article investigates how India's aid policy combines the ideals of South-South cooperation and mutual development, as well as the ramifications for recipient countries. Furthermore, the paper assesses the efficacy and sustainability of India's aid operations in Africa. It takes into account the elements that influence their success, the problems they face, and the amount to which they contribute to local development goals, community empowerment, and poverty alleviation. The study also focuses on the accountability systems, transparency, and knowledge transfer aspects of India's development assistance. By providing a detailed examination of India's aid endeavors in Africa, the paper adds to the current literature on international development cooperation. By offering fresh insights into the motives, strategies, and impacts of India's assistance programs, it seeks to enhance understanding of the emerging patterns in South-South cooperation and the complex dynamics of contemporary international aid architecture.

Keywords: India, Africa, developmental assistance, aid projects and South-South cooperation

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Authors: Chithra A. V., Somoshree Datta, Sandeep Nithyanandan

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Sign Language Recognition (SLR) is the process of interpreting and translating sign language into spoken or written language using technological systems. It involves recognizing hand gestures, facial expressions, and body movements that makeup sign language communication. The primary goal of SLR is to facilitate communication between hearing- and speech-impaired communities and those who do not understand sign language. Due to the increased awareness and greater recognition of the rights and needs of the hearing- and speech-impaired community, sign language recognition has gained significant importance over the past 10 years. Technological advancements in the fields of Artificial Intelligence and Machine Learning have made it more practical and feasible to create accurate SLR systems. This paper presents a distinct approach to SLR by framing it as a video classification problem using Deep Learning (DL), whereby a combination of Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) has been used. This research targets the integration of sign language recognition into healthcare settings, aiming to improve communication between medical professionals and patients with hearing impairments. The spatial features from each video frame are extracted using a CNN, which captures essential elements such as hand shapes, movements, and facial expressions. These features are then fed into an RNN network that learns the temporal dependencies and patterns inherent in sign language sequences. The INCLUDE dataset has been enhanced with more videos from the healthcare domain and the model is evaluated on the same. Our model achieves 91% accuracy, representing state-of-the-art performance in this domain. The results highlight the effectiveness of treating SLR as a video classification task with the CNN-RNN architecture. This approach not only improves recognition accuracy but also offers a scalable solution for real-time SLR applications, significantly advancing the field of accessible communication technologies.

Keywords: sign language recognition, deep learning, convolution neural network, recurrent neural network

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Authors: Tonghua Li

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Under the neoliberal corporate food regime, biofuels are a double-edged sword that exacerbates tensions between national food security and trade in green agricultural products. Biofuels have the potential to help achieve green sustainable development goals, but they threaten food security by exacerbating competition for land and changing global food trade patterns. The U.S.-China trade war complicates this debate. Under the influence of different political and corporate coordination mechanisms in China and the US, trade disputes can have different impacts on sustainable agricultural practices. This paper develops an actor-centred ‘network governance framework’ focusing on trade in soybean and corn-based biofuels to explain how trade wars can change the actions of governmental and non-governmental actors in the context of oligopolistic competition and market concentration in agricultural trade. There is evidence that the US-China trade decoupling exacerbates the conflict between national security, free trade in agriculture, and the realities and needs of green and sustainable energy development. The US government's trade policies reflect concerns about China's relative gains, leading to a loss of trade profits, making it impossible for the parties involved to find a balance between the three objectives and, consequently, to get into a biofuels and soybean industry dilemma. Within the setting of prioritizing national security and strategic interests, the government has replaced the dominant position of large agribusiness in the neoliberal food system, and the goal of environmental sustainability has been marginalized by high politics. In contrast, China faces tensions in the trade war between food security self-sufficiency policy and liberal sustainable trade, but the state-capitalist model ensures policy coordination and coherence in trade diversion and supply chain adjustment. Despite ongoing raw material shortages and technological challenges, China remains committed to playing a role in global environmental governance and promoting green trade objectives.

Keywords: food security, green trade, biofuels, soybeans, US-China trade war

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Authors: Tomiwa, Akinyemi Clement

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Tropical regions experience diverse and complex precipitation patterns, posing significant challenges for accurate rainfall estimation and forecasting. This study addresses the problem of effectively classifying tropical rain types and refining the Z-R (Reflectivity-Rain Rate) relationship to enhance rainfall estimation accuracy. Through a combination of remote sensing, meteorological analysis, and machine learning, the research aims to develop an advanced classification framework capable of distinguishing between different types of tropical rain based on their unique characteristics. This involves utilizing high-resolution satellite imagery, radar data, and atmospheric parameters to categorize precipitation events into distinct classes, providing a comprehensive understanding of tropical rain systems. Additionally, the study seeks to improve the Z-R relationship, a crucial aspect of rainfall estimation. One year of rainfall data was analyzed using a Micro Rain Radar (MRR) located at The Federal University of Technology Akure, Nigeria, measuring rainfall parameters from ground level to a height of 4.8 km with a vertical resolution of 0.16 km. Rain rates were classified into low (stratiform) and high (convective) based on various microstructural attributes such as rain rates, liquid water content, Drop Size Distribution (DSD), average fall speed of the drops, and radar reflectivity. By integrating diverse datasets and employing advanced statistical techniques, the study aims to enhance the precision of Z-R models, offering a more reliable means of estimating rainfall rates from radar reflectivity data. This refined Z-R relationship holds significant potential for improving our understanding of tropical rain systems and enhancing forecasting accuracy in regions prone to heavy precipitation.

Keywords: remote sensing, precipitation, drop size distribution, micro rain radar

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Authors: Rafid Doulab

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Elemental Impurities in the Pharmaceuticals industryis are indispensable to ensure pharmaceuticalssafety for 24 elements. Although atomic absorption and inductively coupled plasma are used in the U.S Pharmacopeia and the European Pharmacopoeia, FESEM with energy dispersive spectrometers can be applied as an alternative analysis method for quantitative and qualitative results for a variety of elements without chemical pretreatment, unlike other techniques. This technique characterizes by shortest time, with more less contamination, no reagent consumption, and generation of minimal residue or waste, as well as sample preparations time limiting, with minimal analysis error. Simple dilution for powder or direct analysis for liquid, we analyzed the usefulness of EDS method in testing with field emission scanning electron microscopy (FESEM, SUPRA 55 Carl Zeiss Germany) with an X-ray energy dispersion (XFlash6l10 Bruker Germany). The samples analyzed directly without coating by applied 5µ of known concentrated diluted sample on carbon stub with accelerated voltage according to sample thickness, the result for this spot was in atomic percentage, and by Avogadro converted factor, the final result will be in microgram. Conclusion and recommendation: The conclusion of this study is application of FESEM-EDS in US pharmacopeia and ICH /Q3D guideline to reach a high-precision and accurate method in element impurities analysis of drugs or bulk materials to determine the permitted daily exposure PDE in liquid or solid specimens, and to obtain better results than other techniques, by the way it does not require complex methods or chemicals for digestion, which interfere with the final results with the possibility of to keep the sample at any time for re analysis. The recommendation is to use this technique in pharmacopeia as standard methods like inductively coupled plasma both ICP-AES, ICP-OES, and ICP-MS.

Keywords: pharmacopoeia, FESEM-EDS, element impurities, atomic concentration

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Authors: Elif D. Oguz Erkal, David Krackhardt, Erica Cochran-Hameen

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Even though social network analysis (SNA) is an abundantly studied concept for many organizations and industries, a clear SNA approach to the project teams has not yet been adopted by the construction industry. The main challenges for performing SNA in construction and the apparent reason for this gap is the unique and complex structure of each construction project, the comparatively high circulation of project team members/contributing parties and the variety of authentic problems for each project. Additionally, there are stakeholders from a variety of professional backgrounds collaborating in a high-stress environment fueled by time and cost constraints. Within this case study on Project RE, a design & build project performed at the Urban Design Build Studio of Carnegie Mellon University, social network analysis of the project design team will be performed with the main goal of applying social network theory to construction project environments. The research objective is to determine a correlation between the network of how individuals relate to each other on one’s perception of their own professional strengths and weaknesses and the communication patterns within the team and the group dynamics. Data is collected through a survey performed over four rounds conducted monthly, detailed follow-up interviews and constant observations to assess the natural alteration in the network with the effect of time. The data collected is processed by the means of network analytics and in the light of the qualitative data collected with observations and individual interviews. This paper presents the full ethnography of this construction design team of fourteen architecture students based on an elaborate social network data analysis over time. This study is expected to be used as an initial step to perform a refined, targeted and large-scale social network data collection in construction projects in order to deduce the impacts of social networks on project performance and suggest better collaboration structures for construction project teams henceforth.

Keywords: construction design teams, construction project management, social network analysis, team collaboration, network analytics

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Authors: Namugenyi Ephrance Eunice, Julianne Sansa Otim, Marco Zennaro, Stephen D. Wolthusen

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The Internet of Things (IoT) is a network of connected data processing devices, mechanical and digital machinery, items, animals, or people that may send data across a network without requiring human-to-human or human-to-computer interaction. Each component has sensors that can pick up on specific phenomena, as well as processing software and other technologies that can link to and communicate with other systems and/or devices over the Internet or other communication networks and exchange data with them. IoT is increasingly being used in fields other than consumer electronics, such as public safety, emergency response, industrial automation, autonomous vehicles, the Internet of Medical Things (IoMT), and general environmental monitoring. Consumer-based IoT applications, like smart home gadgets and wearables, are also becoming more prevalent. This paper presents the main IoT deployment areas for environmental monitoring in developing regions and the backhaul options suitable for them. A detailed review of each of the list of papers selected for the study is included in section III of this document. The study includes an overview of existing IoT deployments, the underlying communication architectures, protocols, and technologies that support them. This overview shows that Low Power Wireless Area Networks (LPWANs), as summarized in Table 1, are very well suited for monitoring environment architectures designed for remote locations. LoRa technology, particularly the LoRaWAN protocol, has an advantage over other technologies due to its low power consumption, adaptability, and suitable communication range. The prevailing challenges of the different architectures are discussed and summarized in Table 3 of the IV section, where the main problem is the obstruction of communication paths by buildings, trees, hills, etc.

Keywords: communication technologies, environmental monitoring, Internet of Things, IoT deployment challenges

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Authors: Ramona Georgeta Biholar

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Gender-based violence against women plagues societies around the world. The work to eliminate it is an ongoing battle. At the international level, Article 5 (a) CEDAW establishes an agenda for social and cultural transformation: it imposes on States parties to CEDAW an obligation to modify sex roles and stereotypical social and cultural patterns of conduct. Also, it provides for the protection of women from violence stemming from such gender norms. Yet, the lived realities of women are frequently disconnected from this agenda. Nonetheless, it is the reality of the local that is crucial for the articulation, implementation and realization of women’s rights in general, and for the elimination of gender-based violence against women in particular. In this paper we discuss the transformation of sex roles and gender stereotyping with a view to realize women’s right to be free from gender-based violence. This paper is anchored in qualitative data collection undertaken in Jamaica and socio-legal research. Based on this research, 1) We explain the process of vernacularisation as a strategy that enables women’s human rights to hit the ground and benefit rights holders, and 2) We present a synergistic model for the implementation of Article 5 (a) CEDAW so that women’s right to be free from gender-based violence can be realized in a concrete national jurisdiction. This model is grounded in context-based demands and recommendations for social and cultural transformation as a remedy for the incidence of gender-based violence against women. Moreover, the synergistic model offers directions that have a general application for the implementation of CEDAW and Article 5 (a) CEDAW in particular, with a view to realize women’s right to be free from gender-based violence. The model is thus not only a conceptual tool of analysis, but also a prescriptive tool for action. It contributes to the work of both academics and practitioners, such as Governmental officials, and national and local civil society representatives. Overall, this paper contributes to understanding the process necessary to bridge that gap between women’s human rights norms and women’s life realities of discrimination and violence.

Keywords: CEDAW, gender-based violence against women, international human rights law, women’s rights implementation, the Caribbean

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Authors: Jennifer Hunter, Francisco Ramirez, Neil A. Nedley, Thania Solorio, Christian Freed, Erica Kinjo

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People who have autoimmune disease are often at an increased risk for psychological disorders such as anxiety. Untreated psychological conditions can affect the development of disease and can affect one’s general quality of life. In this study, it was hypothesized that an educational community-based intervention would be useful in decreasing the anxiety levels of participants with autoimmune disease. Programs, 2-hours long each, were held weekly over a period of eight weeks. During every meeting, a 45-minute DVD presentation by a skilled physician was shown, a small group discussion was guided by trained facilitators, and weekly practical assignments were given to each participant. The focus of the program was to educate participants about healthy lifestyle behaviors such as exercise, nutrition, sleep hygiene, helpful thought patterns etc., and to provide a group environment in which each participant was supported. Participants were assessed pre-post program for anxiety using the Depression and Anxiety Assessment Test (registration TX 7-398-022), a validated mental health test based on DSM-5 criteria and demographics. Anxiety scores were classified according to the DSM-5 criteria into 4 categories: none (0-6), mild (7-10), moderate (11-19) or severe (20 or more). Out of the participants who participated in programs conducted in the manner explained above (n=431), the average age was 54.9 (SD 16.6) and 81.9% were female. At baseline, the mean group anxiety level was 9.4 (SD 5.4). Within the baseline group, anxiety levels were as follows: none (21.1%), mild (22.0%), moderate (27.1%) and severe (29.7%). After the program, mean group anxiety decreased to 4.7 (SD 4.0). Post-program anxiety levels were as follows: none (54.8%), mild (27.1%), moderate (12.5%), severe (5.6%). The decrease in overall anxiety levels was significant t(431)=19.3 p<.001, 95% CI [0.815, 1.041]. It was concluded that the eight-week intensive was beneficial in decreasing the anxiety levels of participants. A long-term follow-up study would be beneficial in determining how lasting such improvements are especially since autoimmune diseases are often chronic. Additionally, future studies that utilize a control group would aid in establishing whether the improvements seen are due to the use of this specific lifestyle-educational program.

Keywords: anxiety, auto-immune disease, community-based educational program, lifestyle

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Authors: Saeed Poormoaied

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Perishability and developing an intelligent control policy for perishable items are the major concerns of marketing managers in a supply chain. In this study, we address a two-echelon supply chain problem for perishable items with a single vendor and a single buyer. The buyer adopts an aged-based continuous review policy which works by taking both the stock level and the aging process of items into account. The vendor works under the warehouse framework, where its lot size is determined with respect to the batch size of the buyer. The model holds for a positive and fixed lead time for the buyer, and zero lead time for the vendor. The demand follows a Poisson process and any unmet demand is lost. We provide exact analytic expressions for the operational characteristics of the system by using the renewal reward theorem. Items have a fixed lifetime after which they become unusable and are disposed of from the buyer's system. The age of items starts when they are unpacked and ready for the consumption at the buyer. When items are held by the vendor, there is no aging process which results in no perishing at the vendor's site. The model is developed under the centralized framework, which takes the expected profit of both vendor and buyer into consideration. The goal is to determine the optimal policy parameters under the service level constraint at the retailer's site. A sensitivity analysis is performed to investigate the effect of the key input parameters on the expected profit and order quantity in the supply chain. The efficiency of the proposed age-based policy is also evaluated through a numerical study. Our results show that when the unit perishing cost is negligible, a significant cost saving is achieved.

Keywords: two-echelon supply chain, perishable items, age-based policy, renewal reward theorem

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Authors: Saâd Oukkass, Abderrahim Bouftou, Rachid Ouchn, L. Lebrun, Miloudi Hlaibi

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We invariably exist in a world steeped in colors, whether in our clothing, food, cosmetics, or even medications. However, most of the dyes we use pose significant problems, being both harmful to the environment and resistant to degradation. Among these dyes, methylene blue and acid yellow 61 stand out, commonly used to dye various materials such as cotton, wood, and silk. Fortunately, various methods have been developed to treat and remove these polluting dyes, among which membrane processes play a prominent role. These methods are praised for their low energy consumption, ease of operation, and their ability to achieve effective separation of components. Adsorption on activated carbon is also a widely employed technique, complementing the basic processes. It proves particularly effective in capturing and removing organic compounds from water due to its substantial specific surface area while retaining its properties unchanged. In the context of our study, we examined two crucial aspects. Firstly, we explored the possibility of selectively extracting methylene blue from a mixture containing another dye, acid yellow 61, using a polymer inclusion membrane (PIM) made of PVA. After characterizing the morphology and porosity of the membrane, we applied kinetic and thermodynamic models to determine the values of permeability (P), initial flux (J0), association constant (Kass), and apparent diffusion coefficient (D*). Subsequently, we measured activation parameters (activation energy (Ea), enthalpy (ΔH#ass), entropy (ΔS#)). Finally, we studied the effect of activated carbon on the processes carried out through the membrane, demonstrating a clear improvement. These results make the membrane developed in this study a potentially pivotal player in the field of membrane separation.

Keywords: dyes, methylene blue, membrane, activated carbon

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Authors: Aishi Kundu, Elhan Raza

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"Necessity is the mother of invention" - Rapid increase in the global human population has directed the agricultural domain toward machine learning. The basic need of human beings is considered to be food which can be satisfied through farming. Farming is one of the major revenue generators for the Indian economy. Agriculture is not only considered a source of employment but also fulfils humans’ basic needs. So, agriculture is considered to be the source of employment and a pillar of the economy in developing countries like India. This paper provides a brief review of the progress made in implementing Machine Learning in the agricultural sector. Accurate predictions are necessary at the right time to boost production and to aid the timely and systematic distribution of agricultural commodities to make their availability in the market faster and more effective. This paper includes a thorough analysis of various machine learning algorithms applied in different aspects of agriculture (crop management, soil management, water management, yield tracking, livestock management, etc.).Due to climate changes, crop production is affected. Machine learning can analyse the changing patterns and come up with a suitable approach to minimize loss and maximize yield. Machine Learning algorithms/ models (regression, support vector machines, bayesian models, artificial neural networks, decision trees, etc.) are used in smart agriculture to analyze and predict specific outcomes which can be vital in increasing the productivity of the Agricultural Food Industry. It is to demonstrate vividly agricultural works under machine learning to sensor data. Machine Learning is the ongoing technology benefitting farmers to improve gains in agriculture and minimize losses. This paper discusses how the irrigation and farming management systems evolve in real-time efficiently. Artificial Intelligence (AI) enabled programs to emerge with rich apprehension for the support of farmers with an immense examination of data.

Keywords: machine Learning, artificial intelligence, crop management, precision farming, smart farming, pre-harvesting, harvesting, post-harvesting

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Authors: Rebecca S. Hock, Cyralene P. Bryce, Kevin Williams, Arielle G. Rabinowitz, Janina R. Galler

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Background: Findings have been mixed regarding whether offspring of parents who were abused or neglected as children have a greater risk of experiencing abuse or neglect themselves. In addition, many studies on this topic are restricted to physical abuse and take place in a limited number of countries, representing a small segment of the world's population. Methods: We examined relationships between childhood maltreatment history assessed in a subset (N=68) of the original longitudinal birth cohort (G1) of the Barbados Nutrition Study and their now-adult offspring (G2) (N=111) using the Childhood Trauma Questionnaire-Short Form (CTQ-SF). We used Pearson correlations to assess relationships between parent and offspring CTQ-SF total and subscale scores (physical, emotional, and sexual abuse; physical and emotional neglect). Next, we ran multiple regression analyses, using the parental CTQ-SF total score and the parental Sexual Abuse score as primary predictors separately in our models of G2 CTQ-SF (total and subscale scores). Results: G1 total CTQ-SF scores were correlated with G2 offspring Emotional Neglect and total scores. G1 Sexual Abuse history was significantly correlated with G2 Emotional Abuse, Sexual Abuse, Emotional Neglect, and Total Score. In fully-adjusted regression models, parental (G1) total CTQ-SF scores remained significantly associated with G2 offspring reports of Emotional Neglect, and parental (G1) Sexual Abuse was associated with offspring (G2) reports of Emotional Abuse, Physical Abuse, Emotional Neglect, and overall CTQ-SF scores. Conclusions: Our findings support a link between parental exposure to childhood maltreatment and their offspring's self-reported exposure to childhood maltreatment. Of note, there was not an exact correspondence between the subcategory of maltreatment experienced from one generation to the next. Compared with other subcategories, G1 Sexual Abuse history was the most likely to predict G2 offspring maltreatment. Further studies are needed to delineate underlying mechanisms and to develop intervention strategies aimed at preventing intergenerational transmission.

Keywords: trauma, family, adolescents, intergenerational trauma, child abuse, child neglect, global mental health, North America

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Authors: V. M. Mmbengwa, J. R. M. Mabuso, C. P. Du Plooy, S. Laurrie, H. D. van Schalkwyk

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Sweet potato products are necessary for the provision of essential nutrients in every household, regardless of their poverty status. Their consumption appears to be highly influenced by socio-economic factors, such as malnutrition, food insecurity and unemployment. Therefore, market availability is crucial for these cultivars to resolve some of the socio-economic factors. The aim of the study was to investigate market availability of sweet potato cultivars in the North West Province. In this study, both qualitative and quantitative research methodologies were used. Qualitative methodology was used to explain the quantitative outcomes of the variables. On the other hand, quantitative results were used to test the hypothesis. The study used SPSS software to analyse the data. Cross-tabulation and Chi-square statistics were used to obtain the descriptive and inferential analyses, respectively. The study found that the Blesbok cultivar is dominating the markets of the North West Province, with the Monate cultivar dominating in the Bojanala Platinum (75 %) and Dr Ruth Segomotsi Mompati (25 %) districts. It is also found that a unit increase in the supply of sweet potato cultivars in both local and district municipal markets is accompanied by a reduced demand of 28 % and 33 % at district and local markets, respectively. All these results were found to be significant at p<0.05. The results further revealed that in four out of nine local municipality markets, the Blesbok cultivar seems to be solely available in those four local municipal markets of North West Province. It can be concluded that Blesbok, relative to other cultivars, is the most commercialised sweet potato variety and that consumers across this Province are highly aware of it. For other cultivars to assume market prominence in this Province, a well-designed marketing campaign for creating awareness may be required. This campaign may be based on nutritional advantages of different cultivars, of which Blesbok is relatively inferior, compared to orange-fleshed sweet potato varieties.

Keywords: cultivar, malnutrition, markets, sweet potato

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Authors: Cesar A. Nava-Gaxiola, C. Barrado

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Harmonized with SESAR (Single European Sky Research) initiatives, a new concept related with airspace structures have been introduced in Europe, the Free Route Airspace. The key of free route is based in an airspace where users may freely plan a route between a defined entry and exit waypoint, with the possibility of routing via intermediate points, the free route flights remain subject to air traffic control (ATC) for the established separations. Free route airspace does not present anymore fixed airways to airspace users, as a consequence it brings a new paradigm for managing safe separations of aircrafts inside these airspace blocks . Nowadays, several European nations have been introduced the concept, some of them in a complete or partial stage, but finally offering limited benefits to airspace users for this condition. This research evaluates the future scenario of free route implementation across Europe, considering a unique airspace block configuration with a complete upper airspace with free route. The paper is centered in investigating the benefits for airspace users, and the study of possible increments of Air Traffic Controllers task loads with a full application. In this research, fast time simulations are carrying out for discovering how much flight time and distance aircrafts can save with an overall free route establishment. In the other side, the paper explains the evolution of conflicts derivate from possible separation losses between aircrafts in this new environment. Free route conflicts can emerges in any points of the airspace, requiring a great effort for solving it, in comparison with fixed airways, where conflicts normally were found by controllers in known waypoints, and they solved using the fixed network as reference. The airspace configuration modelled in this study take into account the actual navigation waypoints structure, moving into a future scenario, where new ones waypoints are added and new traffic flow patterns appears. In this sense, this research explores the advantages and unknown difficulties that a large scale application of free route concept can carry out in the European airspace.

Keywords: ATC conflicts, efficiency, free route airspace, SESAR

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Authors: Sofya Komarova, Frashia Ndungu, Alessia Gavazzoli, Roberta Mineo

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Modern society requires people to be flexible and to develop innovative solutions to unexpected situations. Creativity refers to the “interaction among aptitude, process, and the environment by which an individual or group produces a perceptible product that is both novel and useful as defined within a social context”. It allows humans to produce novel ideas, generate new solutions, and express themselves uniquely. Only a few scientific studies have examined group dynamics' influence on individuals' creativity. There exist some gaps in the research on creative thinking, such as the fact that collaborative effort frequently results in the enhanced production of new information and knowledge. Therefore, it is critical to evaluate creativity via social settings. The study aimed at exploring the group dynamics of young adults in small group settings and the influence of these dynamics on their creativity. The study included 30 participants aged 20 to 25 who were attending university after completing a bachelor's degree. The participants were divided into groups of three, in gender homogenous and heterogeneous groups. The groups’ creative task was tied to the Lego mosaic created for the Scintillae laboratory at the Reggio Children Foundation. Group dynamics were operationalized into patterns of behaviors classified into three major categories: 1) Social Interactions, 2) Play, and 3) Distraction. Data were collected through audio and video recording and observation. The qualitative data were converted into quantitative data using the observational coding system; then, they were analyzed, revealing correlations between behaviors using median points and averages. For each participant and group, the percentages of represented behavior signals were computed. The findings revealed a link between social interaction, creative thinking, and creative activities. Other findings revealed that the more intense the social interaction, the lower the amount of creativity demonstrated. This study bridges the research gap between group dynamics and creativity. The approach calls for further research on the relationship between creativity and social interaction.

Keywords: group dynamics, creative thinking, creative action, social interactions, group play

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Authors: Thomas Wimmer, Bernhard Weigand

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The improvement of gas turbine efficiency is one of the main drivers of research and development in the gas turbine market. This has led to elevated gas turbine inlet temperatures beyond the melting point of the utilized materials. The turbine parts need to be actively cooled in order to withstand these harsh environments. However, the usage of compressor air as coolant decreases the overall gas turbine efficiency. Thus, coolant consumption needs to be minimized in order to gain the maximum advantage from higher turbine inlet temperatures. Therefore, sophisticated cooling designs for gas turbine parts aim to minimize coolant mass flow. New design space is accessible as additive manufacturing is maturing to industrial usage for the creation of hot gas flow path parts. By making use of this technology more efficient cooling schemes can be manufacture. In order to find such cooling schemes a generative design method is being developed. It generates cooling schemes randomly which adhere to a set of rules. These assure the sanity of the design. A huge amount of different cooling schemes are generated and implemented in a simulation environment where it is validated. Criteria for the fitness of the cooling schemes are coolant mass flow, maximum temperature and temperature gradients. This way the whole design space is sampled and a Pareto optimum front can be identified. This approach is applied to a flat plate, which resembles a simplified section of a hot gas flow path part. Realistic boundary conditions are applied and thermal barrier coating is accounted for in the simulation environment. The resulting cooling schemes are presented and compared to representative conventional cooling schemes. Further development of this method can give access to cooling schemes with an even better performance having higher complexity, which makes use of the available design space.

Keywords: additive manufacturing, cooling, gas turbine, heat transfer, heat transfer design, optimization

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Authors: Mohammed Seyam, Faridah Othman, Ahmed El-Shafie

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The early warning of high stream flow events (HSF) and floods is an important aspect in the management of surface water and rivers systems. This process can be performed using either process-based models or data driven-based models such as artificial intelligence (AI) techniques. The main goal of this study is to develop efficient AI-based model for predicting the real-time hourly stream flow (Q) and apply it as early warning tool of HSF and floods in the downstream area of the Selangor River basin, taken here as a paradigm of humid tropical rivers in Southeast Asia. The performance of AI-based models has been improved through the integration of the lag time (Lt) estimation in the modelling process. A total of 8753 patterns of Q, water level, and rainfall hourly records representing one-year period (2011) were utilized in the modelling process. Six hydrological scenarios have been arranged through hypothetical cases of input variables to investigate how the changes in RF intensity in upstream stations can lead formation of floods. The initial SF was changed for each scenario in order to include wide range of hydrological situations in this study. The performance evaluation of the developed AI-based model shows that high correlation coefficient (R) between the observed and predicted Q is achieved. The AI-based model has been successfully employed in early warning throughout the advance detection of the hydrological conditions that could lead to formations of floods and HSF, where represented by three levels of severity (i.e., alert, warning, and danger). Based on the results of the scenarios, reaching the danger level in the downstream area required high RF intensity in at least two upstream areas. According to results of applications, it can be concluded that AI-based models are beneficial tools to the local authorities for flood control and awareness.

Keywords: floods, stream flow, hydrological modelling, hydrology, artificial intelligence

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Authors: Muhammed Saeed Rasheed

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Knowledge of the zinc and phytic acid (PA) concentrations of staple cereal crops are essential when evaluating the nutritional health of national and regional populations. In the present study, a total of 120 farmers’ fields in Iraqi Kurdistan were surveyed for zinc status in soil and wheat grain samples; wheat is the staple carbohydrate source in the region. Soils were analysed for total concentrations of phosphorus (PT) and zinc (ZnT), available P (POlsen) and Zn (ZnDTPA) and for pH. Average values (mg kg-1) ranged between 403-3740 (PT), 42.0-203 (ZnT), 2.13-28.1 (POlsen) and 0.14-5.23 (ZnDTPA); pH was in the range 7.46-8.67. The concentrations of Zn, PA/Zn molar ratio and estimated Zn bioavailability were also determined in wheat grain. The ranges of Zn and PA concentrations (mg kg⁻¹) were 12.3-63.2 and 5400 – 9300, respectively, giving a PA/Zn molar ratio of 15.7-30.6. A trivariate model was used to estimate intake of bioaccessible Zn, employing the following parameter values: (i) maximum Zn absorption = 0.09 (AMAX), (ii) equilibrium dissociation constant of zinc-receptor binding reaction = 0.680 (KP), and (iii) equilibrium dissociation constant of Zn-PA binding reaction = 0.033 (KR). In the model, total daily absorbed Zn (TAZ) (mg d⁻¹) as a function of total daily nutritional PA (mmole d⁻¹) and total daily nutritional Zn (mmole Zn d⁻¹) was estimated assuming an average wheat flour consumption of 300 g day⁻¹ in the region. Consideration of the PA and Zn intake suggest only 21.5±2.9% of grain Zn is bioavailable so that the effective Zn intake from wheat is only 1.84-2.63 mg d-1 for the local population. Overall results suggest available dietary Zn is below recommended levels (11 mg d⁻¹), partly due to low uptake by wheat but also due to the presence of large concentrations of PA in wheat grains. A crop breeding program combined with enhanced agronomic management methods is needed to enhance both Zn uptake and bioavailability in grains of cultivated wheat types.

Keywords: phosphorus, zinc, phytic acid, phytic acid to zinc molar ratio, zinc bioavailability

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Authors: Fatmah Almathkour

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Managing and controlling the construction supply chain (CSC) are very important components of effective construction project execution. The goals of managing the CSC are to reduce uncertainty and optimize the performance of a construction project by improving efficiency and reducing project costs. The heart of much SC activity is addressing risk, and the CSC is no different. The delivery and consumption of construction materials is highly variable due to the complexity of construction operations, rapidly changing demand for certain components, lead time variability from suppliers, transportation time variability, and disruptions at the job site. Current notions of managing and controlling CSC, involve focusing on one project at a time with a push-based material ordering system based on the initial construction schedule and, then, holding a tremendous amount of inventory. A two-stage methodology was proposed to coordinate the feed-forward control of advanced order placement with a supplier to a feedback local control in the form of adding the ability to transship materials between projects to improve efficiency and reduce costs. It focused on the single supplier integrated production and transshipment problem with multiple products. The methodology is used as a design tool for the CSC because it includes an external storage site not associated with one of the projects. The idea is to add this feature to a highly constrained environment to explore its effectiveness in buffering the impact of variability and maintaining project schedule at low cost. The methodology uses deterministic optimization models with objectives that minimizing the total cost of the CSC. To illustrate how this methodology can be used in practice and the types of information that can be gleaned, it is tested on a number of cases based on the real example of multiple construction projects in Kuwait.

Keywords: construction supply chain, inventory control supply chain, transshipment

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Authors: Thomas Louis, Irina Primac, Florent Morfoisse, Tania Durre, Silvia Blacher, Agnes Noel

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In vitro and in vivo lymphangiogenesis assays are essential for the identification of potential lymphangiogenic agents and the screening of pharmacological inhibitors. In the present study, we analyse three biological models: in vitro lymphatic endothelial cell spheroids, in vivo ear sponge assay, and in vivo lymph node colonisation by tumour cells. These assays provide suitable 3D models to test pro- and anti-lymphangiogenic factors or drugs. 3D images were acquired by confocal laser scanning and light sheet fluorescence microscopy. Virtual scan microscopy followed by 3D reconstruction by image aligning methods was also used to obtain 3D images of whole large sponge and ganglion samples. 3D reconstruction, image segmentation, skeletonisation, and other image processing algorithms are described. Fixed and time-lapse imaging techniques are used to analyse lymphatic endothelial cell spheroids behaviour. The study of cell spatial distribution in spheroid models enables to detect interactions between cells and to identify invasion hierarchy and guidance patterns. Global measurements such as volume, length, and density of lymphatic vessels are measured in both in vivo models. Branching density and tortuosity evaluation are also proposed to determine structure complexity. Those properties combined with vessel spatial distribution are evaluated in order to determine lymphangiogenesis extent. Lymphatic endothelial cell invasion and lymphangiogenesis were evaluated under various experimental conditions. The comparison of these conditions enables to identify lymphangiogenic agents and to better comprehend their roles in the lymphangiogenesis process. The proposed methodology is validated by its application on the three presented models.

Keywords: 3D image segmentation, 3D image skeletonisation, cell invasion, confocal microscopy, ear sponges, light sheet microscopy, lymph nodes, lymphangiogenesis, spheroids

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Authors: Zahid Ullah, Atlas Khan

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In today's data-driven world, the role of mathematics in bridging the gap between theory and applications is becoming increasingly vital. This abstract highlights the significance of mathematics as a powerful tool for analyzing, interpreting, and extracting meaningful insights from vast amounts of data. By integrating mathematical principles with real-world applications, researchers can unlock the full potential of data-driven decision-making processes. This abstract delves into the various ways mathematics acts as a bridge connecting theoretical frameworks to practical applications. It explores the utilization of mathematical models, algorithms, and statistical techniques to uncover hidden patterns, trends, and correlations within complex datasets. Furthermore, it investigates the role of mathematics in enhancing predictive modeling, optimization, and risk assessment methodologies for improved decision-making in diverse fields such as finance, healthcare, engineering, and social sciences. The abstract also emphasizes the need for interdisciplinary collaboration between mathematicians, statisticians, computer scientists, and domain experts to tackle the challenges posed by the data-driven landscape. By fostering synergies between these disciplines, novel approaches can be developed to address complex problems and make data-driven insights accessible and actionable. Moreover, this abstract underscores the importance of robust mathematical foundations for ensuring the reliability and validity of data analysis. Rigorous mathematical frameworks not only provide a solid basis for understanding and interpreting results but also contribute to the development of innovative methodologies and techniques. In summary, this abstract advocates for the pivotal role of mathematics in bridging theory and applications in a data-driven world. By harnessing mathematical principles, researchers can unlock the transformative potential of data analysis, paving the way for evidence-based decision-making, optimized processes, and innovative solutions to the challenges of our rapidly evolving society.

Keywords: mathematics, bridging theory and applications, data-driven world, mathematical models

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Authors: Kwan Hee Han

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External environment of enterprise is rapidly changing majorly by global competition, cost reduction pressures, and new technology. In these situations, production scheduling function plays a critical role to meet customer requirements and to attain the goal of operational efficiency. It deals with short-term decision making in the production process of the whole supply chain. The major task of production scheduling is to seek a balance between customer orders and limited resources. In manufacturing companies, this task is so difficult because it should efficiently utilize resource capacity under the careful consideration of many interacting constraints. At present, many computerized software solutions have been utilized in many enterprises to generate a realistic production schedule to overcome the complexity of schedule generation. However, most production scheduling systems do not provide sufficient information about the validity of the generated schedule except limited statistics. Process mining only recently emerged as a sub-discipline of both data mining and business process management. Process mining techniques enable the useful analysis of a wide variety of processes such as process discovery, conformance checking, and bottleneck analysis. In this study, the performance of generated production schedule is evaluated by mining event log data of production scheduling software system by using the process mining techniques since every software system generates event logs for the further use such as security investigation, auditing and error bugging. An application of process mining approach is proposed for the validation of the goodness of production schedule generated by scheduling software systems in this study. By using process mining techniques, major evaluation criteria such as utilization of workstation, existence of bottleneck workstations, critical process route patterns, and work load balance of each machine over time are measured, and finally, the goodness of production schedule is evaluated. By using the proposed process mining approach for evaluating the performance of generated production schedule, the quality of production schedule of manufacturing enterprises can be improved.

Keywords: data mining, event log, process mining, production scheduling

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Authors: B. Chen, F. Kuznik, M. Horgnies, K. Johannes, V. Morin, E. Gengembre

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More attention on renewable energy has been done after the achievement of Paris Agreement against climate change. Solar-based technology is supposed to be one of the most promising green energy technologies for residential buildings since its widely thermal usage for hot water and heating. However, the seasonal mismatch between its production and consumption makes buildings need an energy storage system to improve the efficiency of renewable energy use. Indeed, there exist already different kinds of energy storage systems using sensible or latent heat. With the consideration of energy dissipation during storage and low energy density for above two methods, thermochemical energy storage is then recommended. Recently, ettringite (3CaO∙Al₂O₃∙3CaSO₄∙32H₂O) based materials have been reported as potential thermochemical storage materials because of high energy density (~500 kWh/m³), low material cost (700 €/m³) and low storage temperature (~60-70°C), compared to reported salt hydrates like SrBr₂·6H₂O (42 k€/m³, ~80°C), LaCl₃·7H₂O (38 k€/m³, ~100°C) and MgSO₄·7H₂O (5 k€/m³, ~150°C). Therefore, they have the possibility to be largely used in building sector with being coupled to normal solar panel systems. On the other side, the lack in terms of extensive examination leads to poor knowledge on their thermal properties and limit maturity of this technology. The aim of this work is to develop a modular reactor adapting to thermal characterizations of ettringite-based material particles of different sizes. The filled materials in the reactor can be self-compacted vertically to ensure hot air or humid air goes through homogenously. Additionally, quick assembly and modification of reactor, like LEGO™ plastic blocks, make it suitable to distinct thermochemical energy storage material samples with different weights (from some grams to several kilograms). In our case, quantity of stored and released energy, best work conditions and even chemical durability of ettringite-based materials have been investigated.

Keywords: dehydration, ettringite, hydration, modular reactor, thermochemical energy storage

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Authors: John Lamb, Robert Epstein, Vasundhara L. Bhupathi, Sanjeev Kumar Marimekala

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In this paper, we focus on the importance of scalable architecture for data centers and buildings in general to help an enterprise achieve environmental sustainability. The scalable architecture helps in many ways, such as adaptability to the business and user requirements, promotes high availability and disaster recovery solutions that are cost effective and low maintenance. The scalable architecture also plays a vital role in three core areas of sustainability: economy, environment, and social, which are also known as the 3 pillars of a sustainability model. If the architecture is scalable, it has many advantages. A few examples are that scalable architecture helps businesses and industries to adapt to changing technology, drive innovation, promote platform independence, and build resilience against natural disasters. Most importantly, having a scalable architecture helps industries bring in cost-effective measures for energy consumption, reduce wastage, increase productivity, and enable a robust environment. It also helps in the reduction of carbon emissions with advanced monitoring and metering capabilities. Scalable architectures help in reducing waste by optimizing the designs to utilize materials efficiently, minimize resources, decrease carbon footprints by using low-impact materials that are environmentally friendly. In this paper we also emphasize the importance of cultural shift towards the reuse and recycling of natural resources for a balanced ecosystem and maintain a circular economy. Also, since all of us are involved in the use of computers, much of the scalable architecture we have studied is related to data centers.

Keywords: scalable architectures, sustainability, application design, disruptive technology, machine learning and natural language processing, AI, social media platform, cloud computing, advanced networking and storage devices, advanced monitoring and metering infrastructure, climate change

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Authors: Frederic Heymes, Michael Albrecht Birk, Roland Eyssette

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Boiling Liquid Expanding Vapor Explosion (BLEVE) has been a well know industrial accident for over 6 decades now, and yet it is still poorly predicted and avoided. BLEVE is created when a vessel containing a pressure liquefied gas (PLG) is engulfed in a fire until the tank rupture. At this time, the pressure drops suddenly, leading the liquid to be in a superheated state. The vapor expansion and the violent boiling of the liquid produce several shock waves. This works aimed at understanding the contribution of vapor ad liquid phases in the overpressure generation in the near field. An experimental work was undertaken at a small scale to reproduce realistic BLEVE explosions. Key parameters were controlled through the experiments, such as failure pressure, fluid mass in the vessel, and weakened length of the vessel. Thirty-four propane BLEVEs were then performed to collect data on scenarios similar to common industrial cases. The aerial overpressure was recorded all around the vessel, and also the internal pressure changed during the explosion and ground loading under the vessel. Several high-speed cameras were used to see the vessel explosion and the blast creation by shadowgraph. Results highlight how the pressure field is anisotropic around the cylindrical vessel and highlights a strong dependency between vapor content and maximum overpressure from the lead shock. The time chronology of events reveals that the vapor phase is the main contributor to the aerial overpressure peak. A prediction model is built upon this assumption. Secondary flow patterns are observed after the lead. A theory on how the second shock observed in experiments forms is exposed thanks to an analogy with numerical simulation. The phase change dynamics are also discussed thanks to a window in the vessel. Ground loading measurements are finally presented and discussed to give insight into the order of magnitude of the force.

Keywords: phase change, superheated state, explosion, vapor expansion, blast, shock wave, pressure liquefied gas

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