Search results for: advanced networking and storage devices

Authors: Zheng Wang, Zhenhong Li, Jon Mills

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Ground-based synthetic aperture radar (GBSAR) represents a powerful remote sensing tool for deformation monitoring towards various geohazards, e.g. landslides, mudflows, avalanches, infrastructure failures, and the subsidence of residential areas. Unlike spaceborne SAR with a fixed revisit period, GBSAR data can be acquired with an adjustable temporal resolution through either continuous or discontinuous operation. However, challenges arise from processing high temporal-resolution continuous GBSAR data, including the extreme cost of computational random-access-memory (RAM), the delay of displacement maps, and the loss of temporal evolution. Moreover, repositioning errors between discontinuous campaigns impede the accurate measurement of surface displacements. Therefore, a versatile package with two complete chains is developed in this study in order to process both continuous and discontinuous GBSAR data and address the aforementioned issues. The first chain is based on a small-baseline subset concept and it processes continuous GBSAR images unit by unit. Images within a window form a basic unit. By taking this strategy, the RAM requirement is reduced to only one unit of images and the chain can theoretically process an infinite number of images. The evolution of surface displacements can be detected as it keeps temporarily-coherent pixels which are present only in some certain units but not in the whole observation period. The chain supports real-time processing of the continuous data and the delay of creating displacement maps can be shortened without waiting for the entire dataset. The other chain aims to measure deformation between discontinuous campaigns. Temporal averaging is carried out on a stack of images in a single campaign in order to improve the signal-to-noise ratio of discontinuous data and minimise the loss of coherence. The temporal-averaged images are then processed by a particular interferometry procedure integrated with advanced interferometric SAR algorithms such as robust coherence estimation, non-local filtering, and selection of partially-coherent pixels. Experiments are conducted using both synthetic and real-world GBSAR data. Displacement time series at the level of a few sub-millimetres are achieved in several applications (e.g. a coastal cliff, a sand dune, a bridge, and a residential area), indicating the feasibility of the developed GBSAR data processing package for deformation monitoring of a wide range of scientific and practical applications.

Keywords: ground-based synthetic aperture radar, interferometry, small baseline subset algorithm, deformation monitoring

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Authors: Jana Andzane, Gunta Kunakova, Margarita Baitimirova, Mikelis Marnauza, Floriana Lombardi, Donats Erts

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Bismuth selenide (Bi₂Se₃) is known as a narrow band gap semiconductor with pronounced thermoelectric (TE) and topological insulator (TI) properties. Unique TI properties offer exciting possibilities for fundamental research as observing the exciton condensate and Majorana fermions, as well as practical application in spintronic and quantum information. In turn, TE properties of this material can be applied for wide range of thermoelectric applications, as well as for broadband photodetectors and near-infrared sensors. Nanostructuring of this material results in improvement of TI properties due to suppression of the bulk conductivity, and enhancement of TE properties because of increased phonon scattering at the nanoscale grains and interfaces. Regarding TE properties, crystallographic growth direction, as well as orientation of the nanostructures relative to the growth substrate, play significant role in improvement of TE performance of nanostructured material. For instance, Bi₂Se₃ layers consisting of randomly oriented nanostructures and/or of combination of them with planar nanostructures show significantly enhanced in comparison with bulk and only planar Bi₂Se₃ nanostructures TE properties. In this work, a catalyst-free vapour-solid deposition technique was applied for controlled obtaining of different types of Bi₂Se₃ nanostructures and continuous nanostructured layers for targeted applications. For example, separated Bi₂Se₃ nanoplates, nanobelts and nanowires can be used for investigations of TI properties; consisting from merged planar and/or randomly oriented nanostructures Bi₂Se₃ layers are useful for applications in heat-to-power conversion devices and infrared detectors. The vapour-solid deposition was carried out using quartz tube furnace (MTI Corp), equipped with an inert gas supply and pressure/temperature control system. Bi₂Se₃ nanostructures/nanostructured layers of desired type were obtained by adjustment of synthesis parameters (process temperature, deposition time, pressure, carrier gas flow) and selection of deposition substrate (glass, quartz, mica, indium-tin-oxide, graphene and carbon nanotubes). Morphology, structure and composition of obtained Bi₂Se₃ nanostructures and nanostructured layers were inspected using SEM, AFM, EDX and HRTEM techniques, as well as home-build experimental setup for thermoelectric measurements. It was found that introducing of temporary carrier gas flow into the process tube during the synthesis and deposition substrate choice significantly influence nanostructures formation mechanism. Electrical, thermoelectric, and topological insulator properties of different types of deposited Bi₂Se₃ nanostructures and nanostructured coatings are characterized as a function of thickness and discussed.

Keywords: bismuth seleinde, nanostructures, topological insulator, vapour-solid deposition

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Authors: Amit Bhunia, Mohit Kumar Singh, Maryam Al Huwayz, Mohamed Henini, Shouvik Datta

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We report [https://arxiv.org/abs/2107.13518] experimental detection and control of Schrodinger’s Cat like macroscopically large, quantum coherent state of a two-component Bose-Einstein condensate of spatially indirect electron-hole pairs or excitons using a resonant tunneling diode of III-V Semiconductors. This provides access to millions of excitons as qubits to allow efficient, fault-tolerant quantum computation. In this work, we measure phase-coherent periodic oscillations in photo-generated capacitance as a function of an applied voltage bias and light intensity over a macroscopically large area. Periodic presence and absence of splitting of excitonic peaks in the optical spectra measured by photocapacitance point towards tunneling induced variations in capacitive coupling between the quantum well and quantum dots. Observation of negative ‘quantum capacitance’ due to a screening of charge carriers by the quantum well indicates Coulomb correlations of interacting excitons in the plane of the sample. We also establish that coherent resonant tunneling in this well-dot heterostructure restricts the available momentum space of the charge carriers within this quantum well. Consequently, the electric polarization vector of the associated indirect excitons collective orients along the direction of applied bias and these excitons undergo Bose-Einstein condensation below ~100 K. Generation of interference beats in photocapacitance oscillation even with incoherent white light further confirm the presence of stable, long-range spatial correlation among these indirect excitons. We finally demonstrate collective Rabi oscillations of these macroscopically large, ‘multipartite’, two-level, coupled and uncoupled quantum states of excitonic condensate as qubits. Therefore, our study not only brings the physics and technology of Bose-Einstein condensation within the reaches of semiconductor chips but also opens up experimental investigations of the fundamentals of quantum physics using similar techniques. Operational temperatures of such two-component excitonic BEC can be raised further with a more densely packed, ordered array of QDs and/or using materials having larger excitonic binding energies. However, fabrications of single crystals of 0D-2D heterostructures using 2D materials (e.g. transition metal di-chalcogenides, oxides, perovskites etc.) having higher excitonic binding energies are still an open challenge for semiconductor optoelectronics. As of now, these 0D-2D heterostructures can already be scaled up for mass production of miniaturized, portable quantum optoelectronic devices using the existing III-V and/or Nitride based semiconductor fabrication technologies.

Keywords: exciton, Bose-Einstein condensation, quantum computation, heterostructures, semiconductor Physics, quantum fluids, Schrodinger's Cat

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Authors: A. Onur Kutlu, H. Tolga Bolukbasi

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Since the 1990s, governments, international organizations and scholars have drawn increasing attention to the significance of women in the labour force. While advanced industrial countries in North Western Europe and North America have managed to increase female labour force participation (FLFP) in the early post world war two period, emerging economies of the 1970s have only been able to increase FLFP only a decade later. Among these areas, Southern Europe features a wave of remarkable bounce backs in FLFP. However, despite striking similarities between the features in Southern Europe and those in Turkey, Turkey has not been able to pull women into the labour force. Despite a host of institutional similarities, Turkey has failed to reach to the level of her Southern European neighbours. This paper addresses the puzzle why Turkey lag behind in FLFP in comparison to her Southern European neighbours. There are signs showing that FLFP is currently reaching a critical threshold at a time when structural factors may allow a trend. It is not known, however, the constellation of conditions which may bring rising FLFP in Turkey. In order to gain analytical leverage from similar transitions in countries that share similar labour market and welfare state regime characteristics, this paper identifies the conditions in Southern Europe that brought rising FLFP to be able to explore the prospects for Turkey. Second, this paper takes these variables in the fuzzy set Qualitative Comparative Analysis (fsQCA) as conditions which can potentially explain the outcome of rising FLFP in Portugal, Spain, Italy, Greece and Turkey. The purpose here is to identify any causal pathway there may exist that lead to rising FLFP in Southern Europe. In order to do so, this study analyses two time periods in all cases, which represent different periods for different countries. The first period is identified on the basis of low FLFP and the second period on the basis of the transition to significantly higher FLFP. Third, the conditions are treated following the standard procedures in fsQCA, which provide equifinal: two distinct paths to higher levels of FLFP in Southern Europe, each of which may potentially increase FLFP in Turkey. Based on this analysis, this paper proposes that there exist two distinct paths leading to higher levels of FLFP in Southern Europe. Among these paths, salience of left parties emerges as a sufficient condition. In cases where this condition was not present, a second path combining enlarging service sector employment, increased tertiary education among women and increased childcare enrolment rates led to increasing FLFP.

Keywords: female labour force participation, fsQCA, Southern Europe, Turkey

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Authors: Maureen Kamau, Gulnaz Mohamoud, Adelaide Lusambili, Njeri Nyanja

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Life expectancy has increased over the last century amongst older individuals, and in particular, those 60 years and over. The World Health Organization estimates that the world's population of persons over 60 years will rise to 22 per cent by the year 2050. Ageing is associated with increasing disability, multiple chronic conditions, and an increase in the use of health services. These multiple chronic conditions are managed with polypharmacy. Polypharmacy has numerous adverse effects including non-adherence, poor compliance to the various medications, reduced appetite, and risk of fall. Studies on polypharmacy and ageing are few and poorly understood especially in low and middle - income countries. The aim of this study was to explore the knowledge, attitudes and beliefs of older people towards polypharmacy. A qualitative study of 15 patients aged 60 years and above, taking more than five medications per day were conducted at the Aga Khan University using Semi-structured in-depth interviews. Three interviews were pilot interviews, and data analysis was performed on 12 interviews. Data were analyzed using NVIVO 12 software. A thematic qualitative analysis was carried out guided by Braun and Clarke (2006) framework. Themes identified; - knowledge of their co-morbidities and of the medication that older persons take, sources of information about medicines, and storage of the medication, experiences and attitudes of older patients towards polypharmacy both positive and negative, older peoples beliefs and their coping mechanisms with polypharmacy. The study participants had good knowledge on their multiple co-morbidities, and on the medication they took. The patients had positive attitudes towards medication as it enhanced their health and well-being, and enabled them to perform their activities of daily living. There was a strong belief among older patients that the medications were necessary for their health. All these factors enhanced compliance to the multiple medication. However, some older patients had negative attitudes due to the pill burden, side effects of the medication, and stigma associated with being ill. Cost of healthcare was a concern, with most of the patients interviewed relying on insurance to cover the cost of their medication. Older patients had accepted that the medication they were prescribed were necessary for their health, as it enabled them to complete their activities of daily living. Some concerns about the side effects of the medication arose, and brought about the need for patient education that would ensure that the patients are aware of the medications they take, and potential side effects. The effect that the COVID 19 pandemic had in the healthcare of the older patients was evident by the number of the older patients avoided coming to the hospital during the period of the pandemic. The relationship with the primary care physician and the older patients is an important one, especially in LMICs such as Kenya, as many of the older patients trusted the doctors wholeheartedly to make the best decision about their health and about their medication. Prescription review is important to avoid the use of potentially inappropriate medication.

Keywords: polypharmacy, older patients, multiple chronic conditions, Kenya, Africa, qualitative study, indepth interviews, primary care

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Authors: Rajkumar Ghosh, Shyama Pada Gorai

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Access to safe drinking water is a fundamental human right; however, regions like Purulia, Bankura, Birbhum, Malda, Dinajpur in West Bengal, India, face formidable challenges due to heightened fluoride levels. This paper delves into the hurdles of fresh drinking water production, presenting comprehensive solutions derived from literature reviews, field surveys, and scientific analyses. Encompassing fluoride-affected areas in Purulia, Bankura, Birbhum, Malda, North-South Dinajpur, and South 24 Parganas, the study emphasizes an integrated and sustainable approach. Employing a multidisciplinary methodology, combining scientific analysis and community engagement, the study identifies key factors influencing water quality and proposes sustainable strategies. Elevated fluoride concentrations exceeding international health standards (Purulia: 0.126 – 8.16 mg/L, Bankura: 0.1 – 12.2 mg/L, Malda: 0.1 – 4.54 mg/L, Birbhum: 0.023 – 18 mg/L) necessitate urgent intervention. Infrastructure deficiencies impede water treatment and distribution, while limited awareness obstructs community participation. The proposed solutions embrace advanced water treatment technologies, infrastructure development, community education, and sustainable water management practices. This comprehensive effort aims to provide clean drinking water, safeguarding the health of affected populations. Building on these foundations, the study explores the potential of rooftop rainwater harvesting as an effective and sustainable strategy to mitigate challenges in fresh drinking water production. By addressing fluoride contamination concerns and promoting community involvement, this approach presents a holistic solution to water quality issues in affected regions. The findings underscore the importance of integrating sustainable practices with community engagement to achieve long-term water security in Purulia, Bankura, Birbhum, Malda, North-South Dinajpur, and South 24 Parganas. This study serves as a cornerstone for further research and policy development, addressing fluoride contamination's impact on public health in affected areas. Recommendations include the establishment of long-term monitoring programs to assess the effectiveness of implemented solutions and conducting health impact studies to understand the long-term effects of fluoride contamination on the local population.

Keywords: fluoride mitigation, rainwater harvesting, water quality, sustainable water management, community engagement

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Authors: Skyler Kim

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An early diagnosis of leukemia has always been a challenge to doctors and hematologists. On a worldwide basis, it was reported that there were approximately 350,000 new cases in 2012, and diagnosing leukemia was time-consuming and inefficient because of an endemic shortage of flow cytometry equipment in current clinical practice. As the number of medical diagnosis tools increased and a large volume of high-quality data was produced, there was an urgent need for more advanced data analysis methods. One of these methods was the AI approach. This approach has become a major trend in recent years, and several research groups have been working on developing these diagnostic models. However, designing and implementing a leukemia diagnostic system in real clinical environments based on a deep learning approach with larger sets remains complex. Leukemia is a major hematological malignancy that results in mortality and morbidity throughout different ages. We decided to select acute lymphocytic leukemia to develop our diagnostic system since acute lymphocytic leukemia is the most common type of leukemia, accounting for 74% of all children diagnosed with leukemia. The results from this development work can be applied to all other types of leukemia. To develop our model, the Kaggle dataset was used, which consists of 15135 total images, 8491 of these are images of abnormal cells, and 5398 images are normal. In this paper, we design and implement a leukemia diagnostic system in a real clinical environment based on deep learning approaches with larger sets. The proposed diagnostic system has the function of detecting and classifying leukemia. Different from other AI approaches, we explore hybrid architectures to improve the current performance. First, we developed two independent convolutional neural network models: VGG19 and ResNet50. Then, using both VGG19 and ResNet50, we developed a hybrid deep learning architecture employing transfer learning techniques to extract features from each input image. In our approach, fusing the features from specific abstraction layers can be deemed as auxiliary features and lead to further improvement of the classification accuracy. In this approach, features extracted from the lower levels are combined into higher dimension feature maps to help improve the discriminative capability of intermediate features and also overcome the problem of network gradient vanishing or exploding. By comparing VGG19 and ResNet50 and the proposed hybrid model, we concluded that the hybrid model had a significant advantage in accuracy. The detailed results of each model’s performance and their pros and cons will be presented in the conference.

Keywords: acute lymphoblastic leukemia, hybrid model, leukemia diagnostic system, machine learning

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Authors: Egemen Sert, Leila Hedayatifar, Rachel A. Rigg, Amir Akhavan, Olha Buchel, Dominic Elias Saadi, Aabir Abubaker Kar, Alfredo J. Morales, Yaneer Bar-Yam

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The complexity of providing timely and cost-effective distribution of finished goods from industrial facilities to customers makes effective operational coordination difficult, yet effectiveness is crucial for maintaining customer service levels and sustaining a business. Logistics planning becomes increasingly complex with growing numbers of customers, varied geographical locations, the uncertainty of future orders, and sometimes extreme competitive pressure to reduce inventory costs. Linear optimization methods become cumbersome or intractable due to a large number of variables and nonlinear dependencies involved. Here we develop a complex systems approach to optimizing logistics networks based upon dimensional reduction methods and apply our approach to a case study of a manufacturing company. In order to characterize the complexity in customer behavior, we define a “customer space” in which individual customer behavior is described by only the two most relevant dimensions: the distance to production facilities over current transportation routes and the customer's demand frequency. These dimensions provide essential insight into the domain of effective strategies for customers; direct and indirect strategies. In the direct strategy, goods are sent to the customer directly from a production facility using box or bulk trucks. In the indirect strategy, in advance of an order by the customer, goods are shipped to an external warehouse near a customer using trains and then "last-mile" shipped by trucks when orders are placed. Each strategy applies to an area of the customer space with an indeterminate boundary between them. Specific company policies determine the location of the boundary generally. We then identify the optimal delivery strategy for each customer by constructing a detailed model of costs of transportation and temporary storage in a set of specified external warehouses. Customer spaces help give an aggregate view of customer behaviors and characteristics. They allow policymakers to compare customers and develop strategies based on the aggregate behavior of the system as a whole. In addition to optimization over existing facilities, using customer logistics and the k-means algorithm, we propose additional warehouse locations. We apply these methods to a medium-sized American manufacturing company with a particular logistics network, consisting of multiple production facilities, external warehouses, and customers along with three types of shipment methods (box truck, bulk truck and train). For the case study, our method forecasts 10.5% savings on yearly transportation costs and an additional 4.6% savings with three new warehouses.

Keywords: logistics network optimization, direct and indirect strategies, K-means algorithm, dimensional reduction

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Authors: Baye Berihun Getahun, Mulugeta Atnaf Tiruneh, Richard G. F. Visser

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Resource-poor farmers practice low-input farming systems, and yet, most breeding programs give less attention to this huge farming system, which serves as a source of food and income for several people in developing countries. The high-input conventional breeding system appears to have failed to adequately meet the needs and requirements of 'difficult' environments operating under this system. Moreover, the unavailability of resources for crop production is getting for their peaks, the environment is maltreated by excessive use of agrochemicals, crop productivity reaches its plateau stage, particularly in the developed nations, the world population is increasing, and food shortage sustained to persist for poor societies. In various parts of the world, genetic gain at the farmers' level remains low which could be associated with low adoption of crop varieties, which have been developed under high input systems. Farmers usually use their local varieties and apply minimum inputs as a risk-avoiding and cost-minimizing strategy. This evidence indicates that the conventional high-input plant breeding system has failed to feed the world population, and the world is moving further away from the United Nations' goals of ending hunger, food insecurity, and malnutrition. In this review, we discussed the rationality of focused breeding programs for low-input farming systems and, the technical aspect of crop breeding that accommodates future food needs and its significance for developing countries in the decreasing scenario of resources required for crop production. To this end, the application of exotic introgression techniques like polyploidization, pan-genomics, comparative genomics, and De novo domestication as a pre-breeding technique has been discussed in the review to exploit the untapped genetic diversity of the crop wild relatives (CWRs). Desired recombinants developed at the pre-breeding stage are exploited through appropriate breeding approaches such as evolutionary plant breeding (EPB), rhizosphere-related traits breeding, and participatory plant breeding approaches. Populations advanced through evolutionary breeding like composite cross populations (CCPs) and rhizosphere-associated traits breeding approach that provides opportunities for improving abiotic and biotic soil stress, nutrient acquisition capacity, and crop microbe interaction in improved varieties have been reviewed. Overall, we conclude that low input farming system is a huge farming system that requires distinctive breeding approaches, and the exotic pre-breeding introgression techniques and the appropriate breeding approaches which deploy the skills and knowledge of both breeders and farmers are vital to develop heterogeneous landrace populations, which are effective for farmers practicing low input farming across the world.

Keywords: low input farming, evolutionary plant breeding, composite cross population, participatory plant breeding

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Authors: Natia Jalagonia, Jimsher Maisuradze, Karlo Barbakadze, Tinatin Kuchukhidze

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At present intensive scientific researches of ceramics, cermets and metal alloys have been conducted for improving materials physical-mechanical characteristics. In purpose of increasing impact strength of ceramics based on alumina, simple method of graphene homogenization was developed. Homogeneous distribution of graphene (homogenization) in pressing composite became possible through the connection of functional groups of graphene oxide (-OH, -COOH, -O-O- and others) and alumina superficial OH groups with aluminum organic compounds. These two components connect with each other with -O-Al–O- bonds, and by their thermal treatment (300–500°C), graphene and alumina phase are transformed. Thus, choosing of aluminum organic compounds for modification is stipulated by the following opinion: aluminum organic compounds fragments fixed on graphene and alumina finally are transformed into an integral part of the matrix. By using of other elements as modifier on the matrix surface (Al2O3) other phases are transformed, which change sharply physical-mechanical properties of ceramic composites, for this reason, effect caused by the inclusion of graphene will be unknown. Fixing graphene fragments on alumina surface by alumoorganic compounds result in new type graphene-alumina complex, in which these two components are connected by C-O-Al bonds. Part of carbon atoms in graphene oxide are in sp3 hybrid state, so functional groups (-OH, -COOH) are located on both sides of graphene oxide layer. Aluminum organic compound reacts with graphene oxide at the room temperature, and modified graphene oxide is obtained: R2Al-O-[graphene]–COOAlR2. Remaining Al–C bonds also reacts rapidly with surface OH groups of alumina. In a result of these process, pressing powdery composite [Al2O3]-O-Al-O-[graphene]–COO–Al–O–[Al2O3] is obtained. For the purpose, graphene oxide suspension in dry toluene have added alumoorganic compound Al(iC4H9)3 in toluene with equimolecular ratio. Obtained suspension has put in the flask and removed solution in a rotary evaporate presence nitrogen atmosphere. Obtained powdery have been researched and used to consolidation of ceramic materials based on alumina. Ceramic composites are obtained in high temperature vacuum furnace with different temperature and pressure conditions. Received ceramics do not have open pores and their density reaches 99.5 % of TD. During the work, the following devices have been used: High temperature vacuum furnace OXY-GON Industries Inc (USA), device of spark-plasma synthesis, induction furnace, Electronic Scanning Microscopes Nikon Eclipse LV 150, Optical Microscope NMM-800TRF, Planetary mill Pulverisette 7 premium line, Shimadzu Dynamic Ultra Micro Hardness Tester DUH-211S, Analysette 12 Dynasizer and others.

Keywords: graphene oxide, alumo-organic, ceramic

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Authors: Gachara Grace, Kebira Anthony, Harvey Jagger, Wainaina James

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Aflatoxin contamination of maize in Africa poses a major threat to food security and the health of many African people. In Kenya, aflatoxin contamination of maize is high due to the environmental, agricultural and socio-economic factors. Many studies have been conducted to understand the scope of the problem, especially at pre-harvest level. This research was carried out to gather scientific information on the fungi population, diversity and aflatoxin level during the post-harvest period. The study was conducted in three geographical locations of; Kitui, Kitale and Nakuru. Samples were collected from storage structures of farmers and transported to the Biosciences eastern and central Africa (BecA), International Livestock and Research Institute (ILRI) hub laboratories. Mycoflora was recovered using the direct plating method. A total of five fungal genera (Aspergillus, Penicillium, Fusarium, Rhizopus and Bssyochlamys spp.) were isolated from the stored maize samples. The most common fungal species that were isolated from the three study sites included A. flavus at 82.03% followed by A.niger and F.solani at 49% and 26% respectively. The aflatoxin producing fungi A. flavus was recovered in 82.03% of the samples. Aflatoxin levels were analysed on both the maize samples and in vitro. Most of the A. flavus isolates recorded a high level of aflatoxin when they were analysed for presence of aflatoxin B1 using ELISA. In Kitui, all the samples (100%) had aflatoxin levels above 10ppb with a total aflatoxin mean of 219.2ppb. In Kitale, only 3 samples (n=39) had their aflatoxin levels less than 10ppb while in Nakuru, the total aflatoxin mean level of this region was 239.7ppb. When individual samples were analysed using Vicam fluorometer method, aflatoxin analysis revealed that most of the samples (58.4%) had been contaminated. The means were significantly different (p=0.00<0.05) in all the three locations. Genetic relationships of A. flavus isolates were determined using 13 Simple Sequence Repeats (SSRs) markers. The results were used to generate a phylogenetic tree using DARwin5 software program. A total of 5 distinct clusters were revealed among the genotypes. The isolates appeared to cluster separately according to the geographical locations. Principal Coordinates Analysis (PCoA) of the genetic distances among the 91 A. flavus isolates explained over 50.3% of the total variation when two coordinates were used to cluster the isolates. Analysis of Molecular Variance (AMOVA) showed a high variation of 87% within populations and 13% among populations. This research has shown that A. flavus is the main fungal species infecting maize grains in Kenya. The influence of aflatoxins on human populations in Kenya demonstrates a clear need for tools to manage contamination of locally produced maize. Food basket surveys for aflatoxin contamination should be conducted on a regular basis. This would assist in obtaining reliable data on aflatoxin incidence in different food crops. This would go a long way in defining control strategies for this menace.

Keywords: aflatoxin, Aspergillus flavus, genotyping, Kenya

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Authors: Ritika Chaturvedi

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Introduction: Sexual objectification, characterized by the reduction of an individual to a mere object of sexual desire, remains a pervasive societal issue with profound repercussions on individual well-being. Such experiences, often rooted in systemic and cultural norms, have long-lasting implications for mental and emotional health. This study aims to explore the intricate relationship between experiences of sexual objectification and insidious trauma, further investigating the potential moderating effects of overexcitability as proposed by Dabrowski's theory of positive disintegration. Methodology: The research involved a comprehensive cohort of 204 women, spanning ages from 18 to 65 years. Participants were tasked with completing self-administered questionnaires designed to capture their experiences with sexual objectification. Additionally, the questionnaire assessed symptoms indicative of insidious trauma and explored overexcitability across five distinct domains: emotional, intellectual, psychomotor, sensory, and imaginational. Employing advanced statistical techniques, including multiple regression and moderation analysis, the study sought to decipher the intricate interplay among these variables. Findings: The study's results revealed a compelling positive correlation between experiences of sexual objectification and the onset of symptoms indicative of insidious trauma. This correlation underscores the profound and detrimental effects of sexual objectification on an individual's psychological well-being. Interestingly, the moderation analyses introduced a nuanced understanding, highlighting the differential roles of various overexcitability. Specifically, emotional, intellectual, and sensual overexcitability were found to exacerbate trauma symptomatology. In contrast, psychomotor overexcitability emerged as a protective factor, demonstrating a mitigating influence on the relationship between sexual objectification and trauma. Implications: The study's findings hold significant implications for a diverse array of stakeholders, encompassing mental health practitioners, educators, policymakers, and advocacy groups. The identified moderating effects of overexcitability emphasize the need for tailored interventions that consider individual differences in coping and resilience mechanisms. By recognizing the pivotal role of overexcitability in modulating the traumatic consequences of sexual objectification, this research advocates for the development of more nuanced and targeted support frameworks. Moreover, the study underscores the importance of continued research endeavors to unravel the intricate mechanisms and dynamics underpinning these relationships. Such endeavors are crucial for fostering the evolution of informed, evidence-based interventions and strategies aimed at mitigating the adverse effects of sexual objectification and promoting holistic well-being.

Keywords: sexual objectification, insidious trauma, emotional overexcitability, intellectual overexcitability, sensual overexcitability, psychomotor overexcitability, imaginational overexcitability

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Authors: Peter Kus, Anna Ostroverkh, Yurii Yakovlev, Yevheniia Lobko, Roman Fiala, Ivan Khalakhan, Vladimir Matolin

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Hydrogen economy is a concept of low-emission society which harvests most of its energy from renewable sources (e.g., wind and solar) and in case of overproduction, electrochemically turns the excess amount into hydrogen, which serves as an energy carrier. Proton exchange membrane water electrolyzers (PEMWE) are the backbone of this concept. By fast-response electricity to hydrogen conversion, the PEMWEs will not only stabilize the electrical grid but also provide high-purity hydrogen for variety of fuel cell powered devices, ranging from consumer electronics to vehicles. Wider commercialization of PEMWE technology is however hindered by high prices of noble metals which are necessary for catalyzing the redox reactions within the cell. Namely, platinum for hydrogen evolution reaction (HER), running on cathode, and iridium for oxygen evolution reaction (OER) on anode. Possible way of how to lower the loading of Pt and Ir is by using conductive high-surface nanostructures as catalyst supports in conjunction with thin-film catalyst deposition. The presented study discusses unconventional technique of membrane electron assembly (MEA) preparation. Noble metal catalysts (Pt and Ir) were magnetron sputtered in very low loadings onto the surface of porous sublayers (located on gas diffusion layer or directly on membrane), forming so to say localized three-phase boundary. Ultrasonically sprayed corrosion resistant TiC-based sublayer was used as a support material on anode, whereas magnetron sputtered nanostructured etched nitrogenated carbon (CNx) served the same role on cathode. By using this configuration, we were able to significantly decrease the amount of noble metals (to thickness of just tens of nanometers), while keeping the performance comparable to that of average state-of-the-art catalysts. Complex characterization of prepared supported catalysts includes in-cell performance and durability tests, electrochemical impedance spectroscopy (EIS) as well as scanning electron microscopy (SEM) imaging and X-ray photoelectron spectroscopy (XPS) analysis. Our research proves that magnetron sputtering is a suitable method for thin-film deposition of electrocatalysts. Tested set-up of thin-film supported anode and cathode catalysts with combined loading of just 120 ug.cm⁻² yields remarkable values of specific current. Described approach of thin-film low-loading catalyst deposition might be relevant when noble metal reduction is the topmost priority.

Keywords: hydrogen economy, low-loading catalyst, magnetron sputtering, proton exchange membrane water electrolyzer

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Authors: Judson P. LaGrone

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Simulation-based education in curricula was once a luxurious component of nursing programs but now serves as a vital element of an individual’s learning experience. A debriefing occurs after the simulation scenario or clinical experience is completed to allow the instructor(s) or trained professional(s) to act as a debriefer to guide a reflection with a purpose of acknowledging, assessing, and synthesizing the thought process, decision-making process, and actions/behaviors performed during the scenario or clinical experience. Debriefing is a vital component of the simulation process and educational experience to allow the learner(s) to progressively build upon past experiences and current scenarios within a safe and welcoming environment with a guided dialog to enhance future practice. The aim of this integrative review was to assess current practices of debriefing models in simulation-based education for health care professionals and students. The following databases were utilized for the search: CINAHL Plus, Cochrane Database of Systemic Reviews, EBSCO (ERIC), PsycINFO (Ovid), and Google Scholar. The advanced search option was useful to narrow down the search of articles (full text, Boolean operators, English language, peer-reviewed, published in the past five years). Key terms included debrief, debriefing, debriefing model, debriefing intervention, psychological debriefing, simulation, simulation-based education, simulation pedagogy, health care professional, nursing student, and learning process. Included studies focus on debriefing after clinical scenarios of nursing students, medical students, and interprofessional teams conducted between 2015 and 2020. Common themes were identified after the analysis of articles matching the search criteria. Several debriefing models are addressed in the literature with similarities of effectiveness for participants in clinical simulation-based pedagogy. Themes identified included (a) importance of debriefing in simulation-based pedagogy, (b) environment for which debriefing takes place is an important consideration, (c) individuals who should conduct the debrief, (d) length of debrief, and (e) methodology of the debrief. Debriefing models supported by theoretical frameworks and facilitated by trained staff are vital for a successful debriefing experience. Models differed from self-debriefing, facilitator-led debriefing, video-assisted debriefing, rapid cycle deliberate practice, and reflective debriefing. A reoccurring finding was centered around the emphasis of continued research for systematic tool development and analysis of the validity and effectiveness of current debriefing practices. There is a lack of consistency of debriefing models among nursing curriculum with an increasing rate of ill-prepared faculty to facilitate the debriefing phase of the simulation.

Keywords: debriefing model, debriefing intervention, health care professional, simulation-based education

Procedia PDF Downloads 142

Authors: G. C. Santini, C. Potrich, L. Lunelli, L. Vanzetti, S. Marasso, M. Cocuzza, C. Pederzolli

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The relevance of circulating miRNAs as non-invasive biomarkers for several pathologies is nowadays undoubtedly clear, as they have been found to have both diagnostic and prognostic value able to add fundamental information to patients’ clinical picture. The availability of these data, however, relies on a time-consuming process spanning from the sample collection and processing to the data analysis. In light of this, strategies which are able to ease this procedure are in high demand and considerable effort have been made in developing Lab-on-a-chip (LOC) devices able to speed up and standardise the bench work. In this context, a very promising polydimethylsiloxane (PDMS)-based microdevice which integrates the processing of the biological sample, i.e. purification of extracellular miRNAs, and reverse transcription was previously developed in our lab. In this study, we aimed at the improvement of the miRNA extraction performances of this micro device by increasing the ability of its surface to absorb extracellular miRNAs from biological samples. For this purpose, we focused on the modulation of two properties of the material: roughness and charge. PDMS surface roughness was modulated by casting with several templates (terminated with silicon oxide coated by a thin anti-adhesion aluminum layer), followed by a panel of curing conditions. Atomic force microscopy (AFM) was employed to estimate changes at the nanometric scale. To introduce modifications in surface charge we functionalized PDMS with different mixes of positively charged 3-aminopropyltrimethoxysilanes (APTMS) and neutral poly(ethylene glycol) silane (PEG). The surface chemical composition was characterized by X-ray photoelectron spectroscopy (XPS) and the number of exposed primary amines was quantified with the reagent sulfosuccinimidyl-4-o-(4,4-dimethoxytrityl) butyrate (s-SDTB). As our final end point, the adsorption rate of all these different conditions was assessed by fluorescence microscopy by incubating a synthetic fluorescently-labeled miRNA. Our preliminary analysis identified casting on thermally grown silicon oxide, followed by a curing step at 85°C for 1 hour, as the most efficient technique to obtain a PDMS surface roughness in the nanometric scaleable to trap miRNA. In addition, functionalisation with 0.1% APTMS and 0.9% PEG was found to be a necessary step to significantly increase the amount of microRNA adsorbed on the surface, therefore, available for further steps as on-chip reverse transcription. These findings show a substantial improvement in the extraction efficiency of our PDMS microdevice, ultimately leading to an important step forward in the development of an innovative, easy-to-use and integrated system for the direct purification of less abundant circulating microRNAs.

Keywords: circulating miRNAs, diagnostics, Lab-on-a-chip, polydimethylsiloxane (PDMS)

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Authors: Maryam Ziaee

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This research proposes a new approach and provides an opportunity for manufacturing companies to produce large amounts of products that meet their prospective customers’ tastes, needs, and expectations and simultaneously enable manufacturers to increase their profit. Mass customization is the production of products or services to meet each individual customer’s desires to the greatest possible extent in high quantities and at reasonable prices. This process takes place at different levels such as the customization of goods’ design, assembly, sale, and delivery status, and classifies in several categories. The main focus of this study is on one class of mass customization, called optional customization, in which companies try to provide their customers with as many options as possible to customize their products. These options could range from the design phase to the manufacturing phase, or even methods of delivery. Mass customization values customers’ tastes, but it is only one side of clients’ satisfaction; on the other side is companies’ fast responsiveness delivery. It brings the concept of agility, which is the ability of a company to respond rapidly to changes in volatile markets in terms of volume and variety. Indeed, mass customization is not effectively feasible without integrating the concept of agility. To gain the customers’ satisfaction, the companies need to be quick in responding to their customers’ demands, thus highlighting the significance of agility. This research offers a different method that successfully integrates mass customization and fast production in manufacturing industries. This research is built upon the hypothesis that the success key to being agile in mass customization is to forecast demand, cooperate with suppliers, and control inventory. Therefore, the significance of the supply chain (SC) is more pertinent when it comes to this stage. Since SC behavior is dynamic and its behavior changes constantly, companies have to apply one of the predicting techniques to identify the changes associated with SC behavior to be able to respond properly to any unwelcome events. System dynamics utilized in this research is a simulation approach to provide a mathematical model among different variables to understand, control, and forecast SC behavior. The final stage is delayed differentiation, the production strategy considered in this research. In this approach, the main platform of products is produced and stocked and when the company receives an order from a customer, a specific customized feature is assigned to this platform and the customized products will be created. The main research question is to what extent applying system dynamics for the prediction of SC behavior improves the agility of mass customization. This research is built upon a qualitative approach to bring about richer, deeper, and more revealing results. The data is collected through interviews and is analyzed through NVivo software. This proposed model offers numerous benefits such as reduction in the number of product inventories and their storage costs, improvement in the resilience of companies’ responses to their clients’ needs and tastes, the increase of profits, and the optimization of productivity with the minimum level of lost sales.

Keywords: agility, manufacturing, resilience, supply chain

Procedia PDF Downloads 89

Authors: A. Sgobba, C. Meskell

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The feasibility of on-site electricity production from solar and wind and the resulting load management for a specific manufacturing plant in Ireland are assessed. The industry sector accounts directly and indirectly for a high percentage of electricity consumption and global greenhouse gas emissions; therefore, it will play a key role in emission reduction and control. Manufacturing plants, in particular, are often located in non-residential areas since they require open spaces for production machinery, parking facilities for the employees, appropriate routes for supply and delivery, special connections to the national grid and other environmental impacts. Since they have larger spaces compared to commercial sites in urban areas, they represent an appropriate case study for evaluating the technical and economic viability of energy system integration with low power density technologies, such as solar and wind, for on-site electricity generation. The available open space surrounding the analysed manufacturing plant can be efficiently used to produce a discrete quantity of energy, instantaneously and locally consumed. Therefore, transmission and distribution losses can be reduced. The usage of storage is not required due to the high and almost constant electricity consumption profile. The energy load of the plant is identified through the analysis of gas and electricity consumption, both internally monitored and reported on the bills. These data are not often recorded and available to third parties since manufacturing companies usually keep track only of the overall energy expenditures. The solar potential is modelled for a period of 21 years based on global horizontal irradiation data; the hourly direct and diffuse radiation and the energy produced by the system at the optimum pitch angle are calculated. The model is validated using PVWatts and SAM tools. Wind speed data are available for the same period within one-hour step at a height of 10m. Since the hub of a typical wind turbine reaches a higher altitude, complementary data for a different location at 50m have been compared, and a model for the estimate of wind speed at the required height in the right location is defined. Weibull Statistical Distribution is used to evaluate the wind energy potential of the site. The results show that solar and wind energy are, as expected, generally decoupled. Based on the real case study, the percentage of load covered every hour by on-site generation (Level of Autonomy LA) and the resulting electricity bought from the grid (Expected Energy Not Supplied EENS) are calculated. The economic viability of the project is assessed through Net Present Value, and the influence the main technical and economic parameters have on NPV is presented. Since the results show that the analysed renewable sources can not provide enough electricity, the integration with a cogeneration technology is studied. Finally, the benefit to energy system integration of wind, solar and a cogeneration technology is evaluated and discussed.

Keywords: demand, energy system integration, load, manufacturing, national grid, renewable energy sources

Procedia PDF Downloads 129

Authors: Iris Xiaohong Quan

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The global digital health market reached 175 billion U.S. dollars in 2019, and is expected to grow at about 25% CAGR to over 650 billion USD by 2025. Different terms such as digital health, e-health, mHealth, telehealth have been used in the field, which can sometimes cause confusion. The term digital health was originally introduced to refer specifically to the use of interactive media, tools, platforms, applications, and solutions that are connected to the Internet to address health concerns of providers as well as consumers. While mHealth emphasizes the use of mobile phones in healthcare, telehealth means using technology to remotely deliver clinical health services to patients. According to FDA, “the broad scope of digital health includes categories such as mobile health (mHealth), health information technology (IT), wearable devices, telehealth and telemedicine, and personalized medicine.” Some researchers believe that digital health is nothing else but the cultural transformation healthcare has been going through in the 21st century because of digital health technologies that provide data to both patients and medical professionals. As digital health is burgeoning, but research in the area is still inadequate, our paper aims to clear the definition confusion and provide an overall picture of digital health companies. We further investigate how business models are designed and differentiated in the emerging digital health sector. Both quantitative and qualitative methods are adopted in the research. For the quantitative analysis, our research data came from two databases Crunchbase and CBInsights, which are well-recognized information sources for researchers, entrepreneurs, managers, and investors. We searched a few keywords in the Crunchbase database based on companies’ self-description: digital health, e-health, and telehealth. A search of “digital health” returned 941 unique results, “e-health” returned 167 companies, while “telehealth” 427. We also searched the CBInsights database for similar information. After merging and removing duplicate ones and cleaning up the database, we came up with a list of 1464 companies as digital health companies. A qualitative method will be used to complement the quantitative analysis. We will do an in-depth case analysis of three successful unicorn digital health companies to understand how business models evolve and discuss the challenges faced in this sector. Our research returned some interesting findings. For instance, we found that 86% of the digital health startups were founded in the recent decade since 2010. 75% of the digital health companies have less than 50 employees, and almost 50% with less than 10 employees. This shows that digital health companies are relatively young and small in scale. On the business model analysis, while traditional healthcare businesses emphasize the so-called “3P”—patient, physicians, and payer, digital health companies extend to “5p” by adding patents, which is the result of technology requirements (such as the development of artificial intelligence models), and platform, which is an effective value creation approach to bring the stakeholders together. Our case analysis will detail the 5p framework and contribute to the extant knowledge on business models in the healthcare industry.

Keywords: digital health, business models, entrepreneurship opportunities, healthcare

Procedia PDF Downloads 183

Authors: Riya Bose, Ashok Bera, Manas R. Parida, Anirudhha Adhikari, Basamat S. Shaheen, Erkki Alarousu, Jingya Sun, Tom Wu, Osman M. Bakr, Omar F. Mohammed

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This work reports visualization of charge carrier dynamics on the surface of copper indium gallium selenide (CIGSe) nanocrystals in real space and time using four-dimensional scanning ultrafast electron microscopy (4D S-UEM) and correlates it with the optoelectronic properties of the nanocrystals. The surface of the nanocrystals plays a key role in controlling their applicability for light emitting and light harvesting purposes. Typically for quaternary systems like CIGSe, which have many desirable attributes to be used for optoelectronic applications, relative abundance of surface trap states acting as non-radiative recombination centre for charge carriers remains as a major bottleneck preventing further advancements and commercial exploitation of these nanocrystals devices. Though ultrafast spectroscopic techniques allow determining the presence of picosecond carrier trapping channels, because of relative larger penetration depth of the laser beam, only information mainly from the bulk of the nanocrystals is obtained. Selective mapping of such ultrafast dynamical processes on the surfaces of nanocrystals remains as a key challenge, so far out of reach of purely optical probing time-resolved laser techniques. In S-UEM, the optical pulse generated from a femtosecond (fs) laser system is used to generate electron packets from the tip of the scanning electron microscope, instead of the continuous electron beam used in the conventional setup. This pulse is synchronized with another optical excitation pulse that initiates carrier dynamics in the sample. The principle of S-UEM is to detect the secondary electrons (SEs) generated in the sample, which is emitted from the first few nanometers of the top surface. Constructed at different time delays between the optical and electron pulses, these SE images give direct and precise information about the carrier dynamics on the surface of the material of interest. In this work, we report selective mapping of surface dynamics in real space and time of CIGSe nanocrystals applying 4D S-UEM. We show that the trap states can be considerably passivated by ZnS shelling of the nanocrystals, and the carrier dynamics can be significantly slowed down. We also compared and discussed the S-UEM kinetics with the carrier dynamics obtained from conventional ultrafast time-resolved techniques. Additionally, a direct effect of the state trap removal can be observed in the enhanced photoresponse of the nanocrystals after shelling. Direct observation of surface dynamics will not only provide a profound understanding of the photo-physical mechanisms on nanocrystals’ surfaces but also enable to unlock their full potential for light emitting and harvesting applications.

Keywords: 4D scanning ultrafast microscopy, charge carrier dynamics, nanocrystals, optoelectronics, surface passivation, trap states

Procedia PDF Downloads 295

Authors: Ghita Benayad

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Asset allocation, which affects the long-term profitability of portfolios by distributing assets to fulfill a range of investment objectives, is the cornerstone of investment management in the dynamic and complicated world of financial markets. This paper offers a technique for optimizing strategic asset allocation with the goal of improving portfolio performance by addressing the inherent complexity and uncertainty of the market through the use of Principal Component Analysis (PCA) in a multi-objective modeling framework. The study's first section starts with a critical evaluation of conventional asset allocation techniques, highlighting how poorly they are able to capture the intricate relationships between assets and the volatile nature of the market. In order to overcome these challenges, the project suggests a PCA-driven methodology that isolates important characteristics influencing asset returns by decreasing the dimensionality of the investment universe. This decrease provides a stronger basis for asset allocation decisions by facilitating a clearer understanding of market structures and behaviors. Using a multi-objective optimization model, the project builds on this foundation by taking into account a number of performance metrics at once, including risk minimization, return maximization, and the accomplishment of predetermined investment goals like regulatory compliance or sustainability standards. This model provides a more comprehensive understanding of investor preferences and portfolio performance in comparison to conventional single-objective optimization techniques. While applying the PCA-driven multi-objective optimization model to historical market data, aiming to construct portfolios better under different market situations. As compared to portfolios produced from conventional asset allocation methodologies, the results show that portfolios optimized using the proposed method display improved risk-adjusted returns, more resilience to market downturns, and better alignment with specified investment objectives. The study also looks at the implications of this PCA technique for portfolio management, including the prospect that it might give investors a more advanced framework for navigating financial markets. The findings suggest that by combining PCA with multi-objective optimization, investors may obtain a more strategic and informed asset allocation that is responsive to both market conditions and individual investment preferences. In conclusion, this capstone project improves the field of financial engineering by creating a sophisticated asset allocation optimization model that integrates PCA with multi-objective optimization. In addition to raising concerns about the condition of asset allocation today, the proposed method of portfolio management opens up new avenues for research and application in the area of investment techniques.

Keywords: asset allocation, portfolio optimization, principle component analysis, multi-objective modelling, financial market

Procedia PDF Downloads 47

Authors: Abhishek Sraw, Amit Sobti, Yamini Pandey, R. K. Wanchoo, Amrit Pal Toor

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Monocrotophos (MCP) is a widely used pesticide in India, which belong to an extremely toxic organophosphorus family, is persistent in nature and its toxicity is widely reported in all environmental segments in the country. Advanced Oxidation Process (AOP) is a promising solution to the problem of water pollution. TiO₂ is being widely used as a photocatalyst because of its many advantages, but it has a large band gap, due to which it is modified using metal and nonmetal dopant to make it active under sunlight and visible light. The use of nanosized powdered catalysts makes the recovery process extremely complicated. Hence the aim is to use low cost, easily available, eco-friendly clay material in form of bead as the support for the immobilization of catalyst, to solve the problem of post-separation of suspended catalyst from treated water. A recirculation type photocatalytic reactor (RTPR), using ultraviolet light emitting source (blue black lamp) was designed which work effectively for both suspended catalysts and catalyst coated clay beads. The bare, TiO₂ and W-TiO₂ coated clay beads were characterized by scanning electron microscopy (SEM), electron dispersive spectroscopy (EDS) and N₂ adsorption–desorption measurements techniques (BET) for their structural, textural and electronic properties. The study involved variation of different parameters like light conditions, recirculation rate, light intensity and initial MCP concentration under UV and sunlight for the degradation of MCP. The degradation and mineralization studies of the insecticide solution were performed using UV-Visible spectrophotometer, and COD vario-photometer and GC-MS analysis respectively. The main focus of the work lies in checking the recyclability of the immobilized TiO₂ over clay beads in the developed RTPR up to 30 continuous cycles without reactivation of catalyst. The results demonstrated the economic feasibility of the utilization of developed RTPR for the efficient purification of pesticide polluted water. The prepared TiO₂ clay beads delivered 75.78% degradation of MCP under UV light with negligible catalyst loss. Application of W-TiO₂ coated clay beads filled RTPR for the degradation of MCP under sunlight, however, shows 32% higher degradation of MCP than the same system based on undoped TiO₂. The COD measurements of TiO₂ coated beads led to 73.75% COD reduction while W-TiO₂ resulted in 87.89% COD reduction. The GC-MS analysis confirms the efficient breakdown of complex MCP molecules into simpler hydrocarbons. This supports the promising application of clay beads as a support for the photocatalyst and proves its eco-friendly nature, excellent recyclability, catalyst holding capacity, and economic viability.

Keywords: immobilized clay beads, monocrotophos, recirculation type photocatalytic reactor, TiO₂

Procedia PDF Downloads 178

Authors: Mustafa Metin Donma, Orkide Donma

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Vitamin deficiencies are common in obese individuals. Particularly, the status of vitamin B12 and its association with vitamin B9 (folate) and vitamin D is under investigation in recent time. Vitamin B12 is closely related to many vital processes in the body. In clinical studies, its involvement in fat metabolism draws attention from the obesity point of view. Obesity, in its advanced stages and in combination with metabolic syndrome (MetS) findings, may be a life-threatening health problem. Pediatric obesity is particularly important because it may be a predictor of severe chronic diseases during the adulthood period of the child. Due to its role in fat metabolism, vitamin B12 deficiency may disrupt metabolic pathways of the lipid and energy metabolisms in the body. The association of low B12 levels with obesity degree may be an interesting topic to be investigated. Obesity indices may be helpful at this point. Weight- and fat-based indices are available. Of them, body mass index (BMI) is in the first group. Fat mass index (FMI), fat-free mass index (FFMI) and diagnostic obesity notation model assessment-II (D2I) index lie in the latter group. The aim of this study is to clarify possible associations between vitamin B12 status and obesity indices in the pediatric population. The study comprises a total of one hundred and twenty-two children. Thirty-two children were included in the normal body mass index (N-BMI) group. Forty-six and forty-four children constitute groups with morbid obese children without MetS and with MetS, respectively. Informed consent forms and the approval of the institutional ethics committee were obtained. Tables prepared for obesity classification by World Health Organization were used. Metabolic syndrome criteria were defined. Anthropometric and blood pressure measurements were taken. Body mass index, FMI, FFMI, D2I were calculated. Routine laboratory tests were performed. Vitamin B9, B12, D concentrations were determined. Statistical evaluation of the study data was performed. Vitamin B9 and vitamin D levels were reduced in MetS group compared to children with N-BMI (p>0.05). Significantly lower values were observed in vitamin B12 concentrations of MetS group (p<0.01). Upon evaluation of blood pressure as well as triglyceride levels, there exist significant increases in morbid obese children. Significantly decreased concentrations of high density lipoprotein cholesterol were observed. All of the obesity indices and insulin resistance index exhibit increasing tendency with the severity of obesity. Inverse correlations were calculated between vitamin D and insulin resistance index as well as vitamin B12 and D2I in morbid obese groups. In conclusion, a fat-based index, D2I, was the most prominent body index, which shows a strong correlation with vitamin B12 concentrations in the late stage of obesity in children. A negative correlation between these two parameters was a confirmative finding related to the association between vitamin B12 and obesity degree.

Keywords: body mass index, children, D2I index, fat mass index, obesity

Procedia PDF Downloads 206

Authors: Zuyong Chen, Jianghao Wu, Yanlai Zhang

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Flapping-wing micro aerial vehicle (FMAV) is a new type of aircraft by mimicking the flying behavior to that of small birds or insects. Comparing to the traditional fixed wing or rotor-type aircraft, FMAV only needs to control the motion of flapping wings, by changing the size and direction of lift to control the flight attitude. Therefore, its transmission system should be designed very compact. Lightweight design can effectively extend its endurance time, while engineering experience alone is difficult to simultaneously meet the requirements of FMAV for structural strength and quality. Current researches still lack the guidance of considering nonlinear factors of 3D printing material when carrying out topology optimization, especially for the tiny FMAV transmission system. The coupling of non-linear material properties and non-linear contact behaviors of FMAV transmission system is a great challenge to the reliability of the topology optimization result. In this paper, topology optimization design based on FEA solver package Altair Optistruct for the transmission system of FMAV manufactured by 3D Printing was carried out. Firstly, the isotropic constitutive behavior of the Ultraviolet (UV) Cureable Resin used to fabricate the structure of FMAV was evaluated and confirmed through tensile test. Secondly, a numerical computation model describing the mechanical behavior of FMAV transmission structure was established and verified by experiments. Then topology optimization modeling method considering non-linear factors were presented, and optimization results were verified by dynamic simulation and experiments. Finally, detail discussions of different load status and constraints were carried out to explore the leading factors affecting the optimization results. The contributions drawn from this article helpful for guiding the lightweight design of FMAV are summarizing as follow; first, a dynamic simulation modeling method used to obtain the load status is presented. Second, verification method of optimized results considering non-linear factors is introduced. Third, based on or can achieve a better weight reduction effect and improve the computational efficiency rather than taking multi-states into account. Fourth, basing on makes for improving the ability to resist bending deformation. Fifth, constraint of displacement helps to improve the structural stiffness of optimized result. Results and engineering guidance in this paper may shed lights on the structural optimization and light-weight design for future advanced FMAV.

Keywords: flapping-wing micro aerial vehicle, 3d printing, topology optimization, finite element analysis, experiment

Procedia PDF Downloads 168

Authors: Pardis Moslemzadeh Tehrani

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Due to the emergence of blockchain technology and the benefits of cryptocurrencies, intelligent or smart contracts are gaining traction. Artificial intelligence (AI) is transforming our lives, and it is being embraced by a wide range of sectors. Smart contracts, which are at the heart of blockchains, incorporate AI characteristics. Such contracts are referred to as "smart" contracts because of the underlying technology that allows contracting parties to agree on terms expressed in computer code that defines machine-readable instructions for computers to follow under specific situations. The transmission happens automatically if the conditions are met. Initially utilised for financial transactions, blockchain applications have since expanded to include the financial, insurance, and medical sectors, as well as supply networks. Raw material acquisition by suppliers, design, and fabrication by manufacturers, delivery of final products to consumers, and even post-sales logistics assistance are all part of supply chains. Many issues are linked with managing supply chains from the planning and coordination stages, which can be implemented in a smart contract in a blockchain due to their complexity. Manufacturing delays and limited third-party amounts of product components have raised concerns about the integrity and accountability of supply chains for food and pharmaceutical items. Other concerns include regulatory compliance in multiple jurisdictions and transportation circumstances (for instance, many products must be kept in temperature-controlled environments to ensure their effectiveness). Products are handled by several providers before reaching customers in modern economic systems. Information is sent between suppliers, shippers, distributors, and retailers at every stage of the production and distribution process. Information travels more effectively when individuals are eliminated from the equation. The usage of blockchain technology could be a viable solution to these coordination issues. In blockchains, smart contracts allow for the rapid transmission of production data, logistical data, inventory levels, and sales data. This research investigates the legal and technical advantages and disadvantages of AI-blockchain technology in the supply chain business. It aims to uncover the applicable legal problems and barriers to the use of AI-blockchain technology to supply chains, particularly in the food industry. It also discusses the essential legal and technological issues and impediments to supply chain implementation for stakeholders, as well as methods for overcoming them before releasing the technology to clients. Because there has been little research done on this topic, it is difficult for industrial stakeholders to grasp how blockchain technology could be used in their respective operations. As a result, the focus of this research will be on building advanced and complex contractual terms in supply chain smart contracts on blockchains to cover all unforeseen supply chain challenges.

Keywords: blockchain, supply chain, IoT, smart contract

Procedia PDF Downloads 126

Authors: Marina Shakleina, Konstantin Shaklein, Stanislav Yakiro

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The digitalization of modern human life over the last decade has facilitated the acquisition, storage, and processing of data, which are used to detect changes in consumer preferences and to improve the internal efficiency of the production process. This emerging trend has attracted academic interest in the use of big data in research. The study focuses on modeling the social comfort of the Russian population for the period 2010-2021 using big data. Big data provides enormous opportunities for understanding human interactions at the scale of society with plenty of space and time dynamics. One of the most popular big data sources is Google Trends. The methodology for assessing social comfort using big data involves several steps: 1. 574 words were selected based on the Harvard IV-4 Dictionary adjusted to fit the reality of everyday Russian life. The set of keywords was further cleansed by excluding queries consisting of verbs and words with several lexical meanings. 2. Search queries were processed to ensure comparability of results: the transformation of data to a 10-point scale, elimination of popularity peaks, detrending, and deseasoning. The proposed methodology for keyword search and Google Trends processing was implemented in the form of a script in the Python programming language. 3. Block and summary integral indicators of social comfort were constructed using the first modified principal component resulting in weighting coefficients values of block components. According to the study, social comfort is described by 12 blocks: ‘health’, ‘education’, ‘social support’, ‘financial situation’, ‘employment’, ‘housing’, ‘ethical norms’, ‘security’, ‘political stability’, ‘leisure’, ‘environment’, ‘infrastructure’. According to the model, the summary integral indicator increased by 54% and was 4.631 points; the average annual rate was 3.6%, which is higher than the rate of economic growth by 2.7 p.p. The value of the indicator describing social comfort in Russia is determined by 26% by ‘social support’, 24% by ‘education’, 12% by ‘infrastructure’, 10% by ‘leisure’, and the remaining 28% by others. Among 25% of the most popular searches, 85% are of negative nature and are mainly related to the blocks ‘security’, ‘political stability’, ‘health’, for example, ‘crime rate’, ‘vulnerability’. Among the 25% most unpopular queries, 99% of the queries were positive and mostly related to the blocks ‘ethical norms’, ‘education’, ‘employment’, for example, ‘social package’, ‘recycling’. In conclusion, the introduction of the latent category ‘social comfort’ into the scientific vocabulary deepens the theory of the quality of life of the population in terms of the study of the involvement of an individual in the society and expanding the subjective aspect of the measurements of various indicators. Integral assessment of social comfort demonstrates the overall picture of the development of the phenomenon over time and space and quantitatively evaluates ongoing socio-economic policy. The application of big data in the assessment of latent categories gives stable results, which opens up possibilities for their practical implementation.

Keywords: big data, Google trends, integral indicator, social comfort

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Authors: Francis Gyapong, Denis Yar

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The use of cell phones has become an indispensable tool in the hospital's settings. Cell phones are used in hospitals without restrictions regardless of their unknown microbial load. However, the indiscriminate use of mobile devices, especially at health facilities, can act as a vehicle for transmitting pathogenic bacteria and other microorganisms. These potential pathogens become exogenous sources of infection for the patients and are also a potential health hazard for self and as well as family members. These are a growing problem in many health care institutions. Innovations in mobile communication have led to better patient care in diabetes, asthma, and increased in vaccine uptake via SMS. Notwithstanding, the use of cell phones can be a great potential source for nosocomial infections. Many studies reported heavy microbial contamination of cell phones among healthcare workers and communities. However, limited studies have been reported in our region on bacterial contamination on cell phones among healthcare workers. This study assessed microbial contamination of cell phones of health care workers (HCWs) at the Mampong Municipal Government Hospital (MMGH), Ghana. A cross-sectional design was used to characterize bacterial microflora on cell phones of HCWs at the MMGH. A total of thirty-five (35) swab samples of cell phones of HCWs at the Laboratory, Dental Unit, Children’s Ward, Theater and Male ward were randomly collected for laboratory examinations. A suspension of the swab samples was each streak on blood and MacConkey agar and incubated at 37℃ for 48 hours. Bacterial isolates were identified using appropriate laboratory and biochemical tests. Kirby-Bauer disc diffusion method was used to determine the antimicrobial sensitivity tests of the isolates. Data analysis was performed using SPSS version 16. All mobile phones sampled were contaminated with one or more bacterial isolates. Cell phones from the Male ward, Dental Unit, Laboratory, Theatre and Children’s ward had at least three different bacterial isolates; 85.7%, 71.4%, 57.1% and 28.6% for both Theater and Children’s ward respectively. Bacterial contaminants identified were Staphylococcus epidermidis (37%), Staphylococcus aureus (26%), E. coli (20%), Bacillus spp. (11%) and Klebsiella spp. (6 %). Except for the Children ward, E. coli was isolated at all study sites and predominant (42.9%) at the Dental Unit while Klebsiella spp. (28.6%) was only isolated at the Children’s ward. Antibiotic sensitivity testing of Staphylococcus aureus indicated that they were highly sensitive to cephalexin (89%) tetracycline (80%), gentamycin (75%), lincomycin (70%), ciprofloxacin (67%) and highly resistant to ampicillin (75%). Some of these bacteria isolated are potential pathogens and their presence on cell phones of HCWs could be transmitted to patients and their families. Hence strict hand washing before and after every contact with patient and phone be enforced to reduce the risk of nosocomial infections.

Keywords: mobile phones, bacterial contamination, patients, MMGH

Procedia PDF Downloads 103

Authors: Seema Dhariwal, Kiran Maan, Ruchi Baghel, Apoorva Sharma, Poonam Rana

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Introduction: Traumatic brain injury (TBI) is defined as the temporary or permanent alteration in brain function and pathology caused by an external mechanical force. It represents the leading cause of mortality and morbidity among children and youth individuals. Various models of TBI in rodents have been developed in the laboratory to mimic the scenario of injury. Blast overpressure injury is common among civilians and military personnel, followed by accidents or explosive devices. In addition to this, the lateral Controlled cortical impact (CCI) model mimics the blunt, penetrating injury. Method: In the present study, we have developed two different mild TBI models using blast and CCI injury. In the blast model, helium gas was used to create an overpressure of 130 kPa (±5) via a shock tube, and CCI injury was induced with an impact depth of 1.5mm to create diffusive and focal injury, respectively. C57BL/6J male mice (10-12 weeks) were divided into three groups: (1) control, (2) Blast treated, (3) CCI treated, and were exposed to different injury models. Serum was collected on Day1 and day7, followed by biphasic extraction using MTBE/Methanol/Water. Prepared samples were separated on Charged Surface Hybrid (CSH) C18 column and acquired on UHPLC-Q-TOF-MS using ESI probe with inhouse optimized parameters and method. MS peak list was generated using Markerview TM. Data were normalized, Pareto-scaled, and log-transformed, followed by multivariate and univariate analysis in metaboanalyst. Result and discussion: Untargeted profiling of lipids generated extensive data features, which were annotated through LIPID MAPS® based on their m/z and were further confirmed based on their fragment pattern by LipidBlast. There is the final annotation of 269 features in the positive and 182 features in the negative mode of ionization. PCA and PLS-DA score plots showed clear segregation of injury groups to controls. Among various lipids in mild blast and CCI, five lipids (Glycerophospholipids {PC 30:2, PE O-33:3, PG 28:3;O3 and PS 36:1 } and fatty acyl { FA 21:3;O2}) were significantly altered in both injury groups at Day 1 and Day 7, and also had VIP score >1. Pathway analysis by Biopan has also shown hampered synthesis of Glycerolipids and Glycerophospholipiods, which coincides with earlier reports. It could be a direct result of alteration in the Acetylcholine signaling pathway in response to TBI. Understanding the role of a specific class of lipid metabolism, regulation and transport could be beneficial to TBI research since it could provide new targets and determine the best therapeutic intervention. This study demonstrates the potential lipid biomarkers which can be used for injury severity diagnosis and identification irrespective of injury type (diffusive or focal).

Keywords: LipidBlast, lipidomic biomarker, LIPID MAPS®, TBI

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Authors: Sanjeev Kumar Appicharla

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This paper presents the results of the modelling and analysis of the European Railway Traffic Management (ERTMS) safety-critical incident to raise awareness of biases in the systems engineering process on the Cambrian Railway in the UK using the RAIB 17/2019 as a primary input. The RAIB, the UK independent accident investigator, published the Report- RAIB 17/2019 giving the details of their investigation of the focal event in the form of immediate cause, causal factors, and underlying factors and recommendations to prevent a repeat of the safety-critical incident on the Cambrian Line. The Systems for Investigation of Railway Interfaces (SIRI) is the methodology used to model and analyze the safety-critical incident. The SIRI methodology uses the Swiss Cheese Model to model the incident and identify latent failure conditions (potentially less than adequate conditions) by means of the management oversight and risk tree technique. The benefits of the systems for investigation of railway interfaces methodology (SIRI) are threefold: first is that it incorporates the “Heuristics and Biases” approach advanced by 2002 Nobel laureate in Economic Sciences, Prof Daniel Kahneman, in the management oversight and risk tree technique to identify systematic errors. Civil engineering and programme management railway professionals are aware of the role “optimism bias” plays in programme cost overruns and are aware of bow tie (fault and event tree) model-based safety risk modelling techniques. However, the role of systematic errors due to “Heuristics and Biases” is not appreciated as yet. This overcomes the problems of omission of human and organizational factors from accident analysis. Second, the scope of the investigation includes all levels of the socio-technical system, including government, regulatory, railway safety bodies, duty holders, signaling firms and transport planners, and front-line staff such that lessons are learned at the decision making and implementation level as well. Third, the author’s past accident case studies are supplemented with research pieces of evidence drawn from the practitioner's and academic researchers’ publications as well. This is to discuss the role of system thinking to improve the decision-making and risk management processes and practices in the IEC 15288 systems engineering standard and in the industrial context such as the GB railways and artificial intelligence (AI) contexts as well.

Keywords: accident analysis, AI algorithm internal audit, bounded rationality, Byzantine failures, heuristics and biases approach

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Authors: Yesim Sucullu Karadag, Pinar Kurt, Sule Bilen, Nese Subutay Oztekin, Fikri Ak

Abstract:

Background: Primary cervical dystonia is thought to be a purely motor disorder. But recent studies revealed that patients with dystonia had additional non-motor features. Sensory and psychiatric disturbances could be included into the non-motor spectrum of dystonia. The Basal Ganglia receive inputs from all cortical areas and throughout the thalamus project to several cortical areas, thus participating to circuits that have been linked to motor as well as sensory, emotional and cognitive functions. However, there are limited studies indicating cognitive impairment in patients with cervical dystonia. More evidence is required regarding neurocognitive functioning in these patients. Objective: This study is aimed to investigate neurocognitive profile of cervical dystonia patients in comparison to healthy controls (HC) by employing a detailed set of neuropsychological tests in addition to self-reported instruments. Methods: Totally 29 (M/F: 7/22) cervical dystonia patients and 30 HC (M/F: 10/20) were included into the study. Exclusion criteria were depression and not given informed consent. Standard demographic, educational data and clinical reports (disease duration, disability index) were recorded for all patients. After a careful neurological evaluation, all subjects were given a comprehensive battery of neuropsychological tests: Self report of neuropsychological condition (by visual analogue scale-VAS, 0-100), RAVLT, STROOP, PASAT, TMT, SDMT, JLOT, DST, COWAT, ACTT, and FST. Patients and HC were compared regarding demographic, clinical features and neurocognitive tests. Also correlation between disease duration, disability index and self report -VAS were assessed. Results: There was no difference between patients and HCs regarding socio-demographic variables such as age, gender and years of education (p levels were 0.36, 0.436, 0.869; respectively). All of the patients were assessed at the peak of botulinum toxine effect and they were not taking an anticholinergic agent or benzodiazepine. Dystonia patients had significantly impaired verbal learning and memory (RAVLT, p<0.001), divided attention and working memory (ACTT, p<0.001), attention speed (TMT-A and B, p=0.008, 0.050), executive functions (PASAT, p<0.001; SDMT, p= 0.001; FST, p<0.001), verbal attention (DST, p=0.001), verbal fluency (COWAT, p<0.001), visio-spatial processing (JLOT, p<0.001) in comparison to healthy controls. But focused attention (STROOP-spontaneous correction) was not different between two groups (p>0.05). No relationship was found regarding disease duration and disability index with any neurocognitive tests. Conclusions: Our study showed that neurocognitive functions of dystonia patients were worse than control group with the similar age, sex, and education independently clinical expression like disease duration and disability index. This situation may be the result of possible cortical and subcortical changes in dystonia patients. Advanced neuroimaging techniques might be helpful to explain these changes in cervical dystonia patients.

Keywords: cervical dystonia, neurocognitive impairment, neuropsychological test, dystonia disability index

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Authors: Paula Marín, Mohammad Saffari, Alvaro de Gracia, Luisa F. Cabeza, Svetlana Ushak

Abstract:

Climate control represents an important issue when referring to energy consumption of buildings and associated expenses, both in installation or operation periods. The climate control of a building relies on several factors. Among them, localization, orientation, architectural elements, sources of energy used, are considered. In order to study the thermal behaviour of a building set up, the present study proposes the use of energy simulation program Energy Plus. In recent years, energy simulation programs have become important tools for evaluation of thermal/energy performance of buildings and facilities. Besides, the need to find new forms of passive conditioning in buildings for energy saving is a critical component. The use of phase change materials (PCMs) for heat storage applications has grown in importance due to its high efficiency. Therefore, the climatic conditions of Northern Chile: high solar radiation and extreme temperature fluctuations ranging from -10°C to 30°C (Calama city), low index of cloudy days during the year are appropriate to take advantage of solar energy and use passive systems in buildings. Also, the extensive mining activities in northern Chile encourage the use of large numbers of containers to harbour workers during shifts. These containers are constructed with lightweight construction systems, requiring heating during night and cooling during day, increasing the HVAC electricity consumption. The use of PCM can improve thermal comfort and reduce the energy consumption. The objective of this study was to evaluate the thermal and energy performance of containers of 2.5×2.5×2.5 m3, located in four cities of Chile: Antofagasta, Calama, Santiago, and Concepción. Lightweight envelopes, typically used in these building prototypes, were evaluated considering a container without PCM inclusion as the reference building and another container with PCM-enhanced envelopes as a test case, both of which have a door and a window in the same wall, orientated in two directions: North and South. To see the thermal response of these containers in different seasons, the simulations were performed considering a period of one year. The results show that higher energy savings for the four cities studied are obtained when the distribution of door and window in the container is in the north direction because of higher solar radiation incidence. The comparison of HVAC consumption and energy savings in % for north direction of door and window are summarised. Simulation results show that in the city of Antofagasta 47% of heating energy could be saved and in the cities of Calama and Concepción the biggest savings in terms of cooling could be achieved since PCM reduces almost all the cooling demand. Currently, based on simulation results, four containers have been constructed and sized with the same structural characteristics carried out in simulations, that are, containers with/without PCM, with door and window in one wall. Two of these containers will be placed in Antofagasta and two containers in a copper mine near to Calama, all of them will be monitored for a period of one year. The simulation results will be validated with experimental measurements and will be reported in the future.

Keywords: energy saving, lightweight construction, PCM, simulation

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