Search results for: electric driven heat pump

Authors: I. Szer, J. Szer, K. Czarnocki, E. Błazik-Borowa

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People on construction scaffoldings work in dynamically changing, often unfavourable climate. Additionally, this kind of work is performed on low stiffness structures at high altitude, which increases the risk of accidents. It is therefore desirable to define the parameters of the work environment that contribute to increasing the construction worker occupational safety level. The aim of this article is to present how changes in microclimate parameters on scaffolding can impact the development of dangerous situations and accidents. For this purpose, indicators based on the human thermal balance were used. However, use of this model under construction conditions is often burdened by significant errors or even impossible to implement due to the lack of precise data. Thus, in the target model, the modified parameter was used – apparent environmental temperature. Apparent temperature in the proposed Scaffold Use Risk Assessment Model has been a perceived outdoor temperature, caused by the combined effects of air temperature, radiative temperature, relative humidity and wind speed (wind chill index, heat index). In the paper, correlations between component factors and apparent temperature for facade scaffolding with a width of 24.5 m and a height of 42.3 m, located at south-west side of building are presented. The distribution of factors on the scaffolding has been used to evaluate fitting of the microclimate model. The results of the studies indicate that observed ranges of apparent temperature on the scaffolds frequently results in a worker’s inability to adapt. This leads to reduced concentration and increased fatigue, adversely affects health, and consequently increases the risk of dangerous situations and accidental injuries

Keywords: apparent temperature, health, safety work, scaffoldings

Procedia PDF Downloads 183

Authors: Jiyoung Lee, Andrew D. Gershoff, Jerry Jisang Han

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Most extant research on consumer privacy concerns and their willingness to share personal data has focused on contextual factors (e.g., types of information collected, type of compensation) that lead to consumers’ personal information disclosure. Unfortunately, the literature lacks a clear understanding of how consumers’ incidental psychological needs may influence consumers’ decisions to share their personal information with companies or brands. In this research, we investigate how social exclusion, which is an increasing societal problem, especially since the onset of the COVID-19 pandemic, leads to increased information disclosure intentions for consumers. Specifically, we propose and find that when consumers become socially excluded, their desire for social connection increases, and this desire leads to a greater willingness to disclose their personal information with firms. The motivation to form and maintain interpersonal relationships is one of the most fundamental human needs, and many researchers have found that deprivation of belongingness has negative consequences. Given the negative effects of social exclusion and the universal need to affiliate with others, people respond to exclusion with a motivation for social reconnection, resulting in various cognitive and behavioral consequences, such as paying greater attention to social cues and conforming to others. Here, we propose personal information disclosure as another form of behavior that can satisfy such social connection needs. As self-disclosure can serve as a strategic tool in creating and developing social relationships, those who have been socially excluded and thus have greater social connection desires may be more willing to engage in self-disclosure behavior to satisfy such needs. We conducted four experiments to test how feelings of social exclusion can influence the extent to which consumers share their personal information with brands. Various manipulations and measures were used to demonstrate the robustness of our effects. Through the four studies, we confirmed that (1) consumers who have been socially excluded show greater willingness to share their personal information with brands and that (2) such an effect is driven by the excluded individuals’ desire for social connection. Our findings shed light on how the desire for social connection arising from exclusion influences consumers’ decisions to disclose their personal information to brands. We contribute to the consumer disclosure literature by uncovering a psychological need that influences consumers’ disclosure behavior. We also extend the social exclusion literature by demonstrating that exclusion influences not only consumers’ choice of products but also their decision to disclose personal information to brands.

Keywords: consumer-brand relationship, consumer information disclosure, consumer privacy, social exclusion

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Authors: Lei Zhang, Jean-Michel Ghidaglia, Anela Kumbaro

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This work focuses on numerical simulation of two-phase flows based on the bi-fluid six-equation model widely used in many industrial areas, such as nuclear power plant safety analysis. A pressure-based numerical method is adopted in our studies due to the fact that in two-phase flows, it is common to have a large range of Mach numbers because of the mixture of liquid and gas, and density-based solvers experience stiffness problems as well as a loss of accuracy when approaching the low Mach number limit. This work extends the semi-implicit pressure solver in the nuclear component CUPID code, where the governing equations are solved on unstructured grids with co-located variables to accommodate complicated geometries. A conservative version of the solver is developed in order to capture exactly the shock in one-phase flows, and is extended to two-phase situations. An inter-facial pressure term is added to the bi-fluid model to make the system hyperbolic and to establish a well-posed mathematical problem that will allow us to obtain convergent solutions with refined meshes. The ability of the numerical method to treat phase appearance and disappearance as well as the behavior of the scheme at low Mach numbers will be demonstrated through several numerical results. Finally, inter-facial mass and heat transfer models are included to deal with situations when mass and energy transfer between phases is important, and associated industrial numerical benchmarks with tabulated EOS (equations of state) for fluids are performed.

Keywords: two-phase flows, numerical simulation, bi-fluid model, unstructured grids, phase appearance and disappearance

Procedia PDF Downloads 394

Authors: Luzie Krings, Sven Liebehentze, Maximilian Gehring, Uwe Rüppel

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The integration of renewable energy into the energy grid is essential for decarbonization, and leveraging electrified vehicles (EVs) as mobile storage units offers a pathway to address grid challenges. The decentralized nature of EVs and the intermittency of renewable energy sources, such as photovoltaic (PV) and wind power, complicate grid stability. Vehicle-to-Grid (V2G) technology presents a promising solution, enabling EVs to support grid stability through services like redispatch, congestion mitigation, and enhanced renewable energy utilization. Freight transport, contributing 38% of transport emissions, holds significant potential as its aggregated energy storage capacity can stabilize the grid and optimize renewable energy integration. This study introduces a risk-averse optimization model for marketing EV flexibilities in Germany’s energy markets, with a strong focus on improving grid stability and maximizing renewable energy potential. Using a linear optimization framework, the model incorporates technical, regulatory, and operational constraints to simulate EV fleets as scalable energy storage solutions. The integration of proprietary PV and wind energy systems is also modeled to evaluate benefits. Benchmarks compare bidirectional charging with unidirectional charging under dynamic tariffs. The methodology employs the Python-based energypilot tool to optimize participation in Day-Ahead, Intraday, and Redispatch markets, accounting for trading conditions and temporal offsets. Results demonstrate that redispatch utilization substantially supports grid stability, while bidirectional charging increased renewable energy integration by 15% and economic benefits by 20%. Longer charging cycles offered greater financial returns compared to fragmented cycles, emphasizing the potential of fleets with extended idle periods for storing renewable energy. This research highlights the critical role of EVs in stabilizing the grid and utilizing renewable energy effectively by expanding storage capacity. The optimization framework addresses key challenges in energy trading, offering a transferable methodology for broader energy storage applications. This supports the transition to a sustainable energy system by improving environmental outcomes and economic incentives.

Keywords: Electric Vehicles, Energy Grid, Energy Storages, Redispatch

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Authors: Ghada El-Husseiny, Dina Yousri, Christian Richter

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Social services are often characterized by market failures, which justifies government intervention in the provision of these services. It is widely acknowledged that government intervention breeds corruption since resources are being transferred from one party to another. However, what is still being extensively studied is the magnitude of the negative impact of corruption on publicly provided services and development outcomes. Corruption has the power to hinder development and cripple our march towards the Sustainable Development Goals. Corruption diminishes the efficiency and effectiveness of public health and education spending and directly impacts the outcomes of these sectors. This paper empirically examines the impact of Institutional Failure on public sector services provision, with the sole purpose of studying the impact of corruption on SDG3 and 4; Good health and wellbeing and Quality education, respectively. The paper explores the effect of corruption on these goals from various perspectives and extends the analysis by examining if the impact of corruption on these goals differed when it accounted for the current corruption state. Using Pooled OLS(Ordinary Least Square) and Fixed effects panel estimation on 22 corrupt and 22 clean countries between 2000 and 2017. Results show that corruption in both corrupt and clean countries has a more severe impact on Health than the Education sector. In almost all specifications, corruption has an insignificant effect on School Enrollment rates but a significant effect on Infant Mortality rates. Results further indicate that, on average, a 1 point increase in the CPI(Consumer Price Index) can increase health expenditures by 0.116% in corrupt and clean countries. However, the fixed effects model indicates that the way Health and Education expenditures are determined in clean and corrupt countries are completely country-specific, in which corruption plays a minimal role. Moreover, the findings show that School Enrollment rates and Infant Mortality rates depend, to a large extent, on public spending. The most astounding results-driven is that corrupt countries, on average, have more effective and efficient healthcare expenditures. While some insights are provided as to why these results prevail, they should be further researched. All in all, corruption impedes development outcomes, and any Anti-corrupt policies taken will bring forth immense improvements and speed up the march towards sustainability.

Keywords: corruption, education, health, public spending, sustainable development

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Authors: Sanan Raza, Tariq Abbas, Ahmad Yar Qamar, Muhammad Younus, Hamayun Khan, Mujahid Zafar

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Water Buffaloes contribute significantly in Asian agriculture. The objective of this study was to evaluate the efficacy of two synchronization protocols in enhancing pregnancy rate in 105 mixed parity buffaloes particularly in summer season. Buffaloes are seasonal breeders showing more fertility from October to January in subtropical environment of Pakistan. In current study 105 lactating buffaloes of mixed parity were used having normal estrous cycle, age ranging 5-9 years, weighing between 400-650 kg, BCS 4 ± 0.5 (1-5) and lactation varied from first to 5th. Experimental animals were divided into three groups based on corpus leteummorphometry. Morphometry of C.L was done using rectal population and ultrasonography. All animals were injected 25mg of PGi.m. (Cloprostenol). In Group-1 (n=35) hCG was administered at follicular size of 10mm having scanned after detection of heat. Similarly Group-2 (n=35) received 25 mg EB i.m (Estradiol Benzoate) after confirmation of follicular size of 10mm with ultrasound. Likewise, buffaloes of Group-3 (n=35) were administered normal saline respectively using as control. All buffaloes of three groups were inseminated after 12h of hCG, EB, and normal saline administration respectively. Pregnancy was assessed by ultrasound at 18th and 45th day post insemination. Pregnancy rates at 18th day were 38.2%, 34.5%, and 27.3% for G1, G2, and G3 respectively indicating that hCG and EB administered groups have no difference in results except control group having lower conception rate than both groups respectively. Similarly on 42nd day, these were 40.4%, 32.7% for G1 and G2 which are significantly higher than G3= 26.6 (control Group). Also, hCG and EB treated buffaloes have more probability of pregnancy than control group. Based on the findings of current study, it seems reasonable that the use of hCG and EB has been associated with improving pregnancy rates in non-breeding season of buffaloes.

Keywords: buffalo, hCG, EB, pregnancy rate, follicle, insemination

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Authors: Lorena Polovina, Maddy Kennedy-Parrott, Mohammad Fakoor

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The construction industry accounts for approximately 40% of total GHG emissions worldwide. In order to limit global warming to 1.5 degrees Celsius, ambitious reductions in the carbon intensity of our buildings are crucial. Passive House presents an opportunity to reduce operational carbon by as much as 90% compared to a traditional building through improving thermal insulation, limiting thermal bridging, increasing airtightness and heat recovery. Up until recently, Passive House design was mainly concerned with meeting the energy demands without considering embodied carbon. As buildings become more energy-efficient, embodied carbon becomes more significant. The main objective of this research is to calculate the embodied carbon impact of a Passive House and compare it with the BC Energy Step Code (ESC). British Columbia is committed to increasing the energy efficiency of buildings through the ESC, which is targeting net-zero energy-ready buildings by 2032. However, there is a knowledge gap in the embodied carbon impacts of more energy-efficient buildings, in particular Part 3 construction. In this case study, life cycle assessments (LCA) are performed on Part 3, a multi-unit residential building in Victoria, BC. The actual building is not constructed to the Passive House standard; however, the building envelope and mechanical systems are designed to comply with the Passive house criteria, as well as Steps 1 and 4 of the BC Energy Step Code (ESC) for comparison. OneClick LCA is used to perform the LCA of the case studies. Several strategies are also proposed to minimize the total carbon emissions of the building. The assumption is that there will not be significant differences in embodied carbon between a Passive House and a Step 4 building due to the building envelope.

Keywords: embodied carbon, energy modeling, energy step code, life cycle assessment

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Authors: Ruthanne Tobin

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As our data-driven, cloud-based, knowledge-centric lives become ever more global, mobile, and digital, educational systems everywhere are struggling to keep pace. Schools need to prepare students to become critical-thinking, tech-savvy, life-long learners who are engaged and adaptable enough to find their unique calling in a post-industrial world of work. Recognizing that no nation can afford poor achievement or high dropout rates without jeopardizing its social and economic future, the thirty-two nations of the OECD are launching initiatives to redesign schools, generally under the banner of Personalized Learning or 21st Century Learning. Their intention is to transform education by situating students as co-enquirers and co-contributors with their teachers of what, when, and how learning happens for each individual. In this focused review of the 2007-2017 literature on personalized learning, the author sought answers to two main questions: “What are the theoretical frameworks that guide personalized learning?” and “What is the conceptual understanding of the model?” Ultimately, the review reveals that, although the research area is overly theorized and under-substantiated, it does provide a significant body of knowledge about this potentially transformative educational restructuring. For example, it addresses the following questions: a) What components comprise a PL model? b) How are teachers facilitating agency (voice & choice) in their students? c) What kinds of systems, processes and procedures are being used to guide the innovation? d) How is learning organized, monitored and assessed? e) What role do inquiry based models play? f) How do teachers integrate the three types of knowledge: Content, pedagogical and technological? g) Which kinds of forces enable, and which impede, personalizing learning? h) What is the nature of the collaboration among teachers? i) How do teachers co-regulate differentiated tasks? One finding of the review shows that while technology can dramatically expand access to information, expectations of its impact on teaching and learning are often disappointing unless the technologies are paired with excellent pedagogies in order to address students’ needs, interests and aspirations. This literature review fills a significant gap in this emerging field of research, as it serves to increase conceptual clarity that has hampered both the theorizing and the classroom implementation of a personalized learning model.

Keywords: curriculum change, educational innovation, personalized learning, school reform

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Authors: Rahmat Ali, Inamullah Khan, Amjad Naseer, Abid A. Shah

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Hydronic Heating and Cooling systems in concrete slab based buildings are increasingly becoming a popular substitute to conventional heating and cooling systems. In exploring the materials, techniques employed, and their relative performance measures, a fair bit of uncertainty exists. This research has identified the simplest method of determining the thermal field of a single hydronic pipe when acting as a part of a concrete slab, based on which the spacing and positioning of pipes for a best thermal performance and surface temperature control are determined. The pipe material chosen is the commonly used PEX pipe, which has an all-around performance and thermal characteristics with a thermal conductivity of 0.5W/mK. Concrete Test samples were constructed and their thermal fields tested under varying input conditions. Temperature sensing devices were embedded into the wet concrete at fixed distances from the pipe and other touch sensing temperature devices were employed for determining the extent of the thermal field and validation studies. In the first stage, it was found that the temperature along a specific distance was the same and that heat dissipation occurred in well-defined layers. The temperature obtained in concrete was then related to the different control parameters including water supply temperature. From the results, the temperature of water required for a specific temperature rise in concrete is determined. The thermally effective area is also determined which is then used to calculate the pipe spacing and positioning for the desired level of thermal comfort.

Keywords: thermally activated building systems, concrete slab temperature, thermal field, energy efficiency, thermal comfort, pipe spacing

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Authors: Ronaldo de Lima Cardoso, Thiago V. C. Marcos, Felipe J. da Costa, Antonio C. da Oliveira, Paulo G. P. Toro

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The 14-X is a strategic project of the Brazil Air Force Command to develop a technological demonstrator of a hypersonic air-breathing propulsion system based on supersonic combustion programmed to flight in the Earth's atmosphere at 30 km of altitude and Mach number 10. The 14-X is under development at the Laboratory of Aerothermodynamics and Hypersonic Prof. Henry T. Nagamatsu of the Institute of Advanced Studies. The program began in 2007 and was planned to have three stages: development of the wave rider configuration, development of the scramjet configuration and finally the ground tests in the hypersonic shock tunnel T3. The install configuration of the model based in the scramjet of the 14-X in the test section of the hypersonic shock tunnel was made to proportionate and test the flight conditions in the inlet of the combustion chamber. Experimental studies with hypersonic shock tunnel require special techniques to data acquisition. To measure the pressure along the experimental model geometry tested we used 30 pressure transducers model 122A22 of PCB®. The piezoeletronic crystals of a piezoelectric transducer pressure when to suffer pressure variation produces electric current (PCB® PIEZOTRONIC, 2016). The reading of the signal of the pressure transducers was made by oscilloscope. After the studies had begun we observed that the pressure inside in the combustion chamber was lower than expected. One solution to improve the pressure inside the combustion chamber was install an obstacle to providing high temperature and pressure. To confirm if the combustion occurs was selected the spectroscopy emission technique. The region analyzed for the spectroscopy emission system is the edge of the obstacle installed inside the combustion chamber. The emission spectroscopy technique was used to observe the emission of the OH*, confirming or not the combustion of the mixture between atmospheric air in supersonic speed and the hydrogen fuel inside of the combustion chamber of the model. This paper shows the results of experimental studies of the supersonic combustion induced by shock wave performed at the Hypersonic Shock Tunnel T3 using the scramjet 14-X model. Also, this paper provides important data about the combustion studies using the model based on the engine of 14-X (second stage of the 14-X Program). Informing the possibility of necessaries corrections to be made in the next stages of the program or in other models to experimental study.

Keywords: 14-X, experimental study, ground tests, scramjet, supersonic combustion

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Authors: Srinivasa Reddy Mallampati, Chi-Hyeon Lee, Nguyen Thanh Truc, Byeong-Kyu Lee

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Organic polymeric materials (plastics) are widely used in our daily life and various industrial fields. The separation of waste plastics is important for its feedstock and mechanical recycling. One of the major problems in incineration for thermal recycling or heat melting for material recycling is the polyvinyl chloride (PVC) contained in waste plastics. This is due to the production of hydrogen chloride, chlorine gas, dioxins, and furans originated from PVC. Therefore, the separation of PVC from waste plastics is necessary before recycling. The separation of heavy polymers (PVC 1.42, PMMA 1.12, PC 1.22 and PET 1.27 g/cm3 ) from light ones (PE and PP 0.99 g/cm3) can be achieved on the basis of their density. However it is difficult to separate PVC from other heavy polymers basis of density. There are no simple and inexpensive techniques to separate PVC from others. If hydrophobic the PVC surface is selectively changed into hydrophilic, where other polymers still have hydrophobic surface, flotation process can separate PVC from others. In the present study, the selective surface hydrophilization of polyvinyl chloride (PVC) by microwave treatment after alkaline/acid washing and with activated carbon was studied as the pre-treatment of its separation by the following froth flotation. In presence of activated carbon as absorbent, the microwave treatment could selectively increase the hydrophilicity of the PVC surface (i.e. PVC contact angle decreased about 19o) among other plastics mixture. At this stage, 100% PVC separation from other plastics could be achieved by the combination of the pre- microwave treatment with activated carbon and the following froth floatation. The hydrophilization of PVC by surface analysis would be due to the hydrophilic groups produced by microwave treatment with activated carbon. The effect of optimum condition and detailed mechanism onto separation efficiency in the froth floatation was also investigated.

Keywords: Hydrophilic, PVC, contact angle, additive, microwave, froth floatation, waste plastics

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Authors: Suganya Chandrababu, Dhundy Bastola

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Like in the gut, the subgingival microbiota plays a crucial role in oral hygiene, health, and cariogenic diseases. Human activities like diet, antibiotics, and periodontal treatments alter the bacterial communities, metabolism, and functions in the oral cavity, leading to a dysbiotic state and changes in the plaques of orthodontic patients. Fixed periodontal appliances hinder oral hygiene and cause changes in the dental plaques influencing the subgingival microbiota. However, the microbial species’ diversity and complexity pose a great challenge in understanding the taxa’s community distribution patterns and their role in oral health. In this research, we analyze the subgingival microbial samples from individuals with fixed dental appliances (metal/clear) using an in silico approach. We employ exploratory hypothesis-driven multivariate and regression analysis to shed light on the microbial community and its functional fluctuations due to dental appliances used and identify risks associated with complex disease phenotypes. Our findings confirm the changes in oral microbiota composition due to the presence and type of fixed orthodontal devices. We identified seven main periodontic pathogens, including Bacteroidetes, Actinobacteria, Proteobacteria, Fusobacteria, and Firmicutes, whose abundances were significantly altered due to the presence and type of fixed appliances used. In the case of metal braces, the abundances of Bacteroidetes, Proteobacteria, Fusobacteria, Candidatus saccharibacteria, and Spirochaetes significantly increased, while the abundance of Firmicutes and Actinobacteria decreased. However, in individuals With clear braces, the abundance of Bacteroidetes and Candidatus saccharibacteria increased. The highest abundance value (P-value=0.004 < 0.05) was observed with Bacteroidetes in individuals with the metal appliance, which is associated with gingivitis, periodontitis, endodontic infections, and odontogenic abscesses. Overall, the bacterial abundances decrease with clear type and increase with metal type of braces. Regression analysis further validated the multivariate analysis of variance (MANOVA) results, supporting the hypothesis that the presence and type of the fixed oral appliances significantly alter the bacterial abundance and composition.

Keywords: oral microbiota, statistical analysis, fixed or-thodontal appliances, bacterial abundance, multivariate analysis, regression analysis

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Authors: Esther Pearl Palmer

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Driven by the increased pressure on Higher Education Institutions (HEIs) to produce work-ready graduates for the modern world of work, this study reflects on triad teaching and learning practices to increase student engagement and employability. In the South African higher education context, the employability of graduates is imperative in strengthening the country’s economy and in increasing competitiveness. Within this context, the field of Human Resource Management (HRM) calls for innovative methods and approaches to teaching and learning and assessing the skills and competencies of graduates to render them employable. Digital competency in Human Resource Information Systems (HRIS) is an important component and prerequisite for employment in HRM. The purpose of this research is to reflect on the subject HRIS developed by lecturers at the Central University of Technology, Free State (CUT), with the intention to actively engage students in real-world learning activities and increase their employability. The Enrichment Triad Model (ETM) was used as theoretical framework to develop the subject as it supports a triad teaching and learning approach to education. It is, furthermore, an inter-structured model that supports collaboration between industry, academics and students. The study follows a mixed-method approach to reflect on the learning experiences of the industry, academics and students in the subject field over the past three years. This paper is a work in progress and seeks to broaden the scope of extant studies about student engagement in work-related learning to increase employability. Based on the ETM as theoretical framework and pedagogical practice, this paper proposes that following a triad teaching and learning approach will increase work-related skills of students. Findings from the study show that students, academics and industry alike regard educational opportunities that incorporate active learning experiences with the world of work enhances student engagement in learning and renders them more employable.

Keywords: digital competence, enriched triad model, human resource information systems, student engagement, triad pedagogy.

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Authors: Rubina Jahan, Mohammad Zayeed Bin Alam, Sazzad Chowdhury, Sadia Chowdhury

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Access to mental health services in Bangladesh is a tale of urban privilege and rural struggle. Mental health services in the country are primarily centered in urban medical hospitals, with only 260 psychiatrists for a population of more than 162 million, while rural populations face far more severe and daunting challenges. In alignment with the World Health Organization's perspective on mental health as a basic human right and a crucial component for personal, community, and socioeconomic development; SAJIDA Foundation a value driven non-government organization in Bangladesh has introduced a Community Based Mental Health (CMHI) program to fill critical gaps in mental health care, providing accessible and affordable community-based services to protect and promote mental health, offering support for those grappling with mental health conditions. The CMHI programme is being implemented in 3 districts in Bangladesh, 2 of them are remote and most climate vulnerable areas targeting total 6,797 individual. The intervention plan involves a screening of all participants using a 10-point vulnerability assessment tool to identify vulnerable individuals. The assumption underlying this is that individuals assessed as vulnerable is primarily due to biological, psychological, social and economic factors and they are at an increased risk of developing common mental health issues. Those identified as vulnerable with high risk and emergency conditions will receive Mental Health First Aid (MHFA) and undergo further screening with GHQ-12 to be identified as cases and non-cases. The identified cases are then referred to community lay counsellors with basic training and knowledge in providing 4-6 sessions on problem solving or behavior activation. In situations where no improvement occurs post lay counselling or for individuals with severe mental health conditions, a referral process will be initiated, directing individuals to ensure appropriate mental health care. In our presentation, it will present the findings from 6-month pilot implementation focusing on the community-based screening versus outcome of the lay counseling session and barriers and facilitators of implementing community based mental health care in a resource constraint country like Bangladesh.

Keywords: community-based mental health, lay counseling, rural bangladesh, treatment gap

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Authors: Rofaida Ashour

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This study discusses the implementation of quality improvement initiatives aimed at reducing contamination rates in cultured karyotyping samples. The primary objective was to enhance patient outcomes through systematic audits and targeted staff engagement. Recognizing the critical impact of sample integrity on diagnostic accuracy, a thorough analysis was conducted to identify the root causes of contamination. The project involved two audit cycles, which facilitated a comprehensive assessment of adherence to local protocols. Key issues identified included lapses in the use of personal protective equipment (PPE) and inadequate awareness of proper sample handling procedures among staff. To address these challenges, a multi-faceted approach was adopted. Firstly, a presentation was delivered to the laboratory team emphasizing the significance of strict adherence to PPE guidelines during the collection and handling of samples. This session aimed to raise awareness and foster a culture of safety within the unit. Additionally, informative posters illustrating the correct procedures were strategically placed around the laboratory to serve as ongoing visual reminders for staff. Recognizing the heightened risk associated with patients exhibiting fever or signs of infection, special measures were introduced to manage their sample collection. These proactive strategies were designed to minimize the likelihood of introducing contaminated samples into the culture process. The results of the audits demonstrated a significant reduction in contamination rates, underscoring the effectiveness of the interventions. This experience reinforced the importance of continuous quality improvement in healthcare settings, particularly in ensuring the delivery of high-quality, safe, and efficient services. Conducting regular audits not only provided valuable insights into operational practices but also highlighted the critical role of active team engagement and a data-driven approach in decision-making. Effective communication and collaboration among team members emerged as essential components for the success of quality improvement initiatives.

Keywords: quality improvement, contamination rates, karyotyping samples, healthcare protocols, staff engagement

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Authors: John E. Foley, Martin Miele, Raul Fonda, Jon Jacobson

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This paper presents development and implementation of new and innovative data collection and analysis methodologies based on deployment of total field magnetometer arrays. Our research has focused on the development of a vertically-integrated suite of platforms all utilizing common data acquisition, data processing and analysis tools. These survey platforms include low-altitude helicopters and ground-based vehicles, including robots, for terrestrial mapping applications. For marine settings the sensor arrays are deployed from either a hydrodynamic bottom-following wing towed from a surface vessel or from a towed floating platform for shallow-water settings. Additionally, sensor arrays are deployed from tethered remotely operated vehicles (ROVs) for underwater settings where high maneuverability is required. While the primary application of these systems is the detection and mapping of unexploded ordnance (UXO), these system are also used for various infrastructure mapping and geologic investigations. For each application, success is driven by the integration of magnetometer arrays, accurate geo-positioning, system noise mitigation, and stable deployment of the system in appropriate proximity of expected targets or features. Each of the systems collects geo-registered data compatible with a web-enabled data management system providing immediate access of data and meta-data for remote processing, analysis and delivery of results. This approach allows highly sophisticated magnetic processing methods, including classification based on dipole modeling and remanent magnetization, to be efficiently applied to many projects. This paper also briefly describes the initial development of magnetometer-based detection systems deployed from low-altitude helicopter platforms and the subsequent successful transition of this technology to the marine environment. Additionally, we present examples from a range of terrestrial and marine settings as well as ongoing research efforts related to sensor miniaturization for unmanned aerial vehicle (UAV) magnetic field mapping applications.

Keywords: dipole modeling, magnetometer mapping systems, sub-surface infrastructure mapping, unexploded ordnance detection

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Authors: Yaling Gou, Sucai Yang, Pengwei Qiao

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Integrated chemical-biological treatment is an attractive alternative to remove polycyclic aromatic hydrocarbons (PAHs) from contaminated soil; wherein indigenous bacteria is the key factor for the biodegradation of residual PAHs concentrations after the application of chemical oxidation. However, the systematical study on the impact of persulfate (PS) oxidation on indigenous bacteria as well as PAHs removal is still scarce. In this study, the influences of different PS dosages (1%, 3%, 6%, and 10% [w/w]), as well as various activation methods (native iron, H2O2, alkaline, ferrous iron, and heat) on PAHs removal and indigenous bacteria in highly contaminated aged soil were investigated. Apparent degradation of PAHs in the soil treated with PS oxidation was observed, and the removal efficiency of total PAHs in the soil ranged from 38.28% to 79.97%. The removal efficiency of total PAHs in the soil increased with increasing consumption of PS. However, the bacterial abundance in soil was negatively affected following oxidation for all of the treatments added with PS, with bacterial abundance in the soil decreased by 0.89~2.88 orders of magnitude compared to the untreated soil. Moreover, the number of total bacteria in the soil decreased as PS consumption increased. Different PS activation methods and PS dosages exhibited different influences on the bacterial community composition. Bacteria capable of degrading PAHs under anoxic conditions were composed predominantly by Proteobacteria and Firmicutes. The total amount of Proteobacteria and Firmicutes also decreased with increasing consumption of PS. The results of this study provide important insight into the design of PAHs contaminated soil remediation projects.

Keywords: activation method, chemical oxidation, indigenous bacteria, polycyclic aromatic hydrocarbon

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Authors: Nikolai N. Bogolubov, Andrey V. Soldatov

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Terahertz radiation occupies a range of frequencies somewhere from 100 GHz to approximately 10 THz, just between microwaves and infrared waves. This range of frequencies holds promise for many useful applications in experimental applied physics and technology. At the same time, reliable, simple techniques for generation, amplification, and modulation of electromagnetic radiation in this range are far from been developed enough to meet the requirements of its practical usage, especially in comparison to the level of technological abilities already achieved for other domains of the electromagnetic spectrum. This situation of relative underdevelopment of this potentially very important range of electromagnetic spectrum is known under the name of the 'terahertz gap.' Among other things, technological progress in the terahertz area has been impeded by the lack of compact, low energy consumption, easily controlled and continuously radiating terahertz radiation sources. Therefore, development of new techniques serving this purpose as well as various devices based on them is of obvious necessity. No doubt, it would be highly advantageous to employ the simplest of suitable physical systems as major critical components in these techniques and devices. The purpose of the present research was to show by means of conventional methods of non-equilibrium statistical mechanics and the theory of open quantum systems, that a thoroughly studied two-level quantum system, also known as an one-electron two-level 'atom', being driven by external classical monochromatic high-frequency (e.g. laser) field, can radiate continuously at much lower (e.g. terahertz) frequency in the fluorescent regime if the transition dipole moment operator of this 'atom' possesses permanent non-equal diagonal matrix elements. This assumption contradicts conventional assumption routinely made in quantum optics that only the non-diagonal matrix elements persist. The conventional assumption is pertinent to natural atoms and molecules and stems from the property of spatial inversion symmetry of their eigenstates. At the same time, such an assumption is justified no more in regard to artificially manufactured quantum systems of reduced dimensionality, such as, for example, quantum dots, which are often nicknamed 'artificial atoms' due to striking similarity of their optical properties to those ones of the real atoms. Possible ways to experimental observation and practical implementation of the predicted effect are discussed too.

Keywords: terahertz gap, two-level atom, resonant fluorescence, quantum dot, resonant fluorescence, two-level atom

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Authors: Vanessa Kummer, Maik Meusel

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Real estate demand estimates are typically derived from transaction data. However, in regions with excess demand, transactions are driven by supply and therefore do not indicate what people are actually looking for. To estimate the demand for housing in Switzerland, search subscriptions from all important Swiss real estate platforms are used. These data do, however, suffer from missing information—for example, many users do not specify how many rooms they would like or what price they would be willing to pay. In economic analyses, it is often the case that only complete data is used. Usually, however, the proportion of complete data is rather small which leads to most information being neglected. Also, the data might have a strong distortion if it is complete. In addition, the reason that data is missing might itself also contain information, which is however ignored with that approach. An interesting issue is, therefore, if for economic analyses such as the one at hand, there is an added value by using the whole data set with the imputed missing values compared to using the usually small percentage of complete data (baseline). Also, it is interesting to see how different algorithms affect that result. The imputation of the missing data is done using unsupervised learning. Out of the numerous unsupervised learning approaches, the most common ones, such as clustering, principal component analysis, or neural networks techniques are applied. By training the model iteratively on the imputed data and, thereby, including the information of all data into the model, the distortion of the first training set—the complete data—vanishes. In a next step, the performances of the algorithms are measured. This is done by randomly creating missing values in subsets of the data, estimating those values with the relevant algorithms and several parameter combinations, and comparing the estimates to the actual data. After having found the optimal parameter set for each algorithm, the missing values are being imputed. Using the resulting data sets, the next step is to estimate the willingness to pay for real estate. This is done by fitting price distributions for real estate properties with certain characteristics, such as the region or the number of rooms. Based on these distributions, survival functions are computed to obtain the functional relationship between characteristics and selling probabilities. Comparing the survival functions shows that estimates which are based on imputed data sets do not differ significantly from each other; however, the demand estimate that is derived from the baseline data does. This indicates that the baseline data set does not include all available information and is therefore not representative for the entire sample. Also, demand estimates derived from the whole data set are much more accurate than the baseline estimation. Thus, in order to obtain optimal results, it is important to make use of all available data, even though it involves additional procedures such as data imputation.

Keywords: demand estimate, missing-data imputation, real estate, unsupervised learning

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Authors: Fang Liu, JiaJia Yao, GuanLin Wu, ZuMaoLi, XueYan Yang, HePeng Zhang, ZhiPeng Sun, JunShuai Xue

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The explosive increasing needs of data processing and information storage strongly drive the advancement of the binary logic system to multiple-valued logic system. Inherent negative differential resistance characteristic, ultra-high-speed switching time, and robust anti-irradiation capability make III-nitride resonant tunneling diode one of the most promising candidates for multi-valued logic devices. Here we report the monolithic integration of GaN resonant tunneling diodes in series to realize multiple negative differential resistance regions, obtaining at least three stable operating states. A multiply-by-three circuit is achieved by this combination, increasing the frequency of the input triangular wave from f0 to 3f0. The resonant tunneling diodes are grown by plasma-assistedmolecular beam epitaxy on free-standing c-plane GaN substrates, comprising double barriers and a single quantum well both at the atomic level. Device with a peak current density of 183kA/cm² in conjunction with a peak-to-valley current ratio (PVCR) of 2.07 is observed, which is the best result reported in nitride-based resonant tunneling diodes. Microwave oscillation event at room temperature was discovered with a fundamental frequency of 0.31GHz and an output power of 5.37μW, verifying the high repeatability and robustness of our device. The switching behavior measurement was successfully carried out, featuring rise and fall times in the order of picoseconds, which can be used in high-speed digital circuits. Limited by the measuring equipment and the layer structure, the switching time can be further improved. In general, this article presents a novel nitride device with multiple negative differential regions driven by the resonant tunneling mechanism, which can be used in high-speed multiple value logic field with reduced circuit complexity, demonstrating a new solution of nitride devices to break through the limitations of binary logic.

Keywords: GaN resonant tunneling diode, negative differential resistance, multiple-valued logic system, switching time, peak-to-valley current ratio

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Authors: Catherine Joke Adeseko

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Enzymatic browning is an economically important disorder that degrades organoleptic properties and prevent the consumer from purchasing fresh fruit and vegetables. Prevention and control of enzymatic browning in fruit and its product is imperative. Therefore, this study sought to investigate the catalytic effect of polyphenol oxidase (PPO) in the adverse browning of African bush mango (Irvingia gabonensis) fruit peel and pulp. PPO was isolated and purified, and its physicochemical properties, such as the effect of pH with SDS, temperature, and thermodynamic studies, which invariably led to thermal inactivation of purified PPO at 80 °C, were evaluated. The pH and temperature optima of PPO were found at 7.0 and 50, respectively. There was a gradual increase in the activity of PPO as the pH increases. However, the enzyme exhibited a higher activity at neutral pH 7.0, while enzymatic inhibition was observed at acidic region, pH 2.0. The presence of SDS at pH 5.0 downward was found to inhibit the activity of PPO from the peel and pulp of I. gabonensis. The average value of enthalpy (ΔH), entropy (ΔS), and Gibbs free energy (ΔG) obtained at 20 min of incubation and temperature 30 – 80 °C were respectively 39.93 kJ.mol-1, 431.57 J.mol-1 .K-1 and -107.99 kJ.mol-1 for peel PPO, and 37.92 kJ.mol-1, -442.51J.mol-1.K-1, and -107.22 kJ.mol-1 for pulp PPO. Thermal inactivation of PPO from I. gabonensis exhibited a reduction in catalytic activity as the temperature and duration of heat inactivation increases using catechol, reflected by an increment in k value. The half-life of PPO (t1/2) decreases as the incubation temperature increases due to the instability of the enzyme at high temperatures and was higher in pulp than peel. Both D and Z values decrease with increase in temperature. The information from this study suggests processing parameters for controlling PPO in the potential industrial application of I. gabonensis fruit in order to prolong the shelf-life of this fruit for maximum utilization.

Keywords: enzymatic, browning, characterization, activity

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Authors: S. Jigna, K. Nanda Kumar, T. Anna

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Being a major contributor to the Indian economy and a critical facilitator for the country’s digital India vision, the Indian telecommunications industry is also a major source of employment for the country. Since the last few years, the Indian telecommunication service providers (TSPs), however, are facing business challenges related to increasing competition, losses, debts, and decreasing revenue. The strategic use of digital technologies for a successful digital transformation has the potential to equip organizations to meet these business challenges. Despite an increased focus on digital transformation, the telecom service providers globally, including Indian TSPs, have seen limited success so far. The purpose of this research was thus to identify the factors that are critical for the digital transformation and to what extent they influence the successful digital transformation of the Indian TSPs. The literature review of more than 300 digital transformation-related articles, mostly from 2013-2019, demonstrated a lack of an empirical model consisting of factors for the successful digital transformation of the TSPs. This study theorizes a research framework grounded in multiple theories, and a research model consisting of 7 constructs that may be influencing business success during the digital transformation of the organization was proposed. The questionnaire survey of senior managers in the Indian telecommunications industry was seeking to validate the research model. Based on 294 survey responses, the validation of the Structural equation model using the statistical tool ADANCO 2.1.1 was found to be robust. Results indicate that Digital Capabilities, Digital Strategy, and Corporate Level Data Strategy in that order has a strong influence on the successful Business Performance, followed by IT Function Transformation, Digital Innovation, and Transformation Management respectively. Even though Digital Organization did not have a direct significance on Business Performance outcomes, it had a strong influence on IT Function Transformation, thus affecting the Business Performance outcomes indirectly. Amongst numerous practical and theoretical contributions of the study, the main contribution for the Indian TSPs is a validated reference for prioritizing the transformation initiatives in their strategic roadmap. Also, the main contribution to the theory is the possibility to use the research framework artifact of the present research for quantitative validation in different industries and geographies.

Keywords: corporate level data strategy, digital capabilities, digital innovation, digital strategy

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Authors: T. A. Rosy, M. R. I. Talukdar, N. S. Juyena, F. Y. Bari, M. N. Islam

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The ovarian follicular dynamics, vaginal electrical resistance (VER) and progesterone (P4) and estrogen (E2) profiles were investigated during estrus cycle in four indigenous ewes. Daily VER values were recorded with heat detector. The follicles were observed and measured by trans-rectal ultrasonography. Blood was collected daily for hormonal profiles. Results showed a significant variation in VER values (P<0.05) at estrus in regards to ewes and cycles. The day difference between two successive lower values in VER waves ranged from 13-17 days which might indicate the estrus cycle in indigenous ewes. Trans-rectal ultrasonography of ovaries revealed the presence of two to four waves of follicular growth during the study period. Results also showed that follicular diameter was negatively correlated with VER values. Study of hormonal profiles by ELISA revealed a positive correlation between E2 concentration and development of follicle and negative correlation between P4 concentration and development of follicle. The concentrations of estradiol increased at the time of estrus and then fall down in a basal level. Development of follicular size was accompanied by an increase in the concentration of serum estradiol. Inversely, when follicles heed to ovulation concentration of progesterone starts to fall down and after ovulation it turns its way to the zenith and remains at this state until next ovulatory follicle comes to its maximum diameter. This study could help scientists to set up a manipulative reproductive technique for improving genetic values of sheep in Bangladesh.

Keywords: ovarian follicle, hormonal profile, sheep, ultrasonography, vaginal electrical resistance

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Authors: Jonathan Gong

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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deep learning, image processing, machine learning

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Authors: Rafał Kamiński, Joel Rech, Philippe Bertrand, Christophe Desrayaud

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Additive manufacturing is a hot topic for industry. Among the additive techniques, Selective Laser Melting (SLM) becomes even more popular, especially for making parts for aerospace applications, thanks to its design freedom (customized and light structures) and its reduced time to market. However, some functional surfaces have to be machined to achieve small tolerances and low surface roughness to fulfill industry specifications. The complex shapes designed for SLM (ex: titanium turbine blades) necessitate the use of ball end milling operations like in the conventional process after forging. However, the metallurgical state of TA6V is very different from the one obtained usually from forging, because of the laser sintering layer by layer. So this paper aims to investigate the influence of new TA6V metallurgies produced by SLM on the machinability in ball end milling. Machinability is considered as the property of a material to obtain easily and by a cheap way a functional surface. This means, for instance, the property to limit cutting tool wear rate and to get smooth surfaces. So as to reach this objective, SLM parts have been produced and heat treated with various conditions leading to various metallurgies that are compared with a standard equiaxed α+β wrought microstructure. The machinability is analyzed by measuring surface roughness, tool wear and cutting forces for a range of cutting conditions (depth of cut 'ap', feed per tooth 'fz', spindle speed 'N') in accordance with industrial practices. This work has revealed that TA6V produced by SLM can lead to a better machinability that standard wrought alloys.

Keywords: ball milling, selective laser melting, surface roughness, titanium, wear

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Authors: Ekere E. Kokonne, Isimi C. Yetunde, Okoh E. Judith, Okafor E. Ijeoma, Ajeh J. Isaac, Olobayo O. Kunle, Emeje O. Martins

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NIPRIMAL® is a mono herbal formulation of Nauclea latifolia used in the treatment of malaria. The stability of extracts made from plant material is essential to ensure the quality, safety and efficacy of the finished product. This study assessed the stability of the formulation under three different storage conditions; normal room temperature, infrared and under refrigeration. Differential Scanning Calorimetry (DSC) and Thin Layer Chromatography (TLC) were used to monitor the formulations. The DSC analysis was done from 0oC to 350oC under the three storage conditions. Results obtained indicate that NIPRIMAL® was stable at all the storage conditions investigated. Thin layer chromatography (TLC) after 6 months showed there was no significant difference between retention factor (RF) values for the various storage conditions. The reference sample had four spots with RF values of 0.47, 0.68, 0.76, 0.82 respectively and these spots were retained in the test formulations with corresponding RF values were after 6 months at room temperature and refrigerated temperature been 0.56, 0.73, 0.80, 0.92 and 0.47, 0.68, 0.76, 0.82 respectively. On the other hand, the RF values (0.55, 0.74, 0.77, 0.93) obtained under infrared after 1 month varied slightly from the reference. The sample exposed to infrared had a lower heat capacity compared to that stored under room temperature or refrigeration. A combination of TLC and DSC measurements has been applied for assessing the stability of NIPRIMAL®. Both methods were found to be rapid, sensitive and reliable in determining its stability. It is concluded that NIPRIMAL® can be stored under any of the tested conditions without degradation. This study is a major contribution towards developing appropriate stability monitoring parameters for herbal products.

Keywords: differential scanning calorimetry, formulation, NIPRIMAL®, stability, thin layer hromatography

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Authors: Sudha T., Naveen C.

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Dengue is a serious public health issue that causes significant annual economic and welfare burdens on nations. However, enhanced optimization techniques and quantitative modeling approaches can predict the incidence of dengue. By advocating for a data-driven approach, public health officials can make informed decisions, thereby improving the overall effectiveness of sudden disease outbreak control efforts. The National Oceanic and Atmospheric Administration and the Centers for Disease Control and Prevention are two of the U.S. Federal Government agencies from which this study uses environmental data. Based on environmental data that describe changes in temperature, precipitation, vegetation, and other factors known to affect dengue incidence, many predictive models are constructed that use different machine learning methods to estimate weekly dengue cases. The first step involves preparing the data, which includes handling outliers and missing values to make sure the data is prepared for subsequent processing and the creation of an accurate forecasting model. In the second phase, multiple feature selection procedures are applied using various machine learning models and optimization techniques. During the third phase of the research, machine learning models like the Huber Regressor, Support Vector Machine, Gradient Boosting Regressor (GBR), and Support Vector Regressor (SVR) are compared with several optimization techniques for feature selection, such as Harmony Search and Genetic Algorithm. In the fourth stage, the model's performance is evaluated using Mean Square Error (MSE), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) as assistance. Selecting an optimization strategy with the least number of errors, lowest price, biggest productivity, or maximum potential results is the goal. In a variety of industries, including engineering, science, management, mathematics, finance, and medicine, optimization is widely employed. An effective optimization method based on harmony search and an integrated genetic algorithm is introduced for input feature selection, and it shows an important improvement in the model's predictive accuracy. The predictive models with Huber Regressor as the foundation perform the best for optimization and also prediction.

Keywords: deep learning model, dengue fever, prediction, optimization

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Authors: Hugh Battye

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In recent years, Muslim identity in China has strengthened against the backdrop of a worldwide Islamic revival. One discussion arising from this has been focused around the Hui, an ethnicity created by the Communist government in the 1950s covering the Chinese speaking 'Sino-Muslims' as opposed to those with their own language. While the term Hui in Chinese has traditionally meant 'Muslim', the strengthening of Hui identity in recent decades has led to a debate among scholars as to whether this identity is primarily ethnically or religiously driven. This article looks at the case of a mixed ethnic community in rural Gansu Province, Central Northwest China, which not only contains the official Hui ethnicity but also members of the smaller Muslim Salar and Bonan minority groups. In analyzing the close interaction between these groups, the paper will argue that, despite government attempts to promote the Hui as an ethnicity within its modern ethnic paradigm, in rural Gansu and the general region, Hui is still essentially seen as a religious identity. Having provided an overview of the historical evolution of the Hui ethnonym in China and presented the views of some of the important scholars involved in the discussion, the paper will then offer its findings based on participant observation and survey work in Gansu. The results will show that, firstly, for the local Muslims, religious identity clearly dominates ethnic identity. On the ground, the term Hui continues to be used as a catch-all term for Muslims, whether they belong to the official 'Hui' nationality or not, and against this backdrop, the ethnic importance of being 'Hui', 'Bonan' or 'Salar' within the Muslim community itself is by contrast minimal. Secondly, however, this local Muslim solidarity is not at present pointing towards some kind of national pan-ethnic Islamic movement that could potentially set itself up in opposition to the Chinese government; rather it is better seen as part of an ongoing negotiation by local Muslims with the state in the context of its ascribed ethnic categories. The findings of this study in a region where many of the Muslims are more conservative in their beliefs is not necessarily replicated in other contexts, such as in urban areas and in eastern and southern China, and hence reification of the term Hui as one idea extending all across China should be avoided, whether in terms of a united religious 'ummah' or of a real or imagined 'ethnic group.' Rather, this localized case study seeks to demonstrate ways in which Muslims of rural Central Northwest China are 'being Hui,' as a contribution to the broader discussion on what it means to be Muslim and Chinese in the reform era.

Keywords: China, ethnicity, Hui, identity, Muslims

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Authors: A. B. Chehreh, M. Grätzel, M. Klein, J. P. Bergmann, F. Walther

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Friction stir welding (FSW) is an advantageous method in the thermal joining processes, featuring the welding of various dissimilar and similar material combinations, joining temperatures below the melting point which prevents irregularities such as pores and hot cracks as well as high strengths mechanical joints near the base material. The FSW process consists of a rotating tool which is made of a shoulder and a probe. The welding process is based on a rotating tool which plunges in the workpiece under axial pressure. As a result, the material is plasticized by frictional heat which leads to a decrease in the flow stress. During the welding procedure, the material is continuously displaced by the tool, creating a firmly bonded weld seam behind the tool. However, the mechanical properties of the weld seam are affected by the design and geometry of the tool. These include in particular microstructural and surface properties which can favor crack initiation. Following investigation compares the dynamic properties of FSW weld seams with conventional and stationary shoulder geometry based on load increase test (LIT). Compared to classical Woehler tests, it is possible to determine the fatigue strength of the specimens after a short amount of time. The investigations were carried out on a robotized welding setup on 2 mm thick EN AW 5754 aluminum alloy sheets. It was shown that an increased tensile and fatigue strength can be achieved by using the stationary shoulder concept. Furthermore, it could be demonstrated that the LIT is a valid method to describe the fatigue behavior of FSW weld seams.

Keywords: aluminum alloy, fatigue performance, fracture, friction stir welding

Procedia PDF Downloads 153

Authors: Mandy Wilson, Emma Vieira, Jocelyn Jones, Alice V. Brown, Lindey Andrews, Louise Southalan, Jackie Oakley, Dorothy Bagshaw, Patrick Egan, Laura Dent, Duc Dau, Lucy Spanswick

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Alcohol and drug dependency are pertinent issues for those experiencing homelessness. This includes Aboriginal and Torres Strait Islander people, Australia’s traditional owners, living in Perth, Western Australia (WA). Societal narratives around the drivers behind drug and alcohol dependency in Aboriginal communities, particularly those experiencing homelessness, have been biased and unchanging, with little regard for complexity. This can include the idea that Aboriginal people have ‘chosen’ to use alcohol or other drugs without consideration for intergenerational trauma and the trauma of homelessness that may influence their choices. These narratives have flow-on impacts on policies and services that directly impact Aboriginal people experiencing homelessness. In 2021, we commenced a project which aimed to listen to and elevate the voices of 70-90 Aboriginal people experiencing homelessness in Perth. The project is community-driven, led by an Aboriginal Community Controlled Organisation in partnership with a university research institute. A community-ownership group of Aboriginal Elders endorsed the project’s methods, chosen to ensure their suitability for the Aboriginal community. In this paper, we detail these methods, including semi-structured interviews influenced by an Aboriginal yarning approach – an important style of conversation for Aboriginal people which follows cultural protocols; and photovoice – supporting people to share their stories through photography. Through these engagements, we detail the reasons Aboriginal people in Perth shared for using alcohol or other drugs while experiencing homelessness. These included supporting their survival on the streets, managing their mental health, and coping while on the journey to finding support. We also detail why they sought to discontinue alcohol and other drug use, including wanting to reconnect with family and changing priorities. Finally, we share how Aboriginal people experiencing homelessness have said they are impacted by their family’s alcohol and other drug use, including feeling uncomfortable living with a family who is drug and alcohol-dependent and having to care for grandchildren despite their own homelessness. These findings provide a richer understanding of alcohol and drug use for Aboriginal people experiencing homelessness in Perth, shedding light on potential changes to targeted policy and service approaches.

Keywords: Aboriginal and Torres Strait Islander peoples, alcohol and other drugs, homelessness, community-led research

Procedia PDF Downloads 135