Search results for: process safety management (PSM)

Authors: N. Singh, G. K. Darbha

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Since the last decade, a wave of research has begun to study the prevalence and impact of ever-increasing plastic pollution in the environment. The wide application and ubiquitous distribution of plastic have become a global concern due to its persistent nature. The disposal of plastics has emerged as one of the major challenges for waste management landfills. Microplastics (MPs) have found its existence in almost every environment, from the high altitude mountain lake to the deep sea sediments, polar icebergs, coral reefs, estuaries, beaches, and river, etc. Microplastics are fragments of plastics with size less than 5 mm. Microplastics can be classified as primary microplastics and secondary microplastics. Primary microplastics includes purposefully introduced microplastics into the end products for consumers (microbeads used in facial cleansers, personal care product, etc.), pellets (used in manufacturing industries) or fibres (from textile industries) which finally enters into the environment. Secondary microplastics are formed by disintegration of larger fragments under the exposure of sunlight, mechanical abrasive forces by rain, waves, wind and/or water. A number of factors affect the quantity of microplastic present in freshwater environments. In addition to physical forces, human population density proximal to the water body, proximity to urban centres, water residence time, and size of the water body also affects plastic properties. With time, other complex processes in nature such as physical, chemical and biological break down plastics by interfering with its structural integrity. Several studies demonstrate that microplastics found in wastewater sludge being used as manure for agricultural fields, thus having the tendency to alter the soil environment condition influencing the microbial population as well. Inadequate data are available on the fate and transport of microplastics under varying environmental conditions that are required to supplement important information for further research. In addition, microplastics have the tendency to absorb heavy metals and hydrophobic organic contaminants such as PAHs and PCBs from its surroundings and thus acting as carriers for these contaminants in the environment system. In this study, three kinds of microplastics (polyethylene, polypropylene and expanded polystyrene) of different densities were chosen. Plastic samples were placed in sand with different aqueous media (distilled water, surface water, groundwater and marine water). It was incubated at varying temperatures (25, 35 and 40 °C) and agitation levels (rpm). The results show that the number of plastic fragments enhanced with increase in temperature and agitation speed. Moreover, the rate of disintegration of expanded polystyrene is high compared to other plastics. These results demonstrate that temperature, salinity, and mechanical abrasion plays a major role in degradation of plastics. Since weathered microplastics are more harmful as compared to the virgin microplastics, long-term studies involving other environmental factors are needed to have a better understanding of degradation of plastics.

Keywords: environmental contamination, fragmentation, microplastics, temperature, weathering

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Authors: Rajkumar Ghosh, Bhabani Prasad Mukhopadhay

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Groundwater contamination with fluoride has emerged as a global concern affecting millions of people, leading to the widespread occurrence of fluorosis. It affects bones and teeth, leading to dental and skeletal fluorosis. This study presents a comprehensive analysis of the relationship between groundwater contamination and fluorosis. It delves into the causes of fluoride contamination in groundwater, its spatial distribution, and adverse health impacts of fluorosis on affected communities. Fluoride contamination in groundwater can be attributed to both natural and anthropogenic sources. Geogenic sources involve the dissolution of fluoride-rich minerals present in the aquifer materials. On the other hand, anthropogenic activities such as industrial discharges, agricultural practices, and improper disposal of fluoride-containing waste contribute to the contamination of groundwater. The spatial distribution of fluoride contamination varies widely across different regions and geological formations. High fluoride levels are commonly observed in areas with fluorine-rich geological deposits. Additionally, agricultural and industrial centres often exhibit elevated fluoride concentrations due to anthropogenic contributions. Excessive fluoride ingestion during tooth development leads to dental fluorosis, characterized by enamel defects, discoloration, and dental caries. The severity of dental fluorosis varies based on fluoride exposure levels during tooth development. Long-term consumption of fluoride-contaminated water causes skeletal fluorosis, resulting in bone and joint pain, decreased joint mobility, and skeletal deformities. In severe cases, skeletal fluorosis can lead to disability and reduced quality of life. Various defluoridation techniques such as activated alumina, bone char, and reverse osmosis have been employed to reduce fluoride concentrations in drinking water. These methods effectively remove fluoride, but their implementation requires careful consideration of cost, maintenance, and sustainability. Diversifying water sources, such as rainwater harvesting and surface water supply, can reduce the reliance on fluoride-contaminated groundwater, especially in regions with high fluoride concentrations. Groundwater contamination with fluoride remains a significant public health challenge, leading to the widespread occurrence of fluorosis globally. This scientific report emphasizes the importance of understanding the relationship between groundwater contamination and fluorosis. Implementing effective mitigation strategies and preventive measures is crucial to combat fluorosis and ensure sustainable access to safe drinking water for communities worldwide. Collaborative efforts between government agencies, local communities, and scientific researchers are essential to address this issue and safeguard the health of vulnerable populations. Additionally, the report explores various mitigation strategies and preventive measures to address the issue and offers recommendations for sustainable management of groundwater resources to combat fluorosis effectively.

Keywords: fluorosis, fluoride contamination, groundwater contamination, groundwater resources

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Authors: Xingyu Gao, Qiang Wu, Yuanyuan Liu, Yue Yang

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In the era of the knowledge economy, the relationship between scientific knowledge and patents has garnered significant attention. Understanding the intricate interplay between the foundations of science and technological innovation has emerged as a pivotal challenge for both researchers and policymakers. This study establishes a coupled network of artificial intelligence patents based on co-cited scientific papers. Leveraging centrality metrics from network analysis offers a fresh perspective on understanding the influence of information flow and knowledge sharing within the network on patent impact. The study initially obtained patent numbers for 446,890 granted US AI patents from the United States Patent and Trademark Office’s artificial intelligence patent database for the years 2002-2020. Subsequently, specific information regarding these patents was acquired using the Lens patent retrieval platform. Additionally, a search and deduplication process was performed on scientific non-patent references (SNPRs) using the Web of Science database, resulting in the selection of 184,603 patents that cited 37,467 unique SNPRs. Finally, this study constructs a coupled network comprising 59,379 artificial intelligence patents by utilizing scientific papers co-cited in patent backward citations. In this network, nodes represent patents, and if patents reference the same scientific papers, connections are established between them, serving as edges within the network. Nodes and edges collectively constitute the patent coupling network. Structural characteristics such as node degree centrality, betweenness centrality, and closeness centrality are employed to assess the scientific connections between patents, while citation count is utilized as a quantitative metric for patent influence. Finally, a negative binomial model is employed to test the nonlinear relationship between these network structural features and patent influence. The research findings indicate that network structural features such as node degree centrality, betweenness centrality, and closeness centrality exhibit inverted U-shaped relationships with patent influence. Specifically, as these centrality metrics increase, patent influence initially shows an upward trend, but once these features reach a certain threshold, patent influence starts to decline. This discovery suggests that moderate network centrality is beneficial for enhancing patent influence, while excessively high centrality may have a detrimental effect on patent influence. This finding offers crucial insights for policymakers, emphasizing the importance of encouraging moderate knowledge flow and sharing to promote innovation when formulating technology policies. It suggests that in certain situations, data sharing and integration can contribute to innovation. Consequently, policymakers can take measures to promote data-sharing policies, such as open data initiatives, to facilitate the flow of knowledge and the generation of innovation. Additionally, governments and relevant agencies can achieve broader knowledge dissemination by supporting collaborative research projects, adjusting intellectual property policies to enhance flexibility, or nurturing technology entrepreneurship ecosystems.

Keywords: centrality, patent coupling network, patent influence, social network analysis

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Authors: Karen Koellner, Nanette Seago, Jennifer Jacobs, Helen Garnier

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Although studies of teacher professional development (PD) are prevalent, surprisingly most have only produced incremental shifts in teachers’ learning and their impact on students. There is a critical need to understand what teachers take up and use in their classroom practice after attending PD and why we often do not see greater changes in learning and practice. This paper is based on a mixed methods efficacy study of the Learning and Teaching Geometry (LTG) video-based mathematics professional development materials. The extent to which the materials produce a beneficial impact on teachers’ mathematics knowledge, classroom practices, and their students’ knowledge in the domain of geometry through a group-randomized experimental design are considered. Included is a close-up examination of a small group of teachers to better understand their interpretations of the workshops and their classroom uptake. The participants included 103 secondary mathematics teachers serving grades 6-12 from two US states in different regions. Randomization was conducted at the school level, with 23 schools and 49 teachers assigned to the treatment group and 18 schools and 54 teachers assigned to the comparison group. The case study examination included twelve treatment teachers. PD workshops for treatment teachers began in Summer 2016. Nine full days of professional development were offered to teachers, beginning with the one-week institute (Summer 2016) and four days of PD throughout the academic year. The same facilitator-led all of the workshops, after completing a facilitator preparation process that included a multi-faceted assessment of fidelity. The overall impact of the LTG PD program was assessed from multiple sources: two teacher content assessments, two PD embedded assessments, pre-post-post videotaped classroom observations, and student assessments. Additional data were collected from the case study teachers including additional videotaped classroom observations and interviews. Repeated measures ANOVA analyses were used to detect patterns of change in the treatment teachers’ content knowledge before and after completion of the LTG PD, relative to the comparison group. No significant effects were found across the two groups of teachers on the two teacher content assessments. Teachers were rated on the quality of their mathematics instruction captured in videotaped classroom observations using the Math in Common Observation Protocol. On average, teachers who attended the LTG PD intervention improved their ability to engage students in mathematical reasoning and to provide accurate, coherent, and well-justified mathematical content. In addition, the LTG PD intervention and instruction that engaged students in mathematical practices both positively and significantly predicted greater student knowledge gains. Teacher knowledge was not a significant predictor. Twelve treatment teachers self-selected to serve as case study teachers to provide additional videotapes in which they felt they were using something from the PD they learned and experienced. Project staff analyzed the videos, compared them to previous videos and interviewed the teachers regarding their uptake of the PD related to content knowledge, pedagogical knowledge and resources used. The full paper will include the case study of Ana to illustrate the factors involved in what teachers take up and use from participating in the LTG PD.

Keywords: geometry, mathematics professional development, pedagogical content knowledge, teacher learning

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Authors: Mir Afzal

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Introduction: Pakistan is a country with an ever-increasing population of largely diverse ethnic, cultural, religious and sectarian divisions. Whereas diversity is seen as a strength in many societies, in Pakistan, it has become a source of conflict and more a weakness than a strength due to lack of understanding and divisions based on ethnic, cultural, political, religious, and sectarian branding. However, amid conflicts and militancy across the country, the rural, mountainous communities in the Northern Areas of Pakistan enjoy not only peace and harmony but also a continuous process of social and economic transformation supported by strong civil society institutions. These community-based institutions have organized the rural, mountainous people of diverse ethnic and religious backgrounds into village organizations, women organizations, and Local Support Organizations engaged in self-help development and peace building in the region. The Study and its Methodology: A qualitative study was conducted in one district of the Northern Pakistan to explore the contributions of the civil society institutions (CSIs) and community-based organizations to uplifting the educational and socio-economic conditions of the people with an ultimate aim of developing a thriving, peaceful and pluralistic society in this mountainous region. The study employed an eclectic set of tools, including interviews, focused group discussions, observations of CSIs’ interventions, and analysis of documents, to generate rich data on the overall role and contributions of CSIs in promoting peace and pluralism in the region. Significance of the Study: Common experiences and empirical studies reveal that such interventions by CSIs have not only contributed to the socio-economic, educational, health and cultural development of these regions but these interventions have really transformed the rural, mountainous people into organized and forward looking communities. However, how such interventions have contributed to promoting pluralism and appreciation for diversity in these regions had been an unexplored but significant area. Therefore this qualitative research study funded by the Higher Education Commission of Pakistan was carried out by the Aga Khan University Institute for Educational Development to explore the role and contributions of CSIs in promoting peace and pluralism and appreciations for diversity in one district of Northern Pakistan which is home to people of different ethnic, religious, cultural and social backgrounds. Findings and Conclusions: The study has a comprehensive list of findings and conclusions covering various aspects of CSIs and their contributions to the transformation and peaceful co-existence of rural communities in the regions. However, this paper discusses only four major contributions of CSIs, namely enhancing economic capacity, community mobilization and organization, increasing access and quality of education, and building partnerships. It also discusses the factors influencing the role of CSIs, the issues, implications, and recommendations for CSIs, policy makers, donors and development agencies, and researchers. The paper concludes that by strengthening strong networks of CSIs and community based organizations, Pakistan will not only uplift its socio-economic attainments but it will also be able to address the critical challenges of terrorism, sectarianism, and other divisions and conflicts in its various regions.

Keywords: civil society, Pakistan, peace, rural

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Authors: Rana Mohamed, Ahmed E. Gomaa, Gehan Safwat, Ayman Diab

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Background: Bio-fabrication is a multidisciplinary research field that combines several principles, fabrication techniques, and protocols from different fields. The open-source-software movement is a movement that supports the use of open-source licenses for some or all software as part of the broader notion of open collaboration. Additive manufacturing is the concept of 3D printing, where it is a manufacturing method through adding layer-by-layer using computer-aided designs (CAD). There are several types of AM system used, and they can be categorized by the type of process used. One of these AM technologies is Digital light processing (DLP) which is a 3D printing technology used to rapidly cure a photopolymer resin to create hard scaffolds. DLP uses a projected light source to cure (Harden or crosslinking) the entire layer at once. Current applications of DLP are focused on dental and medical applications. Other developments have been made in this field, leading to the revolutionary field 3D bioprinting. The open-source movement was started to spread the concept of open-source software to provide software or hardware that is cheaper, reliable, and has better quality. Objective: Modification of desktop 3D printer into 3D bio-printer and the integration of DLP technology and bio-fabrication to produce an antibacterial dental model. Method: Modification of a desktop 3D printer into a 3D bioprinter. Gelatin hydrogel and sodium alginate hydrogel were prepared with different concentrations. Rhizome of Zingiber officinale, Flower buds of Syzygium aromaticum, and Bulbs of Allium sativum were extracted, and extractions were selected on different levels (Powder, aqueous extracts, total oils, and Essential oils) prepared for antibacterial bioactivity. Agar well diffusion method along with the E. coli have been used to perform the sensitivity test for the antibacterial activity of the extracts acquired by Zingiber officinale, Syzygium aromaticum, and Allium sativum. Lastly, DLP printing was performed to produce several dental models with the natural extracted combined with hydrogel to represent and simulate the Hard and Soft tissues. Result: The desktop 3D printer was modified into 3D bioprinter using open-source software Marline and modified custom-made 3D printed parts. Sodium alginate hydrogel and gelatin hydrogel were prepared at 5% (w/v), 10% (w/v), and 15%(w/v). Resin integration with the natural extracts of Rhizome of Zingiber officinale, Flower buds of Syzygium aromaticum, and Bulbs of Allium sativum was done following the percentage 1- 3% for each extract. Finally, the Antimicrobial dental model was printed; exhibits the antimicrobial activity, followed by merging with sodium alginate hydrogel. Conclusion: The open-source movement was successful in modifying and producing a low-cost Desktop 3D Bioprinter showing the potential of further enhancement in such scope. Additionally, the potential of integrating the DLP technology with bioprinting is a promising step toward the usage of the antimicrobial activity using natural products.

Keywords: 3D printing, 3D bio-printing, DLP, hydrogel, antibacterial activity, zingiber officinale, syzygium aromaticum, allium sativum, panax ginseng, dental applications

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Authors: Z. Gharaee

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Recognizing actions performed by others is important in our daily lives since it is necessary for communicating with others in a proper way. We perceive an action by observing the kinematics of motions involved in the performance. We use our experience and concepts to make a correct recognition of the actions. Although building the action concepts is a life-long process, which is repeated throughout life, we are very efficient in applying our learned concepts in analyzing motions and recognizing actions. Experiments on the subjects observing the actions performed by an actor show that an action is recognized after only about two hundred milliseconds of observation. In this study, hierarchical action recognition architecture is proposed by using growing grid layers. The first-layer growing grid receives the pre-processed data of consecutive 3D postures of joint positions and applies some heuristics during the growth phase to allocate areas of the map by inserting new neurons. As a result of training the first-layer growing grid, action pattern vectors are generated by connecting the elicited activations of the learned map. The ordered vector representation layer receives action pattern vectors to create time-invariant vectors of key elicited activations. Time-invariant vectors are sent to second-layer growing grid for categorization. This grid creates the clusters representing the actions. Finally, one-layer neural network developed by a delta rule labels the action categories in the last layer. System performance has been evaluated in an experiment with the publicly available MSR-Action3D dataset. There are actions performed by using different parts of human body: Hand Clap, Two Hands Wave, Side Boxing, Bend, Forward Kick, Side Kick, Jogging, Tennis Serve, Golf Swing, Pick Up and Throw. The growing grid architecture was trained by applying several random selections of generalization test data fed to the system during on average 100 epochs for each training of the first-layer growing grid and around 75 epochs for each training of the second-layer growing grid. The average generalization test accuracy is 92.6%. A comparison analysis between the performance of growing grid architecture and self-organizing map (SOM) architecture in terms of accuracy and learning speed show that the growing grid architecture is superior to the SOM architecture in action recognition task. The SOM architecture completes learning the same dataset of actions in around 150 epochs for each training of the first-layer SOM while it takes 1200 epochs for each training of the second-layer SOM and it achieves the average recognition accuracy of 90% for generalization test data. In summary, using the growing grid network preserves the fundamental features of SOMs, such as topographic organization of neurons, lateral interactions, the abilities of unsupervised learning and representing high dimensional input space in the lower dimensional maps. The architecture also benefits from an automatic size setting mechanism resulting in higher flexibility and robustness. Moreover, by utilizing growing grids the system automatically obtains a prior knowledge of input space during the growth phase and applies this information to expand the map by inserting new neurons wherever there is high representational demand.

Keywords: action recognition, growing grid, hierarchical architecture, neural networks, system performance

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Authors: Harriet Bothwell, Lowri Evans, Kevin Jones

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Background: The University of Bristol provides all medical students the opportunity to undertake student selected components (SSCs) at multiple stages of the undergraduate programme. SSCs enable students to explore areas of interest that are not necessarily covered by the curriculum. Students are required to produce a written report and most use SSCs as an opportunity to undertake an audit or small research project. In 2013 Swindon Academy, based at the Great Western Hospital, offered eight students the opportunity of a global health SSC which included a two week trip to rural hospital in Uganda. This SSC has since expanded and in 2017 a total of 20 students had the opportunity to undertake small research projects at two hospitals in rural Uganda. 'Tomorrows Doctors' highlights the importance of understanding healthcare from a 'global perspective' and student feedback from previous SSCs suggests that self-assessed knowledge of global health increases as a result of this SSC. Through the most recent version of this SSC students had the opportunity to undertake projects in a wide range of specialties including paediatrics, palliative care, surgery and medical education. Methods: An anonymous online questionnaire was made available to students following the SSC. There was a response rate of 80% representing 16 out of the 20 students. This questionnaire surveyed students’ satisfaction and experience of the SSC including the level of academic, project and spiritual support provided as well as perceived challenges in completing the project and barriers to healthcare delivery in the low resource setting. This survey had multiple open questions allowing the collection of qualitative data. Further qualitative data was collected from the students’ project report. The suggested format included a reflection and all students completed these. All qualitative data underwent thematic analysis. Results: All respondents rated the overall experience of the SSC as 'good' or 'excellent'. Preliminary data suggest that students’ confidence in their knowledge of global health, diagnosis of tropical diseases and management of tropical diseases improved after completing this SSC. Thematic analysis of students' reflection is ongoing but suggests that students gain far more than improved knowledge of tropical diseases. Students reflect positively on having the opportunity to research in a low resource setting and feel that by completing these projects they will be 'useful' to the hospital. Several students reflect the stark contrast to healthcare delivery in the UK and recognise the 'privilege' of having a healthcare system that is free at the point of access. Some students noted the different approaches that clinicians in Uganda had to train in 'taking ownership' of their own learning. Conclusions: Students completing this SSC report increased knowledge of global health and tropical medicine. However, their reflections reveal much broader learning outcomes and demonstrate considerable insight in multiple topics including conducting research in the low resource setting, training and healthcare inequality.

Keywords: global health, medical education, student feedback, undergraduate

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Authors: Yan Zhang

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Predictive maintenance is a technique to predict when an in-service machine will fail so that maintenance can be planned in advance. Analytics-driven predictive maintenance is gaining increasing attention in many industries such as manufacturing, utilities, aerospace, etc., along with the emerging demand of Internet of Things (IoT) applications and the maturity of technologies that support Big Data storage and processing. This study aims to build an end-to-end analytics solution that includes both real-time machine condition monitoring and machine learning based predictive analytics capabilities. The goal is to showcase a general predictive maintenance solution architecture, which suggests how the data generated from field machines can be collected, transmitted, stored, and analyzed. We use a publicly available aircraft engine run-to-failure dataset to illustrate the streaming analytics component and the batch failure prediction component. We outline the contributions of this study from four aspects. First, we compare the predictive maintenance problems from the view of the traditional reliability centered maintenance field, and from the view of the IoT applications. When evolving to the IoT era, predictive maintenance has shifted its focus from ensuring reliable machine operations to improve production/maintenance efficiency via any maintenance related tasks. It covers a variety of topics, including but not limited to: failure prediction, fault forecasting, failure detection and diagnosis, and recommendation of maintenance actions after failure. Second, we review the state-of-art technologies that enable a machine/device to transmit data all the way through the Cloud for storage and advanced analytics. These technologies vary drastically mainly based on the power source and functionality of the devices. For example, a consumer machine such as an elevator uses completely different data transmission protocols comparing to the sensor units in an environmental sensor network. The former may transfer data into the Cloud via WiFi directly. The latter usually uses radio communication inherent the network, and the data is stored in a staging data node before it can be transmitted into the Cloud when necessary. Third, we illustrate show to formulate a machine learning problem to predict machine fault/failures. By showing a step-by-step process of data labeling, feature engineering, model construction and evaluation, we share following experiences: (1) what are the specific data quality issues that have crucial impact on predictive maintenance use cases; (2) how to train and evaluate a model when training data contains inter-dependent records. Four, we review the tools available to build such a data pipeline that digests the data and produce insights. We show the tools we use including data injection, streaming data processing, machine learning model training, and the tool that coordinates/schedules different jobs. In addition, we show the visualization tool that creates rich data visualizations for both real-time insights and prediction results. To conclude, there are two key takeaways from this study. (1) It summarizes the landscape and challenges of predictive maintenance applications. (2) It takes an example in aerospace with publicly available data to illustrate each component in the proposed data pipeline and showcases how the solution can be deployed as a live demo.

Keywords: Internet of Things, machine learning, predictive maintenance, streaming data

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Authors: Jarrod Haar, David Brougham

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The present study explores the links between supporting employee well-being and the potential benefits to employee performance. We focus on employee innovative work behaviors (IWBs), which have three stages: (1) development, (2) adoption, and (3) implementation of new ideas and work methods. We explore the role of organizational support focusing on employee well-being via High-Performance Work Systems (HPWS). HPWS are HR practices that are designed to enhance employees’ skills, commitment, and ultimately, productivity. HPWS influence employee performance through building their skills, knowledge, and abilities and there is meta-analytic support for firm-level HPWS influencing firm performance, but less attention towards employee outcomes, especially innovation. We explore HPWS-wellbeing being offered (e.g., EAPs, well-being App, etc.) to capture organizational commitment to employee well-being. Under social exchange theory, workers should reciprocate their firm's offering of HPWS-wellbeing with greater efforts towards IWBs. Further, we explore playful work design as a mediator, which represents employees proactively creating work conditions that foster enjoyment/challenge but don’t require any design change to the job itself. We suggest HPWS-wellbeing can encourage employees to become more playful, and ultimately more innovative. Finally, beyond direct effects, we examine whether these relations are similar by gender and ultimately test a moderated mediation model. Using N=1135 New Zealand employees, we established measures with confirmatory factor analysis (CFA), and all measures had good psychometric properties (α>.80). We controlled for age, tenure, education, and hours worked and analyzed data using the PROCESS macro (version 4.2) specifically model 8 (moderated mediation). We analyzed overall IWB, and then again across the three stages. Overall, we find HPWS-wellbeing is significantly related to overall IWBs and the three stages (development, adoption, and implementation) individually. Similarly, HPWS-wellbeing shapes playful work design and playful work design predicts overall IWBs and the three stages individually. It only partially mediates the effects of HPWS-wellbeing, which retains a significant indirect effect. Moderation effects are supported, with males reporting a more significant effect from HPWS-wellbeing on playful work design but not IWB (or any of the three stages) than females. Females report higher playful work design when HPWS-wellbeing is low, but the effects are reversed when HPWS-wellbeing is high (males higher). Thus, males respond stronger under social exchange theory from HPWS-wellbeing, at least towards expressing playful work design. Finally, evidence of moderated mediation effects is found on overall IWBs and the three stages. Males report a significant indirect effect from HPWS-wellbeing on IWB (through playful work design), while female employees report no significant indirect effect. The benefits of playful work design fully account for their IWBs. The models account for small amounts of variance towards playful work design (12%) but larger for IWBs (26%). The study highlights a gap in the literature on HPWS-wellbeing and provides empirical evidence of their importance towards worker innovation. Further, gendered effects suggest these benefits might not be equal. The findings provide useful insights for organizations around how providing HR practices that support employee well-being are important, although how they work for different genders needs further exploration.

Keywords: human resource practices, wellbeing, innovation, playful work design

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Authors: Guillaume Soubeyran, Fabrice Micoud, Benoit Morin, Jean-Philippe Poirot-Crouvezier, Magali Reytier

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Proton Exchange Membrane Fuel Cell (PEMFC) technology is considered as a solution for the reduction of CO2 emissions. However, this technology still meets several challenges for high-scale industrialization. In this context, the increase of durability remains a critical aspect for competitiveness of this technology. Fortunately, performance degradations in nominal operating conditions is partially reversible, meaning that if specific conditions are applied, a partial recovery of fuel cell performance can be achieved, while irreversible degradations can only be mitigated. Thus, it is worth studying the optimal conditions to rejuvenate these reversible degradations and assessing the long-term impact of such procedures on the performance of the cell. Reversible degradations consist mainly of anode Pt active sites poisoning by carbon monoxide at the anode, heterogeneities in water management during use, and oxidation/deactivation of Pt active sites at the cathode. The latter is identified as a major source of reversible performance loss caused by the presence oxygen, high temperature and high cathode potential that favor platinum oxidation, especially in high efficiency operating points. Hence, we studied here a recovery procedure aiming at reducing the platinum oxides by decreasing cathode potential during operation. Indeed, the application of short air starvation phase leads to a drop of cathode potential. Cell performances are temporarily increased afterwards. Nevertheless, local temperature and current heterogeneities within the cells are favored and shall be minimized. The consumption of fuel during the recovery phase shall also be considered to evaluate the global efficiency. Consequently, the purpose of this work is to find an optimal compromise between the recovery of reversible degradations by air starvation, the increase of global cell efficiency and the mitigation of irreversible degradations effects. Different operating parameters have first been studied such as cell voltage, temperature and humidity in single cell set-up. Considering the global PEMFC system efficiency, tests showed that reducing duration of recovery phase and reducing cell voltage was the key to ensure an efficient recovery. Recovery phase frequency was a major factor as well. A specific method was established to find the optimal frequency depending on the duration and voltage of the recovery phase. Then, long-term degradations have also been studied by applying FC-DLC cycles based on NEDC cycles on a 4-cell short stack by alternating test sequences with and without recovery phases. Depending on recovery phase timing, cell efficiency during the cycle was increased up to 2% thanks to a mean voltage increase of 10 mV during test sequences with recovery phases. However, cyclic voltammetry tests results suggest that the implementation of recovery phases causes an acceleration of the decrease of platinum active areas that could be due to the high potential variations applied to the cathode electrode during operation.

Keywords: durability, PEMFC, recovery procedure, reversible degradation

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Authors: Charlotte K. Lee, Henrique R. N. Aguiar, Ralph Smith, James Baldock, Sam Botchey

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Background: Femoral neck stress fractures (FNSF) are uncommon, making up 1 to 7.2% of stress fractures in healthy subjects. FNSFs are prevalent in young women, military recruits, endurance athletes, and individuals with energy deficiency syndrome or female athlete triad. Presentation is often non-specific and is often misdiagnosed following the initial examination. There is limited research addressing the return–to–activity time after FNSF. Previous studies have demonstrated prognostic time predictions based on various imaging techniques. Here, (1) OxSport clinic FNSF practice standards are retrospectively reviewed, (2) FNSF cohort demographics are examined, (3) Regression models were used to predict return–to–activity prognosis and consequently determine bone stress risk factors. Methods: Patients with a diagnosis of FNSF attending Oxsport clinic between 01/06/2020 and 01/01/2020 were selected from the Rheumatology Assessment Database Innovation in Oxford (RhADiOn) and OxSport Stress Fracture Database (n = 14). (1) Clinical practice was audited against five criteria based on local and National Institute for Health Care Excellence guidance, with a 100% standard. (2) Demographics of the FNSF cohort were examined with Student’s T-Test. (3) Lastly, linear regression and Random Forest regression models were used on this patient cohort to predict return–to–activity time. Consequently, an analysis of feature importance was conducted after fitting each model. Results: OxSport clinical practice met standard (100%) in 3/5 criteria. The criteria not met were patient waiting times and documentation of all bone stress risk factors. Importantly, analysis of patient demographics showed that of the population with complete bone stress risk factor assessments, 53% were positive for modifiable bone stress risk factors. Lastly, linear regression analysis was utilized to identify demographic factors that predicted return–to–activity time [R2 = 79.172%; average error 0.226]. This analysis identified four key variables that predicted return-to-activity time: vitamin D level, total hip DEXA T value, femoral neck DEXA T value, and history of an eating disorder/disordered eating. Furthermore, random forest regression models were employed for this task [R2 = 97.805%; average error 0.024]. Analysis of the importance of each feature again identified a set of 4 variables, 3 of which matched with the linear regression analysis (vitamin D level, total hip DEXA T value, and femoral neck DEXA T value) and the fourth: age. Conclusion: OxSport clinical practice could be improved by more comprehensively evaluating bone stress risk factors. The importance of this evaluation is demonstrated by the population found positive for these risk factors. Using this cohort, potential bone stress risk factors that significantly impacted return-to-activity prognosis were predicted using regression models.

Keywords: eating disorder, bone stress risk factor, femoral neck stress fracture, vitamin D

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Authors: Sricheta Chowdhury

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To require a woman to choose between her work and her personal life is the most acute form of discrimination that can be meted out against her. No woman should be given a choice to choose between her motherhood and her career at Bar, yet that is the most detrimental discrimination that has been happening in Indian Bar, which no one has questioned so far. The falling number of women in practice is a reality that isn’t garnering much attention given the sharp rise in women studying law but is not being able to continue in the profession. Moving from a colonial misogynist whim to a post-colonial “new-age construct of Indian woman” façade, the policymakers of the Indian Judiciary have done nothing so far to decolonize itself from its rudimentary understanding of ‘equality of gender’ when it comes to the legal profession. Therefore, when Indian jurisprudence was (and is) swooning to the sweeping effect of transformative constitutionalism in the understanding of equality as enshrined under the Indian Constitution, one cannot help but question why the legal profession remained out of brushing effect of achieving substantive equality. The Airline industry’s discriminatory policies were not spared from criticism, nor were the policies where women’s involvement in any establishment serving liquor (Anuj Garg case), but the judicial practice did not question the stereotypical bias of gender and unequal structural practices until recently. That necessitates the need to examine the existing Bar policies and the steps taken by the regulatory bodies in assessing the situations that are in favor or against the purpose of furthering women’s issues in present-day India. From a comparative feminist point of concern, South Africa’s pro-women Bar policies are attractive to assess their applicability and extent in terms of promoting inclusivity at the Bar. This article intends to tap on these two countries’ potential in carving a niche in giving women an equal platform to play a substantive role in designing governance policies through the Judiciary. The article analyses the current gender composition of the legal profession while endorsing the concept of substantive equality as a requisite in designing an appropriate appointment process of the judges. It studies the theoretical framework on gender equality, examines the international and regional instruments and analyses the scope of welfare policies that Indian legal and regulatory bodies can undertake towards a transformative initiative in re-modeling the Judiciary to a more diverse and inclusive institution. The methodology employs a comparative and analytical understanding of doctrinal resources. It makes quantitative use of secondary data and qualitative use of primary data collected for determining the present status of Indian women legal practitioners and judges. With respect to quantitative data, statistics on the representation of women as judges and chief justices and senior advocates from their official websites from 2018 till present have been utilized. In respect of qualitative data, results of the structured interviews conducted through open and close-ended questions with retired lady judges of the higher judiciary and senior advocates of the Supreme Court of India, contacted through snowball sampling, are utilized.

Keywords: gender, higher judiciary, legal profession, representation, substantive equality

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Authors: Naresh Kumar, Savita Kumari, Naresh Kochhar

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The objective of the study was to assess the role of mineralogy and subsurface structure on water quality of Tosham, Malani Igneous Suite (MIS), Western Rajasthan, India. MIS is the largest (55,000 km2) A-type, anorogenic and high heat producing acid magmatism in the peninsular India and owes its origin to hot spot tectonics. Apart from agricultural and industrial wastes, geogenic activities cause fluctuations in quality parameters of water resources. Twenty water samples (20) selected from Tosham and surrounding areas were analyzed for As, Pb, B, Al, Zn, Fe, Ni using Inductive coupled plasma emission and F by Ion Chromatography. The concentration of As, Pb, B, Ni and F was above the stipulated level specified by BIS (Bureau of Indian Standards IS-10500, 2012). The concentration of As and Pb in surrounding areas of Tosham ranged from 1.2 to 4.1 mg/l and from 0.59 to 0.9 mg/l respectively which is higher than limits of 0.05mg/l (As) and 0.01 mg/l (Pb). Excess trace metal accumulation in water is toxic to humans and adversely affects the central nervous system, kidneys, gastrointestinal tract, skin and cause mental confusion. Groundwater quality is defined by nature of rock formation, mineral water reaction, physiography, soils, environment, recharge and discharge conditions of the area. Fluoride content in groundwater is due to the solubility of fluoride-bearing minerals like fluorite, cryolite, topaz, and mica, etc. Tosham is comprised of quartz mica schist, quartzite, schorl, tuff, quartz porphyry and associated granites, thus, fluoride is leached out and dissolved in groundwater. In the study area, Ni concentration ranged from 0.07 to 0.5 mg/l (permissible limit 0.02 mg/l). The primary source of nickel in drinking water is leached out nickel from ore-bearing rocks. Higher concentration of As is found in some igneous rocks specifically containing minerals as arsenopyrite (AsFeS), realgar (AsS) and orpiment (As2S3). MIS consists of granite (hypersolvus and subsolvus), rhyolite, dacite, trachyte, andesite, pyroclasts, basalt, gabbro and dolerite which increased the trace elements concentration in groundwater. Nakora, a part of MIS rocks has high concentration of trace and rare earth elements (Ni, Rb, Pb, Sr, Y, Zr, Th, U, La, Ce, Nd, Eu and Yb) which percolates the Ni and Pb to groundwater by weathering, contacts and joints/fractures in rocks. Additionally, geological setting of MIS also causes dissolution of trace elements in water resources beneath the surface. NE–SW tectonic lineament, radial pattern of dykes and volcanic vent at Nakora created a way for leaching of these elements to groundwater. Rain water quality might be altered by major minerals constituents of host Tosham rocks during its percolation through the rock fracture, joints before becoming the integral part of groundwater aquifer. The weathering process like hydration, hydrolysis and solution might be the cause of change in water chemistry of particular area. These studies suggest that geological relation of soil-water horizon with MIS rocks via mineralogical variations, structures and tectonic setting affects the water quality of the studied area.

Keywords: geochemistry, groundwater, malani igneous suite, tosham

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Authors: Priyajeet Kaur Kaleka

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Introduction: A dentist is often the first responder in the battle for a patient’s healthy body and maybe the first health professional to observe signs of child abuse, be it physical, emotional, and/or sexual mistreatment. Therefore, it is an ethical responsibility for the dental clinician to detect and report suspected cases of child abuse and neglect (CAN). The main reasons for not reporting suspected cases of CAN, with special emphasis on the third: 1) Uncertainty of the diagnosis, 2) Lack of knowledge of the reporting procedure, and 3) Child abuse and neglect somewhat remained the subject of ignorance among dental professionals because of a lack of advance clinical training. Given these epidemic proportions, there is a scope of further research about dental school curriculum design. Purpose: This study aimed to assess the knowledge and attitude of dentists in Canada regarding signs and symptoms of child abuse and neglect (CAN), reporting procedures, and whether educational strategies followed by dental schools address this sensitive issue. In pursuit of that aim, this abstract summarizes the evidence related to this question. Materials and Methods: Data was collected through a specially designed questionnaire adapted and modified from the author’s previous cross-sectional study on (CAN), which was conducted in Pune, India, in 2016 and is available on the database of PubMed. Design: A random sample was drawn from the targeted population of registered dentists and dental students in Canada regarding their knowledge, professional responsibilities, and behavior concerning child abuse. Questionnaire data were distributed to 200 members. Out of which, a total number of 157 subjects were in the final sample for statistical analysis, yielding response of 78.5%. Results: Despite having theoretical information on signs and symptoms, 55% of the participants indicated they are not confident to detect child physical abuse cases. 90% of respondents believed that recognition and handling the CAN cases should be a part of undergraduate training. Only 4.5% of the participants have correctly identified all signs of abuse due to inadequate formal training in dental schools and workplaces. Although nearly 96.3% agreed that it is a dentist’s legal responsibility to report CAN, only a small percentage of the participants reported an abuse case in the past. While 72% stated that the most common factor that might prevent a dentist from reporting a case was doubt over the diagnosis. Conclusion: The goal is to motivate dental schools to deal with this critical issue and provide their students with consummate training to strengthen their capability to care for and protect children. The educational institutions should make efforts to spread awareness among dental students regarding the management and tackling of CAN. Clinical Significance: There should be modifications in the dental school curriculum focusing on problem-based learning models to assist graduates to fulfill their legal and professional responsibilities. CAN literacy should be incorporated into the dental curriculum, which will eventually benefit future dentists to break this intergenerational cycle of violence.

Keywords: abuse, child abuse and neglect, dentist knowledge, dental school curriculum, problem-based learning

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Authors: Andre Pastori D'Aurea, Lauriston Bertelli Feranades, Luis Eduardo Ferreira, Leandro Dias Pinto, Fabiana Ayumi Shiozaki

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The aim of this study was to improve the production of beef cattle on tropical pasture without harming this environment. On tropical pastures, cattle's live weight gain is lower than feedlot, and forage production is seasonable, changing from season to season. Thus, concerned with sustainable livestock production, the Premix Company has developed strategies to improve the production of beef cattle on tropical pasture to ensure sustainability of welfare and production. There are two important principles in this productivity system: 1) increase individual gains with use of better supplementation and 2) increase the productivity units with better forage quality like corn silage or other forms of forage conservations, actually used only in winter, and adding natural additives in the diet. This production system was applied from June 2017 to May 2018 in the Research Center of Premix Company, Patrocínio Paulista, São Paulo State, Brazil. The area used had 9 hectares of pasture of Brachiaria brizantha. 36 steers Nellore were evaluated for one year. The initial weight was 253 kg. The parameters used were daily average gain and gain per area. This indicated the corrections to be made and helped design future fertilization. In this case, we fertilized the pasture with 30 kg of nitrogen per animal divided into two parts. The diet was pasture and protein-energy supplements (0.4% of live weight). The supplement used was added with natural additive Fator P® – Premix Company). Fator P® is an additive composed by amino acids (lysine, methionine and tyrosine, 16400, 2980 and 3000 mg.kg-1 respectively), minerals, probiotics (Saccharomyces cerevisiae, 7 x 10E8 CFU.kg-1) and essential fatty acids (linoleic and oleic acids, 108.9 and 99g.kg-1 respectively). Due to seasonal changes, in the winter we supplemented the diet by increasing the offer of forage, supplementing with maize silage. It was offered 1% of live weight in silage corn and 0.4% of the live weight in protein-energetic supplements with additive Fator P ®. At the end of the period, the productivity was calculated by summing the individual gains for the area used. The average daily gain of the animals were 693 grams per day and was produced 1.005 kg /hectare/year. This production is about 8 times higher than the average of Brazilian meat national production. To succeed in this project, it is necessary to increase the gains per area, so it is necessary to increase the capacity per area. Pasture management is very important to the project's success because the dietary decisions were taken from the quantity and quality of the forage. We, therefore, recommend the use of animals in the growth phase because the response to supplementation is greater in that phase and we can allocate more animals per area. This system's carbon footprint reduces emissions by 61.2 percent compared to the Brazilian average. This beef cattle production system can be efficient and environmentally friendly to the natural. Another point is that bovines will benefit from their natural environment without competing or having an impact on human food production.

Keywords: cattle production, environment, pasture, sustainability

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Authors: Grâce Chidikofan, François Pinta, A. Benoist, G. Volle, J. Valette

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Statement of the Problem: biomass gasification systems may be relevant for decentralized power generation from recoverable agricultural and wood residues available in rural areas. In recent years, many systems have been implemented in all over the world as especially in Cambodgia, India. Although they have many positive effects, these systems can also affect the environment and human health. Indeed, during the process of biomass gasification, black wastewater containing tars are produced and generally discharged in the local environment either into the rivers or on soil. However, in most environmental assessment studies of biomass gasification systems, the impact of these releases are underestimated, due to the difficulty of identification of their chemical substances. This work deal with the analysis of the environmental impacts of tars from wood gasification in terms of human toxicity cancer effect, human toxicity non-cancer effect, and freshwater ecotoxicity. Methodology: A Life Cycle Assessment (LCA) approach was adopted. The inventory of tars chemicals substances was based on experimental data from a downdraft gasification system. The composition of six samples from two batches of raw materials: one batch made of tree wood species (oak+ plane tree +pine) at 25 % moisture content and the second batch made of oak at 11% moisture content. The tests were carried out for different gasifier load rates, respectively in the range 50-75% and 50-100%. To choose the environmental impacts assessment method, we compared the methods available in SIMAPRO tool (8.2.0) which are taking into account most of the chemical substances. The environmental impacts for 1kg of tars discharged were characterized by ILCD 2011+ method (V.1.08). Findings Experimental results revealed 38 important chemical substances in varying proportion from one test to another. Only 30 are characterized by ILCD 2011+ method, which is one of the best performing methods. The results show that wood species or moisture content have no significant impact on human toxicity noncancer effect (HTNCE) and freshwater ecotoxicity (FWE) for water release. For human toxicity cancer effect (HTCE), a small gap is observed between impact factors of the two batches, either 3.08E-7 CTUh/kg against 6.58E-7 CTUh/kg. On the other hand, it was found that the risk of negative effects is higher in case of tar release into water than on soil for all impact categories. Indeed, considering the set of samples, the average impact factor obtained for HTNCE varies respectively from 1.64 E-7 to 1.60E-8 CTUh/kg. For HTCE, the impact factor varies between 4.83E-07 CTUh/kg and 2.43E-08 CTUh/kg. The variability of those impact factors is relatively low for these two impact categories. Concerning FWE, the variability of impact factor is very high. It is 1.3E+03 CTUe/kg for tars release into water against 2.01E+01 CTUe/kg for tars release on soil. Statement concluding: The results of this study show that the environmental impacts of tars emission of biomass gasification systems can be consequent and it is important to investigate the ways to reduce them. For environmental research, these results represent an important step of a global environmental assessment of the studied systems. It could be used to better manage the wastewater containing tars to reduce as possible the impacts of numerous still running systems all over the world.

Keywords: biomass gasification, life cycle analysis, LCA, environmental impact, tars

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Authors: L. Kutateldze, T. Urushadze, R. Khvedelidze, N. Zakariashvili, I. Khokhashvili, T. Sadunishvili

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Microbial cellulase/xylanase have shown their potential application in various industries including pulp and paper, textile, laundry, biofuel production, food and feed industry, brewing, and agriculture. Extremophilic micromycetes and their enzymes that are resistant to critical values of temperature and pH, and retaining enzyme activity for a long time are of great industrial interest. Among strains of microscopic fungi from the collection of S. Durmishidze Institute of Biochemistry and Biotechnology, strains isolated from different ecological niches of Southern Caucasus-active producers of cellulase/xylanase have been selected by means of screening under deep cultivation conditions. Extremophilic micromycetes and their enzymes that are resistant to critical values of temperature and pH, and retaining enzyme activity for a long time are of great industrial interest. Among strains of microscopic fungi from the collection of S. Durmishidze Institute of Biochemistry and Biotechnology, strains isolated from different ecological niches of Southern Caucasus-active producers of cellulase/xylanase have been selected by means of screening under deep cultivation conditions. Representatives of the genera Aspergillus, Penicillium and Trichoderma are outstanding by relatively high activities of these enzymes. Among the producers were revealed thermophilic strains, representatives of the genus Aspergillus-Aspergillus terreus, Aspergillus versicolor, Aspergillus wentii, also strains of Sporotrichum pulverulentum and Chaetomium thermophile. As a result of optimization of cultivation media and conditions, activities of enzymes produced by the strains have been increased by 4 -189 %. Two strains, active producers of cellulase/xylanase – Penicillium canescence E2 (mesophile) and Aspergillus versicolor Z17 (thermophile) were chosen for further studies. Cellulase/xylanase enzyme preparations from two different genera of microscopic fungi Penicillium canescence E2 and Aspergillus versicolor Z 17 were obtained with activities 220 U/g /1200 U/g and 125 U/g /940 U/g, correspondingly. Main technical characteristics were as follows: the highest enzyme activities were obtained for mesophilic strain Penicillium canescence E2 at 45-500C, while almost the same enzyme activities were fixed for the thermophilic strain Aspergillus versicolor Z 17 at temperature 60-65°C, exceeding the temperature optimum of the mesophile by 150C. Optimum pH of action of the studied cellulase/xylanases from mesophileic and thermophilic strains were similar and equaled to 4.5-5.0 It has been shown that cellulase/xylanase technical preparations from selected strains of Penicillium canescence E2 and Aspergillus versicolor Z17 hydrolyzed cellulose of untreated wheat straw to reducible sugars by 46-52%, and to glucose by 22-27%. However the thermophilic enzyme preparations from the thermophilic A.versicolor strains conducted the process at 600C higher by 100C as compared to mesophlic analogue. Rate of hydrolyses of the pretreated substrate by the same enzyme preparations to reducible sugars and glucose conducted at optimum for their action 60 and 500C was 52-61% and 29-33%, correspondingly. Thus, maximum yield of glucose and reducible sugars form untreated and pretreated wheat straw was achieved at higher temperature (600C) by enzyme preparations from thermophilic strain, which gives advantage for their industrial application.

Keywords: cellulase/xylanase, cellulose hydrolysis, microscopic fungi, thermophilic strain

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Authors: Yujie Yuan, Yiyang Fan, Hong Fan

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Objective: The RNA methylation recognition protein Aly/REF export factor (ALYREF) is considered one type of “reader” protein acting as a recognition protein of m5C, has been reported involved in several biological progresses including cancer initiation and progression. 5-methylcytosine (m5C) is a conserved and prevalent RNA modification in all species, as accumulating evidence suggests its role in the promotion of tumorigenesis. It has been claimed that ALYREF mediates nuclear export of mRNA with m5C modification and regulates biological effects of cancer cells. However, the systematical regulatory pathways of ALYREF in cancer tissues have not been clarified, yet. Methods: The expression level of ALYREF in pan-cancer and their normal tissues was compared through the data acquired from The Cancer Genome Atlas (TCGA). The University of Alabama at Birmingham Cancer data analysis Portal UALCAN was used to analyze the relationship between ALYREF and clinical pathological features. The relationship between the expression level of ALYREF and prognosis of pan-cancer, and the correlation genes of ALYREF were figured out by using Gene Expression Correlation Analysis database GEPIA. Immune related genes were obtained from TISIDB (an integrated repository portal for tumor-immune system interactions). Immune-related research was conducted by using Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) and TIMER. Results: Based on the data acquired from TCGA, ALYREF has an obviously higher-level expression in various types of cancers compared with relevant normal tissues excluding thyroid carcinoma and kidney chromophobe. The immunohistochemical images on The Human Protein Atlas showed that ALYREF can be detected in cytoplasm, membrane, but mainly located in nuclear. In addition, a higher expression level of ALYREF in tumor tissue generates a poor prognosis in majority of cancers. According to the above results, cancers with a higher expression level of ALYREF compared with normal tissues and a significant correlation between ALYREF and prognosis were selected for further analysis. By using TISIDB, we found that portion of ALYREF co-expression genes (such as BIRC5, H2AFZ, CCDC137, TK1, and PPM1G) with high Pearson correlation coefficient (PCC) were involved in anti-tumor immunity or affect resistance or sensitivity to T cell-mediated killing. Furthermore, based on the results acquired from GEPIA, there was significant correlation between ALYREF and PD-L1. It was exposed that there is a negative correlation between the expression level of ALYREF and ESTIMATE score. Conclusion: The present study indicated that ALYREF plays a vital and universal role in cancer initiation and progression of pan-cancer through regulating mitotic progression, DNA synthesis and metabolic process, and RNA processing. The correlation between ALYREF and PD-L1 implied ALYREF may affect the therapeutic effect of immunotherapy of tumor. More evidence revealed that ALYREF may play an important role in tumor immunomodulation. The correlation between ALYREF and immune cell infiltration level indicated that ALYREF can be a potential therapeutic target. Exploring the regulatory mechanism of ALYREF in tumor tissues may expose the reason for poor efficacy of immunotherapy and offer more directions of tumor treatment.

Keywords: ALYREF, pan-cancer, immunotherapy, PD-L1

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Authors: S M Abdus Sattar

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Introduction: The tourism industry is a vital component of economies, providing opportunities for economic growth and cultural exchange. At the heart of this industry lies the concept of hospitality. Tourism refers to the activity of traveling for leisure or business and hospitality refers to the welcoming, amenities and providing of services to guests in the travel and accommodation industries. Tourism is one of the fastest growing industries in the world today. Objectives: The most important objective of Tourism and Hospitality study are: To assess different aspects, To identify the reasons, To analyze the contribution in GDP of Bangladesh, To identify importances of hospitality, To identify challenges, To Development of leadership characteristics, communication, teamwork skill, customer service and problem-solving, To provide welcoming treatment to guests, offering accommodation, food, transportation and entertainment services to ensure guests feel safe and comfortable away from home, To explore future prospects in Bangladesh and To suggests some recommendations for development of these sector. Methodology: Statistical method has been adopted in this study. Common characteristics of the people of particular area are found out. Tourism data is collected through various methods, such as surveys, interviews, visitor registration, travel agency records, hotel bookings, transport ticketing systems, online platforms, social media, Bangladesh Tourism Corporation, World Travel and Tourism Council, Quantitative and qualitative research methods are used while collecting and analyzing data. Findings: Tourism and Hospitality focuses on marketing, management, attractions, recreation events, travel related services, lodging, operations of restaurants and food services. Tourism offers great opportunities for emerging economies and developing countries. It creates jobs, strengthens the local economy, contributes to local infrastructure development, can help to conserve the natural environment, cultural assets, traditions, reduce poverty and inequality. The hospitality industry contributes to the economy of a country by employing its human resources. It generates new employment, contributing to the Gross Domestic Product (GDP) of a country. Around 330 million people were employed in the Tourism and Hospitality sector in globally. Tourism and Hospitality industry is creating high tax revenues. Tourism is a rising industry in Bangladesh. Studying hospitality can also help develop a range of essential skills that are valuable in any industry. Conclusion: As the conclusion, tourism industry is focused on providing quality attractions and events in order to entice tourists to come. The hospitality industry provides the good service for client. Hospitality and Tourism are closely related. Hospitality built up the relationship between host and guest. The importance of hospitality in tourism industry is immense. The Tourism and Hospitality industry is an important contributor to Bangladesh's economy. It is necessary to develop the Tourism infrastructure, maintain tourist destinations, railway stations, airports, rest house, hotels and improve the quality of services.

Keywords: tourism, hospitality, GDP, employment, economy

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Authors: Jing (Claire) LI

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More than two decades from 2000 to 2020 of economic reforms have brought China unprecedented economic growth. There is an urgent call of research towards corporate social responsibility (CSR) in the context of China because while China continues to develop into a global trading market, it suffers from various serious problems relating to CSR. This study analyses the factors affecting the adoption of CSR practices by Chinese listed companies. The author proposes a new framework of factors of CSR adoption. Following common organisational factors and external factors in the literature (including organisational support, company size, shareholder pressures, and government support), this study introduces two additional factors, dynamic capability and regional culture. A survey questionnaire was conducted on the CSR adoption of Chinese listed companies in Shen Zhen and Shang Hai index from December 2019 to March 2020. The survey was conducted to collect data on the factors that affect the adoption of CSR. After collection of data, this study performed factor analysis to reduce the number of measurement items to several main factors. This procedure is to confirm the proposed framework and ensure the significant factors. Through analysis, this study identifies four grouped factors as determinants of the CSR adoption. The first factor loading includes dynamic capability and organisational support. The study finds that they are positively related to the first factor, so the first factor mainly reflects the capabilities of companies, which is one component in internal factors. In the second factor, measurement items of stakeholder pressures mainly are from regulatory bodies, customer and supplier, employees and community, and shareholders. In sum, they are positively related to the second factor and they reflect stakeholder pressures, which is one component of external factors. The third factor reflects organisational characteristics. Variables include company size and cultural score. Among these variables, company size is negatively related to the third factor. The resulted factor loading of the third factor implies that organisational factor is an important determinant of CSR adoption. Cultural consistency, the variable in the fourth factor, is positively related to the factor. It represents the difference between perception of managers and actual culture of the organisations in terms of cultural dimensions, which is one component in internal factors. It implies that regional culture is an important factor of CSR adoption. Overall, the results are consistent with previous literature. This study is of significance from both theoretical and empirical perspectives. First, from the significance of theoretical perspective, this research combines stakeholder theory, dynamic capability view of a firm, and neo-institutional theory in CSR research. Based on association of these three theories, this study introduces two new factors (dynamic capability and regional culture) to have a better framework for CSR adoption. Second, this study contributes to empirical literature of CSR in the context of China. Extant Chinese companies lack recognition of the importance of CSR practices adoption. This study built a framework and may help companies to design resource allocation strategies and evaluate future CSR and management practices in an early stage.

Keywords: China, corporate social responsibility, CSR adoption, dynamic capability, regional culture

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Authors: Qianxi Lv, Junying Liang

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Among the various modes of interpreting, simultaneous interpreting (SI) is regarded as a ‘complex’ and ‘extreme condition’ of cognitive tasks while consecutive interpreters (CI) do not have to share processing capacity between tasks. Given that SI exerts great cognitive demand, it makes sense to posit that the output of SI may be more compromised than that of CI in the linguistic features. The bulk of the research has stressed the varying cognitive demand and processes involved in different modes of interpreting; however, related empirical research is sparse. In keeping with our interest in investigating the quantitative linguistic factors discriminating between SI and CI, the current study seeks to examine the potential lexical simplification, syntactic complexity and sequential organization mechanism with a self-made inter-model corpus of transcribed simultaneous and consecutive interpretation, translated speech and original speech texts with a total running word of 321960. The lexical features are extracted in terms of the lexical density, list head coverage, hapax legomena, and type-token ratio, as well as core vocabulary percentage. Dependency distance, an index for syntactic complexity and reflective of processing demand is employed. Frequency motif is a non-grammatically-bound sequential unit and is also used to visualize the local function distribution of interpreting the output. While SI is generally regarded as multitasking with high cognitive load, our findings evidently show that CI may impose heavier or taxing cognitive resource differently and hence yields more lexically and syntactically simplified output. In addition, the sequential features manifest that SI and CI organize the sequences from the source text in different ways into the output, to minimize the cognitive load respectively. We reasoned the results in the framework that cognitive demand is exerted both on maintaining and coordinating component of Working Memory. On the one hand, the information maintained in CI is inherently larger in volume compared to SI. On the other hand, time constraints directly influence the sentence reformulation process. The temporal pressure from the input in SI makes the interpreters only keep a small chunk of information in the focus of attention. Thus, SI interpreters usually produce the output by largely retaining the source structure so as to relieve the information from the working memory immediately after formulated in the target language. Conversely, CI interpreters receive at least a few sentences before reformulation, when they are more self-paced. CI interpreters may thus tend to retain and generate the information in a way to lessen the demand. In other words, interpreters cope with the high demand in the reformulation phase of CI by generating output with densely distributed function words, more content words of higher frequency values and fewer variations, simpler structures and more frequently used language sequences. We consequently propose a revised effort model based on the result for a better illustration of cognitive demand during both interpreting types.

Keywords: cognitive demand, corpus-based, dependency distance, frequency motif, interpreting types, lexical simplification, sequential units distribution, syntactic complexity

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Authors: Ram Sharma, Esha Chatterjee, Santosh Kumar Guru, Kunal Nepali

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A tractable anti-lung cancer agent was identified via the installation of a Ring C expanded synthetic analogue of the alkaloid vasicinone [7,8,9,10-tetrahydroazepino[2,1-b] quinazolin-12(6H)-one (TAZQ)] as a surface recognition part in the HDAC inhibitory three-component model. Noteworthy to mention that the candidature of TAZQ was deemed suitable for accommodation in HDAC inhibitory pharmacophore as per the results of the fragment recruitment process conducted by our laboratory. TAZQ was pinpointed through the fragment screening program as a synthetically flexible fragment endowed with some moderate cell growth inhibitory activity against the lung cancer cell lines, and it was anticipated that the use of the aforementioned fragment to generate hydroxamic acid functionality (zinc-binding motif) bearing HDAC inhibitors would boost the antitumor efficacy of TAZQ. Consistent with our aim of applying epigenetic targets to the treatment of lung cancer, a strikingly potent anti-lung cancer scaffold (compound 6) was pinpointed through a series of in-vitro experiments. Notably, the compounds manifested a magnificent activity profile against KRAS and EGFR mutant lung cancer cell lines (IC50 = 0.80 - 0.96 µM), and the effects were found to be mediated through preferential HDAC6 inhibition (IC50 = 12.9 nM). In addition to HDAC6 inhibition, the compounds also elicited HDAC1 and HDAC3 inhibitory activity with an IC50 value of 49.9 nM and 68.5 nM, respectively. The HDAC inhibitory ability of compound 6 was also confirmed from the results of the western blot experiment that revealed its potential to decrease the expression levels of HDAC isoforms (HDAC1, HDAC3, and HDAC6). Noteworthy to mention that complete downregulation of the HDAC6 isoform was exerted by compound 6 at 0.5 and 1 µM. Moreover, in another western blot experiment, treatment with hydroxamic acid 6 led to upregulation of H3 acK9 and α-Tubulin acK40 levels, ascertaining its inhibitory activity toward both the class I HDACs and Class II B HDACs. The results of other assays were also encouraging as treatment with compound 6 led to the suppression of the colony formation ability of A549 cells, induction of apoptosis, and increase in autophagic flux. In silico studies led us to rationalize the results of the experimental assay, and some key interactions of compound 6 with the amino acid residues of HDAC isoforms were identified. In light of the impressive activity spectrum of compound 6, a pH-responsive nanocarrier (hyaluronic acid-compound 6 nanoparticles) was prepared. The dialysis bag approach was used for the assessment of the nanoparticles under both normal and acidic circumstances, and the pH-sensitive nature of hyaluronic acid-compound 6 nanoparticles was confirmed. Delightfully, the nanoformulation was devoid of cytotoxicity against the L929 mouse fibroblast cells (normal settings) and exhibited selective cytotoxicity towards the A549 lung cancer cell lines. In a nutshell, compound 6 appears to be a promising adduct, and a detailed investigation of this compound might yield a therapeutic for the treatment of lung cancer.

Keywords: HDAC inhibitors, lung cancer, scaffold, hyaluronic acid, nanoparticles

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Authors: Laura N. Bolivar T.

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The tourism importance for regional development is mainly highlighted by the collaborative, cooperating and competitive relationships of the involved agents. The fostering of associativity processes, in particular, the cluster approach emphasizes the beneficial outcomes from the concentration of enterprises, where innovation and entrepreneurship flourish and shape the dynamics for tourism empowerment. Considering the department of Huila, it is located in the south-west of Colombia and holds the biggest coffee production in the country, although it barely contributes to the national GDP. Hence, its economic development strategy is looking for more dynamism and Huila could be consolidated as a leading destination for cultural, ecological and heritage tourism, if at least the public policy making processes for the tourism management of La Tatacoa Desert, San Agustin Park and Bambuco’s National Festival, were implemented in a more efficient manner. In this order of ideas, this study attempts to address the potential restrictions and beneficial factors for the consolidation of the tourism sector of Huila-Colombia as a cluster and how could it impact its regional development. Therefore, a set of theoretical frameworks such as the Tourism Routes Approach, the Tourism Breeding Environment, the Community-based Tourism Method, among others, but also a collection of international experiences describing tourism clustering processes and most outstanding problematics, is analyzed to draw up learning points, structure of proceedings and success-driven factors to be contrasted with the local characteristics in Huila, as the region under study. This characterization involves primary and secondary information collection methods and comprises the South American and Colombian context together with the identification of involved actors and their roles, main interactions among them, major tourism products and their infrastructure, the visitors’ perspective on the situation and a recap of the related needs and benefits regarding the host community. Considering the umbrella concepts, the theoretical and the empirical approaches, and their comparison with the local specificities of the tourism sector in Huila, an array of shortcomings is analytically constructed and a series of guidelines are proposed as a way to overcome them and simultaneously, raise economic development and positively impact Huila’s well-being. This non-exhaustive bundle of guidelines is focused on fostering cooperating linkages in the actors’ network, dealing with Information and Communication Technologies’ innovations, reinforcing the supporting infrastructure, promoting the destinations considering the less known places as well, designing an information system enabling the tourism network to assess the situation based on reliable data, increasing competitiveness, developing participative public policy-making processes and empowering the host community about the touristic richness. According to this, cluster dynamics would drive the tourism sector to meet articulation and joint effort, then involved agents and local particularities would be adequately assisted to cope with the current changing environment of globalization and competition.

Keywords: innovative strategy, local development, network of tourism actors, tourism cluster

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Authors: Amandeep Kaur

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Farming is one of the most influential traditions which started around 10000 BC and has revolutionized human civilization. It is believed that farming originated at a separate location. Thus it has a great impact on local culture, which in turn gave rise to diversified farming practices. Farming activities are influenced by the culture of a particular region or community as local people have their own knowledge and belief system about soil and crops. With the inception of the Green Revolution, 'a high tech machinery model' in Punjab, various traditional farming methods and techniques changed. The present research concentrates on the local knowledge of farmers and local farming systems from an anthropological perspective. In view of the prevailing agrarian crisis in Punjab, this research is focused on farmer’s experiences and their perception regarding farming practices. Thus an attempt has to be made to focus on the local knowledge, perception, and experience of farmers for eco-friendly and sustainable agricultural development. Farmers voices are used to understand the relationship between farming practices and socio-cultural life of farmers in Faridkot district, Punjab. The research aims to comprehend the nature of changes taking place in the socio-cultural life of people with the development of capitalism and agricultural modernization. The study is based on qualitative methods of ethnography in Sarawan village of Faridkot District. Inferences drawn from in-depth case studies collected from 60 agricultural households lead to the concept of the process of diffusion, innovation, and adoption of farming technology, a variety of crops and the dissemination of agricultural skills regarding various cultural farming practices. The data is based on random sampling; the respondents were both males and females above the age of 18 years to attain a holistic understanding across the generations. A Quasi-participant observation related to lifestyle, the standard of living, and various farming practices performed by them were done. Narratives derived from the fieldwork depicts that farmers usually oppose the restrictions imposed by the government on certain farming practices, especially ban on stubble burning. This paper presents the narratives of farmers regarding the dissemination of awareness about the use of new varieties of seeds, technology, fertilizers, pesticides, etc. The study reveals that farming systems have developed in ways reflecting the activities and choices of farmers influenced by environmental, socio-cultural, economic, and political situations. Modern farming practices have forced small farmers into debt as farmers feel pride in buying new machinery. It has also led to the loss of work culture and excessive use of drugs among youngsters. Even laborers did not want to work on the land with cultivating farmers primarily for social and political reasons. Due to lack of proper marketing of crops, there is a continuum of the wheat-rice cycle instead of crop diversification in Punjab. Change in the farming system also affects the social structure of society. Agricultural modernization has commercialized the socio-cultural relations in Punjab and is slowly urbanizing the rural landscape revolutionizing the traditional social relations to capitalistic relations.

Keywords: agricultural modernization, capitalism, farming practices, narratives

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Authors: Innocent Atuhe, Babra Nalwadda, Grace Mulyowa, Annabella Habinka Ejiri

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Background: Atopic Dermatitis (AD) is one of the most prevalent and growing chronic inflammatory skin diseases in African prisons. AD care is limited in African due to a lack of information about the disease amongst primary care workers, limited access to dermatologists, lack of proper training of healthcare workers, and shortage of appropriate treatments. We designed and implemented the Prisons Telederma project based on the recommendations of the International Society of Atopic Dermatitis. We aimed at; i) increase awareness and understanding of teledermatology among prison health workers and ii) improve treatment outcomes of prisoners with atopic dermatitis through increased access to and utilization of consultant dermatologists through teledermatology in Uganda prisons. Approach: We used Store-and-forward Teledermatology (SAF-TD) to increase access to dermatologist-led care for prisoners and prison staff with AD. We conducted five days of training for prison health workers using an adapted WHO training guide on recognizing neglected tropical diseases through changes on the skin together with an adapted American Academy of Dermatology (AAD) Childhood AD Basic Dermatology Curriculum designed to help trainees develop a clinical approach to the evaluation and initial management of patients with AD. This training was followed by blended e-learning, webinars facilitated by consultant Dermatologists with local knowledge of medication and local practices, apps adjusted for pigmented skin, WhatsApp group discussions, and sharing pigmented skin AD pictures and treatment via zoom meetings. We hired a team of Ugandan Senior Consultant dermatologists to draft an iconographic atlas of the main dermatoses in pigmented African skin and shared this atlas with prison health staff for use as a job aid. We had planned to use MySkinSelfie mobile phone application to take and share skin pictures of prisoners with AD with Consultant Dermatologists, who would review the pictures and prescribe appropriate treatment. Unfortunately, the National Health Service withdrew the app from the market due to technical issues. We monitored and evaluated treatment outcomes using the Patient-Oriented Eczema Measure (POEM) tool. We held four advocacy meetings to persuade relevant stakeholders to increase supplies and availability of first-line AD treatments such as emollients in prison health facilities. Results: We have the very first iconographic atlas of the main dermatoses in pigmented African skin. We increased; i) the proportion of prison health staff with adequate knowledge of AD and teledermatology from 20% to 80%; ii) the proportion of prisoners with AD reporting improvement in disease severity (POEM scores) from 25% to 35% in one year; iii) increased proportion of prisoners with AD seen by consultant dermatologist through teledermatology from 0% to 20% in one year and iv)Increased the availability of AD recommended treatments in prisons health facilities from 5% to 10% in one year. Our study contributes to the use, evaluation, and verification of the use of teledermatology to increase access to specialist dermatology services to the most hard to reach areas and vulnerable populations such as that of prisoners.

Keywords: teledermatology, prisoners, reaching, un-reachable

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Authors: Bitewulign Mekonnen

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Context: This scientific paper focuses on the use of near-infrared (NIR) spectroscopy to determine glucose concentration in aqueous solutions accurately and rapidly. The study compares six different machine learning methods for predicting glucose concentration and also explores the development of a deep learning model for classifying NIR spectra. The objective is to optimize the detection model and improve the accuracy of glucose prediction. This research is important because it provides a comprehensive analysis of various machine-learning techniques for estimating aqueous glucose concentrations. Research Aim: The aim of this study is to compare and evaluate different machine-learning methods for predicting glucose concentration from NIR spectra. Additionally, the study aims to develop and assess a deep-learning model for classifying NIR spectra. Methodology: The research methodology involves the use of machine learning and deep learning techniques. Six machine learning regression models, including support vector machine regression, partial least squares regression, extra tree regression, random forest regression, extreme gradient boosting, and principal component analysis-neural network, are employed to predict glucose concentration. The NIR spectra data is randomly divided into train and test sets, and the process is repeated ten times to increase generalization ability. In addition, a convolutional neural network is developed for classifying NIR spectra. Findings: The study reveals that the SVMR, ETR, and PCA-NN models exhibit excellent performance in predicting glucose concentration, with correlation coefficients (R) > 0.99 and determination coefficients (R²)> 0.985. The deep learning model achieves high macro-averaging scores for precision, recall, and F1-measure. These findings demonstrate the effectiveness of machine learning and deep learning methods in optimizing the detection model and improving glucose prediction accuracy. Theoretical Importance: This research contributes to the field by providing a comprehensive analysis of various machine-learning techniques for estimating glucose concentrations from NIR spectra. It also explores the use of deep learning for the classification of indistinguishable NIR spectra. The findings highlight the potential of machine learning and deep learning in enhancing the prediction accuracy of glucose-relevant features. Data Collection and Analysis Procedures: The NIR spectra and corresponding references for glucose concentration are measured in increments of 20 mg/dl. The data is randomly divided into train and test sets, and the models are evaluated using regression analysis and classification metrics. The performance of each model is assessed based on correlation coefficients, determination coefficients, precision, recall, and F1-measure. Question Addressed: The study addresses the question of whether machine learning and deep learning methods can optimize the detection model and improve the accuracy of glucose prediction from NIR spectra. Conclusion: The research demonstrates that machine learning and deep learning methods can effectively predict glucose concentration from NIR spectra. The SVMR, ETR, and PCA-NN models exhibit superior performance, while the deep learning model achieves high classification scores. These findings suggest that machine learning and deep learning techniques can be used to improve the prediction accuracy of glucose-relevant features. Further research is needed to explore their clinical utility in analyzing complex matrices, such as blood glucose levels.

Keywords: machine learning, signal processing, near-infrared spectroscopy, support vector machine, neural network

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Authors: Feyi Olorunshola

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Over the last few years, the senior travel market has been noted for its potential in the wider tourism industry. The tourism sector includes the hotel and hospitality, travel, transportation, and several other subdivisions to make it economically viable. In particular, the hotel attracts a substantial part of the expenditure in tourism activities as when people plan to travel, suitable accommodation for relaxation, dining, entertainment and so on is paramount to their decision-making. The global retail value of the hotel as of 2018 was significant for tourism. But, despite indications of the hotel to the tourism industry at large, very few empirical studies are available to establish how this sector can leverage on the senior demographic to achieve competitive advantage. Predominantly, studies on the mature market have focused on destination tourism, with a limited investigation on the hotel which makes a significant contribution to tourism. Also, several scholarly studies have demonstrated the importance of the senior travel market to the hotel, yet there is very little empirical research in the field which has explored the driving factors that will become the accepted new normal for this niche segment post-pandemic. Giving that the hotel already operates in a highly saturated business environment, and on top of this pre-existing challenge, the ongoing global health outbreak has further put the sector in a vulnerable position. Therefore, the hotel especially the full-service luxury category must evolve rapidly for it to survive in the current business environment. The hotel can no longer rely on corporate travelers to generate higher revenue since the unprecedented wake of the pandemic in 2020 many organizations have invented a different approach of conducting their businesses online, therefore, the hotel needs to anticipate a significant drop in business travellers. However, the rooms and the rest of the facilities must be occupied to keep their business operating. The way forward for the hotel lies in the leisure sector, but the question now is to focus on the potential demographics of travelers, in this case, the seniors who have been repeatedly recognized as the lucrative market because of increase discretionary income, availability of time and the global population trends. To achieve the study objectives, a mixed-method approach will be utilized drawing on both qualitative (netnography) and quantitative (survey) methods, cognitive and decision-making theories (means-end chain) and competitive theories to identify the salient drivers explaining senior hotel choice and its influence on their decision-making. The target population are repeated seniors’ age 65 years and over who are UK resident, and from the top tourist market to the UK (USA, Germany, and France). Structural equation modelling will be employed to analyze the datasets. The theoretical implication is the development of new concepts using a robust research design, and as well as advancing existing framework to hotel study. Practically, it will provide the hotel management with the latest information to design a competitive marketing strategy and activities to target the mature market post-pandemic and over a long period.

Keywords: competitive advantage, covid-19, full-service hotel, five-star, luxury hotels

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Authors: Ruth Hegarty, Noel Connaughton

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Sustainability reporting has become a priority for many global multinational companies. This is associated with ever-increasing expectations from key stakeholders for companies to be transparent about their strategies, activities and management with regard to sustainability issues. The Global Reporting Initiative (GRI) encourages reporters to only provide information on the issues that are really critical in order to achieve the organisation’s goals for sustainability and manage its impact on environment and society. A key challenge for most reporting organisations is how to identify relevant issues for sustainability reporting and prioritise those material issues in accordance with company and stakeholder needs. A recent study indicates that most of the largest companies listed on the world’s stock exchanges are failing to provide data on key sustainability indicators such as employee turnover, energy, greenhouse gas emissions (GHGs), injury rate, pay equity, waste and water. This paper takes an indepth look at the approaches used by a select number of international sustainability leader corporates to identify key sustainability issues. The research methodology involves performing a detailed analysis of the sustainability report content of up to 50 companies listed on the 2014 Dow Jones Sustainability Indices (DJSI). The most recent sustainability report content found on the GRI Sustainability Disclosure Database is then compared with 91 GRI Specific Standard Disclosures and a small number of GRI Standard Disclosures. Preliminary research indicates significant gaps in the information disclosed in corporate sustainability reports versus the indicator content specified in the GRI Content Index. The following outlines some of the key findings to date: Most companies made a partial disclosure with regard to the Economic indicators of climate change risks and infrastructure investments, but did not focus on the associated negative impacts. The top Environmental indicators disclosed were energy consumption and reductions, GHG emissions, water withdrawals, waste and compliance. The lowest rates of indicator disclosure included biodiversity, water discharge, mitigation of environmental impacts of products and services, transport, environmental investments, screening of new suppliers and supply chain impacts. The top Social indicators disclosed were new employee hires, rates of injury, freedom of association in operations, child labour and forced labour. Lesser disclosure rates were reported for employee training, composition of governance bodies and employees, political contributions, corruption and fines for non-compliance. The reporting on most other Social indicators was found to be poor. In addition, most companies give only a brief explanation on how material issues are defined, identified and ranked. Data on the identification of key stakeholders and the degree and nature of engagement for determining issues and their weightings is also lacking. Generally, little to no data is provided on the algorithms used to score an issue. Research indicates that most companies lack a rigorous and thorough methodology to systematically determine the material issues of sustainability reporting in accordance with company and stakeholder needs.

Keywords: identification of key stakeholders, material issues, sustainability reporting, transparency

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Authors: Sunil Chandra, Himanshu Rawat, Vikas Gusain, Triparna Barman

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Forest fires are a recurrent phenomenon in the Himalayan region owing to the presence of vulnerable forest types, topographical gradients, climatic weather conditions, and anthropogenic pressure. The present study focuses on the identification of forest fire-affected areas in a small part of the West Himalayan region using a differential normalized burnt ratio method and spectral unmixing methods. The study area has a rugged terrain with the presence of sub-tropical pine forest, montane temperate forest, and sub-alpine forest and scrub. The major reason for fires in this region is anthropogenic in nature, with the practice of human-induced fires for getting fresh leaves, scaring wild animals to protect agricultural crops, grazing practices within reserved forests, and igniting fires for cooking and other reasons. The fires caused by the above reasons affect a large area on the ground, necessitating its precise estimation for further management and policy making. In the present study, two approaches have been used for carrying out a burnt area analysis. The first approach followed for burnt area analysis uses a differenced normalized burnt ratio (dNBR) index approach that uses the burnt ratio values generated using the Short-Wave Infrared (SWIR) band and Near Infrared (NIR) bands of the Sentinel-2 image. The results of the dNBR have been compared with the outputs of the spectral mixing methods. It has been found that the dNBR is able to create good results in fire-affected areas having homogenous forest stratum and with slope degree <5 degrees. However, in a rugged terrain where the landscape is largely influenced by the topographical variations, vegetation types, tree density, the results may be largely influenced by the effects of topography, complexity in tree composition, fuel load composition, and soil moisture. Hence, such variations in the factors influencing burnt area assessment may not be effectively carried out using a dNBR approach which is commonly followed for burnt area assessment over a large area. Hence, another approach that has been attempted in the present study utilizes a spectral mixing method where the individual pixel is tested before assigning an information class to it. The method uses a neural network approach utilizing Sentinel-2 bands. The training and testing data are generated from the Sentinel-2 data and the national field inventory, which is further used for generating outputs using ML tools. The analysis of the results indicates that the fire-affected regions and their severity can be better estimated using spectral unmixing methods, which have the capability to resolve the noise in the data and can classify the individual pixel to the precise burnt/unburnt class.

Keywords: categorical data, log linear modeling, neural network, shifting cultivation

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