Search results for: objective assessment

Authors: Lan Cheng, Harry Qin, Yang Wang

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Background: COVID-19 has induced the largest digital learning experiment in history. There is also emerging research evidence that students have paid a high cost of learning loss from virtual learning. University-wide survey results demonstrate that digital learning remains difficult for students who struggle with learning challenges, isolation, or a lack of resources. Large-scale efforts are therefore increasingly utilized for digital education. To better prepare students in higher education for this grand scientific and technological transformation, STEM education has been prioritized and promoted as a strategic imperative in the ongoing curriculum reform essential for unfinished learning needs and whole-person development. Building upon five key elements identified in the STEM education literature: Problem-based Learning, Community and Belonging, Technology Skills, Personalization of Learning, Connection to the External Community, this case study explores the potential of pedagogical innovation that integrates computational and experimental methodologies to support, enrich, and navigate STEM education. Objectives: The goal of this case study is to create a high-fidelity prototype design for STEM education with knowledge transfer technology that contains a Cooperative Multi-Agent System (CMAS), which has the objectives of (1) conduct assessment to reveal a virtual learning mechanism and establish strategies to facilitate scientific learning engagement, accessibility, and connection within and beyond university setting, (2) explore and validate an interactional co-creation approach embedded in project-based learning activities under the STEM learning context, which is being transformed by both digital technology and student behavior change,(3) formulate and implement the STEM-oriented campaign to guide learning network mapping, mitigate the loss of learning, enhance the learning experience, scale-up inclusive participation. Methods: This study applied a case study strategy and a methodology informed by Social Network Analysis Theory within a cross-disciplinary communication paradigm (students, peers, educators). Knowledge transfer technology is introduced to address learning challenges and to increase the efficiency of Reinforcement Learning (RL) algorithms. A co-creation learning framework was identified and investigated in a context-specific way with a learning analytic tool designed in this study. Findings: The result shows that (1) CMAS-empowered learning support reduced students’ confusion, difficulties, and gaps during problem-solving scenarios while increasing learner capacity empowerment, (2) The co-creation learning phenomenon have examined through the lens of the campaign and reveals that an interactive virtual learning environment fosters students to navigate scientific challenge independently and collaboratively, (3) The deliverables brought from the STEM educational campaign provide a methodological framework both within the context of the curriculum design and external community engagement application. Conclusion: This study brings a holistic and coherent pedagogy to cultivates students’ interest in STEM and develop them a knowledge base to integrate and apply knowledge across different STEM disciplines. Through the co-designing and cross-disciplinary educational content and campaign promotion, findings suggest factors to empower evidence-based learning practice while also piloting and tracking the impact of the scholastic value of co-creation under the dynamic learning environment. The data nested under the knowledge transfer technology situates learners’ scientific journey and could pave the way for theoretical advancement and broader scientific enervators within larger datasets, projects, and communities.

Keywords: co-creation, cross-disciplinary, knowledge transfer, STEM education, social network analysis

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Authors: Wenfan Yan, Yumei Han

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Objectives: Educational inequality persists between China's ethnic minority regions and the mainland. The key to rectifying this disparity lies in enhancing the quality of educators. This paper delves into the Chinese government's innovative policy, "Group Educators Supporting Tibet" (GEST), designed to bridge the shortage of high-quality teachers in Tibet, a representative underprivileged ethnic minority area. GEST aims to foster collective action by networking provincial expert educators with Tibetan counterparts and collaborating between supporting provincial educational entities and Tibetan education entities. Theoretical Framework: The unequal distribution of social capital contributes significantly to the educational gap between ethnic minority areas and other regions in China. Within the framework of social network theory, motivated GEST educators take action to foster resources and relationships. This study captures grassroots perspectives to outline how social networking contributes to the policy objective of enhancing Tibetan teachers' quality and eradicating educational injustice. Methodology: A sequential mixed-methods approach was adopted to scrutinize policy impacts from the vantage point of social networking. Quantitative research involved surveys for GEST and Tibetan teachers, exploring demographics, perceptions of policy significance, motivations, actions, and networking habits. Qualitative research included focus group interviews with GEST educators, local teachers, and students from program schools. The findings were meticulously analyzed to provide comprehensive insights into stakeholders' experiences and the impacts of the GEST policy. Key Findings: The policy empowers individuals to impact Tibetan education significantly. Motivated GEST educators with prior educational support experiences contribute to its success. Supported by a collective -school, city, province, and government- the new social structure fosters higher efficiency. GEST's approach surpasses conventional methods. The individual, backed by educators, realizes the potential of transformative class design. Collective activities -pedagogy research, teaching, mentoring, training, and partnerships- equip Tibetan teachers, enhancing educational quality and equity. This collaborative effort establishes a robust foundation for the policy's success, emphasizing the collective impact on Tibetan education. Contributions: This study contributes to international policy studies focused on educational equity through collective teacher action. Using a mixed-methods approach and guided by social networking theory, it accentuates stakeholders' perspectives, elucidating the genuine impacts of the GEST policy. The study underscores the advancement of social networking, the reinforcement of local teacher quality, and the transformative potential of cultivating a more equitable and adept teaching workforce in Tibet. Limitations of the Study and Suggestions for Future Research Directions: While the study emphasizes the positive impacts of motivated GEST educators, there might be aspects or challenges not fully explored. A more comprehensive understanding of potential drawbacks or obstacles would provide a more balanced view. For future studies, investigating the long-term impact of the GEST policy on educational quality could provide insights into the sustainability of the improvements observed. Also, understanding the perspectives of Tibetan teachers who may not have directly benefited from GEST could reveal potential disparities in policy implementation.

Keywords: teacher development, social networking, teacher quality, mixed research method

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Authors: Alberto Alfano, Sergio D’ambrosio, Darshankumar Parecha, Donatella Cimini, Chiara Schiraldi.

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The main objective of this study regards the setup of an efficient small-scale platform for the conversion of local renewable waste materials, such as whey, into added-value products, thereby reducing environmental impact and costs deriving from the disposal of processing waste products. The buffalo milk whey derived from the cheese-making process, called second cheese whey, is the main by-product of the dairy industry. Whey is the main and most polluting by-product obtained from cheese manufacturing consisting of lactose, lactic acid, proteins, and salts, making whey an added-value product. In Italy, and in particular, in the Campania region, soft cheese production needs a large volume of liquid waste, especially during late spring and summer. This project is part of a circular economy perspective focused on the conversion of potentially polluting and difficult to purify waste into a resource to be exploited, and it embodies the concept of the three “R”: reduce, recycle, and reuse. Special focus was paid to the production of health-promoting biomolecules and biopolymers, which may be exploited in different segments of the food and pharmaceutical industries. These biomolecules may be recovered through appropriate processes and reused in an attempt to obtain added value products. So, ultrafiltration and nanofiltration processes were performed to fractionate bioactive components starting from buffalo milk whey. In this direction, the present study focused on the implementation of a downstream process that converts waste generated from food and food processing industries into added value products with potential applications. Owing to innovative downstream and biotechnological processes, rather than a waste product may be considered a resource to obtain high added value products, such as food supplements (probiotics), cosmeceuticals, biopolymers, and recyclable purified water. Besides targeting gastrointestinal disorders, probiotics such as Lactobacilli have been reported to improve immunomodulation and protection of the host against infections caused by viral and bacterial pathogens. Interestingly, also inactivated microbial (probiotic) cells and their metabolic products, indicated as parabiotic and postbiotics, respectively, have a crucial role and act as mediators in the modulation of the host’s immune function. To boost the production of biomass (both viable and/or heat inactivated cells) and/or the synthesis of growth-related postbiotics, such as EPS, efficient and sustainable fermentation processes are necessary. Based on a “zero-waste” approach, wastes generated from local industries can be recovered and recycled to develop sustainable biotechnological processes to obtain probiotics as well as post and parabiotic, to be tested as bioactive compounds against gastrointestinal disorders. The results have shown it was possible to recover an ultrafiltration retentate with suitable characteristics to be used in skin dehydration, to perform films (i.e., packaging for food industries), or as a wound repair agent and a nanofiltration retentate to recover lactic acid and carbon sources (e.g., lactose, glucose..) used for microbial cultivation. On the side, the last goal is to obtain purified water that can be reused throughout the process. In fact, water reclamation and reuse provide a unique and viable opportunity to augment traditional water supplies, a key issue nowadays.

Keywords: biotech process, downstream process, probiotic growth, from waste to product, buffalo whey

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Authors: Daniela Salih Khidir, Mohamed G. Al Kuwari, Mercia V. Walt, Izzeldin J. Ibrahim

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Background: University-based physical activity interventions aim to establish durable social patterns during the transition to adulthood. This study is a comprehensive evaluation of a 3-year intervention-based program to increase the culture of physical activity (PA) routine in Qatar campuses community, using a holistic approach. Methodology: General assessment methods: formative evaluation-SIH Campuses logic model design, stakeholders’ identification; process evaluation-members’ step counts analyze and qualitative Appreciative Inquiry session (4-D model); daily steps categorized as: ≤5,000, inactive; 5,000-7,499 low active; ≥7,500, physically active; outcome evaluation - records 3 years interventions. Holistic PA interventions methods: walking interventions - pedometers distributions and walking competitions for students and staff; educational interventions - in campuses implementation of bilingual educational materials, lectures, video related to PA in prevention of non-communicable diseases (NCD); articles published online; monthly emails and sms notifications for pedometer use; mass media campaign - radio advertising, yearly pre/post press releases; community stakeholders interventions-biyearly planning/reporting/achievements rewarding/ qualitative meetings; continuous follow-up communication, biweekly steps reports. Findings: Results formative evaluation - SIH in Campuses logic model identified the need of PA awareness and education within universities, resources, activities, health benefits, program continuity. Results process evaluation: walking interventions: Phase 1: 5 universities recruited, 2352 members, 3 months competition; Phase 2: 6 new universities recruited, 1328 members in addition, 4 months competition; Phase 3: 4 new universities recruited in addition, 1210 members, 6 months competition. Results phase 1 and 2: 1,299 members eligible for analyzes: 800 females (62%), 499 males (38%); 86% non-Qataris, 14% Qatari nationals, daily step count 5,681 steps, age groups 18–24 (n=841; 68%) students, 25–64; (n=458; 35.3%) staff; 38% - low active, 37% physically active and 25% inactive. The AI main themes engaging stakeholders: awareness/education - 5 points (100%); competition, multi levels of involvement in SIH, community-based program/motivation - 4 points each (80%). The AI points represent themes’ repetition within stakeholders’ discussions. Results education interventions: 2 videos implementation, 35 000 educational materials, 3 online articles, 11 walking benefits lectures, 40 emails and sms notifications. Results community stakeholders’ interventions: 6 stakeholders meetings, 3 rewarding gatherings, 1 focus meeting, 40 individual reports, 18 overall reports. Results mass media campaign: 1 radio campaign, 7 press releases, 52 campuses newsletters. Results outcome evaluation: overall 2013-2016, the study used: 1 logic model, 3 PA holistic interventions, partnerships 15 universities, registered 4890 students and staff (aged 18-64 years), engaged 30 campuses stakeholders and 14 internal stakeholders; Total registered population: 61.5% female (2999), 38.5% male (1891), 20.2% (988) Qatari nationals, 79.8% (3902) non-Qataris, 55.5% (2710) students aged 18 – 25 years, 44.5% (2180) staff aged 26 - 64 years. Overall campaign 1,558 members eligible for analyzes: daily step count 7,923; 37% - low active, 43% physically active and 20% inactive. Conclusion: The study outcomes confirm program effectiveness and engagement of young campuses community, specifically female, in PA. The authors recommend implementations of 'holistic PA intervention program approach in Qatar' aiming to impact the community at national level for PA guidelines achievement in support of NCD prevention.

Keywords: campuses, evaluation, Qatar, step-count

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Authors: Zeinab Zaremohzzabieh, Syasya Firzana Azmi, Haslinda Abdullah, Soh Kim Geok, Aini Azeqa Ma'rof, Hayrol Azril Mohammed Shaffril

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The escalating prevalence of doping in sports, casting a shadow over both high-performance and recreational settings, has emerged as a formidable concern, particularly within the realm of young athletes. Doping, characterized by the surreptitious use of prohibited substances to gain a competitive edge, underscores the pressing need for comprehensive and efficacious preventive measures. This study aims to address a crucial void in current research by unraveling the motivations that drive clean adolescent athletes to steadfastly abstain from performance-enhancing substances. In navigating this intricate landscape, the study adopts a positive psychology perspective, investigating into the conditions and processes that contribute to the holistic well-being of individuals and communities. At the heart of this exploration lies the application of the PERMA model, a comprehensive positive psychology framework encapsulating positive emotion, engagement, relationships, meaning, and accomplishments. This model functions as a distinctive lens, dissecting intervention results to offer nuanced insights into the complex dynamics of clean sport behavior. The research is poised to usher in a paradigm shift from conventional anti-doping strategies, predominantly fixated on identifying deficits, towards an innovative approach firmly rooted in positive psychology. The objective of this study is to evaluate the efficacy of a positive education intervention program tailored to promote clean sport behavior among Malaysian adolescent athletes. Representing unexplored terrain within the landscape of anti-doping efforts, this initiative endeavors to reshape the focus from deficiencies to strengths. The meticulously crafted pilot study engages thirty adolescent athletes, divided into a control group of 15 and an experimental group of 15. The pilot study serves as the crucible to assess the effectiveness of the prepared intervention package, providing indispensable insights that will meticulously guide the finalization of an all-encompassing intervention program for the main study. The main study adopts a pioneering two-arm randomized control trial methodology, actively involving adolescent athletes from diverse Malaysian high schools. This approach aims to address critical lacunae in anti-doping strategies, specifically calibrated to resonate with the unique context of Malaysian schools. The study, cognizant of the imperative to develop preventive measures harmonizing with the cultural and educational milieu of Malaysian adolescent athletes, aspires to cultivate a culture of clean sport. In conclusion, this research aspires to contribute unprecedented insights into the efficacy of positive education interventions firmly rooted in the PERMA model. By unraveling the intricacies of clean sport behavior, particularly within the context of Malaysian adolescent athletes, the study seeks to introduce transformative preventive methods. The adoption of positive psychology as an avant-garde anti-doping tool represents an innovative and promising approach, bridging a conspicuous gap in scholarly research and offering potential panaceas for the sporting community. As this study unfurls its chapters, it carries the promise not only to enrich our understanding of clean sport behavior but also to pave the way for positive metamorphosis within the realm of adolescent sports in Malaysia.

Keywords: positive education interventions, a pilot study, clean sport behavior, adolescent athletes, Malaysia

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Authors: Fani Sakellariadou

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The Blue Economy includes all marine-based and marine-related activities. They correspond to established, emerging as well as unborn ocean-based industries. Seabed mining is an emerging marine-based activity; its operations depend particularly on cutting-edge science and technology. The 21st century will face a crisis in resources as a consequence of the world’s population growth and the rising standard of living. The natural capital stored in the global ocean is decisive for it to provide a wide range of sustainable ecosystem services. Seabed mineral deposits were identified as having a high potential for critical elements and base metals. They have a crucial role in the fast evolution of green technologies. The major categories of marine mineral deposits are deep-sea deposits, including cobalt-rich ferromanganese crusts, polymetallic nodules, phosphorites, and deep-sea muds, as well as shallow-water deposits including marine placers. Seabed mining operations may take place within continental shelf areas of nation-states. In international waters, the International Seabed Authority (ISA) has entered into 15-year contracts for deep-seabed exploration with 21 contractors. These contracts are for polymetallic nodules (18 contracts), polymetallic sulfides (7 contracts), and cobalt-rich ferromanganese crusts (5 contracts). Exploration areas are located in the Clarion-Clipperton Zone, the Indian Ocean, the Mid Atlantic Ridge, the South Atlantic Ocean, and the Pacific Ocean. Potential environmental impacts of deep-sea mining include habitat alteration, sediment disturbance, plume discharge, toxic compounds release, light and noise generation, and air emissions. They could cause burial and smothering of benthic species, health problems for marine species, biodiversity loss, reduced photosynthetic mechanism, behavior change and masking acoustic communication for mammals and fish, heavy metals bioaccumulation up the food web, decrease of the content of dissolved oxygen, and climate change. An important concern related to deep-sea mining is our knowledge gap regarding deep-sea bio-communities. The ecological consequences that will be caused in the remote, unique, fragile, and little-understood deep-sea ecosystems and inhabitants are still largely unknown. The blue economy conceptualizes oceans as developing spaces supplying socio-economic benefits for current and future generations but also protecting, supporting, and restoring biodiversity and ecological productivity. In that sense, people should apply holistic management and make an assessment of marine mining impacts on ecosystem services, including the categories of provisioning, regulating, supporting, and cultural services. The variety in environmental parameters, the range in sea depth, the diversity in the characteristics of marine species, and the possible proximity to other existing maritime industries cause a span of marine mining impact the ability of ecosystems to support people and nature. In conclusion, the use of the untapped potential of the global ocean demands a liable and sustainable attitude. Moreover, there is a need to change our lifestyle and move beyond the philosophy of single-use. Living in a throw-away society based on a linear approach to resource consumption, humans are putting too much pressure on the natural environment. Applying modern, sustainable and eco-friendly approaches according to the principle of circular economy, a substantial amount of natural resource savings will be achieved. Acknowledgement: This work is part of the MAREE project, financially supported by the Division VI of IUPAC. This work has been partly supported by the University of Piraeus Research Center.

Keywords: blue economy, deep-sea mining, ecosystem services, environmental impacts

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Authors: Victoria L. Chester, Usha Kuruganti

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The forest industry is a major economic sector of Canada and also one of the most dangerous industries for workers. The use of mechanized mobile forestry harvesting machines has successfully reduced the incidence of injuries in forest workers related to manual labor. However, these machines have also created additional concerns, including a high machine operation learning curve, increased the length of the workday, repetitive strain injury, cognitive load, physical and mental fatigue, and increased postural loads due to sitting in a confined space. It is critical to obtain objective performance data for employers to develop appropriate work practices for this industry, however ergonomic field studies of this industry are lacking mainly due to the difficulties in obtaining comprehensive data while operators are cutting trees in the woods. The purpose of this study was to establish a measurement and experimental protocol to examine the effects of worker skill level and movement training speed (joystick crane speed) on harvesting performance using a forestry simulator. A custom wrist angle measurement device was developed as part of the study to monitor Euler angles during operation of the simulator. The device of the system consisted of two accelerometers, a Bluetooth module, three 3V coin cells, a microcontroller, a voltage regulator and an application software. Harvesting performance and crane data was provided by the simulator software and included tree to frame collisions, crane to tree collisions, boom tip distance, number of trees cut, etc. A pilot study of 3 operators with various skill levels was tested to identify factors that distinguish highly skilled operators from novice or intermediate operators. Dependent variables such as reaction time, math skill, past work experience, training movement speed (e.g. joystick control speeds), harvesting experience level, muscle activity, and wrist biomechanics were measured and analyzed. A 10-channel wireless surface EMG system was used to monitor the amplitude and mean frequency of 10 upper extremity muscles during pre and postperformance on the forestry harvest stimulator. The results of the pilot study showed inconsistent changes in median frequency pre-and postoperation, but there was the increase in the activity of the flexor carpi radialis, anterior deltoid and upper trapezius of both arms. The wrist sensor results indicated that wrist supination and pronation occurred more than flexion and extension with radial-ulnar rotation demonstrating the least movement. Overall, wrist angular motion increased as the crane speed increased from slow to fast. Further data collection is needed and will help industry partners determine those factors that separate skill levels of operators, identify optimal training speeds, and determine the length of training required to bring new operators to an efficient skill level effectively. In addition to effective and employment training programs, results of this work will be used for selective employee recruitment strategies to improve employee retention after training. Further, improved training procedures and knowledge of the physical and mental demands on workers will lead to highly trained and efficient personnel, reduced risk of injury, and optimal work protocols.

Keywords: EMG, forestry, human factors, wrist biomechanics

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Authors: Loretta Ichim, Dan Popescu, Grigore Stamatescu

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The paper reports the collaboration between a top university from Romania and three companies for the implementation of a research project in a multidisciplinary domain, focusing on the impact and benefits both for the education and industry. The joint activities were developed under the Space Technology and Advanced Research Program (STAR), funded by the Romanian Space Agency (ROSA) for a university-industry partnership. The context was defined by linking the European Space Agency optional programs, with the development and promotion national research, with the educational and industrial capabilities in the aeronautics, security and related areas by increasing the collaboration between academic and industrial entities as well as by realizing high-level scientific production. The project name is Multisensory Robotic System for Aerial Monitoring of Critical Infrastructure Systems (MUROS), which was carried 2013-2016. The project included the University POLITEHNICA of Bucharest (coordinator) and three companies, which manufacture and market unmanned aerial systems. The project had as main objective the development of an integrated system for combined ground wireless sensor networks and UAV monitoring in various application scenarios for critical infrastructure surveillance. This included specific activities related to fundamental and applied research, technology transfer, prototype implementation and result dissemination. The core area of the contributions laid in distributed data processing and communication mechanisms, advanced image processing and embedded system development. Special focus is given by the paper to analyzing the impact the project implementation in the educational process, directly or indirectly, through the faculty members (professors and students) involved in the research team. Three main directions are discussed: a) enabling students to carry out internships at the partner companies, b) handling advanced topics and industry requirements at the master's level, c) experiments and concept validation for doctoral thesis. The impact of the research work (as the educational component) developed by the faculty members on the increasing performances of the companies’ products is highlighted. The collaboration between university and companies was well balanced both for contributions and results. The paper also presents the outcomes of the project which reveals the efficient collaboration between high education and industry: master thesis, doctoral thesis, conference papers, journal papers, technical documentation for technology transfer, prototype, and patent. The experience can provide useful practices of blending research and education within an academia-industry cooperation framework while the lessons learned represent a starting point in debating the new role of advanced research and development performing companies in association with higher education. This partnership, promoted at UE level, has a broad impact beyond the constrained scope of a single project and can develop into long-lasting collaboration while benefiting all stakeholders: students, universities and the surrounding knowledge-based economic and industrial ecosystem. Due to the exchange of experiences between the university (UPB) and the manufacturing company (AFT Design), a new project, SIMUL, under the Bridge Grant Program (Romanian executive agency UEFISCDI) was started (2016 – 2017). This project will continue the educational research for innovation on master and doctoral studies in MUROS thematic (collaborative multi-UAV application for flood detection).

Keywords: education process, multisensory robotic system, research and innovation project, technology transfer, university-industry partnership

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Authors: Kristina F. Wolff

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Background: In the Federal Republic of Germany, violence against women is deeply embedded in society. Germany is, as of March 2020, the most populous member state of the European Union with 83.2 million inhabitants and, although more than half of its inhabitants are women, gender equality was not certified in the Basic Law until 1957. Women have only been allowed to enter paid employment without their husband's consent since 1977 and have marital rape prosecuted only since 1997. While the lack of equality between men and women is named in the preamble of the Istanbul Convention as the cause of gender-specific, structural, traditional violence against women, Germany continues to sink on the latest Gender Equality Index. According to Police Crime Statistics (PCS), women are significantly more often victims of lethal violence, emanating from men than vice versa. The PCS, which, since 2015, also collects gender-specific data on violent crimes, is kept by the Federal Criminal Police Office, but without taking into account the relevant criteria for targeted prevention, such as the history of violence of the perpetrator/killer, weapon, motivation, etc.. Institutions such as EIGE or the World Health Organization have been asking Germany for years in vain for comparable data on violence against women in order to gain an overview or to develop cross-border synergies. The PCS are the only official data collection on violence against women. All players involved are depend on this data set, which is published only in November of the following year and is thus already completely outdated at the time of publication. In order to combat German femicides causally, purposefully and efficiently, evidence-based data was urgently needed. Methodology: Beginning in January 2019, a database was set up that now tracks more than 600 German femicides, broken down by more than 100 crime-related individual criteria, which in turn go far beyond the official PCS. These data are evaluated on the one hand by daily media research, and on the other hand by case-specific inquiries at the respective public prosecutor's offices and courts nationwide. This quantitative long-term study covers domestic violence as well as a variety of different types of gender-specific, lethal violence, including, for example, femicides committed by German citizens abroad. Additionallyalcohol/ narcotic and/or drug abuse, infanticides and the gender aspect in the judiciary are also considered. Results: Since November 2020, evidence-based data from a scientific survey have been available for the first time in Germany, supplementing the rudimentary picture of reality provided by PCS with a number of relevant parameters. The most important goal of the study is to identify "red flags" that enable general preventive awareness, that serve increasingly precise hazard assessment in acute hazard situations, and from which concrete instructions for action can be identified. Already at a very early stage of the study it could be proven that in more than half of all femicides with a sexual perpetrator/victim constellation there was an age difference of five years or more. Summary: Without reliable data and an understanding of the nature and extent, cause and effect, it is impossible to sustainably curb violence against girls and women, which increasingly often culminates in femicide. In Germany, valid data from a scientific survey has been available for the first time since November 2020, supplementing the rudimentary reality picture of the official and, to date, sole crime statistics with several relevant parameters. The basic research provides insights into geo-concentration, monthly peaks and the modus operandi of male violent excesses. A significant increase of child homicides in the course of femicides and/or child homicides as an instrument of violence against the mother could be proven as well as a danger of affected persons due to an age difference of five years and more. In view of the steadily increasing wave of violence against women, these study results are an eminent contribution to the preventive containment of German femicides.

Keywords: femicide, violence against women, gender specific data, rule Of law, Istanbul convention, gender equality, gender based violence

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Authors: Ali Kazemi

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Those within the volatile and interconnected international economic markets, appropriately predicting market trends, hold substantial fees for traders and financial establishments. Traditional device mastering strategies have made full-size strides in forecasting marketplace movements; however, monetary data's complicated and networked nature calls for extra sophisticated processes. This observation offers a groundbreaking method for monetary marketplace prediction that leverages the synergistic capability of Graph Convolutional Networks (GCNs) and Long Short-Term Memory (LSTM) networks. Our suggested algorithm is meticulously designed to forecast the traits of inventory market indices and cryptocurrency costs, utilizing a comprehensive dataset spanning from January 1, 2015, to December 31, 2023. This era, marked by sizable volatility and transformation in financial markets, affords a solid basis for schooling and checking out our predictive version. Our algorithm integrates diverse facts to construct a dynamic economic graph that correctly reflects market intricacies. We meticulously collect opening, closing, and high and low costs daily for key inventory marketplace indices (e.g., S&P 500, NASDAQ) and widespread cryptocurrencies (e.g., Bitcoin, Ethereum), ensuring a holistic view of marketplace traits. Daily trading volumes are also incorporated to seize marketplace pastime and liquidity, providing critical insights into the market's shopping for and selling dynamics. Furthermore, recognizing the profound influence of the monetary surroundings on financial markets, we integrate critical macroeconomic signs with hobby fees, inflation rates, GDP increase, and unemployment costs into our model. Our GCN algorithm is adept at learning the relational patterns amongst specific financial devices represented as nodes in a comprehensive market graph. Edges in this graph encapsulate the relationships based totally on co-movement styles and sentiment correlations, enabling our version to grasp the complicated community of influences governing marketplace moves. Complementing this, our LSTM algorithm is trained on sequences of the spatial-temporal illustration discovered through the GCN, enriched with historic fee and extent records. This lets the LSTM seize and expect temporal marketplace developments accurately. Inside the complete assessment of our GCN-LSTM algorithm across the inventory marketplace and cryptocurrency datasets, the version confirmed advanced predictive accuracy and profitability compared to conventional and opportunity machine learning to know benchmarks. Specifically, the model performed a Mean Absolute Error (MAE) of 0.85%, indicating high precision in predicting day-by-day charge movements. The RMSE was recorded at 1.2%, underscoring the model's effectiveness in minimizing tremendous prediction mistakes, which is vital in volatile markets. Furthermore, when assessing the model's predictive performance on directional market movements, it achieved an accuracy rate of 78%, significantly outperforming the benchmark models, averaging an accuracy of 65%. This high degree of accuracy is instrumental for techniques that predict the course of price moves. This study showcases the efficacy of mixing graph-based totally and sequential deep learning knowledge in economic marketplace prediction and highlights the fee of a comprehensive, records-pushed evaluation framework. Our findings promise to revolutionize investment techniques and hazard management practices, offering investors and economic analysts a powerful device to navigate the complexities of cutting-edge economic markets.

Keywords: financial market prediction, graph convolutional networks (GCNs), long short-term memory (LSTM), cryptocurrency forecasting

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Authors: Justin Woulfe

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Siloed logistics and supply chain management systems throughout the Department of Defense (DOD) has led to disparate approaches to modeling and simulation (M&S), a lack of understanding of how one system impacts the whole, and issues with “optimal” solutions that are good for one organization but have dramatic negative impacts on another. Many different systems have evolved to try to understand and account for uncertainty and try to reduce the consequences of the unknown. As the DoD undertakes expansive digital transformation initiatives, there is an opportunity to fuse and leverage traditionally disparate data into a centrally hosted source of truth. With a streamlined process incorporating machine learning (ML) and artificial intelligence (AI), advanced M&S will enable informed decisions guiding program success via optimized operational readiness and improved mission success. One of the current challenges is to leverage the terabytes of data generated by monitored systems to provide actionable information for all levels of users. The implementation of a cloud-based application analyzing data transactions, learning and predicting future states from current and past states in real-time, and communicating those anticipated states is an appropriate solution for the purposes of reduced latency and improved confidence in decisions. Decisions made from an ML and AI application combined with advanced optimization algorithms will improve the mission success and performance of systems, which will improve the overall cost and effectiveness of any program. The Systecon team constructs and employs model-based simulations, cutting across traditional silos of data, aggregating maintenance, and supply data, incorporating sensor information, and applying optimization and simulation methods to an as-maintained digital twin with the ability to aggregate results across a system’s lifecycle and across logical and operational groupings of systems. This coupling of data throughout the enterprise enables tactical, operational, and strategic decision support, detachable and deployable logistics services, and configuration-based automated distribution of digital technical and product data to enhance supply and logistics operations. As a complete solution, this approach significantly reduces program risk by allowing flexible configuration of data, data relationships, business process workflows, and early test and evaluation, especially budget trade-off analyses. A true capability to tie resources (dollars) to weapon system readiness in alignment with the real-world scenarios a warfighter may experience has been an objective yet to be realized to date. By developing and solidifying an organic capability to directly relate dollars to readiness and to inform the digital twin, the decision-maker is now empowered through valuable insight and traceability. This type of educated decision-making provides an advantage over the adversaries who struggle with maintaining system readiness at an affordable cost. The M&S capability developed allows program managers to independently evaluate system design and support decisions by quantifying their impact on operational availability and operations and support cost resulting in the ability to simultaneously optimize readiness and cost. This will allow the stakeholders to make data-driven decisions when trading cost and readiness throughout the life of the program. Finally, sponsors are available to validate product deliverables with efficiency and much higher accuracy than in previous years.

Keywords: artificial intelligence, digital transformation, machine learning, predictive analytics

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Authors: Michael Radwan Omary

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Context: This scientific innovation demonstrate organic catalysis engineered media effective desalination of surface and groundwater. The author has developed a technology called “Storm-Water Ions Filtration Treatment” (SWIFTTM) cold reactor modules designed to retrofit typical urban street storm drains or catch basins. SWIFT triggers biochemical redox reactions with water stream-embedded toxic total dissolved solids (TDS) and electrical conductivity (EC). SWIFTTM Catalysts media unlock the sub-molecular bond energy, break down toxic chemical bonds, and neutralize toxic molecules, bacteria and pathogens. Research Aim: This research aims to develop and design lower O&M cost, zero-brine discharge, energy input-free, chemical-free water desalination and disinfection systems. The objective is to provide an effective resilient and sustainable solution to urban storm-water and groundwater decontamination and disinfection. Methodology: We focused on the development of organic, non-chemical, no-plugs, no pumping, non-polymer and non-allergenic approaches for water and waste water desalination and disinfection. SWIFT modules operate by directing the water stream to flow freely through the electrically charged media cold reactor, generating weak interactions with a water-dissolved electrically conductive molecule, resulting in the neutralization of toxic molecules. The system is powered by harvesting sub-molecular bonds embedded in energy. Findings: The SWIFTTM Technology case studies at CSU-CI and CSU-Fresno Water Institute, demonstrated consistently high reduction of all 40 detected waste-water pollutants including pathogens to levels below a state of California Department of Water Resources “Drinking Water Maximum Contaminants Levels”. The technology has proved effective in reducing pollutants such as arsenic, beryllium, mercury, selenium, glyphosate, benzene, and E. coli bacteria. The technology has also been successfully applied to the decontamination of dissolved chemicals, water pathogens, organic compounds and radiological agents. Theoretical Importance: SWIFT technology development, design, engineering, and manufacturing, offer cutting-edge advancement in achieving clean-energy source bio-catalysis media solution, an energy input free water and waste water desalination and disinfection. A significant contribution to institutions and municipalities achieving sustainable, lower cost, zero-brine and zero CO2 discharges clean energy water desalination. Data Collection and Analysis Procedures: The researchers collected data on the performance of the SWIFTTM technology in reducing the levels of various pollutants in water. The data was analyzed by comparing the reduction achieved by the SWIFTTM technology to the Drinking Water Maximum Contaminants Levels set by the state of California. The researchers also conducted live oral presentations to showcase the applications of SWIFTTM technology in storm water capture and decontamination as well as providing clean drinking water during emergencies. Conclusion: The SWIFTTM Technology has demonstrated its capability to effectively reduce pollutants in water and waste water to levels below regulatory standards. The Technology offers a sustainable solution to groundwater and storm-water treatments. Further development and implementation of the SWIFTTM Technology have the potential to treat storm water to be reused as a new source of drinking water and an ambient source of clean and healthy local water for recharge of ground water.

Keywords: catalysis, bio electro interactions, water desalination, weak-interactions

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Authors: Claire Harrison, Raajit K. Rampal, Vikas Gupta, Srdan Verstovsek, Moshe Talpaz, Jean-Jacques Kiladjian, Ruben Mesa, Andrew Kuykendall, Alessandro Vannucchi, Francesca Palandri, Sebastian Grosicki, Timothy Devos, Eric Jourdan, Marielle J. Wondergem, Haifa Kathrin Al-Ali, Veronika Buxhofer-Ausch, Alberto Alvarez-Larrán, Sanjay Akhani, Rafael Muñoz-Carerras, Yury Sheykin, Gozde Colak, Morgan Harris, John Mascarenhas

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Myelofibrosis (MF) is characterized by bone marrow fibrosis, anemia, splenomegaly and constitutional symptoms. Progressive bone marrow fibrosis results from aberrant megakaryopoeisis and expression of proinflammatory cytokines, both of which are heavily influenced by bromodomain and extraterminal domain (BET)-mediated gene regulation and lead to myeloproliferation and cytopenias. Pelabresib (CPI-0610) is an oral small-molecule investigational inhibitor of BET protein bromodomains currently being developed for the treatment of patients with MF. It is designed to downregulate BET target genes and modify nuclear factor kappa B (NF-κB) signaling. MANIFEST-2 was initiated based on data from Arm 3 of the ongoing Phase 2 MANIFEST study (NCT02158858), which is evaluating the combination of pelabresib and ruxolitinib in Janus kinase inhibitor (JAKi) treatment-naïve patients with MF. Primary endpoint analyses showed splenic and symptom responses in 68% and 56% of 84 enrolled patients, respectively. MANIFEST-2 (NCT04603495) is a global, Phase 3, randomized, double-blind, active-control study of pelabresib and ruxolitinib versus placebo and ruxolitinib in JAKi treatment-naïve patients with primary MF, post-polycythemia vera MF or post-essential thrombocythemia MF. The aim of this study is to evaluate the efficacy and safety of pelabresib in combination with ruxolitinib. Here we report updates from a recent protocol amendment. The MANIFEST-2 study schema is shown in Figure 1. Key eligibility criteria include a Dynamic International Prognostic Scoring System (DIPSS) score of Intermediate-1 or higher, platelet count ≥100 × 10^9/L, spleen volume ≥450 cc by computerized tomography or magnetic resonance imaging, ≥2 symptoms with an average score ≥3 or a Total Symptom Score (TSS) of ≥10 using the Myelofibrosis Symptom Assessment Form v4.0, peripheral blast count <5% and Eastern Cooperative Oncology Group performance status ≤2. Patient randomization will be stratified by DIPSS risk category (Intermediate-1 vs Intermediate-2 vs High), platelet count (>200 × 10^9/L vs 100–200 × 10^9/L) and spleen volume (≥1800 cm^3 vs <1800 cm^3). Double-blind treatment (pelabresib or matching placebo) will be administered once daily for 14 consecutive days, followed by a 7 day break, which is considered one cycle of treatment. Ruxolitinib will be administered twice daily for all 21 days of the cycle. The primary endpoint is SVR35 response (≥35% reduction in spleen volume from baseline) at Week 24, and the key secondary endpoint is TSS50 response (≥50% reduction in TSS from baseline) at Week 24. Other secondary endpoints include safety, pharmacokinetics, changes in bone marrow fibrosis, duration of SVR35 response, duration of TSS50 response, progression-free survival, overall survival, conversion from transfusion dependence to independence and rate of red blood cell transfusion for the first 24 weeks. Study recruitment is ongoing; 400 patients (200 per arm) from North America, Europe, Asia and Australia will be enrolled. The study opened for enrollment in November 2020. MANIFEST-2 was initiated based on data from the ongoing Phase 2 MANIFEST study with the aim of assessing the efficacy and safety of pelabresib and ruxolitinib in JAKi treatment-naïve patients with MF. MANIFEST-2 is currently open for enrollment.

Keywords: CPI-0610, JAKi treatment-naïve, MANIFEST-2, myelofibrosis, pelabresib

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Authors: Manavjit Singh Dhindsa, Ursula Das, Kshirasagar Naik, Marzia Zaman, Richard Purcell, Srinivas Sampalli, Abdul Mutakabbir, Chung-Horng Lung, Thambirajah Ravichandran

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These days, wildland fires, also known as forest fires, are more prevalent than ever. Wildfires have major repercussions that affect ecosystems, communities, and the environment in several ways. Wildfires lead to habitat destruction and biodiversity loss, affecting ecosystems and causing soil erosion. They also contribute to poor air quality by releasing smoke and pollutants that pose health risks, especially for individuals with respiratory conditions. Wildfires can damage infrastructure, disrupt communities, and cause economic losses. The economic impact of firefighting efforts, combined with their direct effects on forestry and agriculture, causes significant financial difficulties for the areas impacted. This research explores different forest fire spread models and presents a comprehensive review of various techniques and methodologies used in the field. A forest fire spread model is a computational or mathematical representation that is used to simulate and predict the behavior of a forest fire. By applying scientific concepts and data from empirical studies, these models attempt to capture the intricate dynamics of how a fire spreads, taking into consideration a variety of factors like weather patterns, topography, fuel types, and environmental conditions. These models assist authorities in understanding and forecasting the potential trajectory and intensity of a wildfire. Emphasizing the need for a comprehensive understanding of wildfire dynamics, this research explores the approaches, assumptions, and findings derived from various models. By using a comparison approach, a critical analysis is provided by identifying patterns, strengths, and weaknesses among these models. The purpose of the survey is to further wildfire research and management techniques. Decision-makers, researchers, and practitioners can benefit from the useful insights that are provided by synthesizing established information. Fire spread models provide insights into potential fire behavior, facilitating authorities to make informed decisions about evacuation activities, allocating resources for fire-fighting efforts, and planning for preventive actions. Wildfire spread models are also useful in post-wildfire mitigation strategies as they help in assessing the fire's severity, determining high-risk regions for post-fire dangers, and forecasting soil erosion trends. The analysis highlights the importance of customized modeling approaches for various circumstances and promotes our understanding of the way forest fires spread. Some of the known models in this field are Rothermel’s wildland fuel model, FARSITE, WRF-SFIRE, FIRETEC, FlamMap, FSPro, cellular automata model, and others. The key characteristics that these models consider include weather (includes factors such as wind speed and direction), topography (includes factors like landscape elevation), and fuel availability (includes factors like types of vegetation) among other factors. The models discussed are physics-based, data-driven, or hybrid models, also utilizing ML techniques like attention-based neural networks to enhance the performance of the model. In order to lessen the destructive effects of forest fires, this initiative aims to promote the development of more precise prediction tools and effective management techniques. The survey expands its scope to address the practical needs of numerous stakeholders. Access to enhanced early warning systems enables decision-makers to take prompt action. Emergency responders benefit from improved resource allocation strategies, strengthening the efficacy of firefighting efforts.

Keywords: artificial intelligence, deep learning, forest fire management, fire risk assessment, fire simulation, machine learning, remote sensing, wildfire modeling

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Authors: Liane J. Ioannou, Jonathan Serpell, Cino Bendinelli, David Walters, Jenny Gough, Dean Lisewski, Win Meyer-Rochow, Julie Miller, Duncan Topliss, Bill Fleming, Stephen Farrell, Andrew Kiu, James Kollias, Mark Sywak, Adam Aniss, Linda Fenton, Danielle Ghusn, Simon Harper, Aleksandra Popadich, Kate Stringer, David Watters, Susannah Ahern

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BACKGROUND: There are significant variations in the management, treatment and outcomes of thyroid cancer, particularly in the role of: diagnostic investigation and pre-treatment scanning; optimal extent of surgery (total or hemi-thyroidectomy); use of active surveillance for small low-risk cancers; central lymph node dissections (therapeutic or prophylactic); outcomes following surgery (e.g. recurrent laryngeal nerve palsy, hypocalcaemia, hypoparathyroidism); post-surgical hormone, calcium and vitamin D therapy; and provision and dosage of radioactive iodine treatment. A proven strategy to reduce variations in the outcome and to improve survival is to measure and compare it using high-quality clinical registry data. Clinical registries provide the most effective means of collecting high-quality data and are a tool for quality improvement. Where they have been introduced at a state or national level, registries have become one of the most clinically valued tools for quality improvement. To benchmark clinical care, clinical quality registries require systematic measurement at predefined intervals and the capacity to report back information to participating clinical units. OBJECTIVE: The aim of this study was to develop a core set clinical indicators that enable measurement and reporting of quality of care for patients with thyroid cancer. We hypothesise that measuring clinical quality indicators, developed to identify differences in quality of care across sites, will reduce variation and improve patient outcomes and survival, thereby lessening costs and healthcare burden to the Australian community. METHOD: Preparatory work and scoping was conducted to identify existing high quality, clinical guidelines and best practice for thyroid cancer both nationally and internationally, as well as relevant literature. A bi-national panel was invited to participate in a modified Delphi process. Panelists were asked to rate each proposed indicator on a Likert scale of 1–9 in a three-round iterative process. RESULTS: A total of 236 potential quality indicators were identified. One hundred and ninety-two indicators were removed to reflect the data capture by the Australian and New Zealand Thyroid Cancer Registry (ANZTCR) (from diagnosis to 90-days post-surgery). The remaining 44 indicators were presented to the panelists for voting. A further 21 indicators were later added by the panelists bringing the total potential quality indicators to 65. Of these, 21 were considered the most important and feasible indicators to measure quality of care in thyroid cancer, of which 12 were recommended for inclusion in the final set. The consensus indicator set spans the spectrum of care, including: preoperative; surgery; surgical complications; staging and post-surgical treatment planning; and post-surgical treatment. CONCLUSIONS: This study provides a core set of quality indicators to measure quality of care in thyroid cancer. This indicator set can be applied as a tool for internal quality improvement, comparative quality reporting, public reporting and research. Inclusion of these quality indicators into monitoring databases such as clinical quality registries will enable opportunities for benchmarking and feedback on best practice care to clinicians involved in the management of thyroid cancer.

Keywords: clinical registry, Delphi survey, quality indicators, quality of care

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Authors: Rebeca V. Tholen, Elaine Bundy

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Background: Liver transplantation (LT) is considered the only curative treatment for end-stage liver disease Background: Liver transplantation (LT) is considered the only curative treatment for end-stage liver disease (ESLD). The effects of alcoholism can cause irreversible liver damage, cirrhosis and subsequent liver failure. Alcohol relapse after transplant occurs in 20-50% of patients and increases the risk for recurrent cirrhosis, organ rejection, and graft failure. Alcohol relapse after transplant has been identified as a problem among liver transplant recipients at a large urban academic transplant center in the United States. Transplantation will reverse the complications of ESLD, but it does not treat underlying alcoholism or reduce the risk of relapse after transplant. The purpose of this quality improvement project is to implement and evaluate the effectiveness of a High-Risk Alcoholism Relapse (HRAR) Scale to screen and identify patients at high-risk for alcohol relapse after receiving an LT. Methods: The HRAR Scale is a predictive tool designed to determine the severity of alcoholism and risk of relapse after transplant. The scale consists of three variables identified as having the highest predictive power for early relapse including, daily number of drinks, history of previous inpatient treatment for alcoholism, and the number of years of heavy drinking. All adult liver transplant recipients at a large urban transplant center were screened with the HRAR Scale prior to hospital discharge. A zero to two ordinal score is ranked for each variable, and the total score ranges from zero to six. High-risk scores are between three to six. Results: Descriptive statistics revealed 25 patients were newly transplanted and discharged from the hospital during an 8-week period. 40% of patients (n=10) were identified as being high-risk for relapse and 60% low-risk (n=15). The daily number of drinks were determined by alcohol content (1 drink = 15g of ethanol) and number of drinks per day. 60% of patients reported drinking 9-17 drinks per day, and 40% reported ≤ 9 drinks. 50% of high-risk patients reported drinking ≥ 25 years, 40% for 11-25 years, and 10% ≤ 11 years. For number of inpatient treatments for alcoholism, 50% received inpatient treatment one time, 20% ≥ 1, and 30% reported never receiving inpatient treatment. Findings reveal the importance and value of a validated screening tool as a more efficient method than other screening methods alone. Integration of a structured clinical tool will help guide the drinking history portion of the psychosocial assessment. Targeted interventions can be implemented for all high-risk patients. Conclusions: Our findings validate the effectiveness of utilizing the HRAR scale to screen and identify patients who are a high-risk for alcohol relapse post-LT. Recommendations to help maintain post-transplant sobriety include starting a transplant support group within the organization for all high-risk patients. (ESLD). The effects of alcoholism can cause irreversible liver damage, cirrhosis and subsequent liver failure. Alcohol relapse after transplant occurs in 20-50% of patients, and increases the risk for recurrent cirrhosis, organ rejection, and graft failure. Alcohol relapse after transplant has been identified as a problem among liver transplant recipients at a large urban academic transplant center in the United States. Transplantation will reverse the complications of ESLD, but it does not treat underlying alcoholism or reduce the risk of relapse after transplant. The purpose of this quality improvement project is to implement and evaluate the effectiveness of a High-Risk Alcoholism Relapse (HRAR) Scale to screen and identify patients at high-risk for alcohol relapse after receiving a LT. Methods: The HRAR Scale is a predictive tool designed to determine severity of alcoholism and risk of relapse after transplant. The scale consists of three variables identified as having the highest predictive power for early relapse including, daily number of drinks, history of previous inpatient treatment for alcoholism, and the number of years of heavy drinking. All adult liver transplant recipients at a large urban transplant center were screened with the HRAR Scale prior to hospital discharge. A zero to two ordinal score is ranked for each variable, and the total score ranges from zero to six. High-risk scores are between three to six. Results: Descriptive statistics revealed 25 patients were newly transplanted and discharged from the hospital during an 8-week period. 40% of patients (n=10) were identified as being high-risk for relapse and 60% low-risk (n=15). The daily number of drinks were determined by alcohol content (1 drink = 15g of ethanol) and number of drinks per day. 60% of patients reported drinking 9-17 drinks per day, and 40% reported ≤ 9 drinks. 50% of high-risk patients reported drinking ≥ 25 years, 40% for 11-25 years, and 10% ≤ 11 years. For number of inpatient treatments for alcoholism, 50% received inpatient treatment one time, 20% ≥ 1, and 30% reported never receiving inpatient treatment. Findings reveal the importance and value of a validated screening tool as a more efficient method than other screening methods alone. Integration of a structured clinical tool will help guide the drinking history portion of the psychosocial assessment. Targeted interventions can be implemented for all high-risk patients. Conclusions: Our findings validate the effectiveness of utilizing the HRAR scale to screen and identify patients who are a high-risk for alcohol relapse post-LT. Recommendations to help maintain post-transplant sobriety include starting a transplant support group within the organization for all high-risk patients.

Keywords: alcoholism, liver transplant, quality improvement, substance abuse

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Authors: Julie M. Novak, Simone K. Brennan, Lacey Brim

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Undergraduate medical education (UME) curriculum notably addresses micro-level communications (e.g., patient-provider, intercultural, inter-professional), yet frequently under-examines the role and impact of organizational communication, a more macro-level. Organizational communication, however, functions as foundation and through systemic structures of an organization and thereby serves as hidden curriculum and influences learning experiences and outcomes. Yet, little available research exists fully examining how students experience organizational communication while in medical school. Extant literature and best practices provide insufficient guidance for UME programs, in particular. The purpose of this study was to map and examine current organizational communication systems and processes in a UME program. Employing a phenomenology-grounded and participatory approach, this study sought to understand the organizational communication system from medical students' perspective. The research team consisted of a core team and 13 medical student co-investigators. This research employed multiple methods, including focus groups, individual interviews, and two surveys (one reflective of focus group questions, the other requesting students to submit ‘examples’ of communications). To provide context for student responses, nonstudent participants (faculty, administrators, and staff) were sampled, as they too express concerns about communication. Over 400 students across all cohorts and 17 nonstudents participated. Data were iteratively analyzed and checked for triangulation. Findings reveal the complex nature of organizational communication and student-oriented communications. They reveal program-impactful strengths, weaknesses, gaps, and tensions and speak to the role of organizational communication practices influencing both climate and culture. With regard to communications, students receive multiple, simultaneous communications from multiple sources/channels, both formal (e.g., official email) and informal (e.g., social media). Students identified organizational strengths including the desire to improve student voice, and message frequency. They also identified weaknesses related to over-reliance on emails, numerous platforms with inconsistent utilization, incorrect information, insufficient transparency, assessment/input fatigue, tacit expectations, scheduling/deadlines, responsiveness, and mental health confidentiality concerns. Moreover, they noted gaps related to lack of coordination/organization, ambiguous point-persons, student ‘voice-only’, open communication loops, lack of core centralization and consistency, and mental health bridges. Findings also revealed organizational identity and cultural characteristics as impactful on the medical school experience. Cultural characteristics included program size, diversity, urban setting, student organizations, community-engagement, crisis framing, learning for exams, inefficient bureaucracy, and professionalism. Moreover, they identified system structures that do not always leverage cultural strengths or reduce cultural problematics. Based on the results, opportunities for productive change are identified. These include leadership visibly supporting and enacting overall organizational narratives, making greater efforts in consistently ‘closing the loop’, regularly sharing how student input effects change, employing strategies of crisis communication more often, strengthening communication infrastructure, ensuring structures facilitate effective operations and change efforts, and highlighting change efforts in informational communication. Organizational communication and communications are not soft-skills, or of secondary concern within organizations, rather they are foundational in nature and serve to educate/inform all stakeholders. As primary stakeholders, students and their success directly affect the accomplishment of organizational goals. This study demonstrates how inquiries about how students navigate their educational experience extends research-based knowledge and provides actionable knowledge for the improvement of organizational operations in UME.

Keywords: medical education programs, organizational communication, participatory research, qualitative mixed methods

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Authors: Volker Wannack

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Regional, national, and international strategies focusing on hydrogen (H₂) and blockchain are driving significant advancements in hydrogen and blockchain technology worldwide. These strategies lay the foundation for the groundbreaking "Blockchain Based Hydrogen Market (BBH₂)" project. The primary goal of this project is to develop a functional Blockchain Minimum Viable Product (B-MVP) for the hydrogen market. The B-MVP will leverage blockchain as an enabling technology with a common database and platform, facilitating secure and automated transactions through smart contracts. This innovation will revolutionize logistics, trading, and transactions within the hydrogen market. The B-MVP has transformative potential across various sectors. It benefits renewable energy producers, surplus energy-based hydrogen producers, hydrogen transport and distribution grid operators, and hydrogen consumers. By implementing standardized, automated, and tamper-proof processes, the B-MVP enhances cost efficiency and enables transparent and traceable transactions. Its key objective is to establish the verifiable integrity of climate-friendly "green" hydrogen by tracing its supply chain from renewable energy producers to end users. This emphasis on transparency and accountability promotes economic, ecological, and social sustainability while fostering a secure and transparent market environment. A notable feature of the B-MVP is its cross-border operability, eliminating the need for country-specific data storage and expanding its global applicability. This flexibility not only broadens its reach but also creates opportunities for long-term job creation through the establishment of a dedicated blockchain operating company. By attracting skilled workers and supporting their training, the B-MVP strengthens the workforce in the growing hydrogen sector. Moreover, it drives the emergence of innovative business models that attract additional company establishments and startups and contributes to long-term job creation. For instance, data evaluation can be utilized to develop customized tariffs and provide demand-oriented network capacities to producers and network operators, benefitting redistributors and end customers with tamper-proof pricing options. The B-MVP not only brings technological and economic advancements but also enhances the visibility of national and international standard-setting efforts. Regions implementing the B-MVP become pioneers in climate-friendly, sustainable, and forward-thinking practices, generating interest beyond their geographic boundaries. Additionally, the B-MVP serves as a catalyst for research and development, facilitating knowledge transfer between universities and companies. This collaborative environment fosters scientific progress, aligns with strategic innovation management, and cultivates an innovation culture within the hydrogen market. Through the integration of blockchain and hydrogen technologies, the B-MVP promotes holistic innovation and contributes to a sustainable future in the hydrogen industry. The implementation process involves evaluating and mapping suitable blockchain technology and architecture, developing and implementing the blockchain, smart contracts, and depositing certificates of origin. It also includes creating interfaces to existing systems such as nomination, portfolio management, trading, and billing systems, testing the scalability of the B-MVP to other markets and user groups, developing data formats for process-relevant data exchange, and conducting field studies to validate the B-MVP. BBH₂ is part of the "Technology Offensive Hydrogen" funding call within the research funding of the Federal Ministry of Economics and Climate Protection in the 7th Energy Research Programme of the Federal Government.

Keywords: hydrogen, blockchain, sustainability, innovation, structural change

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Authors: Jai Bakliya, Palak Dhamecha

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Today customer satisfaction is given utmost priority be it any industry. But when it comes to hospitality industry this applies even more as they come in direct contact with customers while providing them services. Employee engagement is new concept adopted by Human Resource Department which impacts customer satisfactions. To satisfy your customers, it is necessary to see that the employees in the organisation are satisfied and engaged enough in their work that they meet the company’s expectations and contribute in the process of achieving company’s goals and objectives. After all employees is human capital of the organisation. Employee engagement has become a top business priority for every organisation. In this fast moving economy, business leaders know that having a potential and high-performing human resource is important for growth and survival. They recognize that a highly engaged manpower can increase innovation, productivity, and performance, while reducing costs related to retention and hiring in highly competitive talent markets. But while most executives see a clear need to improve employee engagement, many have yet to develop tangible ways to measure and tackle this goal. Employee Engagement is an approach which is applied to establish an emotional connection between an employee and the organisation which ensures the employee’s commitment towards his work which affects the productivity and overall performance of the organisation. The study was conducted in hospitality industry. A popular branded hotel was chosen as a sample unit. Data were collected, both qualitative and quantitative from respondents. It is found that employee engagement level of the organisation (Hotel) is quite low. This means that employees are not emotionally connected with the organisation which may in turn, affect performance of the employees it is important to note that in hospitality industry individual employee’s performance specifically in terms of emotional engagement is critical and, therefore, a low engagement level may contribute to low organisation performance. An attempt to this study was made to identify employee engagement level. Another objective to take this study was to explore the factors impeding employee engagement and to explore employee engagement facilitation. While in the hospitality industry where people tend to work for as long as 16 to 18 hours concepts like employee engagement is essential. Because employees get tired of their routine job and in case where job rotation cannot be done employee engagement acts as a solution. The study was conducted at Trident Hotel, Udaipur. It was conducted on the sample size of 30 in-house employees from 6 different departments. The various departments were: Accounts and General, Front Office, Food & Beverage Service, Housekeeping, Food & Beverage Production and Engineering. It was conducted with the help of research instrument. The research instrument was Questionnaire. Data collection source was primary source. Trident Udaipur is one of the busiest hotels in Udaipur. The occupancy rate of the guest over there is nearly 80%. Due the high occupancy rate employees or staff of the hotel used to remain very busy and occupied all the time in their work. They worked for their remuneration only. As a result, they do not have any encouragement for their work nor they are interested in going an extra mile for the organisation. The study result shows working environment factors including recognition and appreciation, opinions of the employee, counselling, feedback from superiors, treatment of managers and respect from the organisation are capable of increasing employee engagement level in the hotel. The above study result encouraged us to explore the factors contributed to low employee engagement. It is being found that factors such as recognition and appreciation, feedback from supervisors, opinion of the employee, counselling, feedback from supervisors, treatment from managers has contributed negatively to employee engagement level. Probable reasons for the low contribution are number of employees gave the negative feedback in accordance to the factors stated above of the organisation. It seems that the structure of organisation itself is responsible for the low contribution of employee engagement. The scope of this study is limited to trident hotel situated in the Udaipur. The limitation of the study was that that the results or findings were only based on the responses of respondents of Trident, Udaipur. And so the recommendations were also applicable in Trident, Udaipur and not to all the like organisations across the country. Through the data collected was further analysed, interpreted and concluded. On the basis of the findings, suggestions were provided to the hotel for improvisation.

Keywords: human resource, employee engagement, research, study

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Authors: Essam Gooda, Chadi Abdallah, Hamdi Seif, Safaa Baydoun, Rouya Hdeib, Hilal Obeid

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Floods are common natural disaster occurring in semi-arid regions in Lebanon. This results in damage to human life and deterioration of environment. Despite their destructive nature and their immense impact on the socio-economy of the region, flash floods have not received adequate attention from policy and decision makers. This is mainly because of poor understanding of the processes involved and measures needed to manage the problem. The current understanding of flash floods remains at the level of general concepts; most policy makers have yet to recognize that flash floods are distinctly different from normal riverine floods in term of causes, propagation, intensity, impacts, predictability, and management. Flash floods are generally not investigated as a separate class of event but are rather reported as part of the overall seasonal flood situation. As a result, Lebanon generally lacks policies, strategies, and plans relating specifically to flash floods. Main objective of this research is to improve flash flood prediction by providing new knowledge and better understanding of the hydrological processes governing flash floods in the East Catchments of El Assi River. This includes developing rainstorm time distribution curves that are unique for this type of study region; analyzing, investigating, and developing a relationship between arid watershed characteristics (including urbanization) and nearby villages flow flood frequency in Ras Baalbeck and Fekha. This paper discusses different levels of integration approach¬es between GIS and hydrological models (HEC-HMS & HEC-RAS) and presents a case study, in which all the tasks of creating model input, editing data, running the model, and displaying output results. The study area corresponds to the East Basin (Ras Baalbeck & Fakeha), comprising nearly 350 km2 and situated in the Bekaa Valley of Lebanon. The case study presented in this paper has a database which is derived from Lebanese Army topographic maps for this region. Using ArcMap to digitizing the contour lines, streams & other features from the topographic maps. The digital elevation model grid (DEM) is derived for the study area. The next steps in this research are to incorporate rainfall time series data from Arseal, Fekha and Deir El Ahmar stations to build a hydrologic data model within a GIS environment and to combine ArcGIS/ArcMap, HEC-HMS & HEC-RAS models, in order to produce a spatial-temporal model for floodplain analysis at a regional scale. In this study, HEC-HMS and SCS methods were chosen to build the hydrologic model of the watershed. The model then calibrated using flood event that occurred between 7th & 9th of May 2014 which considered exceptionally extreme because of the length of time the flows lasted (15 hours) and the fact that it covered both the watershed of Aarsal and Ras Baalbeck. The strongest reported flood in recent times lasted for only 7 hours covering only one watershed. The calibrated hydrologic model is then used to build the hydraulic model & assessing of flood hazards maps for the region. HEC-RAS Model is used in this issue & field trips were done for the catchments in order to calibrated both Hydrologic and Hydraulic models. The presented models are a kind of flexible procedures for an ungaged watershed. For some storm events it delivers good results, while for others, no parameter vectors can be found. In order to have a general methodology based on these ideas, further calibration and compromising of results on the dependence of many flood events parameters and catchment properties is required.

Keywords: flood risk management, flash flood, semi arid region, El Assi River, hazard maps

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Authors: Veenapani Rajeev Verma

Abstract:

Context: Assessing facility readiness is paramount as it can indicate capacity of facilities to provide essential care for resilience to health challenges. In the context of decentralization, estimation of supply side readiness indices at sub national level is imperative for effective evidence based policy but remains a colossal challenge due to lack of dependable and representative data sources. Setting: District Poonch of Jammu and Kashmir was selected for this study. It is remote, rural district with unprecedented topographical barriers and is identified as high priority by government. It is also a fragile area as is bounded by Line of Control with Pakistan bearing the brunt of cease fire violations, military skirmishes and sporadic militant attacks. Hilly geographical terrain, rudimentary/absence of road network and impoverishment are quintessential to this area. Objectives: Objective of the study is to a) Evaluate the service readiness of health facilities and create a concise index subsuming plethora of discrete indicators and b) Ascertain supply side barriers in service provisioning via stakeholder’s analysis. Study also strives to expand analytical domain unravelling context and area specific intricacies associated with service delivery. Methodology: Mixed method approach was employed to triangulate quantitative analysis with qualitative nuances. Facility survey encompassing 90 Subcentres, 44 Primary health centres, 3 Community health centres and 1 District hospital was conducted to gauge general service availability and service specific availability (depth of coverage). Compendium of checklist was designed using Indian Public Health Standards (IPHS) in form of standard core questionnaire and scorecard generated for each facility. Information was collected across dimensions of amenities, equipment, medicines, laboratory and infection control protocols as proposed in WHO’s Service Availability and Readiness Assesment (SARA). Two stage polychoric principal component analysis employed to generate a parsimonious index by coalescing an array of tracer indicators. OLS regression method used to determine factors explaining composite index generated from PCA. Stakeholder analysis was conducted to discern qualitative information. Myriad of techniques like observations, key informant interviews and focus group discussions using semi structured questionnaires on both leaders and laggards were administered for critical stakeholder’s analysis. Results: General readiness score of health facilities was found to be 0.48. Results indicated poorest readiness for subcentres and PHC’s (first point of contact) with composite score of 0.47 and 0.41 respectively. For primary care facilities; principal component was characterized by basic newborn care as well as preparedness for delivery. Results revealed availability of equipment and surgical preparedness having lowest score (0.46 and 0.47) for facilities providing secondary care. Presence of contractual staff, more than 1 hr walk to facility, facilities in zone A (most vulnerable) to cross border shelling and facilities inaccessible due to snowfall and thick jungles was negatively associated with readiness index. Nonchalant staff attitude, unavailability of staff quarters, leakages and constraint in supply chain of drugs and consumables were other impediments identified. Conclusions/Policy Implications: It is pertinent to first strengthen primary care facilities in this setting. Complex dimensions such as geographic barriers, user and provider behavior is not under precinct of this methodology.

Keywords: effective coverage, principal component analysis, readiness index, universal health coverage

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Authors: Jocelyn Doucet, Jean-Philippe Laviolette, Ali Eslami

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The end-of-life management and recycling of polymer wastes remains a key environment issue in on-going efforts to increase resource efficiency and attaining GHG emission reduction targets. Half of all the plastics ever produced were made in the last 13 years, and only about 16% of that plastic waste is collected for recycling, while 25% is incinerated, 40% is landfilled, and 19% is unmanaged and leaks in the environment and waterways. In addition to the plastic collection issue, the UN recently published a report on chemicals in plastics, which adds another layer of challenge when integrating recycled content containing toxic products into new products. To tackle these important issues, innovative solutions are required. Chemical recycling of plastics provides new complementary alternatives to the current recycled plastic market by converting waste material into a high value chemical commodity that can be reintegrated in a variety of applications, making the total market size of the output – virgin-like, high value products - larger than the market size of the input – plastic waste. Access to high-quality feedstock also remains a major obstacle, primarily due to material contamination issues. Pyrowave approaches this challenge with its innovative nano-recycling technology, which purifies polymers at the molecular level, removing undesirable contaminants and restoring the resin to its virgin state without having to depolymerise it. This breakthrough approach expands the range of plastics that can be effectively recycled, including mixed plastics with various contaminants such as lead, inorganic pigments, and flame retardants. The technology allows yields below 100ppm, and purity can be adjusted to an infinitesimal level depending on the customer's specifications. The separation of the polymer and contaminants in Pyrowave's nano-recycling process offers the unique ability to customize the solution on targeted additives and contaminants to be removed based on the difference in molecular size. This precise control enables the attainment of a final polymer purity equivalent to virgin resin. The patented process involves dissolving the contaminated material using a specially formulated solvent, purifying the mixture at the molecular level, and subsequently extracting the solvent to yield a purified polymer resin that can directly be reintegrated in new products without further treatment. Notably, this technology offers simplicity, effectiveness, and flexibility while minimizing environmental impact and preserving valuable resources in the manufacturing circuit. Pyrowave has successfully applied this nano-recycling technology to decontaminate polymers and supply purified, high-quality recycled plastics to critical industries, including food-contact compliance. The technology is low-carbon, electrified, and provides 100% traceable resins with properties identical to those of virgin resins. Additionally, the issue of low recycling rates and the limited market for traditionally hard-to-recycle plastic waste has fueled the need for new complementary alternatives. Chemical recycling, such as Pyrowave's microwave depolymerization, presents a sustainable and efficient solution by converting plastic waste into high-value commodities. By employing microwave catalytic depolymerization, Pyrowave enables a truly circular economy of plastics, particularly in treating polystyrene waste to produce virgin-like styrene monomers. This revolutionary approach boasts low energy consumption, high yields, and a reduced carbon footprint. Pyrowave offers a portfolio of sustainable, low-carbon, electric solutions to give plastic waste a second life and paves the way to the new circular economy of plastics. Here, particularly for polystyrene, we show that styrene monomer yields from Pyrowave’s polystyrene microwave depolymerization reactor is 2,2 to 1,5 times higher than that of the thermal conventional pyrolysis. In addition, we provide a detailed understanding of the microwave assisted depolymerization via analyzing the effects of microwave power, pyrolysis time, microwave receptor and temperature on the styrene product yields. Furthermore, we investigate life cycle environmental impact assessment of microwave assisted pyrolysis of polystyrene in commercial-scale production. Finally, it is worth pointing out that Pyrowave is able to treat several tons of polystyrene to produce virgin styrene monomers and manage waste/contaminated polymeric materials as well in a truly circular economy.

Keywords: nanorecycling, nanomaterials, plastic recycling, depolymerization

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Authors: Hosein Maghsoudi

Abstract:

Rheumatois arthritis (RA) is progressive inflammatory autoimmune diseases that primarily affect the joints, characterized by synovial hyperplasia and inflammatory cell infiltration, deformed and painful joints, which can lead tissue destruction, functional disability systemic complications, and early dead and socioeconomic costs. The cause of rheumatoid arthritis is unknown, but genetic and environmental factors are contributory and the prognosis is guarded. However, advances in understanding the pathogenesis of the disease have fostered the development of new therapeutics, with improved outcomes. The current treatment strategy, which reflects this progress, is to initiate aggressive therapy soon after diagnosis and to escalate the therapy, guided by an assessment of disease activity, in pursuit of clinical remission. The pathobiology of RA is multifaceted and involves T cells, B cells, fibroblast-like synoviocyte (FLSc) and the complex interaction of many pro-inflammatory cytokine. Novel biologic agents that target tumor necrosis or interlukin (IL)-1 and Il-6, in addition T- and B-cells inhibitors, have resulted in favorable clinical outcomes in patients with RA. Despite this, at least 30% of RA patients are résistance to available therapies, suggesting novel mediators should be identified that can target other disease-specific pathway or cell lineage. Among the inflammatory cell population that might participated in RA pathogenesis, FLSc are crucial in initiaing and driving RA in concert of cartilage and bone by secreting metalloproteinase (MMPs) into the synovial fluid and by direct invasion into extracellular matrix (ECM), further exacerbating joint damage. Invasion of fibroblast-like synoviocytes (FLSc) is critical in the pathogenesis of rheumatoid-arthritis. The metalloproteinase (MMPs) and activator of Toll-like receptor 4 (TLR4)/nuclear factor- κB pthway play a critical role in RA-FLS invasion induced by lipopolysaccharide (LPS). The present study aimed to explore the anti-invasion activity of Glycyrrhizic Acid as a pharmacologically safe phytochemical agent with potent anti-inflammatory properties on IL-1beta and TNF-alpha signalling pathways in Bovine fibroblast-like synoviocyte ex- vitro, on LPS-stimulated bovine FLS migration and invasion as well as MMP expression and explored the upstream signal transduction. Results showed that Glycyrrhizic Acid suppressed LPS-stimulated bovine FLS migration and invasion by inhibition MMP-9 expression and activity. In addition our results revealed that Glycyrrhizic Acid inhibited the transcriptional activity of MMP-9 by suppression the nbinding activity of NF- κB in the MMP-9 promoter pathway. The extract of licorice (Glycyrrhiza glabra L.) has been widely used for many centuries in the traditional Chinese medicine as native anti-allergic agent. Glycyrrhizin (GL), a triterpenoidsaponin, extracted from the roots of licorice is the most effective compound for inflammation and allergic diseases in human body. The biological and pharmacological studies revealed that GL possesses many pharmacological effects, such as anti-inflammatory, anti-viral and liver protective effects, and the biological effects, such as induction of cytokines (interferon-γ and IL-12), chemokines as well as extrathymic T and anti-type 2 T cells. GL is known in the traditional Chinese medicine for its anti-inflammatory effect, which is originally described by Finney in 1959. The mechanism of the GL-induced anti-inflammatory effect is based on different pathways of the GL-induced selective inhibition of the prostaglandin E2 production, the CK-II- mediated activation of both GL-binding lipoxygenas (gbLOX; 17) and PLA2, an anti-thrombin action of GL and production of the reactive oxygen species (ROS; GL exerts liver protection properties by inhibiting PLA2 or by the hydroxyl radical trapping action, leading to the lowering of serum alanine and aspartate transaminase levels. The present study was undertaken to examine the possible mechanism of anti-inflammatory properties GL on IL-1beta and TNF-alpha signalling pathways in bovine fibroblast-like synoviocyte ex-vivo, on LPS-stimulated bovine FLS migration and invasion as well as MMP expression and explored the upstream signal transduction. Our results clearly showed that treatment of bovine fibroblast-like synoviocyte with GL suppressed LPS-induced cell migration and invasion. Furthermore, it revealed that GL inhibited the transcription activity of MMP-9 by suppressing the binding activity of NF-κB in the MM-9 promoter. MMP-9 is an important ECM-degrading enzyme and overexpression of MMPs in important of RA-FLSs. LPS can stimulate bovine FLS to secret MMPs, and this induction is regulated at the transcription and translational levels. In this study, LPS treatment of bovine FLS caused an increase in MMP-2 and MMP-9 levels. The increase in MMP-9 expression and secretion was inhibited by ex- vitro. Furthermore, these effects were mimicked by MMP-9 siRNA. These result therefore indicate the the inhibition of LPS-induced bovine FLS invasion by GL occurs primarily by inhibiting MMP-9 expression and activity. Next we analyzed the functional significance of NF-κB transcription of MMP-9 activation in Bovine FLSs. Results from EMSA showed that GL suppressed LPS-induced NF-κB binding to the MMP-9 promotor, as NF-κB regulates transcriptional activation of multiple inflammatory cytokines, we predicted that GL might target NF-κB to suppress MMP-9 transcription by LPS. Myeloid differentiation-factor 88 (MyD88) and TIR-domain containing adaptor protein (TIRAP) are critical proteins in the LPS-induced NF-κB and apoptotic signaling pathways, GL inhibited the expression of TLR4 and MYD88. These results demonstrated that GL suppress LPS-induced MMP-9 expression through the inhibition of the induced TLR4/NFκB signaling pathway. Taken together, our results provide evidence that GL exerts anti-inflammatory effects by inhibition LPS-induced bovine FLSs migration and invasion, and the mechanisms may involve the suppression of TLR4/NFκB –mediated MMP-9 expression. Although further work is needed to clarify the complicated mechanism of GL-induced anti-invasion of bovine FLSs, GL might be used as a further anti-invasion drug with therapeutic efficacy in the treatment of immune-mediated inflammatory disease such as RA.

Keywords: glycyrrhizic acid, bovine fibroblast-like synoviocyte, tlr4/nf-κb, metalloproteinase-9

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Authors: David J. Foran, Nhan Do, Samuel Ajjarapu, Wenjin Chen, Tahsin Kurc, Joel H. Saltz

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The large-scale data and computational requirements of investigators throughout the clinical and research communities demand an informatics infrastructure that supports both existing and new investigative and translational projects in a robust, secure environment. In some subspecialties of medicine and research, the capacity to generate data has outpaced the methods and technology used to aggregate, organize, access, and reliably retrieve this information. Leading health care centers now recognize the utility of establishing an enterprise-wide, clinical data warehouse. The primary benefits that can be realized through such efforts include cost savings, efficient tracking of outcomes, advanced clinical decision support, improved prognostic accuracy, and more reliable clinical trials matching. The overarching objective of the work presented here is the development and implementation of a flexible Intelligent Retrieval and Interrogation System (IRIS) that exploits the combined use of computational imaging, genomics, and data-mining capabilities to facilitate clinical assessments and translational research in oncology. The proposed System includes a multi-modal, Clinical & Research Data Warehouse (CRDW) that is tightly integrated with a suite of computational and machine-learning tools to provide insight into the underlying tumor characteristics that are not be apparent by human inspection alone. A key distinguishing feature of the System is a configurable Extract, Transform and Load (ETL) interface that enables it to adapt to different clinical and research data environments. This project is motivated by the growing emphasis on establishing Learning Health Systems in which cyclical hypothesis generation and evidence evaluation become integral to improving the quality of patient care. To facilitate iterative prototyping and optimization of the algorithms and workflows for the System, the team has already implemented a fully functional Warehouse that can reliably aggregate information originating from multiple data sources including EHR’s, Clinical Trial Management Systems, Tumor Registries, Biospecimen Repositories, Radiology PAC systems, Digital Pathology archives, Unstructured Clinical Documents, and Next Generation Sequencing services. The System enables physicians to systematically mine and review the molecular, genomic, image-based, and correlated clinical information about patient tumors individually or as part of large cohorts to identify patterns that may influence treatment decisions and outcomes. The CRDW core system has facilitated peer-reviewed publications and funded projects, including an NIH-sponsored collaboration to enhance the cancer registries in Georgia, Kentucky, New Jersey, and New York, with machine-learning based classifications and quantitative pathomics, feature sets. The CRDW has also resulted in a collaboration with the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) at the U.S. Department of Veterans Affairs to develop algorithms and workflows to automate the analysis of lung adenocarcinoma. Those studies showed that combining computational nuclear signatures with traditional WHO criteria through the use of deep convolutional neural networks (CNNs) led to improved discrimination among tumor growth patterns. The team has also leveraged the Warehouse to support studies to investigate the potential of utilizing a combination of genomic and computational imaging signatures to characterize prostate cancer. The results of those studies show that integrating image biomarkers with genomic pathway scores is more strongly correlated with disease recurrence than using standard clinical markers.

Keywords: clinical data warehouse, decision support, data-mining, intelligent databases, machine-learning.

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Authors: Garima Sarkar

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The main purpose of the present paper is to investigate the development and progress achieved by women in the decision-making sphere and to access the level of their political-participation in Parliamentary Elections of Malaysia and their status in overall Malaysian political domain. The paper also focuses on the role and status of women in the major political parties of the state both the parties in power as well as the parties in opposition. The primary objective of the study is to focus on the major hindrances and social malpractices faced by women and also Muslim women’s access to justice in Malaysia. It also demonstrates the linkages between national policy initiatives and the advancement of women in various areas, such as economics, health, employment, politics, power-sharing, social development and law and most importantly evaluating their status in the dominant religion of the nation. In Malaysia, women’s political participation is being challenged from every nook and corner of the society. A high percentage of women are getting educated, forming a significant labor force in present day Malaysia, who can be employed in the manufacturing sector, retail trade, hotels and restaurant, agriculture etc. Women today consist of almost half of the population and exceed boys in the tertiary sector by a ratio of 80:20. Despite these achievements, however, women’s labor force engagement remains confined to ‘ traditional women’s occupations’, such as those of primary school teachers, data entry clerks and organizing polls during elections and motivating other less enlightened women to cast their votes. In the political arena, the past few General Elections of Malaysia clearly exhibited a slight change in the number of women Members of Parliament from 10.6% (20 out of 193 Parliamentary seats in 1999) to 10.5% (23 out of 219 Parliamentary seats in 2004). Amidst the political posturing for the recent General Election in 2013 of Malaysia, women’s political participation remains a prime concern in Malaysia. It is evident that while much of the attention of women revolves around charitable assistance, they are much less likely to be portrayed as active participants in electoral politics and governance. According to the electoral roll for the third quarter of 2012, 6,578,916 women are registered as voters. They represent 50.2% of the total number of the registered voters. However, this parity in terms of voter registration is not reflected in the number of elected representatives at the Parliamentary level. Only 10.4% of sitting Members of Parliament are women. The women’s participation in the legislature and executive branches are important since their presence brings the spotlight squarely on issues that have been historically neglected and overlooked. In the recent 2013 General Elections in Malaysia out of 35 full ministerial position only two, or 5.7% have been filled by women. In each of the 2009, 2010, and in the present 2013 Cabinet members, there have only been two women ministers, with this number reduced to one briefly when the Prime Minister appointed himself placeholder in the Ministry of Women, Family and Community Development. In the recent past, in its Election Manifesto, Barisan Nasional made a pledge of ‘increasing the number of women participating in national decision-making processes’. Even after such pledges, the Malaysian leadership has failed to mirror the strong presence of women in leadership positions of public life which primarily includes politics, the judiciary and in business. There has been a strong urge to political parties by various gender-sensitive groups to nominate more women as candidates for contesting elections at the Parliamentary as well as at the State level. The democratization process will never be truly democratic without a proper gender agenda and representation. Although Malaysia signed the Beijing Platform for Action document in 1995, the state has a long way to go in enhancing the participation of women in every segment of Malaysian political, economic and cultural. There has been a small percentage of women representation in decision-making bodies compared to the 30% targeted by the Beijing Platform for Action. Thus, democratization in terms of representation of women in leadership positions and decision-making positions or bodies is essential since it’s a move towards a qualitative transformation of women in shaping national decision-making processes. The democratization process has to ensure women’s full participation and their goals of development and their full participation has to be included in the process of formulating and shaping the developmental goals.

Keywords: women, gender equality, Islam, democratization, political representation, Parliament

Procedia PDF Downloads 235