Search results for: water level change

Authors: Yuliya Y. Gavrichenko

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Background and Aims: The increasing bacterial resistance to almost all the available antibiotics has encouraged scientists to search for alternative sources of antibacterial agents. Nowadays, it is known that many plant secondary metabolites have diverse biological activity. These compounds can be potentially active against human bacterial and viral infections. Extended research has been carried out to explore the use of the luminescent bacterial test as a rapid, accurate and inexpensive method to assess the antibacterial properties and to predict the biological activity spectra for plant origin substances. Method: Botanical material of fifteen species was collected from their natural and cultural habitats on the Crimean peninsula. The aqueous extracts of following plants were tested: Robinia pseudoacacia L., Sideritis comosa, Cotinus coggygria Scop., Thymus serpyllum L., Juglans regia L., Securigera varia L., Achillea millefolium L., Phlomis taurica, Corylus avellana L., Sambucus nigra L., Helichrysum arenarium L., Glycyrrhiza glabra L., Elytrigia repens L., Echium vulgare L., Conium maculatum L. The test was carried out using luminous strains of marine bacteria Photobacterium leiognathi, which was isolated from the Sea of Azov as well as four Escherichia coli MG1655 recombinant strains harbouring Vibrio fischeri luxCDABE genes. Results: The bactericidal capacity of plant extracts showed significant differences in the study. Cotinus coggygria, Phlomis taurica, Juglans regia L. proved to be the most toxic to P. leiognathi. (EC50 = 0.33 g dried plant/l). Glycyrrhiza glabra L., Robinia pseudoacacia L., Sideritis comosa and Helichrysum arenarium L. had moderate inhibitory effects (EC50 = 3.3 g dried plant/l). The rest of the aqueous extracts have decreased the luminescence of no more than 50% at the lowest concentration (16.5 g dried plant/l). Antibacterial activity of herbal extracts against constitutively luminescent E. coli MG1655 (pXen7-lux) strain was observed at approximately the same level as for P. leiognathi. Cotinus coggygria and Conium maculatum L. extracts have increased light emission in the mutant E. coli MG1655 (pFabA-lux) strain which is associated with cell membranes damage. Sideritis comosa, Phlomis taurica, Juglans regia induced SOS response in E. coli (pColD-lux) strain. Glycyrrhiza glabra L. induced protein damage response in E. coli MG1655 (pIbpA-lux) strain. Conclusion: The received results have shown that the plants’ extracts had nonspecific antimicrobial effects against both E. coli (pXen7-lux) and P. leiognathi biosensors. Mutagenic, cytotoxic and protein damage effects have been observed. In general, the bioluminescent inhibition test result correlated with the traditional use of screened plants. It leads to the following conclusion that whole-cell luminescent biosensors could be the indicator of overall plants antibacterial capacity. The results of the investigation have shown a possibility of bioluminescent method in medicine and pharmacy as an approach to research the antibacterial properties of medicinal plants.

Keywords: antibacterial property, bioluminescence, medicinal plants, whole-cell biosensors

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Authors: Babak Forouraghi

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A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations of previous approaches, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with attention mechanism. In a previous work on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: transformers, generative ai, gene expression design, classification

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Authors: Alfredo Fortunato, Carmelofrancesco Origlia, Sara Laurita, Rossella Nicoletti

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In the post-pandemic recovery phase of tourism, the role of a Destination Management Organization (DMO) as a coordinated management system of all the elements that make up a destination (attractions, access, marketing, human resources, brand, pricing, etc.) is also becoming relevant for local territories. The objective of a DMO is to maximize the visitor's perception of value and quality while ensuring the competitiveness and sustainability of the destination, as well as the long-term preservation of its natural and cultural assets, and to catalyze benefits for the local economy and residents. In carrying out the multiple functions to which it is called, the DMO can leverage a collective intelligence that comes from the ability to pool information, explicit and tacit knowledge, and relationships of the various stakeholders: policymakers, public managers and officials, entrepreneurs in the tourism supply chain, researchers, data journalists, schools, associations and committees, citizens, etc. The DMO potentially has at its disposal large volumes of data and many of them at low cost, that need to be properly processed to produce value. Based on these assumptions, the paper presents a conceptual framework for building an information system to support the DMO in the intelligent management of a tourist destination tested in an area of southern Italy. The approach adopted is data-informed and consists of four phases: (1) formulation of the knowledge problem (analysis of policy documents and industry reports; focus groups and co-design with stakeholders; definition of information needs and key questions); (2) research and metadatation of relevant sources (reconnaissance of official sources, administrative archives and internal DMO sources); (3) gap analysis and identification of unconventional information sources (evaluation of traditional sources with respect to the level of consistency with information needs, the freshness of information and granularity of data; enrichment of the information base by identifying and studying web sources such as Wikipedia, Google Trends, Booking.com, Tripadvisor, websites of accommodation facilities and online newspapers); (4) definition of the set of indicators and construction of the information base (specific definition of indicators and procedures for data acquisition, transformation, and analysis). The framework derived consists of 6 thematic areas (accommodation supply, cultural heritage, flows, value, sustainability, and enabling factors), each of which is divided into three domains that gather a specific information need to be represented by a scheme of questions to be answered through the analysis of available indicators. The framework is characterized by a high degree of flexibility in the European context, given that it can be customized for each destination by adapting the part related to internal sources. Application to the case study led to the creation of a decision support system that allows: •integration of data from heterogeneous sources, including through the execution of automated web crawling procedures for data ingestion of social and web information; •reading and interpretation of data and metadata through guided navigation paths in the key of digital story-telling; •implementation of complex analysis capabilities through the use of data mining algorithms such as for the prediction of tourist flows.

Keywords: collective intelligence, data framework, destination management, smart tourism

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Authors: Jacqueline Eleonora Ek, Michael Spiteri, Chris Giordimaina, Pierre Agius

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Background: Malta is known for being a key player as a frontline country with regard to irregular immigration from Africa to Europe. Every year the island experiences an influx of migrants as boat movement across the Mediterranean continues to be a humanitarian challenge. Irregular immigration and applying for asylum is both a lengthy and mentally demanding process. Those doing so are often faced with multiple challenges, which can adversely affect their mental health. Between January and August 2020, Malta disembarked 2 162 people rescued at sea, 463 of them between July & August. Given the small size of the Maltese islands, this regulation places a disproportionately large burden on the country, creating a backlog in the processing of asylum applications resulting in increased time periods of detention. These delays reverberate throughout multiple management pathways resulting in prolonged periods of detention and challenging access to health services. Objectives: To better understand the spatial dimensions of this humanitarian crisis, this study aims to assess disparities in the acute medical management of migrants presenting to the emergency department (ED) with acute mental health presentations as compared to that of local and non-local residents. Method: In this retrospective study, 17795 consecutive ED attendances were reviewed to look for acute mental health presentations. These were further evaluated to assess discrepancies in transportation routes to hospital, nature of presenting complaint, effects of language barriers, use of CT brain, treatment given at ED, availability of psychiatric reviews, and final admission/discharge plans. Results: Of the ED attendances, 92.3% were local residents, and 7.7% were non-locals. Of the non-locals, 13.8% were migrants, and 86.2% were other-non-locals. Acute mental health presentations were seen in 1% of local residents; this increased to 20.6% in migrants. 56.4% of migrants attended with deliberate self-harm; this was lower in local residents, 28.9%. Contrastingly, in local residents, the most common presenting complaint was suicidal thought/ low mood 37.3%, the incidence was similar in migrants at 33.3%. The main differences included 12.8% of migrants presenting with refused oral intake while only 0.6% of local residents presented with the same complaints. 7.7% of migrants presented with a reduced level of consciousness, no local residents presented with this same issue. Physicians documented a language barrier in 74.4% of migrants. 25.6% were noted to be completely uncommunicative. Further investigations included the use of a CT scan in 12% of local residents and in 35.9% of migrants. The most common treatment administered to migrants was supportive fluids 15.4%, the most common in local residents was benzodiazepines 15.1%. Voluntary psychiatric admissions were seen in 33.3% of migrants and 24.7% of locals. Involuntary admissions were seen in 23% of migrants and 13.3% of locals. Conclusion: Results showed multiple disparities in health management. A meeting was held between entities responsible for migrant health in Malta, including the emergency department, primary health care, migrant detention services, and Malta Red Cross. Currently, national quality-improvement initiatives are underway to form new pathways to improve patient-centered care. These include an interpreter unit, centralized handover sheets, and a dedicated migrant health service.

Keywords: emergency department, communication, health, migration

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Authors: F. Iberraken, R. Medjoudj, D. Aissani

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The development of the smart grids concept is built around two separate definitions, namely: The European one oriented towards sustainable development and the American one oriented towards reliability and security of supply. In this paper, we have investigated reliability merits enabling decision-makers to provide a high quality of service. It is based on system behavior using interruptions and failures modeling and forecasting from one hand and on the contribution of information and communication technologies (ICT) to mitigate catastrophic ones such as blackouts from the other hand. It was found that this concept has been adopted by developing and emerging countries in short and medium terms followed by sustainability concept at long term planning. This work has highlighted the reliability merits such as: Benefits, opportunities, costs and risks considered as consistent units of measuring power customer satisfaction. From the decision making point of view, we have used the analytic hierarchy process (AHP) to achieve customer satisfaction, based on the reliability merits and the contribution of such energy resources. Certainly nowadays, fossil and nuclear ones are dominating energy production but great advances are already made to jump into cleaner ones. It was demonstrated that theses resources are not only environmentally but also economically and socially sustainable. The paper is organized as follows: Section one is devoted to the introduction, where an implicit review of smart grids development is given for the two main concepts (for USA and Europeans countries). The AHP method and the BOCR developments of reliability merits against power customer satisfaction are developed in section two. The benefits where expressed by the high level of availability, maintenance actions applicability and power quality. Opportunities were highlighted by the implementation of ICT in data transfer and processing, the mastering of peak demand control, the decentralization of the production and the power system management in default conditions. Costs were evaluated using cost-benefit analysis, including the investment expenditures in network security, becoming a target to hackers and terrorists, and the profits of operating as decentralized systems, with a reduced energy not supplied, thanks to the availability of storage units issued from renewable resources and to the current power lines (CPL) enabling the power dispatcher to manage optimally the load shedding. For risks, we have razed the adhesion of citizens to contribute financially to the system and to the utility restructuring. What is the degree of their agreement compared to the guarantees proposed by the managers about the information integrity? From technical point of view, have they sufficient information and knowledge to meet a smart home and a smart system? In section three, an application of AHP method is made to achieve power customer satisfaction based on the main energy resources as alternatives, using knowledge issued from a country that has a great advance in energy mutation. Results and discussions are given in section four. It was given us to conclude that the option to a given resource depends on the attitude of the decision maker (prudent, optimistic or pessimistic), and that status quo is neither sustainable nor satisfactory.

Keywords: reliability, AHP, renewable energy resources, smart grids

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Authors: Sara Mosteller, Larissa K. Samuelson, Sobanawartiny Wijeakumar, John P. Spencer

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This study was designed to examine how humans are able to teach and learn semantic information as well as cooperate in order to jointly achieve sophisticated goals. Specifically, we are measuring individual differences in how these abilities develop from foundational building blocks in early childhood. The current study adopts a paradigm for novel noun learning developed by Samuelson, Smith, Perry, and Spencer (2011) to a hyperscanning paradigm [Cui, Bryant and Reiss, 2012]. This project measures coordinated brain activity between a parent and child using simultaneous functional near infrared spectroscopy (fNIRS) in pairs of 2.5, 3.5 and 4.5-year-old children and their parents. We are also separately testing pairs of adult friends. Children and parents, or adult friends, are seated across from one another at a table. The parent (in the developmental study) then teaches their child the names of novel toys. An experimenter then tests the child by presenting the objects in pairs and asking the child to retrieve one object by name. Children are asked to choose from both pairs of familiar objects and pairs of novel objects. In order to explore individual differences in cooperation with the same participants, each dyad plays a cooperative game of Jenga, in which their joint score is based on how many blocks they can remove from the tower as a team. A preliminary analysis of the noun-learning task showed that, when presented with 6 word-object mappings, children learned an average of 3 new words (50%) and that the number of objects learned by each child ranged from 2-4. Adults initially learned all of the new words but were variable in their later retention of the mappings, which ranged from 50-100%. We are currently examining differences in cooperative behavior during the Jenga playing game, including time spent discussing each move before it is made. Ongoing analyses are examining the social dynamics that might underlie the differences between words that were successfully learned and unlearned words for each dyad, as well as the developmental differences observed in the study. Additionally, the Jenga game is being used to better understand individual and developmental differences in social coordination during a cooperative task. At a behavioral level, the analysis maps periods of joint visual attention between participants during the word learning and the Jenga game, using head-mounted eye trackers to assess each participant’s first-person viewpoint during the session. We are also analyzing the coherence in brain activity between participants during novel word-learning and Jenga playing. The first hypothesis is that visual joint attention during the session will be positively correlated with both the number of words learned and with the number of blocks moved during Jenga before the tower falls. The next hypothesis is that successful communication of new words and success in the game will each be positively correlated with synchronized brain activity between the parent and child/the adult friends in cortical regions underlying social cognition, semantic processing, and visual processing. This study probes both the neural and behavioral mechanisms of learning and cooperation in a naturalistic, interactive and developmental context.

Keywords: communication, cooperation, development, interaction, neuroscience

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Authors: Tzipi Eshet

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The primary objectives of this work are the examination of public preferences and attributed importance to different characteristics of coastal cliff protection alternatives, and drawing conclusions about the applicable alternative in Beit-Yanai beach. Erosion of coastal cliffs is a natural phenomenon that occurs in many places in the world. This creates problems along the coastlines, which are densely populated areas with highly developed economic activity. In recent years, various aspects of the aeolianite cliffs along the Israeli coast have been studied extensively. There is a consensus among researchers regarding a general trend of cliff retreat. This affects civilian infrastructure, wildlife habitats and heritage values, as well as Increases the risk to human life. The Israeli government, committed to the integrated coastal zones management approach, decided on a policy and guidelines to deal with cliff erosion, which includes establishing physical protection on land and in the sea, sand nourishment and runoff drainage. Physical protection solutions to reduce the rate of retreat of the cliffs are considerably important both for planning authorities and visitors to the beach. Direct costs of different protection alternatives, as well as external costs and benefits, may vary, thus affecting consumer preferences. Planning and execution of sustainable coastal cliff protection alternatives must take into account the different characteristics and their impact on aspects of economics, environment and leisure. The rocky shore of Beit-Yanai Beach was chosen as a case study to examine the nature of the influence of various protective solutions on consumer preferences. This beach is located in the center of Israel's coastline, and acts as a focus of attraction for recreation, land and sea sports, and educational activities as well. If no action will be taken, cliff retreat will continue. A survey was conducted to reveal the importance of coastal protection alternatives characteristics and the visual preferences to visitors at beach Beit-Yanai and residents living on the cliff (N=287). Preferences and willingness-to-pay were explored using Contingent-Ranking and Choice-Experiments techniques. Results show that visitors’ and residents’ willingness-to-pay for coastal cliff protection alternatives is affected both by financial and environmental aspects, as well as leisure. They prefer coastal cliff protection alternatives that are not visible and do not need constant maintenance, do not affect the quality of seawater or the habitats of wildlife and do not lower the security level of the swimmers. No significant difference was found comparing willingness-to-pay among local and non-local users. Additionally, they mostly prefer a protection solution which is integrated in the coastal landscape and maintains the natural appearance of the beach. Of the possible protection alternatives proposed for the protection of the cliff in Beit Yanai beach are two techniques that meet public preferences: rock revetments and submerged detached breakwaters. Results indicate that the visiting public prefer the implementation of these protection alternatives and will be willing to pay for them. Future actions to reduce retreat rate in Beit-Yanai have to consider implications on the economic, environmental and social conditions, along with weighting public interest against the interest of the individual.

Keywords: contingent-ranking, choice-experiments, coastal cliff protection, erosion of coastal cliffs, environment

Procedia PDF Downloads 267

Authors: Mei Chen, Yingping Hou, Michelle Hao, Soheil Aghamohammadzadeh, Esteban Terzo, Roger Clark, Vijay Modur

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Background: Recessive Dystrophic Epidermolysis Bullosa (RDEB) is a genetic skin condition characterized by skin tearing and unremitting blistering upon minimal trauma. Repeated blistering, fibrosis, and scarring lead to aggressive squamous cell carcinoma later in life. RDEB is caused by mutations in the COL7A1 gene encoding collagen type VII (C7), the major component of anchoring fibrils mediating epidermis-dermis adherence. Nonsense mutations in the COL7A1 gene of a subset of RDEB patients leads to premature termination codons (PTC). Similarly, most Junctional Epidermolysis Bullosa (JEB) cases are caused by nonsense mutations in the LAMB3 gene encoding the β3 subunit of laminin 332. Currently, there is an unmet need for the treatment of RDEB and JEB. Zikani Therapeutics has discovered an array of macrocyclic compounds with ring structures similar to macrolide antibiotics that can facilitate readthrough activity of nonsense mutations in the COL7A1 and LAMB3 genes by acting as Ribosome Modulating Agents (RMAs). The medicinal chemistry synthetic advancements of these macrocyclic compounds have allowed targeting the human ribosome while preserving the structural elements responsible for the safety and pharmacokinetic profile of clinically used macrolide antibiotics. Methods: C7 expression was used as a measure of readthrough activity by immunoblot assays in two primary human fibroblasts from RDEB patients (R578X/R578X and R163X/R1683X-COL7A1). Similarly, immunoblot assays in C325X/c.629-12T > A-LAMB3 keratinocytes were used to measure readthrough activity for JEB. The relative readthrough activity of each compound was measured relative to Gentamicin. An imaging-based fibroblast migration assay was used as an assessment of C7 functionality in RDEB-fibroblasts over 16-20 hrs. The incubation period for the above experiments was 48 hrs for RDEB fibroblasts and 72 hours for JEB keratinocytes. Results: 9 RMAs demonstrated increased protein expression in both patient RDEB fibroblasts. The highest readthrough activity at tested concentrations without cytotoxicities increased protein expression up to 179% of Gentamicin (400 µg/ml), with favored readthrough activity in R163X/R1683X-COL7A1 fibroblasts. Concurrent with protein expression, fibroblast hypermotility phenotype observed in RDEB was rescued by reducing motility by ~35% to WT levels (the same level as 690 µM Gentamicin treated cells). Laminin β3 expression was also shown to be increased by 6 RMAs in keratinocytes to 33-83% of (400 µg/ml) Gentamicin. Conclusions: To date, 9 RMAs have been identified that enhance the expression of functional C7 in a mutation-dependent manner in two different RDEB patient fibroblast backgrounds (R578X/R578X and R163X/R1683X-COL7A1). A further 6 RMAs have been identified that enhance the readthrough of C325X-LAMB3 in JEB patient keratinocytes. Based on the clinical trial conducted by us with topical gentamycin in 2017, Zikani’s RMAs achieve clinically significant levels of read-through for the treatment of recessive dystrophic and Junctional Epidermolysis Bullosa.

Keywords: epidermolysis bullosa, nonsense mutation, readthrough, ribosome modulation

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Authors: Lynn Sheridan, Dennis Alonzo, Hoa Nguyen, Andy Gao, Tracy Durksen

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Disruptions to teaching (e.g., COVID-related) have increased work demands for teachers. There is an opportunity for research to explore evidence-informed steps to support teachers. Collective evidence informs data on teachers’ personal attributes (e.g., self-efficacy beliefs) in the workplace are seen to promote success in teaching and support teacher engagement. Teacher engagement plays a role in students’ learning and teachers’ effectiveness. Engaged teachers are better at overcoming work-related stress, burnout and are more likely to take on active roles. Teachers’ commitment is influenced by a host of personal (e.g., teacher well-being) and environmental factors (e.g., job stresses). The job demands-resources model provided a conceptual basis for examining how teachers’ well-being, and is influenced by job demands and job resources. Job demands potentially evoke strain and exceed the employee’s capability to adapt. Job resources entail what the job offers to individual teachers (e.g., organisational support), helping to reduce job demands. The application of the job demands-resources model involves gathering an evidence-base of and connection to personal attributes (job resources). The study explored the association between constructs (resilience, adaptability, commitment, self/collective efficacy) and a teacher’s engagement with the job. The paper sought to elaborate on the model and determine the associations between key constructs of well-being (resilience, adaptability), commitment, and motivation (self and collective-efficacy beliefs) to teachers’ engagement in teaching. Data collection involved online a multi-dimensional instrument using validated items distributed from 2020-2022. The instrument was designed to identify construct relationships. The participant number was 170. Data Analysis: The reliability coefficients, means, standard deviations, skewness, and kurtosis statistics for the six variables were completed. All scales have good reliability coefficients (.72-.96). A confirmatory factor analysis (CFA) and structural equation model (SEM) were performed to provide measurement support and to obtain latent correlations among factors. The final analysis was performed using structural equation modelling. Several fit indices were used to evaluate the model fit, including chi-square statistics and root mean square error of approximation. The CFA and SEM analysis was performed. The correlations of constructs indicated positive correlations exist, with the highest found between teacher engagement and resilience (r=.80) and the lowest between teacher adaptability and collective teacher efficacy (r=.22). Given the associations; we proceeded with CFA. The CFA yielded adequate fit: CFA fit: X (270, 1019) = 1836.79, p < .001, RMSEA = .04, and CFI = .94, TLI = .93 and SRMR = .04. All values were within the threshold values, indicating a good model fit. Results indicate that increasing teacher self-efficacy beliefs will increase a teacher’s level of engagement; that teacher ‘adaptability and resilience are positively associated with self-efficacy beliefs, as are collective teacher efficacy beliefs. Implications for school leaders and school systems: 1. investing in increasing teachers’ sense of efficacy beliefs to manage work demands; 2. leadership approaches can enhance teachers' adaptability and resilience; and 3. a culture of collective efficacy support. Preparing teachers for now and in the future offers an important reminder to policymakers and school leaders on the importance of supporting teachers’ personal attributes when faced with the challenging demands of the job.

Keywords: collective teacher efficacy, teacher self-efficacy, job demands, teacher engagement

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Authors: Md. Abu Sufian, Robiqul Islam, Imam Hossain Shajid, Mahesh Hanumanthu, Jarasree Varadarajan, Md. Sipon Miah, Mingbo Niu

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Coronary Heart Disease (CHD) remains a principal cause of global morbidity and mortality, characterized by atherosclerosis—the build-up of fatty deposits inside the arteries. The study introduces an innovative methodology that leverages cloud-based platforms like AWS Live Streaming and Artificial Intelligence (AI) to early detect and prevent CHD symptoms in web applications. By employing novel simulation processes and AI algorithms, this research aims to significantly mitigate the health and societal impacts of CHD. Methodology: This study introduces a novel simulation process alongside a multi-phased model development strategy. Initially, health-related data, including heart rate variability, blood pressure, lipid profiles, and ECG readings, were collected through user interactions with web-based applications as well as API Integration. The novel simulation process involved creating synthetic datasets that mimic early-stage CHD symptoms, allowing for the refinement and training of AI algorithms under controlled conditions without compromising patient privacy. AWS Live Streaming was utilized to capture real-time health data, which was then processed and analysed using advanced AI techniques. The novel aspect of our methodology lies in the simulation of CHD symptom progression, which provides a dynamic training environment for our AI models enhancing their predictive accuracy and robustness. Model Development: it developed a machine learning model trained on both real and simulated datasets. Incorporating a variety of algorithms including neural networks and ensemble learning model to identify early signs of CHD. The model's continuous learning mechanism allows it to evolve adapting to new data inputs and improving its predictive performance over time. Results and Findings: The deployment of our model yielded promising results. In the validation phase, it achieved an accuracy of 92% in predicting early CHD symptoms surpassing existing models. The precision and recall metrics stood at 89% and 91% respectively, indicating a high level of reliability in identifying at-risk individuals. These results underscore the effectiveness of combining live data streaming with AI in the early detection of CHD. Societal Implications: The implementation of cloud-based AI for CHD symptom detection represents a significant step forward in preventive healthcare. By facilitating early intervention, this approach has the potential to reduce the incidence of CHD-related complications, decrease healthcare costs, and improve patient outcomes. Moreover, the accessibility and scalability of cloud-based solutions democratize advanced health monitoring, making it available to a broader population. This study illustrates the transformative potential of integrating technology and healthcare, setting a new standard for the early detection and management of chronic diseases.

Keywords: coronary heart disease, cloud-based ai, machine learning, novel simulation techniques, early detection, preventive healthcare

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Authors: Diana Reckien

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Vulnerability assessments are increasingly used to support policy-making in complex environments, like urban areas. Usually, vulnerability studies include the construction of aggregate (sub-) indices and the subsequent mapping of indices across an area of interest. Vulnerability studies show a couple of advantages: they are great communication tools, can inform a wider general debate about environmental issues, and can help allocating and efficiently targeting scarce resources for adaptation policy and planning. However, they also have a number of challenges: Vulnerability assessments are constructed on the basis of a wide range of methodologies and there is no single framework or methodology that has proven to serve best in certain environments, indicators vary highly according to the spatial scale used, different variables and metrics produce different results, and aggregate or composite vulnerability indicators that are mapped easily distort or bias the picture of vulnerability as they hide the underlying causes of vulnerability and level out conflicting reasons of vulnerability in space. So, there is urgent need to further develop the methodology of vulnerability studies towards a common framework, which is one reason of the paper. We introduce a social vulnerability approach, which is compared with other approaches of bio-physical or sectoral vulnerability studies relatively developed in terms of a common methodology for index construction, guidelines for mapping, assessment of sensitivity, and verification of variables. Two approaches are commonly pursued in the literature. The first one is an additive approach, in which all potentially influential variables are weighted according to their importance for the vulnerability aspect, and then added to form a composite vulnerability index per unit area. The second approach includes variable reduction, mostly Principal Component Analysis (PCA) that reduces the number of variables that are interrelated into a smaller number of less correlating components, which are also added to form a composite index. We test these two approaches of constructing indices on the area of New York City as well as two different metrics of variables used as input and compare the outcome for the 5 boroughs of NY. Our analysis yields that the mapping exercise yields particularly different results in the outer regions and parts of the boroughs, such as Outer Queens and Staten Island. However, some of these parts, particularly the coastal areas receive the highest attention in the current adaptation policy. We imply from this that the current adaptation policy and practice in NY might need to be discussed, as these outer urban areas show relatively low social vulnerability as compared with the more central parts, i.e. the high dense areas of Manhattan, Central Brooklyn, Central Queens and the Southern Bronx. The inner urban parts receive lesser adaptation attention, but bear a higher risk of damage in case of hazards in those areas. This is conceivable, e.g., during large heatwaves, which would more affect more the inner and poorer parts of the city as compared with the outer urban areas. In light of the recent planning practice of NY one needs to question and discuss who in NY makes adaptation policy for whom, but the presented analyses points towards an under representation of the needs of the socially vulnerable population, such as the poor, the elderly, and ethnic minorities, in the current adaptation practice in New York City.

Keywords: vulnerability mapping, social vulnerability, additive approach, Principal Component Analysis (PCA), New York City, United States, adaptation, social sensitivity

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Authors: Vijaya Dixit Aasheesh Dixit

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Shipbuilding industry operates in Engineer Procure Construct (EPC) context. Product mix of a shipyard comprises of various types of ships like bulk carriers, tankers, barges, coast guard vessels, sub-marines etc. Each order is unique based on the type of ship and customized requirements, which are engineered into the product right from design stage. Thus, to execute every new project, a shipyard needs to upgrade its production expertise. As a result, over the long run, holistic learning occurs across different types of projects which contributes to the knowledge base of the shipyard. Simultaneously, in the short term, during execution of a project comprising of multiple sister ships, repetition of similar tasks leads to learning at activity level. This research aims to capture above learnings of a shipyard and incorporate learning curve effect in project scheduling and materials procurement to improve project performance. Extant literature provides support for the existence of such learnings in an organization. In shipbuilding, there are sequences of similar activities which are expected to exhibit learning curve behavior. For example, the nearly identical structural sub-blocks which are successively fabricated, erected, and outfitted with piping and electrical systems. Learning curve representation can model not only a decrease in mean completion time of an activity, but also a decrease in uncertainty of activity duration. Sister ships have similar material requirements. The same supplier base supplies materials for all the sister ships within a project. On one hand, this provides an opportunity to reduce transportation cost by batching the order quantities of multiple ships. On the other hand, it increases the inventory holding cost at shipyard and the risk of obsolescence. Further, due to learning curve effect the production scheduled of each consequent ship gets compressed. Thus, the material requirement schedule of every next ship differs from its previous ship. As more and more ships get constructed, compressed production schedules increase the possibility of batching the orders of sister ships. This work aims at integrating materials management with project scheduling of long duration projects for manufacturing of multiple sister ships. It incorporates the learning curve effect on progressively compressing material requirement schedules and addresses the above trade-off of transportation cost and inventory holding and shortage costs while satisfying budget constraints of various stages of the project. The activity durations and lead time of items are not crisp and are available in the form of probabilistic distribution. A Stochastic Mixed Integer Programming (SMIP) model is formulated which is solved using evolutionary algorithm. Its output provides ordering dates of items and degree of order batching for all types of items. Sensitivity analysis determines the threshold number of sister ships required in a project to leverage the advantage of learning curve effect in materials management decisions. This analysis will help materials managers to gain insights about the scenarios: when and to what degree is it beneficial to treat a multiple ship project as an integrated one by batching the order quantities and when and to what degree to practice distinctive procurement for individual ship.

Keywords: learning curve, materials management, shipbuilding, sister ships

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Authors: Sara Saboonian, Pierre Filion

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The dispersed-suburban model has been the dominant one across North America for the past seventy years, characterized by automobile reliance, low density, and land-use specialization. Two planning models have emerged as possible alternatives to address the ills inflicted by this development pattern. First, there is intensification, which promotes efficient infrastructure by connecting high-density, multi-functional, and walkable nodes with public transit services within the suburban landscape. Second is green infrastructure, which provides environmental health and human well-being by preserving and restoring ecosystem services. This research studies incompatibilities and the possibility of amalgamating the two alternatives in an attempt to develop a comprehensive alternative to suburban model that advocates density, multi-functionality and transit- and pedestrian-conduciveness, with measures capable of mitigating the adverse environmental impacts of compactness. The research investigates three Canadian urban growth centers, where intensification is the current planning practice, and the awareness of green infrastructure benefits is on the rise. However, these three centers are contrasted by their development stage, the presence or absence of protected natural land, their environmental approach, and their adverse environmental consequences according to the planning cannons of different periods. The methods include reviewing the literature on green infrastructure planning, criticizing the Ontario provincial plans for intensification, surveying residents’ preferences for alternative models, and interviewing officials who deal with the local planning for the centers. Moreover, the research draws on recalling debates between New Urbanism and Landscape/Ecological Urbanism. The case studies expose the difficulties in creating urban growth centres that accommodate green infrastructure while adhering to intensification principles. First, the dominant status of intensification and the obstacles confronting intensification have monopolized the planners’ concerns. Second, the tension between green infrastructure and intensification explains the absence of the green infrastructure typologies that correspond to intensification-compatible forms and dynamics. Finally, the lack of highlighted social-economic benefits of green infrastructure reduces residents’ participation. Moreover, the results from the research provide insight into predominating urbanization theories, New Urbanism and Landscape/Ecological Urbanism. In order to understand political, planning, and ecological dynamics of such blending, dexterous context-specific planning is required. Findings suggest the influence of the following factors on amalgamating intensification and green infrastructure. Initially, producing ecosystem services-based justifications for green infrastructure development in the intensification context provides an expert-driven backbone for the implementation programs. This knowledge-base should be translated to effectively imbue different urban stakeholders. Moreover, due to the limited greenfields in intensified areas, spatial distribution and development of multi-level corridors such as pedestrian-hospitable settings and transportation networks along green infrastructure measures are required. Finally, to ensure the long-term integrity of implemented green infrastructure measures, significant investment in public engagement and education, as well as clarification of management responsibilities is essential.

Keywords: ecosystem services, green infrastructure, intensification, planning

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Authors: Juliane Toce, Steven Holochwost

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A substantial and growing literature has demonstrated that arts education benefits young children’s socioemotional and cognitive development. Less is known about the capacity of arts-integrated instruction to yield benefits to similar domains, particularly among demographically and socioeconomically diverse groups of young children. However, the small literature on this topic suggests that arts-integrated instruction may foster young children’s socioemotional and cognitive development by presenting opportunities to 1) engage in instructional content in diverse ways, 2) experience and regulate strong emotions, 3) experience growth-oriented feedback, and 4) engage in collaborative work with peers. Start with the Art is a new program of arts-integrated instruction currently being implemented in four schools in a school district that serves students from a diverse range of backgrounds. The program employs a co-teaching model in which teaching artists and classroom teachers engage in collaborative lesson planning and instruction over the course of the academic year and is currently the focus of an impact study featuring a randomized-control design, as well as an implementation study, both of which are funded through an Educational Innovation and Research grant from the United States Department of Education. The paper will present the early results from the Start with the Art implementation study. These results will provide an overview of the extent to which the program was implemented in accordance with design, with a particular emphasis on the degree to which the four opportunities enumerated above (e.g., opportunities to engage in instructional content in diverse ways) were presented to students. There will be a review key factors that may influence the fidelity of implementation, including classroom teachers’ reception of the program and the extent to which extant conditions in the classroom (e.g., the overall level of classroom organization) may have impacted implementation fidelity. With the explicit purpose of creating a program that values and meets the needs of the teachers and students, Start with the Art incorporates the feedback from individuals participating in the intervention. Tracing its trajectory from inception to ongoing development and examining the adaptive changes made in response to teachers' transformative experiences in the post-pandemic classroom, Start with the Art continues to solicit input from experts in integrating artistic content into core curricula within educational settings catering to students from under-represented backgrounds in the arts. Leveraging the input from this rich consortium of experts has allowed for a comprehensive evaluation of the program’s implementation. The early findings derived from the implementation study emphasize the potential of arts-integrated instruction to incorporate restorative practices. Such practices serve as a crucial support system for both students and educators, providing avenues for children to express themselves, heal emotionally, and foster social development, while empowering teachers to create more empathetic, inclusive, and supportive learning environments. This all-encompassing analysis spotlights Start with the Art’s adaptability to any learning environment through the program’s effectiveness, resilience, and its capacity to transform - through art - the classroom experience within the ever-evolving landscape of education.

Keywords: arts-integration, social emotional learning, diverse learners, co-teaching, teaching artists, post-pandemic teaching

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Authors: Nada Poropat Jeletic, Gordana Hrzica

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Bilingual conversational corpora represent a meaningful and the most comprehensive data source for investigating the genuine contact phenomena in non-monitored bi-lingual speech productions. They can be particularly useful for bilingual research since some features of bilingual interaction can hardly be accessed with more traditional methodologies (e.g., elicitation tasks). The method of language sampling provides the resources for describing language interaction in a bilingual community and/or in bilingual situations (e.g. code-switching, amount of languages used, number of languages used, etc.). To capture these phenomena in genuine communication situations, such sampling should be as close as possible to spontaneous communication. Bilingual spoken corpus design is methodologically demanding. Therefore this paper aims at describing the methodological challenges that apply to the corpus design of the conversational corpus design of the Istrian Istrovenetian-Croatian Bilingual Corpus. Croatian is the first official language of the Croatian-Italian officially bilingual Istria County, while Istrovenetian is a diatopic subvariety of Venetian, a longlasting lingua franca in the Istrian peninsula, the mother tongue of the members of the Italian National Community in Istria and the primary code of informal everyday communication among the Istrian Italophone population. Within the CLARIN infrastructure, TalkBank is being used, as it provides relevant procedures for designing and analyzing bilingual corpora. Furthermore, it allows public availability allows for easy replication of studies and cumulative progress as a research community builds up around the corpus, while the tools developed within the field of corpus linguistics enable easy retrieval and analysis of information. The method of language sampling employed is kept at the level of spontaneous communication, in order to maximise the naturalness of the collected conversational data. All speakers have provided written informed consent in which they agree to be recorded at a random point within the period of one month after signing the consent. Participants are administered a background questionnaire providing information about the socioeconomic status and the exposure and language usage in the participants social networks. Recording data are being transcribed, phonologically adapted within a standard-sized orthographic form, coded and segmented (speech streams are being segmented into communication units based on syntactic criteria) and are being marked following the CHAT transcription system and its associated CLAN suite of programmes within the TalkBank toolkit. The corpus consists of transcribed sound recordings of 36 bilingual speakers, while the target is to publish the whole corpus by the end of 2020, by sampling spontaneous conversations among approximately 100 speakers from all the bilingual areas of Istria for ensuring representativeness (the participants are being recruited across three generations of native bilingual speakers in all the bilingual areas of the peninsula). Conversational corpora are still rare in TalkBank, so the Corpus will contribute to BilingBank as a highly relevant and scientifically reliable resource for an internationally established and active research community. The impact of the research of communities with societal bilingualism will contribute to the growing body of research on bilingualism and multilingualism, especially regarding topics of language dominance, language attrition and loss, interference and code-switching etc.

Keywords: conversational corpora, bilingual corpora, code-switching, language sampling, corpus design methodology

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Authors: Stanislav Babaev, Vladimir Cuk, Sjef Cobben, Jan Desmet

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The procedures for performing harmonic studies for medium-voltage distribution feeders have become relatively mature topics since the early 1980s. The efforts of various electric power engineers and researchers were mainly focused on handling large harmonic non-linear loads connected scarcely at several buses of medium-voltage feeders. In order to assess the impact of these loads on the voltage quality of the distribution system, specific modeling and simulation strategies were proposed. These methodologies could deliver a reasonable estimation accuracy given the requirements of least computational efforts and reduced complexity. To uphold these requirements, certain analysis assumptions have been made, which became de facto standards for establishing guidelines for harmonic analysis. Among others, typical assumptions include balanced conditions of the study and the negligible impact of impedance frequency characteristics of various power system components. In latter, skin and proximity effects are usually omitted, and resistance and reactance values are modeled based on the theoretical equations. Further, the simplifications of the modelling routine have led to the commonly accepted practice of neglecting phase angle diversity effects. This is mainly associated with developed load models, which only in a handful of cases are representing the complete harmonic behavior of a certain device as well as accounting on the harmonic interaction between grid harmonic voltages and harmonic currents. While these modelling practices were proven to be reasonably effective for medium-voltage levels, similar approaches have been adopted for low-voltage distribution systems. Given modern conditions and massive increase in usage of residential electronic devices, recent and ongoing boom of electric vehicles, and large-scale installing of distributed solar power, the harmonics in current low-voltage grids are characterized by high degree of variability and demonstrate sufficient diversity leading to a certain level of cancellation effects. It is obvious, that new modelling algorithms overcoming previously made assumptions have to be accepted. In this work, a simulation approach aimed to deal with some of the typical assumptions is proposed. A practical low-voltage feeder is modeled in PowerFactory. In order to demonstrate the importance of diversity effect and harmonic interaction, previously developed measurement-based models of photovoltaic inverter and battery charger are used as loads. The Python-based script aiming to supply varying voltage background distortion profile and the associated current harmonic response of loads is used as the core of unbalanced simulation. Furthermore, the impact of uncertainty of feeder frequency-impedance characteristics on total harmonic distortion levels is shown along with scenarios involving linear resistive loads, which further alter the impedance of the system. The comparative analysis demonstrates sufficient differences with cases when all the assumptions are in place, and results indicate that new modelling and simulation procedures need to be adopted for low-voltage distribution systems with high penetration of non-linear loads and renewable generation.

Keywords: electric power system, harmonic distortion, power quality, public low-voltage network, harmonic modelling

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Authors: Monica Arnaudo, Monika Topel, Bjorn Laumert

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Within the Swedish context, the current trend of relatively low electricity prices promotes the electrification of the energy infrastructure. The residential heating sector takes part in this transition by proposing a switch from a centralized district heating system towards a distributed heat pumps-based setting. When it comes to urban environments, two issues arise. The first, seen from an electricity-sector perspective, is related to the fact that existing networks are limited with regards to their installed capacities. Additional electric loads, such as heat pumps, can cause severe overloads on crucial network elements. The second, seen from a heating-sector perspective, has to do with the fact that the indoor comfort conditions can become difficult to handle when the operation of the heat pumps is limited by a risk of overloading on the distribution grid. Furthermore, the uncertainty of the electricity market prices in the future introduces an additional variable. This study aims at assessing the extent to which distributed heat pumps can penetrate an existing heat energy network while respecting the technical limitations of the electricity grid and the thermal comfort levels in the buildings. In order to account for the multi-disciplinary nature of this research question, a cosimulation modeling approach was adopted. In this way, each energy technology is modeled in its customized simulation environment. As part of the cosimulation methodology: a steady-state power flow analysis in pandapower was used for modeling the electrical distribution grid, a thermal balance model of a reference building was implemented in EnergyPlus to account for space heating and a fluid-cycle model of a heat pump was implemented in JModelica to account for the actual heating technology. With the models set in place, different scenarios based on forecasted electricity market prices were developed both for present and future conditions of Hammarby Sjöstad, a neighborhood located in the south-east of Stockholm (Sweden). For each scenario, the technical and the comfort conditions were assessed. Additionally, the average cost of heat generation was estimated in terms of levelized cost of heat. This indicator enables a techno-economic comparison study among the different scenarios. In order to evaluate the levelized cost of heat, a yearly performance simulation of the energy infrastructure was implemented. The scenarios related to the current electricity prices show that distributed heat pumps can replace the district heating system by covering up to 30% of the heating demand. By lowering of 2°C, the minimum accepted indoor temperature of the apartments, this level of penetration can increase up to 40%. Within the future scenarios, if the electricity prices will increase, as most likely expected within the next decade, the penetration of distributed heat pumps can be limited to 15%. In terms of levelized cost of heat, a residential heat pump technology becomes competitive only within a scenario of decreasing electricity prices. In this case, a district heating system is characterized by an average cost of heat generation 7% higher compared to a distributed heat pumps option.

Keywords: cosimulation, distributed heat pumps, district heating, electrical distribution grid, integrated energy systems

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Authors: Majed Al Otaibi, Melissa Lessard-Beaudoin, Amel Loudghi, Raphael Chouinard-Watkins, Melanie Plourde, Frederic Calon, C. Alexandre Castellano, Stephen Cunnane, Helene Payette, Pierrette Gaudreau, Denis Gris, Rona K. Graham

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Introduction: Alzheimer disease (AD) is a chronic disorder that affects millions of individuals worldwide. Symptoms include memory dysfunction, and also alterations in attention, planning, language and overall cognitive function. Olfactory dysfunction is a common symptom of several neurological disorders including AD. Studying the mechanisms underlying the olfactory dysfunction may therefore lead to the discovery of potential biomarkers and/or treatments for neurodegenerative diseases. Objectives: To determine if olfactory dysfunction predicts future cognitive impairment in the aging population and to characterize the olfactory system in a murine model expressing a genetic factor of AD. Method: For the human study, quantitative olfactory tests (UPSIT and OMT) have been done on 93 subjects (aged 80 to 94 years) from the Quebec Longitudinal Study on Nutrition and Successful Aging (NuAge) cohort accepting to participate in the ORCA secondary study. The telephone Modified Mini Mental State examination (t-MMSE) was used to assess cognition levels, and an olfactory self-report was also collected. In a separate cohort, olfactory cortical volume was calculated using MRI results from healthy old adults (n=25) and patients with AD (n=18) using the AAL single-subject atlas and performed with the PNEURO tool (PMOD 3.7). For the murine study, we are using Western blotting, RT-PCR and immunohistochemistry. Result: Human Study: Based on the self-report, 81% of the participants claimed to not suffer from any problem with olfaction. However, based on the UPSIT, 94% of those subjects showed a poor olfactory performance and different forms of microsmia. Moreover, the results confirm that olfactory function declines with age. We also detected a significant decrease in olfactory cortical volume in AD individuals compared to controls. Murine study: Preliminary data demonstrate there is a significant decrease in expression levels of the proform of caspase-3 and the caspase substrate STK3, in the olfactory bulb of mice expressing human APOE4 compared with controls. In addition, there is a significant decrease in the expression level of the caspase-9 proform and caspase-8 active fragment. Analysis of the mature neuron marker, NeuN, shows decreased expression levels of both isoforms. The data also suggest that Iba-1 immunostaining is increased in the olfactory bulb of APOE4 mice compared to wild type mice. Conclusions: The activation of caspase-3 may be the cause of the decreased levels of STK3 through caspase cleavage and may play role in the inflammation observed. In the clinical study, our results suggest that seniors are unaware of their olfactory function status and therefore it is not sufficient to measure olfaction using the self-report in the elderly. Studying olfactory function and cognitive performance in the aging population will help to discover biomarkers in the early stage of the AD.

Keywords: Alzheimer's disease, APOE4, cognition, caspase, brain atrophy, neurodegenerative, olfactory dysfunction

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Authors: R. Pardo, P. Menendez, MA Gil-Olarte, S. Sanchez, E. García, R. Quintana, J. Martín

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Introduction : Within oncoplastic breast techniques there is increased interest in immediate partial breast reconstruction. The volume resected is greater than that of conventional conservative techniques. Central tumours of the breast have classically been treated with a mastectomy with regard to oncological safety and cosmetic secondary effects after wide central resection of the nipple and breast tissue beneath. Oncological results for central quadrantectomy have a recurrence level, disease- free period and survival identical to mastectomy. Grissoti flap is an oncoplastic surgical technique that allows the surgeon to perform a safe central quadrantectomy with excellent cosmetic results. Material and methods: The Grissoti flap is a glandular cutaneous advancement rotation flap that can fill the defect in the central portion of the excised breast. If the inferior border is affected by tumour and further surgery is decided upon at the Multidisciplinary Team Meeting, it will be necessary to perform a mastectomy. All patients with a Grisotti flap undergoing surgery since 2009 were reviewed obtaining the following data: age, hystopathological diagnosis, size, operating time, volume of tissue resected, postoperative admission time, re-excisions due to positive margins affected by tumour, wound dehiscence, complications and recurrence. Analysis and results of sentinel node biopsy were also obtained. Results: 12 patients underwent surgery between 2009-2015. The mean age was 54 years (34-67) . All had a preoperative diagnosis of ductal infiltrative carcinoma of less than 2 cm,. Diagnosis was made with Ultrasound, Mamography or both . Magnetic resonance was used in 5 cases. No patients had preoperative positive axilla after ultrasound exploration. Mean operating time was 104 minutes (84-130). Postoperative stay was 24 hours. Mean volume resected was 159 cc (70-286). In one patient the surgical border was affected by tumour and a further procedure with resection of the affected border was performed as ambulatory surgery. The sentinel node biopsy was positive for micrometastasis in only two cases. In one case lymphadenectomy was performed in 2009. In the other, treated in 2015, no lymphadenectomy was performed as the patient had a favourable histopathological prognosis and the multidisciplinary team meeting agreed that lymphadenectomy was not required. No recurrence has been diagnosed in any of the patients who underwent surgery and they are all disease free at present. Conclusions: Conservative surgery for retroareolar central tumours of the breast results in good local control of the disease with free surgical borders, including resection of the nipple areola complex and pectoral major muscle fascia. Reconstructive surgery with the inferior Grissoti flap adequately fills the defect after central quadrantectomy with creation of a new cutaneous disc where a new nipple areola complex is reconstructed with a local flap or micropigmentation. This avoids the need for contralateral symmetrization. Sentinel Node biopsy can be performed without added morbidity. When feasible, the Grissoti flap will avoid skin-sparing mastectomy for central breast tumours that will require the use of an expander, prosthesis or myocutaneous flap, with all the complications of a more complex operation.

Keywords: Grisotti flap, oncoplastic surgery, central tumours, breast

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Authors: O. Zlatkin-Troitschanskaia, J. Fischer, C. Lautenbach, H. A. Pant

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In 21st century higher education (HE), the diversity among students has increased in recent years due to the internationalization and higher mobility. Offering and providing equal and fair opportunities based on students’ individual skills and abilities instead of their social or cultural background is one of the major aims of HE. In this context, valid, objective and transparent assessments of students’ preconditions and academic competencies in HE are required. However, as analyses of the current states of research and practice show, a substantial research gap on assessment practices in HE still exists, calling for the development of effective solutions. These demands lead to significant conceptual and methodological challenges. Funded by the German Federal Ministry of Education and Research, the research program 'Modeling and Measuring Competencies in Higher Education – Validation and Methodological Challenges' (KoKoHs) focusses on addressing these challenges in HE assessment practice by modeling and validating objective test instruments. Including 16 cross-university collaborative projects, the German-wide research program contributes to bridging the research gap in current assessment research and practice by concentrating on practical and policy-related challenges of assessment in HE. In this paper, we present a differentiated overview of existing assessments of HE at the national and international level. Based on the state of research, we describe the theoretical and conceptual framework of the KoKoHs Program as well as results of the validation studies, including their key outcomes. More precisely, this includes an insight into more than 40 developed assessments covering a broad range of transparent and objective methods for validly measuring domain-specific and generic knowledge and skills for five major study areas (Economics, Social Science, Teacher Education, Medicine and Psychology). Computer-, video- and simulation-based instruments have been applied and validated to measure over 20,000 students at the beginning, middle and end of their (bachelor and master) studies at more than 300 HE institutions throughout Germany or during their practical training phase, traineeship or occupation. Focussing on the validity of the assessments, all test instruments have been analyzed comprehensively, using a broad range of methods and observing the validity criteria of the Standards for Psychological and Educational Testing developed by the American Educational Research Association, the American Economic Association and the National Council on Measurement. The results of the developed assessments presented in this paper, provide valuable outcomes to predict students’ skills and abilities at the beginning and the end of their studies as well as their learning development and performance. This allows for a differentiated view of the diversity among students. Based on the given research results practical implications and recommendations are formulated. In particular, appropriate and effective learning opportunities for students can be created to support the learning development of students, promote their individual potential and reduce knowledge and skill gaps. Overall, the presented research on competency assessment is highly relevant to national and international HE practice.

Keywords: 21st century skills, academic competencies, innovative assessments, KoKoHs

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Authors: Awatef Ahmed Ben Ramadan, Aqsa Arshad

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Background: There is a huge Muslim migration movement to North America and Europe for several reasons, primarily refuge from war areas and partly to search for better work and educational chances. There are always concerns regarding first-Generation Immigrant women's health and computer literacy, an adequate understanding of the health systems, and the use of the existing healthcare technology and services effectively and efficiently. Language proficiency level, preference for cultural and traditional remedies, socioeconomic factors, fear of stereotyping, limited accessibility to health services, and general unfamiliarity with the existing health services and resources are familiar variables among these women. Aims: The current study aims to assess the health and digital literacy of first-generation Muslim women in Atlanta city. Also, the study aims to examine how the COVID-19 pandemic has encouraged the use of health information technology and increased technology awareness among the targeted women. Methods: The study design is cross-sectional correlational research. The study will be conducted to produce preliminary results that the investigators want to have to supplement an NIH grant application about leveraging information technology to reduce the health inequalities amongst the first-generation immigrant Muslim women in Atlanta City. The investigators will collect the study data in two phases using different tools. Phase one was conducted in June 2022; the investigators used tools to measure health and digital literacy amongst 42 first-generation immigrant Muslim women. Phase two was conducted in November 2022; the investigators measured the Knowledge, Attitude, and Practice (KAP) of using health information technology such as telehealth from a sample of 45 first-generation Muslim immigrant women in Atlanta; in addition, the investigators measured how the current pandemic has affected their KAP to use telemedicine and telehealth services. Both phases' study participants were recruited using convenience sampling methodology. The investigators collected around 40 of 18 years old or older first-generation Muslim immigrant women for both study phases. The study excluded Immigrants who hold work visas and second-generation immigrants. Results: At the point of submitting this abstract, the investigators are still analyzing the study data to produce preliminary results to apply for an NIH grant entitled "Leveraging Health Information Technology (Health IT) to Address and Reduce Health Care Disparities (R01 Clinical Trial Optional)". This research will be the first step of a comprehensive research project to assess and measure health and digital literacy amongst a vulnerable community group. The targeted group might have different points of view from the U.S.-born inhabitants on how to: promote their health, gain healthy lifestyles and habits, screen for diseases, adhere to health treatment and follow-up plans, perceive the importance of using available and affordable technology to communicate with their providers and improve their health, and help in making serious decisions for their health. The investigators aim to develop an educational and instructional health mobile application considering the language and cultural factors that affect immigrants' ability to access different health and social support sources, know their health rights and obligations in their communities, and improve their health behavior and behavior lifestyles.

Keywords: first-generation immigrant Muslim women, telehealth, COVID-19 pandemic, health information technology, health and digital literacy

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Authors: Shayan Mohajer Hamidi

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Federated Learning (FL) has emerged as a promising paradigm for training machine learning models on distributed data without the need for centralized data aggregation. In the realm of wireless communications, FL has the potential to leverage the vast amounts of data generated by wireless devices to improve model performance and enable intelligent applications. However, the fairness aspect of FL in wireless communications remains largely unexplored. This abstract presents an idea for fair federated learning in wireless communications, addressing the challenges of imbalanced data distribution, privacy preservation, and resource allocation. Firstly, the proposed approach aims to tackle the issue of imbalanced data distribution in wireless networks. In typical FL scenarios, the distribution of data across wireless devices can be highly skewed, resulting in unfair model updates. To address this, we propose a weighted aggregation strategy that assigns higher importance to devices with fewer samples during the aggregation process. By incorporating fairness-aware weighting mechanisms, the proposed approach ensures that each participating device's contribution is proportional to its data distribution, thereby mitigating the impact of data imbalance on model performance. Secondly, privacy preservation is a critical concern in federated learning, especially in wireless communications where sensitive user data is involved. The proposed approach incorporates privacy-enhancing techniques, such as differential privacy, to protect user privacy during the model training process. By adding carefully calibrated noise to the gradient updates, the proposed approach ensures that the privacy of individual devices is preserved without compromising the overall model accuracy. Moreover, the approach considers the heterogeneity of devices in terms of computational capabilities and energy constraints, allowing devices to adaptively adjust the level of privacy preservation to strike a balance between privacy and utility. Thirdly, efficient resource allocation is crucial for federated learning in wireless communications, as devices operate under limited bandwidth, energy, and computational resources. The proposed approach leverages optimization techniques to allocate resources effectively among the participating devices, considering factors such as data quality, network conditions, and device capabilities. By intelligently distributing the computational load, communication bandwidth, and energy consumption, the proposed approach minimizes resource wastage and ensures a fair and efficient FL process in wireless networks. To evaluate the performance of the proposed fair federated learning approach, extensive simulations and experiments will be conducted. The experiments will involve a diverse set of wireless devices, ranging from smartphones to Internet of Things (IoT) devices, operating in various scenarios with different data distributions and network conditions. The evaluation metrics will include model accuracy, fairness measures, privacy preservation, and resource utilization. The expected outcomes of this research include improved model performance, fair allocation of resources, enhanced privacy preservation, and a better understanding of the challenges and solutions for fair federated learning in wireless communications. The proposed approach has the potential to revolutionize wireless communication systems by enabling intelligent applications while addressing fairness concerns and preserving user privacy.

Keywords: federated learning, wireless communications, fairness, imbalanced data, privacy preservation, resource allocation, differential privacy, optimization

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Authors: Lei Ye, Min Liu, Yong-Li Gao, Jun Zhang

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Purpose: The aims of the study are to investigate the status of health-promoting lifestyle and to compare the healthy lifestyle of emergency nurses in different levels of hospitals in Sichuan province, China. The investigation is mainly about the health-promoting lifestyle, including spiritual growth, health responsibility, physical activity, nutrition, interpersonal relations, stress management. Then the factors were analyzed influencing the health-promoting lifestyle of emergency nurses in hospitals of Sichuan province in order to find the relevant models to provide reference evidence for intervention. Study Design: A cross-sectional research method was adopted. Stratified cluster sampling, based on geographical location, was used to select the health facilities of 1389 emergency nurses in 54 hospitals from Sichuan province in China. Method: The 52-item, six-factor structure Health-Promoting Lifestyle Profile II (HPLP- II) instrument was used to explore participants’ self-reported health-promoting behaviors and measure the dimensions of health responsibility, physical activity, nutrition, interpersonal relations, spiritual growth, and stress management. Demographic characteristics, education, work duration, emergency nursing work duration and self-rated health status were documented. Analysis: Data were analyzed through SPSS software ver. 17.0. Frequency, percentage, mean ± standard deviation were used to describe the general information, while the Nonparametric Test was used to compare the constituent ratio of general data of different hospitals. One-way ANOVA was used to compare the scores of health-promoting lifestyle in different levels hospital. A multiple linear regression model was established. P values which were less than 0.05 determined statistical significance in all analyses. Result: The survey showed that the total score of health-promoting lifestyle of nurses at emergency departments in Sichuan Province was 120.49 ± 21.280. The relevant dimensions are ranked by scores in descending order: interpersonal relations, nutrition, health responsibility, physical activity, stress management, spiritual growth. The total scores of the three-A hospital were the highest (121.63 ± 0.724), followed by the senior class hospital (119.7 ± 1.362) and three-B hospital (117.80 ± 1.255). The difference was statistically significant (P=0.024). The general data of nurses was used as the independent variable which includes age, gender, marital status, living conditions, nursing income, hospital level, Length of Service in nursing, Length of Service in emergency, Professional Title, education background, and the average number of night shifts. The total score of health-promoting lifestyle was used as dependent variable; Multiple linear regression analysis method was adopted to establish the regression model. The regression equation F = 20.728, R2 = 0.061, P < 0.05, the age, gender, nursing income, turnover intention and status of coping stress affect the health-promoting lifestyle of nurses in emergency department, the result was statistically significant (P < 0.05 ). Conclusion: The results of the investigation indicate that it will help to develop health promoting interventions for emergency nurses in all levels of hospital in Sichuan Province through further research. Managers need to pay more attention to emergency nurses’ exercise, stress management, self-realization, and conduct intervention in nurse training programs.

Keywords: emergency nurse, health-promoting lifestyle profile II, health behaviors, lifestyle

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Authors: Md. Nuru Miah, A. F. M. Akhter Uddin

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Medicinal plants are grown naturally in a tropical environment in Bangladesh and used as drug and therapeutic agents in the health care system. According to Bangladesh Agricultural Research Institute (BARI), there are 722 species of medicinal plants in the country. Of them, 255 plants are utilized by the manufacturers of Ayurvedic and Unani medicines. Medicinal plants like Aloevera, Ashwagonda, shotomul,Tulsi, Vuikumra, Misridana are extensively cultivated in some selected areas as well; where Aloevera scored the highest position in production. In the early 1980, Ayurvedic and Unani companies procured 80 percent of medicinal plants from natural forests, and the rest 20 percent was imported. Now the scenario has changed; 80 percent is imported, and the rest 20 percent is collected from local products(Source: Astudy on sectorbased need assessment of Business promotion council-Herbal products and medicinal plants, page-4). Uttara Development Program Society, a leading Non- Government development organization in Bangladesh, has been implementing a value chain development project under promoting Agricultural commercialization and Enterprises of Pally Karma Sahayak Foundation (PKSF) funded by the International Fund for Agricultural Development (IFAD) in Natore Sadar Upazila from April 2017 to sustainably develop the technological interventions for products and market development. The ultimate goal of the project is to increase income, generate employment and develop this sector as a sustainable business enterprise. Altogether 10,000 farmers (Nursery owners, growers, input supplier, processors, whole sellers, and retailers) are engaged in different activities of the project. The entrepreneurs engaged in medicinal plant cultivation did not know and follow environmental and good agricultural practices. They used to adopt traditional methodology in production and processing. Locally the farmers didn’t have any positive initiative to expand their business as well as developvalue added products. A lot of diversified products could be possible to develop and marketed with the introduction of post-harvest processing technology and market linkage with the local and global buyer. Training is imparted to the nursery owners and herbal growers on production technologies, sowing method, use of organic fertilizers/compost/pesticides, harvesting procedures, and storage facilities. Different types of herbal tea like Rosella, Moringa, Tulshi, and Basak are being produced and packed locally with a good scope of its marketing in different cities of the country. The project has been able to achieve a significant impact in the development of production technologies, but still, there is room for further improvement in processing, packaging, and marketing level. The core intervention of the current project to develop some entrepreneurs for branding, packaging, promotion, and marketing while considering environment friendly practices. The present strategies will strengthen the knowledge and skills of the entrepreneurs for the production and marketing of their products, maintaining worldwide accepted compliance system for easy access to the global market.

Keywords: aloe vera, herbs and shrubs, market, interventions

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Authors: Chethana V. Casiker, Jagadishakumara B., Sunil G. M., Chaithra K., M. Soubadra Devy

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A majority of the world’s food crops depends on insects for pollination, among which bees are the most dominant taxon. Bees pollinate vegetables, fruits and oilseeds which are rich in essential micronutrients. Besides being a prerequisite for a nutritionally secure diet, agrarian economies such as India depend heavily on pollination for good yield and quality of the product. As cities all over the world expand rapidly, large tracts of green spaces are being built up. This, along with high usage of agricultural chemicals has reduced floral diversity and shrunk bee habitats. Indeed, pollinator decline is being reported from various parts of the world. Further, the FAO has reported a huge increase in the area of land under cultivation of pollinator-dependent crops. In the light of increasing demand for pollination and disappearing natural habitats, it is critical to understand whether and how urban spaces can support pollinators. To this end, this study investigates the influence of landscape and local habitat quality on bee community dynamics. To capture the dynamics of expanding cityscapes, the study employs a space for time substitution, wherein a transect along the gradient of urbanization substitutes a timeframe of increasing urbanization. This will help understand how pollinators would respond to changes induced by increasing intensity of urbanization in the future. Bengaluru, one of the fastest growing cities of Southern India, is an excellent site to study impacts associated with urbanization. With sites moving away from the Bengaluru’s centre and towards its peripheries, this study captures the changes in bee species diversity and richness along a gradient of urbanization. Bees were sampled under different land use types as well as in different types of vegetation, including plantations, croplands, fallow land, parks, lake embankments, and private gardens. The relationship between bee community metrics and key drivers such as a percentage of built-up area, land use practices, and floral resources was examined. Additionally, data collected using questionnaire interviews were used to understand people’s perceptions towards and level of dependence on pollinators. Our results showed that urban areas are capable of supporting bees. In fact, a greater diversity of bees was recorded in urban sites compared to adjoining rural areas. This suggests that bees are able to seek out patchy resources and survive in small fragments of habitat. Bee abundance and species richness correlated positively with floral abundance and richness, indicating the role of vegetation in providing forage and nesting sites which are crucial to their survival. Bee numbers were seen to decrease with increase in built-up area demonstrating that impervious surfaces could act as deterrents. Findings from this study challenge the popular notion of cities being biodiversity-bare spaces. There is indeed scope for conserving bees in urban landscapes, provided that there are city-scale planning and local initiative. Bee conservation can go hand in hand with efforts such as urban gardening and terrace farming that could help cities urbanize sustainably.

Keywords: bee, landscape ecology, urbanization, urban pollination

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Authors: Alexander David Natanson

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This paper focuses on the effect of Sanctuary and Immigration and Customs Enforcement (ICE) policies on local economies. "Sanctuary cities" refers to municipal jurisdictions that limit their cooperation with the federal government's efforts to enforce immigration. Using county-level data from the American Community Survey and ICE data on economic indicators from 2006 to 2018, this study isolates the effects of local immigration policies on U.S. counties. The investigation is accomplished by simultaneously studying the policies' effects in counties where immigrants' families are persecuted via collaboration with Immigration and Customs Enforcement (ICE), in contrast to counties that provide protections. The analysis includes a difference-in-difference & two-way fixed effect model. Results are robust to nearest-neighbor matching, after the random assignment of treatment, after running estimations using different cutoffs for immigration policies, and with a regression discontinuity model comparing bordering counties with opposite policies. Results are also robust after restricting the data to a single-year policy adoption, using the Sun and Abraham estimator, and with event-study estimation to deal with the staggered treatment issue. In addition, the study reverses the estimation to understand what drives the decision to choose policies to detect the presence of reverse causality biases in the estimated policy impact on economic factors. The evidence demonstrates that providing protections to undocumented immigrants increases economic activity. The estimates show gains in per capita income ranging from 3.1 to 7.2, median wages between 1.7 to 2.6, and GDP between 2.4 to 4.1 percent. Regarding labor, sanctuary counties saw increases in total employment between 2.3 to 4 percent, and the unemployment rate declined from 12 to 17 percent. The data further shows that ICE policies have no statistically significant effects on income, median wages, or GDP but adverse effects on total employment, with declines from 1 to 2 percent, mostly in rural counties, and an increase in unemployment of around 7 percent in urban counties. In addition, results show a decline in the foreign-born population in ICE counties but no changes in sanctuary counties. The study also finds similar results for sanctuary counties when separating the data between urban, rural, educational attainment, gender, ethnic groups, economic quintiles, and the number of business establishments. The takeaway from this study is that institutional inclusion creates the dynamic nature of an economy, as inclusion allows for economic expansion due to the extension of fundamental freedoms to newcomers. Inclusive policies show positive effects on economic outcomes with no evident increase in population. To make sense of these results, the hypothesis and theoretical model propose that inclusive immigration policies play an essential role in conditioning the effect of immigration by decreasing uncertainties and constraints for immigrants' interaction in their communities, decreasing the cost from fear of deportation or the constant fear of criminalization and optimize their human capital.

Keywords: inclusive and exclusive institutions, post matching, fixed effect, time trend, regression discontinuity, difference-in-difference, randomization inference and sun, Abraham estimator

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Authors: Taghrid Asfar, Olusanya J. Oluwole, Michael Schmidt, Alejandra Casas, Zoran Bursac, Wasim Maziak.

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Waterpipe (WP) smoking (a.k.a. hookah) has increased dramatically in the US mainly due to the misperception that it is safer than cigarette smoking. Mounting evidence show that WP smoking is addictive and harmful. Health warning labels (HWLs) are effective in communicating smoking-related risks. Currently, the FDA requires that WP tobacco packages have a textual HWL about nicotine. While this represents a good step, it is inadequate given the established harm of WP smoking beyond addiction and the superior performance of pictorial HWLs over text-only ones. We developed 24 WP pictorial HWLs in a Delphi study among international expert panel. HWLs were grouped into 6 themes: addiction, harm compared to cigarettes, harm to others, health effects, quitting, and specific harms. This study aims to compare the effect of the pictorial HWLs compared to the FDA HWL, and 2) the effect of pictorial HWLs between the 6 themes. A 2x7 between/within subject online factorial experimental study was conducted among a national convenience sample of 300 (50% current WP smokers; 50% nonsmokers) US adults (females 71.1%; mean age of 31.1±3.41 years) in March 2022. The first factor varied WP smoking status (smokers, nonsmokers). The second factor varied the HWL theme and type (text, pictorial). Participants were randomized to view and rate 7 HWLs: 1 FDA text HWL (control) and 6 HWLs, one from each of the 6 themes, all presented in random order. HWLs were rated based on the message impact framework into five categories: attention, reaction (believability, relevance, fear), perceived effectiveness, intentions to quit WP among current smokers, and intention to not initiate WP among nonsmokers. measures were assessed on a 5-point Likert scale (1=not at all to 5=very much) for attention and reaction and on a 7-point Likert scale (1=not at all to 7=very much) for the perceived effectiveness and intentions to quit or not initiate WP smoking. Means and SDs of outcome measures for each HWL type and theme were calculated. Planned comparisons using Friedman test followed by pairwise Wilcoxon signed-rank test for multiple comparisons were used to examine distributional differences of outcomes between the HWL type and themes. Approximately 74.4 % of participants were non-Hispanic Whites, 68.4% had college degrees, and 41.5% were under the poverty level. Participants reported starting WTS on average at 20.3±8.19 years. Compared with the FDA text HWL, pictorial HWLs elicited higher attention (p<0.0001), fear (p<0.0001), harm perception (p<0.0003), perceived effectiveness (p<0.0001), and intentions to quit (p=0.0014) and not initiate WP smoking (p<0.0003). HWLs in theme 3 (harm to others) achieved the highest rating in attention (4.14±1), believability (4.15±0.95), overall perceived effectiveness (7.60±2.35), harm perception (7.53±2.43), and intentions to quit (7.35±2.57). HWLs in theme 2 (WP harm compared to cigarettes) achieved the highest rating in discouraging WP smoking initiation (7.32±2.54). Pictorial HWLs were superior to the FDA text-only for several communication outcomes. Pictorial HWLs related to WP harm to others and WP harm compared to cigarette are promising. These findings provide strong evidence for the potential implementation of WP-specific pictorial HWLs.

Keywords: health communication, waterpipe smoking, factorial experiment, reaction, harm perception, tobacco regulations

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Authors: Babak Forouraghi

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A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of the flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on the spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts, as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with an attention mechanism. In previous works on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work, with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on the presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: machine learning, classification and regression, gene circuit design, bidirectional transformers

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Authors: Alon Cohen, Jeffrey Kantor, Shalom Levy

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The use of the audit risk model in auditing has faced limitations and difficulties, leading auditors to rely on a conceptual level of its application. The qualitative approach to assessing risks has resulted in different risk assessments, affecting the quality of audits and decision-making on the adoption of CAATTs. This study aims to investigate risk factors impacting the implementation of the audit risk model and propose a complementary risk-based instrument (KRIs) to form substance risk judgments and mitigate against heightened risk of material misstatement (RMM). The study addresses the question of how risk factors impact the implementation of the audit risk model, improve risk judgments, and aid in the adoption of CAATTs. The study uses a three-stage scale development procedure involving a pretest and subsequent study with two independent samples. The pretest involves an exploratory factor analysis, while the subsequent study employs confirmatory factor analysis for construct validation. Additionally, the authors test the ability of the KRIs to predict audit efforts needed to mitigate against heightened RMM. Data was collected through two independent samples involving 767 participants. The collected data was analyzed using exploratory factor analysis and confirmatory factor analysis to assess scale validity and construct validation. The suggested KRIs, comprising two risk components and seventeen risk items, are found to have high predictive power in determining audit efforts needed to reduce RMM. The study validates the suggested KRIs as an effective instrument for risk assessment and decision-making on the adoption of CAATTs. This study contributes to the existing literature by implementing a holistic approach to risk assessment and providing a quantitative expression of assessed risks. It bridges the gap between intuitive risk evaluation and the theoretical domain, clarifying the mechanism of risk assessments. It also helps improve the uniformity and quality of risk assessments, aiding audit standard-setters in issuing updated guidelines on CAATT adoption. A few limitations and recommendations for future research should be mentioned. First, the process of developing the scale was conducted in the Israeli auditing market, which follows the International Standards on Auditing (ISAs). Although ISAs are adopted in European countries, for greater generalization, future studies could focus on other countries that adopt additional or local auditing standards. Second, this study revealed risk factors that have a material impact on the assessed risk. However, there could be additional risk factors that influence the assessment of the RMM. Therefore, future research could investigate other risk segments, such as operational and financial risks, to bring a broader generalizability to our results. Third, although the sample size in this study fits acceptable scale development procedures and enables drawing conclusions from the body of research, future research may develop standardized measures based on larger samples to reduce the generation of equivocal results and suggest an extended risk model.

Keywords: audit risk model, audit efforts, CAATTs adoption, key risk indicators, sustainability

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Authors: Luciano Tarantino

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Gas gangrene is a rare, severe infection with a very high mortality rate caused by Clostridium species. The infection causes a non-suppurative localized producing gas lesion from which harmful toxins that impair the inflammatory response cause vessel damage and multiple organ failure. Gas gangrene of the liver is very rare and develops suddenly, often as a complication of abdominal surgery and liver transplantation. The present paper deals with a case of gas gangrene of the liver that occurred after percutaneous MW ablation of hepatocellular carcinoma, resulting in progressive liver necrosis and multi-organ failure in spite of specific antibiotics administration. The patient was successfully treated with percutaneous Radiofrequency ablation. Case report: Female, 76 years old, Child A class cirrhosis, treated with synchronous insertion of 3 MW antennae for large HCC (5.5 cm) in the VIII segment. 24 hours after treatment, the patient was asymptomatic and left the hospital . 2 days later, she complained of fever, weakness, abdominal swelling, and pain. Abdominal US detected a 2.3 cm in size gas-containing area, eccentric within the large (7 cm) ablated area. The patient was promptly hospitalized with the diagnosis of anaerobic liver abscess and started antibiotic therapy with Imipenem/cilastatine+metronidazole+teicoplanine. On the fourth day, the patient was moved to the ICU because of dyspnea, congestive heart failure, atrial fibrillation, right pleural effusion, ascites, and renal failure. Blood tests demonstrated severe leukopenia and neutropenia, anemia, increased creatinine and blood nitrogen, high-level FDP, and high INR. Blood cultures were negative. At US, unenhanced CT, and CEUS, a progressive enlargement of the infected liver lesion was observed. Percutaneous drainage was attempted, but only drops of non-suppurative brownish material could be obtained. Pleural and peritoneal drainages gave serosanguineous muddy fluid. The Surgeon and the Anesthesiologist excluded any indication of surgical resection because of the high perioperative mortality risk. Therefore, we asked for the informed consent of the patient and her relatives to treat the gangrenous liver lesion by percutaneous Ablation. Under conscious sedation, percutaneous RFA of GG was performed by double insertion of 3 cool-tip needles (Covidien LDT, USA ) into the infected area. The procedure was well tolerated by the patient. A dramatic improvement in the patient's condition was observed in the subsequent 24 hours and thereafter. Fever and dyspnea disappeared. Normalization of blood tests, including creatinine, was observed within 4 days. Heart performance improved, 10 days after the RFA the patient left the hospital and was followed-up with weekly as an outpatient for 2 months and every two months thereafter. At 18 months follow-up, the patient is well compensated (Child-Pugh class B7), without any peritoneal or pleural effusion and without any HCC recurrence at imaging (US every 3 months, CT every 6 months). Percutaneous RFA could be a valuable therapy of focal GG of the liver in patients non-responder to antibiotics and when surgery and liver transplantation are not feasible. A fast and early indication is needed in case of rapid worsening of patient's conditions.

Keywords: liver tumor ablation, interventional ultrasound, liver infection, gas gangrene, radiofrequency ablation

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