Miracle-dz/UniFAR-FTUs huggingface dataset:
Dissolved Oxygen Dispersion Model Within Green Mussel Farming Area in Sri Racha Bay, Chonburi Province, Thailand

Dissolved oxygen (DO) is a major parameter in the aquatic environment and it is also necessary for all marine organisms, including mollusks. Thus, a case study was developed to model the DO distribution within a green mussel farming area in Sri Racha Bay, Chonburi province, Thailand. The model indicated that the water was well mixed, based on a mass balancing equation. The DO concentration varied depending on the sources and sinks of the DO which were applied to the model. A solution for the model was considered by an implicit method of successive over relaxation. In the model, the velocity of water was computed by the Princeton Ocean Model (POM). The output of the POM revealed that the seawater moved northward during the flood tide, while during the ebb tide, it moved southward with a maximum speed approximately 1 m.sec -1 . The model was applied by adding and removing DO terms which were obtained from empirical experiments. On 29 January 2010 at 2100 hours, when low tide occurred, the DO concentration in the center of a floating raft of green mussel (Perna viridis) was lowest while the advection of water was dramatically slackened. Moreover, during night time, when there was no photosynthesis, the DO concentration was lowest. The results obtained from the model were acceptable compared with actual field observations. Similarly, the pattern of DO dispersion from the prediction at low tide also corresponded to the pattern of DO dispersion from the survey at low tide. Thus, the model could be used as a tool for predicting and estimating the amount of DO in a marine culture area in order to increase production and the preservation of the environment.
Access control based on CRDTs for Collaborative Distributed Applications

—A key feature for most collaborative applications is their ability to distinguish access rights to shared documents in a dynamic group of collaborators. To achieve high availability and avoid single points of failure, systems can replicate this access control policy across sites. Increasingly, Conflict-free Replicated Data Types (CRDTs) are used to this end. They embed conflict resolution strategies that take into account concurrent modifications to the policy but also to the document that it manages. However, few systems in the literature support multiple administrators, and those which do fall short of considering distributed applications where no node or group of nodes is central to its operation. To allow multiple concurrent edits of the policy in massively collaborative settings with no central server, we devise a specialized causal model that minimizes concurrency. Crucially our model allows to correct the document state in case operations have become unauthorized following a policy change. We apply our model to a CRDT replicating an access control policy with read and write rights on a collaborative document and admin rights on the policy. We end by studying flexible conflict resolution strategies, providing our underlying algorithms.
SOMATOTYPE AND BODY COMPOSITION OF ADOLESCENT BADMINTON PLAYERS IN KERALA

Purpose: The athletes succeeding in certain sports have distinctive body characteristics that differ according to the demands of the type of sports. The present study attempted to evaluate the somatotype and body composition of the adolescent badminton players in Kerala state and compare it with the overseas counterparts. Methods: 30 male badminton players were chosen from various districts in Kerala state as the subjects of the study. Their mean age was 17.6+/-1.7 years, height 165.5+/-5.3cm and weight 63.5+/-4.9kg. Anthropometric measurements included skinfolds (triceps, subscapular, suprailiac, abdomen and calf), bicondylar breadths (humerus and femur) and girths (biceps and calf). Percent Body Fat was calculated using the formula prescribed by Faulkner J.A. while somatotype assessed using the Heath-Carter method. Results: The badminton players of this study fell into the somatotype category of balanced mesomorphs with a score of 3.0-4.1-2.5. Their mean body fat percentage was 11.4 +/-1.3% and average total weight of fat was 7.3+/-0.8kg. It was also found that their body fat% is higher than their overseas
Edinburgh Research Explorer Developmental expression of orphan g protein-coupled receptor 50 in the mouse brain

: Mental disorders have a complex etiology resulting from interactions between multiple genetic risk factors and stressful life events. Orphan G protein-coupled receptor 50 (GPR50) has been identi ﬁ ed as a genetic risk factor for bipolar disorder and major depression in women, and there is additional genetic and functional evidence linking GPR50 to neurite outgrowth, lipid metabolism, and adaptive thermogenesis and torpor. However, in the absence of a ligand, a speci ﬁ c function has not been identi ﬁ ed. Adult GPR50 expression has previously been reported in brain regions controlling the HPA axis, but its developmental expression is unknown. In this study, we performed extensive expression analysis of GPR50 and three protein interactors using rt-PCR and immunohistochemistry in the developing and adult mouse brain. Gpr50 is expressed at embryonic day 13 (E13), peaks at E18, and is predominantly expressed by neurons. Additionally we identi ﬁ ed novel regions of Gpr50 expression, including brain stem nuclei involved in neurotransmitter signaling: the locus coeruleus, substantia nigra, and raphe nuclei, as well as nuclei involved in metabolic homeostasis. Gpr50 colocalizes with yeast-two-hybrid interactors Nogo-A, Abca2, and Cdh8 in the hypothalamus, amygdala, cortex, and selected brain stem nuclei at E18 and in the adult. With this study, we identify a link between GPR50 and neurotransmitter signaling and strengthen a likely role in stress response and energy homeostasis.
Clostridium perfringens sialidase interaction with Neu5Ac α-Gal sialic acid receptors by in-silico observation and its impact on monolayers cellular behavior structure

Objective: This study aims to evaluate the effect of Clostridium perfringens sialidase treatment on monolayer cell behavior using computational screening and an in vitro approach to demonstrate interaction between enzyme-based drugs and ligands in host cells. Materials and Methods: The in silico study was carried out by molecular docking analysis used to predict the interactions between atoms that occur, followed by genetic characterization of sialidase from a wild isolate. Sialidase, which has undergone further production and purification processes exposed to chicken embryonic fibroblast cell culture, and observations-based structural morphology of cells compared between treated cells and normal cells without treatment. Results: Based on an in silico study, C. perfringens sialidase has an excellent binding affinity with Neu5Acα (2.3) Gal ligand receptor with Gibbs energy value (∆G)—7.35 kcal/mol and Ki value of 4.11 µM. Wild C. perfringens isolates in this study have 99.1%–100% similarity to the plc gene, NanH, and NanI genes, while NanJ shows 93.18% similarity compared to the reference isolate from GenBank. Sialidase at 750 and 150 mU may impact the viability, cell count, and cell behavior structure of fibroblast cells by significantly increasing the empty area and perimeter of chicken embryo fibroblast (CEF) cells, while at 30 mU sialidase shows no significant difference compared with mock control. Conclusion: Sialidase-derived C. perfringens has the capacity to compete with viral molecules for attachment to host sialic acid based on in silico analysis. However, sialidase treatment has an impact on monolayer cell fibroblasts given exposure to high doses.
Understanding Deepfake Research and Trends through Topic Modelling

Deepfake research has gained traction in recent years. Surveys have been conducted to summarize work on the detection and generation of deepfakes. However, a more comprehensive and quantitative overview that encompasses both technical and non‐technical areas is lacking. We address this gap using topic modelling to discover deepfake research topics in academic publications. Our results show that while detection techniques topics dominate the research field, other areas, such as privacy and legal research, offer potential avenues for further exploration.
AI‐Based Research Tool for Large Genealogical Corpora: The Case of Jewish Communities Worldwide

This paper presents a new methodology for AI‐based research and exploration of large genealogical corpora. The proposed approach is based on an automatic quantitative question‐answering (QA) system that enables researchers to ask questions in natural language and learn about trends related to individuals, families, and communities in the corpus of the study. The proposed methodology includes: 1) an automatic method for training dataset generation, 2) a transformer‐based table selection method, and 3) an optimized transformer‐based quantitative QA model. The findings indicate that the proposed architecture outperforms the state‐of‐the‐art models by achieving 87% accuracy on the large corpus of Jewish genealogical data. This study may have practical implications for genealogical information centers and museums, making genealogical data research easy and scalable for experts as well as the general public.
“How Do You Measure a Relationship?” Assessment and Evaluation Challenges of Knowledge Exchange Activities in Information Work

Today there is increasing emphasis on knowledge exchange (KE), the movement of knowledge and expertise amongst diverse groups to enhance research uptake, use, and impact in healthcare, government, and community settings. Library and information science (LIS) professionals are central actors in KE though community engagement, scholarly communication, literacy, and cultural heritage initiatives, but (how) is this work formally documented and evaluated? Through interviews with 24 information professionals working in varied settings, we considered how KE activities fit into the current library assessment and evaluation landscape. Using thematic analysis, we identified challenges with placing this work within current assessment practices and evaluation frameworks and showing its value, as well as a desire for alternative, more dynamic assessment and evaluation methods. We discuss these findings with respect to previous research in LIS and KE more broadly to consider professional and organizational implications.
Measuring Citizen's Perceptions of AI Adoption for Instrumental and Value‐Added Tasks

This preliminary study reports citizens' perceptions of using artificial intelligence (AI) in instrumental and value‐added decision‐making. We analyzed 5,153 responses from the Pew Research Center's American Trends Panel Survey, collected in 2021. The findings suggest that concerns outweigh excitement when it comes to adopting AI systems for complex value‐added decisions while they welcome AI systems for instrumental tasks on behalf of humans.
Daily flow hydrograph simulation using regional flow duration curves for ungauged region of Dongjiang basin

Regional flow duration curves are generated by using the relation of discharge and watershed characteristics.In traditional procedures of rainfall runoff model calibration,an observed stream flow hydrograph is ordinarily adapted as the objective function for model calibration.The feasibility and simulation precision of the method are deeply analyzed.The regional flow duration curves are developed by the study region made of the 11 catchments,and the calculation results are satisfactory.The flow duration curves are utilized as a new objective function for TOPMODEL model parameter calibration.The calculation results of Xingfeng and Yuecheng catchment show that the method is feasible,and it may obtain the satisfying simulation precision.The method may be applied in daily flow hydrograph simulation for other ungauged region.
An Investigation of the Use of Theories in Misinformation Studies

This paper examines social science and humanity theories that have been applied to studies dealing with misinformation. We identified 273 articles published from 2012 to 2023 from Web of Science, Scopus, and ScienceDirect. These articles are empirical studies that have applied one or more social science or humanity theories. Applying content analysis approach, we identified 124 theories that authors have used in their studies. These theories belong to different disciplines or fields, such as political science, psychology, communication, sociology, and economics. We discuss the top 11 theories and how they have been used to understand misinformation and its impacts. This study provides insights into understanding current misinformation studies and rich resources for information evaluation and information literacy education.
Coactive Vicarious Learning in Danmaku Contexts: A New Perspective of Informal Learning

Vicarious learning (VL), a concept widely explored in organizational behavior, has also received attention in social media research in recent years. Compared to live streaming e‐commerce and online communities, less VL has been studied based on danmaku, an instant commentary in video sites. We consider the characteristics of human information interaction in danmaku contexts and focus on exploring the core elements of coactive vicarious learning (CVL), where five core elements are identified. We will explore the influencing factors through content analysis and semi‐structured interviews. And a preliminary conceptual framework of CVL experience in danmaku contexts will try to be brought out for future empirical investigation.
Characterizing and Early Predicting User Performance for Adaptive Search Path Recommendation

User search performance is multidimensional in nature and may be better characterized by metrics that depict users' interactions with both relevant and irrelevant results. Despite previous research on one‐dimensional measures, it is still unclear how to characterize different dimensions of user performance and leverage the knowledge in developing proactive recommendations. To address this gap, we propose and empirically test a framework of search performance evaluation and build early performance prediction models to simulate proactive search path recommendations. Experimental results from four datasets of diverse types (1,482 sessions and 5,140 query segments from both controlled lab and natural settings) demonstrate that: 1) Cluster patterns characterized by cost‐gain‐based multifaceted metrics can effectively differentiate high‐performing users from other searchers, which form the empirical basis for proactive recommendations; 2) whole‐session performance can be reliably predicted at early stages of sessions (e.g., first and second queries); 3) recommendations built upon the search paths of system‐identified high‐performing searchers can significantly improve the search performance of struggling users. Experimental results demonstrate the potential of our approach for leveraging collective wisdom from automatically identified high‐performance user groups in developing and evaluating proactive in‐situ search recommendations.
Strategies for Conducting Critical Research in Information Science by Designing Social Justice Research Informed by Intersectionality

This panel will present examples of how to conduct critical social justice research in Information Science (IS) that acknowledges intersectionality. Each of the panelists has extensive experience in designing and conducting IS investigations with communities underrepresented in research who may belong to various, interdependent social identities. The panelists will present their specific empirical research and/or make a theoretical contribution that applies the intersectionality framework. Each of the panelists will give a presentation followed by a Q&A session.
Public Library‐University Partnerships in Library and Information Science: Approaches, Challenges, Implications for Translating Research into Practice

While the potential and benefits of research‐practice partnership are well documented, there is limited discussion around approaches and challenges of establishing and sustaining public library‐university partnerships in LIS research to bridge the gap between research and practice. This panel brings together five groups of panelists to highlight a diversity of public library‐university partnerships within LIS and their approaches, models, practices, and implications toward consequential pedagogies and programming at public libraries. Through a collaborative panel discussion, this 90‐minute panel will convene scholars and members of the ASIS&T community to improve concrete approaches and practices involved in public library‐university partnerships to develop pedagogies and programming that are informed by the voices, needs, and interests across various communities.
Les cellules neuronales d´eriv´ees des cellules souches pluripotentes induites humaines : mod´elisation des maladies du motoneurone

– Neuronal cells derived from induced pluripotent stem cells to model motoneuron diseases. Among motor neuron diseases, spinal muscular atrophy type 1 and amyotrophic lateral sclerosis are very aggressive diseases with no cure. With the breakthrough of human induced pluripotent stem cells, iPS, researchers have now at their disposal a powerful tool to generate human motor neurons in culture and study the pathological defects in patient cells. In this review, we will see which tools for the study of patients motoneurons were developed from iPS cells and the diﬀerent cellular models that were generated. We will also see how these models were validated and current research to identify new therapeutic leads.
The changing structure of American innovation: Cautionary remarks for economic growth

A defining feature of modern economic growth is the systematic application of science to advance technology. However, despite continuous progress in scientific knowledge, recent productivity growth in the U.S. has been disappointing. We review major changes in the American innovation ecosystem over the past century and note that the past three decades have been marked by a growing division of labor between universities focusing on research and large corporations focusing on development. Knowledge produced by universities is not often in forms that can be readily digested and turned into new goods and services by companies, especially as large companies themselves withdraw from research. Small firms and university technology transfer offices cannot fully substitute for corporate research, which integrated multiple disciplines and components at the scale required to solve significant technical problems. Therefore, whereas the division of innovative labor may have raised the volume of science by universities, it also slowed, at least for a period of time, the transformation of that knowledge into novel products and processes. ∗Duke University, Fuqua School of Business and NBER †Duke University, Fuqua School of Business and NBER ‡University of East Anglia §Duke University, Fuqua School of Business
Clostridium perfringens Toxins

Clostridium perfringens is an important pathogen known to cause critical clinical disease. C . perfringens type A strains produces two types of toxins which is alpha-toxin and endotoxin. They have different attachment, internalization mechanisms and structures that lead them to diverse functions and several diseases. Alpha-toxin is a protein produces by the bacteria and cause gas gangrene once it invades the cell bilayer membrane’s fluidity. However, endotoxin cause Gastrointestinal (GI) Disease by rapid pores creating, invasion of the toxin to multiple receptors in intestine lumen, tight junction disruption. Although there are similarities in general molecular structure for both toxins, they obtain unique differentiae in the active domains. However, alpha-toxin and endotoxin have endogenous phospholipase C (PLC) and C-terminal domain that responsible for the virulence biological activities respectively. Despite that low dose of the endotoxins leads to apoptosis and high dose leads to oncosis, the endotoxin has been used now in clinical purposes such as cancer therapy and vaccination. Additionally , C. perfringens is not only foodborne human diseases but also non-foodborne disease since it has been founded in soil, water and animal’s gut. Food poising can be prevented successfully through rapid cooking from 55 to 15°C within 90 minutes and store in refrigerator/freezer temperatures. This paper will illustrate the mode of action of both toxins and how they lead to cause illness.
Employee Performance and Knowledge Management in a Manufacturing Company: Internal and External Factors to Consider

: Manufacturing firms play an important economic role by producing necessary goods and services. Manufacturing organizations must constantly enhance their operations and processes to remain competitive in today's global market. One method is to concentrate on staff performance and knowledge management practices. Many manufacturing organizations, however, struggle to identify the elements that influence these sectors. This study sought to fill this void by identifying internal and external factors influencing employee performance and knowledge management practices in a manufacturing organization. The study employed a mixed-methods strategy to gather and analyze data, including surveys, interviews, and case studies. Data from employees and managers in a manufacturing company were collected and analyzed using qualitative and quantitative approaches. This study examined the elements influencing employee performance and knowledge management practices in a manufacturing company context, drawing on prior research and fresh data. This study's conclusions are essential for industrial organizations looking to enhance their operations and processes and university scholars studying staff performance and knowledge management. This study can assist manufacturing businesses in developing successful strategies for increasing employee performance and knowledge management practices by identifying the crucial elements that influence these areas.
Detection of Monkeypox and Acne using AlexNet

: Our skin is one of the important parts of our body that covers and protects our internal parts. While doing so our skin can get affected by various allergies, irritants, or diseases which can lead to a skin condition. Skin disease is one of the conditions which affects our skin and causes various kinds of skin-related problems. We have come across various kind of skin diseases which involves a wide range of varieties while some of them can leave a permanent mark on our skin and some don’t. If it’s not cured early skin diseases can also cause a social impact on a patient. With the various advancement in the field of image processing and detection techniques, these diseases can be detected early and cured. In this paper, we have explored diseases like monkeypox, acne and detected them successfully using AlexNet, a CNN deep learning model with an accuracy of 97.2%, precision of 98.9%, F1 score of 97.24% and recall of 95.64%.