Miracle-dz/UniFAR-FTUs huggingface dataset:
Tuning Graph2vec with Node Labels for Abuse Detection in Online Conversations (extended abstract)

In recent years, online social media have allowed people to meet and discuss world-wide. These popular platforms are confronted with increasing abusive content. In order to automate the detection of abusive content in such social media, researchers have proposed various methods based on Natural Language Processing (NLP), and have leveraged behavioral information about users and the structure of conversations. In our previous work, we proposed to combine NLP and conversational graph-based features to detect abusive messages in chat logs extracted from an online game. These conversational graphs model interactions between users (i.e. who is arguing with whom? ), while completely ignoring the language content of the messages. We characterized the structure of these graphs by computing a large set of manually selected topological measures, and used them as features to train a classifier into detecting abusive messages. Graph embedding methods allow representing graphs as low-dimensional vectors while preserving at least a part of their topological properties. In addition to the plain structure, certain methods are able to capture additional information such as node labels or the weight and direction of edges. These representations are automatically learned, so they have the advantage of not requiring to perform any feature selection or feature engineering. One can distinguish four main categories of graph embedding methods, depending on the nature of the considered objects: node, edge, subgraph and whole-graph embeddings. Each category better fits the needs of different applications and problems. In this paper, we focus on the information that is used in addition to the plain structure by some embedding approaches. Especially, we study the impact of the node labels that are used by Graph2vec, a whole-graph embedding method. We study the effectiveness of such additional information in the context of online abuse detection.
A cooperative agents-based workflow-level distributed data placement strategy for scientific cloud workflows

Within the Cloud Computing context, the placement of massive data used by scientific workflows environment appears to be costly in terms of energy consumption and data transfer time. Indeed, due to the large size of consumed and generated datasets of scientific workflows tasks, the data placement problem becomes more challenging task. This problem is considered as NP-Hard problem. Ensuring an optimal mapping of data to Cloud Storage Services at a reasonable time turns out to be necessary. Many task-level approaches have been hence proposed while considering shared datasets within individual workflows to reduce data transfer cost, which is not efficient enough for the situation of multiple workflows. In the same perspective, taking into account the fixed datasets still an important issue. In the present paper, cooperative agents and Formal Analysis Concepts (FCA) based-data placement strategy for workflow-level data-intensive workflows is proposed. The proposed approach deals with three main concerns: i) treating multiple workflows simultaneously, ii) considering all types of data, specifically, fixed datasets, and iii) reducing the execution time of the data placement algorithm based on a set of cooperative intelligent agents. Experimental results show that the distribution of the proposed data placement strategy among a set of cooperative agents and the FCA approach can be more cost-effective than its task-level counterpart. Eventually, the proposed strategy proves to reduce the execution time during the execution of the tasks of multiple workflows.
The Study on Accounting Information Value Relevance in the Practice of IFRS 16 - An Empirical Study of Taiwan

The study uses Taiwan listed companies as a sample to test whether relevant financial rations have changed significantly, Base on the Ohlson(1995) evaluation model, this study examines the effect of net income and equity book value on the value relevance after IFRS 16. This research sample takes all listed firms as full research sample. Next, this study divides the sample into leasing asset sensitive industries and non-sensitive industries, and discusses separately. First, paired sample T test is adopted to detect whether the financial ratios are affected significantly after implementing IFRS 16. It is found that debt ratio, debt to equity ratio, total asset turnover ratio and depreciation expenses are all significantly changed whether in sensitive or non-sensitive industries. However, current ratio and interest expense rate have not changed. Based on Ohlson evaluation model, this study examines the value-relevance effect of net income, equity book value on the stock price after adopting IFRS 16. When testing with 2018 and 2019 third quarter financial data, equity book value and earning per share all have higher value relevance on stock price after adopting IFRS 16. However, in terms of annual data, the degree of influence is all not significant. It might be that, since the IFRS 16 leasing assets and liabilities have been revealed in the interim financial report, the stock price has been reflected in the middle of the year. It is also possible that when annual report is announced, the stock price of each company has fallen sharply due to the impact of COVID-19, and financial information is no longer value-relevant.
Analysis of Algorithms Predicting Blood: Air and Tissue: Blood Partition Coefficient from Solvent Partition Coefficients for Use in Complex Mixture Physiological Based Pharmacokinetic/Pharmacodynamic Modeling

Abstract : Algorithms predicting tissue and blood partition coefficients (PCs) from solvent properties (octanol:water, saline or water:air, oil:air coefficients) were compared to assess their usefulness for a petroleum mixtures physiologically based pharmacokinetic/pharmacodynamic model. Measured blood:air and tissue:blood PCs were sought from literature resources for 14 JP-8 components. PCs, mainly from vial equilibration experiments, were separated by species (rat and human) and averaged by tissue and chemical. Average experimental PCs were then compared with predicted PCs calculated using algorithms from nine published sources. The algorithms chosen use solvent PCs due to the relative accessibility of these parameters. Tissue:blood PCs were calculated from ratios of predicted tissue:air and experimental blood:air values (PCEB). Calculated PCs were evaluated using percent error compared to the experimental value. Of the 231 calculated values, 29% performed within +/- 20% of the experimental PC values. Algorithms were divided into three main types. Empirical equations (derived from linear regression of experimental PC data), physiologically based equations (based on water and lipid components of a tissue type), and hybrid equations (physiological parameters and empirical factors combined) each performed equally well. PCEs values were compared with tissue:blood PCs calculated from ratios of predicted tissue:air and predicted blood:air values (PC(sub pb). Overall, 68% of PCER values had smaller absolute percent errors than PC(sub pb) values. Physiological equations should not be used to calculate PC(sub pb) values as 100% of these PCps values had higher absolute percent errors than corresponding PC(sub eb) values. If calculated PC values must be used in models, a comparison of experimental and predicted PCs for chemically similar compounds is advisable, so one understands the expected error level in calculated values.
Adoption of Electronic Medical Record in Hospitals in Indonesia based on Technology Readiness and Acceptance Model

Entering the era of Healthcare 4.0, Indonesia has made various efforts in increasing the use of digital technology in hospitals in Indonesia. One of the technologies that has begun to be implemented and developed is Electronic Medical Record (EMR). However, many hospitals in Indonesia have not very successful in the implementation of the EMR. Previous studies mentioned that the readiness and acceptance of a technology will affect the successful implementation of the technology. Therefore, in this study we analyze the effect of each variable on the acceptance of EMR technology using Technology Readiness and Acceptance Model (TRAM) to identify which factor acts as a key “driver” on the acceptance of EMR. We used PLS-SEM to examine and test the model. From the analysis conducted in this study, it was found that the personality traits – in the form of technology readiness variables – have no significant effect on the acceptance of EMR technology. This study also found that perceived ease of use is the factor that has a significant direct influence on the acceptance of EMR and innovativeness is the factor that has a significant indirect influence on the acceptance of EMR technology in hospitals in Indonesia. These two influential variables are then used as the basis for deciding a strategy to improve the implementation of EMR.
Regaining Lost Seconds: Efficient Page Preloading for SGX Enclaves

Intel SGX is already here, with a strong emphasis on security and privacy. However, it is not free. Studies have shown that it incurs a significant performance overhead to take advantage of the security and privacy enhancement offered by SGX. In particular, it only provides limited physical memory for applications to use SGX. As a result, page faults can be frequently triggered during program execution, especially for memory-intensive applications with a large memory footprint. Therefore, it is imperative to look into possible optimization opportunities to enhance the efficiency of SGX. To this end, this paper proposes to leverage memory page preloading techniques to mitigate such a problem. More specifically, we propose two effective schemes to preload memory pages before they are accessed. This way, the number of page faults can be significantly reduced. To demonstrate the effectiveness of the proposed schemes, we have implemented them in a prototype using LLVM and an untrusted operating system. Experimental results on benchmarks from SPEC CPU2017 and a micro-benchmark program show that, on average, these two mechanisms can achieve 11.4% and 7.0% performance improvement with a maximum performance improvement of 18.6% and 9.0%, respectively. The two mechanisms are also evaluated when they are deployed together. The combined approach can achieve an improvement of 7.1% on some real-world applications such as SIFT and MSER.
A Robust Modulus-Based Matrix Splitting Iteration Method for Mixed-Cell-Height Circuit Legalization

Modern circuits often contain standard cells of different row heights to meet various design requirements. Taller cells give larger drive strengths and higher speed at the cost of larger areas and power. Multi-row height standard cells incur challenging issues for layout designs, especially the mixed-cell-height legalization problem with heterogeneous cell structures. Honoring the good cell positions from global placement, we present in this article a robust modulus-based matrix splitting iteration method (RMMSIM) to solve the mixed-cell-height legalization problem. Fixing the cell ordering from global placement and relaxing the right-boundary constraints, our proposed method first converts the problem into an equivalent linear complementarity problem (LCP), and then properly splits the matrices in the LCP so that the RMMSIM can solve the LCP optimally. The RMMSIM effectively explores the sparse characteristic of a circuit, and takes only linear time per iteration; as a result, it can solve the QP very efficiently. Finally, an allocation scheme for illegal cells is used to align such cells to placement sites on rows and fix the placement of out-of-right-boundary cells, if any. Experimental results show the effectiveness and efficiency of our proposed algorithm. In addition, the RMMSIM convergence and optimality are theoretically proved and empirically validated. In particular, this article provides a new RMMSIM formulation for various optimization problems that require solving large-scale convex quadratic programming problems efficiently.
Strategy to Increase Behavior Intention of Using NetSuite in Food Service Industry Study Case: Company X

To face Industrial Revolution 4.0, company start to invest Information Technology (IT) system to improve effectiveness and efficiency in decision making and business processes. One of the technology investments chosen by a lot of companies is using the Enterprise Resources Planning (ERP) system. However, the ERP implementation has a 60-90% failure risk (Ahmad, 2014) and user technology readiness is the main key for the success of ERP implementation (Sun, 2011). To make strategies that fit the needs of food service company, this research was evaluating the Technology Readiness Index (TRI) of the workers and researching the relation between technology readiness and the acceptance of ERP technology named NetSuite in Company X. To evaluating the TRI, the researcher used the updated Technology Readiness Index method developed by Parasuraman in (2014). To research the correlation between technology readiness and the technology acceptance model, the researcher uses Technology Readiness and Acceptance Model (TRAM) and processed by Partial Least Square- Structural Equation Modelling (PLS-SEM). The result is Company X has a High Readiness Technology and the variable that affects the behavior intention of using NetSuite is perceived ease of use, the variable affected the perceived ease of use are optimism, innovativeness, and discomfort. The strategy plan designed by the result of the research and validated using Importance-Performance Analysis (IPA).
Depth insight for data scientist with RapidMiner « an innovative tool for AI and big data towards medical applications»

RapidMiner tool is considered among the advanced analytics and powerful platform services in the field of artificial intelligence besides the Big Data storage. This solution has emerged towards several industries such as Financial Services, Energy, Logistics, Life Science and Healthcare and has shown a crucial impact for predictive decisions in this area. This work seeks to describe the solution strategy of this tool for data scientist by depicting a depth insight of this concept which contains more 1500 native algorithms, data preparation and data science functions. This features allows professionals to support any machine learning libraries and integrate python and R codes. RapidMiner offers three different modalities to access to their products which are the main Platform, the automated data science and the AI cloud.
Corneal Cross-Linking for Keratoconus: Current Knowledge and Practice and Future Trends

Abstract Corneal collagen cross-linking (CXL) with riboflavin is an accepted universal standard of care for our keratoconus patients with progressive disease. It has been a game changer in how we manage keratoconus. Early diagnosis and treatment is essential in paediatric patients as younger patients progress more rapidly and have poorer transplant outcomes. There is an ongoing debate around standard, accelerated, and transepithelial protocols of CXL, the role of CXL, and the combination of laser refractive surgery. Future developments will improve CXL safety and efficacy and the scope of utilization, but we must be careful not to leap too far ahead with clinical applications before publication of basic science research and good clinical results with standardized protocols.
Zingiber officinale (ginger) extract as a histological dye for muscle fibers and cytoplasm

Background: The rhizome of Zingiber officinale belongs to the family Zingiberaceae, which has a deep yellow color. It is generally called ginger and consumed whole as a medicine or used as a spice in cooking, manufacturing drinks, and tea. Previous studies have shown the importance of this plant in traditional medicine for the treatment of several ailments and even in the dye industry. The later use could be owing to its deep yellowish coloration, which could benefit the histologist and histoscientist when used in an improvised manner.Therefore, this study was carried out to determine the staining potential of crude ethanolic extract of Z.officinale on tissue sections taken from the heart, lungs, spleen, and liver of Wistar rats. Objective: To study Z. officinale (ginger) extract as a histological dye for muscle fibers and cytoplasm. Materials and Methods: Tissue samples were obtained from the heart, spleen, lungs, and liver of adult Wistar rats. The tissues were histologically processed and sectioned with a rotary microtome. Zingiber officinale was obtained from a local store in Owo, Ondo state, Nigeria,and extracted with 90% ethanol, thereby giving rise to a crude extract, which was then used to counterstain the sections earlier stained with alum hematoxylin. The control tissue sections were correspondingly stained with hematoxylin and counterstained with eosin. Result: The ethanolic extract of Z.officinale, when used as a counterstain for alum hematoxylin, stained the muscle fibers and the cytoplasm yellowish, and the nuclei stained deeply green within 4 min. The staining reaction was suspected to be similar to alum hematoxylin and eosin, except for its greenish yellow color. Conclusion: Zingiber officinale is a promising histological natural dye that is not only cheap but also readily available.
Assessment of commercially available computerized neurocognitive testing in the adolescent concussed athlete: A retrospective analysis.

Brock Hardin, Andrew Gilliland, Thomas Belmaggio, Charles Giangarra, John R. Castillo, and Mark K. Timmons Author Affiliations Brock Hardin (Marshall University, Huntington, West Virginia), Andrew Gilliland (Marshall University, Huntington, West Virginia), Thomas Belmaggio (Marshall University, Huntington, West Virginia), Charles Giangarra (Marshall University, Huntington, West Virginia), John R. Castillo (Marshall University, Huntington, West Virginia), Mark K. Timmons (Marshall University, Huntington, West Virginia)
Anatomy of a twin DNA replication factory

The replication of DNA in chromosomes is initiated at sequences called origins at which two replisome machines are assembled at replication forks that move in opposite directions. Interestingly, in vivo studies observe that the two replication forks remain fastened together, often referred to as a replication factory. Replication factories containing two replisomes are well documented in cellular studies of bacteria (Escherichia coli and Bacillus subtilis) and the eukaryote, Saccharomyces cerevisiae. This basic twin replisome factory architecture may also be preserved in higher eukaryotes. Despite many years of documenting the existence of replication factories, the molecular details of how the two replisome machines are tethered together has been completely unknown in any organism. Recent structural studies shed new light on the architecture of a eukaryote replisome factory, which brings with it a new twist on how a replication factory may function.
2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2021.

The American Diabetes Association (ADA) "Standards of Medical Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee (https://doi.org/10.2337/dc21-SPPC), are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations, please refer to the Standards of Care Introduction (https://doi.org/10.2337/dc21-SINT). Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes. org/SOC.
A COMPARISON OF HEAT-INDUCED CHANGES OF INTRAMUSCULAR CONNECTIVE TISSUE AND COLLAGEN OF BEEF SEMITENDINOSUS MUSCLE DURING WATER BATH AND MICROWAVE HEATING

The main objective of this study was to characterize the thermal properties of intramuscular connective tissue (IMCT) and collagen in beef semitendinosus (ST) muscle from Chinese yellow bulls during water bath and microwave heating. Beef ST muscle was heated to internal endpoint temperature of 40, 50, 60, 70, 80 and 90C by water bath and microwave oven, respectively. The results indicated that insoluble collagen contents of microwave-heated meat were higher than water bath heated except for 90C, and showed significant differences at 80 and 90C (P < 0.05). Mechanical strength of IMCT showed significant difference (P < 0.05) at 60C between water bath- and microwave-heated meat. Perimysial portion content of microwave-heated meat was significantly higher than water bath heated at 60, 70, 80 (P < 0.05) and 90°C (P < 0.01), and endomysial portion content showed a gradual decrease during heating. A heating temperature of 60C was critical, and affects the maximum shrinkage temperatures (Tmax) of IMCT for both heated meat. With the increase in heating temperature, granulation changes of IMCT and disorderly changes of collagenous fibers arrangement have resulted. PRACTICAL APPLICATIONS It is well known that the characteristics of intramuscular connective tissue (IMCT) and collagen are related to meat quality, especially for the meat tenderness. Besides, heating is an important step for the conversion of inedible (raw) meat to edible meat, and can make remarkable effects on the eating quality of meat. Based on those viewpoints, we reported the comparative research of water bath and microwave heating on the effects of meat quality and thermal characteristics of IMCT and collagen. Results reported in this article would be useful either for the science community or for the food industry of beef production. Moreover, our study can provide the reference for the systematic researches for Chinese yellow bulls in the future.
Neuronal Innervation of the Intestinal Crypt.

Mucosal damage is a key feature of inflammatory bowel diseases (IBD) and healing of the mucosa is an endpoint of IBD treatment that is often difficult to achieve. Autonomic neurons of the parasympathetic and sympathetic nervous system may influence intestinal epithelial cell growth and modulating epithelial innervation could for that reason serve as an interesting therapeutic option to improve mucosal healing. Understanding of the biological processes triggered by nonspecific and specific epithelial adrenergic and cholinergic receptor activation is of key importance. At present, with rising technological advances bioelectronics neuromodulation as treatment modality has gained momentum. We discuss the current view on state-of-the-art innervation of the intestinal crypt and its impact on epithelial cell growth and differentiation. Furthermore, we outline bioelectronic technology and review its relevance to wound healing processes.