Miracle-dz/UniFAR-FTUs huggingface dataset:
A Local Self-Attention Sentence Model for Answer Selection Task in CQA Systems

Current evidence indicates that the semantic representation of question and answer sentences is better generated by deep neural network-based sentence models than traditional methods in community answer selection tasks. In particular, as a widely recognized language model, the self-attention model computes the similarity between the specific word and the whole sets of words in the same sentence and generates new semantic representation through the similarity-weighted summation of semantic representations of the whole words. However, the self-attention operation entirely considers all the signals with a weighted sum operation, which disperses the distribution of attention, which may result in overlooking the relation of neighboring signals. This issue becomes serious when applying the self-attention model to online community question answering platforms because of the varied length of the user-generated questions and answers. To address this problem, we introduce an attention mechanism enhanced local self-attention (LSA), which restricts the range of original self-attention by a local window mechanism, thereby scaling linearly when increasing the sequence length. Furthermore, we propose stacking multiple LSA layers to model the relationship of multiscale $n$ -gram features. It captures the word-to-word relationship in the first layer and then captures the chunk-to-chunk (such as lexical $n$ -gram phrases) relationship in its deeper layers. We also test the effectiveness of the proposed model by applying the learned representation through the LSA model to a Siamese and a classification network in community question answer selection tasks. Experiments on the public datasets show that the proposed LSA achieves a good performance.
Integrated Analysis of the microRNA–mRNA Network Predicts Potential Regulators of Atrial Fibrillation in Humans

Atrial fibrillation (AF) is a form of sustained cardiac arrhythmia and microRNAs (miRs) play crucial roles in the pathophysiology of AF. To identify novel miR–mRNA pairs, we performed RNA-seq from atrial biopsies of persistent AF patients and non-AF patients with normal sinus rhythm (SR). Differentially expressed miRs (11 down and 9 up) and mRNAs (95 up and 82 down) were identified and hierarchically clustered in a heat map. Subsequently, GO, KEGG, and GSEA analyses were run to identify deregulated pathways. Then, miR targets were predicted in the miRDB database, and a regulatory network of negatively correlated miR–mRNA pairs was constructed using Cytoscape. To select potential candidate genes from GSEA analysis, the top-50 enriched genes in GSEA were overlaid with predicted targets of differentially deregulated miRs. Further, the protein–protein interaction (PPI) network of enriched genes in GSEA was constructed, and subsequently, GO and canonical pathway analyses were run for genes in the PPI network. Our analyses showed that TNF-α, p53, EMT, and SYDECAN1 signaling were among the highly affected pathways in AF samples. SDC-1 (SYNDECAN-1) was the top-enriched gene in p53, EMT, and SYDECAN1 signaling. Consistently, SDC-1 mRNA and protein levels were significantly higher in atrial samples of AF patients. Among negatively correlated miRs, miR-302b-3p was experimentally validated to suppress SDC-1 transcript levels. Overall, our results suggested that the miR-302b-3p/SDC-1 axis may be involved in the pathogenesis of AF.
Empagliflozin Ameliorates Progression From Prediabetes to Diabetes and Improves Hepatic Lipid Metabolism: A Systematic Review

Diabetes mellitus (DM) and hepatic steatosis are two of the most common metabolic syndromes that affect the health of people globally. Empagliflozin (EMPA) is a promising drug of choice for the diabetic population. Recent studies have shown its beneficial effects not only on diabetic patients but also on patients suffering from cardiac, hepatic, neurological, or pancreatic anomalies. In this paper, we systematically searched electronic databases to compile literature that focuses on EMPA’s effect on the prediabetic population, diabetic population, and hepatic lipid metabolism. We focus on the mechanism of EMPA, specifically by which it increases insulin sensitivity and fat browning and reduces fat accumulation. Overall, we hypothesized that by its effect on weight loss and reducing inflammatory markers and insulin resistance (IR), EMPA decreases the rate of prediabetes to diabetes conversion. We concluded that by improving hepatic and serum triglyceride, decreasing visceral fat, and its positive impact on hepatic steatosis, the drug improves hepatic lipid metabolism. Further research should be done on this matter.
Digitalization of Knowledge Development in the Media Industry

Disruption in the global media and publishing industry is prevalent due to digitalization and new business models. The Scandinavian media market have already for a decade experienced disruptive technology and digital changes. The old highly profitable two-sided business model of both selling newspapers and adds has evaporated. Remaining is a freemium or even worse – a free content and a small margin from selling online advertisements. To compensate for revenue reduction the media organizations digitalize, and consequently have made a lot of media workers redundant. To create competitive advantage in this digital landscape, the players in the media industry needs to utilize big data analytics to make better decisions and to learn. It requires media organizations to gather, process, and act on a lot of information by combining digital multisided platforms. To know customer preferences and behavior there is a strong need to analyze, learn and explore rich information sources. They also need to be better at knowledge management to transform insight from data to organizational changes. To date there is limited empirical research detailing this learning process involving big data analytics and knowledge management. We offer insight from a case study of one of Norway’s larger publishing houses, with ownership in several newspapers and online media platforms. The case study was conducted during 2021 and is based on 10 different interviews with newspaper editors, journalists, commercial managers, and business analysts. Learning is an essential part of developing dynamic capabilities and this study is built on frameworks developed on knowledge development by applying the 4Iorganizational learning framework as an analytical lens. Our findings reveal important triggers and barriers for use of digital analytical tools and organizational learning processes. Especially intuiting, by providing more granularity to this dimension of the 4I framework corresponding better to the contemporary digitalized organizational reality. From this in-depth study of big data we gain insight into organizational learning from the intuition process. What triggers information retrieval can be categorized in three different areas: Strategic, Development and Cooperative aspects. In terms of strategic, availability of analytical tools is a crucial factor for a data-driven publishing business. From a development perspective, hypothesis-testing, developing new business models and new services is the core of big data analytics. The last dimension identified is cooperation as it is easier to find a common ground and direction for the organization. Big data analytics creates a coordination element in the organization. Although big data is a frequent business concept, relatively few articles address the challenges of using business analytical tools for understanding how organizations convert knowledge and learn and from big data.
Diagnose Diabetic Mellitus Illness Based on IoT Smart Architecture

Obtaining a quick remote diagnosis of heart disease has proven problematic in recent days. To overcome such issues in e-Healthcare systems, Internet of Things (IoT) applications have been deployed using cloud computing (CC) approaches. There are still a number of disadvantages to using CC, including latency, bandwidth, energy usage, and security and privacy concerns. Fog computing (FC), a CC development, may be able to overcome these obstacles. DiaFog enabling remote users for real-time diagnosis of diabetic mellitus disease (DMD) has been proposed in this study, which is based on the combined ideas of IoT, cloud, and fog computing, as well as an ensemble deep learning (EDL) technique. The proposed system is trained with EDL approaches on the integrated dataset of two diabetes mellitus disease datasets (DMDDs), namely, Pima Indians Diabetes Dataset (PIDD) and Hospital Frankfurt Germany Diabetes Dataset (HFGDD), obtained from the UCI-ML and Kaggle repository, respectively, and the integrated dataset of these two. The suggested system has been used to demonstrate accuracy, precision, recall, F -measure, latency, arbitration time, jitter, processing time, throughput, energy consumption, bandwidth utilization, network utilization, scalability, and more. In the remote instantaneous diagnosis of diabetic patients, the integration of IoT-fog-cloud is useful. The results of the trials show the value of employing FC principles and their applicability for speedy diabetic patient remote diagnosis. PACS-key is describing text of that key PACS-key describing text of that key.
Algebras of sets and combinatorics

Introduction Main results The main idea Finite sequences of algebras (1). Proof of Theorems 2.1 and 2.2 Countable sequences of algebras (1). Proof of Theorem 2.4 Proof of the Gitik-Shelah theorem, and more from set theory Proof of Theorems 1.17, 2.7, 2.8 Theorems on almost $\sigma$-algebras. Proof of Theorem 2.9 Finite sequences of algebras (2). The function $\mathfrak{g}(n)$ A description of the class of functions $\Psi_*^7$ The general problem. Proof of Theorems 2.15 and 2.20 Proof of Theorems 2.21(1,3), 2.24 The inverse problem Finite sequences of algebras (3). Proof of Theorems 2.27, 2.31, 2.36, 2.38 Preliminary notions and lemmas Finite sequences of algebras (4). Proof of Theorems 2.39(1,2), 2.45(1,2) Countable sequences of algebras (2). Proof of Theorems 2.29, 2.32, 2.46 A refinement of theorems on $\sigma$-algebras. Proof of Theorems 2.34, 2.44 Semistructures and structures of sets. Proof of Theorem 2.48 Final comments. Generalization of Theorem 2.1 Appendix: On a question of Grinblat by S. Shelah Bibliography Index.
Enhancing brand equity in branded apps: A hedonic and utilitarian motivation´s perspective

Although an increasing amount of research nowadays investigates the impact of mobile apps, how branded apps influence desirable outcomes, such as brand equity, remains underexplored. This research develops a conceptual model to capture how perceived motivations and task-service fit influence brand engagement and enhance brand equity via branded apps. Data collected from 292 mobile app users show that utilitarian motivations positively impact task-service fit, that task-service fit has a positive impact on consumer brand engagement and brand equity, and that consumer brand engagement has a positive impact on brand equity. Conversely, hedonic motivations do not significantly influence task-service fit. This work provides a better understanding of the influence of task-service fit on brand equity via branded apps. It also generates practical implications for brands to successfully develop their apps and use them to enhance brand equity.
Strategies of adults for dealing with feelings of guilt – findings from a large web-based survey

BACKGROUND Feelings of guilt are common in adulthood. Depending on the situation, individuals need different strategies for dealing with these usually unpleasant experiences. The aim of this study was to provide comprehensive empirical information about such different guilt-related strategies used in adulthood. PARTICIPANTS AND PROCEDURE A cross-sectional web-based survey was conducted (05/2019-04/2020) collecting autobiographical information on guilt experiences. Stated strategies for dealing with feelings of guilt were classified into inductively defined categories, and the frequency of the categorized strategies was calculated (total, gender-, age-specific). Associations between applied strategies and gender and age were analyzed using Cramér’s φ and V as appropriate. RESULTS Analyzing statements of 579 participants (18-84 years), we differentiated 34 different categories of guilt-related strategies. The most frequently used strategies were “Self-reflection; contemplation; analyzing/reviewing things one feels guilty about” and “Repressing/ignoring/(actively) forgetting/not thinking about/bottling up the feelings of guilt”. Female and male participants showed a significantly different use only in the strategy of utilizing “Professional support/therapy/counseling” (10.57% vs. 3.67%; Cramér’s φ = .13, p = .001). Additionally, only a few differences were found with regard to age. CONCLUSIONS Adults use a broad variety of different strategies for dealing with feelings of guilt. Strategies regulating emotional responses to the problem causing feelings of guilt seem to be at least as important as strategies targeting the problem itself. Many strategies do not serve pro-social functions. Feelings of guilt are an issue relevant for mental health care since several of the adults with feelings of guilt utilize professional help, and an even higher number may need such help.
Theory of algebraic invariants

Preface Introduction Part I. The Elements of Invariant Theory: 1. The forms 2. The linear transformation 3. The concept of an invariant 4. Properties of invariants and covariants 5. The operation symbols D and D 6. The smallest system of conditions for the determination of the invariants and covariants 7. The number of invariants of degree g 8. The invariants and covariants of degree two and three 9. Simultaneous invariants and covariants 10. Covariants of covariants 11. The invariants and covariants as functions of the roots 12. The invariants and covariants as functions of the one-sided derivatives 13. The symbolic representation of invariants and covariants Part II. The Theory of Invariant Fields: 14. Proof of the finitenesss of the full invariant system via representation by root differences 15. A generalizable proof for the finiteness of the full invariant system 16. The system of invariants I I1, I2, . , Ik 17. The vanishing of the invariants 18. The ternary nullform 19. The finiteness of the number of irreducible syzygies and of the syzygy chain 20. The inflection point problem for plane curves of order three 21. The generalization of invariant theory 22. Observations about new types of coordinates.
Serological Investigation and Epidemiological Analysis of Bovine Leptospirosis in Egypt

Bovine leptospirosis is a bacterial zoonotic disease of worldwide distribution. Little information is available regarding the occurrence of the disease in the Nile Delta provinces, Egypt. The present study investigated the seroprevalence of leptospirosis among cattle from Dakahlia province, Northern Egypt, and identified the individual variables factors associated with infection. To this end, a total of 600 serum samples from cattle of small stakeholders with various clinical manifestations possibly associated with leptospirosis were collected from different localities across Dakahlia province, Egypt. Sera were examined serologically via ELISA to investigate the occurrence of the disease among animals. Chi-square test and multivariable logistic regression analyses were applied to determine the association between hypothesized risk factors and the disease. Interestingly, our findings showed that 39.33% of the examined sera were positive for Leptospira antibodies, with significant differences among different localities. In addition, statistical analysis showed significant differences among age groups. Notably, the highest prevalence rate (22%) was observed in those aged between 3 and 5 years (p < 0.0001), whereas the lowest prevalence (2.66%) was reported in cattle <1 year old (p < 0.0001). Moreover, females had a significantly higher prevalence rate (35.33%) than males (4%) (p < 0.0001). Furthermore, our results showed significant differences in the occurrence of infection and reported clinical signs (p < 0.0001). Multivariable logistic regression identified repeated breeder and drop milk yield as the best predictors for prediction of ELISA results and linear discriminant analysis (LDA) model showed that overall classification accuracy of ELISA result using clinical signs and demographic data as predictors was 70.7%. The current study concluded a relative high prevalence of leptospirosis among cows bred in movable herds and households in the studied area and that age, repeated breeder and drop milk yield can be considered major risk factors associated with infection.
Effectiveness and Safety of the Traditional Chinese Medicine Treatment (HuoxueHuayu Therapy) for Malignant Tumors: A Systematic Review and Meta-Analysis

Background A malignant tumor is one of the refractory diseases that threaten human life and health. HuoxueHuayu therapy (one of the Traditional Chinese Medicine therapies to promote blood circulation and remove blood stasis) is widely used as an antitumor supplementary method. However, its efficacy and safety are still controversial. Therefore, the objective of this study was to provide evidence-based evidence for HuoxueHuayu therapy in the treatment of malignant tumors and confirm its safety and effectiveness. Methods A systematic search in 8 electronic databases targeted randomized clinical studies evaluating HuoxueHuayu therapy for response evaluation, tumor progression rate, quality of life (QoL), peripheral hemogram, performance status, immunologic function, tumor marker, and blood coagulation function in cancer patients, published from the establishment of the database to December 31, 2020. Risk ratio (RR) was used for counting data, mean difference (MD) or standardized mean difference (SMD) was used for measurement data, and 95% confidence interval (CI) was used as efficacy analysis statistics. Results Our search identified 69 studies, evaluating 4402 patients in total. Randomized controlled trials (RCTs) evaluated gastric (n = 14), lung (n = 18), pancreatic (n = 2), colorectal (n = 10), liver (n = 14), breast (n = 2), ovarian (n = 2), gallbladder (n = 1), esophagus (n = 1), and combined (n = 14) cancers and hematological malignancies (n = 2). The duration of HuoxueHuayu therapy ranged from 3 to 48 weeks. Methodological bias was low in 64 studies and high in 5 studies. HuoxueHuayu therapy was associated with significant improvement in response evaluation (Response Evaluation Criteria in Solid Tumor (RECIST): RR: 1.44, 95% CI: 1.27 to 1.63, I2 = 0%, n = 33 studies; World Health Organization Criteria in Solid Tumors (WHOCIST): RR: 1.40, 95% CI: 1.23 to 1.59, I2 = 0%, n = 26 studies), recurrence rate (RR: 0.85, 95% CI: 0.72 to 0.99, I2 = 0%, n = 2 studies), quality of life, performance status (MD: 5.60, 95% CI: 5.04 to 6.15, p < 0.001), immunologic function (CD3: SMD: 1.23, 95% CI: 0.79 to 1.66, p < 0.001; CD4: SMD: 1.25, 95% CI: 0.77 to 1.74, p < 0.001; CD4/CD8: SMD: 1.05, 95% CI: 0.69 to 1.42, p < 0.001; natural killer cell (NK): SMD: 0.74, 95% CI: 0.32 to 1.15, p < 0.001), tumor marker, and blood coagulation function (D-dimer (D-D); fibrinogen (FIB)). In addition, HuoxueHuayu therapy could reduce toxicity caused by chemotherapy and radiotherapy without risks of liver and kidney injury or bleeding, although the effect on tumor metastasis was uncertain. Conclusions The present update of our systematic review and meta-analyses provided essential evidence for the beneficial effect of HuoxueHuayu therapy to show promise in cancer treatment, improving quality of life, addressing cancer-related symptoms, and reducing toxicity in a secure way.
Hepatitis C Virus Reactivation in Anti-HCV Antibody-Positive Patients with Chronic Hepatitis B Following Anti-HBV Therapies

Background and Aims: Whether hepatitis C virus (HCV) reactivation occurs and how the viral load evolves in anti-HCV antibody-positive chronic hepatitis B (CHB) patients who underwent nucleos(t)ide analogue (Nuc) therapies remain unsolved. Methods: A cohort of 66 such patients was studied. Results: At the start of Nuc treatment (baseline), all patients had detectable hepatitis B virus (HBV) DNA levels (6.05 ± 1.88 log IU/mL), while HCV RNA levels (3.79 ± 1.43 log IU/mL) were detected (i.e., chronic hepatitis C (CHC)) in only 13 patients (19.7%). Following Nuc therapies, HBV DNA levels reached the nadirs at end of therapy (EOT) (6.05 ± 1.88 vs. 0.25 ± 0.99 log IU/mL, p < 0.0001) and relapsed at 6 months after EOT (6mEOT) at a level of 3.45 ± 2.64 log IU/mL compared with EOT (p < 0.0001). Among the 13 CHC patients, a non-significant decrease in HCV RNA was noted at EOT (3.52 ± 1.71 vs. 2.77 ± 2.63 log IU/mL, p = 0.166) but tended to decrease further at 6mEOT (2.77 ± 2.63 vs. 1.89 ± 2.06 log IU/mL, p = 0.063). Two of the thirteen CHC patients showed an increase in HCV-RNA ≥ 1 log10 IU/mL at EOT, and one of the fifty-three patients with undetectable HCV RNA at baseline (i.e., resolved past HCV infection) showed detectable HCV RNA at year 1 (3200 IU/mL) and year 2 (1240 IU/mL) following entecavir therapy. Conclusions: HCV reactivation did occur during HBV suppression, and the rate was 4.5% (3/66), 15.4% (2/13), and 1.9% (1/53), for all patients, CHC patients, and patients with resolved past HCV infection, respectively. The reverse HBV and HCV viral evolutions at 6mEOT indicate that HBV relapse may suppress HCV replication again.
The Early History of Microquasar Research

Microquasars are compact objects (stellar-mass black holes and neutron stars) that mimic, on a smaller scale, many of the phenomena seen in quasars. Their discovery provided new insights into the physics of relativistic jets observed elsewhere in the universe, and the accretion--jet coupling. Microquasars are opening new horizons for the understanding of ultraluminous X-ray sources observed in external galaxies, gamma-ray bursts of long duration, and the origin of stellar black holes and neutron stars. Microquasars are one of the best laboratories to probe General Relativity in the limit of the strongest gravitational fields, and as such, have become an area of topical interest for both high energy physics and astrophysics.
Initial Testing of an Approximated, Fast Calculation Procedure for Personalized Dosimetry in Radionuclide Therapy Based on Planar Whole-Body Scan and Monte-Carlo Specific Dose Rates from the OpenDose Project

Individualized dosimetry in nuclear medicine is currently at least advisable in order to obtain the best risk–benefit balance in terms of the maximal dose to lesions and under-threshold doses to radiosensitive organs. This article aims to propose a procedure for fast dosimetric calculations based on planar whole-body scintigraphy (WBS) images and developed to be employed in everyday clinical practice. Methods: For simplicity and legacy reasons, the method is based on planar imaging dosimetry, complemented with some assumptions on the radiopharmaceutical kinetics empirically derived from single-photon emission tomography/computed tomography (SPECT/CT) image analysis. The idea is to exploit a rough estimate of the time-integrated activity as has been suggested for SPECT/CT dosimetry but using planar images. The resulting further reduction in dose estimation accuracy is moderated by the use of a high-precision Monte-Carlo S-factor, such as those available within the OpenDose project. Results: We moved the problem of individualized dosimetry to a transformed space where comparing doses was imparted to the ICRP Average Male/Female computational phantom, resulting from an activity distribution related to patient’s pharmaceutical uptake. This is a fast method for the personalized dosimetric evaluation of radionuclide therapy, bearing in mind that the resulting doses are meaningful in comparison with thresholds calculated in the same framework. Conclusion: The simplified scheme proposed here can help the community, or even the single physician, establish a quantitative guide-for-the-eye approach to individualized dosimetry.