Miracle-dz/UniFAR-FTUs huggingface dataset:
The Impact of Knowledge Capture and Knowledge Sharing on Learning, Adaptability, Job Satisfaction and Staying Intention: A Study of the Banking Industry in Bangladesh

Abstract The Knowledge Management (KM) has been defined as performing activites in discovering, capturing, sharing and applying knowledge in a more effective and effieicnt way. This study looks at only two such processes namely: capruring and sharing knowledge and their sub-processes. The purpose of this study is to conduct exploratory research to investigate the extent to which the sub-processes of knowledge capture and knowledge sharing of knowledge management impact the employee learning, adaptability, Job satisfaction and intention to stay on the job. This research was conducted using a purposive sample from financial services firms in Bangladesh. The sample consisted of 254 respondents from 23 different branches of eight commercial banks drawing from all levels of employees in the organizational hierarchy. The partial least squares (PLS) approach using Smart PLS has been used to test both the measurement and structural models. The findings of this study confirm that it is not the KM processes rather the sub-processes of KM process that can positively impact on employees' outcomes. This study involved self-administrated questionnaires and was open to all levels of staff and measured perceptions of the employees as opposed to actual behavior. This study suggests that employees' learning and adaptability depend on the usability and comfortability of the knowledge management initiatives undertaken by the management. Practitioners may employ the same experimental method using the instruments developed for this study to analyze the impact of the subprocesses of knowledge capture and knowledge sharing on employee outcomes. This study contributes to the existing literature of knowledge management that how the sub-processes of knowledge capture and knowledge sharing motivate employees to learn and adapt and how learning and adaptability contribute to job satisfaction and staying intention.
The Parallel Tiled WZ Factorization Algorithm for Multicore Architectures

Abstract The aim of this paper is to investigate dense linear algebra algorithms on shared memory multicore architectures. The design and implementation of a parallel tiled WZ factorization algorithm which can fully exploit such architectures are presented. Three parallel implementations of the algorithm are studied. The first one relies only on exploiting multithreaded BLAS (basic linear algebra subprograms) operations. The second implementation, except for BLAS operations, employs the OpenMP standard to use the loop-level parallelism. The third implementation, except for BLAS operations, employs the OpenMP task directive with the depend clause. We report the computational performance and the speedup of the parallel tiled WZ factorization algorithm on shared memory multicore architectures for dense square diagonally dominant matrices. Then we compare our parallel implementations with the respective LU factorization from a vendor implemented LAPACK library. We also analyze the numerical accuracy. Two of our implementations can be achieved with near maximal theoretical speedup implied by Amdahl’s law.
LMI–Based Robust Control of Uncertain Nonlinear Systems via Polytopes of Polynomials

Abstract This investigation is concerned with robust analysis and control of uncertain nonlinear systems with parametric uncertainties. In contrast to the methodologies from the field of linear parameter varying systems, which employ convex structures of the state space representation in order to perform analysis and design, the proposed approach makes use of a polytopic form of a generalisation of the characteristic polynomial, which proves to outperform former results on the subject. Moreover, the derived conditions have the advantage of being cast as linear matrix inequalities under mild assumptions.
Investigating Statistical Privacy Frameworks from the Perspective of Hypothesis Testing

Abstract Over the last decade, differential privacy (DP) has emerged as the gold standard of a rigorous and provable privacy framework. However, there are very few practical guidelines on how to apply differential privacy in practice, and a key challenge is how to set an appropriate value for the privacy parameter ɛ. In this work, we employ a statistical tool called hypothesis testing for discovering useful and interpretable guidelines for the state-of-the-art privacy-preserving frameworks. We formalize and implement hypothesis testing in terms of an adversary’s capability to infer mutually exclusive sensitive information about the input data (such as whether an individual has participated or not) from the output of the privacy-preserving mechanism. We quantify the success of the hypothesis testing using the precision- recall-relation, which provides an interpretable and natural guideline for practitioners and researchers on selecting ɛ. Our key results include a quantitative analysis of how hypothesis testing can guide the choice of the privacy parameter ɛ in an interpretable manner for a differentially private mechanism and its variants. Importantly, our findings show that an adversary’s auxiliary information - in the form of prior distribution of the database and correlation across records and time - indeed influences the proper choice of ɛ. Finally, we also show how the perspective of hypothesis testing can provide useful insights on the relationships among a broad range of privacy frameworks including differential privacy, Pufferfish privacy, Blowfish privacy, dependent differential privacy, inferential privacy, membership privacy and mutual-information based differential privacy.
Can You Ink While You Blink? Assessing Mental Effort in a Sensor-Based Calligraphy Trainer

Sensors can monitor physical attributes and record multimodal data in order to provide feedback. The application calligraphy trainer, exploits these affordances in the context of handwriting learning. It records the expert’s handwriting performance to compute an expert model. The application then uses the expert model to provide guidance and feedback to the learners. However, new learners can be overwhelmed by the feedback as handwriting learning is a tedious task. This paper presents the pilot study done with the calligraphy trainer to evaluate the mental effort induced by various types of feedback provided by the application. Ten participants, five in the control group and five in the treatment group, who were Ph.D. students in the technology-enhanced learning domain, took part in the study. The participants used the application to learn three characters from the Devanagari script. The results show higher mental effort in the treatment group when all types of feedback are provided simultaneously. The mental efforts for individual feedback were similar to the control group. In conclusion, the feedback provided by the calligraphy trainer does not impose high mental effort and, therefore, the design considerations of the calligraphy trainer can be insightful for multimodal feedback designers.
Protein Vaccination Directs the CD4+ T Cell Response toward Shared Protective Epitopes That Can Be Recalled after Influenza Virus Infection

Most current and new influenza vaccine candidates consist of a single influenza virus protein or combinations of influenza virus proteins. For these vaccines to elicit CD4+ T cells that can be recalled after infection, the peptide epitopes should be shared between the two modes of confrontation. Recently, questions regarding the relatedness of epitope selection by influenza virus infection and protein vaccination have been raised. However, the studies reported here show that the specificity of CD4+ T cells elicited by protein-based vaccines overlaps that of T cells elicited by infection and that CD4+ T cells primed by protein vaccines are recalled and contribute to protection of the host from a future infection. ABSTRACT Vaccination is widely used to generate protective immunity against influenza virus. CD4+ T cells contribute in diverse ways to protective immunity, most notably, in the provision of help for the production of neutralizing antibodies. Several recent reports have suggested that influenza virus infection elicits CD4+ T cells whose specificity only partially overlaps that of T cells elicited by vaccination. This finding has raised serious concerns regarding the utility of currently licensed inactivated influenza virus vaccines and novel protein-based vaccines. Here, using controlled animal models that allowed a broad sampling of the CD4+ T cell repertoire, we evaluated protein vaccine- versus infection-generated CD4+ T cell epitopes. Our studies revealed that all the infection-elicited CD4+ T cell epitope specificities are also elicited by protein vaccination, although the immunodominance hierarchies can differ. Finally, using a reverse-engineered influenza virus and a heterologous protein vaccination and infection challenge strategy, we show that protein vaccine-elicited CD4+ memory T cells are recalled and boosted after infection and provide early help to accelerate hemagglutinin (HA)-specific antibody responses. The early CD4+ T cell response and HA-specific antibody production are associated with lowered viral titers during the infection challenge. Our data lend confidence to the ability of current protein-based vaccines to elicit influenza virus-specific CD4+ T cells that can potentiate protective immunity upon influenza virus infection. IMPORTANCE Most current and new influenza vaccine candidates consist of a single influenza virus protein or combinations of influenza virus proteins. For these vaccines to elicit CD4+ T cells that can be recalled after infection, the peptide epitopes should be shared between the two modes of confrontation. Recently, questions regarding the relatedness of epitope selection by influenza virus infection and protein vaccination have been raised. However, the studies reported here show that the specificity of CD4+ T cells elicited by protein-based vaccines overlaps that of T cells elicited by infection and that CD4+ T cells primed by protein vaccines are recalled and contribute to protection of the host from a future infection.
High-dose levocetirizine for the treatment of refractory chronic spontaneous urticaria and the effect on the serum inositol triphosphate level

Objective The second messenger inositol triphosphate (IP3) is involved in signal transduction in multiple cell types. We evaluated the effects of high-dose levocetirizine on chronic spontaneous urticaria (CSU) and examined the significance of serum IP3 level in the pathogenesis of CSU. Methods Fifteen patients with refractory CSU were given oral levocetirizine at a dose of 15 mg once daily for 7 days, and treatment efficacy was determined using the Urticaria Activity Score and by evaluating wheal-and-erythema reactions and itching. The serum concentration of IP3 at specific time points was determined by enzyme-linked immunosorbent assay. Results The mean serum concentration of IP3 was 43.54 ± 41.97 pg/mL prior to treatment, 18.40 ± 17.53 pg/mL after treatment, and 1.31 ± 0.92 pg/mL in a healthy control group. The mean concentration of IP3 was significantly higher before treatment than after treatment, and the level of IP3 in the patient group before and after treatment was significantly higher than that in the control group. Conclusion High-dose levocetirizine was shown to be effective in the treatment of CSU. The level of serum IP3 was positively correlated with CSU activity, indicating that IP3 may play an important role in the pathogenesis of this condition.
Microstructural damage of normal-appearing white matter in subcortical ischemic vascular dementia is associated with Montreal Cognitive Assessment scores

Objectives This study was performed to determine whether multimodal biomarkers are more strongly associated with the Montreal Cognitive Assessment (MoCA) scores compared with the Mini-Mental State Examination (MMSE) scores, and whether they are correlated with the Clinical Dementia Rating (CDR) in patients with subcortical ischemic vascular dementia (SIVD). Methods Patients diagnosed with SIVD were enrolled. Peripheral blood hypersensitive C-reactive protein, white matter lesion volume (WMLV), fractional anisotropy (FA)/mean diffusivity (MD) of whole brain white matter (WBWM), and normal-appearing white matter (NAWM) were measured and correlated with MMSE, MoCA, and CDR scores. Results Bivariate analyses of data from 48 included patients revealed that both MoCA and MMSE were significantly associated with age, education, and FA of NAWM. Only MD of NAWM was correlated with MoCA scores. In partial correlation analysis adjusted for demographic and neuroimaging variables, MD/FA of NAWM and the MoCA scores were significantly correlated. FA/MD of NAWM had a modest trend toward a correlation with the CDR, but it was not significant. Conclusions In the patients with SIVD, FA/MD of NAWM were more strongly related to MoCA scores compared with MMSE scores.
Artificial intelligence in the interpretation of breast cancer on MRI

Advances in both imaging and computers have led to the rise in the potential use of artificial intelligence (AI) in various tasks in breast imaging, going beyond the current use in computer‐aided detection to include diagnosis, prognosis, response to therapy, and risk assessment. The automated capabilities of AI offer the potential to enhance the diagnostic expertise of clinicians, including accurate demarcation of tumor volume, extraction of characteristic cancer phenotypes, translation of tumoral phenotype features to clinical genotype implications, and risk prediction. The combination of image‐specific findings with the underlying genomic, pathologic, and clinical features is becoming of increasing value in breast cancer. The concurrent emergence of newer imaging techniques has provided radiologists with greater diagnostic tools and image datasets to analyze and interpret. Integrating an AI‐based workflow within breast imaging enables the integration of multiple data streams into powerful multidisciplinary applications that may lead the path to personalized patient‐specific medicine. In this article we describe the goals of AI in breast cancer imaging, in particular MRI, and review the literature as it relates to the current application, potential, and limitations in breast cancer.
Interaction of Dietary Linoleic Acid and α-Linolenic Acids with rs174547 in FADS1 Gene on Metabolic Syndrome Components among Vegetarians

Fatty acid desaturase 1 (FADS1) gene controls the fatty acid metabolism pathway in the human body. The lower intake of α-linolenic acid (ALA) than linoleic acid (LA) among vegetarians may disrupt the fatty acid metabolism and limit the conversion of ALA to anti-inflammatory products such as eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). This cross-sectional study aimed to determine the interaction of rs174547 in FADS1 gene with LA and ALA on metabolic syndrome (MetS) components. A total of 200 Chinese and Indian vegetarians in Kuala Lumpur and Selangor, Malaysia participated in the present study. The data on socio-demographic characteristics, vegetarianism practices, dietary practices, anthropometric measurements, blood pressure (BP), and overnight venous fasting blood samples were collected from the vegetarians. The rs174547 in FADS1 gene was significantly associated with MetS and its components such as waist circumference (WC) and fasting blood glucose (FBG). Multiple logistic regression analyses revealed that vegetarians with TT genotype of rs174547 in FADS1 gene had higher odds for MetS, larger WC, higher BP, and a lower level of HDL-c. Two-way ANOVA analysis showed that LA interacts with rs174547 in FADS1 gene to affect HDL-c (p < 0.05) among vegetarians. The present findings suggest the need to develop dietary guidelines for vegetarians in Malaysia. Prospective studies are also needed to affirm the interaction between LA and rs174547 in FADS1 gene on HDL-c among Malaysian vegetarians.
A Longitudinal Investigation of Empathic Exchanges in Online Cancer Support Groups: Message Reception and Expression Effects on Patients’ Psychosocial Health Outcomes

Recent studies have devoted attention to the effects of both expression and reception in communication process. However, there remain both theoretical and methodological complexities concerning whether and under what condition message expression and reception play significant but different roles in explaining various psychosocial health outcomes. Relying on theoretical insights from the social support literature and methodological innovations offered by computational social science, this study aims to examine the effects of empathic exchanges on cancer patient’s short- and long-term psychosocial health outcomes. Our findings suggest that both empathy expression and reception are crucial to attaining benefits for cancer patients, each predicting differential cognitive and affective health outcomes. Further, our finding supports the stress-buffering hypothesis such that empathy reception provides a beneficial effect for patients who experienced a higher degree of depression associated with their cancer diagnosis and follow-up treatments.
Self-care strategies and sources of knowledge on menstruation in 12,526 young women with dysmenorrhea: A systematic review and meta-analysis

Introduction: Dysmenorrhea (period pain) is common and affects around three quarters of all young women under the age of 25. The majority of young women, for a variety of reasons, think of period pain as ‘normal’ and something to be managed or endured. This normalisation of pain often is reinforced by family and friends and results in young women using self-care strategies to manage their pain rather than seeking medical advice. This systematic review and meta-analysis examined observational studies reporting on the prevalence of different types of self-care, both pharmaceutical and non-pharmaceutical, self-rated effectiveness of self-care and the sources of information on menstruation in young women under 25 Methods: A search of Medline, PsychINFO, EMBASE and CINAHL in English was carried out from 1980 to December 2018. Studies that reported on menstrual self-care strategies in young women were included. Results: Nine hundred and forty-seven articles were screened. Twenty-four studies including 12,526 young women were eligible and included in the meta-analysis. Fifteen studies were from low, lower-middle or upper-middle-income countries (LMIC) and nine studies were from high income countries (HIC). Self-care was used by over half of all young women (55%, 95%CI 34.1–74.3) with both pharmaceutical (48%, 95%CI 40.0–57.0) and non-pharmaceutical (51.8%, 95%CI 31.3–71.7) options used. Paracetamol was the most common analgesic used (28.7%, 95%CI 19.6–39.9) but did not always provide sufficient pain relief in almost half of those using it. Contraceptive use was significantly higher (P<0.001) in HIC (22%) compared to LMIC (1%). Only 11% (95%CI 8.4–15.2) of young women reported seeing a medical doctor for their period pain. Conclusions: Self-care usage, both pharmaceutical and non-pharmaceutical, was common, but young women were not necessarily choosing the most effective options for pain management. High-quality information on self-care for period pain is urgently needed.
On the Evaluation of the NB-IoT Random Access Procedure in Monitoring Infrastructures

NarrowBand IoT (NB-IoT) is emerging as a promising communication technology offering a reliable wireless connection to a large number of devices employed in pervasive monitoring scenarios, such as Smart City, Precision Agriculture, and Industry 4.0. Since most of the NB-IoT transmissions occur in the uplink, the random access channel (that is the primary interface between devices and the base station) may usually become the main bottleneck of the entire system. For this reason, analytical models and simulation tools able to investigate its behavior in different scenarios are of the utmost importance for driving current and future research activities. Unfortunately, scientific literature partially addresses the current open issues by means of simplified and, in many cases, not standard-compliant approaches. To provide a significant step forward in this direction, the contribution of this paper is three-folded. First, it presents a flexible, open-source, and 3GPP-compliant implementation of the NB-IoT random access procedure. Second, it formulates an analytical model capturing both collision and success probabilities associated with the aforementioned procedure. Third, it presents the cross-validation of both the analytical model and the simulation tool, by taking into account reference applications scenarios of sensor networks enabling periodic reporting in monitoring infrastructures. Obtained results prove the remarkable accuracy, demonstrating a well-calibrated instrument, which will be also useful for future research activities.
Retrospective frailty determination in critical illness from a review of the intensive care unit clinical record

Frailty is one of the major challenges for intensive care, affecting one-third of intensive care unit patients and being associated with a range of poor health outcomes. Determination of frailty in critical illness using the Clinical Frailty Scale has recently been adopted by the Australian and New Zealand Intensive Care Society, but it is not known whether this is able to be measured from the clinical record without interviewing patients or their relatives. The aims of this retrospective cohort study were to test whether a Clinical Frailty Scale score could be assigned in an intensive care unit population from the clinical record, and to assess the inter-rater reliability of frailty measured in this manner. A total of 144 patients were enrolled. Of these, 137 (95%) were able to have a Clinical Frailty Scale score assigned, and 22 (15%) were scored as frail (Clinical Frailty Scale ≥5). Cohen’s kappa coefficient for inter-rater reliability between assessors was 0.67, confirming substantial agreement. Consistent with other critically ill cohorts, frailty was associated on multivariate analysis with age, Charlson comorbidity score, dependence with activities of daily living, and limitation of medical treatment, indicating validity of this approach to frailty measurement. Our results imply that frailty measurement is possible and feasible from the intensive care unit clinical record, which is of importance as routine measurement and reporting of frailty in intensive care units in our region increases. Future work should seek to validate an assigned Clinical Frailty Scale score with that obtained directly from patients or their next of kin.