Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-level meta-modeling architectures applied to eHealth

Over the last decade, a growing digital universe of unstructured or semistructured human-sourced information, structured process-mediated data, and well-structured machine-generated data, encourages the adoption of innovative forms of data modeling and information processing to enable enhanced insight, decision making, and process automation applied to a variety of different contexts. Healthcare comprises a notable domain of interest, where the availability of a large amount of information can be exploited to take relevant and tangible benefits in terms of efficiency of the care process, improved outcomes and reduced health system costs. However, due to the complex nature of clinical data, a number of challenges needs to be faced, mainly related on how data characterized by volume, variety, variability, velocity, and veracity can be effectively and efficiently modeled, and how these data can be exploited for increasing the domain knowledge and supporting decision-making processes. The aim of this dissertation is to describe the crucial role played by software architectures in order to overcome challenges posed by the healthcare context. Specifically, this dissertation addresses the development and applicability of multi-level meta-modeling architectures to various scenarios of eHealth, where flexibility and changeability represent primary requirements. Meta-modeling principles are concretely exploited in the implementation of an adaptable patient-centric Electronic Health Record (EHR) system to face a number of challenging requirements, including: adaptability to different specialities and organizational contexts; run-time configurability by domain experts; interoperability of heterogeneous data produced by various sources and accessed by various actors; applicability of guideline recommendations for evaluating clinical practice compliance; applicability of Activity Recognition techniques for monitoring and classifying human activities in pervasive intelligent environments.
Hybrid WK-recursive on-chip network for multi-core system

WK-recursive based networks well conform to a modular design due to the properties of regularity and scalability. Here, the focus is on a triplet-based WK-recursive topology and its implementation using tiled shapes in multi-core processors design is explored. To further improve the network throughput and reduce the network latency, a pair of heterogeneous topologies is proposed to separate the core communication from the memory communication. It is demonstrated that the triangular topologies are feasible to be implemented with rectangular tile floor-planning.
The ectomycorrhizal association of Tricholoma matsutake and two allied species, T. bakamatsutake and T. fulvocastaneum, with native hosts in subtropical China

ABSTRACT Accurate identification of edible ectomycorrhizal (ECM) mushrooms and their host trees in nature is key to commercial production for consumption. For the first time we describe the ectomycorrhizal association of the three most common species of edible matsutake mushrooms with their native host trees in Yunnan Province in China. We collected ECM samples from three different localities in subtropical forests known to be highly productive areas of Tricholoma. Additionally, we collected basidiomata of Tricholoma from the field and markets in Yunnan. ECM samples were analyzed using morphological and molecular methods. We conducted phylogenetic analyses of nuc rDNA internal transcribed spacer region ITS1-5.8S-ITS2 (ITS) and analyzed the intergenic spacer of cpDNA psbA-trnH to identify basidiomata and plant hosts, respectively. Three species of Tricholoma were identified: T. bakamatsutake, T. fulvocastaneum, and T. matsutake. Four ECM associations in the study area were detected: Tricholoma bakamatsutake + Castanopsis tibetana, T. fulvocastaneum + C. tibetana, T. fulvocastaneum + Pinus yunnanensis, and T. matsutake + P. yunnanensis. Detailed descriptions and illustrations of the ECM associations are presented.
Quantitative Strain and Topography Mapping of 2D Materials Using Nanobeam Electron Diffraction

Abstract It is known that 2D materials can exhibit a nonflat topography, which gives rise to an inherent strain. Since local curvature and strain influence mechanical, optical, and electrical properties, but are often difficult to distinguish from each other, a robust measurement technique is needed. In this study, a novel method is introduced, which is capable of obtaining quantitative strain and topography information of 2D materials with nanometer resolution. Relying on scanning nanobeam electron diffraction (NBED), it is possible to disentangle strain from the local sample slope. Using the positions of the diffraction spots of a specimen at two different tilts to reconstruct the locations and orientations of the reciprocal lattice rods, the local strain and slope can be simultaneously retrieved. We demonstrate the differences to strain measurements from a single NBED map in theory, simulation, and experiment. MoS2 monolayers with different shapes are used as simulation test structures. The slope and height information are recovered, as well as tensile and angular strain which have an absolute difference of less than 0.2% and 0.2° from the theoretical values. An experimental proof of concept using a freely suspended WSe2 monolayer together with a discussion of the accuracy of the method is provided.
Using the Biopsychosocial Approach to Identify Factors Associated with Major Depressive Disorder for Individuals with Hypothyroidism

Abstract Previous research has found that major depressive disorder (MDD) commonly occurs in hypothyroid populations. The purpose of this study was to use the biopsychosocial model to investigate factors associated with MDD and hypothyroidism by comparing hypothyroid patients with MDD and without MDD. A sample of 386 participants with hypothyroidism completed both cognitive and psychosocial self-reported assessments along with a questionnaire rating the severity of common hypothyroid symptoms. Participants were divided into two groups (MDD and no MDD) using the diagnostic criteria of the Patient Health Questionnaire. Univariate comparisons were used to assess differences in the severity of physical, psychological, and social correlates in participants with and without MDD. Participants with MDD reported significantly worse symptom severity, increased stress, and disruptions of cognitive functioning. Compared to individuals without MDD, they also indicated poorer quality of life, doctor–patient relationships, and treatment adherence. Individuals with comorbid depression and hypothyroidism reported worse outcomes across physical symptoms, social factors, and psychological and cognitive states than individuals without MDD. Integrating depression screeners and independent treatment for MDD, in addition to the patient’s hypothyroid treatment plan, may result in hypothyroid symptom relief and greater quality of life.
RhoBTB1 reverses established arterial stiffness in angiotensin II–induced hypertension by promoting actin depolymerization

Arterial stiffness predicts cardiovascular disease and all-cause mortality, but its treatment remains challenging. Mice treated with angiotensin II (Ang II) develop hypertension, arterial stiffness, vascular dysfunction, and a downregulation of Rho-related BTB domain–containing protein 1 (RhoBTB1) in the vasculature. RhoBTB1 is associated with blood pressure regulation, but its function is poorly understood. We tested the hypothesis that restoring RhoBTB1 can attenuate arterial stiffness, hypertension, and vascular dysfunction in Ang II–treated mice. Genetic complementation of RhoBTB1 in the vasculature was achieved using mice expressing a tamoxifen-inducible, smooth muscle–specific RhoBTB1 transgene. RhoBTB1 restoration efficiently and rapidly alleviated arterial stiffness but not hypertension or vascular dysfunction. Mechanistic studies revealed that RhoBTB1 had no substantial effect on several classical arterial stiffness contributors, such as collagen deposition, elastin content, and vascular smooth muscle remodeling. Instead, Ang II increased actin polymerization in the aorta, which was reversed by RhoBTB1. Changes in the levels of 2 regulators of actin polymerization, cofilin and vasodilator-stimulated phosphoprotein, in response to RhoBTB1 were consistent with an actin depolymerization mechanism. Our study reveals an important function of RhoBTB1, demonstrates its vital role in antagonizing established arterial stiffness, and further supports a functional and mechanistic separation among hypertension, vascular dysfunction, and arterial stiffness.
Enabling sustainable energy futures: factors influencing green supply chain collaboration

Abstract To explore the relationship between sustainability strategies and future energy needs, supply chains need to reduce their CO2 emissions through developing their green credentials and improving performance. Knowledge management (KM) is an enabler to support collaboration efforts. The SCM and KM areas have largely focused on improving organisational performance. While the latter has yielded successful outcomes in different sectors, there is still a scarcity of research on identifying influential factors highlighting those aspects which may enable green supply chain collaboration (GrSCC), thus leading to sustainable energy futures and carbon-efficient production. This paper examines the role of KM in facilitating GrSCC. Through the identification of key factors extrapolated from the literature, a model for implementing GrSCC using a futures-based perspective is proposed. This paper inductively demonstrates the relationship between identified GrSCC factors through fuzzy cognitive mapping technique. Findings support a futures-based perspective that enhances understanding and refines forward-looking strategies for GrSCC.
Capsule endoscopy in gastrointestinal disease: Evaluation, diagnosis, and treatment

Capsule endoscopy, also known as wireless capsule endoscopy or video capsule endoscopy, is a noninvasive procedure that uses a swallowed capsule-shaped miniature camera for direct visual and diagnostic evaluation of gastrointestinal (GI) disease. Although originally intended as a tool to examine the small intestine, which is mostly beyond the reach of conventional endoscopy, capsule endoscopy is now also being used to examine the entire length of the GI tract. The procedure is mainly used to evaluate obscure bleeding in the small bowel, but it is also used in the evaluation and diagnosis of a wide range of gastrointestinal conditions.
Spatio-temporal variation of fractional vegetation coverage in the Aydingkol Lake Basin

Abstract. As one of the driest and lowest regions in Asia, the vegetation variation in the Aydingkol Lake Basin in Xinjiang, China, reveals the status of its ecological recovery. To more accurately retrieve the fractional vegetation index (FVC) to investigate the vegetation variation in this basin, we proposed an innovative method—the random forest (RF) method—based on multiple remote sensing indices. The retrieval shows a satisfactory accuracy with a mean error, mean square error, mean relative error (RE) percentage, and determination coefficient of 0.01,0.04,14.61% and 0.95, respectively. In the Aydingkol Lake Basin, the average annual FVC peaked in 2015 with a value of 0.08. The annual average value of FVC decreases at a rate of 0.06 * 10 − 2 / a during these eight years. The reduction of FVC is mainly distributed in the central-western part of the basin. In exploring the influence on FVC, average annual precipitation has the most significant impact on the FVC. Its correlation coefficient with FVC is 0.87. With increasing elevation and slope, most FVC showed a decreasing trend. In recent years, the conversion of cropland to barren land and cropland to grassland had the greatest impact on decreasing of the FVC, and the mean FVC decreases from 0.19 to 0.17 before and after the land-use change. Moreover, human impact had a significant influence on the variation in FVC. Due to the establishment of the Aydingkol Lake Basin Wetland Reserve (the SAIC Volkswagen Test Site), the annual average FVC in the corresponding place increases from 0.06 to 0.13 (decreases from 0.148 to 0.005). This study is helpful to guide ecological protection in similar arid regions.
Curricula Design & Pedagogy for Sketching Within HCI & UX Education

Sketching is recognised as an important tool in the journey of research and practical processes of Human Computer Interaction (HCI) and User Experience Design (UX). However, it is not always included in higher education curriculum, in which HCI and UX is often a single module in one year group amongst more “traditional” approaches in computer science. The benefits of sketching and visualisation practice can be used by students across the board in computing degrees, but especially so within HCI and UX, where novel approaches and ideation are valued and practiced. By the time learners leave higher education, they may or may not have engaged with this valuable skill. HCI has a lot in common with UX, and the two are commonly conflated to be the same thing, though despite this, there is not a focus on practical sketching and visualisation skills. In comparison, within the UX workplace environment, sketching is part of design thinking and vital for the structuring of ideas, storyboards, user journey maps and more. We focus on the incorporation and exploration of sketching as an educational tool, technique and output within HCI, and how this learning is given and received over a number of contexts. This paper outlines case studies where sketching has been included in both formal and informal learning with both undergraduate, postgraduate, and post education populations, and how this knowledge exchange has been both enhanced and changed by the recent compulsory move to online teaching during the COVID-19 pandemic. We discuss practice and learning in the context of four case studies: Data-Sketching in a First Year Minor; Sketching in a 2nd Year HCI Cohort; Sketching as a Foundational Tool for MSc User Experience Design; and, Sketching in HCI for Peer-to-Peer Learning. Further, we make recommendations for incorporating sketching practice and theory into both undergraduate and postgraduate university programs, as well as for peer-to-peer learning in both public and private contexts.
Recruitment Through AI in Selected Indian Companies

Artificial intelligence (AI) is being used very pervasively with the ever-evolving and competitive business world and has become the 21st-century buzzword. Countless innovations in technology have pushed businesses to make their value creation processes more effective and customer friendly. Digitization has played a significant role in reshaping the different human resource functions and processes. This study aims to elucidate the acceptance of automation in human resource management by employers and the degree to which recruiters can use AI to hire people. The study incorporates a thematic analysis approach, and the data is collected from primary sources by conducting semi-structured interviews with four experts working in IT organizations. This research would be useful for recruiters and HR managers to consider the fields of AI implementation and management to take advantage of cost-cutting technical developments.
Automated Cell Recognition using Single-cell RNA Sequencing with Machine Learning

This paper investigates the superiority and limitations of different dimensionality reduction schemes and classification methods in specific single-cell RNA sequencing (scRNA-seq) data sets. With systematic analysis as well as variables-controlled experiments, a pipeline was constructed from rpkm data to final cell type recognition and multiple dimension reduction methods are applied (including PCA, AutoEncoder, ISOMAP, and the combination algorithm of PCA+t-SNE) and multiple classifiers (Random Forest and Support Vector Machine, etc.) to obtain the accuracy difference of multiple solutions. By comparing the variation of different models and parameters on the final classification accuracy, this paper summarizes and outlook the information loss and classification effects of different processing schemes on the data set and seeks to find the best combination from them. Using the combination of PCA+SVM, this work obtained 53.13% global maximum accuracy and based on this result to further explore the possibility of improving accuracy and model transfer learning in a wider range of applications.
IT Solutions for Preventing and Monitoring Adverse Drug Reactions: A Systematic Literature Review

∗ Patient safety is one of the most crucial aspects in the healthcare industry. Minimizing adverse drug reactions (ADR) and medical errors are the focus for improving patient’s quality of life. However, it is undeniable that no drug is free from side effects. In fact, ADR caused 2.3% to 21.2% of hospital admissions, and ADR cases are also hard to trace because less than 5% of cases were reported directly by the patient. An increasing amount of research has been conducted to see the potential of information technology (IT) for preventing and monitoring ADR. However, we rarely find a comprehensive article review to discuss IT solutions for preventing and monitoring ADR. Therefore, this paper conducted a systematic review of papers published in 2016-2021 to see the current IT solutions for preventing and monitoring ADR. This paper focuses on clinical decision support system (CDSS) as the solutions for preventing ADR, and Patient Health Monitoring (PHM) software for monitoring ADR. Our study found most previous research conducted by developed countries with cardiology and endocrinology as the most prevalent disease domain. In relation to prior research on CDSS, the use of knowledge-based CDSS still dominates the previous research. At the same time, mobile is the most used platform for monitoring ADR. We also attempted to categorize the features based on the approaches to give drug recommendations and report ADR.
Expression and biochemical significance of Piwil2 in stem cell lines

Abstract Introduction P-element induced wimpy testis-like 2 (Piwil2) is in the Piwi gene family. Piwil2 has important roles in the self-renewal mechanism of stem cell induction and progression of numerous types of human malignancies such as lung, breast, colon, prostate, and cervical cancers. Glutathione S-transferase (GST) acts as detoxification in cancer metabolism. This study aimed to investigate the effects of the stem cell protein Piwil2 on MCF10A and MCF-7 at the GST activity levels. Materials/Methods MCF-7/Piwil2 and MCF10A/Piwil2, transfected with a plasmid carrying the Piwil2 gene, and non-transfected MCF-7 and MCF10A were cultured in a complete DMEM/F12 medium. GST A1 and P1 activity was determined in these cell lines using as substrates CDNB, EA respectively. Results According to experimental results, GST P1 activity decreased in the MCF-7/Piwil2 cells as compared with the non-transfected MCF-7 cells, however, MCF-7/Piwil2 cells demonstrated increases in GST A1 (total GST) activity. The statistically significant differences were found for the comparison of non-transfected MCF-7 and MCF-7/Piwil2 (p<0,0001), for GST enzyme activities by using CDNB and EA as substrates. These results were the same for the MCF10A cell line. Discussion It is shown for the first time that transfection studies may affect GST activity at the cellular mechanism level. The study contributes to determining the effect of transfection on GST isoenzymes and also how the Piwil2 gene may affect GST activity in the stem cell line.
The interaction between stress and metabolic disruption in student population – preliminary study

Abstract Introduction: Approximately 26% of individuals between 18 and 24 years old are overweight or obese, and the number of persons with excessive body mass index (BMI) is growing. Obesity increases the risk of metabolic disruptions, which is well connected with mental health problems. Stressful situations, including entering adulthood and starting university education, affect food choices negatively. The aim of the study was to examine the relationship between psychological stress and body composition in the student population. Materials and methods: The study group consisted of 80 students (76% of women and 24% of men) between 19 and 28 years old from universities in Lublin. To determine anthropometric measurement (fat-free mass (FFM), fat mass (FM), total body water (TBW), intracellular (ICF) and extracellular (ECF) fluids), bioelectrical impedance analysis (BIA) method was applied. The severity of stress symptoms was measured using Perceived Stress Scale (PSS-10). Results: When it comes to 41.25% of participants, they used relaxation techniques, mainly meditation, yoga practice and walking. Most students had optimal body weight. While 60% of individuals had high stress levels. The perceived stress was not related to using the relaxation methods. Individuals with the high stress severity were characterized by lower: TBW, ECF and ICF expressed in liters, and lower FFM represented in kilograms. The inverse relationship between the severity of stress and the aforementioned parameters was also detected (p<0.05). Conclusions: Implementing appropriate healt h education programs to prevent negat ive changes in ant hropometric measurements, psychological stress, and their health-related consequences in the student population should be considered.
QT INTERVAL PROLONGATION IS A NOVEL PREDICTOR OF 1-YEAR MORTALITY IN PATIENTS WITH COVID-19 INFECTION

Background QT interval prolongation is common in critically ill patients and is associated with increased mortality. However, the predictive value of a prolonged corrected QT interval (QTc) for myocardial injury and long-term mortality among patients hospitalized with COVID-19 infection is not well known. Purpose To evaluate the association of prolonged QTc with myocardial injury and with 1-year mortality among patients hospitalized with COVID-19 infection. Materials and Methods A total of 335 consecutive patients hospitalized with COVID-19 infection were prospectively studied. All patients underwent a comprehensive echocardiographic evaluation within 48 h from admission. Using the Bazett formula, the QTc interval was calculated from the first ECG tracing recorded at the ER. QTc ≥ 440 ms in males and ≥450 ms in females was considered prolonged. Patients with elevated cardiac biomarkers and/or echocardiographic signs of myocardial dysfunction were considered to have myocardial injury. The predictive value of QTc prolongation for myocardial injury was calculated using a multivariate binary regression model. One-year mortality rate of patients with and without QTc prolongation was compared using the log-rank test, and a multivariate Cox regression model adjusting for multiple covariates was performed to evaluate the 1-year mortality risk. Results One-hundred and nine (32.5%) patients had a prolonged QTc. Compared to patients without QTc prolongation, patients with prolonged QTc were older (70 ± 14.4 vs. 62.7 ± 16.6, p < 0.001), had more comorbidities, and presented with a more severe disease. Prolonged QTc was an independent predictor for severe or critical disease (adjusted HR 2.14, 95% CI 1.3–3.5; p = 0.002) and myocardial injury (adjusted HR 2.07, 95% CI 1.22–3.5; p = 0.007). One-year mortality of patients with prolonged QTc was higher than those with no QTc prolongation (40.4% vs. 15.5; p < 0.001). Following adjustment to multiple covariates including myocardial injury and disease severity, QTc prolongation was found to be associated with increased 1-year mortality risk (HR 1.69, 95% CI 1.06–2.68, p = 0.027). Conclusion Prolonged QTc is associated with disease severity, myocardial injury and 1-year mortality among patients hospitalized with COVID-19 infection.