Miracle-dz/UniFAR-FTUs huggingface dataset:
Population Pharmacokinetic (Pop-PK) Analysis of Torsemide in Healthy Korean Males Considering CYP2C9 and OATP1B1 Genetic Polymorphisms

Torsemide is a diuretic drug used for several cardiovascular and chronic diseases. With regard to the clinical application of torsemide, studies on individualized pharmacotherapy and modeling that take variability in pharmacokinetics (PKs) within a population into account have been rarely reported. Thus, the objective of this study was to perform population pharmacokinetic (Pop-PK) modeling and to identify effective covariates that could explain the inter-individual variability (IIV) of torsemide PK. Pop-PK modeling for torsemide was performed based on serum concentration data obtained from 112 healthy Korean males and analysis of various genetic and physicochemical parameters. Modeling was performed with nonlinear mixed-effects (NLME) using Phoenix NLME. The finally developed model was fully verified. The model was also reconfirmed using NONMEM software. As a basic model, the PKs of torsemide within the population were well described by a two-compartment model reflecting the lag-time on oral absorption. According to the genetic polymorphisms of OATP1B1 and CYP2C9, significant associations were found in the V/F, CL/F, and CL2/F of torsemide. These were reflected as effective covariates in the final Pop-PK model of torsemide, resulting in an approximately 5–10% improvement in the model parameter IIV values. Considering that torsemide is a substrate for CYP2C9 and OATP1B1, it was important to search for genetic polymorphisms in CYP2C9 and OATP1B1 as covariates to explain the PK diversity of torsemide between individuals. The differences in CL/F and CL2/F between the phenotypes of CYP2C9 were approximately 36.5–51%. The difference in V/F between the phenotypes of OATP1B1 was approximately 41–64.6%. These results suggested that the phenotypes of CYP2C9 and OATP1B1 produced significant differences in torsemide PKs. Considering that CYP2C9 and OATP1B1 phenotypes as covariates affected different PK parameters of torsemide, it could be inferred that torsemide’s cell membrane permeation process by OATP1B1 and the metabolic process by CYP2C9 could independently affect each other in vivo without interplay. There was no significant difference in the parameter estimates between modeling software (Phoenix NLME vs. NONMEM). In this study, the torsemide PK variability between individuals was largely explained. In the future, individualized effective drug therapy of torsemide taking individual patient’s genotypes into account might become possible.
Angiographic Parameters in Diagnosis of Microvascular Dysfunction in Patients with Heart Failure with Preserved Ejection Fraction

Background: Heart failure with preserved ejection fraction (HFpEF) is a health care problem of epidemic proportions, currently accounting for roughly 3 million patients in the United States alone. Objective: To study, using validated angiography indices, coronary blood flow and myocardial perfusion of the microcirculation to assess whether there is greater microvascular disease (MVD) in patients with microvascular angina and HFpEF compared to those who do not have. Patients and methods: This retrospective study took place in El-Mahalla Cardiac Center on 160 patients with stable angina undergoing coronary angiography and echocardiography. All patients were subjected to complete history taking, full clinical examination, echocardiography, coronary angiography and angiography indices. Our patients were divided into two categories: 80 patients with HFpEF and 80 without HFpEF. Results: There were statistically significant differences between the studied groups. We found lower myocardial blush grades (MBG) in three coronary arteries in HFpEF than non-HFpEF patients, with good statistical significance regarding MBG left anterior descending (LAD) and MBG left circumflex (LCX). Also, there was statistically significant difference between the studied groups regarding total MBG value. Between thrombosis in myocardial infarction frame count (TFC) and MBG, there was a good correlation. The best cutoff of total TFC in diagnosis in diagnosis of HFpEF was ≥ 98.55 with sensitivity of 92.5% and specificity of 73.8%. Also, the best cutoff of total MBG in diagnosis in diagnosis of HFpEF was ≤ 6.55 with sensitivity of 80% and specificity of 87.5%. Conclusion: The HFpEF population has a greater involvement of microcirculation than patients without HFpEF.
Development of A Vision-based Tactile Sensor

Receiving tactile information from a slave-robot is a necessary component of telexistence with haptic display, but there are few tactile sensors that can measure the distribution of three-dimensional force vectors on a surface. For this reason, we developed a sensor that provides three-dimensional force distribution by detecting movement vectors in the transparent elastic body with a video camera. From a result of the experiment, it turned out this approach is effective.
Thermodynamic Analysis of Dehydration of K2co3 · 1.5h2o

This work studied the reversible dehydration of potassium carbonate sesquihydrate (K 2 CO 3 ⋅ 1.5H 2 O). The study is based on isobaric and isothermal thermogravimetric measurements conducted at a broad range of vapour pressures and temperatures. By controlling both parameters, we examined the influence of both constraints on the reaction kinetics at a wide extent of supersaturations. We have evaluated our experimental findings by employing two thermodynamic theories, classical nucleation theory and transition state theory. By combining both approaches, we were able to establish that: (1) At low supersaturations in a region close to equilibrium, dehydration is limited by nucleation and growth of the anhydrous phase (2) At high supersaturations, dehydration reaches maximum rate and is controlled by the reaction speed. Furthermore, we show that the dehydration of K 2 CO 3 ⋅ 1.5H 2 O is very sensitive to pressure-temperature conditions and that it does not possess universal activation energy.
The Effect of Phonological Awareness on Preparatory stage EFL Teachers' Pronunciation competence

The purpose of this research was to determine the effect of phonological awareness theory on the preparatorystage EFL teachers’ pronunciationcompetence. The EFL teachers were 20 teachers in Al SaydaZienab directorate-South Cairo District.Three instruments were used:needs analysis questionnaire tocollect the required information from EFL teachersin order to elicit their responses about EFL teacher's pronunciationskills and phonological awareness,a pre-posttest in to investigate the effects of the suggested program based on phonological awareness on developing the required EFL teachers’ pronunciation competancebefore and after the program and scoring rubric in order to be able to measure some features of pronunciation.Results of the study indicated that phonological awareness theory contributed more to EFLpreparatory stage teachers' pronunciation.The study recommended the need for improving preparatory stage EFLteachers' performance through training courses, workshops and ongoing improvement to increase their efficiency within the field of their work.
Reducing Medication Problems among Minority Individuals with Low Socioeconomic Status through Pharmacist Home Visits

Introduction: In this study, pharmacists conducted home visits for individuals of medically underserved populations in Taiwan (i.e., socioeconomically disadvantaged individuals, middle-aged or older adults, and individuals living alone, with dementia, or with disabilities) to understand their medication habits. We quantified medication problems among various groups and investigated whether the pharmacist home visits helped to reduce the medication problems. Materials and Methods: From April 2016 to March 2019, pharmacists visited the homes of the aforementioned medically underserved individuals in Taipei to evaluate their drug-related problems and medication problems. Age, living alone, diagnoses of dementia or disabilities, and socioeconomic disadvantages contributed significantly to inadequate disease and medical treatment knowledge and self-care skills as well as lifestyle inappropriateness among patients. The patients who were living alone and socioeconomically disadvantaged stored their drugs in inappropriate environments. Results: After the pharmacists visited the patients’ homes twice, the patients improved considerably in their disease and medical treatment knowledge, self-care skills, and lifestyles (p < 0.001). Problems related to the uninstructed reduction or discontinuation of drug use (p < 0.05) and use of expired drugs (p < 0.001) were also mitigated substantially. Discussion and conclusion: Through the home visits, the pharmacists came to fully understand the medicine (including Chinese medicine) and health food usage behaviors of the patients and their lifestyles, enabling them to provide thorough health education. After the pharmacists’ home visits, the patients’ drug-related problems were mitigated, and their knowledge of diseases, drug compliance, and drug storage methods and environments improved, reducing drug waste. Our findings can help policymakers address the medication problems of various medically underserved groups, thereby improving the utilization of limited medical resources.
Higher Phytohormone Contents and Weaker Phytohormone Signal Transduction Were Observed in Cold-Tolerant Cucumber

Cucumbers (Cucumis sativus L.) originated from the South Asian subcontinent, and most of them are fragile to cold stress. In this study, we evaluated the cold tolerance of 115 cucumber accessions and screened out 10 accessions showing high resistance to cold stress. We measured and compared plant hormone contents between cold-tolerant cucumber CT90R and cold-sensitive cucumber CT57S in cold treatment. Most of the detected plant hormones showed significantly higher content in CT90R. To elucidate the role of plant hormones, we compared the leaf- and root-transcriptomes of CT90R with those of CT57S in cold stress treatment. In leaves, there were 1209 differentially expressed genes (DEGs) between CT90R and CT57S, while there were 703 in roots. These DEGs were not evenly distributed across the chromosomes and there were significant enrichments at particular positions, including qLTT6.2, a known QTL controlling cucumber cold tolerance. The GO and KEGG enrichment analysis showed that there was a significant difference in the pathway of plant hormone transductions between CT90R and CT57S in leaves. In short, genes involved in plant hormone transductions showed lower transcription levels in CT90R. In roots, the most significantly different pathway was phenylpropanoid biosynthesis. CT90R seemed to actively accumulate more monolignols by upregulating cinnamyl-alcohol dehydrogenase (CAD) genes. These results above suggest a new perspective on the regulation mechanism of cold tolerance in cucumbers.
On the adaption of data mining technology to categorize cancer diseases

Along with data mining, tools and software have emerged to aid in mining the vast and growing amount of data to access knowledge in databases. These tools facilitate work on most scientific disciplines, including sciences, Libraries and information. Accordingly, Data mining became an effective technique for obtaining knowledge to achieve the basic goal of discovering hidden facts that are contained in databases through the use of multiple technologies that include artificial intelligence, statistical analyzes, techniques and data modeling etc. Medical data mining is considered one of the most important tools used in the field of medicine, especially in exploring and knowing health conditions according to records of former patients. In addition, data mining helps not only in categorizing cancer but also in taking the necessary measures. With the spread of cancer at high rates around the world, the need to develop smart methods that have the ability to predict the disease appeared. Applications of data mining techniques spread as human attempts to control this deadly disease, with the aim of awareness, early detection and reduction of treatment costs. This prompted the researcher's curiosity to know the ability of data mining to categorize cancer. This work aims at reviewing ways to solve one of the problems that doctors suffer from, which is the problem of diagnosing diseases that lead to death, including cancer, as there is huge information that has not been used. Therefore, this work tries to solve this problem using data mining technology in addition to helping doctors make the right decision. The study reached several conclusions, namely the fact that the studies presented in the paper demonstrated the effective role of data mining techniques in reducing medical errors in terms of their ability to predict and accurately diagnose the disease, as well as the effectiveness of the algorithms of the data mining technique in predicting the presence of the disease at an early stage. Thus, we found that the clinical field needs to expand research, foster new kinds of calculations, and apply them practically speaking to create the best and most precise outcomes and even to supplant or surpass specialists' performance at this level.
Prediction of Self-Healing of Engineered Cementitious Composite Using Machine Learning Approaches

Engineered cementitious composite (ECC) is a unique material, which can significantly contribute to self-healing based on ongoing hydration. However, it is difficult to model and predict the self-healing performance of ECC. Although different machine learning (ML) algorithms have been utilized to predict several properties of concrete, the application of ML on self-healing prediction is considerably rare. This paper aims to provide a comparative analysis on the performance of various machine learning models in predicting the self-healing capability of ECC. These models include four individual methods, linear regression (LR), back-propagation neural network (BPNN), classification and regression tree (CART), and support vector regression (SVR). To improve prediction accuracy, three ensemble methods, namely bagging, AdaBoost, and stacking, were also studied. A series of experimental works on the self-healing performance of ECC samples was conducted, and the results were used to develop and compare the accuracy among the ML models. The comparison results showed that the Stack_LR model had the best predictive performance, showing the highest coefficient of determination (R2), the lowest root-mean-squared error (RMSE), and the smallest prediction error (MAE). Among all individual models studies, the BPNN model performed the best in terms of the RMSE and R2, while SVR performed the best in terms of the MAE. Furthermore, SVR had the smallest prediction error (MAE) for crack widths less than 60 μm or greater than 100 μm, while CART had the smallest prediction error (MAE) for crack widths between 60 μm and 100 μm. The study concluded that the individual and ensemble methods can be used to predict the self-healing of ECC. Ensemble models were able to improve the accuracy of prediction compared to the individual model used as their base learner, i.e., a 2.3% to 4.9% reduction in MAE. However, selecting an appropriate individual and ensemble method is critical. To improve the performance accuracy, researchers should employ different ensemble methods to compare their effectiveness with different ML models.
Thermal treatment of pulp and paper mill biosludge and digestate to enhance their anaerobic digestibility

Anaerobic digestion of pulp and paper mill biosludge has the potential to reduce sludge disposal costs and generate energy through biogas production. Thermal treatment can couple with anaerobic digestion to enhance the sludge digestibility. Conventionally, thermal pretreatment of biosludge is used by the industry. In this study, three possible thermal treatment-assisted anaerobic digestion configurations were compared: 1. Thermal pretreatment of biosludge; 2. Digestate thermal treatment; 3. Digestate thermal treatment and only recycling the hydrolysate. The thermal pretreatment (1) of biosludge at the theoretical optimal conditions (170 o C for 1 h) did not extend the ultimate biogas yield. The digestate thermal treatment (2) increased the rate and extent of the biogas production; a synergistic effect on biogas production was observed by co-digesting biosludge and treated digestate. Only recycling the hydrolysate (3) is recommended if the thermal treatment is conducted at high intensities such as the one at 210 o C for 30 min.
A Combinatorial Q-Locus and Tubulin-Based Polymorphism (TBP) Approach Helps in Discriminating Triticum Species

The simple and straightforward recognition of Triticum species is not an easy task due to their complex genetic origins. To provide a recommendation, we have compared the performance of different PCR-based methods relying on the discrimination ability of the Q- and γ-gliadin (GAG56D) genes, as well as TBP (Tubulin-Based Polymorphism), a method based on the multiple amplification of genes of the β-tubulin family. Among these approaches, the PCR-RFLP (Restriction Fragment Length Polymorphism) assay based on a single-nucleotide polymorphism (SNP) present in the Q gene is the only one capable of fully discerning hexaploid spelt and common wheat species, while both γ-gliadin and TBP fail with similar error frequencies. The Q-locus assay results in the attainment of either a single fragment or a doublet, depending on the presence of a suitable restriction site, which is affected by the mutation. This dual pattern of resolution limits both the diagnostic effectiveness, when additional Triticum species are assayed and compared to each other, and its usefulness, when commercially available flours are analyzed. These limitations are overtaken by flanking the Q-locus assay with the TBP analysis. In this way, almost all of the Triticum species can be accurately identified.
Evidence-Based Software Engineering and Systematic Reviews

In the decade since the idea of adapting the evidence-based paradigm for software engineering was first proposed, it has become a major tool of empirical software engineering. Evidence-Based Software Engineering and Systematic Reviews provides a clear introduction to the use of an evidence-based model for software engineering research and practice. The book explains the roles of primary studies (experiments, surveys, case studies) as elements of an over-arching evidence model, rather than as disjointed elements in the empirical spectrum. Supplying readers with a clear understanding of empirical software engineering best practices, it provides up-to-date guidance on how to conduct secondary studies in software engineeringreplacing the existing 2004 and 2007 technical reports. The book is divided into three parts. The first part discusses the nature of evidence and the evidence-based practices centered on a systematic review, both in general and as applying to software engineering. The second part examines the different elements that provide inputs to a systematic review (usually considered as forming a secondary study), especially the main forms of primary empirical study currently used in software engineering. The final part provides practical guidance on how to conduct systematic reviews (the guidelines), drawing together accumulated experiences to guide researchers and students in planning and conducting their own studies. The book includes an extensive glossary and an appendix that provides a catalogue of reviews that may be useful for practice and teaching.
Influence of Pavement Moisture Content on the Load-Bearing Capacity of Forest Road

The aim of the study was to analyse the interaction between pave ment moisture content and load-bearing capacity of an unpaved forest road. The selected experimental road sector was divided into three sections (A, B and C), which were flooded with three different amounts of water 10 mm (section A), 20 mm (section B) and 30 mm (section C), compared with the intense rainfall. Three series of tests were conducted at each section: prior to flooding (1 st day of measurements), during the first 24 hours after flooding (2 nd day) and during the next 24 hours after flooding (3 rd day of measurements). Moisture content of structural layers of the road (surface course, base course and subbase course) were determined and the meas urements using a light weight deflectometer (E vd , s/v ) and a static plate ( E 1 , E 2 , I o ) were conducted. Recorded averaged results clearly indicate a negative effect of an increase in pavement layers moisture content (e.g. resulting from heavy rainfall) on the forest road carrying capacity and on compaction parameters of its layers. On the third day of the measurements a decrease in the analysed modulus, on average between 16% ( E 2 ) and 25% ( E vd ) was observed, but a decrease in compaction by 16% ( s/v ) and 4% ( I o ).
Sicherheitsaspekte bei Virtualisierungen

Virtualisierung ist eine sehr stark verbreitete Technologie, umso wichtiger ist ihre Sicherheit. In diesem Werk finden Sie eine kurze Einfuhrung in die Thematik, einen historischen Ruckblick, eine Vorstellung der Privilegierungsmodelle sowie eine Klassifikation von Virtualisierungsarten. In weiterer Folge werden allgemeine Uberlegungen zur Sicherheit gegeben, Schadsoftware und Technologien beschrieben sowie speziell Sicherheitsaspekte bei Server- und Systemvirtualisierungen behandelt. Virtual Machine Monitors (VMM) haben einen besonderen Stellenwert bei gros angelegten Virtualisierungslosungen - die verbreitetsten VMMs werden hinsichtlich Sicherheit untersucht. Einen besonderen Stellenwert haben Virtual Machine Based Rootkits (VMBR) bzw. hardwarevirtualisierende Rootkits, da es diesen gelingen kann, sogar laufende Betriebssysteme zu infiltrieren. Abschliesend wird Virtualisierungssicherheit in Bezug auf Cloud Computing behandelt sowie ein Ausblick gegeben, welcher im Besonderen auch mobile Systeme einschliest.
“Metaphor in Selected Poems by Yahia Lababidi”

This study examines the extensive use of metaphor in the poetry collection entitled Balancing Acts (2016) by Yahia Lababidi (1973), Egyptian Lebanese American poet, philosopher and aphorist . Lababidi’s use of metaphors seems to be the key to his poetry. In Balancing Acts, the poet’s obsession with Egypt is revealed. Besides, his poems express the dilemma of an immigrant poet experiencing a split identity, homesickness, a conflict between selfexpression and self-suppression, and the struggle between an ideal, spiritual existence and the reality of life in the US. While referring to Lakoff’s and Johnson’s definition of conceptual metaphor, this study will also allude to Martin Gannon’s notion of cultural metaphor, Michael Kimmel’s views about metaphor clusters, Zoltan Kövecses’ emotion concepts (2014), as well as Edward Buzila’s evaluation of the power of metaphor. Significantly, Lababidi’s use of metaphor will be analyzed in terms of Tina Krennmayr’s “bottom-up approach” in such a way as to focus on Lababidi’s cultural and universal metaphors in his attempt to reach out to his fellow humans.