Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimization and Characterization of a Novel Exopolysaccharide from Bacillus haynesii CamB6 for Food Applications

Extremophilic microorganisms often produce novel bioactive compounds to survive under harsh environmental conditions. Exopolysaccharides (EPSs), a constitutive part of bacterial biofilm, are functional biopolymers that act as a protecting sheath to the extremophilic bacteria and are of high industrial value. In this study, we elucidate a new EPS produced by thermophilic Bacillus haynesii CamB6 from a slightly acidic (pH 5.82) Campanario hot spring (56.4 °C) located in the Central Andean Mountains of Chile. Physicochemical properties of the EPS were characterized by different techniques: Scanning electron microscopy- energy dispersive X-ray spectroscopy (SEM-EDS), Atomic Force Microscopy (AFM), High-Performance Liquid Chromatography (HPLC), Gel permeation chromatography (GPC), Fourier Transform Infrared Spectroscopy (FTIR), 1D and 2D Nuclear Magnetic Resonance (NMR), and Thermogravimetric analysis (TGA). The EPS demonstrated amorphous surface roughness composed of evenly distributed macromolecular lumps. GPC and HPLC analysis showed that the EPS is a low molecular weight heteropolymer composed of mannose (66%), glucose (20%), and galactose (14%). FTIR analysis demonstrated the polysaccharide nature (–OH groups, Acetyl groups, and pyranosic ring structure) and the presence of different glycosidic linkages among sugar residues, which was further confirmed by NMR spectroscopic analyses. Moreover, D-mannose α-(1→2) and α-(1→4) linkages prevail in the CamB6 EPS structure. TGA revealed the high thermal stability (240 °C) of the polysaccharide. The functional properties of the EPS were evaluated for food industry applications, specifically as an antioxidant and for its emulsification, water-holding (WHC), oil-holding (OHC), and flocculation capacities. The results suggest that the study EPS can be a useful additive for the food-processing industry.
Differentiation of segmentally identical expressions occurring in the same or different sentence zones in Hungarian by duration, pitch, intensity and irregular voicing

The paper presents the interpretation and explanation of the findings of two pieces of experimental research within the framework of Varga's (2016) pitch-tier model of the Hungarian declarative sentence. One of the experiments was established to investigate the information-structural contribution of quantified expressions (such as mindhárom barátom ‘all three of my friends’ and Csaba is ‘Csaba also’). The other experiment explored the acoustic features of the spontaneous-speech specific discourse marker hát ‘well/so’. The two topics can be regarded as interconnected if Varga's model is interpreted in the strong sense that pitch – presumably in a more or less strong correlation with intensity – is responsible for indicating the topic–comment dichotomy and other factors of the discourse-embedding of sentences. Thus, the reconciliation of our data with Varga's model requires the consideration of the pitch-tier substructures in their complex dynamism. The experiments support the plausible hypothesis that the variants of the discourse marker hát as part of the preparatory contour primarily differ in duration, while is-quantifiers in different pitch-tier parts differ in terms of pitch values.
A Novel Approach to Estimating the Cortical Sources of Sleep Spindles Using Simultaneous EEG/MEG

Sleep spindles, defining oscillations of stage II non-rapid eye movement sleep (N2), mediate sleep-dependent memory consolidation. Spindles are disrupted in several neurodevelopmental, neuropsychiatric, and neurodegenerative disorders characterized by cognitive impairment. Increasing spindles can improve memory suggesting spindles as a promising physiological target for the development of cognitive enhancing therapies. This effort would benefit from more comprehensive and spatially precise methods to characterize spindles. Spindles, as detected with electroencephalography (EEG), are often widespread across electrodes. Available evidence, however, suggests that they act locally to enhance cortical plasticity in the service of memory consolidation. Here, we present a novel method to enhance the spatial specificity of cortical source estimates of spindles using combined EEG and magnetoencephalography (MEG) data constrained to the cortex based on structural MRI. To illustrate this method, we used simultaneous EEG and MEG recordings from 25 healthy adults during a daytime nap. We first validated source space spindle detection using only EEG data by demonstrating strong temporal correspondence with sensor space EEG spindle detection (gold standard). We then demonstrated that spindle source estimates using EEG alone, MEG alone and combined EEG/MEG are stable across nap sessions. EEG detected more source space spindles than MEG and each modality detected non-overlapping spindles that had distinct cortical source distributions. Source space EEG was more sensitive to spindles in medial frontal and lateral prefrontal cortex, while MEG was more sensitive to spindles in somatosensory and motor cortices. By combining EEG and MEG data this method leverages the differential spatial sensitivities of the two modalities to obtain a more comprehensive and spatially specific source estimation of spindles than possible with either modality alone.
Circuit Timing and Leakage Analysis in the Presence of Variability

Driven by the need for faster devices and higher transistor densities, technology trends have pushed transistor dimensions into the deep sub-micron regime. This continued scaling, however, has led to many challenges facing digital integrated circuits today. One important challenge is the increased variations in the underlying process and environmental parameters, and the significant impact of this variability on circuit timing and leakage power, making it increasingly difficult to design circuits that achieve a required specification. Given these challenges, there is a need for computer-aided design (CAD) techniques that can predict and analyze circuit performance (timing and leakage) accurately and efficiently in the presence of variability. This thesis presents new techniques for variation-aware timing and leakage analysis that address different aspects of the problem. First, on the timing front, a pre-placement statistical static timing analysis technique is presented. This technique can be applied at an early stage of design, when
Properties of DMF-fossil gasoline RON95 blends in the consideration as the alternative fuel

The use of endless biomass sources form agricultural by-products for the renewable fuel synthesis has been being considered as the extremely useful works meeting the strict strategies of environment protection. In this work, 2,5-dimethylfuran (DMF) synthesized from available rice straw in Vietnam was mixing with fossil gasoline RON95 to determine and measure the key properties of DMF-gasoline RON95 blends based on corresponding ASTM standards in the consideration as a new alternative fuel for modern gasoline engines. Each 5% volume fraction of DMF was used for mixing purposes to create 21 samples with the change of DMF volume fractions from 0% to 100%. As a result, the linearization of density, octane number, and laten heat of vaporization was conducted; meanwhile, the stoichiometric air/fuel ratio, heating value, and self-ignition temperature of DMF-gasoline RON95 blends were also reported. This work provided the full properties of blends of DMF-gasoline RON95 blends based on experimental results, and of course, achieved results could be used for the next steps to investigate the applicability of DMF-gasoline RON95 blends to practical experiments or simulation studies.
Polish Pharmacy Students’ Attitudes toward Undergraduate Teaching and Practical Implementation of Pharmaceutical Care—A Cross Sectional Study

It is necessary to monitor and adapt pharmacy curricula to make graduates ready to effectively meet the health needs of the society. Therefore, the aim of the study was to obtain Polish final year pharmacy students’ opinions on the activities related to pharmaceutical care (PC) andtheir perception of PC. Two questionnaires were used: one evaluating a PC regarding classes and in practice (n = 64), and the other on the assessment of existing educational solutions in the field of professional counseling (n = 118). Statistical analysis showed that the students agreed that there are not enough hours of a PC classes, since these are necessary to enable them to provide PC services in the future (R = 0.05, p = 0.0007). In previous classes, teachers’ knowledge was rated the highest on a five-point scale (4.74), and role play (3.92) and the duration of the classes (3.77) were rated the lowest. Although the students were aware of the role of a PC in the work of a pharmacist, they indicated that more extensive use of active learning methods would better prepare them for the profession. Therefore, pharmacy students’ self-efficacy survey and a curriculum renewal would be recommended in Poland.
SperoPredictor: An Integrated Machine Learning and Molecular Docking-Based Drug Repurposing Framework With Use Case of COVID-19

The global spread of the SARS coronavirus 2 (SARS-CoV-2), its manifestation in human hosts as a contagious disease, and its variants have induced a pandemic resulting in the deaths of over 6,000,000 people. Extensive efforts have been devoted to drug research to cure and refrain the spread of COVID-19, but only one drug has received FDA approval yet. Traditional drug discovery is inefficient, costly, and unable to react to pandemic threats. Drug repurposing represents an effective strategy for drug discovery and reduces the time and cost compared to de novo drug discovery. In this study, a generic drug repurposing framework (SperoPredictor) has been developed which systematically integrates the various types of drugs and disease data and takes the advantage of machine learning (Random Forest, Tree Ensemble, and Gradient Boosted Trees) to repurpose potential drug candidates against any disease of interest. Drug and disease data for FDA-approved drugs (n = 2,865), containing four drug features and three disease features, were collected from chemical and biological databases and integrated with the form of drug-disease association tables. The resulting dataset was split into 70% for training, 15% for testing, and the remaining 15% for validation. The testing and validation accuracies of the models were 99.3% for Random Forest and 99.03% for Tree Ensemble. In practice, SperoPredictor identified 25 potential drug candidates against 6 human host-target proteomes identified from a systematic review of journals. Literature-based validation indicated 12 of 25 predicted drugs (48%) have been already used for COVID-19 followed by molecular docking and re-docking which indicated 4 of 13 drugs (30%) as potential candidates against COVID-19 to be pre-clinically and clinically validated. Finally, SperoPredictor results illustrated the ability of the platform to be rapidly deployed to repurpose the drugs as a rapid response to emergent situations (like COVID-19 and other pandemics). Graphical Abstract Illustration of SperoPredictor repurposing framework. It starts with data collection followed by machine learning models training, model deployment, literature, and molecular docking-based validation.
Spotting the Critical Success Factors of Enterprise Resource Planning Implementation in the Context of Public Higher Education Sector

ABSTRACT The failure of Enterprise Resource Planning (ERP) implementation in higher education institutions (HEIs) worldwide is much higher than other sectors, such as banking or manufacturing, yet limited research has been conducted on this field. To date, previous literature has identified some critical success factors (CSFs) mostly either in the domain of information system (IS) or in the industrial context. Hence, this article identifies and categorises CSFs of ERP implementation in HEIs from multiple aspects. Semi-structured face-to-face interviews were conducted with technicians and managers from three Public Jordanian HEIs. The main finding of this study is the identification and characterization of three new sector- and context-specific CSFs. This research contributes to identifying new CSFs with evidence of successful implementation of ERP systems in the public higher education sector, which has not been fully investigated in any documented literature in the sector. The research also brings out some insights for the need for sustainable ERP in the sector during crisis time.
Live Load Distribution Factors for Skew Stringer Bridges with High-Performance-Steel Girders under Truck Loads

Because the methods used to compute the live load distribution for moment and shear force in modern highway bridges subjected to vehicle loading are generally constrained by their range of applicability, refined analysis methods are necessary when this range is exceeded or new materials are used. This study developed a simplified method to calculate the live load distribution factors for skewed composite slab-on-girder bridges with high-performance-steel (HPS) girders whose parameters exceed the range of applicability defined by the American Association of State Highway and Transportation Officials (AASHTO)’s Load and Resistance Factor Design (LRFD) specifications. Bridge databases containing information on actual bridges and prototype bridges constructed from three different types of steel and structural parameters that exceeded the range of applicability were developed and the bridge modeling verified using results reported for field tests of actual bridges. The resulting simplified equations for the live load distribution factors of shear force and bending moment were based on a rigorous statistical analysis of the data. The proposed equations provided comparable results to those obtained using finite element analysis, giving bridge engineers greater flexibility when designing bridges with structural parameters that are outside the range of applicability defined by AASHTO in terms of span length, skewness, and bridge width.
Mediterranean Dietary Pattern is Associated with Lower Odds of Gastric Cancer: A Case–Control Study

Background Diet pattern is an important modifiable lifestyle factor. However, epidemiological studies show that the association between dietary patterns and gastric cancer (GC) is conflicting. This study aims to assess the impact of several dietary choices on the risk of GC among newly diagnosed Jordanian patients. Methods A case–control study was conducted at major oncology centers and hospitals in Jordan. Study participants included 172 patients with incident gastric cancer and 314 controls. Data was collected using interview-based questionnaires. Dietary intake was estimated using a validated Arabic and reproducible food-frequency questionnaire (FFQ). Dietary patterns were derived using Principal Component Analysis (PCA). Multinomial logistic regression was used to estimate the association between dietary patterns and GC. Results Four dietary patterns were itemized; “Mediterranean”, “Prudent”, “Unhealthy” and “High-fruit” dietary patterns. The “Mediterranean” dietary pattern, which includes a diet rich in fresh fruits, vegetables, milk, yogurt, lentils, and olive oil was associated with a significant decrease in the odds ratio (OR) of GC for the third and fourth quartiles (OR, 0.394 (confidence interval (CI): 0.211–0.736); 0.212 (CI: 0.107–0.419), respectively) after adjusting for age, gender, body mass index, smoking, marital status, total energy intake, education level, and physical activity. While the “Unhealthy” and “Prudent” dietary patterns enhance the risk of developing GC, this risk was insignificant at any quartile. Additionally, the “High-Fruit” dietary pattern shows an insignificant protective effect against the risk of GC. Conclusion The “Mediterranean” dietary pattern was associated with a reduced risk of GC among Jordanians. However, the other three identified dietary patterns were not significantly associated with the risk of GC.
Metabolic Profiling of CHO Cells during the Production of Biotherapeutics

As indicated by an ever-increasing number of FDA approvals, biotherapeutics constitute powerful tools for the treatment of various diseases, with monoclonal antibodies (mAbs) accounting for more than 50% of newly approved drugs between 2014 and 2018 (Walsh, 2018). The pharmaceutical industry has made great progress in developing reliable and efficient bioproduction processes to meet the demand for recombinant mAbs. Mammalian cell lines are preferred for the production of functional, complex recombinant proteins including mAbs, with Chinese hamster ovary (CHO) cells being used in most instances. Despite significant advances in cell growth control for biologics manufacturing, cellular responses to environmental changes need to be understood in order to further improve productivity. Metabolomics offers a promising approach for developing suitable strategies to unlock the full potential of cellular production. This review summarizes key findings on catabolism and anabolism for each phase of cell growth (exponential growth, the stationary phase and decline) with a focus on the principal metabolic pathways (glycolysis, the pentose phosphate pathway and the tricarboxylic acid cycle) and the families of biomolecules that impact these circuities (nucleotides, amino acids, lipids and energy-rich metabolites).
STATIC YIELD STRESS MEASUREMENTS OF FINE AGGREGATES

Fine grained concrete with a maximum grain size of D = 2 mm can be designed as high-performance concrete with outstanding properties. Typical applications are 3Dprinting, grouts, textile-reinforced concrete and thin high-performance structures. Studies reported in the literature that with decreasing grain size the impact of the granulometric properties of the aggregates is increasing. These properties are not only influencing the water demand but also the rheological behavior, such as the static yield stress. In order to investigate and quantify the effects of granulometry on static yield stress measurements six different sands of threedeposits within the range of d/D = 0/2 mm and industrial made glass spheres were tested. The granulometric properties of the materials have been investigated using digital image analyzing. The measurement device was a rotational viscosimeter (Viskomat NT) equipped with a Vane-paddle. Factors as the sample preparation (compaction) and applied shear rateunder a constant shear rate protocol (CSR) were analyzed. An optimum measurement procedure for the grain mixtures was found in using 0.2 rpm and a layerwise static compaction. The analysis showed the importance of the grain size distribution of comparable grain mixtures regarding the static yield torque.
The Effect of Non-Invasive Brain Stimulation on the Downregulation of Negative Emotions: A Meta-Analysis

(1) Background: Emotion regulation (ER) is regarded as a core treatment target for depression and other mental illnesses. In recent years, non-invasive brain stimulation (NIBS) has been extensively used as an intervention for mental illnesses, but there has been no systematic review conducted regarding its effect on emotion regulation. Therefore, we conducted a meta-analysis of the effectiveness of NIBS for emotion regulation; (2) Methods: Systematic searches were conducted in Embase, Web of Science, PubMed, and Cochrane Library. We analyzed the effects of NIBS on tasks assessing emotion regulation using a random-effects model, and further explored the moderating role of the following factors on transcranial direct current stimulation (tDCS) studies by conducting subgroup analyses and meta-regression: target electrode placement, return electrode placement, current intensity, target electrode size, and duration of intervention; (3) Results: A total of 17 studies were included. Our meta-analysis indicated a small but significant effect of NIBS on the downregulation of negative emotions. Separate analyses indicated that repetitive transcranial magnetic stimulation (rTMS) had a medium and significant effect on the downregulation of negative emotions, whereas tDCS had no significant effect. Subgroup analyses showed that the effect of tDCS was moderated by target and return electrode placemen; (4) Conclusions: These results indicate that NIBS had a positive effect on the downregulation of negative emotions. The stimulation protocols should be carefully considered and the underlying mechanisms should be further explored.
Redox Regulation of Soluble Epoxide Hydrolase—Implications for Cardiovascular Health and Disease

Cell responses to changes in their redox state are significantly mediated by reversible oxido-reductive post-translational modifications of proteins, potentially altering their activities or interactions. These modifications are important for the homeostatic responses of cells to environmental changes that alter their redox state. Such redox regulatory mechanisms not only operate to maintain health, but can become dysregulated and contribute to pathophysiology. In this review, we focus on the redox control of soluble epoxide hydrolase (sEH), which is widely expressed, including in blood vessels and cardiomyocytes. We review the different types of oxidative modifications that regulate sEH and how they may alter cardiovascular physiology and affect disease progression during stress.
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Engineered nanomaterials (ENMs) raise questions among the scientific community and public health authorities about their risks to human health. Studying a prospective cohort of workers exposed to ENMs would be considered the gold standard for identifying potential health effects of nanotechnology and confirming the “no effect” levels derived from cellular and animal models. However, because only small, cross-sectional studies have been conducted in the past 5 years, questions remain about the health risks of ENMs. This essay addresses the scientific, methodological, political, and regulatory issues that make epidemiologic research in nanotechnology-exposed communities particularly complex. Scientific challenges include the array of physicochemical parameters and ENM production conditions, the lack of universally accepted definitions of ENMs and nanotechnology workers, and the lack of information about modes of action, target organs, and likely dose-response functions of ENMs. Standardization of data collection and harmonization of research protocols are needed to eliminate misclassification of exposures and health effects. Forming ENM worker cohorts from a combination of smaller cohorts and overcoming selection bias are also challenges. National or international registries for monitoring the exposures and health of ENM workers would be helpful for epidemiological studies, but the creation of such a registry and ENM worker cohorts will require political support and dedicated funding at the national and international levels. Public authorities and health agencies should consider carrying out an ENM awareness campaign to educate and engage all stakeholders and concerned communities to engage in discussion of such a project.