Miracle-dz/UniFAR-FTUs huggingface dataset:
An Introduction to near Infrared Spectroscopy

When you hold your hand out to a burning fire you “feel” the heat being emitted by the fire but what is happening? The fire gives out light and infrared (IR) radiation; from a fire most of this is near infrared (NIR) radiation. Some of the NIR radiation is absorbed by water molecules in your skin. This raises the temperature of the water and results in an increase in temperature in the surrounding tissue which is detected by nerves in your skin. This radiation was discovered in 1800 by William Herschel, a musician and very successful amateur astronomer (he discovered the planet Uranus) because he wanted to know if any particular colour was associated with heat from sunlight. He found that the heat maximum was beyond the red end of the spectrum. Herschel could not believe that light and his “radiant heat” were related but he was wrong. By 18 5 Ampere had demonstrated that the only difference between light and what he named “infrared radiation” was their wavelength. Then in 1864 James Maxwell wrote “This velocity [of electromagnetic force] is so nearly that of light that it seems we have strong reason to conclude that light itself (including radiant heat and other radiations) is an electromagnetic disturbance in the form of waves propagated through the electromagnetic field according to electromagnetic laws”. What we now call the electromagnetic spectrum is shown in Figure 1.
Recent Advances in the High‐Temperature Chemical Synthesis of Magnetic Nanoparticles

One of the most active research areas in functional materials is the chemical synthesis of magnetic nanoparticles. Their potential in biomedical and technological applications has motivated the search for new forms of magnetic nanoparticles with additional chemical and physical functionalities. This review highlights recent advances in the high temperature solution‐phase synthesis of monodisperse, multicomponent magnetic nanoparticles. Particular emphasis is put on iron‐based metal, oxide, alloy and composite nanoparticles and their biomedical applications.
The effects of clinical decision support system for prescribing on patient outcomes and physician practice performance: A systematic review

Background The clinical decision support systems(CDSSs) for prescription medications is one of the technologies aimed at improving physician practice behavior and patient outcomes by reducing drug prescription errors. This study was conducted to investigate the effect of various CDSSs on physician practice behavior and patient outcomes.Methods This systematic review was conducted by searching in PubMed, EMBASE, Web of Science, Scopus and Cochrane Library from January 2005 to November 2019. Two researchers independently evaluated the studies. Any discrepancies over the eligibility of the studies between the two researchers were then resolved by consulting a third researcher. Finally, data were extracted from the articles; however, we could not able to conduct meta-analysis due to the heterogeneity of the studies and the narrative form of the findings.Results Based on the inclusion criteria, 46 studies were considered eligible for the analysis in this review. The CDSS for prescription medications had been used for various diseases, namely cardiovascular diseases, hypertension, diabetes, gastrointestinal and respiratory diseases, AIDS, appendicitis, kidney disease, malaria, high blood potassium, mental disease. Meanwhile, other cases such as the concurrent prescription of multiple drugs for the patient and its effects on the above-mentioned outcomes were evaluated. The analysis shows that in some cases the application of CDSS provides positive effects on patient outcomes and physician practice behaviors. No significant difference was observed in comparison between some other cases and conventional methods. We think that this could be due to the disease type, the quantity and type of CDSS requirements that influence the comparison.Conclusions Our findings suggest that the positive effects of the CDSS are due to factors such as user-friendliness, compliance with clinical guidelines, patient and doctor cooperation, integration of electronic health records, CDSS and pharmaceutical systems, consideration of the views of physicians in assessing the importance of CDSS alerts and their real-time alerts in the prescription.Registration number on PROSPERO CRD42018079936.
English as a lingua franca: Attitudes of Polish interpreting students

Recent decades have witnessed the growing presence of English as a lingua franca (ELF) in international communication, which has emerged as one of the major factors influencing the interpreting profession. What follows is the debate concerning presence of ELF in interpreter training. However, before any curricula modifications are introduced, what needs to be taken into consideration is the perspective of interpreting students – their expectations and preferences concerning the variety of English they want to work with during their studies. The present study is an attempt to investigate attitudes displayed by English philology students enrolled in translation and interpreting programmes towards native and non-native English. The research tool was a questionnaire. The results suggest that the students might not necessarily welcome frequent exposure to ELF at the cost of Standard British or Standard American English during practical classes, including interpreting. However, it is hypothesized that the respondents’ conservative attitude is not the result of a thorough understanding of ELF, but rather the reflection of insufficient knowledge and uncritical embrace of the stereotypical mass-culture narration that tends to romanticize certain varieties of English while dismissing others
Theoretical exploration of seleno and tellurophenols as promising alternatives to sulfur ligands for anchoring to gold (111) materials

It is widely known that sulfur ligands, such as alkanethiols or phenothiols and their derivatives, are useful anchor systems for gold materials due to the high affinity of sulfur to gold surfaces. In this study we use DFT calculations and a 42-atom gold cluster model to study the interaction between selenophenol and tellurophenol-derivatives with the Au(111) surface to gain information towards potential new gold-based materials. We modulated the interaction strength by controlling the charge transfer process of a particular interaction by chemically modifying the ligands. To obtain a complete analysis, we studied the ligands in their protonated, anionic and radical states aiming to cover the three possibilities in which these may interact with the gold cluster. In order to get a deeper insight into the nature of the interaction we used several analysis techniques such as energy decomposition analysis (EDA), non-covalent interactions (NCI) and natural population analysis (NPA). Our results reveal that tellurium in the anionic state provides complexes of better thermodynamic stability by ∼12.0 kcal mol, when compared with the strongest sulfur–gold complex, also in the anionic state. Furthermore, this indicates that the anionic ligand is probably the dominant state for both selenium and tellurium as observed previously for sulfur. The extent to which the interaction strength could be controlled directly depends on the state of the anchor atom. In our case the anionic state is the most suitable for tuning the interaction. Finally, our main findings suggest that exchanging sulfur with selenium or tellurium involves an important increase of the interaction strength, thus, making these selenophenol and tellurophenol derivatives attractive for the development of new functional materials.
The Activities of Streptomyces W-5A as Antibacterial and Antibiofilm towards Methicillin-resistant Staphylococcus aureus 2983

: Methicillin-resistant Staphylococcus aureus (MRSA) causes nosocomial infection worldwide. MRSA can defend itself by forming a biofilm layer, thereby increasing the virulence factor. WHO categorizes MRSA as high risk on the Priority Pathogen List for searching for new antibiotics. Recently, we have reported the potency of Streptomyces W-5A as anti-MRSA based on qualitative screening. Thus, this research aimed to analyze the potency of Streptomyces W-5A as antibacterial and antibiofilm towards MRSA 2983. Cultivation of Streptomyces W-5A used Starch Casein Nitrate (SCN) agar, and anti-MRSA extract production used SCN broth. Samples were taken at incubation times of 0, 3, 6, 9, 12, and 15 days. Each sample was tested for antibacterial activity with the Kirby-Bauer method, whereas inhibition of biofilm formation and biofilm degradation with microtiter method. The results showed that the optimum antibacterial activity was achieved after nine days of incubation with an inhibition zone of 9.589 ± 0.521. The optimum % inhibition of biofilm formation was 77.806 ± 13.595% after 12 days of incubation. The optimum % degradation of biofilm was 80.465 ± 7.586% after nine days of incubation. These findings suggest that Streptomyces W-5A has the potency to produce antibacterial and antibiofilm compounds against MRSA 2983.
Las noticias de portada en la prensa escrita ecuatoriana: espacios de poder y entretenimiento

¿Qué y quién es noticia de portada en los principales medios escritos de Ecuador? Este artículo estudia la agenda mediática del primer año de mandato del presidente Lenín Moreno. Se ha utilizado una metodología cuantitativa, basada en el análisis de contenido de más de 3.500 informaciones de portada publicadas en los periódicos ecuatorianos de tirada nacional durante el período comprendido entre agosto de 2017 y agosto de 2018. Un año que ha estado marcado por el elevado peso en portada de la información política, sustentada en la visión negativa al mandato del expresidente, Rafael Correa. Esta parte de los contenidos se dulcifica con informaciones de entretenimiento, deportes, farándula y espectáculo. Se analizan, además, desde una mirada crítica, los actores y escenarios, mostrando la invisibilización de sectores tan relevantes para el país como los agricultores y mineros. Las mujeres siguen sin apenas representación ni espacio.
Phytochemical properties of Ceiba petandra (Kapok tree), Moringa oleifera (Moringa) and Cymbopogon citratus (Lemon grass) collected from a home garden in Igbor, Gwer East, Benue State, Nigeria

The need for integration of modern science in the study of medicinal plants is very crucial. Without the application of science, herbal medicine would just remain traditional. The broad objective of the study was to identify the phytochemical properties of these three medicinal plants in order to encourage utilization, conservation and management of these plant species. This research sought to contribute to existing knowledge about the phytochemical constituents and medicinal uses of these plants. The highest concentrations of tannin (11.6%) and flavonoid (10.1%) were found in the leaves of Ceiba petandra . Anthraquinone was not found in any of the plant species investigated. Alkaloid was found only in the leaves of Moringa oleifera with a concentration of 5.4%. Terpenoids were found only in the leaves of Ceiba petandra (4.2%) and in the leaves of Moringa oleifera (3.5%). The least concentration of cyanoglycosides (0.1%) was found in the leaves of Ceiba petandra . It was concluded that leaves of Ceiba petandra , Moringa oleifera and Cymbopogon citratus were the major sources of phytochemicals. The study also revealed that higher quantities of phytochemicals were found in Ceiba petandra leaves when compared with other plant species. This showed that the leaves of Ceiba petandra are highly medicinal. It is recommended that Clinical trials should be conducted on these medicinal plant species to determine their efficacy in the treatment of diseases.
Pulsed nanosecond discharge in air at high specific deposited energy: fast gas heating and active particle production

The results of a numerical study on kinetic processes initiated by a pulsed nanosecond discharge in air at high specific deposited energy, when the dissociation degree of oxygen molecules is high, are presented. The calculations of the temporal dynamics of the electron concentration, density of atomic oxygen, vibrational distribution function of nitrogen molecules, and gas temperature agree with the experimental data. It is shown that quenching of electronically excited states of nitrogen N2(B3Πg), N2(С3Πu), N2(a′1Σu−) by oxygen molecules leads to the dissociation of O2. This conclusion is based on the comparison of calculated dynamics of atomic oxygen in air, excited by a pulsed nanosecond discharge, with experimental data. In air plasma at a high dissociation degree of oxygen molecules ([O]/[O2] > 10%), relaxation of the electronic energy of atoms and molecules in reactions with O atoms becomes extremely important. Active production of NO molecules and fast gas heating in the discharge plasma due to the quenching of electronically excited N2(B3Πg, C3Πu, a′1Σu−) molecules by oxygen atoms is notable. Owing to the high O atom density, electrons are effectively detached from negative ions in the discharge afterglow. As a result, the decay of plasma in the afterglow is determined by electron–ion recombination, and the electron density remains relatively high between the pulses. An increase in the vibrational temperature of nitrogen molecules at the periphery of the plasma channel at time delay t = 1–30 μs after the discharge is obtained. This is due to intense gas heating and, as a result, gas-dynamic expansion of a hot gas channel. Vibrationally excited N2(v) molecules produced near the discharge axis move from the axial region to the periphery. Consequently, at the periphery the vibrational temperature of nitrogen molecules is increased.
Selection of an Acceptable Method of Evaluating Nutritional Status in Hemodialysis Patients Compared to Subjective Global Assessment: A Cross-Sectional Study

Background: Protein-energy wasting (PEW) is prevalent among hemodialysis (HD) patients and is associated with poor outcomes. There are various methods for evaluating nutritional status in HD patients that each has its own advantages and disadvantages. We aimed at comparing the methods of normalized protein catabolic ratio (nPCR) and malnutrition universal screening tool (MUST) with subjective global assessment (SGA) in HD patients. Method: We examined 88 HD patients using SGA and MUST questionnaires, and also nPCR were calculated using predialysis and post-dialysis BUN, and Kt/v. Also, patients were assessed for PEW based on the Criteria of the International Society of Renal Nutrition and Metabolism. Methods’ specificity, sensitivity, and precision rates were assessed. Correlations between methods were analyzed using Pearson-correlation. Results: Based on the SGA, MUST, and nPCR methods, almost 41, 30, and 60 percent of patients had malnutrition, respectively. According to the criteria by International Society of Renal Nutrition and Metabolism, more than 90 percent of patients had PEW. SGA was positively and significantly associated with MUST (P≤0.001). Sensitivity for SGA, MUST, and nPCR methods were 100,100, 1.8 %, and their specificity were 98, 98, and 4 %, respectively and their precision rates were 99.7, 98.7, and 3%, respectively. Conclusion: From various methods of nutritional assessment (SGA, MUST, and nPCR), compared to SGA as the common method of nutrition assessment in hemodialysis patients, MUST had the nearest specificity, sensitivity, and precision rate compared to SGA and nPCR method had the lowest ones. nPCR seems to be a flawed marker of malnutrition and it should be more investigated whether MUST can be used instead of SGA or not.
H2O2-Scavenging Activity and Hyaluronidase Inhibition Scutellarin and Apigenin in Basil Leaf Extract

The potential utilization of flavonoid compounds, especially scutellarin, and apigenin, contained in basil (Ocimum basilicum L.) leaf extract to manage the aging effects on the skin, that occurs because of over-activated hyaluronidase enzyme and oxidative stress due to hydrogen peroxide (H2O2) radicals, is not well known. This study was conducted to assess the H2O2 scavenging activity and the inhibition of hyaluronidase from scutellarin and apigenin at various concentrations. The study was conducted by measuring H2O2 scavenging inhibition and hyaluronidase inhibition of scutellarin and apigenin in various concentrations using the spectrophotometry method. The various activity was tested using the One-Way ANOVA test followed by Tukey post hoc test. IC50 values were calculated based on linear regression equations of H2O2 scavenging inhibition and hyaluronidase inhibition. The analysis showed the highest H2O2 scavenging activity was found in scutellarin with IC50 158.76 μg/mL. Scutellarin has greater scavenging activity than apigenin. Hyaluronidase inhibition of scutellarin with IC50 35.25 µg/mL, while apigenin was 162.86 µg/mL. Scutellarin has higher hyaluronidase inhibition activity than apigenin. Antioxidant and antiaging effects of basil leaf extract caused by phytochemical compounds contained, especially scutellarin.
Seven-day Fasting as a multimodal complex interventionfor Adults with Type 1 Diabetes – Feasibility, Bene�t and Safety in a Controlled Pilot StudyFeasibility of Fasting for Adults with Type 1 Diabetes

Aims/Hypothesis: Intermittent as well as prolonged fasting are receiving considerable attention and appear favorable in conditions like the metabolic syndrome, type 2 diabetes, rheumatic diseases and others. Fasting for people with type 1 diabetes is generally considered too risky. However, the ability and possibility to change from carbohydrate to ketone-based fuel supply might also be relevant for people with type 1 diabetes. The aim of this patient-led research was to investigate the feasibility, bene�t and safety of a seven-day multimodal fasting intervention in people with type 1 diabetes. Methods: A non-randomized controlled pilot study, with 20 participants with and 10 without type 1 diabetes. Data acquisition took place prior, post and four months after the intervention and daily during intervention. Results: 29 of 30 participants �nished the intervention. Mean ß-hydroxybutyrate as representative ketone body increased to 2.8 ± 1.9 mmol/L on day 7 while average glucose remained between 4.9 ± 1.5 to 7.5 ± 2.3 mmol/L [89 ± 27 and 136 ± 40 mg/dL]. Fasting-related side effects were all temporary, and slightly more prevalent in those with type 1 diabetes. Mean daily insulin dose was adjusted from 24.4 (3-50) IU on the day before fasting to 7.6 (0-26.7) IU on day 7. Quality of life (WHO-5) normalized from 54.0 ± 4.4 to 68.8 ± 15.0 (p = 0.01) after fasting. There was a decrease from before until the follow-up four month later of weight from 77.6 ± 20.4 kg to 76.6 ± 20.9 kg (p = 0.023) and for the BMI from (27.68 ± 7.04) to (26.74 ± 7.15) kg/m 2 (p = 0.008). Diastolic blood pressure increased from 69.75 ± 11.41 mmHg to 75.74 ± 8.42 mmHg (p = 0.028) and stayed in a healthy range on average. Conclusions/Interpretation: This study demonstrates the feasibility, bene�ts and safety aspects of a 7-day fast in adults with type 1 diabetes.
Student Testing Activity Dataset from Data Structures Course

E-learning platforms became more and more popular not only for distance learning but also for learning in full-time education. As this popularity grows, we can use the data extracted from them to complement the professor's work and make predictions regarding students’ performance. In this paper, we present a dataset extracted from our e-Learning platform, which is based on the logs collected from testing activity. The focus of this paper is to present the dataset; the experiments presented in the paper are meant to explore the dataset along with its capabilities. The dataset consists of attributes relevant to the testing activity and provides labels which consist of average test grade and final exam grade. Our focus when building the dataset was to keep only the attributes relevant for the learning activity and to provide means to analyse and predict the student's final grade or failure. The paper presents the structure of the dataset, the methodology of collecting the data and experiments using several popular algorithms. The experimental results reveal that the actions performed by the users correlate with the results of the tests and the exam failure can be predicted with a pretty good accuracy using the default set of tuning parameters for our algorithms. As feature work, we can extend the set of experiments with other algorithms, and we can also use parameter tuning for each algorithm for a slight increase in performance.
Analysis and Prognosis of COVID-19 Pandemic in India - A Machine Learning Approach

Machine Learning techniques have been used for decades to analyze and predict outcomes in various domains of study as well as in industries. It employs various algorithms to perform different tasks. One of the practical and topical applications in the current scenario is to use the power of Machine Learning to study various aspects of the ongoing pandemic (COVID-19), since the entire world is in its grip. COVID-19 was declared a global pandemic on 11th March 2020 by WHO. Worldwide more than 43 Million people have contracted this viral disease and more than 1.1 million people have succumbed to it (as on 27th October 2020). The number of people affected by COVID-19 in India is increasing at a fast pace and currently India has the second highest number of cases and third highest casualties in the world. In this study, a model is developed to examine and analyze the spread of this disease. Four different Machine Learning algorithms namely Random Forest Regression, Multiple Linear Regression, Support Vector Regression and Lasso Regression have been considered. A Kaggle dataset consisting of figures of confirmed cases, patients recovered, and people that have died due to COVID-19 across India over a particular period of time has been used. The results of this study indicate that Random Forest Regression provides the most accurate results whereas Support Vector Regression is least accurate.