Miracle-dz/UniFAR-FTUs huggingface dataset:
Antioxidant and Cytotoxic Activity Studies in Series of Higher Amino Acid Schiff Bases

In this work, the antioxidant activity of the higher amino acid Schiff bases, which were prepared as the monosodium salts (1a–3a) and the neutral forms (1b–3b) was determined by DPPH scavenging assay. In pure MeOH solution, the scavenging ability of Schiff bases 1a-3a were higher than 1b-3b, but lower than ascorbic acid. The activity followed the order 3 (a,b) > 2 (a,b) > 1 (a,b). On the other hand, Schiff bases 2a and 3a behaved as the most effective scavengers of the DPPH radical in methanol-water mixture (v:v, 1:3). And, they were found to be have lower SC50 values in this mixture compared to pure methanol. In vitro cytotoxicity of these Schiff bases was studied against human cervical cancer cells (HeLa), human breast adenocarcinoma cells (MCF-7), and human normal embryonic kidney cells (HEK293). For HeLa cell line, Schiff bases 1a-3a exhibited a litttle high activity than 1b, but very low activity than doxorubicin. Schiff bases 2b and 3b had no cytotoxicity against HeLa cell. For MCF-7 cell line, Schiff bases 1a, 3a, 1b and 3b nearly were inactive at 100 µM, whereas 2a increased cell proliferation in the all tested concentration range. Differently, Schiff base 2b showed the highest cytotoxicity and killed 90 percent of MCF-7 cells at concentration of 100 µM. For HEK-293, doxorubicin was strongly cytotoxic. Despite this, Schiff bases 1a, 3a and 3b were inactive, whereas the others showed little weak toxicity.
Long-term life cycle and massive blooms of the intertidal hydroid Paracoryne huvei in the North-western Mediterranean Sea

ABSTRACT Paracoryne huvei is a rare encrusting hydrozoan living in the intertidal zone of the North-western Mediterranean Sea, from the Catalan coast to the Ligurian Sea. In 2014, a large bloom of P. huvei was recorded along the cliffs of the Marine Protected Area ‘Isola di Bergeggi’ (Ligurian Sea). The species has shown densities related to important biomass values never previously recorded (wet weight as high as 1600 g m−2), creating a continuous belt up to 1 m wide from February to April. At an increasing distance from the promontory, the species decreased in abundance, assuming a spotted aspect comparable to the colonies recorded by earlier researchers. In the Bergeggi area, the species has exhibited an almost complete cover of the lower intertidal zone, and for the first time it was recorded in the infralittoral and upper intertidal zone and in tide pools, demonstrating a wider range of habitat than had previously been observed. The life cycle appeared significantly shorter than cycles reported in earlier literature, and this phenomenon has been compared with similar observations from other shallow water hydrozoans in the same area. The abundance of the species was continually monitored in 2015–2016 to help assess the inter-annual variations in relation to temperature and rainfall trends and, indirectly, to competition with other species. Finally, a comparison of the 59 years of scattered data of occurrence in the literature has shown P. huvei to be a strict stenothermal species, reported only in winters characterized by average temperatures.
A Hybrid Downscaling Approach for Future Temperature and Precipitation Change

We used empirical–statistical downscaling in a pseudoreality context, in which both large-scale predictors and small-scale predictands were based on climate model results. The large-scale conditions were taken from a global climate model, and the small-scale conditions were taken from dynamical downscaling of the same global model with a convection-permitting regional climate model covering southern Norway. This hybrid downscaling approach, a “perfect model”–type experiment, provided 120 years of data under the CMIP5 high-emission scenario. Ample calibration samples made rigorous testing possible, enabling us to evaluate the effect of empirical–statistical model configurations and predictor choices and to assess the stationarity of the statistical models by investigating their sensitivity to different calibration intervals. The skill of the statistical models was evaluated in terms of their ability to reproduce the interannual correlation and long-term trends in seasonal 2-m temperature T2m, wet-day frequency fw, and wet-day mean precipitation μ. We found that different 30-yr calibration intervals often resulted in differing statistical models, depending on the specific choice of years. The hybrid downscaling approach allowed us to emulate seasonal mean regional climate model output with a high spatial resolution (0.05° latitude and 0.1° longitude grid) for up to 100 GCM runs while circumventing the issue of short calibration time, and it provides a robust set of empirically downscaled GCM runs.
Optimization of Various Process Parameters Using Response Surface Methodology for Exopolysaccharide Production from a Novel Strain Pediococcus acidilactici KM0 (Accession Number KX671557) Isolated from Milk Cream

Optimization of Various Process Parameters Using Response Surface Methodology for Exopolysaccharide Production from a Novel Strain Pediococcus acidilactici KM0 (Accession Number KX671557) Isolated from Milk Cream Kanika Sharma * , Nivedita Sharma, Jasveen Bajwa, Sunita Devi Microbiology Research Laboratory, Department of Basic Sciences, Dr Y S Parmar University of Horticulture and Forestry, Nauni, Solan, HP, India DOI: 10.23956/ijermt/V6N1/117 Abstract—
Students’ Self-Efficacy, Causal Attribution Habits and Test Grades

Why do students vary in their performance on exams? It may be that their test preparation is insufficient because they overestimate their anticipated grade. Our study investigates four issues related to performance on a final examination. First, we analyze whether students’ ability to accurately predict their grade and their subjective confidence in this prediction may account for their grade. Second, we ask whether students at different levels of performance vary in their ability to accurately predict their grade, and if so, whether subjective confidence also differs. Third, we ask whether the accuracy and confidence of learners’ predictions are conditioned by self-efficacy beliefs and causal attribution habits, which serve as indices of motivation for test preparation. Fourth, we ask whether different causal attribution preferences contribute to self-efficacy. We use statistical analysis of data from a general education course at a large public university in the United States. Our results indicate that poor performers’ overestimates are likely to be wishful thinking as they are expressed with low subjective confidence. Self-efficacy is a significant contributor to the inaccuracy of students’ predicted grades and subjective confidence in such predictions. Professors’ understanding of learners’ forecasting mechanisms informs strategies devoted to academic success.
Prevalence and Risk Factors for Nonsuicidal Self-Injury in Transgender and Gender-Expansive Youth at a Rural Gender Wellness Clinic.

Purpose: Transgender and gender-expansive (TGE) populations are at increased risk for nonsuicidal self-injury (NSSI). Rural TGE populations are understudied and underserved in terms of mental health services. The purpose of this study was to determine lifetime prevalence of NSSI among TGE youth at a rural gender wellness clinic and identify demographic and clinical characteristics associated with NSSI. Methods: The Gender Wellness Center Pediatric Patient Registry, a comprehensive database of 185 TGE youth ≤25 years of age, provided an estimate of the lifetime prevalence of NSSI. Univariate logistic regression models were utilized to test associations between patient demographic and clinical characteristics and NSSI. Variables that met the threshold for significance in the univariate analyses (p<0.05) were entered into a multivariate logistic regression model. All statistical analyses were conducted in SAS v.9. 4. Results: Prevalence of NSSI in the sample was 36.8% (n=68). In unadjusted logistic regression models, risk factors for NSSI included female assigned sex at birth, transmasculine spectrum gender identity, history of mood disorder, history of suicidal ideation (SI) or attempt, and history of abuse (p<0.05). In the adjusted model, variables significantly associated with NSSI included female assigned sex at birth, history of mood disorder, and history of SI or attempt. Conclusion: NSSI was highly prevalent in this sample of rural TGE youth, confirming the need for screening and early interventions that target the unique vulnerabilities of TGE youth. The complex interplay of sex assigned at birth, mood disorders, and NSSI requires further research.
Globally Optimal Symbolic Hand-Eye Calibration

Hand-eye calibration (HEC) is a kernel technique guaranteeing precision industrial visual servoing and robotic grasping. Extensive studies have been conducted to various closed-form and iterative solutions to HEC problems using different pose parameterizations. However, these approaches are either sensitive to input noise or time-consuming for implementation. This article provides a new perspective on a deterministic solution to two major branches of HEC problems of forms <inline-formula><tex-math notation="LaTeX">$\boldsymbol {AX} = \boldsymbol {XB}$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">$\boldsymbol {AX} = \boldsymbol {YB}$</tex-math></inline-formula>. We use symbolic methods to derive a globally optimal solution. Different from representatives based on optimization, this method is not only the most accurate against others but also with repeatability of 100%. Experiments via industrial robotic manipulator verify the superiority of the proposed algorithm.
Long-term dynamics in nutrients, chlorophyll a and water quality parameters in the Lagoon of Venice

Since 1997, CNR-ISMAR has been collecting monthly hydrochemical and phytoplankton data in the northern and central basins of the Lagoon of Venice. The data have been part of the International Long-Term Ecosystem Research (LTER) database since 2007, helping to fill a gap in lagoon environmental studies. Analysing our time series (1998-2017), we were able to observe a rise in water temperature due to climate trends, a reduction in trophic status mainly due to the lower input of inorganic dissolved nitrogen nutrients and an increase in transparency and dissolved oxygen related to the increased biomass of macrophytes (macroalgae and seagrasses). Finally, a reduction in phytoplankton biomass and an accompanying increase in seagrass and macroalgal cover were observed. Present and future studies will help to evaluate the ways in which the Lagoon of Venice ecosystem responds to anthropogenic pressures and global climate change.
Topsoil characteristics of forests and lawns along an urban–rural gradient in the Paris region (France)

Urban soils are a crucial component of urban ecosystems, especially in public green spaces, because of the ecosystem services they provide (e.g. public recreation, urban cooling or water infiltration). In this study, we describe the chemical, physical and hydrostructural characteristics of 180 forest and lawn surface soil samples, taken along an urban–rural gradient in the Paris region. This was done in order to identify how these soils have been affected by urbanization. Forests and lawns are the main vegetation types found in this region and represent 21% and 22.2% of the territory's surface area, respectively. Many of the properties of urban forest soils differed from those of other sites (e.g. texture, organic carbon content, total nitrogen and carbonate contents), possibly because the urban forests are much older than the lawns and because of the legacy of the historical management of soils in this region (Haussmann period). Urban lawn soils were more compacted than urban forests, probably due to higher foot traffic. The effects of urbanization were, at times, confounded with other factors (e.g. sandier texture of urban forests), which suggests that surface soil characteristics were influenced by past urban planning. Finally, this study constitutes a baseline analysis for the monitoring of soil quality in the region.
Speech Enhancement for Hearing Aids with Deep Learning on Environmental Noises

Hearing aids are small electronic devices designed to improve hearing for persons with impaired hearing, using sophisticated audio signal processing algorithms and technologies. In general, the speech enhancement algorithms in hearing aids remove the environmental noise and enhance speech while still giving consideration to hearing characteristics and the environmental surroundings. In this study, a speech enhancement algorithm was proposed to improve speech quality in a hearing aid environment by applying noise reduction algorithms with deep neural network learning based on noise classification. In order to evaluate the speech enhancement in an actual hearing aid environment, ten types of noise were self-recorded and classified using convolutional neural networks. In addition, noise reduction for speech enhancement in the hearing aid were applied by deep neural networks based on the noise classification. As a result, the speech quality based on the speech enhancements removed using the deep neural networks—and associated environmental noise classification—exhibited a significant improvement over that of the conventional hearing aid algorithm. The improved speech quality was also evaluated by objective measure through the perceptual evaluation of speech quality score, the short-time objective intelligibility score, the overall quality composite measure, and the log likelihood ratio score.
Searching optimum equations of state of neutron star matter in strong magnetic fields with rotation

Masses and radii of neutron stars are obtained in the presence of strong magnetic fields together with rotation. Mass-radius relations are calculated using 11 equations of state (EoSs: GM1, TM1-a, TM1-b, TM2$\omega\rho$-a, TM2$\omega\rho$-b, NL3-a, NL3-b, NL3$\omega\rho$-a, NL3$\omega\rho$-b, DDME2-a and DDME2-b) in relativistic mean field (RMF) theory. Obtained masses are over and around twice the solar mass ($M_\odot$) for all EoSs in the presence of strong magnetic fields of $3 \times 10^{18}$ G at the center. For NL3$\omega\rho$-a and NL3$\omega\rho$-b EoSs, masses are more than $M=2.17\,M_\odot$(observed maximum mass: $2.14\,M_\odot$) even without magnetic fields. Rotational effects are found to be insignificant in any case, at least up to the Kepler frequency. Suitable EoSs are also selected concerning the constraint on the radius of a neutron star.
Thermal comfort: standard compliant modelling of natural ventilation in adaptive time step solvers

Natural ventilation can help maintain thermal comfort during summer periods. In simulation models for thermal comfort analysis, occupant behaviour related to natural ventilation is often included through definition of ventilation rule sets. For example, windows are opened when room temperature exceeds a given limit while outside temperatures remain below a threshold. Such rules are included in building codes, such as DIN 4108-2 [1]. However, these rules are defined with respect to fixed step time integration methods, often using hourly step sizes. Straight-forward implementation of such rules in error controlled adaptive time step integration solvers (including drivers for Modelica models) fails. The article discusses strategies and model variants that work with such modern solvers and discusses new model parameters such as the delay time or dead-band size. The impact of these parameter choices is illustrated with sensitivity studies using the thermal room model THERAKLES [3-5].
What are they trying to tell me? Large-scale viability of the Start, Stop, Continue teaching evaluation method

ABSTRACT Open-ended qualitative questions aid in participatory evaluation and are alternatives to the typical student evaluation of teaching forms. One method of qualitative evaluation consists of three prompts that ask students to comment on the aspects of the course that they feel the instructor should Stop, Start, and Continue. In order to assess the viability of this method formally, a study was performed in which students were recruited to view one of two videos that intentionally featured instructors with different teaching styles on two different occasions. Textual analysis showed that students used different words to assess the two videos and used similar terms between the two sessions. These analyses show that the open-ended questions of the SSC can act as practical alternatives to the typical close-ended questions in the student evaluation of teaching.
Effective Sentiment Analysis of Twitter with Apache Spark

Today’s interconnected world generates a huge amount of digital data while millions of users share their opinions and feelings on various topics through popular applications such as social media, different micro blogging sites, and various review websites every day. Nowadays, applying sentiment analysis to Twitter data is regarded as a considerable problem, particularly for various organizations or companies who seek to know customers’ feelings and opinions about their products and services. The nature, variety, and enormous size of the data make it considerably practical for several applications ranging from choice and decision making to product assessment. Tweets are being used to convey the sentiment of a tweeter on a specific topic. Those companies keep surveying millions of tweets on some kinds of subjects to evaluate actual opinions and know the customers’ feelings. This paper aims to significantly collect, recognize, filter, reduce, and analyze all such relevant opinions, emotions, and feelings of people on different products or services which could be categorized into positive, negative, or neutral because such categorization improves sales growth of a company's products, films, etc. The Naïve Bayes classifier is the mainly utilized machine learning method for mining feelings from a large quantity of data, like twitter and other popular social networks, due to its higher accuracy rates. This study performs sentiment polarity analysis on Twitter data in a distributed environment, known as Apache Spark.
Simultaneous measurement of bacterial abundance and composition in response to biochar in soybean field soil using 16S rRNA gene sequencing

Biochar is an important soil conditioner. However, we have limited understanding of biochar effects on the microbial community traits of the rhizosphere and bulk soil in the field. The aim of this study was to examine the impacts of biochar amendment on microbial abundance and community in the rhizosphere and bulk soils in soybean‐growing fields. We applied 16S ribosomal RNA (rRNA) gene sequencing with an internal standard gene to quantitatively investigate biochar‐mediated changes in microbial composition and abundance in rhizosphere and bulk soils. The results indicated that the absolute abundance of bacterial taxa with internal standard can be more informative in describing soil microbial population distribution. A linear discriminant analysis effect size differential analysis showed that the biochar amendment significantly altered the soil microbial abundance and community composition. The bacteria in the rhizosphere soil showed more clear responses to biochar addition than the bacteria in the bulk soil. These results highlight the enhanced effect by biochar on bacterial population distribution in the rhizosphere. 16S rRNA gene sequencing with internal standard gene represents an effective method that can substantially improve 16S‐seq based microbiome studies by determining the 16S rRNA gene abundance and bacterial community composition simultaneously.
The Impact of First Timing of Antibiotics for Community Acquired Pneumonia in Emergency Department

Background: The reported associations between time to first antibiotic dose after hospital arrival and short-term mortality have varied in prior studies of CAP. It is unclear the benefit of early antibiotics in all patients given the risks of antibiotic overuse and misdiagnosis; Methods: A PubMed and Google Scholar search was performed to identify articles detailing the epidemiology, prognosis, diagnosis, and preliminary management of CAP; Results: In sepsis, antibiotics should not be delayed, and should be administered as soon as possible after recognition. For moderate or severe CAP patients without sepsis, antibiotics should be administered as soon as the diagnosis of CAP is highly likely. For stable, non–critically ill patients with CAP, the timing of antibiotics is not as clear and available evidence does not recommend strict requirements. Antibiotic timing – both rapid and delayed could be used as indicators of quality care in differing clinical scenarios; Results: The dogma of starting antibiotics quickly, within a rigid timeframe of expectations and guidelines has not improved outcomes in pneumonia patients, and has led to an increase in antibiotic treatment in uninfected patients. Severity of illness is the key factor associated with poor outcomes and should more significantly guide the timing of antibiotic initiation.
Twin Boundary Sliding in Single Crystalline Cu and Al Nanowires

Abstract Twin boundary sliding (TBS) is a deformation mode that is typically observed in nanocrystalline metals and usually occurs at multiple locations in the twinned region, including twin boundaries, of a crystal in a situation in which additional deformation via twinning is limited. Unlike the well-established dislocation slip and necking deformation process that occurs in large crystals, recent theories that explain TBS are often controversial, and much remains unsettled. Herein, we develop a factor that enables the prediction of deformation pathways by quantitatively analyzing the relative tendency for the formation of partial dislocations based on the dislocation and fault energy theories. The developed factor considers the effects of static/extrinsic features, such as the stacking fault energy (SFE) as well as the crystal size and orientation, and dynamic structural states characterized by the various fault energies of a material. The factor is initially validated using a Cu crystal exhibiting low SFE for various orientations and sizes. To determine whether the proposed factor can be generically extended to crystals with high SFE, we perform micro-mechanical tensile tests and molecular dynamics simulations on Al nanowires. The developed factor produces self-consistent results even for metals exhibiting different SFE values. The observations can be used as a guideline to design nanoscale structures for load-carrying applications.