Miracle-dz/UniFAR-FTUs huggingface dataset:
Substituent effect on corrosion inhibition of Schiff bases derived from isatin / Aliyin Abdul Ghani … [et al.]

Two Schiff bases, 3-(4-hydroxyphenylimino)-l,3-dihydroindol-2-one (OPI) and 3-(4-Chloro-phenylimino)-l,3-dihydroindol-2-one (CPI) were successfully synthesized through condensation reactions giving yields of 82% and 63%, respectively. The compounds were characterized via physical and spectroscopic techniques, namely elemental analysis (C, H,N), ], ¹H and ¹³C Nuclear Magnetic Resonance (NMR) spectroscopy, Fourier Transform Infrared (FTIR) spectroscopy and melting point. The corrosion inhibiting property of the Schiff bases on mild steel in 1 M HC1 solution was investigated by the weight loss (WL) measurements, electrochemical impedance spectroscopy (EIS) and linear polarization resistance (LPR). The concentrations of the Schiff bases were varied from 1 x 10⁻³ M to 1 x 10⁻⁵ M. The inhibition efficiencies obtained from all the methods employed were in good agreement where the percentage of inhibition efficiencies increased with concentration. OPI showed better inhibition efficiency than CPI with 91% highest inhibition efficiency at 1 x 10⁻³ M additive concentration. This is likely to be caused by the resonance donating effect due to the presence of the hydroxyl group. The adsorption behaviour obeyed Langmuir isotherm for monolayer formation.
Phenomenology as a Potential Methodology for Subjective Knowing in Science Education Research

Abstract This paper charts the journey that led to the author's discovery of phenomenology as a potential research methodology in the field of science education, and describes the impact on his own thinking and approach of his encounters with the work of Husserl and Heidegger, Merleau-Ponty and Van Manen. Drawing on this theoretical framework, the author argues that, as a methodology for investigating scientific thinking in relation to life experience, learning and curriculum design, phenomenology not only provides a means of accessing subjective knowing and pure perception, but is sufficiently rigorous and systematic to represent the lifeworld experiences of research participants with a high degree of accuracy. In the process, he highlights the uniqueness and value of phenomenology in relation to quantitative and other qualitative research methods. The aim of this paper is to inspire insight into the value in science education research of using a methodology that fosters a deeper understanding of both teachers’ and learners’ lived experience of the scientific world. The challenge to science specialists, whether educators or researchers, would be to shift their default mode of understanding from the object pole to the ego pole, from the physical object to the human subject, from the observable and measurable to the lived as the true source of human knowledge.
Lignocellulolytic enzymes: Biomass to biofuel.

Rajendra Singh 1 , Manoj Kumar 1 , Anshumali Mittal 2 and *Praveen Kumar Mehta. 1. Department of Biochemistry, VP Chest Institute, University of Delhi, Delhi-110007, India. 2. Division of Structural Biology and Biophysics, Mill Hill laboratory, The Francis Crick Institute, London, UK. 3. Centre for Molecular Biology, Central University of Jammu, Jammu -181143, (J&K) India. Manuscript Info Abstract . Manuscript History
A Hybrid Monitoring Technique for Diagnosis of Mechanical Faults in Induction Motor

The paper aims to engineer an efficient technique for the condition monitoring of induction motor that not only provides the detection and identification of the faults but also assesses the operational condition of the motor. Induction motors possess one of the most important roles industrially and commercially. The developing faults in the motors can become catastrophic, if remain unanalyzed. The paper presents an effective novel solution to diagnose the major mechanical faults at the early possible stage by utilizing two efficient condition monitoring techniques to effectively deploy the strategies for the predictive maintenance. Primarily it employs the MCSA (Motor Current Signature Analysis), in which the faults are located by the spectral analysis of the particular harmonic components in the line current at specific characteristic frequencies generated by specific faults as the unique rotating flux. Fuzzy logic system has also been utilized, which assesses severity of the fault and operating condition of machine. The induction machine’s modular Simulink implementation has been presented that unlike other approaches provides the access to almost all parameters of the machine for analysis and control purposes. The mechanical faults specially bearing and eccentricity faults are simulated and successfully detected and localized in the results along with the severity assessment of the operational condition due to simulated faults.
Cyclonic cold-core eddy in the eastern North Atlantic. I Physical description

Many rings or eddies have been described in the western North Atlantic, but only a very few in the eastern part. Here we report on a cyclonic cold-core eddy which cut off from a Polar Front meander in the vicinity of 48.5"N, 22" W in May 1985. The eddy extended down to at least 2500 m depth. Its diameter was of the order of 100 km in the upper layer and 200 km at greater depths. Its surface signal was weak in temperature but strong in salinity. Geostrophic circulation around the eddy reached speeds of 30 to 40 cm S-', and net displacement speed was about 3 cm S-' northeastwards. The ambient water mass consisted mainly of North Atlantic Central Water (NACW) from below the surface layer down to 800 m depth. The interior water (core) of the eddy had an interleaving vertical structure consisting of: a mlxture of water types within the upper layer above 200 m depth; NACW between 200 and 400 m depth; predominantly admixtures of Subarctic Intermediate Water (SAIW) between 400 and 500 m depth. Beneath the SAIW and NACW the eddy showed traces of Mediterranean Water in the layer from 600 to 1000 m and deep water with admixtures of Labrador Sea Water at depths between 1400 and 2000 m.
Use of a Biofeedback Breathing App to Augment Poststress Physiological Recovery: Randomized Pilot Study

Background The speed of physiological recovery from stress may be a marker for cardiovascular disease risk. Stress management programs that incorporate guided breathing have been shown to moderate the stress response and augment recovery. Objective The aim of this study was to examine the effectiveness of an app-based brief relaxation intervention (BioBase) for facilitating physiological recovery in individuals exposed to a brief psychological stressor. Methods A total of 75 participants (44 women) completed a stressor speech task and were randomly assigned to one of three conditions: control, rumination, or an app-based relaxation breathing (BioBase) conditions. Heart rate variability (HRV) was assessed as a measure of autonomic function at baseline (6 min), during stress (6 min), and during recovery (6 min). Results There was a significant increase in subjective stress following stress exposure, but the ratings returned to baseline after recovery in all three groups. In addition, there was a significant decrease in vagally mediated HRV in the poststress period. During recovery, the root mean square of successive differences (P<.001), the percentage of successive interbeat (RR) intervals that differ by >50 ms (pNN50; P<.001), and high-frequency (P<.02) HRV were significantly higher in the BioBase breathing condition than the rumination and control conditions. There was no difference in HRV values between the rumination and control conditions during recovery. Conclusions App-based relaxed breathing interventions could be effective in reducing cardiovascular disease risk. These results provide additional utility of biofeedback breathing in augmenting physiological recovery from psychological stress.
Insight into the Hydrolytic Selectivity of β-Glucosidase to Enhance the Contents of Desired Active Phytochemicals in Medicinal Plants

Most glycosides in herbal medicines become pharmacologically active after hydrolysis or subsequent metabolism to respective aglycones. Hence, the hydrolytic efficiency of glycosidase is a crucial determinant of the pharmacological efficacy of herbal glycosides. In this study, we investigated the enzymatic conversion of the four herbal extracts and their glycosides using the glycoside hydrolase family 3 β-glucosidase from Lactobacillus antri (rBGLa). We show that β-glucosidase substrate specificity depends on the arrangements and linkage types of sugar residues in glycosides. The enzyme rBGLa showed higher hydrolytic selectivity for glucopyranoside than for glucuronide and rhamnopyranoside, and specificity for 1→6 rather than 1→2 linkages. In addition, in silico 3D structural models suggested that D243 and E426 of rBGLa act as catalytic nucleophile and acid/base residues, respectively. These experiments also suggested that substrate specificity is determined by interactions between the C6 residue of the sugar moiety of the substrate glycoside and the oxygen OD1 of D56 in rBGLa. Therefore, despite the broad substrate spectrum of β-glucosidase, differences in hydrolytic selectivity of β-glucosidases for glycoside structures could be exploited to enhance the hydrolysis of the desired medicinal glycosides in herbs using tailored β-glucosidases, allowing for improvement of specific potencies of herbal medicines.
Review of Hematopathology Consult Cases: A Two-Year Experience in a Tertiary Referral Center in Lebanon

Hematopathology remains a difficult diagnostic field. With the significant ongoing changes in the classification system that happened over the past several decades, the general pathologist faces many challenges when dealing with patients suspected to have lymphoma or leukemia. The authors assessed referred hematopathology cases that were reviewed by specialized hematopathologists. Of 309 cases, major discrepancy was found in 23% of them. The discrepancy ranged from lymphoma reclassification to other major revisions that had significant impact on patient treatment and management. This paper highlights some of the challenges that may face the general practicing pathologist when dealing with suspected hematopoietic neoplasms.
Active Anomaly Detection via Ensembles: Insights, Algorithms, and Interpretability

Anomaly detection (AD) task corresponds to identifying the true anomalies from a given set of data instances. AD algorithms score the data instances and produce a ranked list of candidate anomalies, which are then analyzed by a human to discover the true anomalies. However, this process can be laborious for the human analyst when the number of false-positives is very high. Therefore, in many real-world AD applications including computer security and fraud prevention, the anomaly detector must be configurable by the human analyst to minimize the effort on false positives. In this paper, we study the problem of active learning to automatically tune ensemble of anomaly detectors to maximize the number of true anomalies discovered. We make four main contributions towards this goal. First, we present an important insight that explains the practical successes of AD ensembles and how ensembles are naturally suited for active learning. Second, we present several algorithms for active learning with tree-based AD ensembles. These algorithms help us to improve the diversity of discovered anomalies, generate rule sets for improved interpretability of anomalous instances, and adapt to streaming data settings in a principled manner. Third, we present a novel algorithm called GLocalized Anomaly Detection (GLAD) for active learning with generic AD ensembles. GLAD allows end-users to retain the use of simple and understandable global anomaly detectors by automatically learning their local relevance to specific data instances using label feedback. Fourth, we present extensive experiments to evaluate our insights and algorithms. Our results show that in addition to discovering significantly more anomalies than state-of-the-art unsupervised baselines, our active learning algorithms under the streaming-data setup are competitive with the batch setup.
LOCATA challenge: speaker localization with a planar array

This document describes our submission to the 2018 LOCalization And TrAcking (LOCATA) challenge (Tasks 1, 3, 5). We estimate the 3D position of a speaker using the Global Coherence Field (GCF) computed from multiple microphone pairs of a DICIT planar array. One of the main challenges when using such an array with omnidirectional microphones is the front-back ambiguity, which is particularly evident in Task 5. We address this challenge by post-processing the peaks of the GCF and exploiting the attenuation introduced by the frame of the array. Moreover, the intermittent nature of speech and the changing orientation of the speaker make localization difficult. For Tasks 3 and 5, we also employ a Particle Filter (PF) that favors the spatio-temporal continuity of the localization results.
Social Power Evolution in Influence Networks With Stubborn Individuals

This article studies the evolution of social power in influence networks with stubborn individuals. We formulate two models grounded on the Friedkin–Johnsen opinion dynamics and the reflected appraisal mechanism; the models are defined over issue sequences and over a single issue, respectively. The key advance over the original DeGroot–Friedkin dynamics is that the proposed models include the empirically observed phenomenon of stubbornness and are, therefore, more realistic. We obtain various results about the existence of equilibria, their uniqueness, and their global attractivity. For example, we show that the single-issue and issue-sequence models have the same equilibrium social power. We also show that the equilibrium social power depends only upon interpersonal accorded influence and individuals’ stubbornness in several cases. Roughly speaking, a more stubborn individual has more equilibrium social power. In comparison with the original DeGroot–Friedkin model, the introduction of stubbornness leads to fundamental sociological differences: Full autocracy can never be achieved, whereas democracy can be achieved under all network topologies.
Unveiling Exception Handling Guidelines Adopted by Java Developers

Despite being an old language feature, Java exception handling code is one of the least understood parts of many systems. Several studies have analyzed the characteristics of exception handling code, trying to identify common practices or even link such practices to software bugs. Few works, however, have investigated exception handling issues from the point of view of developers. None of the works have focused on discovering exception handling guidelines adopted by current systems – which are likely to be a driver of common practices. In this work, we conducted a qualitative study based on semi-structured interviews and a survey whose goal was to investigate the guidelines that are (or should be) followed by developers in their projects. Initially, we conducted semi-structured interviews with seven experienced developers, which were used to inform the design of a survey targeting a broader group of Java developers (i.e., a group of active Java developers from top-starred projects on GitHub). We emailed 863 developers and received 98 valid answers. The study shows that exception handling guidelines usually exist (70%) and are usually implicit and undocumented (54%). Our study identifies 48 exception handling guidelines related to seven different categories. We also investigated how such guidelines are disseminated to the project team and how compliance between code and guidelines is verified; we could observe that according to more than half of respondents the guidelines are both disseminated and verified through code inspection or code review. Our findings provide software development teams with a means to improve exception handling guidelines based on insights from the state of practice of 87 software projects.
Don't Jump Through Hoops and Remove Those Loops: SVRG and Katyusha are Better Without the Outer Loop

The stochastic variance-reduced gradient method (SVRG) and its accelerated variant (Katyusha) have attracted enormous attention in the machine learning community in the last few years due to their superior theoretical properties and empirical behaviour on training supervised machine learning models via the empirical risk minimization paradigm. A key structural element in both of these methods is the inclusion of an outer loop at the beginning of which a full pass over the training data is made in order to compute the exact gradient, which is then used to construct a variance-reduced estimator of the gradient. In this work we design {\em loopless variants} of both of these methods. In particular, we remove the outer loop and replace its function by a coin flip performed in each iteration designed to trigger, with a small probability, the computation of the gradient. We prove that the new methods enjoy the same superior theoretical convergence properties as the original methods. However, we demonstrate through numerical experiments that our methods have substantially superior practical behavior.
Indexation de pages Web

Le nombre de pages sur le Web augmente chaque jour. L'utilisateur qui recherche des documents sur un sujet precis souhaite les obtenir tous avec un minimum de bruits. De ce point de vue, les moteurs actuels ont encore besoin de beaucoup progresser. La precision de leur reponse pourrait etre amelioree s'ils disposaient d'index fiables des termes constituant une page. Dans cet article, nous proposons l'utilisation de techniques d'acquisition automatisee de terminologie et la prise en compte des specificites des pages Web pour constituer un index des pages qui devra etre une representation la plus fidele possible du contenu de ces documents. Dans le cadre de cette etude, un logiciel d'indexation des pages Web a ete realise qui prend en compte les contraintes precedentes. Il met en oeuvre des techniques traitant de la morphologie, de la syntaxe et de la semantique des termes ainsi que des specificites des pages Web. Nous concluons l'article par une analyse des resultats experimentaux obtenus.
Probabilistic Encoding Models for Multivariate Neural Data

A key problem in systems neuroscience is to characterize how populations of neurons encode information in their patterns of activity. An understanding of the encoding process is essential both for gaining insight into the origins of perception and for the development of brain-computer interfaces. However, this characterization is complicated by the highly variable nature of neural responses, and thus usually requires probabilistic methods for analysis. Drawing on techniques from statistical modeling and machine learning, we review recent methods for extracting important variables that quantitatively describe how sensory information is encoded in neural activity. In particular, we discuss methods for estimating receptive fields, modeling neural population dynamics, and inferring low dimensional latent structure from a population of neurons, in the context of both electrophysiology and calcium imaging data.
Pharmacokinetics, Tissue Distribution, Metabolism, and Excretion of Naringin in Aged Rats

Aging is an inevitable biological process characterized by the loss of functional capacity and associated with changes in all phases of pharmacokinetic processes. Naringin, a dietary flavanone glycoside, has been proved to be beneficial for the treatment of multiple age-associated chronic diseases. To date, the pharmacokinetic processes of naringin in aged individuals are still unknown. Thus, a rapid resolution liquid chromatography tandem triple quadrupole mass spectrometry (RRLC-QQQ-MS/MS) method was established for the determination of naringin and its metabolite naringenin in rat plasma, urine, feces, and tissue homogenate. The pharmacokinetic parameters were calculated and a higher exposure of naringin and naringenin were observed in aged rats. Naringin and naringenin were mostly distributed in gastrointestinal tract, liver, kidney, lung, and trachea. Furthermore, a total of 39 flavonoid metabolites (mainly glucuronides and sulfates) and 46 microbial-derived phenolic catabolites were screened with ultra-fast liquid chromatography-quadrupole-time-of-flight tandem mass spectrometry (UFLC-Q-TOF-MS/MS). Naringenin, hippuric acid, and 3-(4’-hydroxyphenyl)propionic acid were predominated metabolites. This study systemically investigated the pharmacokinetics, tissue distribution, metabolism, and excretion of naringin in aged rats, revealing age- and gender-related changes in the in vivo behavior of naringin. These results would be helpful for the interpretation of pharmacokinetics and pharmacodynamics of naringin in aged population.
Evaluation of a Mindfulness-Based Intervention With and Without Virtual Reality Dialectical Behavior Therapy® Mindfulness Skills Training for the Treatment of Generalized Anxiety Disorder in Primary Care: A Pilot Study

Generalized Anxiety Disorder (GAD) is a very prevalent disorder in primary care (PC). Most patients with GAD never seek treatment, and those who do seek treatment often drop out before completing treatment. Although it is an understudied treatment, Mindfulness-Based Interventions (MBIs) indicate preliminary efficacy for the treatment of GAD symptoms, but many patients with GAD present other associated symptoms (e.g., attention deficits) that complicate the treatment. Virtual Reality DBT® Mindfulness Skills learning has recently been developed to make learning mindfulness easier for patients with emotion dysregulation who have trouble concentrating. Virtual Reality (VR) might serve as a visual guide for practicing mindfulness as it gives patients the illusion of “being there” in the 3D computer generated world. The main goal of this study was to evaluate the effect of two MBIs (a MBI in a group setting alone and the same MBI plus 10 min VR DBT® Mindfulness skills training) to reduce GAD symptoms. A secondary aim was to explore the effect in depression, emotion regulation, mindfulness, and interoceptive awareness. Other exploratory aims regarding the use of VR DBT® Mindfulness skills were also carried out. The sample was composed of 42 patients (roughly half in each group) with GAD attending PC visits. After treatment, both groups of patients showed significant improvements in General Anxiety Disorder measured by the GAD-7 using mixed regression models [MBI alone (B = -5.70; p < 0.001; d = -1.36), MBI+VR DBT® Mindfulness skills (B = -4.38; p < 0.001; d = -1.33)]. Both groups also showed significant improvements in anxiety, depression, difficulties of emotion regulation and several aspects of mindfulness and interoceptive awareness. Patients in the group that received additional 10 min VR DBT Mindfulness Skills training were significantly more adherent to the treatment than those receiving only standard MBI (100% completion rate in MBI + VR vs. 70% completion rate in MBI alone; Fisher = 0.020). Although randomized controlled studies with larger samples are needed, this pilot study shows preliminary effectiveness of MBI to treat GAD, and preliminary evidence that adjunctive VR DBT® Mindfulness Skills may reduce dropouts.