Miracle-dz/UniFAR-FTUs huggingface dataset:
Chapter 6:Multi-scale Simulations of Membrane Sculpting by N-BAR Domains

Cells contain membranes of various shapes, often formed with the help of cellular proteins. In particular, proteins of the BAR domain superfamily participate in various membrane sculpting processes, bending membranes through the concerted action of multiple BAR domains arranged in lattices. Despite extensive experimental studies, information on the dynamics of membrane bending and an explanation of the lattices' role are still lacking. Computational studies can furnish such information. Here we summarize recent work on the dynamics of membrane bending by N-BAR domains, a well-studied member of the BAR domain superfamily, at four levels of resolution: described by all-atom molecular dynamics, residue-based coarse graining (resolving single amino acids and lipid molecules), shape-based coarse graining (resolving overall protein and membrane shapes), and a continuum elastic membrane model. Simulations showed how the membrane curvature generated depends on the arrangement of N-BAR domains on the membrane surface. The lattice arrangements found to be optimal for producing high membrane curvature are composed of protein rows separated by ~5 nm, stability of the rows being maintained through electrostatic interactions between N-BAR domains. Formation of entire membrane tubes by lattices of N-BAR domains over time scales of ~200 μs was observed in coarse-grained simulations; an all-atom simulation of a 2.3 million atom system covering 0.3 μs complemented the coarse-grained simulations.
Webauto_OSSE: University Circulars to Social Media Using JavaScript Open Source Server Environment

An accessibility of up-to date information regarding the events happening in the organization or institute is critical for its stakeholders primarily students. This task is usually accomplished through either the use of on-wall notice boards or posting on the university’s website in the form of a PDF document. This process although efficient on the surface doesn’t always guarantee the flow of information. Another challenge is that the students don’t visit these websites frequently or may miss details due to unforeseen circumstances. To overcome this problem, in this paper, Webauto_OSSE is proposed which automatically scrapes the websites on a regular basis and posts themost recent notices on platforms frequently visited by the student i.e. social media platforms like Facebook, Instagram, etc. This helps in a more direct and appealing way of information flow in the form of image format rather than a PDF. This method of circulating notices would be much more efficient and would result in a much lesser communication gap between the organization’s administration and the major stakeholders i.e. students.
Use of the Grand Canonical Transition-Matrix Monte Carlo Method to Model Gas Adsorption in Porous Materials

We present grand canonical transition-matrix Monte Carlo (GC-TMMC) as an efficient method for simulating gas adsorption processes, with particular emphasis on subcritical gas adsorption in which capillary phase transitions are present. As in other applications of TMMC, the goal of the simulation is to compute a particle number probability distribution (PNPD), from which thermophysical properties of the system can be computed. The key advantage of GC-TMMC is that, by appropriate use of histogram reweighting, one can generate an entire adsorption isotherm, including those with hysteresis loops, from the PNPD generated by a single GC-TMMC simulation. We discuss how to determine various thermophysical properties of an adsorptive system from the PNPD, including the identification of capillary phases and capillary phase transitions, the equilibrium phase transition, other free energies, and the heat of adsorption. To demonstrate the utility of GC-TMMC for studies of adsorption, we apply the method to various sy.
TRACE: Tennessee Research and Creative TRACE: Tennessee Research and Creative Exchange Exchange

Stroke is the 3 rd leading cause of deaths in USA with an equally high number of survivors. Post-stroke rehabilitation is an important part of recovery after stroke as it helps to relearn skills lost due to the eﬀect of stroke on a part of your brain. Stroke rehabilitation can help the subject regain independence and improve their quality of life. During their rehabilitation process, a subject is expected to perform a certain number of exercises and constantly try to use their aﬀected limb. But due to social constraints and psychological stress, the subjects tend to perform the respective activities only in a closed environment and hence only in the presence of a physicist i.e. during their rehabilitation in an hospital, thereby dampening their process of rehabilitation. This thesis aims at laying the foundation to develop a wearable device to track the recovery of a stroke patient while their in-hospital and at home upper limb rehabilitation processes depending on the muscular activity retrieved by a non-invasive sensors placed on the skin of the upper limb of the patient. To achieve this goal multiple steps are involved, but this thesis concentrates on the step which involves identifying the exercise performed by the subject using their bio & kinematic signals. To develop the ideal network for this goal, the thesis initially compares various classic learning techniques used to classify hand gestures using surface-Electromyography(sEMG). From the results obtained from these networks, a CNN is designed speciﬁc to the activities and input signals used in this thesis. The CNN is able to classify these activities with an accuracy of around 91%.
Bond Market Development and Bank Risk-Taking: Evidence from Developing Markets

Liquidity management is key to banks’ successful operation. A shortage of liquidity is a major threat to the soundness of financial institutions and systematic financial stability. Both the 1997/98 Asian financial crisis and the global financial crisis (GFC) showed how the drying up of liquidity can challenge financial stability and harm the real economy when the financial sector, in particular banks, failed to function as a liquidity provider (Acharya and Mora 2015). During a crisis when liquidity is tight, banks face increased financial constraints and their own liquidity positions can worsen (Drehmann and Nikolaou 2013). Ivashina and Scharfstein (2010) show that, during the GFC, credit supply in the banking sector dropped significantly under liquidity pressure from credit-line drawdowns by existing borrowers and a run by short-term depositors. Cornett et al. (2011) document that banks with less liquid asset portfolios tend to reduce their credit supply and increase asset liquidity during financial crises, and only banks with stable funding sources continue lending activities. This evidence points to the importance of liquidity management instruments that can enhance bank resilience to liquidity shocks and contribute to a well-functioning financial system.
DO LEARNERS CONNECT SOCIOPHONETIC VARIATION WITH REGIONAL AND SOCIAL CHARACTERISTICS?

Abstract Learners must develop the ability to perceive linguistic and social meaning in their second language (L2) to interact effectively, but relatively little is known about how learners link social meaning to a single phonetic variable. Using a matched-guise test targeting coda /s/ (realized as [s] or debuccalized [h]), we explore whether L2 Spanish learners identify native speakers’ social characteristics based on phonetic variants. Our results indicate that advanced learners were more sensitive to sociophonetic information; advanced listeners who had completed a phonetics course were significantly more likely to categorize /s/ reducers as Caribbean and those who had studied abroad in aspirating regions recognized a relationship between coda /s/ and status. To account for the complex interplay among proficiency, explicit instruction, and dialectal exposure in the development of L2 sociophonetic perception, we suggest the union of the L2 Linguistic Perception Model with exemplar models of phonological representation and indexical meaning.
Plasma Electrolytic Oxidation Ceramic Coatings on Zirconium (Zr) and ZrAlloys: Part I—Growth Mechanisms, Microstructure, and Chemical Composition

Recently, a significant number of research projects have been directed towards designing and developing ceramic coatings for zirconium-based substrates due to their outstanding surface properties and utilization in modern technologies. The plasma electrolytic oxidation (PEO) coating is an environmentally friendly wet coating method that can be performed in a wide range of electrolytes. The surface characteristics of PEO coatings can be tailored by changing electrochemical parameters, electrolyte composition, and substrate alloying elements to adopt a conformal and adhesive PEO ceramic coating for the final demanding applications in chemical, electronics, and energy technologies. This review focuses on deriving a deeper fundamental understanding of the PEO growth mechanisms and the effect of process parameters on transient discharge behavior at breakdown, initiation, and growth of the oxide layer and incorporating species from the electrolyte. It highlights the fundamental microstructural properties associated with structural defects, phase transformation, and the role of additives.
Management and Secondary Prevention

Zusammenfassung Das akute Koronarsyndrom umfasst ein breites Spektrum myokardialer Ischämien, die von der instabilen Angina pectoris über den Nicht-ST-Hebungsinfarkt bis zum akuten ST-Strecken-Hebungsinfarkt reichen. Akute Koronarsyndrome stellen die häufigste Ursache für kardial bedingte Hospitalisationen dar. Die rasche Diagnose sowie Risikostratifizierung sind für die Einleitung der optimalen medikamentösen und invasiven Behandlung von großer Bedeutung. Therapeutische Maßnahmen umfassen potente antiischämische und antithrombotische Substanzen sowie eine rasche und wirkungsvolle Inhibition der Blutplättchenaggregation. Darüber hinaus profitieren Patienten mit erhöhtem Risiko, wie beispielsweise troponinpositive Patienten, Patienten mit ST-Strecken-Senkungen sowie Diabetiker, von einer frühen invasiven Abklärung. Modifikationen des Lebensstils sowie von Risikofaktoren komplementieren die langfristige medikamentöse Therapie, um das Rezidivrisiko zu minimieren. Akutes Koronarsyndrom. Management und Sekundärprävention Abstract Acute coronary syndromes represent a broad spectrum of ischemic myocardial events including unstable angina, non-ST elevation myocardial infarction and acute ST elevation myocardial infarction, which are associated with high morbidity and mortality. They constitute the most frequent cause of hospital admission related to cardiac disease. Early diagnosis and risk stratification are essential for initiation of optimal medical and invasive management. Therapeutic measures comprise aggressive antiplatelet, antithrombotic, and anti-ischemic agents. In addition, patients with high-risk features, notably positive troponin, ST segment changes and diabetes, benefit from an early invasive as compared to a conservative strategy. Importantly, lifestyle interventions, modification of the risk factor profile, and long-term medical treatment are of pivotal importance in reducing the long-term risk of recurrence.
The rapid and dense assembly of solution-processed single-wall carbon nanotube semiconducting films via an acid-based additive in the aqueous dispersion

The rapid and dense assembly of solution-processed single-wall carbon nanotube (SWCNT) semiconducting films is the key enabling factor for their practical applications to large-area electronics and potentially, roll-to-roll based process development. In this study, we demonstrate a significant reduction in the assembly time for a commercial nanotube dispersion (95%-purified semiconducting SWCNT ink), whilst maintaining a high-quality film with better density, by adding a ∼0.1% volume ratio of nitric acid to the dispersion. A rapidly and densely assembled film was formed after deposition for less than 30 seconds, compared to more than several minutes in a commercial reference ink as previously reported by many research groups. The relationships among the zeta potential, pH concentration, and deposition time of the engineered dispersion were also investigated. The electrostatically weakened force of the ionic surfactants in the engineered inks leads to the rapid formation of densely packed SWCNT films, thereby enabling the fabrication of high-performance SWCNT thin film transistors (TFTs) with a field-effect mobility of 18.80 ± 2.08 cm2 V−1 s−1 and on/off ratios of ≥104 in a significantly reduced process time.
A Review of Low Noise Oscillator

There has been a large number of papers published on low nonetheless, noise oscillators are usually very specific to the basic application. This essay will define a collection of Laws of design that are general and can be used to produce very low noise efficiency oscillators where both flicker noise and additive (thermal noise) are considered. It will describe linear theories which accurately describe noise output of oscillators of the resonator type. The Limits set on the noise output by reactor diodes in it will define tunable oscillators and the noise degradation triggered by the error of the open loop stage would be displayed. Several examples of design are included and these display close correlation with the theory.
High-resolution measurement of the time-modulated orbital electron capture and of the β decay of hydrogen-like

The periodic time modulations, found recently in the two-body orbital electron-capture (EC) decay of both, hydrogen-like 140Pr58+ and 142Pm60+ ions, with periods near to 7 s and amplitudes of about 20%, were re-investigated for the case of 142Pm60+ by using a 245 MHz resonator cavity with a much improved sensitivity and time resolution. We observed that the exponential EC decay is modulated with a period T = 7.11(11) s, in accordance with a modulation period T = 7.12(11) s as obtained from simultaneous observations with a capacitive pick-up, employed also in the previous experiments. The modulation amplitudes amount to aR = 0.107(24) and aP = 0.134(27) for the 245 MHz resonator and the capacitive pick-up, respectively. These new results corroborate for both detectors exactly our previous findings of modulation periods near to 7 s, though with distinctly smaller amplitudes. Also the three-body β decays have been analyzed. For a supposed modulation period near to 7 s we found an amplitude a = 0.027(27), compatible with a = 0 and in agreement with the preliminary result a = 0.030(30) of our previous experiment. These observations could point at weak interaction as origin of the observed 7 s-modulation of the EC decay. Furthermore, the data suggest that interference terms occur in the two-body EC decay, although the neutrinos are not directly observed.
Sensory dimensions of peach-palm fruit (Bactris gasipaes) and implications for future genetics

Introduction. Long-term genetic improvement efforts in Latin America aimed to ameliorate peach-palm fruit farmers’ technical capacities and livelihoods have proven to be ineffective. Although experts agree this is partly the result of large uncertainty regarding consumer preferences, such research remains as virtually nonexistent. Objective. To identify chemical and morphologic attributes that are attractive for final consumers of peach-palm fruit and how these attributes are related to final perceptions of fruit quality, through statistical and econometric methods. Materials and methods. By using the harvest from a large set of varieties from a peach-palm (Bactris gasipaes) germplasm bank in Southwestern Colombia, 482 evaluations were made between April to October of 2016 by local consumers who tasted the fruits and gave a report on their perception of taste/quality in a case study scheme. Combining these data with further information on fruit color, oiliness perception, and additional controls, an ordered logit regression model was set to identify the attributes that describe peach-palm fruits with the most favorable scores for their taste/quality perception. Results. Preferences on oil contents were not linear. Fruits perceived as high-oil were between 9 and 13 % more likely to be considered as having the best taste/quality, while those perceived high-starch content were correlated with a significant aversion towards the fruit, namely 43 % less likely to be among the best fruits. Conclusion. A great deal of research is yet to be done around peach-palm fruit consumer preferences and, furthermore, it should be carried on an interdisciplinary ground. Further analyses of desired fruit traits should be made at sub-national levels, identifying ranges of suitable oiliness and morphological expected attributes and how available genetic material could help to satisfy those needs.
The Effectiveness of Multi-Label Classification and Multi-Output Regression in Social Trait Recognition

First impressions make up an integral part of our interactions with other humans by providing an instantaneous judgment of the trustworthiness, dominance and attractiveness of an individual prior to engaging in any other form of interaction. Unfortunately, this can lead to unintentional bias in situations that have serious consequences, whether it be in judicial proceedings, career advancement, or politics. The ability to automatically recognize social traits presents a number of highly useful applications: from minimizing bias in social interactions to providing insight into how our own facial attributes are interpreted by others. However, while first impressions are well-studied in the field of psychology, automated methods for predicting social traits are largely non-existent. In this work, we demonstrate the feasibility of two automated approaches—multi-label classification (MLC) and multi-output regression (MOR)—for first impression recognition from faces. We demonstrate that both approaches are able to predict social traits with better than chance accuracy, but there is still significant room for improvement. We evaluate ethical concerns and detail application areas for future work in this direction.
New causes of rot in rubber sting panel: case Fusarium spp

Moldy rot on the rubber sting panel decreases the yield and regeneration of its bark. The objective was to identify the causative agent of the disease in San Juan Bautista Tuxtepec, Oaxaca and evaluate its in vitro sensitivity to fungicides. To this end, tissue from the diseased sting panel was collected and made insulations. The isolates were characterized in the nutritive media PDA (papadextrose-agar), CLA (carnation leaves-agar), FLA (liquid fermentation-agar), CDA (coffeedextrose-agar) and ZA (carrot-agar). Growth rates were evaluated and pathogenicity tests were carried out in the laboratory and in the field, as well as in vitro sensitivity to Mancozeb 70%, Benomilo, Carbendazin, Propiconazole, Chlorothalonil, and Carboxamide, in 10 treatments and eight repetitions. The results showed four isolates of the genus Fusarium, which showed polymorphism according to the culture medium, with radial growth and marked rings. Microconidia and macroconidia dispersed in the mycelium and white, orange and blue sporodochs were observed at 36 days. The growth rate varied with the nutrient medium and the inoculated strain. F. circinatum, F. lateririum, F. decemcellulare and F. mangiferae were identified. In the laboratory pathogenicity tests all inoculated strains were positive and in the field only F. circinatum and F. mangiferae. The sensitivity bioassay showed fungicide-dependent response and isolation. These results allow us to conclude that the species F. circinatum, F. mangiferae, F. lateririum and F. decemcellulare can cause moldy rot in the sting panel of clone IAN 710. This is a first report that involves these species. Its control depends on the species of Fusarium and the fungicide used.
SECOND LANGUAGE VOWEL PERCEPTION TRAINING: EFFECTS OF SET SIZE, TRAINING ORDER, AND NATIVE LANGUAGE

This paper reports results of a series of vowel training studies. Study 1 trained two groups of Japanese learners of English on American English vowels and examined the effects of training set sizes (9 vs 3 more difficult vowels); Study 2 trained Korean learners of English and examined the efficiency of training protocols using both 9and 3-vowel sets. Study 3 compared the Japanese and Korean results on the untrained materials. Results suggested following: 1) vowel training works best when a large set of vowels, rather than a subset, is used; 2) training focusing on a smaller yet difficult vowels may have detrimental effects on later learning; and 3) improvement due to training on nonsense words may or may not carry over to untrained real word materials, possibly due to an interaction between native and non-native phonology.
The Five-Level Structure of Soft Computing in an Intelligent System with Direct Imposition of Knowledge

An intellectual system based on the technology of direct imposition of knowledge using a five-level system for handling the fuzziness of the natural language, the relativity of knowledge and the inaccuracy of the logical conclusions used is considered. Special knowledge models – molingas – with confidence factors are used to account for the ambiguity of the natural language. A two-level inference system for decision making on knowledge bases based on molingas is described
Time Series Clustering with Topological and Geometric Mixed Distance

Time series clustering is an essential ingredient of unsupervised learning techniques. It provides an understanding of the intrinsic properties of data upon exploiting similarity measures. Traditional similarity-based methods usually consider local geometric properties of raw time series or the global topological properties of time series in the phase space. In order to overcome their limitations, we put forward a time series clustering framework, referred to as time series clustering with Topological-Geometric Mixed Distance (TGMD), which jointly considers local geometric features and global topological characteristics of time series data. More specifically, persistent homology is employed to extract topological features of time series and to compute topological similarities among persistence diagrams. The geometric properties of raw time series are captured by using shape-based similarity measures such as Euclidean distance and dynamic time warping. The effectiveness of the proposed TGMD method is assessed by extensive experiments on synthetic noisy biological and real time series data. The results reveal that the proposed mixed distance-based similarity measure can lead to promising results and that it performs better than standard time series analysis techniques that consider only topological or geometrical similarity.
ATTEMPT TO FIND NUMBER OF PETALS OF FLOWER IMAGES AND CLASSIFY FLOWERS USING COMPUTER VISION

: It is imperative for researchers, botanists having inquisitive mind for flower species of given unknown flower. Petals of flowers detected through an automated process will be an exciting advantage for them. There were many studies conducted to classify flowers based on hand-crafted methodologies and recently machine learning and deep learning techniques through computers. In this work, few novel ideas are attempted to find out the petals from the flower images using machine learning methods irrespective of its colour, shape or orientation. This information is augmented as a description during flower classification by using deep learning models like ResNet50 and LSTM. The models are trained using images collected from Oxford University’s flower image database. Among many different attempts to perceive flower petal counts like k Means algorithm, region based, edge based, watershed transformation and hue based image segmentation, the last one has better accuracy in finding the correct numbers of petals. A robust convolution neural network classifier is built to classify the flowers thereafter. The predicted result includes petals count information derived by the above said method.