Miracle-dz/UniFAR-FTUs huggingface dataset:
Protective Effects of Remimazolam on Cerebral Ischemia/Reperfusion Injury in Rats by Inhibiting of NLRP3 Inflammasome-Dependent Pyroptosis

Introduction Remimazolam is a novel benzodiazepine γ-aminobutyric acid A (GABAa) receptor agonist used for sedation and the induction as well as maintenance of general anesthesia. Previous research proved that anesthetic agents acting on GABAa receptor, such as thiopentone, propofol and midazolam, have protective actions for cerebral ischemia/reperfusion (I/R) injury. We here probed into remimazolam for its protective effect and potential mechanism of action against cerebral I/R injury. Material and Methods A rat model of middle cerebral artery occlusion (MCAO) with focal transient cerebral I/R injury was established and was given tail vein injection of gradient remimazolam (5, 10, 20 mg/kg) after 2 h of ischemia. Following 24 h of reperfusion, neurological function, brain infarct volume, morphology of cerebral cortical neurons, and expressions of corticocerebral NLRP3, ASC, caspase-1, GSDMD, IL-1β and IL-18 were evaluated. Results The results showed that remimazolam could effectively improve the neurological dysfunction, reduce the infarct volume and alleviate the damage of cortical neurons after I/R injury. Notably, the expression of NLRP3 inflammasome pathway was down-regulated, suggesting that remimazolam exerted protective actions on I/R injury by suppressing pyroptosis with decreased expression and release of inflammatory factors, and the involvement of the NLRP3 inflammasome pathway might be the core during that process. Overall, our results indicate that NLRP3 inflammation is a promising target. Conclusion Based on this mechanism, remimazolam may be one of the ideal anesthetic drugs for patients with ischemic stroke.
Speed Limits of Railway Train Braking

The definitions,influential factors,verifying bases and different determinate methods for speed limits of railway train emergency braking and service braking are clarified and founded.According to the mathematical relation between the distance limit and the speed limit of railway train emergency braking,the values of speed limit of emergency braking under different conditions can be solved.Simplified empirical formula and particular correlative empirical coefficient for all kinds of existing trains are made and suggested.Based on the limiting binding condition that the total deceleration force equals to zero,the speed limits of general freight train service braking are calculated and their diagram are made.Then by diagram method,the whole diagram of general freight train braking speed limit,including the switched boundary between the speed limit of emergency braking and service braking,are established comprehensively.Making use of correlative simplified empirical formula and diagram of speed limit of train braking,the concrete value or list of speed limit of train braking can be made easily and exactly.
The Differential Impact of the COVID-19 Pandemic in Geography in the United States

The COVID-19 pandemic has disrupted work and home life in unfathomable ways that have shaped and will continue to shape academia and the discipline of geography more specifically. As has been well documented, the pandemic had an outsized impact on the lives and labors of women, particularly women with small children; Black, Indigenous, and people of color; lesbian, gay, bisexual, transgender, and queer teaching faculty; precariously unemployed people; and other marginalized groups. In this article we draw on interviews with academic teaching staff from across the United States to examine the uneven impacts of the pandemic, with a focus on work as well as home life and the implications of those impacts for current and future configurations of the discipline. We conclude with recommendations for how to ameliorate the impacts of the pandemic.
Signatures of Bright‑To‑Dark Exciton Conversion in Corrugated Mos2 Monolayers

In this study, we investigated the effect of periodic uniaxial strains on electron and phonon transports of poly-crystalline and single-crystal molybdenum disulphide (MoS 2 ) monolayers on a periodically corrugated sapphire surface. Analysis of micro-Raman, polarized photoluminescence and second harmonic generation results shows the anisotropy of the corrugation-induced strain in both single-and polycrystalline MoS 2 monolayers. AFM topography measurements show periodically-rippled surfaces of the MoS 2 in the nanometre scale. Our results show that the application of the periodic strain produces two major effects on the band structure of MoS 2 monolayers: modulations on the band gap anisotropy and reduction of out-of-plane spin-relaxation time due to substrate-induced bending of MoS 2 . Spin memory loss, in other words, shortening the spin relaxation time, enables an electron spin-flip scattering process that can convert a formerly bright exciton to a dark exciton. Such conversion is reflected in decreasing intensity of photoluminescence and in the light intensity collected by scanning near-field microscope. Our results demonstrate the ability to control both the bandgap and exciton character in monolayer MoS 2 via periodic strains imposed by corrugated sapphire substrates. This approach offers an effective means in designing novel electronic devices for photovoltaic applications. The bright-to-dark excitons conversion in photovoltaic devices can boast longer lifetimes than their bright exciton counterparts so they can be more efficiently collected by external electrodes. The strain-induced conversion of the bright-to-dark excitons makes the hybrid MoS 2 /corrugated sapphire structure an interesting platform for future photovoltaic applications.
An Online Kernel Adaptive Filtering-Based Approach for Mid-Price Prediction

The idea of multivariate and online stock price prediction via the kernel adaptive filtering (KAF) paradigm is proposed in this article. The prediction of stock prices is traditionally done with regression and classification, thereby requiring a large set of batch-oriented and independent training samples. This is problematic considering the nonstationary nature of a financial time series. In this research, we propose an online kernel adaptive filtering-based approach for stock price prediction to overcome this challenge. To examine a stock's performance and demonstrate the work's superiority, we use ten different KAF family of algorithms. In this paper, we take on this challenge and propose an approach for predicting stock prices. To analyze a stock's performance and demonstrate the work's superiority, we use ten distinct KAF algorithms. Besides, the results are analyzed on nine-time windows such as one day, sixty minutes, thirty minutes, twenty five minutes, twenty minutes, fifteen minutes, ten minutes, five minutes, and one minute. We are the first to experiment with several time windows for all fifty stocks on the Indian National Stock Exchange, to the best of our knowledge. It should be noted here that the experiments are performed on stocks making up the main index: Nifty-50. In terms of performance and compared to existing methods, we have a 66% probability of correctly predicting a stock's next upward or downward movement. This number clearly shows the edge that the proposed method has in actual deployment. Furthermore, the experimental findings show that KAF is not only a better option for predicting stock prices but that it may also be used as an alternative in high-frequency trading due to its low latency.
Role of EBUS-TBNA in Non-Neoplastic Mediastinal Lymphadenopathy: Review of Literature

Mediastinal lymphadenopathy is a condition in which one or more mediastinal lymph nodes are enlarged for malignant or benign causes, generally more than 10 mm. For a long time, the only way to approach the mediastinum was surgery, while in last decades endoscopic techniques gained their role in neoplastic diseases. At the present time, EBUS is the technique of choice for studying the mediastinum in the suspicion of cancer, while there are not strong indications in guidelines for the study of benign mediastinal lymphadenopathy. We reviewed the literature, looking for evidence of the role of EBUS in the diagnostics of non-neoplastic mediastinal lymphadenopathy, with special regard for granulomatous disease, both infectious and non-infectious. EBUS is a reliable alternative to surgery in non-neoplastic mediastinal lymphadenopathy, even if more evidence is needed for granulomatous diseases other than tuberculosis and sarcoidosis.
Stability Characteristics of the Mesopause Region Above the Andes

We report a detailed analysis of atmospheric stabilities in the mesopause region (85–100 km) based on over 2,000 hr of high‐resolution temperature and horizontal wind measurements made with a Na lidar at the Andes Lidar Observatory, located in Cerro Pachón, Chile (30.25°S, 70.74°W). The square of Brunt–Väisälä frequency and the Richardson number are calculated, and occurrence probabilities of convective and dynamic instabilities are derived. An approach to assess the biases due to measurement uncertainties is used to obtain more accurate occurrence probabilities. The overall occurrence probabilities of convective and dynamic instabilities are 2.7% and 6.7%, respectively. High‐, medium‐, and low‐ frequency gravity wave (GW) contributions to these probabilities are isolated, which show that the high‐frequency GWs contribute most but simultaneous presence of high‐ and medium frequency GWs is much more effective in increasing the probabilities. Convective and dynamic instabilities are mainly generated because of the joint effect of different‐scale GWs. Isolated parts of GWs have much less contribution to the generation of both convective and dynamic instabilities. The dynamic instability is mainly contributed from less stable stratification and large wind shear together. Either factor can lead to about 15% of dynamic instability.
Development of Bactericidal Peptides against Multidrug-Resistant Acinetobacter baumannii with Enhanced Stability and Low Toxicity

Pathogenic superbugs are the root cause of untreatable complex infections with limited or no treatment options. These infections are becoming more common as clinical antibiotics have lost their effectiveness over time. Therefore, the development of novel antibacterial agents is urgently needed to counter these microbes. Antimicrobial peptides (AMPs) are a viable treatment option due to their bactericidal potency against multiple microbial classes. AMPs are naturally selected physiological microbicidal agents that are found in all forms of organisms. In the present study, we developed two tilapia piscidin 2 (TP2)-based AMPs for antimicrobial application. Unlike the parent peptide, the redesigned peptides showed significant antimicrobial activity against multidrug-resistant bacterial species. These peptides also showed minimal cytotoxicity. In addition, they were significantly active in the presence of physiological salts, 50% human serum and elevated temperature. The designed peptides also showed synergistic activity when combined with clinical antibiotics. The current approach demonstrates a fruitful strategy for developing potential AMPs for antimicrobial application. Such AMPs have potential for progression to further trials and drug development investigations.
A New Approach for Continual Planning (Extended Abstract)

Devising intelligent robots or agents that interact with humans is a major challenge for artificial intelligence. In such contexts, agents must constantly adapt their decisions according to human activities and modify their goal. In this extended abstract, we present a novel continual planning approach, called Moving Goal Planning (MGP) to adapt plans to goal evolutions. This approach draws inspiration from Moving Target Search (MTS) algorithms. In order to limit the number of search iterations and to improve its efficiency, MGP delays as much as possible the start of new searches when the goal changes over time. To this purpose, MGP uses two strategies: Open Check (OC) that checks if the new goal is still in the current search tree and Plan Follow (PF) that estimates whether executing actions of the current plan brings MGP closer to the new goal.
Two measures are better than one: Combining iconicity ratings and guessing experiments for a more nuanced picture of iconicity in the lexicon

Iconicity in language is receiving increased attention from many fields, but our understanding of the roles of iconicity in language is only as good as the measures we use to quantify it. We conducted iconicity rating and guessing experiments with 304 Japanese ideophones and prosaic words with sensory meanings, e.g. fuwafuwa ‘fluffy’, jawarakai ‘soft’. For both word groups, ratings and guesses were positively correlated—suggesting the two measures pick up on the same associations. Ideophones were consistently associated with higher iconicity ratings, but not higher guessing accuracy. We suggest that the structural markedness of ideophones enhances their perceived iconicity in the rating task, but does not provide any advantage (over and above form-meaning associations) in the guessing task. Thus, guesses and ratings could be used together to tease apart the relative contribution of structural markedness to iconic effects. Some ideophones were also poorly guessed, highlighting that construals of iconicity can be language-specific. Finally, we present some methodological contributions, including a new guessing paradigm that improves on the robustness, sensitivity and discriminability of previous approaches, and a reproducible workflow for creating rating and guessing experiments with a Python package, icotools, which we hope will improve comparability between future studies.
On Learning-free Detection and Representation of Textline Texture in Digitized Documents

: Textline detection and extraction is an integral part of any document analysis and recognition (DAR) system bridging the signal2symbol gap in order to relate a raw digital document of whatever sort to the computational analysis up to understanding of its semantic content. Key is the computational recovery of a rich representation of the salient visual structure which we conceive texture composed of periodic and differently scaled textlines in blocks with varying local spatial frequency and orientation. Our novel learning-free approach capitalizes on i) a texture model based upon linear system theory and ii) the complex Gabor transform utilizing both real even and imaginary odd kernels for the purpose of imposing a quadrilinear representation of textline characteristics as in typography. The resulting representation of textlines, be they either linear, curvilinear or even circular, then serves as input to subsequent computational processes. Via an experimental methodology allowing for controlled experiments with a broad range of digital data of increasing complexity (e.g. from synthetic 1D data to historical newspapers up to medieval manuscripts), we demonstrate the validity of our approach, discuss success and failure, and propose ensuing research.
Valuation of Loyalty Tokens

Valuation of tokens is a wager on the platform adoption. This study investigates the effect of platform adoption on the valuation of loyalty tokens and the contingent claims with the token as an underlying. The platform adoption is modelled using the classical Bass Model. The example selected is that of airmiles, but the approach could be extended to loyalty token with other numeraires as well. After assuming few monetary policy rules for the platform governance, the proposed simple model predicts that the Bass Model parameters could have significant influence on the valuation of loyalty tokens and the contingent claims with the token as an underlying. This study presents a simple model to value the loyalty token traded on a blockchain based and regulator mandated digital loyalty platform. The objective of the loyalty platform considered in this study is to foster customer loyalty by increasing the customer participation and decreasing the deferred revenue-based liability of the airlines. While the airmiles exhibit a decline in value, the loyalty tokens serve as a store of value thus increasing the customer participation. Miles though can be bought but cannot be traded in the open market, the proposed digital loyalty platform will address this need of the customers by pooling together many customers to transact with each other. Loyalty tokens will be used exclusively to trade miles on the platform and blockchain will facilitate smart contracts between the customers. But, unlike financial assets whose value depend on the underlying cash flows, the value of loyalty token is derived from the exclusivity that it provides the customers to trade miles on the platform and a prudent monetary policy adopted by the platform. An initial and future offering of tokens based on the platform adoption serves as financing for the development and maintenance of the platform. The initial offering of the loyalty tokens is different from a standard Initial Coin Offering where in, the initial sale of coin is auction based. The initial offering of loyalty tokens is proposed at a fixed – pre-set price and by a fair lottery, if the subscription is more than the quantity of initial offering.
Geometric Quality Testing of the WorldView-2 Image Data Acquired over the JRC Maussane Test Site using ERDAS LPS, PCI Geomatics and Keystone digital photogrammetry software packages - Inital Findings

This report presents the geometric quality results recorded for the five samples of the WorldView-2 Basic and Standard (processing level 1A and 2A) imagery acquired over the JRC Maussane Test Site. Different mathematical models of the WV2 sensor were tested, i.e. RPC-based and rigorous models implemented into PCI Geomatics, Keystone Spacemetric, and ERDAS IMAGINE& LPS software based on the following auxiliary data: several configurations (eg. 9, 6, 4) of equally distributed GCPs of 0.1m DEM of 2m grid and RMSEz=0.6m; 12 well-distributed independent check points (ICPs) of RMSEx,y,z The preliminary results of the analysis show that the 1-D RMSE of the WV2 image characterised by large off- nadir angle, i.e. greater than 30 degrees (or elevation angle less than 56 deg) is close to or below the 2.5m EU acceptable threshold. Further testing is required, especially for less accurate DTM data, diverse terrains and images characterised by high satellite inclination angle. Consequently, this report recommends that at least 6 (or 9 in areas with terrain slope diversity or high off-nadir angle) well-distributed ground control points during the WV2 sensor modelling phase using the Rational Functions mathematical model should be used. The rigorous model requires a minimum 9 or more ground control points. Accuracy requirements for auxiliary date, i.e. ground control points and DEM, given in ‘Guidelines for Best Practice and Quality Checking of Ortho Imagery’ should be strictly followed.
Status of Tuberculosis Infection and the Progression of HIV: Literature Study

Abstract—There are several factors that affect the development of HIV, one of which is TB co-infection. HIV and TB both play a role in reducing the function of the immune system. The aim of this study was to examine the relationship between the status of TB infection in HIV+ patients with the development/progression of HIV to AIDS and to observe the variation in the development/progression of HIV to AIDS in HIV+ patients who were co-infected with TB. Research articles were identified from the four databases Pub Med, BMC Public Health, Science Direct and Pro Quest. The review was undertaken to synthesize the findings in articles published between January 2010October 2020 with the protocol and evaluation of the study using PRISMA. A total of 6 articles met the inclusion and exclusion criteria, consisting of 4 retrospective cohort studies and 2 prospective cohorts. The results of the analysis found that 4 articles discussed about TB/HIV with CD4 cells and all were significant. Two articles noted a decrease in CD4 cell count in the TB/HIV group and the other two found an increase in CD4 cell count. Although there was an increase, compared to the non-TB group, the total of CD4 in TB/HIV co-infected individuals tended to be lower. In viral load, two articles noted a decrease, but only one article mentioned a significant difference but did not compare it with the non-TB group. The progression of HIV to AIDS was noted in two articles and it was found that the risk of progression in the TB/HIV group was higher than in the non-TB group. TB infection in HIV patients affects the development of HIV through the interaction of the immune system. Further research on tuberculosis infection progressing from HIV to AIDS needs to examine the type or location of tuberculosis. Keywords—Tuberculosis infection status; HIV; disease progression
Binaural Acoustic Scene Classification Using Wavelet Scattering, Parallel Ensemble Classifiers and Nonlinear Fusion

The analysis of ambient sounds can be very useful when developing sound base intelligent systems. Acoustic scene classification (ASC) is defined as identifying the area of a recorded sound or clip among some predefined scenes. ASC has huge potential to be used in urban sound event classification systems. This research presents a hybrid method that includes a novel mathematical fusion step which aims to tackle the challenges of ASC accuracy and adaptability of current state-of-the-art models. The proposed method uses a stereo signal, two ensemble classifiers (random subspace), and a novel mathematical fusion step. In the proposed method, a stable, invariant signal representation of the stereo signal is built using Wavelet Scattering Transform (WST). For each mono, i.e., left and right, channel, a different random subspace classifier is trained using WST. A novel mathematical formula for fusion step was developed, its parameters being found using a Genetic algorithm. The results on the DCASE 2017 dataset showed that the proposed method has higher classification accuracy (about 95%), pushing the boundaries of existing methods.