Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Family of Acinetobacter Mega-Plasmids Are Disseminating Multi-Drug Resistance Across the Globe While Acquiring Location-Specific Accessory Genes

Acinetobacter species are emerging as major nosocomial pathogens, aided by their ability to acquire resistance to all classes of antibiotics. A key factor leading to their multi-drug resistance phenotypes is the acquisition of a wide variety of mobile genetic elements, particularly large conjugative plasmids. Here, we characterize a family of 21 multi-drug resistance mega-plasmids in 11 different Acinetobacter species isolated from various locations across the globe. The plasmid family exhibits a highly dynamic and diverse accessory genome, including 221 antibiotic resistance genes (ARGs) that confer resistance to 13 classes of antibiotics. We show that plasmids isolated within the same geographic region are often evolutionarily divergent members of this family based on their core-genome, yet they exhibit a more similar accessory genome. Individual plasmids, therefore, can disseminate to different locations around the globe, where they then appear to acquire diverse sets of accessory genes from their local surroundings. Further, we show that plasmids from several geographic regions were enriched with location-specific functional traits. Together, our findings show that these mega-plasmids can transmit across species boundaries, have the capacity for global dissemination, can accumulate a diverse suite of location-specific accessory genes, and can confer multi-drug resistance phenotypes of significant concern for human health. We therefore highlight this previously undescribed plasmid family as a serious threat to healthcare systems worldwide. These findings also add to the growing concern that mega-plasmids are key disseminators of antibiotic resistance and require global surveillance.
Effect of Chemical Pretreatments on the Physico-Chemical and Sensory Attributes of Sweet Potato-Gari

The effect of addition of sodium metabisulphite, NaS 2 O 5 (2.5 and 0.5%) and lime juice (2.5 and 0.5%) on the quality of sweet potato-gari was investigated. Untreated sweet potato-gari and cassava-gari served as control. Moisture content of cassava-gari and sweet potato-gari ranged between 7.95 and 8.80% db. The pH and TTA values of sweet potato-gari were 5.8 to 6.0 and 0.94 to 0.99, respectively, while cassava-gari had pH 4.42 and Total Titratable A of 1.11% lactic acid. Swelling capacity showed that sweet potato-gari pretreated with 2.5% NaS 2 O 5 had the lowest value of 252% compared to those pretreated with 0 . 5% lime with highest value of 301% while cassava-gari recorded 430%. Sample from 2.5% NaS 2 O 5 treatment had the highest average particle size index followed by sample treated with 2.5% lime having the lowest. There were significant differences (P<0.05) in the sensory attributes of sweet potato-gari and cassava-gari also in the treated sweet potato-gari and untreated sweet potato-gari samples. The gari samples containing 2.5% lime juice and 0.5% Sodium metabisulphite were comparable to colour of cassava-gari.
Privacy Risks, Emotions, and Social Media

This study proposes a novel coping model of privacy that extends prior privacy work in two important ways: first, the reconceptualization of privacy coping reflecting both problem- and emotion-focused strategies, and second, the incorporation of discrete emotions as a driver of privacy coping. Results from online survey data (N = 605) show that Facebook users’ adaptation to privacy risks consists of multifaceted coping strategies that are problem-focused, emotion-focused, and communication-focused. These coping strategies have selective relationships with theoretical antecedents such as cognitive appraisals (i.e., threat appraisals and coping appraisals) and negative emotions (i.e., anger, frustration, regret, and anxiety/fear). Discrete emotions play a crucial functional role in determining users’ coping responses to privacy risks by selectively activating (or deactivating) emotionally congruent (or incongruent) coping strategies. Specifically, approach-associated emotions such as frustration and regret lead to problem-focused privacy coping strategies, whereas avoidance-associated emotions such as anxiety and fear lead to emotion-focused strategies. We also find a new type of privacy coping strategy: communication-focused coping strategies that are affected by regret and anxiety/fear.
Barriers and Value Co-Destruction in a B2B Project Management Context: Agile Software Development Adoption and Rejection in Japanese Organizations

A new service concept meets some resistance from those who face it prior to adoption. If the resistance cannot be overcome, the new service will not be diffused. There have been many studies of business-to-consumer (B2C) contexts on adoption and rejection of product and service innovation. The question remains, what barriers should be overcome in the diffusion process of new services in the business-to-business (B2B) contexts? For example, if you implement a new service concept to your organization to create new value with your customers, what barriers does your organization need to overcome? Few studies to date have revealed the issue. To identify barriers for adoption, this study focuses on the diffusion process of the Agile software development method in Japanese organizations, which is still in progress, and attempts to approach the adoption barriers for service innovation in the B2B context to understand the barriers and leverage point for overcoming them. The Agile software development method is an innovation of software development. But there is a possibility that its diffusion will be stopped due to the resistance of project managers involved in a software development. This may lead service systems to value co-destruction as well.
Multimodal Coordination Measures to Understand Users and Tasks

Physiological and behavioral measures allow computing devices to augment user interaction experience by understanding their mental load. Current techniques often utilize complementary information between different modalities to index load level typically within a specific task. In this study, we propose a new approach utilizing the timing between physiology/behavior change events to index low and high load level of four task types. Findings from a user study where eye, speech, and head movement data were collected from 24 participants demonstrate that the proposed measures are significantly different between low and high load levels with high effect size. It was also found that voluntary actions are more likely to be coordinated during tasks. Implications for the design of multimodal-multisensor interfaces include (i) utilizing event change and interaction in multiple modalities is feasible to distinguish task load levels and load types and (ii) voluntary actions should be allowed for effective task completion.
Mahalanobis distance–based kernel supervised machine learning in spectral dimensionality reduction for hyperspectral imaging remote sensing

Spectral dimensionality reduction is a crucial step for hyperspectral image classification in practical applications. Dimensionality reduction has a strong influence on image classification performance with the problems of strong coupling features and high band correlation. To solve these issues, we propose the Mahalanobis distance–based kernel supervised machine learning framework for spectral dimensionality reduction. With Mahalanobis distance matrix–based dimensional reduction, the coupling relationship between features and the elimination of the scale effect are removed in low-dimensional feature space, which benefits the image classification. The experimental results show that compared with other methods, the proposed algorithm demonstrates the best accuracy and efficiency. The Mahalanobis distance–based multiples kernel learning achieves higher classification accuracy than the Euclidean distance kernel function. Accordingly, the proposed Mahalanobis distance–based kernel supervised machine learning method performs well with respect to the spectral dimensionality reduction in hyperspectral imaging remote sensing.
Vertical Integration and Zero-Rating Interplay: An Economic Analysis of Ad-Supported and Ad-Free Digital Content

ABSTRACT We discuss the economic impacts of the interplay between vertical integration and zero-rating for digital content. To this end, we develop a game-theoretic model that involves an Internet Service Provider (ISP), two competing content providers (CPs)—one an ad-supported CP, the other ad-free—and consumers. While previous studies have separately examined vertical integration and zero-rated content, none to our knowledge has explored the simultaneous interaction of both phenomena, which became apparent after the historic merger of AT&T and Time Warner. This vertical integration of an ISP and a CP has sparked an intense debate among policymakers and practitioners alike over the economic implications and consequent business practices (e.g., zero-rated content). The results of our analysis show that an ISP can generate higher profits after the merger with zero-rated content. Surprisingly, we find that the consumer valuation of the ad-free content significantly affects how the ISP will decide to maximize its profit. We extend our model to additionally consider the CPs’ partial sponsorship of their consumers’ data usage as well as the ISP’s different pricing schemes for its consumers and the CPs. Our analysis, which illustrates the various arrangements between vertical integration and zero-rated content, and our findings on consumer surplus and social welfare should be helpful to policymakers as well as to the ISPs, CPs, and consumers of digital content.
Richard Lester's Institutional‐Industrial Relations Model of Labor Markets and the Near‐Zero Minimum Wage Employment Effect: The Model Card and Krueger Ignored but Shouldn't Have

Abstract: David Card and Alan Krueger dedicate their minimum wage book Myth and Measurement (1995) to Richard Lester, an institutional‐industrial relations labor economist and key figure in the marginalist controversy of the 1940s. Lester claimed a minimum wage law's employment effect is likely zero or near‐zero, the same as Card and Krueger found a half‐century later, but they did not follow Lester's theoretical explanation and instead advanced a marginalist dynamic monopsony model. Numerous empirical studies have followed, with substantial evidence pointing to a relatively small and perhaps zero employment effect, but existing theoretical models, such as competitive, search, and monopsony, remain unable to provide a satisfactory explanation. Hence, to advance the minimum wage research program this article synthesizes and formalizes from Lester's writings an alternative institutionalist model of labor markets, represented in a set of five diagrams. The model provides considerable new insight and explanation for a zero/near‐zero employment effect, anchored on lack of a well‐defined labor demand curve, alternative cost‐absorbing managerial actions, and aggregate demand effect.
A Brief Review on the Application of Lanchester’s Models of Combat in Nonhuman Animals

Abstract The Lanchester models of combat were originally created for human warfare. These models were inspired by advances in technology and automatic weaponry at the turn of the 20th century. They parameterize army group size and individual fighting ability to explain the mortality rate of soldiers in a group during battle. In the last few decades, they have been applied to conflicts involving interactions between groups of nonhuman animals of varying degrees of sociality. This review focuses on the predictions and applications of Lanchester laws to nonhuman animal contests. Behavioral researchers have used the Lanchester models to interpret a variety of life history strategies and behaviors, such as colony fission in army ants, size differences in native versus non-native ants, recruitment behavior in chimpanzees, and dominance hierarchies in birds. These researchers assumed that the Lanchester laws apply qualitatively, and sometimes quantitatively, to the specific circumstances studied. To increase their biological realism, mathematical modifications have been proposed. While applications suggest that these laws may explain a multitude of social behaviors, there are surprisingly few empirical tests. Thus, further empirical data are needed to fully assess the accuracy of the models in predicting outcomes in nonhuman animals and their usefulness to biological systems.
CoSaMP

Compressive sampling (CoSa) is a new paradigm for developing data sampling technologies. It is based on the principle that many types of vector-space data are compressible, which is a term of art in mathematical signal processing. The key ideas are that randomized dimension reduction preserves the information in a compressible signal and that it is possible to develop hardware devices that implement this dimension reduction efficiently. The main computational challenge in CoSa is to reconstruct a compressible signal from the reduced representation acquired by the sampling device. This extended abstract describes a recent algorithm, called, CoSaMP, that accomplishes the data recovery task. It was the first known method to offer near-optimal guarantees on resource usage.
Chinese Stroke Association guidelines for clinical management of cerebrovascular disorders: executive summary and 2019 update of clinical management of intracerebral haemorrhage

Aim This evidence-based guideline aims to present current and comprehensive recommendations for the diagnosis and management of spontaneous intracerebral haemorrhage (ICH). Methods A formal literature search was conducted on MEDLINE (1 January 1990 to 30 June 2019). Data were synthesised using evidence tables. The members of the working group met by teleconference to update and formulate data-based recommendations. The recommendations are graded according to levels of evidence grading algorithm of the Chinese Stroke Association. The guideline draft has been reviewed by Chinese Stroke Association Stroke Council Guideline Writing Committee. Results Evidence-based guideline is proposed for the management of patients with ICH. The focus of the guideline is divided into the diagnosis and aetiology of ICH, management of ICH in emergency department, surgical treatment for removal of hematoma, management of complications and prevention of secondary ICH. Conclusions This guideline provides a framework for ICH management. Early active and reasonable treatment may improve the clinical outcome of patients.
Full snapshot reconstruction in hybrid architecture antenna arrays

In the context of this research work, we study the so-called problem of full snapshot reconstruction in hybrid antenna array structures that are utilized in mmWave communication systems. It enables the recovery of the snapshots that would have been obtained if a conventional (non-hybrid) uniform linear antenna array was employed. The problem is considered at the receiver side where the hybrid architecture exploits in a novel way the antenna elements of a uniform linear array. To this end, the recommended scheme is properly designed so as to be applicable to overlapping and non-overlapping architectures. Moreover, the full snapshot recoverability is addressed for two cases, namely for time-varying and constant signal sources. Simulation results are also presented to illustrate the consistency between the theoretically predicted behaviors and the simulated results, and the performance of the proposed scheme in terms angle-of-arrival estimation, when compared to the conventional MUSIC algorithm and a recently proposed hybrid version of MUSIC (H-MUSIC).
Hydrogen generation from biomass materials: challenges and opportunities

In this review, various processes for conversion of ligno(hemi)cellulosic biomass into hydrogen gas are comprehensively reviewed in terms of two main groups, namely (1) thermochemical processes [pyrolysis, catalytic pyrolysis, different gasification, co‐gasification, supercritical water gasification (SCWG)] and (2) biochemical‐cum‐biological conversions, along with electrolytic and photolytic processes. This review depicts much about the thermochemical processes for hydrogen production and its utilization via pyrolysis of biomass, gasification, gasification combined with pyrolysis, supercritical water (fluid‐gas) extraction, steam reforming (SR), auto thermal reforming (ATR), dry reforming (DR), liquid phase reforming (LPR), aqueous‐phase reforming (APR), and partial oxidation (POX) of renewable carboxylates such as bioethanol, acetic acid, phenol, glycerol, carbohydrates, different water‐soluble sugars, and bio‐oil, which are some of the areas to be explored for widespread awareness of hydrogen usage. Biomass‐based hydrogen production systems are emphasized and discussed in terms of their energetic and exergetic aspects with the help of reaction mechanisms. Different oxygenate compounds as derived from biomass with their potential catalyst tested by several literature studies and potential methods are then summarized. WIREs Energy Environ 2015, 4:139–155. doi: 10.1002/wene.111
A structured workshop enhanced Physiotherapists’ skills in clinical decision-making: A pre-post study

Context: Effective clinical decision-making skills enhance the quality of patient care. Clinical reasoning and decision-making are fundamental aspects of best physiotherapy clinical practice. Aims: To evaluate the effectiveness of an evidence-based structured educational workshop in enhancing physiotherapists’ clinical decision-making skills. Settings and Designs: A pre-post design conducted in a medical college Methods and Materials: A workshop protocol was developed based on the existing evidence and clinical practice guidelines. The workshop was advertised on the social media page of Nepal Physiotherapy association. On the first come first serve method; physiotherapists were selected. Those who met eligibility criteria were recruited for one of two workshops. Discussion was made on clinical scenarios aimed at enhancing clinical decision-making skills. Data were collected before and after the workshop using a self-administered clinical decision-making skills assessment tool to evaluate effectiveness of the workshop. Paired and unpaired t-tests were used to analyze within and between groups respectively. Results: Significant improvement in clinical decision-making skills was found for all individual items (P < 0.001 in all items, effect size: 0.6 – 0.9), total EP score (P < 0.001, effect size: 0.8) and total clinical decision-making score (P < 0.001, effect size: 0.9). A significant difference was found between Bachelor and Master level education (P < 0.05). Conclusions: An evidence-based structured educational workshop enhanced physiotherapists’ clinical decision-making skills. The findings of this study could be relevant to all health care professionals working in clinical practice. Larger studies with a control group are recommended to strengthen the findings of this study.
Functional repertoire of protein kinases and phosphatases in synaptic plasticity and associated neurological disorders

Protein phosphorylation and dephosphorylation are two essential and vital cellular mechanisms that regulate many receptors and enzymes through kinases and phosphatases. Ca2+- dependent kinases and phosphatases are responsible for controlling neuronal processing; balance is achieved through opposition. During molecular mechanisms of learning and memory, kinases generally modulate positively while phosphatases modulate negatively. This review outlines some of the critical physiological and structural aspects of kinases and phosphatases involved in maintaining postsynaptic structural plasticity. It also explores the link between neuronal disorders and the deregulation of phosphatases and kinases.
Bayesian estimation of pharmacokinetic parameters: an important component to include in the teaching of clinical pharmacokinetics and therapeutic drug monitoring

Bayesian estimation of pharmacokinetic parameters (PKP), as discussed in this review, provides a powerful approach towards the individualization of dosing regimens. The method was first described by Lewis Sheiner and colleagues and it is well suited in clinical environs where few blood fluid measures of drugs are available in the clinic. This makes it a valuable tool in the effective implementation of therapeutic drug monitoring. The principle behind the method is Bayes theorem, which incorporates elements of variability in a priori-known population estimates and variability in the pharmacokinetic parameters, and known errors intrinsic to the assay method used to estimate the blood fluid drug concentrations. This manuscript reviews the Bayesian method. The literature was scanned using Pubmed to provide background into the Bayesian method. An Add-in for Excel program was used to show the ability of the method to estimate PKP using sparse blood fluid concentration vs time data. Using a computer program, the method was able to find reasonable estimates of individual pharmacokinetic parameters, assessed by comparing the estimated data to the true PKP. Education of students in clinical pharmacokinetics is incomplete without some mention and instruction of the Bayesian forecasting method. For a complete understanding, a computer program is needed to demonstrate its utility.
Entacapone promotes hippocampal neurogenesis in mice

Entacapone, a catechol-O-methyltransferase inhibitor, can strengthen the therapeutic effects of levodopa on the treatment of Parkinson’s disease. However, few studies are reported on whether entacapone can affect hippocampal neurogenesis in mice. To investigate the effects of entacapone, a modulator of dopamine, on proliferating cells and immature neurons in the mouse hippocampal dentate gyrus, 60 mice (7 weeks old) were randomly divided into a vehicle-treated group and the groups treated with 10, 50, or 200 mg/kg entacapone. The results showed that 50 and 200 mg/kg entacapone increased the exploration time for novel object recognition. Immunohistochemical staining results revealed that after entacapone treatment, the numbers of Ki67-positive proliferating cells, doublecortin-positive immature neurons, and phosphorylated cAMP response element-binding protein (pCREB)-positive cells were significantly increased. Western blot analysis results revealed that treatment with tyrosine kinase receptor B (TrkB) receptor antagonist significantly decreased the exploration time for novel object recognition and inhibited the expression of phosphorylated TrkB and brain-derived neurotrophic factor (BDNF). Entacapone treatment antagonized the effects of TrkB receptor antagonist. These results suggest that entacapone treatment promoted hippocampal neurogenesis and improved memory function through activating the BDNF-TrkB-pCREB pathway. This study was approved by the Institutional Animal Care and Use Committee of Seoul National University (approval No. SNU-130730-1) on February 24, 2014.