Miracle-dz/UniFAR-FTUs huggingface dataset:
A synergistic effect of copper and nickel ions on the growth ratesofPseudomonas aeroginosa andStaphylococcusaureusisolates

Two isolates of bacteria : Pseudomonas aeroginosa and Staphylococcus aureus were exposed to different concentrations ( 25, 50 and 100 ppm ) of copper and nickel ions (as single and mixed ),and growth rate of these isolates were measured after different exposure periods of ( 0 , 2 , 4 , 24 and 72) hrs. The results were showed that the effect of ions on the growth rate of these isolates were depending on ion type , concentration of ions in the medium , the nature of medium ( solid or liquid ) , the group of bacteria( Gram or Gram ) , and the periods of exposure . Also , the results were showed a synergistic effect caused by the mixture of the two metals ions on the growth rate of these isolates , and this effect including an elongation in the lag phase , decreasing of colonies numbers and colonies diameter , and dead of bacteria according to the ions concentration in the medium .
SINGLE-NEURON CONVEXIFICATION FOR BINARIZED NEURAL NETWORKS

Binarized neural networks are an important class of neural network in deep learning due to their computational eﬃciency. This paper contributes towards a better understanding of the structure of bi-narized neural networks, speciﬁcally, ideal convex representations of the activation functions used. We describe the convex hull of the graph of the signum activation function associated with a single neuron, deriving closed forms for the convex and concave envelopes that improve upon those used in the literature. The new formulations lead to improved methods to verify the robustness of a binarized neural network via convex optimization.
An Open-source Model for Simulation and Corrective Measure Assessment of the 2021 Texas Power Outage

Unprecedented winter storms that hit across Texas in February 2021 have caused at least 4.5 million customers to experience load shedding due to the wide-ranging generation capacity outage and record-breaking electricity demand. While much remains to be investigated on what, how, and why such wide-spread power outages occurred across Texas, it is imperative for the broader research community to develop insights based on a coherent electric grid model and data set. In this paper, we collaboratively release an open-source large-scale baseline model that is synthetic but nevertheless provides a realistic representation of the actual energy grid, accompanied by open-source cross-domain data sets. Leveraging the synthetic grid model, we reproduce the blackout event and critically assess several corrective measures that could have mitigated the blackout under such extreme weather conditions. We uncover the regional disparity of load shedding. The analysis also quantifies the sensitivity of several corrective measures with respect to mitigating the power outage, as measured in energy not served (ENS). This approach and methodology are generalizable for other regions experiencing significant energy portfolio transitions.
UNVEILING THE ORIGIN OF GRB090709A: LACK OF PERIODICITY IN A REDDENED COSMOLOGICAL LONG-DURATION GAMMA-RAY BURST

We present broadband (gamma-ray, X-ray, near-infrared, optical, and radio) observations of the gamma-ray burst (GRB) 090709A and its afterglow in an effort to ascertain the origin of this highenergy transient. Previous analyses suggested that GRB090709A exhibited quasi-periodic oscillations with a period of 8.06 s, a trait unknown in long-duration GRBs but typical of flares from soft gammaray repeaters. When properly accounting for the underlying shape of the power-density spectrum of GRB090709A, we find no conclusive (> 3σ) evidence for the reported periodicity. In conjunction with the location of the transient (far from the Galactic plane and absent any nearby host galaxy in the local universe) and the evidence for extinction in excess of the Galactic value, we consider a magnetar origin relatively unlikely. A long-duration GRB, however, can account for the majority of the observed properties of this source. GRB090709A is distinguished from other long-duration GRBs primarily by the large amount of obscuration from its host galaxy (AK,obs & 2mag). Subject headings: gamma rays: bursts – stars: neutron
Is Transparency Good For You?

In this paper we show that those countries that have increased the quality and quantity of information released to markets since the emerging market crises of the 1990s have experienced an economically important decline in borrowing costs. We show this using data from a natural experiment generated when the IMF created three new ways for member countries to increase their transparency. We use two-stage least-squares to address endogeneity in the timing of reforms, exploiting internal IMF timetables that influenced the timing of adoption of the reforms but are unrelated to country events. We then examine some of the mechanisms by which transparency can affect spreads. We present a simple theoretical model illustrating how transparency can help solve a moral hazard problem or allow countries to signal their quality. Using high frequency data and a multi-country panel GARCH news effect methodology, we show these reforms led to better informed markets. We also find evidence that is consistent with the moral hazard version of our model, and other evidence that is inconsistent with the case where signaling leads to a loss in world output. The authors would like to thank Abhijit Banerjee, Charis Christofides, Przemek Gajdeczka, Bryan Graham, Simon Johnson, Michael Kremer, Paolo Mauro, Ydahlia Metzgen, Christian Mulder, Ron Smith, Antonio Spilimbergo, Andrew Tiffin, and seminar participants at the IMF, and Harvard University for useful comments, Erkut Kucukboy for research assistance. Rachel Glennerster would like to thank John Hicklin and Ydahlia Metzgen for giving her the time to undertake this research. 1 Rachel Glennerster is a staff member of the International Monetary Fund. She is currently on leave from the Policy Development and Review Department and is Executive Director of the Poverty Action Lab at the Massachusetts Institute of Technology, rglenner@mit.edu. The views expressed here are the authors and do not necessarily reflect those of the IMF. 2 Yongseok Shin is an assistant professor at the University of Wisconsin yshin@ssc.wisc. edu.
Efficient Resource-Constrained Monitoring

Monitoring network traffic is an important building block for various management and security systems. Typically, the number of active flows in a network node is much larger than the number of available monitoring resources, making it imprac-tical to maintain a "per-flow" state at the node. This situation gave rise to the recent interest in streaming algorithms where complex data structures are used to perform monitoring tasks efficiently. However, these solutions often require complicated "per-packet" operations, which are not feasible in current devices line-rate. Even when the amortized (expected average) complexity is O(1) operations per-packet, some packets may experience a much longer delay, which again is impractical. In this dissertation we study three important monitoring problems (that were recently studied in the context of streaming algorithms) and for each of them we present practical, efficient resource-constrained algorithms.
The implications of a changing academic workforce for the university as a critical institution (0047)

The paper will re-examine the findings of a study funded by the UK Higher Education Academy (HEA) on changing academic roles, careers and development needs, within a conceptual frame of the critical university. The study identified a number of gaps between the perceptions of individuals and institutional policies about, for instance, criteria for promotion and development opportunities. In this paper, it will be argued that sustaining a critical workspace is likely to involve, for instance, clarity about the basis for decision making around individual careers; judgements about the appropriate use of evidence such as student feedback; and a willingness to consider alternative options in relation to professional development. The paper will demonstrate ways in which institutional middle managers such as heads of department have a key role to play in creating and sustaining this space for criticality.
Strategical Survey of Wireless Based Target Detection and Classification System Using seismic and PIR Sensors

Wireless based target detection can also be used to detect the vehicles and human or animals. These systems are usually lightweight devices that automatically monitor the local activities in-situ, and transfer target detection and classification reports to the processing center through wireless. It is necessary that the monitoring system at borders must prove to be more efficient. This system based on Seismic sensor and PIR sensor is designed to find the target which is moving on the ground. Ref[1,2,3,4] In the existing system the Unattended Ground Sensors are used in target detection. The efficiency of the existing system is limited by false alarm rates. Also power consumption becomes a consideration in the existing system. In the proposed system PIR and seismic sensors are used in target detection. The PIR Sensor is used to track down whether the moving object is living body or machine. If it is living body, the seismic sensor is used to track down whether it is human being or animal based on the absorbed signals. If it is vehicle, then seismic sensor is used to classify the type of vehicle moving on the ground. All these process are monitored and controlled using PIC16F877A microcontroller. The status is sent through GSM as a message to the Mobile Section. © 2014 Elixir All rights reserved. ARTICLE INF O Articl e h istory: Received: 2 May 2013; Received in revised form: 15 October 2014; Accepted: 28 October 2014;
Inhibiting IL-6 During Cytokine Storm in COVID-19: Potential Role of Natural Products

Plant species with anti-inflammatory properties might play an essential role in combatting COVID-19 via reducing cytokine storms. We aimed to review the extant evidence of the potential therapeutic efficacy of natural products against cytokine storms by inhibiting interleukin-6 (IL-6) as a major pathological mediator. Data were collected following an electronic search in major databases (Pubmed, Scopus, Web of Science, Google Scholar) and also preprint articles on preprint and medRxiv servers by using a combination of relevant keywords. Seventeen active compounds and medicinal plants were found and reviewed in the present review. Results of both in-vivo and in-vitro experiments conducted on these compounds showed that Phillyrin, SMFM, Qiangzhi decoction, curcumin, Shen-Fu, Forsythia, and Alpha-Mangostin inhibit the production of IL-6. Andrographolide and Liu Shen Wan have an inhibitory effect on releasing this agent, while Ilex Asprella and Deoxy-11,12-didehydroandrographolide and naringin reduce the expression of IL-6. Theaflavin and Cholorogenic acid inhibit the secretion of IL-6, Xuebijing, and Chai-Hu-Gui-Zi-Gan-Jiang-Tang and Lipanpaidu prescription can reduce the serum level of IL-6. These agents also effectively improve infected lungs, increase survival rates, and minimize tissue damage. Medicinal plants and their phytochemical ingredients with down-regulatory effects on the expression of IL-6 have a potential influence on the inhibition of cytokine storms during viral infection caused by COVID-19. Therefore, phytochemicals could be regarded as promising candidates for managing cytokine storm inflammatory responses due to COVID-19 infection.
Predicting Localized Primordial Star Formation with Deep Convolutional Neural Networks

We investigate applying 3D deep convolutional neural networks as fast surrogate models of the formation and feedback effects of primordial stars in hydrodynamic cosmological simulations of the first galaxies. Here, we present the surrogate model to predict localized primordial star formation; the feedback model will be presented in a subsequent paper. The star formation prediction model consists of two submodels: the first is a 3D volume classifier that predicts which (10 comoving kpc)3 volumes will host star formation, followed by a 3D Inception-based U-net voxel segmentation model that predicts which voxels will form primordial stars. We find that the combined model predicts primordial star-forming volumes with high skill, with F 1 > 0.995 and true skill score (TSS) >0.994. The star formation is localized within the volume to ≲53 voxels (∼1.6 comoving kpc3) with F 1 > 0.399 and TSS >0.857. Applied to simulations with low spatial resolution, the model predicts star-forming regions in the same locations and at similar redshifts as sites in resolved full-physics simulations that explicitly model primordial star formation and feedback. When applied to simulations with lower mass resolution, we find that the model predicts star-forming regions at later redshift due to delayed structure formation resulting from lower mass resolution. Our model predicts primordial star formation without halo finding, so it will be useful in spatially under-resolved simulations that cannot resolve primordial star-forming halos. To our knowledge, this is the first model that can predict primordial star-forming regions that match highly resolved cosmological simulations.
Endobronchial ultrasound-guided transbronchial needle aspiration combined with either endoscopic ultrasound-guided fine-needle aspiration or endo- scopic ultrasound using the EBUS scope-guided fine-needle aspiration for diagnosing and staging mediastinal diseases: a systematic review and meta- analy

The present systematic review and meta-analysis aimed to evaluate the available evidence base on endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) combined with either endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) or endoscopic ultrasound using the EBUS scopeguided fine-needle aspiration (EUS-B-FNA) for diagnosing and staging mediastinal diseases. PubMed, Web of Science, and Embase were searched to identify suitable studies up to June 30, 2019. Two investigators independently reviewed articles and extracted relevant data. Data were pooled using random effect models to calculate diagnostic indices that included sensitivity and specificity. Summary receiver operating characteristic (SROC) curves were used to summarize the overall test performance. Data pooled from up to 16 eligible studies (including 10 studies of 963 patients about EBUS-TBNA with EUSFNA and six studies of 815 patients with EUS-B-FNA) indicated that combining EBUS-TBNA with EUS-FNA was associated with slightly better diagnostic accuracy than combining it with EUS-B-FNA, in terms of sensitivity (0.87, 95%CI 0.83 to 0.90 vs. 0.84, 95%CI 0.80 to 0.88), specificity (1.00, 95%CI 0.99 to 1.00 vs. 0.96, 95%CI 0.93 to 0.97), diagnostic odds ratio (413.39, 95%CI 179.99 to 949.48 vs. 256.38, 95%CI 45.48 to 1445.32), and area under the SROC curve (0.99, 95%CI 0.97 to 1.00 vs. 0.97, 95%CI 0.92 to 1.00). The current evidence suggests that the combination of EBUS-TBNA with either EUS-FNA or EUS-B-FNA provides relatively high accuracy for diagnosing mediastinal diseases. The combination with EUS-FNA may be slightly better.
NSS_A_287165 547..556

1Department of Neurology, Clinica Nueva Rafael, Cali, Valle del Cauca, Colombia; 2Department of Neurology, Fundación Cardioinfantil, Bogotá, Cundinamarca, Colombia; 3Department of Neurology, Hospital Mederi, Bogotá, Cundinamarca, Colombia; 4Grupo de Neurociencias de la Universidad del Rosario (NEUROS), Universidad del Rosario, Bogotá, Cundinamarca, Colombia; 5Department of Biology, Faculty of Natural Sciences, Universidad del Rosario, Bogotá, Colombia; 6Clinical Research Group, School of Medicine and Health Sciences, Universidad del Rosario, Bogotá, Cundinamarca, Colombia; 7Neurology department, School of Medicine and Health Sciences, Bogotá, Cundinamarca, Colombia Purpose: Obstructive sleep apnea (OSA) is a common sleep disorder which prevalence is 22% in men and 17% in women. It is well described that females presented different clinical and polysomnographic characteristics compared with men. Those studies were performed in plain areas. We described the analysis by gender and clinical profiles of a sample of patients with diagnostic of OSA and living at high altitude. Patients and Methods: It is an observational study that describes differences between clinical and polysomnographic characteristics by gender in patients with OSA. Additionally, an unsupervised cluster algorithm was used to find groups of patients with similar clinical and polysomnographic characteristics. Results: We included 709 patients, 51.6% were females and 48.3% were males with mean age of 64 and 62 years old, respectively, in which 90.97% presented OSA. Men presented a higher apnea and hypopnea index than women (p=0.002), besides presented more sleep polysomnographic alterations. Meanwhile, women evidenced better sleep quality based on parameters. Additionally, in the sample of patients, we found four separated clinical profiles characterized mainly by differences in the severity of polysomnographic parameters. Conclusion: The patients were more obese, older, and had lower SpO2 values than most of those previously reported. Men had greater severity in most of the parameters measured by polysomnography. Polysomnographic variables were different both in the OSA patient profiles and in the gender comparison. However, the REM sleep apnea hypopnea index did not differ between sexes, indicating the importance of this variable in the evaluation of OSA severity in women. In contrast to previous reports, clinical and demographic characteristics showed few differences in both analyses. This result suggests that the behavior of OSA at high altitudes may have particularities with respect to low altitudes.
The Effect of Sarbanes-Oxley Act on CFO Compensation and Rank

We examine the increasing prominence of CFOs in the executive suite in relation to the passage of Sarbanes-Oxley Act (SOX) and provide insight into three related questions: the level of CFO compensation and rank, the likelihood of the CFO being in the top five highest paid executives, and the relationship between CFO pay and performance. We find that CFO compensation and the compensation rank within the set of top five highest paid executives exhibit an increasing trend over the 1994-2006 period. The logistic regression analysis on the S&P 1,500 firms reveals that the probability of the CFO being in the top five is larger post–SOX controlling for the firm characteristics and board structure. In the OLS regressions on CFO compensation that control for the time trend and the unobserved industry characteristics along with firm characteristics and governance structure, the coefficients on the Post_SOX dummy is positive and significant at the conventional levels. Based on the CFO responsibilities on communicating effectively with analysts and the investing community, we proxy for CFO performance with the dispersion in analyst forecasts and earnings surprises. When we examine the effect of CFO-specific performance variables on CFO pay, we find that CFO compensation is positively related to earnings surprises and negatively related to the dispersion in analyst forecasts.
Creating a Physicist: The Impact of Informal Physics Programs on University Student Development

Physics outreach programs provide a critical context for informal experiences that promote the transition from new student to contributing physicist. Prior studies have suggested a positive link between participation in informal physics outreach programs and the development of a student’s physics identity. In this study, we adopt a student-focused investigation to explore the effects of informal programs on dimensions of physics identity, sense of community, 21st century skill development, and motivation. We employed a mixed methods study combining a survey instrument (117 responses) and interviews (35) with current and former undergraduate and graduate students who participated in five programs through a physics and astronomy department at a large landgrant university. To examine interviews, we employed a framework based on situated learning theory, transformative learning theory, and the Dynamic Systems Model of Role Identity. Our findings, based on self-reported data, show that students who facilitated informal physics programs positively developed their physics identity, experienced increased sense of belonging to the physics community, and developed 21st century career skills. Specifically, students reported positive benefits to their communication, teamwork and networking, and design skills. The benefits of these programs can be achieved by departments of any size without significant commitment of funds or changes to curriculum.
DMSO_A_274413 3919..3924

*These authors contributed equally to this work Background: Previous studies have reported that patients with diabetes mellitus (DM) have a higher incidence of cognitive decline and an increased risk of developing all types of dementia. The aim was to elucidate the association between serum human epididymal protein 4 and cognitive function in patients with DM. Methods: Serum levels of HE4 were measured in 205 patients with DM. All DM patients were followed up for a median period of 48 months (range=5–49) prospectively. Cox proportional hazard analysis was used to evaluate the predictive value of serum HE4 for predicting cognitive decline (end point). Results: Multivariate linear regression analysis revealed that serum HE4 was independently associated with MOCA score after adjusting for age, gender, BMI, current smoker, current drinker, admission systolic and diastolic BP, CVD history and laboratory measurements in patients with DM at baseline (Sβ= −0.120; 95% CI, −0.151– −0.069; P<0.001). The multivariate Cox proportional hazard analysis revealed that serum HE4 (HR=2.408, 95% CI 1.669–5.238, P<0.001) was an independent prognostic factor for cognitive decline in these DM patients. Conclusion: Our results showed that serum HE4 was significantly and independently associated with cognitive decline and had independent predictive value for cognitive decline in patients with DM. Serum HE4 might enable early recognition of senile dementia among DM patients.
Superpixel-Based Filtering for Image Noise Reduction

—The paper presents a superpixel-based image filtering algorithm for additive white Gaussian noise (AWGN) reduction. The algorithm processes an image by connected homogeneous regions of small size (superpixels). Each superpixel is restored using the least squares method. The mean square error (MSE) between a reconstructed image and an ideal image provided by the proposed algorithm is compared with the MSE provided by the Wiener filter. The experimental part shows that the proposed superpixel filtering algorithm outperforms the Wiener filter, providing lower MSE values.
Dynamic Repositioning in Free-Floating Bike Sharing Systems Using Approximate Dynamic Programming

In bike sharing systems, the spatiotemporal imbalance of bike flows leads to shortages of bikes in some areas and overages in some others, depending on the time of the day, resulting in user dissatisfaction. Repositioning needs to be performed timely to deal with the spatiotemporal imbalance and to meet customer demand in time. In this paper, we study the dynamic repositioning of bikes under stochastic demand in free-floating bike sharing systems. Considering that customers can drop off bikes almost anywhere in free-floating systems, we study the simultaneous reposition of bikes among gathering points and collection of scattered bikes. We formulate the problem as a Markov Decision Process (MDP), design a policy function approximation (PFA) algorithm, and apply the optimal computing budget allocation (OCBA) method to search for the optimal policy parameters. We perform a comprehensive numerical study, which demonstrates the outperformance of the proposed PFA policy against the benchmark policies and the practical implications on the value of repositioning and the impact of bike scatteredness.