Miracle-dz/UniFAR-FTUs huggingface dataset:
The Emergence of Mupirocin Resistance among Staphylococcus aureus in a Tertiary Care Hospital in South India: The Necessity for Routine Susceptibility Testing

Methicillin-resistant Staphylococcus aureus (MRSA) is difficult to treat, causing considerable morbidity and mortality. Nasal carriage of MRSA can occur both in healthcare workers and patients. Mupirocin is used as a topical agent for the eradication of such isolates. The present study aims to study the prevalence of mupirocin resistance among the MRSA and MSSA (Methicillin-sensitive Staphylococcus aureus) isolates. A total of 148 Staphylococcus aureus isolates were tested. Antibiotic susceptibility testing was done by Kirby Bauer disc diffusion method for amoxicillin, penicillin, cotrimoxazole, clindamycin, mupirocin(5 µg and 200 µg discs for low and high-level resistance), erythromycin, gentamicin and linezolid. MRSA isolates were detected by cefoxitin disc diffusion and Mec A detection by PCR (Polymerase Chain Reaction). MRSA was detected among 44 (29.7%) of the isolates. Among MSSA, good susceptibility was observed for cotrimoxazole 89 (85.5%) and clindamycin 92 (88.4%). An overall mupirocin resistance of 12(8.1%) was observed, with high-level resistance at 4 (2.7%) and low-level resistance at 8 (5.4%). The mupirocin resistance pattern between MRSA and MSSA was not statistically significant (p=0.1833). The emergence of mupirocin resistance highlights the necessity for creating cognizance among clinicians before prescribing mupirocin. In eradicating nasal carriage of MRSA, all the isolates should always be tested for mupirocin susceptibility to prevent the selection and spread of drug-resistant isolates.
Transformer-Based Detection for Highly Mobile Coded OFDM Systems

This paper is concerned with mobile coded orthogonal frequency division multiplexing (OFDM) systems. In the high-speed railway wireless communication system, an equalizer or detector should be used to mitigate the intercarrier interference (ICI) and deliver the soft message to the decoder with the soft demapper. In this paper, a Transformer-based detector/demapper is proposed to improve the error performance of the mobile coded OFDM system. The soft modulated symbol probabilities are computed by the Transformer network, and are then used to calculate the mutual information to allocate the code rate. Then, the network computes the codeword soft bit probabilities, which are delivered to the classical belief propagation (BP) decoder. For comparison, a deep neural network (DNN)-based system is also presented. Numerical results show that the Transformer-based coded OFDM system outperforms both the DNN-based and the conventional system.
Effects of Community Connectivity on the Spreading Process of Epidemics

Community structure exists widely in real social networks. To investigate the effect of community structure on the spreading of infectious diseases, this paper proposes a community network model that considers both the connection rate and the number of connected edges. Based on the presented community network, a new SIRS transmission model is constructed via the mean-field theory. Furthermore, the basic reproduction number of the model is calculated via the next-generation matrix method. The results reveal that the connection rate and the number of connected edges of the community nodes play crucial roles in the spreading process of infectious diseases. Specifically, it is demonstrated that the basic reproduction number of the model decreases as the community strength increases. However, the density of infected individuals within the community increases as the community strength increases. For community networks with weak strength, infectious diseases are likely not to be eradicated and eventually will become endemic. Therefore, controlling the frequency and range of intercommunity contact will be an effective initiative to curb outbreaks of infectious diseases throughout the network. Our results can provide a theoretical basis for preventing and controlling the spreading of infectious diseases.
Treatment-Altered VEGF-Associated Network in GBM BVZ-Responsive Subtypes: Bioinformatics Case Studies

Objective: As an anti-angiogenetic treatment, bevacizumab (BVZ) therapy for GBM patients targets vascular endothelial growth factor A (VEGF), which can significantly reduce tumor sizes in the early stage based on imaging studies. However, the related mechanism of the VEGF-associated network has not yet been elucidated. Recently, subtypes of GBM BVZ response were classified and detected, so the treatment effects and related mechanisms could be reassessed individually for these different subtypes. In this study, we want to further explore possible mechanisms, effects
Mathematical Optimization on Hybrid Channel Pricing Digital Products in Two-Sided Market with Network Effect

In the two-sided market where the third-party platforms connect the providers and consumers, the online platforms become the significant distribution channel of digital products; therefore, the digital product firms face the hybrid channel pricing problem in the two-sided market in which the products are launched through the platform channel and the existing direct channel. Because the network externality effect is the significant economic characteristic of digital products and services, the current work presents the models of consumers’ utility obtained by adopting digital products from the direct and platform channels, and the utility models use the network effect in the direct and platform channels as the parameters. The optimization model on pricing is derived from the utility models and solved mathematically. The closed-form solutions show that the price in the direct channel is supposed to be lower than that in the platform channel, while the prices of digital products would be affected by the network effect only when the products are distributed through the direct channel. The comparative statics analysis on the network effect illustrates that the network effect in the direct channel and the platform channel would, respectively, have the positive and negative impact on the products’ prices and the firms’ profit. The current work explores the hybrid channel pricing problem and provides insights for the digital product firms on the optimal pricing decision in the context of the emerging platform economy.
DAC Linearization Techniques for Sigma-delta Modulators

DAC Linearization Techniques for Sigma-delta Modulators. (December 2011) Akshay Godbole, B.E. , Birla Institute of Technology & Science, Pilani Co-Chairs of Advisory Committee: Dr. Jose Silva-Martinez Dr. Aydin I. Karsilayan Digital-to-Analog Converters (DAC) form the feedback element in sigma-delta modulators. Any non-linearity in the DAC directly degrades the linearity of the modulator at low and medium frequencies. Hence, there is a need for designing highly linear DACs when used in high performance sigma-delta modulators. In this work, the impact of current mismatch on the linearity performance (IM3 and SQNR) of a 4-bit current steering DAC is analyzed. A selective calibration technique is proposed that is aimed at reducing the area occupancy of conventional linearization circuits. A statistical element selection algorithm for linearizing DACs is proposed. Current sources within the required accuracy are selected from a large set of current sources available. As compared with existing calibration techniques, this technique achieves higher accuracy and is more robust to variations in process and temperature. In contrast to existing data weighted averaging techniques, this technique does not degrade SNR performance of the ADC. A 5 th order, 500 MS/s, 20 MHz sigmadelta modulator macro-model was used to test the linearity of the DAC.
A First Course in Mathematical Logic and Set Theory

If you are looking for a book by Michael L. O'Leary A First Course in Mathematical Logic and Set Theory in pdf form, in that case you come on to correct website. We present complete version of this ebook in txt, DjVu, doc, PDF, ePub forms. You may read by Michael L. O'Leary online A First Course in Mathematical Logic and Set Theory either downloading. In addition to this book, on our website you may read the manuals and another art books online, or downloading them as well. We like to draw on consideration what our website not store the book itself, but we provide ref to website whereat you may load or read online. If you want to downloading A First Course in Mathematical Logic and Set Theory pdf by Michael L. O'Leary, then you've come to faithful site. We own A First Course in Mathematical Logic and Set Theory txt, doc, PDF, ePub, DjVu formats. We will be pleased if you return to us again and again.
Generalized exponential geometric extreme distribution

Recently, Louzada et al. proposed a new three-parameter distribution with decreasing, increasing, and unimodal hazard functions. They have provided several properties of the distribution, and discussed different inferential issues. In this article we discuss a generalized version of the model following the approach of Marshall and Olkin. The proposed model is more flexible than the Louzada-Marchi-Roman model, although they have the same number of parameters. The model has three unknown parameters, and the hazard function can take different shapes. We propose using the expectation-maximization (EM) algorithm to compute the maximum likelihood estimators of the unknown parameters. We further consider the bivariate generalization of the proposed model and discuss its different properties. The EM algorithm can be used to estimate the unknown parameters in case of the bivariate model also. One bivariate data set has been analyzed for illustrative purposes, and the performance is quite satisfactory.
Properties of right Haar predictive inference

Consider an invariant prediction problem where the group is transitive on the parameter space. The Haar predictive distribution (Haar inference) is obtained as the formal predictive distribution using the right Haar measure as a prior. This Haar inference is discussed in three different contexts: model matching, Fisherian pivoting, and de Finetti's coherence. It, is shown that the Haar inference enjoys exact probability matching for highest probability density (HPD) regions. Fisherian pivotal distributions agree with Haar inference when pivoting is possible. Further any invariant inference that is essentially different from the Haar inference is incoherent.
Modeling of Wave Impact Using a Pendulum System

Modeling of Wave Impact Using a Pendulum System. (May 2010) Chunyong Nie, B.S., Harbin Engineering University Chair of Advisory Committee: Dr. John M. Niedzwecki For high speed vessels and offshore structures, wave impact, a main source of environmental loads, causes high local stresses and structural failure. However, the prediction of wave impact loads presents numerous challenges due to the complex nature of the instant structure-fluid interaction. The purpose of the present study is to develop an effective wave impact model to investigate the dynamic behaviors of specific shaped elements as they impact waves. To achieve this objective, a wave impact model with a body swinging on a pendulum system is developed. The body on the pendulum goes through a wave free surface driven by gravity at the pendulum’s natural frequency. The system’s motion and impact force during the entire oscillation time beginning from the instant of impact are of interest. The impact force is calculated by applying von Karman’s method, which is based on momentum considerations. The usual wave forces are presented in the Morison’s equation and incorporated into dynamic systems with other wave forces. For each body shape, the dynamic system is described by a strongly nonlinear ordinary differential equation and then solved by a Runge-Kutta differential equation solver. The dynamic response behavior and the impact force time history are obtained numerically and the numerical results show support the selection of a pendulum
Mechanical Stability and Sticking in a Model Microelectromechanical systems (MEMS) under Casimir Forces–Part II: The Role of the Casimir Effect

Mechanical stability and sticking are the troublesome problems in the microfabrication process and operating when components in MEMS working in the sub-micrometer regime. In this paper, the analysis of the role of the Casimir effect on a membrane strip structure is presented. With nothing other than the Casimir force loading the strip, there exist a stable static equilibrium state and an unstable static equilibrium state. The state can be determined by the value of dimensionless constant K. The membrane strip will collapse if Κ is larger than the critical value of Kc. The critical value of Kc varies with the value of w0. This provides a way to check if a system of given dimensions and material properties will have a stable equilibrium position in the absence of other forces, such as an electrostatic actuation force, or a capillary force during and after the wet etching of a sacrificial layer. This also provides a way to design a membrane strip with high aspect ratio (L/h) that is not easily to collapse into the surface S.
Optimum k-Nearest Neighbors for Heading Synchronization on a Swarm of UAVs under a Time-Evolving Communication Network

Heading synchronization is fundamental in flocking behaviors. If a swarm of unmanned aerial vehicles (UAVs) can exhibit this behavior, the group can establish a common navigation route. Inspired by flocks in nature, the k-nearest neighbors algorithm modifies the behavior of a group member based on the k closest teammates. This algorithm produces a time-evolving communication network, due to the continuous displacement of the drones. Nevertheless, this is a computationally expensive algorithm, especially for large groups. This paper contains a statistical analysis to determine an optimal neighborhood size for a swarm of up to 100 UAVs, that seeks heading synchronization using a simple P-like control algorithm, in order to reduce the calculations on every UAV, this is especially important if it is intended to be implemented in drones with limited capabilities, as in swarm robotics. Based on the literature of bird flocks, that establishes that the neighborhood of every bird is fixed around seven teammates, two approaches are treated in this work: (i) the analysis of the optimum percentage of neighbors from a 100-UAV swarm, that is necessary to achieve heading synchronization, and (ii) the analysis to determine if the problem is solved in swarms of different sizes, up to 100 UAVs, while maintaining seven nearest neighbors among the members of the group. Simulation results and a statistical analysis, support the idea that the simple control algorithm behaves like a flock of starlings.
Data in Brief

We present a multi-sensor dataset of bimanual human-to-human object handovers. The dataset consists of 240 recordings obtained from 12 pairs of participants performing bi-manual object handovers with 10 objects, and 120 recordings obtained from the same 12 pairs of participants performing unimanual handovers with 5 of those objects. Each recording includes the giver and receiver’s 13 upper-body bone position and orientation trajectories, position trajectories for the 27 markers placed on their upper bodies, object position and orientation trajectories, and two RGB-D data streams. The motion trajectories are recorded at 120Hz and the RGB-D streams are recorded at 30Hz. The recordings are annotated with the three handover phases: reach, transfer, and retreat. The dataset also includes four anthropometric measurements of the participants: height, waistline height, arm span, and weight. Our dataset could help investigations of the bimanual reaching motions and grasps utilized by humans while performing handovers. Also, it can be used to train robots to perform bimanual object handovers with humans.
Cross-Viewpoint Semantic Mapping: Integrating Human and Robot Perspectives for Improved 3D Semantic Reconstruction

Allocentric semantic 3D maps are highly useful for a variety of human–machine interaction related tasks since egocentric viewpoints can be derived by the machine for the human partner. Class labels and map interpretations, however, may differ or could be missing for the participants due to the different perspectives. Particularly, when considering the viewpoint of a small robot, which significantly differs from the viewpoint of a human. In order to overcome this issue, and to establish common ground, we extend an existing real-time 3D semantic reconstruction pipeline with semantic matching across human and robot viewpoints. We use deep recognition networks, which usually perform well from higher (i.e., human) viewpoints but are inferior from lower viewpoints, such as that of a small robot. We propose several approaches for acquiring semantic labels for images taken from unusual perspectives. We start with a partial 3D semantic reconstruction from the human perspective that we transfer and adapt to the small robot’s perspective using superpixel segmentation and the geometry of the surroundings. The quality of the reconstruction is evaluated in the Habitat simulator and a real environment using a robot car with an RGBD camera. We show that the proposed approach provides high-quality semantic segmentation from the robot’s perspective, with accuracy comparable to the original one. In addition, we exploit the gained information and improve the recognition performance of the deep network for the lower viewpoints and show that the small robot alone is capable of generating high-quality semantic maps for the human partner. The computations are close to real-time, so the approach enables interactive applications.
Sputter yield of curved surfaces

The mean sputter yield produced by the impact of a single ion depends on the radii of curvature of the target surface at the point of impact. Using the Sigmund model of ion sputtering, we develop analytical formulas for this dependence for the case in which the radii of curvature are large compared to the size of the ion-induced collision cascade; both locally perpendicular and oblique ion impact are considered. The sputter yield is increased for impact on convex surfaces. The influence of surface curvature along the incident-ion azimuth and perpendicular to it are discussed separately. Our analytical results are in good agreement with Monte Carlo simulations for the specific case of 20 keV Ar ion impact on a cylindrical nanowire consisting of amorphous silicon. We also extend the results for this case to small radii of curvature using both Monte Carlo and molecular dynamics simulations.
Controversial debates about workforce nationalisation: Perspectives from the Qatari higher education industry

ABSTRACT Workforce nationalisation in the Gulf Corporation Council (GCC) countries is a crucial challenge for their development plans. The current study explores controversial debates about workforce nationalisation to understand the existing threats from the views of less examined key stakeholders, namely, educators and senior students. The study argues that the identified obstacles relate not only to policy flaws but also to the education – employability gap, phantom employment, and detrimental social and community perceptions. Given its exploratory nature, the study adopts a qualitative approach and uses 28 semi-structured interviews to identify critical obstacles to effective workforce nationalisation from human development, legal development, and socio-cultural perspectives. The findings contribute to the literature on GCC workforce nationalisation by unpacking educators’ and senior students’ views.
Technological options and design evolution for recycling spent lithium‐ion batteries: Impact, challenges, and opportunities

The lithium‐ion battery (LIB) market is growing, driven by consumer demand and the imperative to reduce greenhouse gas (GHG) emissions. The socio‐environmental impacts of LIBs production are vast; thus, it is of paramount importance to acquire knowledge about the consequences of lithium metal mining on human health, farming and the overall ecosystem. The materials embedded in spent LIBs have high industrial value. To minimize environmental impacts and conserve declining natural resources, the global supply chain for the raw materials for LIBs should not rely solely on mining. Rather, manufacturers should have access to the critical materials recovered from waste, as a sustainable and reliable secondary source of valuable materials. It is also crucial to study the hazards and economic considerations associated with waste LIB management from disassembly to final recycling stage. This article evaluates and highlights various current approaches to recycling and reuse of LIBs, as well as potential future developments. The pros and cons of different technological options for recycling spent LIBs, and opportunities to use small‐scale recycling technology to overcome the associated barriers, are also discussed.
Biomolecular Analysis of Canine Distemper Virus Strains in Two Domestic Ferrets (Mustela putorius furo)

Simple Summary The current study describes a clinical case of canine distemper virus (CDV) infection in ferrets with a particular focus on viral typing. The diagnostic methods that are described herein allow a rapid and sensitive approach to the diagnosis of CDV infection in a susceptible species. Considering the high morbidity and mortality rates of CDV infection in ferrets and the limited therapeutic possibilities, widespread vaccination remains crucial for preventing the disease and counteracting cross-species infection. Abstract Canine distemper is a contagious and severe systemic viral disease that affects domestic and wild carnivores worldwide. In this study, two adult female ferrets (Mustela putorius furo) were evaluated for cutaneous lesions. Scab, fur, and swab samples from the external auditory canal, cutaneous lesions, and scrapings were analyzed. Canine distemper virus (CDV)-positive samples underwent RT-PCR/RFLP with the restriction enzyme PsiI, and the hemagglutinin gene sequence was obtained. According to the restriction enzyme and sequence analyses, the viral strains were typed as CDV field strains that are included within the Europe lineage and distinct from those including vaccinal CDV strains. The sequence analysis showed the highest nucleotide identity rates in older Europe lineage CDV strains collected from dogs and a fox in Europe. This study is the first to report on CDV infection in ferrets in southern Italy and contributes to the current knowledge about natural CDV infection in this species. In conclusion, vaccination remains crucial for preventing the disease and counteracting cross-species infection. Molecular biology techniques can enable the monitoring of susceptible wild animals by ensuring the active surveillance of CDV spread.