Miracle-dz/UniFAR-FTUs huggingface dataset:
A study of nasal carriage of methicillin-resistant staphylococcus aureus in patients undergoing hemodialysis in a tertiary care hospital of Punjab

Background: Infection is one of the major problems encountered in hemodialysis patients. The mortality rate among the patients undergoing hemodialysis remains unsatisfactorily high. Hemodialysis patients have higher nasal carriage rate of Staphylococcus aureus than the healthy population. In long-term hemodialysis patients, colonization is a significant problem and is associated with an increased risk of the bloodstream infections. The antimicrobial resistance to this pathogen is increasing rapidly, and the consequences of methicillin resistance for the outcomes of Staphylococcus aureus infections are drastic.Methods: Two swabs were collected from anterior nares of patients undergoing hemodialysis, and then these swabs were transferred to microbiology laboratory for processing. Isolated strains were subjected to antimicrobial susceptibility testing using Kirby-Bauer disc diffusion. Methicillin resistance was detected by using cefoxitin disc. Inhibition zone diameters were measured as per CLSI criteria. Vancomycin screen agar test was done. Brain heart infusion agar plates containing 6 µg/ml of vancomycin were used. S. aureus ATCC 29213 was used as reference strain.Results: It was observed that 38% (38/100) of the hemodialysis patients were carriers of S. aureus followed by CoNS, followed by aerobic spore bearers. All the S. aureus isolates (100%, 38/38) were methicillin-resistant (MRSA). Conclusions: Staphylococcal nasal carrier status in hemodialysis patients along with antibiotic susceptibility testing should be done in routine and infection control practices should be followed to prevent the transmission of MRSA among chronic hemodialysis patients.
The convergent use of mobile phones: A comparison of user behaviors between Australia and Taiwan

The emergence of device convergence with regard to new design and data services have transformed the use of mobile phones from solely for voice and text communication into various purposes, namely personal information management (PIM), entertainment, e-mail communication, and commercial transactions. However, most of the existing literature on mobile technology adoption has thus far focused on the adoption of mobile phone as a single function device and hence does offer very limited explanatory power to understand the utility of mobile phone as a converged device. In addition, the scope of previous studies has been limited to a single country. Therefore, this paper intends to address both these limitations. The aim is to explain the use of mobile phone as a converged device and the determinants that influence such use. Data were collected based on a cross-national survey in Australia and Taiwan. Although the findings indicate that the individual profiles and usage patterns in both countries are similar, the empirical framework explains more variances in the Australian sample. Among the psychometrical factors, individuals’ perception of enjoyment is the dominant factor that drives people to use mobile phones for various purposes in both Australia and Taiwan. Users’ age does differentiate the use of mobile phones for different purposes in both samples. Gender seems to have some influence as well. Male and female users show significant differences in using their mobile phones for entertainment, e-mail and commercial transactions. The findings also pinpoint the effects of individuals’ perceptions, demographics, and technology choices are heterogeneous when using mobile phones for specific purposes. Some effects, such as risk and enjoyment can be explained by cultural differences. Therefore, product manufacturers and service providers should dedicate their marketing efforts in accordance to match with the heterogeneous demand from their customers. Key words: TAM, mobile commerce, moderating effect, logistic regression.
Challenges and Lessons Learned for Acute Inpatient Rehabilitation of Persons With COVID-19

Objective The aim of the study was to present: (1) physiatric care delivery amid the SARS-CoV-2 pandemic, (2) challenges, (3) data from the first cohort of post–COVID-19 inpatient rehabilitation facility patients, and (4) lessons learned by a research consortium of New York and New Jersey rehabilitation institutions. Design For this clinical descriptive retrospective study, data were extracted from post–COVID-19 patient records treated at a research consortium of New York and New Jersey rehabilitation inpatient rehabilitation facilities (May 1–June 30, 2020) to characterize admission criteria, physical space, precautions, bed numbers, staffing, employee wellness, leadership, and family communication. For comparison, data from the Uniform Data System and eRehabData databases were analyzed. The research consortium of New York and New Jersey rehabilitation members discussed experiences and lessons learned. Results The COVID-19 patients (N = 320) were treated during the study period. Most patients were male, average age of 61.9 yrs, and 40.9% were White. The average acute care length of stay before inpatient rehabilitation facility admission was 24.5 days; mean length of stay at inpatient rehabilitation facilities was 15.2 days. The rehabilitation research consortium of New York and New Jersey rehabilitation institutions reported a greater proportion of COVID-19 patients discharged to home compared with prepandemic data. Some institutions reported higher changes in functional scores during rehabilitation admission, compared with prepandemic data. Conclusions The COVID-19 pandemic acutely affected patient care and overall institutional operations. The research consortium of New York and New Jersey rehabilitation institutions responded dynamically to bed expansions/contractions, staff deployment, and innovations that facilitated safe and effective patient care.
Local binary pattern and deep learning feature extraction fusion for COVID‐19 detection on computed tomography images

The deadly coronavirus virus (COVID‐19) was confirmed as a pandemic by the World Health Organization (WHO) in December 2019. It is important to identify suspected patients as early as possible in order to control the spread of the virus, improve the efficacy of medical treatment, and, as a result, lower the mortality rate. The adopted method of detecting COVID‐19 is the reverse‐transcription polymerase chain reaction (RT‐PCR), the process is affected by a scarcity of RT‐PCR kits as well as its complexities. Medical imaging using machine learning and deep learning has proved to be one of the most efficient methods of detecting respiratory diseases, but to train machine learning features needs to be extracted manually, and in deep learning, efficiency is affected by deep learning architecture and low data. In this study, handcrafted local binary pattern (LBP) and automatic seven deep learning models extracted features were used to train support vector machines (SVM) and K‐nearest neighbour (KNN) classifiers, to improve the performance of the classifier, a concatenated LBP and deep learning feature was proposed to train the KNN and SVM, based on the performance criteria, the models VGG‐19 + LBP achieved the highest accuracy of 99.4%. The SVM and KNN classifiers trained on the hybrid feature outperform the state of the art model. This shows that the proposed feature can improve the performance of the classifiers in detecting COVID‐19.
Impact of Time-Use Behaviour on Residential Energy Consumption in the United Kingdom

In order to have the best possible chance of achieving ‘decent work’ and ‘climate action’ as laid forth in the UN Sustainable Development Goals, government and policy makers must pay close attention to current time-use patterns, as well as the way these might change in the near future. Here we contribute to the existing literature on time-use behaviour through a systematic exploration of the relationship between working patterns and energy consumption from the perspective of time-use. Our starting point is the premise that different work arrangements impact the timing of energy demand not only in workplaces, but also at home. Using the data from the 2014–2015 UK time-use survey, we were able to capture patterns of time-use behaviours and to assess their relationship with daily energy consumption. We propose a systematic time-use-based approach for estimating residential energy consumption with regards to activity timing, activity location, activity coordination, and appliance type. We use this method to discover patterns in residential activities and energy consumption, as well as the causal relationship between residential energy consumption and work patterns. In this study, we unpack the heterogeneity in the work–energy relationship, particularly when comparing full-time and part-time workers. Our results suggest that full-time employees have a higher potential to reduce their energy use compared to part-time employees. We also discover a non-linear change in total energy consumption for respondents with varying levels of work time. Energy consumption reductions associated with differences in work schedules are greatest during the first few hours of the workday, but then level off. Our findings suggests that time-use data can provide useful insights for evaluating and possibly designing energy and labour-market policies.
Transcutaneous carbon dioxide monitoring could reduce physical contact with COVID-19 patients

1Department of Medicine, University of Missouri, Columbia, MO 65212 2Department of Medicine – Division of Pulmonary, Critical Care and Environmental Medicine, University of Missouri, Columbia, MO 65212 3Respiratory Therapy Services, University of Missouri Hospital and Clinics, Columbia, MO 65212 MN 4Department of Medicine– Division of Infectious Diseases, University of Missouri, Columbia, MO 65212
Characterisation of Organic Matter and Its Transformation Processes in On-Site Wastewater Effluent Percolating through Soil Using Fluorescence Spectroscopic Methods and Parallel Factor Analysis (PARAFAC)

This research has used fluorescence spectroscopy and parallel factor analysis (PARAFAC) in order to characterize dissolved organic matter in septic tank effluent, as it passes through the biomat/biozone, infiltrating into the unsaturated zone beneath domestic wastewater treatment systems (DWWTSs). Septic tank effluent and soil moisture samples from the percolation areas of two DWWTSs have been analyzed using fluorescence excitation–emission spectroscopy. Using PARAFAC analysis, a six-component model was obtained whereby individual model components could be assigned to humified organic matter, fluorescent whitening compounds (FWCs), and protein-like compounds. This has shown that fluorescent dissolved organic matter (FDOM) in domestic wastewater was dominated by protein-like compounds and FWCs and that, with treatment in the percolation area, protein-like compounds and FWCs are removed and contributions from terrestrially derived (soil) organic decomposition compounds increase, leading to a higher degree of humification and aromaticity. The results also suggest that the biomat is the most important element determining FDOM removal and consequently affecting DOM composition. Furthermore, no significant difference was found in the FDOM composition of samples from the percolation area irrespective of whether they received primary or secondary effluent. Overall, the tested fluorometric methods were shown to provide information about structural and functional properties of organic matter which can be useful for further studies concerning bacterial and/or virus transport from DWWTSs.
Analysis of a 2-Phase Drag-Cup Induction Machine

The 2-phase drag-cup machine is treated as a linear 4-terminal element. The self-impedance of each phase and the mutual impedance between phases are found by obtaining the electromagnetic field components in the air gap between stator and rotor. These components are derived from a single vector field function, the magnetic vector potential. The impedances are functions of the geometrical dimensions, frequency, and the relative slip.
Travel Time Information Using Global Positioning System and Dynamic Segmentation Techniques

The architecture and application of an updated methodology based on the Global Positioning System (GPS) for conducting travel time studies are described. The methodology is called Travel Time with GPS (TTG). TTG uses a general data model that includes a spatial model, a geographic relational database, and a procedure for linearly referencing GPS data using dynamic segmentation tools. This architecture allows users to conduct travel time studies at various levels of resolution (from regionwide studies down to studies of signalized intersections). The data reduction and data reporting for such a system are outlined. Data reduction is based on linear referencing of GPS data using highway links, where highway links are defined as vector representations of directional centerlines delimited by physical discontinuities. Data reporting is based on the use of dynamic segmentation tools to compute travel time and speed along highway corridors using any highway segmentation scheme. The resulting aggregated data can be used for the production of tabular reports and color-coded maps to document travel time, delay, and speed data. The database management system built into TTG allows users to handle many GPS data files using a centralized, structured procedure, which is critical for data archival purposes and the development of clientserver applications. In conclusion, quantitative values for data storage requirements and processing speeds are provided. Those values should be useful to practitioners currently designing travel time information systems.
Constraining the phonology-phonetics interfaces: with exemplification from Spanish and Italian dialects (1995)

In this thesis, I address the interrelated issues of phonological underspecification and phonetic specification. Working within the model of Modified Contrastive Specification, I provide evidence for underspecification of height features from the phonological and phonetic patterning of vowels in Iberian Spanish and Italian dialects. I argue that (a) the feature [high] is present in inventories only when it is required to appear in order to mark a contrast between high and non-high vowels in the non-low region, and (b) that the mid vowels [e] and [o] are underlyingly underspecified for height features. Given the evidence for underspecification, I explore the relationship between the underspecified phonological representations and more fully specified phonetic representations. To do so, I first present data showing that phonologically underspecified vowels display predictable patterns of phonetic variation. I then derive such patterns from the phonetic rule of enhancement, a rule which inserts non-contrastive features in order to more fully specify underspecified representations. The main goal of this thesis, then, is to argue that the interface between underspecified phonological representations and maximally specified phonetic representations is highly constrained. I demonstrate that there are a limited number of ways to interpret phonologically underspecified representations. I also show that the interpretation of phonetic data--i.e. phonemicization--is similarly constrained, arguing in particular for the possibility of phonemicization without reference to rules.
Flow behavior of magnetic steel powder

Abstract Flow occurs in most powder-based processes, opposed by various cohesive forces. Magnetism is often overlooked for metal powders. Here, flowability and magnetization were measured for a dual-phase steel powder in size fractions from to > 200 µm. The finest fraction did not flow through a Hall flowmeter, then flow time increased continuously with particle size from 12 ± 1 s for the next fraction ( ) to > 28 ± 0.5 s for > 200 µm. Drying had little effect. Key metrics derived from shear tests gave no overall relationship between flow behavior and particle size. Magnetism was considered the most likely reason for this behavior. Magnetometry showed a remanent magnetization of which causes ∼ 5 µN cohesion between 200 µm diameter particles. X-ray diffractometry showed that the powder contained 77 wt%-80 wt% of (magnetic) martensite. Liquid bridging, van der Waals forces and friction (in the Hall flowmeter geometry) contribute 50 µN, 0.08 µN and 4 µN, respectively, to cohesion in 200 µm particles. These results can be used to help explain flow behavior in other magnetic powders and allow optimization of powders and/or powder-based processes.
A Study of Corona Discharges at Water Drops Over the Freezing Temperature Range

Foul weather corona have been observed to behave differently at temperatures above and below the freezing point1.2. Generally speaking, the discharge activities are much more intensive at temperatures above than below the freezing point. Such behaviour of the discharge is so far associated with the differences in the physical properties of water in its liquid and solid phases. No detailed study has, however, been made to correlate the discharges characteristics with the macroscopic changes in the water drop over the freezing temperatures range. In the present study, the development of corona discharge at a watet drop in a cylindrical field was investigated during its transition from the liquid to solid phase. This was done by correlating the discharge current with variations of the water drop temperature. The results obtained show that the noise generation and energy losses are related to both the corona discharges in the surrounding air and to the continuously changing conditions at the water drop during its transition into ice (and vice versa).
Seismic Fragility Evaluation of Lightly Reinforced Concrete-Block Shear Walls for Probabilistic Risk Assessment

AbstractWith the North American seismic codes moving toward adopting performance-based seismic design (PBSD) approaches, there is a need to develop seismic probabilistic risk assessment (PRA) tools for different construction systems, including reinforced masonry (RM). The current study focuses on the development of analytical fragility curves based on the performance of RM walls tested under base excitation generated by a shake table. The study has two phases. In the first phase, the seismic response of the RM shear walls is modeled using a simplified analytical model that was calibrated using previously reported shake table experimental results. The second phase of the study focuses on the development of fragility curves, as an essential component of a PRA framework, for two-story lightly reinforced masonry walls. In this phase, relevant limit states are defined and the corresponding capacities of the walls are quantified based on the shake table test results. The wall seismic demand levels are then dete.
The relationship between attraction, perception of service, opportunities and tourist satisfaction in backwater tourism in Alappuzha district of Kerala in India

This article aims to explore the relationships between destination attractions, tourists’ awareness of eco-tourism and facilities, level of perceived service, opportunities and problems, and tourist satisfaction in backwater tourism in Kerala, India. Using a structured survey instrument, we gathered data from 586 tourists. A conceptual model was developed and tested after checking the psychometric properties of the instrument. We tested the measurement model using the Lisrel package (structural equation modeling), and Hayes (2018) process macros were used to test the moderation hypotheses. The results confirm that (i) attraction and opportunities are positively related to tourist satisfaction, (ii) perception of service positively moderates the relationship between attraction and tourist satisfaction, (iii) perception of service (first moderator) and awareness (second moderator) interact to influence the relationship between attraction and tourist satisfaction, and (iv) problems negatively moderate the positive relationship between opportunities and tourist satisfaction. The implications for the literature on tourism and hospitality and practicing managers are discussed.
Tuning of active vibration controllers for ACTEX by genetic algorithm

This paper is concerned with the optimal tuning of digitally programmable analog controllers on the ACTEX-1 smart structures flight experiment. The programmable controllers for each channel include a third order Strain Rate Feedback (SRF) controller, a fifth order SRF controller, a second order Positive Position Feedback (PPF) controller, and a fourth order PPF controller. Optimal manual tuning of several control parameters can be a difficult task even though the closed-loop control characteristics of each controller are well known. Hence, the automatic tuning of individual control parameters using Genetic Algorithms is proposed in this paper. The optimal control parameters of each control law are obtained by imposing a constraint on the closed-loop frequency response functions using the ACTEX mathematical model. The tuned control parameters are then uploaded to the ACTEX electronic control electronics and experiments on the active vibration control are carried out in space. The experimental results on ACTEX will be presented.
Biophilic urbanism: a case study on Singapore

This paper outlines the characteristics of an emerging new planning paradigm called biophilic urbanism by detailing a case study of Singapore, which, over a number of years, has demonstrated how high density does not have to mean reduced natural systems. The paper looks at how biophilic urbanism works to improve natural systems between buildings and on the façades and rooftops of buildings.
Guidance Laws for Anti-Ship Missiles Using Impact Angle and Impact Time

*† The general objective of most guidance laws is to guide a missile into a collision course so that the missile intercepts a target effectively under several constraint conditions. As the defense system for warships has been advanced recently, many researchers are working on the development of new guidance laws for anti-ship missiles. This paper deals with an impact angle based guidance law and an impact time based guidance law. The impact angle guidance law can be used to generate appropriate trajectories and intercept a target with desired impact angle. How to geometrically set the waypoint passing angles as well as the desired impact angle are proposed. The impact time guidance law based on proportional navigation guidance is also proposed in this paper. The proposed guidance law can be applied for the formation flight of anti-ship missiles. As several missiles intercept a target simultaneously, the missiles can complete the given mission more efficiently. Finally the two guidance laws are combined together to enhance the survivability and kill probability. Numerical simulations are performed to evaluate the performances of the proposed guidance laws using impact angle and impact.