Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of the Quality of Life and Depression in the Elderly with and without a History of COVID-19 Infection in Shiraz, Iran

Background COVID-19 causes many physical and mental complications. The elderly, as one of the vulnerable groups, were more exposed to the problems caused by this pandemic. The aim of this study was to compare the quality of life and depression in the elderly with and without a history of COVID-19 infection. Method This is a cross-sectional descriptive study conducted on 404 elderly people (202 from the affected group and 202 from the nonaffected group) aged over 60 years old in Shiraz city. The elderly participants were selected based on simple random sampling from the elderly list. In order to collect information, the quality of life questionnaire of the World Health Organization and Beck's depression questionnaire were used. Data analysis was done through SPSS software version 22 using statistical tests of chi-square, t-test, analysis of variance, and Pearson's correlation coefficient. An alpha level under 0.05 was considered the significant level. Results The average score of depression in the elderly with a history of COVID-19 (14.66 ± 13.17) was significantly higher than that of the elderly without a history of COVID-19 (9.71 ± 10.12) (p < 0.001). The average score of the quality of life in the elderly with a history of COVID-19 (80.15 ± 14.85) was significantly lower than that of the elderly without a history of COVID-19 (85.25 ± 14.09) (p < 0.001). Conclusion Elderly people with a history of COVID-19 had more depression and lower quality of life compared to people without a history of COVID-19. It is suggested that planners and health policymakers should pay special attention to the use of effective psychological interventions in order to reduce the problems of the elderly.
A short-term cloud forecast scheme using cross correlations

Abstract This paper describes a cloud forecast technique using lag cross correlations. Cloud motion vectors are retrieved at a subset of points through multiple applications of a cross-correlation analysis. An area in the first of two sequential frames of satellite data is correlated with surrounding areas in the second frame to find the one surrounding area best correlated. The location difference of the areas defines the displacement vector. An objective analysis is used to define displacements at every satellite pixel throughout the domain and smooth the local inconsistencies. Using these displacements, forecasts are then produced with a backward trajectory technique. This scheme was tested using two IR satellite images of the same scene a half-hour apart and found to generate realistic, high-quality forecast IR pixel images. Results demonstrate improvements over persistence and movable persistence for forecasts of a few hours’ length. The technique is visually appealing, since forecasts are created in.
Simulation of Neighborhood‐Scale Air Quality With Two‐Way Coupled WRF‐CMAQ Over Southern Lake Michigan‐Chicago Region

The southern Lake Michigan region of the United States, home to Chicago, Milwaukee, and other densely populated Midwestern cities, frequently experiences high pollutant episodes with unevenly distributed exposure and health burdens. Using the two‐way coupled Weather Research Forecast and Community Multiscale Air Quality Model (WRF‐CMAQ), we investigate criteria pollutants over a southern Lake Michigan domain using 1.3 and 4 km resolution hindcast simulations. We assess WRF‐CMAQ's performance using data from the National Climatic Data Center and Environmental Protection Agency Air Quality System. Our 1.3 km simulation slightly improves on the 4 km simulation's meteorological and chemical performance while also resolving key details in areas of high exposure and impact, that is, urban environments. At 1.3 km, we find that most air quality‐relevant meteorological components of WRF‐CMAQ perform at or above community benchmarks. WRF‐CMAQ's chemical performance also largely meets community standards, with substantial nuance depending on the performance metric and component assessed. For example, hourly simulated NO2 and O3 are highly correlated with observations (r > 0.6) while PM2.5 is less so (r = 0.4). Similarly, hourly simulated NO2 and PM2.5 have low biases (<10%), whereas O3 biases are larger (>30%). Simulated spatial pollutant patterns show distinct urban‐rural footprints, with urban NO2 and PM2.5 20%–60% higher than rural, and urban O3 6% lower. We use our 1.3 km simulations to resolve high‐pollution areas within individual urban neighborhoods and characterize seasonal changes in O3 regimes across tight spatial gradients. Our findings demonstrate both the benefits and limitations of high‐resolution simulations, particularly over urban settings.
AN OPERATOR GENERALIZATION OF THE LOGARITHMIC RESIDUE THEOREM AND THE THEOREM OF ROUCHÉ

We obtain the operator generalization of the theorem on the logarithmic residue for meromorphic operator-functions. The proof of the generalization is based on a theorem concerning a special factorization of a meromorphic operator-function at a point. This theorem also allows us to generalize, to the case of meromorphic operator-functions, the formula of M. V. Keldys for the principal part of the resolvent as well as several other theorems.A definition is given for the multiplicity of a pole for a meromorphic operator-function. The basic properties of the multiplicity of a pole are proved, and also a generalization of the Rouche theorem.Bibliography: 16 items.
User Attitudes Towards Controls for Ad Interests Estimated On-device by the Browser

—Online behavioral advertising is a double-edged sword. While relevant display ads are generally considered useful, opaque tracking based on third-party cookies has reached unfettered sprawl and is deemed to be privacy-intrusive. However, existing ways to preserve privacy do not sufficiently balance the needs of both users and the ecosystem. In this work, we evaluate alternative browser controls. We leverage the idea of inferring interests on users’ devices and designed novel browser controls to manage these interests. Through a mixed method approach, we studied how users feel about this approach. First, we conducted pilot interviews with 9 participants to test two design directions. Second, we ran a survey with 2,552 respondents to measure how our final design compares with current cookie settings. Respondents reported a significantly higher level of perceived privacy and feeling of control when introduced to the concept of locally inferred interests with an option for removal.
Analysis of polychlorinated biphenyls (PCBs) in dairy products by modified QuEChERS/GC‐QqQ‐MS/MS method: A risk assessment study

Abstract Polychlorinated biphenyls (PCBs) are harmful chemicals that are persistent in the environment and can accumulate in the food chain. The purpose of the present research was to assess non‐dioxin‐like polychlorinated biphenyls (NDL‐PCBs) in some dairy products (yogurt, doogh, and kashk) using modified QuEChERS (Quick, Easy, Cheap, Effective, Rugged, and Safe) technique and gas chromatography–triple‐quadrupole mass spectrometry (GC‐QqQ‐MS/MS) method and risk assessment study. The LOQs (limit of quantifications), LODs (limit of detections), recovery, and RSD for the PCB analytes were 0.180–0.360, 0.06–0.12 ng/g fat, 97.45–102.63%, and 6.33–8.86%, respectively. The results revealed that the mean concentrations of Ʃ6‐NDL‐PCBs in samples were 15.17 ± 3.44 ng/g fat, which was lower than the standard level established by European Union (EU, 40 ng/g fat). The maximum mean level was PCB 180 (9.98 ± 2.04 ng/g fat) and the minimum mean level of PCBs in samples was PCB 28 (0.09 ± 0.06 ng/g fat). Also, results showed that kashk samples had a maximum mean level of 6‐NDL‐PCBs (18.66 ± 2.42 ng/g fat) and doogh samples had a minimum mean level of 6‐NDL‐PCBs (12.21 ± 2.22 ng/g fat). The mean level of 6‐NDL‐PCBs in yogurt samples was 14.65 ± 2.02 ng/g fat. The heat map results showed the correlation between the spectral indices of 6‐NDL‐PCBs in different dairy products. According to the Monte Carlo method, risk assessment was done using calculating the Estimated Daily Intake (EDI) and Incremental Life Cancer Risk (ILCR). The EDI values of 6 NDL‐PCBs based on the 95th percentile in yogurt, doogh, and kashk were 14.3, 1.49, and 0.5 ng/kg.day, respectively. Considering that the contaminant level in the samples is lower than the EU limit, it can be concluded that dietary exposure to 6 NDL‐PCBs may not pose a risk to the health of consumers.
Behind and beyond the (head count) employment rate

The paper argues that we need more general statistical indices for the analysis of the European labour markets. First, the paper discusses some normative aspects that are implicit in the current definition of the employment rate, which is a fundamental policy target in the new strategy Europe 2020. Second, it proposes a class of generalized indices based on work intensity, as approximated by the total annual hours of work relative to a benchmark value. Third, it derives, in a consistent framework, household level employment indices. These indices provide a more nuanced picture of the European labour markets, which better reflects the diversity in the use of part‐time and fixed term jobs as well as other factors affecting the allocation of work between and within households.
Conditioning in dynamic models

A statistical model is generally defined through a probability on some variables conditionally on other variables and refers to some parameters of interest. Therefore, it seems natural to ask under which conditions such a model does not lose information with respect to a model describing more variables and implying more parameters. Admissibility conditions for reductions by conditioning are investigated both in one-shot and in dynamic models. By so doing, concepts of ‘exogeneity’ and of ‘non-causality’ are integrated into a general framework. This paper is essentially a non-technical introduction to the theory of reduction developed more formally in other papers. It also supplies various examples of the concepts introduced in that theory.
Clumped Isotope Thermometry in Plant‐Derived Carbonates

The genus Celtis includes widespread trees that produce drupes with aragonite endocarps, or “hackberries. ” These carbonate endocarps are preserved in the fossil record, often in cave deposits or packrat middens, and thus are targets for paleoclimate reconstructions. Stable oxygen isotopes in Celtis endocarps have been used as proxies for oxygen isotopic composition of past stream water and for paleothermometry. Here, we explore the suitability of hackberry carbonates for paleoclimate reconstructions based on carbonate clumped‐isotope thermometry. We sampled modern hackberries grown at sites across North America (n = 37) for stable and clumped isotope analyses. Measured clumped‐isotope temperatures are found to be within the range of measured local modern growing season surface temperatures and typically in dual clumped‐isotope equilibrium. As such, we propose that hackberry clumped‐isotope measurements can be used to reconstruct past Earth‐surface air temperatures.
An Antibiogram Study for Urine Culture Testing in Makkah Region Hospitals

Background: The antibiogram profile could be helpful in the selection of the most appropriate antimicrobial treatment for microbial infection and even useful to monitor antibiotic resistance. Objective: This study aims to identify the bacteria in the urine through urine culture and perform their antibiogram to determine the resistance profile between antibiotics and urine tract infection (UTI)-causing bacteria and to determine the effective and non-effective antibiotics. Methods: The study was based on urine culture data from five Makkah hospitals in the Kingdom of Saudi Arabia (KSA). Results: A total of 1000 pathogens were found in the urine culture; 899 were bacterial isolates, and 101 were Candida spp. Seven hundred and seventy-seven of the 899 bacteria isolates were gram-positive, while 122 were gram-negative bacteria. Escherichia coli (44%) was the most frequent UTI-causing bacteria, followed by Klebsiella spp. (20%), Pseudomonas aeruginosa (6%), S. aureus (5.5%), Enterococcus faecalis (4.5%), Enterobacter spp. (2%), and Proteus spp. (1%). There was clear evidence that ampicillin, cefepime, erythromycin, and moxifloxacin were not effective antibiotics for uropathogens in the Makkah area, KSA. The multiple drug resistance (MDR), extensively drug-resistant (XDR), extended spectrum beta lactamase (ESBL), CR, and quinolones resistance (QR) were higher in the gram-negative bacilli. The pandrug resistance (PDR) and AmpC seemed to have fewer ratios of UTIs caused by gram-negative bacteria. On the other hand, S. aureus of the gram-positive type was also involved in the UTI and had a higher ratio of MDR, QR, and methicillin-resistant Staphylococcus aureus (MRSA).
Bayesian and non-Bayesian techniques applied to censored survival data with missing values

This thesis is a comprehensive comparative study of survival analysis methods, in particular the application of the Cox Proportional Hazards (CPH) model to real life data: A data set with 48 right-censored (end of study) patients suffering from multiple myeloma, and the COpenhagen Stroke study (COST) database with 993 right-censored (10 year follow-up) stroke patients. The most frequently applied method, stepwise selection, is a variable selection technique that fits a single model by searching for significant predictors of the survival time in terms of p-values. However, stepwise selection ignores the between-model uncertainty. This leads to biased and overconfident estimates. We compare stepwise selection to a more advanced approach, Bayesian Model Averaging (BMA), to average over all or a subset of models weighted by their posterior model probabilities. We show how to identify a subset of models using Occam's window subset selection with results comparable to an average over all models. We show that BMA has several advantages over stepwise selection. Using an average over models, we can evaluate the model uncertainty and obtain more reliable estimates of the risk factor coefficients. BMA also gives probabilistic evaluations of each risk factor, and we can ask questions such as: " What is the probability that this risk factor coefficient is non-zero, i.e. has an effect? " In stepwise selection, risk factors are either significant or not. We also show how to evaluate and compare the predictive power of competing models using the predictive log-score and a novel evaluation score, the predictive Z-score. We show that BMA improves the predictive power of our models. ii The CPH model is based on an assumption of proportional hazards. We implement two methods for validating this assumption. One can be used before and the other after a model has been fitted. We also show how to implement time-dependent variables and parameters to give a more general Cox regression (CR) model, and how to apply BMA on this model. Most real-life data sets have subjects where all values have not been recorded. Standard survival analysis methods cannot handle missing values, and a lot of valuable information is lost. We present three ways to address this problem: Combining BMA and variable selection, we propose a stepwise BMA method, where variables are removed by evaluating the probability of an effect. When we remove variables with missing values, we reduce the number of subjects with missing values, and significantly increase …
A path towards true inclusion: Disabled students and higher education in America

We live in a moment of immense and developing change, reacting to global challenges that appear with increasing speed and requiring reassessment of priorities and perhaps, reshaping the framework by which we have experienced our lives. Yet these same challenges provide a rare opportunity to empower the more than one billion people with disabilities globally through principles of compassion, respect, dignity and inclusion. We must build a new generation of strong leaders, professionals and advocates tapping the unlimited potential of people with disabilities. The key to unlocking this potential is realizing meaningful access to higher education for students with disabilities. This article examines opportunities and barriers for disabled students in American higher education, drawing on student and administrator interviews and case law to propose a framework based upon principles of access, inclusion, accountability and advocacy, so we may ensure educational opportunities for students with disabilities to allow them to take their rightful places alongside their non-disabled peers as leaders to secure a fully inclusive and equitable future for all.
A robust dual algorithm for topology design of structures in discrete variables

Dual optimization algorithms for the topology optimization of continuum structures in discrete variables are gaining popularity in recent times since, in topology design problems, the number of constraints is small in comparison to the number of design variables. Good topologies can be obtained for the minimum compliance design problem when the perimeter constraint is imposed in addition to the volume constraint. However, when the perimeter constraint is relaxed, the dual algorithm tends to give bad results, even with the use of higher‐order finite element models as we demonstrate in this work. Since, a priori, one does not know what a good value of the perimeter to be specified is, it is essential to have an algorithm which generates good topologies even in the absence of the perimeter constraint. We show how the dual algorithm can be made more robust so that it yields good designs consistently in the absence of the perimeter constraint. In particular, we show that the problem of checkerboarding which is frequently observed with the use of lower‐order finite elements is eliminated. Copyright © 2001 John Wiley & Sons, Ltd.
Rayleigh-Love wave coupling in an azimuthally anisotropic medium.

We present the generalized representation of the equations of motion for an elastic solid in a concise vector form with arbitrary orthogonal curvilinear coordinates and no assumption on symmetry of elastic moduli. For the particular case of the Cartesian coordinates, this representation leads to the generalized y-method for eigenvalues of surface wave dispersion in an anisotropic plane-stratified medium. The generalized y-method is the integration method to find eigenvalues of surface wave dispersion by iterating numerical depth-integration of first-order ordinary differential equations that are derived from the generalized representation of the equations of motion and Hookean law. Based on the generalized y-method, we present some numerical results for dispersion curves and azimuthal variations of surface wave velocities to fully display Rayleigh-Love wave coupling in Kawasaki's (1986) azimuthally anisotropic model for the upper mantle beneath the Pacific ocean. When Rayleigh-Love wave coupling takes place in a particular period range between a pair of nearby modes, surface waves display the following distinct singularities: (1) a difference of phase velocities of the pair of the modes is smaller than about 0.5 km/s, (2) a pair of dispersion curves of group velocities cross each other, (3) polarizations of particle motion directions are twisted along the pair of dispersion curves from Rayleigh- to Love-types and from Love- to Rayleigh-types. These sigularities are dependent on the relative depth- and azimuthal-distribution of the upper mantle anisotropy. When Rayleigh-Love wave coupling does not take place, the first-order perturbation theory works well.
SIMBA survey of southern high-mass star forming regions. I. Physical parameters of the 1.2-mm/IRAS sources

We report the results of a 1.2 mm continuum emission survey toward 146 IRAS sources thought to harbour high- mass star forming regions. The sources have FIR colors typical of UCHII regions and were detected in the CS(2 → 1) line survey of Bronfman et al. (1996). Regions of 15 � × 10 � , centered on each IRAS source, were mapped with an angular resolution of ∼24 �� , using the SIMBA array on the SEST telescope. 1.2 mm emission was detected toward all IRAS sources. We find that the dust cores associated with these sources have typical sizes of 0.4 pc and masses of 5 × 10 3 M� . Dust temperatures and luminosities, derived from the SED, are typically 32 K and 2.3 × 10 5 L� .
Superresolution HRR ATR with high definition vector imaging

A new 1-D template-based automatic target recognition (ATR) algorithm is developed and tested on high range resolution (HRR) profiles formed from synthetic aperture radar (SAR) images of targets taken from the Moving and Stationary Target Acquisition and Recognition (MSTAR) data set. In this work, a superresolution technique known as High Definition Vector Imaging (HDVI) is applied to the HRR profiles before the profiles are passed through ATR classification. The new I-D ATR system using HDVI demonstrates significantly improved target recognition compared with previous I-D ATR systems that use conventional image processing techniques. This improvement in target recognition is quantified by improvement in probability of correct classification (PCC). More importantly, the application of HDVI to HRR profiles helps to maintain the same ATR performance with reduced radar resource requirements.
Regulation and Vibration Control of an FEM-Based Single- Link Flexible Arm Using Sliding-Mode Theory

Compared to the assumed-mode method (AMM), the finite-element method (FEM) is not only more applicable to the modeling of various kinds of flexible structures but also better in estimating the natural frequencies. Motivated from these features and modified from the work of Yeung and Chen for an AMM-based model, the sliding-mode controller introduced in this paper is developed to deal with the regulation problem and vibration suppression of an FEM-based single-link flexible arm. This paper will focus on the issue of how to change the FEM-based model into a form similar to the AMM-based model via the Schur decomposition. A technique to measure the well-estimated state variables required for the control is also presented. Finally, numerical simulation results are given to verify the robustness of the modified sliding-mode controller against payload variation.
Kids, Cats, and Control: Designing Privacy and Security Dashboards for IoT Home Devices

—In the last decade integration of Internet of Things (IoT) ecosystems has increased exponentially, and it is necessary that our understanding of human behavior when interacting with multiple smart devices in an IoT ecosystem keep pace. To better understand users’ perceptions and use of in-home IoT ecosystem over time, we implemented an ecosystem in homes of participants so that we could both test previous findings about individual devices and identify differences that arise in the content of a home with multiple IoT devices. Specifically, we recruited eight participants from separate households who installed identical IoT configurations, and interviewed each participant for five weeks. We included an Android dashboard to provide device control and data transparency. We detail the semi-structured interviews to compare user perceptions of what devices are classified as IoT, the perceived sustainability of IoT devices, interactions with and desires of dashboard information, and exploration of current notification preferences and mitigation strategies. We discuss the factors which participants identified as being relevant to their personal experiences with IoT devices and contribute recommendations for dashboard designs and control mechanisms for IoT devices. We note that the participants uniformly had a more expansive definition of IoT than that found in much of the previous literature, implying that our understanding of perceptions of in-home IoT may be informed by previous research on security systems, wearables, watches, and phones. We identify where our results reify findings of studies