Miracle-dz/UniFAR-FTUs huggingface dataset:
Formation of a coastal barrier jet in the Gulf of Mexico due to the interaction of cold fronts with the Sierra Madre Oriental mountain range

The passage of three cold fronts (CFs) over the Gulf of Mexico was simulated with the Weather Research and Forecasting model to study the mechanisms associated with the formation of a jet parallel to the Sierra Madre Oriental (SMOr) mountain range near the port of Veracruz. Dew‐point temperature (Td = 20 °C) and available convective potential energy best simulated the horizontal propagation of the intense CFs over the Gulf, and equivalent potential temperature helped identify the vertical position of the fronts. Additional simulations with reduced topography showed that mountain heights exceeding 2.5 km, where the SMOr is closest to the coast, were crucial for the formation of a coastal barrier jet. The Froude number (Fr < 1) and the ageostrophic component of the wind at low levels were used to identify the formation of the jet; the Rossby radius of deformation determined its horizontal extent which was 81 km into the Gulf of Mexico in agreement with scatterometer winds during one of the CFs. The interaction of the northeasterly winds (known as Nortes) with the topography produced a blocking effect resulting in a stable region of cold air, a rain‐shadow and a coastal barrier jet of northwesterly direction, which generated strong cold air advection and subsidence in comparison with adjacent zones. The jet region appears as a minimum in the winter precipitation climatology indicating that the barrier jet is an important intraseasonal feature. In two of the case‐studies, maximum jet velocities reached those of a tropical storm (>18 m s−1) and occurred near the surface (<1 km above mean sea level), consistent with observations and similar to other barrier jets in the world. For the first time the jet near the port of Veracruz is documented as a coastal barrier jet. The CFs also produced strong Tehuano gap winds.
Blind Image Deblurring using Kernel-guided Nonlocal Patches and Nonlocal Low-rank Images

Blind Image Deblurring using Kernel-guided Nonlocal Patches and Nonlocal Low-rank Images Suil Son Department of Electrical Engineering and Computer Science College of Engineering The Graduate School Seoul National University Blind image deblurring aims to restore a high-quality image from a blurry image. Blind image deblurring has gained considerable attention in recent years because it involves many challenges in problem formulation, regularization, and optimization. In optimization perspective, blind image deblurring is a severely ill-posed inverse problem; therefore, effective regularizations are required in order to obtain a high-quality latent image from a single blurred one. In this paper, we propose nonlocal regularizations to improve blind image deblurring. First, we propose to use the nonlocal patches selected by similarity weighted by the kernel for the next blur-kernel estimation. Using these kernel-guided nonlocal patches, we impose regularization that nonlocal patches would produce the similar values by convolution. Imposing this regularization improves the kernel estimation. Second, we propose to use a nonlocal low-rank image obtained from the composition of nonlocal similar patches. Using this nonlocal low-rank image, we impose regularization that the latent image is similar to this nonlocal low-rank image. A nonlocal low-rank image contains less noise by
A cylinder flow arising from irregularity of distribution

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Risk Factors for SARS-CoV-2 Infection and Severe Outcomes Among People With Human Immunodeficiency Virus: Cohort Study

Abstract Background Studies on COVID-19 in people with HIV (PWH) have had limitations. Further investigations on risk factors and outcomes of SARS-CoV-2 infection among PWH are needed. Methods This retrospective cohort study leveraged the national OPTUM COVID-19 data set to investigate factors associated with SARS-CoV-2 positivity among PWH and risk factors for severe outcomes, including hospitalization, intensive care unit stays, and death. A subset analysis was conducted to examine HIV-specific variables. Multiple variable logistic regression was used to adjust for covariates. Results Of 43 173 PWH included in this study, 6472 had a positive SARS-CoV-2 result based on a polymerase chain reaction test or antigen test. For PWH with SARS-CoV-2 positivity, higher odds were found for those who were younger (18–49 years), Hispanic White, African American, from the US South, uninsured, and a noncurrent smoker and had a higher body mass index and higher Charlson Comorbidity Index. For PWH with severe outcomes, higher odds were identified for those who were SARS-CoV-2 positive, older, from the US South, receiving Medicaid/Medicare or uninsured, a current smoker, and underweight and had a higher Charlson Comorbidity Index. In a subset analysis including PWH with HIV care variables (n = 5098), those with unsuppressed HIV viral load, a low CD4 count, and no antiretroviral therapy had higher odds of severe outcomes. Conclusions This large US study found significant ethnic, racial, and geographic differences in SARS-CoV-2 infection among PWH. Chronic comorbidities, older age, lower body mass index, and smoking were associated with severe outcomes among PWH during the COVID-19 pandemic. SARS-CoV-2 infection was associated with severe outcomes, but once we adjusted for HIV care variables, SARS-CoV-2 was no longer significant; however, low CD4 count, high viral load, and lack of antiretroviral therapy had higher odds of severe outcomes.
A Filter-Based Approach for the Measurement of Mass Absorption Coefficient of OC and EC Components in Soot

ABSTRACT There is a general consensus that soot produced by hydrocarbon combustion consists of two components, elemental carbon associated with the graphitic nanostructure and organic carbon. Despite the relevance of evaluating their radiative properties, particularly for organic carbon, the knowledge of the spectral absorption behavior remains limited. In this work, a dual-beam five wavelengths absorption photometer is used to estimate the optical properties of particulate matter generated by a laminar premixed ethylene-air flame at different residence times along the flame. The wavelength dependence of the light absorption of aerosols collected on filters is analyzed in terms of both the optical band gap and the absorption Ångström exponent, AAE. The aerosols are then analyzed in terms of the organic and elemental carbon content by a thermal-optical OC-EC analyzer. Combining the results of light absorption and OC-EC analysis, the spectral mass absorption coefficient of both the organic carbon and elemental carbon components in soot are obtained.
G5GIM: Integrity Monitoring for GNSS/5G Integrated Navigation of Urban Vehicles

Integrity monitoring (IM) for navigation systems is critical to ensure the safety of auto-driving vehicles. It refers to accurately raising alarms to a user when navigation positioning errors exceed the performance limitation. Although receiver autonomous IM (RAIM) methods have been widely applied for global navigation satellite system (GNSS) observations via a consistency checking algorithm, the integrity performance for auto-driving would suffer from a large degradation due to the low satellite visibility with signal occlusions and non-line-of-sight (NLOS) receptions in urban environments. To alleviate this problem, the fifth-generation (5G) communication signals are used as an auxiliary urban navigation source to increase the number of observations, and then, an IM method for the integration of GNSS/5G (G5GIM) is proposed to improve the integrity performance. Specifically, the positioning reference signals (PRSs) of the 5G system in urban canyons are modeled to enrich the observations of the vehicle navigation, followed by the horizontal protection level (HPL) estimation method and the fault detection algorithm for the integration of GNSS and 5G observations. Experimental results on the simulation and UrbanNav datasets show that the proposed G5GIM method significantly outperforms the existing GNSS RAIM method in terms of HPL reduction, fault detection rate, and positioning accuracy improvement.
An Alternative Regression-Based Approach to Estimate the Crash Modification Factors of Multiple Treatments Using Before-and-After Data

Before-and-after methods have been effectively used in the road safety studies to estimate Crash Modification Factors (CMFs) of individual treatments as well as the multiple treatments on roadways. Since the common practice is to apply multiple treatments on road segments, it is important to have a method to estimate CMFs of individual treatment so that the effect of each treatment towards improving the road safety can be identified. Even though there are methods introduced by researchers to combine multiple CMFs or to isolate the safety effectiveness of individual treatment from CMFs developed for multiple treatments, those methods have to be tested before using them. This study considered two multiple treatments namely 1) Safety edge with lane widening 2) Adding 2 ft paved shoulders with shoulder rumble strips and/or asphalt resurfacing. The objectives of this research are to propose a regression-based method to estimate individual CMFs estimate CMFs using before-and-after Empirical Bayes method and compare the results. The results showed that having large sample size gives accurate predictions with smaller standard error and p-values of the considered treatments. Also, results obtained from regression method are similar to the EB method even though the values are not exactly the same. Finally, it was seen that the safety edge treatment reduces crashes by 15% - 25% and adding 2 ft shoulders with rumble strips reduces crashes by 25% - 49%.
Resource-Efficient Coverage Path Planning for UAV-Based Aerial IoT Gateway

Unmanned Aerial Vehicles (UAVs) have a lot of potential for developing new applications in a variety of fields, such as traffic monitoring, security, and military applications. In the vast nature of the Internet of Things (IoT) network, UAVs could work as Aerial Gateway (AG) for communications among low-powered and distributed ground IoT Devices (IDs). This research concentrates on the path planning and deployment system that may facilitate decisionmaking and guaranteed resource-efficient UAV mission assignment in serving ground IDs. Due to limited resources, it is essential to take into account several factors when designing such a system, including the AG flight time, the coverage radius, and the ground-to-air system's achievable data rate. As a result, the Energy Efficient Coverage Path Planning (EECPP) algorithm has been proposed. The EECPP is composed of two algorithms: the Stop Point Prediction Algorithm using K-Means, and Path Planning Algorithm using Particle Swarm Optimization. The outcome demonstrates that, in terms of total flight distance, EECPP outperforms Close Enough Traveling Salesman Problem (CETSP) by 19.99%. EECPP reduced energy usage by an average of 56.15% as opposed to Energy-Efficient Path Planning (E2PP). Due to its mobility nature with the addition of effective path planning, the AG is able to hover at each stop point, making it ideal for usage in crowded regions with high demand, emergency circumstances, and distant locations with no access to fixed base stations.
Association of Selected Cardiovascular Markers With Tuberculosis: Community-Based Exploratory Cross-Sectional Analytical Study in Puducherry

Introduction India accounts for one-fourth of the global tuberculosis (TB) burden and also faces a rising burden of non-communicable diseases. Only a few have studied the association between the infective pathogenesis of TB and cardiovascular diseases (CVD). Methods A cross-sectional exploratory analytical design was used to compare CVD risk factors and immunological and radiological parameters. This was a pilot study conducted in two primary health centers in urban Puducherry between February 2020 and March 2021. Household contacts (HHC) were either spouses or siblings of the newly diagnosed pulmonary tuberculosis (PTB) patients selected for comparison as their exposure to infection would be similar to those who were diseased yet did not develop illness. Assuming a difference of 5% in CVD risk between the general population and TB patients, with a 95% confidence interval, the sample size calculated was 153 in each group by nMaster v2.0. Considering the feasibility and resource constrain, we recruited 50 newly diagnosed PTB patients, their age- and gender-matched 50 HHC and 50 PTB patients who completed treatment a year before. CVD risk factors were compared using chi-square or Fisher exact test. Interleukins-6 (IL-6), interferon-gamma (INF-γ), highly specific - C reactive protein (hs-CRP), and carotid intima-media thickness (CIMT) were compared using ANOVA or Kruskal-Wallis test. Results Most participants from each group belonged to lower socio-economic strata and were males (40/50). Alcohol intake was higher among newly diagnosed and treatment-completed PTB patients (82.5% vs 72.5%). Excess salt intake (58%) was present more in newly diagnosed PTB patients. General and abdominal obesity were seen more among HHC (64% and 84%) and treatment-completed PTB patients (50% and 74%). IL-6 was higher in newly diagnosed PTB patients, whereas INF-γ and hs-CRP were higher in treatment-completed PTB patients. The largest proportion of those having high CIMT values was also in the treatment-completed PTB patients. Conclusion Levels of immune markers hint at the role of inflammation due to TB disease being related to the high CIMT values among the newly diagnosed and treatment-completed PTB patients. CVD risk was higher among TB patients even if they had completed treatment and were declared cured.
Are idiosyncrasies in vowel production free or learned? A study of variants of the French vowel system in biological brothers

Speech production displays a number of idiosyncrasies that are individual variations in the way speakers achieve phonetic contrasts in their language. It was shown previously [Menard L. et al., Speech Commun. 2008, 50(1), 14-28] that idiosyncrasies in the production of the height contrast in oral vowels in French are characterized by large variations in the distribution of F1 values, which are associated with a stability of F1 for a given height degree, independent of the place of articulation (front vs. back) and rounding. The current study aimed to assess whether these idiosyncrasies are random or induced by the learning environment. Ten pairs of French Canadian adult male siblings were recruited, and each individual was asked to produce ten repetitions of the ten French oral vowels, which were recorded. F1 values were extracted using linear predictive coding algorithms. There was a trend towards imposed variations, since the distances between F1 values for brothers for a given vowel were significantly .
A Multinomial Framework for Ideal Point Estimation

This paper creates a multinomial framework for ideal point estimation (mIRT) using recent developments in Bayesian statistics. The core model relies on a flexible multinomial specification that includes most common models in political science as “special cases. ” I show that popular extensions (e.g., dynamic smoothing, inclusion of covariates, and network models) can be easily incorporated whilst maintaining the ability to estimate a model using a Gibbs Sampler or exact EM algorithm. By showing that these models can be written and estimated using a shared framework, the paper aims to reduce the proliferation of bespoke ideal point models as well as extend the ability of applied researchers to estimate models quickly using the EM algorithm. I apply this framework to a thorny question in scaling survey responses—the treatment of nonresponse. Focusing on the American National Election Study (ANES), I suggest that a simple but principled solution is to treat questions as multinomial where nonresponse is a distinct (modeled) category. The exploratory results suggest that certain questions tend to attract many more invalid answers and that many of these questions (particularly when signaling out particular social groups for evaluation) are masking noncentrist (typically conservative) beliefs.
Uniport versus Multiport Video Assisted Thoracoscopic Surgery (VATS): Comparisons and Outcomes; a Review Article

There are controversies regarding the number of ports in video-assisted thoracoscopic surgery (VATS). The aim of this review is to compare the outcomes of multiport VATS and uniport VATS in form of postoperative pain, hospital stay, the volume of blood loss, duration of operation, duration of postoperative drainage, and conversion rate. Although lacks a high level of evidence, this short review showed that uniport VATS might be a preferred alternative approach in thoracic surgery. Patients with uniport VATS have shorter hospital stays, less pain, early recovery, and sooner removal of the chest tube.
Magneto-Responsive Textiles for Non-Invasive Heating

Magneto-responsive textiles have emerged lately as an important carrier in various fields, including biomedical engineering. To date, most research has been performed on single magnetic fibers and focused mainly on the physical characterization of magnetic textiles. Herein, from simple woven and non-woven textiles we engineered materials with magnetic properties that can become potential candidates for a smart magnetic platform for heating treatments. Experiments were performed on tissue-mimicking materials to test the textiles’ heating efficiency in the site of interest. When the heat was induced with magneto-responsive textiles, the temperature increase in tissue-mimicking phantoms depended on several factors, such as the type of basic textile material, the concentration of magnetic nanoparticles deposited on the textile’s surface, and the number of layers covering the phantom. The values of temperature elevation, achieved with the use of magnetic textiles, are sufficient for potential application in magnetic hyperthermia therapies and as heating patches or bandages.
Delay-Hybrid-Dependent Stability for Systems With Large Delays

This paper investigates a problem of stability analysis for a class of nonlinear systems with a time-varying delay taking both large and small values in an alternating manner. This problem is a delay-dependent stability analysis one but it shares some features with delay-independent ones. Hence, traditional stability analysis techniques for systems with delay are not applicable. By building upon our previous works, we first introduce the concept of delay-hybrid-dependent stability, which characterizes the delays described above. The considered system is first represented as a system with a switched delay. Then by using switching techniques and Lyapunov–Krasovskii functionals (LKFs), a new stability criterion is developed. Next, in the linear context, it is shown how the needed LKFs can be constructed by developing an original design of LKFs.
Study on the interactions between two identical oscillation bubbles and a free surface in a tank

A boundary element method based on the incompressible potential flow theory is adopted to investigate the interaction between two identical oscillating bubbles and a free surface in a tank. An axisymmetric numerical model is established, and certain numerical techniques are proposed to address coefficient matrix singularity and fluid-structure intersection. Experiments with spark-generated bubbles in a cylindrical tank recorded by a high-speed camera are conducted, and the numerical results are validated. On this basis, a typical case of bubbles interacting with a free surface in a tank with relatively small inter-bubble and bubble-free surface distances is carefully studied. A crown-shaped water column at the free surface is observed both numerically and experimentally. The maximum volume of the lower bubble is found to be much larger than that of the upper one. The effects of the inter-bubble and bubble-wall distances on bubble dynamics and free surface motion are analyzed. The results can provide a use.
The Impact of Mobile Banking Services on the Customer Satisfaction of 
Commercial Banks in Sri Lanka

The primary focus of this study is to identify the decisive factors that affect customer satisfaction with Mobile Banking Services. The identified independent variables of the study are reliability, efficiency, flexibility, easy-to-navigate, and trust. Primary data was collected through a structured questionnaire from 120 mobile bank users of Commercial Banks in Sri Lanka. The study population was mobile banking users of commercial banks in the Colombo District of Sri Lanka. The hypotheses have been tested through multiple linear regression and the correlation coefficient has been used to identify the relationship between the dependent variable and independent variables. The findings of the study show that there is a statistically significant impact of the reliability, efficiency, easy-to-navigate, and trust dimensions of mobile banking services on customer satisfaction whereas flexibility has a statistically insignificant impact. Easy to navigate and reliability were the most influential dimensions compared to the rest of the mobile banking dimensions and the researcher recommended that commercial banks should expand the web and mobile app quality in order to achieve higher customer satisfaction with mobile banking services.
Bag-of-Bags of Words model over irregular graph partitions for image retrieval

The paper presents a novel approach, named bag-of-bags of words (BBoW), to address the problem of Content-Based Image Retrieval (CBIR) from image databases. The proposed bag-of-bags of words model extends the classical bag-of-words (BoW) model. An image is represented as a graph of local features on a regular grid. Then irregular partitions of images are built using different graph cutting methods. Each graph is then represented by its own signature. Compared to existing methods for image retrieval, such as Spatial Pyramid Matching (SPM), the BBoW model does not assume that similar parts of a scene always appear at the same location in images of the same category. The extension of the proposed model to pyramid gives rise to a method we name irregular pyramid matching. The experiments demonstrate the strength of our method for image retrieval when the partitions are stable across an image category. The experimental results for Caltech101 benchmark show that our method achieves comparative results as SPM, and is globally more stable.
By All Memes, I want to learn Arabic: Teachers’ and Students’ Perceptions of Using Memes in AFL Classrooms

As educational technology advances, teachers nowadays tend to incorporate technology into their classroom practices to enhance students’ learning and achieve better outcomes. Memes, which are pictures with texts and sometimes movements circulated mostly among social media users, are a powerful tool to reach learning goals in a fun and engaging way. Researchers explored memes’ effectiveness in various disciplines, yet the field of teaching Arabic as a foreign language (AFL) lacks investigation in this area. Therefore, this study aims to examine teachers’ and students’ perspectives on the use of memes in the classroom. This research also explores the disparities in perceptions and the reason(s) behind them. A mixed methodology is adopted where a questionnaire is utilized along with semi-structured interviews. Findings demonstrate a shared positive attitude towards using memes in AFL classrooms with suggestions by both groups. 72% of the teachers believe that memes are beneficial and 80.7% of the students reported that memes enhance foreign language learning.