Miracle-dz/UniFAR-FTUs huggingface dataset:
Association between Systemic Factors and Vitreous Fluid Cytokines in Proliferative Diabetic Retinopathy

Proliferative diabetic retinopathy (PDR) is a vision-threatening complication of diabetes mellitus (DM). Systemic and intraocular factors are intricately related to PDR, and vitreous fluid (VF) cytokines are representative intraocular biomarkers. However, the associations between systemic factors and VF cytokines and their influence on PDR pathology are unclear. This study aimed to examine the correlation between systemic factors and VF cytokines and analyze their contributions to the pathology of PDR using multivariate analyses. We conducted a retrospective observational study on 26 PDR eyes of 25 patients with type 2 DM, and 30 eyes of 30 patients with idiopathic macular hole or epiretinal membrane as controls. Fifteen systemic and laboratory tests including blood pressure (BP) and body mass index (BMI), and 27 cytokines in VF were analyzed. BP and BMI correlated positively with VF levels of IL-6 and IP-10 in PDR patients, while no significant correlation was found between systemic factors and VF cytokines in controls. MCP-1 and VEGF-A in VF separately clustered with different systemic factors in controls, but these cytokines lost the property similarity with systemic factors and acquired property similarity with each other in PDR. Systemic factors contributed to only 10.4%, whereas VF cytokines contributed to 42.3% out of 52.7% variance of the whole PDR dataset. Our results suggest that intraocular factors play a major role in the pathology of PDR, whereas systemic factors may have limited effects, and that BP and BMI control in PDR could be useful interventions to improve intraocular immune condition.
Epicardial adipocytes in the pathogenesis of atrial fibrillation: An update on basic and translational studies

Epicardial adipose tissue (EAT) is an endocrine organ containing a host of cell types and undoubtedly serving a multitude of important physiologic functions. Aging and obesity cause hypertrophy of EAT. There is great interest in the possible connection between EAT and cardiovascular disease, in particular, atrial fibrillation (AF). Increased EAT is independently associated with AF and adverse events after AF ablation (e.g., recurrence of AF, and stroke). In general, the amount of EAT correlates with BMI or visceral adiposity. Yet on a molecular level, there are similarities and differences between epicardial and abdominal visceral adipocytes. In comparison to subcutaneous adipose tissue, both depots are enriched in inflammatory cells and chemokines, even in normal conditions. On the other hand, in comparison to visceral fat, epicardial adipocytes have an increased rate of fatty acid release, decreased size, and increased vascularity. Several studies have described an association between fibrosis of EAT and fibrosis of the underlying atrial myocardium. Others have discovered paracrine factors released from EAT that could possibly mediate this association. In addition to the adjacent atrial cardiomyocytes, EAT contains a robust stromal-vascular fraction and surrounds the ganglionic plexi of the cardiac autonomic nervous system (cANS). The importance of the cANS in the pathogenesis of atrial fibrillation is well known, and it is quite likely that there is feedback between EAT and the cANS. This complex interplay may be crucial to the maintenance of normal sinus rhythm or the development of atrial fibrillation. The extent the adipocyte is a microcosm of metabolic health in the individual patient may determine which is the predominant rhythm.
A Distributed Positioning Scheme Based on Neural Network for Radiation Source

To avoid the high calculating requirement of the central node in the centralized positioning system, a distributed scheme with multiple localization sub-networks to localize an unknown radiation source (RS) is discussed in this paper. Furthermore, in order to reduce the adverse effect of the potential information loss in the parameter estimation of the traditional two-step localization algorithm, a neural network to deduce the objective position from the hybrid localization parameters is designed for each sub-network to replace the solving of positioning equations involved in the two-step localizer. Finally, in order to obtain more accurate localization results, two fusion methods based on the weighted sum and the neural network are given at the final control center to fuse the localization results of all the sub-networks. The experimental results show that the proposed scheme significantly outperforms the traditional single-parameter based two-step localization method even though the latter one adopts the centralized positioning strategy. Furthermore, the neural network based fusion method can improve the final positioning precision obviously for signal to noise ratio (SNR) higher than 10dB.
Natural rennet sterilisation by non-thermic methods for fresh cheese manufacture

Abstract Natural rennet is widely used in artisanal cheese shops to produce fresh cheese with particular characteristics such flavour, in comparison to artificial rennet. This rennet is produced by the cheesemakers under non-hygienic conditions. The use of non-thermal technologies such as ultrasound and UV light can be an alternative of rennet sanitisation. The objective of the present work was to evaluate the effect of applying of different times of ultrasound or ultraviolet on the microbial growth in natural rennet for fresh cheese manufacture, its curd yield and curd hardness texture. Natural rennet was prepared and divided into three samples, one of which was exposed to ultrasound for 5, 10 and 15 min, the second one received UV radiation for 30, 60 and 90 min, and the last one was considered as the control treatment. A microbial test was conducted to analyse total coliforms, Escherichia coli, Staphylococcus aereus and Salmonella spp. Fresh cheeses were manufactured using the different rennets and the coagulant effect was tested by way of with a texture test (hardness). The results showed the highest microbial growth in the control treatment; none of the US treatments allowed microbial growth and the UV radiation was effective for all microorganisms at a 90 min exposure. All rennet treatments maintained their coagulant effect. In conclusion, the use of non-thermal methods was effective for rennet sterilisation, although it affected curd yield (2% less). Highlights Ultrasound inhibits pathogenic microorganisms growing in natural rennet. Sterilisation by non-thermal methods does not affect the coagulation process. A 42 kHz ultrasound at, 70 W power caused the best reduction of pathogenic bacteria.
An Investigation of Warm Rainfall Microphysics in the Southern Appalachians: Orographic Enhancement via Low-Level Seeder-Feeder Interactions

AbstractObservations of the vertical structure of rainfall, surface rain rates, and drop size distributions (DSDs) in the southern Appalachians were analyzed with a focus on the diurnal cycle of rainfall. In the inner mountain region, a 5-yr high-elevation rain gauge dataset shows that light rainfall, described here as rainfall intensity less than 3 mm h−1 over a time scale of 5 min, accounts for 30%–50% of annual accumulations. The data also reveal warm-season events characterized by heavy surface rainfall in valleys and along ridgelines inconsistent with radar observations of the vertical structure of precipitation. Next, a stochastic column model of advection–coalescence–breakup of warm rain DSDs was used to investigate three illustrative events. The integrated analysis of observations and model simulations suggests that seeder–feeder interactions (i.e., Bergeron processes) between incoming rainfall systems and local fog and/or low-level clouds with very high number concentrations of small drops (<0.2 .
Regression Analysis & Visualization of Twitch Dataset

This paper examines Twitch dataset in order to determine and unveil various aspects and relationship among attributes of dataset. Twitch is an online platform used for video game live streaming. The models used by authors in their analysis are Logistic regression, Naïve Bayes, K-Nearest Neighbour and Decision tree. As demonstrated by the authors, K-Nearest Neighbour and logistic regressions outperform other model by yielding an accuracy of 97.7% and 97.4 %.
Effectiveness of Transition Care Intervention Targeted to High-Risk Patients to Reduce Readmissions: Study Protocol for the TARGET-READ Multicenter Randomized-Controlled Trial

Hospital readmissions within 30 days represent a burden for the patients and the entire health care system. Improving the care around hospital discharge period could decrease the risk of avoidable readmissions. We describe the methods of a trial that aims to evaluate the effect of a structured multimodal transitional care intervention targeted to higher-risk medical patients on 30-day unplanned readmissions and death. The TARGET-READ study is an investigator-initiated, pragmatic single-blinded randomized multicenter controlled trial with two parallel groups. We include all adult patients at risk of hospital readmission based on a simplified HOSPITAL score of ≥4 who are discharged home or nursing home after a hospital stay of one day or more in the department of medicine of the four participating hospitals. The patients randomized to the intervention group will receive a pre-discharge intervention by a study nurse with patient education, medication reconciliation, and follow-up appointment with their referring physician. They will receive short follow-up phone calls at 3 and 14 days after discharge to ensure medication adherence and follow-up by the ambulatory care physician. A blind study nurse will collect outcomes at 1 month by phone call interview. The control group will receive usual care. The TARGET-READ study aims to increase the knowledge about the efficacy of a bundled intervention aimed at reducing 30-day hospital readmission or death in higher-risk medical patients.
Association of obesity with the development of end stage renal disease in IgA nephropathy patients

Background and aim Immunoglobulin A nephropathy (IgAN) is the most common primary glomerulonephritis worldwide. We aimed to evaluate whether obesity is a risk factor for IgAN patients. Methods A total of 1054 biopsy-proven IgAN patients were analyzed in this retrospective study. Patients were divided into four groups according to their body weight index (BMI) at the period of renal biopsy: underweight group (BMI< 18.5, N=75), normal weight group (18.5≤BMI<24, N=587), overweight group (24≤BMI<28, N=291) and obesity group (28≤BMI, N=101). The endpoint of our study was end stage renal disease (ESRD: eGFR <15 mL/min/1.73 m2 or having renal replacement treatment). Kaplan-Meier analyses and Cox proportional hazard models were performed to evaluate renal survival. Propensity-score matching (PSM) was performed to get the matched cohort to evaluate the role of obesity in IgAN patients. Besides, the effect modification of obesity and hypertension in IgAN patients was clarified by the synergy index. Results IgAN patients complicated with obesity had more severe renal dysfunction at the time of renal biopsy than those with optimal body weight. In addition, patients with obesity tended to have higher risk of metabolic disorders, such as hyperuricemia (64.4% vs 37%, p<0.001), hypertriglyceridemia (71.3% vs 32.5%, p<0.001) and hypercholesterolemia (46.5% vs 35.6%, p=0.036). It was observed that obesity patients had higher rate of unhealthy behaviors, such as smoking (27.7% vs 16.4%, p=0.006) and alcohol drinking (29.7% vs 19.9%, p=0.027). Although obesity was not confirmed as an independent risk factor for IgAN patients, we found that IgAN patients with obesity presented with higher incidence of hypertension, as well as lower event-free renal survival rate (log-rank p < 0.001), especially in patients with 24-h urine protein ≥ 1g (log-rank p =0.002). In addition, the synergy index showed that there was positive interaction between obesity and hypertension in IgAN. Conclusion Obesity is an important risk factor for IgAN patients when combined with hypertension. Hypertension appears to be common in obese IgAN patients.
Electronic Cigarette Use during Pregnancy: Is It Harmful?

Although combustible cigarette smoking rates have declined in recent years, alternative tobacco product use, particularly electronic cigarette use (“vaping”), has increased among young adults. Recent studies indicate that vaping during pregnancy is on the rise, possibly due to the perception that it is a safer alternative to combustible cigarette smoking. However, e-cigarette aerosols may contain several newer, potentially toxic compounds, including some known developmental toxicants that may adversely impact both the mother and the fetus. However, there is paucity of studies that have examined the effects of vaping during pregnancy. While the adverse perinatal outcomes of cigarette smoking during pregnancy are well established, the specific risks associated with inhaling vaping aerosols during pregnancy requires more research. In this article, we discuss the existing evidence and knowledge gaps on the risks of vaping during pregnancy. Studies that investigate vaping-associated systemic exposure and its effects (i.e., biomarker analyses) and maternal and neonatal clinical health outcomes are needed to reach more robust conclusions. We particularly emphasize the need to go beyond comparative studies with cigarettes, and advocate for research that objectively evaluates the safety of e-cigarettes and other alternative tobacco products.
A Novel Mandelbrot Fractal Microstrip Antenna with Fourth Set Degree and Different Iteration Numbers

This paper proposes a novel fractal microstrip antenna based on the Mandelbrot-set geometries with an iteration number of 3, 5 and 20. The Mandelbrot fractal geometry is designed from a circular geometry and can intrinsically enable a size reduction for patch elements. In the design, the key step of converting a bitmap shape into an emulate-able antenna design is introduced and the influence of Mandelbrot fractal patch geometry with different iterations on the performance of antennas is simulated and analyzed. Simulations show that the proposed Mandelbrot fractal antennas have a good performance in gains, radiation patterns, and reduction of dimensions, and could be very useful for millimeter-wave communications.
Migratory Wild Birds as Potential Long-Distance Transmitters of Toxoplasma gondii Infection

Toxoplasma gondii is a worldwide distributed zoonotic protozoan capable of infecting a wide range of mammals (including humans) and birds as intermediate hosts. Migratory wild birds, through interconnecting countries along their flyways, can play a role in the spatial spread of T. gondii and could contribute to its sylvatic cycle. Additionally, hunted wild birds used for meat consumption could represent a further source of human infection. To determine the presence of T. gondii in wild birds, a total of 50 individuals belonging to the Anseriformes and Charadriiformes orders were sampled during the 2021–2022 hunting season in Northern Italy. Cardiac muscle samples of three Northern shovelers (Anas clypeata), two wild mallards (A. platyrhynchos), one Eurasian teal (A. crecca), and one Northern lapwing (Vanellus vanellus) were positive for the molecular detection of T. gondii based on a targeted amplification of the B1 gene. A 14% (7/50) overall positivity was observed in the sampled population. Results from this study suggest a moderate exposure of wild aquatic birds to T. gondii, highlighting the importance of a further characterization of T. gondii in its wildlife hosts.
Mathematical Analysis of a Soccer Game. Part I: Individual and Collective Behaviors

Detailed time series analysis of a soccer match is given based on the detailed data of the 2D motions of all 22 players and of the ball for the match. The whole analysis includes two parts. In Part I, the individual and collective behaviors of the players of the two teams as well as the motion of the ball are presented as various time series. Geometrical centers, radii, expansion speeds, possession functions of the two teams are defined and calculated as functions of time. Major ranges of all players as well as of different groups of players (defenders, midfielders, forwards) of the two teams during the entire first half, the attacking phase of team A and the attacking phase of team B are calculated, respectively, showing the structures of the two teams during different phases. Distance coverage of each player and the mean distances covered by different groups of players (defenders, midfielders, forwards) during different phases are calculated. The time portions of possession of the ball by each team and the time portions of different phases are also calculated. In Part II, energy and spectral analysis and various correlations will be derived. The relation between various parameters and potential indicators will be discussed. The major purpose of the present study is to offer some general mathematical tools for the detailed analysis and to reveal some general features of soccer match when the detailed 2D data are available. The results would offer the raw materials for various potential indicators which may eventually be used in the coaching process to enhance the performance and in the prediction of the results of soccer matches.
The relationship between return on investment and Jordanian banks value

Bank stakeholders such as investors, creditors, and other stakeholders of a bank, expect full disclosure to evaluate banks’ financial statements. To achieve this goal, bank managers can increase the value of a bank by enhancing the return on their investments. This study examines the impact of financial performance on the market value of Jordanian public shareholding banks. The study model examines the effect of return on investment (ROI), debt ratio, dividend policy, and current ratio while controlling for bank size. Bank value is measured using the market value. The sample is Jordanian banks listed on the Amman Stock Exchange between 2005 and 2020. To investigate the link between the study variables, the random effect model, panel least squares approach, correlation analysis, and descriptive measures are used. The findings indicate that banks own 3.025 JD from current assets for each JD from current liabilities. In addition, the debt ratio is 38.4% from total assets. Adj R2 for the study model is 22.1%. The results show that profitability, leverage, and bank size significantly affect the value of Jordanian banks, while dividend policy and liquidity do not have a significant impact.
Pipeline Leakage Detection Using Acoustic Emission and Machine Learning Algorithms

Pipelines play a significant role in liquid and gas resource distribution. Pipeline leaks, however, result in severe consequences, such as wasted resources, risks to community health, distribution downtime, and economic loss. An efficient autonomous leakage detection system is clearly required. The recent leak diagnosis capability of acoustic emission (AE) technology has been well demonstrated. This article proposes a machine learning-based platform for leakage detection for various pinhole-sized leaks using the AE sensor channel information. Statistical measures, such as kurtosis, skewness, mean value, mean square, root mean square (RMS), peak value, standard deviation, entropy, and frequency spectrum features, were extracted from the AE signal as features to train the machine learning models. An adaptive threshold-based sliding window approach was used to retain the properties of both bursts and continuous-type emissions. First, we collected three AE sensor datasets and extracted 11 time domain and 14 frequency domain features for a one-second window for each AE sensor data category. The measurements and their associated statistics were transformed into feature vectors. Subsequently, these feature data were utilized for training and evaluating supervised machine learning models to detect leaks and pinhole-sized leaks. Several widely known classifiers, such as neural networks, decision trees, random forests, and k-nearest neighbors, were evaluated using the four datasets regarding water and gas leakages at different pressures and pinhole leak sizes. We achieved an exceptional overall classification accuracy of 99%, providing reliable and effective results that are suitable for the implementation of the proposed platform.
Russia's Nuclear Icebreaker Fleet

Nuclear icebreakers remain important for the economic survival of Russia's Arctic regions and are a central element of the Northern Sea Route development strategy. Reactor life extension activities are critical to sustaining the nuclear fleet, as several of the currently operated nuclear icebreakers are reaching the end of design service life. Russia is also finishing a new icebreaker and is planning to build additional nuclear ships within the next 10–15 years. Nuclear icebreaker reactors are fueled with highly-enriched uranium (HEU), which has to be reliably protected against theft and diversion.
Design of X-Band Microstrip Leaky-Wave Antenna with Horizontal Beam Scanning

A periodic leaky-wave antenna with horizontal backward-to-forward beam scanning is designed in this paper. The proposed leaky-wave antenna is based on a microstrip structure with interlaced additional patches and defected ground on the top and the bottom layers, respectively. The equivalent currents on the edges of the ground plane and the patch are in the same direction, and thus the two edges can be equivalent to a dipole unit, contributing to the horizontal energy leakage. Subsequently, a pair of stubs are loaded on the strip to suppress the open-stop band effect. As validation, a prototype with broadside frequency of 10 GHz is designed, fabricated, and measured, aiming for applications in X-band. The measured results show that the proposed antenna scans from-50° through the broadside to+27° along the horizontal plane, as the frequency varies from 8.0 GHz to 12.0 GHz.
Comparative Study of Path Tracking Controllers on Low Friction Roads for Autonomous Vehicles

This paper presents a comparison among path tracking controllers on low-friction roads for autonomous vehicles. There are two goals in this paper. The first is to check the performance of path tracking controllers on low-friction roads, and the second is to check the effectiveness of four-wheel steering (4WS) for path tracking. To fully investigate the performance of path-tracking controllers on low-friction roads in this paper, the pure pursuit method, Stanley method, PID control, linear quadratic regulator, sliding mode control and model predictive control are designed and compared in terms of some measures. Front and four-wheel steering are adopted as actuators for path tracking. To utilize 4WS in the pure pursuit method, Stanley method and PID control, a yaw rate tracking control is adopted. With the designed path tracking controllers, a simulation is conducted on vehicle simulation software. From the simulation results, it is shown that most path tracking controllers are effective for path tracking on low-friction roads if finely tuned, and that 4WS is not recommended for path tracking on low-friction roads.