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This study, conducted at two university-based infectious disease clinics, included 216 patients with chronic hepatitis C. The primary objective was to assess the positive and negative predictive values, sensitivity, and specificity of achieving a sustained virological response (SVR) at 4 weeks compared to 12 weeks post-therapy. The results demonstrated a maximum sensitivity of 100% for achieving SVR at 12 weeks after reaching SVR at 4 weeks for all analyzed genotypes, except for genotype 1b treated with EBR/GZR therapy, where the specificity was 75%. Additionally, younger age and less advanced liver fibrosis were identified as independent predictors of achieving a sustained virological response at both 4 and 12 weeks. The significant normalization of various biochemical parameters was observed after treatment, indicating an overall improvement in liver function. This study suggests that shortening the monitoring period to 4 weeks might be effective for younger patients without significant fibrosis, potentially reducing loss to follow-up, which is a critical issue in HCV treatment. These findings align with the “test and treat” approach. Further research is needed to confirm these findings and incorporate them into official guidelines, which could simplify and enhance the effectiveness of HCV treatment protocols, aiding global efforts to eliminate HCV as a public health issue by 2030.

This study aimed to comprehensively understand the performance and degradation of both p- and n-channel vertical double diffused MOS (VDMOS) transistors under bias temperature stress. Conducted experimental investigations involved various stress conditions and annealing processes to analyze the impacts of BT stress on the formation of oxide trapped charge and interface traps, leading to threshold voltage shifts. Findings revealed meaningful threshold voltage shifts in both PMOS and NMOS devices due to stresses, and the subsequent annealing process was analyzed in detail. The study also examined the influence of stress history on self-heating behavior under real operating conditions. Additionally, the study elucidated the complex correlation between stress-induced degradation and device reliability. The insights contribute to optimizing the performance and permanence of VDMOS transistors in practical applications, advancing semiconductor technology. This study underscored the importance of considering stress-induced effects on device reliability and performance in the design and application of VDMOS transistors.

Legionella pneumophila is a rarely diagnosed microorganism in Serbia. It causes legionellosis, usually a mild respiratory infection. However, in some cases it can be severe and even life threatening. In June 2020, during the COVID-19 pandemic, a patient with symptoms of the aforesaid infection, namely severe pneumonia and acute respiratory distress syndrome, was admitted to the hospital. The multiplex polymerase chain reaction (PCR) test (The BioFire FilmArray Pneumonia Panel plus) detected the presence of L. pneumophila in the patient’s bronchial secretions. The specific culture for the detection of that organism, however, remained sterile. The patient’s paired sera had been sent for serology and the results in both of them came back positive for Legionella spp . 1–6, while the assays specific for each one of the 10 serogroups detected more than a fourfold increase of antibody titers in an uncommon serogroup 2 only. The patient was treated with moxifloxacin; he recovered well and was discharged after 26 days of hospitalization. Having being diagnosed with the L. pneumophila infection correctly through the multiplex PCR test, the patient was given the right therapy with moxifloxacin. The serologic assays corroborated this result and revealed the uncommon group 2, thus confirming the necessity of carrying out all the tests available to attain the exact diagnosis of legionellosis.

Abstract Background The global epidemic of nosocomial diarrhea caused by Clostridioides (Clostridium) difficile started in 2000, with high mortality rates and emergence of a new hypervirulent strain NAP1/BI/027. The aim of this study was to assess the presence of ribotype 027 and other C. difficile ribotypes in a Serbian University Hospital, compare the temporal variability of ribotypes 3 years apart, as well as to compare clinical, demographic and laboratory characteristics and disease outcome among patients infected with 027 and non-027 ribotype. This was a prospective observational cohort study addressing 4-month intervals during 2014/2015 and 2017/2018. Results Ribotyping was performed in 64 non-duplicate C. difficile strains. Ribotype 027 was the most prevalent, and was detected in 53 (82.8%) patients (43/45 and 10/19 patients in 2014–2015 and 2017/2018, respectively). Other detected ribotypes were 001/072 in 4 (6.3%), 002 in 4 (6.3%), 014/020 in 2 (3.1%) and 176 in 1 (1.5%) patient. The percentage of the patients infected with ribotype 027 significantly decreased during the 3-year period, from 95.6 to 52.6% (p

The Western Balkans (WB) region is highly prone to water erosion processes, and therefore, the estimation of rainfall erosivity (R-factor) is essential for understanding the complex relationships between hydro-meteorological factors and soil erosion processes. The main objectives of this study are to (1) estimate the spatial-temporal distribution R-factor across the WB region by applying the RUSLE and RUSLE2 methodology with data for the period between 1991 and 2020 and (2) apply cluster analysis to identify places of high erosion risk, and thereby offer a means of targeting suitable mitigation measures. To assess R-factor variability, the ERA5 reanalysis hourly data (0.25° × 0.25° spatial resolution) comprised 390 grid points were used. The calculations were made on a decadal resolution (i.e., for the 1990s, the 2000s, and the 2010s), as well as for the whole study period (1991–2020). In order to reveal spatial patterns of rainfall erosivity, a k-means clustering algorithm was applied. Visualization and mapping were performed in python using the Matplotlib, Seaborn, and Cartopy libraries. Hourly precipitation intensity and monthly precipitation totals exhibited pronounced variability over the study area. High precipitation values were observed in the SW with a >0.3 mm h−1 average, while the least precipitation was seen in the Pannonian Basin and far south (Albanian coast), where the mean intensity was less than an average of 0.1 mm h−1. R-factor variability was very high for both the RUSLE and RUSLE2 methods. The mean R-factor calculated by RUSLE2 was 790 MJ mm ha−1·h−1·yr−1, which is 58% higher than the mean R-factor obtained from RUSLE (330 MJ mm ha−1·h−1·yr−1). The analysis of the R-factor at decadal timescales suggested a rise of 14% in the 2010s. The k-means algorithm for both the RUSLE and RUSLE2 methods implies better spatial distribution in the case of five clusters (K = 5) regarding the R-factor values. The rainfall erosivity maps presented in this research can be seen as useful tools for the assessment of soil erosion intensity and erosion control works, especially for agriculture and land use planning. Since the R-factor is an important part of soil erosion models (RUSLE and RUSLE2), the results of this study can be used as a guide for soil control works, landscape modeling, and suitable mitigation measures on a regional scale.

Copyright of Veterinarski Glasnik is the property of Veterinarski Glasnik and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Veterinarski Glasnik is the property of Veterinarski Glasnik and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Improperly scheduled signal timing plans are one of the main reasons for reduced efficiency of traffic signals at coordinated urban arterials. Recently, most urban arterial roads are equipped with intelligent transportation systems devices capable of reporting the collected data on high temporal and spatial resolution, which gives us the opportunity to overcome traditional signal timing planning flaws. Previous studies have proposed methods for scheduling signal timing plans based on small quantities of data combined with various optimization approaches that ultimately require domain expert intervention to fine-tune proposed solutions. Consequently, the signal timing plans scheduling problem is still being addressed without a comprehensive approach. In this study, we propose a novel data-driven procedure based on visual analytics principles to identify the dominant traffic profiles and appropriate scheduling of signal timing plans. The medium-resolution volume data collected over a one-year period on a real-world corridor consisting of 12 signalized intersections were used to validate the proposed methodology. Applied principles from the visual analytics domain allow for a better understanding of traffic characteristics and ultimately alleviate the development of appropriate signal timing schedules. The results show that the proposed method more reliably schedules signal timing plans when compared to current practice.

Abstract We recently proposed a concept, called Combined Alternate-Direction Lane Assignment and Reservation-based Intersection Control (CADLARIC), for organizing directionally unrestricted traffic flows in automated vehicle environment. The conflicts between through movements are handled by a reservation-based algorithm while the turning conflicts at the intersections are avoided altogether. This paper extends this research by analyzing the impacts that CADLARIC’s parameters, used to control the conflict-resolution processes, have on the efficiency and surrogate safety indicators. The investigated parameters include: (i) buffer time in cell’s reservation schedule; (ii) allowed speed to cross the reserved cell; (iii) distance from intersection from which a vehicle can make reservation, and (iv) duration of the lane-change process. For most of the investigated parameters, the numerical results show that less efficient operations lead not just to an increase in delay time and number of stops but also increase number of conflicting situations, because of vehicular queues formed within the intersection zone.

Optimizing traffic signals to improve traffic progression relies on minimizing mobility performance measures (e.g., delays and stops). However, delay and stop minimizations do not necessarily lead to minimal sustainability measures (e.g., fuel consumption and emissions). For that reason, researchers have focused, for decades, on integrating traffic models, signal optimization models, and fuel consumption and emissions models to minimize sustainability metrics while keeping acceptable levels of mobility metrics. Therefore, this paper reviews, classifies, and analyzes studies found in the literature regarding optimizing sustainable traffic signals. This paper provides researchers with a good starting point to further develop solutions which can address sustainable traffic control. To achieve that, this study details the most notable sustainable signal timing optimization studies from six perspectives: traffic models, fuel consumption and emissions models, optimization methods, objective functions, operating conditions, and reported sustainability savings. Outcomes of this research show that the previous studies deployed many combinations of elements from the six-perspective mentioned above, leading to a wide range of fuel consumption and emissions savings. The study also concludes that the available fuel consumption and emissions models are relatively old. Hence, future research is needed to develop new fuel consumption and emissions models based on recently collected data.

Express lanes (ELs) implementation is a proven strategy to deal with freeway traffic congestion. Dynamic toll pricing schemes effectively achieve reliable travel time on ELs. The primary inputs for the typical dynamic pricing algorithms are vehicular volumes and speeds derived from the data collected by sensors installed along the ELs. Thus, the operation of dynamic pricing critically depends on the accuracy of data collected by such traffic sensors. However, no previous research has been conducted to explicitly investigate the impact of sensor failures and erroneous sensors’ data on toll computations. This research fills this gap by examining the effects of sensor failure and faulty detection scenarios on ELs tolls calculated by a dynamic pricing algorithm. The paper’s methodology relies on applying the dynamic toll pricing algorithm implemented in the field and utilizing the fundamental speed-volume relationship to ‘simulate’ the sensors’ reported data. We implemented the methodology in a case study of ELs on Interstate-95 in Southeast Florida. The results have shown that the tolls increase when sensors erroneously report higher than actual traffic demand. Moreover, it has been found that the accuracy of individual sensors and the number of sensors utilized to estimate traffic conditions are critical for accurate toll calculations.