Spatial assessment of soil erosion is an important indicator of ecological soil change and global environmental changes. This is especially true for countries with rich forest cover such as Bosnia and Herzegovina. In this study, the risk of soil erosion was assessed using the Revised Universal Soil Loss Equation (RUSLE) model and the impact of changes in the forest ecosystem, current conditions were compared with possible future forest management scenarios, and measures and solutions were proposed to reduce soil erodibility in vulnerable areas of the Pale Municipality in Bosnia and Herzegovina. The studied area is at increased risk of soil erosion due to natural conditions (mountain relief, climate change, and the frequency of extreme climatic events—drought and heavy rains, which occur more and more frequently in a short period of time) and due to anthropogenic factors, such as large-scale deforestation and conversion of mountain areas for tourism purposes, tracing and construction of ski slopes and ski resorts in general, and expansion of settlements. All this leads to threats to water conservation areas, landslides, floods, forest fires, and additional reduction of forest areas due to drying of forests and expansion of settlements. GIS as a tool provides us with a quick and accurate way to find possible solutions to problems resulting from the intensive use and inadequate monitoring. In this study, we have tried to offer possible solutions and show the benefits that can be obtained by varying the factors that affect soil erodibility and depend on vegetation cover, that is, land use (C-factor). This study presents the application of RUSLE methods in combination with GIS for the purpose of planning economic activities, such as winter tourism development in the community of Pale. An increase in soil loss due to inappropriate land use was found, with the average annual soil loss due to deforestation in the ski area increasing to 909.43 t ha−1 year−1.

Immunotherapy, based on immune checkpoint inhibitors (ICIs) targeting the programmed cell death ligand 1 (PD-L1) and/or programmed death receptor 1 (PD-1), has substantially improved the outcomes of patients with various cancers. However, only ~30% of patients benefit from ICIs. Tumor PD-L1 expression, assessed by immunohistochemistry (IHC), is the most widely validated and used predictive biomarker to guide the selection of patients for ICIs. PD-L1 assessment may be challenging due to the necessity of different companion diagnostic assays for required specific ICIs and a relatively high level of inter-assay variability in terms of performance and cutoff levels. In this review, we discuss the role of PD-L1 IHC as a predictive test in immunotherapy (immuno-oncology), highlight the complexity of the PD-L1 testing landscape, discuss various preanalytical, analytical, and clinical issues that are associated with PD-L1 assays, and provide some insights into optimization of PD-L1 as a predictive biomarker in immuno-oncology.

In order to decide the appropriate arrangements of fictitious charges in the charge simulation method, the use of the Monte Carlo method is proposed for the estimation of the probability density function of two variables, the radius ratio, and the angle ratio. Τhe scale and shape parameters of the Weibull's distribution are determined by the maximum likelihood estimator. The obtained results are used to calculate the electric field at arbitrary points in the neighborhood of high voltage transmission lines. The comparisons between the results computed by this method, the results calculated by the genetic algorithm, and those measured, confirm the effectiveness and accuracy of the proposed method.

Introduction Data on safety and effectiveness of RPV from the real-world setting as well as comparisons with other NNRTIs such as efavirenz (EFV) remain scarce. Methods Participants of EuroSIDA were included if they had started a RPV- or an EFV-containing regimen over November 2011-December 2017. Statistical testing was conducted using non-parametric Mann–Whitney U test and Chi-square test. A logistic regression model was used to compare participants’ characteristics by treatment group. Kaplan–Meier analysis was used to estimate the cumulative risk of virological failure (VF, two consecutive values > 50 copies/mL). Results 1,355 PLWH who started a RPV-based regimen (11% ART-naïve), as well as 333 initiating an EFV-containing regimen were included. Participants who started RPV differed from those starting EFV for demographics (age, geographical region) and immune-virological profiles (CD4 count, HIV RNA). The cumulative risk of VF for the RPV-based group was 4.5% (95% CI 3.3–5.7%) by 2 years from starting treatment (71 total VF events). Five out of 15 (33%) with resistance data available in the RPV group showed resistance-associated mutations vs. 3/13 (23%) among those in the EFV group. Discontinuations due to intolerance/toxicity were reported for 73 (15%) of RPV- vs. 45 (30%) of EFV-treated participants (p = 0.0001). The main difference was for toxicity of central nervous system (CNS, 3% vs. 22%, p < 0.001). Conclusion Our estimates of VF > 50 copies/mL and resistance in participants treated with RPV were similar to those reported by other studies. RPV safety profile was favourable with less frequent discontinuation due to toxicity than EFV (especially for CNS).

The evolution of fifth-generation (5G) networks needs to support the latest use cases, which demand robust network connectivity for the collaborative performance of the network agents, such as multirobot systems and vehicle-to-anything (V2X) communication. Unfortunately, the user device’s limited communication range and battery constraint confirm the unfitness of known robustness metrics suggested for fixed networks, when applied to time-switching communication graphs. Furthermore, the calculation of most of the existing robustness metrics involves nondeterministic polynomial (NP)-time complexity, and hence are best fitted only for small networks. Despite a large volume of works, the complete analysis of a low-complexity temporal robustness metric for a communication network is absent in the literature, and the present work aims to fill this gap. More in detail, our work provides a stochastic analysis of network robustness for a massive machine-type communication (mMTC) network. The numerical investigation corroborates the exactness of the proposed analytical framework for the temporal robustness metric. Along with studying the impact on network robustness of various system parameters, such as cluster head (CH) probability, power threshold value, network size, and node failure probability, we justify the observed trend of numerical results probabilistically.

Studies focusing on affective factors/emotions in learning are a mainstay in second language (L2) research. L2 teacher-focused research has also made advances in this domain and established the importance of affective factors for both learners and teachers. Despite the field’s understanding of the emotional complexity of L2 teaching, much remains undiscovered. The aim of this qualitative research was to investigate L2 teachers’ (N = 21) emotional experiences in the classroom. Specifically, by using a teacher diary we set out to document: (1) the emotions teachers reported in their place of work and during their interactions with learners, (2) the classroom activities teachers were engaged in when they experienced specific emotions, and (3) the regulatory practices they engaged in when dealing with both pleasant and unpleasant emotions. Our findings show that L2 teachers most frequently experienced pleasant emotions such as satisfaction, joy, and pride. In regard to unpleasant emotions, they primarily revealed frustration, irritability, and disappointment. Both types of emotions were mostly instigated by their learners and were related to L2 classroom activities in the areas of grammar, speaking, and reading. The teachers admitted to regulating both pleasant and unpleasant emotions. Finally, teachers revealed that they used down-regulation, reappraisal, deep breathing, and suppression as the most frequent emotion regulation strategies.

Background: The gene encoding the extracellular matrix (ECM) protease ADAMTS-7 was associated with coronary artery disease (CAD) in genome-wide association studies. ADAMTS-7 is expressed at all stages in human plaques and mice lacking Adamts-7 displayed reduced atherosclerotic plaque formation. While these findings render ADAMTS-7 a promising therapeutic target, the underlying mechanisms remain unknown. Methods and Results: Here, we sought to identify downstream mechanisms of ADAMTS-7 in atherosclerotic plaque formation. Targets of Adamts-7 were identified by high-resolution mass spectrometry of atherosclerotic plaques in Apoe-/- and Apoe-/-Adamts7-/- mice. ECM proteins were identified using solubility profiling. The endogenous inhibitor of matrix metalloproteinases (MMP) Timp-1 was identified as a novel target of Adamts-7. Adamts-7 and Timp-1 were found to be co-localized in atherosclerotic plaques and co-immunoprecipitation (Co-IP) studies revealed TIMP-1 as the first putative target to bind to the catalytic domain of ADAMTS-7. In vitro degradation assays demonstrated that ADAMTS-7 degrades TIMP-1. Co-IP furthermore revealed less binding of TIMP-1 to its canonical target MMP-9 when ADAMTS-7 was present. In line, scaffolding and degradation of TIMP-1 by ADAMTS-7 impaired TIMP-1-mediated inhibition of MMP-9 in vitro. As a downstream mechanism, we investigated collagen content in atherosclerotic plaques of Apoe-/- and Apoe-/- Adamts7-/- mice after Western diet. Collagen stainings of the aortic root revealed less collagen as a readout of higher MMP-9 activity in Apoe-/- as compared to Apoe-/- Adamts7-/- mice. Since ADAMTS-7 might exert its pro-atherogenic effects through interaction with TIMP-1, we established a TIMP-1-ADAMTS-7-interaction assay based on Förster resonance energy transfer (FRET) to identify inhibitors of this protein-protein interaction. Conclusion and Outlook: TIMP-1 represents a novel downstream target of ADAMTS-7 that can explain the role of this novel risk factor in CAD. Our FRET-based protein-protein interaction assay may be used for high-throughput screening to identifiy inhibitors and prevent the initiation or slow the progression of atherosclerosis.

Electrochemical low-cost sensors, suitable for the monitoring of different air quality parameters such as carbon monoxide or nitrogen dioxide levels, are viable tools for creating affordable handheld devices for short-term or dense air quality monitoring networks for long-term measurements and IoT applications. However, most devices that utilize such sensors are based on proprietary hardware and software and, therefore, do not offer users the ability to replace sensors or interact with the hardware, software, and data in a meaningful way. Initiatives that focus on an open framework for air quality monitoring, such as the AirSensEUR project, offer competitive open source alternatives. In this study, we examined the feasibility of the application of such devices. Five AirSensEUR units equipped with chemical sensors were placed next to a reference air quality measuring station in Vienna, Austria. During co-location, concentrations of 0.20 ± 0.06 ppm, 7.14 ± 8.66 ppb, and 17.58 ± 9.90 ppb were measured for CO, NO, and NO2, respectively. The process of evaluating the performance of the low-cost sensors was carried out and compared to similar studies. Data analysis was carried out with the help of the basic functions in MS Excel. We investigated the linear correlation between the sensor and reference data and thus calculated the coefficient of determination, the average and maximum residuals, and the correlation coefficient. Furthermore, we discuss sensor properties in regard to selectivity and long-term stability.

BACKGROUND: Medical devices (MDs) represent the backbone of the modern healthcare system. Considering their importance in daily medical practice, the process of manufacturing, marketing and usage has to be regulated at all levels. Harmonized evidence-based conformity assessment of MDs during PMS relying on traceability of medical device measurements can contribute to higher reliability of MD performance and consequently to higher reliability of diagnosis and treatments. OBJECTIVE: This paper discusses issues within MD post-market surveillance (PMS) mechanisms in order to set a path to harmonization of MD PMS. METHODS: Medline (1980–2021), EBSCO (1991–2021), and PubMed (1980–2021) as well as national and international legislation and standard databases along with reference lists of eligible articles and guidelines of relevant regulatory authorities such as the European Commission and the Food and Drug Administration were searched for relevant information. Journal articles that contain information regarding PMS methodologies concerning stand-alone medical devices and relevant national and international legislation, standards and guidelines concerning the topic were included in the review. RESULTS: The search strategy resulted in 2282 papers. Out of those only 24 articles satisfied the eligibility criteria and were finally included in the review. Papers were grouped per categories: medical device registry, medical device adverse event reporting, and medical device performance evaluation. In addition to journal articles, national and international legislation, standards, and guidelines were reviewed to assess the state of PMS in different regions of the world. CONCLUSION: Although the regulatory framework prescribes PMS of medical devices, the process itself is not harmonized with international standards. Particularly, conformity assessment of MDs, as an important part of PMS, is not measured and managed in a traceable, evidence-based manner. The lack of harmonization within PMS results in an environment of increased adverse events involving MDs and overall mistrust in medical device diagnosis and treatment results.