Syneresis represents the appearance of separation of whey on the surface of the product and is considered an important parameter of the quality of fermented dairy products. For the production of the fermented milk drink, kombucha was used as a non-traditional starter. Two sweeteners were used, honey and sucrose.The aim of the work was to examine the influence of starter and sweetener on changes in the subsequent acidity and intensity of syneresis of the samples during storage. The results were compared with a control sample obtained by inoculation with a conventional starter culture. During storage, there was a drop in pH value and an increase in titratableacidity, as a resultof the constant metabolic activity of the microflora and the production of lactic acid in the produced samples. Honey, as a sweetener, had an effect on the lower pH value of the fermented milk drink samples. The analysis of variance showed a statistically significant difference in the titratable acidity results and the intensity of syneresis of the samples during storage.Samples that were produced with kombucha as a starter showed better structure stability during storage and better quality. During storage, sample kb4 showed the best structural stability and the lowest intensity of syneresis. KEYWORDS:stinging nettle extract;bioactive components;extraction;antioxidant

High-risk human papillomaviruses (HPVs) are considered risk factors in the origin of several human malignancies, such as breast, cervical, head and neck, as well as colorectal cancers. However, there are no data reported on the HPV status in colorectal cancer in the State of Qatar. Therefore, we herein examined the presence of high-risk HPVs (16, 18, 31, 33, 35, 45, 51, 52, and 59), using polymerase chain reaction (PCR) in a cohort of 100 Qatari colorectal cancer patients, and their association with tumor phenotype. We found that high-risk HPV types 16, 18, 31, 35, 45, 51, 52, and 59 were present in 4, 36, 14, 5, 14, 6, 41, and 17% of our samples, respectively. Overall, 69 (69%) of the 100 samples were HPV positive; among these, 34/100 (34%) were positive for single HPV subtypes, while 35/100 (35%) of the samples were positive for two or more HPV subtypes. No significant association was noted between the presence of HPV and tumor grade, stage, or location. However, the presence of coinfection of HPV subtypes strongly correlated with advanced stage (stage 3 and 4) colorectal cancer, indicating that the copresence of more than one HPV subtype can significantly worsen the prognosis of colorectal cancer. The results from this study imply that coinfection with high-risk HPV subtypes is associated with the development of colorectal cancer in the Qatari population.

The microservices architectural style has been increasingly adopted in recent years due to its advantageous characteristics. While there exist design patterns for microservices that are theoretically beneficial for ensuring performance (and anti-patterns that should be avoided), they do not always lead to the expected impact. Some designs are solutions for achieving quality properties other than performance, and while they might be categorized as anti-patterns in theory, their influence on system performance can be minimal, depending on the context. Architects find it hard to reason about these trade-offs and the impact that design decisions will have on performance before implementing them. To solve this problem, in this paper, we propose an approach that enables rapid evaluation of high-level architectural models by combining both static and dynamic analysis. The static analysis identifies the design anti-patterns that are known to hinder system performance and guides the architect in reasoning about these design decisions. The approach then generates source code for the system under study based on the architectural design model for a subsequent dynamic analysis to assess whether the statically detected anti-patterns do indeed have a negative effect on the performance of the analyzed system.

The adoption of autonomous cars requires operational critical functions even in the event of HW faults and/or SW defects, and protection of safety-critical functions against security threats. Defining appropriate safe and secure architectures is challenging and costly. In previous work, we have proposed tools to automate the recommendation of safety and security patterns for safety-critical systems. However, safety and security measures may (negatively) influence system performance, besides introducing additional development effort. We present a design space exploration approach, a model-based engineering workflow and tool prototype for automated guidance on trade-off decisions when applying safety and security patterns on a given (unsafe) baseline architecture. Based on models that abstract the vehicle’s functionality and its software and hardware components, as well as an engine for the automated pattern recommendation, we investigate the optimization of HW/SW deployments, and provide a trade-off analysis for different architecture candidates. We implemented our approach in an open-source tool and evaluate it with a model of the Apollo autonomous driving platform.

Introduction After successful reperfusion is achieved (extended Thrombolysis in Cerebral Infarction (eTICI) ≥ 2b50), decision on pursuing additional treatment strategies in order to achieve complete reperfusion (eTICI = 2c/3), is multifactorial and depends on patient’s clinical and imaging characteristics. We have developed and validated a clinical decision tool to provide individualized predictions on achieving delayed reperfusion based on individual patient data. Methods Single‐center registry analysis for all consecutive patients admitted between 02/2015 – 12/2020. Primary variable of interest was perfusion imaging outcome in patients with incomplete reperfusion (eTICI 2a‐2c), evaluated on the 24‐hour follow‐up imaging. This variable was dichotomized into delayed reperfusion, in case of non‐observable perfusion deficit, and persistent perfusion deficit, in case of perfusion deficit captured on the final angiography imaging. Final model variable selection was performed via bootstrapped (n = 200) stepwise backwards regression. Model was split into a training and testing set (80:20 ratio), with 10‐fold cross validation resampling. Results 372 patients (50.8% female, mean age 74) were included, with 228 (61.2%) of them having delayed reperfusion. Final model identified seven variables of importance including: age, sex, atrial fibrillation, Intervention‐to‐Follow‐Up time, maneuver count, eTICI and collateral status. Model’s discriminative ability for predicting delayed reperfusion was adequate (AUC 0.83, 95% CI 0.74 –0.92), with an overall adjusted calibration (Brier score 0.17, 95% CI 0.15‐0.18). Conclusions Current model presents a tool that may aid clinical decision‐making process in selection of patients for pursuing additional treatment strategies after incomplete reperfusion has been achieved. This is an important next step towards personalized treatment of stroke patients undergoing mechanical thrombectomy.

In the current era of mobile communications and next-generation networks, mobility analysis has a key role in guaranteeing the quality of service/experience in the available services. Although a vast amount of work has analyzed mobility from both analytic and stochastic points of view, much of it has focused on a time-based analysis and disregarded spectral features. In this article, we propose a method of analyzing the main features of mobility traces in the frequency domain and determining the possible relationships between typical mobility grades (in terms of average and maximum speed) and the required sampling frequencies. The collection and storage of mobility pattern samples when they are not required is impractical, and therefore, we attempt to demonstrate how mobility can be sampled to avoid information loss or oversampling (many works in the literature are based on a default sampling period of 1 s). The work also contributes with the proposal of a closed form for relating the sampling period and average moving speed with the spectral components. We conducted numerous simulations to confirm that, compared with classical sampling approaches that provide static behavior, it is possible to obtain a gain of about 35%–65% in the collected samples, with a negligible loss of accuracy in the reconstructed signal.

Heavy metals represent a very significant group of environmental pollutants because they are potential metabolic inhibitors. Therefore, a study was conducted where the height of the wheat stem, as well as the surface of the leaves in the budding and leafing stages, were examined when contaminated with a mixture of heavy metals in concentrations of 250 and 500 ppm. The aim of the research was to determine the influence of heavy metals on the initial phenophase of wheat varieties Pobeda and Ljiljana. An experiment was carried out in volumetric flasks where two different concentrations of a mixture of heavy metals 250 ppm and 500 ppm were added under controlled conditions.