In primary hyperoxaluria type 1 excessive endogenous production of oxalate and glycolate leads to increased urinary excretion of these metabolites. Although genetic testing is the most definitive and preferred diagnostic method, quantification of these metabolites is important for the diagnosis and evaluation of potential therapeutic interventions. Current metabolite quantification methods use laborious, technically highly complex and expensive liquid, gas or ion chromatography tandem mass spectrometry, which are available only in selected laboratories worldwide. Incubation of ortho-aminobenzaldehyde (oABA) with glyoxylate generated from glycolate using recombinant mouse glycolate oxidase (GO) and glycine leads to the formation of a stable dihydroquinazoline double aromatic ring chromophore with specific peak absorption at 440 nm. The urinary limit of detection and estimated limit of quantification derived from eight standard curves were 14.3 and 28.7 µmol glycolate per mmol creatinine, respectively. High concentrations of oxalate, lactate and L-glycerate do not interfere in this assay format. The correlation coefficient between the absorption and an ion chromatography tandem mass spectrometry method is 93% with a p value < 0.00001. The Bland–Altmann plot indicates acceptable agreement between the two methods. The glycolate quantification method using conversion of glycolate via recombinant mouse GO and fusion of oABA and glycine with glyoxylate is fast, simple, robust and inexpensive. Furthermore this method might be readily implemented into routine clinical diagnostic laboratories for glycolate measurements in primary hyperoxaluria type 1.

The protection and preservation of the privacy of personal data are one of the main requirements when it comes to an application dealing with the processing of such data. It is no different when it comes to information systems that store and process data about students in higher education systems. The public presentation of such data represents a serious threat to the safety of students as well as their status within the higher education system. For this reason, it is necessary to use the possibility of advanced technologies in order to raise data security to the highest level. One such technology that is able to provide transparency, security and data protection at a high level is blockchain technology. In this work, the Hyperledger Fabric distributed ledger private blockchain network was analyzed and its usability in terms of user rights management in higher education system was evaluated. Experimental analysis showed that such a platform has the ability to take advantage of private blockchain technologies in terms of user rights management and to provide security, flexibility and scalability of the system.

Maintaining and establishing transparency, security and privacy, when the data that should be included as part of documents that should serve as public educational documents in the labor market, are a challenging task, especially nowadays when we have more frequent cyber-attacks on public institutions. Setting up the security mechanisms of information systems that should store, process and show this type of data can be a very demanding job. For this reason, the introduction of new technologies in this area, such as blockchain technology, leads to considerable system and implementation relief. In this paper, private blockchain platforms are analyzed from the point of view of processing digital certificates or diplomas in the higher education system. An overview of the most popular platforms of this type is given. The most appropriate solution for these needs are discussed and proposed.

Mycotoxins have become a serious issue in the animal feed industry and have also affected the aquaculture industry. Mycotoxins can create serious health problems in aquatic and terrestrial animals, and their presence in agricultural products may result in significant economic losses. To reduce the impact of mycotoxins on Nile tilapia fry, two commercially available products—Organically Modified Clinoptilolite (OMC) and multi-component mycotoxin detoxifying agent (MMDA)—were used in this study. Six diets as treatments (T1 = Control (C); T2 = Control + OMC 2 g/kg (OMC); T3 = Control + MMDA 2 g/kg (MMDA); T4 = AFB1 0.5 mg/kg (AF); T5 = AFB1 0.5 mg/kg + 2 g/kg OMC (AFOMC); T6 = AFB1 0.5 mg/kg + MMDA 2 g/kg (AFMMDA)) with similar crude protein levels (35.75 ± 0.35%) were formulated and fed to Nile tilapia fry (1.97 ± 0.1 g) for a period of 84 days. These fish were housed in 18 aquaria (100 L) at a density of 50 fish/aquarium. The results from this study showed that MMDA significantly (p < 0.05) improved the survival of fish by 16% as compared to the control group. Nevertheless, growth parameters were not affected among the treatments. These results also indicated that protein intake was significantly higher in the control and OMC diet (T2) compared to aflatoxin B1-fed tilapia. The protein efficiency ratio (PER) was significantly higher in the AFMMDA as compared to the control and MMDA. A 14-day bacterial challenge test with Aeromonas hydrophila demonstrated that diets containing MMDA or OMC improved survival when AFB1 was present in the diet. Therefore, the supplementation of feed with MMDA or OMC is recommended to ameliorate the negative effects of AFB1 in Nile Tilapia feeds.

Web developers utilize responsive web design principles and frameworks to develop websites that are accessible on various platforms. As consumers often access websites through laptops, tablets, mobile phones, and desktop computers, it is necessary for the website to adjust its appearance according to the device's display frame width. However, the quality assurance process for responsive web pages is typically manual, time-consuming, and error prone. This study introduces ReDeCheck, an open-source automated website layout checking tool developed by Thomas A. Walsh, Gregory M. Kapfhammer, and Phil McMinn. The tool identifies the most common types of responsive design failures by utilizing a set of display frame widths based on the presentation of the website's dynamic layout, also known as the Responsive Layout Graph. This paper verifies the tool's functionality and its underlying concepts.

Objectives The addition of CT-derived fractional flow reserve (FFR-CT) increases the diagnostic accuracy of coronary CT angiography (CCTA). We assessed the impact of FFR-CT in routine clinical practice on clinical decision-making and patient prognosis in patients suspected of stable coronary artery disease (CAD). Methods This retrospective, single-center study compared a cohort that received CCTA with FFR-CT to a historical cohort that received CCTA before FFR-CT was available. We assessed the clinical management decisions after FFR-CT and CCTA and the rate of major adverse cardiac events (MACEs) during the 1-year follow-up using chi-square tests for independence. Kaplan–Meier curves were used to visualize the occurrence of safety outcomes over time. Results A total of 360 patients at low to intermediate risk of CAD were included, 224 in the CCTA only group, and 136 in the FFR-CT group. During follow-up, 13 MACE occurred in 12 patients, 9 (4.0%) in the CCTA group, and three (2.2%) in the FFR-CT group. Clinical management decisions differed significantly between both groups. After CCTA, 60 patients (26.5%) received optimal medical therapy (OMT) only, 115 (51.3%) invasive coronary angiography (ICA), and 49 (21.9%) single positron emission CT (SPECT). After FFR-CT, 106 patients (77.9%) received OMT only, 27 (19.9%) ICA, and three (2.2%) SPECT ( p  < 0.001 for all three options). The revascularization rate after ICA was similar between groups ( p  = 0.15). However, patients in the CCTA group more often underwent revascularization ( p  = 0.007). Conclusion Addition of FFR-CT to CCTA led to a reduction in (invasive) diagnostic testing and less revascularizations without observed difference in outcomes after 1 year. Key Points • Previous studies have shown that computed tomography–derived fractional flow reserve improves the accuracy of coronary computed tomography angiography without changes in acquisition protocols. • This study shows that use of computed tomography-derived fractional flow reserve as gatekeeper to invasive coronary angiography in patients suspected of stable coronary artery disease leads to less invasive testing and revascularization without observed difference in outcomes after 1 year. • This could lead to a significant reduction in costs, complications and (retrospectively unnecessary) usage of diagnostic testing capacity, and a significant increase in patient satisfaction.

Since depletion of natural resources and the amount of construction and demolition waste have overcome the socially and environmentally acceptable level, the construction industry must address this issue and reduce its impact on the environment. A step towards sustainability in the construction industry is the application of recycled aggregates and supplementary cementitious materials as integral components of concretes, which provides conserving natural aggregates and waste reduction. This study adopts a holistic approach to producing green self-compacting concrete with the highest portion of recycled aggregate as a replacement for natural aggregate and fly ash as filler. Based on the particle packing density method, four series of self-compacting concrete were prepared: the first series was made with natural fine and coarse aggregate, the second series was made with fine natural aggregate and recycled coarse aggregate, the third with 50 % (by mass) of fine natural aggregate replaced by recycled fine aggregate and recycled coarse aggregate, and the fourth series completely with recycled fine and coarse aggregate. The content of fly ash remained constant. Regardless of the expected decrease of workability in a fresh state with the increase of the recycled aggregate content, all series exceeded the requirements set for the hardened structural concrete.

As the demand for sustainable and renewable energy sources grows, the use photovoltaic (PV) systems have seen rise in popularity and recognition. The performance of PV systems is influenced by numerous factors such as solar irradiance, temperature, and the tilt angle of the PV modules. Among these factors, the tilt angle of the PV modules plays a crucial role in determining the amount of energy that can be generated by a PV system. This paper explores the impact of tilt angle on the output and performance of grid-connected PV systems by using the software PVsyst. The study will examine how different tilt angles affect the energy yield, electrical characteristics, and performance ratio of PV system. A study was conducted to compare the performance of a PV system with fixed tilt angle versus seasonal tilt arrangement. The results showed that a seasonal tilt arrangement led to improved performance and increased electricity generation.

When students enroll at universities, various datasets can be available to managers and teachers. Clustering techniques can be applied in order to divide the instances within those datasets into natural groups. In this paper, one clustering-based approach combined with attribute selection methods for identifying specific input dataset variables meaningful for the disjunction of distinct students' profiles has been proposed. Also, an analysis of the descriptive students' model obtained by the proposed methodology is performed.

New forms of communication are created as a result of the advancement of information and communication technologies, particularly the Internet and the WWW. These technologies introduce technological solutions as a response to ongoing difficulties. Relying on the predominant written form, besides its semantics, content on WWW must convey additional information like its structure, formatting, and relationships between its parts. Markup languages were born. Although markup languages addressed the issue at hand, they also raised several new issues, one of which is how to exchange material between disparate markup languages. In this paper, creating a meta-model of the two most commonly used markup languages, Markdown and HTML, is shown. The meta-model is created using the Eclipse Modeling Framework (EMF) ECore model, which relies on grammar obtained from markup languages. This meta-model simplifies comprehension of the relationship between markup language content and its model, which represents the first step towards the automatic transformation between models, i.e., the interchange of their content.

In research to determine the degree of interest in enrolling students in certain high schools, predictive analysis and comparison models are rarely used when classifying and processing different data. All this leads to large fluctuations in enrolment in secondary schools, where certain schools are unable to enrol numerous students who show an interest in a particular field. On the other hand, students lose interest in certain schools, which leads to the discontinuation of certain courses necessary for the needs of today's labour market. Institutions responsible for organizing the educational process do not sufficiently compare and connect teaching and non-teaching activities when analysing the talents and interests of elementary school students from different fields. The goal of this work is to predict the enrolment of students in secondary schools, using the classifiers of programming languages, based on the results that students express during regular classes in elementary schools.The results show that the accuracy of the data during the training of the Random Forest predictor is 52%, while in Wolfram Alpha it is 62%

The increase in the number of wind farms and their share in the total electrical energy generation leads to the need for a different approach to this source in cases where the stability of the power system is potentially impaired. With the development of different types of wind power plants, equipped with power electronics devices, there is the possibility of quick power management and injection, in conditions when it is needed, where a huge amount of accumulated kinetic energy can also be used. This paper presents the influence of a wind power plant equipped with a full-scale converter on the transient stability in cases of close and distant short circuits, during the outage of a heavily loaded line. Special attention was paid to the Rate of Change of Frequency (RoCoF) in the power system in cases with and without a wind farm where fast power injections were possible.

The contribution of renewable energy sources to the power system stability will have to be greater in the future. The problem will arise if the share of wind power plants in total production increases and large failures occur. Then, wind farms, which are often called inertia-less sources in the literature, will have to help maintain the frequency in a normal amount by changing the management method and based on fast PMU measurements. This can be done by using the synthetic inertia size, which is defined for sources that are derived from the system via energy converters and which do not participate in defining the total inertia of the system. This paper provides a better insight into the understanding of the concept of synthetic inertia, as well as insight into the current development of management and the application of synthetic inertia in maintaining the stability of the power system.

In this article, an upgraded version of CUDA-Quicksort - an iterative implementation of the quicksort algorithm suitable for highly parallel multicore graphics processors, is described and evaluated. Three key changes which lead to improved performance are proposed. The main goal was to provide an implementation with increased scalability with the size of data sets and number of cores with modern GPU architectures, which was successfully achieved. The proposed changes also lead to significant reduction in execution time. The execution times were measured on an NVIDIA graphics card, taking into account the possible distributions of the input data.

Air pollution represents one of the most complex problems of humanity. Traffic contributes significantly to this by emitting large amounts of harmful gases. This problem is particularly pronounced at urban intersections due to frequent changes in vehicle movement dynamics. This paper primarily presents the influence of intersection geometry on pollutant emissions levels. In addition, the influence of various traffic policies promoting greater use of public transport and zero-emission vehicles is also examined. The research combines the field part of recording existing intersections in Sarajevo, Bosnia and Herzegovina with traffic microsimulation. Detailed data on vehicles’ movements were obtained by advanced video processing using the DataFromSky tool, while the PTV Vissim 2022 and Bosch ESTM (2022) software were used to simulate traffic and estimate emissions at geometrically different intersections. The results showed that, in saturated traffic conditions, signalized intersections cause up to 50% lower emissions compared with two-lane and turbo roundabouts and that the impact of the geometric change is more significant than the impact of zero-emission vehicles. In unsaturated conditions, the differences in emissions at different intersections are negligible, with the highest reductions in pollution achieved by using zero-emission vehicles.