The primary objective of the protocol is to establish and develop several scientific methodological procedures applicable to the design and selection of a suitable mine dewatering management plan. A significant challenge and contribution of the research lies in the initial hypothesis, which posits the feasibility of organizing a multidisciplinary team to collaboratively determine the optimal solution for long-term mine dewatering. Protection against groundwater is a highly complex hydrogeological challenge, particularly in mining operations. Mines are inherently dynamic systems, constantly expanding both horizontally and vertically, from the very beginning of mining, also reaching significant depths. Given the inherent uncertainty in geologic systems, such as ore deposits, the entire dewatering process requires continuous “learning” and hierarchical problem-solving. Addressing these complexities involved forming a team of experts, leveraging their knowledge and experience, as well as several methodological procedures based on applied mathematics in geosciences and mining engineering, such as numerical modeling and simulation, fuzzy optimization and decision analysis. These circumstances necessitated continual adjustment to evolving operating conditions and prompted the development of a protocol for effective dewatering planning and mineral ore protection against groundwater. Such a protocol generates alternative mine dewatering solutions and considers their individual characteristics. Additionally, it defines and analyzes multiple criteria for evaluating the solutions and selecting a method that ensures optimal decision-making. The applied methods constitute a holistic system, represented by a single protocol, which includes an interdisciplinary approach to creating sustainable groundwater management strategies.

Postmortem biochemistry is a valuable tool in forensic investigations, providing insights into the tissue damage and organ dysfunction associated with death. This study aimed to identify biochemical markers that distinguish primary and secondary hypothermia. Twenty-one Wistar rats were allocated into three groups: the Control group (n = 7), which was exposed only to hypothermic conditions, the Alcohol + Hypothermia group (n = 7), and the Benzodiazepines + Hypothermia group (n = 7). The temperature metrics assessed included the normal core temperature, the post-ketamine (0.3 ml injection) core temperature, the immersion temperature, temperature at the onset of hypothermia, and temperature at death. Blood samples were collected from the thoracic aorta in EDTA vacuum tubes for biochemical analysis. The key biochemical parameters measured included the Total Protein (g/L), Albumin (g/L), Globulin (g/L), Albumin to Globulin Ratio, Alanine Aminotransferase (U/L), Alkaline Phosphatase (U/L), Cholesterol (mmol/L), Amylase (U/L), and Lipase (U/L), using an automated IDEXX (Netherlands) cell counter. Significant between-group differences were found for the total protein and globulin levels (p < 0.001 and p = 0.002, respectively), with post-hoc tests confirming differences between the alcohol and control, and benzodiazepine and control groups. The cholesterol levels were found to be significantly different through an omnibus test (p = 0.03), but post hoc tests did not confirm these differences on a statistically significant level. The amylase levels varied significantly across all groups (p < 0.001), with post hoc tests confirming significant differences among all pairs: alcohol vs. benzodiazepine (p = 0.002), alcohol vs. control (p = 0.003), and benzodiazepine vs. control (p < 0.001). The lipase levels showed significant differences in the omnibus test (p = 0.030), but there was no significance in the post hoc tests. Amylase emerged as the most significant parameter in our study, with reduced levels strongly associated with secondary hypothermia. These findings highlight the potential use of total protein, globulin, and amylase levels as biomarkers to differentiate between primary and secondary hypothermia in forensic contexts.

This article delves into the complex and evolving landscape of defamation as a criminal offence in 19th century Europe. The crime of defamation, encapsulating the act of damaging a reputation through spoken or written words, became a contentious issue, closely interwoven with the burgeoning principles of freedom of expression and the evolving legal systems of the time. This study employs a comparative legal historical approach to investigate how defamation was defined, prosecuted, and perceived across different European countries. As societies transitioned from aristocratic hierarchies to more egalitarian systems, defamation cases often served as a platform for public discourse on power dynamics, individual rights, and the role of the media in shaping public opinion. The study of defamation in 19th century Europe provides a unique perspective on the delicate balance between the protection of personal reputation and the promotion of democratic values in a rapidly changing world.

In the study an estimation of the influence of target material type on the penetration capability of the 12.7 mm API-T (armor-piercing incendiary with tracer) projectile is performed. The literature review contains 14 references regarding 12.7 mm ammunition studies. A relatively large number of metallic targets are taken into consideration in a computer simulation that assesses the influence of the target type on the penetration capabilities of the given projectile. By comparing the acquired findings with the data of other authors, the numerical model was first successfully validated. Simulation results indicate that bainitic steels are by far the most resilient steels. Because of their hardness, these steels displayed significant erosion of the penetrator tip and significant projectile fragmentation upon impact. Iron targets, as expected, performed worse than steel targets, with more penetration seen. Mild steel had a significantly deeper penetration compared to armor steel. The performance of other steels employed in the study was comparable. Numerical simulations have shown to be a very effective technique in ammunition and armor design, resulting in substantial time and cost savings (fewer experimental experiments). Furthermore, by utilizing simulations, researchers can estimate certain physical processes that would be challenging to detect in actual testing.

This paper deals with a sensitivity analysis of engineering critical assessment, using a fracture assessment diagram of through-thickens axial flaws on pressure equipment. Basic option calculations are performed per BS 7910, using engineering fracture mechanics principles, followed by the provision of assessment points. For evaluation purposes, arbitrary design properties of pressure equipment and temperature-dependent materials properties were used. Several through-thickness axial flaw sizes were used for critical assessment. Furthermore, the sensitivity of critical assessment is evaluated by varying stress states and material fracture toughness. Finally, the sensitivity analysis shows how axial flaw growth may become critical, or its acceptability, depending on varying stress states and temperature-dependent material properties, on selected pressure equipment.

Attempts to adopt agile practices are challenged by outsourcing and distributed ways of working popularized in the world today. This paper focuses on outsourcing vendors and empirically examines the progress of agile and Scrum adoption in such environments through the case of information technology companies in Bosnia and Herzegovina. Qualitative content analysis was employed to analyze data obtained from 142 professionals from 43 companies, whose clients are located around the globe. The empirical results reveal a fairly good level of agile awareness in the tested community, but also confirm the findings of earlier research that obstacles to implementing Scrum in outsourced projects exist, emphasizing issues originating from distant Product Owners, diminished Scrum Master role, and customer influence. Team self-organization is recognized as the best adopted Scrum practice, while the product backlog definition, Scrum events, and the process managed through excessive meetings are among those that still require significant improvements.

Early detection of atrial fibrillation plays a crucial role in the timely prevention, diagnosis, and treatment of cardiovascular diseases. This paper proposes two different network architectures for automated atrial fibrillation detection. In the first architecture, a 1D CNN is used as a feature extractor and classifier. In the second hybrid architecture, a 1D CNN is used only as a feature extractor from ECG time series signals that supply a KNN with the most relevant features for further classification. Experimental results showed that the hybrid architecture achieved remarkable results and outperformed a 1D CNN.

The building integrated photovoltaic (BIPV) systems are a popular option for integrating renewable energy sources in the power system, and for users to reduce energy bills. This paper analyzes the performance of inverters in BIPV systems with oversized PV configurations. Oversizing PV systems has become a common practice to optimize energy production, particularly in periods of low sunlight, but it raises concerns about efficiency, power quality, and potential economic implications. Performance analysis is performed on two inverters, one operating under an overloaded regime due to the oversized PV installation and another under normal conditions. Several performance metrics are compared, including efficiency, thermal behavior, THD, and economic factors. The results demonstrate that although oversizing can slightly increase the inverter’s temperature and affect power quality, the efficiency was better for the overloaded inverter, although the investment costs have increased. These results offer practical insights for designing PV systems, showing that oversizing can be beneficial if properly managed.

Ultrasound images are used in various branches of medicine to detect diseases. The process of obtaining this data is complex due to procedures and legal restrictions, leading to scarce datasets. Different data augmentation techniques can be employed to improve classification performance. This paper shows that augmenting the ultrasound breast cancer images dataset using generative adversarial networks (GANs) increased the classification accuracy compared to the original dataset and compared to the dataset augmented using standard techniques.

Modern IoT devices used for remote health monitoring use basic parameters such as heart rate, skin temperature and oxygen saturation. Maximum heart rate is an important parameter used for calculating heart rate zones that is helpful in diagnosis and prevention of cardiovascular diseases. This paper presents an information system that contains an IoT subsystem for heart rate measurement, and a web-server subsystem for monitoring by doctors that includes heart rate zone monitoring.

Smart wearable devices often contain heart rate monitoring capabilities. This paper presents an experimental study that compares the accuracy of smart watches (Xiaomi Amazfit Bip 3 and GEEKIN X10) to microcontroller-based systems that use raw sensors (HW-827 and MAX30102). The achieved results indicate that the accuracy of raw sensors is lower compared to smart watches and that the level of inaccuracy depends on the level of physical activity of the test subjects.

This paper presents a method based on Artificial Neural Networks (ANN) for magnetic flux density harmonics estimation in the vicinity of overhead lines. The proposed method can be employed for the magnetic flux density estimation in the cases of excitation currents with a pure sinusoidal waveform, as well as for excitation currents with harmonically distorted waveforms. The method utilizes two ANNs that are trained in a such way that enables their application for overhead lines of arbitrary phase conductor configurations and arbitrary current harmonic spectrum. In this paper, the proposed method is applied for magnetic flux density harmonics estimation in the vicinity of a typical distribution overhead line. The proposed method is validated by comparison with Biot-Savart based method. The obtained results demonstrate not only the accuracy and effectiveness of the proposed method but also the importance of considering the magnetic flux density harmonics in the vicinity of power facilities.

Generative AI approaches such as ChatGPT are very popular and can be used for multiple purposes. This paper explores the possibility of using ChatGPT-4o for analysing visual information about 2D objects on provided images and returning annotated image results to the user. The achieved results indicate that ChatGPT can be used for the analysis of visual data and detect approximate values of desired parameters, however its generative capabilities are lacking and often unusable.