Cutting processes, in general, and wood cutting processes in particular, are complex to explain and describe, depending on a number of influencing factors such as material characteristics, cutting tool geometry and cutting parameters. A thorough understanding of the characteristics of woodworking machining, such as cutting tool wear, cutting forces, energy consumption, and cutting tool stress, gives the opportunity to improve product quality, increase production efficiency, or improve the technological process. In this paper, some characteristic parameters of processing in flat, extensive milling of solid wood of different species are analysed in order to determine the significance of the selected parameters, as well as their mutual influences on the required cutting power.

Dynamic analysis can be used to determine dynamic displacements, time history, and the frequency content of loads. One of the analytical techniques for calculating the linear response of structures to dynamic loading is modal analysis. In modal analysis, the structural response is decomposed into several modes of oscillation. A mode is defined by its frequency and shape. Engineers refer to the mode with the lowest frequency (longest period) as the fundamental mode of oscillation. This paper presents Holzer’s approximate method for determining the modes and periods of oscillation for frame structures. The proposed approximation method, based on the relative stiffness of floors and the ground level, is also analyzed. The results obtained using the proposed approximate procedure do not significantly deviate from those obtained through more precise calculations. Therefore, it is emphasized that the method can be used both in practice and for verifying computer analyses of complex systems.

In this paper, a comparison between serverless databases and conventional data storage models is discussed, with a focus placed on architectural differences, performance measures, cost-benefit analysis, and use case applicability. In cloud-native applications, the use of serverless databases, in which resources are dynamically allocated as needed, is increasingly observed. In contrast, traditional databases require manual operations for infrastructure provisioning and maintenance. Situations in which serverless databases are preferable, as well as those where traditional approaches remain suitable, are characterized in this work. A guide for selecting a database system in modern computing environments is provided, based on an evaluation of systems such as AWS Aurora Serverless, Firebase, PostgreSQL, and MongoDB.

Summary Background Timely and comprehensive analyses of causes of death stratified by age, sex, and location are essential for shaping effective health policies aimed at reducing global mortality. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023 provides cause-specific mortality estimates measured in counts, rates, and years of life lost (YLLs). GBD 2023 aimed to enhance our understanding of the relationship between age and cause of death by quantifying the probability of dying before age 70 years (70q0) and the mean age at death by cause and sex. This study enables comparisons of the impact of causes of death over time, offering a deeper understanding of how these causes affect global populations. Methods GBD 2023 produced estimates for 292 causes of death disaggregated by age-sex-location-year in 204 countries and territories and 660 subnational locations for each year from 1990 until 2023. We used a modelling tool developed for GBD, the Cause of Death Ensemble model (CODEm), to estimate cause-specific death rates for most causes. We computed YLLs as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. Probability of death was calculated as the chance of dying from a given cause in a specific age period, for a specific population. Mean age at death was calculated by first assigning the midpoint age of each age group for every death, followed by computing the mean of all midpoint ages across all deaths attributed to a given cause. We used GBD death estimates to calculate the observed mean age at death and to model the expected mean age across causes, sexes, years, and locations. The expected mean age reflects the expected mean age at death for individuals within a population, based on global mortality rates and the population's age structure. Comparatively, the observed mean age represents the actual mean age at death, influenced by all factors unique to a location-specific population, including its age structure. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 250-draw distribution for each metric. Findings are reported as counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2023 include a correction for the misclassification of deaths due to COVID-19, updates to the method used to estimate COVID-19, and updates to the CODEm modelling framework. This analysis used 55 761 data sources, including vital registration and verbal autopsy data as well as data from surveys, censuses, surveillance systems, and cancer registries, among others. For GBD 2023, there were 312 new country-years of vital registration cause-of-death data, 3 country-years of surveillance data, 51 country-years of verbal autopsy data, and 144 country-years of other data types that were added to those used in previous GBD rounds. Findings The initial years of the COVID-19 pandemic caused shifts in long-standing rankings of the leading causes of global deaths: it ranked as the number one age-standardised cause of death at Level 3 of the GBD cause classification hierarchy in 2021. By 2023, COVID-19 dropped to the 20th place among the leading global causes, returning the rankings of the leading two causes to those typical across the time series (ie, ischaemic heart disease and stroke). While ischaemic heart disease and stroke persist as leading causes of death, there has been progress in reducing their age-standardised mortality rates globally. Four other leading causes have also shown large declines in global age-standardised mortality rates across the study period: diarrhoeal diseases, tuberculosis, stomach cancer, and measles. Other causes of death showed disparate patterns between sexes, notably for deaths from conflict and terrorism in some locations. A large reduction in age-standardised rates of YLLs occurred for neonatal disorders. Despite this, neonatal disorders remained the leading cause of global YLLs over the period studied, except in 2021, when COVID-19 was temporarily the leading cause. Compared to 1990, there has been a considerable reduction in total YLLs in many vaccine-preventable diseases, most notably diphtheria, pertussis, tetanus, and measles. In addition, this study quantified the mean age at death for all-cause mortality and cause-specific mortality and found noticeable variation by sex and location. The global all-cause mean age at death increased from 46·8 years (95% UI 46·6–47·0) in 1990 to 63·4 years (63·1–63·7) in 2023. For males, mean age increased from 45·4 years (45·1–45·7) to 61·2 years (60·7–61·6), and for females it increased from 48·5 years (48·1–48·8) to 65·9 years (65·5–66·3), from 1990 to 2023. The highest all-cause mean age at death in 2023 was found in the high-income super-region, where the mean age for females reached 80·9 years (80·9–81·0) and for males 74·8 years (74·8–74·9). By comparison, the lowest all-cause mean age at death occurred in sub-Saharan Africa, where it was 38·0 years (37·5–38·4) for females and 35·6 years (35·2–35·9) for males in 2023. Lastly, our study found that all-cause 70q0 decreased across each GBD super-region and region from 2000 to 2023, although with large variability between them. For females, we found that 70q0 notably increased from drug use disorders and conflict and terrorism. Leading causes that increased 70q0 for males also included drug use disorders, as well as diabetes. In sub-Saharan Africa, there was an increase in 70q0 for many non-communicable diseases (NCDs). Additionally, the mean age at death from NCDs was lower than the expected mean age at death for this super-region. By comparison, there was an increase in 70q0 for drug use disorders in the high-income super-region, which also had an observed mean age at death lower than the expected value. Interpretation We examined global mortality patterns over the past three decades, highlighting—with enhanced estimation methods—the impacts of major events such as the COVID-19 pandemic, in addition to broader trends such as increasing NCDs in low-income regions that reflect ongoing shifts in the global epidemiological transition. This study also delves into premature mortality patterns, exploring the interplay between age and causes of death and deepening our understanding of where targeted resources could be applied to further reduce preventable sources of mortality. We provide essential insights into global and regional health disparities, identifying locations in need of targeted interventions to address both communicable and non-communicable diseases. There is an ever-present need for strengthened health-care systems that are resilient to future pandemics and the shifting burden of disease, particularly among ageing populations in regions with high mortality rates. Robust estimates of causes of death are increasingly essential to inform health priorities and guide efforts toward achieving global health equity. The need for global collaboration to reduce preventable mortality is more important than ever, as shifting burdens of disease are affecting all nations, albeit at different paces and scales. Funding Gates Foundation.

Background: The European honey market is reported to be in a trou-bling state, far from being considered healthy. A comparison of honey with other food commodities has been conducted to identify specific characteristics of the conducing sector that may provide inspiration for measures to regulate hon y markets. Market indicators: Several general indicators used to describe markets for food production have been analysed to examine the current state of the honey market, offering insight into the primary market challenges or honey-anessential prerequisite developing strategies to address these identified challenges. Variations in market indicators between EU Member States are also presented. Policies related to market indicators: The overarching aim of the European Union, as defined by the Lisbon Treaty, is summarized, alongside a review of some relevant EU and national regulations related to apiculture. Policy me sures previously implemented to regulate certain aspects of other food commodity markets are evaluated for their feasibility in the hon y market. Results and conclusions: It is argued that regulatory me sures could potentially impro e the stability and security of income for beekeep-ers within the honey market. However, there is a risk, or possibly an opportunity, that such measures could drive production towards larger and more professional beekeepers, while smaller, amateur beekeepers may face economic and other difficulties in meeting the stricter regulatory requirements

In this paper, we will process the results of experimental and numerical analysis on the example of the boom of a machine tool - a rotary excavator. Rotary excavator SRs 1200/630 KW - 22/2, engine no. 1, field “D”, produced by “LAUHAMER” - German Democratic Republic, is intended for mining coal and tailings at the surface mine of the JP RB “KOLUBARA” Lazarevac mine. During the regular overhaul and after 35 years of operation of the rotary excavator, it was concluded that it would be necessary to assess the stress and deformation state of both the rotary excavator as a whole and its vital parts individually (primarily the excavator booms) through adequate tests. The goal is to determine the critical points on the arrow structure after the tests have been carried out and act preventively to avoid accidents and additional unnecessary costs. By comparing the experimental and numerical results, we obtained a representation of the stresses and strains on the shaft construction and defined the critical stresses and strains.

Mathematical modeling is a key tool in engineering as it enables the analysis and prediction of material behavior under specific conditions. This study focuses on material strength, which is one of the most critical aspects of engineering design and manufacturing. Understanding material strength is essential for ensuring the reliability and safety of structures and products. The structure of the paper includes a theoretical overview of the fundamentals of mathematical modeling and regression analysis, a detailed description of the experimental research, the development of a model based on collected data, and the evaluation of the obtained mathematical model. Testing was conducted using a tensile testing machine, with samples of standard dimensions in accordance with EN 10002.

Considering that two-layer parquet is composed of two lamellas—most commonly 10 mm birch plywood and 4 mm solid oak—bonded together with adhesive, and that profiling is required to create a joint that serves a mechanical function, the process becomes complex and imposes significant demands on the cutting tool. This paper presents an experimental analysis of how the type of cutting tool affects the surface quality, profile stability, and edge wear of the tool after a certain machining length. Two different technological solutions were analyzed: a tool with replaceable tungsten carbide (TC) inserts and a tool with an integrated polycrystalline diamond (PCD) cutting edge. A particular focus of the analysis is the wear of the TC tool in the area of the oak and plywood joint profile, where selective wear of the TC edge occurs, potentially causing profile deformation and a weaker joint. The obtained results show that using PCD tools in two-layer parquet profiling achieves better surface finish, longer tool life, more consistent geometry of the cutting edge, and thus a more stable parquet profile.

Background and objectives: Melanocytic nevi are among the most common skin lesions, yet their relationship with the peripheral nervous system has remained understudied. Given the neural crest origin of melanocytes and Schwann cells, and the neurotrophic signaling capabilities of pigment cells, this study aimed to investigate the density of nerve fibers within nevi and assess how it varies with respect to histological subtype and anatomical location. Materials and Methods: A total of 90 nevi were analyzed, including junctional, compound, and intradermal types, distributed across the head, trunk, and limbs. Immunofluorescence staining for the pan-neuronal marker PGP 9.5 and for CGRP were performed and nerve fiber density was quantified. Statistical evaluation using two-way ANOVA revealed that both nevus type and anatomical site significantly influenced the degree of total innervation. Results: Junctional nevi demonstrated the highest total nerve fiber density, significantly exceeding that of compound and intradermal nevi. Likewise, nevi located on the head exhibited a significantly greater density of PGP 9.5-positive nerve fibers compared to those on the trunk and limbs. No significant correlation was observed between nevus type and location, suggesting that both factors contribute independently to the differences in innervation. CGRP-positive innervation was uniform regardless of the histological type of nevus and anatomical location. Conclusions: These findings likely reflect the facts that junctional nevi reside at the dermo-epidermal junction, where nerve fibers are most abundant, while the skin of the head and neck is well known to be more richly innervated than other regions. In contrast, analysis of CGRP-positive fibers suggests that the heterogeneity detected with PGP 9.5 is primarily driven by other neuronal populations. The results support the hypothesis of a dynamic relationship between nevi and the peripheral nervous system, potentially mediated by neurotrophic factors. Understanding this interaction may provide insight into nevus biology, sensory symptoms reported in some lesions, and the evolving role of nerves in the tumor microenvironment.

The machinability of wood is an insufficiently researched problem that is mainly related to the machinability of metals. The machinability of a material is a technological property that expresses the ability to remove the maximum amount of crisps from the machined surface in the shortest possible time with satisfactory machining quality and the lowest possible cutting forces and tool wear. The quality and efficiency of the production process when milling solid wood is influenced by the following factors: type of wood, density and moisture content of the wood, temperatures and dimensions of the workpiece as well as the hardness and strength of the wood. The parameters of the milling mode, such as the main and auxiliary motion, the cutting force and power and the power of the drive unit, have a direct effect on the milling process and are related to the milling tool, i.e. the type and quality of the material from which it is made, the number of cutting edges, the geometry of the cutting edge and the sharpness of the tool. In this work, the influence of significant input parameters on the machinability of solid wood in flat peripheral milling is analysed as a function of the cutting force as an output parameter by planning an experiment. The experimental results are mathematically modelled with the aim of obtaining a mathematical model of the process of large-scale milling of solid wood, i.e. its parameters as a function of the cutting force. The results of the experimental part and the results of the models are analysed and compared in order to draw appropriate conclusions and

BACKGROUND Community pharmacists' roles are expanding beyond traditional tasks to include digital health interventions. Despite the growing integration of digital health technologies, gaps remain in understanding pharmacists' digital health technology literacy (DHTL). Adequate DHTL is essential for supporting patients and ensuring the effective implementation of digital tools in pharmacy practice. OBJECTIVES To assess general digital literacy (gDL) and identify specific levels of DHTL among community pharmacists. METHODS A version of the DHTL Assessment Questionnaire (DHTL-AQ), specifically validated for use by community pharmacists, was distributed via online and paper-based formats. In addition to the DHTL-AQ, the questionnaire also included supplementary items assessing gDL. The sample size was calculated on the basis of the targeted pharmacist population. The data were analysed via SPSS. ROC curves were used to determine cut-off scores, whereas chi-square and Kruskal-Wallis tests were used to assess group differences and associations. RESULTS A total of 368 valid responses were collected. Among the respondents, 15.2% had low, 68.8% had medium, and 16.0% had high gDL. On the basis of these findings, DHTL cut-off scores were defined as low (35.9%), medium (19.6%), and high (44.5%). Significant differences in DHTL levels were associated with years of working experience. While 41.3% did not use social media professionally, Facebook, YouTube, Instagram, and Viber were the most commonly used platforms among pharmacists. CONCLUSION This study provides the first comprehensive assessment of DHTL among Serbian community pharmacists, revealing high general digital literacy but highlighting the need for targeted DHTL training. Future research should focus on expanding the sample size and addressing specific DHTL gaps. The approach used in this study offers a practical framework for assessing DHTL that can be applied internationally to inform the development of relevant, tailored training programs and support the expansion of pharmacist-led services in an increasingly digital health environment.