The functional performance and in-service quality of products are strongly influenced by surface roughness, which is a direct outcome of material removal processes. In general, surface roughness is function by the input parameters of the machining process and the extent of tool wear, the increase of which leads to an increase cutting forces, torque, acoustic emission level, vibrations, and temperature. Finding the dependence between machining parameters, tool wear indicators, and surface roughness parameters enables real-time prediction of surface quality and contributes to appropriate processing quality. In this study, based on data obtained through experiment conducted using the Taguchi design of experiment, predictive models were developed using multiple regression analysis and artificial neural networks (ANN). These models establish a relationship between input drilling parameters, axial drilling force, and the maximum height of the surface roughness profile.

Background: Assessment of the fetal nervous system - both in its anatomical structure and functional behaviour - has long been a challenge in perinatal medicine. Recent advances in ultrasound technology, especially 3D and 4D ultrasound, now allow detailed real-time observation of fetal anatomy and behavior. The development and maturation of the fetal brain in utero (and its continuity into extrauterine life) is a complex dynamic process: fetal neurobehavior is thought to follow a reproducible, gestational-age–dependent pattern that reflects neurological integrity. If normative fetal neurodevelopmental stages could be recognized and standardized, then deviations - abnormal neurobehaviors - could be identified, enabling prompt prenatal diagnosis of nervous-system pathology. Objective: The aim of this study was to emphasize the potential of 4D ultrasound–based fetal neurobehavioral evaluation (specifically with the Kurjak Antenatal Neurodevelopmental Test, KANET) in detecting abnormal neurobehavior prenatally, and to underline how this method may allow early identification of fetuses at risk for neurodevelopmental impairment. Methods: Review of the concept of fetal neurobehavioral assessment using 4D ultrasound. The KANET test applies 4D ultrasound to observe fetal behavior (movements, facial expressions, general/isolated movements) across gestation, akin to how neonates are neurologically assessed postnatally. By standardizing a scoring system for fetal behaviors relative to gestational age, KANET distinguishes between normal, borderline, and abnormal fetal neurobehavior. Evidence from multicenter studies and clinical/practice settings is considered to assess the feasibility and predictive value of KANET. Results: a) 4D ultrasound makes it possible to observe a wide repertoire of fetal behaviors (limb movements, facial expressions, mouth movements, hand-to-face, general movements), with increasing complexity and organization through gestation - reflecting central nervous system (CNS) maturation. PubMed+2De Gruyter Brill+2; b) Application of KANET in both low-risk and high-risk pregnancies (including growth-restricted and diabetic pregnancies) has shown significant differences in fetal behavior patterns. PubMed+2journaljammr.com+2; c) Postnatal follow-up in some studies found that fetuses with abnormal prenatal KANET scores indeed displayed adverse neurological outcomes - suggesting KANET’s potential as a predictive tool. PubMed+2PubMed+2; d) A recent systematic review (2025) found consistent evidence that behaviors observed via 4D ultrasound (e.g., yawning, hand-to-face, startle, general movements) increase in complexity between approx. 24–34 weeks gestation, coinciding with known neurodevelopmental milestones (e.g., thalamocortical connectivity). PubMed+1; e) However, despite growing evidence for structured fetal behavior as a marker of neural integration, the review cautions that such behaviors cannot yet be equated with consciousness or subjective awareness. PubMed+1.- Conclusion: The advent of 3D/4D ultrasound - and standardized tools like KANET - enables non-invasive prenatal assessment not only of fetal anatomy but also of functional neurodevelopment. Observing and scoring fetal behavior provides a promising avenue for early detection of neurodevelopmental abnormalities. While current evidence supports the use of KANET in clinical practice to identify fetuses at risk for neurodevelopmental impairment, interpretation should remain cautious: observed behaviors likely reflect maturation and neural integration but do not equate to consciousness. Further large-scale, long-term follow-up studies are needed to solidify the predictive validity and clinical utility of prenatal neurobehavioral assessment.

Background: Regular physical training in young athletes leads to physiological cardiovascular adaptations, often manifested as electrocardiographic (ECG) changes. Identifying predictors of such changes is essential for distinguishing normal adaptations from potential pathological findings. Objective: The aim of this study was to investigate body mass index (BMI), systolic and diastolic blood pressure (SBP/DBP), and heart rate (HR) as potential predictive factors for sinus arrhythmia, incomplete right bundle branch block (IRBBB), and ST-segment elevation in young endurance and strength athletes. Methods: This retrospective-prospective study included 60 male athletes aged 12–17 years (30 endurance, 30 strength athletes) who underwent a five-year follow-up with regular ECG monitoring. Anthropometric and cardiovascular parameters (BMI, SBP, DBP, HR) were recorded, and associations with ECG findings were analyzed using descriptive statistics, Student’s t-test, Mann-Whitney U test, Chi-square test, and logistic regression. Results: Endurance athletes showed a significant increase in BMI during follow-up (p = 0.035), while in strength athletes BMI was significantly associated with sinus arrhythmia (p = 0.045). Systolic blood pressure at the end of the study significantly differed in endurance athletes with and without ST-segment elevation (p = 0.029). However, logistic regression analysis demonstrated that BMI, SBP, DBP, and HR were not independent predictors of ECG abnormalities in either group. Conclusion: Basic cardiovascular parameters such as BMI, blood pressure, and heart rate do not appear to independently predict ECG changes in young athletes. Other factors, including training intensity and genetic predisposition, likely play a greater role. Preventive cardiovascular screening remains crucial for the early detection of clinically relevant abnormalities in this population.

In Bosnia and Herzegovina, black alder appears in scattered smaller forest stands, fragments and patches that are still not spatially separated and allocated in management plans, despite its high ecological importance. The objective of this study is to model a black alder ecological niche considering combined effects of climate, hydrological and air quality determinants to support decision-making of conservation and restoration activities on a local/regional level. Black alder occurrence was registered on 72 temporary sample plots representing about 1500 trees in the Bosna River basin corresponding to Level 6, EU-Hydro River Network Database. Six climatic variables (average annual temperature, minimum temperature, maximum temperature, sum of temperature above 5°, sum of precipitation, maximum precipitation), five hydrological variables (average annual flow, minimum flow, maximum flow, flow between 1961–1990 and water level) and five air quality variables (average annual concentration of air particulate matter of PM2.5 and PM10 mm, SO2, NO2, maximum CO2) were interpolated spatially on 10 m grain size based on hydro-meteorological data from 13 national stations. The MaxEnt method was used to predict spatial distribution model, where predicted occurrence probabilities are classified in habitat suitability classes. The MaxEnt model revealed high-quality spatial prediction (AUC=0.95). The most significant determinants were average annual sum of precipitation and average annual 24-hour maximum CO2 concentration (cumulative about a 72% contribution). The highest occurrence probabilities were related to areas with less than 1400 mm of annual sum precipitation and elevated CO2 linked to low NO2. The areas with high species occurrence are mainly located in continental Bosnian Internal Dinarides in the valley and partly on hilly and sub-mountainous positions overlapping pedunculated oak-hornbeam and Illyrian sub-mountainous beech forests. Modeled ranges of precipitations and air variables concentrations indicate that black alder prefers continental low hilly and plane positions covering forest edges, although some suitable ecological niches are predicted in sub-urban and peri-urban green areas. The obtained model of species distribution determined spatially ecological niches important for conservation and restoration to maintain ecological services and biodiversity as well as aesthetic and recreational roles of black alder, which are important for local communities.

The growing need for reducing ܥܱଶemissions in the context of sustainable development has intensified the search for efficient analytical approaches to understand and manage emission drivers. In this paper, three machine learning models were developed using multiple linear regression for the countries of Bosnia and Herzegovina, Croatia and Slovenia. Renewable energy consumption, ܲܯଶ,ହ air pollution, ܦܩܲ per capita, foreign direct investment, urban population, forest area, and total population were used as inputs in the models, while ܥܱଶ emissions for the period from 2000 to 2020 were used as outputs. The developed models for all three countries have good performance, with ܴଶvalues of 91,34%, 77,91%, and 77,20% respectively. For Bosnia and Herzegovina urban population increases ܥܱଶemission, while renewable energy consumption and forest area decrease ܥܱଶ emission. In Croatia ܲܯଶ,ହ was the most influential factor that increases ܥܱଶemission.In Slovenia population growth decreases ܥܱଶ emissions, whileGDP per capita increases ܥܱଶ emissions. Also, hypothesis testing for differences between means was performed for all variables between all three countries. The findings showed that for almost all variables there were statistically significant differences in mean differences between all countries. Regarding ܥܱଶ emission there are not enough statistical evidence that Bosnia and Herzegovina have higher ܥܱଶ emissions than Croatia, while both Bosnia and Herzegovina, and Croatia have significantly higher ܥܱଶ emissions than Slovenia. This research shows the potential of machine learning models as tools for data-driven policymaking in the transition towards Industry 5.0 and a sustainable industrial future.

The focus of this monograph is on the profound changes brought by the Fourth Industrial Revolution and the transition to the post-digital era, in which digital technologies, automation, and innovations shape industries, institutions, and everyday life. Digital transformation enables small and medium-sized enterprises (SMEs) and startups to achieve a more level playing field compared to global corporations, creating conditions for the development of dynamic entrepreneurial ecosystems. Startups, defined as temporary organizations designed to find a scalable, repeatable business model, are key drivers of economic development. The monograph focuses on digital entrepreneurship, business model innovation, open innovation, entrepreneurial finance, entrepreneurial marketing, the digitization of processes and global value chains, and the sustainable growth and development of post-startup ventures within contemporary ecosystems. Special attention is given to the circular economy as a key approach to reducing negative environmental impacts and transitioning from the linear “take–make–dispose” model to sustainable business models based on reuse, recycling, and repair. In this context, the growing importance of ESG principles is emphasized, as they integrate environmental, social, and governance dimensions into business strategies and contribute to long-term value and corporate reputation. The monograph addresses the critical question of the benefits that growing enterprises can achieve by adopting ESG principles, as well as how innovative business models create value for all stakeholders. Managing the development of micro, small, and medium-sized enterprises, digital entrepreneurship, growth strategies, and entrepreneurial management represents a thematic continuation and qualitative enhancement of the author’s previous editions. Finally, the monograph highlights the importance of continuously building entrepreneurial culture and innovative ecosystems as prerequisites for societal prosperity and for motivating new generations of entrepreneurs, researchers, and creators.

Background: The expansive advancement of technology has prompted scholars to investigate the links between external factors that influence the success of technology-based entrepreneurs, with particular emphasis on the link between national culture and technological entrepreneurial orientation. Purpose: This paper examines the relationship between national culture and technological entrepreneurial orientation during the early stages of entrepreneurial activity, utilizing Hofstede's national culture dimensions as a theoretical framework. Study design/methodology/approach: The empirical analysis was conducted using multiple linear regression, based on data obtained from the Global Entrepreneurship Monitor (GEM) database. The sample comprises 8,000 participants from Southeastern Europe. Findings/conclusions: The research findings indicate a statistically significant relationship between national culture and technological entrepreneurial orientation. A similar standard of living, associated with a lower index of power distance, is positively linked to technological entrepreneurial orientation, whereas the perception of entrepreneurship as a desirable professional career, typical of an individualistic society, is statistically significant but negatively associated with technological entrepreneurial orientation. A lower index of Power distance encourages innovativeness and efficiency in entrepreneurial ventures within high-tech sectors; conversely, Individualistic societies lead to a greater prevalence of enterprises in low-tech sectors. Limitations/future research: A group of drivers of technological entrepreneurial orientation was examined. We recommend that future research, in addition to national culture, also considers other factors, such as individual or sociodemographic factors.

Background: Lyme disease represent an emergent zoonosis caused by the spirochete Borrelia burgdorferi. The disease is transmitted from animals to humans by hematophagous insects, primarily ticks. The question of the existence of chronic borreliosis in children and adults is today a stumbling block in diagnostics and therapy at the global level. Objective: The aim of this article is to answer the questions: is the diagnosis of Lyme disease complicated and is Borrelia burgdorferi the cause of chronic Lyme disease in children and adults. Methods: A retrospective-prospective clinical study of outpatients treated and monitored in a private infectious disease clinic over 13 years from January 1, 2013 – November 30, 2025 was conducted. The study was clinical, descriptive and analytical, and was conducted in three phases; the first retrospective and two prospective phases. The diagnosis of the disease was made on the basis of anamnestic-epidemiological data, clinical picture, clinical findings of new clinical markers and the course of the disease, and verified by serological detection of specific antibodies using ELISA, WB methods, detection of antibodies to protein sequences by Immunoblot0m, and detection of Borrelia burgdorferi bacteria in serum using a light microscope in a dark field. Results: In the investigated period, a total of 1,095 patients with Lyme disease symptoms were treated. Of that number, 120 children and 975 adults were treated. M : F = 436 : 659. The average age of children was 10.7 years, and of adults 50.1 years. 11.62% of patients had an acute and subacute phase of the disease, the rest were chronic patients with Lyme disease, children and adults. Out of 105 patients who were examined for Borrelia by light microscopy in the dark field, Borrelia was confirmed in 31 patients before therapy and in 19 relapses. In 21 patients before the therapy, as expected, Borrelia was not found in the blood, nor in 46 controls after the therapy, which was carried out intermittently for more than 50 days. In 3 patients, who had a slow recovery, Borrelia was found in the blood after 30 and 80 days of intermittent therapy. Conclusion: Lyme borreliosis is a persistent infection and in susceptible individuals it has a chronic remitting course. Diagnosis of the disease is simple if an individual approach is adopted, an adequate history is taken, new clinical markers are found on the skin and confirmed by the detection of antibodies to the Borrelia protein sequences in Immunoblot. The confirmatory test is the detection of Borrelia by light microscopy in the dark field. Chronic borreliosis in children and adults and vertical transmission from mother to child are unquestionable.

Southeast European transition economies continue to struggle with turning innovative ideas into sustainable commercial successes. This paper examines the factors that drive effective and lasting Technology Transfer (TT) within emerging open innovation ecosystems in Bosnia and Herzegovina, Serbia, North Macedonia, and Albania. Unlike earlier studies that focus on a single country or rely on limited methods, this research adopts a comprehensive mixed-methods approach, combining a two-round Delphi study, focus groups, a needs analysis, and a survey of 100 companies.Using Partial Least Squares Structural Equation Modelling (PLS-SEM) on data collected from companies and research institutions, the study demonstrates that robust Intellectual Property Protection (IPP) exerts a significant and direct influence on enhancing technology transfer. In contrast, innovation capabilities alone do not significantly affect transfer outcomes. Instead, network dynamics strengthen these capabilities, which in turn support technology transfer — but only when embedded within solid institutional frameworks. These findings challenge the common assumption that innovation capabilities are sufficient for successful technology commercialization. They emphasize the critical importance of institutional quality and cooperation networks in transitional economies. At the theoretical level, the study integrates resource-based, institutional, and open innovation perspectives to address the “innovation-implementation” gap. Practically, it highlights key policy priorities: strengthening IPP enforcement, establishing specialized IPP courts, and fostering partnerships between universities and industry, as well as within innovation clusters. For companies and universities, developing absorptive capacity and engaging in cross-border collaborations are essential for maximizing the benefits of external knowledge. While limited by its regional focus and cross-sectional design, this research offers a nuanced framework for sustainable technology transfer in Southeast Europe and underscores the need for further comparative and longitudinal studies to deepen our understanding of this phenomenon.

The clinical outcome of chronic mitral regurgitation (MR) in children and adolescents, specifically the time it takes for Mr to develop significant changes in the configuration and function of the left atrium (LA), is a relatively understudied area. Numerous echocardiographic parameters demonstrate significant changes in the size, volume, and functional behavior of the LA; however, they lack the ability for early and fine detection of LA dysfunction. Left atrial strain (LAS) analysis represents a newer non-invasive technique for assessing LA function and early detection of its deformation and dysfunction. In the analysis of patients with chronic and significant Mr, it emerges as a method that could verify early deformative, functional, and possibly fibrotic changes in the LA and thus predispose rhythm disturbances and clinical manifestations. This study relates to strain analysis of LA function, which can have prognostic and clinical implications in pediatric cardiology and be of great assistance in deciding when to initiate Mr treatment.

The imperatively excellent performance of wavelength-division multiplexing (WDM) transmission over a fiber optic link, demands flat, i.e. not wavelength-selective transfer function. This implies that, mostly during installation and commissioning of a WDM-aimed fiber link, it is of interest to measure its frequency response, by complex stimulus-response tests using a tunable laser source coupled with an optical spectrum analyzer. On the contrary, a simple and practically costless alternative that we propose here, is testing in time domain by means of the ubiquitous optical time-domain reflectometer (OTDR), considering its distinctly reflective trace pattern as approximation of the fiber channel two-way power-delay profile, whose rms delay spread is the straightforward indicator of the fiber attenuation vs. wavelength characteristics’ unflatness qualifying the fiber as either appropriate for WDM transport, or requiring piecewise “flattening” of the transfer function by applying coherent optical orthogonal frequency-division multiplexing (CO-OFDM). Specifically, the proposed OTDR – aided WDM suitability fiber test model applied on the exemplar traces, showed significant peak-to-peak DWDM spectrum unflatness, i.e. the pronounced frequency selectivity strongly indicating the need for introducing CO-OFDM on top of WDM. This was found to be monotonically tracked by the WDM transmission performance – the bit-error rate (BER) values in particular, measured with and without the CO-OFDM applied.