Echinococcus multilocularis, the causative agent of alveolar echinococcosis (AE), is a parasitic zoonosis of increasing public health significance in Europe. Although previously confirmed in red foxes in Bosnia and Herzegovina, this study provides the first report of E. multilocularis in golden jackals (Canis aureus) in the country. Between December 2024 and March 2025, a total of 44 golden jackals were examined across 15 localities in Bosnia and Herzegovina, with E. multilocularis detected in 6.8 % of the samples from three sites in Western and Central Bosnia and Herzegovina. Adult Echinococcus spp. worms were first detected using the intestinal scraping technique and identified by microscopy. To confirm these findings and differentiate between Echinococcus species, DNA extracted from adult worms was then subjected to species-specific PCR targeting a fragment of the mitochondrial 12S ribosomal RNA gene. PCR-positive samples for E. multilocularis were further validated by next-generation sequencing (NGS) of a 203 bp amplicon of the 12S rRNA gene. These findings indicate an expanding distribution of E. multilocularis in Bosnia and Herzegovina, highlighting the role of golden jackals as definitive hosts for the parasite. Given the growing jackal population in the country and the increasing public health concerns, enhanced surveillance and further research are warranted, particularly regarding human cases of E. multilocularis infection, to better understand the associated epidemiological risks.

Floating modular energy islands (FMEIs) are modular, interconnected floating structures designed to collectively produce, store, convert, and transport renewable energy. This review aims to establish a foundation for developing innovative approaches to sustainably harness multi-energy sources in offshore environments. It leverages existing technological expertise while exploring new solutions to address specific challenges associated with FMEIs. The review initially presents existing technologies for floating energy structures and assesses their applicability to FMEI. The structural materials that could be utilised for the construction of a floating energy island are subsequently reviewed. Next, the offshore construction technologies suitable for FMEI are reviewed. Finally, studies on the life cycle assessment of hybrid energy systems are examined, highlighting the environmental advantages of integrating multiple renewable energy sources, thereby underscoring the potential of FMEIs.

African swine fever virus (ASFV) is a major threat for pig health and meat production in many countries. The development and commercialization of vaccine candidates are complicated by efficacy and safety concerns. Improved vaccine design requires further studies to identify factors that regulate immune responses to vaccines leading to protective immunity against a virulent challenge. In a previous study, we reported that infection with the moderately virulent ASFV field strain Estonia 2014 was less severe in specific pathogen-free (SPF) pigs than in conventional farm pigs, which differ in their gut microbiome and their basal immune activation status. As shown previously using intramuscular infection, SPF pigs were more resilient to oronasal infection with the ASFV Estonia 2014 strain compared to farm pigs, which showed increased fever and clinical signs. All SPF and farm pigs nevertheless survived the infection and remained viremic for approximately 4 months. When all animals had no detectable viremia, both groups were rechallenged with the virulent ASFV Armenia 2008 strain. SPF pigs were fully protected against disease and showed little or no viremia upon re-challenge. In contrast, farm pigs developed high viremia, high proinflammatory cytokine responses, severe clinical signs, and 40% (2 of 5 pigs) reached humane endpoints. Our findings suggest that limited prior immune exposure to other pathogens and/or the microbiome composition of SPF pigs promotes resilience to infection with a moderately virulent strain such as Estonia 2014, and importantly promotes the development of a strong protective immune response against a second challenge with a virulent ASFV strain. In conclusion, testing safety and efficacy of live attenuated vaccine candidates should take into account the specific hygiene conditions and the associated changes of general immune status of pigs in clinical trials.

The class \(\mathcal{S}^{\sharp \flat }(\sigma_0, \sigma_1)\) is a very broad class of \(L\) functions that contains the Selberg class, the class of all automorphic \(L\) functions and the Rankin–Selberg \(L\) functions, as well as products of suitable shifts of those functions. In this paper, we consider generalized Euler-Stieltjes constants \(\gamma_n(F)\) attached to functions \(F(s)\) from the class \(\mathcal{S}^{\sharp \flat }(\sigma_0, \sigma_1)\). These are coefficients in Laurent series expansion of function \(F(s)\) at its pole. We derive an integral representation and an upper bound for these constants. The application of the obtained results in the case of product of suitable shifts of the Riemann zeta function is presented.

The Radiological Society of North America (RSNA) Lumbar Degenerative Imaging Spine Classification (LumbarDISC) dataset is the largest publicly available dataset of adult MRI lumbar spine examinations annotated for degenerative changes. The dataset includes 2,697 patients with a total of 8,593 image series from 8 institutions across 6 countries and 5 continents. The dataset is available for free for non-commercial use via Kaggle and RSNA Medical Imaging Resource of AI (MIRA). The dataset was created for the RSNA 2024 Lumbar Spine Degenerative Classification competition where competitors developed deep learning models to grade degenerative changes in the lumbar spine. The degree of spinal canal, subarticular recess, and neural foraminal stenosis was graded at each intervertebral disc level in the lumbar spine. The images were annotated by expert volunteer neuroradiologists and musculoskeletal radiologists from the RSNA, American Society of Neuroradiology, and the American Society of Spine Radiology. This dataset aims to facilitate research and development in machine learning and lumbar spine imaging to lead to improved patient care and clinical efficiency.

The analysis of emotional speech has gained significant attention in the fields of s peech r ecognition a nd natural language processing. From emotion recognition to emotional text-to-speech synthesis, emotional speech plays a crucial role, particularly in areas such as human-computer interaction and intelligent robotics. However, this area remains underexplored. Recent research trends emphasize the use of multimodal data, such as emotional audio and video recordings. Although effective, these approaches require additional resources, which can be time-consuming and costly, especially for low-resource languages such as Serbian. On the other hand, a significant g ap exists in understanding cognitive processes involved in human emotional speech production. To address this, emotional speech from an information-theoretic perspective was explored. Specifically, surprisal values, estimated using five s tate-of-the-art language models were analyzed for their correlation with spoken word duration. The results indicated variations in Pearson's coefficient between these parameters in different emotional states, with general multilingual models outperforming Serbian-specific models in surprising estimation. These results can offer valuable insights into emotional speech production in other South Slavic languages as well, such as in Croatian, Bosnian, and Montenegrin.

This study offers a comprehensive evaluation of two English language textbooks, Way to Go 8 and Challenges 4, widely used in primary schools in the Canton of Central Bosnia. Utilizing Littlejohn's analytical framework for material analysis and Xiao's model of cultural categorization, the research investigates the structural design, learner engagement strategies, curriculum alignment, and cultural content integration in both textbooks. The findings reveal that Challenges 4 exhibits greater coherence in design and organization, while Way to Go 8 demonstrates a fragmented presentation of topics and grammar. Both textbooks predominantly emphasize individual written exercises, focusing on information decoding and selection, while offering limited opportunities for developing functional skills such as problem-solving, communication, and critical thinking. Although both textbooks align with the official curriculum regarding topics, grammar, and vocabulary, the integration of cultural content is minimal and lacks depth, with cultural references being sporadic and not thoroughly embedded within the learning material. The study suggests that enhancing the incorporation of functional skill development activities and more substantial cultural content could improve the effectiveness of these textbooks in fostering comprehensive language proficiency among learners.  Article visualizations:

One of the study's objectives was to detect differences in body image satisfaction among women who engage in kinesiological activities, with respect to their chronological age. One of the fundamental functions of the human body is physical activity. As defined, physical activity requires increased energy expenditure. Energy expenditure is most commonly expressed as the amount of oxygen consumed per unit of time, measured in absolute (ml×min⁻¹) or relative oxygen uptake (ml×min⁻¹·kg⁻¹). Physical activity is described through four dimensions: frequency, duration, intensity, and type of activity (Caspersen, Powell & Christensen, 1985). Frequency refers to the number of activity repetitions within a given timeframe (weekly or monthly).Total physical activity includes, alongside all other forms, health-oriented physical activities that are specifically aimed at improving health. Given that a high capacity for physical performance is a positive health criterion (Mišigoj-Duraković et al., 1999), health-oriented physical activity also includes structured and planned non-competitive exercise and sports.A potential classification of influencing factors can be divided into four categories: (1) personalcharacteristics (e.g., age, gender, education level, experience, type of occupation, body mass index, health status), (2) psychological and behavioral characteristics (e.g., self-efficacy, enjoyment, self-motivation, perceived barriers), (3) environmentalfactors (social and physical) (e.g., social support, access and opportunities for physical activity, climate conditions, safety), and (4) characteristics of the physicalactivity itself (e.g., intensity, type, perceived exertion) (Nahas, Goldfine & Collins, 2003).Keywords: Age, activity, differences, correlations, time.

Objective. This study aimed to investigate the potential of contrastive learning to improve auditory attention decoding (AAD) using electroencephalography (EEG) data in challenging cocktail-party scenarios with competing speech and background noise. Approach. Three different models were implemented for comparison: a baseline linear model (LM), a non-LM without contrastive learning (NLM), and a non-LM with contrastive learning (NLMwCL). The EEG data and speech envelopes were used to train these models. The NLMwCL model used SigLIP, a variant of CLIP loss, to embed the data. The speech envelopes were reconstructed from the models and compared with the attended and ignored speech envelopes to assess reconstruction accuracy, measured as the correlation between the reconstructed and actual speech envelopes. These reconstruction accuracies were then compared to classify attention. All models were evaluated in 34 listeners with hearing impairment. Results. The reconstruction accuracy for attended and ignored speech, along with attention classification accuracy, was calculated for each model across various time windows. The NLMwCL consistently outperformed the other models in both speech reconstruction and attention classification. For a 3-second time window, the NLMwCL model achieved a mean attended speech reconstruction accuracy of 0.105 and a mean attention classification accuracy of 68.0%, while the NLM model scored 0.096 and 64.4%, and the LM achieved 0.084 and 62.6%, respectively. Significance. These findings demonstrate the promise of contrastive learning in improving AAD and highlight the potential of EEG-based tools for clinical applications, and progress in hearing technology, particularly in the design of new neuro-steered signal processing algorithms.

When the strong-field ionization of atoms is induced by an ultrashort pulse instead of a long pulse with a flat envelope, many symmetry properties of the photoelecton momentum distribution are broken. The induced asymmetry is measured using the asymmetry parameter which depends on the values of the driving-pulse parameters and the type of the target. We investigate the driving pulses with two carrier frequencies because in this case the dependence of the asymmetry on the characteristics of the target is more robust. Particular attention is devoted to the pulse which consists of two circularly polarized few-cycle waves and the pulse which has two linearly polarized components with mutually orthogonal polarizations. In the former case, we show that the asymmetry parameter is highly sensitive to the ionization potential and to the structure of the ground state. This is particularly the case for the photoelectron energy just above the value for which the contribution of the electrons which do not interact with the core after the ionization becomes negligible. We explain this sensitivity by investigating the dependence of the short-travel-time saddle-point solutions on the characteristics of the target. On the other hand, for the driving pulse with linearly polarized components, the dependence of the asymmetry parameter on the ionization potential is significant, while the dependence on the structure of the ground state is relatively small. In conclusion, we show that the characteristics of the target are imprinted in the asymmetry parameter and this signature is more pronounced for two-component pulses than for the linearly polarized driving pulse with one carrier frequency. Published by the American Physical Society 2025

: This paper shows the preliminary results of an investigation into the possibility of using red mud slag (RMS) for phosphate sorption from aqueous solutions. The red mud slag was obtained from red mud treatment, specifically from carbothermal reduction at high temperatures. This process resulted in forming a metallic phase (iron) and slag enriched with other elements. The preliminary analysis of slag is performed to investigate its potential for use as a phosphate sorbent in wastewater treatment. The slag is divided into three categories. Two of them are obtained by sieving an original slag sample in the fine fraction and the coarse fraction (the slag residual after sieving). The third sample is the raw slag. After an experiment that included 24 h shaking of slag and phosphate solution, the results show potential for using red mud slag in phosphate sorption. It is an initial experiment that will be a starting point for further investigation of the sorption characteristics of red mud slag.

The aim of the research is to determine the effects of the pandemic caused by the Coronavirus (COVID-19) on the mental and physical health of young adult women, using standardized instruments for the assessment of mental and physical health. The sample of 40 women was selected into two groups according to the continuity of recreational physical activity during the pandemic caused by the Coronavirus. An increase in symptoms of depression and anxiety was recorded in both groups during the pandemic, but it could be noted that respondents from the discontinuous level of physical activity group recorded a higher degree of depression and anxiety compared to respondents from the continuous level of physical activity group. In terms of physical health, respondents who continued physical activity maintained relatively stable physical health results during the pandemic, while respondents who did not maintain continuity of work showed significantly worse results compared to the period before the pandemic. Thus, regular physical activity is associated with better mental and physical health during the pandemic caused by the Coronavirus (COVID-19). Overall, this research emphasizes the importance of maintaining regular recreational activities, even during crisis situations, as a key factor for preserving psychophysical health.Keywords: Depression, anxiety, HAD scale, EQ thermometer.