Abstract Unfounded—conspiracy and health—beliefs about COVID-19 have accompanied the pandemic worldwide. Here, we examined cross-nationally the structure and correlates of these beliefs with an 8-item scale, using a multigroup confirmatory factor analysis. We obtained a two-factor model of unfounded (conspiracy and health) beliefs with good internal structure (average CFI = 0.98, RMSEA = 0.05, SRMR = 0.04), but a high correlation between the two factors (average latent factor correlation = 0.57). This model was replicable across 50 countries (total N = 13,579), as evidenced by metric invariance between countries (CFI = 0.96, RMSEA = 0.06, SRMS = 0.07) as well as scalar invariance across genders (CFI = 0.98, RMSEA = 0.04, SRMS = 0.03) and educational levels (CFI = 0.98, RMSEA = 0.04, SRMS = 0.03). Also, lower levels of education, more fear of COVID-19, and more cynicism were weakly associated with stronger conspiracy and health beliefs. The study contributes to knowledge about the structure of unfounded beliefs, and reveals the potential relevance of affective (i.e., fear of COVID-19) and cognitive (i.e., cynicism) factors along with demographics, in endorsing such beliefs. In summary, we obtained cross-cultural evidence for the distinctiveness of unfounded conspiracy and health beliefs about COVID-19 in terms of their structure and correlates.

Human life and body represent social values that have always been and remain the subject of criminal law protection. Precisely, the authors in the first part of the work point to the incrimination of the crime of murder throughout the historical era of Serbia and the neighboring countries, and also that the life and body of members of certain social classes were not subject to criminal law protection, and in certain eras the criminal law protection of life and body was not provided equally to every person. The continuous development of society and changes in all spheres led to the need for more and more contact between people, and their relationships led to various conflicts and the desire to be resolved at their own discretion. The second part of the work deals with conflict situations that led to mutual attacks in order to resolve the situations that ended with an attack and endangering the physical integrity of people. Thus, when studying the criminal offense of murder, which is one of the classics, perhaps even the oldest criminal offense which has already been discussed so much from a theoretical point of view and, at first glance, it seems that everything has already been said, there are still a lot of disputed questions that need to be discussed, in a theoretical, criminological sense, as well as to clarify the problems that arise in judicial practice. Some research indicates that a high percentage (even over 80 percent) of perpetrators of criminal acts would not have started committing criminal acts if they had known for sure that they would be discovered as perpetrators of the same. Research data indicate that violence in Serbia has increased by 74%. The third part of the work deals with the incrimination of the most serious criminal offense from the aspect of modern and international criminal law, as well as their recommendations for the purpose of prevention and repression.

Attacks by dogs, primarily stray dogs, are a very common problem faced by both underdeveloped and developed local goverments. The damage caused by attacks from stray dogs has multiple, and often long-lasting, harmful consequences for their victims, which are also reflected on members of their families. This manuscript provides a veterinary-epidemiological definition of the concept of dogs, as well as their legal definition in the context of „dangerous things“, and the psychological aspect that is regularly manifested in victims. Analyzing the legislation of Bosnia and Herzegovina, with a comparative presentation of the regulations of the EU member states, systematic overviews and answers are given, which are important for the improvement of existing regulations and harmonization of law and jurisprudence.

Background and Objectives: Cranial defects pose significant challenges in low and middle-income countries (LIMCs), necessitating innovative and cost-effective craniofacial reconstruction strategies. The purpose of this study was to present the Bosnia and Herzegovina model, showcasing the potential of a multidisciplinary team and 3D-based technologies, particularly PMMA implants, to address cranial defects in a resource-limited setting. Materials and Methods: An observational, non-experimental prospective investigation involved three cases of cranioplasty at the Department of Neurosurgery, Cantonal Hospital Zenica, Bosnia and Herzegovina, between 2019 and 2023. The technical process included 3D imaging and modeling with MIMICS software (version 10.01), 3D printing of the prototype, mold construction and intraoperative modification for precise implant fitting. Results: The Bosnia and Herzegovina model demonstrated successful outcomes in cranioplasty, with PMMA implants proving cost-effective and efficient in addressing cranial defects. Intraoperative modification contributed to reduced costs and potential complications, while the multidisciplinary approach and 3D-based technologies facilitated accurate reconstruction. Conclusions: The Bosnia and Herzegovina model showcases a cost-effective and efficient approach for craniofacial reconstruction in LIMICs. Collaborative efforts, 3D-based technologies, and PMMA implants contribute to successful outcomes. Further research is needed to validate sustained benefits and enhance craniofacial reconstruction strategies in resource-constrained settings.

To continue downscaling transistors, new materials must be explored. Two-dimensional (2D) materials are appealing due to their thinness and bandgap. The relatively weak van der Waals forces between layers in 2D materials allow easy exfoliation and device fabrication but also result in poor heat transfer between layers and to the substrate, which is the main path for heat removal, resulting in self-heating and thermal degradation of mobility. This study explores the electrothermal properties of five popular 2D materials (MoS2, MoSe2, WS2, WSe2, and 2D black phosphorous). We simulate various devices with self-heating with a range of gate and drain biases and examine the effects on mobility and change in device temperature. The effects are compared to the isothermal case to ascertain the impact of self-heating. We observe that Joule heating has a significant effect on temperature rise, layerwise drain current, and effective mobility. We show that black phosphorous performs the best thermally, owing to its relatively high thermal conductance to the substrate, while WSe2 performs the best electrically. This study will inform future thermally aware designs of nanoelectronic devices based on 2D materials.

The process of fish cage inspections, which is a necessary maintenance task at any fish farm, be it small-scale or industrial, is a task that has the potential to be fully automated. Replacing trained divers who perform regular inspections with autonomous marine vehicles would lower the costs of manpower and remove the risks associated with humans performing underwater inspections. Achieving such a level of autonomy implies developing an image processing algorithm that is capable of estimating the state of biofouling buildup. The aim of this work is to propose a complete solution for automating the said inspection process; from developing an autonomous control algorithm for an ROV, to automatically segmenting images of fish cages, and accurately estimating the state of biofouling. The first part is achieved by modifying a commercially available ROV with an acoustic SBL positioning system and developing a closed-loop control system. The second part is realized by implementing a proposed biofouling estimation framework, which relies on AI to perform image segmentation, and by processing images using established computer vision methods to obtain a rough estimate of the distance of the ROV from the fish cage. This also involved developing a labeling tool in order to create a dataset of images for the neural network performing the semantic segmentation to be trained on. The experimental results show the viability of using an ROV fitted with an acoustic transponder for autonomous missions, and demonstrate the biofouling estimation framework’s ability to provide accurate assessments, alongside satisfactory distance estimation capabilities. In conclusion, the achieved biofouling estimation accuracy showcases clear potential for use in the aquaculture industry.

In recent years, more and more attention has been paid to the behavior of tourists and their intention to choose a destination based on various factors. The goal of this research was to determine to what extent environmental risks and the attractiveness of the destination influence the choice of destination and the behavior of tourists. Furthermore, the goal was to determine the influence of psychological groups of tourists on their decision to choose a tourist destination using three psychographic techniques: BFI-10 (Big Five Inventories), AIO (Activities, Interests, and Opinions), and VALS 2 (Values and Lifestyle), and a freely determined six-level scale of risk and tourist attractiveness of imagined destinations. Analyzing the results obtained through the structural modeling-path analysis model, it was determined that tourists grouped in almost all psychographic orientations, resulting from lifestyles, negatively perceive destinations with a high degree of risk and attractiveness, while, with the VALS 2 technique, only members of the action orientation tend to accept ecologically risky destinations. Despite the fact that many studies have looked at how tourists perceive various risks and behave, it is still uncommon to use an integrated approach that considers the simultaneous application of several psychological tests and a unique method of gathering responses from travelers by presenting them with descriptively imagined destinations that differ in their levels of environmental risk and tourist appeal. As a result, this study can provide a conceptual framework for theoretical and practical implications for improved risk management strategies in a specific travel destination and in areas vulnerable to environmental hazards, as well as for completing knowledge about traveler behavior in risky destinations.

The rapid development of machine learning (ML) techniques has opened up the data-dense field of microbiome research for novel therapeutic, diagnostic, and prognostic applications targeting a wide range of disorders, which could substantially improve healthcare practices in the era of precision medicine. However, several challenges must be addressed to exploit the benefits of ML in this field fully. In particular, there is a need to establish “gold standard” protocols for conducting ML analysis experiments and improve interactions between microbiome researchers and ML experts. The Machine Learning Techniques in Human Microbiome Studies (ML4Microbiome) COST Action CA18131 is a European network established in 2019 to promote collaboration between discovery-oriented microbiome researchers and data-driven ML experts to optimize and standardize ML approaches for microbiome analysis. This perspective paper presents the key achievements of ML4Microbiome, which include identifying predictive and discriminatory ‘omics’ features, improving repeatability and comparability, developing automation procedures, and defining priority areas for the novel development of ML methods targeting the microbiome. The insights gained from ML4Microbiome will help to maximize the potential of ML in microbiome research and pave the way for new and improved healthcare practices.

G protein-coupled receptors are among the most widely studied classes of drug targets. A major challenge in this field is to develop ligands that will selectively modulate a single receptor subtype to overcome the disadvantages of undesired “off target” effects caused by lack of target and thus signaling specificity. In the current study, we explored ligand design for the melanocortin 4 receptor (MC4R) since it is an attractive target for developing antiobesity drugs. Endogenously, the receptor is activated by peptide ligands, i.e., three melanocyte-stimulating hormones (α-MSH, β-MSH, and γ-MSH) and by adrenocorticotropic hormone. Therefore, we utilized a peptide drug design approach, utilizing “molecular grafting” of pharmacophore peptide sequence motifs onto a stable nature-derived peptide scaffold. Specifically, protegrin-4-like-peptide-1 (Pr4LP1) and arenicin-1-like-peptide-1 (Ar3LP1) fully activated MC4R in a functional cAMP assay with potencies of 3.7 and 1.0 nM, respectively. In a nanoluciferase complementation assay with less signal amplification, the designed peptides fully recruited mini-Gs with subnanomolar and nanomolar potencies. Interestingly, these novel peptide MC4R ligands recruited β-arrestin-2 with ∼2-fold greater efficacies and ∼20-fold increased potencies as compared to the endogenous α-MSH. The peptides were inactive at related MC1R and MC3R in a cAMP accumulation assay. These findings highlight the applicability of animal-derived disulfide-rich scaffolds to design pathway and subtype selective MC4R pharmacological probes. In the future, this approach could be exploited to develop functionally selective ligands that could offer safer and more effective obesity drugs.

ABSTRACT Introduction Antimicrobial resistance (AMR) is a global concern. Currently, the greatest mortality due to AMR is in Africa. A key driver continues to be high levels of dispensing of antibiotics without a prescription. Areas covered A need to document current rates of dispensing, their rationale and potential ways forward including antimicrobial stewardship programmes (ASPs). A narrative review was undertaken. The highest rates of antibiotic purchasing were in Eritrea (up to 89.2% of antibiotics dispensed), Ethiopia (up to 87.9%), Nigeria (up to 86.5%), Tanzania (up to 92.3%) and Zambia (up to 100% of pharmacies dispensing antibiotics without a prescription). However, considerable variation was seen with no dispensing in a minority of countries and situations. Key drivers of self-purchasing included high co-payment levels for physician consultations and antibiotic costs, travel costs, convenience of pharmacies, patient requests, limited knowledge of antibiotics and AMR and weak enforcement. ASPs have been introduced in some African countries along with quality targets to reduce inappropriate dispensing, centering on educating pharmacists and patients. Expert Opinion ASP activities need accelerating among community pharmacies alongside quality targets, with greater monitoring of pharmacists’ activities to reduce inappropriate dispensing. Such activities, alongside educating patients and healthcare professionals, should enhance appropriate dispensing of antibiotics and reduce AMR.

This research investigated renovation considerations and design strategies for post-pandemic, hybrid office environment within an academic institution. The focus was on two case-study office spaces that are part of the same organization at the University of Utah, where the existing physical space was insufficient for future growth and non-functional for its novel, hybrid work mode structure. The objective was to evaluate the physical conditions of the existing office spaces, to investigate the employees’ working patterns and office culture, and to propose renovation strategies that would meet both the current and the projected future needs that support a hybrid work structure. The study was based on mixed-mode research methods, which included qualitative and quantitative methods. Qualitative methods included archival and empirical research of the existing office space conditions, as well as users’ input through online survey and focus group interviews. Using the latest, as-built construction drawings and current state photographs, 3D BIM models of each of the two office wings were developed, inclusive of their structural elements, partition walls, existing lighting fixture locations and specific furniture arrangements. These models were then used for egress, circulation, daylighting, and existing space planning analysis. Literature review was also conducted, identifying rising trends and design considerations for hybrid office workflow. Surveys and focus group interviews were conducted with current employees of the two offices to evaluate work patterns and space needs through user insight. Meanwhile, quantitative methods included quantitative analysis of the survey and focus group interview results, computational modeling, and visualization of the existing and proposed design strategies, as well as a review and validation of final design’s egress and accessibility compliance. Through several design option iterations, these results were used to provide space planning strategies and recommendations that meet the specific needs of these two office spaces. The final design, which considered users’ input regarding team dynamics, work schedules, and specific space and function needs, achieved a significant improvement in balances between team and individual space functions, private and public circulation, access to daylight and accessibility, while respecting the existing wall partitions, egress paths and occupancy counts. Moreover, the design solutions provided inclusive, comfortable, and functional spaces that catered to the specific work culture and individualized needs of employees. While this research focused on two specific case-studies, results demonstrate that through a user-integrated approach, significant improvements can be achieved to provide well-functioning spaces and a more comfortable and inclusive working environment. Additionally, the presented process that focuses on user-input and participation in the renovation design process can be applied to other existing, traditionally structured office spaces when transitioning to a hybrid office structure.

COVID-19 is characterised by systemic immunological perturbations in the human body, which can lead to multi-organ damage. Many of these processes are considered to be mediated by the blood. Therefore, to better understand the systemic host response to SARS-CoV-2 infection, we performed systematic analyses of the circulating, soluble proteins in the blood through global proteomics by mass-spectrometry (MS) proteomics. Here, we show that a large part of the soluble blood proteome is altered in COVID-19, among them elevated levels of interferon-induced and proteasomal proteins. Some proteins that have alternating levels in human cells after a SARS-CoV-2 infection in vitro and in different organs of COVID-19 patients are deregulated in the blood, suggesting shared infection-related changes.The availability of different public proteomic resources on soluble blood proteome alterations leaves uncertainty about the change of a given protein during COVID-19. Hence, we performed a systematic review and meta-analysis of MS global proteomics studies of soluble blood proteomes, including up to 1706 individuals (1039 COVID-19 patients), to provide concluding estimates for the alteration of 1517 soluble blood proteins in COVID-19. Finally, based on the meta-analysis we developed CoViMAPP, an open-access resource for effect sizes of alterations and diagnostic potential of soluble blood proteins in COVID-19, which is publicly available for the research, clinical, and academic community.

In this research, the SWAT+ model was employed to elucidate hydrological dynamics within the Beas Basin. The primary objectives encompassed the calibration of the SWAT model for accurate water balance quantification, annual simulation of salient hydrological components, and a decadal analysis of trends in fluvial discharge and sediment transport. The methodology encompasses simulating hydrological data with the SWAT+ model, followed by calibration and validation using flow data from Larji and Mahadev hydroelectric plants. The model’s efficacy in depicting streamflow and other hydrological components is corroborated by statistical measures such as the Nash–Sutcliffe efficiency and PBIAS. The water balance analysis delivers insights into the basin’s hydrological characteristics, including surface flow, water yield, and evapotranspiration. The temporal analysis exposes intricate seasonal and interannual variability in flow and sediment discharge, while spatial distribution highlights heterogeneity across the basin. These findings have practical implications for water resource management, including optimizing water allocation, hydroelectric power generation, irrigation, and environmental concerns. Limitations, such as data quality and model simplifications, are acknowledged, and future data collection and observations are recommended for improved model performance. In essence, these researches enhance understanding of the Beas Basin’s hydrology, setting a course for future investigations to integrate more data sources, refine model parameters, and consider climate and land-use changes for a richer comprehension of the basin’s hydrological dynamics.