This research aims to investigate the concept of industrial symbiosis as a change agent in the Circular Economy, with its consequent effects on the economy, the environment, and society in terms of sustainable development. This study employs qualitative research with quantitative support from a structured survey of 152 IS project experts, researchers, and practitioners, utilizing a questionnaire comprising Likert-type and multiple-choice questions. Data were aggregated into composite indicators and analyzed by using a log-log multiple regression model. Empirical results reveal that economic benefits are the most significant positive drivers. The actors’ involvement also contributes positively, highlighting the importance of multi-stakeholder collaboration. Conversely, barriers have the strongest and the highest negative scale impact on perceived IS synergies. Broader economic and social conditions moderately enhance synergies, while awareness and training show a weaker but positive effect. IS is both economically viable and environmentally necessary, but its expansion depends on reducing financial, regulatory, and infrastructural barriers. Certain economic policy-driven interventions, such as fiscal incentives, regulatory clarity, and investment, enable infrastructure to scale up the adoption of IS.

Fifth-generation (5 G) network slicing enables multiple logical networks to share the same infrastructure, each designed to support distinct Service Level Agreements (SLAs). While network slicing is well supported in the Radio Access Network (RAN) and 5 G Core (5GC), the Transport Network (TN) backhaul is often treated as a slice-agnostic forwarding substrate. As a result, resource contention on shared links can significantly degrade network performance, such as latency and throughput, breaking end-to-end SLAs. This paper addresses this gap by making the TN sliceaware through a lightweight framework that translates slice requirements into concrete backhaul policies. The framework (i) associates each slice with TN identifiers at domain boundaries, (ii) turns slice requirements into per-slice forwarding and scheduling policies (e.g., priority and queue selection, bandwidth bounds, and optional congestion signals), and (iii) exports perslice measurements for monitoring and closed-loop control. We deploy a proof of concept on a programmable switch and evaluate it on a real-life 5 G testbed. Our results show that, under link saturation, slices designed for mission-critical services preserve their SLAs, while best-effort traffic degrades predictably.

This paper compiles results from six systematic reviews and meta-analyses on associations between environmental and occupational exposure to chemicals and levels of DNA strand breaks in human leukocytes, measured by the comet assay. There are no differences in effect sizes when using different comet descriptors. However, lower central tendencies are obtained by using a non-parametric test as compared to the standard parametric analysis, indicating that the standard meta-analyses tend to overestimate the effect size. The compiled results indicate that exposures can be sorted into three groups with decreasing effect size: high (pesticides), moderate (volatile organic compounds, heavy metals and antineoplastic drugs), and low (anaesthetic gases and air pollution). Interestingly, studies from middle-income countries have higher effect sizes than those seen in studies from high-income countries. This may be related to higher exposures or lower socioeconomic status in middle-income countries. However, there is also some co-variability between studies from middle-income countries and the risk of comet assay measurement bias, assessed as information provided in published papers. Lack of information on assay controls and blinded/coded sample analysis appears to be a general issue in studies on comet assay results. Risk of exposure misclassification is mainly related to the type of exposure; there are good biomarkers for some exposures (e.g. heavy metals), whereas other exposures are more challenging to assess with biomarkers (e.g. pesticides). In conclusion, all examined exposures result in significant increases in DNA strand breaks at the population level, though to varying degrees.

Background: Breast clip marker movement after ultrasound-guided biopsy can negatively affect lesion re-localisation rates and surgical outcomes, underscoring the need for improved understanding of the factors influencing clip displacement. Thus, this study aimed to compare four different breast clip markers and identify risk factors for clip migration and dislocation after ultrasound-guided placement. Methods: This retrospective study included 350 patients who underwent ultrasound-guided biopsy of a newly diagnosed breast lesion with placement of one of four types of breast clips (UltraClip Dual Trigger Biodur 108 Coil Marker [UC], TUMARK Professional [TP], TUMARK Vision [TV] and HydroMARK Breast Biopsy Site Marker [HM]). Clip migration and dislocation were assessed immediately after placement and during follow-up imaging for at least 3 months. A binary logistic regression analysis was performed to identify predictors of clip dislocation including lesional, perilesional and procedural parameters. Results: Clip migration rates were 26.0%, 18.0%, 10.0% and 25.0% and clip dislocation rates were 14.0%, 20.0%, 9.0% and 38.0% for UC, TP, TV and HM, respectively. Features significantly associated with clip dislocation included predominantly fatty surrounding tissue (p = 0.046) with low perilesional shear wave velocities (p = 0.054), smooth lesion contours (p = 0.041), soft lesion strain elastography (p =0.001), low clip-to-lesion-surface distance (p = 0.002) and the use of an HM breast clip (p = 0.032). Conclusions: The type of breast clip-marker, as well as perilesional and lesional characteristics, influence the likelihood of clip dislocation. Notably, the hydrogel-coated clip (HM) exhibited the highest rate of dislocation.

The management of locally-advanced, resectable head and neck squamous cell carcinoma (HNSCC) is undergoing a major shift driven by the integration of neoadjuvant immunotherapy (nIO). The rationale for nIO lies in its administration within an immunologically active, treatment-naïve microenvironment that enhances immune priming and anti-tumor response. Despite encouraging clinical data, including the pivotal KEYNOTE-689 trial and multiple phase II studies, methodological heterogeneity in trial design, endpoint definitions, and response criteria currently hampers data comparability and the establishment of new standards of care. This expert narrative review proposes a structured framework for standardizing clinical, pathologic, imaging, and translational endpoints in HNSCC nIO trials, highlighting harmonized definitions of pathologic response, practical reporting templates, and methods to evaluate immune priming. Standardization of response evaluation, biomarker integration, and trial methodology is essential to accelerate the translation of neoadjuvant immunotherapy into routine clinical practice for HNSCC.

The aim of this study was to evaluate outcomes of surgical correction of penile curvature using autologous graft materials in patients with Peyronie’s disease, with emphasis on functional recovery, penile length changes, cosmetic results and patient-reported satisfaction. Due to unavailability of commercial extracellular matrix grafts, autologous materials including buccal mucosa, rectus fascia, fascia of the tensor fasciae latae and saphenous vein were utilized. This study included male patients treated for penile curvature due to Peyronie’s disease at the Department of Urology, Clinical Centre University of Sarajevo between 2018 and 2023. All patients had stable disease for more than 12 months. Preoperative assessment included penile Doppler ultrasonography, curvature measurement and flaccid penile length evaluation. Erectile function was measured using the validated International Index of Erectile Function (IIEF-5), and disease burden was assessed via the Peyronie’s Disease Questionnaire (PDQ). A postoperative patient satisfaction survey was performed combining validated components (Erection Hardness Score and EDITS satisfaction elements) with a graft-specific preference scale. Patients were divided into four groups based on graft type. Groups 3 and 4 demonstrated superior functional and cosmetic outcomes following surgery (p<0.05). There were no significant differences in complication rates among groups (p>0.05). Curvature recurrence was more frequently observed in Group 4, although not statistically significant (p>0.05). Penile shortening occurred more often in Groups 1 and 2 (p<0.05). Improvement in postoperative IIEF-5 scores was most pronounced in Groups 3 and 4. The patient satisfaction survey showed that patients reported higher postoperative satisfaction, better perceived length preservation, and greater overall acceptability when buccal mucosa was used as graft material compared to other autologous grafts. In settings where commercial grafts are unavailable, autologous graft materials represent a viable option for surgical correction of Peyronie-related curvature. Based on postoperative functional outcomes and validated patient satisfaction measures, buccal mucosa and saphenous vein grafts demonstrated the most favorable profiles and should be considered preferred autologous grafting options. No

Field-of-view (FoV) prediction is critical for reducing device energy consumption and enhancing user quality of experience (QoE) in immersive streaming. To address the high computational and energy costs of standard DL-based FoV prediction, we propose PRECEPT, an energy-efficient, system-oriented two-stage framework. PRECEPT splits the prediction pipeline by adding a lightweight, CPU-based classifier to identify tile change. PRECEPT's classifier successfully filters approximately 80% of “no-change” events. PRECEPT activates the resource-intensive DL model only during identified tile change. This design reduces the average inference delay and energy consumption by up to 69% in a real mobile deployment. PRE-CEPT's two-stage design enables sustainable, high-performance FoV prediction on resource-constrained devices.

This study examines spatial marginalization in Bosansko Grahovo, one of the most depopulated and socio-economically underdeveloped municipalities in Bosnia and Herzegovina, located on the EU border with Croatia. Using a mixed-methods approach, the study integrates a previously developed Geographical Marginalization Index (GMAR) with survey data and interviews. The findings reveal a strong convergence between quantitative indicators of marginalization and residents’ perceptions, supporting the interpretation of Bosansko Grahovo as an example of double periphery defined by geographical remoteness and systemic exclusion. While the border itself is not perceived as the primary driver of decline, post-war legacies, institutional fragmentation and infrastructural deficits interact cumulatively to produce what is conceptualized as a selfreinforcing vicious circle of marginalization. Combining quantitative indicators with perception-based evidence allows for a better understanding of how marginalization persists in peripheral border areas.

Background: The diagnosis of urinary tract infection (UTI) remains a clinical challenge, with urine culture as the gold standard. In developing countries like Bosnia and Herzegovina, a high prevalence of antimicrobial resistance and frequent empirical treatment pose significant clinical challenges. Automated urine flow cytometry has emerged as a rapid tool to optimize diagnostic processes. Objectives: To determine the correlation of age, gender, and laboratory parameters—such as white blood cell (WBC) count, neutrophil count, and C-reactive protein (CRP)—with both urinary bacterial counts and urine culture results. Methods: This retrospective study analyzed 200 adult patients (≥18 years) with symptoms suggestive of UTI at the University Clinical Center Tuzla. Data on age, gender, WBC, neutrophils, CRP, and urine flow cytometry (Sysmex UF-4000) were collected. Statistical analysis was performed using R software (version 4.5.1), utilizing logistic regression models via the ‘glm’ function to identify independent predictors, with statistical significance set at p < 0.05. Results: The mean age of the population was 68.61 ± 15.19 years. Logistic regression demonstrated that WBC count (OR = 1.06, p = 0.004), neutrophil count (OR = 1.04, p = 0.014), and patient age (OR = 1.03, p = 0.001) were significant independent predictors of UTI. Furthermore, patients with a urinary bacterial count > 1200/μL had 83 times higher odds of a positive urine culture (OR = 83, 95% CI 32.25–200, p < 0.001). Conversely, CRP levels and gender were not significant predictors (p > 0.05). Conclusions: Patient age, WBC, and neutrophil counts are key factors for predicting UTIs. Integrating these parameters with urine flow cytometry bacterial counts can significantly enhance diagnostic accuracy and rapid screening in clinical practice.