Svako ko je radio pod mentorskom rukom prof. Ugljena, od projektantskog tima A4 na čelu s dugogodišnjim saradnikom, uvaženim arhitektom Brankom Tadićem, pa do kolone generacija studenata koji su prošli kroz čuvena institutska vrata pod brojem 345, upoznao je šta znači zahtjevnost arhitektonske profesije. Kad se spoje jedinstvena autorska vizija, visoki projektantski kriteriji i nemogući rokovi, onda noću svijetle institutski uredi... Strpljivo i s velikom dozom respekta prate tako snažnu stvaralačku ličnost koja mnoštvo svojih djela kreira u duhu Gesamkunstwerka – totalnog dizajna. Do krajnosti je profesor posvećen detaljima, bez obzira na to da li kreira svijećnjak, zdjelu ili ručku na vratima. Ništa ne prepušta slučaju i sve mora biti potčinjeno jedinstvenoj umjetničkoj naraciji. Svestrani interes i iskonsku mladalačku radoznalost iskazuje još u studentskim danima, čemu svjedoče zadnje stranice antologijske knjige Arhitektura Bosne i put u savremeno. Prof. Neidhardt izdvaja raznolike projekte talentiranog učenika Zlatka Ugljena: od uređenja prodavnice, dizajna stolice, skice bosanske seljanke u narodnoj nošnji do makete savremenog enterijera inspiriranog tradicionalnim elementima. 

The electromagnetic coupling phase at the complex resonance pole is a fundamental property of nucleon excitations. However, its extraction from pion photoproduction data remains model-dependent, particularly for the Δ(1232) resonance, where modern multichannel analyses report helicity amplitude phases ranging from +3° to −18°. In this Letter, we present a largely model-independent geometric S-matrix formalism that provides a physical constraint for this ambiguity. By imposing Watson’s final-state interaction theorem, a direct consequence of S-matrix unitarity and time-reversal symmetry, on the real energy axis and performing an analytic continuation, we isolate the kinematic threshold barriers of the photoproduction (k·q) and elastic (q3) amplitudes. For the dominant M1+ multipole transition of the Δ(1232), our method yields a kinematically constrained prediction of ϕEM=−8.5°−1.0°+0.6° for the electromagnetic residue phase. This geometric constraint explains the numerical results of coupled-channel phenomenological fits, validating the extractions by the SAID and Bonn–Gatchina groups, and establishes a theoretical benchmark for evaluating resonance properties.

Titanium fastener technology is increasingly adopted for use in minimally invasive valve surgery and open procedures to facilitate faster operative times and reproducible fastening of sutures. The objective of this study was to evaluate the technical feasibility and short-term safety of automated titanium fastener technology for securing sutures in heart valve repair and/or heart valve replacement procedures. The CRIMP study is a multicenter, prospective study that enrolled patients undergoing heart valve repair or replacement via open or minimally invasive approaches at three centers (n = 120). The primary endpoints were device success and prosthesis implantation time. Mean age was 62.5 (SD 11.1) years, 33.3% of patients was female and the cohort was characterized as low surgical risk (EuroSCORE II 1.6%; SD 2.3%). Predominant valve disease was mitral regurgitation. Median procedure time was 178 (IQR 145–210) min. Median aortic cross-clamp time was 82 (IQR 59–107) min. The majority of procedures was minimally invasive (76.7%). In aortic valve procedures, median prosthesis implantation time (first stitch until last COR-KNOT placement) was 25 (IQR 18–46) min and in mitral valve procedures median implantation time was 50 (IQR 48–52) min. Device success was 100%, since no automated titanium fastener failed to grip or crimp appropriately. Median number of COR-KNOTS used was 14 (IQR 12–16) per valve. In-hospital mortality was 0.8%. All observed adverse events were considered unrelated to the device and there was no valve prosthesis dehiscence at 30-days of follow-up. The use of automated titanium fastener technology for suture fixation in heart valve surgery was technically feasible and showed short-term safety in all patients, with no obvious device-related adverse events observed. Graphical abstract available for this article. Clinical trial registration number: DRKS00038956. Heart valve surgery often requires surgeons to tie many small sutures to secure repaired or replaced valves. Automated titanium fastener devices can replace manual knot tying and may help surgeons work faster and more consistently. This study evaluated whether this technology is safe during short-term observation and technically feasible when used in heart valve repair or replacement surgery. The CRIMP study was a prospective study conducted at three hospitals and included 120 patients undergoing heart valve surgery. Procedures included mitral, tricuspid, and aortic valve repair or replacement. The average patient age was about 63 years, one-third were women, and overall surgical risk was low. Researchers measured if the fastener device worked and how long it took to implant the valve prostheses. The automated titanium fasteners functioned successfully in all cases, meaning every fastener properly secured the sutures. In aortic valve procedures, placing and fastening the sutures took about 25 min, while in mitral valve procedures it took about 50 min. Around 14 fasteners were used per valve. In-hospital mortality was low (0.8%), and no complications were related to the fastener device. At 30 days after surgery, no patients experienced loosening of the implanted valve. However, the study only had one group, which was observed without a comparative group of patients undergoing manual knot tying, and the follow-up period was relatively short, which are important limitations. Overall, the results suggest that automated titanium fastener technology show short-term safety and are technically feasible for securing sutures in heart valve surgery.

This cross-sectional two-step study aimed to investigate the prevalence of eating disorder (ED) symptoms and associated mental health difficulties among elite athletes and an age-and sex matched comparison group. National team athletes were recruited through national sport federations, while participants in the comparison group were recruited via social media. A total of 408 participants (athletes n = 256; comparison group n = 152) (72.1% female), completed an anonymous online survey comprising validated psychometric measures of ED symptoms, exercise addiction, depression and psychological flexibility. Participants who screened positive for ED symptoms and providing contact details were invited to undergo a clinical assessment using the ED Examination Interview (EDE 17.0D). Overall, 25.0% (n = 102) reported ED symptoms, with a higher prevalence in the comparison group than among athletes (37.5% vs. 17.6%, p < 0.001). Interviews were completed by 78.0% (n = 18) of athletes and 47.0% (n = 16) of comparison group participants who screened positive for ED symptoms, confirming an ED diagnosis in all but one athlete. Furthermore, 18.6% (n = 76) reported clinically relevant symptoms of depression, and 22.8% (n = 93) of exercise addiction. Associations were observed between ED symptoms and symptoms of exercise addiction, depression, and psychological inflexibility in the total sample, among athletes and in the comparison group. ED symptoms were common among athletes and the comparison group and were associated with depressive symptoms, problematic exercise behaviour, and psychological inflexibility. To safeguard athlete health and optimise performance, national sports organisations should implement systematic preventive strategies, promote early identification, establish clear referral pathways, and ensure access to coordinated multidisciplinary care.

Acidic wastewater generated during sulfuric acid leaching of reduced tionite within the EUROTITAN process was treated using three low-cost adsorbents: fly ash, bentonite, and red mud slag. Tionite is a solid residue originating from the sulfate route of TiO2 production, whereas the investigated wastewater is a secondary acidic stream produced during hydrometallurgical treatment of reduced tionite. The initial wastewater was characterized by low pH and elevated concentrations of Fe, Al, Ti, B, Cu, Mn, Pb, Cr, and Li. Batch adsorption experiments were carried out by varying contact time from 4 to 24 h and adsorbent dosage from 5 to 15 g/L. The results showed distinct selectivity depending on adsorbent type and solution chemistry. Bentonite exhibited the most stable performance, achieving nearly complete removal of Pb, Cu, B, and Li, while Fe and Al were only partially removed and Ti removal remained limited. Fly ash showed high affinity toward Pb and Cu, but its performance was strongly affected by dosage and contact time. Red mud slag demonstrated excellent Pb removal, high Cu removal, and time- and dosage-dependent Ti removal, although partial dissolution of Fe- and Al-bearing phases occurred under strongly acidic conditions. Overall, the results confirm that industrial by-products and natural clay materials can contribute to partial purification of acidic metallurgical wastewater, while additional neutralization or polishing steps are required for complete treatment.

Purpose: To review the potential relationship between vitamin B12 and colorectal cancer, with particular emphasis on its involvement in one-carbon metabolism and epigenetic regulation.Methods: This narrative review summarises current evidence on the biological mechanisms and epidemiological associations linking vitamin B12 status with colorectal cancer risk.Results: Available evidence indicates a biologically plausible but epidemiologically inconsistent relationship between vitamin B12 and colorectal cancer. Studies assessing dietary intake frequently report an inverse association, particularly for rectal cancer, whereas analyses of circulating vitamin B12 concentrations yield heterogeneous, and often conflicting findings.Conclusion: Vitamin B12 does not act as an isolated protective factor but as part of a complex metabolic and nutritional system. Although its potential protective role in colorectal carcinogenesis is biologically based, it remains insufficiently confirmed, emphasising the need for further integrated research.

Inertial motion sensing plays an important role in real-time human–machine interaction applications, including interactive systems, virtual environments, and motion-controlled interfaces, where low latency and accurate motion tracking are important. This paper presents the design and implementation of an embedded inertial sensing system that acquires, processes, and transmits motion data from consumer-grade inertial measurement units (IMUs) under real-time constraints. Rather than introducing a new sensor fusion algorithm, the contribution lies in a systems-oriented methodology comprising a predictive clock-advancement mechanism that prevents cumulative timing drift, an automated matrix-based calibration procedure for hardware-agnostic deployment, and a benchmarking framework for end-to-end real-time system evaluation. Implemented on a resource-constrained embedded platform, the framework integrates sensor acquisition, lightweight filtering, sensor fusion, and real-time orientation estimation within a single processing pipeline. Motion data are transmitted using the CemuHook UDP (User Datagram Protocol) motion protocol (DSU) to demonstrate interoperability with existing motion-control software while maintaining low end-to-end latency and stable throughput. Experimental results show stable sampling frequency, low communication latency, accurate orientation estimation, and low computational overhead. The presented system provides an embedded inertial sensing framework that can be adapted to a range of real-time motion-sensing applications beyond the communication protocol used for demonstration.

We study conditions under which stability of the origin of stochastic differential equations is robust to small perturbations. We express robustness in two ways, firstly in the sense that stochastic stability is maintained under small parametric perturbations not exceeding a state-dependent bound vanishing at the origin but positive elsewhere, and secondly via stochastic input-to-state stability (ISS) which allows non-zero perturbations everywhere. We prove the former property assuming the existence of a Lyapunov function certifying stochastic stability of the nominal system. Under the same assumption, stochastic ISS holds under a suitable state-dependent perturbation scaling. Stochastic exponential stability is maintained under proportionally bounded perturbations and implies exponential ISS even without perturbation scaling. Finally, we propose a novel approach to stochastic integrator backstepping in pure-feedback form that uses the tools from our robustness analysis.

One of the most often used welding processes for unalloyed structural steels is MAG, which is relatively simple, yet achieving high deposition rates. On the other side, there are standards describing weld quality based on weld geometry. This paper describes influence of heat input on weld geometry for MAG fillet welds of unalloyed steel with thicknesses of 8 mm, in horizontal and overhead position. Independently varied parameters were welding current and speed. Influence is described through models based on linear regression analysis. Comparison is made between models developed for different positions, as well as with those available in literature.

BACKGROUND The optimal management of isolated posterior cerebral artery occlusion (iPCAO) remains unclear. We investigated whether baseline perfusion imaging parameters are associated with clinical outcomes and whether they modify the association between endovascular therapy (EVT) and outcomes in iPCAO. METHODS This prespecified secondary analysis of the international, multicenter, observational PLATO (Posterior Cerebral Artery Occlusion) registry (35 centers, 10 countries, 2015-2025) included consecutive adults with unilateral iPCAO and baseline perfusion imaging (computed tomography or magnetic resonance imaging) with reconstructed parameters. Primary end point was an excellent 90-day outcome (modified Rankin Scale score, 0-1). Perfusion parameters included hypoperfusion volume, infarct core volume, and mismatch ratio. The primary analysis used multivariable mixed-effects regression models (center as random effect) to assess associations between perfusion parameters and outcomes, adjusting for age, sex, treatment year, prestroke modified Rankin Scale score, baseline National Institutes of Health Stroke Scale score, diabetes, stroke cause, posterior circulation Acute Stroke Prognosis Early Computed Tomography Score, occlusion site, intravenous thrombolysis, and onset-to-door time. To test whether the association between EVT and outcomes varies according to baseline perfusion parameters, we evaluated treatment-by-perfusion interactions by including interaction terms (treatment×perfusion parameter) in inverse probability of treatment weighting-adjusted models, with results expressed as ratios of odds ratios (ORs). RESULTS Of 1811 patients with iPCAO, 443 met inclusion criteria (median age, 74 years; 41.8% female). Larger hypoperfusion volume was associated with lower odds of excellent outcome (adjusted OR, 0.72 [95% CI, 0.58-0.89] per 1-unit increase in natural logarithm-transformed volume). No interaction between perfusion parameters and EVT was observed for the primary outcome. However, increasing core volume was associated with a progressively less favorable modified Rankin Scale score shift (ratio of OR, 0.66 [95% CI, 0.48-0.90]; Pinteraction=0.009) and higher mortality (ratio of OR, 1.82 [95% CI, 1.10-3.03]; Pinteraction=0.021) with EVT compared with medical management. Increasing hypoperfusion volume was associated with a higher risk of symptomatic intracranial hemorrhage with EVT (ratio of OR, 10.15 [95% CI, 1.06-96.93]; Pinteraction=0.044). CONCLUSIONS In iPCAO, perfusion imaging provides independent prognostic information but does not identify patients with potential benefit from EVT and may instead indicate those at higher procedural risk. REGISTRATION URL: https://osf.io/62mwt; Unique identifier: XXXX.

Multimodal emotion and sentiment recognition is commonly addressed by early fusion, which concatenates modalities before classification, or late fusion, which combines independently trained unimodal predictors. Early fusion can be accurate but monolithic, while late fusion is modular but may lose cross-modal interactions. This paper revisits XAI-guided adaptive fusion (\xgaf), a tree-based mixture of unimodal and cross-modal experts whose sample-level weights are derived from TreeSHAP attribution magnitudes. We focus on the effect of SHAP attribution reduction when experts have unequal feature dimensionalities. In this setting, mean-abs and median-abs reductions can suppress high-dimensional cross-modal experts, whereas sum-abs reduction preserves total attribution mass. On MELD 7-class emotion recognition, sum-abs \xgaf{} nearly matches early fusion across three face-sequence aggregators; the Transformer variant reaches 0.5983 \wf{}, compared with 0.6018 for early fusion and 0.4598 for probability-average late fusion. McNemar testing shows no significant difference between sum-abs \xgaf{} and early fusion on MELD ($p=1.000$), while \xgaf{} remains significantly better than late fusion ($p<0.0001$). On CMU-MOSEI 3-class sentiment recognition, sum-abs \xgaf{} reaches 0.6519 \wf{}, slightly exceeding early fusion (0.6485) and late fusion (0.5696). Ablation studies show that the main gain comes from adding cross-modal experts, especially the trimodal expert, rather than from complex per-sample routing. Diagnostics further show that mean-abs and median-abs weights are nearly uniform, while sum-abs weights concentrate on the trimodal expert. Thus, the main contribution is a transparent empirical analysis of how SHAP reduction, expert dimensionality, and cross-modal expert design affect modular multimodal fusion.

This thesis addresses the challenge of supporting novice programmers in the GenAI era without undermining fundamental skill acquisition. Using digital activity logs, self-reported characteristics, and GenAI usage patterns from an introductory programming course, it develops models that capture student learning behaviors. These models are then used to create personalized AI-based intervention strategies that guide students toward independent problem-solving.