The increasing demand for lithium-ion batteries (LIBs) and their limited lifespan emphasize the urgent need for sustainable recycling strategies. This study investigates the application of tetrabutylphosphonium-based ionic liquids (ILs) as alternative leaching agents for recovering critical metals, Li(I), Co(II), Ni(II), and Mn(II), from spent NMC cathode materials. Initial screening experiments evaluated the leaching efficiencies of nine tetrabutylphosphonium-based ILs for Co(II), Ni(II), Mn(II), and Li(I), revealing distinct metal dissolution behaviors. Three ILs containing HSO4−, EDTA2−, and DTPA3− anions exhibited the highest leaching performance and were selected for further optimization. Key leaching parameters, including IL and acid concentrations, temperature, time, and solid-to-liquid ratio, were systematically adjusted, achieving leaching efficiencies exceeding 90%. Among the tested systems, [TBP][HSO4] enabled near-complete metal dissolution (~100%) even at room temperature. Furthermore, an aqueous biphasic system (ABS) was investigated utilizing [TBP][HSO4] in combination with ammonium sulfate, enabling the complete extraction of all metals into the salt-rich phase while leaving the IL phase metal-free and potentially suitable for reuse, indicating the feasibility of integrating leaching and extraction into a continuous, interconnected process. This approach represents a promising step forward in LIB recycling, highlighting the potential for sustainable and efficient integration of leaching and extraction within established hydrometallurgical frameworks.

We consider the problem of exact maximum likelihood estimation of potentially high‐order ( p>50 ) autoregressive models. We propose an extremely fast coordinate‐wise algorithm for fitting autoregressive models. This fast algorithm exploits several properties of the negative log‐likelihood when parameterised in terms of partial autocorrelations. We consider extensions to learning a single autoregressive model from multiple time series and to the more general case of regressions with autoregressive residuals. An implementation of the coordinate‐wise descent algorithm is shown to be the orders of magnitude faster than competing algorithms and appears to be the fastest known algorithm for maximum likelihood estimation of autoregressive models.

BACKGROUND Few questionnaires with established measurement properties can globally measure sleep in preschoolers and sleep-related family practices. OBJECTIVE To examine (1) concurrent validity of the SUNRISE parent questionnaire against an accelerometer for measuring sleep in preschoolers and (2) test-retest reliability of the questionnaire for sleep and related family practices. METHODS Sleep was measured using the questionnaire and Actigraph GTX3+ accelerometer using a decision-tree algorithm and the Sadeh algorithm in 1737 preschoolers (4.4±0.6years) from 30 countries. Concurrent validity was examined using correlation analysis (duration, timing, and quality), paired t test or the Wilcoxon signed-rank test, Bland-Altman plot (duration, timing), and analysis of sensitivity, specificity, and accuracy (variability). Test-retest variability was examined for sleep and family practice variables in a subsample of 163 participants (4.3±0.6years) from eight countries. RESULTS Questionnaire measures of sleep timing and duration were correlated with the accelerometer measures (r=0.43-0.75; p<.001). Although statistically significant mean differences were observed between questionnaire and accelerometer measures of sleep timing and duration variables, the difference in nighttime sleep duration had a small effect size (-14 min/d; Cohen's d=-0.2). The questionnaire was less able to provide adequate measurement for sleep quality and variability. High levels of reliability were observed for sleep (ICC=0.63-0.83; Kappa=0.53-0.62) and family practice (ICC=0.81-0.94; Kappa=0.73-0.86) variables. CONCLUSION The SUNRISE questionnaire appears reliable in assessing preschooler sleep characteristics and related family practices, particularly in disadvantaged settings. It could be used in global surveillance of nighttime sleep duration and in studies examining associations of sleep timing and duration with health indicators in preschoolers.

Background Non-ST-elevation myocardial infarction (NSTEMI) represents a prevalent form of acute coronary syndrome associated with substantial early risk of adverse outcomes. Inflammatory and metabolic disturbances are increasingly recognized as key contributors to the disease. Hematologic indices such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), and pan-immune-inflammation value (PIV), along with the triglyceride-glucose index adjusted for BMI (TyG-BMI), have emerged as promising prognostic markers. However, their dynamic behavior in early NSTEMI remains insufficiently explored. Materials and methods This prospective study included 170 patients hospitalized for NSTEMI at the University Clinical Centre Tuzla between February 2022 and January 2023. Hematologic and metabolic indices were calculated at admission and repeated 24 hours later. Patients were followed for three months to document major adverse cardiovascular events (MACE), including cardiovascular death, reinfarction, and urgent revascularization. The median age was 67 years, and 60.6% of patients were male. Hypertension, hyperlipidemia, and diabetes mellitus were the most common comorbidities. Results Significant 24-hour reductions were observed in NLR, PLR, SII, SIRI, and PIV (all p < 0.01), while C-reactive protein (CRP) levels more than doubled (p < 0.001). Patients who developed MACE showed persistently elevated inflammatory indices and smaller declines in PIV and SIRI. Change in SIRI (ΔSIRI) demonstrated the strongest predictive value (AUC = 0.63), followed by SII and TyG-BMI. Notably, reduced resolution of PIV and persistently elevated TyG-BMI were significantly associated with adverse outcomes. Overall, MACE occurred in 51.2% of patients, including a 14.7% mortality rate. Conclusion Early changes in systemic inflammation and metabolic stress, particularly SIRI and TyG-BMI dynamics, offer valuable prognostic insight and may enhance early risk stratification in NSTEMI patients.

Background/Aim: Rheumatoid arthritis (RA) is an autoimmune inflammatory disease, characterized by the production of numerous pro-inflammatory cytokines, such as tumor necrosis factor α (TNF-α), interleukin-6 (IL-6), and interleukin-1β (IL-1β), which lead to pathophysiological changes in innate and acquired immunity. The existing evidence shows that pro-inflammatory cytokines in rheumatoid arthritis impact monoaminergic neurotransmission, neurotropic factors, and synaptic activity, which may lead to the development of depression. Materials and Methods: In our study, we explored the association between TNF-α and IL-6, disease activity, and the degree of depression in patients with RA. The association between TNF-α and IL-6 and the Beck and Hamilton depression scales was analyzed in a group of 116 RA patients with depression. We investigated the same correlation in 45 patients with primary depression who represented the control group. Results: A Spearman test showed that IL-6 levels had a positive association with the Beck and Hamilton scales (p < 0.05) and that TNF-α had a positive association with the Hamilton scale (p < 0.05). Also, the Hamilton depression scale was the more sensitive scale in the detection of depressive symptoms. Conclusions: Our study indicates that elevated values of pro-inflammatory cytokines are associated with the degree of depression in patients with RA. Future preclinical and clinical studies will contribute to a better understanding of the pathophysiological mechanism of depression in patients with RA and may serve as the basis for new treatment modalities. By detecting depression promptly, with the help of the HAM-D as the more sensitive scale, we could influence the future modality of treatment, and with a multidisciplinary approach, we could ensure an improvement in the quality of life of patients with RA.

Faecal incontinence is a debilitating anorectal disorder that can severely affect a person's quality of life. The variability in reported outcomes in studies on treatments for faecal incontinence complicates the synthesis of evidence, thereby weakening treatment recommendations. Furthermore, the emphasis on clinical outcomes often neglects outcomes that are crucial to patients' daily lives. Incorporating diverse stakeholder perspectives, we aimed to develop a core outcome set (COS)-a minimum set of outcomes that should be measured in future studies evaluating the efficacy of a treatment in adults with faecal incontinence. Following guidelines from the COMET initiative, this study proceeded through three steps: identifying outcomes via patient interviews and a systematic literature review; ranking and refining outcomes through two rounds of Delphi surveys involving patients, health-care professionals, and researchers; and finalising the COS through a consensus meeting with relevant stakeholders. Round 1 of the Delphi survey included 109 participants (73 health-care professionals and researchers and 36 patients) and round 2 involved 74 participants (54 and 20, respectively). In both rounds, participants ranked the importance of potential outcomes on a 9-point Likert scale. Of the 58 outcomes that entered round 1 and the three that were later added, 27 outcomes were voted out and the remaining 34 were discussed during a consensus meeting to finalise the COS. The final COS encompasses 13 outcomes: seven quality of life-related outcomes (quality of life, influence on daily activities, social functioning, treatment satisfaction, enjoyment in life, embarrassment, and peace of mind) and six clinical outcomes (severity of faecal incontinence, number of faecal incontinence episodes, urgency, stool consistency, adverse events, and adherence to therapy). This study establishes what outcomes should be included in a COS for use in faecal incontinence research, but future research is needed to identify the appropriate measurement instruments for each outcome and to establish appropriate timing for their assessment, which will further refine outcome definitions before this COS can be implemented. Once these aspects are clarified, the COS can be adopted into faecal incontinence research, which we hope will ultimately improve clinical care.

Maars are volcanoes with a central crater surrounded by an ejecta ring formed through surface explosive processes from underlying magma interacting with fluids. The study of terrestrial maar volcanoes, as analogs to explosive volcanic vents on the Moon and other planets, can improve our understanding of planetary volcanism and evolution. In this study, we conducted a series of geophysical experiments at Kilbourne Hole Maar, New Mexico, a well‐preserved crater used for both science and crewed exploration lunar analog studies. The surveys included multiple active source seismic lines that sampled the geological units of both the crater rim and floor. We demonstrate the effectiveness of shallow seismic reflection methods integrated with P wave refraction and surface wave analysis to determine the elastic properties and create detailed near‐surface structural models in a terrestrial volcanic setting. The reflection profiles capture the top‐down strata of the crater rim. The velocity changes derived from independent inversions of refraction travel times and surface wave dispersions indicate varying (6–15 m) ash thickness around the rim and reveal the presence of high‐velocity anomalies in possible connection with crater collapse beneath the crater floor. Additionally, we estimate a base surge volume of approximately 6.4×106 $6.4\times {10}^{6}$ m3 ${\mathrm{m}}^{3}$ present on the rim. The integrated results highlight the potential for characterizing the subsurface of planetary bodies in greater detail and provide high‐fidelity data simulations for astronaut training. The operational insights serve as a valuable guideline for future crewed lunar missions and contribute to the development of strategies for optimizing planetary exploration.

Abstract This paper examines the key aspects of corporate governance of state-owned enterprises (SOEs) through a comparative survey conducted in Bosnia and Herzegovina, Croatia, and Serbia. The research explores two distinct perspectives: the state’s view on the necessity and governance of SOEs, and the perspective of SOE boards on operational and strategic challenges. From the state’s perspective, the survey addresses issues such as the protection of national economic interests, state ownership in key industries, equitable service provision, and the reinvestment of SOE profits into public projects. Findings suggest a strong alignment among respondents across all three countries, supporting the idea that state ownership ensures economic sovereignty and guarantees fair access to essential services. On the other hand, the board perspective highlights concern about the bureaucratic barriers faced by SOEs, the influence of political interference on financial performance, and the limitations of public ownership in enhancing global competitiveness. Board respondents expressed the need for greater autonomy in decision-making and stressed the importance of partnerships with the private sector to optimise SOE efficiency and market position. The article synthesises these findings to address the broader question: Are SOEs essential in modern economies, or do they require reform to meet contemporary challenges? The results indicate that while SOEs hold strategic importance, reforms focused on reducing bureaucracy, enhancing governance, and promoting public-private partnerships are crucial for their future viability.

Extreme weather events, which are becoming more frequent due to climate change, result in intensified nutrient losses and may override effects of agricultural mitigation measures. Using a landscape connectivity approach, we study the potential of water flow attenuation in upstream forest areas to prevent or mitigate waterlogging and flooding of downstream arable land, thereby contributing to reduced phosphorus (P) losses. We use soil distribution maps, high-resolution elevation data, land use maps and distributed modelling to quantify water storage potential and possible P reductions. In three out of four study catchments (119-915 km2), calculated storage potential of detention basins located in upstream wetland and forest areas was sufficient to retain water volumes (0.7-3.6 million m3) corresponding to discharge volumes produced during an episode with a 50 -year return period. Furthermore, it was estimated that 9-57 % of targeted annual P load reductions from arable land could be reached if stored water volumes bypass arable land without causing waterlogging/flooding leading to P mobilization and transport. As water storage potential is site-specific, prioritization and selection criteria need to be developed in collaboration with relevant stakeholders to achieve cost-efficient implementation of these measures. The methodology and results of this study have significant potential for application in landscapes with a mixture of forests and arable agriculture to aid land owners and managers to secure food production and improve water quality.

Abstract In the modern business environment, big data analytics and data mining techniques are increasingly recognized as tools for improving fiscal discipline and more efficient management of public revenues. This paper explores the possibility of applying the knowledge discovery process from databases to detect patterns of financial behavior that may indicate tax non-compliance. A quantitative approach based on the analysis of secondary data from ten joint-stock companies from the Federation of Bosnia and Herzegovina, for which financial statements and tax debt data are available, was used. The relationship between key financial indicators (EPS, financial stability ratio, total asset turnover ratio and debt ratio) and the amount of tax debt was examined using descriptive statistics and regression analysis. The results show that lower profitability and poorer financial stability significantly correlate with higher tax debt, while high operational efficiency and debt have a more complex and statistically marginal impact. The findings confirm the possibility of using publicly available financial data for early identification of risky taxpayers, which opens up space for further development of predictive models in the domain of tax analytics.

The severity and frequency of short-term but highly damaging urban floods have increased in recent years worldwide and have been caused by climate change. The casualties of urban floods are usually not high, but the material damage and economic losses can be quite significant due to the population density of these areas and the various economic activities concentrated in urban regions. For this reason, this type of flooding is always catastrophic. This paper explores the impact of urban flooding on the tourism infrastructure in Bihać using the multi-criteria ArcGIS analysis. The results show that 55.8% of the studied area is at a low elevation and has gentle slopes, making it particularly susceptible to flooding. Annual precipitation reaches up to 1,305 mm, with 35–38% of the total rainfall recorded in the urban centre of Bihać, where the key tourism infrastructure is located. The buffer zone analysis revealed that most hospitality and accommodation facilities are situated within 20 to 100 meters of the Una River’s shoreline, making them directly vulnerable during seasonal floods. Despite this, the number of tourist arrivals has been steadily increasing – from 33,433 arrivals in 2021 to 48,330 in 2023, with foreign tourists accounting for 60% of all visitors. The research findings highlight the need for the implementation of precise spatial plans and protective measures to reduce the negative impact of floods on tourism trends in this city.

Abstract Background Rapid changes and dynamic markets significantly impact the way businesses operate. Many companies fail to adapt and innovate their business models, which jeopardises their sustainability. Managers, as key decision-makers, play a pivotal role in the innovation process, whereby their entrepreneurial competencies directly influence various dimensions of business model innovation. Objectives The main aim of this study is to examine the impact of entrepreneurial competencies on the new value proposition dimension of business model innovation (BMI), exploring competencies such as opportunity recognition, analytical thinking, innovativeness, tenacity, and passion for work. It investigates how these competencies contribute to developing new offerings and new channels, attracting new customers and markets, and building new customer relations. Methods/Approach The study is conducted on a sample of 267 managers of medium and large companies across various industries in Bosnia and Herzegovina. The data were analysed using Structural Equation Modelling (SEM). Results The results show that different entrepreneurial competencies have a significant impact on various aspects of a new value proposition. Conclusions The study contributes to a deeper understanding of the influence of different entrepreneurial competencies on new value proposition dimensions within BMI. Managers who effectively utilise these competencies can enhance their companies’ value propositions, thereby increasing competitiveness and business success.