Search Results (2,233)

This study examines the governance of digitalization in municipal administration, with a focus on city planning services, specifically spatial planning, building permits, and geodata management, in a large Swedish municipality. Digitalization is understood here not as the adoption of isolated technologies, but as organizational and process-oriented transformation enabled by digital systems such as GIS platforms, case management systems, and digital planning information. While national policy frameworks set ambitious digitalization goals, previous research shows that local authorities often face significant obstacles, including fragmented processes, technical limitations, and complex governance structures. These challenges create a persistent gap between strategic ambitions and daily work practices. This study employs a qualitative case study approach drawing on semi-structured interviews with employees in technical, operational, and strategic roles, as well as an analysis of policy documents and internal process descriptions. Using a socio-technical perspective, the analysis applies the Technology–Organization–Environment (TOE) framework to examine how digital systems, organizational structures, and external institutional demands interact in practice. The findings highlight substantial challenges related to system integration, data quality, uneven digital competencies, and the ongoing disconnect between strategic goals and operational realities. The study emphasizes the need for clearer governance structures, stronger cross-functional collaboration, and work practices that bridge technical and organizational dimensions. Building on the empirical analysis, the study proposes a conceptual framework that extends the TOE framework by identifying three interrelated structural mechanisms: technological lock-in, organizational inertia, and institutional uncertainty. This framework contributes theoretically by deepening the understanding of socio-technical digitalization dynamics in local government. Practically, it provides municipalities with an analytical tool to assess and reflect on their digitalization conditions. Full article

Carpal Tunnel Syndrome (CTS) is the most common upper-limb entrapment neuropathy and remains a major contributor of work-related disability. While Carpal Tunnel Release (CTR) reliably improves symptoms, functional recovery is less consistently reported. Return-to-Work (RTW) has emerged as a practical functional outcome, but definitions and reporting remain heterogeneous. We conducted a narrative review of English-language studies reporting RTW or work-absence outcomes following open, endoscopic, ultrasound-guided, ultraminimally invasive, and microinvasive CTR techniques. Due to variability in study design and RTW definitions, findings were synthesised descriptively. Across the literature, RTW durations progressively shortened as procedural invasiveness decreased. Open CTR commonly reported RTW at four to six weeks, endoscopic techniques at two to four weeks, and ultrasound-guided approaches at approximately 10–21 days. Recent ultraminimally invasive and microinvasive systems frequently reported RTW within one to two weeks when performed under local anaesthesia. These findings highlighted RTW as a meaningful functional benchmark and underscore the role of imaging-guided access minimisation in accelerating postoperative recovery. Full article

Operationally, energy transition takes place at the local level, that is, in cities and rural municipalities. Its effectiveness is, therefore, dependent on individual actions undertaken in enterprises and households. It also constitutes a particularly challenging task for industrial regions with centuries-old mining traditions. Meanwhile, the opinions of residents living in mining cities receive little attention in the literature. For these reasons, this study used survey research conducted in 19 Silesian cities with county rights and on a representative sample of 1863 residents. In this way, answers were sought to the following research questions: (1) How do urban residents in a developing economy in a post-mining region assess their knowledge regarding environmental protection and energy transition? (2) How do they evaluate local authorities’ actions concerning the replacement of non-ecological heating sources in households? The analysis of results employed descriptive statistics and non-parametric statistical tests, identifying differences in respondents’ assessments according to gender, age, education, and place of residence. The analyses conducted indicate that residents assess their environmental awareness as average. They also rate their knowledge of the energy transition below average, despite being in the midst of it. The assessments of men, older individuals, and those with vocational and secondary education are higher in both cases than the assessments of women, younger generations, and respondents with primary, post-secondary, and higher education. Respondents also rate financial and informational–educational support for heating source replacement as average. Importantly, however, these actions are noticed and appreciated. They meet the expectations of less formally educated individuals (formal education level: primary, vocational, and secondary). However, they do not generate enthusiasm among those with post-secondary and higher education, whose environmental needs and expectations may be higher. The level of financial support, and to a lesser extent informational–educational support, differs significantly among the studied cities, indicating the absence of a coherent regional policy. This may also result in deepening environmental disparities and inequalities in quality of life among the studied urban centers. The two-dimensional assessment reveals that the majority of the examined cities fall into the stagnator category, exhibiting average levels of both environmental awareness and institutional support for energy transition. The most favorable prospects for effective energy transition are observed in Gliwice and Żory, while Zabrze, Świętochłowice, and Jastrzębie-Zdrój—post-mining cities burdened by limited development potential and financial constraints—demonstrate the least promising outlook. The conclusions and recommendations derived from this article directly align with the implementation of Sustainable Development Goal 7—Affordable and Clean Energy (SDG 7)—which addresses energy transition, including the adoption of clean heat sources. They also support the development of sustainable cities, thereby contributing to the achievement of Sustainable Development Goal 11—Sustainable Cities and Communities (SDG 11). Full article

Background: This study examines the competitive dynamics of the artisanal wooden furniture industry in Misantla, Veracruz, Mexico, a predominantly informal productive system characterized by family-managed production units and strong territorial embeddedness. Methods: A mixed-methods research design was employed. Quantitative data were collected from 187 family-managed production units (86 woodworking units and 101 workshops) using a structured questionnaire based on five-level Likert scales assessing external efficiency, collective efficiency, and innovation. Statistical analyses included descriptive measures and chi-square tests to examine associations between competitiveness and collective strategies, while qualitative validation and thematic interpretation based on expert assessments were used to contextualize sectoral practices and structural constraints. Results: The findings indicate a low overall competitiveness score (1.92/5), associated with informal practices, limited technical training, and weak supply chain integration. Despite these constraints, the sector maintains a strong cultural identity and contributes to its local economy. Conclusions: Artisanal supply chains can achieve functional levels of logistics performance through internal coordination dynamics. Strengthening collaboration mechanisms is a viable strategy for improving logistics performance in artisanal manufacturing systems in emerging economies. These findings provide empirical evidence to support the design of collaborative strategies that integrate traditional craftsmanship with modern supply chain practices in artisanal micro-industries. Full article

The genus Xylaria comprises numerous species, particularly prevalent in tropical ecosystems such as those of Ecuador. Despite its ecological importance, the taxonomy of the genus remains challenging, and much of its diversity in the Neotropics remains under-documented. This study provides a preliminary characterization of the Xylaria diversity at the Estación Científica San Francisco, an Andean biodiversity hotspot in Southern Ecuador. Through an integrated approach including detailed macro- and micro-morphological descriptions and nuclear ribosomal DNA (nrDNA ITS and LSU) phylogenetic analyses, 20 Xylaria specimens were examined. As a result, ten species were recognized: Xylaria adscendens, X. cf. anisopleura, X. apiculata, X. curta, X. enterogena, X. fissilis, X. globosa, X. aff. telfairii, X. tuberoides, and X. aenea, the latter representing a new record for Ecuador. The phylogenetic analysis presented here serves as a preliminary systematic positioning of these specimens within the genus rather than a comprehensive global reconstruction. While these ribosomal markers provided preliminary insights into species relationships, partial incongruence with morphospecies highlights the evolutionary complexity of certain lineages and underscores the need for future multilocus studies. Furthermore, four additional phylotypes found in their anamorphic state are documented, suggesting that local diversity exceeds current records. By providing detailed morphological documentation supported by preliminary barcode data from a poorly sampled region, this study contributes vital information to the global understanding of Xylaria and underscores the importance of Southern Ecuador as a reservoir of fungal diversity. Full article

A comprehensive characterization of the wave climate on the coast at Manzanillo, Colima, Mexico, based on an 11-year hindcast (2008–2018), was performed using a hybrid approach that integrates hydrodynamic numerical models with machine learning techniques. Wave conditions were analyzed at 23 nearshore sites, including headlands, outer beaches, and sheltered beaches. The effects of the complex coastal morphology on wave propagation were evident, especially regarding storm waves. Two distinct wave climates were seen: a low-energy regime in the dry season (November–April) and a more energetic regime in the rainy season (May–October). Spatial variability was greatly modulated by headlands, bays, and port infrastructure, leading to sharp local contrasts in wave height, slope, and wave power. For instance, mean wave power ranged from 9.34 kW/m at exposed sites such as El Faro de Campos to only 0.36 kW/m near sheltered areas, such as San Pedrito beach. From these findings, it is clear that a regional scale description of the wave climate is insufficient when assessing coastal vulnerability in this morphologically complex area. The new dataset is a valuable baseline for use in coastal management, port planning, and risk assessments for Manzanillo, which is one of Mexico’s most important ports. Full article

Population aging and climate change are two long-term processes that increasingly intersect, yet their interrelationship remains insufficiently explored in Southeast Europe. This article examines how adults aged 50+ in Serbia and Bulgaria understand, perceive, and respond to climate risks, with the aim of identifying age-specific vulnerabilities as well as opportunities for climate action. We administered the ClimateMind50+ questionnaire to purposive national samples comprising 309 respondents in Serbia (CAPI, 82 municipalities) and 155 respondents in Bulgaria (CAWI, 74 municipalities). Socio-demographic differences were analyzed using descriptive statistics and χ² tests. The findings indicate moderate levels of self-assessed climate literacy, strong concern about the impacts of climate change on future generations, and heightened anxiety regarding extreme heat and prolonged dry periods. During climate-related emergencies, respondents rely predominantly on family networks rather than local institutions, and overall preparedness for extreme events remains limited. Adaptive and pro-environmental behaviors are modest and vary by gender, education level, and type of settlement. Population aging interacts with socio-economic vulnerability, energy poverty, regional decline, and governance constraints, shaping both exposure to climate risks and the capacity for behavioral adaptation. Climate strategies in both countries should therefore become more age-inclusive and socially responsive, recognizing older adults not only as a vulnerable group but also as active contributors to resilience. Full article

Access to quality seed is a critical driver of smallholder productivity and household food security in South Africa, yet rural communities in the Eastern Cape continue to rely heavily on informal seed systems. Limited seed literacy among farmers and vendors is widely recognized as a constraint to the effective selection and use of high-quality seed. The purpose of this study is to assess seed literacy levels among smallholder farmers in KwaMkhiva village and evaluate how knowledge gaps shape farmers’ seed sourcing patterns and access to quality seed. The study hypothesizes that low seed literacy significantly increases reliance on informal seed systems and reduces adoption of certified or improved varieties. A quantitative, cross-sectional survey design was used to collect data from 50 smallholder farmers and 12 informal seedling vendors, complemented by semi-structured interviews with three extension officers. Descriptive statistics, chi-square tests, correlation analysis, and a composite Seed Literacy Index (SLI) were employed to assess literacy dimensions and their association with seed choices. Findings show that 49% of farmers rely on local markets and 40% use farm-saved seed, with 75% assessing quality visually rather than through germination or varietal indicators. Only 10% had received any seed-related training, and awareness of seed adaptability and crop rotation was below 20%. Higher SLI scores were positively associated with adoption of certified seed (r = 0.42, p < 0.01) and crop diversification. The study concludes that seed literacy is a critical yet underserved capability that shapes smallholder seed access within dual seed economies. Strengthening farmer-centred seed literacy programmes, revitalising extension services, and supporting community seed banks could enhance access to quality seed and improve smallholder resilience. Full article

Understanding wave-packet deformation and spreading is central to the description of transport and localization phenomena in both classical and quantum systems. In this work, we introduce information-theoretic and complexity-based indicators. We analyze the evolution of the probability distribution using Shannon and linear entropies, together with the inverse participation ratio, to quantify localization–delocalization processes and their associated fluctuations. These measures naturally motivate the use of statistical complexity definitions, including the López–Mancini–Calbet ($C_{LMC}$) and Shiner–Davison–Landsberg ($C_{SDL}$) complexities. In addition, we compute the probability current for both single-particle and two-particle configurations, providing a dynamical description of transport in terms of particle motion. The influence of an external field on entropy production, complexity, and probability currents is also examined, highlighting the interplay between information spreading, localization, and transport in lattice systems. Full article

Laser Powder Bed Fusion (LPBF)-processed AlSi10Mg produces highly heterogeneous microstructures, where fine α-Al cells, Si-rich networks, and melt-pool boundaries govern local mechanical behavior. Nanoindentation has emerged as a key tool for probing these variations, yet systematic understanding of the links between processing parameters, microstructure, and nano-mechanical response remains limited. This critical review examines how laser processing parameters influence local mechanical response through their impact on microstructural features. Key challenges in interpreting nanoindentation are highlighted, alongside inconsistencies in experimental protocols and reporting practices that hinder cross-study comparisons. Beyond summarizing existing findings, underexplored aspects of nanoindentation in LPBF AlSi10Mg are identified, including spatially correlated microstructure-mechanical mapping, depth-resolved measurements, and integration with advanced characterization and data-driven approaches. By synthesizing current knowledge and clarifying methodological constraints, this review positions nanoindentation not merely as a descriptive tool, but as a mechanistically informed approach for linking processing conditions, microstructural heterogeneity, and local mechanical response. These insights aim to support more rigorous interpretation of small-scale mechanical data and to guide future studies toward predictive understanding and rational process optimization in additively manufactured aluminum alloys. Full article

Low-cost air quality sensors, such as PurpleAir monitors, have rapidly expanded fine particulate matter (PM2.5) monitoring across the United States, providing dense, hyper-local measurements. While prior research has focused largely on sensor accuracy and calibration, less is known about where these sensors are deployed and whether they persist long enough to support multi-year analyses relevant to exposure assessment and policy. Using publicly available PurpleAir data, we characterized the geographic distribution, deployment longevity, and persistence of outdoor sensors across the United States from 2016 to 2025. We quantified deployment duration as the time between first and last publicly available observations and summarized patterns nationally, by U.S. Census region, and by state. Most publicly shared sensors remained deployed for more than three years, indicating substantial potential for multi-year applications, particularly in the western United States, where sensor density and longevity were highest. As an illustrative component, we present descriptive summaries of PM2.5 concentrations in four high-coverage states (California, Minnesota, Pennsylvania, and Texas) by deployment duration and urban–rural classification to demonstrate the types of analyses enabled by these networks. These results establish a national baseline of sensor availability and temporal continuity. By focusing on deployment patterns, this study provides foundational context for future exposure modeling, epidemiologic studies, and targeted expansion of community air quality monitoring networks. Full article

Background/Objectives: Root canal procedures on multi-rooted teeth, including first molars, depend on experience, tactile perception, and anatomical knowledge to avoid perforation in the furcation region. Studies using various methodologies and populations have reported discrepant findings on pulpal floor thickness. No study using micro-computed tomography (Micro-CT), the gold standard, has been conducted on a Black South African sample to evaluate pulpal floor thickness. Methods: In this cross-sectional, descriptive, quantitative study, Micro-CT scans of 91 maxillary and 77 mandibular first molars were reconstructed in 3D and oriented according to a reference plane along the cemento-enamel junction using Avizo software. Measurements were taken from the midpoint of the pulpal chamber floor to the perpendicular point on the furcation. In maxillary molars, an additional measurement between the mesiobuccal and distobuccal roots was taken. The effects of arch, side, age, and sex were assessed. Results: Neither sex, arch, nor side had a significant influence on the pulpal floor thickness. The central mandibular and maxillary pulpal floor thicknesses increased significantly with aging, while the effect on the buccal maxillary pulpal floor thickness was not significant. The mean central mandibular and maxillary pulpal floor thicknesses were 2.66 and 2.83 mm, respectively, while the buccal maxillary pulpal floor thickness was significantly smaller at 2.37 mm. Conclusions: More accurate and repeatable findings compared to the literature could be attributed to the use of Micro-CT, which provides higher resolution images, and to Avizo, which enables precise localization of 3D points. Variations from the literature might also be explained by differences in the age and geographical origin of the samples. Full article

As remarked by Boltzmann, the Second Law of Thermodynamics is notable for the fact that it is readily proved using elementary statistical arguments, but becomes harder and harder to verify the more precise the microscopic description of a system. In this article, we investigate one particular realization of the 2nd Law, namely Joule heating in a wire under electrical bias. We analyze the production of entropy in an exactly solvable model of a quantum wire wherein the conserved flow of entropy under unitary quantum evolution is taken into account using an exact formula for the entropy current of a system of independent quantum particles. In this exact microscopic description of the quantum dynamics, the entropy production due to Joule heating does not arise automatically. Instead, we show that the expected entropy production is realized in the limit of a large number of local measurements by a series of floating thermoelectric probes along the length of the wire, which inject entropy into the system as a result of the information obtained via their continuous measurements of the system. The decoherence resulting from inelastic processes introduced by the local measurements is essential to the phenomenon of entropy production due to Joule heating, and would be expected to arise due to inelastic scattering in real systems of interacting particles. Full article

Retaining the green workforce, employees driving sustainability and environmental innovation, is essential for organizational resilience and long-term environmental goals. While prior Green HRM research has primarily relied on survey-based methodologies and theoretical frameworks to examine retention factors, these approaches lack predictive capability and fail to provide actionable, employee-specific insights. This study advances beyond descriptive and correlational analyses by employing explainable artificial intelligence (XAI) to develop a transparent, data-driven framework for identifying attrition drivers and quantitatively evaluating retention strategies. Unlike existing studies that rely on self-reported perceptions, our approach leverages objective HR data and machine learning to predict individual-level attrition risk with calibrated probabilities. Leveraging the IBM HR Analytics dataset as a proxy for sustainability-focused roles, we construct an interpretable logistic regression model with strong predictive performance and isotonic regression calibration. Global and local interpretability techniques, including SHAP, LIME, and permutation importance, show that non-monetary factors, such as excessive overtime, frequent business travel, and limited promotion opportunities, have a greater impact on turnover risk than salary levels. These findings align with Green Human Management (Green HRM) principles, which emphasize work–life balance and employee well-being. Crucially, our policy simulation framework, absent from prior Green HRM studies, demonstrates that eliminating overtime could reduce predicted attrition probability by 17.35% for affected employees, potentially retaining 31 staff members, substantially outperforming modest salary adjustments. This work expands the value of predictive AI into HR analytics by consolidating HR analytics with Green HRM through a novel methodology that bridges the gap between prediction and actionable intervention. It represents the first systematic integration of XAI-based predictive modeling with counterfactual policy simulation in environmentally conscious sustainable organizations. Full article

Textual and visual representations of data play a key role in data science and artificial intelligence by supporting effective and user-friendly communication. Among existing approaches, automatic data-to-text generation aims to produce natural language descriptions from structured data sources. This paper presents an interpretable fuzzy framework for generating data to text based on linguistic contexts and computational perception networks evaluated through formal concept analysis. The proposed framework is organized into four main stages: (i) transforming numerical data sets into linguistic contexts, (ii) generating computational perceptions from linguistic contexts, (iii) building computational perceptions networks to automatically generate natural language summaries, and (iv) validating the generated texts through comparison with summaries obtained using formal concept analysis–based baselines. To the best of our knowledge, this is the first work to address the generation of linguistic summaries through an interpretable process that transforms data into linguistic contexts and subsequently into computational perceptions. Another key difference from previous work lies in the verification of the linguistic summaries generated through these computational perceptions by using a formal method. A software prototype was implemented and evaluated using real photovoltaic station data provided by a local energy operator in Puerto Real (Cádiz, Spain). Experimental results show that the proposed fuzzy framework improves the interpretability and consistency of the generated summaries when compared with others approaches, demonstrating its potential for explainable and user-centered data-to-text generation. Full article