Search Results (9,522)

This paper examines how colonial and neoliberal logics have influenced the ideas of self-management, democracy, and participation and how a decolonial perspective might reinterpret them. Although democracy and participation are celebrated in mainstream development discourse, they frequently serve as technologies of control that uphold market rationalities and dependency. The paper presents a conceptual model for comprehending how political and organisational practices in the Global South are both resisted by and limited by these dynamics, drawing on the framework of the colonial matrix of power. With reference to grassroots movements like Abahlali base Mjondolo, which represent alternative democratic logics based on collective self-management and epistemic justice, South Africa is used as a focal case. How gaps in the global architecture of dominance create opportunities for pluriversal futures is further demonstrated by comparative observations from Latin America and other Global South contexts. By (i) exposing the limitations of institutionalised participatory frameworks, (ii) highlighting radical democracy at the grassroots level, and (iii) describing the structural and epistemic prerequisites for significant change, the paper adds to discussions on decolonial political economy. By doing this, it reinterprets participation as a fight for liberating alternatives outside of colonial modernity rather than as inclusion within the status quo. Full article

Background and Objectives: Hand joint deformity remains a main cause impairing quality of life in rheumatoid arthritis (RA). This study aimed to investigate the association between biologic and targeted-synthetic disease-modifying antirheumatic drugs (b/tsDMARDs) treatment and the prevalence of hand joint deformity in RA patients. Materials and Methods: This cross-sectional analysis included RA patients recruited between 2019 and 2024. Hand joint deformity was defined as the presence of specific deformity in any of 28 hand joints, including the metacarpophalangeal (MCP) joints I-V, proximal interphalangeal (PIP) joints I-V, and distal interphalangeal (DIP) joints II-V. The key exposure was the use of b/tsDMARDs. Multivariable logistic regression was used to assess the association between b/tsDMARDs treatment and hand joint deformity. Results: A total of 1083 RA patients with a mean age of 52.6 ± 12.4 years and a median disease duration of 5 (2,11) years were included. Hand joint deformity was present in 25.4% (275/1083) of patients. The top three deformed joint locations were PIP V (12.9%, 140/1083), PIP III (11.6%, 126/1083), and PIP IV (10.9%, 118/1083). The top three deformity types were ulnar deviation of MCP II-V (8.0%, 87/1083), boutonniere deformity of II-V fingers (6.8%, 74/1083), and swan neck deformity of II-V fingers (6.7%, 73/1083). In total, 17.4% (188/1083) of patients had received b/tsDMARDs. After 1:1 propensity score matching for age, sex, and disease duration, the prevalence of deformity was significantly lower in patients treated with conventional medicine (csDMARDs and/or GCs) add-on b/tsDMARDs compared to those treated with conventional medicine (27.1% vs. 61.7%, p < 0.001). Multivariable logistic regression analysis showed that b/tsDMARDs use was independently associated with a lower prevalence of hand joint deformity after adjusting for confounding factors (OR = 0.211, 95%CI: 0.129–0.345, p < 0.001). Conclusions: The use of b/tsDMARDs was independently associated with a lower prevalence of hand joint deformity in RA. Full article

Background/Objectives: Perineoplasty can be performed as an adjunct to native tissue pelvic organ prolapse (POP) surgery; the optimal indication for perineoplasty is unknown due to limited evidence regarding its benefits and the absence of clear clinical guidelines. This study aims to describe patient-related factors associated with surgeons’ decisions to add perineoplasty to POP surgery and to quantify the frequency of intraoperative changes from preoperative surgical plans. Methods: In this multicenter observational cohort study, women ≥ 18 years scheduled for primary native tissue POP surgery between April 2023 and November 2024 were included. Baseline characteristics, pelvic floor anatomy (POP-Q), genital hiatus (GH), perineal body (PB) measurements, and surgeon-reported considerations regarding perineoplasty were collected. Surgical plans (“with”, “without”, or “undecided”) were documented and compared with the actual performed procedure. Logistic and linear regression analyses were used to identify factors associated with perineoplasty. Results: Among the 305 enrolled women, 285 underwent surgery, of whom 135 (47%) received perineoplasty. Patients who underwent perineoplasty had a larger GH size (5.2 cm) compared to patients without perineoplasty (4.5 cm). Obesity was associated with an increased rate of perineoplasty compared to normal weight (OR 2.3 95%CI 1.2–4.6). There was a strong exponential association between childbirth and perineoplasty, with a fivefold increase for two children (95%CI 1.3–17.1) and thirtyfold increase for four or more children (95%CI 6.3–142) compared to one child. Nearly all procedures (92%) followed the preoperative plan; surgeons were more likely to omit than add perineoplasty intraoperatively. Surgeons frequently reported GH/PB size and age as key considerations to perform perineoplasty and lack of evidence and fear of dyspareunia as reasons to not perform perineoplasty. Conclusions: Surgeons more often perform perineoplasty in patients with factors that have been associated with a higher risk of recurrent prolapse. Prospective comparative studies are required to determine whether perineoplasty reduces recurrent POP after primary surgical repair. Full article

Background: Port digital transition is central to competitiveness and sustainability, yet existing frameworks devoted to such transition toward smart port are descriptive, technology-centered, or weak on data governance. This study designs and empirically refines a comprehensive and novel ten-step roadmap relative to existing Port/Industry 4.0 models, synthesized from 14 partial frameworks that each cover only subsets of the transition, by considering data governance and consolidating cost, time, and impact in the selection step. Methods: We synthesized recent Industry 4.0 and smart port-related frameworks into a normalized sequence of steps embedded in the so-called roadmap, then examined it in an exploratory case of a technology deployment project in a Canadian port using stakeholder interviews and project documents. Evidence was coded with a step-aligned scheme, and stakeholder feedback and implementation observations assessed whether each step’s outcomes were met. Results: The sequence proved useful yet revealed four recurrent hurdles: limited maturity assessment, uneven stakeholder engagement, ad hoc technology selection and integration, and under-specified data governance. The refined roadmap adds a diagnostic maturity step with target-state setting and gap analysis, a criteria-based selection worksheet, staged deployment with checkpoints, and compact indicators of transformation performance, such as reduced logistics delays, improved energy efficiency, and technology adoption. Conclusions: The work couples theory-grounded synthesis with empirical validation and provides decision support to both ports and public authorities to prioritize investments, align stakeholders, propose successful policies and digitalization supporting programs, and monitor outcomes, while specifying reusable steps and indicators for multi-port testing and standardized metrics. Full article

This study proposes a human-in-the-loop dynamic graph-based planning framework designed to elevate LLM-based Embodied Agents from simple tools to trustworthy collaborative partners. To achieve this, we address the trade-off between the structural rigidity of plan-centric approaches and the instability of reactive methods. The framework utilizes a Directed Acyclic Graph (DAG) with AND/OR nodes to ensure robustness while maintaining flexibility. Critically, the agent features an Automated Recovery Mechanism for self-correction and a Dynamic Modification Mechanism that employs Relevance Analysis to effectively translate human interventions (Switch, Add, Delete) into graph updates. Comparative experiments in Minecraft with 30 participants validated the method’s effectiveness. The proposed agent (Agent B) outperformed the reactive baseline (Agent A), reducing mission completion time by 9.3%. Notably, the agent demonstrated high instruction compliance and reduced user frustration by approximately 20%, leading to statistically higher satisfaction scores (PSSUQ). These results confirm that by ensuring planning robustness and responsiveness, the proposed framework successfully enables agents to function as trustworthy partners in complex environments. Full article

Background and Objectives: Dermatology relies on a complex terminology encompassing lesion types, distribution patterns, colors, and specialized sites such as hair and nails, while dermoscopy adds an additional descriptive framework, making interpretation subjective and challenging. Our study aims to evaluate the ability of a chatbot (Gemini 2) to generate dermatology descriptions across multiple languages and image types, and to assess the influence of prompt language on readability, completeness, and terminology consistency. Our research is based on the concept that non-English prompts are not mere translations of the English prompts but are independently generated texts that reflect medical and dermatological knowledge learned from non-English material used in the chatbot’s training. Materials and Methods: Five macroscopic and five dermoscopic images of common skin lesions were used. Images were uploaded to Gemini 2 with language-specific prompts requesting short paragraphs describing visible features and possible diagnoses. A total of 2400 outputs were analyzed for readability using LIX score and CLEAR (comprehensiveness, accuracy, evidence-based content, appropriateness, and relevance) assessment, while terminology consistency was evaluated via SNOMED CT mapping across English, French, German, and Greek outputs. Results: English and French descriptions were found to be harder to read and more sophisticated, while SNOMED CT mapping revealed the largest terminology mismatch in German and the smallest in French. English texts and macroscopic images achieved the highest accuracy, completeness, and readability based on CLEAR assessment, whereas dermoscopic images and non-English texts presented greater challenges. Conclusions: Overall, partial terminology inconsistencies and cross-lingual variations highlighted that the language of the prompt plays a critical role in shaping AI-generated dermatology descriptions. Full article

The removal of protein-bound uremic toxins (PBUTs) from the blood of kidney failure patients with conventional dialysis is limited. However, as their harmful effects and association with morbidity and mortality in dialysis patients are increasingly recognized, PBUTs have become important therapeutic targets. In this review, PBUT removal with current state-of-the-art dialysis technologies and future perspectives are discussed. Strategies to enhance PBUT clearance include methods that interfere with PBUT–albumin binding, such as chemical displacers, high ionic strength, pH changes, or electromagnetic fields, thereby increasing the free fraction available for dialysis. While these methods have shown promise in vitro, and some also in vivo, long-term safety data are lacking. PBUT removal can also be increased by adsorption, either directly via hemoperfusion, or indirectly, e.g., via sorbents incorporated in a mixed-matrix membrane or dissolved in the dialysate. In the kidney, PBUTs are secreted in the proximal tubules; hence, a cell-based bioartificial kidney (BAK) that secretes PBUTs is proposed as an add-on to current dialysis. Yet both PBUT adsorption strategies and, in particular, BAKs face considerable challenges in upscaling and mass production at acceptable costs. In conclusion, many novel technologies are under development, all requiring further (pre)clinical testing and upscaling before these strategies can be applied in the clinic. Full article

This paper analyses several mathematical games developed 50 years ago by Manfred Eigen and Ruthild Winkler in their famous book “Laws of the Game: How the Principles of Nature Govern Chance,” published for the first time in German in 1975. These games are intended to represent the essential aspects of chemical selection processes via symmetry breaking in biological systems. Special attention is paid to games that model biochemical kinetics, in which a chessboard is used to represent different types of substrates. The time-dependent statistical outcomes of several games are studied by Monte Carlo techniques. Analytical stochastic models applied to these games relate game rules to partial differential equation problems with appropriate initial and boundary conditions: rationalizing their outcomes, they confirm the intuitions of the original authors and add new insights. The potential impact of game-based models on current research on biological homochirality is discussed. Full article

Five prevention is an important technical means to prevent maloperations in substations, and knowledge extraction from wiring diagrams is the key to intelligent “five prevention logic verification”. To address the error accumulation caused by multimodal object matching in traditional methods, this paper proposes a hierarchical recognition-based approach for topological knowledge extraction. This method establishes a multi-level recognition framework utilizing image tiling, decomposing the wiring diagram recognition task into three hierarchical levels from top to bottom: connection modes, bay types, and switching devices. A depth-first strategy is employed to establish parent–child node relationships, forming an initial topological structure. Based on the recognition results, the proposed approach performs regularized parsing and leverages a bay topology knowledge base to achieve automated matching of inter-device topological relationships. To enhance recognition accuracy, the model incorporates a Swin Transformer block to strengthen global feature perception and adds an ultra-small target detection layer to improve small-object recognition. The experimental results demonstrate that all recognition layers achieve mAP@0.5 exceeding 90%, with an overall precision of 93.9% and a recall rate of 91.7%, outperforming traditional matching algorithms and meeting the requirements for wiring diagram topology knowledge extraction. Full article

Background/Objectives: Primary Progressive Aphasia (PPA) is a neurodegenerative disorder characterized by gradual and progressive deterioration of speech and language abilities. Speech and language therapy is considered an important intervention to slow decline and support the recovery of linguistic functions in individuals with PPA. This study aims to examine the effectiveness of an elaborated Semantic Feature Analysis (SFA) approach in enhancing naming abilities and semantic networks in individuals with the logopenic and semantic variants of PPA. Methods: Fourteen participants were recruited, including seven individuals with logopenic PPA and seven with semantic PPA. All participants received an elaborated SFA intervention twice weekly for four weeks. The Aphasia Language Assessment Test (ADD), the Turkish Picture Naming Test (T-RAT), and the SAQOL-39 were conducted at the following three time points: prior to treatment (pre-test), immediately after treatment (post-test), and one month post-treatment (follow-up). Results: Significant improvements were observed in ADD, T-RAT, and SAQOL-39 scores in both logopenic and semantic PPA groups following treatment (p < 0.05). Although follow-up scores declined compared to posttest performance (p < 0.05), several follow-up scores remained higher than pretest levels. Between-group comparisons indicated no significant difference in ADD scores; however, logopenic PPA participants demonstrated higher T-RAT scores (p < 0.05), while semantic PPA participants showed higher SAQOL-39 scores, except at follow-up (p < 0.05). Conclusions: Preliminary results suggest that the elaborated SFA intervention is effective in improving naming skills, language functioning, and quality of life in both logopenic and semantic variants of PPA. Although treatment gains partially decreased after one month, many improvements were maintained above baseline, supporting the clinical value of SFA in managing language decline in PPA. Full article

Newborn screening (NBS) for sickle cell disease (SCD) has been performed in the United States (US) for decades, significantly reducing infant morbidity and mortality. A landmark clinical trial demonstrated that early identification of SCD enabled timely and life-saving prophylactic penicillin; this led to recommendations for universal NBS across the US. Early use of hydroxyurea as a safe and effective treatment for SCD further improved clinical outcomes by preventing acute and chronic disease complications. These advances add to the importance of early diagnosis through NBS, providing an opportunity for early treatment intervention. In recent years, high-resource countries—including those in Europe, the UK, and Canada—have adopted NBS for SCD using diverse strategies. Simultaneously, pilot programs in lower-resource settings such as Africa, Brazil, and India have demonstrated local feasibility and impact through implementation efforts. An overarching equity gap for achieving global NBS for SCD is the variable access to simple, accurate, and affordable testing. Other challenges include timing of NBS testing, targeted populations, laboratory methods, and parental education with genetic counseling. Questions remain about the equitable enrollment of affected infants worldwide into comprehensive care to ensure early treatment. These challenges raise concerns about sustainability, underscore the need for long-term funding and a strategic plan, and highlight persistent inequities from the lack of global NBS standards. Full article

Background. Determining the cause and manner of death in scenes involving multiple and putrified bodies found in the same environment is a real challenge for forensic pathologists. While common scenarios include fires, vehicle crashes, and natural disasters, one of the most common causes is drug intoxication or poisoning, and the scene must be carefully evaluated based on circumstantial evidence. Carbon monoxide (CO) (also called “the silent killer”) remains one of the leading agents capable of producing simultaneous fatalities. In multi-body scenes, distinguishing between homicide–suicide, double suicide, and accidental deaths adds further complexity. The aim of this study is to highlight the limitations of toxicological and pathological investigations in advanced putrefaction and to emphasize the role of scene investigation in the interpretation of suspected CO-related deaths. Methods. The authors report a case of suspected CO intoxication involving two bodies in an advanced stage of decomposition recovered from the same room. The scene investigation, coupled with the presence of a malfunctioning combustion source, raised suspicion of CO exposure; however, analytical interpretation was severely constrained by the altered condition of biological samples. Results. Advanced decomposition magnifies these challenges. Putrefactive changes can mimic traumatic injuries, hide hypostasis, and compromise both macroscopic and microscopic evaluations due to autolysis and gas formation. Toxicological investigations are frequently hindered by the degradation or absence of key biological matrices such as blood, cavity fluids, or vitreous humor, rendering carboxyhaemoglobin quantification unreliable or impossible. These limitations may lead to incorrect medico-legal conclusions. Conclusions. Determining the cause and manner of death in complex multi-body scenes requires careful evaluation of circumstantial evidence and scene investigation, particularly when advanced decomposition compromises biological analyses and toxicological interpretation. Full article

The global shipping industry is surging ahead, and with it, a quiet revolution is taking place on the water: marine lithium-ion batteries have emerged as a crucial clean energy carrier, powering everything from ferries to container ships. When these vessels dock, they increasingly rely on shore power charging systems to refuel—essentially, plugging in instead of idling on diesel. But predicting how much power they will need is not straightforward. Think about it: different ships, varying battery sizes, mixed charging technologies, and unpredictable port stays all come into play, creating a load profile that is random, uneven, and often concentrated—a real headache for grid planners. So how do you forecast something so inherently variable? This study turned to the Monte Carlo method, a probabilistic technique that thrives on uncertainty. Instead of seeking a single fixed answer, the model embraces randomness, feeding in real-world data on supply modes, vessel types, battery capacity, and operational hours. Through repeated random sampling and load simulation, it builds up a realistic picture of potential charging demand. We ran the numbers for a simulated fleet of 400 vessels, and the results speak for themselves: load factors landed at 0.35 for conventional AC shore power, 0.39 for high-voltage DC, 0.33 for renewable-based systems, 0.64 for smart microgrids, and 0.76 when energy storage joined the mix. Notice how storage and microgrids really smooth things out? What does this mean in practice? Well, it turns out that Monte Carlo is not just academically elegant, it is practically useful. By quantifying uncertainty and delivering load factors within confidence intervals, the method offers port operators something precious: a data-backed foundation for decision-making. Whether it is sizing infrastructure, designing tariff incentives, or weighing the grid impact of different shore power setups, this approach adds clarity. In the bigger picture, that kind of insight matters. As ports worldwide strive to support cleaner shipping and align with climate goals—China’s “dual carbon” ambition being a case in point—achieving a reliable handle on charging demand is not just technical; it is strategic. Here, probabilistic modeling shifts from a simulation exercise to a tangible tool for greener, more resilient port energy management. Full article

Rapid urbanization and climate change have intensified flood risk and ecological degradation along urban riverfronts. Recent literature suggests that combining green and grey infrastructure can enhance resilience while delivering ecological and social co-benefits. This study analyzes and compares five riverfront projects in China and Spain, assessing how their tactic mixes operationalize three urban flood-resilience strategies—Resist, Delay, and Store/reuse—and how these mixes translate into ecological, social, and urban impacts. A six-phase framework was applied: (1) literature review; (2) case selection; (3) categorization of resilience strategies; (4) systematization and typification of tactics into green vs. grey infrastructure; (5) percentage analysis and qualitative matrices; and (6) comparative synthesis supported by an alluvial diagram. Across cases, Delay emerges as the structural backbone—via wetlands, terraces, vegetated buffers, and floodable spaces—while Resist is used selectively where exposure and erodibility require it. Store/reuse appears in targeted settings where operational capacity and water-quality standards enable circular use. The comparison highlights hybrid, safe-to-fail configurations that integrate public space, ecological restoration, and hydraulic performance. Effective urban riverfront resilience does not replace grey infrastructure but hybridizes it with nature-based solutions. Planning should prioritize Delay with green systems, add Resist where necessary, and enable Store/reuse when governance, operation and maintenance, and water quality permit, using iterative monitoring to adapt the green–grey mix over time. Full article

The proposed research aims to analyse the effects of the relationship between Sustainability Governance (SG) and Climate Impact (CI), taking into consideration Green Finance (GF). Furthermore, it examines how Institutional Support (IS) enhances the governance systems governing these variables. The research provides a holistic approach for analysing the effects of financial dynamics on climate impacts. Partial Least Squares Structural Equation Modelling (PLS-SEM) was employed in this research study. The data were collected from various industries using a standardised questionnaire. The structural model examined the direct and indirect relationships between variables such as GF, SG, and CI. IS emerged as the moderated variable. The outcomes of the study confirmed that “GF has an important and direct as well as indirect (through SG as the mediator) impact on CI. IS significantly increases SG and thus exerts an overall enhancing effect on the impact of GF on the climate.” The study has supported the research objectives and aims. The limitations of this study comprised constraints related to both time and cost. The researchers encountered limitations in accessing senior managers and directors of various organisations for the study. IS emerged as an important intermediate factor that can significantly link various actions and activities that impact the climate. This study supports both global and local research objectives. The study offers significant insights, underscoring the critical role of SG within Green Business (GB). Additionally, IS emerges as a vital enabling tool that strengthens the overall governance framework. The study contributes significantly to the development of integrated frameworks for institutions seeking to effectively address environmental challenges. The implications for action indicate that furthering entrenched institutional structures and instilling good governance practices can add tremendous value to the transformation potential of GF and usher in accelerated efforts to achieve national and international objectives on climate change. Full article