Search Results (514)

This study explores the transformative potential of blockchain technology in overhauling conventional housing rental systems. It specifically addresses persistent issues, such as information asymmetry, fraudulent listings, weak Rental Agreements, and data breaches. A comprehensive review of ten academic publications highlights the architectural frameworks, underlying technologies, and myriad benefits of decentralized rental platforms. The intrinsic characteristics of blockchain—immutability, transparency, and decentralization—are pivotal in enhancing the credibility of rental information and proactively preventing fraudulent activities. Smart contracts emerge as a key innovation, enabling the automated execution of Rental Agreements, thereby significantly boosting efficiency and minimizing reliance on intermediaries. Furthermore, Decentralized Identity (DID) solutions offer a robust mechanism for securely managing identities, effectively mitigating risks associated with data leakage, and fostering a more trustworthy environment. The suitability of platforms such as Hyperledger Fabric for developing such sophisticated rental systems is also critically evaluated. Blockchain-based systems promise to dramatically increase market transparency, bolster transaction security, and enhance fraud prevention. They also offer streamlined processes for dispute resolution. Despite these significant advantages, the widespread adoption of blockchain in the rental sector faces several challenges. These include inherent technological complexity, adoption barriers, the need for extensive legal and regulatory adaptation, and critical privacy concerns (e.g., ensuring compliance with GDPR). Furthermore, blockchain scalability limitations and the intricate balance between data immutability and the necessity for occasional data corrections present considerable hurdles. Future research should focus on developing user-friendly DID solutions, enhancing blockchain performance and cost-efficiency, strengthening smart contract security, optimizing the overall user experience, and exploring seamless integration with emerging technologies. While current challenges are undeniable, blockchain technology offers a powerful suite of tools for fundamentally improving the rental market’s efficiency, transparency, and security, exhibiting significant potential to reshape the entire rental ecosystem. Full article

Cattle manure accounts for approximately one-third of the total livestock manure produced in the Republic of Korea and is typically composted. To elucidate its feasibility as a renewable resource, this study evaluated the conversion of cattle manure into a solid biofuel and the nutrient recovery potential of its combustion residues. Solid fuel was prepared from cattle manure collected in Gyeongsangbuk-do, Korea, and its fuel characteristics and ash composition were analyzed after combustion. Combustion tests conducted using a dedicated solid fuel boiler showed that an average lower heating value of 13.27 MJ/kg was achieved, meeting legal standards. Under optimized combustion, CO and NO_x emissions (129.9 and 41.5 ppm) were below regulatory limits (200 and 90 ppm); PM was also within the 25 mg/Sm³ standard. The bottom ash contained high concentrations of P₂O₅ and K, and its heavy metal content was below the regulatory threshold, suggesting its potential reuse as a fertilizer material. Although the Zn concentration in the fly ash exceeded the standard, its quantity was negligible. Therefore, the solid fuel conversion of cattle manure can become a viable and environmentally sustainable solution for both bioenergy production and nutrient recycling, contributing to improved waste management in livestock operations. Full article

Common ragweed (Ambrosia artemisiifolia L.) has been identified as one of the most harmful invasive weed species in Europe due to its allergenic pollen and competitive growth in diverse habitats. In the first part of this review [Common Ragweed—Ambrosia artemisiifolia L.: A Review with Special Regards to the Latest Results in Biology and Ecology], its biological characteristics and ecological behavior were described in detail. In the current paper, control strategies are summarized, focusing on integrated weed management adapted to the specific habitat where the species causes damage—arable land, semi-natural vegetation, urban areas, or along linear infrastructures. A range of management methods is reviewed, including agrotechnical, mechanical, physical, thermal, biological, and chemical approaches. Particular attention is given to the spread of herbicide resistance and the need for diversified, habitat-specific interventions. Among biological control options, the potential of Ophraella communa LeSage, a leaf beetle native to North America, is highlighted. Furthermore, innovative technologies such as UAV-assisted weed mapping, site-specific herbicide application, and autonomous weeding robots are discussed as environmentally sustainable tools. The role of legal regulations and pollen monitoring networks—particularly those implemented in Hungary—is also emphasized. By combining traditional and advanced methods within a coordinated framework, effective and ecologically sound ragweed control can be achieved. Full article

Background/Objectives: Artificial intelligence (AI) is beginning to be applied in wound ballistics, showing preliminary potential to improve the accuracy and objectivity of forensic analyses. This review explores the current state of AI applications in forensic firearm wound analysis, emphasizing its potential to address challenges such as subjective interpretations and data heterogeneity. Methods: A systematic review adhering to PRISMA guidelines was conducted using databases such as Scopus and Web of Science. Keywords focused on AI and GSW classification identified 502 studies, narrowed down to 4 relevant articles after rigorous screening based on inclusion and exclusion criteria. Results: These studies examined the role of deep learning (DL) models in classifying GSWs by type, shooting distance, and entry or exit characteristics. The key findings demonstrated that DL models like TinyResNet, ResNet152, and ConvNext Tiny achieved accuracy ranging from 87.99% to 98%. Models were effective in tasks such as classifying GSWs and estimating shooting distances. However, most studies were exploratory in nature, with small sample sizes and, in some cases, reliance on animal models, which limits generalizability to real-world forensic scenarios. Conclusions: Comparisons with other forensic AI applications revealed that large, diverse datasets significantly enhance model performance. Transparent and interpretable AI systems utilizing techniques are essential for judicial acceptance and ethical compliance. Despite the encouraging results, the field remains in an early stage of development. Limitations highlight the need for standardized protocols, cross-institutional collaboration, and the integration of multimodal data for robust forensic AI systems. Future research should focus on overcoming current data and validation constraints, ensuring the ethical use of human forensic data, and developing AI tools that are scientifically sound and legally defensible. Full article

This study investigates how demographic characteristics, severity of intimate partner violence (IPV), social support, gender equality awareness, and demographic factors (e.g., living with children at home) influence help-seeking behaviors among 2527 IPV-experienced women in Beijing, Shanghai, Guangzhou, and Shenzhen. Drawing on the help-seeking model and conservation of resource theory, the study distinguishes between formal (e.g., police, legal aid) and informal (e.g., family, friends) help-seeking. Logistic regression results reveal that greater violence severity, stronger perceived social support, and higher gender equality awareness significantly increase both formal and informal help-seeking. Notably, living with children is associated with a higher likelihood of seeking formal help, possibly due to increased concerns for children’s safety and the desire to change the abusive environment. While help-seeking behavior is on the rise overall, particularly among women with strong support networks and progressive gender attitudes, structural and cultural barriers remain. The findings underscore the need to improve public education, reduce stigma, and enhance accessibility of support systems. This study contributes to the growing literature on IPV in China and provides evidence for refining policy interventions and service delivery. Full article

Recent research in digital migration studies analyzes both refugee populations’ social media use and so-called integration outcomes. Against the backdrop of digitalization, we argue for understanding belonging as part of an ongoing process in physical, virtual and hybrid continuities, where material aspects cannot be divorced from imagined constructions. We take the case of Ukrainian women arriving in the Netherlands following the Russian aggression against Ukraine, in 15 semi-structured interviews from 2023. Adopting an intersectional lens, our research asks the following questions: How does social media use mediate or inform a sense of belonging? How do observations correspond to or differ from previous studies on refugees and social media, given this population’s temporary protection (TP) status? As participants leverage digital platforms differently in evolving situations, they navigate connectedness to the new community; we argue this may be linked to distinct TP status and other characteristics of difference, including educational levels and digital literacy. Conclusions indicate that an intersectional lens could be applied in understanding Ukrainian perspectives in other Member States—or beneficiaries of differing origin—to better account for how intersectional dimensions like legal status can be mutually constitutive of virtual connectedness versus material, physical rootedness or vulnerability. Full article

Brain metastases (BMs) are the most common intracranial tumors in adults. Their heterogeneity, potential multifocality, and complex biomolecular behavior pose significant diagnostic and therapeutic challenges. Artificial intelligence (AI) has the potential to revolutionize BM diagnosis by facilitating early lesion detection, precise imaging segmentation, and non-invasive molecular characterization. Machine learning (ML) and deep learning (DL) models have shown promising results in differentiating BMs from other intracranial tumors with similar imaging characteristics—such as gliomas and primary central nervous system lymphomas (PCNSLs)—and predicting tumor features (e.g., genetic mutations) that can guide individualized and targeted therapies. Intraoperatively, AI-driven systems can enable optimal tumor resection by integrating functional brain maps into preoperative imaging, thus facilitating the identification and safeguarding of eloquent brain regions through augmented reality (AR)-assisted neuronavigation. Even postoperatively, AI can be instrumental for radiotherapy planning personalization through the optimization of dose distribution, maximizing disease control while minimizing adjacent healthy tissue damage. Applications in systemic chemo- and immunotherapy include predictive insights into treatment responses; AI can analyze genomic and radiomic features to facilitate the selection of the most suitable, patient-specific treatment regimen, especially for those whose disease demonstrates specific genetic profiles such as epidermal growth factor receptor mutations (e.g., EGFR, HER2). Moreover, AI-based prognostic models can significantly ameliorate survival and recurrence risk prediction, further contributing to follow-up strategy personalization. Despite these advancements and the promising landscape, multiple challenges—including data availability and variability, decision-making interpretability, and ethical, legal, and regulatory concerns—limit the broader implementation of AI into the everyday clinical management of BMs. Future endeavors should thus prioritize the development of generalized AI models, the combination of large and diverse datasets, and the integration of clinical and molecular data into imaging, in an effort to maximally enhance the clinical application of AI in BM care and optimize patient outcomes. Full article

3D (three-dimensional) property volume is an important data carrier for 3D land administration by using 3D cadastral technology, which can be used to express the legal space (property rights) scope matching with physical entities such as buildings and land. A 3D property volume is represented by a dense set of 3D coordinate points arranged in a predefined order and is displayed alongside the parcel map for reference and utilization by readers. To store a 3D property volume in the database, it is essential to record the connectivity relationships among the original 3D coordinate points, the associations between points and lines for representing boundary lines, and the relationships between lines for defining surfaces. Only by preserving the data structure that represents the relationships among points, lines, and surfaces can the 3D property volume in a parcel map be fully reconstructed. This approach inevitably results in the database storage volume significantly exceeding the original size of the point set, thereby causing storage redundancy. Consequently, this paper introduces a reversible 3D property volume compression coding method (called 3DPV-CC) to address this issue. By analyzing the distribution characteristics of the coordinate points of the 3D property volume, a specific rule for sorting the coordinate points is designed, enabling the database to have the ability of data storage and recovery by merely storing a reordered point set. The experimental results show that the 3DPV-CC method has excellent support capabilities for 3D property volumes of the vertical and slopped types, and can compress and restore the coordinate point set of the 3D property volume for drawing 3D parcel maps. The compression capacity of our method in the test is between 23.66% and 38.42%, higher than the general data compression methods (ZIP/7Z/RAR: 8.37–10.32%). By means of this method, land or real estate administrators from government departments can store 3D property volume data at a lower cost. This is conducive to enhancing the informatization level of land management. Full article

This research is focused on housing stock rehabilitation and construction in Urban Rehabilitation Areas located in diverse contexts in the Portuguese territory. The main objective of this research is to show how the local actors have managed the ARUs’ opportunities to restore and develop the housing in these areas in the Portuguese territory. An analytical national legal framework is made to show that the diffuse criteria at national and regional levels are reflected in the limited effectiveness of the ARUs’ flexible criteria in local implementation. A national legislative and regulatory framework in Portugal, focusing on urban rehabilitation and housing promotion themes, is discussed to emphasize the potential role of Urban Rehabilitation Area (ARU) particularities and housing provision and preservation in diverse contexts in Portugal. A comparative analysis is conducted of five ARUs—Belmonte, Soure, Penacova, Vila Real, and Devesas—located in Portugal, in the North and Center regions, to highlight the particularities/diversity of urban contexts, including towns, small to medium-sized cities, and historic centres. The analysis assesses the effectiveness of ARU urban rehabilitation strategy implementation over time. The analysis of five ARUs will discuss the following: (i) ARU physical characteristics; (ii) ARU population profile; (iii) ARU urban rehabilitation strategies progress (initial, intermediate, and final); and (iv) ARU alignment with PDM priorities in urban rehabilitation. The findings underscore the pivotal role that ARUs and their actors can have in housing rehabilitation provision and preservation on different scales and contexts within the territory. The outcomes show different strategies that each ARU has used to prioritize building rehabilitation. Full article

Purpose: Suicide is a leading cause of death among children and adolescents worldwide. This study examined the prevalence and characteristics of suicides among children and adolescents (aged ≤ 19 years) over a 13-year period in the broader area of Athens, Greece. Key aspects analyzed included victim demographics, circumstances surrounding the incidents, and methods employed. Methods: A retrospective analysis was conducted on autopsy cases performed at the Department of Forensic Medicine and Toxicology, National and Kapodistrian University of Athens, from 1 January 2011, to 31 December 2023. Results: Out of 5819 autopsies conducted between 2011 and 2023, 371 were classified as suicides. Among these, 12 cases (representing 3.2% of suicides) involved children and adolescents aged ≤ 19 years and met the study’s inclusion criteria for detailed forensic analysis. The average age of the victims was 17.7 ± 2.1 years (range: 14–19), with males representing 58.3% of cases. Hanging was the most common method of suicide (9 cases, 75.0%), followed by firearm use, falls from height, and hydrogen sulfide inhalation (one case each). Death occurred in the home in 10 cases (83.3%), with 6 specifically taking place in the bedroom. Scars indicative of prior self-harming behavior were present in two cases (16.7%), while suicide notes were found in three cases (25.0%). Toxicological analysis revealed alcohol and cannabis use in one case, cannabis alone in one case, and alcohol alone in two cases. Four victims (33.3%) had a documented psychiatric diagnosis, with two of them under antidepressant treatment at the time of death. Conclusions: This study highlights the forensic value of autopsy-based investigations in unveiling hidden patterns of adolescent suicidality and informs targeted prevention strategies. Integrating medico-legal findings into public health responses may enhance early identification and intervention in vulnerable youth populations. Full article

Introduction: Humanitarian Corridors are part of Protected Entry Procedures (PEPs), which allow for the safe and legal arrival in Europe of refugees in need of protection (art. 25 of Regulation (CE) n.810/2009) and were implemented for the first time in Italy in 2015. They represent an alternative to dangerous journeys, and they also bring benefits to local communities. The National Institute for Health, Migration and Poverty (NIHMP) represents the first filter at entry with regard to health needs, as it guarantees an overall individual health assessment to verify the possible presence of ongoing infectious pathologies and of issues that may require management and medical investigation. The aim of this study is to expose the organizational activity and analyze the sociodemographic and health data relating to the Humanitarian Corridors implemented in Italy and in which the NIHMP has participated from 2018 to 2024. Materials and Methods: The organizational lists and health data of each corridor were collected. The analysis was carried out in relation to trend, sociodemographic characteristics of the sample, identification, reception and health. The p-value was considered statistically significant if less than 0.01. In all cases in which the p-value was found to be statistically significant, Cramer’s V was calculated to evaluate the strength of the individual correlation. Results: The NIHMP has participated in 14 Humanitarian Corridors, allowing 1250 refugees to enter Italy; a total of 174 unaccompanied foreign minors (UFMs) arrived, and there were 451 refugees reported as vulnerable (36.1%). Contagious infectious conditions were identified in 223 refugees (17.8%), and other health findings were identified in 414 refugees (33.1%). In the analysis by sex, there are statistically significant differences in the reports of vulnerability and in nationality and education. The inferential analysis carried out by age groups presents statistically significant differences in the reports of vulnerability and in sex and nationality. The analysis relating to the differences by nationality shows statistically significant results in the individual corridors in the reports of vulnerability and in schooling, skin manifestations and infectious diseases and the presence of other health findings. Conclusions: The data reported and analyzed in this work can be considered the first attempt at a complete and detailed analysis regarding the actual implementation and effectiveness of Humanitarian Corridors as programs for legal and safe entry into Italy. The significant gap in research is the reason why there are characteristics of our sample that have no counterpart in the literature. Despite this, for other characteristics, it is possible to find statistical significance and scientific value in line with the data reported both on the websites dedicated to the topic and on the limited scientific literature on the subject. Full article

Jurors and other legal decision-makers are often required to make judgments about the likely memory accuracy of another person. Legal systems tend to presume that decision-makers are well-placed to make such judgments (at least in the majority of cases) as a result of their own experiences with memory. However, existing research highlights weaknesses in our abilities to assess the memories of others and suggests that these weaknesses are not easily ameliorated through the provision of information. In this work we examine the accuracy of layperson assessments of “real” eyewitness identifications following observation of a mock crime. We examine whether novel instructions, characteristics and beliefs of assessors, and underlying reasoning strategies are associated with improved or impaired judgment accuracy. The results support prior research in demonstrating a tendency towards over-belief in the accuracy of identifications. They suggest that reliance on what witnesses have said rather than attempts to make inferences from their statements (e.g., in relation to the level of detail provided or non-verbal cues in testimony) is associated with greater accuracy in assessments and that some individual differences and beliefs about memory are also associated with greater accuracy. However, there was no evidence that the instructions tested were effective. We discuss the implications of results for procedure surrounding the evaluation of memory in the legal context. Full article

Background/Objectives: The aim of the present study was to examine the association between the systolic (SBP) as well as diastolic blood pressure (DBP) levels of school-aged children and the adherence of both children and their parents to the Mediterranean Diet. Methods: Detailed data on sociodemographic characteristics, eating habits, and anthropometry were collected from each child (N = 102) and their accompanied parent or legal guardian (N = 102). KIDMED (range: −4 to 12) was used to evaluate children’s level of adherence to the Mediterranean Diet and MedDietScore (range: 0–55) was used for parents. Children’s blood pressure (BP) was measured using a validated automated oscillometric device. Results: Children with higher adherence to the Mediterranean Diet had significantly lower SBP (p < 0.001), DBP (p = 0.009), and hip circumference (p = 0.01) compared to those with lower adherence. Similarly, children of parents with high adherence to the Mediterranean Diet exhibited lower body weight (p = 0.03), waist circumference (p = 0.03), SBP (p < 0.001), and DBP (p = 0.004). In fully adjusted models, for each unit increase in children’s KIDMED scores, a 1.33 unit reduction in SBP (p < 0.001), and a 0.77 unit reduction in DBP were found. Similarly, parental MedDietScore was independently associated with significant reductions in children’s SBP (1.01 mmHg) and DBP (0.75 mmHg) (all p’s < 0.05). Conclusions: Adherence to the Mediterranean dietary pattern by children and parents seems to be associated with lower BP in childhood, supporting the potential value of a family-based approach, particularly involving mothers. Full article

Engineering contract management is a critical component of project management systems, serving as a key mechanism for ensuring successful project implementation. This study systematically analyzes 349 s-instance judicial cases related to construction engineering contract disputes in the Yangtze River Delta Economic Zone from 2017 to 2021, based on data obtained from the China Judgments Online database. The research identifies contractual risk characteristics across dimensions such as regional distribution, dispute terminology, legal citation patterns, and appellate role transitions. The key findings include the following: (1) Primary risks involve payment disputes, quality assurance failures, contractual validity issues, and schedule compliance challenges. (2) Litigation patterns reveal complex interdependencies between contracting parties and stakeholders, posing significant risk management challenges. (3) High second-instance modification rates stem from procedural irregularities, new evidence, improper legal application, and factual errors in initial trials. The study proposes stratified risk mitigation strategies, including governmental regulatory improvements and enterprise-level management optimizations. These findings offer valuable insights into advancing risk governance in construction contract administration, particularly through an enhanced understanding of dispute complexity and systemic vulnerabilities. Full article

Peripheral nerve injuries represent a significant challenge in legal medicine, and their proper management and evaluation are at the intersection of clinical medicine, anatomical science, and legal medicine. In this review, we aimed to integrate current knowledge about the anatomy, physiology, clinical management, and paraclinical assessment of peripheral nerve injuries, targeted explicitly for medical–legal practice. We conducted a comprehensive review of the medical–legal evaluation framework needed to evaluate peripheral nerve injuries, with particular emphasis on anatomical variations, imaging techniques, and methods to assess the timing of injury. Peripheral nerve injuries should be analyzed using a complex approach, which includes anatomical characteristics, variants, microanatomy, physiopathology, imaging, and other paraclinical evaluations. The analysis of causation and timing of injury should be heavily based on objective criteria and should be performed using a reproducible, objective, and scientifically based approach. Full article