Search Results (20,952)

Pottery is one of the most common and abundant types of human remains found in archaeological contexts. The analysis of archaeological pottery involves the reconstruction of pottery vessels from their sherds, which represents a laborious and repetitive task. In this work, we investigate a deep learning-based approach to make that process more efficient, accurate, and fast. In that regard, given a sherd’s digital point cloud in a standard, so-called canonical position, the proposed method predicts the geometric transformation, which moves the sherd to its expected normalized position relative to the vessel’s coordinate system. Among the main components of the proposed method, a pair of deep 1D convolutional neural networks trained to predict the 3D Euclidean transformation parameters stands out. Herein, rotation and translation components are treated as independent problems, so while the first network is dedicated to predicting translation moments, the other infers the rotation parameters. In practical applications, once a vessel’s shape is identified, the networks can be trained to predict the target transformation parameter values. Thus, given a 3D model of a complete vessel, it may be virtually broken down countless times for the production of sufficient data to meet deep neural network training demands. In addition to overcoming the scarcity of real sherd data, given a virtual sherd in its original position, that procedure provides paired canonical and normalized point clouds, as well as the target Euclidean transformation. The herein proposed 1D convolutional neural network architecture, the so-called PotNet, was inspired by the PointNet architecture. While PointNet was motivated by 3D point cloud classification and segmentation applications, PotNet was designed to perform non-linear regressions. The method is able to provide an initial estimate for the correct position of a sherd, reducing the complexity of the problem of fitting candidate pairs of sherds, which could be then carried out by a classical adjustment method like ICP, for instance. Experiments using three distinct real vessels were carried out, and the reported results suggest that the proposed method can be successfully used for aiding pottery reconstruction. Full article

Litter serves as a crucial source of soil nutrients in sandy land ecosystems. Soil enzyme activities and their stoichiometric ratios act as essential “bridges” linking microbial metabolism with nutrient cycling, thereby reflecting the availability of soil nutrients and the sensitivity to microbial substrate limitations. To investigate the effects of litter quality changes on soil nutrients, enzyme activities, and stoichiometric ratios in sandy land, leaf litter and surface soil were collected from four sand-fixing forests in the Mu Us Sandy Land, including YC (Corethrodendron fruticosum), NT (Caragana korshinskii), ZSH (Amorpha fruticose), and SL (Salix cheilophila). These samples were then used for indoor cultivation. Experiments with these four leaf litter types were carried out; one treatment with no litter added served as the control. Our aim was to systematically study the changing characteristics of enzyme activities related to soil carbon, nitrogen, and phosphorus with different litter inputs. The results indicate the following: (1) Compared to the control treatment with no litter added (CK), the addition of all four types of litter significantly increased soil organic carbon, total nitrogen, and alkaline nitrogen contents. The addition of NT and YC litter significantly increased dissolved organic carbon, microbial biomass carbon (MBC), and microbial biomass nitrogen (MBN). (2) The addition of the four types of litter had different effects on the soil enzyme activity, showing increasing trends overall. A chemical analysis of the enzyme activity revealed that the soil was limited in nitrogen and phosphorus. After the addition of the ZSH, NT, and YC litter, the enzymatic C/P acquisition ratio (E_C/P) and enzymatic N/P acquisition ratio (E_N/P) decreased significantly, alleviating the limitation of phosphorus. After the addition of the NT litter, the enzymatic C/N acquisition ratio (E_C/N) increased significantly, alleviating the limitation of soil nitrogen. (3) A correlation analysis showed that the soil nutrients had varying degrees of correlation with enzyme activity and their stoichiometric ratio. The redundancy analysis results show that MBN, TN, MBC/MBN, organic carbon, and available nitrogen were key factors influencing soil enzyme activity and stoichiometric ratios. These results provide a reference for nutrient cycling during sandy soil restoration, and they provide essential data support for the development of fragile ecosystem models in the context of global change. Full article

Medical image segmentation is a critical task in image analysis and plays an essential role in computer-aided diagnosis. Despite the promising performance of hybrid models combining U-Net and transformer architectures, these approaches face challenges in extracting local features and optimizing attention mechanisms. To address these limitations, we propose the Depthwise Composite Transformer and Depthwise Polarized Attention Network (DC-TransDPANet), a novel framework designed for medical image segmentation. The proposed DC-TransDPANet introduces a Depthwise Composite Attention Module (DW-CAM), which integrates depthwise convolution, and a Composite Attention mechanism to enhance local feature extraction and fuse contextual information. Additionally, a Depthwise Polarized Attention (DPA) block is employed to improve global context representation while preserving high-resolution details, achieving a fine balance between local and global feature extraction. Extensive experiments on benchmark datasets demonstrate that DC-TransDPANet significantly outperforms existing methods in segmentation accuracy. Full article

This article aims to examine the concept of responsibility through the lens of the “integral ecology” proposed by Pope Francis in Laudato Si’. The objective is to demonstrate how the ethics of responsibility developed by Hans Jonas in his seminal 1979 work aligns with Pope Francis’s concerns and simultaneously offers a complementary theoretical–philosophical framework. To this end, we begin by showing how responsibility occupies a central place in the papal encyclical, assuming a multidimensional perspective. From there, we analyze how the understanding of responsibility transitions from ontology (Jonas) and anthropology (Francis) to ethics, taking the biosphere as a new object of responsibility in light of the threats posed by the unchecked advance of technological powers against nature. This investigation is based on a comparative and conceptual analysis of primary texts by Hans Jonas and Pope Francis. This shift also entails the recognition of nature’s intrinsic rights and an understanding of species extinction as both an impoverishment (Jonas) and a mutilation (Francis) of creation. We conclude by demonstrating how the call for integral ecology becomes an urgent task for the present generations in the context of catastrophe prevention. In this way, integral ecology attains its radical meaning when understood as demanding two fundamental transformations: a change in consciousness and a change in lifestyle—from consumerism to frugality. Full article

Over the past 20 years, researchers have shown increasing interest in social network analysis to understand second language acquisition (SLA), especially in a study abroad (SA) context. To date, few longitudinal studies have examined the joint evolution of the learners’ sociolinguistic competence and socialisation during the SA. By shifting the focus from a global view of the study abroad context to a deep analysis of the composition and structure of each learner’ social networks in the host country, we aim to provide a better understanding of the development of sociolinguistic competence in SLA (Gautier & Chevrot, 2015). We apply the sociological concept of a social network to sociolinguistics. To explore the sociolinguistic competence of 29 learners, we focus on two well-described sociolinguistic variables in French: the optional liaison and the negative ne. We also gathered data on their social networks and provided a deep analysis of each participant’s network. We implemented a quantitative approach to analyse and depict the social networks of the learners. Statistically significant relationships were found between changes in the learners’ personal network and their use of the two sociolinguistic variables. The development of L2-oriented social networks (in terms of size, speaking time, and frequency) over nine months of the SA helps learners to reduce their use of standard variants. Conversely, the development of L1-oriented social networks during the SA is associated with greater use of standard variants. Full article

Startups in the clean energy and environmental technology (CEET) sector can develop sustainable innovations, but mobilizing private finance has been difficult. As the venture capital (VC) investment model was found to be not well-suited for the CEET startups, diverse types of investors have received more attention. However, since previous studies have been dominated by a VC-centric perspective in the US and have overlooked collaborative relationships, the roles of various CEET investors have not been systematically analyzed. This study aims to analyze the diverse investors in the CEET investor network formed through co-investment syndication, using Japan as an underexplored regional context. Based on Japan’s comprehensive data from 2008 to 2022, this study examines the evolution, structure, and communities of the network. The analysis identified the development stages of the investor network: the formation stage (2008–2012), the expansion and diversification stage (2013–2017), and the stable growth stage (2018–2022). The results confirmed the strong influence of VCs, while a community analysis suggested the bridging role of governmental venture capital. The findings based on the CEET investor network contribute to expanding both the theoretical understanding and practical implications for overcoming the financing difficulties of CEET startups to address the climate change crisis. Full article

In the era of information explosion, recommendation systems play a crucial role in filtering vast amounts of content for users. Traditional recommendation models leverage knowledge graphs, sentiment analysis, social capital, and generative AI to enhance personalization. However, existing models still struggle to adapt dynamically to users’ evolving interests across multiple content domains in real-time. To address this gap, the cross-domain adaptive recommendation system (CDARS) is proposed, which integrates real-time behavioral tracking with multi-domain knowledge graphs to refine user preference modeling continuously. Unlike conventional methods that rely on static or historical data, CDARS dynamically adjusts its recommendation strategies based on contextual factors such as real-time engagement, sentiment fluctuations, and implicit preference drifts. Furthermore, a novel explainable adaptive learning (EAL) module was introduced, providing transparent insights into recommendations’ evolving nature, thereby improving user trust and system interpretability. To enable such real-time adaptability, CDARS incorporates multimodal sentiment analysis of user-generated content, behavioral pattern mining (e.g., click timing, revisit frequency), and learning trajectory modeling through time-aware embeddings and incremental updates of user representations. These dynamic signals are mapped into evolving knowledge graphs, forming continuously updated learning charts that drive more context-aware and emotionally intelligent recommendations. Our experimental results on datasets spanning social media, e-commerce, and entertainment domains demonstrate that CDARS significantly enhances recommendation relevance, achieving an average improvement of 7.8% in click-through rate (CTR) and 8.3% in user engagement compared to state-of-the-art models. This research presents a paradigm shift toward truly dynamic and explainable recommendation systems, creating a way for more personalized and user-centric experiences in the digital landscape. Full article

In operational testing contexts, testers face dual challenges of constrained timeframes and limited resources, both of which impede the generation of reliability test data. To address this issue, integrating data from similar systems with test data can effectively expand data sources. This study proposes a systematic approach wherein the mission of the system under test (SUT) is decomposed to identify candidate subsystems for data combination. A phylogenetic tree representation is constructed for subsystem analysis and subsequently mapped to a mixed-integer programming (MIP) model, enabling efficient computation of similarity factors. A reliability assessment model that combines data from similar subsystems is established. The similarity factor is regarded as a covariate, and the regression relationship between it and the subsystem failure-time distribution is established. The joint posterior distribution of regression coefficients is derived using Bayesian theory, which are then sampled via the No-U-Turn Sampler (NUTS) algorithm to obtain reliability estimates. Numerical case studies demonstrate that the proposed method outperforms existing approaches, yielding more robust similarity factors and higher accuracy in reliability assessments. Full article

Objective: This study aims to analyze and evaluate the diagnostic methods used to detect multiple myeloma in paleopathological research. As a malignancy characterized by bone lesions, multiple myeloma presents unique opportunities for study through the paleopathological analysis of human skeletal remains. Methods: A literature review was conducted across PubMed, ScienceDirect, Embase, Scopus, Web of Science, and Google Scholar, focusing on macroscopic, radiological, and microscopic methods. A total of 43 original peer-reviewed studies published over six decades were selected. Results: The most commonly used diagnostic technique was macroscopic analysis of bone material, focusing on the characteristics of the lesions. Radiological methods, including X-ray, magnetic resonance imaging, computed tomography (CT), and micro-CT, provided complementary insights. Various microscopic techniques, chemical analyses, and fluoroscopy provided additional diagnostic detail. The diagnostic process is shaped by factors such as preservation, context, and access to technology; despite these variables, characteristic features of lesions were consistently recognized. Conclusion: This review highlights how macroscopic analysis remains central to diagnosis in paleopathology, with radiological and microscopic methods increasingly enhancing accuracy and interpretive depth. A multidisciplinary approach, combining macroscopic, radiological, microscopic, and chemical analyses where feasible, continues to strengthen paleopathological research and offers new insights into the historical presence of multiple myeloma. Full article

Background/Objectives: Type 2 diabetes mellitus (T2DM) is a major global health challenge, primarily driven by insulin resistance and beta-cell dysfunction. This study investigated the roles of p21-activated kinase 1 (PAK1) and calcium/calmodulin-dependent protein kinase II (CAMKII) in insulin secretion, aiming to elucidate their involvement in this process and their implications in T2DM pathophysiology. Methods: Using the Beta-TC-6 insulinoma cell line, we assessed colocalization and interaction of PAK1 and CAMKII under glucose stimulation through indirect immuno-fluorescence (IFI) and proximity ligation assays (PLA). To examine their expression dynamics in a physiological context, we performed immunohistochemistry (IHC) on pancreatic sections from wild-type (WT), prediabetic, and T2DM murine models. Additionally, bioinformatic analysis of publicly available RNA sequencing (RNA-Seq) data from human islets of healthy donors, prediabetic individuals, and T2DM patients provided translational validation. Results: High glucose conditions significantly increased PAK1-CAMKII colocalization, correlating with enhanced insulin secretion. Pharmacological inhibition of these kinases reduced insulin release, confirming their regulatory roles. Murine and human islet analyses showed a progressive increase in kinase expression from prediabetes to T2DM, highlighting their relevance in disease progression. Conclusions: The coordinated function of PAK1 and CaMKII in insulin secretion suggests their potential as biomarkers and therapeutic targets in T2DM. Further studies are warranted to explore their mechanistic roles and therapeutic applications in preserving beta-cell function. Full article

Medical assistance in dying (MAID) remains a sensitive and evolving issue in Europe, frequently linked with discussions about human freedom, life dignity, and healthcare policy. While national consensus in Italy is absent, the Region of Tuscany has enacted Law No. 16/2025, which establishes a MAID procedure based on recent Constitutional Court rulings. The commentary aims to provide a preliminary analysis of the new law, addressing ethical, medico-legal, and social issues that emerge in relation to the Italian and global debate on the topic. The law establishes a three-stage process based on four eligibility criteria: irreversible disease, psycho-physical suffering, life-support dependence, and informed consent. However, Tuscany’s model poses medico-legal and ethical concerns, particularly about the boundaries of regional legislative competence, the duties of healthcare professionals, and the possibility of intra-national inequity or “health migration.” In addition, critical organisational implications derived from informed consent and lethal drug self-administration impede clinical implementation in some individuals with mental or neurological disorders. The lack of clarity in the different steps of the procedure, the uncertain supervision system, and the potential consequences for specific categories of vulnerable people underline the need for comprehensive national regulation. A future regulatory framework must balance procedural clarity with individual autonomy and equitable access, bringing Italy in line with larger European context for end-of-life care. Full article

Studies analyzing the prevalence of associated substance use are limited. Currently, the World Health Organization (WHO) defines polydrug use as the concurrent (simultaneous use) or sequential (use of one drug followed by another) abuse of more than one drug or type of drug, with dependence on at least one. Associated drug consumption can exacerbate the adverse effects and complicate the clinical management of patients. This study aimed to investigate the prevalence of polydrug use, excluding tobacco, in patients presenting with acute intoxication in the Emergency Department (ED) of the Clinical University Hospital Virgen de la Arrixaca (Murcia, Spain) in the year 2023. To this end, a retrospective analysis of 2562 patients was conducted, examining demographic variables, substance use patterns, reasons for presenting to the ED, and the substances consumed by each patient. The study reveals an average patient age of 41 ± 0.5 (SD = 11.96) composed of predominantly male patients (74.4%). A high prevalence of benzodiazepines and cocaine use, often in combination, was observed. The main reasons for attendance included symptoms such as palpitations, dyspnea, vomiting, diarrhea, behavioral disturbances, and self-harm. Only 25.5% of patients admitted to consuming all substances detected in their analyses. Polydrug use is frequent in our environment, which can lead to added complexity in diagnosis and treatment. Consumption patterns show a profile strongly related to the age of the subject. Among the youngest subjects, tetrahydrocannabinol (THC) and benzodiazepines predominate, whilst among older subjects, alcohol and benzodiazepines, and sometimes cocaine, predominate. This study highlights the need to design specific intervention and prevention strategies to address patterns of substance abuse, the importance of family and community support, and the need to tackle challenges in identifying and treating cases of polysubstance abuse. Moreover, cooperation between the healthcare system and law enforcement is also important to obtain up-to-date knowledge of new drugs and their consumption patterns in an emergency context. Full article

Ovarian cancer (OC) is a severe gynecological malignancy with a high mortality rate among women worldwide. It is often diagnosed at advanced stages due to the lack of effective screening methods. This study investigated the expression patterns of microRNAs (miRNAs) hsa-miR-21-5p and hsa-miR-145-5p as potential OC prognostic and diagnostic biomarkers and their correlation with estrogen-dependent (ESR1 & 2, PELP1 and c-SRC) and hypoxia–neovascularization-induced (HIF1A, EPAS1, and VEGFA) pathway genes. Tissue samples obtained from twenty patients with confirmed ovarian cancer and twenty controls were analyzed using quantitative polymerase chain reaction (qPCR) to examine miRNA and mRNA levels. The qPCR analysis revealed significantly higher hsa-miR-21-5p and lower hsa-miR-145-5p expression in OC tissues than controls. Moreover, a significant trend was observed in hsa-miR-21-5p and hsa-miR-145-5p expression levels across normal, non-cancerous changes and malignant ovarian tissues. The hsa-miR-21-5p showed better diagnostic potential than hsa-miR-145-5p. We also observed inconsistent correlations in hsa-miR-21-5p and hsa-mir-145-5p and estrogen-related and hypoxia–neovascularization-dependent genes in ovarian cancer across all groups. This suggests that the relationship between these miRNAs and the selected genes is context-specific. Our findings suggest that hsa-miR-21-5p and hsa-miR-145-5p expression levels may be prognostic or diagnostic markers for ovarian cancer patients. Full article

There has been an increase in the number of users on digital platforms. Similarly, technology is prevalent in the daily lives of young people, therefore, it is crucial to address the topic of digital citizenship with them, ensuring they use technology in a responsible and healthy manner. The present study argues that the foreign language classroom constitutes a privileged space for the promotion of digital citizenship. To address this research gap, the present study examines digital citizenship within the context of foreign language education, with a particular focus on its articulation with the intercultural dimension, and explores its impact on participants’ knowledge, attitudes, and opinions. More specifically, this study aims to determine the effectiveness of a five-session didactic intervention in developing students’ knowledge, attitudes, and opinions regarding digital citizenship within an intercultural dimension in an EFL secondary classroom. The research question formulated is: how can digital citizenship be developed in conjunction with the intercultural dimension in the English language classroom in secondary education, namely concerning students’ knowledge, attitudes, and opinions? With the intention of addressing this question, an intervention project was implemented with a class of 11th-grade students at a school in the Aveiro district, Portugal. The didactic project consisted of five sessions conducted in the English classroom, in a total of 450 min. Through the content analysis conducted on the collected data, it revealed significant improvements in students’ understanding of online rights and responsibilities, and a positive shift in attitudes toward intercultural interaction. While some initial prejudices persisted, the project fostered increased awareness of diverse cultural perspectives in the digital world. These findings suggest that targeted interventions integrating intercultural awareness within digital citizenship education can be effective in promoting responsible digital engagement and intercultural sensitivity in EFL secondary education. Full article

Gastrointestinal parasites impact the health and productivity of domestic birds and may even be more common in production systems with lower biosafety conditions. In this context, backyard poultry production systems (BPPS), defined as small-scale family production systems, could be more affected. However, information about its epidemiology is limited in the Central Zone of Chile. This study aimed to determine the risk factors and spatial distribution of gastrointestinal parasites in BPPS in Central Chile. Thus, feces samples were collected from 51 backyards and analyzed using copro–parasitological techniques. In parallel, an epidemiological survey was conducted on the farmers, and the data were analyzed by multivariable logistic regression to identify risk factors. Spatial analysis was performed with the detected parasite species to determine high-risk clusters. Eimeria spp. was the most frequently detected parasite (72.5%), followed by Capillaria spp. (50.9%) and Ascaridia galli (49%). Regarding parasitic burden, nearly 90% of BPPS showed low parasitic burden for Eimeria spp. and helminths. In turn, the availability of potable drinking water (95% CI: 0.054–0.905; p = 0.036) and proper ventilation of the pens (95% CI: 0.003–0.429; p = 0.009) reduced the presence of parasites. Spatial high-risk clusters were detected for Eimeria spp. (RR = 2.60; p-value < 0.0001), A. galli (RR = 2.93; p-value = 0.021), and Trichostrongylus spp. (RR = 5.85; p-value = 0.050). Full article