Search Results (1,335)

The Internet of Medical Things (IoMT) is revolutionizing healthcare by enabling continuous patient monitoring, early diagnosis, and personalized treatments. However, the het-erogeneity of IoMT devices and the lack of standardized protocols introduce serious security vulnerabilities. To address these challenges, we propose a hybrid BiLSTM-DNN intrusion detection system, named HBiLD-IDS, that combines Bidirectional Long Short-Term Memory (BiLSTM) networks with Deep Neural Networks (DNNs), leveraging both temporal dependencies in network traffic and hierarchical feature extraction. The model is trained and evaluated on the CICIoMT2024 dataset, which accurately reflects the diversity of devices and attack vectors encountered in connected healthcare environments. The dataset undergoes rigorous preprocessing, including data cleaning, feature selection through correlation analysis and recursive elimination, and feature normalization. Compared to existing IDS models, our approach significantly enhances detection accuracy and generalization capacity in the face of complex and evolving attack patterns. Experimental results show that the proposed IDS model achieves a classification accuracy of 98.81% across 19 attack types confirming its robustness and scalability. This approach represents a promising solution for strengthening the security posture of IoMT networks against emerging cyber threats. Full article

Existing heuristic algorithms are based on inspiration sources and have not yet done a good job of basing themselves on optimization principles to minimize and utilize historical information, which may lead to low efficiency, accuracy, and stability of the algorithm. To solve this problem, a personalized-template-guided intelligent evolutionary algorithm named PTG is proposed. The core idea of PTG is to generate personalized templates to guide particle optimization. We also find that high-quality templates can be generated to guide the exploration and exploitation of particles by using the information of the population particles when the optimal value remains unchanged, the knowledge of population distribution changes, and the dimensional distribution properties of particles themselves. By conducting an ablation study and comparative experiments on the challenging CEC2022 test and CEC2005 test functions, we have validated the effectiveness of our method and concluded that the stability and accuracy of the solutions obtained by PTG are superior to other algorithms. Finally, we further verified the effectiveness of PTG through four engineering problems. Full article

Personal Rapid Transit (PRT) and Group Rapid Transit (GRT) are classes of fully automated public transport systems, where passengers can travel in small vehicles on an interconnected, grade-separated network of guideways, non-stop, from origin to destination. PRT and GRT are considered sustainable as they are low-emission and able to attract car drivers. The parameterized cost modeling framework developed in this paper has the advantage that profitability of different PRT/GRT systems can be rapidly verified in a transparent way and in function of a variety of relevant system parameters. This framework may contribute to a more transparent, rapid, and low-cost evaluation of PRT/GRT schemes for planning and decision-making purposes. The main innovation is the introduction of the “peak hour network saturation” S: the number of vehicles in circulation during peak hour divided by the maximum number of vehicles running at line speed with minimum time headways. It is an index that aggregates the main uncertainties in the planning process, namely the demand level relative to the supply level. Furthermore, a maximum S can be estimated for a PRT/GRT project, even without a detailed demand estimation. The profit per trip is analytically derived based on S and a series of more certain parameters, such as fares, capital and maintenance costs, daily demand curve, empty vehicle share, and physical properties of the system. To demonstrate the ability of the framework to analyze profitability in function of various parameters, we apply the methods to a single vehicle PRT, a platooned PRT, and a mixed PRT/GRT. The results show that PRT services with trip length proportional fares could be profitable already for $S>0.25$. The PRT capacity, profitability, and robustness to tripled infrastructure costs can be increased by vehicle platooning or GRT service during peak hours. Full article

Background and Objectives: Heart failure (HF) and chronic kidney disease (CKD) frequently coexist and are closely interrelated, significantly affecting clinical outcomes. Among CKD-related markers, albuminuria and estimated glomerular filtration rate (eGFR) have emerged as key prognostic indicators in HF. However, their specific predictive value across different HF phenotypes—namely HF with preserved ejection fraction (HFpEF) and HF with reduced ejection fraction (HFrEF)—remains incompletely understood. This systematic review aims to evaluate the prognostic significance of albuminuria and eGFR in patients with HF and to compare their predictive roles in HFpEF versus HFrEF populations. Materials and Methods: We conducted a systematic search of major databases to identify clinical studies evaluating the association between albuminuria, eGFR, and adverse outcomes in HF patients. Inclusion criteria encompassed studies reporting on cardiovascular events, all-cause mortality, or HF-related hospitalizations, with subgroup analyses based on ejection fraction. Data extraction and quality assessment were performed independently by two reviewers. Results: Twenty-one studies met the inclusion criteria, including diverse HF populations and various biomarker assessment methods. Both albuminuria and reduced eGFR were consistently associated with increased risk of mortality and hospitalization. In HFrEF populations, reduced eGFR demonstrated stronger prognostic associations, whereas albuminuria was predictive across both HF phenotypes. Heterogeneity in study design and outcome definitions limited comparability. Conclusions: Albuminuria and eGFR are valuable prognostic biomarkers in HF and may enhance risk stratification and clinical decision-making, particularly when integrated into clinical assessment models. Differential prognostic implications in HFpEF versus HFrEF highlight the need for phenotype-specific approaches. Further research is warranted to validate these findings and clarify their role in guiding personalized therapeutic strategies in HF populations. Limitations: The current evidence base consists primarily of observational studies with variable methodological quality and inconsistent reporting of effect estimates. Full article

Background/Objectives: In routine practice, colonoscopy findings are saved as unstructured free text, limiting secondary use. Accurate named-entity recognition (NER) is essential to unlock these descriptions for quality monitoring, personalized medicine and research. We compared named-entity recognition (NER) models trained on real, synthetic, and mixed data to determine whether privacy preserving synthetic reports can boost clinical information extraction. Methods: Three Spark NLP biLSTM CRF models were trained on (i) 100 manually annotated Romanian colonoscopy reports (ModelR), (ii) 100 prompt-generated synthetic reports (ModelS), and (iii) a 1:1 mix (ModelM). Performance was tested on 40 unseen reports (20 real, 20 synthetic) for seven entities. Micro-averaged precision, recall, and F1-score values were computed; McNemar tests with Bonferroni correction assessed pairwise differences. Results: ModelM outperformed single-source models (precision 0.95, recall 0.93, F1 0.94) and was significantly superior to ModelR (F1 0.70) and ModelS (F1 0.64; p < 0.001 for both). ModelR maintained high accuracy on real text (F1 = 0.90), but its accuracy fell when tested on synthetic data (0.47); the reverse was observed for ModelS (F1 = 0.99 synthetic, 0.33 real). McNemar χ² statistics (64.6 for ModelM vs. ModelR; 147.0 for ModelM vs. ModelS) greatly exceeded the Bonferroni-adjusted significance threshold (α = 0.0167), confirming that the observed performance gains were unlikely to be due to chance. Conclusions: Synthetic colonoscopy descriptions are a valuable complement, but not a substitute for real annotations, while AI is helping human experts, not replacing them. Training on a balanced mix of real and synthetic data can help to obtain robust, generalizable NER models able to structure free-text colonoscopy reports, supporting large-scale, privacy-preserving colorectal cancer surveillance and personalized follow-up. Full article

Consumer perceptions of upcycled foods, as well as the determinants of food choices, are still not well understood. The aim of this study was to evaluate the impact of psychological and personal traits on purchase intention (PI) towards upcycled foods of Italian consumers. Additionally, willingness to try (WTT), willingness to buy (WTB), and willingness to pay (WTP) for yogurt, bread, and biscuits made with by-products, namely, hazelnut skin and grape pomace powder, were collected. A web-based survey involving 505 consumers was conducted, and partial least squares structural equation modeling (PLS-SEM) was used to evaluate the model. It resulted that food neophobia and attitude towards upcycled foods had a significant impact on PI. In turn, attitude was affected by food neophobia as well as by objective knowledge about food by-products. Unexpectedly, frugality and environmental concern did not affect PI. WTP was product-specific; when WTP was compared to a reference price, it was higher for the yogurt prototype, followed by the bread and biscuits prototypes. Food neophobia affected WTT, WTB, and WTP. This study contributes to providing new insights into the determinants of consumers’ purchase intention for upcycled foods, which are an emerging category of products. Full article

The present essay aims to make an analysis of a widely analyzed theme held very dear to Pope Saint John Paul II, namely, the right to religious freedom as a foundation for all other forms of freedom. From the way this essay tackles this theme, it is not difficult to understand that John Paul II’s metaphysical view with regard to the human being, as well as his view on the subjectivity of the human person and the dignity of the human person, are essential for an accurate understanding of the relation between freedom and truth. Freedom is rooted in the truth, and it can be achieved only in truth. When it is separated from truth, it becomes just an illusion. For Pope John Paul II, it is very clear that freedom and truth either go together or perish together. The truth to which freedom is linked is not just an abstract truth, but is the Absolute Truth, namely God. Therefore, only in the light of this relationship between freedom and truth can the right to religious freedom, which is the heart of human rights, be explained. Religious freedom allows the human person to live in the truth of her/his faith, according to her/his transcendental dignity. Full article

Our temptation to personify machine intelligence is not unexpected. As a child we named our dolls and took our Teddy Bear to bed with us. Today we ask death bots to comfort us with post-mortem conversation. All the while we know this to be pretend. Yet we must ask: if Artificial General Intelligence (AGI) or even Artificial Super-Intelligence (ASI) become available, will our game of pretend continue? Or will intelligent robots actually become selves deserving of dignity that hitherto could be ascribed only to human persons? If government-imposed guardrails shut the door on development of AGI and ASI in order to preserve human safety and even dignity, we might never learn whether AGI or ASI could develop selfhood, personhood, virtue, or religious sensibilities. As we approach the future, can we live without knowing whether AGI or ASI would be capable of developing selfhood and commanding dignity? Full article

Introduction: Breast cancer therapy is a common cause of lymphedema. The accumulation of protein-rich fluid in the affected extremity leads to a progressive path—swelling, inflammation, and fibrosis—namely, irreversible changes. Methods: A scientific literature analysis was performed on PubMed/Medline, Scopus, Web of Science (WoS), the Cochrane Central Register of Controlled Trials (CENTRAL), and the Physiotherapy Evidence Database (PEDro) from inception until 30 June 2024. Results: Breast cancer-related lymphedema (BCRL) is indeed an important healthcare burden both due to the significant patient-related outcomes and the overall social impact of this condition. Even though lymphedema is not life-threatening, the literature underlined harmful consequences in terms of pain, infections, distress, and functional impairment with a subsequent and relevant decrease in quality of life. Currently, since there is no cure, the therapeutic approach to BCRL aims to slow disease progression and prevent related complications. A comprehensive overview of postmastectomy lymphedema is offered. First, the pathophysiology and risk factors associated with BCRL were detailed; then, diagnosis modalities were depicted highlighting the importance of early detection. According to non-negligible changes in patients’ everyday lives, novel criteria for patients’ functioning assessment are reported. Regarding the treatment modalities, a wide array of conservative and surgical methods both physiologic and ablative were analyzed with their own outcomes and downsides. Conclusions: Combined strategies and multidisciplinary protocols for BCRL, including specialized management by reconstructive surgeons and physiatrists, along with healthy lifestyle programs and personalized nutritional counseling, should be compulsory to address patients’ demands and optimize the treatment of this harmful and non-curable condition. The Lymphedema-specific ICF Core Sets should be included more often in the overall outcome evaluation with the aim of obtaining a comprehensive appraisal of the treatment strategies that take into account the patient’s subjective score. Full article

In novels, readers encounter a variety of characters with distinct personalities, and their satisfaction tends to increase when each character’s utterances consistently reflect their unique traits. Recent advances in large language model (LLM) technology have made it possible to perform complex tasks such as generating long-form narratives and adapting writing styles. However, research on generating character utterances that reflect individual personalities remains limited. In this paper, we identify a key challenge in this task, namely the unconscious influence of the author’s writing style, and propose a novel clustering-based method to mitigate this problem by tuning large language models. We manually annotated Big Five personality trait scores for characters appearing in selected novels and designed prompts to generate examples for instruction-tuning. Experimental results demonstrate that language models trained using our proposed method produce utterances that more consistently reflect character personalities compared to untuned models. Full article

Follicular lymphoma (FL) is one of the most common types of non-Hodgkin’s lymphomas. The tumor is characterized by a wide range of clinical manifestations, ranging from indolent forms to early transformation and progression with a poor prognosis. The search for clinically significant genetic changes is essential for personalized risk assessment and treatment selection. The CREBBP gene is frequently mutated in this type of lymphoma, with changes occurring at the level of the earliest tumor precursor cells. However, the prognostic and diagnostic significance of the CREBBP gene mutation status in FL has not been fully established. In this study, we analyzed sequencing data of exons 22–30 of the CREBBP gene in 86 samples from patients with different grades of FL (1–3B), including those in the 3A–3B subgroup without the t(14;18) translocation. We also investigated the prognostic significance of CREBBP gene mutations in relation to the treatment options, namely high-dose chemotherapy with autologous hematopoietic stem cell transplantation (HDCT/auto-HSCT) and conventional chemotherapy programs (CCT). It was found that FL patients with a single missense mutation in the KAT domain of the CREBBP gene experienced an extremely low number of early adverse events related to lymphoma and had better long-term survival rates, regardless of treatment option. In contrast, when comparing patients with FL without a missense mutation in the KAT domain or those with multiple mutations in the CREBBP gene, overall and progression free survival were worse, and early progression and histological transformation were more common. Compared to standard therapy, patients who underwent HDCT/auto-HSCT in the FL 1–3B (14;18)-positive group without a single missense mutation in the KAT domain had better survival rates and lower rates of transformation and early progression. In addition, among patients with FL 3A–3B (14;18)-negative, we found that there were no cases of a missense mutation in the KAT domain of the CREBBP gene. This suggests that a single missense mutation in the CREBBP gene may be a feature that discriminates 14;18-positive FL with a favorable prognosis from a high-risk disease. FL 3A–3B (14;18)-negative may represent a distinct variant with different biology and underlying mechanisms of development compared to classical FL. Full article

This paper presents an innovative exam-creation and grading system powered by advanced natural language processing and local large language models. The system automatically generates clear, grammatically accurate questions from both short passages and longer documents across different languages, supports multiple formats and difficulty levels, and ensures semantic diversity while minimizing redundancy, thus maximizing the percentage of the material that is covered in the generated exam paper. For grading, it employs a semantic-similarity model to evaluate essays and open-ended responses, awards partial credit, and mitigates bias from phrasing or syntax via named entity recognition. A major advantage of the proposed approach is its ability to run entirely on standard personal computers, without specialized artificial intelligence hardware, promoting privacy and exam security while maintaining low operational and maintenance costs. Moreover, its modular architecture allows the seamless swapping of models with minimal intervention, ensuring adaptability and the easy integration of future improvements. A requirements–compliance evaluation, combined with established performance metrics, was used to review and compare two popular multilingual LLMs and monolingual alternatives, demonstrating the system’s effectiveness and flexibility. The experimental results show that the system achieves a grading accuracy within a 17% normalized error margin compared to that of human experts, with generated questions reaching up to 89.5% semantic similarity to source content. The full exam generation and grading pipeline runs efficiently on consumer-grade hardware, with average inference times under 30 s. Full article

Burnout syndrome is characterized mainly by three criteria (emotional exhaustion, depersonalization, and low personal accomplishment), and further exacerbated by night shift work, with profound implications for individual and societal well-being. The Maslach Burnout Inventory survey applied to 97 medical care professionals (with day and night work) revealed different scores for these criteria. Blood metabolic profiles were obtained by UHPLC-QTOF-ESI⁺-MS untargeted metabolomics and multivariate statistics using the Metaboanalyst 6.0 platform. The Partial Least Squares Discrimination scores and VIP values, Random Forest graphs, and Heatmaps, based on 99 identified metabolites, were complemented with Biomarker Analysis (AUC ranking) and Pathway Analysis of metabolic networks. The data obtained reflected the biochemical implications of night shift work and correlated with each criterion’s burnout scores. Four main metabolic pathways with important consequences in burnout were affected, namely lipid metabolism, especially steroid hormone synthesis and cortisol, the energetic mitochondrial metabolism involving acylated carnitines, fatty acids, and phospholipids as well polar metabolites’ metabolism, e.g., catecholamines (noradrenaline, acetyl serotonin), and some amino acids (tryptophan, tyrosine, aspartate, arginine, valine, lysine). These metabolic profiles suggest potential strategies for managing burnout levels in healthcare professionals, based on validated criteria, including night shift work management. Full article

Major depressive disorder is a mental illness characterized by persistent sadness or loss of interest that affects a person’s daily life. Early detection of this disorder is crucial for providing timely and effective treatment. Neuroimaging modalities, namely, functional magnetic resonance imaging, can be used to identify changes in brain regions related to major depressive disorder. In this study, regional homogeneity images, one of the derivative of functional magnetic resonance imaging is employed to detect major depressive disorder using the proposed feature/sample evolving voting ensemble approach. A total of 2380 subjects consisting of 1104 healthy controls and 1276 patients with major depressive disorder from Rest-meta-MDD consortium are studied. Regional homogeneity features from 90 regions are extracted using automated anatomical labeling template. These regional homogeneity features are then fed as an input to the proposed feature/sample selective evolving voting ensemble for classification. The proposed approach achieves an accuracy of 91.93%, and discriminative features obtained from the classifier are used to identify brain regions which may be responsible for major depressive disorder. A total of nine brain regions, namely, left superior temporal gyrus, left postcentral gyrus, left anterior cingulate gyrus, right inferior parietal lobule, right superior medial frontal gyrus, left lingual gyrus, right putamen, left fusiform gyrus, and left middle temporal gyrus, are identified. This study clearly indicates that these brain regions play a critical role in detecting major depressive disorder. Full article

In Jer 15:19, Yhwh calls the prophet Jeremiah “my mouth”. This unique designation highlights his importance and finds support in several other features: Jeremiah is portrayed as the promised successor to Moses (Jer 1:7, 9), opposes all other contemporary prophets (e.g., Jer 20; 23; 26–29), and has many additional roles and activities. Furthermore, he shares traits with Yhwh’s servant from Isa 49 and 53. His ‘biography’ is extraordinary and is shown at length, unusual for the Latter Prophets, ranging from before his birth (Jer 1:5) to his disappearance in Egypt (Jer 43–44). His ‘confessions’ in Jer 11–20 testify to immense suffering and have become models for personal prayer. Like the prophet, his scroll is unique, too. No other biblical writing deals so extensively with trauma, exemplified at the downfall of Jerusalem in 587 BC, its roots, and its impact. This even leads to an uncommon structure of the scroll, ending with disaster in Jer 52, whereas all other scrolls of prophets contain hope as conclusions. Jer stands out with the analysis of guilt as cause for the catastrophe, yet it conveys also consolation, especially in Jer 29–33. In these chapters, elements for a renewed society emerge, corresponding to the name of the prophet, which signifies “Yhwh will raise up”. The real source for this change lies in the way Jer conceives the biblical God. No other writing in the Bible tells about his weeping, as a sign of helplessness vis-à-vis the continuing resistance of his people. Many prayers in the scroll, including the confessions, focus on the importance of an intimate, personal relationship with him, going beyond traditional piety in several aspects; Moshe Weinfeld has called them “spiritual metamorphosis”. The singularity of Jer applies also to its literary features. Its mixtures of poetry and prose, of divine and human speaking, of narratives about the prophet in first and third person are a challenge for every reader, as well as the ‘unordered’ chronology and retarded information. Jer excels in the use of other scrolls; the degree of intertextuality and the way of combining motifs from ‘foreign’ sources in a synthetic way are outstanding. To grasp fully its message requires familiarity with more than half of what later became the Hebrew Bible. Full article