Search Results (33)

Background: Gastrectomy for gastric cancer is associated with substantial metabolic, nutritional, and immunological disturbances that may significantly influence postoperative recovery. Increasing evidence suggests that perioperative immunonutritional status, particularly when assessed by the Controlling Nutritional Status (CONUT) score, represents an important predictor of surgical outcomes. However, prospective data evaluating sex-related differences in postoperative nutritional recovery after gastrectomy remain limited. The aim of this study was to evaluate sex-related differences in perioperative immunonutritional status and functional recovery after gastrectomy for gastric cancer using serial CONUT score assessment. Methods: This prospective observational cohort study included 150 consecutive patients undergoing curative-intent gastrectomy for gastric adenocarcinoma at a tertiary referral center between 2021 and 2024. Nutritional and immune status were longitudinally assessed using the CONUT score at predefined perioperative timepoints: preoperatively (T0), early postoperatively (T1), and at 3-month follow-up (T3). Functional recovery outcomes, postoperative complications, and mid-term functional parameters were compared between male and female patients. Multivariable logistic regression analysis was performed to identify independent predictors of delayed postoperative recovery. Results: The study population included 91 male patients (60.7%) and 59 female patients (39.3%). Significant postoperative deterioration in albumin levels, lymphocyte counts, total cholesterol, and CONUT scores were observed in the entire cohort (p-time < 0.001 for all comparisons), followed by partial recovery during follow-up. No significant sex-related differences were identified regarding longitudinal immunonutritional evolution, postoperative complications, gastrointestinal recovery, or functional outcomes (p > 0.05). Overall postoperative complications occurred in 31.3% of patients, while 90-day mortality was 2.7%. An elevated baseline CONUT score ≥ 5 (OR 2.74, 95% CI 1.48–5.09, p = 0.001), postoperative CONUT score T1 ≥ 5 (OR 3.36, 95% CI 1.82–6.19, p < 0.001), ASA class III (OR 2.08, 95% CI 1.19–3.63, p = 0.010), and anastomotic leakage (OR 4.91, 95% CI 1.74–13.88, p = 0.003) independently predicted delayed functional recovery. Male sex was not independently associated with adverse postoperative recovery (OR 1.18, 95% CI 0.74–1.89, p = 0.44). Conclusions: Gastrectomy induces significant postoperative immunonutritional deterioration irrespective of sex. Although biological sex did not independently influence postoperative recovery trajectories, impaired perioperative immunonutritional status—particularly elevated postoperative CONUT score—was strongly associated with delayed functional recovery. Serial perioperative CONUT assessment may represent a valuable tool for individualized postoperative risk stratification and nutritional management in gastric cancer patients undergoing gastrectomy. Full article

Plastic pollution has emerged as a critical global environmental challenge, driven by rising production, consumption, and inadequate waste management. Major plastic-consuming economies play a disproportionate role in global plastic leakage and therefore strongly influence international mitigation efforts. This review comparatively examines plastic policy frameworks in the European Union, the United States, China, India, and Japan to identify policy strengths, limitations, and transferable governance strategies. Due to the heterogeneous nature of the information sources, a narrative review methodology was employed, drawing on peer-reviewed literature, policy documents, institutional reports, and statistical datasets. Policy effectiveness was qualitatively evaluated using cross-comparable indicators, including per capita plastic consumption, waste generation, recycling rates, mismanaged waste, environmental leakage, and Extended Producer Responsibility (EPR) coverage. The analysis reveals substantial divergence in policy approaches: the EU demonstrates a comprehensive lifecycle-based framework with strong recycling performance and low leakage; China exhibits high enforcement capacity and effective upstream controls but faces scale-related challenges; the United States shows limited effectiveness due to fragmented governance and low recycling rates; India has robust regulatory intent but is constrained by high mismanaged waste and infrastructure gaps; and Japan achieves high downstream efficiency but relies heavily on thermal recycling with limited upstream reduction. The review highlights that effective plastic governance requires integrated lifecycle policies, strong enforcement, infrastructure investment, and international policy coordination rather than reliance on isolated downstream measures alone. Full article

Trans-border data circulation across multi-jurisdictional boundaries faces an operational conflict between ownership provenance prerequisites and data minimisation mandates, compounded by the tight coupling of large data payloads with synchronous state consensus ledgers, which forces replication of feature matrices across all consensus nodes and leads to network saturation. Existing frameworks remain unequipped to resolve this, as coupling in-band payload routing with synchronous state ledgers generates communication overheads scaling with data volume. The proposed Trusted Data Space with Registration (TDSR) implements a four-layer protocol stack. A dual-plane topology establishes a decoupled storage–ledger mechanism, partitioning asynchronous payload datastores and synchronous consensus ledgers to sustain throughput independent of data dimensionality. Navigating this infrastructure, the Unified Data Resource Identifier (UDRI) executes out-of-band cross-domain routing without exposing verifier intents. Driven by the Oblivious Data Asset Registration (ODAR) mechanism, a two-phase, four-algorithm lifecycle dictates end-to-end ownership provenance. This execution shifts hypothesis testing to isolated sandboxes via an algorithm-agnostic mathematical contract, capping external data transit at a constant leakage bound. A deployed testbed across the Guangdong-Hong Kong-Macao Greater Bay Area validates the proposed architecture, supporting data circulation across divergent legal jurisdictions. Full article

Background: Esophagectomy is associated with substantial postoperative morbidity, with infectious complications remaining a leading cause of mortality. Septic shock represents the most severe infectious complication; however, data on its perioperative predictors and long-term impact after esophagectomy are limited. Methods: We conducted a retrospective observational study including consecutive adult patients who underwent esophagectomy with curative intent for esophageal cancer between January 2015 and December 2024 at a tertiary referral center. Postoperative septic shock was defined according to Sepsis-3 criteria. Demographic, clinical, surgical, laboratory, and oncological variables were analyzed. Independent risk factors for septic shock were identified using multivariate logistic regression. Overall survival was assessed using Kaplan–Meier analysis. Results: Among 106 patients, 19 (17.9%) developed postoperative septic shock. These patients had a lower body mass index, reduced preoperative and postoperative albumin levels, and a higher incidence of advanced lymph node involvement. Septic shock was strongly associated with severe postoperative complications, including anastomotic leakage, hemorrhagic shock, acute respiratory distress syndrome, acute kidney failure, and increased rates of PICU readmission. In multivariate analysis, lower albumin levels at PICU admission (OR 0.54; 95% CI 0.29–0.99) and advanced nodal stage (OR 4.98; 95% CI 1.36–18.3) were independently associated with the development of septic shock. Patients who developed septic shock had significantly higher in-hospital mortality (31.6% vs. 1.1%, p < 0.001) and markedly reduced long-term survival, even among those discharged alive. Conclusions: Postoperative septic shock after esophagectomy is a devastating complication with a profound negative impact on both short- and long-term survival. Hypoalbuminemia and advanced lymph node involvement are independent predictors of septic shock. These findings support the integration of simple clinical and laboratory markers into personalized perioperative risk stratification models, enabling individualized management strategies to reduce severe postoperative complications. Full article

As a common brain-computer interface (BCI) paradigm, electroencephalogram (EEG)-based motor imagery provides a critical pathway for both assistive technology to (restoring communication and control) and active rehabilitation (promoting neural plasticity and functional recovery). Domain adaptation has been shown to effectively enhance the decoding performance of motor intentions for target subjects by leveraging labeled data from source subjects. However, EEG data from source subjects often contains extensive personal privacy, and the direct access to source EEG data easily leads to privacy leakage issues. An important research topic is to achieve domain adaptation without directly accessing the source subjects’ raw data. To address this challenge, a privacy-preserving source-free domain adaptation framework, termed Transformer-based SFDA with Class-balanced Multicentric Dynamic Pseudo-labeling (T-CMDP), is proposed for cross-subject motor-imagery EEG classification. This framework consists of three coupled stages. In the source model training stage, a Transformer-based encoder combined with Riemannian manifold-aware feature extraction is employed to learn transferable and discriminative EEG feature representations. In the source-free target adaptation stage, only the pretrained source model is transferred to the target domain and adapted through knowledge distillation and information maximization, without accessing raw source EEG data. In the self-supervised learning stage, class-balanced multicentric prototypes and high-confidence pseudo-label updates are introduced to progressively refine the target-domain decision boundaries. Extensive experiments on three motor-imagery EEG datasets demonstrate that the proposed T-CMDP framework consistently outperforms eleven representative baselines from traditional machine learning, deep learning, and source-free transfer approaches, achieving average accuracies of 56.85%, 76.34%, and 74.49%, respectively. These results indicate that T-CMDP effectively alleviates inter-subject EEG distribution discrepancies and ensures the privacy preserving of source subjects, thereby facilitating more reliable and practical deployment of EEG-based BCI systems. Full article

Background/Objectives: Post-hepatectomy liver failure is one of the most serious complications after liver resection for hepatocellular carcinoma and is associated with high morbidity and mortality. Traditional clinical scoring systems and statistical models provide limited predictive accuracy. This study aimed to develop and internally validate a deep learning model for predicting post-hepatectomy liver failure using multicenter clinical data. Methods: A retrospective cohort of 498 patients from six centers undergoing curative-intent liver resection for hepatocellular carcinoma was analyzed. Preoperative biochemical parameters, intraoperative surgical variables, and tumor-related characteristics were incorporated into a deep neural network, with logistic regression as a baseline comparator. Data splitting was performed before preprocessing, and imputation/scaling parameters were fitted on the training set only to prevent information leakage. Discrimination was assessed using the area under the receiver operating characteristic curve (AUC) and precision–recall (PR) curves; calibration was assessed using calibration plots and Brier score; and clinical utility was assessed using decision curve analysis (DCA). A sensitivity analysis using a preoperative-only feature set (excluding intraoperative variables) was also conducted. SHapley Additive exPlanations were used to determine variable importance. Results: The deep learning model achieved AUCs of 0.914, 0.892, and 0.906 in the training, validation, and test sets, outperforming logistic regression (0.782, 0.757, and 0.773). Key predictors included ALBI and MELD scores, prothrombin time, intraoperative blood loss, and resection extent. Calibration and decision curve analysis further supported the robustness and clinical utility of the model. Conclusions: The deep learning model provides improved predictive performance for post-hepatectomy liver failure compared with logistic regression in an internally validated multicenter cohort and may support perioperative risk stratification and surgical planning. Full article

Insider threats remain one of the most challenging security risks in modern enterprises due to their subtle behavioral patterns and the difficulty of distinguishing malicious intent from legitimate activity. This paper presents a unified and adaptive generative framework for insider threat detection that integrates Variational Autoencoders (VAEs) and Transformer Autoencoder architectures to learn personalized behavioral baselines from sequential user event logs. Anomalies are identified as significant deviations from these learned baseline distributions. The proposed framework incorporates an adaptive learning mechanism to address both cold-start scenarios and concept drift, enabling continuous model refinement as user behavior evolves. In addition, we introduce a privacy-preserving latent-space design and evaluate the framework under formal privacy attacks, including membership inference and reconstruction attacks, demonstrating strong resilience against data leakage. Experiments performed on the CERT Insider Threat Dataset (v5.2) show that our approach outperforms traditional and deep learning baselines, with the Transformer Autoencoder achieving an F1-score of 0.66 and an AUPRC of 0.59. The results highlight the effectiveness of generative sequence models for privacy-conscious and adaptive insider threat detection in enterprise environments, providing a comparative analysis of two powerful architectures for practical implementation. Full article

Sequential recommendations seek to predict the next item a user will interact with by modeling historical behavior, yet most approaches emphasize either temporal dynamics or item relationships and thus miss how structural co-intents interact with dynamic preference shifts under realistic evaluation. IntentGraphRec introduces a dual-level framework that builds an intent graph from session co-occurrences to learn intent-aware item representations with a lightweight GNN, paired with a shift-aware Transformer that adapts attention to evolving preferences via a learnable fusion gate. To avoid optimistic bias, evaluation is performed with a leakage-free, full-catalog ranking protocol that forms prefixes strictly before the last target occurrence and scores against the entire item universe while masking PAD and prefix items. On MovieLens-1M and Gowalla, IntentGraphRec is competitive but does not surpass strong Transformer baselines (SASRec/BERT4Rec); controlled analyses indicate that late fusion is often dominated by sequence representations and that local co-intent graphs provide limited gains unless structural signals are injected earlier or regularized. These findings provide a reproducible view of when structural signals help, and when they do not, in sequential recommendations and offer guidance for future graph–sequence hybrids. Full article

This study critically examines the methodological rigor in credit card fraud detection research, revealing how fundamental evaluation flaws can overshadow algorithmic sophistication. Through deliberate experimentation with improper evaluation protocols, we demonstrate that even simple models can achieve deceptively impressive results when basic methodological principles are violated. Our analysis identifies four critical issues plaguing current approaches: (1) pervasive data leakage from improper preprocessing sequences, (2) intentional vagueness in methodological reporting, (3) inadequate temporal validation for transaction data, and (4) metric manipulation through recall optimization at precision’s expense. We present a case study showing how a minimal neural network architecture with data leakage outperforms many sophisticated methods reported in literature, achieving 99.9% recall despite fundamental evaluation flaws. These findings underscore that proper evaluation methodology matters more than model complexity in fraud detection research. The study serves as a cautionary example of how methodological rigor must precede architectural sophistication, with implications for improving research practices across machine learning applications. Compared to several recent studies reporting near-perfect recall (often exceeding 99%) using complex deep models, our corrected evaluation with a simple MLP baseline yields more modest but reliable metrics, exposing the overestimation common in flawed pipelines. Full article

Background/Objectives: Catheter-related bladder discomfort (CRBD) commonly occurs in patients undergoing urologic surgery and significantly affects patient comfort and recovery. We evaluated the efficacy and safety of continuous local ropivacaine infusion using a specialized multi-porous urethral catheter in reducing postoperative CRBD. Methods: This multicenter, prospective, randomized, single-blind trial enrolled 136 male patients undergoing short-term catheterization after urologic surgery. Participants were randomized into three groups—a control group receiving saline infusion, Group 1 receiving 0.5% ropivacaine at 1 mL/h, and Group 2 receiving 0.5% ropivacaine at 2 mL/h—for up to 48 h via a multi-porous urethral catheter. The primary outcome was the incidence of CRBD at 24 h postoperatively. Secondary outcomes included changes in urethral pain assessed by a visual analog scale (VAS), urinary symptom scores, complication rates, and patient-reported catheter inconvenience and reuse intention using Likert scales. Results: The incidence of CRBD was significantly lower in Group 1 (19.6%) and Group 2 (11.1%) compared to the control group (44.4%; p = 0.001), demonstrating a clear dose–response relationship. Changes in urethral pain scores (VAS) from baseline were significantly lower in the ropivacaine groups compared to the control (p = 0.023). Complication rates were similar among groups (control 13.3%, Group 1 6.5%, Group 2 15.6%; p = 0.378), although catheter leakage occurred more frequently in Group 2, without statistical significance (p = 0.122). Conclusions: Continuous local ropivacaine infusion using a multi-porous urethral catheter effectively reduces the incidence of postoperative CRBD without increasing side effects. This approach may improve patient comfort during perioperative catheter management. Full article

Smart homes offer promising opportunities for risk prevention in private households, especially concerning safety and health. For instance, they can reduce safety risks by detecting water leakages quickly and support health by monitoring air quality. Current research on smart home technology predominantly focuses on usability, performance expectations, and cyber risks, overlooking the potential importance of risk prevention benefits to prospective users. We address this gap by utilizing data from a recent survey to construct a structural equation model. Our overarching hypothesis is that prevention benefits and comfort considerations positively influence adoption. The results confirm the relevance of comfort, as suggested by previous research. In addition, the results reveal significant prevention benefits in safety and health, which are positively related to technology expectations and the intention to adopt smart homes. Furthermore, newly included variables such as technology affinity and active aging lifestyle emerge as indicators of potential smart home users, extending the knowledge of user characteristics beyond traditional sociodemographic indicators. The findings contribute to filling a gap in the current risk and technology literature and are also relevant for smart home device manufacturers and risk and insurance practitioners looking to evolve their business models. Full article

The exponential growth and widespread adoption of Internet of Things (IoT) devices have introduced many vulnerabilities. Attackers frequently exploit these flaws, necessitating advanced technological approaches to protect against emerging cyber threats. This paper introduces a novel approach utilizing hardware honeypots as an additional defensive layer against hardware vulnerabilities, particularly hardware Trojans (HTs). HTs pose significant risks to the security of modern integrated circuits (ICs), potentially causing operational failures, denial of service, or data leakage through intentional modifications. The proposed system was implemented on a Raspberry Pi and tested on an emulated HT circuit using a Field-Programmable Gate Array (FPGA). This approach leverages hardware honeypots to detect and mitigate HTs in the IoT devices. The results demonstrate that the system effectively detects and mitigates HTs without imposing additional complexity on the IoT devices. The Trojan-agnostic solution offers full customization to meet specific security needs, providing a flexible and robust layer of security. These findings provide valuable insights into enhancing the security of IoT devices against hardware-based cyber threats, thereby contributing to the overall resilience of IoT networks. This innovative approach offers a promising solution to address the growing security challenges in IoT environments. Full article

This study defines the intrinsic and extrinsic motivational factors that influence the prevention of industrial technology leakage by high-tech company employees. It also investigates how these factors affect the employees’ intention to prevent leakage. Based on the TPB (theory of planned behavior), this study analyzes the relationship between “attitude toward behavior”, “subjective norm”, and “perceived behavioral control”, which in turn influences the behavioral intention to prevent such leakage. Specifically, an online survey was conducted among office workers in South Korea’s high-tech industry. A total of 200 questionnaires were collected and analyzed. As the analysis results show, intrinsic motivation has a positive effect on attitude toward behavior, subjective norms, and perceived behavioral control. Extrinsic motivation has a positive effect on subjective norms and perceived behavioral control but a negative effect on attitudes toward behavior. This study also proved, based on the TPB, that the three variables impact the behavioral intention to prevent technology leakage. These results confirm that, in the high-tech sector, where employees are highly specialized and autonomous, technical security behaviors are primarily influenced by individual professional ethics and judgment rather than by organizational regulation or extrinsic motivation. Full article

Background: The global shift from open esophagectomy (OE) to minimally invasive esophagectomy (MIE) for treating esophageal cancer is well-established. Recent data indicate that transitioning from hybrid minimally invasive esophagectomy (hMIE) to total minimally invasive esophagectomy (tMIE) can be challenging due to concerns about higher leakage rates and lower lymph node counts, especially at the beginning of the learning curve. This study aimed to demonstrate that a safe transition from OE to tMIE for cancer is possible using process management methodology. Methods: A step-change approach was adopted in process management planning, with hMIE serving as an intermediate step between OE and tMIE. This single-center, case–control study included 150 patients who underwent the Ivor Lewis procedure with curative intent for esophageal cancer. Among these patients, 50 underwent OE, 50 hMIE (laparoscopic procedure followed by conventional right thoracotomy), and 50 tMIE (laparoscopic and thoracoscopic approach). A preceptored training scheme was implemented during execution, and treatment results were monitored and controlled to ensure a safe transition. Results: During the transition, the tMIE group was not worse than the hMIE and OE groups regarding operation duration (p = 0.135), overall postoperative complications (p = 0.020), anastomotic leakage rates (p = 0.773), 30-day mortality (p = 1.0), and oncological outcomes (based on R status (p = 0.628) and 2-year survival (p = 0.967)). Additionally, the tMIE group showed superior results in terms of major postoperative pulmonary complications (p = 0.004) and ICU stay duration (p < 0.001). Conclusions: Utilizing managerial methodology and practice in surgery, as a bridge between interdisciplinary and transdisciplinary approaches, demonstrated that transitioning from OE to tMIE, with hMIE as an intermediate step, is safe and feasible without compromising outcomes. Full article

For a large benign lesion within the maxillary sinus, such as an antral pseudocyst, maxillary sinus floor augmentation is more commonly performed using a two-stage approach. This involves first removing the lesion, and then, re-entry following several months of healing. In this case series, we described the “one-bony-window” approach, which is a technical surgical modification of the previous one-stage approach, for simultaneous cyst removal and maxillary sinus floor augmentation. Four patients with large maxillary antral pseudocysts were included. The “one-bony-window” approach involves the preparation of a large window opening of approximately 15 mm × 20 mm at the lateral wall. A mesiodistally extended intentional perforation was made in the upper part of the exposed membrane to enhance the access for instrumentation. The antral pseudocyst was removed in its entirety without being deformed to prevent rupture or leakage of the cystic contents. Subsequent detachment and elevation of the Schneiderian membrane at the sinus floor significantly reduced the perforation site, and bone grafting with implant placement was performed simultaneously. This alleviated the need to surgically repair the perforation. The lateral opening was either uncovered or repositioned using bony window lids. Healing abutments were connected after six months, and the final prosthesis was placed after two months. At the 1-year follow-up, the antral pseudocysts had resolved with no specific recurrence, and the stability of the augmented sinus was maintained with excellent implant survival. Within the limitations of our findings, the “one-bony-window” technique can be suggested for the simultaneous removal of large antral pseudocysts and maxillary sinus floor augmentation with favorable clinical outcomes. Full article