Search Results (3,147)

Automated legacy code modernization using Large Language Models lacks rigorous evaluation frameworks and multi-objective quality assessment methodologies. Existing research suffers from three critical deficiencies: single-metric evaluation paradigms creating pathological optimization incentives, statistical validation limited to p-values without effect size analysis, and absence of systematic transformation pattern taxonomies explaining what works and why. We present a novel multi-objective statistical framework that jointly assesses Cyclomatic Complexity (CC) and Maintainability Index (MI) while providing comprehensive effect size analysis addressing software engineering research gaps. Applied to 47 legacy Java samples from Apache Ant (version 1.10.x, commit rel/1.10.14), our framework achieves 97.9% metric-level improvement with very large practical effects (Cohen’s $d=1.86$, 95% CI [1.36, 2.35], $p<0.0001$) for maintainability—substantially exceeding prior work and conventional significance thresholds. We note that this success rate reflects quality metric improvement; functional equivalence was verified through syntactic validation and manual inspection of a 20% random sample, while comprehensive automated test-based verification remains a limitation addressed in future work. We contribute: (1) first multi-objective quality assessment framework for code modernization with weighted composite scoring and sensitivity analysis, (2) rigorous statistical methodology with effect size analysis beyond p-values, (3) systematic transformation pattern taxonomy identifying four successful patterns and three failure modes with predictive value (inter-rater agreement $\kappa =0.82$), and (4) negative result showing iterative refinement provides no benefit ($d=0.08$, $p=0.179$), saving community resources. Our transformation taxonomy enables practitioners to predict success likelihood from code characteristics, while our statistical framework provides replicable methodology for evaluating LLM-based software engineering tools. The very large effect size indicates metric-level improvements are materially meaningful for real-world software maintenance, not merely statistically detectable. Full article

To address the limitations of static message aggregation and training instability in the existing Shared Neural Normalized Min-Sum (SNNMS) algorithm, this paper proposes A-SNNMS, an attentive deep LDPC decoding network with adaptive training. First, an attention mechanism is introduced into the variable node update phase to dynamically weight incoming messages based on their reliability, effectively suppressing noise interference. Second, a collaborative training scheme incorporating an exponential decay adaptive learning rate and L2 regularization is designed to mitigate convergence oscillation and overfitting in long-code training. Simulation results for IEEE 802.16e standard codes demonstrate that A-SNNMS achieves a net coding gain of approximately 0.4 dB over the baseline SNNMS at a Bit Error Rate (BER) of 10⁻³. Furthermore, it achieves comparable performance with only 50% of the iterations required by the baseline. In conclusion, the A-SNNMS decoder significantly improves both decoding efficiency and system robustness, offering a promising solution for high-reliability communications. Full article

The coelomic cavity of sea turtles is affected by congenital, developmental, traumatic, infectious, and organ- or system-specific disorders, making accurate anatomical knowledge essential for veterinary practice. This study presents an open-access, interactive two-dimensional (2D) anatomical atlas of the coelomic cavity of the loggerhead sea turtle (Caretta caretta), developed using images obtained from osteology, gross anatomical dissections, computed tomography (CT), and magnetic resonance imaging (MRI). The atlas comprises six osteology images, sixteen anatomical dissection images, eight transverse CT images acquired using bone and soft-tissue windows, six three-dimensional (3D) volume-rendered CT images, and fourteen MRI images (four transverse, five dorsal, and five sagittal), all provided in PNG format. Relevant anatomical structures were segmented and colour-coded for each figure using manual layer-based segmentation software. The Unity 3D platform was employed for image visualisation and assessment, supporting the development of interactive two-dimensional content. This atlas serves as a useful interactive tool for anatomical learning and clinical reference for professionals and students engaged in the conservation of loggerhead sea turtles. Full article

The Italian peninsula is, as shown by satellite and ground-based measurements, a pollution hotspot. In recent years, ground-based MAX-DOAS commercial systems have been installed in the Po Valley and the area surrounding Rome to monitor NO${}_2$ tropospheric column densities and validate coincident satellite (e.g., TROPOMI) products. Three of the instruments are located in the Po Valley at San Pietro Capofiume (Bologna), Bologna city, and Mount Cimone (Modena), and one is located in Tor Vergata (Rome). The chosen system is the SkySpec-2D from Airyx. All the recorded spectra are saved in the FRM4DOAS format and processed with QDOAS software to obtain slant column densities (SCDs) of NO${}_2$, O${}_4$, and other trace gases. The MAX-DOAS SCD sequences are then analysed with the DEAP code to retrieve tropospheric profiles of NO${}_2$ and aerosol extinction, while zenith-sky SCDs are used to retrieve NO${}_2$ total columns. A dedicated campaign, involving the network instruments, has been conducted in the Po Valley to compare the performance of the individual instruments in the network with respect to the one that participated in the CINDI-3 campaign (Cabauw, the Netherlands). The results of the intercomparison campaign indicated that all instruments showed comparable performance. As an example of obtainable products, one year (from September 2024 to August 2025) of NO${}_2$ tropospheric columns, as well as their comparison with TROPOMI measurements, is presented, highlighting the potential of this network for both air quality studies and satellite validation. Due to Italy’s location in the highly complex Mediterranean hotspot region, these data represent an important contribution to satellite validation efforts, particularly in view of upcoming missions such as Copernicus Sentinel-4, Sentinel-5, and the Copernicus Anthropogenic Carbon Dioxide Monitoring (CO2M) constellation. We found a negative TROPOMI bias relative to SkySpec-2D for NO${}_2$ tropospheric columns ranging from −13% in San Pietro Capofiume, to −25% in Bologna and −44% in Rome Tor Vergata. The comparison between NO${}_2$ total columns from TROPOMI and SkySpec-2D at Mount Cimone shows generally good agreement, with TROPOMI being 15% higher. Full article

Longwall top coal caving is one of the most effective methods for extracting steeply inclined and ultra-thick coal seams. To investigate the influence of caving ratio (the proportion between mining height and top coal thickness) on top coal recovery behavior and ground pressure characteristics, this study employs both the Particle Flow Code (PFC) discrete element method and a coupled FLAC^3D–PFC^3D numerical simulation approach. The effects of different caving ratios (1:3, 1:3.2, and 1:3.4) on the top coal recovery ratio, stress distribution, and gangue accumulation characteristics were analyzed. The results show that the caving ratio has a significant impact on top coal recovery. At a caving ratio of 1:3.2, adopting a two-cut-one-cave interval resulted in a top coal recovery ratio as high as 94.8%. A stress-relief zone with an arch-like distribution formed above the goaf, while a stress concentration zone developed ahead of the coal wall, where the coal–rock mass underwent compression and failure. The roof displacement exhibited an arch-shaped distribution, while the floor displacement was asymmetrical, with greater heaving observed at the lower end. As the working face advanced, the horizontal development of the plastic zone expanded rapidly, while the vertical extent changed only slightly. Throughout the caving process, the top coal demonstrated favorable caving behavior with good flowability and accumulation characteristics. These findings provide theoretical support for achieving high mining recovery in thick coal seam operations and offer practical guidance for optimizing caving process parameters in practice. Full article

Colorectal cancer (CRC) continues to represent a substantial worldwide health burden. Accurate risk classification and early detection have a significant impact on prognosis. There is still a significant percentage of patients who are diagnosed at advanced stages, notwithstanding the progress that has been made in screening and treatment. Thus, improved molecular tools that encompass the biological complexity of CRC are needed. High-throughput technologies have expanded the biomarker array for CRC screening, prognosis, and therapeutic prediction. This review summarizes evidence on established and emerging molecular tools from tumor tissue, blood, and stool samples, such as DNA mutations, methylation markers, RNA signatures, circulating tumor DNA (ctDNA), circulating cell-free DNA (cfDNA), extracellular vesicles, and multi-omic composite assays. These provide alternatives to conventional approaches that are relatively less invasive and more sensitive. Prognostic biomarkers—such as RAS, BRAF, HER2 alterations, mismatch repair deficiency, tumor mutational burden, methylation signatures, and non-coding RNAs—provide insight into tumor behavior and recurrence risk. To guide targeted therapies, immunotherapies, and chemotherapy response, predictive biomarkers such as RAS/BRAF mutations, HER2 amplification, MSI-H/dMMR status, POLE/POLD1 mutations, DNA methylation panels, miRNAs, lncRNAs, and liquid biopsy markers are crucial. Emerging technologies such as multi-omics, AI-enhanced biomarker discovery, and novel liquid biopsy components (evDNA, circRNAs) pave the way to precision oncology. These molecular tools have the potential to change how CRC is managed by earlier detection and more precise predictive biomarkers. However, large-scale validation and clinical standardization are still crucial for their extensive utilization. Full article

Background/Objectives: An accurate description of facial sexual dimorphism is essential in clinical, forensic, and anthropological contexts to support accurate diagnosis of craniofacial dysmorphisms and differences, treatment planning and evaluation, as well as biological profiling, craniofacial reconstruction, and personal identification. This study investigates sexual dimorphism of the facial soft tissues in a sample of healthy Italian adults, providing reference data and deepening our understanding of normal craniofacial variation. Methods: Three-dimensional stereophotogrammetric facial images of 342 Italian adults (172 males and 170 females; 18–40 years old) were analyzed using a 3D spatially dense geometric morphometric approach to assess both shape and form. Principal Component Analysis (PCA) and Partial Least Squares Regression (PLSR) were used to explore facial variation and to quantify sex-related differences. Results: Centroid size was significantly larger in males. While PCA revealed that sex is a significant factor in facial shape and form variation, PLSR highlighted the existence of significant associations between sex and both shape and form. Color-coded morphometric maps underlined the most sexually dimorphic traits: males exhibited bigger faces with deep-set eyes and central facial projection extending from the supraorbital rims to the chin, whereas females display smaller faces with fuller cheeks, and a more vertical forehead profile. Conclusions: While our results are consistent with those of previous studies, our study revealed important, distinctive group-specific traits: flatter labiomandibular folds in males and wider temples and fuller cheeks in the infraorbital region extending to zygomatic and mandibular areas in females. Thus, this study provides high-resolution reference data supporting related applications. Full article

This study investigates the complex relationship between fracture patterns and acoustic emission (AE) mechanisms during triaxial deformation experiments on Westerly granite under various confining pressures (5, 10, 20, and 40 MPa). Using numerical simulations with the Particle Flow Code (PFC2D, 6.0, Itasca Consulting Group Inc, Minneapolis, USA), this research emphasizes the significant influence of confining pressure on crack development, AE events, spatiotemporal distribution, energy dissipation, and peak stress in the samples. AE source mechanisms, categorized into T-Type, C-Type, and S-Type, show the dominance of T-Type fractures during post-peak unstable failure and the emergence of C-Type fractures as precursors to critical damage. Additionally, increasing confining pressure is found to correlate with changes in fracture dynamics, evidenced by an increase in big events and a decrease in small events. The analysis of b-values across different pressures reveals fluctuations that indicate change in fracture features. Fractures originate in the model center and propagate towards both ends as loading progresses, ultimately leading to failure. In summary, these findings provide important insights into the fracture patterns of granite and the underlying mechanisms of AE release. Moreover, they carry practical implications for identifying failure precursors and for the potential application of early warning systems in rock engineering. Full article

Background/Objectives Sports-related musculoskeletal injuries remain a major challenge in physically active populations, with substantial interindividual variability in susceptibility and recovery that cannot be fully explained by biomechanics or genetics alone. Epigenetic mechanisms, including DNA methylation, histone modifications, and non-coding RNAs, provide a dynamic interface through which mechanical loading, inflammation, and metabolic signals regulate gene expression during tissue adaptation and repair. This narrative review synthesizes current evidence on “epigenetically active” dietary supplements and their potential relevance to sports injuries, focusing on methyl donors, polyphenols, omega-3 fatty acids, vitamin D, and redox-active nutrients. Methods Targeted searches of PubMed, Scopus, and Web of Science (2000–2026) were performed using epigenetics-, injury-, exercise-, and supplementation-related terms, prioritizing mechanistic and translational evidence. Results Available data indicate that these compounds can influence molecular mechanisms implicated in musculoskeletal recovery. However, human evidence is largely derived from peripheral tissues and indirect molecular markers, with limited clear linkage to clinically significant injury outcomes such as injury incidence, severity, or return-to-play timelines. Accordingly, these nutrients are best viewed as modulators of recovery-related biology rather than as direct therapeutic agents. Conclusions This review highlights a notable translational gap between mechanistic plausibility and clinical evidence and discusses practical implications for sports nutrition from a personalized perspective. Future research priorities include tissue-relevant epigenetic assessments, integration of multi-omics approaches, and longitudinal trials incorporating injury endpoints. Nutritional epigenomics, therefore, represents a promising avenue to support musculoskeletal health while underscoring the need for rigorous clinical validation. Full article

To compare the mechanical performance differences between sleeve grouting lap and butt joints, a total of 41 lap joints, including 27 standard lap joints and 14 anti-deflection lap joints, and 20 butt joints were subjected to tensile and high-stress cyclic tensile-compression tests. The results indicate that both types of joints failed by tensile fracture of the rebars in uniaxial tension, with the load-bearing capacity, total elongation at maximum force, and ductility generally meeting the code requirements. In high-stress cyclic tests, the load-bearing capacity of both types of joints increased, while the initial stiffness and ductility decreased. The residual deformation of the anti-deflection lap joints and butt joints generally met the specification requirements. Anti-deflection measures can reduce the residual deformation of lap joints; however, their constraint stiffness is limited, resulting in slightly greater residual deformation of lap joints compared to butt joints. After the completion of the high-stress cyclic tensile–compression tests, the maximum longitudinal strain near the reinforcement side of the sleeve’s middle cross-section in lap joints and the absolute value of the maximum circumferential compressive strain were both less than those in butt joints, indicating that lap joints have lower tensile performance requirements for the sleeve. Based on experimental results, a lap length of 12.5 d is recommended, with an additional 4–6 d allowance to enhance splice reliability under high-stress cyclic loading. Full article

Background: Obesity is traditionally defined by excess fat mass; however, the preservation of fat-free mass (FFM), particularly skeletal muscle, has gained increasing relevance due to its metabolic, endocrine, and functional roles. Weight loss interventions, including hypocaloric diets, pharmacological treatments, and bariatric surgery, are frequently associated with unintended loss of skeletal mass, increasing the risk of sarcopenic obesity and related complications. Objective: This study aimed to systematically evaluate the effectiveness of whey protein supplementation in preserving fat-free mass and muscle-related outcomes in adults with obesity undergoing weight loss interventions. Methods: A systematic review was conducted in accordance with PRISMA guidelines. Randomized controlled trials published in English were identified through searches of PubMed/MEDLINE, CENTRAL, Embase, Scopus, ClinicalTrials.gov, and WHO ICTRP, searched up to September 2025. Eligible studies included adults (>18 years) with obesity receiving whey protein supplementation as part of a hypocaloric diet, compared with placebo or standard interventions. Primary outcomes were changes in fat-free mass assessed by validated methods (DXA, BIA, MRI), while secondary outcomes included body weight, fat mass, metabolic parameters, adherence, and safety. Risk of bias was assessed using the Cochrane RoB 2.0 tool, and certainty of evidence was evaluated with GRADE. The abstract was registered in PROSPERO with code CRD420251069996. There was no funding and no conflicts of interest. Results: Fourteen randomized controlled trials were included. Whey protein supplementation generally supported the maintenance or modest improvement of fat-free mass, particularly when combined with resistance exercise or anabolic-enriched formulations such as leucine or vitamin D. Several trials, however, reported neutral effects, especially in the absence of structured physical activity. Overall, effect estimates ranged from small gains to null or uncertain differences, and the certainty of evidence was frequently downgraded due to limited sample sizes, wide confidence intervals, heterogeneity across interventions and assessment methods, short follow-up periods, and methodological limitations including open-label designs and inconsistent adherence monitoring. Conclusions: Whey protein supplementation may support fat-free mass preservation during weight loss in adults with obesity, particularly as part of a multimodal intervention. Further high-quality trials are needed to define optimal dosing strategies and target populations. Full article

Food waste is a major global problem that worsens food insecurity and contributes to environmental challenges and resource depletion. Reducing food waste, especially before it reaches consumers, is a crucial strategy for combating food insecurity and advancing environmental sustainability. This scoping review examines the factors, impacts, and practices related to food loss and waste (FLW) in the pre-consumption stage of the U.S. supply chain using a predefined coding scheme. A machine learning technique (i.e., topic modeling) was used to supplement the manual coding to identify themes. Findings from 104 articles from 2015 to 2024 revealed that (a) macro and micro-level factors were understudied; (b) impacts of FLW were predominantly assessed in terms of environmental consequences, with less attention given to economic, social, cultural, and political impacts; (c) despite the high concentration on donation, prevention, recovery, and recycling as solutions, there were critical gaps in the exploration of policy and regulatory strategies, as well as education and awareness; and (d) minimization is the most dominant approach compared to prevention. We recommend that more research focus on causes of food loss, economic, social, cultural, and political impacts, policy and regulatory strategies, as well as education and awareness. We also recommend shifting from weak minimization efforts to strong prevention practices, emphasizing cooperation among all participants in the supply chain. Full article

In molecular communication via diffusion (MCvD) uplinks where multiple nano-sensors report concurrently to a fusion center (FC), the long channel memory and the near–far imbalance jointly create strong multiple access interference (MAI) coupled with residual inter-symbol/inter-chip effects. This paper studies an oversampling-enabled time-domain reception for an uplink molecular code-division multiple-access (MoCDMA) system employing bipolar molecular signalling. By exploiting intra-chip oversampling at the FC, three linear detectors following the principles of maximum ratio combining (MRC), zero-forcing (ZF), and minimum mean-square error (MMSE) are developed and further enhanced through a feedback-assisted interference subtraction (FAIS) scheme that combines single-tap ISI feedback equalization with near-to-far successive MAI subtraction. Owing to the complementary structure of bipolar molecular emissions, the signal-dependent counting noise corresponding to the two molecule types can be jointly modeled in a symmetric and information-independent manner to support unified linear detection and FAIS processing. Numerical results demonstrate that oversampling effectively improves detection reliability, while increasing the molecular emission budget alone is insufficient to mitigate near–far effects. Moreover, FAIS provides significant performance gains, particularly for far NSs. Full article

In the Middle East and North Africa (MENA) region, the prevalence of Type 2 Diabetes (T2D) is 17–18%, substantially higher than the ~9–10% reported in Western populations, with some Gulf states approaching 25% in adults. Historically, Arab diets, characterized by high fiber intake from whole grains, legumes, and fermented dairy products, have contrasted markedly with the Western dietary pattern increasingly prevalent among urbanized Arab populations. These nutritional shifts have been associated with changes in gut microbial composition, including lower representation of short-chain fatty acid–producing bacteria and higher abundance of dysbiosis-associated taxa. Concurrently, diet-derived compounds and microbial metabolites have been associated with changes in DNA methylation, histone modifications, and non-coding RNA expression. Epigenome-wide association studies revealed both shared and population-specific methylation signatures in patients with T2D. However, integrated multi-omics studies remain limited in Arab populations, where the disease burden is highest. This review integrates emerging evidence on diet-linked epigenetic alterations, microbiome-associated metabolic pathways, and their intersection in potentially contributing to T2D risk and progression. Given the heterogeneity of T2D across populations, there is a pressing need for culturally contextualized precision medicine frameworks that integrate population-specific diet–microbiome–epigenome dynamics rather than extrapolating findings across populations. Additionally, this review synthesizes evidence that dietary patterns are associated with T2D-relevant pathways through the diet–microbiome–epigenome axis, with emphasis on Arab/MENA populations and Western comparator cohorts. Full article

The integration of wearable inertial measurement units (IMU) in animal welfare Internet of Things (IoT) systems has become crucial for monitoring animal behaviors and enhancing welfare management. However, the vulnerability of IoT devices to network and hardware attacks poses significant risks, potentially compromising data integrity and misleading caregivers, negatively impacting animal welfare. Additionally, current animal monitoring solutions often rely on intrusive tagging methods, such as Radio Frequency Identification (RFID) or ear tagging, which may cause unnecessary stress and discomfort to animals. In this study, we propose a lightweight integrity and provenance-oriented security stack that complements standard transport security, specifically tailored to IMU-based animal motion IoT systems. Our system utilizes a 1D-convolutional neural network (CNN) model, achieving 88% accuracy for precise motion recognition, alongside a lightweight behavioral fingerprinting CNN model attaining 83% accuracy, serving as an auxiliary consistency signal to support collar–animal association and reduce mis-attribution risks. We introduce a dynamically generated pre-shared key (PSK) mechanism based on SHA-256 hashes derived from motion features and timestamps, further securing communication channels via application-layer Hash-based Message Authentication Code (HMAC) combined with Message Queuing Telemetry Transport (MQTT)/Transport Layer Security (TLS) protocols. In our design, MQTT/TLS provides primary device authentication and channel protection, while behavioral fingerprinting and per-window dynamic–HMAC provide auxiliary provenance cues and tamper-evident integrity at the application layer. Experimental validation is conducted primarily via offline, dataset-driven experiments on a public canine IMU dataset; system-level overhead and sensor-to-edge latency are measured on a Raspberry Pi-based testbed by replaying windows through the MQTT/TLS pipeline. Overall, this work integrates motion recognition, behavioral fingerprinting, and dynamic key management into a cohesive, lightweight telemetry integrity/provenance stack and provides a foundation for future extensions to multi-species adaptive scenarios and federated learning applications. Full article