Search Results (5,355)

Automated feeding in cage-based rabbit production is challenging because cage geometry and limited workspace require a compact manipulator with sufficient reach, low mass, and reliable task-level positioning. This study developed a lightweight five-degree-of-freedom manipulator integrated with a vision-guided positioning framework for cage-based rabbit feeding applications. The prototype achieved an effective task reach of 1.20 m with a total mass of 12.37 kg. The design incorporated lightweight carbon-fiber-reinforced polymer (CFRP) long-span links, integrated actuators selected according to joint torque requirements, task-constrained kinematics, closed-form inverse kinematics, and Cartesian trajectory planning. A red–green–blue and depth (RGB-D) localization interface used four ordered feed-port keypoints and a horizontal-plane constraint to provide three-dimensional upper-tier task targets for the manipulator. All representative task points were numerically reachable under the defined software joint limits, and the maximum planned joint velocity was 0.525 rad s${}^{-1}$. Component-level linear-static finite-element analysis predicted no yielding in the four analyzed aluminum components under the simplified conservative 5 kg verification load case. Static loading of the assembled arm produced mean downward displacements of 3.0–20.0 mm at the J5 flange under 1–5 kg loads. Laboratory evaluation demonstrated three-dimensional repeatability radii of 1.68–4.63 mm. Across four upper-tier locations, the mean Euclidean feed-port localization error ranged from 9.01 to 20.47 mm, with all 80 trials satisfying the $\pm 20$ mm-per-axis criterion. The mean tool center point (TCP)-equivalent end-point error ranged from 18.23 to 37.15 mm. These laboratory results support the feasibility of the developed manipulator for upper-tier vision-guided positioning in rabbit-feeding geometry, while indicating that multi-point calibration and spatial compensation are needed to further reduce system-level positioning error. Validation was limited to laboratory testing; no feed was discharged and no rabbit-house operation was evaluated. Full article

This article examines how Philippe Thomassin’s Last Judgment (1606) engraving traveled from Rome to the colonial Spanish Americas, acting as a powerful tool for reshaping both local belief systems and the physical environment. Moving beyond simple artistic analysis, I show how this image promoted a worldview that prioritized human salvation over the survival of the natural world. I connect this historical visual culture to the modern destruction of the Amazon rainforest by apocalypticist religious groups, who view clearing the forest not as an environmental disaster but as the preparation of a divine paradise. By linking early modern prints to today’s climate crisis, I argue that art history must address the active role of eschatological images such as Thomassin’s: they do not just depict the end of the world but can actively help bring it about. This case study reveals how colonial visuality continues to shape the precarious future of the Amazonian biosphere. Full article

Background/Objectives: Psychological distress, anxiety, depressive symptoms and fear of cancer recurrence affect many women treated for breast cancer and often persist beyond active treatment. Mindfulness-based cognitive therapy (MBCT) is manualised and can be delivered in groups or over the internet, which makes it a candidate component of personalised supportive care, but its effect has not been quantified separately from that of other mindfulness programmes. We estimated the association between MBCT, including internet-delivered formats, and four psychological outcomes in adult women with breast cancer and rated the certainty of the evidence. Methods: This study represents a systematic review and meta-analysis of parallel-group randomised controlled trials, reported in accordance with the PRISMA 2020 statement. PubMed/MEDLINE, Scopus, Web of Science Core Collection and Embase were searched from inception without language restriction. The search was updated on 17 September 2026 in PubMed/MEDLINE, Scopus and Web of Science Core Collection; Embase, searched in the original search, could not be included in the update because its records could not be exported and institutional access subsequently ended; this is reported as a limitation. Trials were eligible when participants with breast cancer could be identified separately or, where they could not, when at least 90% of randomised participants were women with breast cancer, a threshold defined before data extraction. Two reviewers independently screened records, extracted post-intervention data directly from the published tables of each trial and appraised risk of bias with the Cochrane Risk of Bias 2 tool. We fitted random-effects models (restricted maximum likelihood); Hartung–Knapp intervals, fixed-effect estimates and a synthesis restricted to trials enrolling women with breast cancer only were sensitivity analyses defined before data extraction. Certainty was rated with GRADE. Results: Three trials (353 randomised participants, 340 of them women with breast cancer; one trial randomised 137 women with breast cancer and 13 men with prostate cancer and did not report results separately by tumour type) from Japan and Denmark were included; no outcome was informed by more than two trials. MBCT was associated with reductions in anxiety (Hedges’ g = −0.69, 95% CI −1.25 to −0.13; two trials, 182 participants) and in depressive symptoms (g = −0.90, 95% CI −1.46 to −0.35; two trials, 182 participants). Associations with total psychological distress (mean difference −5.09, 95% CI −10.20 to 0.02; two trials, 178 participants) and with fear of cancer recurrence, which rested on one trial, were imprecise and compatible with no benefit. Hartung–Knapp intervals included no effect for every outcome, and the anxiety and depressive-symptom analyses reduced to a single trial when the trial with a mixed cancer population was excluded, so neither apparent effect was robust to the method used to quantify uncertainty. Certainty was very low for all four outcomes. Conclusions: MBCT is associated with moderate-to-large short-term reductions in anxiety and depressive symptoms, but each estimate rests on two trials, is not robust to the inferential method used and is of very low certainty; three trials are too few to support firm recommendations, and the programme should be regarded as promising rather than established. Adequately powered trials with active comparators, common outcome measures and longer follow-up are needed. Routine checking for redundant publication is also required: one retrievable report, classified as a suspected redundant report on numerical comparison alone, presents data largely identical to those of an included trial. Full article

Developing reliable numerical tools and analytical methodologies is essential to optimize the design phase of composite structures. The quasi-static fracture behaviour of glass-fibre reinforced polymer bonded joints was evaluated for bidirectional and quasi-isotropic sequences. The specimens were bonded with a two-component epoxy-based adhesive system. The complete mixed-mode I+II fracture envelope was obtained using double cantilever beam, three-point bending End-Notched Flexure, and mixed-mode bending configurations. A data reduction scheme based on the equivalent crack method was adapted to calculate fracture energies as a function of the compliance evolution recorded during the tests. The power law energy fracture criterion was used to describe the complete mixed-mode I+II fracture envelope. The criterion proved to be very accurate in predicting the mixed-mode fracture behaviour for both series. A cohesive zone model with a trapezoidal softening law was used to validate the experimental procedure of the three test configurations. The results obtained for the fracture envelope using the power law criterion and the local strengths were used as input for the numerical simulations. The model efficiently described the full fracture envelope of both stacking sequences, with a deviations below 3% for the B series and below 7.5% for the Q series. Full article

A growing number of individuals experiencing anxiety and other mental health difficulties require accessible approaches to mental health support. This paper presents a hybrid AI-assisted framework designed as a potential complementary support tool for future therapist-supervised mental health care rather than as a replacement for clinical decision-making. The framework integrates a flexible dialogue-generation architecture, an interactive embodied avatar, and an ethical and safety-oriented component emphasizing privacy and human-centered governance. An exploratory survey including structured and open-ended questions was conducted with 102 university students following a live demonstration of the proposed framework. Overall, 76.2% of participants agreed or strongly agreed that AI could help some people with mental health support, 59.4% indicated that they would use AI-assisted support if freely available, while 55.0% preferred interacting with a human therapist. Open-ended responses highlighted accessibility and continuous availability as potential advantages, while concerns included emotional understanding, privacy, and the accuracy and reliability of AI-generated responses. These findings provide preliminary information about university students’ perceptions following exposure to the proposed framework but do not constitute an evaluation of therapeutic effectiveness, clinical utility, or clinical safety. Further research involving direct user interaction, clinically relevant populations, validated outcome measures, and appropriate safety protocols is needed. Full article

Carbon fiber-reinforced composites provide exceptional specific strength for lightweight structures but are associated with high global warming potential (GWP) during production. This study evaluates the GWP reduction potential of carbon/flax fiber hybrid composites for a one-piece main frame of a children’s bicycle. A simplified, scenario-based assessment was performed using a 3.0 kg reference mass and a fixed 70:30 reinforcement-to-resin mass ratio. The analysis varied flax substitution levels (0–40 wt.%), resin systems (epoxy and unsaturated polyester), manufacturing processes (resin transfer molding and prepreg/press), and end-of-life (EoL) treatments (incineration and landfill). Increasing flax content consistently reduced GWP across all scenarios. At 40 wt.% flax substitution, resin transfer molding achieved a 29.6–32.7% GWP reduction, whereas prepreg/press processing yielded a 21.5–23.0% GWP reduction. Material production dominated the GWP footprint in molding processes, whereas higher manufacturing burdens in prepreg/press routes partially offset the substitution benefits. GWP break-even mass ratios ranged from 1.273 to 1.486, indicating that hybrid frames can accommodate moderate mass increases without compromising environmental advantages. These results demonstrate that flax hybridization effectively reduces GWP, though the magnitude of reduction depends critically on manufacturing and EoL management choices. The proposed screening framework provides a practical tool for early-stage material and process selection in lightweight composite design. Full article

Background: Esthesioneuroblastoma (ENB) is a rare neuroectodermal tumor arising from the olfactory epithelium. This study aimed to identify survival determinants and construct a prognostic web-based nomogram to provide individualized survival predictions for ENB patients. Methods: Patients diagnosed with ENB between 2000 and 2022 were identified using the Surveillance, Epidemiology, and End Results (SEER) database. Patient demographics, tumor characteristics, and treatment data were analyzed using Cox proportional hazards models and Kaplan–Meier survival curves. A web-based nomogram was constructed to predict 5- and 10-year survival probabilities individualized to a specific patient. Results: Nine hundred and forty-one ENB patients were analyzed. Overall survival (OS) rates at 1-, 2-, 5-, and 10-years were 89%, 85%, 75%, and 58%, respectively. Multivariable analysis revealed that age over 50 (p < 0.001) and tumor size over 6.0 cm (p < 0.01) were independent predictors of worse OS. Compared to patients treated with gross total resection (GTR) alone, worse OS was observed in those treated with chemotherapy (CT) only (p < 0.01), CT and radiation (RT, p < 0.01), GTR + CT (p < 0.05), RT only (p < 0.01), or no treatment (p < 0.001). No statistically significant differences in OS were found between GTR alone and GTR + RT, GTR + RT + CT, subtotal resection (STR), or STR with adjuvant therapies. The resulting ENB prognostic nomogram demonstrated acceptable predictive performance, with a C-index of 0.733 ± 0.041 and AUC of 0.749. Conclusions: Age and tumor size are critical survival determinants in ENB, and GTR continues to be the foundational treatment. The developed prognostic web-based nomogram successfully quantifies individualized survival probabilities, providing clinicians with a tailored tool to guide evidence-based counseling and management for ENB patients. Full article

This research focuses on the development of a robotic cell test bench for manufacturing variable-geometry tubular parts with minimal manual intervention. The system integrates dual-arm manipulation with cutting and laser-welding stations and was evaluated in collaboration with an industrial partner with strict requirements on joint strength and sealing performance. The experimental investigation characterized the influence of key welding process parameters, particularly the robot end-effector travel speed (mm/s) and laser power (W), on the mechanical performance of the welded joints. These parameters were subsequently used to manufacture representative three-dimensional duct geometries. In addition, preliminary sealing evaluations were used to assess the ability of the welded components to withstand internal pressures. These results highlight the influence of mechanical components, geometries, and material behavior, as well as the need for advanced digital tools. A preliminary automated path-generation methodology is introduced to support adaptable robot trajectories. Overall, the results support the feasibility of the integrated robotic manufacturing concept while identifying the additional developments required before fully automated production can be achieved. Full article

Background: Identification of immunogenic neoantigens remains one of the major computational bottlenecks limiting the development of effective personalized cancer vaccines. Although various computational methods have been proposed for neoantigen discovery, there is little independent evidence regarding which approaches most effectively prioritize vaccine candidates using experimentally validated datasets. We focused on an independent multi-cohort benchmark of widely used neoantigen discovery pipelines and neoantigen scoring tools using publicly available datasets with experimentally validated immunogenic peptide–Major Histocompatibility complexes (MHC). Methods: In order to evaluate computational strategies used for selection of candidate vaccine peptides, five end-to-end neoantigen prediction pipelines and seven neoantigen scoring and prioritization tools were independently benchmarked using experimentally validated neoantigen datasets. End-to-end pipelines were evaluated on the TESLA cohort using raw WES and RNA-seq data from five patients, while individual prediction tools were additionally assessed on the TESLA, NCI, and HiTIDE validation cohorts comprising experimentally verified immunogenic and non-immunogenic peptide–MHC complexes. Results: NeoHunter achieved the highest overall recovery of experimentally validated neoantigens among the evaluated pipelines, while the scoring and prioritization tools NetMHCpan, MixMHCpred, and MHCFlurry generally showed the strongest ranking performance, although their relative performance varied substantially between datasets and patients. Precision–recall, average precision, and top K analyses demonstrated that no single predictor consistently dominated across cohorts and revealed a clear trade-off between candidate list size, precision, and recovery of validated neoantigens. Analysis of clinically relevant candidate selection thresholds demonstrated that restricting vaccine design to only the highest-ranked peptides substantially reduces sensitivity, whereas broader candidate selection improves recovery at the expense of increased experimental burden. Conclusions: These findings provide practical recommendations for computational selection of vaccine targets and highlight current limitations that must be addressed to improve the success of personalized neoantigen-based vaccines. Full article

The MELD-based scoring system is the most important tool to date for liver transplant allocation. It is useful as an index of the severity of the disease, but not a true measure of functional capacity, physiologic reserve or of the wider implications of end-stage liver disease. Frailty and sarcopenia have gained attention as important prognostic markers that provide information beyond traditional laboratory tests. This narrative review examines current evidence on the role of frailty and sarcopenia in liver transplant candidates. Focus is placed on waitlist mortality, post-transplant outcomes, and potential implications for decision-making. Studies evaluating the Liver Frailty Index (LFI), radiologic measures of sarcopenia and associated outcomes in patients with cirrhosis were reviewed. The LFI is a commonly used measurement of frailty. It is linked with increased risk of waitlist mortality even after adjusting for current MELD-based allocation models, ascites and hepatic encephalopathy. Frailty has been demonstrated not to be fixed and even modest gains are associated with reductions in mortality. Liver transplantation should not be precluded only based on frailty, as liver transplant recipients experience a survival benefit across the full spectrum of frailty severity. There is also a strong correlation between sarcopenia, myosteatosis and poor outcomes such as increased waitlist and post-transplant mortality; complications and prolonged hospital stay. Frailty and sarcopenia are closely related and when taken together, they give a better overall picture than either measure alone. Frailty and sarcopenia are complementary predictors of outcomes in liver transplant candidates, addressing important gaps in MELD-based allocation models. Incorporating performance and body composition measures into pre-transplant evaluation may improve prognostic accuracy, help identify patients for prehabilitation and support a better approach to patient assessment and management. Full article

This review critically examines product-specific deterioration pathways in fresh dairy products and evaluates how analytical technologies, kinetic models, chemometric tools, and machine learning approaches support quality assessment and shelf-life prediction. Current evidence shows that many studies identify storage-related changes; however, few can predict the point at which a product reaches its acceptability limit and end of shelf-life. Reliable shelf-life prediction therefore requires a clear definition of the dominant deterioration pathway, a representative quality indicator, and a well-defined microbiological, physicochemical, structural, or sensory acceptability threshold. The analytical signal must demonstrate a validated mechanistic or predictive relationship with the selected quality threshold, rather than merely correlate with storage duration. Adopting an endpoint-centered framework would enable a more efficient integration of deterioration mechanisms, analytical measurements, and predictive modeling approaches, thereby providing a stronger scientific basis for shelf-life determination and quality management in fresh dairy products. Future progress will depend on the generation of representative multi-batch datasets, independent validation, realistic time–temperature histories, and model evaluation across diverse storage and distribution scenarios. Full article

Background: Evaluating end-of-life care quality remains a central challenge in health systems facing population ageing and complex chronic disease trajectories. Given the clinical challenges of direct data collection at the end-of-life, bereaved family members act as critical proxies, providing data on the care delivered in the final months of life. However, most available instruments lack the contextual sensitivity required for national-level epidemiological surveillance. Objectives: This study aims to develop and establish the face validity of a national questionnaire to evaluate the healthcare trajectory of adults with advanced chronic disease from the proxy perspective. Methods: A four-stage developmental protocol was implemented: (1) conceptual framework definition; (2) item generation through a review of national regulations, a scoping review of seven international instruments, and a focus group with clinical experts; (3) item reduction and refinement through expert panel review; and (4) face validity and feasibility testing through cognitive interviews and a pilot study. Results: The consensus process and pilot testing resulted in a final instrument comprising 84 items, structured into 7 sections and 17 thematic clusters. The questionnaire covers core care trajectories, the last 48 h of life, and bereavement support, while integrating specific national settings like integrated continuous care, alongside items on spiritual care and communication. The pilot study yielded a mean completion time of 14.6 min, while cognitive interview and pilot testing supported participant acceptability and feasibility for both telephone-assisted and self-administration modes. Conclusions: This questionnaire provides a face-validated, evidence-informed tool for post-death proxy reporting at the end-of-life. By aligning international quality indicators with country-specific healthcare structures, the instrument is ready for further testing of its reliability and validity and may support future comparative research, clinical auditing and health policy development. Full article

Malnutrition and protein-energy wasting (PEW) are closely related yet distinct clinical entities. While malnutrition broadly refers to nutritional deficits arising primarily from inadequate dietary intake, PEW is a complex syndrome specific to chronic kidney disease characterized by the progressive loss of body protein mass and energy reserves driven by systemic hypercatabolism, uremic toxicity, chronic inflammation that cannot be corrected by dietary intake alone. Nutritional impairment remains one of the most prevalent and clinically significant complications of end-stage kidney disease (ESKD), affecting a substantial proportion of patients receiving maintenance hemodialysis and peritoneal dialysis despite advances in dialysis technology and multidisciplinary care. Traditionally, nutritional impairment in dialysis was evaluated through isolated surrogate markers such as serum albumin or body weight. However, these conventional measures capture only a fraction of the underlying biological complexity and are heavily confounded by non-nutritional factors, including systemic inflammation and volume overload. Recognizing the intertwined contributions of uremic milieu, inflammation, oxidative stress, and hypercatabolism led to a paradigm shift toward composite nutritional assessment tools, most notably the Malnutrition–Inflammation Score (MIS), which integrates dietary, anthropometric, clinical, and biochemical parameters to comprehensively quantify PEW severity and systemic risk. Current evidence supports a broader conceptual framework in which nutritional status is recognized as an important clinical correlate and potential contributor to metabolic health and multisystem complications, including immune dysfunction, cardiovascular disease, frailty, hospitalization, and all-cause mortality. Consequently, nutritional impairment in dialysis should be viewed as a multifactorial clinical condition requiring comprehensive, multi-domain assessment rather than reliance on isolated biomarkers. This review examines the systemic consequences of malnutrition and PEW in maintenance dialysis patients, highlighting emerging evidence linking nutritional deficits with host immune impairment, cardiovascular disease, and adverse clinical outcomes. Full article

Growing development of biomaterials has stimulated the biomedical sector to seek innovative alternatives to conventional medical technologies. Bio-optoelectronic devices are emerging as promising tools, integrating biologically derived components, biodegradable end-of-life approaches, and highly biocompatible materials with optoelectronic systems. The devices combine optical and electronic properties with biological interfaces, enabling more effective interaction with tissues and cellular systems. Applied research is motivated by the need to improve the efficacy and biocompatibility of medical devices while reducing invasiveness and adverse effects. Wearable devices and implants based on flexible, biodegradable, or bioinspired materials allow better adaptation to biological tissues and real-time monitoring or modulation of physiological processes. Proteins are attracting increasing attention due to their biocompatibility, biodegradability, mechanical flexibility, and ability to respond to optical and electrical stimuli. Furthermore, the combination of proteins with synthetic materials and nanomaterials in biohybrid platforms offers new opportunities for advanced bio-optoelectronic systems. This review summarizes key developments in bio-optoelectronic devices, focusing on protein-based materials; their roles in sensing, imaging, and neuromodulation; and their use in wearable, implantable, and biotech systems. Crucial challenges, including long-term stability and integration with biological systems, are also discussed, together with future perspectives for diagnostic and therapeutic applications. Full article

With the tightening of global methane regulations (EU Methane Regulation 2024/1787, U.S. EPA GHG rules, OGMP 2.0) and China’s dual-carbon commitments, precise and traceable carbon accounting for natural gas gathering systems has become an urgent engineering imperative. To tackle manual workflows, data isolation, low precision, and poor traceability in carbon accounting for natural gas field surface systems, this study develops a four-tier digital delivery framework. The main goal is to establish an end-to-end engineering paradigm that transforms carbon management from passive post-hoc statistics into an active, traceable decision-support tool. By embedding carbon attributes into seed files and adopting a unified one-code-through equipment coding scheme, static design data, dynamic SCADA measurements, and emission factor databases are interoperably consolidated within a central data hub. The hub implements a three-stage progressive accounting workflow and closed-loop emission mitigation. Methodologically, a three-tier progressive accounting model (Tier 1: system-level, Tier 2: process-level, Tier 3: equipment-level) is constructed, with Tier 3 supported by OGMP 2.0 source-level emission factors locally calibrated against 386 field LDAR measurements. Deployed at Gas Field A, the framework realizes full diagram-model consistency and narrows systematic error from ±30% to ±3.5%. Tier-2 accounting quantifies gathering, compression, and dehydration emissions at 322,000, 504,300, and 162,500 tCO₂e, while Tier-3 analysis pinpoints reciprocating compressors and heaters as the primary contributors (51.70% of total emissions). Optimizations including compressor energy conservation, enhanced LDAR, and waste heat recovery provide an estimated annual mitigation potential of 97,400 tCO₂e (10.10%). In conclusion, this framework mitigates data fragmentation and accuracy defects, delivering a transferable technical route for oil and gas operators to advance methane abatement and dual-carbon targets. Full article