Search Results (8,377)

To improve the efficiency of comparative process-window screening in selective laser melting (SLM), this study developed a finite element simulation-driven machine learning framework for 316L stainless steel. A simulation dataset covering laser power (LP), scanning speed (SS), heat-source diameter (HSD), and substrate preheating temperature (SPH) was generated using ANSYS and used to train nine regression models. In the present work, the primary machine learning target was defined as the simulated average thermal stress, σ_avg, which is used as a simulation-derived comparative thermal stress indicator for ranking process conditions within the investigated parameter window rather than as a direct prediction of the final residual-stress field. Among the evaluated models, the Backpropagation Neural Network (BPNN) showed the best predictive performance and was selected as the representative surrogate model because of its strong predictive accuracy, stable behavior, and direct applicability to the present structured tabular dataset. Shapley additive explanations (SHAP) and partial dependence plots (PDPs) indicated that LP is the dominant variable governing the σ_avg-based response, followed by SPH, whereas SS and HSD mainly affect the response through secondary or coupled effects. Within the investigated parameter window, conditions near 180–200 W corresponded to a relatively lower predicted σ_avg level. Experimental observations provided limited but meaningful trend-level support for the simulation-guided screening results: metallographic examination showed improved forming quality near 200 W, while XRD-derived macroscopic stress estimates exhibited a similar variation trend to the simulated σ_avg values under the tested LP–SS conditions. These results suggest that the proposed framework can serve as an efficient surrogate-based tool for comparative parameter screening in SLM-fabricated 316L stainless steel within the assumptions and parameter range of the present model. Full article

The abuse of γ-hydroxybutyric acid (GHB) and its precursors, γ-butyrolactone (GBL) and 1,4-butanediol (1,4-BD), has increased in recent years, with these substances frequently being illicitly added to beverages. GHB is colorless and odorless and exhibits anesthetic and hypnotic psychoactive effects, which are often exploited in drug-facilitated sexual assault, posing a significant public safety concern. Chromatography–tandem mass spectrometry is a conventional analytical approach for narcotic drug determination due to its high sensitivity and accuracy; however, its large instrumentation footprint and high operational cost limit its suitability for on-site rapid screening. In response to the growing demand for field-deployable analytical tools, rapid detection technologies for GHB have progressively evolved. This review summarizes and compares the advantages and limitations of current rapid detection methods for GHB and discusses their potential future developmental trends, with the aim of providing a reference for researchers and relevant authorities. Full article

Rectangular sinking wells are widely used in underground and hydraulic engineering, where maintaining vertical alignment during construction is essential for safe serviceability and long-term performance. Even moderate inclination may cause eccentric transfer of the vertical load to the concrete plug, leading to non-uniform contact stresses beneath the base. This study presents a closed-form analytical framework for assessing the admissible tilt of rectangular sinking wells based on stress redistribution under one-axis inclination. The well is modeled as a rigid body, and the resulting load eccentricity is related to the shaft height and tilt angle. Classical eccentric compression theory is then used to derive explicit expressions for the maximum and minimum base stresses, from which a serviceability-based admissibility criterion is formulated. The obtained solution provides the allowable inclination directly as a function of shaft height, plan dimensions, and an adopted stress amplification factor. Parametric analyses show that the admissible tilt decreases with increasing shaft height and increases with larger base dimensions. A distinct directional anisotropy is observed for rectangular plans, whereas square wells recover symmetric behavior with identical limits in both orthogonal directions. This identifies square geometry as the symmetry-preserving limit case of the proposed model. Sensitivity analyses further demonstrate the influence of admissible stress amplification on permissible inclination levels. The proposed formulation offers a transparent screening tool for construction monitoring and post-construction assessment, while also illustrating how geometric symmetry reduction governs the mechanical response of inclined foundation systems. Full article

Background/Objectives: Cisplatin-exposed pediatric cancer patients are at increased risk of ototoxicity, particularly those under 5 years of age. In this group, audiological monitoring is challenging, as interpretation of otoacoustic emissions (OAEs) and tympanometry, used to supplement behavioral audiometry, is subject to interindividual variability. This study aimed to identify key challenges and establish an international consensus on optimal testing procedures and interpretation criteria for assessing early cochlear damage. Methods: Audiological data from 11 children (<5 years) exposed to cisplatin in utero were evaluated. An international panel of 10 pediatric oncology audiology experts reviewed tympanometry, transient evoked OAEs (TEOAEs), and distortion product OAEs (DPOAEs). Areas of disagreement were analyzed, and consensus was sought regarding testing conditions, interpretation, and clinical application. Results: Agreement on cochlear status was good in 10/22 ears, moderate in 3/22 ears, and poor in 9/22 ears, highlighting substantial variability in interpretation. Consensus was achieved on minimal technical and interpretative requirements for OAE testing in this population. The panel proposes a classification framework integrating OAEs and tympanometry to guide clinical follow-up. Importantly, normal OAE results were not considered sufficient to exclude ototoxic damage or mild hearing loss. Conclusions: OAEs, particularly DPOAEs, are valuable as a screening tool in ototoxicity monitoring programs for young children, provided that testing conditions and interpretation are standardized. However, OAEs alone are insufficient for definitive assessment. Longitudinal monitoring and confirmatory testing with behavioral audiometry or ABR/ASSR remain essential. Further validation of the proposed classification system is warranted. Full article

Background/Objectives: General-purpose and domain-specific multimodal foundation models show considerable promise in medical image analysis. In this study, we evaluated the classification accuracy of diabetic retinopathy vs. normal fundus images using general-purpose conversational models (Gemini 3 Flash, GPT-5.2, and Pixtral-Large), a medical conversational model (MedGemma-1.5), and its image-encoder (MedSigLIP), as well as ophthalmology-specific models (RETFound and EyeCLIP). Methods: We applied zero-/few-shot to general-purpose conversational models, linear probing, and fine-tuning approaches to domain-specific models for evaluation purposes. Results: We found that the zero-shot accuracies for Pixtral-Large (70.7%) and fine-tuned RETFound (77.1%) were comparable but lower than those of GPT-5.2 (77.9%), MedGemma-1.5 (88.2%), and Gemini 3 (88.5%) as well as the fine-tuned EyeCLIP (85.8%) and MedSigLIP (94.8%). The accuracy gains from few-shot prompting were substantial for Pixtral-Large (+7.4%) but were limited for GPT-5.2 (+3.6%), Gemini 3 (−3.4%), and MedGemma-1.5 (−1.1%). Embedding-based linear probing further improved accuracy over fine-tuning for RETFound (+9.7%) and yielded only marginal gains for EyeCLIP (+2.3%) but did not benefit MedSigLIP (−0.8%). Overall, with minimal prompting enhancement, general-purpose conversational models such as Gemini 3 and GPT-5.2 achieved performance comparable to ophthalmology-specific models that were either fine-tuned or enhanced via embedding-based linear probing, but remained inferior to MedSigLIP and its conversational counterpart, MedGemma-1.5. Conclusions: The findings highlight a trade-off between specialization and flexibility, where domain-specific models provide higher accuracy and stability, while general-purpose multimodal models offer greater accessibility, adaptability, and interactive reasoning, serving as complementary tools for retinal disease screening and clinical decision support. Full article

Background/Objectives: Several subunit vaccines for tuberculosis (TB), such as MVA85A and H4:IC3, have not demonstrated ideal protective efficacy in clinical trials, which may be attributed to their limited antigenic profile and lack of effective latency-associated antigens. In this study, we combined bioinformatics with experimental validation to screen for latency-associated antigens that have immune-protective effects. Methods: Highly expressed antigens were identified from models related to latent infections, such as hypoxia and nutritional starvation. Their physicochemical properties and immunogenicity were predicted using online tools such as Expasy-ProParam, IEBD, and VaxiJen. The immunogenicity of these antigens was then evaluated in multiple mycobacterium infection models. Finally, a systematic evaluation of the immune response and protective effects induced by the candidate antigens was performed in a mouse model using intracellular cytokine detection, mycobacterium growth inhibition assays (MGIAs), antibody-dependent cellular phagocytosis (ADCP), and a latent tuberculosis infection (LTBI) mouse model. Results: The antigen Rv2656c is highly expressed in the nutritional starvation model and demonstrates strong immunogenicity in both infected humans and cattle. Moreover, Rv2656c exerted a significant inhibitory effect against Mycobacterium tuberculosis (M. tuberculosis) and Mycobacterium avium (M. avium) infections in MGIA. The humoral immune response elicited by Rv2656c enhanced the phagocytosis and killing of Mycobacteria by macrophages in vitro. Furthermore, in a mouse model of LTBI established using the attenuated M. tuberculosis H37Ra strain, treatment with Rv2656c significantly decreased the bacterial load in the lungs of the mice. Conclusions: Latency-associated Rv2656c may serve as an immune-protective antigen, offering potential for the development of novel multi-stage antigen subunit vaccine against TB. Full article

Mechanical engineering systems must sense, inspect, and navigate constrained environments and operate adaptively under uncertainty—requirements that map structurally onto capabilities achieved by biological systems through distributed sensing, morphology-driven locomotion, multimodal perception, and decentralised control. Biomimetics can therefore be interpreted not merely as a source of design inspiration but also as a functional engineering framework relevant to industrial monitoring, inspection, maintenance, and autonomous operation. This study presents a PRISMA 2020-guided systematic mapping review of the biomimetics literature explicitly relevant to mechanical-engineering functions over the decade 2016–2026. A Scopus corpus of 11,114 records was screened through a two-stage abstract-level process. After deduplication and broad relevance filtering, a stricter eligibility audit retained 505 studies assignable to five predefined functional clusters: robotics and access (235 records; 46.5%), mechanical surfaces and tribology (141; 27.9%), sensing and monitoring (106; 21.0%), vision and inspection (14; 2.8%), and control and computation (9; 1.8%). Publication output accelerated markedly after 2022, with 2025 yielding the highest annual count. The principal gap identified is not a shortage of biomimetic concepts, but their limited consolidation into deployable industrial inspection and maintenance architectures. A translational taxonomy connecting biological principles, engineering abstractions, enabling technologies, and mechanical use cases is proposed as an interpretive structuring tool for future research prioritisation and technology-readiness discussion. Full article

Edge Internet of Things (IoT) blockchain deployments increasingly rely on continuous transaction ingestion from resource-constrained IoT devices to nearby edge gateways over heterogeneous wireless links. In this setting, transient channel noise and packet corruption can inject invalid payloads into the edge processing pipeline and trigger unnecessary buffering, parsing, and, most critically, computationally expensive cryptographic operations such as digital signature verification. This leads to wasted computation, increased latency, and reduced energy efficiency at the edge, particularly under dense IoT traffic. This paper presents an energy-aware and fault-tolerant Quantum-Dot Cellular Automata (QCA)-based integrity pre-filter for IoT-to-edge blockchain transaction ingestion. At the circuit level, we adapt and modify a previously reported fault-tolerant five-input majority gate (MV5) structure and use it as a robust primitive for nanoscale integrity-screening circuits. Building on this modified MV5, we design a set of QCA integrity blocks, including a parity checker, a compact XNOR gate circuit, a parity-bit generation circuit, and a sender-to-channel/receiver nano-communication integrity workflow suitable for early screening of corrupted payloads. Compared with the best previously reported baseline considered in this study, the modified MV5 achieves 76.47% tolerance to single-cell omission defects, corresponding to a 17.47 percentage-point increase and an approximately 29.61% relative improvement over the prior 59% omission-tolerance result, while preserving 100% tolerance against extra-cell deposition defects. At the system level, the proposed circuit is discussed as a potential early screening stage for edge-IoT blockchain transaction ingestion. A bounded analytical model is used to estimate the possible reduction in unnecessary signature-verification workload under assumed corruption and detection conditions. This analysis is not intended as a deployment-level validation; full edge-node implementation, throughput measurement, queueing-delay evaluation, real traffic traces, retransmission behavior, and empirical signature-verification profiling remain future work. The proposed parity/chunk-parity pre-filter is designed for low-cost detection of random transmission-induced corruption and does not replace cryptographic authentication, hashing, digital signatures, CRC-based detection, or blockchain validation. All proposed designs are validated using QCADesigner tools. Full article

A modified Pitot-tube jet (PTJ) separation pump combines centrifugal phase separation with pressure buildup and enables compact oil–water treatment, where a water-rich stream can be discharged at elevated pressure. This work advances an existing laboratory PTJ configuration toward a turbomachinery-oriented rotor concept for systematic design studies and subsequent field-oriented prototypes. Starting from a centrifuge-like reference configuration without blades that prioritizes separation stability, an impeller with trimmed blades is introduced to increase pressure head while limiting blade interaction with the oil–water interface by operating primarily in the outer, water-rich annulus. Comparative experiments with and without the impeller show a pronounced increase in pressure head, up to about a factor of three at the maximum speed investigated. The results also indicate a purity penalty caused by blade-induced mixing and secondary flows. This exposes the central design trade-off of the PTJ machine. Higher specific work input increases pressure head but can reduce discharge quality. Hydraulic optimization, therefore, needs to be coupled to ppm-level purity constraints. Density-based monitoring lacks resolution in the relevant trace range, and chemical-based analyses are too slow for systematic investigations. An imaging-based fluorescence method using Nile Red as a selective tracer is, therefore, implemented as a rapid analysis tool. High-resolution imaging with automated region of interest evaluation provides a robust calibration from 5–500 ppm for safe, non-fluorescent model oils such as sunflower oil. This enables efficient operating-window mapping and comparative screening of rotor concepts under reproducible conditions. Full article

Objectives: To develop and rigorously evaluate a Hybrid Multi-Path Attention Convolutional Neural Network (HMPA-CNN) for the classification of kidney diseases across heterogeneous institutional datasets and imaging modalities. Materials and Methods: The proposed HMPA-CNN employs dual parallel pathways to disentangle spatial (3 × 3 convolutions) and textural (5 × 5 convolutions) representations, followed by attention-based feature recalibration and gated fusion. Performance was assessed on five geographically distinct datasets comprising 29,148 CT and MRI images collected from Turkey, Bangladesh, Jordan, Iraq, and publicly available international sources. The evaluation framework included three-class tumor discrimination, four-class renal pathology classification, six-class tumor subtyping, binary kidney stone detection, and chronic kidney disease (CKD) assessment under cross-modality conditions. Results: The model achieved 99.76% overall accuracy on the KidneyNeXt three-class dataset, 99.96% on the four-class multi-institutional CT dataset, and 99.74% on the independent Jordan cohort under a four-class configuration. In the more granular six-class tumor subtyping task, overall accuracy was 96.36%. The same architecture achieved 93.85% overall accuracy on the MRI-based CKD classification task, suggesting that the framework can be adapted to a different imaging modality. Across most classification tasks, specificity exceeded 99%, with benign–malignant misclassification remaining below 2%. Performance declined to 91.96% for kidney stone detection, reflecting the intrinsic difficulty of small-object localization in axial CT images. Conclusions: The dual-path architecture consistently preserved high discriminative performance across institutions, diagnostic granularities, and imaging modalities. Its stable specificity and low benign–malignant confusion suggest potential utility as a supportive tool within renal imaging workflows, particularly for screening and structured diagnostic assistance. Clinically, benign–malignant misclassification is the most critical error, as it may delay oncologic evaluation or lead to unnecessary follow-up. Therefore, the model should be used as a decision-support tool rather than an autonomous diagnostic system. Further prospective validation is required to determine its impact in routine clinical practice. Full article

Background/Objectives: Although comprehensive transthoracic echocardiography (TTE) is part of the diagnostic workup in acute ischemic stroke, it is not cost-effective to use it for all patients. Guidelines recommend using it only for selected patients to guide secondary prevention. Neurologist-led, stroke-focused cardiac ultrasound (S-FoCUS) is an emerging bedside screening tool that optimizes cardiac evaluation in acute stroke care. We hypothesize that the implementation of S-FoCUS screening may reduce resource utilization in terms of hospital stay and TTE procedures. Methods: We conducted a retrospective before-and-after cohort study of patients with suspected acute ischemic stroke or TIA admitted to our comprehensive stroke center. We compared two 6-month periods: the pre-S-FoCUS period, during which patients underwent TTE as the initial cardiac imaging modality; and the post-S-FoCUS period, during which patients initially underwent S-FoCUS, with subsequent TTE performed only in the presence of abnormal findings or at the clinician’s discretion. We compared the time from admission to first cardiac ultrasound assessment, length of stay, relative reduction in TTE procedures and estimated in-hospital costs. Results: The pre-S-FoCUS period included 224 patients, and the post-S-FoCUS period included 229 patients. The S-FoCUS protocol reduced the median time to first cardiac ultrasound assessment by two days (median [IQR] 3 [2–5] vs. 1 [1–2], p < 0.001) and the median length of stay by one day (6 [4–9] vs. 5 [3–10], p = 0.014). Implementing the S-FoCUS protocol was associated with an exploratory estimate of lower in-hospital costs (approximately €716 per screened patient) driven mainly by a shorter length of stay. The distribution of the frequency of predefined cardioembolic sources was similar between both periods. There was a high agreement rate between the S-FoCUS and TTE findings in patients who underwent both tests: mitral stenosis (κ = 0.78), left atrial severe enlargement (κ = 0.74), left ventricular hypokinesia/akinesia (κ = 0.84), and depressed LVEF (κ = 0.88). Conclusions: Neurologist-led S-FoCUS is a feasible triage strategy to improve efficiency in the acute stroke pathway. Full article

Prenatal alcohol exposure (PAE) can cause fetal alcohol spectrum disorder (FASD). The FASD continuum encompasses facial dysmorphism, growth failure, and central nervous system (CNS) abnormalities/dysfunctions. Because some of these features may not be apparent in newborns, detecting PAE in the neonatal period is challenging, while early diagnosis may improve neurodevelopmental outcomes. Maternal self-reported alcohol consumption is limited by recall bias and denial, leading to misdiagnosis. Currently, there is a lack of universally implemented and standardized tools for identifying PAE/FASD in children across clinical settings. We aimed to review the existing literature on PAE assessment methods. Analysis of alcohol metabolites in neonatal meconium is the most widely studied and appears to be feasible for routine use, but it has some limitations. Recent advances in understanding the effects of alcohol on neurotransmitters, growth factors, and gene activity have contributed to the development of novel diagnostic strategies and have brought us closer to effective PAE detection. Some laboratory assays appear to be feasible for implementation in routine clinical practice, i.e., testing for pro- and anti-inflammatory cytokines, including interleukins (IL): IL-6, IL-1β, IL-10, and tumor necrosis factor-alpha (TNF-α) and Insulin-like Growth Factor 1(IGF1). These molecular approaches hold promise but require replication and validation before becoming the standard in clinical practice. Further research on biomarkers and other screening tools should continue to determine their feasibility and availability. Full article

Background: The Testamentary Capacity Assessment Tool (ΤCAT) is a brief instrument with good psychometric properties, specifically designed for the assessment of testamentary capacity (TC) in individuals with dementia. It assesses memory, perception of financial matters, and judgment, as well as cognitive functions, such as theory of mind, not measured by other traditional tools. Additionally, it does not require collateral sources of financial information. The aim of the present study was to provide an updated report on the use of the TCAT in research and systematic review studies. Methods: This narrative review includes studies that have used the TCAT for clinical use, validation in different cultures, and comparison with the two other specialized TC assessment tools. The PubMed database was searched using the keyword “Testamentary Capacity Assessment Tool”. Results: The TCAT has been validated in a healthy Italian population and was found to be a useful adjunct instrument for TC assessments in older adults. Another study demonstrated its clinical utility in patients with acute ischemic stroke. A systematic review compared the TCAT to the other two existing specialized TC assessment tools, namely the Testamentary Capacity Instrument (TCI) and the Testamentary Definition Scale (TDS), highlighting the superiority of the TCAT in clinical practice. Conclusions: The TCAT is a useful, specialized screening tool that is easily applicable in clinical practice by both experts and non-experts. Further studies are recommended across different cultures, in both healthy and cognitively impaired adults, to support its standardized use in forensic and clinical settings. Full article

Background/Objectives: Military and Veteran families face unique challenges, including deployment-related difficulties and transitions, mental health issues, educational setbacks, and more. The needs of Veteran families, specifically, are often overlooked and research among this population is insufficient. In an effort to promote the well-being of children of Veterans and their families, we developed a screening tool for identifying family needs and a workflow to implement the screening tool within the Veterans Health Administration. The objective of this quality improvement initiative was to then provide those in need with appropriate referrals and connect them to timely care. Methods: The screening tool was developed with input from key stakeholders and adjusted after an initial pilot. Screens were offered to all Veterans seen at the participating sites. Veterans completed the self-report screen consisting of demographic information and items regarding household composition, the quality of relationships with family members, and the Veteran’s perceptions of difficulties experienced by family members. Descriptive statistics were conducted to summarize the data with regard to demographics, relationship difficulties, and related needs of Veteran family members. Results: Among familial relationships, Veterans reported experiencing the most difficulties with their partner/spouse as compared to other family members. Veterans self-reported that many of their children 18 years old and younger demonstrated difficulties related to learning, development, and behavioral and emotional concerns. Conclusions: More than a third of Veterans screened in this process requested further contact for consultation and referrals, and half of those were provided referrals. The development and implementation of this screening tool and referral procedure was successful in identifying needs and facilitating a connection to care that might otherwise have not occurred, bridging the gap between research and practice as it relates to Veteran family needs. Full article

Water toxicity screening requires sensitive tools to rapidly detect environmental pollutants. While complex analytical methods accurately determine known contaminants, fast screening tests utilizing biological processes, such as photosynthesis, are increasingly being developed to evaluate the toxicity of environmental waters. We describe the isolation of the psychrotolerant Coccomyxa sp. LT4 from Scarisoara Ice Cave (Romania), representing the first report of green algae inhabiting this type of environment, and provide a preliminary assessment of its isolated thylakoids as novel biorecognition components for water toxicity screening. Photosynthetic activity and diuron sensitivity were measured amperometrically and compared with thylakoids from the reference cyanobacterium Synechococcus elongatus PCC 7942. The bioreceptor’s response to various pollutants and water salinities was also investigated. The microalgal thylakoids were more sensitive to diuron than the reference thylakoids, generated stable photocurrents across a broad salinity range and, when lyophilized with sucrose, retained their activity for over two years at −20 °C. Consequently, these thylakoids, isolated from a cold-environment microalga, provide a promising basis for developing biosensors for in situ toxicity screening in low-temperature aquatic ecosystems. Full article