Search Results (10,321)

Background: The efficient control of hygiene and Campylobacter’s contamination status at various steps of poultry meat production is essential for the prevention of Campylobacter transmission to humans. Microbiological methods are laborious and time-consuming, and molecular methods of detection are often too skill- and infrastructure-demanding. Methods: We have developed CampyTube, a simple and user-friendly format for the integration of isothermal DNA amplification with embedded instrument-free detection on a miniaturized lateral flow test in a single vial. All test components, from the dry amplification reagents to the mini lateral flow tests, are incorporated into a standard single vial, which is closed after the addition of the liquid sample and never has to be opened again. This ensures the absolute prevention of carry-over contamination and makes the system very safe and simple to use in point-of-need settings. Results: As few as 60 Campylobacter genome copies per reaction could be successfully detected with CampyTube. We have primarily developed and evaluated CampyTube for the detection of Campylobacter in chicken neck skin samples and could reach 100% sensitivity and 100% specificity in the samples exceeding the regulatory limit of 1000 CFU/g confirmed microbiologically, while the sensitivity in all samples that tested positive using qPCR (1.4 × 10²–2.5 × 10⁶ genome copies/g) was 71.1%. We discuss the impact of sample preparation on CampyTube performance and suggest further options for test optimization. Conclusions: CampyTube is a highly versatile and efficient, yet simple, affordable, and material-saving system that can be adapted for other targets and sample types. Full article

Porous intermetallic compounds have the properties of porous materials as well as a combination of covalent and metallic bonds, and they exhibit high porosity, structural stability, and corrosion resistance. In this work, a porous TiNi₃ intermetallic compound was fabricated through reactive synthesis of elemental powders. Next, detailed studies of its phase composition and pore structure characteristics at different sintering temperatures, as well as its corrosion behavior against an alkaline environment, were carried out. The results show that the as-prepared porous TiNi₃ intermetallic compound has abundant pore structures, with an open porosity of 56.5%, which can be attributed to a combination of the bridging effects of initial powder particles and the Kirkendall effect occurring during the sintering process. In 1 M KOH solution, a higher positive corrosion potential (−0.979 V_SCE) and a lower corrosion current density (1.18 × 10⁻⁴ A∙cm⁻²) were exhibited by the porous TiNi₃ intermetallic compound, compared to the porous Ni, reducing the thermodynamic corrosion tendency and the corrosion rate. The corresponding corrosion process is controlled by the charge transfer process, and the increased charge transfer resistance value (713.9 Ω⋅cm²) of TiNi₃ makes it more difficult to charge-transfer than porous Ni (204.5 Ω⋅cm²), thus decreasing the rate of electrode reaction. The formation of a more stable passive film with the incorporation of Ti contributes to this improved corrosion resistance performance. Full article

Background/Objectives: Cannabidiol (CBD) is a non-intoxicating cannabinoid touted for a variety of medical benefits, including alleviation of anxiety. While legalization of hemp-derived products in the United States (containing ≤0.3% delta-9-tetrahydrocannabinol [d9-THC] by weight) has led to a rapid increase in the commercialization of hemp-derived CBD products, most therapeutic claims have not been substantiated using clinical trials. This trial aimed to assess the impact of 6 weeks of treatment with a proprietary hemp-derived, full-spectrum, high-CBD sublingual solution similar to those available in the marketplace in patients with anxiety. Methods: An open-label pilot clinical trial (NCT04286594) was conducted in 12 patients with at least moderate levels of anxiety. Patients self-administered a hemp-derived, high-CBD sublingual solution twice daily during the 6-week trial (target daily dose: 30 mg/day CBD). Clinical change over time relative to baseline was assessed for anxiety, mood, sleep, and quality of life, as well as changes in cognitive performance on measures of executive function and memory. Safety and tolerability of the study product were also evaluated. Results: Patients reported significant reductions in anxiety symptoms over time. Concurrent improvements in mood, sleep, and relevant quality of life domains were also observed, along with stable or improved performance on all neurocognitive measures. Few side effects were reported, and no serious adverse events occurred. Conclusions: These pilot findings provide initial support for the efficacy and tolerability of the hemp-derived, high-CBD product in patients with moderate-to-severe levels of anxiety. Double-blind, placebo-controlled studies are indicated to obtain robust data regarding efficacy and tolerability of these types of products for anxiety. Full article

Rural regions face significant barriers to adopting IoT technologies, due to limited connectivity, energy constraints, and poor technical infrastructure. While urban environments benefit from advanced digital systems and cloud services, rural areas often lack the necessary conditions to deploy and evaluate secure and autonomous IoT solutions. To help overcome this gap, this paper presents the Smart Rural IoT Lab, a modular and reproducible testbed designed to replicate the deployment conditions in rural areas using open-source tools and affordable hardware. The laboratory integrates long-range and short-range communication technologies in six experimental scenarios, implementing protocols such as MQTT, HTTP, UDP, and CoAP. These scenarios simulate realistic rural use cases, including environmental monitoring, livestock tracking, infrastructure access control, and heritage site protection. Local data processing is achieved through containerized services like Node-RED, InfluxDB, MongoDB, and Grafana, ensuring complete autonomy, without dependence on cloud services. A key contribution of the laboratory is the generation of structured datasets from real network traffic captured with Tcpdump and preprocessed using Zeek. Unlike simulated datasets, the collected data reflect communication patterns generated from real devices. Although the current dataset only includes benign traffic, the platform is prepared for future incorporation of adversarial scenarios (spoofing, DoS) to support AI-based cybersecurity research. While experiments were conducted in an indoor controlled environment, the testbed architecture is portable and suitable for future outdoor deployment. The Smart Rural IoT Lab addresses a critical gap in current research infrastructure, providing a realistic and flexible foundation for developing secure, cloud-independent IoT solutions, contributing to the digital transformation of rural regions. Full article

Flocculants are indispensable in water and wastewater treatment, enabling the aggregation and removal of suspended particles, colloids, and emulsions. However, the conventional development and application of flocculants rely heavily on empirical methods, which are time-consuming, resource-intensive, and environmentally problematic due to issues such as sludge production and chemical residues. Recent advances in machine learning (ML) have opened transformative avenues for the design, optimization, and intelligent application of flocculants. This review systematically examines the integration of ML into flocculant research, covering algorithmic approaches, data-driven structure–property modeling, high-throughput formulation screening, and smart process control. ML models—including random forests, neural networks, and Gaussian processes—have successfully predicted flocculation performance, guided synthesis optimization, and enabled real-time dosing control. Applications extend to both synthetic and bioflocculants, with ML facilitating strain engineering, fermentation yield prediction, and polymer degradability assessments. Furthermore, the convergence of ML with IoT, digital twins, and life cycle assessment tools has accelerated the transition toward sustainable, adaptive, and low-impact treatment technologies. Despite its potential, challenges remain in data standardization, model interpretability, and real-world implementation. This review concludes by outlining strategic pathways for future research, including the development of open datasets, hybrid physics–ML frameworks, and interdisciplinary collaborations. By leveraging ML, the next generation of flocculant systems can be more effective, environmentally benign, and intelligently controlled, contributing to global water sustainability goals. Full article

Restaurants and open markets generate considerable quantities of organic waste. Converting these residues into poultry feed ingredients offers a sustainable disposal route. This study aimed to evaluate the nutritional and sensory viability of a novel feed complement formulated from Bonito fish meal (Sarda chiliensis chiliensis) and Única potato peel flour (Solanum tuberosum L. cv. Única). This study was conducted in three phases: (i) production and nutritional characterization of the two by-product flours; (ii) formulation of a 48:52 (w/w) blend, incorporated into broiler diets at 15%, 30%, and 45% replacement levels over a 7-week trial divided into starter (3 weeks), grower (3 weeks), and finisher (1 week) phases; and (iii) assessment of growth performance (weight gain, final weight, and feed conversion ratio), followed by a sensory evaluation of the resulting meat using a Check-All-That-Apply (CATA) analysis. The Bonito fish meal exhibited 50.78% protein, while the Única potato peel flour was rich in carbohydrates (74.08%). The final body weights of broiler chickens ranged from 1872.1 to 1886.4 g across treatments, and the average feed conversion ratio across all groups was 0.65. Replacing up to 45% of commercial feed with the formulated complement did not significantly affect growth performance (p > 0.05). Sensory analysis revealed that meat from chickens receiving 15% and 45% substitution levels was preferred in terms of aroma and taste, whereas the control group was rated higher in appearance. These findings suggest that the formulated feed complement may represent a viable poultry-feed alternative with potential sensory and economic benefits, supporting future circular-economy strategies. Full article

Obstructive sleep apnea (OSA) is a prevalent disorder linked to metabolic complications such as diabetes and cardiovascular disease. By fragmenting normal sleep architecture, OSA perturbs the growth hormone/insulin-like growth factor (GH/IGF) axis and alters circulating levels of IGF-binding proteins (IGFBPs). A prior clinical observation of elevated IGFBP4 in OSA patients motivated the present investigation in a controlled animal model. Building on the previously reported protocol, OSA was induced in male C57BL/6 mice (9–12 weeks old) through intralingual injection of polytetrafluoroethylene (PTFE), producing tongue hypertrophy, intermittent airway obstruction, and hypoxemia. After 8–10 weeks, the study assessed (1) hypoxia biomarkers—including HIF-1α and VEGF expression—and (2) neurobehavioral outcomes in anxiety and cognition using the open-field and novel object recognition tests. PTFE-treated mice exhibited a significant increase in circulating IGFBP4 versus both baseline and control groups. Hepatic Igfbp4 mRNA was also upregulated. Behaviorally, PTFE mice displayed heightened anxiety-like behavior and impaired novel object recognition, paralleling cognitive deficits reported in human OSA. These findings validate the PTFE-induced model as a tool for studying OSA-related hypoxia and neurocognitive dysfunction, and they underscore IGFBP4 as a promising biomarker and potential mediator of OSA’s systemic effects. Full article

Postharvest losses amongst small-scale farmers in developing countries are high due to inadequate resources and infrastructure. Among the various affected crops, tomatoes are particularly vulnerable; however, studies on postharvest losses of most fruits and vegetables are limited. Therefore, this study aimed to assess postharvest tomato losses under different production systems within the small-scale supply chain using the indirect assessment (questionnaires and interviews) and direct quantification of losses. Farmers reported tomato losses due to insects (82.35%), cracks, bruises, and deformities (70.58%), and diseases (64.71%). Chemical sprays were the main form of pest and disease control reported by all farmers. The direct quantification sampling data revealed that 73.07% of the tomatoes were substandard at the farm level, with 47.92% and 25.15% categorized as medium-quality and poor-quality, respectively. The primary contributors to the losses were decay (39.92%), mechanical damage (31.32%), and blotchiness (27.99%). Postharvest losses were significantly higher under open-field production systems compared to closed tunnels. The fungi associated with decay were mainly Geotrichum, Fusarium spp., and Alternaria spp. These findings demonstrate the main drivers behind postharvest losses, which in turn highlight the critical need for intervention through training and support, including the use of postharvest loss reduction technologies to enhance food security. Full article

This study takes four parallel axial-flow pumps (three in operation + one on standby) as the research object. Using a 1D–3D coupling method, it explores the flow characteristics of axial-flow pumps under different startup strategies during multi-pump parallel operation. Through comparative analysis, the following conclusions are drawn: when all three pumps start simultaneously, the internal pressure exceeds the rated head by 23.43%, and the reverse flow reaches 10.57% of the rated flow. When starting the pumps sequentially with 5 s intervals, the pressure can be reduced to 11.41% above the rated head, but the reverse flow increases to 13.87%. Further extending the startup interval to 15 s results in only minimal improvements compared to 5 s intervals: the maximum internal pressure and maximum reverse flow decrease by just 0.97% and 0.05%, respectively. When valve coordination is added to the 5 s sequential startup strategy (pre-opening the valve to 60% before pump startup), the pressure exceeds the rated head by 10.49%, and the reverse flow exceeds the rated flow by 6.04%. In this scenario, the high-pressure areas and high-turbulence zones on the blade back surfaces are significantly reduced, achieving optimal flow stability. Therefore, the parallel system startup should adopt a coordinated strategy combining moderate time intervals with 60% valve pre-opening. This approach can both avoid excessive pressure impact and effectively control reverse flow phenomena, providing an important basis for optimizing the startup of multi-pump parallel systems. Full article

A two-phase closed thermosyphon (TPCT), a gravity-assisted heat pipe, is a highly efficient heat transmitter involving liquid–vapor phase change. It is used in many applications, including heat spreading, thermal management and control, and energy saving. The main objective of this study is to investigate the effects of the operating conditions for a thermosyphon used in solar water heaters. The study particularly focuses on the influence of the inclination angle. Thus, a comprehensive simulation model is developed using the volume of fluid (VOF) approach. Complex and related phenomena, including two-phase flow, phase change, and heat exchange, are taken into account. To implement the model, an open-source CFD toolbox based on finite volume formulation, OpenFOAM, is used. The model is then validated by comparing numerical results to the experimental data from the literature. The obtained results show that the simulation model is reliable for investigating the effects of various operating conditions on the transient and steady-state behavior of the thermosyphon. In fact, bubble creation, growth, and advection can be tracked correctly in the liquid pool at the evaporator. The effects of the designed operating conditions on the heat transfer parameters are also discussed. In particular, the optimal tilt angle is shown to be 60° for the intermediate saturation temperature (<50 °C) and 90° for the larger saturation temperature (>60 °C). Full article

This work focuses on the possibilities of generating synthetic data for machine learning in hazard prediction in area-based speed monitoring systems. The purpose of the research conducted was to develop a methodology for generating realistic synthetic data to support the design of a continuous vehicle speed monitoring system to minimize the risk of traffic accidents caused by speeding. The SUMO traffic simulator was used to model driver behavior in the analyzed area and within a given road network. Data from OpenStreetMap and field measurements from over a dozen speed detectors were integrated. Preliminary tests were carried out to record vehicle speeds. Based on these data, several simulation scenarios were run and compared to real-world observations using average speed, the percentage of speed limit violations, root mean square error (RMSE), and percentage compliance. A new metric, the Combined Speed Accuracy Score (CSAS), has been introduced to assess the consistency of simulation results with real-world data. For this study, a basic hazard prediction model was developed using LoRaWAN sensor network data and environmental contextual variables, including time, weather, location, and accident history. The research results in a method for evaluating and selecting the simulation scenario that best represents reality and drivers’ propensities to exceed speed limits. The results and findings demonstrate that it is possible to produce synthetic data with a level of agreement exceeding 90% with real data. Thus, it was shown that it is possible to generate synthetic data for machine learning in hazard prediction for area-based speed control systems using traffic simulators. Full article

As Chinese open-pit mines progressively transition to deeper operations, challenges such as rising stripping ratios, declining slope stability, and environmental degradation have become increasingly pronounced. The sustainability of traditional open-pit mining models faces substantial challenges. Underground mining, offering higher resource recovery rates and minimal environmental disruption, is emerging as a pivotal technological pathway for the green transformation of mining. Consequently, the transition from open-pit to underground mining has emerged as a central research focus within mining engineering. This paper provides a comprehensive review of key technological advancements in this transition, emphasizing core issues such as mine development system selection, mining method choices, slope stability control, and crown pillar design. A typical case study of the Anhui Xinqiao Iron Mine is presented to analyze its engineering approaches and practical experiences in joint development, backfilling mining, and ecological restoration. The findings indicate that the mine has achieved multi-objective optimization of resource utilization, environmental coordination, and operational capacity while ensuring safety and recovery efficiency. This offers a replicable and scalable technological demonstration for the green transformation of similar mines around the world. Full article

Superhydrophobic and superoleophilic nanofibrous or microfibrous membranes are regarded as ideal oil/water separation materials owing to their controllable porosity, superior separation efficiency, and ease of operation. However, developing efficient, scalable, and environmentally friendly strategies for fabricating such membranes remains a significant challenge. In this study, isotactic polypropylene (iPP) fibrous membranes with morphologies ranging from ellipsoidal stacking to microfiber stacking were successfully fabricated via a multistage stretching extrusion and leaching process using in situ microfibrillar composites (MFCs). The results establish a significant relationship between microfiber morphology and membrane oil adsorption performance. Compared with membranes formed from high-aspect-ratio microfibers, those comprising short microfibers feature larger pores and a more open structure, which enhances their oil adsorption capacity. Among the fabricated membranes, the iPP membrane with an ellipsoidal stacking morphology exhibits optimal performance, achieving a porosity of 65% and demonstrating both hydrophobicity and superoleophilicity, with a silicone oil adsorption capacity of up to 312.5%. Furthermore, this membrane shows excellent reusability and stability over ten adsorption–desorption cycles using chloroform. This study presents a novel approach leveraging in situ microfibrillar composites to prepare high-performance oil/water separation membranes in this study, underscoring their considerable promise for practical use. Full article

The evaluation of large language models (LLMs) increasingly relies on other LLMs acting as automated judges. While this approach offers scalability and efficiency, it raises serious concerns regarding evaluator reliability, positional bias, and ranking stability. This paper presents a scalable framework for diagnosing positional bias and instability in LLM-based evaluation by using controlled pairwise comparisons judged by multiple independent language models. The system supports mirrored comparisons with reversed response order, prompt injection, and surface-level perturbations (e.g., paraphrasing, lexical noise), enabling fine-grained analysis of evaluator consistency and verdict robustness. Over 3600 pairwise comparisons were conducted across five instruction-tuned open-weight models using ten open-ended prompts. The top-performing model (gemma:7b-instruct) achieved a 66.5% win rate. Evaluator agreement was uniformly high, with 100% consistency across judges, yet 48.4% of verdicts reversed under mirrored response order, indicating strong positional bias. Kendall’s Tau analysis further showed that local model rankings varied substantially across prompts, suggesting that semantic context influences evaluator judgment. All evaluation traces were stored in a graph database (Neo4j), enabling structured querying and longitudinal analysis. The proposed framework provides not only a diagnostic lens for benchmarking models but also a blueprint for fairer and more interpretable LLM-based evaluation. These findings underscore the need for structure-aware, perturbation-resilient evaluation pipelines when benchmarking LLMs. The proposed framework offers a reproducible path for diagnosing evaluator bias and ranking instability in open-ended language tasks. Future work will apply this methodology to educational assessment tasks, using rubric-based scoring and graph-based traceability to evaluate student responses in technical domains. Full article

Background and objectives: Trismus is a frequent and debilitating complication in people with head and neck cancer (HNC) which leads to significant functional limitations and reduced quality of life. Rehabilitation interventions are commonly recommended to manage or prevent trismus. However, in many randomized controlled trials (RCTs), the theoretical justification for these interventions is poorly articulated, and the underlying biological or physiological mechanisms are not described in detail, limiting our understanding of why certain treatments may (or may not) work. This review aimed to identify and analyze how RCTs report the rationale for rehabilitation interventions and the explanations used to manage this population. Materials and Methods: A scoping review was conducted in accordance with the PRISMA-ScR guidelines. Five databases (PubMed, PEDro, Web of Science, Scopus, and EMBASE) were searched up to May 2025 for RCTs evaluating rehabilitation interventions for the management or prevention of treatment-induced trismus in patients with HNC. Data were extracted and synthesized narratively, focusing on the type of intervention, the rationale for its use, and the proposed mechanisms of action. Results: Of 2215 records identified, 24 RCTs met the inclusion criteria. Thirteen studies focused on preventive interventions—primarily exercise therapy—while the remainder addressed established trismus using exercise, manual therapy, electrotherapy, or combined treatment modalities. The rationales provided for intervention selection were heterogeneous and often lacked depth, with most studies justifying interventions based on their potential to improve mouth opening or reduce fibrosis but rarely grounding these claims in detailed pathophysiological models. Only half of the studies provided any mechanistic explanation for the intervention’s effects, and these were typically generic or speculative. Conclusions: RCTs investigating rehabilitation interventions for treatment-induced trismus in patients with HNC frequently lack comprehensive rationales and mechanistic explanations for their interventions. This gap limits the ability to refine and optimize treatment approaches, as the underlying processes driving clinical improvements remain poorly understood. Future research should be guided by theoretical models and include objective outcomes to better elucidate the mechanisms of action of interventions to inform clinical practice. Full article