Search Results (3,063)

We present the ML-CALMO framework, which integrates machine learning with queueing theory for last-mile delivery optimization under dynamic conditions. The system combines Long Short-Term Memory (LSTM) demand forecasting, Convolutional Neural Network (CNN) traffic prediction, and Deep Q-Network (DQN)-based routing with theoretical stability guarantees. Evaluation on modern benchmarks, including the 2022 Multi-Depot Dynamic VRP with Stochastic Road Capacity (MDDVRPSRC) dataset and real-world compatible data from OSMnx-based spatial extraction, demonstrates measurable improvements: 18.5% reduction in delivery time and +8.9 pp (≈12.2% relative) gain in service efficiency compared to current state-of-the-art methods, with statistical significance (p < 0.01). Critical limitations include (1) computational requirements that necessitate mid-range GPU hardware, (2) performance degradation under rapid parameter changes (drift rate > 0.5/min), and (3) validation limited to simulation environments. The framework provides a foundation for integrating predictive machine learning with operational guarantees, though field deployment requires addressing identified scalability and robustness constraints. All code, data, and experimental configurations are publicly available for reproducibility. Full article

Per- and polyfluoroalkyl substances (PFAS) are environmentally persistent organofluorines linked to cancer, organ dysfunction, and other health problems. This study used quantitative structure–property relationship (QSPR) and quantitative structure–activity relationship (QSAR) modeling to examine the binding of PFAS to estrogen receptor alpha (ERα) and beta (ERβ). Molecular docking of 14,591 PFAS compounds was performed, and docking scores were used as a measure of receptor affinity. QSPR models were built for two datasets: the ERα and ERβ top binders (TBs), and a set of commonly exposed (CE) PFAS. These models quantified how chemical descriptors influence binding affinity. Across the models, higher density and electrophilicity indicated positive correlations with affinity, while surface tension indicated negative correlations. Electrostatic descriptors, including HOMO energy and positive Fukui index (F⁺ max), were part of the models but showed inconsistent trends. The CE QSPR models displayed correlations that conflicted with those of the TB models. Following QSPR analysis, 66 QSAR models were developed using a mix of top binders and experimental data. These models achieved strong performance, with R² values averaging 0.95 for training sets and 0.78 for test sets, that indicated reliable predictive ability. To improve generalizability, large-set QSAR models were created for each receptor. After outlier removal, these models reached R² values of 0.68–0.71, which supports their use in screening structurally diverse PFAS. Overall, QSPR and QSAR analyses reveal key chemical features that influence PFAS–ER binding. This predictive approach provides a scalable framework to assess the binding interactions of structurally diverse PFAS to ERs and other nuclear receptors. All the codes, data, and the GUI visualization of the results are freely available at sivaGU/QSPR-QSAR-Molecular-Visualization-Tool. Full article

The Yangtze River fishing ban policy is a central measure in China’s watershed governance, and the adaptability of its policy tools and collaborative mechanisms directly influences the sustainability and effectiveness of basin management. This study systematically examines the evolution of policy themes, the characteristics of policy tool combinations, and their alignment with intergovernmental collaborative governance needs, drawing on 120 central government policy texts issued between 2002 and 2024. Using frequency analysis and policy tool coding, the findings reveal that (1) policy themes have shifted from fishery resource control to comprehensive ecological protection and, more recently, to integrated watershed management, thereby driving progressively higher demands for intergovernmental collaboration. (2) The policy tool structure has long been dominated by environmental tools, supplemented by supply-side tools, while demand-side tools remain underdeveloped. Imbalances persist, such as excessive emphasis on resource inputs over capacity building in supply-side tools, rigid constraints with limited flexibility in environmental tools, and a reliance on publicity while underutilizing market incentives in demand-side tools. (3) Tool combinations have adapted to changing collaboration needs, evolving from rigid constraints and fiscal subsidies to institutional frameworks and cross-regional cooperation, ultimately forming a governance model characterized by systemic guarantees and diversified collaboration. Based on these findings, this study recommends strengthening long-term governance mechanisms, improving cross-regional collaborative structures, authorizing local governments to design context-specific implementation details, enhancing fishermen’s livelihood security and social development, expanding public participation and oversight, and exploring market mechanisms for realizing ecological product value. These measures aim to advance collaborative governance in the Yangtze River Basin and foster a balanced integration of ecological protection and social development. Full article

Model-based simulation of farmland evapotranspiration and crop growth facilitates precise monitoring of crop and farmland dynamics with high efficiency, real-time responsiveness, and continuity. However, there are still significant limitations in using crop models to simulate the dynamic process of evapotranspiration and cotton growth in mulched drip-irrigated cotton fields under different irrigation gradients. The SWAP crop growth model effectively simulates crop growth. However, the original SWAP model lacks a dedicated module to consider the impact of mulching on cotton field evapotranspiration and cotton dry matter mass. Therefore, in this study, the source codes of the soil moisture, evapotranspiration, and crop growth modules of the SWAP model were improved. The evapotranspiration and cotton growth data of the mulched drip-irrigated cotton fields under three irrigation treatments (W1 = 3360 m³·hm⁻², W2 = 4200 m³·hm⁻², and W3 = 5040 m³·hm⁻²) in 2023 and 2024 at the Xinjiang Modern Water-saving Irrigation Key Experimental Station of the Corps were used to verify the simulation accuracy of the improved SWAP model. Research shows the following: (1) The average relative errors of the simulated evapotranspiration, leaf area index, and dry matter weight of cotton in the improved SWAP crop growth model are all <20% compared with the measured values. The root means square errors of the three treatments (W1, W2, and W3) ranged from 0.85 to 1.38 mm, from 0.03 to 0.18 kg·hm⁻², and 55.01 to 69 kg·hm⁻², respectively. The accuracy of the improved model in simulating evapotranspiration and cotton growth in the mulched cotton field increased by 37.49% and 68.25%, respectively. (2) The evapotranspiration rate of cotton fields is positively correlated with the irrigation water volume and is most influenced by meteorological factors such as temperature and solar radiation. During the flowering stage, evapotranspiration accounted for 62.83%, 62.09%, 61.21%, 26.46%, 40.01%, and 38.8% of the total evapotranspiration. Therefore, the improved SWAP model can effectively simulate the evaporation and transpiration of the mulched drip-irrigated cotton fields in the Manas River Basin. This study provides a scientific basis for the digital simulation of mulched farmland in the arid regions of Northwest China. Full article

Welding-based manufacturing and joining processes are extensively used in various areas of industrial production. While welding has been used as a primary method of joining in many applications, its capability to fabricate metal components such as the Wire Arc Additive Manufacturing (WAAM) method should not be undermined. WAAM is a promising method for producing large metal parts, but it is still prone to defects such as porosity that can reduce structural reliability. To ensure these defects are found and measured in a consistent way, inspection methods must be tied directly to code-based acceptance limits. In this work, a three-pass WAAM joint specimen was made in a welded-joint configuration using robotic GMAW-based deposition. This setup provided a stable surface for Phased Array Ultrasonic Testing (PAUT) while still preserving WAAM process conditions. The specimen, which was intentionally seeded with porosity, was divided into five zones and inspected using the 6 dB drop method for defect length and amplitude-based classification, with AWS D1.5 serving as the reference code. The results showed that porosity was not uniform across the bead. Zones 1 and 3 contained the longest clusters (15 mm and 16.5 mm in length) and exceeded AWS length thresholds, while amplitude-based classification suggested they were less critical than other regions. This difference shows the risk of relying on only one criterion. By embedding these results in a DMAIC (Define–Measure–Analyze–Improve–Control) workflow, the inspection outcomes were linked to likely causes such as unstable shielding and cooling effects. Overall, the study demonstrates a code-referenced, dual-criteria approach that can strengthen quality control for WAAM. Full article

Carbon-aware AI demands clear links between algorithmic choices and verified emission outcomes. This study measures and steers the carbon footprint of swarm-based optimization in HPC by coupling a job-level Emission Impact Metric with sub-minute power and grid-intensity telemetry. Across 480 runs covering 41 algorithms, we report grams CO₂ per successful optimisation and an efficiency index $\eta$ (objective gain per kg CO₂). Results show faster swarms achieve lower integral energy: Particle Swarm emits 24.9 g CO₂ per optimum versus 61.3 g for GridSearch on identical hardware; Whale and Cuckoo approach the best $\eta$ frontier, while L-SHADE exhibits front-loaded power spikes. Conservative scale factor schedules and moderate populations reduce emissions without degrading fitness; idle-node suppression further cuts leakage. Agreement between CodeCarbon, MLCO2, and vendor telemetry is within 1.8%, supporting reproducibility. The framework offers auditable, runtime controls (throttle/hold/release) that embed carbon objectives without violating solution quality budgets. Full article

This study examined child outcomes for five minimally verbal (or non-speaking) autistic preschoolers who participated in cascading coaching programs in which naturalistic developmental behavioral intervention (NDBI) techniques were taught to graduate student clinicians and Hispanic caregivers (three who primarily spoke English, and two who spoke Spanish). While prior studies reported on adult participant outcomes, this study analyzed child multimodal communication outcomes, using multiple baselines/probes single case experimental designs across contexts. Neurodiversity-affirming and culturally responsive principles were embedded within the intervention procedures. Following the introduction of a coached NDBI, all five children (three who received the intervention in English and two who received the intervention in Spanish) demonstrated increased use of (a) the total targeted communicative responses and (b) the targeted unprompted communicative responses, across both student clinician-led and caregiver-led play sessions. The Tau-U effect size measures revealed large-to-very large effects across all of the variables. Overall, higher rates of communication responses were observed during student clinician-led sessions than in caregiver-led sessions. Additionally, behavioral coding of the multimodal response forms (e.g., gestures, aided augmentative and alternative communication, signs, vocal words) using the Communication Matrix revealed that the children used a variety of response topographies during the intervention sessions beyond their preferred communication mode (e.g., signs for three participants). Four of the five children used symbolic communication forms consistently across both caregiver and student clinician-led sessions. Importantly, adults’ reinforcement of pre-symbolic or less advanced communication forms during the intervention did not inhibit the use of more advanced forms. Full article

The aim of this retrospective clinical pilot study is to evaluate multiparametric ultrasound liver parenchyma assessments in the diagnosis of Osler’s disease, and to detect micro-shunts using SRCEUS with quantifications at the capillary level. Material/Method: All examinations were performed by an experienced examiner with a multi-frequency probe on a high-resolution matrix ultrasound device (SC 7-1U), convex probe (Mindray A 20), and were stored digitally in the PACS system. Vascular ultrasound was performed using colour-coded Doppler ultrasound (CCDS) and ultrasound microangiography (UMA). The recent M-Ref tool was utilised for the purpose of liver tissue characterisation, encompassing the domains of shear wave elastography, fat evaluation, and viscosity. Dynamic CEUS, HiFR CEUS, and SR CEUS were performed after the intravenous bolus injection of 1–2.4 mL of ultrasound contrast agent (SonoVue^®). Measurements of SR CEUS capillary changes were performed independently by PACS-stored digital cine loops up to 5 s. Results: In the context of angiomas or haemangiomas, the initial contrast enhancement of echogenic or almost echogenic foci within 25 s without late wash-out was observed in 5/10 cases. In the evaluation of microvasculature, the presence of capsule-proximal shunts in Osler’s disease was observed, resulting in the identification of increased numbers of dilated capillaries within both peripheral and central shunts. In the control group, general liver tissue changes (20 cases) were observed in instances of inflammation (3/20 cases), peripherally in 4/20 cases with micro-shunts in altered parenchyma. In the context of multiparametric ultrasound, 16 out of 30 cases exhibited elevated fibrosis values, with a maximum recorded as high as 1.7 m/s, and in 13 out of 30 cases, there was an increase in fat values up to 0.65 dB/cm/MHz, indicative of moderate steatosis. Additionally, in seven cases, there was an increase in viscosity values up to 2.7 Pa·s, suggesting reactive changes. Conclusions: Recent advancements in medical imaging technology, specifically SR CEUS contrast ultrasound imaging, have led to the development of novel diagnostic tools that facilitate the evaluation of tissue and haemodynamic changes, in addition to capillary alterations, associated with Osler’s disease. Full article

ADHD classification has traditionally relied on accelerometer-derived tabular features, which summarise static activity but fail to capture spatial-temporal patterns, potentially limiting model performance. We developed a multimodal deep learning framework that transforms raw accelerometer signals into images and integrates them with clinical tabular data, enabling the joint exploration of dynamic activity patterns and static clinical characteristics. Data were collected from children aged 7–13 years, including accelerometer recordings from Apple Watches and clinical measures from standardised questionnaires. Deep learning models for image feature extraction and multiple fusion strategies were evaluated to identify the most effective representation and integration method. Our analyses indicated that combining activity images with clinical variables facilitated the classification of ADHD, with the ViT-BiLSTM model using cross-attention fusion achieving the highest performance. These findings suggest that multimodal learning can become a robust approach to ADHD classification by leveraging complementary information from activity dynamics and clinical data. Our framework and code will be made publicly available to support reproducibility and future research. Full article

Precise kinematic positioning using low-cost android smartphones remains a significant research focus, particularly with the growing integration of Global Navigation Satellite System (GNSS) capabilities in these devices. This research explores the accuracy of the single-frequency quad-constellation carrier-phase-based real-time kinematic (RTK) and code-only relative positioning (RP) techniques using Xiaomi 11T smartphone for transportation applications. Kinematic GNSS measurements from Xiaomi 11T are acquired using vehicle trajectory in New Aswan City, Egypt; then, the acquired data are processed utilizing various constellation combinations scenarios including GPS-only, GPS/Galileo, GPS/GLONASS, GPS/BeiDou, and GPS/Galileo/GLONASS/BeiDou. The processing outputs demonstrate that sub-meter and meter-level horizontal position accuracy is achieved for both scenarios using RTK and RP, respectively. The quad-constellation processing scenario has superiority with 0.456 m and 1.541 m root mean square error (RMSE) values in the horizontal component involving RTK and RP, respectively; on the other hand, the GPS-only solution achieved 0.766 m and 1.703 m horizontal RMSE values using RTK and RP, respectively. Based on the attained accuracy, the cost-effective Xiaomi 11T provides sufficient positioning accuracy to support transportation applications such as an intelligent transportation system, urban/public transportation monitoring, fleet management, vehicle tracking, and mobility analysis, aiding smart city planning and transportation system optimization. Full article

Smart polyester materials with embedded near-infrared (NIR) functionalities offer a promising pathway for low-cost, covert tagging, and object identification. In this study we present the development and characterization of polyester packaging surfaces printed with spectrally matched twin dyes that are invisible under visible light but selectively absorbed in the NIR region. The dye patterns were applied using a Direct-to-Film transfer (DTF) method onto polyester substrates. To validate their optical behavior, we applied a dual measurement approach. Laboratory grade NIR absorbance spectroscopy was used to characterize the spectral profiles of the twin dyes in the 400–900 nm range. A custom photodiode-based detection system was constructed to evaluate the feasibility of low-cost, embedded NIR absorbance sensing. Results from both methods show correlation in absorbance contrast between the dye pairs, confirming their suitability for spectral tagging. The developed materials were evaluated in a real-world detection scenario using commercially available NIR cameras. Under dark field conditions with edge illuminated planar lighting, the twin dye patterns were successfully recognized through custom software, enabling non-contact identification and spatial localization of the NIR codes. This work presents a low-cost, scalable approach for smart packaging applications based on optical detection of actively illuminated twin dyes using accessible NIR imaging systems. Full article

The topic of the present study is the aerodynamic performance of a Natural Laminar Flow (NLF) wing for UAVs at low speed. The basis is a thoroughly tested NLF airfoil in the wind tunnel of NASA which is well-customized for light aircrafts. The aim of this work is the numerical verification that a typical wing design (tapered with moderate aspect ratio and wash-out), being constructed out of aerodynamically highly efficient NLF airfoils during cruise, can deliver high aerodynamic loading under minimal freestream turbulence as well as realistic atmospheric conditions of intermediate turbulence. Thus, high mission flexibility is achieved, e.g., short take off/landing capabilities on the deck of ship where moderate air turbulence is prevalent. Special attention is paid to the effect of the Wing Tip Vortex (WTV) under minimal inflow turbulence regimes. The flight conditions are take off or landing at moderate Reynolds number, i.e., one to two millions. The numerical simulation is based on an open source CFD code and parallel processing on a High Performance Computing (HPC) platform. The aim is the identification of both mean flow and turbulent structures around the wing and subsequently the formation of the wing tip vortex. Due to the purely three-dimensional character of the flow, the turbulence is resolved with advanced modeling, i.e., the Improved Delayed Detached Eddy Simulation (IDDES) which is well-customized to switch modes between Delayed Detached Eddy Simulation (DDES) and Wall-Modeled Large Eddy Simulation (WMLES), thus increasing the accuracy in the shear layer regions, the tip vortex and the wake, while at the same time keeping the computational cost at reasonable levels. IDDES also has the capability to resolve the transition of the boundary layer from laminar to turbulent, at least with engineering accuracy; thus, it serves as a high-fidelity turbulence model in this work. The study comprises an initial benchmarking of the code against wind tunnel measurements of the airfoil and verifies the adequacy of mesh density that is used for the simulation around the wing. Subsequently, the wing is positioned at near-stall conditions so that the aerodynamic loading, the kinematics of the flow and the turbulence regime in the wing vicinity, the wake and far downstream can be estimated. In terms of the kinematics of the WTV, a thorough examination is attempted which comprises its inception, i.e., the detachment of the boundary layer on the cut-off wing tip, the roll-up of the shear layer to form the wake and the motion of the wake downstream. Moreover, the effect of inflow turbulence of moderate intensity is investigated that verifies the bibliography with regard to the performance degradation of static airfoils in a turbulent atmospheric regime. Full article

The practice of the assessment of the safety of existing masonry structures is related to the safety of people’s lives and property. However, the current assessment method, described in “GB50292-2015 Standard for appraisal of reliability of civil buildings”, fails to fully consider the uncertainty-related characteristics of the structures, which easily leads to unreasonable assessment results. This paper proposes a method of safety assessment for existing masonry structures that considers the updating of resistance and load probability models and different member weights. First, based on the resistance probability model measured in the field, the resistance model in the current code (GB50292-2015) is updated through Bayesian theory. Then, the variable load model is updated for different subsequent working years through the equal-exceeding-probability method. Finally, the safety grade of the existing masonry structure is obtained by the analytic hierarchy process, using the affiliation set as the assessment index. This method of analysis solves the problem relating to the “jump” in the middle of the break-point of the traditional safety grading standard. It also fully considers the uncertainty-related characteristics of the existing structure, and its evaluation results align with the existing structure’s actual situation, which is critical to the assessment of the safety of the existing masonry structure. Full article

Routine Early Intervention services are an ideal context to evaluate parent-mediated intervention (PMI) delivery. While effectiveness research suggests that receiving manualized PMIs positively affects caregivers’ learning and use of intervention strategies, the impact of other aspects of delivery, such as PMI adaptation, on caregiver engagement and learning is less clear. The current study aimed to address this gap by closely characterizing the delivery and associated outcomes of an autism PMI, Project ImPACT, within an Early Intervention (EI) Part C system. In total, 21 EI providers and 23 caregivers of children with social communication delays participated. Following training in Project ImPACT, the providers submitted videos of their Project ImPACT sessions as part of routine service delivery. The sessions were behaviorally coded for Project ImPACT coaching fidelity and instances in which Project ImPACT was adapted. After each session, the caregivers rated their participatory engagement and therapeutic alliance. Before and immediately following the intervention, the caregivers also completed measures of their self-efficacy and their child’s social communication skills, and their use of Project ImPACT strategies (i.e., fidelity) was behaviorally coded. The results demonstrated that EI providers’ Project ImPACT coaching fidelity was not related to caregiver ratings of therapeutic alliance or participatory engagement at the session level. Augmenting Project ImPACT sessions was associated with higher caregiver ratings of therapeutic alliance but not with participatory engagement. Although provider coaching fidelity was not associated with changes in caregiver ratings of self-efficacy, it was associated with caregiver use of Project ImPACT strategies focused on teaching their children new skills. There was no association between provider fidelity and caregiver report of child social communication outcomes. The current study highlights the complicated relationship between the delivery of autism PMIs and caregiver-reported outcomes. The findings highlight the value of holistic delivery models that support adaptations in response to child- and family-level factors. Full article

Research that explores which computational thinking (CT) skills resonate with the abilities and interests of preschoolers is limited. Even more limited is the availability of assessments that can be used to measure young children’s CT learning. This study describes the process employed to generate a series of developmentally appropriate assessment tasks designed to draw inferences of young children’s learning of CT components and engagement in CT practices. Assessment tasks were designed and pilot-tested with a sample of 57 preschool children in Virginia and California. Item responses were coded and analyzed using classical test theory to examine item difficulty and discrimination. The reliability of the final set of items was calculated using Cronbach’s alpha. The overall difficulty of the items was relatively high, and discrimination values were generally adequate. The total summated score was also found to be reliable. Our assessment and design process reveals challenges and shares ideas for item formats that allow gathering evidence of young children’s CT learning. Full article