Search Results (1,627)

The formation and stability of river ice covers in regulated waterways are critical for uninterrupted hydro-electric operations. This study investigates the modelling of ice cover development in the Beauharnois Canal along the St. Lawrence River with the presence and absence of ice booms. Ice booms are deployed in this canal to promote the rapid formation of a stable ice cover during freezing events, minimizing disruptions to dam operations. Remote sensing data were used to assess the spatial extent and temporal evolution of an ice cover and to calibrate the river ice model RIVICE. The model was applied to simulate ice formation for the 2019–2020 ice season, first for the canal with a series of three ice booms and then rerun under a scenario without booms. Comparative analysis reveals that the presence of ice booms facilitates the development of a relatively thinner and more uniform ice cover. In contrast, the absence of booms leads to thicker ice accumulations and increased risk of ice jamming, which could impact water management and hydroelectric generation operations. Computational efficiencies of the RIVICE model were also sought. RIVICE was originally compiled with a Fortran 77 compiler, which restricted modern optimization techniques. Recompiling with NVFortran significantly improved performance through advanced instruction scheduling, cache management, and automatic loop analysis, even without explicit optimization flags. Enabling optimization further accelerated execution, albeit marginally, reducing redundant operations and memory traffic while preserving numerical integrity. Tests across varying ice cross-sectional spacings confirmed that NVFortran reduced runtimes by roughly an order of magnitude compared to the original model. A test GPU (Graphics Processing Unit) version was able to run the data interpolation routines on the GPU, but frequent data transfers between the CPU (Central Processing Unit) and GPU caused by shared memory blocks and fixed-size arrays made it slower than the original CPU version. Achieving efficient GPU execution would require substantial code restructuring to eliminate global states, adopt persistent data regions, and parallelize at higher level loops, or alternatively, rewriting in a GPU-friendly language to fully exploit modern architectures. Full article

Incremental computing is becoming increasingly important for processing large-scale datasets. In satellite imagery, spatial resolution, temporal depth, and large files pose significant computational challenges, requiring efficient architectures to manage processing time and resource usage. Accordingly, in this study, we propose a dynamic architecture, termed Multi-Cube, for optical satellite time series. The framework introduces a modular and baseline-aware approach that enables scalable subdivision, incremental growth, and consistent management of spatiotemporal data. Built on NetCDF, xarray, and Zarr, Multi-Cube automatically constructs stable multidimensional data cubes while minimizing redundant reprocessing, formalizing automated internal decisions governing cube subdivision, baseline reuse, and incremental updates to support recurrent monitoring workflows. Its performance was evaluated using more than 83,000 Sentinel-2 images (covering 2016–2024) across multiple areas of interest. The proposed approach achieved a 5.4× reduction in end-to-end runtime, decreasing execution time from 53 h to 9 h, while disk I/O requirements were reduced by more than two orders of magnitude compared with a traditional sequential reprocessing pipeline. The framework supports parallel execution and on-demand sub-cube extraction for responsive large-area monitoring while internally handling incremental updates and adaptive cube management without requiring manual intervention. The results demonstrate that the Multi-Cube architecture provides a decision-driven foundation for integrating dynamic Earth observation workflows with analytical modules. Full article

This article presents a database focused on measuring the experimental performance of a pilot parabolic trough collector (PTC) combined with the meteorological conditions corresponding to the installation site. Water was chosen as the fluid to recirculate through the PTC circuit. The data were recorded between August and September, assuming that global radiation was adequate for use in the concentration process. The database comprises seven experimental tests, which contain variables such as time, inlet temperature, outlet temperature, ambient temperature, global radiation, diffuse radiation, wind direction, wind speed, and volumetric flow rate. Based on the data obtained from this pilot PTC system, it is possible to provide relevant information for the installation and construction of large-scale solar collectors. Furthermore, the climatic conditions considered allow key factors in the design of multiple collectors to be determined, such as the type of arrangement (series or parallel) and manufacturing materials. In addition, the data collected in this study are key to validating future theoretical models of the PTC. Finally, considering the real operating conditions of a PTC in conjunction with meteorological variables could also be useful for predicting the system’s thermal performance using artificial intelligence-based models. Full article

High rock slopes are extensively distributed in areas of major engineering constructions, such as transportation infrastructure, hydraulic projects, and mining operations. The stability and failure evolution mechanism during their multi-stage excavation process have consistently been a crucial research topic in geotechnical engineering. In this paper, a series of two-dimensional rock slope models, incorporating various combinations of slope height and slope angle, were established utilizing the Discrete Element Method (DEM) software PFC2D. This systematic investigation delves into the meso-mechanical response of the slopes during multi-stage excavation. The Parallel Bond Model (PBM) was employed to simulate the contact and fracture behavior between particles. Parameter calibration was performed to ensure that the simulation results align with the actual mechanical properties of the rock mass. The research primarily focuses on analyzing the evolution of displacement, the failure modes, and the changing characteristics of the force chain structure under different geometric conditions. The results indicate that as both the slope height and slope angle increase, the inter-particle deformation of the slope intensifies significantly, and the shear band progressively extends deeper into the slope mass. The failure mode transitions from shallow localized sliding to deep-seated overall failure. Prior to instability, the force chain system exhibits an evolutionary pattern characterized by “bundling–reconfiguration–fracturing,” serving as a critical indicator for characterizing the micro-scale failure mechanism of the slope body. Full article

Nowadays various coupling strategies have been developed to combine the strengths of different numerical methods in computational fluid dynamics (CFD), among which the coupled algorithm of the lattice Boltzmann-finite volume method (LBM-FVM) has gained widespread attention. However, research on parallel optimization of LBM-FVM coupled solvers remains limited, mostly focused on independent solvers. In this work, we proposed a flexible framework and optimization schemes to explore the coordinated balance of accuracy-efficiency-hardware adaptability. First, we designed a processor layout strategy to address load imbalance and communication redundancy in the coupled solver. We then developed several parallelization techniques, including LBM restructuring, data reuse, and SIMD optimization for targeted kernels on the most advanced architecture of the Sunway series in China, namely SW26010P heterogeneous many-core processors, which provide hardware architectural advantages well suited for large-scale parallel computational fluid dynamics. Finally, the accuracy of the LBM-FVM coupling simulations was validated through benchmark simulations of 2D/3D lid-driven cavity flow. The results show that our LBM-FVM coupling solver can accurately capture flow characteristics, with vortex structures consistent with experimental data. Additionally, we achieved a 152× speedup for the LBM solver and a 126× speedup for the coupled simulation compared to the standalone FVM simulation on the New Sunway supercomputer system. Our approach marks a milestone in the field of LBM implementations and provides a promising future for coupled algorithms in CFD. Full article

The hospital-at-home (HaH) model delivers hospital-level care to patients in their homes, with point-of-care ultrasonography (PoCUS) serving as a cornerstone diagnostic tool for respiratory illnesses such as pneumonia. This review—the third in a series—addresses the prognostic, synchronous, and potential overdiagnostic concerns of lung ultrasound (LUS) in managing pneumonia within HaH settings. LUS offers advantages of safety and repeatability, allowing clinicians to identify “red flag” sonographic findings that signal complicated or severe disease, including pleural line abnormalities, fluid bronchograms, absent Doppler perfusion, or poor diaphragmatic motion. Serial LUS examinations correlate closely with clinical recovery, showing progressive resolution of consolidations, B-lines, and pleural effusions, and thus provide a non-invasive method for monitoring therapeutic response. Compared with chest radiography, LUS demonstrates superior sensitivity in detecting pneumonia, pleural effusion, and interstitial syndromes across pediatric and adult populations. However, specificity may decline in tuberculosis-endemic or obese populations due to technical limitations and overlapping imaging patterns. Overdiagnosis remains a concern, as highly sensitive ultrasonography may identify minor or clinically irrelevant lesions, potentially leading to overtreatment. To mitigate this, PoCUS should be applied in parallel with conventional diagnostics and integrated into comprehensive clinical assessment. Standardized training, multi-zone scanning protocols, and structured image acquisition are recommended to improve reproducibility and inter-operator consistency. Full article

Preterm infants in neonatal intensive care units (NICUs) experience impaired neurodevelopment and dysregulated stress responses, partly due to a lack of tactile stimulation. Although massage therapy offers proven therapeutic benefits by stimulating C-tactile afferents through (gentle) dynamic touch, existing methods are limited by clinical staff variability and resource constraints. This work presents a compact soft-pneumatic actuator array (SPAA) utilizing four nylon–TPU actuators (modules) connected in series or in parallel to perform a sequential actuation; this array is designed to deliver safe, shear-free, and massage-like normal compression tailored for preterm infants. Actuator performance was characterized using a load-cell and a pressure sensor under different preloads (10–30 g), establishing operating internal pressures of 20–50 kPa, which produced target force ranges between 0.1 and 0.3 N. Two SPAA architectures were evaluated: (i) parallel manifold with branch resistances and (ii) series chain with graded outlet resistances, using passive fluidic sequencing for controlled activation. The series configuration achieved repeatable sequential actuation with programmable delays, essential for mimicking therapeutic massage patterns. These results demonstrate that passive soft-pneumatic sequencing can reliably deliver dynamic tactile stimuli within neurophysiological and safety constraints, laying the groundwork for standardized, automated neonatal massage therapy in NICUs. Full article

Background: Parkinson’s disease (PD) involves progressive neurodegeneration with clinical or subclinical disturbance of the gut–brain axis, including altered gastrointestinal motility and enteric nervous system involvement. Clinical studies have reported gut microbiome alterations in PD, with shifts in taxa associated with inflammatory signalling and short-chain fatty acid (SCFA) metabolism. Photobiomodulation (PBM), a non-invasive light therapy, has been investigated as a potential adjunctive treatment for PD, with proposed effects on neural, metabolic, and immune pathways. We previously reported the five-year clinical outcomes in a PBM-treated Parkinson’s disease case series. Here we report the five-year gut microbiome outcomes based on longitudinal samples collected from the same participants. This was an exploratory, open-label longitudinal study without a control group. Objective: Our objective was to assess whether long-term PBM was associated with changes in gut microbiome diversity and composition in the same Parkinson’s disease cohort as previously assessed for changes in Parkinson’s symptoms. Methods: Six participants from the earlier PBM proof-of-concept study who had been diagnosed with idiopathic PD and who had continued treatment (transcranial light emitting diode [LED] plus abdominal and neck laser) for five years had their faecal samples analysed by 16S rDNA sequencing to assess microbiome diversity and taxonomic composition. Results: Microbiome analysis revealed significantly reduced evenness (α-diversity) and significant shifts in β-diversity over five years, as assessed by Permutational Multivariate Analysis of Variance (PERMANOVA). At the phylum level, Pseudomonadota and Methanobacteriota decreased in four of the six participants. Both of these phyla are often increased in the Parkinson’s microbiome compared with the microbiomes of healthy controls. Family-level changes included increased acetate-producing Bifidobacteriaceae (five of the six participants); decreased pro-inflammatory, lipopolysaccharide (LPS)-producing Enterobacteriaceae (two of the three participants who have this bacterial family present); and decreased LPS- and H₂S-producing Desulfovibrionaceae (five of six). At the genus level, Faecalibacterium, a key butyrate producer, increased in four of the six participants, potentially leading to more SCFA availability, although other SCFA-producing bacteria were decreased. This was accompanied by reductions in pro-inflammatory LPS and H₂S-producing genera that are often increased in the Parkinson’s microbiome. Conclusions: This five-year case series represents the longest follow-up of microbiome changes in Parkinson’s disease, although the interpretation of results is limited by very small numbers, the lack of a control group, and the inability to control for lifestyle influences such as dietary changes. While causal relationships cannot be inferred, the parallel changes in improvements in mobility and non-motor Parkinson’s symptoms observed in this cohort, raises the hypothesis that PBM may interact with the gut–brain axis via the microbiome. Controlled studies incorporating functional multi-omics are needed to clarify potential mechanistic links between microbial function, host metabolism, and clinical outcomes. Full article

Rapid urbanization drives economic growth but also brings complex environmental and social issues, highlighting the urgent need for efficient urbanization monitoring techniques. However, datasets for urbanization monitoring are often lacking in rapidly developing urban areas. At the methodological level, Convolutional Neural Networks (CNNs) and Transformer-based models for urbanization monitoring exhibit limitations in balancing computational efficiency and global modeling. The recently emerging parallel large kernel convolutional networks partially alleviate the conflict between global modeling and computational efficiency, but they employ simple element-wise addition to fuse multi-scale features. This crude mechanism struggles to fully leverage multi-scale information. To address this, this paper takes Accra, the capital of Ghana, as a case study and proposes an urbanization monitoring framework covering both dataset construction and model design. Methodologically, we propose the Multi-Scale Spatial-Channel Attention Network (MSCANet). Its core component, the Multi-Scale Spatial-Channel Attention Module (MSCAM), jointly models spatial and channel dimensions to mitigate the common confusion problem in parallel large kernel convolutional architectures. Furthermore, we adaptively modified the MSCAM to propose the Multi-Scale Spatial-Channel Attention Feature Fusion Module (MSCA-FFM) module for effectively integrating multi-modal information during the fusion stage. Experimental results show that MSCANet achieves optimal performance on the self-built Accra dataset, with a mean intersection over union (mIoU) of 95.02%, an overall accuracy (OA) of 98.70%, and a mean F1 Score (mF1) of 97.43%. To further validate the model’s generalization capability, supplementary experiments were conducted on the public ISPRS Potsdam dataset. The results demonstrate that the MSCANet series of models remain competitive, achieving an overall mIoU of 80.92%, with particularly strong performance in the “Building” (mIoU 92.26%) and “Impervious surface” (mIoU 84.63%) categories. Full article

A novel series of benzoxazole-derived iminocoumarins was synthesized via a Knoevenagel condensation and fully characterized using NMR, UV–Vis spectroscopy, and computational methods. Their photophysical properties were systematically examined in solvents of varying polarity, revealing pronounced effects of both substituents and solvent environment on absorption maxima and intensity. Derivatives bearing electron-donating substituents on the coumarin core exhibited distinct and reversible pH-responsive spectral shifts, confirming their potential as optical pH probes. Experimental pK_a values derived from absorption titrations showed excellent agreement with DFT-calculated data, validating the proposed protonation-deprotonation equilibria and associated electronic structure changes. Structure–property relationships revealed that electron-donating groups enhance intramolecular charge transfer, while electron-withdrawing substituents modulate spectral response and stability. In parallel, the compounds were evaluated for antiproliferative, antiviral, and antifungal activities in vitro. Strong electron-donating substituents were associated with potent but non-selective cytotoxicity, whereas derivatives bearing electron-withdrawing groups displayed moderate and more selective antiproliferative effects against leukemia cell lines. Antifungal screening revealed moderate inhibition of phytopathogenic fungi, particularly for compounds with electron-withdrawing or methoxy substituents. Overall, these findings demonstrate that benzoxazole iminocoumarins represent a promising class of multifunctional heterocycles with potential applications as optical pH sensors and scaffolds for bioactive compound development. Full article

Angiosperms include many taxa with dimorphic unisexual reproductive structures. These are well studied in some grasses, with maize as a key model, but other wind-pollinated lineages in Poales remain less explored. Within Poales, the family Restionaceae has the highest known proportion of dioecious species. In its Australian subfamily Leptocarpoideae, the sexually dimorphic Leptocarpus denmarkicus has raised questions about the basic flowering unit and the developmental basis of dimorphism. Here, we analyze inflorescence architecture and floral development in Eurychorda complanata, the sister lineage to the remainder of Leptocarpoideae. Using comparative morphology, light microscopy and scanning electron microscopy, we reconstruct synflorescence topology, floral organography, and ontogeny in both sexes and compare them with those in L. denmarkicus. In Eurychorda, both sexes produce polytelic paniculate synflorescences with distinct inhibition zones and many-flowered simple spikelets as the basic flowering unit. Male and female spikelets bear up to 50 and up to 15 fertile flowers, respectively. Male flowers have two stamens and a dimerous pistillode, whereas female flowers possess two long filamentous staminodes and a dimerous gynoecium. Ontogenetic series show that flowers of both sexes initiate both androecial and gynoecial structures, and that functional unisexuality is achieved through late arrest of the organs of one sex. Defining spikelets as racemose axes with lateral sessile flowers clarifies homologies of reproductive structures and supports reinterpretation of the dimorphic female unit in L. denmarkicus as a derived compound spike generated through shifts in branching rank and the timing of lateral initiation. The compound female spike of L. denmarkicus has a striking overall similarity to the simple female spikelet in Eurychorda, illustrating fascinating parallelism in the evolution of reproductive organs within Restionaceae and Poales more broadly. At the male side, Eurychorda achieves anther exsertion via filament elongation, whereas in L. denmarkicus filaments are very short and anthers remain within the perianth, but male spikelets sit on long, flexible peduncles that invert the spikelet and promote trembling, thereby ventilating the perianth chamber and aiding pollen escape. These two solutions—filament elongation versus spikelet-peduncle flexibility—represent alternative strategies of pollen release in wind-pollinated flowers. Full article

Aquaponics is a water-reusing, circular form of controlled-environment agriculture, but its sustainability benefits depend on reliable, constraint-aware nutrient dosing under delayed inflow effects. Aquaponics involves coupling hydroponics with aquaculture but is difficult to control because the greenhouse/crop state at the current time step ($t$) must anticipate water-quality changes that arrive at the next time step ($t+1$), under hard EC–pH and dose constraints. We propose the Analysis System for Nutrient Requirements in Hydroponics (ASNRH), a two-module, constraint-aware framework that directly regresses next-step elemental supplementation (N, P, K; mg·L⁻¹). First, the Fish-farm By-product Prediction Module (FBPM) uses a lightweight GRU forecaster to predict inflow chemistry at $t+1$ (e.g., NH₄⁺/NO₂⁻/NO₃⁻, alkalinity) from standard aquaculture sensors. Second, the Nutrient Requirement Prediction Module (NRPM) encodes the current hydroponic and crop state at t in parallel with the FBPM inflow at $t+1$ via a dual-branch architecture and fuses both representations to produce non-negative dose recommendations while penalizing forecasted EC/pH violations and excessive actuation volatility. The data pipeline assumes low-cost greenhouse and aquaculture sensors with chronological, leakage-free splits. A protocol-first simulation evaluates ASNRH against time-series and rule-based baselines using accuracy metrics (MAE/RMSE/R²), EC/pH violation rates, and robustness under missingness/noise; ablations isolate the contributions of the inflow branch, constraint-aware losses, and lightweight physics priors. The framework targets deployability in decoupled or coupled aquaponics by structurally resolving $t$ vs. $t+1$ asynchrony and internalizing domain constraints during learning; procedures are specified to support reproducibility and subsequent field trials. By operationalizing anticipatory dosing from reused aquaculture byproducts under EC/pH feasibility constraints, ASNRH is designed to support sustainability goals such as reduced nutrient wastage and fewer corrective water exchanges in coupled or decoupled aquaponics. Full article

With the irregular integration of small-capacity distributed generators (DG) and single-phase loads, rural low-voltage distribution transformers are faced with issues such as three-phase imbalance, light-heavy loading, and feeder terminal voltage excursions, impacting the safe and stable operation of the system. To address this issue, a coordinated control strategy based on direct power control (DPC) for low-voltage substation series-parallel coordination is proposed. A flexible interconnection topology for multi-substation series-parallel coordination is designed to achieve coordinated optimization of alternating current–direct current (AC-DC) power quality. Addressing the three-phase imbalance, light-heavy loading, and feeder terminal voltage excursions in rural low-voltage distribution transformers, a series-parallel coordinated optimization control strategy is proposed. This strategy incorporates a DC bus voltage control strategy based on sequence-separated power compensation and a closed-loop control strategy based on phase-separated power compensation, effectively addressing three-phase imbalances and load balancing in each power distribution areas. Furthermore, a series-connected phase compensation control strategy based on DPC is proposed, efficiently mitigating feeder terminal voltage excursions. A corresponding circuit model is established using Matlab/Simulink, and simulation results validate the effectiveness of the proposed strategy. Full article

With the widespread deployment of Industrial Cyber-Physical Systems (ICPS), their inherent vulnerabilities have increasingly exposed them to sophisticated cybersecurity threats. Although existing protective mechanisms can block attacks at runtime, the risk of defense failure remains. To proactively evaluate and harden ICPS security, we design a distributed crowdsourced testing platform tailored to the four-layer cloud ICPS architecture—spanning the workshop, factory, enterprise, and external network layers. Building on this architecture, we develop a Distributed Input–Output Testing and Verification Framework (DIOTVF) that models ICPS as systems with spatially separated injection and observation points, and supports controllable communication delays and multithreaded parallel execution. The framework incorporates a dynamic test–task management model, an asynchronous concurrent testing mechanism, and an optional LLM-assisted thread controller, enabling efficient scheduling of large testing workloads under asynchronous network conditions. We implement the proposed framework in a prototype platform and deploy it on a virtualized ICPS testbed with configurable delay characteristics. Through a series of experimental validations, we demonstrate that the proposed framework can improve testing and verification speed by approximately 2.6 times compared to Apache JMeter. Full article

This paper proposes a novel method for feeding a half-turn quadrifilar helix antenna (QHA) operating in backfire mode. A self-phasing and self-supporting antenna is obtained using a specific method demonstrated numerically. Four straight parallel wires, by which a couple of short-circuited stubs are realized and connected in series with helix loops, constitute both the mast of the QHA and the feeding network. A prototype operating at 1 GHz is designed, realized, and measured. The results show a good axial ratio (measured cross-polar gain is about 25 dB below the co-polar one at the boresight) and good impedance matching over an adequately large frequency band. Full article