Browse Articles

General two-level framework for demand-responsive transport optimization

Abstract This paper proposes a generalized optimization framework for demand-responsive transport (DRT), a modern form of transport organization in which services are planned and provided directly in response to the client demand. The developed framework has a two-level structure. The first level includes basic features essential to every DRT system. The second level takes into account the electric vehicle energy consumption and charging, predefined initial parts of vehicle routes for combining consecutive vehicle planning windows, as well as special passenger requests, such as a dedicated space for disabled people or Wi-Fi network availability. Three variants of models have been prepared, differing in how vehicles move between bus stops: freely point-to-point planning (General), restricted sections of the vehicle path (Sections) and fixed routes of every vehicle (Routes). During experiments, the developed model was thoroughly tested, in particular, its effectiveness in the basic version and with additional extensions was evaluated. The tests were performed on a dataset created based on the real public transport system of Rzeszow, Poland, from which 64 bus stops were mapped. The optimization process involved 200 passengers. The experiments confirmed the usefulness of the proposed solution.

Mechanical properties analysis of geopolymer concrete based on the sugarcane bagasse ash using machine learning

Dynamic characteristics and adaptability research of high-speed railway roadbed with silt-cement improved aeolian sand

Analysis of segment uplift during shield tunnel construction considering stratum seepage effects

A prototype for producing oxygen-rich air using novel magnetic separation cell and magnetic mixed poly(etheresulfone) matrix membranes

Abstract A meticulously designed prototype for the production of oxygen-rich air was developed, focusing on the separation of oxygen and nitrogen gases through a bespoke magnetic gas separation cell utilizing magnetic mixed matrix membranes. The nanostructured Fe 10 Ni 90 and Fe 20 Ni 80 alloys were fabricated by simple reduction and were embedded in a Poly(ethersulfone) (PES) matrix. The separation mechanism exploits the divergent magnetic properties of the gases—oxygen being paramagnetic and nitrogen diamagnetic—whereby magnetic attraction facilitates the extraction of oxygen molecules from the gas stream, enriching the permeate. Central to this study are three pivotal areas: first, the membrane preparation method employs an innovative attraction mechanism between permanent magnetic alloys and an iron casting knife, enabling a linear alignment of fillers without sedimentation and eliminating the need for a magnetic field during casting. This significantly enhances the integrity and performance of the fabricated mixed PES matrix membrane. Second, the flat sheet gas separation cell features a unique ribbed structure on the permeate side, filled with a magnetic Fe 10 Ni 90 alloy, poised to optimize gas permeation rates by augmenting the separation force on both the membrane and permeate side. Third, the robust stainless-steel construction and specific dimensions of the cell, providing an effective area of 95 cm², stand in stark contrast to older, more complex geometries. This comprehensive approach resulted in a remarkable 55% increase in permeability and a 40% enhancement in oxygen content.

Characterization of T-cell receptor loci and expressed repertoire reveals a capacity for robust T-cell response in Atlantic cod (Gadus morhua)

Abstract The Atlantic cod presents a peculiar case in fish immunology, due to the loss of MHCII and CD4 genes. Despite the absent antibody response to T cell-dependent antigens, it is a prolific species. Characterization of T-cell receptor loci and the expressed repertoire is necessary to further our understanding of how the Atlantic cod can mount an effective immune response and to characterize its immune system on the molecular level. A comprehensive annotation of the Atlantic cod genome (gadmor3.0) revealed all four chains of T-cell receptors, residing on chromosomes 5 and 8. Moderate germline diversity was observed with signs of recent expansion in the triplicate TRB locus. Sequencing of the expressed repertoire showed a surprisingly high repertoire diversity for TRA, TRB and TRD chains. Only small fractions of the repertoires were public with further untapped diversity available through differential gene usage especially for TRA and TRD chains. Our study revealed that despite its modest genomic T-cell receptor sequence diversity, the Atlantic cod maintains a diverse, mostly private expressed repertoire. This work provides a baseline for comparative studies and investigations of TR repertoire changes during vaccination and infection experiments.

Rhizosphere microbiome dynamics and hormonal interactions regulating tiller development in sugarcane cultivars

Abstract Sugarcane tillering is a key determinant of crop productivity, yet the integrated roles of rhizosphere microbiome dynamics, nutrient status, and hormone signaling in regulating tiller development remain poorly understood. Here, we compared rhizosphere microbial communities, endogenous hormone profiles, and nutrient element concentrations in sugarcane cultivars with contrasting tillering capacities. High-tillering varieties exhibited significantly greater microbial diversity and more complex co-occurrence network structures in the rhizosphere, characterized by enrichment of Acidobacteriota, Chloroflexi, and Planctomycetes and functional pathways related to nitrogen fixation, phosphorus solubilization, and auxin biosynthesis. In contrast, low-tillering varieties harbored simplified, stress-adapted microbial consortia and prioritized pathways linked to oxidative stress response and heavy metal detoxification. Hormonal analysis revealed that high-tillering cultivars maintained higher levels of growth-promoting hormones—particularly auxin (IAA) and active cytokinins—in tiller buds while low-tillering cultivars accumulated elevated abscisic acid (ABA) and inactive cytokinin conjugates. Nutrient analysis indicated that high-tillering genotypes possessed higher nitrogen and phosphorus contents, supporting vigorous axillary bud activation and shoot proliferation, whereas low-tillering varieties accumulated more zinc and manganese, potentially reflecting stress adaptation. Network-level integration of microbial, hormonal, and nutrient profiles underscored genotype-specific feedback between rhizosphere microbiota and plant physiological states, highlighting modular associations that link microbial hubs with tissue-specific nutrient and hormone signatures. Our findings reveal a systems-level mechanism by which rhizosphere microbial community structure and function interact with plant-nutrient–hormonal status to regulate tillering in sugarcane. These insights provide a basis for microbiome-informed strategies to enhance sugarcane productivity through integrated nutrient–hormonal–microbe management.

Lightweight FMCW radar framework for human activity recognition under limited data conditions

Abstract Human activity recognition (HAR) using frequency-modulated continuous wave (FMCW) millimeter-wave radar is a promising alternative to wearable and vision-based systems due to its unobtrusive and privacy-preserving nature. However, modeling multi-dimensional radar data under limited training samples while remaining robust to user and environmental variations is challenging, particularly for edge-based applications. To address this challenge, we propose a lightweight artificial intelligence-based framework for FMCW radar-based HAR that enables accurate and computationally efficient activity recognition on edge devices. The framework processes radar-derived Range-Doppler, Range-Azimuth, and Range-Elevation feature maps as structured multi-dimensional data vectors rather than conventional two-dimensional images, allowing compact representation of motion dynamics and spatial relationships. A lightweight deep learning architecture combining a modified ResNet-18 with depthwise separable convolutions and a bidirectional long short-term memory module is employed to extract spatial–temporal features with reduced complexity. To improve generalization under limited data conditions, we used data augmentation strategies including spatial shifting, intensity scaling with bias shift, horizontal Doppler flipping, and additive Gaussian noise. The framework is evaluated on a newly collected 60 GHz FMCW radar dataset covering seven daily activities in a realistic home-like environment. Experiments using cross-scene and leave-one-person-out validation demonstrate superior performance over baseline methods, achieving up to 91.98% accuracy and 89.82% F1-score.

Segmented optimization for river ecological corridor width based on ecosystem services: a case study of the North Canal River, China

Abstract Adapting to climate change requires a better understanding of how the spatial configuration of river ecological corridors influences both ecological connectivity and ecosystem service delivery. Corridor width is a critical factor in corridor planning, yet uniform design approaches often overlook the strong spatial heterogeneity between urban and rural river segments. In this study, we investigated the North Canal River in Beijing, quantifying the effects of corridor width on ecosystem service value through integration land use data (1990–2020), landscape pattern metrics, and segmented regression analysis. The results revealed pronounced contrasts in land–use trajectories between urban and rural corridors. Urban cropland declined by more than 70%, while built–up land expanded substantially before partially retreating following large–scale ecological restoration after 2015. Rural corridors experienced more moderate cropland loss and consistently maintained higher landscape aggregation and lower fragmentation. Increasing corridor width enhanced spatial connectivity and landscape stability, particularly in rural segments. Ecosystem service value exhibited a clear non–linear response to corridor width. Urban river corridors were increasingly dominated by cultural services, whereas rural corridors retained robust regulation and supporting services. Breakpoint models identified service–based width thresholds at approximately 126 m for urban and 311 m for rural corridors, respectively. These findings underscore the importance of context–specific corridor design that accounts for spatial heterogeneity in ecosystem service responses and provide quantitative support for adaptive river corridor planning in rapidly urbanizing regions.

Fermentation and chemical composition as determinants of genetic and biochemical variation in cocoa (Theobroma cacao L.) bean colour

Excess cardiovascular morbidity in psoriatic arthritis and cardioprotective effects of biologic dmards: a propensity-matched analysis

Metagenomic and functional insights into root endophytic bacteria associated with drought stress in cowpea

Abstract Endophytic bacterial communities enhance plant drought resilience, yet their dynamics in cowpeas ( Vigna unguiculata ) remain poorly understood. To explore this, we analyzed the root endophytic bacteriome under drought stress using 16 S rRNA gene metagenomics and evaluated isolated bacteria for plant growth-promoting traits. Drought significantly reduced both alpha and beta diversity, indicating a loss of microbial richness and evenness and community homogenization. Taxonomic shifts revealed enrichment of Cyanobacteriota, Cyanophyceae, and Marileptolyngbya sina in drought conditions. Forty-seven endophytic isolates were identified and characterized, including Enterobacter spp., Bacillus spp., Leclercia adecarboxylata , and Stenotrophomonas spp. The isolated strains exhibited plant growth-promoting traits in vitro and, in a pot assay, some enhanced wheat biomass under both control and drought conditions. The reduction in diversity due to drought indicates a loss of microbial richness and evenness, along with homogenization of microbial composition, suggesting that drought selectively enriches specific taxa, which may enhance plant stress resilience through specialized metabolic functions. By combining metagenomic profiling with functional assays, this study highlights the role of drought-induced bacterial shifts in supporting plant growth and development. These insights could lead to the development of microbial inoculants to improve crop drought tolerance.

Identification of novel blood-borne soluble binding partners of factor H-related proteins

Abstract The deposition of circulating complement factor H-related (FHR) proteins in tissues around the body has been implicated in a series of complement-mediated diseases. However, the array of blood-borne binding partners with which they interact remains unclear. Here, we identify novel blood-borne binding partners of FHR proteins, firstly through preliminary untargeted immunoprecipitation and mass spectrometry, and subsequently validating direct interactions through solid-phase binding assays. We uncover direct interactions between FHRs and soluble immune mediators including complement C4 (C4), cathepsin G (CTSG), mannose-binding lectin 2 (MBL2), and platelet basic protein (PPBP). Functional assays show that FHR-1 and FHR-2 attenuate CTSG-mediated C3b degradation, while FHR-5 and FHL-1 appear to affect lectin pathway activation via MBL2 binding. These interactions suggest that FHRs perhaps confer activity not only through surface competition with factor H, but also via selective engagement with circulating ligands. Our findings expand the known FHR interactome and reveal potential new avenues for understanding FHR biology and targeting complement dysregulation in disease.

Spatial-spectral resolution analysis using drone hyperspectral and satellite multispectral imagery for shallow coastal water monitoring

Mechanistic role of gut microbiota metabolites in hypertension-insomnia comorbidity via integrated network pharmacology and molecular dynamics

Eco-friendly RP-HPLC determination of bambuterol hydrochloride and montelukast sodium in tablet dosage with dissolution analysis

Abstract A simple, eco-friendly, and precise isocratic RP-HPLC method was developed and validated for the simultaneous determination of bambuterol hydrochloride (BBL) and montelukast sodium (MTK). Separation was performed on an Inertsil C18 column (250 × 4.6 mm, 5 μm) using ethanol/0.025 M phosphate buffer (pH 3.0) at 70:30 (v/v) on an Agilent 1200 Infinity II system. The method complied with ICH criteria and showed linearity over 1.20–100.00 µg mL⁻¹ (BBL) and 5.00–100.00 µg mL⁻¹ (MTK). Application to a combined tablet dosage form yielded mean recoveries of 100.92 ± 1.08% (BBL) and 99.39 ± 1.41% (MTK). Dissolution profiling was performed in 900 mL of 0.5% sodium lauryl sulfate medium. Method greenness and sustainability were benchmarked against a reported procedure using multiple tools, Analytical Eco-Scale, MoGAPI, AGREE, RGB-12, D-CHEMS-1, GEAR, CaFRI, CACI, and BAGI demonstrating a safer solvent profile via ethanol/buffer. Notably, the separation time is longer (≈ 16 min), indicating a deliberate trade-off between reduced solvent hazard and throughput; analytical performance was maintained. Overall, the method offers a robust, greener alternative for routine assay and dissolution testing of BBL and MTK in pharmaceuticals.

Deep maximum margin matrix factorization

DFT based photophysical assessment of 2-substituted-3-(pyridin-2-yl)-benzo-[d][1,3]-azaphosphole P-oxide for organic optoelectronic applications

Study on the failure effect of gas tunnel blasting considering the influence of delay time and its engineering application

Persistent cycles and network resilience: a hypernetwork-based framework for temporal graph analysis

Abstract Temporal networks capture systems whose interactions occur as time-stamped events, where resilience depends on whether time-respecting connectivity can be maintained under disruptions. Existing assessments often rely on static aggregation or path-centric indicators, which may overlook higher-order redundancy that emerges and dissolves over time. We propose a persistence-aware, cycle-driven framework that treats recurrent temporal cycles as resilience-relevant building blocks. The method detects cycles within sliding windows, tracks their recurrence to quantify persistence, and encodes cycles that exceed a persistence threshold as hyperedges in a temporal hypernetwork. Based on this representation, we introduce two dynamic node-level metrics—Temporal Cycle Number (TCN) and Temporal Cycle Ratio (TCR)—to quantify persistent cycle participation and to identify nodes that anchor durable closure. We evaluate the framework on six real-world temporal networks spanning social, transportation, biological, communication, infrastructure, and economic domains using controlled node-removal experiments and temporal-efficiency loss as the primary impact measure. Under the adopted windowing scheme, datasets, and disruption protocols, TCN and TCR exhibit higher rank-based association with disruption impact than the representative static and temporal baselines considered. Moreover, in the same experimental setting, targeted removal of high-TCN/TCR nodes tends to yield larger efficiency degradation than degree-based attacks, which is consistent with the interpretation that recurrent cycle closure can coincide with time-respecting detours that support connectivity. A direct comparison with persistence-weighted scores derived from non-closed temporal motifs (2-paths) further shows that topological closure, rather than motif persistence alone, is the primary driver of the observed predictive advantage. These findings provide empirical support—within the scope of our evaluation—that persistence is an informative factor when using cycle closure as a redundancy signal, and that hypernetwork-encoded persistent cycles offer a compact and interpretable representation for temporal resilience analysis.