Search Results (24,423)

Wheat, soybean, and peanut are recognized as major food allergens, with their prevalence rising globally, necessitating rapid and reliable detection methods. A new detection approach was developed in this research, which integrates Ladder-shape Melting Temperature Isothermal Amplification (LMTIA) with Proofreading Enzyme-Mediated Probe Cleavage (Proofman) technology to enable the concurrent identification of wheat, soybean, and peanut allergens. Compared with the loop-mediated isothermal amplification (LAMP) method under the experimental conditions set in this study, this approach can reduce the false-positive results associated with LAMP, and it does not rely on sophisticated instrumentation required by technologies like mass spectrometry. The GAG56D (wheat), Ara h 2.01 (peanut), and Lectin (soybean) genes were selected as target genes for the three allergens. Specific primers and probes were designed according to these target genes, and the reaction system was optimized. A systematic evaluation of the triplex Proofman-LMTIA method was then conducted regarding its specificity, sensitivity, limit of detection, and repeatability. Finally, the method’s practical applicability was validated using commercial products. The optimized system achieved simultaneous detection within 40 min at 61 °C, showing no cross-reactivity with common foods. The method demonstrated good sensitivity, with a sensitivity of 5 pg/μL for genomic DNA and a detection limit of 5% (w/w) in a powder matrix, along with excellent repeatability. In practical sample testing, the results were fully consistent with product label declarations, accurately identifying single and multiple allergen contaminations. The Proofman-LMTIA detection method, with its rapid, simple, sensitive, and specific characteristics, demonstrates significant potential for applications in food safety supervision. Full article

Generative no-code development tools enable users to create applications directly from natural-language prompts, shifting interface design from manual construction to AI-mediated generation. However, identical prompts frequently produce substantially different user interface (UI) outcomes across tools and even across repeated executions within the same tool. This paper presents a systematic literature review examining how generative no-code systems make design and aesthetic decisions with respect to layout structure, visual consistency, usability, accessibility, and reproducibility. Twenty peer-reviewed studies (2021–2025) were analyzed following a structured review protocol. Existing research predominantly evaluates usability and accessibility in isolation while providing limited insight into aesthetic coherence, design variability, and prompt-to-output stability. Across studies, generative tools exhibit implicit design priors and stochastic behavior that lead to inconsistent visual outcomes and partial misalignment with human-centered design principles. These findings indicate that generative no-code tools do not act as deterministic translators of user intent but instead introduce their own stylistic tendencies. The paper identifies critical evaluation gaps and outlines requirements for future systems, including reproducible generation, transparent design reasoning, and user-directed control, to support reliable and predictable interface development. Full article

Agile methodologies have become a dominant approach in contemporary software development due to their emphasis on adaptability, iterative delivery, and rapid feedback. However, variations in how agile practices are implemented, particularly in terms of planning frequency and sprint duration, often lead to significantly different project outcomes. This study investigates the strategic effectiveness of agile approaches by examining sprint duration as a critical design parameter rather than a procedural convention. This study employs a comparative case study methodology involving four software development projects with identical functional requirements and comparable scope. Each project adopted a different planning horizon daily, weekly, and bi-weekly while maintaining a consistent team structure, estimation techniques, and development context. This design enables isolation of the effects of planning frequency and development cycle duration on workflow continuity, team productivity, and resource utilization. The findings indicate that excessively short planning cycles, such as daily planning, may increase operational fragility and disrupt project flow, particularly in small teams with centralized decision-making. In contrast, weekly and bi-weekly planning approaches demonstrate greater resilience, more consistent utilization of working time, and improved continuity of development. Notably, the two-week sprint structure achieves a balanced trade-off between adaptability and stability, supporting the concept of an optimal “golden mean” sprint duration discussed in the agile literature. The study contributes empirical evidence to ongoing discussions on agile implementation effectiveness and offers practical guidance for tailoring sprint duration to project dynamics and organizational constraints. Full article

Backgroundand Objectives: Targeted therapies are increasingly used in the management of chronic lymphocytic leukemia (CLL); however, real-world data from routine clinical practice remain limited. Materials and Methods: We performed a retrospective analysis of 47 patients with CLL who received at least one targeted therapy at a tertiary university hospital. Clinical characteristics, treatment responses, and adverse events were assessed. A total of 58 treatment events were included. Results: Obinutuzumab, ibrutinib, and venetoclax were administered in 34.5%, 46.5%, and 19.0% of treatment events, respectively. Numerically higher response rates were observed in treatment events involving obinutuzumab compared with ibrutinib and venetoclax (92.9% vs. 54.5% and 55.6%, respectively); however, treatment allocation was not randomized and these findings should be interpreted descriptively. Median overall survival from initiation of the first targeted therapy was 30.9 months. Adverse events occurred in more than 80% of treatment events. Neutropenia was more frequent with obinutuzumab and venetoclax, whereas bleeding events were more common with ibrutinib. Conclusions: In this real-world cohort, targeted therapies showed response patterns and safety findings consistent with routine clinical practice. Obinutuzumab was more frequently prescribed in older and more comorbid patients, reflecting treatment patterns rather than comparative superiority. These findings should be considered descriptive and hypothesis-generating, given the retrospective and single-center design. Full article

Industrial symbiosis (IS) research has documented many successful ecosystems but still lacks an empirically grounded typology linking resource flow configurations to environmental outcomes across diverse contexts. This study develops such a typology and tests whether distinct configurations achieve comparable environmental performance through different pathways—the configurational principle of equifinality. Drawing on 68 documented IS ecosystems across 48 countries, we apply k-means clustering to five flow-intensity dimensions—material, energy, water, logistics, and knowledge—and characterise the resulting partition using one-way ANOVA, Tukey HSD post hoc tests, multinomial logistic regression, and a Cox proportional-hazards model. Four configurations emerge: a dominant low-flow group (n = 34) and three coordinated configurations—energy–knowledge (n = 11), material-dominant (n = 16), and water-oriented (n = 7). The three coordinated configurations all significantly outperform the low-flow group on environmental performance (F(3, 57) = 11.60, p < 0.001), with effect sizes very similar and no significant differences among them, providing direct empirical evidence for equifinality. Economic performance does not differ significantly across configurations, and the multinomial model of contextual predictors is jointly insignificant—a pattern we read as consistent with equifinal contextual pathways rather than as a methodological flaw. Robustness checks across alternative clustering algorithms, operationalisations, and sub-samples support the typology’s stability. This study contributes an empirically grounded framework for circular economy practice that moves beyond one-size-fits-all prescriptions and offers a configurational lens for the design of sustainable industrial ecosystems. Full article

Engineer-to-order (ETO) manufacturers face persistent cost and complexity challenges driven by product variety, including duplicate components, redundant variants, and inconsistent procurement setups. Although enterprise resource planning (ERP) and product lifecycle management (PLM) systems contain detailed Bills of Materials (BOMs) and procurement records, they typically lack portfolio-wide support for systematic cross-product commonality analysis without substantial manual effort. Structured approaches to design reuse and modularization in ETO contexts exist, but lightweight portfolio-level analytics tools operating on exported enterprise data remain scarce, and companies often still rely on ad hoc spreadsheet analyses. This paper introduces product commonality analysis tools (PCATs) and develops and evaluates one such tool in an action-research collaboration with a European ETO laser manufacturer. The PCAT operates on exported enterprise data to provide interactive portfolio-level views of component reuse and cross-product consistency. Usefulness is evaluated through scenario-based think-aloud usability sessions and a functional comparison against Excel workarounds, standard ERP/PLM reporting, and vendor customizations. The results indicate that a lightweight PCAT can integrate into existing ERP/PLM workflows with minimal disruption and reduce the effort required to prepare reusable portfolio views for engineering and procurement reviews. Full article

Sonar is a fundamental tool for underwater target detection. However, conventional detection systems often suffer from poor sensor consistency and high fabrication costs. More critically, for low-frequency operation, the required array aperture becomes prohibitively large, limiting their deployment on small, mobile underwater platforms. To address the demand for compact, high-performance sensing solutions, this paper presents a miniaturized Micro-electromechanical Systems (MEMS) hydrophone array designed for underwater target detection. The array consists of six elements with a spacing of 0.25 m. Each element is approximately 22 mm in diameter and encapsulated in polyurethane via a casting and curing process. The core sensing element, a MEMS acoustic pressure hydrophone, exhibits a sensitivity of −177.2 ± 1.5 dB (re: 1 V/µPa) across the 20 Hz to 4 kHz frequency range and a noise resolution of approximately 59.5 dB (re: 1 µPa/√Hz) at 1 kHz. A key challenge in array-based detection is the phase mismatch among acquisition channels, which degrades algorithm performance. To mitigate this, we propose a phase self-correction method based on interleaved ADC acquisition control, enabling synchronous multi-channel sampling and effectively eliminating system-level phase errors. Furthermore, to overcome the inherent aperture limitations of conventional beamforming (CBF) applied to a miniaturized array, a differential beamforming (DBF) algorithm is adopted. This approach is less frequency-dependent and can approximate a frequency-invariant beam pattern, making it well-suited for miniaturized arrays. Simulation results confirm the theoretical validity of the DBF algorithm for the proposed MEMS hydrophone array. Sea trial data further demonstrate that this method achieves higher target detection accuracy compared to CBF techniques. Full article

Breast cancer is the most common malignant tumor in women worldwide. Triple-negative cancers have the worst prognosis, due to the low effectiveness of current therapies. In recent years, research has been conducted on the relationship between inflammatory process and the development of malignant tumors, including breast cancer. One of the elements influencing the inflammatory process is interleukins. These are small protein molecules belonging to the cytokine family that participate in the function of the human immune and hematopoietic systems. Interleukins are still being studied, and this is an area with significant knowledge gaps. More than 60 cytokines have been designated as interleukins over time, but not all of these designations are consistently used or universally accepted. In the available literature, we have only found information on 41. This is the first review to detail all 41 interleukins and their effects on breast cancer development. The review shows that interleukins affect the development of both locally advanced breast cancer and the development of distant metastases, mainly to the bones. Clinical trials are also underway in these areas: some have failed, and others are still ongoing. Due to the lack of success in the use of interleukins in the treatment of breast cancer, the latest strategies are based on combining several elements of the inflammatory process pathway occurring in breast cancer. This can probably bring us closer to therapeutic success in this area. Full article

Laminated bamboo (LB) has emerged as a promising sustainable structural material due to its rapid renewability, high strength-to-weight ratio, and favorable mechanical performance. Drawing on a comprehensive review of over 90 published experimental and analytical studies, this paper provides a critical synthesis of the structural behavior of LB, with emphasis on its compression, tension, flexure, shear, and creep responses. Reported mechanical properties exhibit variability, largely influenced by bamboo species, fiber orientation, processing methods, adhesives, lamination quality, and loading configuration. While LB demonstrates high tensile and flexural strengths comparable to or exceeding conventional timber products, pronounced anisotropy and brittle failure modes are consistently observed, particularly under shear and rolling shear loading. Recent studies on cross-laminated bamboo (CLB) highlight the significant role of interlaminar behavior and adhesive performance in controlling failure mechanisms, indicating that rolling shear capacities often govern the design of planar elements. Beyond mechanical behavior, this review synthesizes available research on thermal and fire performance. Emerging research on LB connections indicates that joint behavior often governs global structural performance, with strength and ductility strongly influenced by fastener type and embedment behavior. Key knowledge gaps are identified, underscoring the need for unified design frameworks to enable broader structural adoption of laminated bamboo systems. Full article

The deep foundation pit excavation of subway will cause horizontal displacement, uneven settlement and other adverse effects on the adjacent shield. The use of servo steel strut has a certain effect on deflection correction, but the current understanding of the influencing factors of deflection correction is not comprehensive. Based on structural and spatial symmetry, the influence of tunnel depth, tunnel and foundation pit clear distance and deformation control quantity of enclosure structure on deflection correction quantity was studied by symmetrically designed model test and numerical simulation, and the prediction formula of deflection correction quantity considering tunnel and foundation pit clear distance and deformation control quantity of enclosure structure was proposed. The results show that with an increase in the tunnel’s burial depth, deflection correction decreases significantly. When the tunnel is near the foundation pit bottom, there is no significant correction effect, and the control law of the tunnel ground pressure under the servo steel strut loading is consistent with the correction law. Deflection correction is negatively correlated with the tunnel and foundation pit clear distance, and positively correlated with the deformation control of the diaphragm wall. The curve of the deformation control of the enclosure structure and the deflection correction is parabolic. The deflection correction is an exponential function of the ratio of the deformation control of the enclosure structure to the clear distance between the tunnel and the foundation pit, and the servo deflection correction follows a normal distribution along the longitudinal axis of the tunnel, showing obvious symmetry characteristics in the foundation pit influence zone. Full article

With the growing adoption of data-driven workflows and the need to compare numerous interior design alternatives in housing renewal, scalable and consistent assessment of interior space quality is increasingly important; however, current practice still depends on manual scoring and expert judgment. To address this gap, we propose an automation-ready framework that evaluates interior space quality from visual data. We construct the Functionality–Healthiness–Aesthetics Spatial Interior Dataset-10K (FHASID-10K) with 13,962 images for systematic validation. Three sub-models quantify functionality via space utilization and circulation smoothness, healthiness via detection of health-related visual elements, and aesthetics via semantic visual representations with regression-based prediction. Dimension scores are standardized and fused using the analytic hierarchy process (AHP) and the technique for order preference by similarity to ideal solution (TOPSIS) to produce a comprehensive score for ranking and grading. Experiments show stable score distributions and clear differentiation across space categories and style–space combinations. A gradient-boosted decision tree (GBDT) surrogate reconstructs the fused score with high accuracy (test R² = 0.9992; MSE = 1.1 × 10⁻⁵), and human-subject evaluation shows strong agreement with overall-quality ratings (r = 0.760, p < 0.001). Overall, the framework enables scalable benchmarking, scheme comparison, and decision support. Full article

The large-scale integration of distributed energy resources poses numerous challenges to distribution networks. At present, multi-terminal flexible interconnection has become a key development trend for active distribution networks integrated with high-penetration distributed energy resources. Conventional unified power flow controllers (UPFCs) are mainly designed for high-voltage transmission networks and lack distribution-adapted control strategies, making it difficult for them to meet the networking requirements for multi-terminal interconnection. Moreover, most existing studies still focus on two-terminal devices, soft open points and improved UPFC topologies for transmission networks. Existing multi-port schemes mostly adopt only shunt-side structures without series compensation branches, which fail to regulate voltage magnitude and phase difference, thus failing to suppress closing inrush currents and mitigate busbar voltage sags. Meanwhile, such schemes struggle with three-phase imbalance, feeder load imbalance and bidirectional power flow fluctuations in distribution networks, and lack adaptive power allocation capability among multiple ports. To solve the above problems, this paper proposes a VSC-based series–shunt hybrid multi-terminal flexible interconnection converter. The proposed topology consists of one series-side VSC and n − 1 shunt-side VSCs connected through a common DC capacitor; it removes the shunt-side transformer, and effectively reduces cost and volume, while achieving phase shifting, voltage regulation and power flow control. Meanwhile, dual closed-loop PI cross-decoupling control and a flexible closing strategy are adopted to independently regulate the active and reactive power of each feeder, adapt to three-phase imbalance and load imbalance conditions, suppress inrush currents, and realize flexible power mutual support among multiple ports, thereby significantly enhancing adaptability to distribution networks. Full article

Background: Prostate cancer (PCa) arises from complex interactions among host genetics, androgen signaling, and microbial communities. Emerging genomic evidence supports the presence of microbial consortia within prostate tissue, suggesting that microbial genes, metabolites, and host–microbe interactions may contribute to chronic inflammation, oncogenic signaling, and therapeutic resistance. Methods: We conducted a narrative review using targeted searches of PubMed and Google Scholar for studies published between 2020 and 2025, complemented by selected mechanistic reports published in March 2026. Human studies and experimental research providing mechanistic insights into prostate models were prioritized. Due to the heterogeneous methodologies, evidence was synthesized qualitatively, with an emphasis on genomic and signaling perspectives. Results: Low-biomass microbial DNA is consistently detected in prostate tissue. Proteomic analyses of Corpora amylacea suggest a “fossil record” of past infections through sequestered microbial DNA and antimicrobial proteins, potentially priming tissue for long-term carcinogenic processes, although contamination remains a key limitation. Recurrent bacterial and viral signals, including Cutibacterium acnes, Escherichia coli, Pseudomonas, Acinetobacter, human papillomavirus, Epstein–Barr virus, and cytomegalovirus, appear to converge on a restricted set of tumor-relevant pathways, including TLR–NF-κB, MAPK, PI3K/AKT/mTOR, cGAS–STING, and p53/pRb disruption. These interactions may promote cytokine production, oxidative stress, DNA damage, epithelial–mesenchymal transition, extracellular matrix remodeling, immune evasion, and resistance to therapy. The gut–prostate axis further links intestinal dysbiosis and microbial metabolites with systemic IGF-1 signaling and castration resistance. Conclusions: Microbial genomic consortia in the prostate and gut may shape inflammatory, metabolic, and immune networks that influence PCa initiation and progression. However, most available data remain correlative and are limited by low-biomass sampling, contamination risk, and heterogeneous study designs. Future research should prioritize rigorous contamination control, longitudinal and prostate-specific mechanistic studies, and integrated multi-omic approaches to clarify causality and identify actionable microbial targets for prevention, diagnosis, and therapy. Full article

Automated pavement distress classification using high-resolution Unmanned Aerial Vehicle (UAV) imagery is pivotal for intelligent transportation systems. However, long-term UAV monitoring faces a continuous stream of evolving distress types and changing remote sensing background textures, necessitating Class-Incremental Learning (CIL) capabilities. Existing methods struggle to balance stability and plasticity, especially under the severe storage limitations typical of local edge stations in air–ground collaborative systems. This data scarcity leads to catastrophic forgetting and confusion among fine-grained distress categories. To address these challenges, we propose a data-efficient approach named Analytic Geometric Alignment (AGA). Our framework mainly consists of three key components. First, to overcome the optimization gap between the feature extractor and the fixed geometric target, we introduce a Subspace-Aware Analytic Initialization (SAI) that computes a closed-form projection to instantly align the feature subspace with the ETF manifold before each task training. Second, on this aligned basis, a Decoupled Geometric Adapter (DGA) is incorporated to facilitate continuous non-linear adaptation to complex aerial textures. Finally, for stable incremental training, we design a Memory-Prioritized Regression (MPR) loss to enforce tighter geometric constraints on replay samples, significantly enhancing model stability. Extensive experiments on the UAV-PDD2023 dataset demonstrate that AGA significantly outperforms state-of-the-art methods, showcasing excellent robustness and data efficiency. Full article

Aerosol optical depth (AOD), fine-mode fraction (FMF), and absorption aerosol optical depth (AAOD) are essential for quantifying aerosol extinction and related climate and air-quality effects. Yet, most satellite retrievals target a single wavelength or parameter. In this study, a deep neural network (DNN) framework was developed to synergistically retrieve AOD, FMF, and AAOD from Sentinel-5P/TROPOMI at seven wavelengths across 380–772 nm. Parameter-specific feature engineering was designed by incorporating physical linkages among aerosol optical properties. Bayesian optimization was employed to tune hyperparameters, and SHAP (Shapley additive explanations) was used to interpret feature contributions. The proposed model demonstrated high accuracy and robustness on an independent test set. The retrieved AOD showed excellent agreement with AERONET (R = 0.960, MAE = 0.034, RMSE = 0.070), and similarly strong performance was achieved for FMF (R = 0.955, MAE = 0.027, RMSE = 0.039). For AAOD, an overall correlation of 0.86 was obtained (MAE = 0.005, RMSE = 0.008). Comparisons with existing satellite products indicated globally consistent spatial patterns and improved spatial continuity under high aerosol loading. Overall, the proposed data-driven approach enhances the efficiency and coverage of multi-parameter aerosol retrieval while maintaining high accuracy, supporting absorbing aerosol monitoring, aerosol-type discrimination, and climate-effect assessment. Full article