Search Results (23,724)

This study aims to enhance the value of the Montepulciano d’Abruzzo PDO supply chain by integrating multi-elemental and isotopic profiling with chemometric analysis. The objective is to establish a pilot study for origin authentication, supporting strategic, managerial, and regulatory decision-making for stakeholders in the wine sector. Wine and soil samples from producers in the Abruzzo region were analyzed for 63 elements and selected isotopic ratios using HR-ICP-MS and MC-ICP-MS. Exploratory data analysis, including PCA and clustering, was employed to investigate intrinsic data structure. Variable selection techniques identified the most discriminant markers, and multiple classification models were tested to assess producer-level differentiation. The combined elemental and isotopic dataset showed strong intrinsic structure. Four variables—Mo, ²⁰⁸Pb/²⁰⁶Pb, P, and ⁸⁷Sr/⁸⁶Sr—emerged as key discriminants. Quadratic Discriminant Analysis and Artificial Neural Networks achieved 100% accuracy in classifying samples by producer. The results demonstrate that integrating multi-elemental and isotopic data with chemometric tools offers a pilot approach to authenticate wine origin and enhance transparency across the PDO supply chain. Beyond scientific innovation, this study provides a pilot decision support model that can strengthen competitive differentiation, regulatory compliance, and sustainable territorial development, highlighting opportunities for digital transformation in PDO management. Full article

In this study, deep tight sandstone was selected as an example to propose a complete method for predicting reservoir pore structure by capillary pressure curves and conventional well log data. This method pioneers the integration of grey relational analysis, principal component analysis, ensemble clustering, and deep neural networks to establish a systematic predictive framework for transitioning from conventional logging data to pore structure types. A total of 186 core data from three wells were used in this study. First, sensitive pore structure parameters from mercury injection capillary pressure data were extracted using grey correlation analysis and principal component analysis. Then, unsupervised clustering analysis was applied to classify the reservoir pore structures in the study area, dividing it into three categories. These category labels were combined with conventional well logs to create learning samples for a deep neural network (DNN) model developed to predict reservoir pore structure categories. The accuracy of the training set of the model reached 88.2%, while the accuracy of the testing set was 80.43%. Finally, the method was applied to field well log data. The results showed significant differences in pore structure classifications among gas layers, water–gas layers, and dry layers. This method is versatile, with its core components transferable to other deep sandstone reservoir studies, and can accurately predict the pore structure of tight sandstone reservoirs, which is critical for advancing the characterization of deep and complex oil and gas reservoirs. Full article

DNA-protecting proteins (Dps) are crucial for safeguarding chromosomal DNA in starved cells during the stationary phase under stressful conditions. In previous research, the two Dps proteins in Deinococcus geothermalis, Dgeo_0257 (Dps3) and Dgeo_0281 (Dps1), were found to complement each other in protecting DNA from oxidative damage. This study investigates the physiological changes and transposition of insertion sequences (ISs) in a double-knockout (DK) mutant lacking both dps genes. Comparisons between the wild-type and mutant strains revealed significant phenotypic differences in viability under oxidative stress conditions induced by hydrogen peroxide and ferrous ions, particularly during the stationary phase. Notably, oxidative stress triggered the transposition of the IS families IS701 and IS5, with IS66 being transposed exclusively in the DK mutant into a gene encoding phytoene desaturase. Transcriptomic analysis using RNA-seq revealed substantial fold changes in gene expression across the genome. For example, the dgeo_1459–1460 gene cluster, which encodes a DUF421 domain-containing protein and a hypothetical protein, was highly upregulated under both oxidative and non-oxidative conditions. Interestingly, catalase, encoded by a single gene in D. geothermalis, was upregulated in the DK mutant during the stationary phase, with expression levels exceeding those observed in the single dps gene-deficient mutants. Conversely, a prominent downregulation of the Fur family regulator was detected. These findings highlight the growth phase-dependent physiological adaptation of the dps-DK mutant and reveal a novel IS transposition event of the ISBst12 group involving the IS66 family. Therefore, this study provides new observations into the influence of DNA-protective protein deficiency on oxidative stress responses and IS transposition in D. geothermalis, as well as the regulatory mechanisms of the catalase induction pathway, raising the need for further investigation into the role of OxyR. Full article

Desertification is the impoverishment of fertile land, caused by various factors and environmental effects, such as temperature and humidity. An appropriate Internet of Things (IoT) architecture, routing algorithms based on artificial intelligence (AI), and emerging technologies are essential to monitor and avoid desertification. However, the classical AI algorithms usually suffer from falling into local optimum issues and consuming more energy. This research proposed an improved multi-objective routing protocol, namely, the efficient quantum (EQ) artificial rabbit optimisation (ARO) based on edge computing (EC) and a software-defined network (SDN) concept (EQARO-ECS), which provides the best cluster table for the IoT network to avoid desertification. The methodology of the proposed EQARO-ECS protocol reduces energy consumption and improves data analysis speed by deploying new technologies, such as the Cloud, SDN, EC, and quantum technique-based ARO. This protocol increases the data analysis speed because of the suggested iterated quantum gates with the ARO, which can rapidly penetrate from the local to the global optimum. The protocol avoids desertification because of a new effective objective function that considers energy consumption, communication cost, and desertification parameters. The simulation results established that the suggested EQARO-ECS procedure increases accuracy and improves network lifetime by reducing energy depletion compared to other algorithms. Full article

The wnt gene family encodes a group of highly conserved secreted glycoproteins that play essential roles in vertebrate development, including tissue patterning, cell differentiation, and gonadal regulation. However, the genomic organization, evolutionary dynamics, and functional roles of Wnt signaling components in flatfish remain poorly understood. In this study, we performed a comprehensive genome-wide identification, evolutionary characterization, expression profiling, and functional analysis of wnt genes in Cynoglossus semilaevis, a flatfish species exhibiting ZW/ZZ sex determination and temperature-induced sex reversal. A total of 20 wnt genes were identified and classified into 13 subfamilies, displaying conserved structural organization and phylogenetic relationships consistent with other teleosts. Chromosomal mapping revealed lineage-specific WNT clusters, including a unique wnt3–wnt7b–wnt5b–wnt16 block, as well as syntenic associations with reproduction-related genes (e.g., adipor2, sema3a, nape-pld, erc2, lamb2), suggesting coordinated genomic regulation. Tissue transcriptome analysis demonstrated strong sex- and tissue-biased expression patterns, with wnt5a predominantly expressed in ovaries and wnt5b specifically upregulated in pseudo-male testes. Functional assays revealed that knockdown of wnt5a or wnt5b induced testis-specific genes (sox9b, tesk1) and suppressed ovarian markers (foxl2, cyp19a1a), indicating antagonistic regulatory roles in gonadal fate determination. Promoter analysis identified yy1a as a selective repressor of wnt5b, but not wnt5a, providing a mechanistic basis for paralog divergence. Furthermore, pull-down combined with LC–MS/MS analysis showed that WNT5b interacts with proteins enriched in ribosome biogenesis and ubiquitin-mediated proteolysis, suggesting a role in translational regulation and protein turnover during spermatogenesis. Together, these findings establish WNT5 signaling—particularly wnt5b—as a key driver of testicular development in C. semilaevis and provide new insights into the molecular mechanisms underlying sex differentiation and sex reversal in flatfish. Full article

Research on road transport infrastructures is rapidly evolving as electrification, automation, and digital connectivity reshape how systems are designed, operated, and managed. This study presents a combined bibliometric, scientometric, and network analysis of 2755 publications published between 2021 and 2025 to map the intellectual structure, main contributors, and dominant technological themes shaping contemporary road transport research. Using data from the Web of Science Core Collection, co-occurrence mapping, thematic analysis, and collaboration networks were generated using Bibliometrix and VOSviewer. The results reveal strong growth in research output, with China, the United States, and Europe forming the core of high-impact publication and collaboration networks. Six bibliometric clusters were identified and consolidated into three overarching domains: road transport systems, emphasizing vehicle dynamics, control, and real-time computational frameworks; energy and efficiency-oriented mobility research, focusing on electrification, optimization, and infrastructure integration; and emerging digital technologies, including IoT, AI, and autonomous vehicles. The analysis highlights persistent research gaps related to interoperability, cybersecurity, large-scale deployment, and governance of intelligent transport infrastructures. Overall, the findings provide a data-driven overview of current research priorities and structural patterns shaping next-generation road transport systems. Full article

Global warming poses a threat to food security, particularly for essential crops like cowpea, which exhibits sensitivity to heat stress. This study aimed to evaluate the morpho-agronomic diversity of cowpea genotypes under different daily temperature regimes. The experiment was conducted in growth chambers, and biometric and productive traits were measured to quantify genetic divergence using Mahalanobis distance and UPGMA clustering. Temperature increases markedly altered trait expression. Under the 20–26–33 °C regime, 100-grain weight, leaf dry weight, pod weight, and stem dry weight accounted for 54.44% of the total variation. Under the higher temperature regime (24.8–30.8–37.8 °C), number of pods, plant height, stem fresh weight, and leaf dry weight explained 67.27% of the diversity, evidencing the impact of heat stress on vegetative and productive traits. Cluster analysis identified five distinct groups, confirming genetic variability and temperature-dependent dissimilarity patterns. Genotypes Bico de Ouro 17-53, Bico de Ouro 17-33 and BRS Tumucumaque maintained higher grain number and grain weight under elevated temperatures, whereas others showed yield reductions of up to 65%. These findings demonstrate exploitable genetic variability for heat tolerance in cowpea and support the use of morpho-agronomic traits as effective criteria for selecting genotypes adapted to warmer environments. Full article

This study conducts a landslide deformation assessment in Tianshui, Gansu Province, on the Chinese Loess Plateau, utilizing the Small Baseline Subset InSAR (SBAS-InSAR) method integrated with velocity direction conversion and Z-score clustering. The Chinese Loess Plateau is one of the most landslide-prone regions in China due to frequent rains, strong topographical gradients and severe soil erosion. By constructing subsets of interferograms, SBAS-InSAR can mitigate the influence of decorrelation to a certain extent, making it a highly effective technique for monitoring regional surface deformation and identifying landslides. To overcome the limitations of the satellite’s one-dimensional Line-of-Sight (LOS) measurements and the challenge of distinguishing true landslide signals from noise, two optimization strategies were implemented. First, LOS velocities were projected onto the local steepest slope direction, assuming translational movement parallel to the slope. Second, a Z-score clustering algorithm was employed to aggregate measurement points with consistent kinematic signatures, enhancing identification robustness, with a slight trade-off in spatial completeness. Based on 205 Sentinel-1 Single-Look Complex (SLC) images acquired from 2014 to 2024, the integrated workflow identified 69 “active, very slow” and 63 “active, extremely slow” landslides. These results were validated through high-resolution historical optical imagery. Time series analysis reveals that creep deformation in this region is highly sensitive to seasonal rainfall patterns. This study demonstrates that the SBAS-InSAR post-processing framework provides a cost-effective, millimeter-scale solution for updating landslide inventories and supporting regional risk management and early warning systems in loess-covered terrains, with the exception of densely forested areas. Full article

Tocosh, a traditional Peruvian fermented potato product, is known for its health-promoting properties, including its antioxidant, anti-inflammatory, probiotic, and antibiotic effects, which have popularized its consumption, particularly in rural areas. To gain a better understanding of its antimicrobial properties, this study aimed to perform a comprehensive whole-genome analysis and functional assessment of the Bacillus velezensis TCSH0001 strain isolated from tocosh. The isolate was identified through whole-genome sequencing using the MinION nanopore platform. AntiSMASH analysis revealed nine biosynthetic gene clusters (BGCs) potentially responsible for producing secondary metabolites with antibiotic potential. Notably, seven BGCs showed a 100% similarity to known clusters involved in the biosynthesis of polyketide synthases (PKSs) and non-ribosomal peptides (NRPSs), including difficidin, bacillibactin, bacilysin, macrolactin H, bacillaene, fengycin, and bacillomycin D. In vitro analysis revealed antimicrobial activity against S. aureus strains. In addition, RT-qPCR indicated that the expression of the baeJ (bacillaene), bmyA (bacillomycin D), and pks2A (macrolactin H) occurs predominantly during the exponential growth phase. Our results suggest that this B. velezensis strain has the capacity to produce a diverse array of bioactive compounds, supporting the traditional use of tocosh as a natural antimicrobial agent, and revealing the potential of the strain as a high NRPS producer. Full article

Rainfall–triggered clustered landslides pose severe risks to communities and infrastructure in mountainous regions. High–precision susceptibility assessment is essential for early warning and hazard mitigation. The traditional buffering method neglects physical slope stability mechanisms, leading to the misclassification of potentially unstable areas. To improve susceptibility model accuracy, we propose an improved non–landslide sampling strategy that integrates the physical–model TRIGRS (Transient Rainfall Infiltration and Grid–based Regional Slope–Stability Model) with 50 m buffering constraints. A hybrid physics–machine learning framework is used to evaluate the performance of landslide susceptibility assessment across four machine learning models, such as Multi–Layer Perceptron (MLP), Random Forest (RF), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost). Among the four models, the TRIGRS model integrated with MLP achieves the highest accuracy in susceptibility mapping. The improved non–landslide sampling strategy increased average Area Under the Curve (AUC) by 16.46% in random cross–validation and improved spatial generalization capability by 29% in spatial cross–validation, demonstrating its robustness in unseen areas. SHAP factor analysis further confirms rainfall, groundwater table, and human activity as the primary influencing factors, which aligns with physical mechanisms and improves model interpretability. Therefore, the proposed non–landslide sampling strategy coupled with the TRIGRS and MLP models outperforms traditional buffering method in evaluating regional landslide susceptibility, providing a more physically basis for geohazard risk assessment. Full article

In the diagnostics of plasmas heated by neutral beam injection (NBI), which serves as a fundamental heating technique, critical core parameters such as ion temperatures and rotational velocities can be measured through NBI’s associated diagnostic methods. However, conventional spectral analysis methods applied in NBI-based Beam Emission Spectroscopy diagnostics face a significant limitation: a relatively high false detection rate during characteristic peak detection and boundary determination. This issue stems from three primary factors: persistent noise interference, overlapping spectral peaks, and dynamic broadening effects. To address this critical issue, we propose a spectral feature extraction method based on morphological segmentation and optimized clustering, with three key innovations that work synergistically: (1) an adaptive chunking algorithm driven by gradient, Laplacian, and curvature features to dynamically partition spectral regions, laying a foundation for localized analysis; (2) a hierarchical residual iteration mechanism combining dynamic thresholding and Gaussian template subtraction to enhance weak peak signals; (3) optimized DBSCAN clustering integrated with morphological closure to refine peak boundaries accurately. Among them, the adaptive chunking technique is distinct from general adaptive methods: its chunking granularity can be dynamically adjusted according to peak structures and can accurately adapt to low signal-to-noise ratio (SNR) scenarios. Experimental results based on measured data from the EAST device demonstrate that the adaptive chunking strategy maintains a missed detection rate of 0–20% across the full signal-to-noise ratio (SNR) range, with false positive rates limited to 16.67–50.00%. Notably, it achieves effective peak detection even under extremely low SNR conditions. Full article

Despite its ecological and economic importance, Hampala macrolepidota (Cyprinidae: Smiliogastrinae) remains taxonomically debated, having undergone historical reclassifications across multiple taxonomic ranks. These challenges highlight the urgent need for integrative genomic analyses to resolve its phylogeny and assess genome-wide diversity, establishing a baseline for effective management and conservation. In this study, the newly assembled mitogenome of H. macrolepidota from within its native range in Lake Dibawah, West Sumatra, Indonesia, was sequenced. The mitogenome spanned 17,104 bp, encoded 37 genes and a control region, and exhibited a nucleotide composition biased toward adenine and thymine. The protein-coding genes (PCGs) predominantly utilized ATG as the initiation codon and showed a higher proportion of hydrophobic compared to hydrophilic amino acids. The nonsynonymous (Ka) and synonymous (Ks) substitution ratios were below ‘1’, which indicates negative selection on most of the PCGs within Hampala and other Smiliogastrinae species. Mitogenome-wide analysis revealed overall high intraspecific genetic diversity (≥2.7%) in the native Indonesian population compared to mainland populations in Southeast Asia. The Bayesian and maximum-likelihood phylogenetic analyses elucidated matrilineal evolutionary relationships within the subfamily Smiliogastrinae, with the Hampala species forming a monophyletic cluster. The present mitogenome-based phylogenetic topologies also supported the taxonomic placement of several species in the revised classification, which previously were classified under the genera Puntius and Barbus, respectively. Additionally, the investigation of partial mitochondrial COI and Cytb genes further elucidated the population genetic structure of H. macrolepidota across Southeast and East Asia. The observed genetic divergence (0–4.2% in COI and 0–4.5% in Cytb), together with well-resolved phylogenetic clustering and the presence of both shared and distinct haplotypes among Indonesian samples, provides strong evidence for long-term population isolation and local adaptation. These patterns are most plausibly driven by historical hydrological dynamics, paleo-drainage connectivity, and persistent geographic barriers that have structured population divergence over time. In addition, this study emphasizes the need to generate mitogenomes of seven additional Hampala species from Southeast Asia to better understand their evolutionary patterns. Further, broader sampling of wild H. macrolepidota populations across their biogeographical range will be essential to strengthen understanding of their genetic diversity and guide effective conservation strategies. Full article

The total cavopulmonary anastomosis (Fontan procedure), a palliative procedure for single-ventricle congenital heart disease, improves survival but is associated with progressive multiorgan complications and high long-term morbidity. Prior blood-based proteomic studies in adults have been limited to targeted antibody-based panels or focused on methodological comparisons. Systemic molecular alterations in younger, clinically heterogeneous patients, particularly in untargeted pathways, remain incompletely characterized. Serum samples from 48 Fontan patients and 48 age- and sex-matched healthy controls were analyzed using mass spectrometry with TMT labeling. 2228 proteins were quantified, of which 124 were significantly differentially abundant (fold change > 1.5 or <0.67, FDR-adjusted p < 0.05). Network analysis identified three major functional clusters: extracellular matrix (ECM) organization (predominantly increased), actin cytoskeleton organization, and platelet-related pathways (both predominantly decreased). Stratified analyses showed reduced ECM protein abundance in high-risk patients, suggesting a shift from active remodeling toward a more established fibrotic state, and uniquely elevated cytochrome b5 reductase 3 (CYB5R3), implicating altered redox homeostasis, nitric oxide metabolism, and cellular aging. Overall, our findings extend prior targeted analyses, reveal potential biomarkers such as CYB5R3 and underscore the complexity of the Fontan circulation, with implications for risk stratification and therapeutic targeting. Full article

Although cytoplasmic male sterility (CMS) is well established in eggplant, CMS-based interspecific hybrids with allied species have not yet been reported or studied. In this study, five previously developed CMS-based interspecific F₁ hybrids between eggplant and Solanum aethiopicum Group Aculeatum (=S. integrifolium) and Group Gilo (=S. gilo), together with their parental lines, were morphologically evaluated for 67 seedling, vegetative, floral, and fruit traits, and their heterosis for vegetative growth was studied. Male fertility was assessed based on anther morphology and pollen viability, while female fertility was evaluated through backcrosses to both parents. The hybrids exhibited predominantly intermediate phenotypes and clustered distinctly from parental lines as confirmed by principal component analysis. Remarkable heterosis was observed for most growth-related traits, indicating favorable nuclear–cytoplasmic interactions despite the use of CMS eggplant lines as maternal parents. All hybrids showed complete male sterility, characterized by non-viable pollen and pronounced anther homeotic alterations, the latter indicating CMS-related effects on male fertility. Female fertility was severely reduced, likely due to meiotic irregularities, as evidenced by the failure of most attempted backcrosses. However, successful recovery of BC₁ progeny after backcrossing one CMS-based F₁ hybrid to S. gilo demonstrates partial reproductive compatibility and provides a genetic bridge for CMS introgression into S. gilo. These results indicate that CMS systems are suitable for eggplant interspecific crosses aimed at vigorous rootstock production and CMS cytoplasm introgression into allied germplasm. Full article

By addressing the challenges of management difficulties, insufficient integration of driver analysis, and single-dimensional analysis in the governance of illegal land use and illegal construction (collectively referred to as the “Two Illegalities”) under rapid urbanization, this study designs and implements a GIS-based governance system using Xiamen City as the study area. First, we propose a standardized data-processing workflow and construct a comprehensive management platform integrating multi-source data fusion, spatiotemporal visualization, intelligent analysis, and customized report generation, effectively lowering the barrier for non-professional users. Second, utilizing methods integrated into the platform, such as Moran’s I and centroid trajectory analysis, we deeply analyze the spatiotemporal evolution and driving mechanisms of “Two Illegalities” activities in Xiamen from 2018 to 2023. The results indicate that the distribution of “Two Illegalities” exhibits significant spatial clustering, with hotspots concentrated in urban–rural transition zones. The spatial morphology evolved from multi-core diffusion to the contraction of agglomeration belts. This evolution is essentially the result of the dynamic adaptation between regional economic development gradients, urbanization processes, and policy-enforcement synergy mechanisms. Through a modular, open technical architecture and a “Data-Technology-Enforcement” collaborative mechanism, the system significantly improves information management efficiency and the scientific basis of decision-making. It provides a replicable and scalable technical framework and practical paradigm for similar cities to transform “Two Illegalities” governance from passive disposal to active prevention and control. Full article