Search Results (1,084)

Understanding and forecasting energy consumption patterns is crucial for improving energy efficiency and human well-being, especially in diverse infrastructures like Spain. This research addresses a significant gap in energy demand forecasting across three building types by comparing six machine learning algorithms: Artificial Neural Networks, Random Forest, XGBoost, Radial Basis Function Network, Autoencoder, and Decision Trees. The primary aim is to identify the most effective model for predicting energy consumption based on historical data, contributing to the relationship between energy systems and urban well-being. The study emphasizes challenges in energy use and advocates for sustainable management practices. By forecasting energy demand over the next three years using linear regression, it provides actionable insights for energy providers, enhancing resilience in urban environments impacted by climate change. The findings deepen our understanding of energy dynamics across various building types and promote a sustainable energy future. Stakeholders will receive targeted recommendations for aligning energy production with consumption trends while meeting environmental responsibilities. Model performance is rigorously evaluated using metrics like Squared Mean Root Percentage Error (RMSPE) and Coefficient of Determination (R²), ensuring robust analysis. Training times for models in the LUCIA building ranged from 2 to 19 s, with the Decision Tree model showing the shortest times, highlighting the need to balance computational efficiency with model performance. Full article

Rural revitalization, as a crucial strategic goal for rural development in contemporary China, encompasses multidimensional connotations and requirements. Following the establishment of the ‘three rights separation’ system in 2014, land transfer has increasingly assumed a vital role, demonstrating a close and complex intrinsic logical relationship with rural revitalization. To comprehensively analyze the diverse impacts of land transfer on rural revitalization as discussed in the literature, we employ a ‘goal–strategy–indicator–outcome’ analytical framework to conduct a meta-analysis and visual assessment of 131 cases drawn from 52 articles published over the past decade. We systematically explore the pathways by which land transfer impacts rural revitalization and validate the results using typical cases reported by the Ministry of Agriculture and Rural Affairs through Python 3.9 analysis. The findings reveal the following: (1) Land transfer generally exerts a positive impact on rural revitalization (81.7% of 107 cases). (2) It significantly boosts living standards (84% positive cases) and industrial prosperity (88.4% positive cases); rural cultural civilization shows 100% positive cases yet with statistically insignificant coefficients, while its impacts on ecological livability (60%) and effective governance (70.6%) are insignificant. (3) Among 12 indicators, those related to agricultural production and farmers’ livelihoods are positive, whereas those concerning rural ecology and governance are negative. This study indicates that land transfer plays a key role in the rural revitalization strategy, but the ecological impacts and governance challenges that it presents require ongoing attention and optimization at the policy level. Full article

Niche complementarity is suggested to be a main driver of productivity overyielding in diverse environments due to enhanced resource use efficiency and reduced competition. Here, we combined multiple different approaches to demonstrate that niche overlap is the most likely cause to explain a lack of overyielding of three tree species when grown in different species combinations. First, in an experimental planting we found no relationship between productivity and species diversity for leaf, wood, or root production (no slope was significantly different from zero), suggesting a lack of niche differences among species. Second, data extracted from the United States Department of Agriculture Forest Inventory and Analysis revealed that the species do not significantly co-occur in natural stands (p = 0.4065) as would be expected if coexistence was common across their entire range. Third, we compared trait differences among our species and found that they are not significantly different in multi-dimensional trait space (p = 0.1724). By combining multiple analytical approaches, we provide evidence of potential niche overlap that precludes coexistence and a positive diversity–productivity relationship between these three tree species. Full article

China’s national strategies emphasize both achieving carbon peaking and neutrality (“dual carbon” objectives) and fostering high-quality economic development. This dual focus highlights the critical importance of the Green and Low-Carbon Transition (GLCT) of the economy and the development of New Quality Productive Forces (NQPF). Firms are central actors in this transformation, prompting the core research question: How does corporate engagement in GLCT contribute to the formation of NQPF? We investigate this relationship using panel data comprising 33,768 firm-year observations for A-share listed companies across diverse industries in China from 2012 to 2022. Corporate GLCT is measured via textual analysis of annual reports, while an NQPF index, incorporating both tangible and intangible dimensions, is constructed using the entropy method. Our empirical analysis relies primarily on fixed-effects regressions, supplemented by various robustness checks and alternative econometric specifications. The results demonstrate a significantly positive relationship: corporate GLCT robustly promotes the development of NQPF, with dynamic lag structures suggesting delayed productivity realization. Mechanism analysis reveals that this effect operates through three primary channels: improved access to financing, stimulated collaborative innovation and enhanced resource-allocation efficiency. Heterogeneity analysis indicates that the positive impact of GLCT on NQPF is more pronounced for state-owned enterprises (SOEs), firms operating in high-emission sectors, those in energy-efficient or environmentally friendly industries, technology-intensive sectors, non-heavily polluting industries and companies situated in China’s eastern regions. Overall, our findings suggest that corporate GLCT enhances NQPF by improving resource-utilization efficiency and fostering innovation, with these effects amplified by specific regional advantages and firm characteristics. This study offers implications for corporate strategy, highlighting how aligning GLCT initiatives with core business objectives can drive NQPF, and provides evidence relevant for policymakers aiming to optimize environmental governance and foster sustainable economic pathways. Full article

Since the mid-19th century, researchers have explored the potential of bio-based polymeric materials for diverse applications, with particular promise in medicine. This review provides a focused and detailed examination of natural and synthetic biopolymers relevant to tissue engineering and biomedical applications. It emphasizes the structural diversity, functional characteristics, and processing strategies of major classes of biopolymers, including polysaccharides (e.g., hyaluronic acid, alginate, chitosan, bacterial cellulose) and proteins (e.g., collagen, silk fibroin, albumin), as well as synthetic biodegradable polymers such as polycaprolactone, polylactic acid, and polyhydroxybutyrate. The central aim of this manuscript is to elucidate how intrinsic properties—such as molecular weight, crystallinity, water retention, and bioactivity—affect the performance of biopolymers in biomedical contexts, particularly in drug delivery, wound healing, and scaffold-based tissue regeneration. This review also highlights recent advancements in polymer functionalization, composite formation, and fabrication techniques (e.g., electrospinning, bioprinting), which have expanded the application potential of these materials. By offering a comparative analysis of structure–property–function relationships across a diverse range of biopolymers, this review provides a comprehensive reference for selecting and engineering materials tailored to specific biomedical challenges. It also identifies key limitations, such as production scalability and mechanical performance, and suggests future directions for developing clinically viable and environmentally sustainable biomaterial platforms. Full article

In this cross-disciplinary investigation, we uncover a suite of previously unexamined factors and their intricate interplay that hold causal relationships with the distribution of Trachurus japonicus in the northern reaches of the South China Sea, thereby extending the existing research paradigms. Leveraging advanced machine learning algorithms and causal inference, our robust experimental design uncovered nine key global and regional factors affecting the distribution of T. japonicus density. A robust experimental design identified nine key factors significantly influencing this density: mean sea-level pressure (msl-0, msl-4), surface pressure (sp-0, sp-4), Summit ozone concentration (Ozone_sum), F10.7 solar flux index (F10.7_index), nitrate concentration at 20 m depth (N3M20), sonar-detected effective vertical range beneath the surface (Height), and survey month (Month). Crucially, stable causal relationships were identified among Ozone_sum, F10.7_index, Height, and N3M20. Variations in Ozone_sum likely impact surface UV radiation levels, influencing plankton dynamics (a primary food source) and potentially larval/juvenile fish survival. The F10.7_index, reflecting solar activity, may affect geomagnetic fields, potentially influencing the migration and orientation behavior of T. japonicus. N3M20 directly modulates primary productivity by limiting phytoplankton growth, thereby shaping the availability and distribution of prey organisms throughout the food web. Height defines the vertical habitat range acoustically detectable, intrinsically linking directly to the vertical distribution and availability of the fish stock itself. Surface pressures (msl-0/sp-0) and their lagged effects (msl-4/sp-4) significantly influence sea surface temperature profiles, ocean currents, and stratification, all critical determinants of suitable habitats and prey aggregation. The strong influence of Month predominantly reflects seasonal changes in water temperature, reproductive cycles, and associated shifts in nutrient supply and plankton blooms. Rigorous robustness checks (Data Subset and Random Common Cause Refutation) confirmed the reliability and consistency of these causal findings. This elucidation of the distinct biological and physical pathways linking these diverse factors leading to T. japonicus density provides a significantly improved foundation for predicting distribution patterns globally and offers concrete scientific insights for sustainable fishery management strategies. Full article

Stylolites are ubiquitous diagenetic products in carbonate rocks. They play a significant role in enhancing or reducing fluid flow in subsurface reservoirs. This study unravels the relationship between stylolite networks, carbonate microfacies, and the elemental geochemistry of Upper Cretaceous limestones of the Kometan Formation (shallow to moderately deep marine) in Northern Iraq. Stylolites exhibit diverse morphologies across mud- and grain-supported limestone facies. Statistical analyses of stylolite spacing, wavelength, amplitude, and their intersections and connectivity indicate that grain size, sorting, and mineral composition are key parameters that determine the geometrical properties of the stylolites and stylolite networks. Stylolites typically exhibit weak connectivity and considerable vertical spacing when hosted in packstone facies with moderate grain sorting. Conversely, mud-supported limestones, marked by poor sorting and high textural heterogeneity, host well-developed stylolite networks characterized by high amplitude and frequent intersections, indicating significant dissolution and deformation processes. Stylolites in mud-supported facies are closely spaced and present heightened amplitudes and intensified junctions, with suture and sharp-peak type. This study unveils that stylolites can potentially enhance porosity in the studied formation. Full article

The S100B protein, known for its role in the central and enteric nervous systems, has recently been identified in dietary sources such as milk, dairy products, fruits, and vegetables. Given its potential interaction with the gut microbiota, this study explores the relationship between dietary intake of S100B and microbiota biodiversity across different diets. A comprehensive study was conducted, estimating S100B concentrations in 13 dietary patterns recommended in different countries. This is the first study to provide a comparative estimation of S100B exposure from the diet and to explore its potential ecological and epidemiological relevance. The association between S100B levels and microbiota biodiversity was statistically analyzed, showing a direct correlation. Microbial diversity was assessed using the Shannon index, based on data extracted from studies reporting microbiota composition across dietary patterns. Additionally, the relative risk of Crohn’s disease was assessed in different populations to examine potential links between dietary patterns, S100B, and chronic disease prevention. A moderate positive correlation (R² = 0.537) was found between S100B concentration and Shannon index, suggesting that diets higher in S100B (e.g., Mediterranean diet) were associated with higher microbial alpha-diversity. Furthermore, Western-style diets, with the lowest S100B levels, exhibited a higher relative risk for Crohn’s disease (R² = 0.780). These findings highlight the potential role of dietary S100B content in modulating gut microbiota diversity and reducing chronic disease risk. Full article

Accurate estimation of aboveground biomass (AGB) in tree–shrub communities is critical for quantifying forest ecosystem productivity and carbon sequestration potential. Although generalized allometric equations offer expediency in natural forest AGB estimation, their neglect of interspecific variability introduces methodological pitfalls. Precise AGB prediction necessitates resolving two biological constraints: phylogenetic conservation of allometric coefficients and ontogenetic regulation of scaling relationships. This study establishes an integrated framework combining the following: (1) phylogenetic signal detection (Blomberg’s K/Pagel’s λ) across 157 species’ allometric equations, revealing weak but significant evolutionary constraints (λ = 0.1249, p = 0.0027; K ≈ 0, p = 0.621); (2) hierarchical error decomposition of 9105 stems in a Mt. Wuyishan forest dynamics plot (15 species), identifying family-level error stratification (e.g., Theaceae vs. Myrtaceae, Δerror > 25%); (3) ontogenetic trajectory analysis of Castanopsis eyrei between Mt. Wuyishan and Mt. Huangshan, demonstrating significant biomass deviations in small trees (5–15 cm DBH, p < 0.05). Key findings resolve the following hypotheses: (1) absence of strong phylogenetic signals validates generalized models for phylogenetically diverse communities; (2) ontogenetic regulation dominates error magnitude, particularly in early developmental stages; (3) differential modeling is recommended: species-specific equations for pure forests/seedlings vs. generalized equations for mixed mature forests. This work establishes an error hierarchy: ontogeny > taxonomy > phylogeny, providing a mechanistic basis for optimizing forest carbon stock assessments. Full article

In recent years, passive acoustic monitoring (PAM) technology has significantly contributed to advancements in aquaculture techniques, system iterations, and increased production yields within intelligent feeding systems for Penaeus vannamei. However, current PAM-based intelligent feeding systems do not incorporate environmental factors into the decision process, limiting the improvement of monitoring accuracy in complex environments such as ponds. To establish a connection between environmental factors and the feeding acoustics of P. vannamei, this study utilized PAM technology combined with video analysis to investigate the effects of three key environmental factors—temperature, ammonia nitrogen, and nitrite nitrogen—on the feeding behavioral characteristics of shrimp, with a specific focus on acoustic signals “clicks”. The results demonstrated a significant correlation between the number of clicks and feed consumption in shrimp across different treatments, establishing this stable relationship as a reliable indicator for assessing shrimp feeding status. When water temperature increased from 20 °C to 32 °C, shrimp feed consumption showed an elevation from 0.46 g to 0.95 g per 30 min, with the average number of clicks increasing from 388 to 2947.58 and sound pressure levels rising accordingly. Conversely, ammonia nitrogen at 12 mg/L reduced feed consumption by 0.15 g and decreased click counts by 911.75 pulses compared to controls, while nitrite nitrogen at 40 mg/L similarly suppressed feed consumption by 0.15 g and the average number of clicks by 304.75. A rise in water temperature stimulated shrimp behaviors such as feeding, swimming, and foraging, while elevated concentrations of ammonia nitrogen and nitrite nitrogen significantly inhibited shrimp activity. Redundancy analysis revealed that temperature was the most prominent factor among the three environmental factors influencing shrimp feeding. This study is the first to quantify the specific effects of common environmental factors on the acoustic feeding signals and feeding behavior of P. vannamei using PAM technology. It confirms the feasibility of using PAM technology to assess shrimp feeding conditions under diverse environmental conditions and the necessity of integrating environmental monitoring modules into future feeding systems. This study provides behavioral evidence for the development of precise feeding technologies and the upgrade of intelligent feeding systems for P. vannamei. Full article

The excessive use of antimicrobials drives the emergence of multidrug resistance (MDR) in bacterial strains, which harbor resistance genes to survive under diverse drug pressures. Such resistance can result in life-threatening infections. The predominance of MDR Pseudomonas spp. poses significant challenges to public health and environmental sustainability, particularly in ecosystems affected by human activities. Characterizing MDR Pseudomonas spp. is crucial for developing effective diagnostic tools and biosecurity protocols, with broader implications for managing other pathogenic bacteria. Strains were diagnosed through 16S rRNA PCR and sequencing, complemented by phylogenetic analysis to evaluate local and global evolutionary connections. Antibiotic susceptibility tests revealed extensive resistance across multiple classes, with MIC values surpassing clinical breakpoints. This study examined the genetic diversity, resistance potential, and phylogenetic relationships among Pseudomonas aeruginosa strain DG2 and Pseudomonas fluorescens strain FM3, which were isolated from solid waste dump sites (n = 30) and dairy farms (n = 22) in West Bengal, India. Phylogenetic analysis reveals distinct clusters that highlight significant geographic linkages and genetic variability among the strains. Significant biofilm production under antibiotic exposure markedly increased resistance levels. RAPD-PCR profiling revealed substantial genetic diversity among the isolates, indicating variations in their genetic makeup. In contrast, SDS-PAGE analysis provided insights into the protein expression patterns that are activated by stress, which are closely linked to MDR. This dual approach offers a clearer perspective on their adaptive responses to environmental stressors. This study underscores the need for vigilant monitoring of MDR Pseudomonas spp. in anthropogenically impacted environments to mitigate risks to human and animal health. Surveillance strategies combining phenotypic and molecular approaches are essential to assess the risks posed by resilient pathogens. Solid waste and dairy farm ecosystems emerge as critical reservoirs for the evolution and dissemination of MDR Pseudomonas spp. Full article

Online reviews play a critical role in shaping consumer decisions and providing valuable insights to enhance the products and services for businesses. As visual content becomes increasingly prevalent in reviews, it is essential to understand how image complexity influences review helpfulness. Despite the growing importance of images, the impact of color diversity and texture homogeneity on review helpfulness remains underexplored. Grounded in Information Diagnosticity Theory and Dual Coding Theory, this study investigates the relationship between image complexity and review helpfulness, as well as the moderating role of review text readability. Using a large-scale dataset from the hotel and travel sectors, the findings reveal that color diversity has a positive effect on review helpfulness, while texture homogeneity follows an inverted U-shaped relationship with helpfulness. Furthermore, text readability strengthens the positive impact of texture homogeneity, making moderately homogeneous images more effective when paired with clear and well-structured text. Heterogeneity analysis demonstrates that these effects vary across product categories. The results advance the understanding of multimodal information processing in online reviews, providing actionable guidance for platforms and businesses to refine the review systems. Full article

Monoterpene indole alkaloids (MIAs) exhibit diverse structures and pharmacological effects. Annotating MIAs in herbal medicines remains challenging when using liquid chromatography combined with high-resolution mass spectrometry (LC-HRMS). This study introduced a new annotation strategy employing LC-HRMS to efficiently identify MIAs in herbal medicines. Briefly, MS² spectra under multiple collision energies (MCEs/MS²) helped capture high-quality product ions across a range of mass-to-charge (m/z) values, revealing key MS² features such as diagnostic product ions (DPIs), characteristic cleavages (CCs), and neutral/radical losses (NLs/RLs). Next, feature-based molecular networking (FBMN) was created to map the structural relationships among MIAs across large MS datasets. Potential MIAs were then graded and annotated through systematic comparison with known biosynthetic pathways (BPs), derived skeletons, and their characteristic substituents. The MCEs/MS²-FBMN/BPs workflow was first applied to annotate MIAs in the alkaloids from the leaf of Alstonia scholaris (ALAS), a new botanical drug for respiratory diseases. A total of 229 MIAs were systematically annotated and classified, forming a solid basis for future clinical research on ALAS. This study offers an effective strategy that enhances the structural annotation of MIAs within complex herbal medicines. Full article

Plant triterpenoids are structurally diverse specialized metabolites with significant ecological, medicinal, and agricultural importance. Oxidosqualene cyclases (OSCs) catalyze the crucial cyclization step in triterpenoid biosynthesis, generating the fundamental carbon skeletons that determine their structural diversity and biological functions. Genome-wide identification of OSC genes was performed using bioinformatics tools, including HMMER and BLASTP, followed by phylogenetic analysis, gene structure analysis, conserved domain and motifs identification, cis-regulatory element prediction, protein–protein interaction analysis, and expression profiling using publicly available transcriptome data from UV-B treated A. annua six-week-old seedlings. We identified 24 AaOSC genes, classified into CAS, LAS, LUS, and unknown subfamilies. Phylogenetic analysis revealed evolutionary relationships with OSCs from other plant species. Gene structure analysis showed variations in exon–intron organization. Promoter analysis identified cis-regulatory elements related to light responsiveness, plant growth and development, hormone signaling, and stress response. Expression profiling revealed differential expression patterns of AaOSC genes under UV-B irradiation. This genome-wide characterization provides insights into the evolution and functional diversification of the OSC gene family in A. annua. The identified AaOSC genes and their regulatory elements lay the foundation for future studies aimed at manipulating triterpenoid biosynthesis for medicinal and biotechnological applications, particularly focusing on enhancing stress tolerance and artemisinin production. Full article

The continuous usage years of mud pits significantly impact the formation of volatile flavor compounds (VFCs) in Wuliangye Baijiu fermentation, yet their role in regulating initial microbial diversity and VFCs during fermentation remains unclear. This research analyzed the dynamic relationships among microorganisms, physicochemical characteristics, and VFCs from two different aged mud pits (continuous usage for 20 years: JC20 and 40 years: JC40). As fermentation advanced, VFCs increased, with JC40 showing a greater increment than JC20. Furthermore, the predominated microorganisms during fermentation of two pits were significantly different, resulting in distinct microbial successions. And the microbial diversity in JC40 was higher than JC20 at the fermentation anaphase from different layers of zaopei samples. Microbes were identified that highly correlated with physicochemical properties and VFCs, and the important microbial species differed between the two pits, proving the importance of mud pit continuous usage years for Wuliangye Baijiu production. Full article