Search Results (309,828)

The integration of environmental sustainability (ES) into strategic planning (SP) has become more vital in the tourism and hospitality (T&H) sector, due to its significant reliance on natural resources and environmental quality. This study seeks to analyze how ES is systematically integrated into strategic planning processes, identify critical dimensions and challenges, and evaluate the degree of organizational awareness and strategic focus on sustainability. A systematic literature review was conducted using the Scopus and Web of Science databases, covering global studies published between 2024 and 2025, resulting in a final sample of 43 articles. A hybrid deductive–inductive methodology was employed to integrate the data. The findings indicate that ES integration is a complex and iterative process involving governance and leadership, strategic development, resource and environmental management, stakeholder involvement, performance assessment, and the application of analytical and technological instruments. The results also emphasize emergent aspects such as digital innovation and adaptive planning. Despite this advancement, implementation is inconsistent due to capacity limitations, fragmented governance, data deficiencies, and environmental–economic trade-offs. The study illustrates a distinct convergence between ES and SP, signifying a transition towards integrated, evidence-based, and adaptable strategic systems. The study enhances the literature by delivering a thorough synthesis of integration mechanisms and presents practical insights for promoting sustainable strategic planning in the T&H sector. Full article

Sustainable crop production in nutrient-poor sandy soils requires fertilization strategies that improve nutrient uptake while reducing environmental impact. This study evaluated anaerobic cattle manure digestate and carbon dot biostimulants as alternatives to conventional mineral NPK (nitrogen–phosphorus–potassium) fertilizer for corn (Zea mays L., cv. AG 1051) during vegetative development. A randomized greenhouse experiment compared nine treatments over three successive 45-day cycles, assessing shoot-tissue macronutrient content (N, P, K) and morphological parameters (shoot dry weight, stem diameter, and plant height). Digestate delivered approximately 1.4× more phosphorus and 8.4× more potassium per pot than mineral NPK, although nitrogen inputs were matched (~77 mg pot⁻¹). Digestate-based treatments achieved shoot dry weight 132% above control and 63% above mineral fertilizer (p < 0.001), with biomass advantages sustained across all three cycles while mineral fertilizer effects dissipated entirely by Cycle 3. Phosphorus content was the strongest biomass predictor (r = 0.86, p < 0.001), and a significant nitrogen–phosphorus antagonism (r = −0.59, p < 0.001) revealed relevant nutrient interaction dynamics. The higher biomass observed under digestate-based treatments reflects both the higher total P and K inputs from digestate and the beneficial effects of organic matter on nutrient bioavailability in this phosphorus-limited system. Carbon dot biostimulants did not improve biomass when applied alone (values at or below control), but they contributed to intermediate biomass gains when combined with nutrient sources, functioning as nutrient uptake enhancers rather than standalone fertilizers. Principal component analysis (74.3% variance explained) classified the nine treatments into three distinct treatment clusters. These findings support digestate valorization as a circular-economy alternative to conventional mineral fertilization, offering higher biomass under N-equivalent application and sustained residual effects in nutrient-poor sandy soils. Full article

Adding inspection trains to existing railway timetables is a complex task that must balance operational efficiency and service reliability, which are essential for the sustainable operation and maintenance of high-speed railway infrastructure. To address this challenge, a feasible region-based space–time network modeling approach is proposed for incorporating Comprehensive Inspection Trains (CITs) into existing railway schedules, aiming to enhance inspection efficiency while minimizing operational disruptions. Firstly, the constraints that need to be considered when scheduling for CIT are comprehensively analysed and modelled, and a mixed-integer nonlinear model with the objective of minimizing the total number of stops is constructed. In order to eliminate the difficulty of solving this model, based on the original space–time network method, more kinds of train event arcs are introduced to accurately portray the train operation process; in particular, the extra time consumed due to the acceleration and deceleration process is also reflected in the network construction process. The feasibility of various event arcs is evaluated with time windows, and the original problem finally transforms into the equivalent shortest path problem on a feasible event arc network. The processing procedure includes key stages, such as station space–time discretization, interval operation event processing, station capacity handling, and network simplification. The experimental results indicate that the approach effectively resolves all station capacity conflicts, compresses inspection durations, and optimizes the number of stops. Remarkably, the number of non-full-speed inspection sections is reduced by 43.16%, demonstrating the model’s efficiency. Additionally, the proposed approach is computationally efficient, improves timetable capacity utilization for infrastructure inspection, and supports the sustainable operation of high-speed railway systems. Full article

This study investigated the contamination characteristics, sources, and ecological risks of organochlorine pesticides (OCPs) in surface sediments from three plateau lakes in southwestern China (Qilu Lake, Dianchi Lake, and Yangzonghai Lake). Significant differences in OCP pollution levels were observed among the three lakes. Hexachlorocyclohexanes (HCHs) were identified as the dominant contaminants, reflecting historical technical HCH input and subsequent long-term aging, whereas dichlorodiphenyltrichloroethanes (DDTs) exhibited generally low concentrations and originated primarily from historical technical use, with predominantly aerobic degradation. Principal component analysis (PCA) revealed that agricultural non-point source pollution was the main contributor to OCP residues. Ecological risk assessment demonstrated that most OCPs posed low or negligible risk; however, γ-HCH (lindane) ubiquitously presented moderate risk across all lakes, with one site exceeding the high-risk threshold. Endrin derivatives and methoxychlor further elevated combined risks at specific sites. Notably, the unique hydrological characteristics of plateau lakes may enhance OCP retention and accumulation in sediments. These findings provide a scientific basis for ecological risk management and pollution control in plateau lakes. Full article

Horqin Sandy Land suffers from desertification, drought, and low fertility, limiting soybean production. Agrivoltaics provides a promising integrated model; however, the effects of agrivoltaics combined with water–fertilizer management on crop productivity remain unclear. A 2-year field experiment was conducted in a semi-arid area with three treatments, open-field control (Open), shaded area under panels (Under), and light-exposed area inter-panels (Gap). Results showed that photovoltaic systems combined with integrated water–fertilizer management improved soybean yield, soil water, and nutrient conditions. Soybean grain yield was 60.7% and 38.2% higher in the Gap and Under treatments, respectively, than in the Open. The highest yield in the Gap treatment resulted from both enhanced photosynthesis and improved root development. The Under endured light stress but exhibited morphological plasticity (plant height and leaf area increased by 43.1%, 48.2%), and shading alleviated water stress since soil water content was increased by 81.6–119.0% during growing seasons, transpiration rate (Tr) decreased by 55.1%, and leaf water use efficiency (WUE) increased by 48.8%. The Open suffered from soil degradation and water and fertilizer loss, resulting in severely limited yield. Agrivoltaics increased net income by 1466 CNY·ha⁻¹ and improved soil nutrients, demonstrating economic and ecological benefits. Thus, it is a suitable technical model for semi-arid sandy regions. Full article

Accurate cultivar identification of commercial dried goji berries is essential for raw material sorting, batch consistency assessment, and quality control during processing and distribution. Conventional approaches based on manual judgment or physicochemical analysis are often subjective, labor-intensive, time-consuming, and costly, making them unsuitable for rapid commercial sorting and quality inspection. To develop a rapid, low-cost, and nondestructive method for dried goji berry cultivar identification, this study proposes a visual recognition framework that integrates RGB imaging with lightweight deep learning. A dataset comprising 25,899 RGB images from five cultivars of commercial dried goji berry samples, namely Ningqi No. 7, Linqi No. 5, Ningqi No. 1, Keqi 6082, and Jingqi No. 1, was constructed. Given the pronounced surface shrinkage, complex texture, and subtle inter-cultivar appearance differences of dried goji berries, an image quality enhancement method was designed to strengthen the representation of color gradation, textural details, and edge information. For model development, CoAtNet was selected as the baseline network and redesigned for lightweight deployment. By integrating an improved feature extraction module and an information-preserving downsampling module, the proposed LSH-CoAtNet model enhances fine-grained feature representation while reducing computational cost. On the quality-enhanced image dataset, the proposed method achieved an accuracy of 98.80%, a precision of 98.81%, a recall of 98.80%, and an F1-score of 98.80%. The model contained only 6.41 M parameters and required 1.60 GFLOPs, outperforming the baseline model in both classification performance and computational efficiency. Ablation experiments and five-fold cross-validation further confirmed the effectiveness of the image quality enhancement strategy, the contribution of each improved module, and the stability of the model. Overall, the proposed method, which combines RGB image quality enhancement with LSH-CoAtNet, provides a low-cost, nondestructive, and efficient technical solution for rapid cultivar identification, raw material sorting, batch consistency assessment, and quality control of commercial dried goji berries during processing and distribution. It may also serve as a reference for intelligent classification and quality inspection of other specialty dried horticultural products. Full article

Photoacoustic spectroscopy (PAS), quartz-enhanced photoacoustic spectroscopy (QEPAS), and light-induced thermoelastic spectroscopy (LITES) represent indirect absorption spectroscopy techniques for trace gas sensing, whose performance has long been advanced through hardware-oriented enhancement strategies. However, as hardware technologies continue to advance, conventional hardware-based enhancements are increasingly bottlenecked by weak responses, complex cross-interferences, and coupled multiphysics parameters. To transcend these limitations, algorithm-assisted methods, including traditional algorithms, machine learning, deep learning, and intelligent optimization, are being systematically integrated into these spectroscopic systems. This review summarizes recent progress in intelligent indirect absorption spectroscopy from three interconnected dimensions. First, we outline advanced signal processing and spectral reconstruction strategies designed to achieve weak-signal recovery and background noise suppression. Second, the focus shifts to data-driven parameter inversion, showing how multidimensional artificial intelligence models contribute to concentration retrieval, environmental compensation, multicomponent recognition, spectral-overlap decoupling, and front–back-end collaborative waveform coding and demultiplexing. Third, intelligent system optimization is examined, in which surrogate modeling, swarm-intelligence search, physics-guided topology optimization and multi-objective algorithms are employed to improve the design efficiency of the key elements such as photoacoustic resonators and multipass cells (MPCs). Additionally, prospects for future technological developments are also discussed in the concluding section. Full article

The primary objective of this article is to examine the organizational, economic, and sustainability-related implications of implementing artificial intelligence (AI) systems in small and medium-sized enterprises (SMEs) in Poland. The study combines a survey of 112 SMEs in the Kuyavian–Pomeranian region, including 70 AI-using firms, with 13 in-depth interviews with managers. The quantitative analysis applies logit models to identify determinants of perceived AI effects on internal processes: working time and workload reduction, automation, cost effects, and creativity. The qualitative component explains how AI is adopted and embedded in business practice. The results show that AI adoption in SMEs is increasingly common but remains uneven and mostly operational. The strongest effects concern workload reduction and time efficiency, particularly in service firms and where AI is used intensively. Advanced AI adoption increases the probability of perceiving workload and cost-related effects. However, these effects should not be interpreted simply as direct cost reduction. Rather, AI improves productivity and work capacity while creating new costs related to paid tools, data preparation, integration, output verification, and governance. The interviews show that AI implementation follows a staged path: from curiosity-driven experimentation, through cognitive work augmentation, to workflow integration and, in selected cases, AI-enabled business model innovation. The transition from ad hoc use to strategic implementation depends less on firm size alone and more on process maturity, capabilities, and data readiness. Barriers also change with maturity: early-stage firms face a lack of knowledge, time, and clear use cases, whereas advanced users encounter data quality, hallucinations, security, integration, and governance problems. The study finds that sustainability considerations, particularly environmental impacts and ESG-related implications of AI, remain largely unperceived in SME decision-making. Entrepreneurs primarily interpret sustainability through the lenses of organizational resilience, long-term competitiveness, adaptability, and responsible digital transformation rather than through formal environmental metrics. The findings suggest that SME managers should implement AI gradually, link adoption to measurable process-level outcomes, and invest in AI literacy and governance. They should also integrate responsible AI principles into organizational strategy to support sustainable digital transformation. The study contributes to the literature by showing that AI adoption in SMEs should be understood not only as a productivity-enhancing process but also as a broader organizational transition shaping long-term sustainability and resilience. Full article

Despite the significant reduction in the overall cultivated area registered in recent decades, poplar still plays an important economic role in the Po Valley–Italy, where many farms involved in the plantation of this species are present, and the leading wood-processing industries are located. This paper describes the current organization of the poplar plywood wood-chain and explores the challenges in introducing new cultivars into the sector. In particular, it analyzes the main physico-mechanical properties of solid wood from five selected poplar clones (‘Dvina’, ‘Lux’, ‘Mella’, ‘Soligo’, ‘Taro’) that are characterized by fast growth, more sustainable agronomic practices, and increased disease resistance. These clones were cultivated in a seven-year-old linear plantation located in Northern Italy. This model, widely used in the past, is being re-proposed as a complement to the traditional system with square planting distances. The peeling yields and some performances of plywood manufactured from their veneers were also investigated. Results indicate that all clones have a much higher (from +30% to +56%) wood basic density than the ‘I-214’, which remains the lighter and preferred reference. These clones appeared also suitable for rotary cutting, but only ‘Lux’ and ‘Soligo’, and to a lesser extent ‘Mella’, provided veneers of the best quality class. Interesting mechanical features were registered for the sample plywood produced, especially in relation to the age of the harvested timber, which reached a diameter adequate for processing in a shorter time compared to the turnover adopted in conventional plantations. Except for ‘Dvina’, for all the clones, bending MOE and MOR were found to be comparable with those of spruce plywood made of similar thickness and the same lay-up. The findings suggest that the availability of new poplar cultivars and that of different cultivation models designed to enhance fast growth, when supported by targeted research and cooperation among multiple stakeholders (including farmers and industrial manufacturers), can lead to new applications where their plywood performances are valued. This, in turn, allows the resulting panels to meet specific needs in previously unexplored sectors, offering additional market opportunities. Full article

Conventional forensic DNA profiling predominantly utilizes established core sets of autosomal short tandem repeats (STRs), such as the FBI’s Combined DNA Index System (CODIS) and the European Standard Set (ESS). While these panels are effective for standard forensic casework, they may be inadequate in more demanding scenarios, including severely degraded samples, complex multi-contributor mixtures, and kinship cases with deficiencies, where enhanced discriminatory capability is crucial. Additional non-core STR loci address these challenges while maintaining the non-coding, phenotypically uninformative nature that ensures the legal and ethical acceptability of forensic genetic evidence in court. This review assesses the forensic applications, population genetic parameters, validation requirements, and ethical considerations associated with non-core STR loci. A representative supplementary STR panel is presented as a case study to illustrate both the forensic value and the analytical requirements associated with the implementation of extended non-core STR systems. Challenges in implementation were identified in areas such as nomenclature standardization, backward compatibility with existing national databases, and geographic gaps in population reference data. The review concludes that a hybrid strategy, which retains core capillary electrophoresis (CE)-based profiling for routine casework and employs extended non-core panels for complex cases, represents the most practical path for the field. Full article

Breast cancer is among the most commonly diagnosed malignancies in women and remains difficult to treat due to therapy resistance and the adverse effects associated with conventional chemotherapeutic regimens. In this study, the anticancer activity of the ethanolic root extract of Salvadora persica (S. persica), commonly known as Miswak, was evaluated in human breast cancer cells using a combination of in vitro assays, phytochemical profiling, and computational analyses. HRLC-MS/MS characterization revealed a wide range of bioactive constituents, including alkaloids, flavonoid derivatives, glucosinolates, and fatty acid–based molecules detected under both ionization modes. The extract exhibited a concentration-dependent cytotoxic effect on breast cancer MCF-7 and MDA-MB-231 cells, with IC₅₀ values of 144.1 and 176.3 µg/mL, respectively, as determined by the MTT assay, while exerting negligible toxicity toward normal Vero cells. Miswak extract enhanced intracellular ROS production, disruption of MMP, nuclear condensation, and increased apoptotic cell populations, along with S-phase cell cycle arrest, pointing toward activation of mitochondrial-mediated apoptosis. In silico docking results indicated that key phytoconstituents exhibit strong binding interactions with multiple breast cancer–relevant targets such as ERα, PR, EGFR, HER3, IGF-1R, and GPER. Additionally, pharmacokinetic and toxicity predictions suggested favorable drug-like properties with minimal safety concerns. Thus, these findings support its potential as a promising plant-derived therapeutic candidate for breast cancer. Full article

Propolis, a resinous substance biosynthesized by honeybees from plant exudates and beeswax, has been valued for centuries in traditional medicine and is now increasingly recognized as a promising natural bioactive compound for functional food applications. Its complex phytochemical profile, mainly comprising flavonoids, phenolic acids, and terpenoids, confers potent antioxidant, antimicrobial, and anti-inflammatory properties that position it as a compelling candidate for use as a natural food preservative and bioactive additive. Despite this considerable potential, the widespread incorporation of propolis into food systems remains largely constrained by two main physicochemical limitations: its intense characteristic aroma, attributable to volatile terpenes and phenolic esters, which adversely affects sensory acceptance, and its inherent hydrophobicity, which prevents uniform dispersion in aqueous food matrices. This review critically examines three major technological strategies developed to overcome these barriers: (i) microencapsulation employing biopolymer wall materials, including alginate, chitosan, whey protein, and arabic gum, to mask organoleptic properties and enable controlled release; (ii) nanoemulsification to enhance water dispersibility and improve oral bioavailability; and (iii) the formulation of water-soluble propolis extracts through polyethylene glycol-based solvents or cyclodextrin complexation. In addition, this review provides a comprehensive assessment of the global chemical diversity of propolis and its bioactive properties as they relate to food preservation efficacy. Notwithstanding recent technological advances, critical research gaps persist regarding optimal effective concentrations, validated delivery systems, and scalable formulation strategies necessary for commercial food-grade applications. Addressing these gaps is essential for propolis to fulfill its considerable potential as a safe, widely accepted, and commercially viable natural food additive in next-generation functional food systems. Full article

Conventional depletion development and waterflooding are often ineffective in tight oil reservoirs because of their ultra-low permeability, complex fracture–matrix architecture, and limited fluid mobility. Although inter-fracture CO₂ flooding has demonstrated considerable potential for enhanced oil recovery (EOR), the coupled effects of key operational parameters on reservoir pressure evolution, fracture–matrix mass transfer, and oil mobilization remain inadequately understood. In this study, a multi-component compositional simulation model, constrained by detailed geological characterization and calibrated through production history matching of the Yuan 284 block in the Changqing Oilfield, was developed to systematically evaluate the effects of CO₂ injection rate, injection–production time ratio, and shut-in duration on recovery performance and reservoir response. The results show that increasing the CO₂ injection rate from 1000 to 50,000 m³/d improves the recovery factor from 40.49% to 49.90%; however, the incremental recovery gain decreases markedly beyond 30,000 m³/d, which is aggravated by enhanced gas channeling through high-conductivity fracture pathways. Analysis of the injection–production time ratio indicates that an optimal ratio of 0.50 provides the best balance between reservoir energy replenishment and oil displacement efficiency, whereas excessively small ratios result in insufficient pressure support and reduced recovery. In contrast, extending the shut-in duration consistently lowers recovery performance by weakening fracture–matrix mass transfer and promoting pressure dissipation, demonstrating that immediate production following injection is more effective than prolonged soaking under the investigated conditions. The optimized operating scheme yields a recovery factor of 48.87%, substantially exceeding the representative waterflooding recovery level of 35.20%. These findings clarify the mechanisms controlling pressure maintenance, CO₂ utilization efficiency, and volumetric sweep during inter-fracture asynchronous CO₂ flooding, and provide both theoretical insights and practical guidance for the efficient development of ultra-low-permeability fractured tight oil reservoirs. Full article

The application of artificial intelligence (AI) resources and robotics tools in education is considered vital for interdisciplinary fields to enhance the quality of the teaching and learning process. It also helps transform assessment techniques and revolutionize the whole pedagogical setting of science teacher education, in particular, AI and robotics integration in the teaching of Science, Technology, Engineering and Mathematics (STEM) subjects’ courses at the primary level. In this study, a scoping review was conducted involving seventeen peer-reviewed research papers published from 2021 to 2025. Efforts are being made to find the current perceptions and practices of preservice teachers (PSTs) at the primary level (Years 1–6; ages 6–12 in the Australian context) regarding the use of AI and robotics resources, for example, generative artificial intelligence (GenAI), foundational robotics and AI-driven robotics in teaching STEM subjects. Findings indicate that there was a significant gap in primary PSTs’ perspectives regarding their pedagogical practices to integrate STEM. As such, this influences future teachers’ knowledge, understanding, AI acceptance, and attitude toward the integration of smart AI and robotics resources in STEM classrooms. Policymakers and teachers’ education providers should align advanced technological AI resources and robotics applications with STEM curriculum guidelines and preservice teachers’ professional training programs within primary school education. Full article

To evaluate the ameliorative effects of different green manure crops on continuously cropped protected pepper soil and to identify suitable green manure species for plateau-protected cultivation systems, a one-factor randomized complete block design was conducted with five treatments: common vetch (L1), pea (L2), hairy vetch (L3), radish (L4), and a control without green manure (CK). Soil physicochemical properties, enzyme activities, and microbial community composition were determined at the full-bloom stage before green manure incorporation. Compared with CK, L1 reduced soil pH from 8.63 to 8.34 and decreased total salt content by 45.5%, increased alkali-hydrolyzable nitrogen by 40.93%, and significantly enhanced catalase activity. L3 increased available phosphorus by 23.72% and urease and sucrase activities by 71.32% and 56.31%, respectively, while significantly affecting fungal β-diversity and community composition. Community composition analysis showed that L3 increased the relative abundances of the bacterial genus Rhizobium and the fungal genus Rhizophagus, while reducing the relative abundance of Ascomycota and several potentially pathogen-associated fungal taxa. Redundancy analysis and Mantel tests indicated that bacterial community composition was mainly associated with soil total salt content, alkaline phosphatase, and available phosphorus, whereas fungal community composition was more closely related to urease and alkaline phosphatase. Random forest analysis and partial least squares path modeling further suggested that sucrase, urease, and catalase were important factors closely associated with changes in the soil quality index (SQI). Overall, common vetch performed better in reducing soil salinity, increasing alkali-hydrolyzable nitrogen, and improving the soil quality index and may therefore be considered a suitable green manure species for improving continuously cropped protected pepper soil on the Qinghai Plateau. Hairy vetch showed advantages in increasing available phosphorus and regulating fungal community composition, indicating its potential suitability for protected soils with limited phosphorus availability. Full article