Search Results (2,116)

Electronic waste (e-waste) is among the fastest-growing global waste streams, with 62 million tonnes generated in 2022 and only 22.3% formally recycled, while generation is projected to reach 82 million tonnes by 2030. Fragmented record-keeping, weak chain-of-custody controls, and limited transparency enable illegal dumping, fraudulent recycling claims, and loss of recoverable materials. This paper presents a narrative literature review of blockchain and distributed ledger technologies applied to electronics and e-waste management. Following a structured search and relevance screening of major scientific databases, publisher platforms and grey literature (last search was run on 15 July 2026), 110 sources published between 2017 and 2026 were thematically synthesized across four domains: technological developments, sustainability and circular-economy implications, traceability and compliance mechanisms, and e-waste management applications. Blockchain delivers value primarily through an auditable chain-of-custody built on three pillars: standardized item and batch identities, standardized lifecycle event schemas, and licensed-actor attestations supported by off-chain evidence anchored on-chain. Recurring design patterns include permissioned consortium networks, hybrid storage, and role-based access control. Persistent barriers include data-input integrity, scalability, governance, and cost. Blockchain immutability protects stored records but cannot correct falsified inputs, making trusted data capture and governance the decisive factors for reliability. Adoption should be evaluated against measurable indicators, such as traceability completeness, audit-time reduction, fraud rates, and verified material recovery, rather than assumed benefits. Full article

Banana bunchy top virus (BBTV) is a devastating pathogen threatening global banana production. The plant ubiquitin–proteasome system (UPS) governs immune signaling and is frequently subverted by invading viruses, yet the molecular mechanism through which BBTV interferes with host UPS remains unclear. Here, we show that BBTV nuclear shuttle protein (NSP) serves as the core viral effector to disrupt banana ubiquitination homeostasis. RT-qPCR time-series assays confirmed that BBTV infection dynamically remodels the transcription of eight phylogenetically divergent RING-type E3 ubiquitin ligases: four subfamily I E3-SIS3 paralogs and E3-HIP1 are significantly upregulated at 14 dpi and 21 dpi, while E3-BOI and E3-RHA1B are suppressed at 21 dpi. Transient expression screening of all six BBTV-encoded proteins verified that only NSP reproduces the UPS perturbation signature triggered by viral infection. Cross-species sequence alignment identified an evolutionarily conserved FNGSF motif within NSP orthologs of all Nanoviridae members. Alanine substitution mutagenesis (NSP^AAAAA) completely abolished NSP’s capacity to alter E3 ligase transcription. Western blot assays further validated that wild-type NSP induces massive accumulation of ubiquitinated host proteins, whereas the FNGSF-deficient mutant does not disrupt cellular ubiquitination. Phylogenetic analysis revealed that NSP-targeted E3 ligases share low overall sequence similarity but retain conserved catalytic RING domains, indicating that NSP exerts broad-spectrum regulatory effects on host UPS via the FNGSF motif. Collectively, this study reveals a novel pathogenic strategy whereby BBTV NSP recruits diverse host RING E3 ligases via its conserved FNGSF motif to dysregulate plant ubiquitination and elicit plant pathogenicity. Our findings provide two promising targets—the NSP FNGSF motif and defense-associated E3-SIS3 ligases—for developing antiviral agents and breeding BBTV-resistant banana germplasm. Full article

The quantitative measurement of TCC at tourist cities involves considerable methodological complexities. Conventional evaluation methods based on fixed numerical criteria are frequently insufficient since tourism systems are characterized by unclear information, gradual shifts, and subjective experiences. To address these methodological constraints, this study develops and implements a hybrid FAHP-weighted Fuzzy Comprehensive Evaluation (FCE) framework to estimate TCC. The framework incorporates four critical indicators, visitor density, waste generation, infrastructure load, visitor perception, reflecting the physical, environmental, infrastructural, and socio-cultural dimensions of tourism development. These indicators are assessed using a structured analytical procedure integrating fuzzification, expert-derived weighting through the fuzzy analytic hierarchy process, fuzzy comprehensive evaluation, and centroid defuzzification. This study presents a hybrid SEM–FAHP–FCE framework, which is a multi-method integrated decision model that combines SEM (structural equation modeling) for visitor perception and behavioral drivers, FAHP (fuzzy analytic hierarchy process) for expert-based indicator weighting and FCE (fuzzy comprehensive evaluation) for final carrying capacity assessment under uncertainty. This combined methodology offers a more adaptive and empirically grounded assessment of TCC by synthesizing quantitative conditions with qualitative stakeholder perceptions within a unified evaluative model. The framework is validated through empirical application to Vrindavan, Uttar Pradesh, one of India’s most visited destinations, across eight study sites and two seasonal conditions (normal and festival-peak). Primary data collection comprises 300 visitor count observation units and field data, i.e., visitor count, waste generation and infrastructure details. The defuzzified FAHP–FCE results for each site (W = 3.94, 3.33, 2.44, 1.95, 3.66, 1.87, 1.86 and 2.71) reveal that major pilgrimage nodes exhibit scores approaching the upper bound of the evaluation scale, indicating that tourism pressure has significantly exceeded carrying capacity during peak periods. This study establishes proof-of-concept for the FAHP–FCE framework as a standardized, replicable instrument for evidence-based TCC governance at tourism cities. Full article

The rapid growth of rural e-commerce is reshaping rural development, yet its implications for territorial sustainability remain unclear. Using panel data from 1503 Chinese counties from 2014 to 2022, the effects of Taobao Village development and the mechanism of territorial sustainability are examined through causal, spatial, and mechanism analyses. The results show the following: (1) Taobao Village development significantly improves territorial sustainability, with stronger effects observed in central and northeastern China, while the impacts vary considerably across regions due to differences in economic foundations, digital infrastructure, and land-use conditions. (2) Spatial analysis reveals that the sustainability-enhancing effects of Taobao Villages are mainly localized, with no significant spillover effects to neighboring counties, indicating the constraints of existing administrative and spatial governance systems. (3) The ecological land-use change induced by Taobao Village development is characterized by quantity reduction with potential quality upgrading. The development of Taobao Village has reduced the ecological land area, but it does not mean a decline in ecological functions. The converted land may be composed of low-quality ecological plots, and the fiscal benefits driven by e-commerce and China’s land use compensation policy may maintain or enhance the overall ecological function. These findings highlight the importance of integrating digital rural development with ecological sustainability and territorial spatial governance. The study provides policy implications for promoting resilient and sustainable rural transformation through differentiated land-use strategies. Full article

In-storage food loss is a persistent yet under-addressed source of economic, environmental, and social waste in small and medium-sized enterprise (SME) cold chains, where continuous monitoring and lean workflows are typically absent. This study asks how such loss can be reduced under SME constraints and what benefits an intervention designed for that setting could yield. Following a design science approach in a Thai chilled warehouse case, it develops an integrated intervention coupling an Internet of Things (IoT) early-warning platform—ESP-32 and DHT22 sensing with commodity-specific alerting through the LINE Messaging API—with value stream mapping (VSM) of the depositing and withdrawing workflows. Monitoring showed that 7.4% of quality-controlled readings exceeded the 6 °C control threshold. Value stream analysis established that elapsed time is governed by information latency rather than physical work and that produce spends 290 min per handling cycle outside controlled conditions. The redesigned workflows project lead-time reductions of 47.5% and 69.4% and remove 125 min of that exposure. An ex ante Triple Bottom Line assessment estimates approximately 19,700 kg of avoided produce loss, 6500 kg CO₂e, and 590,000 THB retained annually. This study contributes a complementarity account of digital monitoring and process improvement, advancing SDG Target 12.3. Full article

India is the most populous country in the world, with a rising urban population and witnessing a surge in noncommunicable diseases such as cancer that impose significant pressure on healthcare professionals, hospitals, and city planners. Over the last decade, India has pursued a vision to transform urban areas into smart cities and roll out digital infrastructure. Rapid urbanization coupled with an ageing population has accelerated demand for precision cancer care (PCC) solutions using advanced technologies such as digital twins (DT), leveraging the developing digital infrastructure in urban India. The fast evolution of e-health technologies and digital infrastructure outstrips healthcare professional readiness, creating challenges for DT adoption for PCC. Past studies on DT adoption primarily focused on organizational adoption and technical implementation challenges. This study addresses this research gap by leveraging the Unified Theory of Acceptance and Use of Technology (UTAUT) framework to investigate the factors that influence the adoption intention of DT for PCC in urban India. The article reports actionable insights and implications for researchers, healthcare professionals, top management of hospitals, smart city planners, government agencies, and urban policymakers. The study will assist stakeholders such as cancer care organizations, technology service providers, and city planners in planning, designing, and implementing DT for PCC. Full article

Artificial intelligence has transformed dynamic pricing by enabling firms to forecast demand more accurately, respond to market uncertainty, and optimize prices in real time. Existing reviews remain fragmented, typically focusing on a single industry or on isolated methodological streams like reinforcement learning or time-series forecasting. To address this gap, this study provides a comprehensive, cross-industry synthesis of AI-based Dynamic Pricing through a systematic bibliometric analysis of 1301 Scopus-indexed publications from January 2005 to August 2025. E-commerce and digital platforms serve as the study’s central analytical lens because they frequently combine real-time transactional data, rapid price adjustment, customer-level behavioral information, platform competition, and algorithmic repricing. The analysis also extends to other digitally mediated pricing environments, including energy, mobility, electric-vehicle charging, hospitality, transportation, and retail, allowing the study to examine how methods, adoption patterns, and governance concerns vary across sectors. Using VOSviewer and CiteSpace, the study maps the intellectual structure of the field and identifies eight major research clusters. The findings reveal a clear methodological shift from rule-based and econometric approaches toward deep learning, multi-agent reinforcement learning, and simulation-driven decision systems. They also show that data-intensive and platform-mediated sectors are becoming increasingly prominent in the development and application of advanced AI-based pricing methods, while established revenue-management domains such as airlines and hospitality remain important foundations of the field. Building on these patterns, the study outlines future research opportunities centered on interpretable and uncertainty-aware pricing models, ethical and fair pricing mechanisms, and cross-industry transfer of methods and regulatory practices. This synthesis provides a structured foundation for advancing theory, methodology, and practice in AI-based DP. Full article

While low-impact development and retention strategies are widely studied in urban and agricultural contexts, a distinct knowledge gap remains regarding the quantitative evaluation of dispersed, natural microretention structures in small, ungauged, mountainous forested catchments under complex topographic conditions. To address this limitation, this study provides a novel quantitative assessment of how natural bioretention interventions—specifically arcuate deadwood log barriers, cascading reservoir systems, and strategic afforestation—influence runoff reduction and substrate infiltration dynamics. Focusing on the 4.57 km² basin of the Stankowice Stream in southwestern Poland, the research integrates field geodetic and hydrological measurements with Iszkowski’s empirical flow formulas and high-resolution digital elevation modeling (SCALGO platform). Delineation of 10 key subcatchments revealed that surface runoff potential is heavily concentrated within specific flow pathways rather than determined solely by subbasin area. In unit No. 9, deploying an arcuate arrangement of 19 deadwood logs achieved an 11% reduction in surface runoff (retaining 8662.50 m³), whereas coupling these log structures with a downstream cascading two-dam system significantly enhanced retention performance by establishing 79,065.68 m³ of depression storage and driving 264,066.16 m³ of subsurface infiltration. Furthermore, multi-scenario land use modeling demonstrated that transforming land cover to forest reduced surface runoff by over 70% in topographically steep subcatchments (e.g., unit No. 7). These findings demonstrate that effective flood mitigation in headwater catchments requires a systemic, targeted hybrid strategy combining decentralized bioretention with localized storage nodes, offering a transferable framework for sustainable regional water governance. Full article

Carbon dioxide water-alternating-gas (CO₂-WAG) flooding simultaneously enables carbon emission mitigation, improved oil displacement efficiency, and expanded gas sweep coverage. Nevertheless, the field performance of this technology remains significantly constrained by gravity override effects, especially in ultra-thick oil reservoirs. In this work, a synthetic heterogeneous dipping mechanistic reservoir model is constructed. Using a quantitative metric for gravity override index in WAG processes, the variation patterns of gravity override under various operational factors are systematically analyzed. Furthermore, the eXtreme Gradient Boosting (XGBoost) machine learning algorithm is employed to conduct feature importance analysis of the controlling factors, identifying parameters with the most substantial impacts. The results indicate that well spacing, oil production rate, WAG injection strategy, and WAG slug duration all exert pronounced effects on both gravity override index and oil recovery factor. Gravity override is confirmed as the dominant factor governing the production performance of WAG flooding in ultra-thick reservoirs. In addition, an optimal combination of operational parameters exists that counterbalances the adverse effects of gravitational and viscous forces, thereby maximizing gas sweep efficiency, delaying gas breakthrough, and enhancing oil recovery. This study provides valuable insights and technical guidance for gas channeling mitigation, vertical gas sweep improvement, and efficient development of analogous ultra-thick reservoirs. Full article

With the rapid development of artificial intelligence, AI-driven algorithmic goal setting has become an important mechanism of digital platform management. In the livestream e-commerce industry, platforms increasingly use algorithmic systems to assign tasks, monitor performance, and regulate streamers’ work. Although this intensive and dynamic form of algorithmic management can improve operational efficiency, it may also be associated with potential ethical risks. Drawing on Conservation of Resources Theory, Emotional Labor Theory, and Sociotechnical Systems Theory, this study examines whether AI-driven algorithmic goal setting is associated with streamers’ unethical selling behavior through emotional dissonance and whether AI transparency moderates this relationship. Using a three-wave time-lagged survey design, data were collected from 427 livestream e-commerce streamers in China. SPSS-based hierarchical regression analysis and bootstrapping were employed to test the proposed moderated mediation model. The results showed that AI-driven algorithmic goal setting was significantly and positively associated with streamers’ unethical selling behavior and that emotional dissonance partially mediated this relationship. Furthermore, the positive relationship between AI-driven algorithmic goal setting and emotional dissonance, as well as the corresponding indirect relationship with unethical selling behavior, was weaker at higher levels of AI transparency. These findings identify emotional dissonance as an important psychological mechanism linking algorithmic performance demands with unethical selling behavior and indicate the conditional buffering role of AI transparency. This study extends algorithmic management research to the livestream e-commerce context and provides practical implications for enhancing algorithmic transparency and reducing ethical risks in platform governance. Full article

This study evaluated potentially toxic element (PTEs) contamination (As, Cd, Co, Cr, Cu, Ni, Pb, and Zn) in soil and grapevine leaves across 36 sites in a historical vineyard near Iași, Romania, transitioning toward residential development. Soil samples were analyzed using energy-dispersive X-ray fluorescence (ED-XRF), while leaf tissues collected during the véraison stage (mid-August) underwent microwave-assisted acid digestion followed by inductively coupled plasma mass spectrometry (ICP-MS). Soil analyses revealed that average concentrations of Cr, Ni, and Pb exceeded national normal legal thresholds, while Cu and As surpassed alert permissible limits. Contamination factor ($CF$) and Geoaccumulation Index ($I_{geo}$) metrics confirmed significant anthropogenic Cu enrichment from historical viticultural treatments. Soil-to-leaf transfer factors ($TF$) approached or exceeded 1 for Cu and Zn, though grapevine was not identified as a hyperaccumulator. Spearman correlation modeling demonstrated a statistical decoupling between soil concentrations and foliar tissue levels for Cu ($r_s=-0.21$) and Zn ($r_s=0.075$), confirming that canopy accumulation is governed by historical agrochemical spraying and atmospheric deposition rather than root-driven uptake. Conversely, Pb ($r_s=0.43$) exhibited a moderate direct soil-to-leaf pathway. The potential ecological risk ($PER$) index indicated moderate-to-considerable cumulative risk, primarily driven by Cu ($E_{Cu}=68.64$) and Cd ($E_{Cd}=59.17$). Human health risk assessments established direct ingestion as the primary exposure pathway, with current non-carcinogenic hazards remaining within tolerable limits ($HI<1$). However, the proposed residential conversion increases exposure risks for vulnerable cohorts, underscoring the necessity of systematic soil screening and remediation prior to land redevelopment. Full article

Potassium (K⁺) is an essential mineral element for plant growth and development. Members of the HAK/KUP/KT (HAK) gene family serve pivotal roles in K⁺ uptake, translocation and homeostasis. Although numerous HAK genes have been extensively identified across diverse plant species, a comprehensive genomic and functional analysis of this family in sweet potato (Ipomoea batatas L.) remains lacking. In this study, 22 putative IbHAK genes were identified and classified into four distinct clades (I–IV). A systematic characterization was performed for each IbHAK gene, including protein physicochemical properties, chromosome distribution, gene structure, synteny, and promoter cis-elements. Notably, five IbHAK5 genes (IbHAK5A–IbHAK5E) clustered on the HAK gene tree with AtHAK5, OsHAK5, and ZmHAK5. This suggests that small-scale duplication events likely drove the expansion of HAK5 in sweet potato. Among them, IbHAK5A, a gene with broad expression across tissues and strong transcriptional induction under low-K⁺ (LK) stress, was cloned. The function was then characterized in a K transporter-deficient yeast mutant and an Arabidopsis hak5 mutant. Transcription factor IbPTL1 directly binds the IbHAK5A promoter, upregulates its expression, and integrates into the K⁺ signaling. In this work, we provide foundational insights into the underlying molecular mechanisms governing K⁺ acquisition in sweet potato. Full article

Sericin, a silk-derived protein recovered as a by-product of the textile industry, is a renewable biomacromolecule with considerable potential for sustainable material development. Chemical modification represents an effective strategy for its valorization. In this study, acetylation using acetyl chloride (AcCl) was selected as a model reaction to systematically investigate the reactivity of sericin in an N,N-dimethylacetamide/lithium chloride (DMA/LiCl) solvent system and to evaluate the influence of reaction parameters on both the extent of functionalization and protein secondary structure. A Design of Experiments (DoE) strategy, comprising an initial full factorial screening followed by Box–Behnken optimization, was employed to investigate the effects of AcCl equivalents, sericin concentration, and LiCl content. A quantitative FTIR workflow based on constrained Gaussian deconvolution was developed to derive functionalization index (FI) and β-sheet index (BI) from both peak areas and peak intensities, enabling the simultaneous evaluation of chemical modification and structural organization. The exploratory screening identified AcCl as the dominant factor governing sericin functionalization. During the optimization phase, the FI models described the general response trends, whereas the BI was successfully represented by robust quadratic models (R² = 0.977–0.978; adjusted R² = 0.936–0.938), revealing significant linear, interaction, and quadratic effects, with LiCl concentration and sericin concentration playing key roles in governing structural organization. The analytical workflow was verified by reproducibility assessment and independent validation experiments. Overall, this study proposes a quantitative DoE–FTIR framework for systematically investigating sericin functionalization and its associated structural evolution, providing support for future studies aimed at sericin industrial valorization. Full article

Chengde, China, is famous for its Qing Dynasty imperial gardens, which are a World Heritage Site. In recent years, it has received increasing attention from heritage research scholars. From a tourism perspective, tourists’ visits are important for supporting economic benefits, heritage conservation, and sustainable development. This study integrated the four dimensions of the 4E heritage communication framework—experience, exchange, everyplace, and evangelism—with heritage interpretation quality to develop a model to uncover cultural heritage visiting behavior. Based on the survey data of 887 Chinese tourists who have visited Chengde’s cultural heritage sites, structural equation modeling (SEM) was employed. The results showed that experience, exchange, everyplace, and evangelism, together with heritage interpretation quality, were all positively associated with cultural heritage visiting behavior. Perceived destination image and perceived conservation both significantly predicted cultural heritage visiting behavior and served as significant mediators in most of the proposed indirect relationships; however, the indirect path of evangelism through perceived destination image was not supported. Source credibility strengthened the relationships between the five antecedents and cultural heritage visiting behavior. Therefore, this article encourages the development of high-quality, comprehensive marketing strategies to attract more people to learn about World Cultural Heritage, while simultaneously improving guided tour services and their quality. It also emphasizes building a more positive cultural tourism image and conducting precise public relations to ensure that World Cultural Heritage receives support and attention from governments, educational institutions, and travel agencies. Full article

Background: Counterfeit governance in e-commerce platforms is a real-world problem characterized by strategic interdependence, information asymmetry and dynamic feedback among platforms, merchants and consumers. Linear or single-actor regulatory approaches are often insufficient to address such complexity, as platform regulation, merchant behaviour, consumer trust and online reputation mechanisms jointly shape the evolution of market trust. Methods: Guided by systems thinking, this study conceptualizes counterfeit governance as a socio-technical system and develops a tripartite evolutionary game model involving e-commerce platforms, merchants and consumers. The model delineates the system boundary around transaction-stage platform governance and incorporates key variables, including regulatory costs, fraudulent gains, honest transaction costs, subsidies, penalties, consumer transaction costs, online word-of-mouth influence and reputation losses. System dynamics simulation using Vensim PLE 10.5.2 is then employed to examine evolutionary trajectories, local stability, parameter sensitivity and threshold regions. Results: The results show that weak or static regulation may allow fraudulent strategies to persist or fluctuate, whereas stronger penalties and subsidies for honest transactions can reshape the payoff structure and promote merchant integrity. Transaction-related consumer incentives and enhanced online word-of-mouth mechanisms support consumer trust and stabilize the system toward trustworthy transactions. Conclusions: This study operationalizes systems thinking through system dynamics, while evolutionary game theory provides behavioural micro-foundations for stakeholder strategy adjustment in digital platform governance. Full article