Search Results (44,174)

The development of biohybrid micro-robots represents a groundbreaking advancement in targeted drug delivery for cancer therapy, offering unprecedented precision and reduced systemic toxicity. These microscale robots integrate synthetic materials with biological components such as bacteria, algae, red blood cells, or spermatozoa, capitalizing on the inherent motility, biocompatibility, and targeting capabilities of living organisms. This hybridization enables active navigation through complex biological environments, overcoming physiological barriers such as the blood–brain and endothelial junctions that impede traditional nanoparticle-based systems. In this study, we propose a multi-functional biohybrid micro-robotic platform composed of magnetically actuated synthetic chassis coated with doxorubicin-loaded lipid vesicles and tethered to Magnetospirillum magneticum for propulsion and tumor-homing capabilities. The results underscore the promise of biohybrid micro-robots as intelligent, minimally invasive agents for next-generation oncological therapies, capable of delivering chemotherapeutics with enhanced spatial and temporal accuracy. Future work will focus on clinical translation pathways, biosafety evaluations, and scalability of production under Good Manufacturing Practice (GMP) standards. Full article

This Perspective sets out to raise awareness about the chemical and photophysical properties of an assortment of blue colorants; it is generally regarded that blue is the most popular color worldwide and is recognized for its serenity and calming effect. In fact, blue colorants have a long and rich history, perhaps starting with Egyptian Blue, and have found colossal usage in the dyeing of uniforms and popular clothing. Other blue colorants have made major contributions to our understanding of the fields of molecular spectroscopy and photophysics and continue to underpin contemporary opto-electronic devices. This is in addition to their socio-cultural, economic, and ecological benefits to society. Originally, blue colorants were extracted from minerals by tedious and ineffectual grinding to give a product carrying an exorbitant price. Later, these materials were supplemented by synthetic analogues, such as copper phthalocyanine, more affordable to the general public. It is stressed that the journal Colorants would welcome submissions that describe the chemistry and/or spectroscopy of other archetypal colorants. Full article

Rapid industrialization has generated large volumes of acidic wastewater that, without adequate treatment, pose serious environmental and public health risks. Traditional remediation processes, such as chemical neutralization, ion-exchange, and membrane filtration, are effective but costly, energy-intensive, and generate toxic secondary waste. In contrast, acidophilic microalgae offer a sustainable, cost-effective, and eco-friendly alternative. Algae rely on their cellular structure and metabolism to adsorb, absorb, bioaccumulate, and transform toxic metals while simultaneously neutralizing wastewater with minimal secondary waste production. Although acidophilic algae tolerate highly toxic and low pH conditions, their growth rate and biomass productivity, key drivers of algae-based bioremediation, are often compromised under such conditions. Thus, identifying robust species and evolving strains to thrive in these wastewaters without compromising productivity will facilitate adoption of algae-based bioremediation on a large scale. Integrating algal wastewater remediation with biofuel and biofertilizer production can contribute to the circular economy. In this review, we synthesize mechanisms employed by acidophilic algal strains when exposed to acidic and metal-enriched environments to remediate wastewater. We highlight recent studies applying these strains to acidic wastewater remediation and biogas upgrading and discuss current biotechnological tools aimed at enhancing strain performance for future use in commercial systems. Full article

Against the backdrop of the carbon peaking and neutrality (“dual-carbon”) goals and evolving new-type power system dispatch, the share of pumped-storage hydropower (PSH) in power systems continues to increase, imposing stricter requirements on units for higher cycling frequency, greater operational flexibility, and rapid, stable startup and shutdown. Focusing on the entire hot-standby-to-generation transition of a PSH plant, a full-flow-path three-dimensional transient numerical model encompassing kilometer-scale headrace/tailrace systems, meter-scale runner and casing passages, and millimeter-scale inter-component clearances is developed. Three-dimensional unsteady computational fluid dynamics are determined, while the surge tank free surface and gaseous phase are captured using a volume-of-fluid (VOF) two-phase formula. Grid independence is demonstrated, and time-resolved validation is performed against the experimental model–test operating data. Internal instability structures are diagnosed via pressure fluctuation spectral analysis and characteristic mode identification, complemented by entropy production analysis to quantify dissipative losses. The results indicate that hydraulic instabilities concentrate in the acceleration phase at small guide vane openings, where misalignment between inflow incidence and blade setting induces separation and vortical structures. Concurrently, an intensified adverse pressure gradient in the draft tube generates an axial recirculation core and a vortex rope, driving upstream propagation of low-frequency pressure pulsations. These findings deepen our mechanistic understanding of hydraulic transients during the hot-standby-to-generation transition of PSH units and provide a theoretical basis for improving transitional stability and optimizing control strategies. Full article

The rapid increase in global population and industrial activities has intensified the discharge of toxic organic pollutants—including antibiotics, dyes, phenolic compounds, and pesticides—into the environment, posing critical threats to both ecosystems and human health. Conventional treatment technologies remain largely inadequate for their complete removal, particularly for pollutants with complex structures and high persistence. Among advanced approaches, photocatalytic systems have emerged as a sustainable and environmentally friendly technology, capable of mineralizing organic pollutants into harmless end products. However, their large-scale application is hindered by inherent limitations such as restricted visible-light activity, low quantum efficiency, and rapid recombination of charge carriers. This mini-review critically examines recent advances aimed at overcoming these bottlenecks, including band gap engineering, metal and non-metal doping, and the incorporation of carbon-based nanomaterials (e.g., CNTs, GO, CQDs). Special emphasis is placed on strategies that enhance photocatalytic activity under visible light, as well as the emerging potential of waste-derived carbon-based photocatalysts for sustainable applications. Finally, key research gaps—such as scalability, long-term stability, and techno-economic feasibility—are discussed to provide future perspectives on the rational design of next-generation photocatalysts. Full article

Set in the vocational education and training sector in England, this article draws attention to how top-down, centre–periphery approaches to curriculum design and development in vocational education fail for at least three reasons. First, they misconstrue the nature of knowledge. Second, they lead to perfunctory and fragmented approaches to curriculum design, coupled with mechanistic measures of quality and achievement, which often require little more than “one-off” and superficially assessed demonstrations of performance. Finally, they underplay the role and importance of the teacher as researcher and artist in putting the cultural resources of society to work in creative curriculum design and pedagogy. Teacher artistry is pivotal in animating and heightening the vitality of vocational curricula. It is through this artistry that teachers make theories, ideas and concepts in vocational subjects and disciplines accessible and meaningful to all learners in coherent ways in the contexts of their learning and their lives. The consequences of the epistemic faux pas underpinning centre-to-periphery models of curriculum design and development are highlighted in this article in vocational tutors’ accounts of experiences of problems and issues in curriculum design, development and assessment encountered in their practice. Participants in the research teach in a variety of vocational education settings, including Apprenticeships and Higher-Level Technical Education; English Language at General Certificate of Secondary Education (GCSE) level; Health and Social Care; Information and Communications Technology; Construction (Plumbing); Digital Production, Design and Development and High-Tech Precision Engineering. Data are analysed and reported through systematic, thematic analysis This article draws upon qualitative data derived from a study funded by the Education and Training Foundation (ETF) in England over a two-year period from 2021 to 2023. The research population consists of a group of eight practitioner–researchers working in three colleges of Further Education (FE) and one Industry Training Centre (ITC) in England. All of the teachers of vocational education reported here volunteered to participate in the study. Research methods include semi-structured interviews, analysis of critical incidents and case studies produced by practitioner–researchers from across the FE and Skills sector in England. Full article

MicroRNAs, pivotal regulators of gene expression and physiology, serve as reliable biomarkers for early cancer diagnosis and therapy. As one of the earliest discovered miRNAs in the human genome, miRNA-21 provides critical information for early cancer diagnosis, drug therapy, and prognosis. In this work, we harness CRISPR as a bridge to integrate target-induced self-priming hairpin isothermal amplification (SIAM) with terminal transferase (TdT) polymerization labeling, constructing a facile, straightforward electrochemical biosensor for sensitive miRNA-21 detection. Unlike conventional single-strand template-based exponential amplification (EXPAR), the SIAM hairpin undergoes target triggered intramolecular conformational change, initiating extension and strand displacement reactions that suppress nonspecific dimer formation and lower background current. Notably, the assay requires only a single probe, enabling unidirectional signal amplification while nonspecific reactions caused by system complexity. The generated SIAM products activate the Cas12a/crRNA complex to trans-cleave PO₄³⁻ modified single-stranded DNAs (ssDNAs); the resulting 3′ hydroxyl ssDNAs are subsequently labeled by TdT, with the assistance of SA-HRP catalyzing hydrogen peroxide, achieving robust signal amplification. Under optimized conditions, the cathodic current exhibits a logarithmic relationship with miRNA concentrations from 20 fM to 5.0 × 10⁸ fM, with a detection limit of 9.2 fM. The biosensor successfully quantified miRNA-21 in commercial serum samples and biological lysates, demonstrating its potential for cancer diagnostics and therapy. Full article

The solvability conditions, symmetric solutions, and antisymmetric solutions of matrix equations $AX=B$ are important research topics in matrix theory. As a higher-order generalization of matrices, tensors have made the research on solving tensor equations a hot topic in recent years. This paper focuses on the representation, properties, and computational methods of tensor generalized inverses under the C-product, and systematically explores their applications in solving the tensor equation $\mathcal{A}{*}_c\mathcal{X}=\mathcal{B}$. Firstly, the definition, existence conditions, analytical expressions, and computational algorithms of tensor generalized inverses under the C-product are discussed. By applying tensor generalized inverses under the C-product, the solvability conditions of tensor equation $\mathcal{A}{*}_c\mathcal{X}=\mathcal{B}$$\mathcal{A}{*}_c$ are derived. The minimum norm solution method for consistent equation $AX=B$ and the minimal norm least squares solution inconsistent equation $\mathcal{A}{*}_c\mathcal{X}=\mathcal{B}$ are presented, respectively. Finally, numerical experiments were provided to verify the correctness of the theoretical analysis and algorithm implementation through numerical experiments, demonstrating the effectiveness of solving tensor equations under the C-product. Full article

Pulmonary hypertension (PH) is a progressive and life-threatening disorder characterized by elevated pulmonary arterial pressure, leading to right ventricular remodeling and significant mortality. Pulmonary arterial remodeling, a critical pathological feature of PH, refers to structural alterations in the pulmonary vasculature driven by various pathogenic factors. Targeting this remodeling process has emerged as a promising strategy for treating and potentially curing the disease. In recent years, growing interest has been directed toward exploring natural products as anti-PH agents. Among them, flavonoids have demonstrated potent efficacy in the cardiopulmonary system. As a prominent class of natural small-molecule compounds, flavonoids exhibit broad biological activities, such as antioxidant, anti-inflammatory, and anti-proliferative properties. They have shown the ability to inhibit remodeling and restore vascular function across various vessel types, including pulmonary arteries. This review summarizes the effects of flavonoids on PH, with emphasis on their inhibition of pulmonary arterial remodeling. We also discuss the therapeutic potential of flavonoids in PH and discuss their underlying mechanisms of action. These insights may guide the development of next-generation PH therapeutics, either through the utilization of flavonoid-based structures or the preparation of compound formulations containing flavonoids. Full article

Investors use information about companies’ social and environmental performance to make investment decisions, a strategy known as Environmental, Social, and Governance (ESG) investment analysis. ESG screening may offer a mechanism to incentivize corporations to improve their health impact. However, there has been limited investigation of the extent to which ESG investment frameworks capture corporate health impacts in major industries. In this study, we sought to characterize the extent to which ESG frameworks address the health-impacting activities of the food and beverage (F&B) industry. To do this, we conducted a deductive framework analysis during the period of September 2023 to March 2024. Specifically, we identified gaps in existing ESG frameworks by comparing the content of five ESG reporting standards and rating systems to the HEALTH-CORP-FB typology, an evidence-based typology that describes the health-impacting activities of the F&B industry across seven domains (Governance Practices, Political Practices, Preference and Perception Shaping Practices, Economic Practices, Employment Practices, Products and Services, and Environmental Practices). To further assess how ESG frameworks account for the health-impacting activities of the F&B industry, we classified health-focused ESG fields in the packaged foods subindustry by two attributes: relevance to the assigned HEALTH-CORP-FB activity (low, medium, high) and type of business operations addressed (e.g., process, performance). Results indicate that, on average, the ESG fields (n = 1348) covered 39% of the 89 HEALTH-CORP-FB activities (range across frameworks: 27–48%). Higher proportions of activities in the Governance, Environmental, Employment, and Economic Practices domains (range across domains: 43–87%) were represented than activities in the Products and Services, Preference and Perception-Shaping Practices, and Political Practices domains (17–36%). Fields assigned to the latter domains were also less likely to be deemed highly relevant and to measure corporate performance. We conclude that the ESG frameworks included in this study capture some of the activities of the F&B industry that affect population health and health equity; however, critical gaps remain. We discuss how integrating key health-focused ESG indicators (e.g., revenue generation from ultra-processed foods) into existing frameworks could enable investors, public health organizations, civil society, and shareholder advocates to strengthen the accountability of the F&B sector with respect to health. Full article

The growing global demand for food and energy requires land-use strategies that support agricultural production and renewable energy generation. Agrivoltaic (APV) systems allow farmland to be used for both agriculture and solar power generation. The aim of this study is to critically synthesize the interactions between the key dimensions of APV implementation—technical, agronomic, legal, and economic—in order to create a multidimensional framework for designing an APV optimization model. The analysis covers APV system topologies, appropriate types of photovoltaic modules, installation geometry, shading conditions, and micro-environmental impacts. The paper categorizes quantitative indicators and critical thresholds that define trade-offs between energy production and crop yields, including a discussion of shade-tolerant crops (such as lettuce, clover, grapevines, and hops) that are most compatible with APV. Quantitative aspects were integrated in detail through a review of mathematical approaches used to predict yields (including exponential-linear, logistic, Gompertz, and GENECROP models). These models are key to quantitatively assessing the impact of photovoltaic modules on the light balance, thus enabling the simultaneous estimation of energy efficiency and yields. Technical solutions that enhance synthesis, such as dynamic tracking systems, which can increase energy production by up to 25–30% while optimizing light availability for crops, are also discussed. Additionally, the study examines regional legal frameworks and the economic factors influencing APV deployment, highlighting key challenges such as land use classification, grid connection limitations, investment costs and the absence of harmonised APV policies in many countries. It has been shown that APV systems can increase water retention, mitigate wind erosion, strengthen crop resilience to extreme weather conditions, and reduce the levelized cost of electricity (LCOE) compared to small rooftop PV systems. A key contribution of the work is the creation of a coherent analytical design framework that integrates technical, agronomic, legal and economic requirements as the most important input parameters for the APV system optimization model. This indicates that wider implementation of APV requires clear regulatory definitions, standardized design criteria, and dedicated support mechanisms. Full article

The increasing threat of Glacial Lake Outburst Floods (GLOFs), intensified by climate change, underscores the urgency for developing advanced early warning systems. The near-annual, cyclical outbursts of Lake Merzbacher in the Tien Shan mountains present a severe downstream threat, yet its remote location and lack of instrumentation pose a significant challenge to traditional monitoring. To bridge this gap, we develop and validate a dynamic risk assessment framework driven entirely by remote sensing data. Methodologically, the framework introduces an innovative Ice-Water Composite Index (IWCI) to resolve the challenge of lake area extraction under mixed ice-water conditions. This is coupled with a high-fidelity 5 m resolution Digital Elevation Model (DEM) of the lake basin, autonomously generated from GF-7 Dual-Line Camera (DLC) imagery, which enables accurate daily volume retrieval. Through systematic feature engineering, nine key hydro-thermal drivers are quantified from MODIS and other products to train a Random Forest (RF) machine learning model, establishing the non-linear relationship between catchment processes and lake volume. The model demonstrates robust predictive performance on an independent validation set (2023–2024) (R² = 0.80, RMSE = 5.15 × 10⁶ m³), accurately captures the complete lake-filling cycle from initiation to near-peak stage. Furthermore, feature importance analysis quantitatively confirms that Positive Accumulated Temperature (PAT) is the dominant physical mechanism governing the lake’s storage dynamics. This end-to-end framework offers a transferable paradigm for GLOF hazard management, enabling a critical shift from static, regional assessments to dynamic, site-specific early warning in data-scarce alpine regions. Full article

English is the first foreign language most Taiwanese have encountered, yet few have achieved proficient speaking skills. This paper presents a generative AI-based English speaking training system designed to enhance oral proficiency through interactive AI agents. The system employs ChatGPT version 5.2 to generate diverse and tailored conversational scenarios, enabling learners to practice in contextually relevant situations. Spoken responses are captured via speech recognition and analyzed by a large language model, which provides intelligent scoring and personalized feedback to guide improvement. Learners can automatically generate scenario-based scripts according to their learning needs. The D-ID AI system then produces a virtual character of the AI agent, whose lip movements are synchronized with the conversation, thereby creating realistic video interactions. Learning with an AI agent, the system maintains controlled emotional expression, reduces communication anxiety, and helps learners adapt to non-native interaction, fostering more natural and confident speech production. Accordingly, the proposed system supports compelling, immersive, and personalized language learning. The experimental results indicate that repeated practice with the proposed system substantially improves English speaking proficiency. Full article

Global climate change results in increasing challenges to the structural security of China’s food system, while pronounced spatial heterogeneities in provincial production and consumption intensify the risk of supply-demand imbalance. This study examines the resilience of China’s inter-provincial staple food flow network from a systemic perspective and identifies its key drivers. Inter-provincial food flows are first inferred using a cost-minimization optimization model. Network resilience is then evaluated by integrating complex network analysis with ecological network resilience theory. Finally, econometric analysis is applied to quantify the relative contributions of multiple structural factors to resilience dynamics. The results reveal an overall decline in the resilience of aggregated staple food, alongside persistently low resilience in soybeans network, indicating heightened structural vulnerability. Substantial heterogeneity is observed across staples in both resilience levels and underlying mechanisms. In general, greater connectivity and diversity of flow paths enhance system resilience, although this effect is markedly weaker for soybeans due to concentrated and import-dependent supply structures. By explicitly linking flow, network structure, and resilience, this study provides system-level insights into the functioning of inter-provincial food flow networks. The proposed analytical framework offers a transferable tool for assessing interregional food flow resilience and supports evidence-based strategies for validating system robustness under uncertainties. Full article

Life Cycle Assessment (LCA) is a fundamental methodology for evaluating environmental impacts across the life cycle of products, processes, and services. However, selecting appropriate LCA software is a complex task due to the wide variety of tools, each with different functionalities, sectoral focuses, and technical requirements. This study conducts a systematic literature review, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, to map the main characteristics, strengths, and limitations of LCA tools. The review includes 41 studies published between 2017 and 2025, identifying and categorizing 24 different tools. Technical and operational features were analyzed, such as modelling capacity, database compatibility, usability, integration capabilities, costs, and user requirements. Among the tools, five stood out for their frequent application: SimaPro, GaBi, OpenLCA, Umberto, and Athena. SimaPro is recognized for flexibility and robustness; GaBi for its industrial applications and Environmental Product Declaration (EPD) support; OpenLCA for being open-source and accessible; Umberto for energy and process modelling; and Athena for integration with Building Information Modelling (BIM) in construction. Despite their advantages, all tools presented specific limitations, including learning curve challenges and limited scope. The results show that no single tool fits all scenarios. In addition to the synthesis of these characteristics, this study also emphasizes the general features of the identified software, the challenges in making a well-supported selection decision, and proposes a decision flowchart designed to guide users through key selection criteria. This visual tool aims to support a more transparent, systematic, and context-oriented choice of LCA software, aligning capabilities with project-specific needs. Tool selection should align with research objectives, available expertise, and context. This review offers practical guidance for enhancing LCA applications in sustainability science. Full article