Search Results (15,734)

The environmental effects of green finance policies involve complex systemic interactions across multiple levels, yet existing studies often adopt fragmented analytical approaches. Drawing on the multi-level perspective (MLP), this study conceptualizes the environmental impacts of Green Finance Reform and Innovation Pilot Zones (GFRIPZs) as a process of systemic green transformation involving interactions among landscape, regime, and niche levels. Using panel data of 287 prefecture-level and above cities in China from 2012 to 2022, this study applies a staggered difference-in-differences (DID) model to evaluate the environmental impacts of GFRIPZs. The results show that GFRIPZs significantly reduce both PM_2.5 concentrations and CO₂ emissions. Mechanism analyses based on multiple mediation models and GSEM reveal pollutant-specific differences in underlying channels. Green technological innovation (GTI) constitutes one observable pathway for PM_2.5, whereas the policy effect is more closely associated with energy structure adjustment for CO₂. Heterogeneity analysis further shows that PM_2.5 mitigation is stronger in colder cities, while CO₂ reduction is more pronounced in developed cities. These findings reveal pollutant-specific mechanisms of green finance and offer policy implications for developing countries seeking to promote systemic green transformation. Full article

Mucopolysaccharidosis (MPS) are a group of inherited lysosomal storage genetic disorders that affect the body’s ability to break down glycosaminoglycans (GAGs) due to the deficiency of required enzymes. This leads to depositions of these GAGs in various tissues and organs resulting in multi-systemic manifestations including pulmonary and sleep related issues. In recent years, there have been significant advancements in therapeutic options and supportive management which have led to the overall improvement in respiratory care, culminating in improved quality of life for MPS patients. Management of pulmonary and sleep disorders in mucopolysaccharidosis requires a multidisciplinary approach due to the multi-systemic affectation of the genetic disorders. Therapeutic options such as enzyme replacement therapy (ERT) and hematopoietic stem cell transplantation (HSCT) have yielded varying success in mitigating respiratory complications. Emerging treatments such as gene therapies have shown exciting and promising results thus far. Supportive therapies such as airway clearance, regular vaccination and use of positive airway pressure devices are also essential. Pre-operative airway and anesthesia planning is critical to mitigate peri-operative and post-operative complications. Early diagnosis, close monitoring and a patient focused individualized approach are essential for respiratory optimization and overall improvement in clinical outcomes. This review article aims to discuss these advancements in a comprehensive format, making it accessible to medical providers who care for this subset of patients. Full article

Educational information systems have evolved into highly interconnected digital landscapes that support learning management platforms, student information systems, institutional repositories, and online assessment environments. As these systems increasingly operate across cloud infrastructures and mobile devices, ensuring the confidentiality, integrity, and availability (CIA Triad) of educational data is critical for safeguarding institutional operations and maintaining trust in digital education services. This paper investigates how next-generation security protocols, such as adaptive multi-factor authentication and advanced access control and data protection mechanisms, can reinforce ISO/IEC 27001:2022 requirements within contemporary educational information systems. The analysis maps emerging protocol capabilities to relevant new ISO/IEC 27001:2022 control domains, illustrating how they mitigate threats associated with unauthorized access, data manipulation, and service disruption. The proposed framework is further supported by an implementation-oriented mapping and an illustrative operational architecture that demonstrates the feasibility of translating prioritized security determinants into practical mechanisms. The FAHP analysis identifies access control mechanisms, backup and recovery, and data validation as the three highest-weighted determinants, with aggregate weights of 0.061, 0.059, and 0.057, respectively. These determinants are translated into a determinant-driven Security Operationalization Matrix that connects ISO/IEC 27001:2022 control domains, CIA dimensions, and technology recommendations, and is complemented by implementation feasibility considerations tailored to the budgetary, infrastructural, and resource constraints characteristic of educational institutions. Based on the prioritization results and conceptual operationalization, the proposed integrative approach provides a structured and progressively adoptable foundation for CIA-oriented security governance in digital educational environments. Full article

This study examines the long- and short-run effects of sustainable development, economic growth, energy consumption, urbanization, investment and trade openness on Carbon Dioxide Emissions (CO₂) in the GCC countries utilizing the PMG-ARDL approach by including the data spanning from 2000 to 2022. In the short -run, the sustainable development index demonstrates a positive and substantial impact while it exhibits adverse long-run impact on CO₂ emission. The study also indicates a U-shaped correlation between economic growth and emissions, contrasting with the conventional Environmental Kuznets Curve (EKC) where economic growth at lower income levels often leads to a reduction in emissions; however, income increases beyond around USD 29,942 per capita correlate with higher emissions. Besides, energy use is identified as the primary factor influencing emissions, reflecting global patterns that indicate greater energy usage, particularly from fossil fuels directly boosts emissions. Moreover, the urbanization intensifies this problem, resulting in higher energy demand and greater emissions. Additionally, the study finds that gross capital formation and investments in infrastructure contribute to emissions in the short run, though these effects diminish over time. Our results are robust as it similar to the outcomes obtained from dynamic panel-data System GMM. The GCC policymakers must utilize the sustainable development framework to legally mandate national planning towards low-carbon paths while balancing for short-term transition costs with significant long-run emission reductions. This necessitates the implementation of market-oriented carbon pricing to address the post-threshold U-shaped emissions rebound, the systematic elimination of fossil fuel subsidies to promote renewable energy adoption, and the enforcement of sustainable development regulations to mitigate urbanization pressures. Full article

Fireworks have been used in China for more than a millennium, though they are an increasing part of celebration globally. Consumption of fireworks is on the rise despite increased regulation of their use. This review examines the key themes that are apparent in contemporary research: contamination of air, water and soil, in addition to waste debris, noise and light pollution, along with contemporary approaches to mitigate environmental impact. Research is, as expected, more frequent from countries with high fireworks use, so some rather small countries such as the Netherlands, Malta and Iceland are notably active. Concentrations of emitted gases (especially SO₂) and fine particles are frequently studied, along with associated toxic metals and semimetals (especially Cu, Zn, Cd, As, Ba and Sr). There are many projections of effects of fireworks, but relatively few epidemiological studies of health outcomes or the impact of contamination on local ecosystems. Fireworks waste and debris is an environmental problem; it is expensive to clear and aesthetically unpleasing. Excessive noise (up to 137 dB) created by fireworks affects pets and wildlife, as well as posing a risk to pyrotechnicians. Fireworks produce bursts of light that can be distracting to motorists and disturb wildlife, while smoke particles cause lowered visibility. Green fireworks and festivals of light with lasers or drone technology present routes to lower impact. Contemporary society is sympathetic towards restricting fireworks, but recognition of their cultural importance remains. Full article

Accurate detection of field insect pests remains a significant challenge for precision agriculture due to the elongated and variable morphology of the target organisms, their frequent resemblance to complex background textures, and the long-tail distribution of species in natural datasets. While deep convolutional neural networks (CNNs) have advanced the field, they are often constrained by a limited effective receptive field and the entanglement of semantic and spatial features, which can lead to elevated false-positive rates and missed detections for low-contrast or rare targets. This paper introduces a novel detection framework that integrates state space modeling with multi-stream feature disentanglement to address these limitations. First, a visual state space module is employed as the backbone feature extractor, enabling the establishment of a global receptive field with linear computational complexity and thereby improving the perception of long-range morphological structures. Second, a Topological Feature Disentanglement Pyramid Network is proposed. This architecture explicitly separates feature representations into semantic and spatial streams and recombines them through graph convolutional interactions, which serves to suppress background interference and enhance localization precision. A meta-auxiliary detection head, active only during training, is introduced to amplify supervision signals for hard, low-contrast samples via adversarial gradient modulation. Furthermore, an implicit neural radiance field augmentation pipeline is used to generate physically consistent synthetic views of underrepresented pest classes, mitigating the negative effects of long-tail data distributions. Experimental evaluations on the public BAU-Insectv2 benchmark demonstrate that the proposed method achieves a mean average precision (mAP@0.5) of 81.8%, representing a 4.4-percentage-point improvement over a comparable baseline, while maintaining a compact parameter count of 2.33 M and an inference speed of 178.6 FPS. The framework exhibits particular efficacy in detecting elongated, minute, and rare pests, suggesting a promising technical approach for real-time, field-based pest surveillance in precision agriculture. Full article

Background/Objectives: Triple-negative breast cancer (TNBC) remains a highly aggressive malignancy with limited therapeutic options due to the absence of well-defined molecular targets. Diet-induced obesity (DIO) promotes TNBC progression by reshaping systemic metabolism and inflammatory responses; however, the key circulating metabolites involved and their mechanisms remain largely unclear. This study aimed to identify key metabolites associated with TNBC progression and further investigate their biological functions and molecular mechanisms. Methods: Targeted metabolomics profiling was performed on serum samples from MMTV-PyMT spontaneous breast cancer mice to identify differential metabolites associated with DIO. Functional assays were conducted to evaluate the effects of hippuric acid on TNBC cell proliferation, migration, and invasion. RNA sequencing was conducted to explore downstream regulatory pathways, followed by validation of candidate targets using gain- and loss-of-function approaches as well as rescue experiments. Results: Hippuric acid was identified as a significantly altered metabolite in DIO conditions. Functional studies demonstrated that hippuric acid markedly inhibited the proliferation, migration, and invasion of TNBC cells, with minimal effects on non-TNBC cells. Transcriptomic analysis identified EGFL8 as a potential downstream target, which was further confirmed by qPCR and functional assays. Overexpression of EGFL8 suppressed malignant phenotypes, whereas its knockdown promoted tumor progression. Rescue experiments showed that EGFL8 partially mitigated the inhibitory effects of hippuric acid on TNBC, suggesting that it functions as an important mediator in this process. Mechanistically, hippuric acid exerted its anti-tumor effects at least in part through modulation of the EGFL8-Notch signaling axis. Conclusions: Hippuric acid suppresses TNBC progression via the EGFL8-Notch signaling pathway. These findings highlight a previously unrecognized role of a gut microbiota-derived metabolite in TNBC and suggest its potential as a therapeutic candidate, providing new prospective targets and a theoretical basis for metabolic intervention for TNBC. Full article

Accurate and wide-area estimation of seaweed biomass is essential for evaluating blue carbon. Conventional diver surveys and two-dimensional (2D) aerial imagery analysis face challenges such as intensive labor and biomass underestimation. While Unmanned Aerial Vehicle-based Light Detection and Ranging (UAV-LiDAR) provides dense 3D spatial data, classifying point clouds in extremely shallow coastal waters with dense kelp and artificial structures remains difficult. This study establishes a high-accuracy biomass estimation method using UAV-LiDAR and PointNet. A heuristic hybrid filtering approach combining physical constraints and local statistics was developed to automatically generate high-quality reference data. The trained PointNet successfully segmented complex point clouds into four classes with an overall accuracy of 94.2%. To calculate biomass, we introduced a volume correction model based on point cloud density (coverage) to mitigate overestimation caused by internal canopy gaps. This correction yielded estimated wet weights nearly identical to the in situ measurements (an approximate 3% difference), confirming highly accurate biomass reproduction. Furthermore, while the conventional 2D maximum likelihood method underestimated total biomass, our 3D point cloud analysis successfully quantified the dense, overlapping canopy. This framework significantly improves the efficiency and accuracy of blue carbon monitoring. Full article

Gestational Diabetes Mellitus (GDM) represents a significant public health concern due to its association with adverse maternal and neonatal outcomes, as well as elevated long-term metabolic risks. Its prevalence varies substantially depending on the diagnostic criteria used and the population studied. Women with GDM frequently experience heightened stress, anxiety, and uncertainty, underscoring the need for accessible information, counseling, and ongoing support to navigate glucose monitoring, dietary adjustments, and treatment regimens. Although clinical management has been extensively studied, research has largely focused on metabolic monitoring and therapeutic interventions, often underemphasizing prevention strategies, women’s informational needs, and maternal psychological well-being. Emerging evidence and international guidelines increasingly advocate for integrating these components into structured, woman-centered GDM care plans that actively involve families. Such approaches empower women to engage in self-management, enhance health literacy, support adherence to lifestyle and pharmacological interventions, and promote sustainable behavioral changes. This narrative review presents a comprehensive, holistic model of care across the perinatal continuum, emphasizing early risk identification, preventive strategies, and multidisciplinary coordination. Core elements include individualized antenatal education, empathetic communication, and family engagement, fostering self-efficacy, continuity of care, and integration of medical, educational, and psychosocial interventions. Equipping healthcare professionals with the competencies to deliver this holistic, woman-centered framework is essential to optimize maternal and neonatal outcomes and mitigate the long-term health consequences of GDM. Full article

This study evaluates the accuracy of various preprocessing methods applied to scanned archival aerial photographs for reconstructing historical terrain in the Czech Republic. Seven workflows were tested on identical imagery and control points, varying parameters such as resolution unification, brightness normalization, focal length calibration, and AI-based denoising. Accuracy was assessed using GNSS checkpoints and high-resolution LiDAR data. Results show that basic brightness correction reduced the vertical RMSE by 59% (to 5.69 m). In contrast, standalone AI preprocessing was associated with increased geometric instability (RMSE 16.48 m) due to over-smoothing and the loss of essential micro-texture. However, the evaluated “Fusion AI” workflow—combining AI enhancement with strict focal length constraints—successfully mitigated this degradation. By restricting the internal orientation, it stabilized the vertical accuracy at 6.48 m, closely matching the best traditional approaches. Statistical analysis revealed strong spatial autocorrelation and non-normal error distributions, highlighting the need for robust validation. Ultimately, this study confirms that AI can be effectively utilized to enhance visual clarity in data-scarce historical reconstruction without sacrificing spatial reliability, provided it is strictly geometrically constrained. This offers an optimal compromise and a tested, reproducible workflow that supports heritage preservation and long-term environmental analysis. Full article

As the prevalence of myopia among adolescents continues to increase, the design and fabrication of myopia control lenses have become an important research direction in modern optics. Existing myopia control lenses mostly adopt purely refractive structures, which suffer from limited design freedom, insufficient chromatic aberration suppression, and relatively large lens thickness, thereby restricting further improvement of optical performance. This paper proposes a refractive–diffractive hybrid design and fabrication method for myopia control lenses. Centered on a harmonic diffractive optical element (HDOE), an optimization model is established to balance achromatization performance and fabrication feasibility. To address the challenges of small period width, tool shadow effect, and sensitivity to machining tolerances in diffractive lenses with large-aperture and high-additional-power, harmonic design is employed to increase the period width, thereby reducing fabrication difficulty and mitigating the influence of shadowing errors on diffraction efficiency. On this basis, two lenses with different phase structures are designed: one adopts a conventional diffractive correction phase to verify the role of HDOE in achromatization and edge-thickness reduction, while the other adopts a high-degree-of-freedom smooth phase to achieve a continuous multifocal visual effect. Both lenses are fabricated by single-point diamond turning (SPDT), and the effects of surface profile and machining parameters on performance are analyzed. Simulations and measurements show that the proposed method provides stable diffraction efficiency and effective chromatic aberration correction across the design band, while reducing the edge thickness by approximately 37.85% without additional thinning of the aspheric substrate. The results indicate that the refractive–diffractive hybrid design provides a feasible design and fabrication approach for functionally more complex myopia control lenses. Full article

Age-related decline in immune system function is characterized by reduced numbers of naïve lymphocytes, the accumulation of senescent cells, impaired function of all immune cell types, and chronic low-grade inflammation (inflammaging). These alterations contribute to increased susceptibility to infections and malignancies, as well as to autoimmunity and other age-associated diseases. This article reviews current evidence on lifestyle interventions that may mitigate immune aging. Lifestyle-related strategies, including regular physical activity, nutritional interventions (e.g., different diets, caloric restriction, and other fasting-related approaches), stress reduction, and vaccination, are discussed as key modulators of immune function and systemic inflammation. Notably, vitamin D supplementation has been shown to reduce the incidence of autoimmune diseases by 22%. In comparison, caloric restriction has led to a decrease in CRP and TNF-α by 40% and 50%, respectively. Emerging complementary approaches, such as mind–body practices and controlled cold exposure, show promise, though current evidence remains limited and inconsistent. Therefore, integrated lifestyle strategies may slow aging-related immune decline and support healthy aging. However, longitudinal trials are required to define the optimal intervention parameters, population-specific thresholds, and the long-term durability of immune rejuvenation. Full article

Understanding the factors that shape firms’ borrowing costs has become increasingly important amid growing concerns about corporate transparency, sustainability, and tax practices. Specifically, the study investigates the relationship between tax avoidance (TA) and the cost of debt (CoD) among non-financial firms listed on an emerging Stock Exchange, while examining the moderating effect of environmental, social, and governance disclosure (ESG disclosure) based on the Panel-Corrected Standard Error (PCSE) approach. The findings indicate a significant positive association between TA and CoD, suggesting that lenders perceive aggressive tax practices as a source of additional risk, which consequently increases borrowing costs. The results further show that ESG disclosure plays a moderating role in this relationship, as the positive effect of TA on borrowing costs becomes weaker among firms with higher levels of ESG disclosure. This implies that stronger ESG disclosure improves transparency and alleviates creditors’ concerns about firms’ tax-related behavior. The findings were further validated through robustness checks using alternative CoD measures, fixed-effects regression, and dynamic panel GMM estimations to address endogeneity concerns. The study contributes to the literature by providing evidence from an emerging market and highlighting the role of ESG disclosure in mitigating the negative financial effects of TA. Full article

The rapid expansion of molecular point-of-care (POC) diagnostics into decentralized settings, including emergency departments, retail pharmacies, and home environments, has shifted the burden of diagnostic performance from laboratory professionals to heterogeneous, often non-expert users. While traditional evaluation frameworks focus on analytical and clinical validity, they often overlook the impact of human-system interactions on real-world reliability. This review introduces the concept of Operational Validity: the ability of a diagnostic system to preserve its intended performance when operated by intended users within the constraints of real-world workflows and environments. To establish a rigorous foundation for this concept, this study provides a critical comparative analysis contrasting Operational Validity against traditional clinical evaluation dimensions (analytical validity, clinical validity, and clinical utility) and post-market metrics. While existing literature outlines isolated usability principles, the significance of this study lies in its synthesis of these fragmented concepts into a formalized, lifecycle-based “Operational Validity” framework that explicitly maps the causal mechanisms connecting initial user interaction directly to downstream clinical outcomes. By synthesizing international standards (IEC 62366-1) alongside the newly finalized May 2026 U.S. Food and Drug Administration (FDA) guidance on the Content of Human Factors Information in Medical Device Marketing Submissions, we examine how human factors engineering (HFE) and usability engineering serve as the methodological foundation for operational validity. We analyze the specific complexities of molecular workflows, identify key parameters of use-related failure modes in pre-analytical and interpretation stages, and detail the mandatory role of iterative formative and final summative usability testing in mitigating these risks. Finally, we propose a lifecycle-based approach to HFE that integrates design, simulated-use validation, and post-market surveillance. Establishing operational validity is essential to ensure that the high analytical sensitivity of molecular POC platforms translates into consistent clinical utility across the full spectrum of decentralized care. Full article

This study investigated balance control during the half squat by analyzing the relationship between the center of mass (CoM) and the center of pressure (CoP) in five experienced male weightlifters performing segmented squats at five load levels (20–80% 1 RM) across four Power-Based Training (PBT) exercises. The area of the 95% confidence ellipse was quantified using the Vicon motion capture system in conjunction with AMTI force plates. Given the small sample size (n = 5), a dual inference approach was implemented—frequentist repeated-measures analysis of variance (ANOVA) complemented by a unified adaptive Bayesian hierarchical model—to mitigate Type II error in low-power scenarios. Regarding the movement phase, a marked effect on center of pressure (CoP) stability was observed, as evidenced by both statistical approaches (frequentist: F(1.65, 6.59) = 19.44, p = 0.002, ηp² = 0.829; Bayesian: P(β_phase < 0) > 0.999). Although external load did not reach statistical significance in the frequentist analysis (p = 0.177, achieved power = 0.27), the Bayesian model provided moderate evidence of a positive impact (β_load = 0.059, 95% HDI [0.005, 0.115], p = 0.981). The area of the center of mass (CoM) ellipse showed no effects of interest. Limb asymmetries were significant and consistent throughout the experiment (frequentist: 48.01 ± 30.13%; Bayesian: 69.48%, 95% HDI [55.86%, 81.44%], P(AI > 20%) = 1.000) and were not modulated by the experimental condition. CoP-CoM coupling was stronger in the mediolateral direction than in the anteroposterior direction. The findings reveal that phase is the primary factor in postural stability, exerting a modest positive influence discernible only through low-powered probabilistic inference, and that the dual framework strengthens inferential robustness in small-sample biomechanical studies. Confirmatory studies with larger samples are recommended. Full article