Search Results (18,678)

While terrestrial carbon storage is vital for achieving global carbon neutrality, its spatiotemporal evolution in ecologically fragile regions—such as the Pisha sandstone area—is complicated by intense erosion and complex environmental drivers. Widely known as the Pisha sandstone area, often referred to as the “Earth’s ecological cancer” due to its unique geological instability (“hard as rock when dry, soft as mud when wet”), this area is a critical but vulnerable carbon sink in the Yellow River Basin. This study aims to clarify these dynamics and identify their non-linear driving mechanisms by integrating a coupled PLUS–InVEST model with an XGBoost–SHAP framework to simulate land-use cover change and quantify carbon sequestration potential from 1990 to 2040. Our results reveal: (1) a robust path dependence in land use, where grassland remained the dominant landscape matrix (>75%), which partly explains the stable regional carbon-stock structure and the moderate FoM value of the PLUS validation; (2) carbon storage followed a fluctuating but overall increasing trajectory, projected to reach a peak of 3.19 × 10⁵ tC by 2040 under the Ecological Conservation Scenario (ECS), which significantly outperforms the economic-driven and natural growth modes; (3) hot spot analysis showed that statistically notable low-carbon cold spots were concentrated mainly along valley corridors, marginal transition zones, and locally disturbed patches, whereas high-carbon hot spots were spatially limited; and, (4) crucially, XGBoost–SHAP results should be interpreted as model-based associations rather than direct causal proof; the whole-region model and the regional models jointly suggest that topography, water availability, socioeconomic pressure, and erosion-related factors contribute differently across bare, loess-covered, and sand-covered Pisha sandstone units. These findings support differentiated land-use and restoration strategies rather than uniform regional management. The findings suggest that future management in the Pisha sandstone area should transition from general restoration toward targeted and differentiated regulation to improve regional ecosystem services. Full article

With the rapid development of general artificial intelligence, large models have gradually become the key force driving the digital transformation of the field. Agriculture has distinct domain characteristics, and traditional deep learning models are difficult to meet its cross-regional and cross-task requirements. Large models specifically designed for the agricultural field can integrate multi-source data and prior knowledge to break through this bottleneck. Therefore, tracking the development trend of large agricultural models is an important prerequisite for building new, quality productive forces in smart agriculture and promoting the digital transformation of agriculture. This article conducts a literature search and review around the research on large agricultural models, following the PRISMA guidelines. It combines the keywords of large models, crops, livestock breeding, etc., and only includes journal papers from 2022 to 2026, totaling 713 articles. Then, it performs topic modeling to deeply clarify the current research and application status, and summarizes the challenges faced and makes future research prospects. Existing evidence indicates that current large agricultural models are gradually developing towards agents and embodied intelligence, and are widely applied in scenarios such as agricultural knowledge services, pest and disease diagnosis and prevention, livestock and fishery breeding, and smart agricultural machinery control. However, they still face many key challenges, and further exploration is needed in theoretical methods and practical applications. In the future, research can be further deepened and expanded in areas such as the construction of high-quality data sets, the construction of domain evaluation systems, strengthening model reliability, building multi-agent systems, and lightweight deployment of large models and embodied intelligence. Full article

How does state-led farmland protection reshape the industrial structure of cities? While farmland protection is widely understood as an ecological policy, its consequences for industrial transformation remain underexplored. This paper argues that farmland protection in China operates through a quantitative-target system enforced via land use regulation: a binding farmland retention target mechanically tightens the supply of construction land, making land use regulation the operative channel through which farmland protection reshapes urban industries. Drawing on the socio-ecological systems framework, we treat the 2010 incorporation of farmland protection into the bureaucratic performance evaluation system as a governance perturbation and apply a continuous difference-in-differences design to a long-term panel of Chinese prefecture-level cities spanning two decades. The estimates show that intensified regulation moves the industrial structure toward more rational and technology-intensive configurations. Mechanism analysis confirms that the policy operates through two complementary channels: restricting construction land supply and enhancing per-area output. Heterogeneity analysis reveals an asymmetric response: structural gains concentrate in non-eastern cities, where binding farmland protection forces a more decisive break with land-extensive growth, whereas eastern cities absorb the policy on the intensive margin, deepening within-sector productivity rather than reorganizing the cross-sector mix. The findings establish farmland protection as a policy lever for industrial upgrading and offer guidance on calibrating regulatory intensity across regions at different developmental stages. Full article

Chemotherapy has been used in cancer treatment for decades; however, standard chemotherapy treatments still have significant weaknesses, including collateral damage to healthy tissue, rapid development of drug resistance, and dose-limiting toxicity that limits therapeutic value. There is now an alternative approach using polymer materials that are responsive to biological stimuli that will allow for improved treatment of cancer while avoiding the limitations. Responsive polymer materials are designed to be inert during circulation until they reach their site of action; then, they will respond to specific triggers. These smart carriers respond to stimuli present in the tumor microenvironment (e.g., low pH, high glutathione levels, and increased proteolytic activity) or external stimuli applied at the bedside (e.g., localized heat, light, ultrasound, and applied magnetic fields). In both cases, there is a consistent pattern where the drug is released exactly where/when it is needed, with minimal drug release occurring outside that location and timeframe. Therefore, it is theorized that the use of polymeric-based delivery systems with stimuli-regulated drug release will significantly increase the concentration of drug delivered intratumorally, decrease the drug toxicity, and provide a potential mechanism to overcome the development of multidrug resistance from a variety of cancer treatments. To date, various types of responsive polymers have been developed and could be combined to give rise to a wide variety of different vehicle systems (e.g., micelles, nanogels, hydrogels, and hybrid delivery systems), with many of these carriers designed to respond to multiple stimuli simultaneously. Nonetheless, significant challenges remain in the clinical application of these materials due to tumor heterogeneity, immune system interactions, reproducibility issues, polymer chemistry advances, surface chemistry, and other interaction mechanisms. As a result of all of these evolving regulatory systems, as well as some of the emerging areas of polymer chemistry and surface engineering, theranostic integration will allow for new routes to provide therapy for patients with cancer. Additionally, because of these scientific advances, there will also be more opportunities to provide targeted, controllable, and on-demand treatments to patients using stimuli-responsive polymers. Full article

In long-endurance and high-precision navigation scenarios, gravity disturbances have become the core bottleneck limiting the performance improvement of high-precision Inertial Navigation Systems (INSs). This paper aims to investigate the compensation efficacy of gravity field spherical harmonic models of different degrees for high-precision INS. The influence mechanisms of gravity disturbances on INS error propagation are derived, and corresponding simulation analyses are performed. The gravity compensation mechanism based on gravity field spherical harmonic models is elaborated, and the performance differences in gravity disturbance compensation among spherical harmonic models of different orders are comparatively analyzed. Based on long-endurance ship trial experiments using high-precision inertial navigation equipment, the compensation efficacy of the 360-order and 2159-order compensation schemes on multiple navigation performance indicators is quantitatively evaluated across sea areas with different gravity characteristics. The experimental results demonstrate that the widely held consensus within the field—that a higher model degree yields better compensation efficacy when improving high-precision INS accuracy based on gravity field spherical harmonic model compensation—does not hold universal applicability. The research findings can provide theoretical support for the engineering implementation of gravity compensation schemes and the selection of model degrees for high-precision INS. Full article

As the foundational sensing element for AI-driven structural health monitoring systems, piezoelectric ceramic (PZT) is widely adopted in civil engineering to capture high-fidelity physical responses. Distinct from existing studies focusing on the actuation mode or static/quasi-static sensing conditions, this study specifically investigates the dynamic strain transfer behavior of surface-bonded PZT sensors in sensing mode by establishing a three-layer analytical model incorporating the adhesive shear lag effect, validated by finite element simulations. Accordingly, a dual-regime dynamic calibration strategy is proposed: employing a single sensitivity value for low-frequency global structural vibrations and frequency-dependent correction for high-frequency elastic wave applications. Parametric analyses on PZT thickness, adhesive thickness, and shear modulus quantitatively demonstrate that reducing PZT/adhesive thicknesses and increasing adhesive shear modulus extend the compensation-negligible frequency range (defined by a 10% strain ratio deviation threshold) and elevate the first-order longitudinal natural frequency; practical sensor fabrication guidelines are further derived from these findings. Additionally, the system’s first-order longitudinal natural frequency stabilizes when the host-to-PZT area ratio (A_s/A_p) exceeds a critical threshold. These findings provide a theoretical basis for the optimal design, dynamic calibration, and engineering application of bonded PZT sensors. Full article

Secure communication is one of the foundational requirements for modern smart grid operations, where Distributed Network Protocol 3 (DNP3) remains a primary protocol for monitoring and control. Key stakeholders in the smart grid—such as transmission operators, distribution operators, utilities, and balancing authorities—are increasingly required to strengthen their cybersecurity protections. They must maintain the reliability of communications across complex, bandwidth-constrained wide-area networks (WANs). This paper presents a practical evaluation of four DNP3 deployment models: DNP3 in its native unsecured form, DNP3 with Secure Authentication (SA), DNP3 over Transport Layer Security (TLS 1.3), and DNP3 protected using IPsec encryption at the network layer. The paper evaluates how each security approach performs in a production-like smart grid environment. This paper primarily focuses on the widely deployed DNP3-SA model, which provides authentication and integrity but not confidentiality. Although newer Secure Authentication versions exist, including SAv6, they are still less common in operational utility environments. Experiments are conducted using a hardware-informed simulation testbed that emulates realistic utility WAN conditions, including multiple routing hops, MPLS as a transport for packets, and varied link capacities. Performance is assessed in terms of bandwidth efficiency, round-trip latency, and additional computational overhead on the field devices. Based on the findings, the paper presents a decision framework to help utilities select DNP3 security implementations that align with regulatory expectations and operational reliability. Full article

Background: An important determinant of mortality in AS is the presence and quantity of myocardial scar. Scar quantification using late gadolinium enhancement (LGE) on cardiovascular magnetic resonance (CMR) imaging may be a useful risk-stratification tool for at-risk patients who do not meet current criteria for valve intervention. The incorporation of this tool into clinical practice is currently limited by a lack of consensus on the best LGE quantification technique to use. Methods: Fifteen patients with severe AS underwent LGE imaging on CMR. A reference estimate of the LGE mass was made using a semi-automatic quantitative visual method. An intensity slider (reporting software provided) was used to mark areas of enhanced signal in each short-axis slice that correlated with the reader’s visual assessment of LGE, which used predetermined imaging criteria. This visual slider method (VslM) of determining LGE mass was then used as a reference for establishing the accuracy of various semi- and fully automated methods for identifying and quantifying LGE burden. These included the signal threshold versus reference mean (STRM) method at thresholds of two-, three-, and five-standard deviations (2SD, 3SD, 5SD, respectively), the full width at half maximum (FWHM) method and the Otsu auto threshold (OAT) method. An intraclass correlation analysis was performed to establish and compare the inter-reader reliability for each method. Results: Three readers demonstrated 100% agreement on the presence of LGE in 12/15 (80%) of study cases. Accuracy determined by the Wilcoxon rank sum, Spearman correlation and Bland–Altman tests suggested that the 5SD method using remote myocardium reference regions of interest only in slices with visually detected LGE was best (Wilcoxon rank sum p-values ranged from 0.3 to 0.5 for the three readers, bias on Bland–Altman was <0.5 g for all three readers). This was followed by the FWHM method, but with wide minimum-maximum ranges observed. Inter-reader reliability was best for the 2SD STRM method (ICC = 0.9, p < 0.001), but accuracy using this method was clinically unacceptable. Inter-reader reliability was statistically acceptable for the VslM (ICC = 0.7, p < 0.001). The FWHM method yielded the best balance between accuracy and reliability but may be limited by the heterogeneity of scars observed from patient to patient. Conclusions: The FWHM appeared to offer a reasonable balance between accuracy and precision. However, it was not always the best fit, e.g., in patients with small or non-bright scars. There may be no additional benefit to using the semi- and fully automated methods in the context of AS, and visual estimation, when performed in the manner described in this study (i.e., the VslM), may be clinically sufficient. Full article

This paper presents a five-phase, two-switch buck-boost (5P-TSBB) converter rated at 75 kW, intended for photovoltaic and energy storage applications that require a wide operating voltage range. The proposed system operates with photovoltaic input voltages ranging from 250 V to 1000 V and regulates the DC-link voltage between 600 V and 950 V. The converter supports two distinct operating modes: an independent multi-input mode for multiple independent input sources and an interleaved mode for a single high-power input. The feasible operating area of the converter is determined in the V_in–V_out plane, taking into account voltage, current, and power limitations. Simulation results and experimental investigations on a laboratory prototype, including measurements of efficiency and power losses, support the theoretical considerations. Full article

Background: Hepatocellular carcinoma (HCC) is one of the most common and deadliest cancers worldwide. Alpha-fetoprotein (AFP), a widely used and accessible tumoral marker, has limited performance in the early detection of HCC among high-risk populations. This study aims to evaluate the potential added value of ccfDNA (circulating cell-free DNA) fragment size, alone or in a multiparameter panel, using accessible, feasible ccfDNA analysis. Methods: A prospective cohort of 125 patients with chronic liver disease was analyzed. Patients with incomplete clinical or laboratory data and patients without cirrhosis were excluded from the final analysis. Nonparametric tests, logistic regression and ROC curve analysis were performed. ccfDNA fragment size was measured using on-chip electrophoresis. Results: ccfDNA fragment size was significantly lower in the cirrhosis-HCC subgroup compared to the cirrhosis-only subgroup (p < 0.001). While AFP remains an independent predictor of HCC among cirrhosis patients, ccfDNA fragment size did not prove to be an independent predictor in this cohort. AUROC (area under the receiver operating characteristic curve) analysis revealed that a combined model of AFP, age, liver reserve, and ccfDNA fragment size did not perform better than the corresponding panel without ccfDNA. Moreover, after DeLong comparison, the difference between the two AUROCs proved statistically insignificant. Age and platelet count remain the strongest independent predictors in our exploratory cohort. Conclusions: Although ccfDNA fragment size proved to be lower in the HCC subgroup, its statistical significance fades when included into a multimarker panel. However, all panels should undergo further validation in a larger cohort, in order to better assess the individual contribution of each parameter and to discriminate between added diagnostic value and confounding effect of age and liver reserve parameters. Full article

Corn stover is an abundant, low-cost, and representative lignocellulosic agricultural residue for bioethanol production, but its recalcitrant structure requires effective pretreatment to improve downstream conversion performance. Ball milling technology has been widely used to pretreat lignocellulosic biomass, where regulating particle size distribution enhances lignin utilization and subsequent ethanol production. However, systematic optimization of ball milling operating parameters remains insufficiently investigated. To bridge the gap between bench-scale experimentation and process-level performance prediction, this study establishes an integrated experimental and simulation framework. Ball milling experiments are conducted to systematically vary key operating parameters, and particle morphology is precisely quantified through optical imaging coupled with digital image analysis. Empirical correlations between these operating conditions and particle size characteristics are derived through polynomial fitting. These correlations are then embedded into an Aspen Plus process model for bioconversion performance evaluation. Evaluation from this integrated framework reveals that system-level optimization of the pretreatment process effectively reduces mean particle size, narrows size distribution, and increases specific surface area. By systematically evaluating the operating space, an optimal window that yields a 2.97% improvement in glucose conversion is identified. This work provides practical guidance and a generalizable framework for optimizing mechanical pretreatment to maximize target product yields. Full article

Photocatalytic extraction of uranium from radioactive wastewater is crucial for environmental safety and sustainable nuclear energy development. It is widely recognized that photocatalysts with donor-acceptor (D-A) or D-π-A structures exhibit enhanced charge separation efficiency, thereby showing excellent photocatalytic performance. Herein, we presented a counterintuitive design of a donor-donor covalent-organic framework (D-D COF) for efficient photocatalytic uranium extraction. A twisted D-D COF (COF-BCTB-Py) was synthesized via solvothermal condensation using bicarbazole and pyrene as dual electron-donor units. The COF featured a well-defined AA-stacked porous structure, high specific surface area (963 m²·g⁻¹), suitable band gap (2.44 eV), and exceptional chemical, thermal, and radiation stability. Impressively, in the presence of 5% methanol, it delivered an ultrahigh uranium uptake capacity of 4278 mg·g⁻¹ with fast kinetics and >97% removal efficiency in complex water matrices, challenging the traditional stereotype of low-activity D-D COFs. Mechanistic studies revealed that soluble U(VI) was converted into crystalline (UO₂)O₂·2H₂O via in situ generated hydrogen peroxide rather than being reduced to U(IV). This work provides an unconventional design strategy to design efficient photocatalysts for uranium recovery from nuclear wastewater. Full article

Reliable rainfall information is fundamental for climate-risk analysis and operational monitoring in Mediterranean regions such as Apulia (Southern Italy), one of the areas most affected by climate change-driven shifts in rainfall patterns. Recent evaluations across Italy and comparable Mediterranean settings consistently show that gridded precipitation performance is highly dependent on orography and dataset typology: reanalyses often provide the best overall agreement with gauges, while satellite and blended products can exhibit larger biases, with persistent challenges in complex terrain and for high-intensity events. In this context—and given the documented spatial heterogeneity of rainfall extremes within Apulia—validation of such gridded datasets with respect to ground observations remains essential for early warning and climatological applications. In the present work, we evaluate four widely used precipitation products—CHIRPS-v2, the newly released CHIRPS-v3, IMERG, and ERA5—benchmarking them against the Apulia region Civil Protection rain-gauge network. We provide diagnostics aligned with early warning and climate monitoring: bias and error statistics, rainfall intensity distributions, and dry spell duration. A key contribution is, to our knowledge, the first dedicated validation of CHIRPS-v3 in Apulia, which is timely given that CHIRPS-v3 was explicitly developed to address shortcomings such as underestimated temporal variance and to leverage expanded station inputs. The results indicate that CHIRPS-v3 yields systematic improvements over CHIRPS-v2 across multiple metrics, while ERA5 generally shows the strongest overall agreement with gauges—consistent with broader Italian evidence. Full article

In soft soil areas, cement–soil mixing piles are widely employed as a building foundation treatment measure, and their construction parameters directly influence pile uniformity and the stability of foundation reinforcement. However, visual and quantitative methods to verify on-site improvement effects are currently lacking. This study aimed to improve the mixing uniformity between jet media and soil layers and proposed a quantitative evaluation method based on numerical simulation and image recognition. Taking the silty soil in the Nansha area in Guangdong Province, China, as the research object, combined with flow tests and discrete element simulations, an experimental simulation based on a linear model of adhesive rolling resistance was established. First, the entire process of the wet water spraying soil mixing method and visualizing particle behavior was simulated. Based on the Danckwerts mixing index, image recognition technology was applied to quantify the uniformity of cement–soil mixing at different rotational speeds. The simulation results revealed that increasing the rotational speed within a certain range (0–100 r/min) significantly improved the uniformity of cement–soil mixing by 33.3%. However, increasing the rotational speed still further (100–200 r/min) resulted in only a 15.8% improvement. Furthermore, excessive rotational speed caused a significant loss of cement within the designed diameter of the pile. Second, based on the cement retention rate inside the pile, a speed balance range suitable for the working conditions of this study was obtained. A good balance was achieved between the effective cement content inside the pile and the uniformity of cement–soil mixing, further ensuring the consolidation effect of the cement–soil pile. Full article

Lockdown drills have become standard practice in K-12 schools across the United States, but there are concerns about the psychological health impact, quality of implementation, and equity implications of current practices. This scoping review compiles the empirical literature on lockdown and active-threat drills to provide insight into how drills are defined and conducted, what outcomes are measured, and the remaining gaps. In accordance with well-researched scoping review methodologies, 27 peer-reviewed U.S.-based studies were aggregated from six primary areas: drill definitions and typologies, implementation practices, reported outcomes, trauma-informed and developmental considerations, equity and disability inclusion, and evidence gaps. Findings reveal wide variability among drill terminology and protocol categorization and most studies emphasize advance warning and low-realism practices. Psychological outcomes are measured much more often than objective measures of implementation fidelity or physical preparedness. Educator and staff experiences, caregiver perceptions, and longitudinal outcomes are underrepresented. Although a number of studies report developmental adaptations and disability accommodations, comprehensive equity analyses remain rare. Overall, potential psychological harms are more clearly documented than protective effects in the literature. This review emphasizes the importance of standardized drill taxonomies, fidelity measurement methods, trauma-informed mental health integration, and inclusive designs to inform school safety policy and practice. Full article