Search Results (4,076)

Cobalt, a rare element in the Earth’s crust, is widely used in industries due to its hardness and antioxidant properties. It also plays a vital role in physiological functions, being a key component of vitamin B₁₂. However, excessive cobalt intake can cause health issues. Detecting cobalt ions, especially Co²⁺, in food is crucial due to potential contamination from various sources. Fluorescent probes offer high sensitivity, selectivity, a rapid response, and ease of use, making them ideal for the accurate and efficient recognition of Co²⁺ in complex samples. In this context, a highly selective fluorescent probe, 2,2′-((3-(1H-benzo[d]imidazol-2-yl)-1,2-phenylene) bis(oxy)) bis(N-(quinolin-8-yl) acetamide) (DQBM-B), was synthesized using chloroacetyl chloride, 8-aminoquinoline, 2,3-dihydroxybenzaldehyde, and benzidine as raw materials for the recognition of Co²⁺. Probe DQBM-B can exhibit fluorescence alone in DMF. However, as the concentration of Co²⁺ increased, Photoinduced Electron Transfer (PET) occurred, which quenched the original fluorescence of the probe. Probe DQBM-B shows better selectivity for Co²⁺ than other ions with high sensitivity (detection limit: 3.56 μmol L⁻¹), and the reaction reaches equilibrium within 30 min. Full article

With rapid global urbanization development, impermeable surface increase, urban population growth, building area expansion, and rising energy consumption, the urban heat island (UHI) effect is becoming increasingly serious. However, the spatial distribution of the UHI cannot be accurately extracted. Therefore, we focused on Luoyang City as the research area and combined the Getis-Ord-Gi* statistic and the greenest image to extract the UHI based on the Google Earth Engine using land surface temperature–spatial autocorrelation characteristics and seasonal changes in vegetation. As bare land considerably influenced the UHI extraction results, we combined the greenest image with the initial extraction results and applied the maximum normalized difference vegetation index threshold method to remove this effect on UHI distribution extraction, thereby achieving improved UHI extraction accuracy. Our results showed that the UHI of Luoyang continuously expanded outward, increasing from 361.69 km² in 2000 to 912.58 km² in 2023, with a continuous expansion rate of 22.95 km²/year. Furthermore, the urban area had a higher UHI area growth rate than the county area. Analysis indicates that the UHI effect in Luoyang has increased in parallel with the expansion of the building area. Intensive urban construction is a primary driver of this growth, directly exacerbating the UHI effect. Additionally, rising temperatures, population growth, and gross domestic product accumulation have collectively contributed to the ongoing expansion of this phenomenon. This study provides scientific guidance for future urban planning through the accurate extraction of the UHI effect, which promotes the development of sustainable human settlements. Full article

Heavy metal pollution, particularly copper contamination, threatens the ecological environment and human survival. In response to this pressing environmental issue, the development of innovative remediation strategies has become imperative. Bioremediation technology is characterized by remarkable advantages, including its ecological friendliness, cost-effectiveness, and operational efficiency. In our previous research, Rossellomorea sp. ZC255 demonstrated substantial potential for environmental bioremediation applications. This study investigated the removal characteristics and underlying mechanism of strain ZC255 and revealed that the maximum removal capacity was 253.4 mg/g biomass under the optimal conditions (pH 7.0, 28 °C, and 2% inoculum). The assessment of the biosorption process followed pseudo-second-order kinetics, while the adsorption isotherm may fit well with both the Langmuir and Freundlich models. Cell surface alterations on the Cu(II)-treated biomass were observed through scanning electron microscopy (SEM). Cu(II) binding functional groups were determined via Fourier transform infrared spectroscopy (FTIR) analysis. Simultaneously, the genomic analysis of strain ZC255 identified multiple genes potentially involved in heavy metal resistance, transport, and metabolic processes. These studies highlight the significance of strain ZC255 in the context of environmental heavy metal bioremediation research and provide a basis for using strain ZC255 as a copper removal biosorbent. Full article

In recent years, most proposed digital image encryption algorithms have primarily focused on encrypting raw pixel data, often neglecting the integration with image compression techniques. Image compression algorithms, such as JPEG, are widely utilized in internet applications, highlighting the need for encryption methods that are compatible with compression processes. This study introduces an innovative color image encryption algorithm integrated with JPEG compression, designed to enhance the security of images susceptible to attacks or tampering during prolonged transmission. The research addresses critical challenges in achieving an optimal balance between encryption security and compression efficiency. The proposed encryption algorithm is structured around three key compression phases: Discrete Cosine Transform (DCT), quantization, and entropy coding. At each stage, the algorithm incorporates advanced techniques such as block segmentation, block replacement, DC coefficient confusion, non-zero AC coefficient transformation, and RSV (Run/Size and Value) pair recombination. Extensive simulations and security analyses demonstrate that the proposed algorithm exhibits strong robustness against noise interference and data loss, effectively meeting stringent security performance requirements. Full article

The Tibetan Plateau (TP) is experiencing higher warming rates than elsewhere, which may affect regional vegetation growth. Particularly on the Eastern Tibetan Plateau (ETP), where the topography is diverse and rich in biodiversity, it is necessary to clarify the drivers of climate and topography on vegetation cover. In this research, we selected the Shaluli Mountains (SLLM) in the ETP as the study area, monitored the spatial and temporal dynamics of the regional vegetation cover using remote sensing methods, and quantified the drivers of vegetation change using Geodetector (GD). The results showed a decreasing trend in annual precipitation (PRE) (−2.4054 mm/year) and the Palmer Drought Severity Index (PDSI) (−0.1813/year) in the SLLM. Annual maximum temperature (TMX) on the spatial and temporal scales showed an overall increasing trend, and the regional climate tended to become warmer and drier. Since 2000, fractional vegetation cover (FVC) has shown a fluctuating upward trend, with an average value of 0.6710, and FVC has spatially shown a pattern of “low in the middle and high in the surroundings”. The areas with non-significant increases (p > 0.05) and significant increases (p < 0.05) in FVC accounted for 46.03% and 5.76% of the SLLM. Altitude (q = 0.3517) and TMX (q = 0.3158) were the main drivers of FVC changes. As altitude and TMX increased, FVC showed a trend of increasing and then decreasing. The results of this study help us to clarify the influence of climate and topography on the vegetation ecosystem of the ETP and provide a scientific basis for regional biodiversity conservation and sustainable development. Full article

Background and Objectives: This study aimed to explore the risk factors of histopathological crescent formation in pediatric IgA vasculitis nephritis (IgAVN). Materials and Methods: Enrolled patients with biopsy-proven IgAVN from Zhejiang University’s hospital were split into two groups: 377 with no crescents on histopathology (Group 1) and 364 with crescentic nephritis (Group 2). Collected data included clinical features, lab indicators, histopathological grading, and factors causing glomerular sclerosis. Logistic regression was used to assess factors affecting crescent formation in IgAVN. Double-immunofluorescence assay was used to detect TGF-β1, MCP-1, α-SMA, Collagen I, and FN1 in kidney biopsy specimens. The relationship between kidney fibrosis factors and histopathological grade were analyzed using Chi-square and Pearson tests. Results: A total of 741 patients with IgAVN were included in the study. Univariate logistic regression identified potential factors related to crescent formation, including age, gender, clinical classification, hematuria grade, 24 h urine protein level, peripheral white blood cells (WBCs), serum albumin, Cystatin-C, APTT, and PT. Multivariate analysis revealed statistical significance for age, 24 h urine protein, and WBCs across pathological grades (p < 0.05). Mantel–Haenszel Chi-square tests indicated a linear relationship between IgAVN pathological grade and α-SMA, TGF-β1, MCP-1, and FN1. Pearson correlation analysis confirmed a positive correlation between pathological grade and these markers. Conclusions: Age, 24 h urinary protein, and blood WBCs are identified as risk factors for histopathological crescent formation in children with IgAVN. Additionally, a higher pathological grade is associated with more pronounced fibrosis indicators. Full article

The junction temperature (T_j) is a key parameter reflecting the thermal behavior of Silicon carbide (SiC) MOSFETs and is essential for condition monitoring and reliability assessment in power electronic systems. However, the limited temperature sensitivity of switching characteristics makes it difficult for traditional single temperature-sensitive electrical parameters (TSEPs) to achieve accurate estimation. To address this challenge and enable practical thermal sensing applications, this study proposes an accurate, application-oriented T_j estimation method based on multivariate linear regression (MLR) using turn-off current fall time (t_fi) and fall loss (E_fi) as complementary TSEPs. First, the feasibility of using current fall time and current fall energy loss as TSEPs is demonstrated. Then, a coupled junction temperature prediction model is developed based on multivariate linear regression using t_fi and E_fi. The proposed method is experimentally validated through comparative analysis. Experimental results demonstrate that the proposed method achieves high prediction accuracy, highlighting its effectiveness and superiority in MLR approach based on the current fall phase characteristics of SiC MOSFETs. This method offers promising prospects for enhancing the condition monitoring, reliability assessment, and intelligent sensing capabilities of power electronics systems. Full article

Protein-bound uraemic toxins (PBUTs), such as indoxyl sulphate (IS) and p-cresyl sulphate (PCS), are poorly cleared by conventional haemodialysis (HD) or haemodiafiltration (HDF). Haemoadsorption combined with HD (HAHD) using the novel pHA130 cartridge may increase PBUT removal, and this trial aimed to compare its efficacy and safety with HDF in patients with end-stage renal disease (ESRD). In this single-centre, open-label trial, 30 maintenance HD patients were randomized (1:1:1) to HDF once every two weeks (HDF-q2w), HAHD once every two weeks (HAHD-q2w), or HAHD once weekly (HAHD-q1w) for 8 weeks, with the primary endpoint being the single-session reduction ratio (RR) of IS. The combined HAHD group (n = 20) demonstrated a significantly greater IS reduction than the HDF-q2w group (n = 10) (46.9% vs. 31.8%; p = 0.044) and superior PCS clearance (44.6% vs. 31.4%; p = 0.003). Both HAHD regimens significantly reduced predialysis IS levels at Week 8. Compared with HDF, weekly HAHD provided greater relief from pruritus and improved sleep quality, with comparable adverse events among groups. In conclusion, HAHD with the pHA130 cartridge is more effective than HDF for enhancing single-session PBUT removal and alleviating uraemic symptoms in patients with ESRD, with weekly application showing optimal symptomatic benefits. Full article

The ecological rice–eel co-culture system is not only beneficial for enhancing productivity and sustainability in agriculture but also plays a crucial role in promoting environmental health. In the present study, based on the long-term positioning trial of the rice–eel co-culture system that began in 2016 and was sampled in 2023, the effects of reduced nitrogen fertilizer application on soil physico-chemical properties and the bacterial community were investigated. Treatments included a conventional regular fertilization treatment (RT), rice–eel co-culture system regular fertilization (IT), and nitrogen-reduction 10%, 30%, and 50% fertilization treatments (IT90, IT70, and IT50). Our research demonstrated the following: (1) Compared to RT, IT significantly increased soil water-stable macroaggregates (R0.25), mean weight diameter (MWD), geometric mean diameter (GMD), and available phosphorus content, with the increases of 15.66%, 25.49%, 36.00%, and 18.42%, respectively. Among the nitrogen-reduction fertilization treatments, IT90 showed the most significant effect. Compared to IT, IT90 significantly increased R0.25, MWD, GMD, and available nitrogen content, with increases of 4.4%, 7.81%, 8.82%, and 28.89%, respectively. (2) Compared to RT, at the phylum level, the diversity of Chloroflexi was significantly increased under IT and IT50, and the diversity of Gemmatimonadota was significantly increased under IT90, IT70, and IT50. The diversity of Acidobacteriota was significantly higher in IT90 and IT70 compared to IT. It was shown that the rice–eel co-culture system and nitrogen fertilizer reduction could effectively improve the degradation capacity of organic matter and promote soil nitrogen cycling. In addition, redundancy analysis (RDA) identified total phosphorus, total nitrogen, and available nitrogen (p = 0.007) as the three most important environmental factors driving changes in the bacterial community. (3) The functional prediction analysis of soil microbiota showed that, compared to RT, the diversity of pathways related to biosynthesis (carbohydrate biosynthesis and cell structure biosynthesis) and metabolism (L-glutamate and L-glutamine biosynthesis) was significantly higher under IT70, IT90, IT, and IT50 (in descending order). However, the diversity of pathways associated with degradation/utilization/assimilation (secondary metabolite degradation and amine and polyamine degradation) was significantly lower under all the rice–eel co-culture treatments. In conclusion, the rice–eel co-culture system improved soil physicochemical properties and the soil microbial environment compared with conventional planting, and the best soil improvement was achieved with 10% less N fertilizer application. Full article

The hypothalamus–pituitary–ovarian (HPO) axis orchestrates reproductive functions through intricate neuroendocrine crosstalk. Here, we integrated single-nucleus RNA sequencing (snRNA-seq) and spatial transcriptomics (ST) to decode the cellular heterogeneity and intercellular communication networks in the reproductive systems of pregnant Mongolian cattle. We retained a total of 6161 high-quality nuclei from the hypothalamus, 14,715 nuclei from the pituitary, and 26,072 nuclei from the ovary, providing a comprehensive cellular atlas across the HPO axis. In the hypothalamus, neurons exhibited synaptic and neuroendocrine specialization, with glutamatergic subtype Glut4 serving as a TGFβ signaling hub to regulate pituitary feedback, while GABAergic GABA1 dominated PRL signaling, likely adapting maternal behavior. Pituitary stem cells dynamically replenished endocrine populations via TGFβ, and lactotrophs formed a PRL–PRLR paracrine network with stem cells, synergizing mammary development. Ovarian luteal cells exhibited steroidogenic specialization and microenvironmental synergy: endothelial cells coregulated TGFβ-driven angiogenesis and immune tolerance, while luteal–stromal PRL–PRLR interactions amplified progesterone synthesis and nutrient support. Granulosa cells (GCs) displayed spatial-functional stratification, with steroidogenic GCs persisting across pseudotime as luteinization precursors, while atretic GCs underwent apoptosis. Spatial mapping revealed GCs’ annular follicular distribution, mediating oocyte–somatic crosstalk, and luteal–endothelial colocalization supporting vascularization. This study unveils pregnancy-specific HPO axis regulation, emphasizing multi-organ crosstalk through TGFβ/PRL pathways and stem cell-driven plasticity, offering insights into reproductive homeostasis and pathologies. Full article

The uncertainties arising from high renewable energy penetration on both the generation and demand sides pose significant challenges to distribution network security. Smart microgrids are considered an effective way to solve this problem. Existing studies exhibit limitations in prediction accuracy, Alternating Current (AC) power flow modeling, and integration with optimization frameworks. This paper proposes a closed-loop technical framework combining high-confidence interval prediction, second-order cone convex relaxation, and robust optimization to facilitate renewable energy integration in distribution networks via smart microgrid technology. First, a hybrid prediction model integrating Variational Mode Decomposition (VMD), Long Short-Term Memory (LSTM), and Quantile Regression (QR) is designed to extract multi-frequency characteristics of time-series data, generating adaptive prediction intervals that accommodate individualized decision-making preferences. Second, a second-order cone relaxation method transforms the AC power flow optimization problem into a mixed-integer second-order cone programming (MISOCP) model. Finally, a robust optimization method considering source–load uncertainties is developed. Case studies demonstrate that the proposed approach reduces prediction errors by 21.15%, decreases node voltage fluctuations by 16.71%, and reduces voltage deviation at maximum offset nodes by 17.36%. This framework significantly mitigates voltage violation risks in distribution networks with large-scale grid-connected photovoltaic systems. Full article

The Karp and Rabin (KR) fingerprint is a special hash-like function widely utilized for efficient string matching. Recently, Sharma et al.leveraged its linear and symmetric properties to facilitate private database queries. However, their approach mainly protects encrypted or secret-shared databases rather than public databases, where only the query privacy is required. In this paper, we focus explicitly on privacy-preserving queries over public read-only databases. We propose a novel fingerprint-based keyword query scheme using the distributed point function (DPF), which effectively hides users’ data access patterns across two symmetric mirror servers. Moreover, we provide a rigorous analysis of the false positive probability inherent in fingerprinting and discuss strategies for its minimization. Our scheme achieves efficiency close to plaintext methods, significantly reducing deployment complexity. Full article

Powdery mildew, caused by Erysiphe quercicola, is one of the primary diseases responsible for the reduction in natural rubber production in China. This disease is a typical airborne pathogen, characterized by its ability to spread via air currents and rapidly escalate into an epidemic under favorable environmental conditions. Accurate prediction and determination of the prevention and control period represent both a critical challenge and key focus area in managing rubber-tree powdery mildew. This study investigates the effects of spore concentration, environmental factors, and infection time on the progression of powdery mildew in rubber trees. By employing six distinct machine learning model construction methods, with the disease index of powdery mildew in rubber trees as the response variable and spore concentration, temperature, humidity, and infection time as predictive variables, a preliminary predictive model for the disease index of rubber-tree powdery mildew was developed. Results from indoor inoculation experiments indicate that spore concentration directly influences disease progression and severity. Higher spore concentrations lead to faster disease development and increased severity. The optimal relative humidity for powdery mildew development in rubber trees is 80% RH. At varying temperatures, the influence of humidity on the disease index differs across spore concentration, exhibiting distinct trends. Each model effectively simulates the progression of powdery mildew in rubber trees, with predicted values closely aligning with observed data. Among the models, the Kernel Ridge Regression (KRR) model demonstrates the highest accuracy, the R² values for the training set and test set were 0.978 and 0.964, respectively, while the RMSE values were 4.037 and 4.926, respectively. This research provides a robust technical foundation for reducing the labor intensity of traditional prediction methods and offers valuable insights for forecasting airborne forest diseases. Full article

The objectives of this study were to prepare whey protein–quercetin–gellan gum conjugates using the pH-shift method and to evaluate the impacts of varying pH values and quercetin concentrations on the interaction mechanisms and functional characteristics of the complexes. Spectroscopic analyses (fluorescence, UV-vis, and FT-IR) revealed that new complexes formed under alkaline conditions. Notably, an increasing quercetin concentration led to a reduction in complex particle size and an increase in the zeta potential value, with these effects being more pronounced under alkaline conditions. The particle size was 425.7 nm, and the zeta potential value was −30.00 mV at a quercetin addition concentration of 15 umol/g protein. Additionally, the complexes formed under alkaline conditions exhibited superior foaming capacity, emulsification properties, and significantly enhanced free radical scavenging activity. The complex’s DPPH and ABTS radical scavenging rates rose by 41.57% and 57.69%, respectively. This study provides theoretical foundations and practical insights for developing protein—polyphenol systems, offering significant implications for the application of quercetin functional foods and supplements in the food science and pharmaceutical industries. Full article

Quasi-solid aqueous zinc batteries (QSAZBs) have wide applications in the energy storage field due to their advantages of high safety, cost-effectiveness, and eco-friendliness. Despite prolific research output in the field of QSAZBs, existing reviews predominantly focus on experimental advancements, with limited synthesis of global research trends, interdisciplinary connections, or knowledge gaps. Herein, we review the research on QSAZBs via bibliometric analysis using the VOSviewer software (version 1.6.20). First, the data from qualitatively evaluated publications on QSAZBs from 2016 and 2024 are integrated. In addition, the annual trends, leading countries/regions and their international collaborations, institutional research and patent distribution, and important keyword cluster analyses in QSAZB research are evaluated. The results reveal that China dominates in terms of publication output (71.16% of total papers), and Singapore exhibits the highest citation impact (103.2 citations/paper). International collaboration networks indicate the central role of China, with strong ties to Singapore, the USA, and Australia. Keyword clustering indicates core research priorities: cathode materials (MnO₂ and V₂O₅), quasi-solid electrolyte optimization (hydrogels and graphene composites), and interfacial stability mechanisms. By mapping global trends and interdisciplinary linkages, this work provides insights to accelerate QSAZBs’ transition from laboratory breakthroughs to grid-scale and wearable applications. Full article