Search Results (18)

The increasingly serious imbalance between the supply and demand of water resources necessitates the establishment of a scientific and reasonable comprehensive evaluation method for industrial water use efficiency (WUE). In this study, a general method for industrial WUE evaluation on an enterprise scale was proposed by combining the analytic hierarchy process (AHP), entropy weight method (EWM), and self-organizing map (SOM), and it was tested in several areas of Zhejiang Province, China. The results show that the composite indexes generated using the AHP and EWM were different and were employed as the input of the SOM to divide enterprises into four categories. Most enterprises were classified as Class A, with a relatively high WUE, accounting for 82.5% of the total, while those in Class D, with a relatively low WUE, only accounted for 0.5% of the total. Furthermore, the differences in WUE for industry classification and spatial distribution were also analyzed. The classification results of several industries were more diverse, especially for those industries in which water plays an important role in production. Moreover, the spatial distribution of WUE classifications also implied that the clustering of enterprises has a positive effect on the improvement in WUE. In other words, it is feasible to improve WUE through industry clustering and sub-industry management. In summary, a comprehensive, detailed evaluation of industrial WUE was conducted on an enterprise scale, which can also be applied to other areas and used as a reference for local water resource managers for formulating targeted policies. Full article

The giant panda, a rare and iconic species endemic to China, has attracted significant attention from both domestic and international researchers due to its crucial ecological role, unique cultural value, and distinct evolutionary history. While substantial progress has been made in the field of individual identification, behavior recognition remains underdeveloped, facing challenges such as the lack of dynamic temporal features and insufficient extraction of behavioral characteristics. To address these challenges, we propose the Swin-Panda model, which leverages transfer learning based on the Video Swin Transformer architecture within the mmaction2 framework. In addition, we introduce two novel modules: the Comprehensive Perception Auxiliary Module and the Spatiotemporal Shift Attention Module. These modules facilitate the extraction of local and spatiotemporal information, allowing the model to more effectively capture the behavioral and movement patterns of giant pandas. Experimental results on the PACV-8 dataset demonstrate that our model achieves an accuracy of 88.02%, outperforming several benchmark models. This approach significantly enhances behavior recognition accuracy, thereby contributing to the advancement of panda welfare and species conservation efforts. Full article

Given the increasing importance of effectively identifying synergistic changes between PM_2.5 and O₃ and comprehensively analyzing their impact on air quality management in China, we employ the Sen+Mann–Kendall (Sen+M-K) trend test in this study to examine the temporal and spatial variation trends of PM_2.5 and O₃ in the Yangtze River Delta (YRD), from 2003 to 2020. We identified the regions where these pollutants exhibited synergistic changes and established the pathways between the pollutants and their potential drivers, using geographically weighted random forest algorithms and structural equation modeling. The study results revealed as follows: (1) Overall, the PM_2.5 concentrations show a decreasing trend, while the O₃ concentrations exhibit an increasing trend, in the YRD. Analysis of the combined trends indicates that approximately 95% of the area displays opposing trends for PM_2.5 and O₃, with only about 4% in the southern region showing synergistic trends for both pollutants. (2) Drought and the average temperature are the main drivers of the changes in PM_2.5 and O₃ concentrations in areas experiencing synergistic changes. Their combined effects alleviate the aggregation of PM_2.5 and reduce the formation of VOCs, indirectly reducing the generation of pollutants. The negative effect of the average temperature on the O₃ concentration may indicate the existence of nonlinear effects and complex interaction effects between the drivers. NO_x and VOCs play important dual roles in the generation and conversion of pollutants, although their overall impact is smaller than meteorological factors. They produce significant indirect effects through their interaction with meteorological and other human factors, further affecting the concentrations of PM_2.5 and O₃. In areas without coordinated changes, the main impact of meteorological factors remains unchanged, and the relationship between the two anthropogenic emission sources and their effects on PM_2.5 and O₃ are complex, with different directions and levels involved. This study provides detailed insights into the drivers of air quality changes in the YRD and offers a scientific basis for environmental management authorities to develop more comprehensive and targeted strategies for balancing the control of PM_2.5 and O₃ pollution. Full article

To understand the influences of emulsified fuel on ship exhaust emissions more comprehensively, the emissions of particulate matter (PM), nitrated, oxygenated and parent polycyclic aromatic hydrocarbons (PAHs) were studied on a ship main engine burning emulsified heavy fuel oil (EHFO) and heavy fuel oil (HFO) as a reference. The results demonstrate that EHFO (emulsified heavy fuel oil) exhibits notable abilities to significantly reduce emissions of particulate matter (PM) and low molecular weight PAHs (polycyclic aromatic hydrocarbons) in the gas phase, particularly showcasing maximum reductions of 13.99% and 40.5%, respectively. Nevertheless, burning EHFO could increase the emission of high molecular weight PAHs in fine particles and pose a consequent higher carcinogenic risk for individual particles. The total average (gaseous plus particulate) ΣBEQ of EHFO exhausts (41.5 μg/m³) was generally higher than that of HFO exhausts (18.7 μg/m³). Additionally, the combustion of EHFO (extra-heavy fuel oil) can significantly alter the emission quantity, composition, and particle-size distribution of PAH derivatives. These changes may be linked to molecular structures, such as zigzag configurations in C=O bonds. Our findings may favor the comprehensive environmental assessments on the onboard application of EHFO. Full article

Forming solid solutions is one of the most effective strategies to suppress the thermal conductivity of thermoelectric materials. However, the accompanying increase in impurity ion scattering usually results in an undesirable loss in hall mobility, negatively impacting the electrical transport properties. In this work, a tellurium–selenium (Te-Se) solid solution with trace antimony (Sb) doping was synthesized via the high pressure and high temperature method. It was found that slight Se doping into the Te sites not only had no impact on the hall mobility and carrier concentration, but also enhanced the density-of-state effective mass of Sb_0.003Te_0.997, leading to an enhanced power factor near room temperature. Additionally, the presence of Se doping caused a significant reduction in the phonon thermal conductivity of Te due to fluctuations in the mass and strain field. The lowest phonon thermal conductivity was as low as ~0.42 Wm⁻¹K⁻¹ at 600 K for Sb_0.003Se_0.025Te_0.972, which approached the theoretical minimum value of Te (~0.28 Wm⁻¹K⁻¹). The effects of Se doping suppressed thermal conductivity, while Sb doping enhanced the power factor, resulting in a larger ZT of ~0.94 at 600 K. Moreover, these findings demonstrate that Sb and Se doping can effectively modulate the electrical and thermal transport properties of Te in a synergistic manner, leading to a significant increase in the average ZT across a wide temperature range. Full article

The objective of this study was to evaluate the discriminative capabilities of radiomics signatures derived from three distinct machine learning algorithms and to identify a robust radiomics signature capable of predicting pathological complete response (pCR) after neoadjuvant chemoradiotherapy in patients diagnosed with locally advanced rectal cancer (LARC). In a retrospective study, 211 LARC patients were consecutively enrolled and divided into a training cohort (n = 148) and a validation cohort (n = 63). From pretreatment contrast-enhanced planning CT images, a total of 851 radiomics features were extracted. Feature selection and radiomics score (Radscore) construction were performed using three different machine learning methods: least absolute shrinkage and selection operator (LASSO), random forest (RF) and support vector machine (SVM). The SVM-derived Radscore demonstrated a strong correlation with the pCR status, yielding area under the receiver operating characteristic curves (AUCs) of 0.880 and 0.830 in the training and validation cohorts, respectively, outperforming the RF and LASSO methods. Based on this, a nomogram was developed by combining the SVM-based Radscore with clinical indicators to predict pCR after neoadjuvant chemoradiotherapy. The nomogram exhibited superior predictive power, achieving AUCs of 0.910 and 0.866 in the training and validation cohorts, respectively. Calibration curves and decision curve analyses confirmed its appropriateness. The SVM-based Radscore demonstrated promising performance in predicting pCR for LARC patients. The machine learning-driven nomogram, which integrates the Radscore and clinical indicators, represents a valuable tool for predicting pCR in LARC patients. Full article

Background: Abnormal accumulation of lipids is found in dopamine neurons and resident microglia in the substantia nigra of patients with Parkinson’s disease (PD). The accumulation of lipids is an important risk factor for PD. Previous studies have mainly focussed on lipid metabolism in peripheral blood, but little attention has been given to cerebrospinal fluid (CSF). We drew the lipidomic signature in CSF from PD patients and evaluated the role of lipids in CSF as biomarkers for PD diagnosis. Methods: Based on lipidomic approaches, we investigated and compared lipid metabolism in CSF from PD patients and healthy controls without dyslipidaemia in peripheral blood and explored the relationship of lipids between CSF and serum by Pearson correlation analysis. Results: A total of 231 lipid species were detected and classified into 13 families in the CSF. The lipid families, including phosphatidylcholine (PC), sphingomyelin (SM) and cholesterol ester (CE), had significantly increased expression compared with the control. Hierarchical clustering was performed to distinguish PD patients based on the significantly changed expression of 34 lipid species. Unsupervised and supervised methods were used to refine this classification. A total of 12 lipid species, including 3-hydroxy-dodecanoyl-carnitine, Cer(d18:1/24:1), CE(20:4), CE(22:6), PC(14:0/18:2), PC(O-18:3/20:2), PC(O-20:2/24:3), SM(d18:0/16:0), SM(d18:2/14:0), SM(d18:2/24:1), SM(d18:1/20:1) and SM(d18:1/12:0), were selected to draw the lipidomic signature of PD. Correlation analysis was performed and showed that the CE family and CE (22:6) in CSF had a positive association with total cholesterol in the peripheral blood from PD patients but not from healthy controls. Conclusions: Our results revealed that the lipidomic signature in CSF may be considered a potential biomarker for PD diagnosis, and increased CE, PC and SM in CSF may reveal pathological changes in PD patients, such as blood–brain barrier leakage. Full article

Establishing an efficient PM_2.5 prediction model and in-depth knowledge of the relationship between the predictors and PM_2.5 in the model are of great significance for preventing and controlling PM_2.5 pollution and policy formulation in the Yangtze River Delta (YRD) where there is serious air pollution. In this study, the spatial pattern of PM_2.5 concentration in the YRD during 2003–2019 was analyzed by Hot Spot Analysis. We employed five algorithms to train, verify, and test 17 years of data in the YRD, and we explored the drivers of PM_2.5 exposure. Our key results demonstrated: (1) High PM_2.5 pollution in the YRD was concentrated in the western and northwestern regions and remained stable for 17 years. Compared to 2003, PM_2.5 increased by 10–20% in the southeast, southwest, and western regions in 2019. The hot spot for percentage change of PM_2.5 was mostly located in the southwest and southeast regions in 2019, while the interannual change showed a changeable spatial distribution pattern. (2) Geographically Weighted Random Forest (GWRF) has great advantages in predicting the presence of PM_2.5 in comparison with other models. GWRF not only improves the performance of RF, but also spatializes the interpretation of variables. (3) Climate and human activities are the most important drivers of PM_2.5 concentration. Drought, temperature, and temperature difference are the most critical and potentially threatening climatic factors for the increase and expansion of PM_2.5 in the YRD. With the warming and drying trend worldwide, this finding can help policymakers better consider these factors for PM_2.5 prediction. Moreover, the effect of interference from humans on ecosystems will increase again after COVID-19, leading to a rise in PM_2.5 concentration. The strong explanatory power of comprehensive ecological indicators for the distribution of PM_2.5 will be a crucial indicator worthy of consideration by decision-making departments. Full article

Bio-oil emulsions were stabilized using coconut shell coke, modified amphiphilic graphene oxide, and hydrophobic nano-fumed silica as solid emulsifiers. The effects of different particles on the stability of bio-oil emulsions were discussed. Over 21 days, the average droplet size of raw bio-oil increased by 64.78%, while that of bio-oil Pickering emulsion stabilized by three particles only changed within 20%. The bio-oil Pickering emulsion stabilized by Ni/SiO₂ was then used for catalytic hydrodeoxygenation. It was found that the bio-oil undergoes polymerization during catalytic hydrogenation. For raw bio-oil hydrodeoxygenation, the polymerization reaction was little affected by the temperature below 200 °C, but when the temperature raised to 250 °C, it was greatly accelerated. However, the polymerization of monocyclic aromatic compounds in the reaction process was partially inhibited under the bio-oil Pickering emulsion system. Additionally, a GC-MS analysis was performed on raw bio-oil and hydrodeoxygenated bio-oil to compare the change in GC-MS-detectable components after hydrodeoxygenation at 200 °C. The results showed that the Pickering emulsion catalytic system greatly promoted the hydrodeoxygenation of phenolic compounds in bio-oil, with most monocyclic phenolic compounds detected by GC-MS converting to near 100%. Full article

In this work, carbon submicron fiber composites loaded with a cobalt-ferric alloy and cobalt-ferric binary metal compounds were prepared by electrospinning and high temperature annealing using cobalt-ferric acetone and ferric acetone as precursors and polyacrylonitrile as a carbon source. The phase transformation mechanism of the carbon submicron fiber-supported Co-Fe bimetallic compound during high temperature annealing was investigated. The electrochemical properties of the carbon submicron fiber-supported Co-Fe alloy and Co-Fe oxide self-supported electrode materials were investigated. The results show that at 138 °C, the heterogeneous submicron fibers of cobalt acetylacetonate and acetylacetone iron began to decompose and at 200 °C, CoFe₂O₄ was generated in the fiber. As the annealing temperature increases further, some metal compounds in the carbon fiber are reduced to CoFe₂O₄ alloy, and two phases of CoFe₂O₄ and CoFe-Fe-alloy exist in the fiber. After 200 cycles, the specific capacity of CF-P500 is 500 mAh g⁻¹. The specific capacity of the composite carbon submicron fiber electrode material can be significantly improved by the introduction of CoFe₂O₄. When the binary metal oxides are used as electrode materials for lithium-ion batteries, alloy dealloying and conversion reactions can occur at the same time in the reverse process of lithium intercalation, the two reactions form a synergistic effect, and the cobalt-iron alloy in the material increases the electrical conductivity. Therefore, the carbon submicron fiber loaded with CoFe₂O₄/CoFe has an excellent electrochemical performance. Full article

(1) Background: To evaluate the efficacy and safety of combined surgery (limited pars plana vitrectomy, anterior-chamber stabilized phacoemulsification, IOL implantation and posterior capsulotomy, LPPV + ACSP + IOL + PC) in complex nanophthalmos. (2) Methods: Patients with complex nanophthalmos were recruited to undergo LPPV + ACSP + IOL + PC from January 2017 to February 2021. Preoperative and post-operative intraocular pressure (IOP), best corrected visual acuity (BCVA), anterior chamber depth (ACD), and number of glaucoma medications were compared using the paired t-test or Wilcoxon signed rank sum tests. Surgical success rate was evaluated. Surgery-associated complications were documented. (3) Results: Forty-five eyes of 37 patients with complex nanophthalmos were enrolled. The mean follow-up period was 21.7 ± 10.6 months after surgery. Mean IOP decreased from 32.7 ± 8.7 mmHg before surgery to 16.9 ± 4.5 mmHg (p < 0.001) at the final follow-up visit, mean logMAR BCVA improved from 1.28 ± 0.64 to 0.96 ± 0.44 (p < 0.001), mean ACD significantly increased from 1.14 ± 0.51 mm to 3.07 ± 0.66 mm (p < 0.001), and the median number of glaucoma medications dropped from 3 (1, 4) to 2 (0, 4) (p < 0.001). The success rate was 88.9% (40 eyes) at the final follow-up visit. Two eyes had localized choroidal detachments which resolved with medical treatment. (4) Conclusions: LPPV + ACSP + IOL + PC is a safe and effective surgical procedure, which can decrease IOP, improve BCVA, deepen the anterior chamber, and reduce the number of glaucoma medications in patients with complex nanophthalmos. It can be considered as one of the first treatment in nanophthalmic eyes with complex conditions. Full article

Currently, many microchips must rely on an external force (such as syringe pump, electro-hydrodynamic pump, and peristaltic pump, etc.) to control the solution in the microchannels, which probably adds manual operating errors, affects the accuracy of fluid manipulation, and enlarges the noise of signal. In addition, the reasonable integration of micropump and microchip remain the stumbling block for the commercialization of microfluidic technique. To solve those two problems, we designed and fabricated a thermal bubble micropump based on MEMS (micro-electro-mechanical systems) technique. Many parameters (voltage, pulse time, cycle delay time, etc.) affecting the performance of this micropump were explored in this work. The experimental results showed the flow rate of solution with the assistance of a micropump reached more than 15 μL/min in the optimal condition. Finally, a method about measuring total aflatoxin in Chinese herbs was successfully developed based on the integrated platform contained competitive immunoassay and our micropump-based microfluidics. Additionally, the limit of detection in quantifying total aflatoxin (AF) was 0.0615 pg/mL in this platform. The data indicate this combined technique of biochemical assays and micropump based microchip have huge potential in automatically, rapidly, and sensitively measuring other low concentration of biochemical samples with small volume. Full article

Thyroid dysfunction and inflammation are individually implicated in the increased risk of heart failure. Given the regulatory role of thyroid hormones on immune cells, this study aimed to investigate their joint association in heart failure. Patients with pre-existing heart failure were enrolled when hospitalized between July 2019 and September 2021. Thyroid function and inflammatory markers were measured at the enrollment. The composite of all-cause mortality or rehospitalization for heart failure were studied in the following year. Among 451 participants (mean age 66.1 years, 69.4% male), 141 incident primary endpoints were observed during a median follow-up of 289 days. TT3 and FT3 levels were negatively correlated with BNP levels (r: −0.40, p < 0.001; r: −0.40, p < 0.001, respectively) and NT-proBNP levels (r: −0.39, p < 0.001; r: −0.39, p < 0.001). Multivariate COX regression analysis revealed that FT3 (adjusted HR: 0.677, 95% CI: 0.551–0.832) and NLR (adjusted HR: 1.073, 95% CI: 1.036–1.111) were associated with adverse event, and similar results for TT3 (adjusted HR: 0.320, 95% CI: 0.181–0.565) and NLR (adjusted HR: 1.072, 95% CI: 1.035–1.110). Restricted cubic splines analysis indicated a linear relationship between T3 level and adverse events. Mechanistically, primary cardiomyocytes showed strong resistance to TNF-α induced apoptosis under optimal T3 concentrations, as evidenced by TUNEL staining, flow cytometry analysis, and LDH release assay as well as increased expression of Bcl-2. Thyroid dysfunction and inflammation are independently associated with cardiovascular risk in heart failure patients, which may concurrently contribute to the ongoing cardiomyocyte loss in the disease progression. Full article

It is of great significance to understand the drivers of PM_2.5 and fire carbon emission (FCE) and the relationship between them for the prevention, control, and policy formulation of severe PM_2.5 exposure in areas where biomass burning is a major source. In this study, we considered northern Laos as the area of research, and we utilized space cluster analysis to present the spatial pattern of PM_2.5 and FCE from 2003–2019. With the use of a random forest and structural equation model, we explored the relationship between PM_2.5 and FCE and their drivers. The key results during the target period of the study were as follows: (1) the HH (high/high) clusters of PM_2.5 concentration and FCE were very similar and distributed in the west of the study area; (2) compared with the contribution of climate variables, the contribution of FCE to PM_2.5 was weak but statistically significant. The standardized coefficients were 0.5 for drought index, 0.32 for diurnal temperature range, and 0.22 for FCE; (3) climate factors are the main drivers of PM_2.5 and FCE in northern Laos, among which drought and diurnal temperature range are the most influential factors. We believe that, as the heat intensifies driven by climate in tropical rainforests, this exploration and discovery can help regulators and researchers better integrate drought and diurnal temperature range into FCE and PM_2.5 predictive models in order to develop effective measures to prevent and control air pollution in areas affected by biomass combustion. Full article

Objectives: To characterize the microflora profile of supragingival biofilm in patients with and without full-crown prostheses. Methods: Plaque samples of full-crown prostheses and teeth in patients with porcelain-fused-to-metal crowns, all-ceramic crowns, and no prostheses were collected (three patients per group), using 16S rRNA high-throughput sequencing technology to conduct DNA sequencing on the samples and using Qiime, R, and PICRUSt2 software to perform bioinformatics analyses and functional analyses on sequencing data. Results: In total, 110,209 valid sequences were obtained in the experiment, corresponding to 11 phyla and 120 genera. The predominant species shared by the three groups were phyla Actinobacteria, Bacteroidetes, Firmicutes, Fusobacteria, and Proteobacteria and genera Rothia, Porphyromonas, Prevotella, Streptococcus, Veillonella, Leptotrichia, Neisseria, Citrobacter, and Pseudomonas. The species-difference analysis showed that genus Hameophilus significantly increased after the patient wore the dental prosthesis. Compared with the no-prosthesis samples, the functional analysis showed that cell motility increased in the samples from full-crown prostheses, while replication and repair, and translation decreased. Conclusions: This study reveals the changes in the oral microbial community of patients with full-crown prostheses, which could provide insights regarding the safety of materials for long-term use in the oral cavity. Full article