Intercalating Organic Hybrid Cadmium Antimony Sulfide Nanoparticles into Graphene Oxide Nanosheets for Electrochemical Lithium Storage.

Inorganic metal sulfides have received extensive investigation as anode materials in lithium-ion batteries (LIBs). However, applications of crystalline organic hybrid metal sulfides as anode materials in LIBs are quite rare. In addition, combining the nanoparticles of crystalline organic hybrid metal sulfides with conductive materials is expected to enhance the electrochemical lithium storage performance. Nevertheless, due to the difficulty of harvesting the nanoparticles of crystalline organic hybrid metal sulfides, this approach has never been tried to date. Herein, nanoparticles of a crystalline organic hybrid cadmium antimony sulfide (1,4-DABH2)Cd2Sb2S6 (DCAS) were prepared by a top-down method, including the procedures of solvothermal synthesis, ball milling, and ultrasonic pulverization. Thereafter, the nanoparticles of DCAS with sizes of ∼500 nm were intercalated into graphene oxide nanosheets through a freeze-drying treatment and a DCAS@GO composite was obtained. Compared with the reported Sb2S3- and CdS-based composites, the DCAS@GO composite exhibited superior electrochemical Li+ ion storage performance, including a high capacity of 1075.6 mAh g-1 at 100 mA g-1 and exceptional rate tolerances (646.8 mAh g-1 at 5000 mA g-1). In addition, DCAS@GO can provide a high capacity of 705.6 mAh g-1 after 500 cycles at 1000 mA g-1. Our research offers a viable approach for preparing the nanoparticles of crystalline organic hybrid metal sulfides and proves that intercalating organic hybrid metal sulfide nanoparticles into GO nanosheets can efficiently boost the electrochemical Li+ ion storage performance.

OLB-AC: toward optimizing ligand bioactivities through deep graph learning and activity cliffs.

MOTIVATION: Deep graph learning (DGL) has been widely employed in the realm of ligand-based virtual screening. Within this field, a key hurdle is the existence of activity cliffs (ACs), where minor chemical alterations can lead to significant changes in bioactivity. In response, several DGL models have been developed to enhance ligand bioactivity prediction in the presence of ACs. Yet, there remains a largely unexplored opportunity within ACs for optimizing ligand bioactivity, making it an area ripe for further investigation. RESULTS: We present a novel approach to simultaneously predict and optimize ligand bioactivities through DGL and ACs (OLB-AC). OLB-AC possesses the capability to optimize ligand molecules located near ACs, providing a direct reference for optimizing ligand bioactivities with the matching of original ligands. To accomplish this, a novel attentive graph reconstruction neural network and ligand optimization scheme are proposed. Attentive graph reconstruction neural network reconstructs original ligands and optimizes them through adversarial representations derived from their bioactivity prediction process. Experimental results on nine drug targets reveal that out of the 667 molecules generated through OLB-AC optimization on datasets comprising 974 low-activity, noninhibitor, or highly toxic ligands, 49 are recognized as known highly active, inhibitor, or nontoxic ligands beyond the datasets' scope. The 27 out of 49 matched molecular pairs generated by OLB-AC reveal novel transformations not present in their training sets. The adversarial representations employed for ligand optimization originate from the gradients of bioactivity predictions. Therefore, we also assess OLB-AC's prediction accuracy across 33 different bioactivity datasets. Results show that OLB-AC achieves the best Pearson correlation coefficient (r2) on 27/33 datasets, with an average improvement of 7.2%-22.9% against the state-of-the-art bioactivity prediction methods. AVAILABILITY AND IMPLEMENTATION: The code and dataset developed in this work are available at github.com/Yueming-Yin/OLB-AC.

Local feature acquisition and global context understanding network for very high-resolution land cover classification.

Very high-resolution remote sensing images hold promising applications in ground observation tasks, paving the way for highly competitive solutions using image processing techniques for land cover classification. To address the challenges faced by convolutional neural network (CNNs) in exploring contextual information in remote sensing image land cover classification and the limitations of vision transformer (ViT) series in effectively capturing local details and spatial information, we propose a local feature acquisition and global context understanding network (LFAGCU). Specifically, we design a multidimensional and multichannel convolutional module to construct a local feature extractor aimed at capturing local information and spatial relationships within images. Simultaneously, we introduce a global feature learning module that utilizes multiple sets of multi-head attention mechanisms for modeling global semantic information, abstracting the overall feature representation of remote sensing images. Validation, comparative analyses, and ablation experiments conducted on three different scales of publicly available datasets demonstrate the effectiveness and generalization capability of the LFAGCU method. Results show its effectiveness in locating category attribute information related to remote sensing areas and its exceptional generalization capability. Code is available at https://github.com/lzp-lkd/LFAGCU .

The Effects of Hydroxypropyl Methyl Cellulose and Metakaolin on the Properties of Self-Compacting Solidified Soil Based on Abandoned Slurry.

As a new type of backfill material, Self-compacting solidified soil (SCSS) takes the abandoned slurry of cast-in-place piles after dewatering and reduction as the main raw material, which brings a problem of coordinating the working performance with the mechanical property under the condition of high mobility. In this paper, hydroxypropyl methyl cellulose (HPMC) and metakaolin were introduced as additives to solve this problem. First, the workability and mechanical properties of SCSS were regulated and optimized by means of the water seepage rate test, the flowability test, and the unconfined compressive strength test. Second, this study also used X-ray diffraction (XRD) and scanning electron microscopy (SEM) to investigate the effects of HPMC and metakaolin on the physical phase and microstructure of SCSS. In this way, the results showed that there was a significant impact on the flowability of SCSS, that is, when the dosage reached 0.3%, the water seepage rate of SCSS was reduced to less than 1%, and the compressive strength at 7 days reached its peak. At the same time, HPMC weakened the strength growth of SCSS in the age period of 7 days to 14 days. However, the addition of metakaolin promoted its compressive strength. XRD analysis showed that the additives had no significant effects on the physical phases. And, from the SEM results, it can be seen that although the water-retaining effect of HPMC makes hydration of cement more exhaustive, more ettringite (AFt) can be observed in the microstructure. In addition, it can be observed that the addition of metakaolin can generate more hydrated calcium silicate (C-S-H) due to the strong surface energy possessed by metakaolin. As a result of the above factors, SCSS filled the voids between particles and improved the interface structure between particles, thus enhanced the compressive strength.

Achieving High Ionic Conductivity and Mechanical Strength by a Leather Gel Electrolyte for Flexible Zinc-Ion Batteries.

The continuous advancement in the field of flexible and wearable electronics has led to increased research interest in safe, low-cost, and flexible zinc-ion batteries, particularly with a focus on flexible electrolytes. In this study, we present a leather gel electrolyte (LGE) that offers robust mechanical properties and an excellent electrochemical performance. LGE exhibits an ionic conductivity of 1.36 × 10-2 S cm-1 and achieves a capacity of 303.7 mAh g-1 in flexible zinc-manganese dioxide batteries. Even after 1000 cycles, the capacity retention remains above 90%, demonstrating outstanding performance in protecting the zinc anode. Furthermore, such a flexible battery shows good resistance to damage due to the strong mechanical strength originating from leather. Notably, LGE utilizes green and sustainable leather as a raw material, making it a promising option for sustainable flexible devices.

Prussian blue analogue derived from leather waste as a bifunctional catalyst in zinc-air batteries.

A Prussian blue analogue was synthesized using biomass leather waste as a precursor by doping with Co2+ ions. This material, demonstrates good performance in both the oxygen reduction reaction and oxygen evolution reaction, and exhibits excellent charge-discharge performance and stability in zinc-air batteries.

Does settlement land expansion necessarily induce the decrease of cultivated land? Differences in national scale and local counties of China.

With the extensive industrialization and urbanization taking place in China during the recent decades, land use throughout the country has experienced profound changes influenced not only by the demand for population growth and living standard improvement but also by the constraints of series of land use policies. However, whether the conflict between the expansion of settlement land (SL) and the loss of cultivated land (CL) have been resolved at the national scale or transferred between the local regions remains unclear. Based on yearly ESA CCI land use and land cover products from 1992 to 2020, the long-term trends of quantity and spatial pattern of SL expansion and CL change in China from national and local views were investigated using trend statistic methods, and finally a comprehensive zoning framework was proposed to recognize the trade-off and synergies relationships between SL expansion and CL change. There are a continuous expansion of SL with global linear trends showing three breakpoints in 2000, 2005, and 2012, and a fluctuation decline of CL presented with four breakpoints in 1997, 2002, 2006, and 2013. Aggregation and dispersion tendencies with linear characteristics of SL expansion and CL change were found with breakpoints in 2001, 2008, 2012, and 2016 and breakpoints in 2001 and 2010, respectively. A spotty spatial pattern of SL was shown spatially coincident with urban agglomerations in China while the planar continuous characteristic was found for CL. Local counties were classified into five tradeoff and synergies zones (TSZs), where general synergies (G-S) and decoupling (D) of SL expansion and CL change were rare cases and the different change in quantity and trend of SL expansion and CL change in local counties was concealed by the national trend. A few scattered counties were belonging to G-S and D TSZs, while most of the counties in the central-east and western China were in General-Tradeoff (G-T) and Superior-Tradeoff (S-T) TSZs. Counties in south and north China with higher percentages of CL were more prevalent in Superior-Synergy (S-S) TSZ. Our findings explicated the complex relationships between SL expansion and CL change of China at the national scale and in local counties, which pointed out the differences of unified land use management activities across scales and could provide insights for future policy-making and management measures of land use to both ensure the national food security and promote regional sustainable development more synchronously.

AviTrap: A novel solution to achieve complete biotinylation.

Site specific biotinylation of AviTagged recombinant proteins using BirA enzyme is a widely used protein labeling technology. However, due to the incomplete biotinylation reactions and the lack of a purification method specific for the biotinylated proteins, it is challenging to purify the biotinylated sample when mixed with the non-biotinylated byproduct. Here, we have developed a monoclonal antibody that specifically recognizes the non-biotinylated AviTag but not the biotinylated sequence. After a ten-minute incubation with the resin that is conjugated with the antibody, the non-biotinylated AviTagged protein is trapped on the resin while the fully biotinylated material freely passes through. Therefore, our AviTrap (anti-AviTag antibody conjugated resin) provides an efficient solution for enriching biotinylated AviTagged proteins via a simple one-step purification.

Canonical AREs are tumor suppressive regulatory elements in the prostate.

The androgen receptor (AR) is the central determinant of prostate tissue identity and differentiation, controlling normal, growth-suppressive prostate-specific gene expression 1 . It is also a key driver of prostate tumorigenesis, becoming "hijacked" to drive oncogenic transcription 2-5 . However, the regulatory elements determining the execution of the growth suppressive AR transcriptional program, and whether this can be reactivated in prostate cancer (PCa) cells remains unclear. Canonical androgen response element (ARE) motifs are the classic DNA binding element for AR 6 . Here, we used a genome-wide strategy to modulate regulatory elements containing AREs to define distinct AR transcriptional programs. We find that activation of these AREs is specifically associated with differentiation and growth suppressive transcription, and this can be reactivated to cause death in AR + PCa cells. In contrast, repression of AREs is well tolerated by PCa cells, but deleterious to normal prostate cells. Finally, gene expression signatures driven by ARE activity are associated with improved prognosis and luminal phenotypes in human PCa patients. This study demonstrates that canonical AREs are responsible for a normal, growth-suppressive, lineage-specific transcriptional program, that this can be reengaged in PCa cells for potential therapeutic benefit, and genes controlled by this mechanism are clinically relevant in human PCa patients.

Proportional feature pyramid network based on weight fusion for lane detection.

Lane detection under extreme conditions presents a highly challenging task that requires capturing each crucial pixel to predict the complex topology of lane lines and differentiate the various lane types. Existing methods predominantly rely on deep feature extraction networks with substantial parameters or the fusion of multiple prediction modules, resulting in large model sizes, embedding difficulties, and slow detection speeds. This article proposes a Proportional Feature Pyramid Network (P-FPN) through fusing the weights into the FPN for lane detection. For obtaining a more accurately detecting result, the cross refinement block is introduced in the P-FPN network. The cross refinement block takes the feature maps and anchors as inputs and gradually refines the anchors from high to low level feature maps. In our method, the high-level features are explored to predict lanes coarsely while local-detailed features are leveraged to improve localization accuracy. Extensive experiments on two widely used lane detection datasets, The Chinese Urban Scene Benchmark for Lane Detection (CULane) and the TuSimple Lane Detection Challenge (TuSimple) datasets, demonstrate that the proposed method achieves competitive results compared with several state-of-the-art approaches.

Guidelines and treatment patterns for primary rhegmatogenous retinal detachments: Expert consensus and survey in Taiwan Retina Society.

Rhegmatogenous retinal detachment (RRD) is a significant cause of vision loss and requires appropriate surgical intervention. There are several approaches available, including observation, laser demarcation, pneumatic retinopexy, scleral buckling, and pars plana vitrectomy, which are chosen based on patient condition, surgeon experience, and national health insurance policies. Despite the various options, there is still no consensus on the optimal intervention. To address this, the Taiwan Retina Society assembled an expert committee with 11 experienced retina specialists to review the current evidence and develop a guideline with seven recommendations for managing RRD patients. Additionally, a survey was conducted with six questions to assess treatment patterns in Taiwan, which included input from the expert committee and an open poll at the 2023 Congress of the Taiwan Retina Society. This report provides a comprehensive summary of the current knowledge and expert consensus on the treatment of RRD, discussing the characteristics of current approaches and providing an overview of current treatment patterns in Taiwan. These findings aim to provide ophthalmologists with the best possible treatment for RRD.

Clinical features of macular telangiectasia type 2 and comparison of staging system in Taiwanese patients.

PURPOSE: The purpose of this study is to report the clinical characteristics of macular telangiectasia type 2 (MacTel 2) in Taiwan. MATERIALS AND METHODS: Retrospective analysis of patients diagnosed with MacTel 2 over a 7-year period in Changhua Christian Hospital. Best-corrected visual acuity (BCVA), fundus photography, fluorescein angiography, optical coherence tomography (OCT), and OCT angiography (OCTA) images were reviewed. Differences in BCVA and central macular thickness (CMT) were compared between the initial/baseline and final visits. The staging was performed according to the Gass and Blodi classification and OCTA. RESULTS: There were 38 eyes in 19 patients were collected (Male: Female = 5:14). The mean age at diagnosis was 65.90 ± 8.26 years and the follow-up duration was 39.26 ± 28.31 months. All patients had both eyes affected, and eight of the 19 patients had a history of diabetes mellitus (DM). The mean initial logarithm of the minimum angle of resolution (logMAR) BCVA was 0.40 ± 0.31 and the mean final logMAR BCVA was 0.61 ± 0.53. Difference of BCVA equal or more than two lines between both eyes was noted in 63.1% (12 of 19) of patients at the initial visit and in 78.9% (15 of 19) of patients at the final follow-up. The mean CMT was 224.42 ± 38.50 µm at baseline and 222.05 ± 40.27 µm at the final visit. OCT illustrated macular hole in three eyes of three patients. At the final follow-up, retinal-choroidal anastomosis was noted in 17 eyes. Subretinal neovascularization (SRNV) was not present in any eye. CONCLUSION: Bilateral involvement, asymmetrical BCVA in both eyes, low incidence of SRNV, and high prevalence of DM were characteristics of patients of MacTel 2 in Taiwan.

Modified early intensive and treat-and-extend regimen of anti-vascular endothelial growth factor for diabetic macular edema in Taiwan.

Given the rising prevalence of patients with diabetes and increasing treatment burden for patients with vision-threatening diabetic macular edema (DME), we aimed to explore the efficacy of modified early intensive and treat-and-extend regimen of anti-vascular endothelial growth factor (VEGF) therapy under the Taiwan National Insurance Bureau reimbursement policy. We obtained data on 69 eyes treated with initial 4-monthly intravitreal injections of aflibercept or ranibizumab, plus individualized treat-and-extend regimen. At 12 months, the mean (SD) change in LogMAR best corrected visual acuity from baseline was - 0.28 (0.31) in all eyes, while that in the aflibercept and ranibizumab groups were - 0.30 (0.34) and - 0.25 (0.28), respectively. Central retinal thickness decreased by 137.2 (122.4) in all eyes, 138.1 (134.2) in the aflibercept group, and 136.2 (110.9) in the ranibizumab group. Additionally, the aflibercept group had a lower mean number of injections than the ranibizumab group (8.5 vs. 8.7). The last extended dosing interval of > 12 weeks was 31.0% and 16.7% of the eyes in the aflibercept and ranibizumab groups, respectively. The modified anti-VEGF regimens effectively managed DME in terms of functional and anatomical outcomes, and efficiently reduced the healthcare burden by reducing the number of injections and extending treatment intervals within 12 months.

The elemental pegging effect in locally ordered nanocrystallites of high-entropy oxide enables superior lithium storage.

High-entropy oxides (HEOs) can be well suited for lithium-ion battery anodes because of their multi-principal synergistic effect and good stability. The appropriate selection and combination of elements play a crucial role in designing conversion-type anode materials with outstanding electrochemical performance. In this study, we have successfully built a single-phase spinel-structured HEO material of (Mn0.23Fe0.23Co0.22Cr0.19Zn0.13)3O4 (HEO-MFCCZ). When the HEO-MFCCZ materials transform into a coexisting state of amorphous and nanocrystalline structures during the cycling process, the inert Zn element can initiate a pegging effect, causing enhanced stability. The transition also introduces many defect sites, effectively reducing the potential barrier for ion transport and accelerating ion transport. The increased electronic and ionic conductivities and pseudocapacitive contribution significantly enhance the rate performance. As a result, a unique and practical approach is provided for developing anode materials for lithium-ion batteries.

Visual change as the presenting symptom of a suspected metastatic brain lesion in esophageal cancer: A case report.

INTRODUCTION: Esophageal cancer is the seventh most common malignancy worldwide and the sixth leading cause of cancer mortality with an overall survival rate of <20%. Esophageal cancer frequently metastasizes to distant lymph nodes, lungs, liver, and bones. Cerebral metastases originating from esophageal cancer are rare and often carry a poor prognosis as do most all metastatic lesions in esophageal cancer. CASE PRESENTATION: In this report, we describe a 55-year-old patient with past history of esophageal carcinoma who presented with blurred vision after taking ethambutol for tuberculosis. Ethambutol-induced optic neuropathy was the lead diagnosis. Initial vision testing was normal so additional testing with visual field examination was warranted. The visual field examination revealed homonymous hemianopsia. Subsequent magnetic resonance imaging of his brain, demonstrated a focal lesion, consistent with but not diagnostic of a brain metastasis likely from his primary esophageal malignancy. CONCLUSION: We conclude that a careful review of the medical history and comprehensive assessment are essential in establishing an obscure clinical diagnosis especially in the event that an uncommon metastatic lesion is encountered.

Effectiveness Analysis of Multiple Initial States Simulated Annealing Algorithm, a Case Study on the Molecular Docking Tool AutoDock Vina.

Simulated Annealing (SA) algorithm is not effective with large optimization problems for its slow convergence. Hence, several parallel Simulated Annealing (pSA) methods have been proposed, where the increase of searching threads can boost the speed of convergence. Although satisfactory solutions can be obtained by these methods, there is no rigorous mathematical analyses on their effectiveness. Thus, this article introduces a probabilistic model, on which a theorem about the effectiveness of multiple initial states parallel SA (MISPSA) has been proven. The theorem also demonstrates that the increasing parallelism in pSA algorithm with the reducing of search depth in each thread could obtain almost the same probability of finding the global optimal solution. We validated our theorem on AutoDock Vina, a widely used molecular docking tool with high accuracy and docking speed. AutoDock Vina uses a pSA strategy to find optimal molecular conformations. Under the premise that the total searching workload (i.e., thread number * iteration depth of each thread) remains unchanged, the docking accuracy from an aggressively parallelized SA searching method is almost the same or even better than those from the default exhaustiveness (parallelism degree) configuration of AutoDock Vina. Taking complex '1hnn' as an example,with the increase (125x) in the number of initial states (from 8 to 1000) and the decrease in the search depth for each thread (from 15540 to 124, or 1/125 of the original search depth), the mean energy is -7.80 and -7.94, while the mean RMSD is 3.4 and 3.14, respectively. The result also implies that a considerable speedup (in this case 125x in theory) can be obtained by a highly parallelized SA algorithm implementation.

Regional proximity effects of landscape pattern evolution: Evidence from 325 county-level areas in the middle reaches of the Yangtze River, China.

Unravelling the evolution of landscape patterns is essential to understand regional socio-ecological processes and to solve conflicts between environment protection and human development. However, the role of landscape transition in regional landscape pattern evolution remains unclear. Taking 325 county-level areas in the middle reaches of the Yangtze River (MRYR) as an example, this study explored the spatiotemporal associations between landscape quantity and pattern from the 1970s to 2020. Employing the methods of landscape metrics and trend and correlation analysis, associations between landscape transition and landscape pattern were found. The main results were as follows: (1) From the 1970s to 2020, urban land nearly doubled from 0.93 to 1.89 million km2. Arable land and forest showed the largest quantity reductions of 0.88 million km2 and 0.28 million km2, respectively. Other landscapes showed both decreasing and increasing trends with a spatial overlap among counties. (2) Transition in landscape quantity drives the change in landscape patches, thus affecting the landscape pattern in counties. The percentage of landscape area at the class level (CPLAND) showed relative changes in the quantities of landscape categories in each observation year, but their extreme outliers presented larger changes. (3) Diverse correlation coefficients in terms of magnitude and direction suggested that the transition from natural landscape to human-influenced landscape and the reverse processes occurred. Aggregation and diversity metrics showed spatial interaction with similar distances and the perimeter-area fractal dimension (PAFRAC) showed spatial autocorrelation at local scale. Optimal bandwidths among arable land, forest, and urban land (129.2 km) revealed direct spatial interactions and causal relationships, as did waters and unused land (66.7 km). The findings explained the evolution of landscape patterns and highlighted key areas where various landscape changes occurred, and can provide scientific support for policy-making in regional landscape transition governance.

KLF4 targets RAB26 and decreases 5-FU resistance through inhibiting autophagy in colon cancer.

BACKGROUND: Accumulating studies demonstrated that resistance of colon cancer (CC) to 5-fluorouracil (5-FU) contributes to adverse prognosis. We investigated how Kruppel-like factor 4 (KLF4) affected 5-FU resistance and autophagy in CC cells. METHODS: KLF4 expression and its downstream target gene RAB26 in CC tissues was analyzed by bioinformatics analysis, and the effect of abnormal KLF4 expression on prognoses of CC patients was predicted. Luciferase reporter assay detected the targeted relationship between KLF4 and RAB26. The viability and apoptosis of CC cells were analyzed by CCK-8 and flow cytometry. The formation of intracellular autophagosomes was detected by confocal laser scanning microscopy and immunofluorescence staining. The mRNA and protein levels were assayed by qRT-PCR and western blot. A xenograft animal model was constructed to verify the function of KLF4. Rescue assay was employed to verify whether KLF4/RAB26 could affect 5-FU resistance in CC cells through autophagy. RESULTS: KLF4 and RAB26 were lowly expressed in CC. KLF4 correlated with patients' survival. KLF4 was down-regulated in 5-FU resistant CC cells. KLF4 overexpression suppressed the proliferation and 5-FU resistance of CC cells, and inhibited LC3 II/I expression and autophagosome formation. Autophagy activator Rapamycin or sh-RAB26 treatment reversed the impact of KLF4 overexpression on 5-FU resistance. In vivo assay verified that KLF4 inhibited 5-FU resistance in CC cells. Rescue experiments revealed that KLF4 targeted RAB26 to inhibit CC cell autophagy, resulting in decreasing the resistance to 5-FU. CONCLUSION: KLF4 strengthened the sensitivity of CC cells to 5-FU by targeting RAB26 to restrain autophagy pathway.

[Sludge Biochar Modified by B-doped and Its Adsorption Behavior and Mechanism of 1,2-DCA in Water].

Sludge biochar (BC600) and B-doped sludge biochar (BBC600) were prepared with the boric acid doping modified co-pyrolysis method using municipal sludge as precursors, and the materials were structurally characterized by SEM, BET, FTIR, and Zeta potential and static contact angle to investigate the adsorption behavior, mechanism of BC600 and BBC600 on 1,2-DCA in water, and the influencing factors. The results of structural characterization showed that the B element content, specific surface area, and pore volume of biochar increased by 76%, 48%, and 30%, respectively, after the B doping modification; the effect of B doping modification on the surface charge and hydrophobicity of biochar was not significant. The results of adsorption experiments showed that the adsorption of 1,2-DCA by BBC600 was better than that by BC600 due to the larger specific surface area and higher strength of oxygen-containing functional groups of BBC600; the pseudo-first-order kinetic equation could better describe the adsorption of 1,2-DCA by BC600, and the pseudo-second-order kinetic equation could better fit the adsorption of 1,2-DCA by BBC600. The intraparticle diffusion was not the only rate-limiting step affecting the adsorption rate; the biochar material was more dispersed and stable under alkaline conditions, and its oxygen-containing functional groups were deprotonated and had enhanced electron-donating ability, which was beneficial to the adsorption of 1,2-DCA. Humic acid (HA) showed a low concentration-promoting and high concentration-inhibiting effect on the adsorption of 1,2-DCA by BC600, whereas both low and high concentrations of HA showed an inhibitory effect on the adsorption of 1,2-DCA by BBC600. The adsorption of 1,2-DCA by BC600 was inhibited by both low and high concentrations of HA, and HA competed with 1,2-DCA for adsorption; Cl-, SO42-, and NO3- all inhibited the adsorption of 1,2-DCA by biochar, and the degree of inhibition ordered from small to large was Cl-

[Analysis of Carbon Emissions and Influencing Factors in China Based on City Scale].

Assessing regional carbon emissions and their relationship with socio-economic conditions is very important for developing strategies for carbon emission reduction. This study explored the impact of the proportion of non-fossil energy, the land development degree, the urbanization rate of permanent residents, the proportion of secondary industry, per capita GDP, and per capita construction land area on per capita CO2 emissions in 339 prefecture-level and above cities in China (excluding some cities in Xinjiang, Hong Kong, Macao, and Taiwan). A Bayesian belief network modeling carbon emissions was constructed to identify the global effects of various factors on per capita CO2 emissions, and multiscale geographically weighted regression was used to analyze their local effects. The results showed that first, per capita CO2 emissions of cities in China increased from the south to the north and decreased from the eastern coast to the inland region. Second, globally, the sensitivity of per capita CO2 emissions to various factors from high to low was in the order of per capita construction land area>per capita GDP>urbanization rate of permanent residents>land development degree>proportion of secondary industry>proportion of non-fossil energy. Third, locally, the direction of the spatial relationship between each factor and per capita CO2 emissions was consistent with the global relationship, and there was spatial heterogeneity in the strength of the relationship. Finally, clean energy, decarbonization technologies, saving and intensive use of land, and green living were effective ways to achieve the dual-carbon goal.