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Layered double hydroxides (LDHs)‐based photocatalysts have generated widespread interest owing to their great potential for solving both energy and environmental issues through directly converting nonconsumable solar energy. Numerous methods have been investigated and analyzed in recent years to promote the photocatalytic efficiency of LDHs. Z‐scheme heterojunction that mimics the artificial photosynthesis is employed in photocatalysis owing to the outstanding advantages, such as high quantum efficiency, separation of redox sites, and low recombination of photocarriers. Herein, various LDHs‐based Z‐scheme heterojunction photocatalysts are briefly reviewed. Z‐scheme heterojunction associated with LDHs‐based materials exhibit high photocatalysis performance, and these types of hybrids are applied in photocatalytic H 2 O splitting, CO 2 reduction, and pollution degradation, which are introduced and summarized in detail. In the end, a brief conclusion focused on future challenges and expectations of LDH‐based Z‐scheme photocatalytic system is presented. We expect that more advances for LDH‐based Z‐scheme photocatalyst can be achieved in the field of photocatalysis in the coming days.

Effective monitoring of human activity in urban areas is essential for social stability and urban development. Traditional monitoring methods include wearable devices, survey sensor networks, and satellite remote sensing, which may be affected by privacy and weather conditions. Ambient seismic noise recorded by seismometers contains rich information about human activity and exhibits significant temporal and spatial variations, which provides valuable insights into social mobility. In this study, we investigated the correlation between human activity and ambient seismic noise in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) using the data recorded by 138 seismometers. Our results indicate that ambient seismic noise produced by human activity in the GBA is mainly concentrated between 2 and 20 Hz. The spatial distribution of ambient seismic noise exhibits a strong correlation with population and economy. Our results show that the analysis of ambient seismic noise can reveal the spatial and temporal impacts of different factors on human activity in the GBA, such as day and night, holidays, weather changes, national policies, and the coronavirus disease 2019 (COVID-19) pandemic. Furthermore, the analysis of 12-year-long ambient seismic noise at the Hong Kong seismic station shows a close connection between long-term changes in ambient seismic noise and local social development. This study suggests that the analysis of ambient seismic noise represents a novel method to gather critical information about human activity. Seismometers, which are widely deployed worldwide, have great potential as innovative tools for sensing human activity.

Photochemical CO 2 conversion to valuable C 2 products is desirable but challenging due to high C-C coupling barriers. This study constructs an acceptor-donor-acceptor type N, N’-bis(4-fluorophenyl) perylene-3,4,9,10-bis(dicarboximide)-supramolecular photocatalyst for efficiently and selectively photo-converting CO 2 and water vapor into C 2 H 6 , achieving a high production rate of 124.84 μmol g -1 h -1 with 85% selectivity under continuous 50-hour illumination. The performance is mainly attributed to giant internal electric field induced by the incorporation of fluorobenzene into the perylene diimide framework, greatly enhancing the separation and transfer of photogenerated charges. Theoretical calculations further elucidate the critical role of fluorobenzene in lowering the activation energy of the reaction and promoting the formation of the key C-C coupling intermediate (*COCO). This work provides insight for the design of high-performance catalysts for CO 2 photoreduction. In this work, an acceptor-donor-acceptor type fluorobenzene-linked perylene diimide photocatalyst was used for selective conversion of CO 2 to C 2 H 6 in pure water.

It is significant to systematically quantify the propagation thresholds of meteorological drought to different levels of agricultural drought in karst areas, and revealit’s the propagation driving mechanisms. This can guide early warning and fine management of agricultural drought. In this study,we selected Guizhou Province as an example. The standardized precipitation evapotranspiration index (SPEI) and standardized soil moisture index (SSI) were used to characterize meteorological and agricultural drought. The run theory was used to identify, merge and eliminate drought events. The maximum correlation coefficient was used to capture the propagation time of meteorological-agricultural drought. The regression models were used to quantify the propagation intensity threshold from meteorological drought to different levels of agricultural drought. Finally, the propagation threshold driving mechanism was explored using geographical detectors. The results show that: (1) in terms of temporal variations during the past 21 years, regional meteorological drought had a shorter duration and a higher intensity than agricultural drought, Particularly, 2011 was a year of severe drought, and agricultural drought was significantly alleviated after 2014. (2) In terms of spatial variations, the \"long duration area\" of meteorological drought duration showed an \"S\" shaped distribution in the northeast, and the \"short duration area\" showed a point-like distribution. The overall duration of agricultural drought showed a spatial distribution of northeast to “medium-high in the northeast and low in the southwest. (3) The drought propagation time showed an alternating distribution of \"valley-peak-valley-peak\" from southeast to northwest. In terms of propagation intensity thresholds, light drought showed an overall spatial distribution of high in the east and low in the west. Moderate, severe, and extreme droughts showed a spatial distribution of low in the center north of southern Guizhou) and high in the borders. (4) There was a strong spatial coupling relationship between karst development intensity, altitude and meteorological-agricultural drought propagation thresholds. The interaction of different factors exhibited a two-factor enhancement and nonlinear enhancement on the propagation threshold. This indicates that synergistic effects of different factors on the propagation threshold were larger than single-factor effects.

Background Insufficient evidence existed about the prognostic role of the advanced lung cancer inflammation index (ALI) for gastric cancer patients who underwent curative resection. The aim of this study was to identify the predictive ability of ALI for survival after curative gastrectomy. Methods We retrospectively analyzed 328 gastric cancer patients who received curative gastrectomy from the database of Chongqing University Cancer Hospital, and investigated the prognostic role of the preoperative ALI compared with clinicopathological variables and other serum biomarkers, such as preoperative neutrophil-to-lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR) and Lymphocyte-monocyte ratio (LMR). To minimize intergroup differences, propensity score matching (PSM) analysis was employed. Additionally, we performed a meta-analysis of four cohort studies published up to October 2023 following the PRISMA guidelines. Results In the overall cohort, patients in the low ALI group had a significantly worse overall survival compared to those in the high ALI group ( P  < 0.0001). Subgroup analysis identified that ALI maintained its prognostic significance across different subgroups. In addition, ROC analysis showed that ALI had a higher AUC value for 3-year overall survival compared to NLR, PLR, and LMR (0.576 vs. 0.573 vs. 0.557 vs. 0.557). Multivariate analysis indicated that ALI, other than other serum biomarkers, was an independent risk factor for decreased overall survival in GC patients following curative surgery (HR = 1.449; 95%CI: 1.028–2.045; P  = 0.034). Consistently, PSM analysis supported all of these findings. The meta-analysis including 4 studies evaluating 2542 patients, confirmed the association between the low ALI and poor survival outcomes. Conclusion The preoperative ALI was an independent prognostic factor for survival in gastric cancer patients who underwent curative gastrectomy.

Timely and accurate agricultural drought monitoring and drought-driven mechanism analysis in karst basins in the context of global warming are highly important for drought disaster monitoring and sustainable ecological development in a basin. In this study, based on MODIS data, meteorological and topographic data and land use data from 2001 to 2020, we used the Sen slope, the Mann–Kendall test and a geographic detector to explore the driving mechanisms of agricultural drought caused by climate change and human activities in the karst basin of southern China from 2001 to 2020. The results showed that (1) the spatial distribution of the TVDI in the karst basin in southern China has obvious regional characteristics, showing a decreasing trend from west to east. (2) According to the interannual trend of drought, the degree of drought in the South China karst basin exhibited a weakening trend over the last 20 years, with the most severe drought occurring in 2003. Regarding the seasonal change in the TVDI, drought in spring, summer and autumn exhibited a decreasing trend, while that in winter exhibited an increasing trend, and the drought intensity decreased in the following order: spring (0.58) > autumn (0.53) > summer (0.5) > winter (0.48). (3) Single-factor detection the results showed that rainfall, temperature and elevation were the main factors driving aridification in the study area; multifactor coupling (mean) drove drought in descending order: rainfall (q = 0.424) > temperature (q = 0.340) > elevation (q = 0.219) > land use (q = 0.188) > population density (q = 0.061) > slope (q = 0.057). Therefore, revealing the mechanism of agricultural drought in karst basins through the study of this paper has important theoretical significance and provides technical guidance for drought relief in karst areas.

This study aims to analyze the demographic characteristics, clinical features, and neurological outcomes of patients with traumatic spinal cord injury (TSCI) admitted to the Intensive Care Unit (ICU), in order to provide scientific evidence for the prevention and management of TSCI. A retrospective analysis was conducted on data from TSCI patients admitted to the ICU between January 2018 and December 2022. Demographic information, neurological injury characteristics, complications during hospitalization, treatment interventions, and prognosis were comprehensively collected. Based on changes in neurological function before and after treatment, patients undergoing surgery were classified into improvement and non-improvement groups. Neurological recovery was assessed using the American Spinal Injury Association (ASIA) impairment scale. Univariate and multivariate logistic regression analyses were performed to identify key factors influencing neurological recovery. A total of 341 TSCI patients were included, with a mean age of 55.2 ± 13.4 years and a male-to-female ratio of 6.3:1. The leading cause of TSCI were high falls (47.5%), traffic accidents (35.8%) and low falls (9.1%). Cervical spinal cord was most common, followed by thoracic and lumbar cord. Among surgical patients, the neurological improvement rate was 14.8%, compared to 12.5% in non-surgical patients, highlighting the potential benefits of surgical intervention. Multivariate analysis revealed that early targeted blood pressure management (MAP ≥ 85 mmHg) (OR=2.296, 95% CI: 1.036-5.086, P = 0.040) and early surgery (≤ 24h) (OR=2.841, 95% CI: 1.088-7.419, P = 0.033) were significant protective factors for neurological improvement. Patients with TSCI admitted to the ICU are predominantly middle-aged men, with high falls and traffic accidents being the primary causes. Early blood pressure optimization and timely surgical intervention are significantly associated with improved neurological outcomes.

Hyperspectral Images (HSI) classification is a challenging task due to a large number of spatial-spectral bands of images with high inter-similarity, extra variability classes, and complex region relationships, including overlapping and nested regions. Classification becomes a complex problem in remote sensing images like HSIs. Convolutional Neural Networks (CNNs) have gained popularity in addressing this challenge by focusing on HSI data classification. However, the performance of 2D-CNN methods heavily relies on spatial information, while 3D-CNN methods offer an alternative approach by considering both spectral and spatial information. Nonetheless, the computational complexity of 3D-CNN methods increases significantly due to the large capacity size and spectral dimensions. These methods also face difficulties in manipulating information from local intrinsic detailed patterns of feature maps and low-rank frequency feature tuning. To overcome these challenges and improve HSI classification performance, we propose an innovative approach called the Attention 3D Central Difference Convolutional Dense Network (3D-CDC Attention DenseNet). Our 3D-CDC method leverages the manipulation of local intrinsic detailed patterns in the spatial-spectral features maps, utilizing pixel-wise concatenation and spatial attention mechanism within a dense strategy to incorporate low-rank frequency features and guide the feature tuning. Experimental results on benchmark datasets such as Pavia University, Houston 2018, and Indian Pines demonstrate the superiority of our method compared to other HSI classification methods, including state-of-the-art techniques. The proposed method achieved 97.93% overall accuracy on the Houston-2018, 99.89% on Pavia University, and 99.38% on the Indian Pines dataset with the 25 × 25 window size.

Background Liquid hot water (LHW) pretreatment has been considered as one of the most industrially viable and environment-friendly methods for facilitating the transformation of lignocelluloses into biofuels through biological conversion. However, lignin fragments in pretreatment hydrolysates are preferential to condense with each other and then deposit back onto cellulose surface under severe conditions. Particularly, lignin tends to relocate or redistribute under high-temperature LHW pretreatment conditions. The lignin residues on the cellulose surface would result in significant nonproductive binding of cellulolytic enzymes, and therefore negatively affect the enzymatic conversion (EC) of glucan in pretreated substrates. Although additives such as bovine serum albumin (BSA) and Tween series have been used to reduce nonproductive binding of enzymes through blocking the lignin, the high cost or non-biocompatibility of these additives limits their potential in industrial applications. Results Here, we firstly report that a soluble soy protein (SP) extracted from inexpensive defatted soy powder (DSP) showed excellent performance in promoting the EC of glucan in LHW-pretreated lignocellulosic substrates. The addition of the SP (80 mg/g glucan) could readily reduce the cellulase (Celluclast 1.5 L®) loading by 8 times from 96.7 to 12.1 mg protein/g glucan and achieve a glucan EC of 80% at a hydrolysis time of 72 h. With the same cellulase (Celluclast 1.5 L®) loading (24.2 mg protein/g glucan), the ECs of glucan in LHW-pretreated bamboo, eucalyptus, and Masson pine substrates increased from 57%, 54% and 45% (without SP) to 87%, 94% and 86% (with 80 mg SP/g glucan), respectively. Similar effects were also observed when Cellic CTec2, a newer-generation cellulase preparation, was used. Mechanistic studies indicated that the adsorption of soluble SP onto the surface of lignin residues could reduce the nonproductive binding of cellulolytic enzymes to lignin. The cost of the SP required for effective promotion would be equivalent to the cost of 2.9 mg cellulase (Celluclast 1.5 L®) protein (or 1.2 FPU/g glucan), if a proposed semi-simultaneous saccharification and fermentation (semi-SSF) model was used. Conclusions Near-complete saccharification of glucan in LHW-pretreated lignocellulosic substrates could be achieved with the addition of the inexpensive and biocompatible SP additive extracted from DSP. This simple but remarkably effective technique could readily contribute to improving the economics of the cellulosic biorefinery industry.

Patients with advanced melanoma have shown an improved outlook after anti-PD1 therapy, but the low response rate restricts clinical benefit; therefore, enhancing anti-PD1 therapeutic efficacy remains a major challenge. Here, our findings showed a significantly increased abundance of α-KG in healthy controls, anti-PD1-sensitive melanoma-bearing mice, and anti-PD1-sensitive melanoma patients; moreover, supplementation with α-KG enhanced the efficacy of anti-PD1 immunotherapy and increased PD-L1 expression in melanoma tumors via STAT1/3. We also found that supplementation with α-KG significantly increased the activity of the methylcytosine dioxygenases TET2/3, which led to an increased 5-hydroxymethylcytosine (5-hmC) level in the PD-L1 promoter. As a consequence, STAT1/3 binding to the PD-L1 promoter was stabilized to upregulate PD-L1 expression. Importantly, single-cell sequencing of preclinical samples and analysis of clinical data revealed that TET2/3-STAT1/3-CD274 signaling was associated with sensitivity to anti-PD1 treatment in melanoma. Taken together, our results provide novel insight into α-KG’s function in anti-PD1 treatment of melanoma and suggest supplementation with α-KG as a novel promising strategy to improve the efficacy of anti-PD1 therapy.