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Abstract Background The arid region of the Qinghai-Tibet Plateau has a harsh natural environment that spans a vast altitudinal range, where plant growth suffers from various environmental stresses such as low temperature and drought. Shrubs are one of the most important plant functional groups in this region, and different shrub types have developed various nutrient strategies in response to these environmental stresses. However, nutrient characteristics and biogeographical patterns in different shrub types have seldom been investigated. The aboveground concentrations of carbon (C), nitrogen (N), and phosphorus (P) of the three shrub types (leaf-normal, leaf-reduced, and succulent shrubs) and soil physicochemical properties were measured in 138 sampling sites in the arid region of the Qinghai-Tibet Plateau. Results Mean C, N, and P concentrations in all shrubs were 382.09 mg/g, 24.63 mg/g, and 1.43 mg/g in the arid region of the Qinghai-Tibet Plateau. Mean C, N, and P concentrations were 347.64, 24.30, and 1.25 mg/g in succulent shrubs, which were significantly lower than those of leaf-normal shrubs (C: 418.43 mg/g; N: 24.57 mg/g; P: 1.55 mg/g) and leaf-reduced shrubs (C: 399.71 mg/g; N: 25.96 mg/g; P: 1.65 mg/g). With increasing in longitude, C, N, and P concentrations in leaf-normal and leaf-reduced shrubs increased but these nutrients in succulent shrubs decreased. Increasing altitude only increased N and P concentrations for leaf-normal shrubs. These results demonstrated that the three shrub types had divergent nutrient biogeographical patterns. N and P concentrations of leaf-normal and leaf-reduced shrubs were directly driven by soil total N and total P concentrations and indirectly regulated by mean annual temperature and mean annual precipitation, promoting the formation of longitude or altitude nutrient patterns. Meanwhile, N and P concentrations in succulent shrubs were only regulated by soil pH, total N, and total P concentrations, driving the formation of longitude nutrient patterns. These results indicated divergent driving factors for nutrient biogeographical patterns among the three shrub types. Conclusions Our study highlights the unique nutrient characteristics of succulent shrubs, reveals driving factors of nutrient biogeographical patterns in the three shrub types, and contributes to the understanding of biogeochemical cycling in arid ecosystems.

Abstract Background Biomaterials used in bone tissue engineering must fulfill the requirements of osteoconduction, osteoinduction, and osseointegration. However, biomaterials with good osteoconductive properties face several challenges, including inadequate vascularization, limited osteoinduction and barrier ability, as well as the potential to trigger immune and inflammatory responses. Therefore, there is an urgent need to develop guided bone regeneration membranes as a crucial component of tissue engineering strategies for repairing bone defects. Methods The mZIF-8/PLA membrane was prepared using electrospinning technology and simulated body fluid external mineralization method. Its ability to induce biomimetic mineralization was evaluated through TEM, EDS, XRD, FT-IR, zeta potential, and wettability techniques. The biocompatibility, osteoinduction properties, and osteo-immunomodulatory effects of the mZIF-8/PLA membrane were comprehensively evaluated by examining cell behaviors of surface-seeded BMSCs and macrophages, as well as the regulation of cellular genes and protein levels using PCR and WB. In vivo, the mZIF-8/PLA membrane’s potential to promote bone regeneration and angiogenesis was assessed through Micro-CT and immunohistochemical staining. Results The mineralized deposition enhances hydrophilicity and cell compatibility of mZIF-8/PLA membrane. mZIF-8/PLA membrane promotes up-regulation of osteogenesis and angiogenesis related factors in BMSCs. Moreover, it induces the polarization of macrophages towards the M2 phenotype and modulates the local immune microenvironment. After 4-weeks of implantation, the mZIF-8/PLA membrane successfully bridges critical bone defects and almost completely repairs the defect area after 12-weeks, while significantly improving the strength and vascularization of new bone. Conclusions The mZIF-8/PLA membrane with dual osteoconductive and immunomodulatory abilities could pave new research paths for bone tissue engineering.

Abstract In response to the growing demand for organ substitutes, tissue engineering has evolved significantly. However, it is still challenging to create functional tissues and organs. Tissue engineering from the ‘bottom-up’ is promising on solving this problem due to its ability to construct tissues with physiological complexity. The workflow of this strategy involves two key steps: the creation of building blocks, and the subsequent assembly. There are many techniques developed for the two pivotal steps. Notably, bioprinting is versatile among these techniques and has been widely used in research. With its high level of automation, bioprinting has great capacity in engineering tissues with precision and holds promise to construct multi-material tissues. In this review, we summarize the techniques applied in fabrication and assembly of building blocks. We elaborate mechanisms and applications of bioprinting, particularly in the 'bottom-up' strategy. We state our perspectives on future trends of bottom-up tissue engineering, hoping to provide useful reference for researchers in this field.

Ovarian cancer is currently the second most common malignant tumor among gynecological cancers worldwide, primarily due to challenges in early diagnosis, high recurrence rates, and resistance to existing treatments. Current therapeutic options are inadequate for addressing the needs of ovarian cancer patients. Ferroptosis, a novel form of regulated cell death with demonstrated tumor-suppressive properties, has gained increasing attention in ovarian malignancy research. A growing body of evidence suggests that ferroptosis plays a significant role in the onset, progression, and incidence of ovarian cancer. Additionally, it has been found that immunotherapy, an emerging frontier in tumor treatment, synergizes with ferroptosis in the context of ovarian cancer. Consequently, ferroptosis is likely to become a critical target in the treatment of ovarian cancer.

Griffithsin (GRFT) is a highly effective, broad-spectrum, safe, and stable viral inhibitor used to suppress a variety of viruses. However, little information is available on whether GRFT can prevent plant viral diseases. In this study, we constructed a GRFT overexpression vector containing the sweetpotato storage cell signal peptide and generated exogenous GRFT overexpression lines through genetic transformation. The transgenic plants showed notable resistance to sweetpotato virus disease in the virus nursery. To verify the antiplant virus function of GRFT, transient expression in tobacco leaves showed that GRFT inhibited the sweetpotato leaf curl virus (SPLCV). The replication of SPLCV was entirely inhibited when the concentration of GRFT reached a certain level. The results of pulldown and BIFC assays showed that GRFT did not interact with the six components of SPLCV. In addition, the mutated GRFTD/A without the binding ability of carbohydrate and anticoronavirus function, in which three aspartate residues at carbohydrate binding sites were all mutated to alanine, also inhibited SPLCV. Quantitative reverse-transcription PCR analyses showed that the tobacco antiviral-related genes HIN1, ICS1, WRKY40, and PR10 were overexpressed after GRFT/GRFTD/A injection. Furthermore, HIN1, ICS1, and PR10 were more highly expressed in the leaves injected with GRFTD/A. The results suggest that sweetpotato is able to express GRFT exogenously as a bioreactor. Moreover, exogenous GRFT expression inhibits plant viruses by promoting the expression of plant antiviral genes.

Nine sweet potato varieties with different flesh colors were cultivated under uniform environmental conditions with potassium (K) fertilizer treatments at levels of 0, 22.5, and 45 kg/ha. The structural and functional properties of the starches were subsequently analyzed. The soluble sugar content in the dry root tuber increased, with higher K levels in most varieties. Amylose content decreased in Sushu16 but increased in Ningzishu1, with no significant differences observed in other varieties across different K levels. Elevated K levels had no effect on starch protein content, crystalline type, or gelatinization enthalpy. The impact of K fertilizer on starch thermal and pasting properties varied among the varieties. PLSR and PLS-DA analyses revealed that genotype background was the primary factor influencing starch properties. This research will provide a reference for the improvement of sweet potato production quality and efficiency and a scientific basis for the cultivation and utilization of sweet potato root tubers.

Three sweet potato varieties grew in natural high temperature (HT) and low temperature (LT) field soils. Their starch physicochemical properties were affected similarly by HT and LT soils. Compared with LT soil, HT soil induced the increases of granule size D[4,3] from 18.0–18.7 to 19.9–21.8 μm and amylopectin average branch-chain length from 21.9–23.1 to 24.1–24.7 DP. Starches from root tubers grown in HT and LT soils exhibited CA- and CC-type XRD pattern, respectively. Starches from root tubers grown in HT soil exhibited stronger lamellar peak intensities (366.8–432.0) and higher gelatinization peak temperature (72.0–76.8 °C) than those (176.2–260.5, 56.4–63.4 °C) in LT soil. Native starches from root tubers grown in LT soil were hydrolyzed more easily (hydrolysis rate coefficient 0.227–0.282 h−1) by amylase than those (0.120–0.163 h−1) in HT soil. The principal component analysis exhibited that starches from root tubers grown in HT and LT soils had significantly different physicochemical properties.

Abstract The purpose of this study was to investigate the correlation between GFR and unit renal volume in infants with congenital hydronephrosis measured by 99mTc-DMSA static renal imaging and ultrasonography. According to the classification of hydronephrosis, 38 infants aged 0–12 months with congenital hydronephrosis were divided into six groups: healthy kidney groups, mild hydronephrosis groups, and severe hydronephrosis groups. Within one week, all patients underwent ultrasound, diuretic dynamic renal imaging, static renal imaging and lateral imagings of both kidneys after static renal imaging respectively. Pediatric renal volume was calculated using the improved formula length × width × thickness × 0.674, and then the renal function in per unit volume (GFR/unit volume, ml/cm3) was obtained. All statistical analysis was done with SPSS Statistics version 24.0. The renal function in per unit volume was a minimum of 1.62 ml/cm3 in left healthy kidney in static renal imaging, but the renal function in per unit volume was a maximum value of 2.20 ml/cm3 in right healthy kidney in ultrasonography. There was a strong positive correlation observed between GFR and renal volume in left healthy kidney group and left and right kidneys with mild hydronephrosis groups (r = 0.865, r = 0.872, r = 0.822). A moderate positive correlation was found between GFR and renal volume in right healthy kidney group and left and right kidneys wih severe hydronephrosis groups (r = 0.783, r = 0.542, r = 0.798). GFR in per unit volume ranged from 1.62 to 2.20 ml/cm3 in healthy kidney, and was significantly higher in right kidney as compared to in left kidney, and also decreased with the progression of hydronephrosis.

Abstract Background The extraction of impacted mandibular third molars might cause large bone defects in the distal area of second molars. A new strategy was innovatively employed here combining autologous bone, Bio-Oss, concentrated growth factors (CGF) gel and CGF membrane for bone repair, and the present study aimed at exploring safety as well as short- and long-term efficacy of this new protocol clinically. Materials and methods A total of 66 participants were enrolled in this randomized single-blind clinical trial, and randomly allocated to control group (only blood clots), test A group (autogenous bone, Bio-Oss with barrier membrane) and test B group (autogenous bone, Bio-Oss, CGF gel with CGF membrane). The postoperative outcomes including PoSSe scale, periodontal probing depth (PD), degree of gingival recession and computed tomography measurements were assessed at 3rd, 6th, 12th month. A p-value 0.05). Conclusion Both two test groups could achieve stable long-term efficacy on bone defect repair. The use of CGF gel and CGF membrane could accelerate early-stage bone repair, alleviate short-term pain after surgery, reduce long-term probing depth and relieve economic cost for patients. This new bone repair protocol is worthy of promoting by clinicians. Trial registration This study was registered with the identification number ChiCTR2300068466 on 20/02/2023 at Chinese Clinical Trial Registry. Also, it was ethically approved from the institutional ethics committee at the Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China (No:2023-010-01), and has been conducted in accordance to the guidelines of the declaration of Helsinki. Written informed consent was obtained from all participants in the study.

Abstract As the incidence of Alzheimer's disease (AD) increases year by year, more people begin to study this disease. In recent years, many studies on reactive oxygen species (ROS), neuroinflammation, autophagy, and other fields have confirmed that hypoxia is closely related to AD. However, no researchers have used bioinformatics methods to study the relationship between AD and hypoxia. Therefore, our study aimed to screen the role of hypoxia-related genes in AD and clarify their diagnostic significance. A total of 7681 differentially expressed genes (DEGs) were identified in GSE33000 by differential expression analysis and cluster analysis. Weighted gene co-expression network analysis (WGCNA) was used to detect 9 modules and 205 hub genes with high correlation coefficients. Next, machine learning algorithms were applied to 205 hub genes and four key genes were selected. Through the verification of external dataset and quantitative real-time PCR (qRT-PCR), the AD diagnostic model was established by ANTXR2, BDNF and NFKBIA. The bioinformatics analysis results suggest that hypoxia-related genes may increase the risk of AD. However, more in-depth studies are still needed to investigate their association, this article would guide the insights and directions for further research.

Abstract Most patients with inflammatory bowel disease (IBD) develop anemia, which is attributed to the dysregulation of iron metabolism. Reciprocally, impaired iron homeostasis also aggravates inflammation. How this iron‐mediated, pathogenic anemia‐inflammation crosstalk is regulated in the gut remains elusive. Herein, it is for the first time revealed that anemic IBD patients exhibit impaired production of short‐chain fatty acids (SCFAs), particularly butyrate. Butyrate supplementation restores iron metabolism in multiple anemia models. Mechanistically, butyrate upregulates ferroportin (FPN) expression in macrophages by reducing the enrichment of histone deacetylase (HDAC) at the Slc40a1 promoter, thereby facilitating iron export. By preventing iron sequestration, butyrate not only mitigates colitis‐induced anemia but also reduces TNF‐α production in macrophages. Consistently, macrophage‐conditional FPN knockout mice exhibit more severe anemia and inflammation. Finally, it is revealed that macrophage iron overload impairs the therapeutic effectiveness of anti‐TNF‐α antibodies in colitis, which can be reversed by butyrate supplementation. Hence, this study uncovers the pivotal role of butyrate in preventing the pathogenic circuit between anemia and inflammation.

Abstract This study selects the financial data of Chinese non-financial listed companies from 2012 to 2021 as the research sample and empirically examines in detail the impact of financial asset allocation on enterprise upgrading and its mechanism. The study finds that financial assets have a dual influence on enterprise upgrading. Short-term financial assets provide the necessary funds for production activities, thus promoting enterprise upgrading. Long-term financial assets crowd out the funds needed for production activities and thus inhibit enterprise upgrading, resulting in an inverted U-shaped relationship between financial assets and enterprise upgrading. Mechanism testing revealed that risk-taking capacity and earnings persistence are important ways in which financial assets affect enterprise upgrading. In addition, the impact of financial assets on enterprise upgrading differs for different types of financial assets. The financial asset significantly impacts the upgrading of over-indebtedness, non-state-owned, and high financing constraints enterprises. This study enriches the research literature on financial assets and enterprise upgrading and provides new micro evidence for understanding the impact of financial assets on the enterprise upgrading of listed companies.

Three sweet potato varieties with white-, yellow- and purple-fleshed root tubers were harvested at 100, 120, 140 and 160 days after planting (DAP). Their starch structural, thermal, pasting and digestion properties were measured to reveal the influences of harvesting dates on the physicochemical properties of sweet potato root tuber starch. Though starches from different varieties displayed some differences in physicochemical properties due to their different genetic backgrounds, they were influenced by harvesting date in similar ways. Starches isolated from root tubers at 100 and 160 DAP exhibited lower granule sizes than those at 120 and 140 DAP. The amylose content was higher in root tubers at 100 and 120 DAP than at 140 and 160 DAP. Starches from root tubers at 100 DAP exhibited CA-type X-ray diffraction patterns, and then the B-type crystallinity gradually increased at later harvesting dates. The different harvesting dates had no significant effects on the short-ranged ordered structure and lamellar thickness of starch, but the lamellar peak intensity decreased significantly at later harvesting dates. Starch had a lower gelatinization temperature and a wider gelatinization temperature range in root tubers at 140 and 160 DAP than at 100 and 120 DAP. The higher peak viscosity and lower pasting temperature were associated with the late harvesting date. The digestion of starch had slight differences among root tubers at different harvesting dates. The harvesting dates of root tubers played more important roles in starch properties than the variety. This study would be helpful for breeders, farmers and sweet potato starch users.

Abstract This is the protocol for an evidence and gap map. The objectives are as follows: To map available randomized control trials, economic evaluations, and systematic reviews that assess the effectiveness and cost‐effectiveness of non‐pharmacological interventions for older people with a diagnosis of depression and identify any existing gaps in the evidence that can inform future research.

Abstract This is the protocol for a Campbell systematic review. The objectives are as follows. We will solve the following questions: (1) What are the characteristics of skills training services for individuals experiencing or at risk of homelessness? (2) How effectively do the different skills training programs improve employment status, work and life skills, or housing stability? (3) What factors are associated with the variation in the effectiveness of skills training services?

Abstract Background Pericardial calcification is usually a marker of chronic diseases, and its occurrence in rapidly progressing malignant primary pericardial mesothelioma (PPM) is extremely rare. Therefore, this atypical imaging appearance contributes to more frequent misdiagnosis of PPM. However, no systematic summary currently exists of the imaging characteristics of malignant pericardial calcification in PPM. In our report, its clinical characteristics are discussed in detail, to provide a reference to reduce the misdiagnosis rates of PPM. Case presentation A 50-year-old female patient was admitted to our hospital, presenting primarily with features suggestive of cardiac insufficiency. Chest computed tomography revealed significant pericardial thickening and localized calcification, suspicious of constrictive pericarditis. A chest examination performed through a midline incision showed a chronically inflamed and easily-ruptured pericardium that was closely adherent to the myocardium. Post-operative pathological examination confirmed a diagnosis of primary pericardial mesothelioma. Six weeks postoperatively, the patient experienced symptom recurrence and abandoned chemotherapy and radiation therapy. Nine months postoperatively, the patient died of heart failure. Conclusion We report this case to highlight the rare finding of pericardial calcification in patients with primary pericardial mesothelioma. This case illustrated that confirmation of pericardial calcification cannot completely rule out rapidly developing PPM. Therefore, understanding the different radiological features of PPM can help to reduce its rate of early misdiagnosis.

Abstract To investigate the role of periosteum on the treatment of buccal dehiscence defects comparing with collagen membrane in canine model. Bilateral dehiscence-type defects at the buccal side on the distal root of the lower 3rd/4th premolars were created in six beagle dogs with a total of 24 defects and assigned into three groups: Group A: blood clot in an untreated defect; Group B: deproteinized bovine bone material (DBBM) covered with an absorbable membrane; Group C: DBBM covered with the periosteum. The structural parameters for trabecular architecture and vertical bone regeneration were evaluated. Histological and histomorphometric evaluation were carried out to observe new bone formation and mineralization in the graft site. Immunohistochemical analysis was performed to identify the expression of osteopontin (OPN) and osteocalcin (OCN) at postoperative 3 months. Group C achieved greater vertical alveolar bone gain than that of group A and group B. The periosteum-covered group showed significantly greater new bone formation and accelerated mineralization. The greater immunolabeling for OPN and OCN was observed in group C than in group A. Periosteal coverage has explicit advantages over collagen membranes for the quality and quantity of new bone regeneration in dehiscence defects repairing.

Ferroptosis has emerged to be a promising approach in cancer therapies; however, colorectal cancer (CRC) is relatively insensitive to ferroptosis. Exactly how the gut microenvironment impacts the ferroptotic sensitivity of CRC remains unknown. Herein, by performing metabolomics, we discovered that butyrate concentrations were significantly decreased in CRC patients. Butyrate supplementation sensitized CRC mice to ferroptosis induction, showing great in vivo translatability. Particularly, butyrate treatment reduced ferroptotic resistance of cancer stem cells. Mechanistically, butyrate inhibited xCT expression and xCT-dependent glutathione synthesis. Moreover, we identified c-Fos as a novel xCT suppressor, and further elucidated that butyrate induced c-Fos expression via disrupting class I HDAC activity. In CRC patients, butyrate negatively correlated with tumor xCT expression and positively correlated with c-Fos expression. Finally, butyrate was found to boost the pro-ferroptotic function of oxaliplatin (OXA). Immunohistochemistry data showed that OXA non-responders exhibited higher xCT expression compared to OXA responders. Hence, butyrate supplementation is a promising approach to break the ferroptosis resistance in CRC.

Understanding the mechanisms underlying the relationship between biodiversity and ecosystem function (BEF) is critical for the implementation of productive and resilient ecosystem management. However, the differences in BEF relationships along altitudinal gradients between forests and shrublands are poorly understood, impeding the ability to manage terrestrial ecosystems and promote their carbon sinks. Using data from 37962 trees of 115 temperate forest and 134 shrubland plots of Taihang Mountains Priority Reserve, we analyzed the effects of species diversity, structural diversity, climate factors and soil moisture on carbon storage along altitudinal gradients in temperate forests and shrublands. We found that: (1) Structural diversity, rather than species diversity, mainly promoted carbon storage in forests. While species diversity had greater positive effect on carbon storage in shrublands. (2) Mean annual temperature (MAT) had a direct negative effect on forest carbon storage, and indirectly affected forest carbon storage by inhibiting structural diversity. In contrast, MAT promoted shrubland carbon storage directly and indirectly through the positive mediating effect of species diversity. (3) Increasing altitudinal gradients enhanced the structural diversity-carbon relationship in forests, but weakened the species diversity-carbon relationship in shrublands. Niche and architectural complementarity and different life strategies of forests and shrubs mainly explain these findings. These differential characteristics are critical for our comprehensive understanding of the BEF relationship and could help guide the differentiated management of forests and shrublands in reaction to environmental changes.

Summary: Background: RNA viruses account for many human diseases and pandemic events but are often not targetable by traditional therapeutics modalities. Here, we demonstrate that adeno-associated virus (AAV) -delivered CRISPR-Cas13 directly targets and eliminates the positive-strand EV-A71 RNA virus in cells and infected mice. Methods: We developed a Cas13gRNAtor bioinformatics pipeline to design CRISPR guide RNAs (gRNAs) that cleave conserved viral sequences across the virus phylogeny and developed an AAV-CRISPR-Cas13 therapeutics using in vitro viral plaque assay and in vivo EV-A71 lethally-infected mouse model. Findings: We show that treatment with a pool of AAV-CRISPR-Cas13-gRNAs designed using the bioinformatics pipeline effectively blocks viral replication and reduces viral titers in cells by >99.99%. We further demonstrate that AAV-CRISPR-Cas13-gRNAs prophylactically and therapeutically inhibited viral replication in infected mouse tissues and prevented death in a lethally challenged EV-A71-infected mouse model. Interpretation: Our results show that the bioinformatics pipeline designs efficient CRISPR-Cas13 gRNAs for direct viral RNA targeting to reduce viral loads. Additionally, this new antiviral AAV-CRISPR-Cas13 modality represents an effective direct-acting prophylactic and therapeutic agent against lethal RNA viral infections. Funding: Agency for Science, Technology and Research (A∗STAR) Assured Research Budget, A∗STAR Central Research Fund UIBR SC18/21-1089UI, A∗STAR Industrial Alignment Fund Pre-Positioning (IAF-PP) grant H17/01/a0/012, MOE Tier 2 2017 (MOE2017-T2-1-078; MOE-T2EP30221-0005), and NUHSRO/2020/050/RO5+5/NUHS-COVID/4.

Hyperspectral images (HSIs) contain abundant spectral and spatial structural information, but they are inevitably contaminated by a variety of noises during data reception and transmission, leading to image quality degradation and subsequent application hindrance. Hence, removing mixed noise from hyperspectral images is an important step in improving the performance of subsequent image processing. It is a well-established fact that the data information of hyperspectral images can be effectively represented by a global spectral low-rank subspace due to the high redundancy and correlation (RAC) in the spatial and spectral domains. Taking advantage of this property, a new algorithm based on subspace representation and nonlocal low-rank tensor decomposition is proposed to filter the mixed noise of hyperspectral images. The algorithm first obtains the subspace representation of the hyperspectral image by utilizing the spectral low-rank property and obtains the orthogonal basis and representation coefficient image (RCI). Then, the representation coefficient image is grouped and denoised using tensor decomposition and wavelet decomposition, respectively, according to the spatial nonlocal self-similarity. Afterward, the orthogonal basis and denoised representation coefficient image are optimized using the alternating direction method of multipliers (ADMM). Finally, iterative regularization is used to update the image to obtain the final denoised hyperspectral image. Experiments on both simulated and real datasets demonstrate that the algorithm proposed in this paper is superior to related mainstream methods in both quantitative metrics and intuitive vision. Because it is denoising for image subspace, the time complexity is greatly reduced and is lower than related denoising algorithms in terms of computational cost.

The purpose of this paper is to give some sufficient conditions for the existence of periodic oscillation of a class of in-host MERS-Cov infection model with cytotoxic T lymphocyte (CTL) immune response. A new technique is developed to obtain a lower bound of the state variable characterizing CTL immune response in the model. Our results expand on some previous works.

Aims: The vegetation classification system of China (China-VCS) is not completed. Stipa steppes are the most important steppes in China. Here we made optimal use of available plot data to classify Stipa steppes into associations in a way that is consistent with International Vegetation Classification. Study Area: the Songnen Plain, Inner Mongolian Plateau, Loess Plateau, Tibetan Plateau, and the northwest mountain areas of China. Methods: We used 1337 plots to partition the Stipa steppes of China into clusters using hierarchical clustering. Supervised noise clustering was used to improve the classifications at the group, alliance, and association levels. Non-metric multidimensional scaling ordination was used to visualize the homogeneity of plots within each cluster, and we overlaid site and climatic vectors. Diagnostic species were identified for each cluster using Indicator Species Analysis. Results: We defined five biogeographic groups, 26 alliances, 91 associations, and 12 communities of Stipa steppes of China. The Stipa-dominated alliances in the framework of the current China-VCS were verified, but the four vegetation subformations of Tussock Steppe were not completely supported by this study. Conclusions: This is the first systematical and comprehensive classification for Stipa steppes in China based on plot data. Our classification used a set of dominant species and diagnostic species to define biogeogrpahic groups, alliances and associations, ensuring compatibility with the International Vegetation Classification. Taxonomic reference: Flora Reipublicae Popularis Sinicae, Flora of China Abbreviations: AMT = Annual Mean Temperature; AP = Annual Precipitation; China-VCS = vegetation classification system of China; IVC = international vegetation classification; MTCQ = Mean Temperature of Coldest Quarter; MTWQ = Mean Temperature of Warmest Quarter; NC = noise clustering; NMDS = non-metric multidimensional scaling; PDQ = Precipitation of Driest Quarter; PS = Precipitation Seasonality; PWQ = Precipitation of Wettest Quarter; TS = Temperature Seasonality

Abstract Background Glioblastoma multiforme (GBM) is the most common aggressive malignant brain tumor. However, the molecular mechanism of glioblastoma formation is still poorly understood. To identify candidate genes that may be connected to glioma growth and development, weighted gene co-expression network analysis (WGCNA) was performed to construct a gene co-expression network between gene sets and clinical characteristics. We also explored the function of the key candidate gene. Methods Two GBM datasets were selected from GEO Datasets. The R language was used to identify differentially expressed genes. WGCNA was performed to construct a gene co-expression network in the GEO glioblastoma samples. A custom Venn diagram website was used to find the intersecting genes. The GEPIA website was applied for survival analysis to determine the significant gene, FUBP3. OS, DSS, and PFI analyses, based on the UCSC Cancer Genomics Browser, were performed to verify the significance of FUBP3. Immunohistochemistry was performed to evaluate the expression of FUBP3 in glioblastoma and adjacent normal tissue. KEGG and GO enrichment analyses were used to reveal possible functions of FUBP3. Microenvironment analysis was used to explore the relationship between FUBP3 and immune infiltration. Immunohistochemistry was performed to verify the results of the microenvironment analysis. Results GSE70231 and GSE108474 were selected from GEO Datasets, then 715 and 694 differentially expressed genes (DEGs) from GSE70231 and GSE108474, respectively, were identified. We then performed weighted gene co-expression network analysis (WGCNA) and identified the most downregulated gene modules of GSE70231 and GSE108474, and 659 and 3915 module genes from GSE70231 and GSE108474, respectively, were selected. Five intersection genes (FUBP3, DAD1, CLIC1, ABR, and DNM1) were calculated by Venn diagram. FUBP3 was then identified as the only significant gene by survival analysis using the GEPIA website. OS, DSS, and PFI analyses verified the significance of FUBP3. Immunohistochemical analysis revealed FUBP3 expression in GBM and adjacent normal tissue. KEGG and GO analyses uncovered the possible function of FUBP3 in GBM. Tumor microenvironment analysis showed that FUBP3 may be connected to immune infiltration, and immunohistochemistry identified a positive correlation between immune cells (CD4 + T cells, CD8 + T cells, and macrophages) and FUBP3. Conclusion FUBP3 is associated with immune surveillance in GBM, indicating that it has a great impact on GBM development and progression. Therefore, interventions involving FUBP3 and its regulatory pathway may be a new approach for GBM treatment.

In this paper, a dynamic model of Middle East Respiratory Syndrome Coronavirus (MERS-CoV) with periodic coefficients is proposed and studied. By using the continuation theorem of the coincidence degree theory, we obtain some sufficient conditions for the existence of positive periodic solutions of the model. The periodic model degenerates to an autonomous case, and our conditions can be degenerated to the basic reproductive number $ R_0 > 1 $. Finally, we give some numerical simulations to illustrate our main theoretical results.

In recent years, graph neural network is used to process graph data and has been successfully applied to graph node classification task. Due to the complexity of graph structure and the difficulty of obtaining node labels, node classification in datasets with fewer labels becomes a challenge. Existing node classification problems with few-label nodes datasets usually use neighbor aggregation schemes. However, these methods lack the “graph pooling mechanism,” which makes these models impossible to make full use of the global graph information. To solve the problem, we propose a Hierarchical Structure-Feature aware Graph Neural Network (HSFGNN) model. The model learns node features by a hierarchical mechanism that repeatedly utilizes coarsening and refining methods at different levels. Firstly, we use topological information, node characteristics and connectivity of the graph to construct an intuitive and effective coarsening part based on multivariable analysis technology. Secondly, we aggregate the unselected nodes’ features into the top-k nodes, so that the coarser nodes contain more abundant valid graph information. Finally, we propose an additional attention mechanism to obtain more accurate final representations of nodes. Experimental results show that the HSFGNN model achieves outstanding classification accuracy on the dataset with less labeled data.

BackgroundGallbladder carcinoma (GBC) is a biliary tract tumor with a high mortality rate. The objectives of this study were to explore the risk factors of GBC in patients with gallstones and to establish effective screening indicators.MethodsA total of 588 patients from medical centers in two different regions of China were included in this study and defined as the internal test samples and the external validation samples, respectively. We retrospectively reviewed the differences in clinicopathologic data of the internal test samples to find the independent risk factors that affect the occurrence of GBC. Then, we constructed three different combined predictive factors (CPFs) through the weighting method, integral system, and nomogram, respectively, and named them CPF-A, CPF-B, and CPF-C sequentially. Furthermore, we evaluated these indicators through calibration and DCA curves. The ROC curve was used to analyze their diagnostic efficiency. Finally, their diagnostic capabilities were validated in the external validation samples.ResultsIn the internal test samples, the results showed that five factors, namely, age (RR = 3.077, 95% CI: 1.731-5.496), size of gallstones (RR = 13.732, 95% CI: 5.937-31.762), course of gallstones (RR = 2.438, 95% CI: 1.350-4.403), CEA (RR = 9.464, 95% CI: 3.394-26.392), and CA199 (RR = 9.605, 95% CI: 4.512-20.446), were independent risk factors for GBC in patients with gallstones. Then, we established three predictive indicators: CPF-A, CPF-B, and CPF-C. These models were further validated using bootstrapping with 1,000 repetitions. Calibration and decision curve analysis showed that the three models fit well. Meanwhile, multivariate analysis showed that CPF-B and CPF-C were independent risk factors for GBC in patients with gallstones. In addition, the validation results of the external validation samples are essentially consistent with the internal test samples.ConclusionAge (≤58.5 vs. >58.5 years), size of gallstones (≤1.95 vs. >1.95cm), course of gallstones (≤10 vs. >10 years), CEA (≤5 vs. >5 ng/ml), and CA199 (≤37 vs. >37 U/ml) are independent risk factors for GBC in patients with gallstones. When positive indicators were ≥2 among the five independent risk factors or the score of the nomogram was >82.64, the risk of GBC was high in gallstone patients.

The strengthening of regional habitat quality is crucial to protect biodiversity and fully utilize ecosystem services such as those provided by forestry and aquatic ecosystems. However, the long-term patterns of change in the habitat quality of the Luoxiao Mountains area, which is both an important ecological barrier area and a concentrated poverty-stricken area, and the driving mechanism remain unclear. In this study, the InVEST model was used to assess the habitat quality of the Luoxiao Mountains area in 1995 to 2020, and the spatial autocorrelation model was used to explore the spatial and temporal variation and distribution characteristics of habitat quality. Further, ordinary least squares (OLS) model, geographically weighted regression (GWR) model, and random forest (RF) algorithm were combined with multidimensional datasets to explore the underlying mechanisms driving changes in habitat quality. According to the results, the habitat quality indices of the Luoxiao Mountains area in 1995, 2005, 2015, and 2020 were 0.822, 0.818, 0.817, and 0.813, respectively, with an overall decreasing trend. The RF model was the best fit for habitat quality, better than the GWR and OLS models. Physical geographic factors such as slope and precipitation, as well as socioeconomic factors such as gross domestic product, were key drivers of habitat quality in the Luoxiao Mountains. Precise implementation of ecological protection and restoration measures, improvements in the efficiency of spatial utilization, and exploration of the value of ecological products are key factors in maintaining a balance between habitat quality and economic growth into the future.

Thura and colleagues report that PRL3 promotes PGCCs, which are found to be enriched in relapsed tumours. The authors demonstrated that this relapse can be prevented using PRL3-zumab for use in adjuvant immunotherapy to target PRL3-expressing PGCCs, thus preventing metastasis and relapse.

Abstract Vegetation community complexity is a critical factor influencing terrestrial ecosystem stability. China, the country leading the world in vegetation greening resulting from human activities, has experienced dramatic changes in vegetation community composition during the past 30 years. However, how China's vegetation community complexity varies spatially and temporally remains unclear. Here, we examined the spatial pattern of China's vegetation community complexity and its temporal changes from the 1980s to 2015 using two vegetation maps of China as well as more than half a million field samples. Spatially, China's vegetation community complexity distribution is primarily dominated by elevation, although temperature and precipitation can be locally more influential than elevation when they become the factors limiting plant growth. Temporally, China's vegetation community complexity shows a significant decreasing trend during the past 30 years, despite the observed vegetation greening trend. Prevailing climate warming across China exhibits a significant negative correlation with the decrease in vegetation community complexity, but this correlation varies with biogeographical regions. The intensity of human activities have an overall negative influence on vegetation community complexity, but vegetation conservation and restoration efforts can have a positive effect on maintaining vegetation composition complexity, informing the critical role of vegetation management policies in achieving the sustainable development goal.

In this paper, we consider a class of SI epidemic model with nonlinear incidence, feedback controls and four different discrete time delays. By skillfully constructing appropriate Lyapunov functionals, and combining Lyapunov-LaSalle invariance principle and Barbalat's lemma, the global dynamics of the model are established. Our results extend and improve related works in the existing literatures.

Affected by electric field generated in power transmission line, live worker on the high-voltage transmission line is in dangerous working environment. In this paper, posture perception, numerical simulation, and risk assessment are adopted to realize the deep fusion of physical trajectory and spatial virtual electric field distribution of live worker, and digital twin bodies of live worker in different live working scenarios are constructed. Firstly, posture trajectories and 3D model of living worker in typical operation conditions are captured and reconstructed by full-body inertial action capture technology and this technology use motion capture unit which include 3-aixs accelerometer/gyroscope/magnetic field sensors. The length of complex gap and body workspace under various live work scenes are also calculated. By static electrical field finite element (FE) numerical modeling, surface electrical field distributions of live worker under different posture trajectories are then calculated. Finally, interactive mechanism between “body-information-physical environment-virtual environment” is introduced, and potential risk of live worker is on-line assessed by live work guide rules. This work develops a new assessment and protection method for virtual training and field operations of high-voltage live worker. Which is of great significance for enhancing operation level and ensuring living workers’ safety.

Jaw defects are common in oral and maxillofacial diseases and require surgical repair in extreme cases. Given the limitations in availability and efficacy of autologous bone grafts or allografts, great effort has been made in finding suitable, biocompatible, and effective artificial bone materials. Considering the key role of inflammation in bone resorption, we sought to identify a polypeptide with anti-inflammatory and bone-promoting effects. Rat bone marrow-derived mesenchymal cells (BMSCs) were treated with lipopolysaccharide (LPS) to induce an inflammatory environment, and 1,538 differentially abundant polypeptides were identified using mass spectrometry. Based on mass spectrometry signal intensity, multiple of difference, and structural stability, PAP was screened out as the polypeptide with the lowest abundance in the inflammatory condition. PAP showed no cytotoxicity to BMSCs with increasing concentrations. PAP (10 μM) also increased alkaline phosphatase activity and mRNA expression of Ocn, Bmp2, and Runx2 in a concentration-dependent manner, which confirmed that it can promote osteogenic induction of rat BMSCs. Moreover, PAP reduced LPS-induced expression of inflammatory cytokines (TNF-α, IL-1β, IL-6) and reactive oxygen species and inhibited polarization of RAW 264.7 macrophages to the inflammatory type. Finally, a skull defect mouse model was established, and mice were injected with LPS and/or PAP. Micro-CT, histological analysis, and immunohistochemical staining showed that PAP significantly reduced the number of LPS-induced bone resorption pits and maintained bone integrity. Overall, the polypeptide PAP screened using LPS stimulation of BMSCs is not cytotoxic and can inhibit the inflammatory reaction process to promote osteogenesis. This study thus provides a basis for development of PAP as a new osteogenic material in the repair of jaw defects.

The output power–voltage (P–V) curve of a solar photovoltaic (PV) power system shows a single peak under an even irradiation environment, nevertheless, but often exhibits seriously nonlinear multi-peak characteristics under partial shading conditions (PSCs). Then, traditional maximum power point tracking (MPPT) control methods may fail to find the maximum power point (MPP). Many different MPPT control methods have been proposed to adjust the peak power output and improve the generating efficiency of the PV system. In this paper, the main MPPT techniques for PV systems are reviewed and summarized, and divided into three groups according to their control theoretic and optimization principles. Especially, the advantages and disadvantages of the MPPT techniques for PV system under PSCs are compared and analyzed. Finally, possible future research directions for MPPT are discussed.

Abstract Grazing is a traditional grassland management technique and greatly alters ecosystem nutrient cycling. The effects of grazing intensity on the nutrient dynamics of soil and plants in grassland ecosystems remain uncertain, especially among microelements. A 2‐year field grazing experiment was conducted in a typical grassland with four grazing intensities (ungrazed control, light, moderate, and heavy grazing) in Inner Mongolia, China. Nutrient concentration was assessed in soil and three dominant plant species (Stipa krylovii, Leymus chinensis, and Cleistogenes squarrosa). Assessed quantities included four macroelements (carbon (C), nitrogen (N), phosphorus (P), and magnesium (Mg)) and four microelements (copper (Cu), iron (Fe), manganese (Mn), and zinc (Zn)). Soil total C, total N, total P, available N, and available P concentrations significantly increased with grazing intensity but soil Mg, Cu, Fe, Mn, Zn concentrations had no significant response. Plant C concentration decreased but plant N, P, Mg, Cu, Fe, Mn, and Zn concentrations significantly increased with grazing intensity. In soil, macroelement dynamics (i.e., C, N, and P) exhibited higher sensitivity with grazing intensity, conversely in plants, microelements were more sensitive. This result indicates macroelements and microelements in soil and plants had asymmetric responses with grazing intensity. The slopes of nutrient linear regression in C. squarrosa were higher than that of S. krylovii and L. chinensis, indicating that C. squarrosa had higher nutrient acquisition capacity and responded more rapidly to heavy grazing. These findings indicate that short‐term heavy grazing accelerates nutrient cycling of the soil–plant system in grassland ecosystems, elucidate the multiple nutrient dynamics of soil and plants with grazing intensity, and emphasize the important function of microelements in plant adaptation in grazing management.

Hyperspectral data have been widely used in various fields due to its rich spectral and spatial information in recent years. Yet, hyperspectral images are always tainted by a variety of mixed noises. These noises seriously limit the accuracy of subsequent applications. To remove noise, this paper, based on low-rank tensor decomposition, combined with non-local self-similar prior information, proposes a tensor-based non-local low-rank denoising model, where non-local self-similarity uses mainly spatial correlation while low-rank tensor decomposition method uses mainly spectral correlation between bands. Traditional tensor-based methods are commonly NP-hard to compute and are sensitive to sparse noise. However, the method proposed in this paper can separate efficiently the low-rank clean image from Gaussian noise and sparse noise (pulses, deadlines, stripes, speckle, etc.) by using a new tensor singular value decomposition (T-SVD) and tensor nuclear norm (TNN). The NP-hard task was also achieved well by the alternating direction multiplier method. Due to the full use of spectral and spatial information of the data, Gaussian noise and sparse noise can be effectively removed. The effectiveness of our algorithm was verified through experiments using simulated and real data.

Based on the boost full bridge isolated converter (BFBIC) topology and considering the sudden changes in the external environment, a global maximum power point tracking (GMPPT) control strategy based on an improved gray wolf optimizer (IGWO) algorithm is proposed in this paper. In the strategy, a nonlinear tangent trigonometric function as a convergence factor is integrated into the gray wolf optimizer (GWO) algorithm. In addition, the active-clamp circuit and phase-shift are used to implement the soft switch technology for BFBIC converter in photovoltage (PV) system. Finally, the maximum power point tracking (MPPT) performance on PV system with the proposed IGWO algorithm under static and dynamic partial shading conditions (PSCs) was investigated and compared with other common perturb and observe(P&O), particle swarm optimization (PSO), artificial bee colony (ABC), adapt inertia weight salp swarm algorithm (WSSA), salp swarm algorithm with grey wolf optimizer (SSA-GWO), SSA with PSO (SSA-PSO), enhanced GWO (EGWO) MPPT algorithms. The effectiveness and stability of the proposed control strategy are validated, especially tracking speed under PSCs. Simulation results show that the BFBIC topology with the proposed IGWO algorithm outperforms other algorithms on most cases, especially only takes the tracking time of 0.24s and reaches the efficiency of 98.54% under the most severe PSCs.

In recent years, sparse unmixing has attracted significant attention, as it can effectively avoid the bottleneck problems associated with the absence of pure pixels and the estimation of the number of endmembers in hyperspectral scenes. The joint-sparsity model has outperformed the single sparse unmixing method. However, the joint-sparsity model might cause some aliasing artifacts for the pixels on the boundaries of different constituent endmembers. To address this shortcoming, researchers have developed many unmixing algorithms based on low-rank representation, which makes good use of the global structure of data. In addition, the high mutual coherence of spectral libraries strongly affects the applicability of sparse unmixing. In this study, adopting combined constraints imposing sparsity and low rankness, a novel algorithm called nonconvex joint-sparsity and low-rank unmixing with dictionary pruning is developed In particular, we impose sparsity on the abundance matrix using the ℓ2,p mixed norm, and we also employ the weighted Schatten p-norm instead of the convex nuclear norm as an approximation for the rank. The key parameter p is set between 0.4 and 0.6, and a good quality sparse solution is generated. The effectiveness of the proposed algorithm is demonstrated on both simulated and real hyperspectral datasets.

For a long time, forestry management has often focused on the protection of species diversity, and mistakenly believed that protecting species diversity protects genetic diversity. Therefore, research that integrates community ecology and population genetics has become important because it can help elucidate whether the targets for protecting specific and genetic diversity are congruent. In this study, we have emphasized the impact of the community on the population because no previous studies have considered the community composition of a place a priori. Based on the Huangshan 10.24 ha dynamics forest plot, we a priori considered the community composition in the plot to test species-genetic diversity among the tree layers. Firstly, a redundancy analysis (RDA) found that Castanopsis eyrei and Pinus massoniana were the dominant species. Secondly, specific and genetic diversity are not congruent in Huang Shan. Finally, the structural equation model (SEM) showed that the different degrees of response by community composition and population structure to environmental heterogeneity are the main reasons for the mismatch between species diversity and genetic diversity. The results suggest that we must focus on genetic diversity, as well as on protecting species diversity.

In this paper, we propose and study a Middle East respiratory syndrome coronavirus (MERS-CoV) infection model with cytotoxic T lymphocyte (CTL) immune response and intracellular delay. This model includes five compartments: uninfected cells, infected cells, viruses, dipeptidyl peptidase 4 (DPP4), and CTL immune cells. We obtained an immunity-inactivated reproduction number R0 and an immunity-activated reproduction number R1. By analyzing the distributions of roots of the corresponding characteristic equations, the local stability results of the infection-free equilibrium, the immunity-inactivated equilibrium, and the immunity-activated equilibrium were obtained. Moreover, by constructing suitable Lyapunov functionals and combining LaSalle’s invariance principle and Barbalat’s lemma, some sufficient conditions for the global stability of the three types of equilibria were obtained. It was found that the infection-free equilibrium is globally asymptotically stable if R0≤1 and unstable if R0>1; the immunity-inactivated equilibrium is locally asymptotically stable if R0>1>R1 and globally asymptotically stable if R0>1>R1 and condition (H1) holds, but unstable if R1>1; and the immunity-activated equilibrium is locally asymptotically stable if R1>1 and is globally asymptotically stable if R1>1 and condition (H1) holds.

Abstract Background Low-molecular-weight chitosan oligosaccharide (LMCOS), a chitosan degradation product, is water-soluble and easily absorbable, rendering it a popular biomaterial to study. However, its effect on bone remodelling remains unknown. Therefore, we evaluated the effect of LMCOS on lipopolysaccharide (LPS)-induced bone resorption in mice. Methods Six-week-old male C57BL/6 mice (n = five per group) were randomly divided into five groups: PBS, LPS, LPS + 0.005% LMCOS, LPS + 0.05% LMCOS, and LPS + 0.5% LMCOS. Then, the corresponding reagents (300 μL) were injected into the skull of the mice. To induce bone resorption, LPS was administered at 10 mg/kg per injection. The mice were injected three times a week with PBS alone or LPS without or with LMCOS and sacrificed 2 weeks later. The skull was removed for micro-computed tomography, haematoxylin-eosin staining, and tartrate-resistant acid phosphatase staining. The area of bone damage and osteoclast formation were evaluated and recorded. Results LMCOS treatment during LPS-induced skull resorption led to a notable reduction in the area of bone destruction; we observed a dose-dependent decrease in the area of bone destruction and number of osteoclasts with increasing LMCOS concentration. Conclusions Our findings showed that LMCOS could inhibit skull bone damage induced by LPS in mice, further research to investigate its therapeutic potential for treating osteolytic diseases is required.

Abstract Fencing is an effective and practical method for restoring degraded grasslands in northern China. However, little is known about the role of excess litter accumulation due to long‐term fencing in regulating abiotic environment and driving changes in community structure and function. We conducted a three‐year field experiment in two fenced grasslands in Inner Mongolia, and monitored light quantity, soil temperature, and soil moisture continuously, and determined community height, community aboveground net primary productivity (ANPP), and the relative dominance of different plant functional groups. Litter accumulation reduced light quantity and soil temperature but increased soil moisture. The regulating effects of litter accumulation on soil temperature and soil moisture fluctuated temporally and gradually weakened over the growing season. Litter accumulation also altered community vertical structure and function by increasing community height and ANPP. The increase in soil moisture increased the relative dominance of rhizome grasses but suppressed bunch grasses, thereby shifting bunch grass grasslands to rhizome grass grasslands. Our findings provide a potential mechanism for community succession in the context of litter accumulation in fenced grasslands and indicate that the vegetation and ecosystem services of degraded grasslands are improved after appropriate fencing.

Fever is a extremely common symptom in infants and young children. Due to the lowresistance of infants and young, long-term fever may cause damage to the child’s body. Clinically,some children with long-term fever was eventually diagnosed with Kawasaki disease (KD). KD, anautoimmune disease, is a systemic vasculitis mainly affecting children younger than 5 years old. Dueto the delayed therapy and diagnosis, coronary artery abnormalities (CAAs) develop in children with KD, and leads to a high risk of acquired heart disease. Later, patients may have myocardial infarctionor even die a sudden death. Unfortunately, at present, the pathogenesis of KD remains unknownand KD lacks of specific and sensitive biomarkers, thus bringing difficulties to diagnosis and therapy.Therefore it is a highly focused topic to research on the mechanism of KD. Some scholars believethat KD is caused by the cross reaction of external infection and organ tissue composition, herebytriggering disorder of the immune system and producing a variety of cytokines. On the basis ofconsidering the cytokines such as vascular endothelial cells, inflammatory factors, adhesion factorsand chemokines, endothelial cell growth factors, put forward a kind of dynamic model of pathogenesisof KD by the theory of ordinary differential equation. It is found that the dynamic model can showcomplex dynamic behavior, such as the forward and backward bifurcation of the equilibria. This articlereveals the possible complexity of KD infection, and provides a theoretical references for the researchof pathogenic mechanism and clinical treatment of KD.

Summary: Non-oxidative propane dehydrogenation (PDH) is an attractive reaction from both an industrial and a scientific viewpoint because it allows direct large-scale production of propene and fundamental analysis of C-H activation respectively. The main challenges are related to achieving high activity, selectivity, and on-stream stability of environment-friendly and cost-efficient catalysts without non-noble metals. Here, we describe an approach for the preparation of supported ultrasmall ZnO nanoparticles (2–4 nm, ZnO NPs) for high-temperature applications. The approach consists of encapsulation of NPs into a nitrogen-doped carbon (NC) layer in situ grown from zeolitic imidazolate framework-8 on a Silicalite-1 support. The NC layer was established to control the size of ZnO NPs and to hinder their loss to a large extent at high temperatures. The designed catalysts exhibited high activity, selectivity, and on-stream stability in PDH. Propene selectivity of about 90% at 44.4% propane conversion was achieved at 600°C after nearly 6 h on stream. : Chemistry; Catalysis; Nanoparticles Subject Areas: Chemistry, Catalysis, Nanoparticles

In this paper, a multi-parameterized proximal point algorithm combining with a relaxation step is developed for solving convex minimization problem subject to linear constraints. We show its global convergence and sublinear convergence rate from the prospective of variational inequality. Preliminary numerical experiments on testing a sparse minimization problem from signal processing indicate that the proposed algorithm performs better than some well-established methods.

The development of green residences is crucial to reducing energy consumption and carbon emissions of the construction industry. However, the study on the spatial distribution characteristics of green residences and its influencing factors has not attracted enough attention in the academic circles. Base on the panel database on the number of each star green residences and their driving factors at the municipal level from 2008 to 2016, this paper employed the Weighted Standard Deviational Ellipse model to reveal the spatial and temporal evolution features of green residences in China, creatively introduced an improved Gini coefficient (G′-score) to measure the green residences development in each city, and utilized the panel Tobit model and average marginal effect to identify the driving mechanisms and key factors of green residences from economy, society, the real estate market, policy and climate. The main conclusions show that: (1) China has formed a relatively stable and clear temporal and spatial evolution path since 2011, such as the center of gravity and coverage having moved to the west, and the direction of development trend having weakened; (2) China’s green residence is mainly distributed in the central and eastern regions, and the main direction layout is northeast–southwest; (3) the development of green residences is the result of the interaction of various factors, and the driving force of each factor varies greatly under the single action and the interaction; (4) the driving effects of the same factor on green residences with different star ratings are inconsistent in sign, magnitude, and significance, the same as for each factor under the same star rating.

Long-term degradation of black soil has led to reductions in soil fertility and ecological service functions, which have seriously threatened national food security and regional ecological security. This study is motivated by the UN’s Sustainable Development Goal (SDG) 2—Zero Hunger, specifically, SDG 2.4 Sustainable Food Production Systems. The aim was to monitor the soil organic matter (SOM) content of black soil and its dynamics via hyperspectral remote sensing inversion. This is of great significance to the effective utilization and sustainable development of black soil resources. Taking the typical black soil area of Northeast China as an example, the hyperspectral data of ground features were compared with SOM contents measured in soil samples to correlate SOM with spectral features. Based on their quantitative relationship, a dynamic fitness inertia weighted particle swarm optimization (DPSO) algorithm is proposed, which balances the global and local search abilities of a particle swarm optimization algorithm. The DPSO algorithm is applied to the parameter adjustment of an artificial neural network (BPNN), which is used instead of a traditional error back propagation algorithm, to build a DPSO-BPNN model. Then a global optimal analytical expression of hyperspectral inversion is obtained to improve the generalization ability and stability of the remote sensing quantitative inversion model. The results show that DPSO-BPNN model is more stable and accurate than existing models, such as multiple stepwise regression, partial least squares, and BP neural network models (adjust complex coefficient of determination = 0.89, root mean square error = 1.58, relative recent deviation = 2.93). The results of DPSO-BPNN inversion are basically consistent with the trend in SOM contents measured during surface geochemical exploration. As such, this study provides a basis for hyperspectral remote sensing inversion and monitoring of the SOM contents in black soil.

With rapid economic and demographic growth, traffic conditions in medium and large cities are becoming extremely congested. Numerous metropolitan management organizations hope to promote the coordination of traffic and urban development by formulating and improving traffic development strategies. The effectiveness of these solutions depends largely on an accurate assessment of the distribution of urban hotspots (centers of traffic activity). In recent years, many scholars have employed the K-Means clustering technique to identify urban hotspots, believing it to be efficient. K-means clustering is a sort of iterative clustering analysis. When the data dimensionality is large and the sample size is enormous, the K-Means clustering algorithm is sensitive to the initial clustering centers. To mitigate the problem, a hybrid heuristic “fuzzy system-particle swarm-genetic” algorithm, named FPSO-GAK, is employed to obtain better initial clustering centers for the K-Means clustering algorithm. The clustering results are evaluated and analyzed using three-cluster evaluation indexes (SC, SP and SSE) and two-cluster similarity indexes (CI and CSI). A taxi GPS dataset and a multi-source dataset were employed to test and validate the effectiveness of the proposed algorithm in comparison to the Random Swap clustering algorithm (RS), Genetic K-means algorithm (GAK), Particle Swarm Optimization (PSO) based K-Means, PSO based constraint K-Means, PSO based Weighted K-Means, PSO-GA based K-Means and K-Means++ algorithms. The comparison findings demonstrate that the proposed algorithm can achieve better clustering results, as well as successfully acquire urban hotspots.