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Abstract The rapid development of UAV communication technology makes it have application potential in wireless systems. However, for the optimization problem of UAV base station providing communication for ground personnel in the disaster area under special natural disasters, traditional deep reinforcement learning is used. Algorithms cannot solve such problems well. This article proposes the AD3QN algorithm combined with the attention mechanism, which can communicate with disaster victims on the ground better and more quickly, providing better information collection for rescue missions and completing the task of communication optimization. In the mission simulation environment, in order to make the environment more realistic, we innovatively designed the ground user distribution model, air-to-ground communication model, and electromagnetic interference model. Finally, the effect of the proposed algorithm is evaluated by comparing different deep reinforcement learning algorithms. The results show that the algorithm we proposed can provide communication services faster and has higher practicability in terms of algorithm.

Abstract The large void space of organic electrodes endows themselves with the capability to store different counter ions without size concern. In this work, a small-molecule organic bipolar electrode called diquinoxalino[2,3-a:2’,3’-c]phenazine-2,6,10-tris(phenoxazine) (DQPZ-3PXZ) is designed. Based on its robust solid structure by the π conjugation of diquinoxalino[2,3-a:2’,3’-c]phenazine (DQPZ) and phenoxazine (PXZ), DQPZ-3PXZ can indiscriminately and stably host 5 counter ions with different charge and size (Li+, Na+, K+, PF6 − and FSI−). In Li/Na/K-based half cells, DQPZ-3PXZ can deliver the peak discharge capacities of 257/243/253 mAh g−1 cathode and peak energy densities of 609/530/572 Wh kg−1 cathode, respectively. The Li/Na/K-based dual-ion symmetric batteries can be constructed, which can be activated through the 1st charge process and show the stable discharge capacities of 85/66/72 mAh g−1 cathode and energy densities of 59/50/52 Wh kg−1 total mass, all running for more than 15000 cycles with nearly 100% capacity retention.

Abstract Background Presenteeism has become a significant issue related to health. However, the effect of fatigue and organizational identification on the relationship between emotional labor and presenteeism among Chinese nurses remains unclear. This study aims to explore the correlation of Chinese nurses’ emotional labor, fatigue and organizational identification with presenteeism, and to analyze the mediating effect of fatigue and the moderating effect of organizational identification on the relationship between emotional labor and presenteeism. Methods A cross-sectional study was performed from June to October 2022 in Changchun City, Jilin Province, China. In total, 1,630 nurses were asked to complete a range of self-administered questionnaires, including the Emotional Labor Scale, the Fatigue Scale, the Organizational Identification Scale and the Stanford Presenteeism Scale. Besides, the PROCESS macro and multiple linear regression were used for moderated mediation analysis. Results Emotional labor (r = 0.108, P

Abstract Background Oral mucositis (OM) is a prevalent and painful complication in patients undergoing anticancer treatment, which significantly impacts patients’ quality of life (QoL) and adherence to therapy. The use of oral probiotics as a preventive strategy for OM has shown promise, but the clinical evidence remains inconclusive. This meta-analysis of randomized controlled trials (RCTs) aims to evaluate the efficacy of probiotics in preventing OM caused by radiotherapy and/or chemotherapy. Methods A comprehensive search of PubMed, EMBASE, Web of Science, Cochrane Library, and ClinicalTrials.gov was conducted up to January 31, 2024, to identify eligible RCTs. The primary outcomes were the incidences of severe OM and all-grade OM. Secondary outcomes included rates of anticancer treatment completion, clinical response, requirement for enteral nutrition, time course of OM, body weight loss, QoL, and adverse events (AEs). Risk ratios (RRs) with 95% confidence intervals (CIs) were calculated. Results A total of 12 RCTs involving 1,376 patients were included in the quantitative analysis. Probiotics administration significantly reduced the risk of severe OM (RR = 0.61, 95%CI: 0.53–0.72, P

Abstract The early diagnosis of liver cancer is crucial for the treatment and depends on the coordinated use of several test procedures. Early diagnosis is crucial for precision therapy in the treatment of the hepatocellular carcinoma (HCC). Therefore, in this study, the NK cell-related gene prediction model was used to provide the basis for precision therapy at the gene level and a novel basis for the treatment of patients with liver cancer. Natural killer (NK) cells have innate abilities to recognize and destroy tumor cells and thus play a crucial function as the “innate counterpart” of cytotoxic T cells. The natural killer (NK) cells is well recognized as a prospective approach for tumor immunotherapy in treating patients with HCC. In this research, we used publicly available databases to collect bioinformatics data of scRNA-seq and RNA-seq from HCC patients. To determine the NK cell-related genes (NKRGs)-based risk profile for HCC, we isolated T and natural killer (NK) cells and subjected them to analysis. Uniform Manifold Approximation and Projection plots were created to show the degree of expression of each marker gene and the distribution of distinct clusters. The connection between the immunotherapy response and the NKRGs-based signature was further analyzed, and the NKRGs-based signature was established. Eventually, a nomogram was developed using the model and clinical features to precisely predict the likelihood of survival. The prognosis of HCC can be accurately predicted using the NKRGs-based prognostic signature, and thorough characterization of the NKRGs signature of HCC may help to interpret the response of HCC to immunotherapy and propose a novel tumor treatment perspective.

Abstract Computer haptics (CH) is about integration of tactile sensation and rendering in Metaverse. However, unlike computer vision (CV) where both hardware infrastructure and software programs are well developed, a generic tactile data capturing device that serves the same role as what a camera does for CV, is missing. Bioinspired by electrophysiological processes in human tactile somatosensory nervous system, here we propose a tactile scanner along with a neuromorphically-engineered system, in which a closed-loop tactile acquisition and rendering (re-creation) are preliminarily achieved. Based on the architecture of afferent nerves and intelligent functions of mechano-gating and leaky integrate-and-fire models, such a tactile scanner is designed and developed by using piezoelectric transducers as axon neurons and thin film transistor (TFT)-based neuromorphic circuits to mimic synaptic behaviours and neural functions. As an example, the neuron-like tactile information of surface textures is captured and further used to render the texture friction of a virtual surface for “recreating” a “true” feeling of touch.

Context In China, HUANGQI is widely used for the treatment of Alzheimer’s disease (AD). However, a comprehensive understanding of its mechanism of anti-AD effects is lacking.Objective To explore the active ingredients of HUANGQI and its potential targets and mechanisms of action in AD.Materials and methods The active ingredients and targets of HUANGQI were screened from databases (TCSMP, ETCM, and BATMan), and AD-related genes were obtained from DrugBank and GeneCards. The same target genes were screened, and a drug-target disease network was constructed. The PPI network was constructed and GO and KEGG pathway enrichment analyses of the targets. The Cell Counting Kit-8 (CCK-8) assay was used to determine suitable HUANGQI treatment concentrations for HT-22 cells between 0-480 μg/mL. CCK-8, FITC-phalloidin and propidium iodide (PI) assays were used to examine the protective effect of (0, 60, 120, 240 μg/mL) of HUANGQI on 20 μM Aβ1-42-induced HT-22 cell cytotoxicity.Results Twelve active ingredients of HUANGQI were selected, with 679 common targets associated with AD. GO and KEGG analysis revealed that the therapeutic mechanisms of HUANGQI involve TNF, AGE, the NF-κB pathway, and nuclear receptor activity-related processes. The CCK-8 assay indicated that HUANGQI was not cytotoxic to HT-22 cells at concentrations less than 240 μg/mL and was able to attenuate Aβ1-42-induced cellular damage (EC50 = 83.46 μg/mL). FITC-phalloidin and PI assays suggested that HUANGQI could alleviate 20 μM Aβ1-42-induced neuronal cell cytotoxicity in a dose-dependent manner.Conclusion HUANGQI has a protective effect on Aβ1-42-induced nerve cell injury; further mechanism research was needed.

Abstract Automatic modulation classification models based on deep learning models are at risk of being interfered by adversarial attacks. In an adversarial attack, the attacker causes the classification model to misclassify the received signal by adding carefully crafted adversarial interference to the transmitted signal. Based on the requirements of efficient computing and edge deployment, a lightweight automatic modulation classification model is proposed. Considering that the lightweight automatic modulation classification model is more susceptible to interference from adversarial attacks and that adversarial training of the lightweight auto‐modulation classification model fails to achieve the desired results, an adversarial attack defense system for the lightweight automatic modulation classification model is further proposed, which can enhance the robustness when subjected to adversarial attacks. The defense method aims to transfer the adversarial robustness from a trained large automatic modulation classification model to a lightweight model through the technique of adversarial robust distillation. The proposed method exhibits better adversarial robustness than current defense techniques in feature fusion based automatic modulation classification models in white box attack scenarios.

Abstract Background Type 2 diabetes mellitus (T2D) is associated with an increased risk of cognitive dysfunction. Angiopoietin-like protein 8 (ANGPTL8) is an important regulator in T2D, but the role of ANGPTL8 in diabetes-associated cognitive dysfunction remains unknown. Here, we explored the role of ANGPTL8 in diabetes-associated cognitive dysfunction through its interaction with paired immunoglobulin-like receptor B (PirB) in the central nervous system. Methods The levels of ANGPTL8 in type 2 diabetic patients with cognitive dysfunction and control individuals were measured. Mouse models of diabetes-associated cognitive dysfunction were constructed to investigate the role of ANGPTL8 in cognitive function. The cognitive function of the mice was assessed by the Barnes Maze test and the novel object recognition test, and levels of ANGPTL8, synaptic and axonal markers, and pro-inflammatory cytokines were measured. Primary neurons and microglia were treated with recombinant ANGPTL8 protein (rA8), and subsequent changes were examined. In addition, the changes induced by ANGPTL8 were validated after blocking PirB and its downstream pathways. Finally, mice with central nervous system-specific knockout of Angptl8 and PirB −/− mice were generated, and relevant in vivo experiments were performed. Results Here, we demonstrated that in the diabetic brain, ANGPTL8 was secreted by neurons into the hippocampus, resulting in neuroinflammation and impairment of synaptic plasticity. Moreover, neuron-specific Angptl8 knockout prevented diabetes-associated cognitive dysfunction and neuroinflammation. Mechanistically, ANGPTL8 acted in parallel to neurons and microglia via its receptor PirB, manifesting as downregulation of synaptic and axonal markers in neurons and upregulation of proinflammatory cytokine expression in microglia. In vivo, PirB −/− mice exhibited resistance to ANGPTL8-induced neuroinflammation and synaptic damage. Conclusion Taken together, our findings reveal the role of ANGPTL8 in the pathogenesis of diabetes-associated cognitive dysfunction and identify the ANGPTL8-PirB signaling pathway as a potential target for the management of this condition.

Abstract Motivation The rational modelling of the relationship among drugs, targets and diseases is crucial for drug retargeting. While significant progress has been made in studying binary relationships, further research is needed to deepen our understanding of ternary relationships. The application of graph neural networks in drug retargeting is increasing, but further research is needed to determine the appropriate modelling method for ternary relationships and how to capture their complex multi-feature structure. Results The aim of this study was to construct relationships among drug, targets and diseases. To represent the complex relationships among these entities, we used a heterogeneous graph structure. Additionally, we propose a DTD-GNN model that combines graph convolutional networks and graph attention networks to learn feature representations and association information, facilitating a more thorough exploration of the relationships. The experimental results demonstrate that the DTD-GNN model outperforms other graph neural network models in terms of AUC, Precision, and F1-score. The study has important implications for gaining a comprehensive understanding of the relationships between drugs and diseases, as well as for further research and application in exploring the mechanisms of drug-disease interactions. The study reveals these relationships, providing possibilities for innovative therapeutic strategies in medicine.

Moringa oleifera Lam. (M. oleifera) has been used as a remedy for diabetes clinically. To discover the underlying mechanism, we investigated its hypoglycemic compounds and shed light on its regulatory targets and pathways using network pharmacology. A total of 13 active compounds of stem were shot, and they may relieve diabetes through 122 core intersecting targets, mainly regulating the biological processes of inflammatory response and apoptosis. Molecular docking showed binding advantages of the active compounds with proteins in apoptosis process. In experiments conducted on MIN6 cells, an islet β-cell line, the extract of M. oleifera stem was validated to protect cells from apoptosis through reducing cellular ROS and endoplasmic reticulum stress. And consistently with its protective effect on islet β-cells, M. oleifera stem alleviated hyperglycemia in Type 2 diabetes mellitus (T2DM) mice. These results offer novel evidence for the development of functional foods to treat T2DM with M. oleifera stem.

ABSTRACT: Carbapenems and colistin are vital antimicrobials used to treat Enterobacteriaceae-caused infections. The present study aimed to characterize the coexistence mechanism of carbapenem and colistin resistance in an Escherichia coli isolated from retail chicken meat. A total of 4 E. coli isolates co-harboring carbapenem resistance gene blaNDM (2 E. coli isolates with blaNDM-5 and 2 with blaNDM-9) and colistin resistance gene mcr-1. Antimicrobial susceptibility testing exhibited that all the 4 E. coli strains had multidrug resistance profile and consistent with the resistance genes they carried. MLST showed that 3 E. coli isolates belonged to a pathogenic E. coli lineage ST354, which is closely associated with human infections and pose a serious threat to public health. Whole genome sequencing (WGS) showed that 4 mcr-1-positive plasmids with sizes of 60.4 kb to 67.4 kb all belonged to the IncI2 type. A total of 5 blaNDM-harboring plasmids ranged from 99.0 kb to 138.3 kb, among which 4 plasmids belonged to unknow type and only pCS5L-NDM belonged to IncFIA/IncFIB group of hybrid plasmids, a novel carrier for blaNDM. Comparative analysis exhibited that the mcr-1 or blaNDM-carrying plasmids of E. coli strains from chicken meat showed high identity with that from Enterobacteriaceae of human origin, which indicated the risk of mcr-1 or blaNDM dissemination from retail meat to human. The simultaneous occurrence of mcr-1 and blaNDM in E. coli emphasizes the significant of antimicrobial resistance surveillance in retail meat.

The instability of anthocyanins significantly reduces their bioavailability as food nutrients. This proof-of-concept study aimed to develop efficient carriers for anthocyanins to overcome this challenge. Characterization of the hydrogels via SEM (scanning electron microscope) and rheological analysis revealed the formation of typical gel structures. MTT (methyl thiazolyl tetrazolium) and hemolysis assays confirmed that their high biocompatibility. Encapsulation efficiency analysis and fluorescence microscopy images demonstrated successful and efficient encapsulation of anthocyanins by pH-responsive hydrogels. Stability studies further validated the effect of peptide hydrogels in helping anthocyanin molecules withstand factors such as gastric acid, high temperatures, and heavy metals. Subsequently, responsive studies in simulated gastric (intestinal) fluid demonstrated that the pH-responsive peptide hydrogels could protect anthocyanin molecules from gastric acid while achieving rapid and complete release in intestinal fluid environments. These results indicate that these peptide hydrogels could stabilize anthocyanins and facilitate their controlled release, potentially leading to personalized delivery systems.

Early-onset epilepsy following ischemic stroke is a severe neurological condition, the pathogenesis of which remains incompletely understood. Recent studies suggest that Neural stem/progenitor cells (NSPCs) play a crucial role in the disease process, yet the precise molecular mechanisms regulating NSPCs have not been thoroughly investigated. This study utilized single-cell transcriptome sequencing and bioinformatics analysis to identify disease-related genes, which were subsequently validated in both in vitro and in vivo experiments. The findings revealed that Hsp90aa1 (heat shock protein 90 kDa alpha, class A member 1), Jun proto-oncogene (JUN), and CC Motif Ligation 2 (Ccl2) constitute an important regulatory axis influencing the migration and differentiation of NSPCs, potentially impacting the onset and progression of early-onset epilepsy post-ischemic stroke. Additionally, the expression of Hsp90aa1 was found to influence the likelihood of seizure occurrence and the severity of brain ischemia.

Lungs are exposed to external oxidants from the environment as in harmful particles and smog, causing oxidative stress in the lungs and consequently respiratory ailment. The NF-E2-related factor 2 (Nrf2) is the one with transcriptional regulatory function, while its related protein Kelch-like ECH-associated protein 1 (Keap1) inhibits Nrf2 activity. Together, they form the Keap1-Nrf2 pathway, which regulates the body's defense against oxidative stress. This pathway has been shown to maintain cellular homeostasis during oxidative stressing, inflammation, oncogenesis, and apoptosis by coordinating the expression of cytoprotective genes and making it a potential therapeutic target for respiratory diseases. This paper summarizes this point in detail in Chapter 2. In addition, this article summarizes the current drug development and clinical research progress related to the Keap1-Nrf2 signaling pathway, with a focus on the potential of Nrf2 agonists in treating respiratory diseases. Overall, the article reviews the regulatory mechanisms of the Keap1-Nrf2 signaling pathway in respiratory diseases and the progress of targeted drug research, aiming to provide new insights for treatment.

Merging bound states in the continuum (BICs) and avoided crossing of resonances (ACR) are promising theoretical approaches to greatly enhance the quality (Q) factors of quasi-BICs in reciprocal space. We observe the phenomena of merging BICs and ACR in millimeter-sized C4v symmetry photonic crystal structures. The ACR at Γ point is obtained in the variation of the structural parameter. In off-Γ region, the merging BICs at arbitrary locations are observed in the experimental measurements. The findings offer a pathway to high-performance photonic devices with potential applications in optoelectronics and microwave experimentation.

Unveiling the ecological and evolutionary mechanisms that guide the differentiation of various plant growth forms into vertical forest strata during forest degradation continues to pose a challenge. We utilized the biogeochemical niche theory to decipher these mechanisms. We measured leaf concentrations of basal elements (C, N, P, K, Ca, and Mg) and used them to generate the biogeochemical niches in herbs, shrubs, trees, and climbers from different vertical strata within a degraded forest and its neighboring mature forest in subtropical montane zones. Our results showed that biogeochemical niches varied significantly among growth forms. Biogeochemical niches also differed significantly between species in the degraded and mature forests, as evidenced by the significantly lower leaf C concentration relative to other nutrients in degraded forest species. This could be attributable mainly to the expansive canopy openness in the degraded forest, facilitating the colonization of light-demanding self-supporters and climbers. The phylogenetic signals in leaf nutrient concentrations were significantly present across all species, suggesting the general similarities in biogeochemical niches among closely related species. Following evolutionary model comparisons, stabilizing selection towards varying optimal leaf nutrient concentrations for distinct growth forms in the degraded or mature forest emerged as the most suitable model. Our study thus highlights the important role of phylogenetic biogeochemical niche conservatism and stabilizing selection towards various optimal leaf nutrient compositions for diverse growth forms in both degraded and mature forests in the formation of vertical plant communities during subtropical forest degradation.

Abstract Background Despite the existence of several Randomized Controlled Trials (RCTs) investigating Low-Dose Computed Tomography (LDCT) as a guide in lung biopsies, conclusive findings remain elusive. To address this contention, we conducted a systematic review and meta-analysis to evaluate the efficacy and safety of LDCT-guided lung biopsies. Methods A comprehensive search across major databases identified RCTs comparing the effectiveness of LDCT-guided with Standard-Dose Computed Tomography (SDCT)-guided lung biopsies. Subsequently, we utilized a random-effects model meta-analysis to assess diagnostic accuracy, radiation dose, operation duration, and clinical complications associated with these procedures. Results Out of 292 scrutinized studies, six RCTs representing 922 patients were included in the final analysis. Results indicated the differences between the LDCT and SDCT groups were not different with statistical significance in terms of diagnostic accuracy rates (Intent-to-Treat (ITT) populations: Relative Risk (RR) 1.01, 95% Confidence interval [CI] 0.97–1.06, p = 0.61; Per-Protocol (PP) populations: RR 1.01, 95% CI 0.98–1.04, p = 0.46), incidence of pneumothorax (RR 1.00, 95% CI 0.75–1.35, p = 0.98), incidence of hemoptysis (RR 0.95, 95% CI 0.63–1.43, p = 0.80), and operation duration (minutes) (Mean Differences [MD] -0.34, 95% CI -1.67-0.99, p = 0.61). Notably, LDCT group demonstrated a lower radiation dose (mGy·cm) with statistical significance (MD -188.62, 95% CI -273.90 to -103.34, p

Abstract Background 3D visualization technology applies computers and other devices to create a realistic virtual world for individuals with various sensory experiences such as 3D vision, touch, and smell to gain a more effective understanding of the relationships between real spatial structures and organizations. The purpose of this study was to comprehensively evaluate the effectiveness of 3D visualization technology in human anatomy teaching/training and explore the potential factors that affect the training effects to better guide the teaching of classroom/laboratory anatomy. Methods We conducted a meta-analysis of randomized controlled studies on teaching human anatomy using 3D visualization technology. We extensively searched three authoritative databases, PubMed, Web of Science, and Embase; the main outcomes were the participants’ test scores and satisfaction, while the secondary outcomes were time consumption and enjoyment. Heterogeneity by I² was statistically determined because I²> 50%; therefore, a random-effects model was employed, using data processing software such as RevMan, Stata, and VOSviewer to process data, apply standardized mean difference and 95% confidence interval, and subgroup analysis to evaluate test results, and then conduct research through sensitivity analysis and meta-regression analysis. Results Thirty-nine randomized controlled trials (2,959 participants) were screened and included in this study. The system analysis of the main results showed that compared with other methods, including data from all regions 3D visualization technology moderately improved test scores as well as satisfaction and enjoyment; however, the time that students took to complete the test was not significantly reduced. Meta-regression analysis also showed that regional factorsaffected test scores, whereas other factors had no significant impact. When the literature from China was excluded, the satisfaction and happiness of the 3D virtual-reality group were statistically significant compared to those of the traditional group; however, the test results and time consumption were not statistically significant. Conclusion 3D visualization technology is an effective way to improve learners’ satisfaction with and enjoyment of human anatomical learning, but it cannot reduce the time required for testers to complete the test. 3D visualization technology may struggle to improve the testers’ scores. The literature test results from China are more prone to positive results and affected by regional bias.

Abstract The collapse of the former Soviet Union signaled failure of large-scale experiment in communitarian property. Privatization reform consequently was taken as the start point to transfer the planned economy to a market economy by the post socialist countries. This also occurred in economic transition countries such as China. However, in overcoming the tragedy of the commons privatization might create anticommons problems. Here we develop a nested common-private interface framework from the perspective of resource system and resource units and apply this framework to explain reforms of rangeland property in China and Kyrgyzstan. We confirmed that the root of the dilemma, either caused by commons or anticommons, can be attributed to the interface mismatch between individual elements and common elements. Trying to overcome the dilemma by changing property arrangements alone cannot eliminate the incentive mismatch caused by the common-private interface. Institutions aimed at alleviating the mismatch are accordingly required. Theoretically, this framework converts Ostrom’s concept of commons into liberal commons that the members have options to exit, which is becoming increasingly common in the current global context of marketization. In the real world, this framework can serve to understand the property reform progress of transition countries, and may enlighten future property reforms.

Abstract The lifetime of electronic coherences found in photosynthetic antennas is known to be too short to match the energy transfer time, rendering the coherent energy transfer mechanism inactive. Exciton-vibrational coherence time in excitonic dimers which consist of two chromophores coupled by excitation transfer interaction, can however be much longer. Uncovering the mechanism for sustained coherences in a noisy biological environment is challenging, requiring the use of simpler model systems as proxies. Here, via two-dimensional electronic spectroscopy experiments, we present compelling evidence for longer exciton-vibrational coherence time in the allophycocyanin trimer, containing excitonic dimers, compared to isolated pigments. This is attributed to the quantum phase synchronization of the resonant vibrational collective modes of the dimer, where the anti-symmetric modes, coupled to excitonic states with fast dephasing, are dissipated. The decoupled symmetric counterparts are subject to slower energy dissipation. The resonant modes have a predicted nearly 50% reduction in the vibrational amplitudes, and almost zero amplitude in the corresponding dynamical Stokes shift spectrum compared to the isolated pigments. Our findings provide insights into the mechanisms for protecting coherences against the noisy environment.

Abstract Metal-organic frameworks (MOFs) with diverse chemistry, structures, and properties have emerged as appealing materials for miniaturized solid-state devices. The incorporation of MOF films in these devices, such as the integrated microelectronics and nanophotonics, requires robust patterning methods. However, existing MOF patterning methods suffer from some combinations of limited material adaptability, compromised patterning resolution and scalability, and degraded properties. Here we report a universal, crosslinking-induced patterning approach for various MOFs, termed as CLIP-MOF. Via resist-free, direct photo- and electron-beam (e-beam) lithography, the ligand crosslinking chemistry leads to drastically reduced solubility of colloidal MOFs, permitting selective removal of unexposed MOF films with developer solvents. This enables scalable, micro-/nanoscale (≈70 nm resolution), and multimaterial patterning of MOFs on large-area, rigid or flexible substrates. Patterned MOF films preserve their crystallinity, porosity, and other properties tailored for targeted applications, such as diffractive gas sensors and electrochromic pixels. The combined features of CLIP-MOF create more possibilities in the system-level integration of MOFs in various electronic, photonic, and biomedical devices.

Highlights The fully-integrated memristor chip for edge learning provides a solid foundation for neural network computation. The fully-integrated memristor chip enables efficient object recognition in noisy backgrounds while minimizing energy consumption. The computing-in-memory chip represents an innovative and interdisciplinary technology that extends beyond multiple research domains.

Abstract This study focused on the production of angiotensin‐converting enzyme inhibitory peptides (ACEIPs) from peanut meal (Arachis hypogaea Linn) fermented by Lactobacillus pentosus. The fermentation process was optimized using the response surface methodology with ACE inhibitory activity as the experimental indicator. ACEIPs were further purified after fermentation using ultrafiltration and Sephadex G‐25 gel chromatography. The effect of different molecular weights (ranging from 0.5 to 1.5 kDa) of ACEIP on ACE inhibitory activity was investigated, and a maximum inhibitory rate of 48.83% was achieved. The content of ACEIP was 78.95%. Amino acid analysis revealed that the hydrophobic amino acids accounted for 43.09% of the total content. Among the identified amino acids, glutamic acid had the highest content of 14.94%, followed by leucine and aspartic acid. Matrix‐assisted laser desorption/ionization time‐of‐flight–mass spectrometry (MS) and liquid chromatography–tandem MS were used to identify the molecular weights of the selected ACEIPs, yielding six ACEIPs with good stability and high hydrophilicity. Flexible docking of the six ACEIPs with ACE was simulated using AutoDock Vina (v1.5.7). The result showed that the ACEIPs formed 11, 8, 7, 9, 7, and 6 hydrogen bonds with ACE residues, and the lowest binding energies between them were −9.8, −8.1, −9.0, −9.3, −8.2, and−9.1 kcal/mol, respectively. Among them, GFGINAENNHRIF exhibited superior ACE inhibitory activity and binding stability.

Synthetic Control Method (SCM) is a popular approach for causal inference in panel data, where the optimal weights for control units are often sparse. But the sparsity of SCM has received little attention in the literature except Abadie (2021), which explores the sparsity from the perspective of predictor space. In this paper, we make three contributions. First, we show that if there is a unique solution, then the number of positive weights is upper-bounded by the number of covariates. Second, we offer a simple alternative explanation about the sparsity of SCM from the perspective of parameter space. Third, we conduct a meta-analysis of empirical studies using SCM in the literature, which shows that the sparsity of SCM decreases with the relative number of covariates. A practical implication is that if the number of positive weights exceeds the number of covariates, there are multiple solutions and possibly unstable weights.

The discovery of MPTP, an industrial chemical and contaminant of illicit narcotics, which causes parkinsonism in humans, non-human primates and rodents, has led to environmental pollutants exposure being convicted as key candidate in Parkinson’s disease (PD) pathogenesis. Though MPTP-induced mitochondrial dysfunction and neuroinflammation are mainly responsible for the causative issue of MPTP neurotoxicity, the underlying mechanism involved remains unclear. Here, we reveal a novel signaling mechanism of CDK5-USP30-MAVS regulating MPTP/MPP+ induced PD. MPP+ (the toxic metabolite of MPTP) treatment not only led to the increased protein levels of USP30 but also to mitophagy inhibition, mitochondrial dysfunction, and MAVS-mediated inflammation in BV2 microglial cells. Both mitophagy stimulation (Urolithin A administration) and USP30 knockdown relieved MAVS-mediated inflammation via restoring mitophagy and mitochondrial function in MPP+-induced cell model. Notably, MPTP/MPP+-induced CDK5 activation regulated USP30 phosphorylation at serine 216 to stabilize USP30. Moreover, CDK5-USP30 pathway promoted MAVS-mediated inflammation in MPTP/MPP+-induced PD model. Inhibition of CDK5 not only had a protective effect on MPP+-induced cell model of PD via suppressing the upregulation of USP30 and the activation of MAVS inflammation pathway in vitro, but also prevented neurodegeneration in vivo and alleviated movement impairment in MPTP mouse model of PD. Overall, our study reveal that CDK5 blocks mitophagy through phosphorylating USP30 and activates MAVS inflammation pathway in MPTP/MPP+-induced PD model, which suggests that CDK5-USP30-MAVS signaling pathway represents a valuable treatment strategy for PD induced by environmental neurotoxic pollutants in relation to MPTP.

Abstract Purpose To assess the effectiveness of autologous blood patch intraparenchymal injection during CT-guided lung biopsies with a focus on the incidence of pneumothorax and the subsequent requirement for chest tube placement. Methods A comprehensive search of major databases was conducted to identify studies that utilized autologous blood patches to mitigate the risk of pneumothorax following lung biopsies. Efficacy was next assessed through a meta-analysis using a random-effects model. Results Of the 122 carefully analyzed studies, nine, representing a patient population of 4116, were incorporated into the final analysis. Conclusion deduced showed a noteworthy reduction in the overall incidence of pneumothorax (RR = 0.65; 95% CI 0.53–0.80; P = 0.00) and a significantly decline in the occasion for chest tube placement due to pneumothorax (RR = 0.45; 95% CI 0.32–0.64; P = 0.00). Conclusions Utilizing autologous blood patch intraparenchymal injection during the coaxial needle retraction process post-lung biopsy is highly effective in diminishing both the incidence of pneumothorax and consequent chest tube placement requirement.

Abstract Osteoclasts are over-activated as we age, which results in bone loss. Src deficiency in mice leads to severe osteopetrosis due to a functional defect in osteoclasts, indicating that Src function is essential in osteoclasts. G-protein-coupled receptors (GPCRs) are the targets for ∼35% of approved drugs but it is still unclear how GPCRs regulate Src kinase activity. Here, we reveal that GPR54 activation by its natural ligand Kisspeptin-10 (Kp-10) causes Dusp18 to dephosphorylate Src at Tyr 416. Mechanistically, Gpr54 recruits both active Src and the Dusp18 phosphatase at its proline/arginine-rich motif in its C terminus. We show that Kp-10 binding to Gpr54 leads to the up-regulation of Dusp18. Kiss1, Gpr54 and Dusp18 knockout mice all exhibit osteoclast hyperactivation and bone loss, and Kp-10 abrogated bone loss by suppressing osteoclast activity in vivo. Therefore, Kp-10/Gpr54 is a promising therapeutic target to abrogate bone resorption by Dusp18-mediated Src dephosphorylation.

Objective The Gouli area is one of the important gold and polymetallic belt in the East Kunlun Orogen. There is no research on lineament identification and mineral exploration based on multisource remote sensing data in the area. Methods In this paper, various enhancement techniques were employed on Landsat 8 OLI, GF-2 and DEM data to delineate structural lineaments. Meanwhile, information on geological, mineral and geochemical anomalies was combined to define prospecting targets in the Gouli area. Results The results show that (1) The tectonic framework of the study area can be divided into two regions by the boundary of Kaketeer-Seride. The lineament in the northern region is most developed in the NNE direction, followed by the near-EW direction, and less distributed in the NW and NE directions. The lineament in the southern region is mainly developed in the near-EW direction, and the NW to NE directions are less distributed. (2) The gold ore is controlled by lineaments. (3) The areas of densely distributed and intersected lineaments, as well as the areas connected by different colors on remote sensing images, are favorable locations for gold mineralization. Finally, based on the comprehensive analysis of multiple geological information and remote sensing interpreted tectonic information, four prospecting targets were identified in the study area and verified in the field. Conclusion This study proves that multisource remote sensing data can better identify the spatial structure characteristics of surface tectonics, which can provide a reference and basis for prospecting new deposits in the Gouli area.

Abstract Background The role of pyroptosis in kidney disease is limited and incomplete. Quercetin, a flavonoid compound present in a variety of fruits, vegetables, and plants, has shown antioxidant and anti-inflammatory properties. This study was designed to validate the importance of pyroptosis in an experimental model of folic acid nephropathy and to explore the effect of quercetin in protecting against pyroptosis. Methods Gene set enrichment analysis (GSEA) and weighted gene co-expression network analysis (WGCNA) were used to establish the correlation between pyroptosis and folic acid nephropathy. Immune cell infiltration, network pharmacology and single-cell RNA sequencing analysis were utilized to ascertain the specific target of quercetin in relation to pyroptosis. Finally, quercetin’s role was verified in vivo and in vitro. Results The GSEA analysis revealed a significant correlation between pyroptosis and folic acid nephropathy (NES = 1.764, P = 0.004). The hub genes identified through WGCNA were closely associated with inflammation. Molecular docking demonstrated a strong binding affinity between quercetin and caspase-1, a protein known to be involved in macrophage function, as confirmed by immune cell infiltration and single-cell analysis. Quercetin demonstrated a significant amelioration of kidney injury and reduction in macrophage infiltration in the animal model. Furthermore, quercetin exhibited a significant inhibition of caspase-1 expression, subsequently leading to the inhibition of pro-inflammatory cytokines expression, such as IL-1β, IL-18, TNF-α, and IL-6. The inhibitory effect of quercetin on macrophage pyroptosis was also confirmed in RAW264.7 cells. Conclusion This study contributes substantial evidence to support the significant role of pyroptosis in the development of folic acid nephropathy, and highlights the ability of quercetin to downregulate caspase-1 in macrophages as a protective mechanism against pyroptosis.

Exploring the natural diversity of functional genes/proteins from environmental DNA in high throughput remains challenging. In this study, we developed a sequence-based functional metagenomics procedure for mining the diversity of copper (Cu) resistance gene copA in global microbiomes, by combining the metagenomic assembly technology, local BLAST, evolutionary trace analysis (ETA), chemical synthesis, and conventional functional genomics. In total, 87 metagenomes were collected from a public database and subjected to copA detection, resulting in 93,899 hits. Manual curation of 1214 hits of high confidence led to the retrieval of 517 unique CopA candidates, which were further subjected to ETA. Eventually, 175 novel copA sequences of high quality were discovered. Phylogenetic analysis showed that almost all these putative CopA proteins were distantly related to known CopA proteins, with 55 sequences from totally unknown species. Ten novel and three known copA genes were chemically synthesized for further functional genomic tests using the Cu-sensitive Escherichia coli (ΔcopA). The growth test and Cu uptake determination showed that five novel clones had positive effects on host Cu resistance and uptake. One recombinant harboring copA-like 15 (copAL15) successfully restored Cu resistance of the host with a substantially enhanced Cu uptake. Two novel copA genes were fused with the gfp gene and expressed in E. coli for microscopic observation. Imaging results showed that they were successfully expressed and their proteins were localized to the membrane. The results here greatly expand the diversity of known CopA proteins, and the sequence-based procedure developed overcomes biases in length, screening methods, and abundance of conventional functional metagenomics.

Large-scale deep learning algorithms have emerged as the primary technology for underwater target detection, demonstrating exceptional inference effectiveness and accuracy. However, the real-time capabilities of these high-accuracy algorithms rely heavily on high-performance computing resources like CPUs and GPUs. It presents a challenge for deploying them on underwater embedded devices, where communication is limited and computational and energy resources are constrained. To overcome this, this paper focuses on constructing a lightweight yet highly accurate deep learning model suitable for real-time underwater target detection on edge devices. We develop a new lightweight model, named YOLO-TN, for real-time underwater object recognition on edge devices using a self-constructed image dataset captured by an underwater unmanned vehicle. This model is obtained by compressing the classical YOLO-V5, utilizing a globally differentiable deep neural architecture search method and a network pruning technique. Experimental results show that the YOLO-TN achieves a mean average precision (mAP) of 0.5425 and an inference speed of 28.6 FPS on embedded devices, while its parameter size is between 0.4 M and 0.6 M. This performance is a fifth of the parameter size and twelve times the FPS of the YOLO-V5 model, with almost no loss in inference accuracy. In conclusion, this framework significantly enhances the feasibility of deploying large-scale deep learning models on edge devices with high precision and compactness, ensuring real-time inference and offline deployment capabilities. This research is pivotal in addressing the computational challenges faced in underwater operations.

In the context of burgeoning global aquaculture, its environmental repercussions, particularly in marine ecosystems, have gained significant attentions. Cage aquaculture, a prominent method, has been observed to significantly influence marine environments by discharging substantial amounts of organic materials and pollutants. It is also one of the important reasons for water eutrophication. This study investigated the impacts of cage aquaculture on microbial diversity and functional potential using metagenomics. Specifically, a comparison was made of the physicochemical indicators and microbial diversity between three grouper aquaculture cage nets in Lingshui Xincun Port and three nearby non-aquaculture area surface waters. We found that compared to non-aquaculture areas, the eutrophication indicators in aquaculture environments significantly increased, and the abundances of Vibrio and Pseudoalteromonas in aquaculture environments significantly rose. Additionally, microbial functional genes related to carbon, nitrogen, and sulfur metabolisms were also found to be significantly affected by aquaculture activities. The correlation analysis between microbial populations and environmental factors revealed that the abundances of most microbial taxa showed positive correlations with dissolved inorganic nitrogen, soluble reactive phosphorus, NH4+, and negative correlations with dissolved oxygen. Overall, this study elucidated the significant impacts of aquaculture-induced eutrophication on the diversity and functions of planktonic bacterial communities.

Abstract Researchers have typically studied the brain by monitoring characteristic signals, such as electrophysiology and neurotransmitters by implanted electronics. Here, real‐time monitoring of dynamic deformations of the brain tissue in vivo, is demonstrated, as a new characteristic parameter that is reflective of brain states. As a proof of concept, a thin capacitive deformation sensor is fabricated and implanted between the skull and cortex, and the sensor is shown to effectively monitor dynamic deformations of the cortical surface in the rat brain as induced by respiration and heartbeat under different degrees of anesthesia. This brain monitoring approach based on deformation signals opens up a new direction for understanding the brain.

PurposeTo identify the most commonly reported drugs associated with QT interval prolongation in the FDA Adverse Event Reporting System (FAERS) and evaluate their risk for QT interval prolongation.MethodsWe employed the preferred term (PT) “electrocardiogram QT prolonged” from the Medical Dictionary for Regulatory Activities (MedDRA) 26.0 to identify adverse drug events (ADEs) of QT interval prolongation in the FAERS database from the period 2004–2022. Reporting odds ratio (ROR) was performed to quantify the signals of ADEs.ResultsWe listed the top 40 drugs that caused QT interval prolongation. Among them, the 3 drugs with the highest number of cases were quetiapine (1,151 cases, ROR = 7.62), olanzapine (754 cases, ROR = 7.92), and citalopram (720 cases, ROR = 13.63). The two most frequently reported first-level Anatomical Therapeutic Chemical (ATC) groups were the drugs for the nervous system (n = 19, 47.50%) and antiinfectives for systemic use (n = 7, 17.50%). Patients with missing gender (n = 3,482, 23.68%) aside, there were more females (7,536, 51.24%) than males (5,158, 35.07%) were involved. 3,720 patients (25.29%) suffered serious clinical outcomes resulting in deaths or life-threatening conditions. Overall, most drugs that caused QT interval prolongation had early failure types according to the assessment of the Weibull's shape parameter (WSP) analysis.ConclusionsOur study offered a list of drugs that frequently caused QT interval prolongation based on the FAERS system, along with a description of some risk profiles for QT interval prolongation brought on by these drugs. When prescribing these drugs in clinical practice, we should closely monitor the occurrence of ADE for QT interval prolongation.

Tetrapyrrole compounds play vital roles in the life processes of animals and plants, such as respiration and photosynthesis, due to their functions in light energy capture and transmission, signal transduction, binding and transport of oxygen, their research originated from the study of heme and chlorophyll chemistry. The special structure of tetrapyrrole determines its various properties, which contribute to its antioxidant, anti-inflammatory, antitumoral, antibacterial, neuroprotective and other biological activities. Although many functions of tetrapyrrole compounds have been excavated and utilized, there is a lack of a complete system to summarize them. This review summarizes the biosynthesis, functional evolution, biological activities and optical applications of tetrapyrrole compounds based on existing research on tetrapyrrole compounds.

The gut microbiota participates in a wide range of biological processes of host, such as growth, feeding and immunity. The rabbitfish (Siganus oramin) is a popular table fish with good taste and rich nutrition. However, there are many potential unknown risks in artificial cultivation process. In this study, for the first time, we performed a 16 s rDNA sequencing analysis of gut microbiota in rabbitfish growing in different environments including marine cage, cement pond and wild environment. The most abundant phylum in all conditions was Proteobacteria, especially in individuals cultured in cement pond, and the relative abundance of Firmicutes, Fusobacteria and Bacteroidetes was obviously higher in marine-cage and wild individuals. At the genus level, Burkholderia-Caballeronia-Paraburkholderia was the most abundant in rabbitfish cultivated in cement pond environment. Moreover, Lipid biosynthesis proteins, Carotenoid biosynthesis, Proximal tubule bicarbonate reclamation, Dioxin degradation and Xylene degradation pathways were found to be highly abundant in rabbitfish cultivated in cement pond, while Sphingolipid metabolism, Plant-pathogen interaction and Glycosphingolipid biosynthesis-globo series pathways were scarce. Interestingly, no obvious difference of gut microbiota was found between marine-cage and wild rabbitfish. All these results would lay a good foundation for developing a microbiota based strategy for artificial cultivation of rabbitfish.

BackgroundWith the rapid growth of global aging, frailty has become a serious public health burden, affecting the life quality of older adults. Depressive symptoms (depression hereafter) and sleep quality are associated with frailty, but the pathways in which sleep quality and depression affect frailty remain unclear.MethodThis cross-sectional study included 1866 community-dwelling older adults. Demographic characteristics and health-related data of them was collected, and we also assessed frailty, depression, and sleep quality. Descriptive statistics were carried out and ordinal logistic regression analysis was used to identify the factors correlated with frailty. Spearman correlation analysis and mediation analysis were employed to assess associations between sleep quality, depression and frailty. Two-sided p

IntroductionAtopic dermatitis (AD) is one of the most common inflammatory skin diseases. Skin microecological imbalance is an important factor in the pathogenesis of AD, but the underlying mechanism of its interaction with humans remains unclear.Methods16S rRNA gene sequencing was conducted to reveal the skin microbiota dynamics. Changes in skin metabolites were tracked by LC–MS metabolomics. We then explored the potential mechanism of interaction by analyzing the correlation between skin bacterial communities and metabolites in corresponding skin-associated samples.ResultsSamples from 18 AD patients and 18 healthy volunteers (HVs) were subjected to 16S rRNA gene sequencing and LC–MS metabolomics. AD patients had dysbiosis of the skin bacterial community with decreased species richness and evenness. The relative abundance of the genus Staphylococcus increased significantly in AD, while the abundances of the genera Propionibacterium and Brevundimonas decreased significantly. The relative abundance of the genera Staphylococcus in healthy females was significantly higher than those in healthy males, while it showed no difference in AD patients with or without lesions. The effects of AD status, sex and the presence or absence of rashes on the number of differentially abundant metabolites per capita were successively reduced. Multiple metabolites involved in purine metabolism and phenylalanine metabolism pathways (such as xanthosine/xanthine and L-phenylalanine/trans-cinnamate) were increased in AD patients. These trends were much more obvious between female AD patients and female HVs. Spearman correlation analysis revealed that the genus Staphylococcus was positively correlated with various compounds involved in phenylalanine metabolism and purine metabolic pathways. The genera Brevundimonas and Lactobacillus were negatively correlated with various compounds involved in purine metabolism, phenylalanine metabolism and sphingolipid signaling pathways.DiscussionWe suggest that purine metabolism and phenylalanine metabolism pathway disorders may play a certain role in the pathogenic mechanism of Staphylococcus aureus in AD. We also found that females are more likely to be colonized by the genus Staphylococcus than males. Differentially abundant metabolites involved in purine metabolism and phenylalanine metabolism pathways were more obvious in female. However, we should notice that the metabolites we detected do not necessarily derived from microbes, they may also origin from the host.

Intra-articular adeno-associated virus (AAV) gene therapy has been explored as a potential strategy for joint diseases. However, concerns of low transduction efficacy, off-target expression, and neutralizing antibodies (Nabs) still need to be addressed. In this study, we demonstrated that AAV6 was the best serotype to transduce joints after screening serotypes 1 to 9. To develop a more effective AAV vector, a set of novel AAV capsids were rationally engineered. The mutant AAV62 created by swapping variable region I (VRI) of AAV2 into AAV6 induced a higher transduction efficiency per AAV genome copy number. To further investigate the roles of specific amino acids in the transduction of AAV62 and AAV6, we found out that AAV6D with the deletion of threonine at residue 265 induced a 2-fold higher transduction than AAV6, while the transduction efficiency from AAV6M with the mutation of alanine to glutamine at residue 263 was 10-fold lower. AAV6D efficiently transduced both synoviocytes and chondrocytes with low AAV genome copy numbers in other tissues and less Nab formation. This study demonstrates that novel AAV mutants with rational engineering may enhance joint transduction after intra-articular administration in mice, with the potential to evade AAV Nabs and minimize off-target effects in the liver.

The limitations of current drug-eluting stent technologies in selectively inhibiting vascular smooth muscle cell proliferation, which often leads to inflammation, call for innovative approaches in coronary artery disease treatment. In the present work, we propose a revolutionary solution: a three-in-one platform for vascular stents, combining arsenic trioxide (ATO) and tacrolimus (TAC) to address anti-proliferation, pro-endothelialization, and anti-inflammation aspects. Our findings demonstrate that the synergistic action of ATO and TAC effectively suppresses aberrant vascular smooth muscle cell proliferation and mitigates endothelial cell inflammation. Remarkably, the combination treatment of TAC/ATO enhances endothelial cell migration and adhesion abilities. Moreover, our TAC/ATO-eluting stent exhibits superior re-endothelialization and anti-restenosis effects in a rabbit and porcine stent implantation model. Both in vitro and in vivo results solidify the notion that the TAC/ATO-eluting stent ensures rapid re-endothelialization and significantly reduces the incidence of in-stent restenosis. Overall, this study represents a promising and novel multifunctional platform with immense potential in the therapy of coronary artery disease.

Peanut protein was fermented by Lactobacillus pentosus, to study the effects of different protein composition of peanut protein isolate, arachin and concomitant arachin on their molecular structure and thermal properties during fermentation, the composite gel was prepared by compounding peanut protein with myofibril protein, the rheological properties of the composite emulsion and the texture properties of the composite gel were studied to reveal the molecular mechanism of the effect of L. pentosus on the gel properties of peanut protein. The results showed that the free sulfhydryl content, surface hydrophobicity and denaturation temperature of arachin were increased, β-sheet content and denaturation enthalpy were decreased by L. pentosus fermentation. It can reduce the content of free sulfhydryl group, surface hydrophobicity and denaturation enthalpy of peanut protein isolate and concomitant arachin, the denaturation temperature and α-helix content of peanut protein isolate and arachin were significantly increased. After fermentation, the structure of arachin developed to the maximum and the thermal stability of arachin was higher, which proved that L. pentosus could promote the gel modification of peanut protein. The complex gel formed by fermentation with arachin is easier to form porous structure and has better macro-elasticity than the complex gel prepared by modification of arachin and isolate protein.

Objective To verificate the performance of enzyme-linked immunosorbent assay (ELISA) in blood screening laboratory. Methods The repeatability, precision, sensitivity, specificity, compliance, detection limit and anti-interference of ELISA items in the laboratory detection system were verified. Results The repeatability was 100%.The intra batch imprecision of each system was less than 10%, and the inter batch imprecision was less than 15%. The sensitivity, specificity and compliance were 100%, with the minimum detection limits of the two reagents at 0.75 NCU/mL and 0.25 NCU/mL respectively, The anti-interference met the requirements of the reagent manual. Conclusion The analysis of the performance verification data of ELISA test items will help continuously improve the performance of detection system and ensure the safety of clinical blood use.

Abstract Phycobiliproteins (PBPs), one of the functional proteins from algae, are natural pigment–protein complex containing various amino acids and phycobilins. It has various activities, such as anti-inflammatory and antioxidant properties. And are potential for applications in food, cosmetics, and biomedicine. Improving their metabolic yield is of great interest. Microalgaes are one of the important sources of PBPs, with high growth rate and have the potential for large-scale production. The key to large-scale PBPs production depends on accumulation and recovery of massive productive alga in the upstream stage and the efficiency of microalgae cells breakup and extract PBPs in the downstream stage. Therefore, we reviewed the status quo in the research and development of PBPs production, summarized the advances in each stage and the feasibility of scaled-up production, and demonstrated challenges and future directions in this field.

Heterogeneous structure is practical to improve the strain hardening abilities of materials due to the effect of hetero-deformation induced hardening, especially of composites. In this study, a series of TiB/TC4 composites with a pseudo core–shell structure of bimodal grain distribution were fabricated via a two-step ball-milling and spark plasma sintering. The synthesized TiB/TC4 composites have a structure of coarse lamella α-Ti grains of average 23.6 μm in diameter surrounded by fine α-Ti lamella grains of average 4.2 μm, with TiB distributed on the primary TC4 surface areas. TiB/TC4 composites with 0.4 wt% TiB2 exhibited the best comprehensive mechanical properties with an ultimate tensile strength of 1161.95 MPa (a 35.1% increase compared with that of pure TC4) and an elongation of 7.57%. In conclusion, the pseudo core–shell structure improved the strength by improving the strain-hardening abilities, achieved by the coordinated deformation between coarse grains and fine grains.

Hierarchical clustering is a common type of clustering in which the dataset is hierarchically divided and represented by a dendrogram. Agglomerative Hierarchical Clustering (AHC) is a common type of hierarchical clustering in which clusters are created bottom-up. In addition, semi-supervised clustering is a new method in the field of machine learning, where supervised and unsupervised learning are combined. Clustering performance is effectively improved by semi-supervised learning, as it uses a small amount of labelled data to aid unsupervised learning. Meanwhile, ensemble clustering by combining the results of several individual clustering methods can achieve better performance compared to each of the individual methods. Considering AHC with semi-supervised learning for ensemble clustering configuration has received less attention in the past literature. In order to achieve better clustering results, we propose a semi-supervised ensemble clustering framework developed based on AHC-based methods. Here, we develop a flexible weighting mechanism along with a new membership similarity measure that can establish compatibility between semi-supervised clustering methods. We evaluated the proposed method with several equivalent methods based on a wide variety of UCI datasets. Experimental results show the effectiveness of the proposed method from different aspects such as NMI, ARI and accuracy.

Kindergartens play a crucial role in nurturing the physical, cognitive, and social development of children. Hence, designing kindergarten buildings requires the consideration of the unique requirements and behavior of children. Considering the rapid urbanization of China and its commitment to achieving the 3060 carbon goal, in this study, we examine the retrofitting of kindergarten buildings in China and propose a retrofit optimization method for kindergarten buildings that considers thermal comfort, daylighting, and life-cycle carbon emissions. Through this method, information on the thermal and daylighting comfort of occupants, weather data, occupant scheduling, and envelope and energy system of the kindergarten building to be retrofitted can be obtained through various approaches, such as video playback, field investigation, literature research, and consult drawings. On this basis, optimization variables are selected, and a physical model is established to guide the retrofit process. Afterward, a rapid comprehensive optimization framework based on parallel computing is adopted to obtain the comprehensive optimal design scheme for the building to be retrofitted. The proposed method is applied to a kindergarten building retrofit case in Nanjing, China, and the results show that the optimal comprehensive scheme results in a reduction in carbon emissions of 34,158.3 kg, an increase in the thermal comfort period of 2.7%, and an improvement in daylighting comfort of 79.7% over the benchmark scheme. The significance of this study extends beyond its potential for widespread application in kindergarten building retrofits. It contributes to advancing sustainable building design and environmental stewardship, creating healthier and more comfortable learning environments for children while mitigating the environmental impact of buildings. Moreover, it emphasizes the importance of considering children’s unique needs and behaviors in building design, ultimately leading to better outcomes for their overall development.

Soil environmental issues in the red bed region are increasingly conspicuous, underscoring the critical importance of assessing soil quality for the region’s sustainable development and ecosystem security. This study examines six distinct land use types of soils—agricultural land (AL), woodland (WL), shrubland (SL), grassland (GL), bare rock land (BRL), and red bed erosion land (REL)—in the Nanxiong Basin of northern Guangdong Province. This area typifies red bed desertification in South China. Principal component analysis (PCA) was employed to establish a minimum data set (MDS) for calculating the soil quality index (SQI), evaluating soil quality, analyzing influencing factors, and providing suggestions for ecological restoration in desertification areas. The study findings indicate that a minimal data set comprising soil organic matter (SOM), pH, available phosphorus (AP), exchangeable calcium (Ca2+), and available copper (A-Cu) is most suitable for evaluating soil quality in the red bed desertification areas of the humid region in South China. Additionally, we emphasize that exchangeable salt ions and available trace elements should be pivotal considerations in assessing soil quality within desertification areas. Regarding comprehensive soil quality indicators across various land use types, the red bed erosion soils exhibited the lowest quality, followed by those in bare rock areas and forest land. Within the minimal data set, Ca2+ and pH contributed the most to overall soil quality, underscoring the significance of parent rock mineral composition in the red bed desertification areas. Moreover, the combined effects of SOM, A-Cu, and AP on soil quality indicate that anthropogenic land management and use, including fertilization methods and vegetation types, are crucial factors influencing soil quality. Our research holds significant implications for the scientific assessment, application, and enhancement of soil quality in desertification areas.

Central Asia (CA) is located in the interior of the Eurasian continent and consists of five countries—Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan. It contains the largest concentration of temperate deserts and mountains of CA biodiversity hotspots. However, regionwide floristic diversity is sorely lacking, and nationwide floristic diversity is seriously outdated in this region. Using the data collected by the Mapping Asia Plants (MAP) project, we describe and analyze the diverse floristic characteristics of plant diversity in CA at both the regional and national levels, including the dominant families and genera, endemic taxa, and floristic similarity. The results allow the compilation of a new checklist of vascular plants in CA, including 9643 taxa (1198 genera within 139 families) and 3409 endemic taxa (414 genera in 66 families). We confirm that there are 5695, 4036, 4542, 3005, and 4222 species of vascular plants within the CA countries, of which 532, 326, 505, 175, and 301 species are endemic taxa in Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan, respectively. The region’s biodiversity is notable for its high degree of endemism—up to 35.35%—which contributes to the floristic uniqueness and the irreplaceability of CA. Tajikistan, encompassing the most dominant area of the CA mountains, has the highest species density (3.19/100 km2) and endemism (11.12%) among the five countries. Neighboring countries such as Tajikistan and Uzbekistan, and Kazakhstan and Kyrgyzstan share more species in common, while Turkmenistan has less species overlap with the other four countries. Trends in endemic and total taxa are consistent. This comprehensive inventory is novel, revealing CA’s plant diversity in two dimensions and providing a solid foundation for subsequent research that will be beneficial to the transboundary conservation and sustainable use of plant resources in CA.