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Abstract To improve our knowledge of the spatio‐temporal correspondence between radar reflectivity and VLF/LF total lightning data, this paper proposes indexes to quantify the horizontal distribution and temporal evolution characteristics between radar composite reflectivity images and total lightning density map, lightning clusters and radar cells with different radar reflectivity thresholds (30, 35, 40, 45 and 50 dBZ), respectively. It is found that the number of radar grid cells with radar reflectivity over 30 dBZ is ten times the number of lightning grid cells. At the identification stage, the lightning activity regions in a radar cell account for less than 30% using thresholds of 30, 35 and 40 dBZ, respectively, and the radar cell has more than one lightning cluster, which means that the mesoscale convective systems typically have more than one draft, and drafts are only small part of the convection. The majority of the centroid deviations is less than 10 km, indicating that there are some shifts between electrically active regions and convective regions. Results suggest that VLF/LF total lightning data are consistent with radar data and total lightning data can be used individually on a smaller spatio‐temporal scale than radar data.

Abstract Effective visualization of infectious disease risks is crucial for the development of efficient prevention and control strategies. However, the efficacy of mainstream models is hindered by a scarcity of reliable data in target areas, a situation that is particularly acute when dealing with emerging or re‐emerging infectious diseases. Additionally, these models typically fail to integrate local disease‐related risk factors in line with the ‘One Health’ concept, resulting in inaccurate predictions. Consequently, accurately assessing infectious disease risks without reliable data is challenging. This study introduces SpatMCDA, an innovative R package designed to assess infectious disease risk areas through spatial multi‐criteria decision analysis (MCDA). SpatMCDA is structured around six core modelling steps: standardizing risk factors, determining factor weights, constructing risk maps, performing One‐at‐a‐Time sensitivity analysis, calculating the Mean of Absolute Change Rates and conducting an uncertainty analysis. By examining the case of West Nile virus (WNV) in China, this study illustrates how SpatMCDA can be useful in identifying disease transmission risks in the absence of reliable outbreak data. The assessment identified areas at risk for WNV in northwestern, eastern and southern China. By integrating spatial and epidemiological data, SpatMCDA enhances infectious diseases risk assessment in situations where data are limited. Its efficiency in using available data for accurate risk mapping and adaptability in weighting various risk factors enables tailored analyses. This tool enhances public health strategies, contributing to global health security.

Abstract Background Breast cancer (BC) is a heterogeneous disease, with the ductal subtype exhibiting significant cellular diversity that influences prognosis and response to treatment. Single-cell RNA sequencing data from the GEO database were utilized in this study to investigate the underlying mechanisms of cellular heterogeneity and to identify potential prognostic markers and therapeutic targets. Methods Bioinformatics analysis was conducted using R packages to analyze the single-cell sequencing data. The presence of highly variable genes and differences in malignant potency within the same BC samples were examined. Differential gene expression and biological function between Type 1 and Type 2 ductal epithelial cells were identified. Lasso regression and Cox proportional hazards regression analyses were employed to identify genes associated with patient prognosis. Experimental validation was performed in vitro and in vivo to confirm the functional relevance of the identified genes. Results The analysis revealed notable heterogeneity among BC cells, with the presence of highly variable genes and differences in malignant behavior within the same samples. Significant disparities in gene expression and biological function were identified between Type 1 and Type 2 ductal epithelial cells. Through regression analyses, CYP24A1 and TFPI2 were identified as pivotal genes associated with patient prognosis. Kaplan-Meier curves demonstrated their prognostic significance, and experimental validation confirmed their inhibitory effects on malignant behaviors of ductal BC cells. Conclusion This study highlights the cellular heterogeneity in ductal subtype breast cancer and delineates the differential gene expressions and biological functions between Type 1 and Type 2 ductal epithelial cells. The genes CYP24A1 and TFPI2 emerged as promising prognostic markers and therapeutic targets, exhibiting inhibitory effects on BC cell malignancy in vitro and in vivo. These findings offer the potential for improved BC management and the development of targeted treatment strategies.

Ultrahigh dose-rate (FLASH) radiotherapy is an emerging technology with excellent therapeutic effects and low biological toxicity. However, tumor recurrence largely impede the effectiveness of FLASH therapy. Overcoming tumor recurrence is crucial for practical FLASH applications. Here, we prepared an agarose-based thermosensitive hydrogel containing a mild photothermal agent (TPE-BBT) and a glutaminase inhibitor (CB-839). Within nanoparticles, TPE-BBT exhibits aggregation-induced emission peaked at 900 nm, while the unrestricted molecular motions endow TPE-BBT with a mild photothermy generation ability. The balanced photothermal effect and photoluminescence are ideal for phototheranostics. Upon 660-nm laser irradiation, the temperature-rising effect softens and hydrolyzes the hydrogel to release TPE-BBT and CB-839 into the tumor site for concurrent mild photothermal therapy and chemotherapy, jointly inhibiting homologous recombination repair of DNA. The enhanced FLASH radiotherapy efficiently kills the tumor tissue without recurrence and obvious systematic toxicity. This work deciphers the unrestricted molecular motions in bright organic fluorophores as a source of photothermy, and provides novel recurrence-resistant radiotherapy without adverse side effects.

This is an article in the field of metallurgical engineering. China is short of bauxite resources, which makes the high alumina fly ash a kind of potential bauxite resources. The extraction of alumina oxide from fly ash will be used as a reserve technology, which will make the in-depth development and research constantly pushed forward. The pre-desilication soda lime sintering method of alumina extraction from fly ash has been introduced as the only large-scale and industrialized manufacture technology. It can provide reference information for technology development and the industrialization, and make the national bauxite strategic reserve system safe.

Pulmonary hypertension (PH) is a progressive cardiopulmonary disease characterized by elevated pulmonary artery pressure and vascular remodeling, resulting in poor prognosis and increased mortality rates. Chemokine-like factor 1 (CKLF1) plays a significant role in inducing inflammation and cell proliferation, both of which are critical processes in the pathogenesis of various diseases. Dihydromyricetin (DMY) has garnered attention for its potent anti-inflammatory properties. This study evaluated the protective effects of DMY against PH, demonstrating that DMY treatment can mitigate pyroptosis in pulmonary artery endothelial cells (PAECs) and pulmonary artery smooth muscle cells (PASMCs) in vivo via the CKLF1/CCR5 axis. Results indicated significant improvements in hemodynamics, inflammatory responses, fibrosis, vascular remodeling, and right ventricular hypertrophy in PH rats following DMY treatment. Furthermore, the interaction between CKLF1 and CCR5 was investigated in CKLF1-/- rats after PH induction. DMY was found to downregulate CKLF1 expression and the inflammatory response in the lungs, with its therapeutic efficacy diminished following CKLF1 knockdown. This study underscores the therapeutic potential of DMY in the management of PH and lays a foundation for future research and clinical applications.

Cold exposure therapy (CE), as an inexpensive method, has shown great potential in cancer therapy. Exploring the combined anti-tumor mechanism of CE and traditional therapies (such as photodynamic therapy (PDT)) is exciting and promising. Here, a bionic aggregation-induced emission photosensitizer system (named THL) is designed for combined CE to enhance anti-tumor immunotherapy. THL inherits the homologous targeting ability of tumor derived exosomes, promoting the enrichment of THL at the tumor site. Under external illumination, THL generates hydroxyl radicals and superoxide anions through type I PDT. In addition, mice are pretreated with cold exposure, which promotes THL mediated PDT and reactive oxygen species (ROS) generation by reducing the production of ATP and GSH in tumor tissue. This combination therapy increases production of ROS within the tumor, inhibits the growth of distant tumors, recurrent and rechallenged tumors and increases the number of cytotoxic CD8+T cells and memory T cells. Compared to PDT alone, combination therapy shows greater advantages in tumor immunotherapy. The combination therapy strategy provides new ideas for cancer immunotherapy.

Background: Sepsis-associated coagulopathy specifically refers to widespread systemic coagulation activation accompanied by a high risk of hemorrhage and organ damage, which in severe cases manifests as disseminated intravascular coagulation (DIC), or even develops into multiple organ dysfunction syndrome (MODS). The complement system and the coagulation system as the main columns of innate immunity and hemostasis, respectively, undergo substantial activation after sepsis. Summary: Dysfunction of the complement, coagulation/fibrinolytic cascades caused by sepsis leads to “thromboinflammation,” which ultimately amplifies the systemic inflammatory response and accelerates the development of MODS. Recent studies have revealed that massive activation of the complement system exacerbates sepsis-induced coagulation and even results in DIC, which suggests that inhibition of complement activation may have therapeutic potential in the treatment of septic coagulopathy. Key Messages: Sepsis-associated thrombosis involves the upregulation or activation of procoagulant factors, down-regulation or inactivation of anticoagulant factors, and impairment of the fibrinolytic mechanism. This review aims to summarize the latest literature and analyze the underlying molecular mechanisms of the activation of the complement system on the abnormal coagulation cascades in sepsis.

Abstract A novel variant of rabbit haemorrhagic disease virus, designated RHDV2/b/GI.2, was first discovered in France in 2010. Subsequently, RHDV2 rapidly spread to Africa, North America, Australia, and Asia. RHDV2 outbreaks have resulted in significant economic losses in the global rabbit industry and disrupted the balance of natural ecosystems. Our study investigated the seasonal characteristics of RHDV2 outbreaks using seasonal indices. RHDV2 is prone to causing significant outbreaks within domestic and wild rabbit populations during the spring season and is more likely to induce outbreaks within wild rabbit populations during late autumn in the Southern Hemisphere. Furthermore, based on outbreak data for domestic and wild rabbits and environmental variables, our study established two MaxEnt models to explore the relationship between RHDV2 outbreaks and the environmental factors and conducted outbreak risk predictions for RHDV2 in global domestic and wild rabbit populations. Both models demonstrated good predictive performance, with AUC values of 0.960 and 0.974, respectively. Road density, isothermality, and population density were identified as important variables in the outbreak of RHDV2 in domestic rabbits, while road density, normalized difference vegetation index, and mean annual solar radiation were considered key variables in the outbreak of RHDV2 in wild rabbits. The environmental factors associated with RHDV2 outbreaks identified in our study and the outbreak risk prediction maps generated in our study will aid in the formulation of appropriate RHDV2 control measures to reduce the risk of morbidity in domestic and wild rabbits.

Precipitation nowcasting refers to the prediction of small-scale precipitation events at minute and kilometer scales within the upcoming 0 to 2 h, which significantly impacts both human activities and daily life. However, prevailing deep learning models have primarily focused on a single radar echo data source, limiting their ability to effectively capture intricate and rapidly evolving precipitation patterns. Thus, meteorological satellite is considered to supplement radar echo data. To achieve a comprehensive integration of multisource data with enhanced details, a two-stage fusion satellite and radar GAN-based prediction network (named FsrGAN) is proposed. In the first stage, we design a satellite-radar fusion prediction network known as FsrNet. This network employs an encoder-fusion-decoder architecture, where a novel spatial-channel attention (SCA) is proposed to enhance the filtering and fusion of multisource and multiscale features. In the second stage, we introduce a GAN-based network (FusionGAN) that also mines the complementary information of satellite images to sharpen the first-stage predicted radar maps with more details. Experiments are conducted on meteorological dataset in the Yangtze River Delta (YRD) region. The test results exhibit the notably superior performance of our model in terms of image quality and precipitation forecasting metrics in comparison to traditional optical flow-based methods and some well-known deep learning methods (ConvLSTM, ConvGRU, TrajGRU and PredRNN++). More importantly, our fusion model using satellite and radar data demonstrates the ability to predict convective initiation.

In this paper, we propose a Holling-IV predator-prey system considering the perturbation of a slow-varying environmental capacity parameter. This study aims to address how the slowly varying environmental capacity parameter affects the behavior of the system. Based on bifurcation theory and the slow-fast analysis method, the critical condition for the Hopf bifurcation of the autonomous system is given. The oscillatory behavior of the system under different perturbation amplitudes is investigated, corresponding mechanism explanations are given, and it is found that the motion pattern of the non-autonomous system is closely related to the Hopf bifurcation and attractor types of the autonomous system. Meanwhile, there is a bifurcation hysteresis behavior of the system in bursting oscillations, and the bifurcation hysteresis mechanism of the system is analyzed by applying asymptotic theory, and its hysteresis time length is calculated. The final study found that the larger the perturbation amplitude, the longer the hysteresis time. These results can provide theoretical analyses for the prediction, regulation, and control of predator-prey populations.

Cross–modal hashing has gained significant attention due to its efficient computational capabilities and impressive retrieval performance. Most supervised methods rely on the auxiliary learning of a similarity matrix, which incurs computational and storage expenses with a complexity of $O(n^{2})$ . By capturing the adjacency relationships between anchor points and original data, the anchor graph learning strategy effectively reduces the time complexity. However, existing anchor graph hashing methods adopt heuristic sampling strategies like k–means or random sampling to determine anchor points. Unfortunately, this approach separates from the anchor graph construction and fails to accurately capture the fine–grained similarity relationships. To overcome this limitation, we introduce a novel method called supervised consensus anchor graph hashing (SCAGH) for cross–modal retrieval with linear complexity. In SCAGH, the anchor points are automatically selected and consensus anchor graph learning is integrated in an unified framework. Through mutual collaboration, a more fine–grained and discriminative consensus anchor graph can be obtained without extra hyper–parameters. Additionally, we utilize anchor graph matrix to approximate the pairwise similarity matrix so that the high complexity can be avoided and enhance the quality of hash codes. Extensive experiments on four benchmark datasets are conducted to verify the superiority of the proposed SCAGH compared to several state–of–the–art methods.

This is an essay in the field of ceramics and composites. With the rapid development of the new energy vehicle industry, the production of power lithium-ion batteries has increased dramatically. However, due to the short service life of power Li-ion batteries and their imminent mass retirement, it is necessary to effectively manage power Li-ion batteries in a resourceful manner. This paper first introduces the main components of power lithium-ion batteries and clarifies the stepwise utilization and pre-treatment process before their cathode materials are recycled. It focuses on an overview of the thermal, wet and biological recycling technologies for used power lithium-ion battery cathode materials, and presents the opportunities and challenges faced by biological recycling in the resourceful disposal of used power lithium-ion battery cathode materials. Our results can provide a certain reference for the green resource-based recycling of power lithium-ion batteries and promote the healthy development of the new energy vehicle industry.

Abstract Marine natural gas hydrate (NGH) is a promising substitutive low-carbon energy resource, whereas NGH-production induced geoengineering concerns remain challenging. Advanced forecast of possible geoengineering risks is the fundamental for eco-friendly NGH exploitation. Reservoir creep deformation is an early symptom of the geoengineering risks. However, whether the creep deformation behaviors of the NGH-bearing strata is predictable remains controversial. In this study, a series of multi-step loading creep test are conducted for sandy gas hydrate bearing sediment (GHBS) samples, during which the ultrasonic responses are recorded simultaneously. The acoustic velocity, compression-to-shear velocity ratio, Poission’s ratio, main frequency, and main frequency amplitude are used to characterize creep failures of the GHBS for the first time. Combining analyses of the creep behaviors and acoustic responses yield the following conclusions. Firstly, the long-term strength derived from creeping test is 0.45–0.60 times of the shear strength derived from triaxial shearing. Ignoring the creep effect might underestimate the scale and intensity of possible geoengineering risks during long-term NGH exploitation. Secondly, the acoustic velocity increases gently and then decreases continuously during creeping. Once the accelerated creep appears, the acoustic velocity plummets significantly, together with a sudden decrease in the compression-to-shear velocity ratio, and fluctuations in the main frequency and its amplitude. Furthermore, the main frequency and its amplitude shall fluctuate abruptly prior to the emergence of the accelerated creep. Therefore, we anticipate that the combination of abnormal fluctuations of main frequency and its amplitude can be used as early-warning indicators for possible creep failure of the GHBS. The results might have great significance for in-situ detection and prediction of possible reservoir failure during long-term NGH exploitation.

This paper introduces a novel hybrid optimization technique aimed at improving the prediction accuracy of solar photovoltaic (PV) outputs using an Improved Hippopotamus Optimization Algorithm (IHO). The IHO enhances the traditional Hippopotamus Optimization (HO) algorithm by addressing its limitations in search efficiency, convergence speed, and global exploration. The IHO algorithm used Latin hypercube sampling (LHS) for population initialization, significantly enhancing the diversity and global search potential of the optimization process. The integration of the Jaya algorithm further refines solution quality and accelerates convergence. Additionally, a combination of unordered dimensional sampling, random crossover, and sequential mutation is employed to enhance the optimization process. The effectiveness of the proposed IHO is demonstrated through the optimization of weights and neuron thresholds in the extreme learning machine (ELM), a model known for its rapid learning capabilities but often affected by the randomness of initial parameters. The IHO-optimized ELM (IHO-ELM) is tested against benchmark algorithms, including BP, the traditional ELM, the HO-ELM, LCN, and LSTM, showing significant improvements in prediction accuracy and stability. Moreover, the IHO-ELM model is validated in a different region to assess its generalization ability for solar PV output prediction. The results confirm that the proposed hybrid approach not only improves prediction accuracy but also demonstrates robust generalization capabilities, making it a promising tool for predictive modeling in solar energy systems.

Using rapeseed straw as a raw material and potassium bicarbonate (KHCO3) and urea (CO(NH2)2) as modification reagents, the pyrolysis raw materials were mixed in a certain proportion, and the unmodified biochar GBC800, KHCO3-modified biochar KGBC800, and (KHCO3)/(CO(NH2)2) co-modified biochar N-KGBC800 were, respectively, prepared using the one-pot method at 800 °C. The physicochemical properties, such as surface morphology, pore characteristics, functional group distribution, and elemental composition of the three biochars, were characterized, and the adsorption performance and mechanism of the typical antibiotic tetracycline (TC) in water were studied. The results showed that the surface of GBC800 was smooth and dense, with no obvious pore structure, and both the specific surface area and total pore volume were small; the surface of KGBC800 showed an obvious coral-like three-dimensional carbon skeleton, the number of micropores and the specific surface area were significantly improved, and the degree of carbonization and aromatization was enhanced; N-KGBC800 had a coral-like three-dimensional carbon skeleton similar to KGBC800, and there were also many clustered carbon groups. The carbon layer changed significantly with interlayer gaps, presenting a multi-level porous structure. After N doping, the content of N increased, and new nitrogen-containing functional groups were formed. When the initial TC concentration was 100 mg/L, pH ≈ 3.4, the temperature was 25 °C, and the dosage of the three biochars was 0.15 g/L, the adsorption equilibrium was reached before 720 min. The adsorption capacities of GBC800, KGBC800, and N-KGBC800 for TC were 16.97 mg/g, 294.86 mg/g, and 604.71 mg/g, respectively. Fitting the kinetic model to the experimental data, the adsorption of TC by the three biochars was more in line with the pseudo-second-order adsorption kinetic model, and the adsorption isotherm was more in line with the Langmuir model. This adsorption process was a spontaneous endothermic reaction, mainly chemical adsorption, specifically involving multiple adsorption mechanisms such as pore filling, electrostatic attraction, hydrogen bonds, n−π interaction, Lewis acid–base interaction, π−π stacking, or cation −π interaction between the aromatic ring structure of the carbon itself and TC. A biochar-adsorption column was built to investigate the dynamic adsorption process of tetracycline using the three biochars against the background of laboratory pure water and salt water. The adsorption results show that the Thomas model and the Yoon–Nelson model both provide better predictions for dynamic adsorption processes. The modified biochars KGBC800 and N-KGBC800 can be used as preferred materials for the efficient adsorption of TC in water.

Cytokines are small proteins that regulate the growth and functional activity of immune cells, and several have been approved for cancer therapy. Oncolytic viruses are agents that mediate antitumor activity by directly killing tumor cells and inducing immune responses. Talimogene laherparepvec is an oncolytic herpes simplex virus type 1 (oHSV), approved for the treatment of recurrent melanoma, and the virus encodes the human cytokine, granulocyte-macrophage colony-stimulating factor (GM-CSF). A significant advantage of oncolytic viruses is the ability to deliver therapeutic payloads to the tumor site that can help drive antitumor immunity. While cytokines are especially interesting as payloads, the optimal cytokine(s) used in oncolytic viruses remains controversial. In this review, we highlight preliminary data with several cytokines and chemokines, including GM-CSF, interleukin 12, FMS-like tyrosine kinase 3 ligand, tumor necrosis factor α, interleukin 2, interleukin 15, interleukin 18, chemokine (C-C motif) ligand 2, chemokine (C-C motif) ligand 5, chemokine (C-X-C motif) ligand 4, or their combinations, and show how these payloads can further enhance the antitumor immunity of oHSV. A better understanding of cytokine delivery by oHSV can help improve clinical benefit from oncolytic virus immunotherapy in patients with cancer.

The purpose of this study was to analyze the characteristics of occurrence and spread of highly pathogenic avian influenza H5N1 (HPAI-H5N1) globally, understand its spatiotemporal characteristics, investigate the risk factors influencing outbreaks, and identify high-risk areas for disease occurrence. We collected the data on global poultry HPAI-H5N1 outbreaks from January 2005 to April 2023, and conducted a thorough analysis of the spatial and temporal characteristics of the disease through time series decomposition and directional distribution analysis. Additionally, an ecological niche model was established to explore the major factors influencing the occurrence of HPAI-H5N1 and to pinpoint high-risk areas. Our findings revealed that HPAI-H5N1 outbreaks were cyclical, and seasonal, exhibiting a rising trend, with a predominant northwest-southeast transmission direction. The ecological niche model highlighted that species factors and economic trade factors are critical in influencing the outbreak of HPAI-H5N1. Variables such as chicken and duck density, population density, isothermality, and road density, contributed to importantly risk of outbreaks. High-risk areas for HPAI-H5N1 occurrence were primarily identified in Europe, West Africa, Southeast Asia, and Southeast China. This study provided valuable insights into the spatial and temporal distribution characteristics and risk factors of global poultry HPAI-H5N1 outbreaks. The identification of high-risk areas provides essential information that can be used to develop more effective prevention and control policies.

Diclofenac (DCF) is often detected in diverse aquatic bodies, and ineffective management can lead to detrimental effects on human health and ecosystems. In this study, degradation of DCF by Fe(III) and Mn(II) activating bisulfite (BS) was investigated. In the Fe(III)/Mn(II)/BS system, 93.4% DCF was degraded at 200 μM BS within 120 s, and additional research on 1000 μM BS achieved 88.4% degradation efficacy. Moreover, kinetics fitting of DCF degradation with the different BS concentrations was studied to find the two highest reaction rates (200 and 1000 μM, kobs = 0.0297 and 0.0317 s−1, respectively). Whereafter, SO4•− and Mn(III) were identified as the main active species at these two concentrations, respectively. Density functional theory (DFT) calculations, molecular frontier orbital theory, and surface electrostatic potential (ESP) forecast electrophilic attack sites. DCF degradation pathways by radical and non-radical ways were proposed by attack site prediction and thirteen intermediates identified by UPLC-QTOF-MS. ECOSAR software 2.2 was used for toxicity assessment. This work studied DCF degradation by the Fe(III)/Mn(II)/BS process in the presence of different concentrations of BS, providing a new insight into water purification.

Hepatic ischemia/reperfusion injury (IRI) is an important factor affecting liver regeneration and functional recovery postoperatively. Many studies have suggested that mesenchymal stem cells (MSCs) contribute to hepatic tissue repair and functional recovery through paracrine mechanisms mediated by exosomes. Minipigs exhibit much more similar characteristics of the liver to those of humans than rodents. This study aimed to explore whether exosomes from adipose-derived MSCs (ADSCs-exo) could actively promote liver regeneration after hepatectomy combined with HIRI in minipigs and the role they play in the cell proliferation process. This study also compared the effects and differences in the role of ADSCs and ADSCs-exo in the inflammatory response and liver regeneration. The results showed that ADSCs-exo suppressed histopathological changes and reduced inflammatory infiltration in the liver; significantly decreased levels of ALT, TBIL, HA, and the pro-inflammatory cytokines TNF-α, IL-6, and CRP; increased levels of the anti-inflammatory cytokine IL-10 and the pro-regeneration factors Ki67, PCNA, CyclinD1, HGF, STAT3, VEGF, ANG1, ANG2; and decreased levels of the anti-regeneration factors SOCS3 and TGF-β. These indicators above showed similar changes with the ADSCs intervention group. Indicating that ADSCs-exo can exert the same role as ADSCs in regulating inflammatory responses and promoting liver regeneration. Our findings provide experimental evidence for the possibility that ADSCs-exo could be considered a safe and effective cell-free therapy to promote regeneration of injured livers.

Abstract Background Mosquitoes play an absolute role in the spread of epidemic arbovirus diseases. Worldwide, Aedes aegypti and Aedes albopictus are the main vectors responsible for the spread of these mosquito-borne diseases. Aedes vexans, a mosquito species native to China, also carries mosquito-borne viruses, such as dengue fever virus and Japanese encephalitis virus, but research on this mosquito has been inadequate. Mapping the potential distribution range of and monthly change in the distribution of these three Aedes species is of particular importance for mosquito surveillance, eradication and disease control. Methods Monitoring data were collected for the three Aedes species in China. Long-term temperature and precipitation data (2001–2021) and land cover data were used to represent various climate and environmental conditions. An ecological niche model was developed using a maximum entropy modeling method to predict the current optimum habitat areas for the three Aedes species and to obtain important variables influencing their monthly distribution. Results The distribution model for the three Aedes species performed well, with an area under the receiver operating characteristic curve value of 0.991 for Ae. aegypti, 0.928 for Ae. albopictus and 0.940 for Ae. vexans. Analysis of the distribution change and mapping of the optimum habitat range for each Aedes species for each month demonstrated that temperature, precipitation and construction land were important factors influencing the distribution of these three Aedes species. Conclusions In China, Aedes aegypti is mainly concentrated in a few tropical regions and along the Yunnan border; Aedes albopictus is widely distributed throughout most of the country, except for the arid and semi-arid regions of northwest China; and Aedes vexans is mainly found in the northern regions. Our results provide a basis for the timing and location of surveillance efforts for high-priority mosquitoes. Graphical abstract

This is a paper in the field of mineral processing engineering. Iron separation experiments of the untabulated ore of Yangtianwo and the untabulated ore of Tianjiacun were carried out by comparing the untabulated ore of Baima in Panxi.Results show that when the TFe grade is equivalent to that of iron concentrate,the iron grinding fineness of Tianjiacun off-table ore is finer than that of Yangtianwoore,the iron concentrate yield and recovery are better than that of Yangtianwo ore,and the content of harmful elements S and P in Tianjiacun iron concentrate is lower than that of Yangtianwo ore,the content of titanium in Tianjiacun high-quality iron concentrate is higher than that of Yangtianwo ore,which is disadvantageous to blast furnace smelting,and the value of titanium in its total iron tailings is lower than that of Yangtianwo ore.The research results provide data support and technical support for the rational utilization of off-balance sheet mineral resources in Tianjiacunand Yangtianwo.

Abstract Grona styracifolia is a photophilous legume that contains abundant flavonoids with multiple pharmacological activities, which is used to cure urethral and biliary calculus in China for thousands of years. The authentication of the rate-limiting enzymes involved in the flavonoids biosynthesis pathway enabled a better understanding of the molecular aspect of quality formation and modulation of this medicinal herb. In this study, the chemical distribution characteristics and content of flavonoids in different tissues of Grona styracifolia were analyzed using ultraperormance liquid chromatography coupled with Q-TOF mass spectrometry and showed that active flavonoids were primarily synthesized and stored in the leaves. Subsequently, RNA sequencing (RNA-seq)-based transcriptome profiling of the different tissues revealed that the flavonoids biosynthesis in the leaves was the most active. Meanwhile, 27 full-length transcripts inferred encoding vital enzymes involved in the flavonoids biosynthesis were preliminarily excavated. Finally, four CHSs, four CHIs, and one FNSII were successfully characterized by heterologous expression, which involved in three rate-limiting steps of the flavonoid biosynthetic pathway. In conclusion, these results laid a foundation for further investigation of the molecular mechanism of the biosynthesis and modulation of active flavonoids in Grona styracifolia.

BackgroundFiber dysplasia is a complex condition that presents with various clinical manifestations, such as deformity, dysfunction, pathological fractures, and endocrine disorders. McCune–Albright syndrome (MAS) is a rare subtype of fiber dysplasia. This article reports a case of atypical McCune–Albright syndrome in a patient with a femoral neck fracture.Case presentationA patient with atypical McCune–Albright syndrome sustained a right femoral neck fracture and underwent multiple treatments, including total hip replacement, intravenous infusion of zoledronic acid, oral calcium supplementation, right supracondylar osteotomy, orthopedic surgery, plate and screw internal fixation for a left femoral shaft fracture, and removal of the right femoral plate. The patient also developed a submaxillary infection complicated by mandibular osteonecrosis.ConclusionPatients with MAS may experience rare complications as a result of their unique condition, regardless of whether they receive drug or surgical treatment. Therefore, personalized drug regimens and feasible surgical options are necessary.

Hepatic ischemia-reperfusion injury (HIRI) is a complication of hepatectomy that affects the functional recovery of the remnant liver, which has been demonstrated to be associated with pyroptosis and apoptosis. Mesenchymal stem cells (MSCs) can protect against HIRI in rodents. Paracrine mechanisms of MSCs indicated that MSCs-derived exosomes (MSCs-exo) are one of the important components within the paracrine substances of MSCs. Moreover, miniature pigs are ideal experimental animals in comparative medicine compared to rodents. Accordingly, this study aimed to investigate whether hepatectomy combined with HIRI in miniature pigs would induce pyroptosis and whether adipose-derived MSCs (ADSCs) and their exosomes (ADSCs-exo) could positively mitigate apoptosis and pyroptosis. The study also compared the differences in the effects and the role of ADSCs and ADSCs-exo in pyroptosis and apoptosis. Results showed that severe ultrastructure damage occurred in liver tissues and systemic inflammatory response was induced after surgery, with TLR4/MyD88/NFκB/HMGB1 activation, NLRP3-ASC-Caspase1 complex generation, GSDMD revitalization, and IL-1β, IL-18, and LDH elevation in the serum. Furthermore, expression of Fas-Fasl-Caspase8 and CytC-APAF1-Caspase9 was increased in the liver. The ADSCs or ADSCs-exo intervention could inhibit the expression of these indicators and improve the ultrastructural pathological changes and systemic inflammatory response. There was no significant difference between the two intervention groups. In summary, ADSCs-exo could effectively inhibit pyroptosis and apoptosis similar to ADSCs and may be considered a safe and effective cell-free therapy to protect against liver injury.

Straw return is a common cultivation to improve soil fertility and realize sustainable agricultural development. However, the effect of returning interval on the corn straw humification process in northeast China is little known. In this study, a four-year field trial was conducted to investigate the characteristics of soil carbon sequestration under the annual deep straw return (T1), the biennial deep straw return (T2), and the non-straw return (T3) in Jilin Province, China. In order to precisely evaluate the soil organic carbon density (SOCD), each soil horizon was divided differently according to the actual situation, rather than a fixed thickness. The results show that both the annual and the biennial deep straw return had a significantly positive influence on the content of soil organic carbon (SOC), humic acid, fulvic acid, and humin in the plough pan (straw-applied horizon), compared to the no-straw return. SOC of the cambic horizon and the C horizon in annual straw return was 28.78%, 47.44% higher than the biennial straw return, but it was 27.58% lower in the plough pan. The SOCD in the plough pan in the biennial straw return was higher than the annual straw return, but their difference in the entire soil profile was not significant. However, the conversion rate of straw carbon to SOC was 18.42% in the annual straw return and 21.05% in the biennial straw return. The straw return amount was not a key factor affecting the SOC sequestration in the cold area; it was restricted by the comprehensive effects of the cold weather, the intensity of soil disturbance, C/V and the initial SOC content. In conclusion, the biennial deep straw return was a better management tool, as it generally had an identical quality and quantity of soil organic carbon and a higher straw conversion rate relative to the annual deep straw return.

The Dongsha area, a key region in the northern South China Sea (SCS), features both diffusive deep and seepage shallow gas hydrate reservoirs. Utilizing sediment samples from gas hydrate reservoirs and adjacent layers at sites W08 and W16 in the Dongsha area, this study aims to uncover the sediment property differences between deep and shallow gas hydrate reservoirs and their impact on gas hydrate accumulation through grain size, X-ray diffraction, and specific surface area (SSA) analyses. The findings classify the study intervals into four distinct layers: shallow non-gas hydrate layer (shallow-NGHL), shallow gas hydrate reservoir (shallow-GHR), deep non-gas hydrate layer (deep-NGHL), and deep gas hydrate reservoir (deep-GHR). In the clayey silt sediment reservoirs, grain size has a minor influence on gas hydrate reservoirs. Both shallow and deep NGHLs, characterized by high smectite content and SSA, possess a complex structure that impedes gas and fluid migration and offers limited potential reservoir space. Consequently, both shallow and deep NGHLs function as sealing beds. The deep GHR, having low smectite content and SSA, exhibits a strong capacity for gas and fluid migration and greater potential reservoir space. As a result, sediment properties significantly influence the deep GHR. Seepage primarily controls the shallow GHR.

In this paper, we obtain some boundedness of the n-dimensional fractional Hardy operators with rough kernels and their commutators on central Morrey spaces with variable exponents.

In recent years, fake news has had a bad impact on individuals and society, which has aroused widespread concern about fake news detection. The existing heterogeneous graph-based fake news detection model (CompareNet) mainly focuses on the semantic consistency analysis between news content and external knowledge, which out-performs traditional content detection models in terms of its efficiency and scalability. However, we found that the framework ignores the fact that the node content of heterogeneous graphs is mostly in the form of short text, and such methods often have difficulty in extracting effective features due to the sparsity problem of short text data. In addition, previous studies have not considered the structural relationship between different writing styles of fake news. Aiming at the above problems this paper proposes a topic-aware fake news detection (FND) method based on heterogeneous graphs, the model investigates the effect of news topics on fake news detection and enhances the discriminative ability of fake news detection. Our model introduces semantically enhanced topic node information in the fake news detector, which fully utilizes three types of information: external knowledge (Wikipedia), news content, and news topics. Therefore, it can better enhance the fake news detection performance.

Precipitation nowcasting underlying various public services from rainstorm warning to flight safety is quite important and remains challenging due to the fast change in convective weather. Although some deep learning models have been proposed to make prediction automatically, most of them just deal with a single radar echo data source, making them hard to adapt to heterogeneous and diverse data in practice. In this article, a heterogeneous spatiotemporal attention fusion prediction (HST-AFP) network is proposed for radar echo extrapolation (deterministic output) and further precipitation nowcasting, which deals with mining and fusing knowledge from multiple heterogeneous spatiotemporal (ST) data sources, including history radar echo observations and numerical weather prediction data. With the help of the proposed attention-based ST diffusion module, the multiencoder is designed to extract information from both dense ST tensor and sparse ST tensor. On the other hand, the fusion decoder achieves very deep trainable residual fusion prediction by integrating scalewise attention fusion module and deep residual spatial and temporal attention mechanism. It can adaptively blend multisource ST features and rescale the multiscale temporalwise and spatialwise features for better prediction. Experiments in a real-world dataset of South China show that compared with the ingenious recurrent-neural-network-based methods and newly proposed UNet-based methods, our HST-AFP network can handle complex input with heterogeneity in both space and time domains, and performs better on the precipitation nowcasting metrics as well as requires remarkable shorter forecast time.

Effect of pre-tension deformation on the rusting behavior of S450EW weathering steel was studied through electrochemical measurements and characterizations on rust layer. The rust layers are no longer stratified and become porous on the deformed samples. Simultaneously, the occlusion effect beneath the rust layer is alleviated. Owing to the above both aspects, the rust layer keeps a composition of approximately 7 wt% γ-FeOOH, 20 wt% α-FeOOH, and 73 wt% Fe3O4/γ-Fe2O3 under each deformation degree. The deformation increases the defects in the incipient passive film, thereby promoting rust generation but leaving inadequate time for the evolution of the rust layer.

Aiming at the fact that the impact of quarantine on network virus propagation has not been considered in existing dynamical models, a network virus paopagation model with dynamical quarantine was proposed on the basis of the simple epidemic SI model. The basic idea of the model is that the suspicious node is quaranteened immediately as soon as the network intrusion detection system finds the suspicious behavior of node. Then, the isolated node is released after a short of period. Furthermore, by using stochastic probability theory, under the assumption that the activity of network nodes follows a Poisson distribution with different degrees of activity, a mathematical expression is obtained for the number of network nodes that may be isolated at any one time. Finally, numerical experiments simulate the change trend of the speed and scale of network virus spread over time with different values of isolation parameters. Simulation results show that quarantine measures can effectively delay the spread of network viruses, and quarantine time has a significant impact on the speed and scale of network viruses. When quarantine time exceeds 0.5 minutes, the scale of network virus spread will be reduced by about 72%.

Background: Germline HLA class I molecule supertypes are shown to correlate with response to anti-PD-1 therapy. Here, we investigate the significance of germline HLA-A and HLA-B supertypes in tumour microenvironment of non-small-cell lung cancer. Methods: Totally 278 NSCLC patients were collected retrospectively. HLA genotyping was conducted using next-generation sequencing. The evaluation of tumour-infiltrating lymphocytes was performed by multiplex immunohistochemistry assay. Correlations among HLA supertypes, tumour infiltrating lymphocytes, and clinicopathological characteristics were assessed. Results: HLA-A03 and HLA-B62 were the supertypes with the highest proportions, at 69.1% and 52.2%, respectively. HLA-A02 or HLA-B62, but not HLA-A03, associated with higher PD-L1+ tumour and stromal cells levels, CD68+ cells, and CD68+PD-L1+ cells. Patients with both HLA-A02 and HLA-B62 supertypes displayed significantly higher PD-L1+ cells, CD68+ cells, and CD8+ cells levels than patients with other supertypes (P = 0.0301, P = 0.0479, P = 0.0192). These cells collectively constitute a hot but immunosuppressive tumour microenvironment. Accordingly, patients with both HLA-A02 and HLA-B62 supertypes had short progression-free survival after surgery (HR = 2.27, P = 0.0373). Conclusions: The HLA-A02B62 supertype could serve as a possible indicator of poor prognosis in early-stage lung cancer. However, it may also act as a favorable prognostic factor for immunotherapy, given its association with a PD-L1-positive tumour microenvironment.

This paper studied the effects of hydrogen plasma irradiation on the corrosion resistance of Mo capillary porous systems (CPSs) in high temperature liquid Sn. Initial Mo CPSs showed a significant morphology change and mass loss rate (1.107 × 10–3 mg/(mm2·h)) after corrosion in liquid Sn at 1,023 K for 100 h. A brief period of irradiation enhanced the corrosion resistance of Mo wires, resulting in a dramatic decrease to 1.23 × 10–4 mg/(mm2·h) in mass loss rate under the same corrosion conditions. To determine whether temperature was the main factor leading to above phenomenon, Mo CPSs were pre-annealed at the same temperature (843 K) as irradiation. The mass loss rate of annealed Mo CPSs (3.09 × 10–4 mg/(mm2·h)), which was lower than that of the initial sample, was still higher than that of the plasma-treated samples. Difference between plasma irradiation and heat treatment was the incident of various particles in hydrogen plasma. Therefore, the suppressed corrosion phenomenon caused by plasma could not only be attributed to the function of high temperature but its synergistic effect with hydrogen isotope retention.

A manganese dioxide-modified red mud (Mn-RM) was developed as an adsorbent for the effective removal of lead ions (Pb2+) from wastewater. Various methods were used to characterize the prepared Mn-RM, analyze its adsorption performance, and evaluate the associated environmental risks post-adsorption. The results revealed that Mn-RM has a large surface area (38.91 m2/g) and a developed porous structure (0.02 cm3/g). The adsorption process exhibited good agreement with the Langmuir isotherm and pseudo-second-order kinetic models, showcasing a theoretical maximum saturation adsorption capacity of 721.35 mg/g. The adsorption mechanism primarily involves electrostatic attraction, ion exchange, and chemical precipitation. The optimal treatment conditions were determined by utilizing a response surface model, resulting in a maximum Pb2+ removal efficiency of 87.45% at pH 5.21, a dosage of 0.83 g/L, and an initial concentration of 301.04 mg/L. The risk assessment code (RAC) for each heavy metal in Mn-RM was less than 1%, indicating low environmental risk. Furthermore, the synthetic toxicity index (STI) values showed a significant decrease post-treatment. This study introduces the concept of “controlling waste with waste”, offering a cost-effective approach to both utilizing red mud and removing aqueous Pb2+ while ensuring environmental safety and minimal ecological impact.

In accordance with the IEEE standard, the zero-sequence impedance test of transformers necessitates an open or short circuit test on the high-voltage side winding. Power source excitation is applied to the high-voltage test winding using a high-capacity test power supply. To circumvent the need for a large-capacity, high-voltage test power supply in field tests, this paper proposes a method for measuring zero-sequence impedance in autotransformers based on low-voltage excitation and disconnection testing. By applying a three-phase power supply to the lowest voltage side of the autotransformer and creating a disconnection condition, an unbalanced test scenario is established. Subsequently, the composite sequence network equivalent circuit for one-phase and two-phase disconnections between the high-voltage side and the low-voltage side of the transformer is formulated. Calculation formulas for the zero-sequence impedance of the autotransformer under various conditions are derived. The accuracy of the zero-sequence impedance is verified using MATLAB/Simulink simulation software 2018b, evaluating double-winding and three-winding autotransformers in breaking tests under different connection modes. The error is found to be less than 3%. The results of this study affirm the high accuracy of the proposed method.

Abstract Background The therapeutic effects of adipose-derived mesenchymal stromal cells (ADSCs) may be mainly mediated by their paracrine effects. The ADSC-secretome can ameliorate hepatic ischemia–reperfusion injury (IRI). We explored the therapeutic effect of the ADSC-secretome from the perspective of excessive hepatocyte autophagy induced by hepatic IRI. Methods We established a miniature pig model of hepatic ischemia–reperfusion (I/R) and hepatectomy using a laparoscopic technique and transplanted ADSCs and the ADSC-secretome into the liver parenchyma immediately after surgery. Liver injury and hepatocyte autophagy were evaluated by histopathological examination and assessment of relevant cytokines and other factors. Results The results showed that the ADSC-secretome alleviated the pathological changes of liver tissue and the microstructural damage of hepatocytes after IRI. Moreover, the expression levels of autophagy-related markers including Beclin-1, ATG5, ATG12, and LC3II/LC3I decreased, whereas those of p62 increased during phagophore expansion. Furthermore, the expression levels of markers related to the autophagy inhibition pathway phosphatidylinositol-3-kinase/Akt/mammalian target of rapamycin (PI3K/Akt/mTOR), including PI3K, Akt, and mTOR, increased. Conclusion The ADSC-secretome attenuates hepatic I/R and hepatectomy-induced liver damage by inhibiting autophagy, which is possibly mediated by activation of the PI3K/Akt/mTOR signaling pathway. In addition, there was no significant difference between ADSCs and the ADSC-secretome in the regulation of hepatocyte autophagy. Therefore, ADSCs may improve the excessive autophagy-induced injury of hepatocytes in hepatic I/R and hepatectomy through paracrine effect. Our findings provide new insight into the therapeutic potential of cell-free products, which could replace cell therapy in liver diseases.

The optical and biological properties of functionalized gold nanoparticles (GNPs) have been widely used in sensing applications. GNPs have a strong binding ability to thiol groups. Furthermore, thiols are used to bind functional molecules, which can then be used, for example, to detect metal ions in solution. Herein, we describe 13 nm GNPs functionalized by glutathione (GSH) and conjugated with a rhodamine 6G derivative (Rh6G2), which can be used to detect Hg(II) in cells. The detection of Hg2+ ions is based on an ion-catalyzed hydrolysis of the spirolactam ring of Rh6G2, leading to a significant change in the fluorescence of GNPs-GSH-Rh6G2 from an “OFF” to an “ON” state. This strategy is an effective tool to detect Hg2+ ions. In cytotoxicity experiments, GNPs-GSH-Rh6G2 could penetrate living cells and detect mercury ions through the fluorescent “ON” form.

Abstract This paper studies unmanned aerial vehicles (UAV) enabled industrial Internet of Things while a UAV dispatched to collect data of low‐power ground sensor nodes (SNs) in multi‐obstacle environment. The authors aim to minimize the completion time while satisfying the communication link constraints of each SN and obstacle avoidance, data collection requirements etc. To this end, the authors first formulate the completion time minimization problem by jointly optimizing the UAV trajectory and collection sequence of SNs. The problem is difficult to be optimally solved, as it is non‐convex. To tackle this problem, the authors first transform the original problem to a Traveling Salesman Problem‐like (TSP‐like) problem based on a hover point that can naturally satisfy the communication link constraints of data collection. The dynamic programming (DP) algorithm to figure out the order in which the UAV collects each SN, which gives the initial path of the UAV traversing each SN from the beginning point to the end point. Next, the authors consider the general scenarios of data collection tasks where the UAV also communicates while flying. The authors construct an equivalent problem with integer variable constraints for the original problem with indicative function constraints. The authors rewrite the non‐convex constraints of the equal problem by introducing slack variables and leveraging the SCA, and add the discrete region threat constraints for the traditional path discretization method. Finally, the simulation results verify the effectiveness of the proposed algorithm under different parameter configurations.

Tumorigenic cancer stem cells (CSCs) represent a subpopulation of cells within the tumor that express genetic and phenotypic profiles and signaling pathways distinct from the other tumor cells. CSCs have eluded many conventional anti-oncogenic treatments, resulting in metastases and relapses of cancers. Effectively targeting CSCs’ unique self-renewal and differentiation properties would be a breakthrough in cancer therapy. A better characterization of the CSCs’ unique signaling mechanisms will improve our understanding of the pathology and treatment of cancer. In this paper, we will discuss CSC origin, followed by an in-depth review of CSC-associated signaling pathways. Particular emphasis is given on CSC signaling pathways’ ligand-receptor engagement, upstream and downstream mechanisms, and associated genes, and molecules. Signaling pathways associated with regulation of CSC development stand as potential targets of CSC therapy, which include Wnt, TGFβ (transforming growth factor-β)/SMAD, Notch, JAK-STAT (Janus kinase-signal transducers and activators of transcription), Hedgehog (Hh), and vascular endothelial growth factor (VEGF). Lastly, we will also discuss milestone discoveries in CSC-based therapies, including pre-clinical and clinical studies featuring novel CSC signaling pathway cancer therapeutics. This review aims at generating innovative views on CSCs toward a better understanding of cancer pathology and treatment.

We analyze, for the first time in the oceanographic literature, pH over the top ~10 m of the sediment (down to 11.9 m) in a deep-sea environment, together with the oxidation/reduction potential and concentrations of solid organic carbon (OC) and CaCO3. A total of 1157 sediment cores were collected from years 2000 to 2011 over >300,000 km2 in the South China Sea, at water depths up to 3702 m. We found that there were marked downward pH increases in the upper 2 m of the sediment (first 20-40 ka, corresponding to the geochemically active period). In deeper, older sediment (up to 200 ka), pH was generally less variable with depth but not uniform, and solid OC may have been consumed down to ≥10 m depth. This reflected interactions between in situ geochemical diagenetic processes, which tended to create vertical variations, and vertical diffusion of ions, which tended to even out vertical variability. In other words, there were slow diagenetic geochemical processes in the sediment layer below 2 m, and the effects of these in situ processes were partly offset by vertical diffusion. Overall, our study identified a previously unknown consistent pH difference between the upper 2 m of the sediment and the underlying layer down to ≥10 m, and suggested combinations of geochemical diagenetic processes and vertical diffusion of ions in the porewater to explain it. These results provide a framework for further studies of pH in the top multi-meter layer of the sediment in the World Ocean.

High-speed laser interferometry is synchronized with a high-speed camera to visualize the dynamic microlayer behavior during bubble growth in a pool boiling under pressures from 0.1 to 0.3 MPa. An Indium–Tin-Oxide (ITO) film coated on sapphire is employed as the heating unit to provide the nominal surface heat fluxes in the range from 90 to 150 kW/m2. Based on the instantaneous microlayer thickness and photographed bubble images, microlayer formation and depletion and their relationship with bubble growth are analyzed. Appreciable effects of pressure on microlayer dynamics and bubble growth have been observed. At higher pressure, the microlayer existence time decreases and consequently, the contribution of the microlayer evaporation becomes less important. At elevated pressure, the effects of liquid subcooling and surface heat flux on bubble growth become more pronounced. The dimensionless instantaneous maximum microlayer thickness, δmax/νt, shows exponential dependence on the ratio rd/rb,1 which increases linearly with time before the microlayer depletion. A correlation is proposed to predict the instantaneous maximum microlayer thickness synthesizing the two relations. The local heat flux will be overestimated and the wall temperature profile is contrary to the experimental observation when the flow inside the microlayer is negligible. During the bubble growth period, only part of the microlayer is evaporated and the internal flow inside cannot be neglected.

Abstract In this study, the problem of estimating multiple frequency‐hopping (FH) signal parameters in situations in which random observations are missing is addressed. A uniform linear array (ULA) is utilized to receive FH signals, and the missing observations are considered to be equivalent to randomly missing elements in the space‐time matrix obtained from the ULA. Bayesian compressed sensing (BCS) estimates the hopping time of received FH signals by the spatial information from the space‐time matrix and restores the missing observations. The estimated hopping time is implemented as the boundary to divide the signals such that each segment contains a superposition of time‐invariant multiple components. Then, the instantaneous frequency (IF) of multiple components can be estimated precisely by atomic norm soft thresholding (AST) within each segment. After estimating the hopping time and IF, the direction of arrival (DOA) of multiple signals is directly calculated using these two parameters. The simulation results show that the proposed method is superior to existing approaches. Provided that sufficient array elements are available, multi‐FH signal parameters can be estimated with satisfactory accuracy even when a large portion of observations is missing.

Abstract As a key method to deal with loop integrals, Integration-By-Parts (IBP) method can be used to do reduction as well as establish the differential equations for master integrals. However, when talking about tensor reduction, the Passarino-Veltman (PV) reduction method is also widely used for one-loop integrals. Recently, we have proposed an improved PV reduction method, i.e., the PV reduction method with auxiliary vector R, which can easily give analytical reduction results for any tensor rank. However, our results are only for integrals with propagators with power one. In this paper, we generalize our method to one-loop integrals with general tensor structures and propagators with general powers. Our ideas are simple. We solve the generalised reduction problem by combining differentiation over masses and proper limit of reduction with power-one propagators. Finally, we demonstrate our method with several examples. With the result in this paper, we have shown that our improved PV-reduction method with auxiliary vector is a self-completed reduction method for one-loop integrals.

The frequent occurrence of extreme meteorological disasters in urban areas during winter poses great impacts on the secure operation of regional energy infrastructures, leading to cascading failures and load losses in integrated energy systems (IESs). To enhance IES’s capacity to cope with extremely cold disasters, we analyze emergency response strategies in the post-disaster period and establish a top–down and bottom–up restoration model. For the top–down strategy, automatic control of the unit and network topology and human resource deployments are considered. For the bottom–up strategy, the energy consumption patterns are adjusted by the users. Post-disaster restoration greatly improves the working performance of the IES in the event of weather disasters by leveraging these two types of strategies and the complementary characteristic between heat and electrical energy. The entire post-disaster recovery process is modeled as a mixed-whole linear program, which can be solved quickly offline. It is tested on an IES with 9 electrical nodes and 32 heat nodes. The results demonstrate that the proposed model is effective and efficient.

Abstract The effects of polycyclic aromatic hydrocarbons on phytoplankton have been extensively documented, but there is limited knowledge about the physiological responses of marine primary producers to phenanthrene at environmentally relevant levels. Here, we investigated the toxicity of phenanthrene (0, 1, and 5 or 10 μg L−1) to the physiological performance of two cosmopolitan phytoplankton species: the green alga Chlorella vulgaris and bloom-forming diatom Skeletonema costatum. The specific growth rates of both species were remarkably inhibited at both low (1 μg L−1) and high phenanthrene concentrations (5 or 10 μg L−1), while their tolerance to phenanthrene differed. At the highest phenanthrene concentration (10 μg L−1), the growth of C. vulgaris was inhibited by 69%, and no growth was observed for S. costatum cells. The superoxide dismutase activity of both species was enhanced at high phenanthrene concentration, and increased activity of catalase was only observed at high phenanthrene concentration in C. vulgaris. Interestingly, the low phenanthrene concentration stimulated the photosynthetic and relative electron transport rates of S. costatum, whereas hormetic effects were not found for growth. Based on our results, phenanthrene could be detrimental to these two species at a environmentally relevant level, while different tolerance levels were detected.

Traumatic brain injury (TBI) is a severe condition that leads to brain damage and affects brain function. Importantly, TBI incurs public health costs due to its high mortality, and effective treatment for TBI is still lacking. Docosahexaenoic acid (DHA) has a neuroprotective effect that can reduce oxidative, apoptosis, and inflammatory processes. Administration of DHA after TBI attenuates oxidative stress and protein accumulation and is regarded as a potential therapeutic. Iduna is a regulator of parthanatos, and upregulation of Iduna reduces cellular damage and mitochondrial dysfunction. Thus, we speculated that overexpression of Iduna might promote DHA therapy in the treatment of TBI. Here, we found that after combination overexpression of Iduna and DHA in a mouse model of TBI, the expression of inflammatory factors was reduced, while the secretion of neuroprotective factors was increased. In addition, we found that these effects might be mediated by the Wnt/MDM2 pathway, and Iduna might be a therapeutic target for TBI.

Faced with the large amount of unlabeled short text data appearing on the Internet, it is necessary to categorize them using clustering that can divide text into several clusters based on similarity degree of text semantics. Recently, combining clustering with contrastive learning has been the focus of clustering research. Due to the excellent representation learning ability of contrastive learning, clustering achieves better results on short texts that are high-dimensional and sparse. However, contrastive learning pays more attention to general feature representation at the instance-level and ignores the semantic-level correlation of data belonging to same cluster in clustering. The inconsistent training objectives of contrastive learning and clustering lead to lower confidence of clustering results and sparse cluster space. To improve this problem, we propose a clustering method based on Dynamic Adjustment for Contrastive Learning (DACL). The method smoothly transitions loss weight of model from contrastive learning to clustering during training and filters negative samples in contrastive learning by the pseudo-labels generated by clustering. To demonstrate the effectiveness of the method, DACL is compared with eight short text clustering models on eight datasets. The results show that we achieve considerable performance improvements on most datasets compared to state-of-the-art short text clustering methods. In addition, The effectiveness of loss smooth transition and negative filtering is proved by ablation experiments.

Abstract Background Alkaline earth metal ions are important protein binding ligands in human body, and it is of great significance to predict their binding residues. Results In this paper, Mg2+ and Ca2+ ligands are taken as the research objects. Based on the characteristic parameters of protein sequences, amino acids, physicochemical characteristics of amino acids and predicted structural information, deep neural network algorithm is used to predict the binding sites of proteins. By optimizing the hyper-parameters of the deep learning algorithm, the prediction results by the fivefold cross-validation are better than those of the Ionseq method. In addition, to further verify the performance of the proposed model, the undersampling data processing method is adopted, and the prediction results on independent test are better than those obtained by the support vector machine algorithm. Conclusions An efficient method for predicting Mg2+ and Ca2+ ligand binding sites was presented.