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AbstractResearch objective To explore the diagnostic value of circ-DENN domain containing 4 C (circDENND4C) in epithelial ovarian cancer (EOC) and the corresponding mechanism.Methods We determined the expression of circDENND4C and miR-200b/c in tissues and serum specimens as well as EOC cell lines using qRT-PCR. Basic clinical data, and serum HE4 and CAl25 levels were acquired from patients’ clinical records. Expression-related correlations and the diagnostic value of serum circDENND4C in EOC were also estimated. CCK-8 and flow cytometry were performed to detect the effect of circDENND4C on cell proliferation and apoptosis.Results circDENND4C level was lowest while miR-200b/c was highest in EOC tissues, followed by benign and normal tissues. Similarly, serum circDENND4C was lowest while miR-200b/c was highest in EOC patients. Moreover, serum circDENND4C was lower in patients with benign ovarian tumors than in healthy women, while miR-200b/c expression was higher. circDENND4C was negatively associated with miR-200b/c in EOC tissues and serum specimens, and serum circDENND4C was also negatively correlated with serum HE4 and CAl25 in EOC patients. circDENND4C expression in both tissue and serum was negatively related to FIGO and TNM stage, and tumor size in EOC. Serum circDENND4C could distinguish healthy persons from patients with benign ovarian tumors and EOC, and they showed a higher specificity and accuracy than serum CA125 or HE4 in EOC diagnosis. circDENND4C upregulation significantly suppressed EOC cell proliferation and facilitated apoptosis by downregulating miR-200b/c in vitro.Conclusions Summarily, circDENND4C acts as a tumor inhibitor by downregulating miR-200b/c in EOC and could be a possible tumor marker for EOC diagnosis.KEY MESSAGEScircDENND4C expression was lowest while miR-200b/c was highest in EOC tissues or serums, followed by benign and normal tissues or serums.circDENND4C was involved in malignant progression of EOC, concretely, overexpression of circDENND4C suppressed EOC cell proliferation and stimulated apoptosis via downregulating miR-200b/c, and circDENND4C expression in both tissue and serum was closely related to FIGO and TNM stages and tumor size in EOC.Serum circDENND4C showed a higher specificity and accuracy than serum CA125 or HE4 in EOC diagnosis.HIGHLIGHTScircDENND4C expression was lowest while miR-200b/c was highest in EOC tissues, followed by benign and normal tissues.Serum circDENND4C was lowest while miR-200b/c was highest in EOC patients, followed by benign patients and healthy women.Overexpression of circDENND4C suppresses EOC cell proliferation and stimulates apoptosis via downregulating miR-200b/c.circDENND4C expression in both tissue and serum was closely related to FIGO and TNM stage and tumor size in EOC.Serum circDENND4C showed a higher specificity and accuracy than serum CA125 or HE4 in EOC diagnosis.

BackgroundWith the increasing use of radiomics in cancer diagnosis and treatment, it has been applied by some researchers to the preoperative risk assessment of endometrial cancer (EC) patients. However, comprehensive and systematic evidence is needed to assess its clinical value. Therefore, this study aims to investigate the application value of radiomics in the diagnosis and treatment of EC.MethodsPubmed, Cochrane, Embase, and Web of Science databases were retrieved up to March 2023. Preoperative risk assessment of EC included high-grade EC, lymph node metastasis, deep myometrial invasion status, and lymphovascular space invasion status. The quality of the included studies was appraised utilizing the RQS scale.ResultsA total of 33 primary studies were included in our systematic review, with an average RQS score of 7 (range: 5–12). ML models based on radiomics for the diagnosis of malignant lesions predominantly employed logistic regression. In the validation set, the pooled c-index of the ML models based on radiomics and clinical features for the preoperative diagnosis of endometrial malignancy, high-grade tumors, lymph node metastasis, lymphovascular space invasion, and deep myometrial invasion was 0.900 (95%CI: 0.871–0.929), 0.901 (95%CI: 0.877–0.926), 0.906 (95%CI: 0.882–0.929), 0.795 (95%CI: 0.693–0.897), and 0.819 (95%CI: 0.705–0.933), respectively.ConclusionsRadiomics shows excellent accuracy in detecting endometrial malignancies and in identifying preoperative risk. However, the methodological diversity of radiomics results in significant heterogeneity among studies. Therefore, future research should establish guidelines for radiomics studies based on different imaging sources.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=364320 identifier CRD42022364320.

ELABELA (ELA), also known as Toddler or Apela, is a novel endogenous ligand of the angiotensin receptor AT1-related receptor protein (APJ). ELA is highly expressed in human embryonic, cardiac, and renal tissues and involves various biological functions, such as embryonic development, blood circulation regulation, and maintaining body fluid homeostasis. ELA is also closely related to the occurrence and development of acute kidney injury, hypertensive kidney damage, diabetic nephropathy, renal tumors, and other diseases. Understanding the physiological role of ELA and its mechanism of action in kidney-related diseases would provide new targets and directions for the clinical treatment of kidney diseases.

Abstract All life forms require pH homeostasis. The disorder of pH homeostasis is associated with many severe diseases, suggesting the significance of pH‐detection for theranostic diseases. Photoacoustic imaging (PAI) technology has piqued great research interests in spatiotemporal detection of pH in vivo due to its non‐invasiveness and non‐ionization, as well as the high resolution and deep tissue penetration. This mini‐review outlines the most recent advances in activatable organic PA probes for pH‐detection with respect to molecular design, response mechanisms, and their in vivo applications. The basic understanding of PA probes is clarified. The pH‐response mechanisms of the PA probes at the molecular level are particularly emphasized to elucidate the structural design strategies. Finally, the challenges and perspectives, mainly focusing on quantitative detection, are discussed. This review aims to pave the way for further exploration of responsive organic PA probes for in vivo pH‐detection.

Thrombosis occurs in both macrovasculature and microvasculature, causing various cardio-cerebral vascular diseases. The lack of effective and safe antithrombotic drugs leads to a public health crisis. Mounting evidence suggests that protein disulfide isomerase (PDI) plays a critical role in the initial stage of thrombus formation, motivating the research of the feasibility of PDI inhibitors as novel anti-thrombotics. Rutin, one of the most potent PDI inhibitors, was reported to suppress platelet aggregation and thrombosis in animal models, but further studies and clinical translation were restricted due to its low aqueous solubility and oral bioavailability. In this work, we fabricated rutin-loaded lipid-based nano-formulation (NanoR) and characterized their physical–chemical properties, release profiles, pharmacokinetic process, and pharmacodynamic function against thrombosis in macrovessels and microvessels. NanoR provided increased solubility and dissolution of rutin to achieve earlier Tmax and higher Cmax than the sodium salt of rutin (NaR) after oral gavage. Ex vivo studies demonstrated that NanoR significantly inhibited thrombin generation and clot formation in the plasma of mice. Importantly, such effect was reversed by exogenous recombinant PDI, demonstrating the specificity of the NanoR. In direct current-induced arterial thrombosis model and ferric chloride-induced microvascular thrombosis model, NanoR exhibited greatly enhanced antithrombotic activity compared with NaR. NanoR also showed good safety performance according to tail bleeding assay, global coagulation tests, and histological analysis. Overall, our current results indicated that NanoR offers a promising antithrombotic treatment with potential for clinical translation.

Background This study was performed to identify metabolites associated with incident acute coronary syndrome (ACS) and explore causality of the associations. Methods and Results We performed nontargeted metabolomics in a nested case‐control study in the Dongfeng‐Tongji cohort, including 500 incident ACS cases and 500 age‐ and sex‐matched controls. Three metabolites, including a novel one (aspartylphenylalanine), and 1,5‐anhydro‐d‐glucitol (1,5‐AG) and tetracosanoic acid, were identified as associated with ACS risk, among which aspartylphenylalanine is a degradation product of the gut‐brain peptide cholecystokinin‐8 rather than angiotensin by the angiotensin‐converting enzyme (odds ratio [OR] per SD increase [95% CI], 1.29 [1.13–1.48]; false discovery rate–adjusted P=0.025), 1,5‐AG is a marker of short‐term glycemic excursions (OR per SD increase [95% CI], 0.75 [0.64–to 0.87]; false discovery rate–adjusted P=0.025), and tetracosanoic acid is a very‐long‐chain saturated fatty acid (OR per SD increase [95% CI], 1.26 [1.10–1.45]; false discovery rate–adjusted P=0.091). Similar associations of 1,5‐AG (OR per SD increase [95% CI], 0.77 [0.61–0.97]) and tetracosanoic acid (OR per SD increase [95% CI], 1.32 [1.06–1.67]) with coronary artery disease risk were observed in a subsample from an independent cohort (152 and 96 incident cases, respectively). Associations of aspartylphenylalanine and tetracosanoic acid were independent of traditional cardiovascular risk factors (P‐trend=0.015 and 0.034, respectively). Furthermore, the association of aspartylphenylalanine was mediated by 13.92% from hypertension and 27.39% from dyslipidemia (P

In this work, we investigated the effects of different acceptors (IT−4F and PC71BM) on the charge dynamics in PM6-based solar cells. The correlation between different acceptors and the performance of organic solar cells was studied by atomic force microscope, steady-state absorption spectrum, transient absorption spectrum, and electrical measurements. Optical absorption exhibited that IT−4F has strong absorption in the near-infrared region for the active layer. Transient absorption measurements showed that different acceptors (IT−4F and PC71BM) had a significant influence on the behaviors of PM6 excitons and charge dynamics. That is, the exciton dissociation rate and delocalized polaron transport in the PM6:IT−4F active layer were significantly faster than that in the PM6:PC71BM active layer. The lifetime of localized polaron in the PM6:PC71BM active layer was longer than that in the PM6:IT−4F active layer. Conversely, the lifetime of delocalized polaron in the PM6:IT−4F active layer was longer than that in the PM6:PC71BM active layer. Electrical measurement analysis indicated that lower bimolecular recombination, higher charge transport, and charge collection ability were shown in the PM6:IT−4F device compared with the PM6:PC71BM device. Therefore, PM6:IT−4F solar cells achieved a higher power conversion efficiency (12.82%) than PM6:PC71BM solar cells (8.78%).

Brain-wide axonal projections of single neurons have been extensively reconstructed without any functional characterization. The authors present a method that allows for developing a precise one-to-one map of both projection patterns and functional features of single neurons in mice.

Abstract Background Early postoperative small bowel obstruction (EPSBO) is a common complication after colorectal cancer surgery. Few studies have specifically studied risk factors for early small bowel obstruction after right colectomy, especially in establishing predictive models. The purpose of the current study was to establish an effective nomogram to predict the incidence of EPSBO after right colectomy. Methods The current study retrospectively analyzed data from a total of 424 patients who underwent right colectomy in a local hospital from January 2014 to March 2021. A logistic regression model was used to identify potential risk factors for EPSBO after right colectomy. A nomogram was established by independent risk factors, and the prediction performance of the model was evaluated using an area under the receiver operating characteristic (ROC) curve and calibration chart. Results A total of 45 patients (10.6%) developed early small bowel obstruction after right colectomy. Male sex, emergency operation, history of abdominal surgery, open surgery, long operative time, anastomotic leakage, and preoperative albumin were closely related to EPSBO. Analysis of postoperative rehabilitation indices showed that EPSBO remarkably slowed the postoperative rehabilitation speed of patients. Multivariate logistic regression analysis showed that male sex, open surgery, operative time, and anastomotic leakage were independent risk factors (P < 0.05), and the operation time had the greatest impact on EPSBO. On the basis of multivariate logistic regression, a nomogram was constructed, which showed moderate accuracy in predicting EPSBO, with a C-statistic of 0.716. The calibration chart showed good consistency between the predicted probability and ideal probability. Conclusion The current study constructed a nomogram based on the clinical data of patients who underwent right colectomy, which had moderate predictability and could provide reference value for clinicians to evaluate the risk of EPSBO.

Telemetry data are the most important basis for ground operators to assess the status of satellites in orbit, and telemetry data-based anomaly detection has become a key tool to improve the reliability and safety of spacecrafts. Recent research on anomaly detection focuses on constructing a normal profile of telemetry data using deep learning methods. However, these methods cannot effectively capture the complex correlations between the various dimensions of telemetry data, and thus cannot accurately model the normal profile of telemetry data, resulting in poor anomaly detection performance. This paper presents CLPNM-AD, contrastive learning with prototype-based negative mixing for correlation anomaly detection. The CLPNM-AD framework first employs an augmentation process with random feature corruption to generate augmented samples. Following that, a consistency strategy is employed to capture the prototype of samples, and then prototype-based negative mixing contrastive learning is used to build a normal profile. Finally, a prototype-based anomaly score function is proposed for anomaly decision-making. Experimental results on public datasets and datasets from the actual scientific satellite mission show that CLPNM-AD outperforms the baseline methods, achieves up to 11.5% improvement based on the standard F1 score and is more robust against noise.

Abstract Background This study was undertaken to discover whether the vaginal microbe of women at childbearing age is different among groups defined by urogenital tract infections, childbearing history and menstrual cycle, respectively. Results This was a multiple case-control study of women at childbearing age who were assigned to case or control groups according to their states of urogenital tract infections. The participants were also grouped by childbearing history and menstrual cycle. Vaginal swabs were collected and stored at − 70 °C until assayed. The V3-V4 region of 16S rRNA gene was amplified using PCR and sequenced on the Illumina MiSeq platform. We tested the hypothesis of whether the relative abundance of microbial species in vaginal microbiota was varied with urogenital tract infections, childbearing history and menstrual cycle. The vaginal microbial richness (Alpha diversity measured by PD_whole tree) was decreased in normal women (without reproductive tract infections) than in those with bacterial vaginosis (BV), and decreased in pregnant women than in other groups of non-pregnancy. Similarly, women from groups of normal and in pregnancy had lower beta diversity on measure of unweighted_unifrac distance in comparison to those of infected and non-pregnant. The top 10 genus relative abundance, especially Lactobacillus, which was the most dominant genus with the relative abundance of 71.55% among all samples, did not differ significantly between groups of childbearing history and menstrual cycle analyzed by ANOVA and nonparametric kruskal_wallis. Lactobacillus iners and Lactobacillus helveticus have the most abundance, totally account for 97.92% relative abundance of genus Lactobacillus. We also found that a higher L.helveticus/L.iners ratio is more likely to present in normal women than in the infected and in pregnant than in non-pregnant, although these comparisons lack statistical significance. Conclusions The relative abundance of dominant bacterial taxa in vaginal microbial communities of women at childbearing age were not different among groups of childbearing history and menstrual cycle. Women from groups of in pregnancy and without reproductive tract infections had lower alpha and beta diversity. The composition of the main lactobacillus species may shift upon phases of a menstrual cycle and the status of reproductive tract infections.

X-ray diffraction technology (XRD) is one of the common means of mineral separation, and peak identification and comparison is a key step. The symmetric zero-area conversion method (SZAC) performs well in peak searching of spectral lines, but its wide application is limited by problems such as inaccurate identification results in specific scenes and dependence of parameter selection on spectral data. In this article, an improved symmetric zero-area conversion method (ISZAC) is proposed by combining the ideas of data fusion and passive anti-counterfeiting. The comparison method and flat peak screening were introduced, and the function group was designed to convert the spectral data after background deduction and intensity screening. The results were fused to obtain the peak address determination. Simulation and experimental results show that the improved method has higher accuracy and applicability. In addition, the method is easy to expand, and the conversion function group can be adjusted according to the spectral data characteristics to improve the recognition efficiency.

In this contribution, we studied the effect of fluorine substitution on photogenerated charge generation, transport, and recombination in polymer solar cells. Two conjugated polymer materials, PBDTTT-E (fluorine free) and PTB7 (one fluorine substitution), were compared thoroughly. Meanwhile, various characterization techniques, including atomic force microscopy, steady-state spectroscopy, transient absorption spectroscopy, spectroelectrochemistry, and electrical measurements, were employed to analyse the correlation between molecular structure and device performance. The results showed that the influence of fluorine substitution on both the exciton binding energy of the polymer and the carrier recombination dynamics in the ultrafast timescale on the polymer was weak. However, we found that the fluorine substitution could enhance the exciton lifetime in neat polymer film, and it also could increase the mobility of photogenerated charge. Moreover, it was found that the SOMO energy level distribution of the donor in a PTB7:PC71BM solar cell could facilitate hole transport from the donor/acceptor interface to the inner of the donor phase, showing a better advantage than the PBDTTT-E:PC71BM solar cell. Therefore, fluorine substitution played a critical role for high-efficiency polymer solar cells.

Chiroptical signals (generally very weak) play significant roles in chiral discrimination that bring great benefits in biochemistry, pharmacy, chemical, and so on. But, high-precise chiroptical detection is still a challenge. In this paper, a high-precise measurement of optical rotatory dispersion (ORD) based on weak value amplification (WVA) is presented. We proposed ORD detection method with parameter separation: by introducing complex coupling strength and dimensionless parameter “intensitiy contrast ratio” pointer, the ORD is only associated with the imaginary part of the weak value while circular dichroism (CD) is only associated with the real part. By designing a suitable WVA scheme, the ORD and CD can be measured separately. In the experiment, the reliability of the parameter separation method for ORD measurement is verified, and the precision reach the order of $10^{-6}$ rad. This method has a broad application prospect in biomedical sensing, medicine, chemical analysis and other fields.

COVID-19 greatly challenges the human health sector, and has resulted in a large amount of medical waste that poses various potential threats to the environment. In this study, we compiled relevant data released by official agencies and the media, and conducted data supplementation based on earlier studies to calculate the net value of medical waste produced in the Hubei Province due to COVID-19 with the help of a neural network model. Next, we reviewed the data related to the environmental impact of medical waste per unit and designed four scenarios to estimate the environmental impact of new medical waste generated during the pandemic. The results showed that a medical waste generation rate of 0.5 kg/bed/day due to COVID-19 resulted in a net increase of medical waste volume by about 3366.99 tons in the Hubei Province. In the four scenario assumptions, i.e., if the medical waste resulting from COVID-19 is completely incinerated, it will have a large impact on the air quality. If it is disposed by distillation sterilization, it will produce a large amount of wastewater and waste residue. Based on the results of the study, we propose three policy recommendations: strict control of medical wastewater discharge, reduction and transformation of the emitted acidic gases, and attention to the emission of metallic nickel in exhaust gas and chloride in soil. These policy recommendations provide a scientific basis for controlling medical waste pollution.

Promoting pro-environmental behavior is an effective means of reducing carbon emissions at the individual end, but the measurement of behavior has long been a problem for scholars. Especially in environmental psychology community, the complexity of social policies and habitat implies greater difficulty in measuring. Due to the limitations of traditional questionnaire, laboratory, and naturalistic observation methods, environmental psychologists need more realistic, accurate, and cost-effective ways to measure behavior. The rapid development of IoT technology lights up the hope for achieving this goal, and its large-scale popularization will bring great changes to the research community. This paper reviews the current methods and their limitations, proposes a framework for measuring behavior using IoT devices, and points out its future research directions.

Abstract A metal‐complex‐modified graphitic carbon nitride (g‐C3N4) bulk heterostructure is presented here as a promising alternative to high‐cost noble metals as artificial photocatalysts. Theoretical and experimental studies of the spectral and physicochemical properties of three structurally similar molecules Fo–D, Pt–D, and Pt–P confirm that the Pt(II) acetylide group effectively expands the electron delocalization and adjusts the molecular orbital levels to form a relatively narrow bandgap. Using these molecules, the donor–acceptor assemblies Fo–D@CN, Pt–D@CN, and Pt–P@CN are formed with g‐C3N4. Among these assemblies, the Pt(II) acetylide‐based composite materials Pt–D@CN and Pt–P@CN with bulk heterojunction morphologies and extremely low Pt weight ratios of 0.19% and 0.24%, respectively, exhibit the fastest charge transfer and best light‐harvesting efficiencies. Among the tested assemblies, 10 mg Pt–P@CN without any Pt metal additives exhibits a significantly improved photocatalytic H2 generation rate of 1.38 µmol h−1 under simulated sunlight irradiation (AM1.5G, filter), which is sixfold higher than that of the pristine g‐C3N4.

Citrus canker, induced by bacterial infection, seriously affects the growth and productivity of citrus around the world and has attracted strong research interest. The current treatment for this disease uses copper salts to inactivate the pathogenic bacteria: Xanthomonas citri subsp. citri (Xcc) strain. However, copper salts may have a negative impact on the environment or plant. In this work, we identify a chemical compound, 2,6-diiodo-1,3,5,7-tetramethyl-8-(P-benzoic acid)-4,4′-difluoroboradiazaindacene (DIBDP), to inactivate the pathogenic Xcc strain (29-1). DIBDP is activated by sunlight and generates reactive oxygen species to kill the bacteria. In order to overcome the degradation of DIBDP under sunlight, an adjuvant agent was identified to limit the photodegradation of DIBDP by forming a photosensitizer complex (PSC). This complex demonstrated significant antimicrobial activity to Xcc 29-1, which was 64-fold more potent than the copper biocides. The antimicrobial efficacy of PSC on citrus leaves infected by Xcc 29-1 also was much stronger than copper agent and, at the same time, the PSC was safe to the host exposed to sunlight. Thus, this PSC is a promising antibacterial agent to control citrus canker disease.

Flexible piezoelectric tactile sensor with transverse planar electrodes based on hydrothermally grown ZnO nanorods (ZnO NRs) was presented by using polydimethylsiloxane (PDMS) as flexible substrate and packaging material. The effects of the content of gold nanoparticles (AuNPs) added into the precursor solution on the structural morphology of ZnO NRs and on the piezoelectric properties of the ZnO NRs tactile sensor were investigated. Tactile sensors show a linear piezoelectric response in the pressure range of 0–1 N, and the sensor for the precursor solution with AuNPs of 100 μ l shows a high sensitivity of 1.42 V N ^−1 due to the large aspect ratio of the ZnO NRs, indicating that a small amount of AuNPs addition can optimize the structural morphology of ZnO NRs and thus improve the piezoelectric response of the sensor. Meanwhile, the sensor is employed to monitor human information in real-time such as bending/stretching motion of finger and distinguish various objects.

Abstract To improve the corrosion resistance and wear resistance of electroless nickel-phosphorus (Ni-P) coating on magnesium (Mg) alloy. Ni-P-Al2O3 coatings were produced on Mg alloy from a composite plating bath. The optimum Al2O3 concentration was determined by the properties of plating bath and coatings. Morphology growth evolution of Ni-P-Al2O3 composite coatings at different times was observed by using a scanning electronic microscope (SEM). The results show that nano-Al2O3 particles may slow down the replacement reaction of Mg and Ni2+ in the early stage of the deposition process, but it has almost no effect on the rate of Ni-P auto-catalytic reduction process. The anti-corrosion and micro-hardness tests of coatings reveal that the Ni-P-Al2O3 composite coatings exhibit better performance compared with Ni-P coating owing to more appropriate crystal plane spacing and grain size of Ni-P-Al2O3 coatings. Thermal shock test indicates that the Al2O3 particles have no effect on the adhesion of coatings. In addition, the service life of composite plating bath is 4.2 metal turnover, suggesting it has potential application in the field of magnesium alloy.

Fine morphological reconstruction of individual neurons across the entire brain is essential for mapping brain circuits. Inference of presynaptic axonal boutons, as a key part of single-neuron fine reconstruction, is critical for interpreting the patterns of neural circuit wiring schemes. However, automated bouton identification remains challenging for current neuron reconstruction tools, as they focus mainly on neurite skeleton drawing and have difficulties accurately quantifying bouton morphology. Here, we developed an automated method for recognizing single-neuron axonal boutons in whole-brain fluorescence microscopy datasets. The method is based on deep convolutional neural networks and density-peak clustering. High-dimensional feature representations of bouton morphology can be learned adaptively through convolutional networks and used for bouton recognition and subtype classification. We demonstrate that the approach is effective for detecting single-neuron boutons at the brain-wide scale for both long-range pyramidal projection neurons and local interneurons.

Meteor radar data collected over Langfang, China (39.4° N, 116.7° E) were used to estimate the momentum flux of short-period (less than 2 h) gravity waves (GWs) in the mesosphere and lower thermosphere (MLT), using the Hocking (2005) analysis technique. Seasonal variations in GW momentum flux exhibited annual oscillation (AO), semiannual oscillation (SAO), and quasi-4-month oscillation. Quantitative estimations of GW forcing toward the mean zonal flow were provided using the determined GW momentum flux. The mean flow acceleration estimated from the divergence of this flux was compared with the observed acceleration of zonal winds displaying SAO and quasi-4-month oscillations. These comparisons were used to analyze the contribution of zonal momentum fluxes of SAO and quasi-4-month oscillations to zonal winds. The estimated acceleration from high-frequency GWs was in the same direction as the observed acceleration of zonal winds for quasi-4-month oscillation winds, with GWs contributing more than 69%. The estimated acceleration due to Coriolis forces to the zonal wind was studied; the findings were opposite to the estimated acceleration of high-frequency GWs for quasi-4-month oscillation winds. The significance of this study lies in estimating and quantifying the contribution of the GW momentum fluxes to zonal winds with quasi-4-month periods over mid-latitude regions for the first time.

The Forestry Reclamation Approach uses uncompacted, mounded spoils to reforest mined-land and has been successful in hardwood forests in the Appalachian region. A surface coalmine reclamation site in the Pacific Northwest was used to compare the site’s standard reclamation approach (Reference) with a modified version of the Forestry Reclamation Approach (FRA) along with a modified FRA treatment that also incorporated an amendment of bottom ash from the coal burning power plant on-site (FRA + Ash). Survival and growth were followed for three growing seasons in bareroot and container Douglas-fir seedlings. Soil characteristics and understory cover were also assessed. Considerable variation in microsite characteristics was observed in the study area. Container seedlings did not improve survival compared to bareroot seedlings. In the soil reclamation treatments, seedling survival was significantly higher in FRA + Ash treatments compared to FRA and Reference treatments at the end of the second growing season. Survival declined in each year of the study, but the order of treatment effectiveness did not change. Relativized growth increment was significantly higher in the FRA treatment compared to both the Reference and FRA + Ash treatments during the third growing season. Understory cover was established after three years, but varied substantially across the study area.

Microbial decomposition of soil organic carbon (SOC) in thawing Arctic permafrost is important in determining greenhouse gas feedbacks of tundra ecosystems to climate. However, the changes in microbial community structure during SOC decomposition are poorly known. Here we examine these changes using frozen soils from Barrow, Alaska, USA, in anoxic microcosm incubation at −2 and 8°C for 122 days. The functional gene array GeoChip was used to determine microbial community structure and the functional genes associated with SOC degradation, methanogenesis, and Fe(III) reduction. Results show that soil incubation after 122 days at 8°C significantly decreased functional gene abundance (P < 0.05) associated with SOC degradation, fermentation, methanogenesis, and iron cycling, particularly in organic-rich soil. These observations correspond well with decreases in labile SOC content (e.g., reducing sugar and ethanol), methane and CO2 production, and Fe(III) reduction. In contrast, the community functional structure was largely unchanged in the −2°C incubation. Soil type (i.e., organic vs. mineral) and the availability of labile SOC were among the most significant factors impacting microbial community structure. These results demonstrate the important roles of microbial community in SOC degradation and support previous findings that SOC in organic-rich Arctic tundra is highly vulnerable to microbial degradation under warming.

Gambogic acid (GA) is a natural compound derived from Chinese herbs that has been approved by the Chinese Food and Drug Administration for clinical trials in cancer patients; however, its molecular targets have not been thoroughly studied. Here, we report that GA inhibits tumor proteasome activity, with potency comparable to bortezomib but much less toxicity. First, GA acts as a prodrug and only gains proteasome-inhibitory function after being metabolized by intracellular CYP2E1. Second, GA-induced proteasome inhibition is a prerequisite for its cytotoxicity and anticancer effect without off-targets. Finally, because expression of the CYP2E1 gene is very high in tumor tissues but low in many normal tissues, GA could therefore produce tissue-specific proteasome inhibition and tumor-specific toxicity, with clinical significance for designing novel strategies for cancer treatment.

In view of the SVM classification for the imbalanced sand-dust storm data sets, this paper proposes a hybrid self-adaptive sampling method named SRU-AIBSMOTE algorithm. This method can adaptively adjust neighboring selection strategy based on the internal distribution of sample sets. It produces virtual minority class instances through randomized interpolation in the spherical space which consists of minority class instances and their neighbors. The random undersampling is also applied to undersample the majority class instances for removal of redundant data in the sample sets. The comparative experimental results on the real data sets from Yanchi and Tongxin districts in Ningxia of China show that the SRU-AIBSMOTE method can obtain better classification performance than some traditional classification methods.

The impulsive complex-valued neural networks with three kinds of time delays including leakage delay, discrete delay, and distributed delay are considered. Based on the homeomorphism mapping principle of complex domain, a sufficient condition for the existence and uniqueness of the equilibrium point of the addressed complex-valued neural networks is proposed in terms of linear matrix inequality (LMI). By constructing appropriate Lyapunov-Krasovskii functionals, and employing the free weighting matrix method, several delay-dependent criteria for checking the global μ-stability of the complex-valued neural networks are established in LMIs. As direct applications of these results, several criteria on the exponential stability, power-stability, and log-stability are obtained. Two examples with simulations are provided to demonstrate the effectiveness of the proposed criteria.

In recent years, theoretical and practical research topics on networked control systems (NCSs) have gained an increasing interest from many researchers in a variety of disciplines owing to the extensive applications of NCSs in practice. In particular, an urgent need has arisen to understand the effects of communication processes on system performances. Sampling and protocol are two fundamental aspects of a communication process which have attracted a great deal of research attention. Most research focus has been on the analysis and control of dynamical behaviors under certain sampling procedures and communication protocols. In this paper, we aim to survey some recent advances on the analysis and synthesis issues of NCSs with different sampling procedures (time- and event-driven sampling) and protocols (static and dynamic protocols). First, these sampling procedures and protocols are introduced in detail according to their engineering backgrounds as well as dynamic natures. Then, the developments of the stabilization, control, and filtering problems are systematically reviewed and discussed in great detail. Finally, we conclude the paper by outlining future research challenges for analysis and synthesis problems of NCSs with different communication processes.

This paper deals with the fault detection problem for a class of discrete-time wireless networked control systems described by switching topology with uncertainties and disturbances. System states of each individual node are affected not only by its own measurements, but also by other nodes’ measurements according to a certain network topology. As the topology of system can be switched in a stochastic way, we aim to design H∞ fault detection observers for nodes in the dynamic time-delay systems. By using the Lyapunov method and stochastic analysis techniques, sufficient conditions are acquired to guarantee the existence of the filters satisfying the H∞ performance constraint, and observer gains are derived by solving linear matrix inequalities. Finally, an illustrated example is provided to verify the effectiveness of the theoretical results.

Nowadays, the real-world systems are usually subject to various complexities such as parameter uncertainties, time-delays, and nonlinear disturbances. For networked systems, especially large-scale systems such as multiagent systems and systems over sensor networks, the complexities are inevitably enhanced in terms of their degrees or intensities because of the usage of the communication networks. Therefore, it would be interesting to (1) examine how this kind of network-enhanced complexities affects the control or filtering performance; and (2) develop some suitable approaches for controller/filter design problems. In this paper, we aim to survey some recent advances on the performance analysis and synthesis with three sorts of fashionable network-enhanced complexities, namely, fading measurements, event-triggered mechanisms, and attack behaviors of adversaries. First, these three kinds of complexities are introduced in detail according to their engineering backgrounds, dynamical characteristic, and modelling techniques. Then, the developments of the performance analysis and synthesis issues for various networked systems are systematically reviewed. Furthermore, some challenges are illustrated by using a thorough literature review and some possible future research directions are highlighted.

In this paper, we consider the robust H∞ control problem for a class of discrete time-delay stochastic systems with randomly occurring nonlinearities. The parameter uncertainties enter all the system matrices; the stochastic disturbances are both state and control dependent, and the randomly occurring nonlinearities obey the sector boundedness conditions. The purpose of the problem addressed is to design a state feedback controller such that, for all admissible uncertainties, nonlinearities, and time delays, the closed-loop system is robustly asymptotically stable in the mean square, and a prescribed H∞ disturbance rejection attenuation level is also guaranteed. By using the Lyapunov stability theory and stochastic analysis tools, a linear matrix inequality (LMI) approach is developed to derive sufficient conditions ensuring the existence of the desired controllers, where the conditions are dependent on the lower and upper bounds of the time-varying delays. The explicit parameterization of the desired controller gains is also given. Finally, a numerical example is exploited to show the usefulness of the results obtained.

A class of fractional-order BAM neural networks with delays in the leakage terms is considered. By using inequality technique and analysis method, several delay-dependent sufficient conditions are established to ensure the uniform stability of such networks. Moreover, the sufficient conditions guaranteeing the existence, uniqueness, and stability of the equilibrium point are also obtained. In addition, three simulation examples are given to demonstrate the effectiveness of the obtained results.

State estimation problem is considered for a kind of wireless network control system with stochastic uncertainty and time delay. A sliding mode observer is designed for the system under the situation that no missing measurement occurs and system uncertainty happens in a stochastic way. The observer designed for the system can guarantee the system states will be driven onto the sliding surface under control law, and the sliding motion of system states on sliding surface will be stable. By constructing proper Lyapunov-Krasovskii functional, sufficient conditions are acquired via linear matrix inequality. Finally, simulation result is employed to show the effectiveness of the proposed method.

This paper is concerned with the leader-following consensus problem in mean-square for a class of discrete-time multiagent systems. The multiagent systems under consideration are the directed and contain arbitrary discrete time-delays. The communication links are assumed to be time-varying and stochastic. It is also assumed that some agents in the network are well informed and act as leaders, and the others are followers. By introducing novel Lyapunov functionals and employing some new analytical techniques, sufficient conditions are derived to guarantee the leader-following consensus in mean-square for the concerned multiagent systems, so that all the agents are steered to an anticipated state target. A numerical example is presented to illustrate the main results.

The guaranteed cost control problem is investigated for a class of nonlinear discrete-time systems with Markovian jumping parameters and mixed time delays. The mixed time delays involved consist of both the mode-dependent discrete delay and the distributed delay with mode-dependent lower bound. The associated cost function is of a quadratic summation form over the infinite horizon. The nonlinear functions are assumed to satisfy sector-bounded conditions. By introducing new Lyapunov-Krasovskii functionals and developing some new analysis techniques, sufficient conditions for the existence of guaranteed cost controllers are derived with respect to the given cost function. Moreover, a convex optimization approach is applied to search for the optimal guaranteed cost controller by minimizing the guaranteed cost of the closed-loop system. Numerical simulation is further carried out to demonstrate the effectiveness of the proposed methods.