Acoustic resonance is an important factor that contributes to aeroengine compressor failure. In this study, a plane cascade of compressor blades was designed to reproduce acoustic resonance via a low-speed wind tunnel test. A high-frequency hot-wire, microphone and strain gauge were used to synchronously measure the fluid, acoustic and structural parameters. We analysed the variation in the amplitude and frequency of the multi-field parameters with increasing mean flow velocity and explored the multi-field interaction mechanism that induces the acoustic resonance of the plane cascade. The plane cascade effectively reproduced the acoustic resonance phenomenon. The first-order acoustic-mode frequency of the plane cascade flow duct, second-order torsional vibration mode frequency of the blade and shedding mode frequency of the tip clearance leakage vortex were equal under acoustic resonance. The fluid, acoustic and structural fields showed a strong interaction effect, achieving the maximum blade vibration amplitude and causing fatigue cracks of torsional vibration at the blade root. The frequency lock-in region of the compressor plane cascade was divided into an ‘acoustic–structure’ interaction region, a ‘fluid–acoustic–structure’ interaction region and a first-order acoustic-mode dominant region with increasing mean flow velocity, which demonstrates an interesting phenomenon in which the fluid–acoustic–structure modes compete: acoustic mode > blade vibration mode > vortex shedding mode. The results demonstrate a unique approach to the study of acoustic resonance that provides insight into the acoustic resonance mechanism in a cascade of compressor blades.

Thanks to its real-time computation efficiency, deep reinforcement learning (DRL) has been widely applied in motion planning for mobile robots. In DRL-based methods, a DRL model computes an action for a robot based on the states of its surrounding obstacles, including other robots that may communicate with it. These methods always assume that the environment is attack-free and the obtained obstacles’ states are reliable. However, in the real world, a robot may suffer from obstacle localization attacks (OLAs), such as sensor attacks, communication attacks, and remote-control attacks, which cause the robot to retrieve inaccurate positions of the surrounding obstacles. In this paper, we propose a robust motion planning method ObsGAN-DRL, integrating a generative adversarial network (GAN) into DRL models to mitigate OLAs in the environment. First, ObsGAN-DRL learns a generator based on the GAN model to compute the approximation of obstacles’ accurate positions in benign and attack scenarios. Therefore, no detectors are required for ObsGAN-DRL. Second, by using the approximation positions of the surrounding obstacles, ObsGAN-DRL can leverage the state-of-the-art DRL methods to compute collision-free motion commands (e.g., velocity) efficiently. Comprehensive experiments show that ObsGAN-DRL can mitigate OLAs effectively and guarantee safety. We also demonstrate the generalization of ObsGAN-DRL.

Major depressive disorder (MDD) is characterized by deficient reward functions in the brain. However, existing findings on functional alterations during reward anticipation, reward processing, and learning among MDD patients are inconsistent, and it was unclear whether a common reward system implicated in multiple reward functions is altered in MDD. Here we meta-analyzed 18 past studies that compared brain reward functions between adult MDD patients (N = 477, mean age = 26.50 years, female = 59.40%) and healthy controls (N = 506, mean age = 28.11 years, females = 55.58%), and particularly examined group differences across multiple reward functions. Jack-knife sensitivity and subgroup meta-analyses were conducted to test robustness of findings across patient comorbidity, task paradigm, and reward nature. Meta-regression analyses assessed the moderating effect of patient symptom severity and anhedonia scores. We found during reward anticipation, MDD patients showed lower activities in the lateral prefrontal-thalamus circuitry. During reward processing, patients displayed reduced activities in the right striatum and prefrontal cortex, but increased activities in the left temporal cortex. During reward learning, patients showed reduced activity in the lateral prefrontal–thalamic–striatal circuitry and the right parahippocampal–occipital circuitry but higher activities in bilateral cerebellum and the left visual cortex. MDD patients showed decreased activity in the right thalamus during both reward anticipation and learning, and in the right caudate during both reward processing and learning. Larger functional changes in MDD were observed among patients with more severe symptoms and higher anhedonia levels. The thalamic-striatal circuitry functional alterations could be the key neural mechanism underlying MDD patients overarching reward function deficiencies.

Grass seeds play a critical and fundamental role in grass breeding and production. Elymus sibiricus L. is a widespread Poaceae forage grass in northern Eurasia which is used for ecological restoration and forage production. Sucrose is the main source of substrate and energy required for starch synthesis in the seeds, so the hydrolysis of sucrose determines and influences starch synthesis and filling in the seeds, especially Poaceae. However, the process behind carbohydrate metabolism during E. sibiricus seed development remains unclear. This study addresses a significant gap in our understanding of the carbohydrate metabolism during seed development in E. sibiricus by employing full-length transcriptome sequencing across five developmental stages for the first time. Full-length transcriptome sequencing was performed on E. sibiricus seeds at five developmental stages (S5, S9, S15, S20, S25) to get better molecular insights. We identified 13,205 differentially expressed genes, with 7,471 up-regulated and 5,734 down-regulated. Through KEGG enrichment analysis, genes were enriched in ‘starch and sucrose metabolism’, ‘photosynthetic-related’ and ‘hormone signal transduction’ pathways. Gene ontology enrichment analysis showed that genes were enriched in the ‘beta-amylase activity’ term of molecular functions. In addition, top 21 transcription factor families were identified as involved in seed development. The homologous genes of ABSCISIC ACID-INSENSITIVE 3 (ABI3), NUCLEAR FACTOR-YB1 (NF-YB1), STARCH SYNTHASE I (SSI) were identified as candidate genes of seed development in E. sibiricus. Combined with physiological index, transcriptome analyses, weighted gene co-expression network analysis and real-time quantitative PCR, the mechanism of starch and sucrose content of seed development was revealed and ten hub genes were identified. Overall, this study provides the molecular bases to understand seed development and starch and sucrose metabolism at the different seed developmental stages in E. sibiricus.

By the technique of augmented truncations, we obtain the perturbation bounds on the distance of the finite-time state distributions of two continuous-time Markov chains (CTMCs) in a type of weaker norm than the V-norm. We derive the estimates for strongly and exponentially ergodic CTMCs. In particular, we apply these results to get the bounds for CTMCs satisfying Doeblin or stochastically monotone conditions. Some examples are presented to illustrate the limitation of the V-norm in perturbation analysis and to show the quality of the weak norm.

Intracytoplasmic sperm injection (ICSI) is a technique that directly injects a single sperm into the cytoplasm of mature oocytes. Here, we explored the safety of single-sperm cryopreservation applied in ICSI. This retrospective study enrolled 186 couples undergoing ICSI-assisted pregnancy. Subjects were allocated to the fresh sperm (group A)/single-sperm cryopreservation (group B) groups based on sperm type, with their clinical baseline/pathological data documented. We used ICSI-compliant sperm for subsequent in vitro fertilization and followed up on all subjects. The recovery rate/cryosurvival rate/sperm motility of both groups, the pregnancy/outcome of women receiving embryo transfer, and the delivery mode/neonatal-related information of women with successful deliveries were recorded. The clinical pregnancy rate, cumulative clinical pregnancy rate, abortion rate, ectopic pregnancy rate, premature delivery rate, live birth delivery rate, neonatal birth defect rate, and average birth weight were analyzed. The two groups showed no significant differences in age, body mass index, ovulation induction regimen, sex hormone [anti-Müllerian hormone (AMH)/follicle-stimulating hormone (FSH)/luteinizing hormone (LH)] levels, or oocyte retrieval cycles. The sperm recovery rate (51.72%-100.00%) and resuscitation rate (62.09% ± 16.67%) in group B were higher; the sperm motility in the two groups demonstrated no significant difference and met the ICSI requirements. Group B exhibited an increased fertilization rate, decreased abortion rate, and increased safety versus group A. Compared with fresh sperm, the application of single-sperm cryopreservation in ICSI sensibly improved the fertilization rate and reduced the abortion rate, showing higher safety.

Thriving at work is closely related to the way employees are embedded in their social contexts, such as the structure of their communication relations with coworkers. In previous research, communication relations have been found to negatively relate to thriving at work. However, social network theory suggests that communication relations are beneficial in obtaining resources in the workplace, which might increase thriving at work. To reconcile the seemingly conflicting mechanisms, we draw on social network theory to unpack the mechanisms underlying communication relations by considering the instrumental and expressive roles. Using a structural equation model, we investigate the indirect effects of communication networks on thriving at work via advice-seeking networks (instrumental) and friendship networks (expressive). Our findings indicate communication relations are negatively related to thriving at work via advice-seeking relations, but are positively related to thriving at work via friendship relations.

Mammary gland health plays a key role in maintaining lactation persistency. As a well-known factor involved in physiological processes, the role of oxygen levels in bovine mammary health and lactation persistency remains to be investigated. The present study aimed at investigating the potential regulatory role of hypoxia in the mammary gland of dairy cows with different lactation persistency. Sixty-one Holstein dairy cows were selected for a 180-day experiment at approximately 88 days in milk (DIM). Plasma, milk and mammary tissue samples from 61 cattle were collected on experimental days 0, 90 and 180 (corresponding to 88, 178 and 268 DIM), respectively. Of the 61 cows, 12 cows with high lactation persistency (HP) and 12 with low lactation persistency (LP) were selected for the current study. No difference was observed in milk yield between two groups on d 0 (Pd 0 = 0.67), whereas differences emerged between animals with different lactation persistency at d 105 (Pd 105 = 0.03) until d 180 (Pd 180 < 0.01). The level of mammary apoptosis was significantly higher in the LP group than in the HP cows (Ppersistency < 0.01). In the oxygen-related variables, plasma concentration of hypoxia-inducible factor 1α (HIF-1α) was higher in the LP cows than in the HP group (Ppersistency < 0.01), especially on d 0 (Pd 0 < 0.01). Compared with HP cows, LP cows had a higher malonaldehyde (Pd 180 = 0.01) and a lower activity of inducible nitric oxide synthase (Pd 180 = 0.01) on d 180, suggesting a possible oxygen alteration between cows with different lactation persistency. RNA-sequencing analysis of the mammary gland on d 0 revealed that HIF-1 associated molecules may play a role in driving mammary gland apoptosis in dairy cows. A lower lactation persistency of dairy cows may be resulted from the altered HIF-1α in the mammary gland.

This paper proposes a design method for designing a wideband filtering power amplifier (PA) based on terminated coupled line structure (TCLS). This method generates four transmission zeros and three transmission poles by loading stepped impedance resonator and short-circuit stubs on the four ports of TCLS, which greatly optimizes the in-band return loss and stopband suppression of the output matching network. In addition, the effective suppression of the second harmonic also increases the efficiency of the PA. In order to verify the effectiveness and superiority of this design method, a wideband bandpass filtering PA is designed and manufactured in 2.9–3.7 GHz. Measurement results show that the saturated output power is from 40.1 dBm to 41.2 dBm, the drain efficiency is greater than 60.3%, and the gain is 10–11.2 dB.

Long-term time series of annual glacier mass balance is important for revealing a glacier's response to regional climate variations. However, for the Tibetan Plateau, time series of annual glacier mass balance with more than 10 consecutive years remains scarce due to the inaccessibility and harsh climate conditions. In this study, we established an albedo-based model to reconstruct annual glacier mass balance for 2000–20 over the Dongkemadi Glacier, based on multitemporal geodetic estimates and annual minimum glacier-wide mean surface albedos. Geodetic glacier mass-balance estimates for 2000–12, 2012–14 and 2014–18 were obtained by comparing glacier surface topographic data. Minimum surface albedos were obtained from the moderate-resolution imaging spectroradiometer daily snow albedo products for 2000–20. The estimated results are supported by the field measurements of annual glacier mass balance. During the early 2000s, we detected a relatively balanced state of glacier mass change, whereas a pronounced mass loss of more than −0.5 m w.e. was found for most years in the 2010s. By analyzing the regional climate variations with the ERA5-Land monthly averaged data, we found that the accelerated glacier mass loss can be attributed to both decreased annual snowfall and increased summer air temperature.

On a global scale, renal cell carcinoma (RCC) is the second most common form of cancer and the 10th leading cause of cancer-related deaths. There are about 70% of cases of RCC that are clear cell renal cell carcinomas (ccRCCs). This study explores possible targets for immune therapy in patients with RCC. In the recent years, immunotherapy has been applied to RCC patients. In order to identify genes that are closely associated with immune cells, a weighted gene coexpression network analysis (WGCNA) was conducted. A close association was found between genes involved in MEred and M0 macrophages, M1 macrophages, and M2 macrophages. A prognostic prediction model is subsequently developed by incorporating the OS and the expression level of key genes from the RCC cohort into a univariate COX regression analysis, a multivariate COX regression analysis, and a combined COX regression analysis. We finally discovered that 6 genes are closely associated with the prognosis of RCC patients, including SLC16A12, SLC2A9, IGF2BP2, EMX2, ANK3, and METTL7A. The survival analysis proved the prognostic prediction value of the model. The 1-year, 3-year, and 5-year AUC of ROC curves are 0.759, 0.723, and 0.733, respectively. For clinical ROC curves, the AUC score for risk score, stage, grade, and T stage is 0.759, 0.824, 0722, and 0.736, respectively. The nomogram was constructed for better prognosis prediction of RCC patients. In addition, GSVA and GO enrichment analysis was performed to explore the potential pathways that are closely associated with genes involved in the prognostic prediction model. Accordingly, our study demonstrates that immune cells play a crucial role in RCC infiltration. The development of a prognostic prediction model is a potential new prognostic biomarker and potential immunotherapy target for tumors.

Osteoarthritis (OA) is a chronic musculoskeletal disease affecting approximately 500 million people worldwide. Globally, OA is one of the most common and leading causes of disability. Several genetic factors are involved in OA, including inherited genes, genetic susceptibility, and genetic predisposition. As the pathogenesis of OA is unknown, there are almost no effective treatments available to prevent the onset or progression of the disease. In recent years, many researchers focused on bioinformatics analysis to explore new biomarkers for the diagnosis, treatment, and prognosis of human diseases. In this work, we obtain the traditional RNA sequencing data of OA patients from the GEO database. By performing the differentially expressed analysis, we successfully obtain the genes that are closely associated with the OA. In addition, the Venn diagram was applied to evaluate the genes that are involved in OA and immune-related genes. The protein-protein interaction analysis was further conducted to explore the hub genes. The single-cell RNA sequencing analysis was used to evaluate the expression distribution of the MMP, VEGFA, SPI1, and IRF8 in synovial tissues of patients with osteoarthritis. Finally, the GSVA enrichment analysis discovered the potential pathways involved in OA patients. Our analysis provides a new direction for the exploration of the process of OA patients. In addition, VEGFA may be considered a promising biomarker in OA.

Pancreatic adenocarcinoma (PAAD) has been a huge challenge to public health due to its increasing incidence, frequent early metastasis, and poor outcome. The molecular basis of tumorigenesis and metastasis in PAAD is largely unclear. Here, we identified a novel tumor-suppressor long noncoding RNA (lncRNA) MBNL1-AS1, in PAAD and revealed its downstream mechanism. Quantitative real-time PCR (qRT-PCR) data showed that MBNL1-AS1 expression was significantly downregulated in PAAD tissues and cells, which was closely associated with metastasis and poor prognosis. Cell counting kit-8 (CCK-8) assay, transwell assay, and western blot verified that overexpression of MBNL1-AS1 suppressed cell proliferation, migration, and epithelial mesenchymal transformation (EMT) behavior in PAAD cells. By using a dual luciferase reporter gene system, we confirmed that miR-301b-3p was a direct target of MBNL1-AS1. Further mechanismic study revealed that upregulation of miR-301b-3p abolished the inhibitory effect of MBNL1-AS1 overexpression on cell proliferation, tumorigenesis, migration and EMT. Our results demonstrate that MBNL1-AS1 plays a tumor-suppressive role in PAAD mainly by downregulating miR-301b-3p, providing a novel therapeutic target for PAAD.

Objective. The aim of the study is to investigate the potential role of keratoconus (KC) in the diagnosis of keratoconus (KC). Methods. GSE151631 and GSE77938 were downloaded from the comprehensive gene expression database (GEO). By using the random forest model (RF), support vector machine model (SVM), and generalized linear model (GLM), important immune-related genes were identified as biomarkers for KC diagnosis. Results. Through the LASSO, RFE, and RF algorithms and comparing the three sets of DEGs, a total of 8 overlapping DEGs were obtained. We took 8 DEGs as the final optimal combination of DEGs: AREG, BBC3, DUSP2, map3k8, Smad7, CDKN1A, JUN, and LIF. Conclusion. Abnormal cell proliferation, apoptosis, and autophagy defects are related to KC, which may be the etiology and potential target of KC.

Objective. Osteomyelitis (OM) is one of the most risky and challenging diseases. Emerging evidence indicates OM is a risk factor for increasing incidence of venous thromboembolism (VTE) development. However, the mechanisms have not been intensively investigated. Methods. The OM-related dataset GSE30119 and VTE-related datasets GSE19151 and GSE48000 were downloaded from the Gene Expression Omnibus (GEO) database and analyzed to identify the differentially expressed genes (DEGs) (OMGs1 and VTEGs1, respectively). Functional enrichment analyses of Gene Ontology (GO) terms were performed. VTEGs2 and OMGs2 sharing the common GO biological process (GO-BP) ontology between OMGs1 and VTEGs1 were detected. The TRRUST database was used to identify the upstream transcription factors (TFs) that regulate VTEGs2 and OMGs2. The protein-protein interaction (PPI) network between VTEGs2 and OMGs2 was constructed using the Search Tool for the Retrieval of Interacting Genes (STRING) database and then visualized in Cytoscape. Topological properties of the PPI network were calculated by NetworkAnalyzer. The Molecular Complex Detection (MCODE) plugin was utilized to perform module analysis and choose the hub modules of the PPI network. Results. A total of 587 OMGs1 and 382 VTEGs1 were identified from the related dataset, respectively. GO-BP terms of OMGs1 and shared DGEs1 were mainly enriched in the neutrophil-related immune response process, and the shared GO-BP terms of OMGs1 and VTEGs1 seemed to be focused on cell activation, immune, defense, and inflammatory response to stress or biotic stimulus. 230 VTEGs2, 333 OMGs2, and 13 shared DEGs2 were detected. 3 TF-target gene pairs (SP1-LSP1, SPI1-FCGR1A, and STAT1-FCGR1A) were identified. The PPI network contained 1611 interactions among 467 nodes. The top 10 hub proteins were TP53, IL4, MPO, ELANE, FOS, CD86, HP, SOCS3, ICAM1, and SNRPG. Several core nodes (such as MPO, ELANE, and CAMP) were essential components of the neutrophil extracellular traps (NETs) network. Conclusion. This is the first data-mining study to explore shared signatures between OM and VTE by the integrated bioinformatic approach, which can help uncover potential biomarkers and therapeutic targets of OM-related VTE.

Ovarian metastasis of gastric cancer indicates that the disease has reached the late stage and the opportunity for radical surgery is restricted. However, the clinical characteristics and prognosis of patients with gastric cancer ovarian metastasis (GCOM) remain to be illustrated. Here, we retrieved the information of 780 GCOM cases from the Surveillance, Epidemiology, and End Results (SEERs) database and analyzed their clinicopathological characteristics as well as their survival. According to our data, most GCOM patients showed poor pathological differentiation, advanced T and N stages. The prognostic factors include patients’ age, tumor size, surgical resection, and chemotherapy treatment. Of note, the marriage status was also identified as an independent prognostic factor. Besides the identification of prognostic factors, we established nomograms to help predict the overall survival and cancer-specific survival of GCOM, respectively.

Traditionally, land subsidence resulting from groundwater over-pumping has often been described by the theory of consolidation. The mechanism of land subsidence due to the dehydration of clay minerals has not been well addressed. Therefore, this study develops a smectite dehydration model to describe the effect of the release of water from the smectite interlayer upon land subsidence. Using a thermodynamic solid-solution model and laboratory studies of clay-water systems, a complete description of the dehydration relationships among the swelling pressure, basal spacing and mw/mc in a Na-smectite water system at 25°C under variable pressure conditions was derived. Accordingly, the evaluation model of the ‘hydration state of smectite’, and the ‘solid-solution model of smectite dehydration’ were formulated rigorously. These two models were applied to quantify the effects of smectite dehydration on the accumulated land subsidence in the Yun Lin offshore industrial infrastructure complex and in the Tai-Shi area. The result reveals that smectite dehydration is of importance in assessing and predicting land subsidence in a shallow sedimentary basin.