Search

The existence of factor and fractional factor in network graph in various settings has raised much attention from both mathematicians and computer scientists. It implies the availability of data transmission and network segmentation in certain special settings. In our paper, we consider P ≥ 2 -factor and P ≥ 3 -factor which are two special cases of general H -factor. Specifically, we study the existence of these two kinds of path factor when some subgraphs are forbidden, and several conclusions on the factor-deleted graph, factor critical-covered graph, and factor uniform graph are given with regards to network parameters. Furthermore, we show that these bounds are best in some sense.

Intestinal barrier dysfunction is associated with the occurrence and development of sepsis. Further, aerobic glycolysis plays an essential role in inflammation and cell death. This study is aimed at investigating the protective effect and mechanism of PFKFB3 inhibition on intestinal barrier dysfunction in sepsis mice. Sepsis mouse models were established by cecal ligation and puncture (CLP) in wild-type mice and Gsdmd-/- mice. The results showed that the expression of 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (PFKFB3) in the small intestines was significantly upregulated in sepsis. 3-(3-Pyridinyl)-1-(4-pyridinyl)-2-propen-1-one (3PO), the specific inhibitor of PFKFB3, and Gsdmd gene knockout significantly inhibited the inflammatory response and cell death caused by sepsis, thus alleviating intestinal damage and barrier dysfunction. 3PO was also shown to significantly inhibit oxidative stress and NLRP3/caspase-1/GSDMD-dependent cell pyroptosis in the small intestines. The in vitro studies revealed that 3PO reduced NLRP3/caspase-1/GSDMD-dependent cell pyroptosis by inhibiting ROS. Taken together, our results suggest that PFKFB3 is involved in inflammation, oxidative stress, and pyroptosis during sepsis and enhances intestinal damage, which may provide important clues about the potential targets to be exploited in this highly lethal disease.

Hair cell death induced by excessive reactive oxygen species (ROS) has been identified as the major pathogenesis of noise-induced hearing loss (NIHL). Recent studies have demonstrated that cisplatin- and neomycin-induced ototoxicity can be alleviated by ferroptosis inhibitors. However, whether ferroptosis inhibitors have a protective effect against NIHL remains unknown. We investigated the protective effect of the ferroptosis inhibitor ferrostatin-1 (Fer-1) on NIHL in vivo in CBA/J mice and investigated the protective effect of Fer-1 on tert-butyl hydroperoxide (TBHP)-induced hair cell damage in vitro in cochlear explants and HEI-OC1 cells. We observed ROS overload and lipid peroxidation, which led to outer hair cell (OHC) apoptosis and ferroptosis, in the mouse cochlea after noise exposure. The expression level of apoptosis-inducing factor mitochondria-associated 2 (AIFM2) was substantially increased following elevation of the expression of its upstream protein P53 after noise exposure. The ferroptosis inhibitor Fer-1was demonstrated to enter the inner ear after the systemic administration. Administration of Fer-1 significantly alleviated noise-induced auditory threshold elevation and reduced the loss of OHCs, inner hair cell (IHC) ribbon synapses, and auditory nerve fibers (ANFs) caused by noise. Mechanistically, Fer-1 significantly reduced noise- and TBHP-induced lipid peroxidation and iron accumulation in hair cells, alleviating ferroptosis in cochlear cells consequently. Furthermore, Fer-1 treatment decreased the levels of TfR1, P53, and AIFM2. These results suggest that Fer-1 exerted its protective effects by scavenging of ROS and inhibition of TfR1-mediated ferroptosis and P53-AIFM2 signaling pathway-mediated apoptosis. Our findings suggest that Fer-1 is a promising drug for treating NIHL because of its ability to inhibit noise-induced hair cell apoptosis and ferroptosis, opening new avenues for the treatment of NIHL.

With the development of science and technology, the rapid development of social economy, the motor as a new type of transmission equipment, in the production and life of people occupies a pivotal position. Under the rapid development of computer and electronic technology, manufacturing equipment is becoming larger, faster, more continuous, and more automated. This has resulted in complex, expensive, accident-damaging, and high-impact equipment for electric motors; even routine maintenance requires significant equipment maintenance and maintenance costs. If a fault occurs, it will cause serious damage to the entire equipment and can even have a major impact on the entire production process, leading to a serious economic and social life. In this paper, a CNN-based machine learning fault diagnosis method is proposed to address the problem of high incidence of motor faults and difficulty in identifying fault types. A fault reproduction test is constructed by machine learning techniques to extract vibration time domain data for normal operating conditions, rotor eccentricity, stator short circuit, and bearing inner ring fault; divide the data segment into 15 speed segments, extract 13 typical time domain features for each speed segment; and perform mathematical statistics for fault diagnosis. Compared with the traditional algorithm, the method has more comprehensive feature information extraction, higher diagnostic accuracy, and faster diagnostic speed, with a fault diagnosis accuracy of 98.7%.

Using large-scale data collection and analysis methods to develop educational models, study the relationship between educational variables, and provide effective support for educational reform will be the inevitable trend of modern information technology teaching in the future. At present, under the high level of higher education system and higher education reform, curriculum evaluation is an important tool to evaluate the quality of classroom teaching and an important basis to test the effectiveness of curriculum reform. On the basis of establishing the teaching evaluation index system based on students’ participation, acceptance, and satisfaction index, this paper establishes three levels of evaluation system: curriculum micro evaluation index system, secondary college comprehensive evaluation index system and school macro evaluation index system. We use teaching quality evaluation to obtain evaluation data and develop CTQ evaluation and feedback system based on the analysis of broader data, so as to improve the quality of classroom teaching.

Cisplatin is a well-known and widely used anticancer drug with high therapeutic efficacy in solid tumors; however, side effects are common with its use. Because cisplatin can be retained in the cochlea, ototoxicity leading to hearing loss limits its clinical applications. Here, we report that Nrf2 knockout (KO) strongly increased cisplatin resistance in HEI-OC1 cells, which are immortalized cells from the murine organ of Corti. The underlying mechanism of this phenomenon was uncovered, and an important novel therapeutic target for combating cisplatin-induced hearing loss was identified. Preliminary investigations determined that Nrf2 KO markedly decreased TfR1 protein levels and increased GPX4 protein levels. Thus, ferroptosis may protect organisms from cisplatin-induced cell death. Furthermore, Nrf2 KO cells were resistant to the classical ferroptosis inducers RSL3 and erastin, providing solid evidence that Nrf2 KO inhibits ferroptosis and that knocking out Nrf2 may be a new clinical strategy to prevent cisplatin-induced hearing loss.

Objective. To compare the merits and demerits of PEG-IFNα-2a and PEG-IFNα-2b for the treatment of hepatitis B e antigen (HBeAg)-positive chronic hepatitis B (CHB). Methods. Clinical files from eighty-four CHB patients admitted to the Second Hospital of Shanxi Medical University between January 2018 and January 2019 were retrospectively analyzed and assigned to two groups: group 2a treated with PEG-IFNα-2a and group 2b treated with PEG-IFNα-2b. The clinical efficacy was compared between the above two arms, and the liver function (ALT, AST, HA, LN, and IV-C), HBV-DNA, HBsAg, HBeAg, and inflammatory factors (IFs, IL-1β, IL-6, IL-8, and TNF-α) were tested at 12 weeks (T1), 24 weeks (T2), and 48 weeks (T3). The alterations of hemodynamics (SBP, DBP, MAP, and CVP), cardiac function (LVEF and BNP), and the incidence of adverse reactions (ARs) during treatment were recorded. Finally, the patients were followed up for 2 years to investigate the quality of life (QOL) as well as the positive seroconversion rate of HBsAg and HBeAg. Results. The overall response rate was similar in the two arms ( P > 0.05 ). After treatment, the liver function, HBV-DNA, HBsAg, HBeAg, IFs, hemodynamics, and cardiac function were enormously improved ( P < 0.05 ), with faster improvement in group 2b compared with group 2a ( P < 0.05 ). The investigation of ARs identified notably lower incidence rates of alopecia, thrombocytopenia, and granulocytopenia in group 2a as compared to group 2b ( P < 0.05 ). The prognostic follow-up results revealed no distinct difference in the QOL score and the positive seroconversion rate of HBsAg and HBeAg ( P > 0.05 ); however, the quantitative results of HBV-DNA, HBsAg, and HBeAg in group 2b were lower than those in group 2a ( P < 0.05 ). Conclusions. Both PEG-IFNα-2a and PEG-IFNα-2b have excellent and stable therapeutic effects on HBeAg-positive CHB, among which PEG-IFNα-2b renders a faster treatment process but higher side effects, which can provide valuable references when choosing a treatment plan for CHB.

Kernel adaptive filtering (KAF) algorithms derived from the second moment of error criterion perform very well in nonlinear system identification under assumption of the Gaussian observation noise; however, they inevitably suffer from severe performance degradation in the presence of non-Gaussian impulsive noise and interference. To resolve this dilemma, we propose a novel robust kernel least logarithmic absolute difference (KLLAD) algorithm based on logarithmic error cost function in reproducing kernel Hilbert spaces, taking into account of the non-Gaussian impulsive noise. The KLLAD algorithm shows considerable improvement over the existing KAF algorithms without restraining impulsive interference in terms of robustness and convergence speed. Moreover, the convergence condition of KLLAD algorithm with Gaussian kernel and fixed dictionary is presented in the mean sense. The superior performance of KLLAD algorithm is confirmed by the simulation results.

Maternal severe zinc (Zn) deficiency resulted in growth retardation and high mortality during embryonic development in human. Therefore, this study is aimed at evaluating the effect of maternal marginal Zn deficiency on the development and redox status to avoid severe Zn deficiency using an avian model. A total of 324 laying duck breeders at 214 days old were randomly allotted into 3 dietary Zn levels with 6 replicates of 18 ducks per replicate. The birds were fed experimental diets including 3 dietary supplemental Zn levels of 0 mg/kg (maternal Zn-deficient group, 29.2 mg Zn/kg diet), 60 mg/kg (maternal Zn-adequate group), and 120 mg/kg (maternal Zn-high group) for 6 weeks. Dietary Zn levels had on effect on egg production and fertility ( P > 0.05 ), whereas dietary Zn deficiency decreased breeder plasma Zn concentration and erythrocytic alkaline phosphatase activity at week 6 and inhibited erythrocytic 5 ′ -nucleotidase (5 ′ -NT) activity at weeks 2, 4, and 6 ( P < 0.05 ), indicating that marginal Zn-deficient status occurred after Zn depletion. Maternal marginal Zn deficiency increased embryonic mortality and contents of superoxide anion radical, MDA, and PPC and reduced MT content and CuZnSOD activity in duck embryonic livers on E29. The MDA content was positively correlated with embryonic mortality. Maternal marginal Zn deficiency increased BCL2-associated X protein and Caspase-9 mRNA expressions as well as decreased B-cell lymphoma-2 and MT1 mRNA and signal AKT1 and ERK1 protein expressions ( P < 0.05 ). Breeder plasma Zn concentration and erythrocytic 5 ′ -NT activities at week 6 were positively correlated with GSH-Px activity and GPx, MT1, and BCL2 mRNA expressions in embryonic livers on E29. In conclusion, erythrocytic 5 ′ -NT activity could be more rapid and reliable to monitor marginal Zn-deficient status. Marginal Zn deficiency impaired hatchability and antioxidant defense system and then induced oxidative damage and apoptosis in the embryonic liver, contributing to the greater loss of duck embryonic death.

The security of a network is closely related to the structure of the network graph. The denser the network graph structure is, the better it can resist attacks. Toughness and isolated toughness are used to characterize the vulnerable programs of the network which have been paid attention from mathematics and computer scholars. On this basis, considering the particularity of the sun component structures, sun toughness was introduced in mathematics and applied to computer networks. From the perspective of modern graph theory, this paper presents the sun toughness conditions of the path factor uniform graph and the path factor critical avoidable graph in P ≥ 2 -factor and P ≥ 3 -factor settings. Furthermore, examples show that the given boundaries are sharp.

Stock price prediction is very important in financial decision-making, and it is also the most difficult part of economic forecasting. The factors affecting stock prices are complex and changeable, and stock price fluctuations have a certain degree of randomness. If we can accurately predict stock prices, regulatory authorities can conduct reasonable supervision of the stock market and provide investors with valuable investment decision-making information. As we know, the LSTM (Long Short-Term Memory) algorithm is mainly used in large-scale data mining competitions, but it has not yet been used to predict the stock market. Therefore, this article uses this algorithm to predict the closing price of stocks. As an emerging research field, LSTM is superior to traditional time-series models and machine learning models and is suitable for stock market analysis and forecasting. However, the general LSTM model has some shortcomings, so this paper designs a LightGBM-optimized LSTM to realize short-term stock price forecasting. In order to verify its effectiveness compared with other deep network models such as RNN (Recurrent Neural Network) and GRU (Gated Recurrent Unit), the LightGBM-LSTM, RNN, and GRU are respectively used to predict the Shanghai and Shenzhen 300 indexes. Experimental results show that the LightGBM-LSTM has the highest prediction accuracy and the best ability to track stock index price trends, and its effect is better than the GRU and RNN algorithms.

Background. The recombinant protein diannexin can inhibit platelet-mediated events, which contribute to acute respiratory distress syndrome (ARDS). Here, we investigated the effect of diannexin and its effect on heme oxygenase-1 (HO-1) in ARDS. Methods. A total of 32 rats were randomized into sham, ARDS, diannexin (D), and diannexin+HO-1 inhibitor (DH) groups. Alveolar-capillary permeability was evaluated by testing the partial pressure of oxygen to fraction of inspired oxygen (PaO2/FiO2) ratio, lung wet/dry weight ratio, and protein levels in the lung. Inflammation was assessed by measuring cytokine levels in the bronchial alveolar lavage fluid (BALF) and serum and nuclear factor-κB (NF-κB) in the lung tissue. Inducible nitric oxide synthase (iNOS), malondialdehyde (MDA), and myeloperoxidase (MPO) were measured to evaluate the oxidative stress response. Lung tissue pathology and apoptosis were also evaluated. We measured HO-1 expression in the lung tissue to investigate the effect of diannexin on HO-1 in ARDS. Results. Compared with the ARDS group, diannexin improved PaO2/FiO2, lung wet/dry weight ratio, and protein levels in the BALF and decreased levels of cytokines and NF-κB in the lung and serum. Diannexin inhibited the oxidative stress response and significantly ameliorated pathological lung injury and apoptosis. The partial reversal of diannexin effects by a HO-1 inhibitor suggests that diannexin may promote HO-1 expression to ameliorate ARDS. Conclusions. We showed that diannexin can improve alveolar-capillary permeability, inhibit the oxidative stress response and inflammation, and protect against ARDS-induced lung injury and apoptosis.

Background Acute gout is an inflammatory response induced by monosodium urate (MSU) crystals. HSP60 is a highly conserved stress protein that acts as a cellular “danger” signal for immune reactions. In this study, we aimed to investigate the role and molecular mechanism of HSP60 in the gout. Methods HSP60 expression was detected in peripheral blood mononuclear cells (PBMCs) and plasma of gout patients. The effect and mechanism of HSP60 in gout were studied in MSU crystals treatment macrophages and C57BL/6 mice. JC-1 probe and MitoSOX Red were used to measure the mitochondrial membrane potential (MMP) and mitochondrial reactive oxygen species (mtROS). Results HSP60 expression was significantly upregulated in the PBMCs and sera of patients with acute gout (AG) compared to those with inter-critical gout (IG) or healthy controls (HCs). MSU crystals induced expression and secretion of HSP60 in the macrophages. HSP60 knockdown or over-expression affects TLR4 and MyD88 expression, IκBα degradation and the nuclear localization of NF-κB in MSU crystal-stimulated inflammation. Further, HSP60 facilitates MMP collapse and mtROS production, and activates the NLRP3 inflammasome in MSU crystal-stimulated macrophages. In MSU crystal-induced arthritis and peritonitis mouse models pre-treated with HSP60 vivo-morpholino, paw swelling, ankle joint swelling, myeloperoxidase (MPO) activity and inflammatory cell infiltration significantly decreased. Conclusion Our study revealed that MSU crystal stimulates the expression of HSP60 which accelerates TLR4-MyD88-NF-κB signaling pathway and exacerbates mitochondrial dysfunction.

Differential gene analyses on gastric cancer usually focus on expression change of single genes between tumor and adjacent normal tissues. However, besides changes on single genes, there are also coexpression and expression network module changes during the development of gastric cancer. In this study, we proposed a pipeline to investigate various levels of changes between gastric cancer and adjacent normal tissues, which were used to repurpose potential drugs for treating gastric cancer. Specifically, we performed a series of analyses on 242 gastric cancer samples (33-normal, 209-cancer) downloaded from the cancer genome atlas (TCGA), including data quality control, differential gene analysis, gene coexpression network analysis, module function enrichment analysis, differential coexpression analysis, differential pathway analysis, and screening of potential therapeutic drugs. In the end, we discovered some genes and pathways that are significantly different between cancer and adjacent normal tissues (such as the interleukin-4 and interleukin-13 signaling pathway) and screened perturbed genes by 2703 drugs that have a high overlap with the identified differentially expressed genes. Our pipeline might be useful for understanding cancer pathogenesis as well as gastric cancer treatment.

The fracability of shale reservoirs is one of the key indicators used for evaluating whether or not the shale can be used as a “sweet spot zone.” It has been determined that the structural properties of rock have important influences on the evaluation of the fracability of reservoirs. In the current study, five rock quality designation (RQD) calculation methods were compared and analyzed for the purpose of selecting an RQDI for characterizing rock structures. Focused on the lack of structural factors included in the previous fracability evaluation methods, a new model for fracability evaluation based on the combination of the brittleness index, structural index, and fracture toughness was constructed using a linear elastic fracture theory. The model showed that good fracability not only included higher brittleness but also required less energy to produce cracks. Meanwhile, good fracability also required more discontinuous structural planes. In the current study, a formation with a higher fracability index was considered to be a fractureable interval and a formation with a lower fracability index was a fracture barrier. Finally, the reservoir fracability index was modeled using the Xike 2 well in the north of Guizhou Province as a case study. Subsequently, a fracability logging evaluation method based on the fracability index model was determined, which will potentially provide a new technical tool for future fracturing optimization processes.

Background. Recent reports about radiation risk gradually raised the safety concerns for interventional therapy. However, limited data exist on the optimized radiation strategy in primary percutaneous coronary intervention (P-PCI) for patients with ST-segment-elevation myocardial infarction (STEMI). Methods. A total of 214 STEMI patients undergoing P-PCI were retrospectively analyzed. Patients were divided into the optimized radiation strategy (ORS) group (N = 151) and normal radiation strategy (NRS) group (N = 63) according to the radiation protocol utilized. The primary endpoint was the relative dose reduction of total air kerma. The secondary endpoint was 30-day major adverse cardiac and cerebrovascular events (MACCE), as a composite of all-cause death, reinfarction, ischemia-driven target vessel revascularization, and stroke. Results. Patient groups were well matched for baseline characteristics. There were no differences in terms of age, body mass index, radial artery access, nonculprit vessel PCI, and fluoroscopy time between 2 groups. With optimized radiation strategy, a 40.9% radiation dose reduction (901.2 ± 628.7 mGy versus 1524.0 ± 866.6 mGy, p<0.001) was obtained for total air kerma. No significant differences were found for 30-day MACCE between 2 groups (2.0% versus 1.6%, adjusted hazard ratio: 0.7, 95% confidence interval: 0.1 to 8.6, p=0.772). Conclusion. With optimized radiation strategy, significant radiation dose reduction could be achieved in P-PCI for STEMI patients. It appears to be feasible and safe to carry out the optimized radiation strategy in P-PCI for STEMI patients.

Filling of Xiangjiaba Reservoir Lake in the Southwest China triggered and reactivated numerous landslides due to water fluctuation. In order to understand the relationship between reservoirs and slope instability, a typical reservoir landslide (Dasha landslide) at the right bank of Jinsha River was selected as a case study for in-depth investigations. The detailed field investigations were carried out to identify the landslide with respect to its surroundings and to find out the slip surface. Boreholes were drilled to find out the subsurface lithology and the depth of failure of Dasha landslide. The in situ geotechnical tests were performed, and the soil samples from exposed slip surface were retrieved for geotechnical laboratory analysis. Finally, stability analysis was done using the 3D strength reduction method under different conditions of reservoir water level fluctuations and rainfall conditions. The in-depth investigations show that the Dasha landslide is a bedding rockslide which was once activated in 1986. The topography of Dasha landslide is relatively flat, while the back scarp and local terrain is relatively steep. The total volume of landslides is about 580×104 m3 with an average thickness of 20 m. Bedrock in the landslide area is composed of Suining Formation of the Jurassic age. The main rock type is silty mudstone with sandstone, and the bedding orientation is 300~310° ∠ 7~22°. The factor of safety (FOS) of Dasha landslide obtained by 3D strength reduction cannot meet the minimum safety requirement under the working condition of reservoir level fluctuation as designed, with effect of rainfall and rapid drawdown.

For the position tracking control problem of permanent magnet linear motor, an improved fast continuous-time nonsingular terminal sliding mode control algorithm based on terminal sliding mode control method is proposed. Specifically, first, for the second-order model of position error dynamic system, a new continuous-time fast terminal sliding surface is introduced and an improved continuous-time fast terminal sliding mode control law is proposed. Then rigorous theoretical analysis is provided to demonstrate the finite-time stability of the closed-loop system by using the Lyapunov function. Finally, numerical simulations are given to verify the effectiveness and advantages of the proposed fast nonsingular terminal sliding mode control method.

Background. To further understand the development of the spinal cord, an exploration of the patterns and transcriptional features of spinal cord development in newborn mice at the cellular transcriptome level was carried out. Methods. The mouse single-cell sequencing (scRNA-seq) dataset was downloaded from the GSE108788 dataset. Single-cell RNA-Seq (scRNA-Seq) was conducted on cervical and lumbar spinal V2a interneurons from 2 P0 neonates. Single-cell analysis using the Seurat package was completed, and marker mRNAs were identified for each cluster. Then, pseudotemporal analysis was used to analyze the transcription changes of marker mRNAs in different clusters over time. Finally, the functions of these marker mRNAs were assessed by enrichment analysis and protein-protein interaction (PPI) networks. A transcriptional regulatory network was then constructed using the TRRUST dataset. Results. A total of 949 cells were screened. Single-cell analysis was conducted based on marker mRNAs of each cluster, which revealed the heterogeneity of neonatal mouse spinal cord neuronal cells. Functional analysis of pseudotemporal trajectory-related marker mRNAs suggested that pregnancy-specific glycoproteins (PSGs) and carcinoembryonic antigen cell adhesion molecules (CEACAMs) were the core mRNAs in cluster 3. GSVA analysis then demonstrated that the different clusters had differences in pathway activity. By constructing a transcriptional regulatory network, USF2 was identified to be a transcriptional regulator of CEACAM1 and CEACAM5, while KLF6 was identified to be a transcriptional regulator of PSG3 and PSG5. This conclusion was then validated using the Genotype-Tissue Expression (GTEx) spinal cord transcriptome dataset. Conclusions. This study completed an integrated analysis of a single-cell dataset with the utilization of marker mRNAs. USF2/CEACAM1&5 and KLF6/PSG3&5 transcriptional regulatory networks were identified by spinal cord single-cell analysis.

There are a lot of bacteria in the environment, and Gram-positive bacteria are the most common ones. Some Gram-positive bacteria are very harmful to the human body, so it is significant to predict Gram-positive bacterial protein subcellular location. And identification of Gram-positive bacterial protein subcellular location is important for developing effective drugs. In this paper, a new Gram-positive bacterial protein subcellular location dataset was established. The amino acid composition, the gene ontology annotation information, the hydropathy dipeptide composition information, the amino acid dipeptide composition information, and the autocovariance average chemical shift information were selected as characteristic parameters, then these parameters were combined. The locations of Gram-positive bacterial proteins were predicted by the Support Vector Machine (SVM) algorithm, and the overall accuracy (OA) reached 86.1% under the Jackknife test. The overall accuracy (OA) in our predictive model was higher than those in existing methods. This improved method may be helpful for protein function prediction.

Background. Sudden sensorineural hearing loss (SSNHL) is an otologic emergency and could lead to social difficulties and mental disorders in some patients. Although many studies have analyzed altered brain function in populations with hearing loss, little information is available about patients with idiopathic SSNHL. This study is aimed at investigating brain functional changes in SSNHL via functional magnetic resonance imaging (fMRI). Methods. Thirty-six patients with SSNHL and thirty well-matched normal hearing individuals underwent resting-state fMRI. Amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), and functional connectivity (FC) values were calculated. Results. In the SSNHL patients, ALFF and fALFF were significantly increased in the bilateral putamen but decreased in the right calcarine cortex, right middle temporal gyrus (MTG), and right precentral gyrus. Widespread increases in FC were observed between brain regions, mainly including the bilateral auditory cortex, bilateral visual cortex, left striatum, left angular gyrus (AG), bilateral precuneus, and bilateral limbic lobes in patients with SSNHL. No decreased FC was observed. Conclusion. SSNHL causes functional alterations in brain regions, mainly in the striatum, auditory cortex, visual cortex, MTG, AG, precuneus, and limbic lobes within the acute period of hearing loss.

In order to express the safety level of hull structures, IACS Common Structure Rules of Bulk Carriers and Oil Tankers (CSR-H) makes new requirements of hull girder ultimate strength. Compared with original CSR (i.e., CSR-OT and CSR-BC), partial safety factors of hull girder ultimate strength in CSR-H have been partly modified, and new requirements of residual strength have been added in the rules for hull safety after grounded/collided damage. This paper compares the rule requirements of ultimate strength in CSR-H and CSR-OT/CSR-BC and explains the technical background of rule requirements. The hull girder ultimate strength is mainly analyzed by SMITH method in rule requirements due to fast and stable calculation results. This paper also uses nonlinear finite element method (NFEM) to explain the critical influence factors for hull girder ultimate strength implied in the rule requirements. Based on 5 typical Bulk Carriers and 4 typical Oil Tankers, the influence of hull girder ultimate strength and residual strength in CSR-H has been evaluated for ship building industry. The actual ship evaluation results can be used to instruct the new CSR-H ship design.

To solve the main shortcoming of numerical method for analysis of the stability of rock slope, such as the selection the convergence condition for the strength reduction method, one method based on the minimum energy dissipation rate is proposed. In the new method, the basic principle of fractured rock slope failure, that is, the process of the propagation and coalescence for cracks in rock slope, is considered. Through analysis of one mining rock slope in western China, this new method is verified and compared with the generally used strength reduction method. The results show that the new method based on the minimum energy dissipation rate can be used to analyze the stability of the fractured rock slope and its result is very good. Moreover, the new method can obtain less safety factor for the rock slope than those by other methods. Therefore, the new method based on the minimum energy dissipation rate is a good method to analyze the stability of the fractured rock slope and should be superior to other generally used methods.

In order to improve the performance of the membrane element with vertex rigid rotational freedom, a new method to establish the local Cartesian coordinate system and calculate the derivatives of the shape functions with respect to the local coordinates is introduced in this paper. The membrane elements with vertex rigid rotational freedom such as GQ12 and GQ12M based on this new method can achieve higher precision results than traditional methods. The numerical results demonstrate that the elements GQ12 and GQ12M with this new method can provide better membrane elements for flat shell elements. Furthermore, this new method presented in this paper offers a new approach for other membrane elements used in flat shell element to improve the computing accuracy.

With the development of radio telescope antennas with large apertures, high gain, and wide frequency bands, compensation methods, such as mechanical or electronic compensation, are obviously essential to ensure the electrical performance of antennas that work in complex environments. Since traditional compensation methods can only adjust antenna pointing but not the surface accuracy, which are limited for obtaining high surface precision and aperture efficiency, active surface adjustment has become an indispensable tool in this field. Therefore, the development process of electrical performance compensation methods for radio telescope antennas is introduced. Further, a series of analyses of the five key technologies of active surface adjustment is presented. Then, four typical large antennas that have been designed with active main reflector technology are presented and compared. Finally, future research directions and suggestions for reflector antenna compensation methods based on active surface adjustment are presented.

The aim of this study was to investigate the long-term prognostic value of pentraxin-3 (PTX3) in patients with chronic heart failure (CHF). 377 patients were prospectively followed up for 3 years to determine cardiac events including cardiac death or rehospitalization for worsening heart failure. The plasma PTX3 levels were significantly higher in CHF patients than in healthy subjects (p<0.001), and they increased with advancing New York Heart Association (NYHA) Functional Classification (p<0.001). Plasma PTX3 levels in CHF patients with cardiac events were significantly higher than in event-free patients (p<0.001). We determined the normal upper limit of plasma PTX3 levels from the mean + 2 SD value of 64 control subjects (3.64 ng/mL). A Kaplan-Meier analysis revealed that patients with increased PTX3 (≥3.64 ng/mL) were at a higher risk for cardiac events than those without increased PTX3 (p<0.01). A multifactorial Cox proportional hazards model showed that increased PTX3 (≥3.64 ngImL) was an independent risk factor for cardiac events in CHF patients (hazard ratio (HR) = 4.224,p<0.01; 95% CI: 1.130–15.783). Plasma PTX3 levels are a long-term independent predictor of prognosis in patients with CHF.

Given a graph G, the general sum-connectivity index is defined as χα(G)=∑uv∈E(G)dGu+dGvα, where dG(u) (or dG(v)) denotes the degree of vertex u (or v) in the graph G and α is a real number. In this paper, we obtain the sharp bounds for general sum-connectivity indices of several graph transformations, including the semitotal-point graph, semitotal-line graph, total graph, and eight distinct transformation graphs Guvw, where u,v,w∈+,-.

The hyper-Zagreb index is an important branch in the Zagreb indices family, which is defined as∑uv∈E(G)‍(d(u)+d(v))2, whered(v)is the degree of the vertexvin a graphG=(V(G),E(G)). In this paper, the monotonicity of the hyper-Zagreb index under some graph transformations was studied. Using these nice mathematical properties, the extremal graphs amongn-vertex trees (acyclic), unicyclic, and bicyclic graphs are determined for hyper-Zagreb index. Furthermore, the sharp upper and lower bounds on the hyper-Zagreb index of these graphs are provided.

As an efficient theoretical tool, graph theory is widely used in computing chemistry. In terms of index computation on molecular graphs, the researchers can learn the potential properties of chemical compounds, including drugs, materials, and organics. In this paper, by means of distance computation, we study the eccentric version indices of cycloalkanes which occur quite frequently in the chemical drugs and other compounds. The promising prospects of the application for the physical, chemical, medical, and pharmacy engineering are illustrated by theoretical conclusions obtained in this article.

Background. The deregulated tumorigenic long non-coding RNA (lncRNA) has been reported in several malignancies. However, there is still no comprehensive study on tongue squamous cell carcinoma (SCC). Methods. Functional reannotation for the human lncRNA was carried out by ncFANs. Real-time quantitative PCR was used to validate the identified lncRNAs. Results. Using the functional annotation algorithm from ncFANs, 8 differentially expressed lncRNAs were identified. Lnc-PPP2R4-5, lnc-SPRR2D-1, lnc-MAN1A2-1, lnc-FAM46A-1, lnc-MBL2-4:1, and lnc-MBL2-4:3 were upregulated in the microdissected tongue SCC tissues. In comparison, lnc-AL355149.1-1 and lnc-STXBP5-1 showed significant downregulation. High level of lnc-MBL2-4:3 was significantly associated with the node positive tongue SCC patients. Further, patients with advanced T-stage demonstrated a further reduction of lnc-AL355149.1-1 in the tumor tissues. Treatment of tongue SCC cells with 5-fluorouracil and paclitaxel can reserve the expression patterns observed in the tongue SCC tissues. Further, changes of lnc-MBL2-4:3 and lnc-AL355149.1-1 expression levels were noticed in the cisplatin-resistant tongue SCC cells. Conclusions. Our results demonstrated that functional reannotation allows us to identify novel lncRNAs using the existing gene expression array dataset. The association of lncRNA with the T-stage and nodal status of tongue SCC patients suggested that lncRNA deregulation was involved in the pathogenesis of tongue SCC., published_or_final_version

The gradient learning model has been raising great attention in view of its promising perspectives for applications in statistics, data dimensionality reducing, and other specific fields. In this paper, we raise a new gradient learning model for ontology similarity measuring and ontology mapping in multidividing setting. The sample error in this setting is given by virtue of the hypothesis space and the trick of ontology dividing operator. Finally, two experiments presented on plant and humanoid robotics field verify the efficiency of the new computation model for ontology similarity measure and ontology mapping applications in multidividing setting.

A graphGis called a fractional(g,f)-deleted graph ifG-{e}admits a fractional(g,f)-factor for anye∈E(G). A graphGis called a fractional(g,f,n)-critical deleted graph if, after deleting anynvertices fromG, the resulting graph is still a fractional(g,f)-deleted graph. The toughness, as the parameter for measuring the vulnerability of communication networks, has received significant attention in computer science. In this paper, we present the relationship between toughness and fractional(g,f,n)-critical deleted graphs. It is determined thatGis fractional(g,f,n)-critical deleted ift(G)≥((b2-1+bn)/a).

Ontology, as a useful tool, is widely applied in lots of areas such as social science, computer science, and medical science. Ontology concept similarity calculation is the key part of the algorithms in these applications. A recent approach is to make use of similarity between vertices on ontology graphs. It is, instead of pairwise computations, based on a function that maps the vertex set of an ontology graph to real numbers. In order to obtain this, the ranking learning problem plays an important and essential role, especiallyk-partite ranking algorithm, which is suitable for solving some ontology problems. A ranking function is usually used to map the vertices of an ontology graph to numbers and assign ranks of the vertices through their scores. Through studying a training sample, such a function can be learned. It contains a subset of vertices of the ontology graph. A good ranking function means small ranking mistakes and good stability. For ranking algorithms, which are in a well-stable state, we study generalization bounds via some concepts of algorithmic stability. We also find that kernel-based ranking algorithms stated as regularization schemes in reproducing kernel Hilbert spaces satisfy stability conditions and have great generalization abilities.

We present a new mixed finite element method for solving the extended Fisher-Kolmogorov (EFK) equation. We first decompose the EFK equation as the two second-order equations, then deal with a second-order equation employing finite element method, and handle the other second-order equation using a new mixed finite element method. In the new mixed finite element method, the gradient∇ubelongs to the weaker(L2(Ω))2space taking the place of the classicalH(div;Ω)space. We prove some a priori bounds for the solution for semidiscrete scheme and derive a fully discrete mixed scheme based on a linearized Crank-Nicolson method. At the same time, we get the optimal a priori error estimates inL2andH1-norm for both the scalar unknownuand the diffusion termw=−Δuand a priori error estimates in(L2)2-norm for its gradientχ=∇ufor both semi-discrete and fully discrete schemes.

Hypoxia is a common feature in most of the solid tumors including head and neck squamous cell carcinoma (HNSCC). Hypoxia reflects the imbalance between oxygen consumption by the rapidly proliferating cancer cells and the insufficient oxygen delivery due to poor vascularization and blood supply. The hypoxic microenvironment in the HNSCC contributes to the development of aggressive carcinoma phenotype with high metastatic rate, resistance to therapeutic agents, and higher tumor recurrence rates, leading to low therapeutic efficiency and poor outcome. To overcome the therapeutic resistance due to hypoxia and improving the prognosis of the HNSCC patients, many approaches have been examined in laboratory studies and clinical trials. In this short paper, we discuss the mechanisms involved in the resistance of radiotherapy and chemotherapy in hypoxic condition. We also exploit the molecular mechanisms employed by the HNSCC cells to adapt the hypoxic condition and their tumorigenic role in head and neck, as well as the strategies to overcome hypoxia-induced therapeutic resistance.

The impact parameter dependence of π-/π+ ratio is examined in heavy-ion collisions at 400 MeV/nucleon within a transport model. It is shown that the sensitivity of π-/π+ ratio on symmetry energy shows a transition from central to peripheral collisions; that is, the stiffer symmetry energy leads to a larger π-/π+ ratio in peripheral collisions while the softer symmetry energy always leads this ratio to be larger in central collisions. After checking the kinematic energy distribution of π-/π+ ratio, we found this transition of sensitivity of π-/π+ ratio to symmetry energy is mainly from less energetic pions; that is, the softer symmetry energy gets the less energetic pions to form a smaller π-/π+ ratio in peripheral collisions while these pions generate a larger π-/π+ ratio in central collisions. Undoubtedly, the softer symmetry energy can also lead more energetic pions to form a larger π-/π+ ratio in peripheral collisions. Nevertheless, considering that most of pions are insufficiently energetic at this beam energy, we therefore suggest the π-/π+ ratio as a probe of the high-density symmetry energy effective only in central at most to midcentral collisions, thereby avoiding the possible information of low-density symmetry energy carried in π-/π+ ratio from peripheral collisions.

Clustering analysis is used in many disciplines and applications; it is an important tool that descriptively identifies homogeneous groups of objects based on attribute values. The ant colony clustering algorithm is a swarm-intelligent method used for clustering problems that is inspired by the behavior of ant colonies that cluster their corpses and sort their larvae. A new abstraction ant colony clustering algorithm using a data combination mechanism is proposed to improve the computational efficiency and accuracy of the ant colony clustering algorithm. The abstraction ant colony clustering algorithm is used to cluster benchmark problems, and its performance is compared with the ant colony clustering algorithm and other methods used in existing literature. Based on similar computational difficulties and complexities, the results show that the abstraction ant colony clustering algorithm produces results that are not only more accurate but also more efficiently determined than the ant colony clustering algorithm and the other methods. Thus, the abstraction ant colony clustering algorithm can be used for efficient multivariate data clustering.

Numerous studies indicate that there is strong inherent relationship between the chemical characteristics of chemical compounds and drugs (e.g., boiling point and melting point) and their molecular structures. Topological indices defined on these chemical molecular structures can help researchers better understand the physical features, chemical reactivity, and biological activity. Thus, the study of the topological indices on chemical structure of chemical materials and drugs can make up for lack of chemical experiments and can provide a theoretical basis for the manufacturing of drugs and chemical materials. In this paper, we focus on the family of smart polymer which is widely used in anticancer drugs manufacturing. Several topological indices are determined in view of edge dividing methods, and these results remedy the lack of chemical and medicine experiments thus providing the theoretical basis for pharmaceutical engineering.

Objectives. To survey and analyse the prognosis, outcome, and changing tendency of the Acute Myocardial Infarction (AMI) patients in Beijing third-grade A-level Traditional Chinese Medicine (TCM) hospitals.Methods. We collected the clinical datum of hospitalized AMI patients in Beijing 6 TCM hospitals from January 1999 to December 2008 and then analysed the clinical datum.Results. (1) The mean age of patients had showed a slowly rising tendency during this ten years. The patients who had previous history of cerebrovascular diseasea and multiple comorbidities had increased year by year. (2) The rate of reperfusion therapy, revascularization and standardized using of drug, and usage of TCM of AMI patients presented a significant increasing tendency in these hospitals. (3) The proportion of AMI patients combined with cardiac arrhythmia and heart failure had decreased significantly. (4) The AMI mortality presented a decreasing tendency in 10 years.Conclusions. The AMI patients in Beijing TCM hospitals had their own unique clinical features, and it can improve their prognosis by combined therapy of Western Medicine and Traditional Chinese Medicine.