Acceleration and displacement dynamic response laws of a shallow-buried bifurcated tunnel

In order to obtain the seismic dynamic laws of the acceleration and displacement of a shallow-buried bifurcated tunnel, the analysis of the numerical simulation was carried out by MIDAS-GTS/NX software. The results of the numerical simulation were verified by a shaking table model test. The results show that: (1) the numerical simulation and shaking table test coincide with each other in terms of variation law and peak value. The results of the numerical simulation are credible. (2) For different tunnel cross-section, the response of acceleration and displacement are significant difference. (3) The seismic response of the small distance tunnel (Section 6) is intense. The seismic response laws of the small distance tunnel are significant difference from other type tunnels. The seismic response of the measuring point at the middle rock column is intense. (4) Along the axis of the tunnel, the displacement of the tunnel firstly increases and then decreases. The displacement of the measuring point at the middle rock column is intense, which is in accordance with the law of the acceleration response. The seismic response laws of the tunnel are significantly affected by the middle rock column. The section structure size has a significant effect on the dynamic response of the tunnel

The Research of Sequential Images: Rebuilding of Gray (Position) ~ Time Function on Direction Lines and Their Applications

Contrasted with other information carriers, such as speech and text, images contains larger amount of information, especially in sequential images, that is waiting to be exploited, in particular the dynamic information of correlation, difference, and temporal relationship between different frames. This dynamic information contributes a great deal in analysis of 4D images. This paper proposes a method for detecting dynamic information from sequential images, based on the rebuilding of their gray (position)~time function on direction lines, an approach that has been analyzed and studied extensively on the setting of various direction lines. This method is based on motion that is presented on sequential images. In particular, the method, Omni directional M-mode Echocardiography system, which we have studied extensively, will be described leading to a robust way of diagnosing heart diseases

B Cells Regulate Neutrophilia during Mycobacterium tuberculosis Infection and BCG Vaccination by Modulating the Interleukin-17 Response

We have previously demonstrated that B cells can shape the immune response to Mycobacterium tuberculosis, including the level of neutrophil infiltration and granulomatous inflammation at the site of infection. The present study examined the mechanisms by which B cells regulate the host neutrophilic response upon exposure to mycobacteria and how neutrophilia may influence vaccine efficacy. To address these questions, a murine aerosol infection tuberculosis (TB) model and an intradermal (ID) ear BCG immunization mouse model, involving both the μMT strain and B cell-depleted C57BL/6 mice, were used. IL (interleukin)-17 neutralization and neutrophil depletion experiments using these systems provide evidence that B cells can regulate neutrophilia by modulating the IL-17 response during M. tuberculosis infection and BCG immunization. Exuberant neutrophilia at the site of immunization in B cell-deficient mice adversely affects dendritic cell (DC) migration to the draining lymph nodes and attenuates the development of the vaccine-induced Th1 response. The results suggest that B cells are required for the development of optimal protective anti-TB immunity upon BCG vaccination by regulating the IL-17/neutrophilic response. Administration of sera derived from M. tuberculosis-infected C57BL/6 wild-type mice reverses the lung neutrophilia phenotype in tuberculous μMT mice. Together, these observations provide insight into the mechanisms by which B cells and humoral immunity modulate vaccine-induced Th1 response and regulate neutrophila during M. tuberculosis infection and BCG immunization. © 2013 Kozakiewicz et al

The Influence of the Expansive Grout on Theoretical Bandwidth for the Measurement of Strain Waves by Borehole Tensor Strainmeters

The scattering model of incident seismic waves by an empty borehole has been presented to investigate the theoretical frequency response and the corresponding bandwidth of borehole tensor strainmeters. Inner-diameter changes of the stainless steel instrument casing are measured by horizontal extensometers (gauges), after the borehole tensor strainmeter is installed at a certain depth of the borehole and boned by expansive grout with the surrounding rock. There is, however, no answer for the difference between this case and the empty case. In this paper, the scattering model of incident elastic seismic waves by a two-ring borehole is introduced to investigate the influence of the expansive grout on theoretical bandwidth for the measurement of strain waves by borehole tensor strainmeters. The calculation of wave fields in the surrounding rock and the two rings by wave function expansion gives the inner-diameter changes of the stainless steel instrument casing. Several cases show that the mechanical parameters of the expansive grout have great influence on the frequency responses of borehole tensor strainmeters for different gauge combinations, but little influence on the bandwidth, which means that the high-frequency bandwidth promises the quantitative measurability of strain waves in the acoustical frequency range for borehole tensor strainmeters

Classifying and Scoring Major Depressive Disorders by Residual Neural Networks on Specific Frequencies and Brain Regions

Major Depressive Disorder (MDD) - can be evaluated by advanced neurocomputing and traditional machine learning techniques. This study aims to develop an automatic system based on a Brain-Computer Interface (BCI) to classify and score depressive patients by specific frequency bands and electrodes. In this study, two Residual Neural Networks (ResNets) based on electroencephalogram (EEG) monitoring are presented for classifying depression (classifier) and for scoring depressive severity (regression). Significant frequency bands and specific brain regions are selected to improve the performance of the ResNets. The algorithm, which is estimated by 10-fold cross-validation, attained an average accuracy rate ranging from 0.371 to 0.571 and achieved average Root-Mean-Square Error (RMSE) from 7.25 to 8.41. After using the beta frequency band and 16 specific EEG channels, we obtained the best-classifying accuracy at 0.871 and the smallest RMSE at 2.80. It was discovered that signals extracted from the beta band are more distinctive in depression classification, and these selected channels tend to perform better on scoring depressive severity. Our study also uncovered the different brain architectural connections by relying on phase coherence analysis. Increased delta deactivation accompanied by strong beta activation is the main feature of depression when the depression symptom is becoming more severe. We can therefore conclude that the model developed here is acceptable for classifying depression and for scoring depressive severity. Our model can offer physicians a model that consists of topological dependency, quantified semantic depressive symptoms and clinical features by using EEG signals. These selected brain regions and significant beta frequency bands can improve the performance of the BCI system for detecting depression and scoring depressive severity

Predictive Value of D-dimer in Preeclamptic Pregnant Women at Different Ages

Background: The aim of this study was to evaluate the relationship and impact of D-dimer levels and preeclamptic pregnancies at different ages in women. Methods: We conducted an observational retrospective cohort study of 325 pregnant women who delivered in Wenzhou People’s Hospital from January 2018 to December 2021. Clinical data including age, neutrophils, lymphocytes, platelets, fibrinogen, gestational age, D-dimer/fibrinogen, blood pressure at admission, and fetal weight were collected from the medical record database. All measurements were made using the same methods. Data for continuous variables were expressed as X ± standard deviation (SD), and inter-group differences in continuous data were compared by independent sample t-test. Continuous variables that do not conform to the normal distribution, such as age and D-dimer, were expressed as median and quartile ranges. The relationship between D-dimer and preeclampsia pregnant women of different ages was evaluated by receiver operating characteristics (ROC) curve analysis. Results: Among the middle-aged pregnant women, the average D-dimer in the normotensive pregnancy group was (1.367 ± 0.03 mg/L), which was significantly lower than that in the preeclampsia group (2.087 ± 0.16 mg/L). The D-dimer/fibrinogen ratio was comparable between the young groups, but there was a difference between the middle-aged groups. Meanwhile, in middle-aged pregnant women, the predicted area of D-dimer for preeclampsia was 70.2% (95% confidence interval (CI) 60–80.43%, p = 0.0002) , which was significantly higher than that in the young group. Conclusions: Prenatal D-dimer levels may be associated with more accurate predictors of preeclampsia in middle-aged women than in young women

Clinical trials of stem cell-based therapies for pediatric diseases: a comprehensive analysis of trials registered on ClinicalTrials.gov and the ICTRP portal site

Abstract Background Research on clinical trials that employ stem cells to treat children’s diseases is limited. The clinical trial registry database provides a unique window to us to get known about clinical trial researches with different statuses. However, few studies aimed to perform a comprehensive and thorough analysis of those registered trials in the aforementioned field based on ClinicalTrials.gov and the ICTRP portal site. Methods Our study covered the clinical researches about stem cell therapy enrolling subjects aged under 18 years old registered on ClinicalTrials.gov and WHO ICTRP before May 18, 2021. A cross-sectional study was implemented to comprehensively describe and analyze the included trials that met the criteria. Results were available on ClinicalTrials.gov, and publications related to the included trials were identified. All analyses were performed utilizing the SPSS 25.0 software. Results Eventually, 202 clinical trials were included and evaluated. The participant number of trials tended to be small; 71.3% were enrolled < 50. And 93.5% of the subjects were without gender restrictions. Till May 2020, 112 trials had been preliminary completed, of which only 39 trials had published papers or uploaded results. Most (73.6%) of 186 interventional trials were in phase 1 and phase 2, where 131 (70.4%) trials were conducted without masking, and 26.3% trials were randomized; 55.4% trials were performed single group assignment. Of 16 observational trials, case-only/series took up 37.5%. Hematopoietic stem cells (37.1%) and mesenchymal stem cells (36.1%) were mostly employed, while umbilical cord blood (UCB)-derived cells (24.3%) and bone marrow (BM)-derived cells (20.8%) were the major sources. Conclusions This study provided an overall picture of utilizing stem cells for treatment and management of childhood diseases. Since clinical trials in this area are insufficient in quantity and quality, there is an urgent need of larger, better-designed trials. Increased investment in clinical research of stem cell treatment products should be carried out to achieve the transformation of results as soon as possible. Moreover, it is important to optimize the management of the registration platform and shorten the time it takes for research results to be published

Reducing GEF-H1 Expression Inhibits Renal Cyst Formation, Inflammation, and Fibrosis via RhoA Signaling in Nephronophthisis

Nephronophthisis (NPHP) is the most prevalent monogenic disease leading to end-stage renal failure in childhood. RhoA activation is involved in NPHP pathogenesis. This study explored the role of the RhoA activator guanine nucleotide exchange factor (GEF)-H1 in NPHP pathogenesis. We analyzed the expression and distribution of GEF-H1 in NPHP1 knockout (NPHP1KO) mice using Western blotting and immunofluorescence, followed by GEF-H1 knockdown. Immunofluorescence and renal histology were used to examine the cysts, inflammation, and fibrosis. A RhoA GTPase activation assay and Western blotting were used to detect the expression of downstream GTP-RhoA and p-MLC2, respectively. In NPHP1 knockdown (NPHP1KD) human kidney proximal tubular cells (HK2 cells), we detected the expressions of E-cadherin and α-smooth muscle actin (α-SMA). In vivo, increased expression and redistribution of GEF-H1, and higher levels of GTP-RhoA and p-MLC2 in renal tissue of NPHP1KO mice were observed, together with renal cysts, fibrosis, and inflammation. These changes were alleviated by GEF-H1 knockdown. In vitro, the expression of GEF-H1 and activation of RhoA were also increased, with increased expression of α-SMA and decreased E-cadherin. GEF-H1 knockdown reversed these changes in NPHP1KD HK2 cells. Thus, the GEF-H1/RhoA/MLC2 axis is activated in NPHP1 defects and may play a pivotal role in NPHP pathogenesis

How K12 Teachers’ Readiness Influences Their Intention to Implement STEM Education: Exploratory Study Based on Decomposed Theory of Planned Behavior

Teachers are the key factors in ensuring the effectiveness of STEM education, and their intentions deeply influence their teaching practices. The existing research about the influencing factors of teachers’ intentions to implement STEM education has some problems, such as small sample sizes, being limited to teachers of a single subject, and the need for optimization of the theoretical model relied on. This research, based on the decomposed theory of planned behavior combined with the readiness of teachers, formed an assumption model of the factors influencing teachers’ STEM education intentions from the aspects of attitudes, subjective norms, and perceived behavioral control. Questionnaires were sent to 532 K12 general teachers in China. A structural equation model (SEM) was used to analyze recycled data and verify the assumption model. The results show the following: (1) The educational readiness of K12 teachers in China was at an upper–middle level. Among them, the level of emotional readiness was the highest, while the level of behavioral readiness was the lowest. (2) The STEM behavioral intention of teachers was at an upper–middle level, and attitudes and perceived behavioral control had direct significant impacts on teachers’ intentions to engage in STEM education. Perceived usefulness, self-efficacy, and behavioral readiness were the three strongest indirect impact factors. (3) The emotional readiness of the teachers directly affected their intentions to implement STEM education. Behavioral readiness and cognitive readiness indirectly had an impact on teachers’ intentions to implement STEM education by influencing self-efficacy