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A wind turbine is subjected to a regime of varying loads. For example, each rotor revolution causes a complete gravity stress reversal in the low-speed shaft, and there are varying stresses from the out-of-plane loading cycle due to fluctuating wind load. Consequently, wind turbine blade design is governed by fatigue rather than ultimate load considerations. Previous studies have adopted many different beam theories, using different techniques and codes, to model the National Renewable Energy Laboratory (NREL) 5 MW offshore wind turbine blade. There are differences, from study to study, in the free vibration results and the dynamic response. Thecontribution of this study is to apply the code written by the authors to the different beam theories used with the aim of comparing the different beam theories presented in the literature and that developed by the authors. This paper reports the investigation of the effects of deformation parameters on the dynamic characteristics of the NREL 5 MW offshore wind turbine blades predicted by the different beam theories. The investigation of free vibrations is a fundamental step in the analysis of structural dynamics, and this study compares different computational structural methods and investigates their effect on the predicted dynamic response. The modalcharacteristics of every model examined have been combined with strip theory to determine the dynamic response of the blade.

Single-cell sequencing is an emerging sequencing technology that can effectively identify the cell types of tumors. In bladder cancer prognosis, muscular invasion often represents a poor prognosis and affects patients' quality of life. This study aims to extract the expression levels of muscle-invasive related genes(MIRGs) in bladder cancer patients and construct a model of MIRG, which can predict bladder cancer patients' prognosis using bioinformatics methods. Methods: Single-cell sequencing data of bladder cancer patients were obtained from the GEO database. After conducting quality control and cell type identification, all epithelial cells in the samples were extracted and classified based on their invasive and non-invasive characteristics, followed by a differential analysis. The results were identified as MIRGs. Subsequently, we downloaded and organized gene data of bladder cancer patients from TCGA and determined the intersection of MIRGs and the sequenced gene set of TCGA patients. Clinical information was then associated with the intersection, and the data were divided into training and test sets, with the training set used for model construction and the test set for model verification. Subsequently, the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm and Cox regression were used to construct a prognostic model based on MIRGs. Based on the prognostic features, risk scores were calculated, and patients were classified into high-risk and low-risk groups. We observed the survival information of patients in the high-risk and low-risk groups in both the training and test sets, constructed ROC curves to assess the predictive ability of the model, and subsequently, we generated nomograms. Results: Three cell types were identified, and epithelial cells were extracted, clustered, and divided into invasive and non-invasive groups based on pathological staging. A total of 411 differentially expressed genes were screened. GO and KEGG analyses revealed that these genes were significantly associated with cellular processes such as apoptosis, cell adhesion, and tumor development and progression.After intersecting the expressed genes, 402 genes were determined for model construction. Following the LASSO algorithm and Cox regression, a risk prediction model consisting of CD74, AKR1B1, EIF3D, EMP1, CRABP2, TRIM31, RPL36A and MRPS6 was established.Survival curves and Receiver Operating Characteristic (ROC) curves demonstrated that the model exhibited good predictive ability. A nomograms was constructed to predict patients' survival rates at 1, 3, and 5 years. The calibration curve of the nomograms indicated that it had a satisfactory prognostic ability for patients. Conclusion: In this study, based on single-cell sequencing data, TCGA sequencing data and clinical information, the bladder cancer muscle-invasive related gene prognostic model constructed using multi-omics methods demonstrated a certain degree of accuracy and reliability in predicting the survival prognosis of bladder cancer patients. This provides a reference for assessing the prognosis of bladder cancer patients.

PURPOSE: To investigate the potential genetic cause in a primary infertility patient with multiple morphological abnormalities of sperm flagella (MMAF). METHODS: The patient’s sperm was observed by light and electron microscopy. Whole-exome sequencing (WES) was carried out to identify candidate genes. Then, the mutation found by WES was verified by Sanger sequencing. The proteins interacting with ARMC2 were revealed by co-immunoprecipitation (co-IP) and mass spectrometry. Intracytoplasmic sperm injection (ICSI) was carried out to achieve successful pregnancy. RESULTS: Typical MMAF phenotype (absent, short, coiled, bent irregular flagella) was shown in the patient’s sperm. A novel homozygous mutation in ARMC2 (c.1264C > T) was identified. The proteins interacting with ARMC2 we found were CEP78, PGAM5, RHOA, FXR1, and SKIV2L2. The ICSI therapy was successful, and boy-girl twins were given birth. CONCLUSION: We found a novel mutation in ARMC2 which led to MMAF and male infertility. This is the first report of ICSI outcome of patient harboring ARMC2 mutation. The interacting proteins indicated that ARMC2 might be involved in multiple processes of spermatogenesis.

The harsh weather conditions offshore wind turbine blades are working under have necessitated the need for a more effective approach for detecting their failures. Dynamic characteristics e.g., vibration, carry useful information related to blades structural health. Critical analysis of the blade’s free vibration represents one of the fundamental steps for assessing structural dynamics. When a rotating blade deflects, either in the plane of rotation or perpendicular to it, the centrifugal force exerts inertia force along the blade span, which increases the blade’s natural frequencies compared with the stationary ones. However, the influence of different blade parameters on the flap-wise vibrations is not very well understood. In this paper, the effects of such parameters on dynamic characteristics of National Renewable Energy Laboratory (NREL) 5-MW wind turbine blades are investigated using different beam theories. The examined models have been used to determine the natural frequencies and mode shapes of the National Renewable Energy Laboratory (NREL) 5-MW wind turbine. Results demonstrate that increasing angular velocity significantly impacts the natural frequencies and mode shapes. The rotary inertia is found to influence the free vibration responses of the studied blades. Moreover, increasing hub radius, pre-cone and pitch angles are found to have less influence on the natural frequencies. Mode shape comparisons were also carried out using MSF (modal scale factor) and MAC (modal assurance criteria). Compared to the other investigated methods, Bernoulli’s based algorithms are found to produce less accurate results.

Due to their large and increasing size and the corrosive nature of salt water and high wind speeds, offshore wind turbines are required to be more robust, more rugged and more reliable than their onshore counterparts. The dynamic characteristics of the blade and its response to applied forces may be influenced dramatically by rotor rotational speed, which may even threaten the stability of the wind turbine. An accurate and computationally efficient structural dynamics model is essential for offshore wind turbines. A comprehensive model that takes the centrifugal stiffening effect into consideration could make rapid and accurate decisions with live data sensed from the structure. Moreover, this can enhance both the performance and reliability of wind turbines. When a rotating blade deflects in its plane of rotation or perpendicular to it, the centrifugal force exerts an inertia force that increases the natural frequencies and changes the mode shapes, leading to changes in the dynamic response of the blade. However, in the previous literature, studies of centrifugal stiffening are rarely found. This study investigates the influence of centrifugal stiffening on the free vibrations and dynamic response of offshore wind turbine blades. The National Renewable Energy Laboratory (NREL) 5 MW blade benchmark was considered to study the effect of angular speed in the flap-wise and edge-wise directions. The results demonstrate that the angular speed directly affects the modal features, which directly impacts the dynamic response. The results also show that the angular velocity effect in the flap-wise direction is more significant than its effect in the edge-wise direction.

Muscle atrophy is a severe clinical problem involving the loss of muscle mass and strength that frequently accompanies the development of numerous types of cancer, including pancreatic, lung and gastric cancers. Cancer cachexia is a multifactorial syndrome characterized by a continuous decline in skeletal muscle mass that cannot be reversed by conventional nutritional therapy. The pathophysiological characteristic of cancer cachexia is a negative protein and energy balance caused by a combination of factors, including reduced food intake and metabolic abnormalities. Numerous necessary cellular processes are disrupted by the presence of abnormal metabolites, which mediate several intracellular signaling pathways and result in the net loss of cytoplasm and organelles in atrophic skeletal muscle during various states of cancer cachexia. Currently, the clinical morbidity and mortality rates of patients with cancer cachexia are high. Once a patient enters the cachexia phase, the consequences are difficult to reverse and the treatment methods for cancer cachexia are very limited. The present review aimed to summarize the recent discoveries regarding the pathogenesis of cancer cachexia‑induced muscle atrophy and provided novel ideas for the comprehensive treatment to improve the prognosis of affected patients.

Electric arc furnace (EAF) slag aggregate, a waste by-product of the steel industry, exhibited a high potential for phosphorus (P) removal and had attracted considerable attention. The main objectives of this study were to evaluate the performance of using EAF slag aggregate as an adsorbent for P removal and identify its P removal capacity. A series of batch tests showed that P removal capacity of EAF slag increases gradually with the increase of pH with a range of 2-10, while the highest P removal capacity (1.94 mg/g) can be obtained at pH 12. The adsorption kinetics of P on EAF slag can be described by pseudo-second-order kinetic equations. Isothermal adsorption simulations showed that the best fitted model was the Freundlich model with a correlation coefficient of 0.9825. A continuous flow column experiment feeding a synthetic influent containing 15 mg P/L was operated for 60 days and the P removal efficiency was greater than 95% with a P removal capacity of 1.6 mg P/g slag. The results obtained in this study showed that EAF slag could act as an efficient adsorbent for P removal. Calcium phosphate precipitation depends on the release of Ca

Recurrent respiratory tract infection(RRTI) are one of the major health problems in children. Different degrees of immune deficiency or immaturity, as well as specific or non-specific immune dysfunction are the main causes of RRTI in children with RRTI. Immunomodulators are the most commonly used treatment. Probiotics are viable bacteria that colonize the intestine and affect the host intestinal microbial balance. Probiotics can participate in local and systemic immune regulation in a variety of ways. The aim of this review was to assess the specific impact of probiotics use on recurrent respiratory tract infection in children, the ability of live bacteria to alter intestinal microbial populations and to exert subsequent benefits for the host.

Additive manufacturing (AM) offers diversity, customisability and creativity, making it an important tool to lead Industry 4.0. Reducing the cost of prototyping, bespoke and small-scale production is some of the key advantages of 3D printing. Parts created by topology optimisation and generative design are usually easier to make by AM. Industrial sectors such as automotive, biomedical and manufacturing have begun to see AM as a cost-effective process for complex components. AM is not without its drawbacks, print failures, distortion, rough surfaces and anisotropic properties, and lack of material data is limiting the quality assurance of this technology. It is known that the mechanical properties of the printed parts are sensitive to specific AM process parameters, e.g. the printing direction to the anisotropic property. In this study, the improvement of the prospective mechanical property of a topologically optimised design of a wheel was carried out. As the mechanical load of a wheel is crucial in its application, the prospective mechanical properties of the wheel to be made by AM are investigated by using simulation so that better outcome from AM may be predicted with the customised process planning.

Kashin-Beck disease (KBD) is an endemic chronic osteochondropathy. The etiology of KBD remains unknown. In this study, we conducted an integrative analysis of genome-wide DNA methylation and mRNA expression profiles between KBD and normal controls to identify novel candidate genes and pathways for KBD. Articular cartilage samples from 17 grade III KBD patients and 17 healthy controls were used in this study. DNA methylation profiling of knee cartilage and mRNA expression profile data were obtained from our previous studies. InCroMAP was performed to integrative analysis of genome-wide DNA methylation profiles and mRNA expression profiles. Gene ontology (GO) enrichment analysis was conducted by online DAVID 6.7. The quantitative real-time polymerase chain reaction (qPCR), Western blot, immunohistochemistry (IHC), and lentiviral vector transfection were used to validate one of the identified pathways. We identified 298 common genes (such as COL4A1, HOXA13, TNFAIP6 and TGFBI), 36 GO terms (including collagen function, skeletal system development, growth factor), and 32 KEGG pathways associated with KBD (including Selenocompound metabolism pathway, PI3K-Akt signaling pathway, and TGF-beta signaling pathway). Our results suggest the dysfunction of many genes and pathways implicated in the pathogenesis of KBD, most importantly, both the integrative analysis and in vitro study in KBD cartilage highlighted the importance of selenocompound metabolism pathway in the pathogenesis of KBD for the first time.

Emerging evidence indicates that microRNAs (miRNAs) are crucial regulators of osteoblast differentiation. A previous study has reported that miR-193a-3p expression is altered during the induction of osteoblast differentiation. However, the precise biological function and regulatory mechanism of miR-193a-3p during osteoblast differentiation remains unclear. In this study, we aimed to investigate the precise role and underlying mechanism of miR-193a-3p in regulating osteoblast differentiation. The results showed that miR-193a-3p expression was significantly down-regulated during the induction of osteoblast differentiation. Functional experiments demonstrated that the overexpression of miR-193a-3p impeded osteoblast differentiation while miR-193a-3p inhibition promoted osteoblast differentiation. Bioinformatics analysis and a luciferase assay revealed that leucine-rich repeat-containing G-protein coupled receptor 4 (LGR4), a critical regulator of osteoblast differentiation, was a target gene of miR-193a-3p. We showed that miR-193a-3p negatively regulated the expression of LGR4 and activating transcription factor 4 (ATF4). Moreover, the knockdown of LGR4 or ATF4 significantly reversed the promotion effect of miR-193a-3p inhibition on osteoblast differentiation. Overall, these findings demonstrate that miR-193a-3p regulates osteoblast differentiation by modulating LGR4/ATF4 signaling and suggests that the miR-193a-3p/LGR4/ATF4 regulation axis may play an important role in regulating bone remodeling.

Purpose This paper aims to develop and estimate a logit model of whether homeownership could be promoted by participation in and use of the Housing Provident Fund (HPF) program, with a focus on factors that influence the use of HPF loans. Design/methodology/approach This paper develops and estimates a logit model of whether homeownership could be promoted by participation in and use of the HPF program, with a focus on factors that influence the use of HPF loans. Findings The results show that coefficients of marital status, educational level, age, duration of employment and employer are significantly related to the use of HPF loan for homeownership. Research limitations/implications Because of the chosen research approach, the research results may lack generalizability. Practical implications The research findings provide a better understanding of homeowners’ characteristics. Originality/value To manage the HPF program effectively, it is important for government to have a better understanding of the underlying demand for homeownership, especially with respect to the different demographic variables and accessibility to HPF loans and the HPF.

To attempt to solve the disposal problems of sewage sludge (SS) and river sediment (RS), these two types of sludge waste were used as the main raw materials for lightweight aggregate (LWA). SiO2 and Al2O3 are the main inorganic oxides of SS and RS. Little is known about their effects on LWA performance, although they are known to contribute to the formation of the basic skeleton structure. The main objective of this research was to systematically evaluate the effects of variations in SiO2 and Al2O3 content on characteristics of LWA, including physical characteristics, morphological structures, crystal phases, and stabilization of heavy metals. Our studies showed that LWA with the highest compressive strength, lowest porosity, and best solidification of heavy metals can be obtained with a SiO2 content between 30% and 45% and an Al2O3 content between 11% and 19%. Heavy metals were encapsulated within the aluminosilicate matrix structure when LWA pellets were sintered at 1100 °C, indicating that harmful heavy metals can be solidified safely within LWA to increase the security, stability, and reliability of its application. Experimental results illustrated that SiO2 and Al2O3 are potentially crucial parameters that can control the physicochemical properties of LWA.

Optically-acquired data, typically from digital image correlation, is increasingly being used in the area of structural dynamics, particularly modal testing and damage identification. One of the problems with such data is its extremely large size. Single images regularly extend to tens or even hundreds of thousands of data points and many thousands of images may be required for a vibration test. Such data must be stored and transmitted efficiently for later remote reconstruction and analysis, typically operational modal analysis. It is this requirement that is addressed in the research presented in this paper. This research builds upon previous work whereby digitised optical data was projected onto an orthogonal basis with coefficients (shape descriptors) of either greater or lesser significance; those deemed to be insignificant, according to a chosen threshold being removed. Data reduction by a combination of shape-descriptor decomposition and compressed-sensing is applied to an industrial printed circuit board and reconstructed for operational modal analysis by l 1 optimisation.

This study investigates the effect of demographic factors on formal and informal borrowing households in rural Fujian Province. The study tests whether credit constraint affects rural farmers&rsquo, welfare in the studied region, using a probit regression and endogenous switching regression model to analyse data collected in 2017 from 960 farm households. Analysis shows that age, poverty, household size, and farmland size operate to constrain credit in formal borrowing. Results also indicate that level of education, farm land size and age have significant impacts on rural household borrowing from informal sources. The results from the endogenous switching model approach suggest that credit constraint does have a significant impact on rural farmers&rsquo, consumption and welfare in Fujian province.

This paper investigates the effects of rural households&rsquo, demographic characteristics on formal credit constraint, and explores the relationship between informal and formal lending in rural China. Using 2013 China&rsquo, s Household Finance survey data, the authors apply probit regression models to investigate the effects of demographic factors on formal credit constraint and the household&rsquo, s decision to borrow from informal credit sources. In addition, the endogenous switching regression model is applied to evaluate the impact of credit constraint on the welfare of rural farm households. The empirical evidence confirms that age, family size, annual household nonagricultural income, level of education, and history of informal borrowing have significant influence over credit constraint. Moreover, annual household nonagricultural income, the presence of children, borrowing from social networks and monthly communication expenses significantly impact rural households&rsquo, decision to utilise informal borrowing. Results from the endogenous switching regression model suggest that credit constraint by formal credit sources has no impact on household consumption.

The aim of the present study was to determine whether hyaluronic acid (HA) or physical therapy agents (PTA) can improve functional parameters in patients with knee Kashin-Beck disease (KBD). For 2 years, patients (n=55) were treated with HA weekly for 5 weeks, then received 6th and 7th injections on the 3rd and 6th month, respectively, for 7 injections in total. Patients (n=53) were treated with PTA five times a week for 3 weeks every month for 6 months. The patients were evaluated with the Western Ontario and McMaster University Osteoarthritis Index (WOMAC) and the visual analog pain scale (VAS). Trial registration, ChiCTR-TRC-12002189 (http://www.chictr.org/). During the study, following treatment interruption, pain increased in the PTA group (from a mean value of 85.7±83.8 mm at month 12 to 145.2±128.8 mm at month 18 and 201.3±150.5 mm at month 24), while it remained stable in the HA group (from a mean value of 80.7±70.6 mm at month 12 to 90.1±95.2 mm at month 18 and 82.6±85.3 mm at month 24), with a statistically significant difference in favor of HA at month 18 (P

Filtering with a syringe filter is a common operation in pharmaceutical analysis. Ophthalmic research often has a limited amount of sample and low amount of drug which is vulnerable to filtering membrane adsorption loss but not well recognized in the research community. Current study investigated drug adsorption by 11 types of syringe filters for 4 hydrophobic compounds commonly encountered in transscleral drug delivery. Among the 11 types of syringe filters surveyed, polytetrafluoroethylene - NBA, polytetrafluoroethylene - NLA, and polypropylene filters caused the least adsorptive drug loss for these four drugs studied. The magnitude of drug adsorption was filter- and drug-specific. Polytetrafluoroethylene-NLA caused the least adsorptive loss (1%) for triamcinolone acetonide, polytetrafluoroethylene-NBA caused the least adsorptive loss (5.4%) for diclofenac, and polypropylene caused the least adsorptive loss for cyclosporine A, 16.8% on average. Tacrolimus had the least adsorptive loss to the filters of polytetrafluoroethylene - NLA and polypropylene; however, the percentage of adsorptive loss from filtration was the highest (32% loss in average) among the four drugs surveyed. CONCLUSION: Low drug concentrations as seen in samples from ophthalmic researches are vulnerable to filtration drug loss. Selecting the right filter via validation is critical to avoid underestimating the drug level and distorting the resultant distribution/clearance profile in the ocular pharmacokinetic analysis.

3'-Phosphoadenosine 5'-phosphosulfate synthetase 2 (PAPSS2) has been shown to be important in the development of normal skeletal structure. The aim of the present study was to evaluate the role of PAPSS2 in the differentiation of chondrocytes as well as their mechanisms. Using RNA interference-mediated via a lentivirus and a retrovirus, PAPSS2 gene silence and overexpression in ATDC5 chondrogenic cells were performed. Chondrocyte differentiation and chondrogenic-related gene markers associated with extracellular matrix formation were noted. The mRNA and protein expression for Wnt4, β-catenin and SOX9 genes were observed. The PAPSS2 transcript expression levels progressively decline in ATDC5-induced chondrocyte-like cells during differentiation. Silencing of PAPSS2 expression had a significantly attenuating effect on cell differentiation and decreased expression of collagen II and X. In contrast, over-expression of PAPSS2 promoted the differentiation of ATDC5 chondrogenic cells. The mRNA expression levels of Wnt4 and SOX9 decreased significantly in PAPSS2 knock down cells vs. control cells. However, this expression was increased in the cells over-expressing PAPSS2. These data indicate that PAPSS2 regulates aggrecan activity as well as cell differentiation. The findings favor a mechanism by which PAPSS2 induces differentiation in ATDC5 cells via direct regulation of early signaling events that promote formation of collagenous matrix components. This control is probably mediated via extracellular matrix formation Wnt/β-catenin signaling pathways.

Osteoporosis (OS) is one of the most common healthy problems characterized by low bone mass. Osteoclast, the primary bone-resorbing cell, is responsible for destructive bone diseases including osteoporosis (OS). Cryptotanshinone (CTS), an active component extracted from the root of Salvia miltiorrhiza bunge, has been shown to prevent the destruction of cartilage and the thickening of subchondral bone in mice osteoarthritis models. However, its molecular mechanism in osteoclastogenesis needs to be determined. The aim of the current study was to explore the effect of CTS on osteoclastogenesis and further evaluate the underlying mechanism. Our results showed that CTS inhibited receptor activator of NF-κB ligand (RANKL)-induced the increase in tartrate-resistant acid phosphatase (TRAP) activity in bone marrow-derived macrophages (BMMs). In addition, the expressions of osteoclastogenesis-related marker proteins and nuclear factor of activated T-cells (NFAT) activation were suppressed by CTS treatment in BMMs. Furthermore, CTS attenuated RANKL-induced ERK phosphorylation and NF-κB activation in BMMs. These findings indicated that CTS inhibited RANKL-induced osteoclastogenesis by inhibiting ERK phosphorylation and NF-κB activation in BMMs. Thus, CTS may function as an inhibitor of osteoclastogenesis and may be considered as an alternative medicine for the prevention and treatment of OS.

The extraction of useful information and removal of redundant noise from data has become a major research topic in recent years. Data compression is necessary for all kinds of analysis, and the demand for efficient compression techniques has gained much attention. Digital image correlation is a camera-based measuring system, which has been widely applied in strain analysis because of the convenience of measuring displacement fields by simply selecting a region of interest. Currently, there is interest in applying such methods to engineering structures in dynamics. However, one of the major issues related to the integration of camera-based systems with dynamic measurement is the generation of huge amounts of data, typically extending to many thousands of data points, because of the requirements of high sampling rate, spatial resolution, and long duration of recording. In this paper a new algorithm is presented that addresses the need for efficiency in full-field data processing. By making use of the data itself and combining the concept of sparse representation with Gram-Schmidt orthogonalisation, the number of basis function used to represent the data can be reduced and a concise decomposition established. In both simulated and experimental cases, the compression ratios for data size and number of signals used in operational modal analysis are substantially diminished, thereby demonstrating the effectiveness of the proposed algorithm. A reduced number of new basis functions is determined for the representation of data under the condition that the reconstructed displacement map reproduces the raw measured data to within a chosen threshold on the coefficient of correlation.

A full-field Digital Image Correlation (DIC) method with integrated Kriging regression is presented in this article. The displacement field is formulated as a best linear unbiased model that includes the correlations between all the locations in the Region of Interest (RoI). A global error factor is employed to extend conventional Kriging interpolation to quantify displacement errors of the control points. An updating strategy for the self-adaptive control grid is developed on the basis of the Mean Squared Error (MSE) determined from the Kriging model. Kriging DIC is shown to outperform several other full-field DIC methods when using open-access experimental data. Numerical examples are used to demonstrate the robustness of Kriging DIC to different choices of initial control points and to speckle pattern variability. Finally Kriging DIC is tested on an experimental example.

Kashin-Beck disease (KBD) is an endemic, chronic, and degenerative osteoarthropathy. Selenium (Se) deficiency plays important role in the pathogenesis of KBD. We aimed to screen Se-related gene from chondrocytes of patients with KBD. Whole-genome oligonucleotide microarrays were used to detect differentially expressed genes. qRT-PCR was used to confirm the microarray results. Comparative Toxicogenomics Database (CTD) was used to screen Se-related genes from differentially expressed genes. Gene Ontology (GO) classifications and network analysis of Se-related genes were constituted by STRING online system. Three hundred ninety-nine differentially expressed genes were obtained from microarray. Among them, 54 Se-related genes were identified by CTD. The qRT-PCR validation showed that four genes expressed similarly with the ones in the microarray transcriptional profiles. The Se-related genes were categorized into 6 cellular components, 8 molecular functions, 44 biological processes, 10 pathways, and 1 network by STRING. The Se-related gene insulin-like growth factor binding protein 2 (IGFBP2), insulin-like growth factor binding protein 3 (IGFBP3), interleukin 6 (IL6), BCL2, apoptosis regulator (BCL2), and BCL2-associated X, apoptosis regulator (BAX), which involved in many molecular functions, biological processes, and apoptosis pathway may play important roles in the pathogenesis of KBD.

To explore the brain default mode network (DMN) in patients with motor aphasia resulting from cerebral infarction, we used resting state functional magnetic resonance imaging (fMRI) to investigate the possible neural mechanism. Thirteen patients with motor aphasia resulting from cerebral infarction and ten matched controls were selected in this study. All subjects were examined using resting state fMRI. We chose the posterior cingulate cortex as the region of interest and then used functional connectivity analysis to calculate the DMN functional connectivity and analyze differences in the functional connectivity between the two groups. Compared with normal controls, aphasia patient group showed a significantly decreased functional connectivity in bilateral medial frontal gyrus, superior frontal gyrus, middle frontal gyrus, middle temporal gyrus, precuneus and cuneus. The aphasia patient group showed increased functional connectivity mainly in bilateral medial frontal gyrus, middle frontal gyrus, inferior frontal gyrus, precentral gyrus, insula. The DMN in cerebral infarction motor aphasia patients showed significantly decreased functional connectivity in the resting state. The DMN most likely plays an important role in motor aphasia resulting from cerebral infarction. Furthermore, functional connectivity in the brain regions surrounding the left and right Broca’s areas was significantly enhanced due to compensatory mechanisms. This may be helpful for the recovery of language function in cerebral infarction patients with motor aphasia.

This article presents a methodology for the treatment of uncertainty in nonlinear, interference-fit, stress analysis problems arising from manufacturing tolerances. Image decomposition is applied to the uncertain stress field to produce a small number of shape descriptors that allow for variability in the location of high-stress points when geometric parameters (dimensions) are changed within tolerance ranges. A meta-model, in this case based on the polynomial chaos expansion, is trained using a full finite element model to provide a mapping from input geometric parameters to output shape descriptors. Global sensitivity analysis using Sobol’s indices provides a design tool that enables the influence of each input parameter on the observed variances of the outputs to be quantified. The methodology is illustrated by a simplified practical design problem in the manufacture of automotive wheels.

A composite bonnet liner subject to a high-velocity (70 m/s), low-energy ( 2 bonnet at 0.2 ms increments for 0.1 s, that is, 500 datasets, and the results have been compared to those predicted by finite element analysis. Image decomposition was utilised to reduce the dimensionality of both datasets by representing them using adaptive geometric moment descriptors; these descriptors were used to perform quantitative comparisons of the datasets and to test the validity of the model based on all the available data. The model was found to be a good representation of the physical experiment during the first half of the impact event but a less good representation in the remainder of the test, probably because damping effects were not adequately incorporated into the simulation. The methodologies for data comparison and evaluation of model validity proposed and demonstrated in this study represent a significant advance in procedures for ensuring model fidelity and for creating model credibility in the simulation of dynamic engineering events.