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Abstract Therapeutic resistance represents a bottleneck to treatment in advanced gastric cancer (GC). Ferroptosis is an iron-dependent form of non-apoptotic cell death and is associated with anti-cancer therapeutic efficacy. Further investigations are required to clarify the underlying mechanisms. Ferroptosis-resistant GC cell lines are constructed. Dysregulated mRNAs between ferroptosis-resistant and parental cell lines are identified. The expression of SOX13/SCAF1 is manipulated in GC cell lines where relevant biological and molecular analyses are performed. Molecular docking and computational screening are performed to screen potential inhibitors of SOX13. We show that SOX13 boosts protein remodeling of electron transport chain (ETC) complexes by directly transactivating SCAF1. This leads to increased supercomplexes (SCs) assembly, mitochondrial respiration, mitochondrial energetics and chemo- and immune-resistance. Zanamivir, reverts the ferroptosis-resistant phenotype via directly targeting SOX13 and promoting TRIM25-mediated ubiquitination and degradation of SOX13. Here we show, SOX13/SCAF1 are important in ferroptosis-resistance, and targeting SOX13 with zanamivir has therapeutic potential.

ABSTRACT: Goose astrovirus (GoAstV) is an emerging avian pathogen that induces gout in goslings with a mortality of up to 50%. Organ damage caused by GoAstV infection was considered the cause of gout, but it is still unclear whether other factors are involved. Human and murine studies have linked the gut microbiome-derived urate and gout, thus we hypothesized that gut microbiome may also play an important role in gout induced by GoAstV infection. This study tested the pathogenicity of our isolated GoAstV genotype 2 strain on goslings, while the appearance of clinical signs, histopathological changes, viral distribution and the blood level of cytokines were monitored for 18 d postinfection (dpi). The dynamics in the gut microbiome were profiled by 16S sequencing and then correlated with GoAstV infection. Results showed that this study successfully developed an experimental infection model for studying the pathogenicity of the GoAstV infection which induces typical symptoms of gout. GoAstV infection significantly altered the gut microbiome of goslings with the enrichment of potential proinflammatory bacteria and depletion of beneficial bacteria that can produce short-chain fatty acids. More importantly, the microbial pathway involved in urate production was significantly increased in goslings infected with GoAstV, suggesting that gut microbiome-derived urate may also contribute to the gout symptoms. Overall, this study demonstrated the role of gut microbiome in the pathogenesis of GoAstV infection, highlighting the potential of gut microbiome-based therapeutics against gout symptoms.

Background: Gout is the most common inflammatory arthritis in adults. Gout is an arthritic disease caused by the deposition of monosodium urate crystal (MSU) in the joints, which can lead to acute inflammation and damage adjacent tissue. Hyperuricemia is the main risk factor for MSU crystal deposition and gout. With the increasing burden of gout disease, the identification of potential biomarkers and novel targets for diagnosis is urgently needed. Methods: For the analysis of this subject paper, we downloaded the human gout data set GSE160170 and the gout mouse model data set GSE190138 from the GEO database. To obtain the differentially expressed genes (DEGs), we intersected the two data sets. Using the cytohubba algorithm, we identified the key genes and enriched them through GO and KEGG. The gene expression trends of three subgroups (normal control group, intermittent gout group and acute gout attack group) were analyzed by Series Test of Cluster (STC) analysis, and the key genes were screened out, and the diagnostic effect was verified by ROC curve. The expression of key genes in dorsal root nerve and spinal cord of gout mice was analyzed. Finally, the clinical samples of normal control group, hyperuricemia group, intermittent gout group and acute gout attack group were collected, and the expression of key genes at protein level was verified by ELISA. Result: We obtained 59 co-upregulated and 28 co-downregulated genes by comparing the DEGs between gout mouse model data set and human gout data set. 7 hub DEGs(IL1B, IL10, NLRP3, SOCS3, PTGS2) were screened out via Cytohubba algorithm. The results of both GO and KEGG enrichment analyses indicate that 7 hub genes play a significant role in regulating the inflammatory response, cytokine production in immune response, and the TNF signaling pathway. The most representative hub genes SOCS3 and PTGS2 were screened out by Series Test of Cluster, and ROC analysis results showed the AUC values were both up to 1.000. In addition, we found that PTGS2 expression was significantly elevated in the dorsal root ganglia and spinal cord in monosodium urate(MSU)-induced gout mouse model. The ELISA results revealed that the expression of SOCS3 and PTGS2 was notably higher in the acute gout attack and intermittent gout groups compared to the normal control group. This difference was statistically significant, indicating a clear distinction between the groups. Conclusion: Through cross-species comprehensive analysis and experimental verification, SOCS3 and PTGS2 were proved to be new biomarkers for diagnosing gout and predicting disease progression.

To address the extended development cycle, high costs, and maintenance difficulties associated with existing microgravity simulation methods, this study has developed a semi-physical simulation platform for robotic arms tailored to different gravity environments and loading conditions. The platform represents difficult-to-model joints as physical objects, while the easily modeled components are simulated based on principles of similarity. In response to the strong coupling, nonlinearity, and excess force disturbance issues in the electric variable load loading system, a fractional-order linear active disturbance rejection control algorithm was employed. The controller parameters were tuned using an improved particle swarm algorithm with modified weight coefficients, and experimental results demonstrate that a fractional-order linear active disturbance rejection control improves response speed and disturbance rejection performance compared to linear sliding mode control. The study investigated the differences in the drive force of joint motors in space robotic arms under varying gravity environments and loading conditions. Experimental results indicate that load torque is the primary influencing factor on joint motor drive force, while radial force serves as a secondary influencing factor. Additionally, when the axis of the joint motor is perpendicular to the ground, it can, to some extent, simulate microgravity conditions on the ground.

Background. Mild cognitive impairment (MCI), an intermediate stage between normal aging and dementia, has emerged as a prominent research area in geriatric care due to its heightened propensity for progressing toward dementia. Sleep plays a pivotal role in cognitive function, with dyssomnias not only exacerbating cognitive and affective symptoms associated with neurodegenerative diseases but also contributing to disease progression. Aim. This bibliometric analysis investigates the global research on MCI with dyssomnias over the past two decades, aiming to discern key findings, research domains, and emerging trends in this field. Methods. In this study, a bibliometric analysis was conducted using the search terms “MCI” and “sleep”. Data were extracted from the Web of Science Core Collection database, and visualization and collaborative analysis were performed using CiteSpace and VOSviewer. Results. This study encompassed 546 publications from 2003 to 2023. The publication volume and citation rate consistently increased over time. Neurosciences, Clinical Neurology, and Geriatrics Gerontology emerged as the top three research fields. The Journal of Alzheimer’s Disease had the highest publication count, while Sleep Medicine received the most citations. USA, China, and Italy led in publication output. Collaborative clusters among authors and institutions were identified, but cooperation between clusters was limited. Active cocited reference clusters included “obstructive sleep apnea”, “possible mediating pathways”, and “isolated rapid eye movement sleep behaviour disorder”. The top frequently mentioned keywords, besides “MCI”, were “Alzheimer’s disease”, “dementia”, “risk factor”, and “Parkinson’s Disease”. Notable keyword clusters spanned circadian rhythm, Parkinson’s disease, MCI, dementia with Lewy body, subjective cognitive impairment, Lewy body disease, Alzheimer’s disease, and dietary patterns. Conclusion. The field of MCI with dyssomnias is rapidly expanding, encompassing a wide range of neurodegenerative disorders and sleep disturbances. Current research endeavors are primarily focused on elucidating the underlying pathogenesis, predicting disease progression, and developing innovative treatment strategies for individuals affected by MCI with dyssomnias.

Abstract Introduction Triple-negative breast cancer (TNBC) is currently the most malignant subtype of breast cancer without effective targeted therapies. DNAJB4 (Dnaj heat shock protein family (Hsp40) member B4) is a member of the human heat shock protein family (Hsp40). The clinical significance of DNAJB4 in breast cancer has been reported in our previous study. However, the biological function of DNAJB4 in TNBC cell apoptosis remains unclear to date. Methods The expression of DNAJB4 in normal breast cells, breast cancer cells, four-paired TNBC tissues, and adjacent noncancerous tissues was quantified by quantitative real-time polymerase chain reaction (qRT-PCR) and western blot assay. The role of DNAJB4 in TNBC cell apoptosis was investigated using a number of gain- and loss-of-function in vitro and in vivo assays. The underlying molecular mechanisms in TNBC cell apoptosis were elucidated via Western blot assay. Results DNAJB4 expression was significantly downregulated in TNBC tissues and cell lines. DNAJB4 knockdown inhibited TNBC cell apoptosis and promoted tumorigenicity in vitro and in vivo, but DNAJB4 overexpression resulted in the opposite. Mechanically, DNAJB4 knockdown inhibited TNBC cell apoptosis through suppression of the Hippo signaling pathway, and the result was reversed after DNAJB4 overexpression. Conclusions DNAJB4 promotes TNBC cell apoptosis by activating the Hippo signaling pathway. Therefore, DNAJB4 may act as a prognostic biomarker and therapeutic target for TNBC.

Abstract Background Uterine corpus endometrial carcinoma (UCEC) is the most common female pelvic malignancy worldwide. N6-methyladenosine (m6A) plays an important role in various cellular responses, especially in cancer progression. However, the correlation between prognostic UCEC and m6A RNA methylation regulators remains unclear. Methods We used The Cancer Genome Atlas (TCGA) to provide a gene signature that could improve the prognostic evaluation of UCEC patients according to the distinct genetic trait of m6A RNA methylation regulators from a bioinformatics perspective. After comparing UCEC subgroups with different genetic profiles of m6A regulators, we identified 71 differentially expressed genes associated with overall survival (OS) and generated a nine-gene signature through least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Finally, we used in vitro and in vivo tumor cell experiments as well as the immune correlation analysis to verify the function of each gene in the proposed gene signature. Results Time-dependent receiver operating characteristic (ROC) curves revealed that the proposed gene signature could predict the outcome of UCEC patients accurately. We found that CDKN2A mainly acted from the perspective of tumor cells, while COL4A4, PXDN, TIGIT, CHODL, LMO3, KCNJ12, L1CAM, and EPHB1 might play a role in UCEC from an immunological point of view. Conclusions From an epigenetics perspective, the m6A RNA methylation regulator-based gene signature can predict the prognosis of UCEC patients and immune therapeutic efficacy.

In this article, a relationship between the electron beams in a longitudinal constant magnetic field and light beams in a parabolic refractive index distribution medium is revealed and demonstrated analytically. We propose a new method to work out the properties of the singularity in that analytical expression and have a discussion on some universal features of electron beams in a longitudinal constant magnetic field. Based on the theories above, we introduce a new type of structured electron beams, which is the Airy transform of electron Landau states (ATLSs). We not only study the dynamic of ATLSs and the magnetic field analytically and numerically but also carry out the movement of centroid and the dual auto-focusing property of ATLSs. Moreover, we have a discussion on the influence on ATLSs of Airy control parameters and the parameters of electron Landau states.

The allocation of biogas between power generation and heat supply in traditional kitchen waste power generation system is unreasonable; for this reason, a biogas prediction method based on feature selection and heterogeneous model integration learning is proposed for biogas production predictions. Firstly, the working principle of the biogas generation system based on kitchen waste is analyzed, the relationship between system features and biogas production is mined, and the important features are extracted. Secondly, the prediction performance of different individual learner models is comprehensively analyzed, and the training set is divided to reduce the risk of overfitting by combining K-fold cross-validation. Finally, different primary learners and meta learners are selected according to the prediction error and diversity index, and different learners are fused to construct the stacking ensemble learning model with a two-layer structure. The experimental results show that the research method has a higher prediction accuracy in predicting biogas production, which provides supporting data for the economic planning of kitchen waste power generation systems.

The integration of large-scale wind power into the power grid threatens the stable operation of the power system. Traditional wind power prediction is based on time series without considering the variability between wind turbines in different locations. This paper proposes a wind power probability density prediction method based on a time-variant deep feed-forward neural network (ForecastNet) considering a spatio-temporal distribution. First, the outliers in the wind turbine data are detected based on the isolated forest algorithm and repaired through Lagrange interpolation. Then, based on the graph attention mechanism, the features of the proximity node information of the individual wind turbines in the wind farm are extracted and the input feature matrix is constructed. Finally, the wind power probability density prediction results are obtained using the ForecastNet model based on three different hidden layer variants. The experimental results show that the ForecastNet model with a hidden layer as a dense network based on the attention mechanism (ADFN) predicts better. The average width of the prediction intervals at achieved confidence levels for all interval coverage is reduced by 34.19%, 35.41%, and 35.17%, respectively, when compared to the model with the hidden layer as a multilayer perceptron. For different categories of wind turbines, ADFN also achieves relatively narrow interval average widths of 368.37 kW, 315.87 kW, and 299.13 kW, respectively.

Hybrid neural networks combine advantages of spiking and artificial neural networks in the context of computing and biological motivation. The authors propose a design framework with hybrid units for improved flexibility and efficiency of hybrid neural networks, and modulation of hybrid information flows.

Wetland is a transitional area where terrestrial ecosystems and aquatic ecosystems interact and influence each other, and it is an important ecosystem on the Earth’s surface. Due to the special characteristics of wetland ecology, the decomposition of wetland plant litter is slightly different from litter in forests, grasslands, and meadows and other traditional areas. The role of litter mineralization in the wetland ecological C cycle and the functional role of plant litter have been neglected. This study analyzes the decomposition mechanism and decomposition model of wetland litter material and focuses on the effects of the decomposition process of wetland litter material on the structure of the soil fauna community, decomposition of soil organic matter, sediment properties, and the dynamic changes in the C cycle of the biological system by combining domestic and international studies from recent years. Finally, we propose that the direction of future research on wetland litter decomposition should be to reveal the mechanism of wetland biodiversity and ecology, as well as the ecological correlation between aboveground and belowground biodiversity, with a view to providing a decision-making basis for wetland phytoremediation and wetland wastewater treatment.

Approximately 22 nucleotide-long non-coding small RNAs (ncRNAs) play crucial roles in physiological and pathological activities, including microRNAs (miRNAs). Long ncRNAs often stay in the cytoplasm, modulating post-transcriptional gene expression. Briefly, miRNA binds with the target mRNA and builds a miRNA-induced silencing complex to silence the transcripts or prevent their translation. Interestingly, data from recent animal and plant studies suggested that mature miRNAs are present in the nucleus, where they regulate transcriptionally whether genes are activated or silenced. This significantly broadens the functional range of miRNAs. Here, we reviewed and summarized studies on the functions of nuclear miRNAs to better understand the modulatory networks associated with nuclear miRNAs.

Origami is an ancient art form and can be divided into rigid and non-rigid origami. Rigid origami is suitable for the design of building structures because the panels are not twisted and deformed during the folding process. Currently, rigid origami structures are generally built with steel. However, compared with natural, non-polluting wood, steel has a high energy consumption and a high environmental impact. Based on this situation, this paper designs a developable wooden building structure using the Yoshimura origami model. First, the Jacobian matrix method was used to analyze the degree of freedom of the basic unit of the Yoshimura origami pattern, following which the motion trajectory required by the target structure was obtained. Secondly, by analyzing the relationship between the plane angle α and dihedral angle θ, three interaction rules were obtained, and the formula for determining the structure size was established by using the plane angle α, dihedral angle θ, the number of valley folds n and the unit length l. Subsequently, two enhancement schemes, the quadrangle enhancement scheme and the triangle enhancement scheme, were proposed to increase the height of the structure. After comparing the deformation and failure types of origami structures based on Cross-Laminated Timber, a triangular reinforcement scheme was chosen to increase the height of the structure. Finally, a new connection method was developed that allowed the origami structure to be practically applied. This research demonstrates the possibility of developing a timber structure based on Yoshimura origami.

Autism spectrum disorder (ASD) is a lifelong neurodevelopmental disease, and its diagnosis is dependent on behavioral manifestation, such as impaired reciprocal social interactions, stereotyped repetitive behaviors, as well as restricted interests. However, ASD etiology has eluded researchers to date. In the past decades, based on strong genetic evidence including mutations in a single gene, gene editing technology has become an essential tool for exploring the pathogenetic mechanisms of ASD via constructing genetically modified animal models which validates the casual relationship between genetic risk factors and the development of ASD, thus contributing to developing ideal candidates for gene therapies. The present review discusses the progress in gene editing techniques and genetic research, animal models established by gene editing, as well as gene therapies in ASD. Future research should focus on improving the validity of animal models, and reliable DNA diagnostics and accurate prediction of the functional effects of the mutation will likely be equally crucial for the safe application of gene therapies.

This study aimed to investigate the association between air pollutants and methylation of peripheral brain-derived neurotrophic factor (BDNF) promoters. A total of 101 individuals were recruited in this panel study. BDNF promoter methylation was detected by bisulfite-PCR amplification and pyrosequencing. Participants’ exposure to air pollutants was estimated using a satellite-based random forests approach. A generalized estimated equation model with natural cubic splines was employed to examine the associations between air pollutants and BDNF promoter methylation levels. The associations between air pollution and BDNF promoter methylation showed nonlinear curves with threshold effects. The threshold concentration for the association of nitrogen dioxide (NO2) with average methylation level was 59.7 μg/m3, and that for the association of particulate matter ≤ 1 µm in diameter (PM1) with CpG2 methylation level was 70.9 μg/m3. The percent change of average methylation level at the 95th percentile of NO2 against the threshold concentration was 43.25% (95%CI: 13.10%, 73.40%), and that of CpG2 methylation at the 95th percentile of PM1 was 128.29% (95%CI: 43.27%, 213.31%). Overall, long-term exposures of PM1, PM2.5, PM10, and NO2 were associated with significant changes in BDNF promoter methylation levels with threshold effects.

ObjectiveTo screen and analyze the genetic mutations in the PPP1CB gene in a patient with Noonan syndrome with loose anagen hair-2 (NSLH2) in Yunnan Province, China and explore the possible molecular pathogenesis.MethodsAfter obtaining informed consent, we collected the patient's medical history and carried out physical and laboratory examinations for the NSLH2 proband and the family members. Genomic DNA was extracted from the peripheral blood of all individuals. The coding regions including all pathogenic exons, parts of introns, and promoters of genes were sequenced by next-generation sequencing. Pathogenic mutations, which were detected in the probands and their parents, were verified by Sanger sequencing.ResultsThe clinical manifestations of NSLH2 included prominent forehead, yellowish hair, slightly wide eye distance, sparse eyebrows, bilateral auricle deformity, reduced muscle tension, and cardiac and visual abnormalities. The proband carried a c.371A>G mutation in exon 3 of PPP1CB, which is a missense mutation. This was a de novo mutation as the parents of the proband showed no mutation at this site.ConclusionIn this study, we identified a novel mutation of PPP1CB, which enriched the mutation spectrum of the PPP1CB gene and provided a basis for the diagnosis of NSLH2.

Aqueous zinc ion batteries (AZIBs) are promising electrochemical energy storage devices due to their high theoretical specific capacity, low cost, and environmental friendliness. However, uncontrolled dendrite growth poses a serious threat to the reversibility of Zn plating/stripping, which impacts the stability of batteries. Therefore, controlling the disordered dendrite growth remains a considerable challenge in the development of AZIBs. Herein, a ZIF-8-derived ZnO/C/N composite (ZOCC) interface layer was constructed on the surface of the Zn anode. The homogeneous distribution of zincophilic ZnO and the N element in the ZOCC facilitates directional Zn deposition on the (002) crystal plane. Moreover, the conductive skeleton with a microporous structure accelerates Zn2+ transport kinetics, resulting in a reduction in polarization. As a result, the stability and electrochemical properties of AZIBs are improved. Specifically, the ZOCC@Zn symmetric cell sustains over 1150 h at 0.5 mA cm−2 with 0.25 mA h cm−2, while the ZOCC@Zn half-cell achieves an outstanding Coulombic efficiency of 99.79% over 2000 cycles. This work provides a simple and effective strategy for improving the lifespan of AZIBs.

PurposeThe magnetic resonance imaging (MRI) findings may overlap due to the complex content of parotid gland tumors and the differentiation level of malignant tumor (MT); consequently, patients may undergo diagnostic lobectomy. This study assessed whether radiomics features could noninvasively stratify parotid gland tumors accurately based on apparent diffusion coefficient (ADC) maps.MethodsThis study examined diffusion-weighted imaging (DWI) obtained with echo planar imaging sequences. Eighty-eight benign tumors (BTs) [54 pleomorphic adenomas (PAs) and 34 Warthin tumors (WTs)] and 42 MTs of the parotid gland were enrolled. Each case was randomly divided into training and testing cohorts at a ratio of 7:3 and then was compared with each other, respectively. ADC maps were digitally transferred to ITK SNAP (www.itksnap.org). The region of interest (ROI) was manually drawn around the whole tumor margin on each slice of ADC maps. After feature extraction, the Synthetic Minority Oversampling TEchnique (SMOTE) was used to remove the unbalance of the training dataset. Then, we applied the normalization process to the feature matrix. To reduce the similarity of each feature pair, we calculated the Pearson correlation coefficient (PCC) value of each feature pair and eliminated one of them if the PCC value was larger than 0.95. Then, recursive feature elimination (RFE) was used to process feature selection. After that, we used linear discriminant analysis (LDA) as the classifier. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance of the ADC.ResultsThe LDA model based on 13, 8, 3, and 1 features can get the highest area under the ROC curve (AUC) in differentiating BT from MT, PA from WT, PA from MT, and WT from MT on the validation dataset, respectively. Accordingly, the AUC and the accuracy of the model on the testing set achieve 0.7637 and 73.17%, 0.925 and 92.31%, 0.8077 and 75.86%, and 0.5923 and 65.22%, respectively.ConclusionThe ADC-based radiomics features may be used to assist clinicians for differential diagnosis of PA and WT from MTs.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that can lead to severe social behavioral difficulties, which mainly manifests as social communication and interaction disorders; narrow interests; and repetitive, stereotyped behaviors. In recent years, the prevalence of ASD has increased annually, and it has evolved from a rare disease to one with a high incidence among childhood developmental disorders. The pathogenesis of ASD is considered to be the interaction of genetic and environmental factors. There is increasing evidence that vitamin D deficiency in pregnancy and early childhood can lead to the occurrence of ASD. Studies have demonstrated that vitamin D intervention can significantly improve the symptoms of ASD, but the underlying mechanism is still unclear. Therefore, exploring the neuroprotective mechanism of vitamin D against ASD is a huge challenge currently being worked on by current basic and clinical researchers, a task which is of great significance for the clinical promotion and optimization of vitamin D in the treatment of ASD. To further clarify the relationship between vitamin D and ASD, this review summarizes the correlation between vitamin D level and ASD, the effects of vitamin D supplementation on ASD, the possible mechanism of vitamin D involved in ASD, and insights from ASD animal models.

Renal cell carcinoma (RCC) recurs frequently due to high metastatic spread, resulting in a high mortality. Cancer stem cells play a critical role in initiating the tumor metastasis. Inhibitor of growth 4 (ING4) is a member of the ING family, but its impact on cancer stem cells in RCC is still unknown. In this study, we found that ING4 significantly promoted the sphere-forming size and number of RCC cells under an ultralow-attachment culture condition in vitro, tumor growth and metastasis in vivo, and the expression of some stem-like or pluripotent biomarkers CD44, MYC, OCT4, and NANOG, indicating that ING4 increased the stemness enrichment of RCC cells. Mechanistically, the ING4-activated p38 MAPK pathway possibly upregulated the expression of type I IFN-stimulated genes to promote the formation of RCC stem cells. ING4 could inhibit the expression of DUSP4 to activate p38 MAPK. In addition, selective pharmacological p38 MAPK inhibitors could significantly inhibit stemness enrichment only in ING4-overexpressed RCC cells, suggesting that the p38 MAPK inhibitors might be effective in patients with high ING4 expression in RCC tissue. Taken together, our findings proposed that ING4 might serve as a potential therapeutic target for metastatic RCC, particularly RCC stem cells.

The environment is one of the factors that may influence occupants’ perception of floor vibration and the assessment of floor serviceability. In this study, laboratory tests were conducted on a 3-ply CLT floor. Occupants’ assessment of the floor serviceability under human-induced vibration was investigated. Virtual reality (VR) technique was used as a research method, simulating two common environments in life. First, the correlation between the occupants’ annoyance rating and serviceability indicators (response factor and vibration dose value (VDV)) was compared with existing standards. The results show that the response factor method in ISO 10137:2007 is conservative for timber floors in both bedroom and gym environments. The VDV method in BS 6472-1:2008 can generally reflect the vibration acceptability of timber floor vibration. Then, the effect of acceleration and environment on the floor serviceability assessment was investigated through statistical methods, respectively. A weak positive correlation between the annoyance rating and the acceleration was found. The effect of the environment on floor vibration assessment was found to be significant.

A dynamic simulation model of a heliostat field and molten salt receiver system are developed on the STAR-90 simulation platform. In addition, a real-time simulation model coupling the above two models is built to study the photothermal conversion process of Delingha’s 50 MW solar power tower plant. The nonuniform and time-varying characteristics of the energy flux density on the receiver surface and the dynamic characteristics under different operating conditions are studied. The operational process of the receiver of a typical day is simulated. It was found that there was a strong positive correlation between the energy flux and DNI, and the maximum energy flux density on the surface of the heat absorbing tube panel moved from the first tube panel to the fourth in sequence from 12:00 to 18:00. At the same time, the energy flux density of the last four panels decreased gradually along the arrangement order of the panels. DNI, molten salt mass flow rate and inlet temperature step disturbance simulations are carried out, and the response curves of the molten salt outlet temperature and tube wall temperature are obtained. The conclusion of this paper has important guiding significance for the establishment of an operational strategy for photothermal coupling in a molten salt solar power tower plant.

Autism Spectrum Disorder (ASD) is a heterogeneous neurodevelopmental disorder with deficient social skills, communication deficits and repetitive behaviors. The prevalence of ASD has increased among children in recent years. Children with ASD experience more sleep problems, and sleep appears to be essential for the survival and integrity of most living organisms, especially for typical synaptic development and brain plasticity. Many methods have been used to assess sleep problems over past decades such as sleep diaries and parent-reported questionnaires, electroencephalography, actigraphy and videosomnography. A substantial number of rodent and non-human primate models of ASD have been generated. Many of these animal models exhibited sleep disorders at an early age. The aim of this review is to examine and discuss sleep disorders in children with ASD. Toward this aim, we evaluated the prevalence, clinical characteristics, phenotypic analyses, and pathophysiological brain mechanisms of ASD. We highlight the current state of animal models for ASD and explore their implications and prospects for investigating sleep disorders associated with ASD.

The tellurite 60TeO2-20PbO-(20-x)ZnO-xBaF2 (x = 1, 3, 5, 6, 7, 9, and 11) series glass samples were prepared. The samples’ SEM, XRD, DSC, density, refractive index, and absorption spectra were tested. A self-made optical platform was used to measure and calibrate the refractive index. The relationship between glass composition and crystallinity was discussed. The effects of density, molar refractive index, and metal standard value on the refractive index of glass samples were studied. The results showed that TPZBF glass has a high refractive index, and the refractive index increases with the increase in BaF2 content.

The behaviour under cyclic bending and in particular the fatigue properties of shape memory alloy (SMA) bars are important for civil engineering applications. In this paper, structural and functional fatigue is studied for both NiTi- and copper-based shape memory alloys. The results are presented from cyclic bending tests on 7 mm diameter NiTi and 12 mm diameter CuAlMn SMA bars targeted at 100,000 cycles. During the tests, dynamic loading at 1 Hz, 5 Hz, and 8 Hz was applied for different strain levels (0.5%, 1%, 2%, and 6%). The stress-strain curve, damping ratio, and secant stiffness were analysed for material characterisation, and the evolution of these parameters was studied to assess functional fatigue. The fatigue life is extended dramatically when the strain is below 1%, and the structural fatigue life of CuAlMn is shown to be better than that of NiTi and to depend on the loading rate. However, decay in stiffness can be found in the CuAlMn SMA, which is considered to be caused particularly by its long grain boundary.

The intermolecular dynamics of liquid water impact most biological processes. Here, the authors use intense terahertz electromagnetic pulses to generate a transient, out-of-equilibrium state of the water network to show that the molecules become oriented and probe the polarizability of this anisotropic state.

Bandwidth is an important parameter for accelerometers, in some cases, even surpassing sensitivity. However, there are few studies focused on the relationship between bandwidth and environmental conditions in practical application of accelerometers. In this paper, we systematically analyze the influence of environment on the bandwidth of accelerometers, obtaining the amplitude–frequency response curves versus damping ratio and properties of materials, wherein temperature and humidity were found as the two dominant factors that influence the bandwidth of accelerometers. Common temperature and humidity variations can result in bandwidth degradation of about 25% according to our theoretical analysis. The finite element method (FEM) is introduced to verify our theoretical analysis, and the accordance of the FEM simulation results and the theoretical results confirmed the validity of our analysis. Furthermore, a modification design is proposed to compensate for the influence of temperature and humidity on the bandwidth of accelerometers. By choosing materials with an appropriate Young’s modulus and coefficient of thermal expansion, the degradation of the bandwidth was substantially diminished by more than one order of magnitude, which can serve as a strong guide for the future realization of accelerometers with a steady and large bandwidth.

A coordinated recovery strategy, based on MIESCR, is proposed for the converters Excessive dynamic reactive power demand and the low speed of power transmission recovery in multi-infeed HVDC system in this paper. Firstly, the article deduces the consistency of two type definition of MIESCR, and uses the respective advantages of the definition to improve the physical meaning of MIESCR; and then it elaborates the role of MIESCR played in in MIDC system voltage and power-angle stability Third, this pages put forward MIESCR as the fundamental to distinguish the strength of AC system, and use the size of MIESCR to arrange the recovery order of DC systems. Furthermore, the parameter of PI controller is used to realize the control of each DC system current. There is a great method to ensure coordinate control of PI controller. The last, a double infeed HVDC system simulation model, based on two actual DC system of China Southern Power Grid, is built on Electromagnetic transient simulation software of PSCAD/EMTDC to confirm the validity of this method proposed in this paper.

This paper presents an advanced Bayesian analysis method to determine the appropriate non-periodic inspection intervals of fatigue-sensitive structures. The calculation procedure of the posterior distribution is improved compared to the previous methods. The method is based on assumptions about the probability density functions of the time until crack initiation, a law of crack propagation, the probability of crack detection and the failure rate before and after crack initiation. A major feature of this method is that even when there are uncertain parameters in the equations, the next inspection interval can be determined. Moreover, the probability density function of the uncertain parameters is updated according to the results of each inspection. A simulation study was conducted to evaluate the proposed method. The proposed method is evaluated and it is statistically shown that this Bayesian approach allows (a) evaluation the inspection interval accurately even with incorrect prior knowledge about the parameters and, (b) estimation of the reliability of a system accurately, even when some of the parameters are uncertain.

This paper examines the dynamic behaviour of timber framed buildings under wind and dynamic loads, focusing on the role of connections being experimentally tested. The main aim of this manuscript is to analyze the in-service dynamic behaviour of a semi-rigid moment-resisting dowel-type connection between timber beam and column. For this purpose, two laboratory tests have been performed, the first on a connection and another one on a portal frame. The results are used to validate a numerical model of the simple portal frame, analyzed in OpenSees. The obtained relationships are also discussed and compared with Eurocode rules. The main result is that the joint stiffness is calculated through the Eurocode (EC) formulation underestimates the experimental one. A mutual agreement is obtained between the numerical model, validated from the experimental stiffness value for the connections, and the experimental results on the portal frame.