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Abstract Background Physical activity(PA) is associated with health-related quality of life (HRQoL) among older adults, and both are associated with mood, such as depression. However, the indirect effects of PA on HRQoL in older adults have not been clearly established. This study explained how different types and intensities of PA were associated with HRQoL while considering the effects of depression in older adults. Methods A cross-sectional study was conducted with 7,518 community-dwelling older adults aged 60 years and older. PA (leisure-time, household, and work-related), depression, and HRQoL were measured using the Physical Activity Scale for the Elderly (PASE), the 30-item Geriatric Depression Scale (GDS-30), and the 36-Item Short-Form Health Survey (SF-36), respectively. Information on age, gender, education, monthly income, activities of daily living, smoking, and alcohol drinking was also collected. Regression analysis was used to explore the relationship between PA, depression and HRQoL, and a mediation effect test process was used to verify the mediating mechanism of the depression on this relationship. Results The study showed that after adjusting for a set of covariates, SF-36 Physical Component Summary (PCS) scores were negatively associated with depression (B = -2.046, 95% CI [2.584, -1.509]) and positively with PA (p

Glycoside hydrolases (GHs), enzymes that break down glycosidic bonds in carbohydrates and between carbohydrates and non-carbohydrates, are prevalent in plants, animals, microorganisms, and other organisms. The tomato is a significant crop that contains the GH17 gene family. However, its role in tomatoes has yet to be fully investigated. In this study, we identified 43 GH17 genes from the tomato genome, distributed unevenly across 12 chromosomes. We further analyzed their gene structure, phylogenetic relationships, promoter elements, and expression patterns. The promoter element analysis indicated their potential roles in response to biotic and abiotic stresses as well as phytohormone effects on growth and development. The expression studies across different tomato tissues revealed that 10 genes were specifically expressed in floral organs, with SlA6 prominently expressed early during bud formation. By using CRISPR/Cas9 gene-editing technology, SlA6 knockout plants were generated. Phenotypic characterization showed that pollen viability, pollen tube germination, fruit weight, and seed number were significantly reduced in the Sla6 mutant, but the soluble solids content (TSS) was significantly higher in the Sla6 mutant, suggesting that SlA6 affects pollen development and fruit quality.

The escalating impact of global warming on crop yield and quality poses a significant threat to future food supplies. Breeding heat-resistant crop varieties holds promise, but necessitates a deeper understanding of the molecular mechanisms underlying plant heat tolerance. Recent studies have shed light on the initial events of heat perception in plants. In this review, we provide a comprehensive summary of the recent progress made in unraveling the mechanisms of heat perception and response in plants. Calcium ion (Ca2+), hydrogen peroxide (H2O2), and nitric oxide (NO) have emerged as key participants in heat perception. Furthermore, we discuss the potential roles of the NAC transcription factor NTL3, thermo-tolerance 3.1 (TT3.1), and Target of temperature 3 (TOT3) as thermosensors associated with the plasma membrane. Additionally, we explore the involvement of cytoplasmic HISTONE DEACETYLASE 9 (HDA9), mRNA encoding the phytochrome-interacting factor 7 (PIF7), and chloroplasts in mediating heat perception. This review also highlights the role of intranuclear transcriptional condensates formed by phytochrome B (phyB), EARLY FLOWERING 3 (ELF3), and guanylate-binding protein (GBP)-like GTPase 3 (GBPL3) in heat perception. Finally, we raise the unresolved questions in the field of heat perception that require further investigation in the future.

ObjectiveThis study examined the moderating effect of overall social support and the different types of social support on cognitive functioning in depressed older adults. We also investigated whether the moderating effect varied according to age.MethodsA total of 2,500 older adults (≥60 years old) from Shanghai, China were enrolled using a multistage cluster sampling method. Weighted linear regression and multiple linear regression was utilized to analyze the moderating effect of social support on the relationship between depressive symptoms and cognitive function and to explore its differences in those aged 60–69, 70–79, and 80 years and above.ResultsAfter adjusting for covariates, the results indicated that overall social support (β = 0.091, p = 0.043) and support utilization (β = 0.213, p

Deciphering drought resistance in crops is crucial for enhancing water productivity. Previous studies have highlighted the significant role of the transcription factor SlHB8 in regulating developmental processes in tomato plants but its involvement in drought resistance remains unclear. Here, gene overexpression (SlHB8-OE) and gene knockout (slhb8) tomato plants were utilized to study the role of SlHB8 in regulating drought resistance. Our findings showed that slhb8 plants exhibited a robust resistant phenotype under drought stress conditions. The stomata of slhb8 tomato leaves displayed significant closure, effectively mitigating the adverse effects of drought stress on photosynthetic efficiency. The slhb8 plants exhibited a decrease in oxidative damage and a substantial increase in antioxidant enzyme activity. Moreover, slhb8 effectively alleviated the degree of photoinhibition and chloroplast damage caused by drought stress. SlHB8 regulates the expression of numerous genes related to photosynthesis (such as SlPSAN, SlPSAL, SlPSBP, and SlTIC62) and stress signal transduction (such as SlCIPK25, SlABA4, and SlJA2) in response to drought stress. Additionally, slhb8 plants exhibited enhanced water absorption capacity and upregulated expression of several aquaporin genes including SlPIP1;3, SlPIP2;6, SlTIP3;1, SlNIP1;2, and SlXIP1;1. Collectively, our findings suggest that SlHB8 plays a negative regulatory role in the drought resistance of tomato plants.

Abstract Background Few studies have explored patterns of physical activity (PA) and examined their relationship with depression among community-dwelling older adults. We aimed to identify the patterns of PA through a person-centered analytical approach and examine the association between quantity and patterns of PA, and depression among community-dwelling older adults. Methods We conducted a cross-sectional survey study in the Minhang district, Shanghai, China, in August 2019, and used a self-administered questionnaire to collect data through home visits. The total sample included 2525 older adults. This study used the Physical Activity Scale for the Elderly (PASE) to assess the quantity of PA in older adults. Depression was evaluated with the Geriatric Depression Scale (GDS). Latent class analysis (LCA) was used to identify subpopulations by shared item response patterns. Logistic regressions were performed to estimate the relationship between PASE score, patterns of PA, and depression. An exploratory analysis of joint levels and patterns of PA effects on depression was based on sample subgroups with combinations of levels and patterns of PA. Logistic regression was used to calculate the odds ratio for combined subgroups. Results Four latent classes were identified: “domestic types,” “athletic types,” “gardening/caring types,” and “walkers.” PASE scores and patterns of PA both were associated with depression. Older adults who were the most active (PASE quartile: 75–100%) and the athletic types had the strongest significant association with depression (OR = 0.19, 95% CI: 0.06–0.65), followed by those who were the most active (PASE quartile: 75–100%) and the walkers (OR = 0.28, 95% CI: 0.14–0.57) when compared with older adults with the least activity (PASE quartile: 0–25%) and domestic types. Conclusion This study suggests both the quantity and patterns of physical activity are associated with depressive symptoms among community-dwelling older adults. Population-level intervention should encourage community-dwelling older adults to increase their quantity of PA to reduce the risk of depression. Athletics and walkers are recommended. To develop individual-level tailored interventions, more attention should be paid to older adults who are highly engaged in gardening/caring for others.

IntroductionDementia has become a public health priority and is irreversible. Mild cognitive impairment (MCI), an intermediate state between normal cognition and dementia, is the prime time for early diagnosis and intervention. The activities of daily living of dementia patients are usually insufficient. Therefore, continuing to explore the risk factors of MCI, especially the influence of physical activity on MCI and its mechanism can enrich the relevant research fields in China.Materials and methodsFor this cross-sectional study, 2,518 adults aged 60 years or older in Xinzhuang, Minhang District, Shanghai were recruited between July 2019 and April 2019, using a multistage, cluster-sampling method. A binary unconditional logistic regression model was used with MCI status as the dependent variable. Different types of physical activity were separately included in the multifactor model to test their correlations. Sensitivity analysis was performed using BADL as a stratification factor. The mediating effect of depression between physical activity and MCI was examined using the Bootstrap method.ResultsThis research includes 271 (10.8%) MCI. Old age (odds ratio 2.967 [95%CI 2.063∼4.269]), having diabetes (1.816 [1.302∼2.534]), and depression (3.012 [2.209∼4.108]) were possible risk factors for MCI. High education level (0.722 [0.523∼0.999]), medium level of physical activity (0.459 [0.326∼0.645]), and high level of physical activity (0.396 [0.270∼0.580]) were possible protective factors. Medium (0.548 [0.396∼0.757]) and high levels (0.557 [0.366∼0.846]) of physical exercise and medium (0.433 [0.318∼0.590]) and high levels (0.487 [0.296∼0.801]) of household chores are possible protective factors of MCI and their significance remained in the mutually adjusted model. Sensitivity analysis showed that physical activity and household chores were possible protective factors in all strata (P < 0.05). Physical exercise and work-related activities showed a protective effect in fully independent older adults, but the effect disappeared in those who cannot be fully independent. Depression played a partially mediating role with an indirect effect of 6.67%.DiscussionOverall, our results highlight that physical activity is a possible protective factor for MCI. Physical exercise and household chores have strong protective effects and future interventions could be targeted from this perspective. Depression plays a partially mediating role and more attention should be paid to the mental health of older adults.

This paper proposes a condition monitoring method based on Dynamic Related ReliefF-SFA (DRRSFA), which solves the problem of huge variable dimensions and strong autocorrelation in process monitoring. First, the samples are mapped into a new space, and the slow projection components (SPCs) of the samples are calculated. The SPCs not only considers the autocorrelation between the variables, but also characterizes the inherent properties of the whole system. Second, the feature selection algorithm ReliefF is used to select the more weighted features, which is called the principal components(PCs) to achieve dimensionality reduction. Then the corresponding statistics and control limits are calculated based on the obtained PCs. Finally, the process monitoring using the proposed algorithm is performed by testing a numerical example and the actual production process data, and the results show the effectiveness of the proposed method.

The System #2 flow loop used in this study is a 4−inch−diameter, high−temperature, high−pressure system. In situ corrosion and electrochemical measurements were performed using a homemade flat corrosion specimen and a three−electrode probe. The experiment results show that temperature has an accelerated influence on the corrosion of antibacterial alloy steel. With the increase of temperature and the presence of O2 in the environment, a loose and porous corrosion product film was formed on the surface of the resistant steel, which made it easier for the corrosion medium to enter the corrosion product film from the pore, thus accelerating the corrosion.

Abstract Background In China, unmarried female migrants are vulnerable to sexual and reproductive health risks. One effective protection strategy is promoting consistent condom use (CCU). Methods We conducted a cross-sectional study to apply the information-motivation-behavioral skills (IMB) model and modified it by addition of psychological and personal factors to examine the related factors of CCU and provide suggestions for intervention among unmarried female migrants. Results Of all 903 eligible participants, only 13.8% of participants reported CCU in the past six months. Both the IMB model and the modified IMB model provided acceptable fit to the data. In both models, information had no direct or indirect influence on CCU (p > 0.05). However, behavioral skills had a positive effect on CCU (β = 0.344, p 0.05). In the modified model, psychological and personality factors influenced CCU directly (β = − 0.100, p = 0.005). Conclusions Our results highlight the importance of conducting CCU promotion among unmarried female migrants. Future intervention strategies should focus on both the traditional IMB model constructs and the added psychological and personality factors.

Early detection of incipient faults is a challenging task in the field of chemical process monitoring. For this problem, this paper proposes a new data-driven process monitoring method called stream data projection transformation analysis (SDPTA). First, we determine a set of projection transformation vectors, orthogonal basis vectors, based on original data to solve the problem that the data space original basis vector has relevance. Then, we use a sliding window to project data onto the basis vectors to obtain the basis vector components which is defined as projection transform components (PTCs). In this way, the stream data local sequence information can be utilized effectively. Furthermore, each PTC represents the coverage of local data on the corresponding basis vector. The length of PTCs can reveal some important process features, implying that condition changes can be detected by monitoring the length of PTCs. Finally, the potential of the window-based SDPTA method in monitoring continuous processes is explored using two case studies (a numerical example and the challenging Tennessee Eastman process). The performance of the proposed method is compared with the existing MSPM methods, such as PCA, DPCA, and RTCSA. The monitoring results clearly demonstrate the superiority of our method.

The decentralized weighted ReliefF-PCA (DWRPCA) method is proposed to improve the performance of principal component analysis (PCA) for fault detection. The improved ReliefF-PCA algorithm is used to select the principal components instead of the traditional cumulative percent variance (CPV) criterion, so that the important information contained in the small variance is considered. The sub-models for different types of faults which are being considered the influence weights of process variables and faults are established respectively to obtain the decentralized weighted model. The Bayesian Information Criterion is adopted to integrate different types of faults for a unified monitoring index. The case study of a numerical example and the Tennessee Eastman process illustrate the effectiveness of the proposed method.

The deployable bridge based on scissor structures is one of the effective methods to quickly restore traffic after natural and man-made disasters. Scissor structures have the advantages of high storage rate, lightweight, and convenient storage and transportation. However, when scissor structures are used as load-bearing structures, their stiffness and bearing capacity are low. In this study, a three-dimensional deployable bridge based on the cable-strengthened scissor structures was proposed. In addition to rapid expansion, steel cables were used to strengthen scissor structures to improve the stiffness and bearing capacity. Besides, the static loading comparative tests on cable-strengthened scissor structures and traditional scissor structures (cable-free scissor structures) were performed. The results show that the stiffness of the cable-free scissor structure is small, the bending moment of members is large, and the stress distribution is uneven. The stiffness of cable-strengthened scissor structure is significantly improved; the bending moment of members is significantly reduced; and the stress distribution in the member section is more uniform. It is proved that cables can be used to improve the stiffness and load-bearing capacity of scissor structures without affecting the deployability.

Background With the rapid increase in ageing population, China is confronted with the daunting challenge of a growing number of patients with neurocognitive disorders (NCDs). This trend makes the maintenance of self-health and early intervention essential, highlighting the need for a tool that assesses self-efficacy of older adults in maintaining brain health or cognitive function.Aim This study aimed to design the Brain Health Self-Efficacy Scale (BHSES) to measure elderly individuals’ attitudes to NCDs, motivations and future plans for controlling risks. The psychometric properties of BHSES have been validated.Methods Based on the current literature and relevant models, a 19-item scale was created during the first stage. A total of 660 older adults in the Yinhang community of Shanghai were included. The statistical approaches of item analysis, exploratory factor analysis (EFA), confirmatory factor analysis (CFA), criterion-related validity and reliability test were used to evaluate the quality of BHSES. In addition, the Geriatric Depression Scale (GDS) and the Self-Rating Anxiety Scale (SAS) were used as criteria to test the criterion-related validity.Results To test item differentiation, the study adopted item analysis and excluded item 8. Selecting a random half of the sample for EFA, the BHSES was refined to 16 items, which were categorised into the following three dimensions: ‘memory belief efficacy’, ‘self-care efficacy’ and ‘future planning efficacy’. These were highly consistent with the hypothesis model. Its cumulative variance contribution rate reached 61.14%, with factor loads of all items above 0.5. The three-factor model was confirmed by the remaining data through CFA. All fit indices reached the acceptable level (χ2=3.045, Goodness of Fit Index=0.898, adjusted Goodness of Fit Index=0.863, Comparative Fit Index=0.916, Incremental Fit Index=0.917, Tucker-Lewis Index=0.900, root mean square error of approximation=0.079 and root mean residual=0.068). The GDS and SAS scores revealed significant correlations with the BHSES score, indicating a high criterion-related validity. The overall Cronbach’s α coefficient was 0.793, with the α coefficients’ distribution of subdimensions ranging from 0.748 to 0.883.Conclusions The 16-item, self-compiled BHSES is a reliable and valid measurement. It could help identify older adults with potential risks for developing NCDs or with high suspicion of cognitive impairment onset in recent periods and also offer insight into tracking brain health self-efficacy in association with cognition status.

In order to study the performance of partially precast partially encased assembled composite beam (PPECB) in reducing costs and reducing carbon dioxide (CO2) emissions, this paper obtained the bearing capacity of PPECBs by a static test. Considering the load conditions and beam height conditions as constraints, the steel-concrete composite beam (SCCB) and reinforced concrete beam (RCB) were optimized and designed based on the principle of fully utilizing the advantages of steel and concrete. On the basis of investigating the quantity of different materials, the cost and CO2 emissions of the three different types of beams were analyzed. The cost and CO2 emission of the PPECB are the lowest, and SCCBs have the highest cost and CO2 emissions. This paper can provide reference for design choice and further research from the perspective of cost and CO2 emission and lay a solid foundation for the realization of economic and environment-friendly buildings.

As key equipment in modern industry, it is important to diagnose and predict the health status of bearings. Data-driven methods for remaining useful life (RUL) prognostics have achieved excellent performance in recent years compared to traditional methods based on physical models. In this paper, we propose a novel data-driven method for predicting the remaining useful life of bearings based on a deep graph convolutional neural network with spatiotemporal domain convolution. This network uses the average sliding root mean square (ASRMS) as the health factor to identify the healthy and degraded states, and then uses correlation coefficient analysis on the hybrid features of the degraded data to construct a spatial graph according to the strength of the correlation between the obtained features. In the time domain, we introduce historical data as the input to the temporal convolution. After the data are processed by the spatial map and the temporal dimension, we perform the prediction of the remaining useful life. The experimental results show the accuracy of the method.

Abstract Background As the most populous nation in the world, China has now becoming an emerging ageing society. Shanghai is the first city facing the challenge of ageing demographics. Against this background, a study that employs self-rated health (SRH) assessment system was designed to explore the health status of Shanghai elders, and learn their attitudes toward health issues; as well as to investigate the determinants of SRH among Shanghai elders. Understanding SRH is crucial for finding appropriate solutions that could effectively tackle the increasing eldercare demand. Methods This study adopted a quantitative research strategy. Using a multistage stratified cluster sampling method, we conducted a questionnaire survey in August 2011 in Shanghai, which collected 2001 valid survey responses. SRH assessments were categorized by five levels: very good, fairly good, average, fairly poor, or poor. The respondents’ functional status was evaluated using the Barthel index of activities for daily living. In the data analysis, we used chi-squared test to determine differences in socio-demographic characteristics among various groups. Along with statistics, several logistic regression models were designed to determine the associations between internal influence factors and SRH. Results Younger age (χ2 = 27.5, p

In view of the characteristics of a high floor and the heavy load of logistics buildings, a partially prefabricated partially encased assembled composite beam (PPEC) is proposed in order to achieve the low cost construction of such buildings. In this research, the mechanical properties of PPEC beams were studied experimentally. The effects of the concrete strength grade, steel content, shear span ratio, and fabrication methods on the mechanical properties of the PPEC beams were analyzed. The results showed that the proposed structural form of the PPEC beams was generally feasible. Based on the test results, a practical shear formula for PPEC beams was proposed, and the calculated results were in good agreement with the test results.

Autoimmune diseases such as rheumatoid arthritis (RA) cause significant morbidity and loss of productivity. Many potent conventionally used drugs are available for these diseases, but their prolonged use is accompanied by severe adverse effects besides a high cost. Therefore, there is an unmet need for effective but less expensive medications for RA and other autoimmune diseases. Natural plant products belonging to the traditional systems of medicine, such as the traditional Chinese medicine and Indian Ayurvedic medicine, offer a vast and promising resource in this regard. However, herbal medicinal products are often poorly characterized for their composition as well as mechanisms of action. We review here the results of our systematically performed studies aimed at defining the anti-arthritic activity of three herbal extracts, namely, modified Huo-luo-xiao-ling dan (HLXL), Celastrus aculeatus Merr., and polyphenolic fraction of green tea (Camellia sinensis), as well as a purified compound Celastrol, a bioactive component of Celastrus. Specifically, we examined the effects of these herbal products on the immunological, biochemical and molecular biological effector pathways in autoimmune arthritis. We have also reviewed here related studies on these herbal products by other investigators. Taken together, we suggest further testing of these herbal products in RA patients.

A high-performance low-power micro hotplate (MHP) hydrogen sensor was fabricated through electrohydrodynamic (EHD) inkjet printing technique. Electrospun Pd loaded SnO2 nanofibers with lengths of 250-850 nm were precisely printed on the suspended central part of an MHP with an area of 100 um × 100 um. The printhead in the printing system was a low-cost metallic needle with an inner diameter of 110 um, which was large enough to prevent clogging by the nanofibers. The printing process was observed by a high-speed camera. Small droplets with diameters of 50-80 um were produced at each ejection by providing a high voltage to the metallic needle. It was found that the bridge-type MHPs used in our experiment can promote the positioning precision due to its bound effect to the droplet. In the gas sensing measurement, the Pd loaded SnO2 MHP gas sensor showed a remarkable response to H2 with a low power of only 9.1 mW. The experiment results demonstrate the excellent adequacy of EHD inkjet printing technique to realize effective mass fabrication of MHP gas sensors or sensor arrays.

ObjectiveThe objective of this study was to evaluate the factors associated with the health status of older Chinese people living in the community, in order to inform strategies to expand access to healthcare.MethodsTwo-phase stratified cluster sampling was applied; 2000 older people participated in this study. Face-to-face interviews were conducted in Shanghai between June and August, 2011. Descriptive analysis was used to examine the respondents' characteristics. Based on Andersen's healthcare utilization model, a chi-squared test and multiple logistic regression were performed to examine the influences of predisposing, enabling, need, and contextual factors on healthcare utilization.ResultsWe found that 44.5% of the older people in the sample had good self-reported health status, while 12.8% were poor, 14.5% had visited hospitals or clinics as outpatients in the previous two weeks, and 16.5% had been hospitalized in the previous year. Logistic regression analysis revealed that outpatient health services were more likely to be used by women and those whose income was from friends or social relief, who had poor to good self-reported health status, who were experiencing declining health, who engaged in volunteer activities, and who had chronic diseases. Meanwhile, hospitalization was more likely among those in the older age groups, those with pension income, living in outer suburbs, with poor self-reported health status, experiencing difficulty with activities of daily living and outdoor activities, or having a chronic disease.ConclusionsThe results showed the impact of economic status, health status, demographic and social characteristics, and other factors on the health service utilization of elderly people living in the community in Shanghai. Need variables were the strongest predictors of health service use, although contextual factors also contributed.