A new bearing fault diagnosis scheme using MED-morphological filter and ridge demodulation analysis

For rolling bearing diagnosis, the major challenge of signal processing technique is to extract the quasi-periodic impulses which generated by rolling bearing fault, especially when rolling bearing operated in the condition of heavy noise. This paper proposed a new bearing fault diagnosis scheme. First, the Minimum Entropy Deconvolution (MED) is taken to obtain the impulse excitations from the bearing vibration signal. Then, two kinds of morphological filter, named average filter(AVG) and difference filter (DIF), are used as the assisted filtering unit to reduce the random noise in original signal and integrate the positive and negative impulse excitations in MED filtered signal, respectively. At last, the STFT based ridge demodulation analysis is applied to the purified signal, and the bearing fault is easily identified by spectral analysis of the demodulated signal. Two simulated signal are analyzed to test the performance of the proposed scheme. In the first case, the periodic impulse signal adding with random noise is analyzed. The result shows that MED-AVG-DIA is the best scheme for impulse feature extraction. In the second case, the pure impulse signal which filtered by MED is analyzed. The result shows that STFT based ridge demodulation analysis can achieve better demodulation effect than other demodulation methods. The proposed fault diagnosis scheme has been further verified by simulation signal and measured vibration signals of defective bearing. The result shown that the proposed scheme is feasible and effective for the fault diagnosis of rolling bearing

STROBE-GnRHa pretreatment in frozen-embryo transfer cycles improves clinical outcomes for patients with persistent thin endometrium: A case-control study.

The well-prepared endometrium with appropriate thickness plays a critical role in successful embryo implantation. The thin endometrium is the main factor of frozen-embryo transfer (FET), resulting in the failure of implantation undergoing FET. Hormone treatment is suggested to improve endometrium thickness; however, among the larger numbers of cases, it cannot reach the sufficient thickness, which leads to a high cancelation rate of embryo transfer as well as waste high-quality embryos. Thus, it increases the burden to patients in both economic and psychological perspectives. We performed a retrospective observational study, which was composed with 2 cohorts, either with the conventional hormone replacement therapy (HRT) protocol or HRT with gonadotrophin-releasing hormone agonist (GnRHa) pretreatment to prepare the endometrium before FET. The measurements of endometrium thickness, hormone level, transfer cycle cancelation rate, pregnancy rate, and implantation rate were retrieved from the medical records during the routine clinic visits until 1 month after embryo transfer. The comparisons between 2 cohorts were performed by t-test or Mann-Whitney U test depending on the different attributions of data. In total, 49 cycles were under HRT with GnRHa pretreatment and 84 cycles were under the conventional HRT protocol. HRT with GnRHa pretreatment group improved the endometrial thickness (8.13 ± 1.79 vs 7.51 ± 1.45, P = .031), decreased the transfer cancelation rate (P = .003), and increased clinical pregnancy rate and implantation rate significantly (both P = .001). Additionally, luteinizing hormone level in pretreatment group was consistently lower than conventional HRT group (P < .05). Our study revealed HRT with GnRHa pretreatment efficiently improved the endometrial thickness, therefore, decreased the FET cycle cancelation. It also elevated the embryo implantation rate and clinical pregnancy rate by improving endometrial receptivity

An intelligent fault diagnosis method using variable weight artificial immune recognizers (V-AIR)

The Artificial Immune Recognition System (AIRS), which has been proved to be a successful classification method in the field of Artificial Immune Systems, has been used in many classification problems and gained good classification effect. However, the network inhibition mechanisms used in these methods are based on the threshold inhibition and the cells with low affinity will be deleted directly from the network, which will misrepresent the key features of the data set for not considering the density information within the data. In this paper, we utilize the concept of data potential field and propose a new weight optimizing network inhibition algorithm called variable weight artificial immune recognizer (V-AIR) where we replace the network inhibiting mechanism based on affinity with the inhibiting mechanism based on weight optimizing. The concept of data potential field was also used to describe the data distribution around training samples and the pattern of a training data belongs to the class with the largest potential field. At last, we used this algorithm to rolling bearing analog fault diagnosis and reciprocating compressor valves fault diagnosis, which get a good classification effect

Synthesis of a molecularly defined single-active site heterogeneous catalyst for selective oxidation of N-heterocycles

Generally, a homogeneous catalyst exhibits good activity and defined active sites but it is difficult to recycle. Meanwhile, a heterogeneous catalyst can easily be reused but its active site is difficult to reveal. It is interesting to bridge the gap between homogeneous and heterogeneous catalysis via controllable construction of a heterogeneous catalyst containing defined active sites. Here, we report that a molecularly defined, single-active site heterogeneous catalyst has been designed and prepared via the oxidative polymerization of maleimide derivatives. These polymaleimide derivatives can be active catalysts for the selective oxidation of heterocyclic compounds to quinoline and indole via the recycling of -C=O and -C-OH groups, which was confirmed by tracing the reaction with GC-MS using maleimide as the catalyst and by FT-IR analysis with polymaleimide as the catalyst. These results might promote the development of heterogeneous catalysts with molecularly defined single active sites exhibiting a comparable activity to homogeneous catalysts

The association between physical activity and fear of falling among community-dwelling older women in China: the mediating role of physical fitness

BackgroundThis study aimed to explore the association between physical activity (PA) and fear of falling (FOF) and to determine whether this relationship was mediated by physical fitness (PF) in community-dwelling older women.MethodsFor this cross-sectional study, a total of 1,108 older women were recruited. Moderate-to-vigorous physical activity (MVPA) and light physical activity (LPA) were objectively measured by accelerometers. Physical fitness indicators including body mass index (BMI), forced vital capacity, choice reaction time, grip strength, sit and reach, and five times sit-to-stand were measured. FOF was evaluated by the Chinese version of the activities-specific balance confidence scale. A stepwise linear regression model analysis was used for mediation analysis, and bootstrap analysis was used to verify the mediation effects.ResultThe Pearson correlation coefficient results suggested that MVPA was significantly and negatively correlated with FOF while LPA was not correlated with FOF. Logistic regression analysis suggested a significant association between MVPA, BMI, forced vital capacity, choice reaction time, sit and reach, grip strength, five times sit-to-stand, and FOF. The mediation analysis showed a negative relationship between MVPA and FOF. BMI completely mediated the relationship between MVPA and FOF while sit and reach, five times sit-to-stand, and forced vital capacity partially mediated the relationship between MVPA and FOF.ConclusionAccumulation of more daily MVPA was associated with reducing the odds of FOF in community-dwelling older women. PF indicators fully or partially mediate the relationship between MVPA and FOF. Therefore, more intervention efforts should focus on the promotion of MVPA to improve PF and thus reduce FOF among older women

CFD Analysis of the Primary Cooling System for the Small Modular Natural Circulation Lead Cooled Fast Reactor SNRLFR-100

Small modular reactor (SMR) has drawn wide attention in the past decades, and Lead cooled fast reactor (LFR) is one of the most promising advanced reactors which are able to meet the safety economic goals of Gen-IV nuclear energy systems. A small modular natural circulation lead cooled fast reactor-100 MWth (SNRLFR-100) is being developed by University of Science and Technology of China (USTC). In the present work, a 3D CFD model, primary heat exchanger model, fuel pin model, and point kinetic model were established based on some reasonable simplifications and assumptions, the steady-state natural circulation characteristics of SNCLFR-100 primary cooling system were discussed and illustrated, and some reasonable suggestions were proposed for the reactor’s thermal-hydraulic and structural design. Moreover, in order to have a first evaluation of the system behavior in accident conditions, an unprotected loss of heat sink (ULOHS) transient simulation at beginning of the reactor cycle (BOC) has been analyzed and discussed based on the steady-state simulation results. The key temperatures of the reactor core are all under the safety limits at transient state; the reactor has excellent thermal-hydraulic performance

Enzyme- and metal-free electrochemical sensor for highly sensitive superoxide anion detection based on nitrogen doped hollow mesoporous carbon spheres

In this work, a highly sensitive enzyme- and metal-free electrochemical method for superoxide anion (O[rad]) detection has been developed by employing screen-printed carbon electrodes (SPCE) modified by nitrogen doped hollow mesoporous carbon spheres (N-HMCS). For comparison, solid carbon spheres (SCS) and hollow mesoporous carbon spheres (HMCS) were also synthesized to fabricate the modified SPCE. Compared with SCS/SPCE and HMCS/SPCE, N-HMCS/SPCE displayed a higher electrochemical performance. When applied for electrochemical detection of O[rad], N-HMCS/SPCE exhibited a high sensitivity of 1.49\ua0μA\ua0cm\ua0μM, better than SCS/SPCE and HMCS/SPCE and many of enzyme- or metal-based superoxide anion sensors. N-HMCS is expected to become a new generation of sensing materials for electrochemical analysis of O[rad]

Management of prolactinoma: a survey of endocrinologists in China

Objective: To assess the current management of prolactinoma among endocrinologists in China. Methods: An online survey of a large sample of endocrinologists was conducted in China. The questionnaire included 21 questions related to controversial issues about the management of prolactinomas. Doctors in the endocrinology department of a university-affiliated hospital or a comprehensive secondary hospital in 12 cities from East, West, South, North and Middle China were surveyed. Results: A total of 290 valid questionnaires were collected, and the response rate was 40%. When hyperprolactinemia occurred, 97% of the respondents would test thyroid-stimulating hormone routinely. 22% of the respondents considered that prolactin levels 250 ng/mL could occur in all the following situations as macroprolactinoma, mircoprolactinoma, macroprolactinemia and drug-induced hyperprolactinemia. Surgery was not recommended by 272 (94%) endocrinologists as the first choice for treating microprolactinomas. 58% and 92% of endocrinologists would start drug treatment for microprolactinomas and macroprolactinomas at diagnosis. 70% and 40% chose to withdraw treatment after 2–3 years of prolactin normalization in microprolactinomas and macroprolactinomas. In case of pregnancy, 57% of the respondents considered bromocriptine as choice for women patients. Drug discontinuation after pregnancy was advocated in 63% and 27% for microprolactinoma and macroprolactinoma. Moreover, 44% of endocrinologists believed that breastfeeding was allowable in both micro- and macroprolactinoma. Conclusion: This is the first study to investigate the management of prolactinomas among endocrinologists in China. We found that the current clinical treatment was not uniform. Therefore, it is necessary to strengthen the training of endocrinologists to improve clinical diagnosis and treatment practices

Cold tolerance identification of nine Rosa L. materials and expression patterns of genes related to cold tolerance in Rosa hybrida

Members of the Rosa genus have a high ornamental value, but their cultivation area is limited by their sensitivity to cold temperatures. The aim of this study was to evaluate the cold tolerance of a range of Rosa materials, and then determine which genes were related to cold tolerance. Nine Rosa materials were subjected to a cold treatment. To identify genes related to cold tolerance, R. hybrida was treated at −15°C for 10 min, and leaves collected before and after this treatment were collected for RNA-Seq analyses. The transcript profiles of four DEGs (POD17, NDUFA9, PMA1, and b-Amy1) in R. hybrida were determined by qRT-PCR at 0 h, 1 h, 2 h, and 3 h at −15°C. Nine Rosa materials were subjected to a cold treatment, and the most cold-tolerant materials were identified as those that showed the lowest levels of electrolyte leakage and the best recovery after 30 d of growth. The most cold-tolerant materials were Rosa hybrida, Rosa rugosa ‘Pingyin 12’, and Rosa rugosa. In total, 204 significantly differentially expressed genes (DEGs) were identified, of which 88 were significantly up-regulated and 116 were significantly down-regulated under cold conditions. Gene Ontology classification and Kyoto Encyclopedia of Genes and Genomes pathway analyses showed that the DEGs were enriched in 57 pathways, especially starch and sucrose metabolism, phenylpropane biosynthesis, MAPK signaling, fructose and mannose metabolism, and oxidative phosphorylation. By transcriptional analysis, PMA1, which was related to H+ ATPase activity, was continuously up-regulated, but the transcript levels of POD17, NDUFA9, and β-Amy1 fluctuated during the freezing treatment. This research uncovered scarce cold-resistant materials and layed the foundation for further research on the cold tolerance mechanism of Rosa plants and the breeding of cold-tolerant varieties

Curdlan Prevents the Cognitive Deficits Induced by a High-Fat Diet in Mice via the Gut-Brain Axis

A high-fat (HF) diet is a major predisposing factor of neuroinflammation and cognitive deficits. Recently, changes in the gut microbiota have been associated with neuroinflammation and cognitive impairment, through the gut-brain axis. Curdlan, a bacterial polysaccharide widely used as food additive, has the potential to alter the composition of the microbiota and improve the gut-brain axis. However, the effects of curdlan against HF diet-induced neuroinflammation and cognitive decline have not been investigated. We aimed to evaluate the neuroprotective effect and mechanism of dietary curdlan supplementation against the obesity-associated cognitive decline observed in mice fed a HF diet. C57Bl/6J male mice were fed with either a control, HF, or HF with curdlan supplementation diets for 7 days (acute) or 15 weeks (chronic). We found that acute curdlan supplementation prevented the gut microbial composition shift induced by HF diet. Chronic curdlan supplementation prevented cognitive declines induced by HF diet. In addition, curdlan protected against the HF diet-induced abnormities in colonic permeability, hyperendotoxemia, and colonic inflammation. Furthermore, in the prefrontal cortex (PFC) and hippocampus, curdlan mitigated microgliosis, neuroinflammation, and synaptic impairments induced by a HF diet. Thus, curdlan-as a food additive and prebiotic-can prevent cognitive deficits induced by HF diet via the colon-brain axis