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Balancing the hardness and electrical conductivity of copper alloys within complex compositions and processes poses a formidable challenge. This study proposes a strategy combining machine learning with the Pareto front techniques to identify optimal combinations of composition and processing for Cu-xTi (1.5 ≤ x ≤ 5.4, in wt.%) alloys. Through thermodynamic calculations, precipitation simulations, and experimental characterizations, the microstructural evolution of β'-Cu4Ti precipitates in the designed alloys was explored. The interpretability and predictability of the machine learning model played a crucial role in understanding impact of complex alloy compositions and processing on the evolution of properties, thereby guiding the design of Cu-Ti alloys towards improved attributes.

Abstract Background Heart failure with reduced ejection fraction (HFrEF) is associated with a high rate of mortality and morbidity. Evidence has shown that sex differences may be an important contributor to phenotypic heterogeneity in patients with HFrEF. Although diabetes mellitus (DM) frequently coexists with HFrEF and results in a worse prognosis, there remains a need to identify sex-related differences in the characteristics and outcomes of this population. In this study, we aimed to investigate the between-sex differences in clinical profile, left ventricular (LV) remodeling, and cardiovascular risk factors and outcomes in patients with HFrEF concomitant with DM. Methods A total of 273 patients with HFrEF concomitant with DM who underwent cardiac MRI were included in this study. Clinical characteristics, LV remodeling as assessed by cardiac MRI, and cardiovascular risk factors and outcomes were compared between sexes. Results Women were older, leaner and prone to have anemia and hypoproteinemia but less likely to have ischemic etiology. Cardiac MRI revealed that despite similar LVEFs between the sexes, there was more LV concentric remodeling, less impaired global systolic peak strain in longitudinal and circumferential components and a decreased likelihood of late gadolinium enhancement presence in women than in men. During a median follow-up time of 34.6 months, women exhibited better overall survival than men did (log-rank P = 0.042). Multivariable Cox proportional hazards analysis indicated different risk factors for predicting outcomes between sexes, with hypertension [hazard ratio (HR) = 2.05, 95% confidence interval (CI) 1.05 to 4.85, P = 0.041] and hypoproteinemia (HR = 2.27, 95% CI 1.06 to 4.37, P = 0.039) serving as independent determinants of outcomes in women, whereas ischemic etiology (HR = 1.96, 95% CI 1.11 to 3.48, P = 0.021) and atrial fibrillation (HR = 1.86, 95% CI 1.02 to 3.41, P = 0.044) served as independent determinants of outcomes in men. Conclusions Among patients with HFrEF concomitant with DM, women displayed different LV remodeling and risk factors and had better survival than men did. Sex-based phenotypic heterogeneity in patients with HFrEF in the context of DM should be addressed in clinical practice.

Abstract The development and utilization of bulk resources provide the basic material needs for industrial systems. However, most current resource utilization patterns are unsustainable, with low efficiencies and high carbon emissions. Here, we report a quantitative tool for resource-based industries to facilitate sustainable and low-carbon transitions within the regional economy. To evaluate the effectiveness of this tool, the saline Qinghai Lake region was chosen as a case study. After optimizing the industrial structure, the benefits of economic output, resource efficiency, energy consumption, solid waste reduction, and carbon emission reduction can be obtained. The scenario analyses exhibit disparities in different transition paths, where the carbon mitigation, economic output, and resource efficiency that benefit from optimal development paths are significantly better than those of the traditional path, indicating the urgency of adopting cleaner technology and industrial symbiosis for regional industries.

Abstract Background Glycemic control, as measured by glycosylated hemoglobin (HbA1c), is an important biomarker to evaluate diabetes severity and is believed to be associated with heart failure development. Type 2 diabetes mellitus (T2DM) and heart failure with reduced ejection fraction (HFrEF) commonly coexist, and the combination of these two diseases indicates a considerably poorer outcome than either disease alone. Therefore, glycemic control should be carefully managed. The present study aimed to explore the association between glycemic control and clinical outcomes, and to determine the optimal glycemic target in this specific population. Methods A total of 262 patients who underwent cardiac MRI were included and were split by HbA1c levels [HbA1c 7.5% (poor control)]. The biventricular volume and function, as well as left ventricular (LV) systolic strains in patients in different HbA1c categories, were measured and compared. The primary and secondary outcomes were recorded. The association of different HbA1c levels with adverse outcomes was assessed. Results Despite similar biventricular ejection fractions, both patients with intensive and poor glycemic control exhibited prominent deterioration of LV systolic strain in the longitudinal component (P = 0.004). After a median follow-up of 35.0 months, 55 patients (21.0%) experienced at least one confirmed endpoint event. Cox multivariable analysis indicated that both patients in the lowest and highest HbA1c categories exhibited a more than 2-fold increase in the risk for primary outcomes [HbA1c 7.5%: HR = 2.24, 95% CI = 1.01–4.99; P = 0.038] and secondary outcomes (HbA1c 7.5%: HR = 2.65, 95% CI = 1.08–6.50; P = 0.038) compared with those in the middle HbA1c category. Conclusions We showed a U-shaped association of glycemic control with clinical outcomes in patients with T2DM and HFrEF, with the lowest risk of adverse outcomes among patients with modest glycemic control. HbA1c between 6.5% and 7.5% may be served as the optimal hypoglycemic target in this specific population.

Abstract Purpose To gain an in-depth and comprehensive understanding of Chinese organ transplant recipients’ perceptions, expectations, and suggestions of pharmacy services to hospital pharmacists. Methods This qualitative study was conducted in central China, from February to December 2020. Participants were collected with a purposive and snowball sampling method. Focus group discussions were conducted with organ transplant recipients and content analysis was applied to identify themes and subthemes. Results 21 recipients participated in the qualitative study. Four themes and thirteen subthemes were identified: (1) perceptions of clinical pharmacists and pharmacy services; (2) expectations for pharmacy service content; (3) expectations for pharmacy service form; and (4) difficulties as a special group. Conclusion The pharmacy services provided by Chinese healthcare institutions are inadequate to meet the needs of organ transplant recipients. However, the acceptance and expectation of pharmacy services by transplant recipients are high. Therefore, China should learn from the experience of developed countries and focus on the actual needs of patients to establish a better pharmacy service system for organ transplantation.

Abstract The structural diversity of biological macromolecules in different environments contributes complexity to enzymological processes vital for cellular functions. Fluorescence resonance energy transfer and electron microscopy are used to investigate the enzymatic reaction of T4 DNA ligase catalyzing the ligation of nicked DNA. The data show that both the ligase–AMP complex and the ligase–AMP–DNA complex can have four conformations. This finding suggests the parallel occurrence of four ligation reaction pathways, each characterized by specific conformations of the ligase–AMP complex that persist in the ligase–AMP–DNA complex. Notably, these complexes have DNA bending angles of ≈0°, 20°, 60°, or 100°. The mechanism of parallel reactions challenges the conventional notion of simple sequential reaction steps occurring among multiple conformations. The results provide insights into the dynamic conformational changes and the versatile attributes of T4 DNA ligase and suggest that the parallel multiple reaction pathways may correspond to diverse T4 DNA ligase functions. This mechanism may potentially have evolved as an adaptive strategy across evolutionary history to navigate complex environments.

AimsPrimary pigmented nodular adrenocortical disease (PPNAD), as a rare kind of Cushing’s syndrome, is frequently misdiagnosed. To get a better understanding of the disease, we analyzed the clinical characteristics and pathogenic variants of PPNAD.MethodsDatabases were searched, and the pathogenic variants and clinical manifestations of patients were summarized from the relevant articles.ResultsA total of 210 patients in 86 articles were enrolled with a median age of 22 and a female-to-male ratio of 2:1. Sixty-six (31.43%) patients were combined with Carney complex (CNC) and 94.29% were combined with osteoporosis/osteopenia. Among 151 patients who underwent genetic testing, 87.42% (132/151) had pathogenic variants. Six gene mutations (PRKAR1A, PDE11A, PRKACA, CTNNB1, PDE8B, and ARMC5) were detected in the patients. The most common mutation was PKAR1A, accounting for 79.47% (120/151). There was a significant correlation between PRKAR1A pathogenic variant and spotty skin pigmentation in CNC concurrent with PPNAD (p < 0.05). Among pregnant patients with PPNAD, those without surgical treatment and with bilateral adrenalectomy suffered from a high-risk perinatal period. However, patients with unilateral adrenalectomy presented a safe perinatal period.ConclusionsFor young patients with Cushing’s syndrome, especially female patients with spotty skin pigmentation and osteoporosis/osteopenia, PPNAD should be considered. Unilateral adrenal resection may be considered as an option for women with fertility needs. In view of the difficulty of PPNAD diagnosis, genetic testing before surgery might be a reasonable option. Patients with PPNAD with spotty skin pigmentation should consider the PRKAR1A pathogenic variant and pay attention to CNC.Systematic review registrationhttps://www.crd.york.ac.uk/prospero, identifier CRD42023416988.

Abstract Background Sarcopenia is frequently found in patients with heart failure with reduced ejection fraction (HFrEF) and is associated with reduced exercise capacity, poor quality of life and adverse outcomes. Recent evidence suggests that axial thoracic skeletal muscle size could be used as a surrogate to assess sarcopenia in HFrEF. Since diabetes mellitus (DM) is one of the most common comorbidities with HFrEF, we aimed to explore the potential association of axial thoracic skeletal muscle size with left ventricular (LV) remodeling and determine its prognostic significance in this condition. Methods A total of 243 diabetes patients with HFrEF were included in this study. Bilateral axial thoracic skeletal muscle size was obtained using cardiac MRI. Patients were stratified by the tertiles of axial thoracic skeletal muscle index (SMI). LV structural and functional indices, as well as amino-terminal pro-B-type natriuretic peptide (NT-proBNP), were measured. The determinants of elevated NT-proBNP were assessed using linear regression analysis. The associations between thoracic SMI and clinical outcomes were assessed using a multivariable Cox proportional hazards model. Results Patients in the lowest tertile of thoracic SMI displayed a deterioration in LV systolic strain in three components, together with an increase in LV mass and a heavier burden of myocardial fibrosis (all P

Abstract Background Gadolinium-enhanced cardiovascular magnetic resonance (CMR) is the most widely used approach for diagnosing myocardial fibrosis with late gadolinium enhancement (LGE) in cardiomyopathy associated with Duchenne muscular dystrophy. Given the limitations and safety of gadolinium use, we wanted to develop and evaluate multi-parametric pre-contrast CMR models for the diagnosis of LGE and investigate whether they could be utilised as surrogates for LGE in DMD patients. Methods A total of 136 DMD patients were prospectively recruited and separated into LGE − and LGE + groups. In the first subset of patients (derivation cohort), regression models for the diagnosis of LGE were built by logistic regression using pre-contrast sequence parameters. In a validation cohort of other patients, the models’ performances were evaluated. Results EF, native T1 and longitudinal strain alone, as well as their combinations form seven models. The model that included EF, native T1 and longitudinal strain had the best diagnostic value, but there was no significant difference in diagnostic accuracy among the other models except EF. In the validation cohort, the diagnosis outcomes of models were moderate consistent with the existence of LGE. The longitudinal strain outperformed the other models in terms of diagnostic value (sensitivity: 83.33%, specificity: 54.55%). Conclusions Pre-contrast sequences have a moderate predictive value for LGE. Thus, pre-contrast parameters may be considered only in a specific subset of DMD patients who cannot cooperate for long-time examinations and have contradiction of contrast agent to help predict the presence of LGE. Trial registration number (TRN) ChiCTR1800018340 Date of registration 20180107

Abstract Necrotizing enterocolitis (NEC) is a life-threatening, inflammatory disease affecting premature infants with intestinal necrosis, but the mechanism remains unclear. Neonatal macrophages are thought to play an important role in the pathogenesis of NEC through the production of proinflammatory cytokines. Restriction of cytokine expression in macrophages of NEC tissues may be beneficial. In adult macrophages, interfering with Rac1 has been shown to influence the expression of cytokines. Here, we investigated whether interfering with Rac1 in neonatal macrophages affects their inflammatory responses. First, we found that Rac1-activation was upregulated in the macrophages of rats with NEC model induction compared to controls. The M1 macrophages derived from human neonatal monocytes showed greater Rac1-activation than the M2 macrophages derived from the same monocytes. Inhibition of Rac1-activation by NSC23766 potently reduced the production of proinflammatory cytokines in these M1 macrophages. While neonatal monocytes differentiated into M1 macrophages in vitro, NSC23766 significantly altered cell function during the first six days of incubation with GM-CSF rather than during the subsequent stimulation phase. However, the same effect of NSC23766 was not observed in adult macrophages. Using mass spectrometry, Y-box binding protein 1 (YB1) was identified as being downregulated upon inhibition of Rac1-activation in the neonatal macrophages. Moreover, we found that inhibition of Rac1-activation shortens the poly A tail of PABPC1 mRNA, thereby reducing the translation of PABPC1 mRNA. Consequently, the downregulation of PABPC1 resulted in a reduced translation of YB1 mRNA. Furthermore, we found that TLR4 expression was downregulated in neonatal macrophages, while YB1 expression was reduced. Adding resatorvid (TLR4 signaling inhibitor) to the macrophages treated with NSC23766 did not further reduce the cytokine expression. These findings reveal a novel Rac1-mediated pathway to inhibit cytokine expression in neonatal M1 macrophages and suggest potential targets for the prevention or treatment of NEC.

Abstract Background Insulin is commonly used in type 2 diabetes mellitus (T2DM) to achieve glycemic control. However, recent evidence showed that insulin use is associated with poor outcomes in the context of heart failure (HF). Since heart failure with reduced ejection fraction (HFrEF) accounts for approximately 50% of cases in the general HF population, we aimed to evaluate the effect of insulin treatment on left ventricular (LV) remodeling and contractility abnormalities in a HFrEF cohort and assess whether insulin was a predictor of adverse outcomes in this entity. Methods A total of 377 HFrEF patients who underwent cardiac MRI were included and divided according to diabetes status and the need for insulin treatment. LV structural and functional indices, as well as systolic strains, were measured. The determinants of impaired myocardial strains were assessed using linear regression analysis. The associated endpoints were determined using a multivariable Cox proportional hazards model. Results T2DM patients on insulin displayed a higher indexed LV end-diastolic volume and LV mass than those with T2DM not on insulin or those without T2DM, despite similar LV ejection fractions, accompanied by a higher three-dimensional spherical index (P

Endogenous peptides, particularly those with post-translational modifications, are increasingly being studied as biomarkers for diagnosing various diseases. However, they are weakly ionizable, have a low abundance in biological samples, and may be interfered with by high levels of proteins, peptides, and other macromolecular impurities, resulting in a high limit of detection and insufficient amounts of post-translationally modified peptides in real biological samples to be examined. Therefore, separation and enrichment are necessary before analyzing these biomarkers using mass spectrometry. Mesoporous materials have regular adjustable pores that can eliminate large proteins and impurities, and their large specific surface area can bind more target peptides, but this may result in the partial loss or destruction of target peptides during centrifugal separation. On the other hand, magnetic mesoporous materials can be used to separate the target using an external magnetic field, which improves the separation efficiency and yield. Core–shell magnetic mesoporous materials are widely utilized for peptide separation and enrichment due to their biocompatibility, efficient enrichment capability, and excellent recoverability. This paper provides a review of the latest progress in core–shell magnetic mesoporous materials for enriching glycopeptides and phosphopeptides and compares their enrichment performance with different types of functionalization methods.

Abstract Background This study aimed to examine the bidirectional relationship between social isolation and cognitive performance among Chinese middle-aged and older adults. Methods We used four waves of data from the China Health and Retirement Longitudinal Study. A latent growth model (LGM) was applied to examine the association between social isolation and cognitive performance across different characteristics. Results In the analysis, we ultimately included 9,367 participants after excluding respondents with missing key variables. Social isolation and cognitive performance showed significant differences across time. After adjusting for the confounders, there was a significant association between higher social isolation and poor cognitive performance (β = −1.38, p

ObjectiveThere is a notable research gap on the mental health challenges faced by hospital pharmacists in the post-pandemic era. Therefore, the present study aims to explore mental health status, influencing factors, coping strategies, and the mediating effect of resilience of home quarantine hospital pharmacists (HQHPs).MethodsAn embedded mixed-method study was conducted in Zhengzhou, a megalopolis in central China, from 20 October to 3 November 2022. For the qualitative study, semi-structured interviews and focus group discussions were conducted among HQHPs to understand their mental health state，the factors that affect their mental health, and the alleviating strategies they used. For the quantitative study, the Generalized Anxiety Disorder Scale (GAD-7) and the Chinese version of the Connor-Davidson Resilience Scale (CD-RISC-25) were used to explore the mental health level of HQHPs. Meanwhile, the mediating effect of resilience was explored and verified with the bootstrap method or the structural equation model.Results20 HQHPs participated in the qualitative study. Two themes were identified in terms of the factors that influenced the HQHPs’ mental health levels. The positive factors include optimism, family company, and connection with friends, while the negative factors include inadequate supplies, inadequate information, and other emergencies. 210 HQHPs participated in the quantitative study, with a median resilience score of 66 [55.75, 74] in the lowest score range and an anxiety score of 5 [2, 7] in the mild anxiety range. The correlation analysis showed that nine of the 10 influencing factors identified in qualitative research were positively correlated with CD-RISC-25 scores and negatively correlated with the GAD-7 score. The mediating effect of resilience on anxiety was significant (95% bootstrap CI [−1.818, −0.384], p

Objective Self-directed learning (SDL) has been embraced by the medical community as a core professional competency, with motivation considered a crucial component of SDL. However, little is known about how hospital pharmacists perceive motivation in SDL in the workplace. This study aimed to examine the intrinsic and external motivation of hospital pharmacists in SDL.Design This study employed a multicentre qualitative design, which lasted 13 months from May 2020 to June 2021. The interviews were audiorecorded, transcribed verbatim and analysed in NVivo V.12.0. Thematic analysis method was used to analyse the data.Setting The study took place in nine public hospitals located in urban areas of Henan Province.Participants Sixteen hospital pharmacists were enrolled from the pharmacy departments of the sample hospitals, using a purposive sampling method.Results Sixteen one-on-one semistructured interviews were conducted, identifying intrinsic and extrinsic motivation in SDL for hospital pharmacists in the workplace. Intrinsic motivation includes curiosity and interest, achievement, self-efficacy and personal growth. Extrinsic motivation includes a more comprehensive set of elements, such as interpersonal motivations, work-related motivations and career-related motivations.Conclusions Personal interests, the influence of surrounding individuals (directly or indirectly), work-related requirements and pressures, and professional development requirements and pressures are the main intrinsic or extrinsic motivations for SDL among hospital pharmacists in China. Future research may focus on these aspects to enhance the SDL competence of hospital pharmacists and other medical personnel.

ObjectiveThe relationship between serum selenium levels and papillary thyroid cancer (PTC), especially the pathological features, still remains controversial. We conducted this study to investigate the relationship between serum selenium levels and PTC in a Chinese population.MethodsCross-sectional data of 284 patients with PTC were collected from the First Affiliated Hospital of Shandong First Medical University. The general clinical characteristics, serum selenium levels, and tumor pathological features were described in PTC. The association between serum selenium levels and pathological features in PTC was analyzed using SPSS 26.0 statistical software.ResultsOur results showed that the median serum selenium level was 79.15 μg/L (IQR: 71.00 - 86.98 μg/L) in PTC patients. Serum selenium levels were lower in females than males (p = 0.035). Serum selenium levels were negatively correlated with the number of lymph node metastases (p = 0.048). High serum selenium (OR = 0.397, 95%CI: 0.217 - 0.725) and diastolic blood pressure (OR = 1.028, 95%CI: 1.005 - 1.051) were related factors for the incidence of bilateral tumors. High serum selenium (OR = 0.320, 95%CI: 0.166 - 0.617) and diastolic blood pressure (OR = 1.066, 95%CI: 1.031 - 1.103) were related factors for tumor multifocal incidence.ConclusionsThe serum selenium levels of PTC patients in females were lower than males. High serum selenium levels might be a protective factor in PTC patients. Further research is necessary to better understand the influence of selenium on PTC progression.

Abstract Background This study presented the mortality trend of ischemic heart disease (IHD) in Chinese residents from 2010 to 2019 and provided a basis for further establishment of relevant interventions. Methods Data, such as sex, age, urban and rural areas, and death status, were extracted from the China Death Surveillance Dataset from 2010 to 2019, with mortality and age-adjusted death rates (AADRs) as the main indicators. The joinpoint regression model was used to analyze mortality and AADRs trends in IHD. A semi-structured expert interview was conducted to propose targeted intervention measures and countermeasures. Results We observed an overall upward trend in IHD mortality rates and AADRs in China from 2010 to 2019 (average annual percentage change [AAPC] = 5.14%, AAPCAADRs = 1.60%, P 0.05) mortality rates increased, with the mortality rate higher in rural areas than in urban areas. In the age analysis, mortality rate was higher in middle-aged and older adults than in other age groups. The age-sex cross-analysis found the highest trend in mortality rates among females aged ≥ 75 years (annual percentage change [APC] = 2.43%, P

ABSTRACT Linker histone H1 plays a crucial role in various biological processes, including nucleosome stabilization, high-order chromatin structure organization, gene expression, and epigenetic regulation in eukaryotic cells. Unlike higher eukaryotes, little about the linker histone in Saccharomyces cerevisiae is known. Hho1 and Hmo1 are two long-standing controversial histone H1 candidates in budding yeast. In this study, we directly observed at the single-molecule level that Hmo1, but not Hho1, is involved in chromatin assembly in the yeast nucleoplasmic extracts (YNPE), which can replicate the physiological condition of the yeast nucleus. The presence of Hmo1 facilitates the assembly of nucleosomes on DNA in YNPE, as revealed by single-molecule force spectroscopy. Further single-molecule analysis showed that the lysine-rich C-terminal domain (CTD) of Hmo1 is essential for the function of chromatin compaction, while the second globular domain at the C-terminus of Hho1 impairs its ability. In addition, Hmo1, but not Hho1, forms condensates with double-stranded DNA via reversible phase separation. The phosphorylation fluctuation of Hmo1 coincides with metazoan H1 during the cell cycle. Our data suggest that Hmo1, but not Hho1, possesses some functionality similar to that of linker histone in Saccharomyces cerevisiae, even though some properties of Hmo1 differ from those of a canonical linker histone H1. Our study provides clues for the linker histone H1 in budding yeast and provides insights into the evolution and diversity of histone H1 across eukaryotes. IMPORTANCE There has been a long-standing debate regarding the identity of linker histone H1 in budding yeast. To address this issue, we utilized YNPE, which accurately replicate the physiological conditions in yeast nuclei, in combination with total internal reflection fluorescence microscopy and magnetic tweezers. Our findings demonstrated that Hmo1, rather than Hho1, is responsible for chromatin assembly in budding yeast. Additionally, we found that Hmo1 shares certain characteristics with histone H1, including phase separation and phosphorylation fluctuations throughout the cell cycle. Furthermore, we discovered that the lysine-rich domain of Hho1 is buried by its second globular domain at the C-terminus, resulting in the loss of function that is similar to histone H1. Our study provides compelling evidence to suggest that Hmo1 shares linker histone H1 function in budding yeast and contributes to our understanding of the evolution of linker histone H1 across eukaryotes.

Abstract Background Cardiac magnetic resonance (CMR) has been used to diagnose and risk-stratify patients with left ventricular noncompaction (LVNC). The prognostic value of CMR parameters for LVNC, especially feature tracking (CMR-FT), is not well known in LVNC patients with left ventricular dysfunction. The present study aimed to investigate whether the combination of CMR-FT with traditional CMR parameters can increase the prognostic value of CMR for LVNC patients with reduced left ventricular ejection fraction (LVEF). Methods A total of 123 candidates were retrospectively included in this multicenter study and 55 LVNC patients (mean age, 45.7 ± 16.2 years; 61.8% men) remained after applying the exclusion criteria. Clinical features, left ventricular (LV) function parameters, global and segment myocardial strain, and late gadolinium enhancement (LGE) were evaluated. The outcomes include the composite events of cardiovascular death, heart transplantation, hospitalization for heart failure, thromboembolic events, and ventricular arrhythmias. Results After a median follow-up of 5.17 years (interquartile range: 0.17 to 10.58 years), 24 (36.8%) patients experienced at least one major adverse cardiovascular event (MACE). The myocardial strain parameters of patients with events were lower than those of patients without events. In the univariable Cox analysis, LVEF, the presence of LGE, global longitudinal strain (GLS) and segmental strains, including longitudinal strain at the apical level and radial and circumferential strain at the basal level, were significantly associated with MACEs. In the multivariate analysis, LGE (hazard ratio (HR) 3.452, 95% CI 1.133 to 10.518, p = 0.029) was a strong predictor of MACEs and significantly improved the predictive value (chi-square of the model after adding LGE: 7.51 vs. 13.47, p = 0.009). However, myocardial strain parameters were not statistically significant for the prediction of MACEs after adjusting for age, body mass index, LVEF and the presence of LGE and did not increase the prognostic value (chi-square of the model after adding GLS: 13.47 vs. 14.14, p = 0.411) in the multivariate model. Conclusions The combination of CMR-FT with traditional CMR parameters may not increase the prognostic value of CMR in LVNC patients with reduced LVEF, while the presence of LGE was a strong independent predictor of MACEs and significantly improved the predictive value.

ObjectivesCancer patients exhibit fear of COVID-19, which could lead to serious consequences. However, minimal information is available about the effect of the COVID-19 pandemic on the mental health of cancer patients. Therefore, this study aims to examine the fear level of COVID-19 among cancer patients in Henan Province, Central China and to identify its causes, results, and coping factors.MethodsAn online survey was conducted among 1,067 cancer patients. The participants reported their individual fear level of COVID-19, risk of COVID-19 infection, risk of death from COVID-19, COVID-19 vaccination concerns, influence level of COVID-19 pandemic on their disease treatment, loneliness due to COVID-19, economic burden from COVID-19, quality of life, safety behavior, information regarding COVID-19 vaccination, psychological guidance, physical activities, and demographic characteristics. Chi-square and cumulative logistic regression were used to determine the predictors of COVID-19 fear level.ResultsThis study indicates that cancer patients report moderate fear level of COVID-19 in Central China (66.9%). The six cause factors (risk of COVID-19 infection, risk of death from COVID-19, COVID-19 vaccination concerns, influence level of COVID-19 pandemic on disease treatment, loneliness due to COVID-19, and economic burden from COVID-19) were positively associated with COVID-19 fear level. Three coping factors (information regarding COVID-19 vaccination, psychological guidance, and physical activities) were negatively associated with COVID-19 fear level. COVID-19 fear level was negatively associated with quality of life and positively associated with safety behavior.ConclusionOur results suggest that governments should improve access to personalized vaccine counseling and psychological guidance by undertaking the responsibility of patients’ attending physicians and increasing publicity. Physical activities should be included in the treatment program to help cancer patients better recover their physical and mental health.

Objective As lifelong learners, hospital pharmacists must continually improve their self-directed learning skills. Reasonable learning strategies have been proven to enhance self-directed learning (SDL) significantly. Therefore, this study aims to investigate the SDL strategies used by hospital pharmacists in depth to provide them with a reference for the development of their SDL skills.Setting The study was conducted in three tertiary hospitals in Henan, China.Design and participants This study employed a multicentre qualitative design and lasted 12 months. One-on-one interviews and focus group discussions were used to collect data. All interviews were transcribed verbatim, and the interview data were analysed using the thematic analysis method. Purposive sampling was used to select interviewees (n=17) from three tertiary hospitals in Henan province in central China.Results After conducting data analysis, we summarised 12 learning strategies related to SDL, which were grouped into four themes: use of information resources, application of cognitive strategies, development of learning plans and use of learning platforms.Conclusion The findings suggest that classic learning strategies, such as cognitive strategies and the development of learning plans, remain the cornerstones of hospital pharmacists’ SDL abilities, while contemporary advances in information technology and changes in learning concepts have enriched the learning resources and learning platforms that are available to hospital pharmacists and have confronted contemporary hospital pharmacists with certain challenges.

PurposeTo determine the efficacy of 1.5 T magnetic resonance imaging (MRI) for the diagnosis of anomalies of the fetal great arteries with comparison to fetal ultrasound, and to compare image quality between 1.5 T and 3.0 T MRI in fetal imaging of the great arteries.MethodsWe compared the results of postnatal exam or surgery and evaluated the application value of prenatal 1.5 T MRI in the assessment of fetal great-vessel anomalies. To further determine the diagnostic potential of 1.5 T MRI, 23 pregnant women with suspected fetal cardiovascular abnormalities who had undergone ultrasound and 3.0 T MRI were enrolled and compared, respectively.ResultsPrenatal MRI was superior to ultrasound in demonstrating aortic arch and branch abnormalities (sensitivity, 92.86% vs. 83.33%; specificity, 66.67% vs. 20%). The mean quality ratings for fetal MRI at 1.5 T was higher than 3.0 T (P

Abstract Background Progressive cardiomyopathy accounts for almost all mortality among Duchenne muscular dystrophy (DMD) patients.‍ Thus, our aim was to comprehensively characterize myocardial involvement by investigating the heterogeneity of native T1 mapping in DMD patients using global and regional (including segmental and layer-specific) analysis across a large cohort. Methods We prospectively enrolled 99 DMD patients (8.8 ± 2.5 years) and 25 matched male healthy controls (9.5 ± 2.5 years). All subjects underwent cardiovascular magnetic resonance (CMR) with cine, T1 mapping and late gadolinium enhancement (LGE) sequences. Native T1 values based on the global and regional myocardium were measured, and LGE was defined. Results LGE was present in 49 (49%) DMD patients. Global native T1 values were significantly longer in LGE-positive (LGE +) patients than in healthy controls, both in basal slices (1304 ± 55 vs. 1246 ± 27 ms, p

Abstract Background This study aimed to reveal the effects of the connectedness of primary health care (PHC) workers in social networks on their job burnout. Methods Cross-sectional survey data of rural PHC workers in China were analyzed. A total of 663 respondents were enrolled. Chi-square and cumulative logistic regression were used to determine the effects of the connectedness of PHC workers in social networks on their job burnout. Results PHC workers in rural China had high levels of emotional exhaustion (24.1%), depersonalization (15.7%), and lack of personal accomplishment (34.7%). More than half of the participants were in the middle connectedness level in terms of their advisory (70.4%) and friendship (70.3%) networks. The degree of emotional exhaustion seemed to increase when participants had a low connectedness in their friendship networks (β = 0.769, 95% CI = 0.080–1.458, P = 0.029). Respondents with the middle level of connectedness in advisory networks had higher levels of depersonalization (β = 0.739, 95% CI = 0.130–1.348, P = 0.017) and lack of personal accomplishment (β = 0.583, 95% CI = 0.111–1.055, P = 0.015) than those with the high degree of connectedness in advisory networks. Conclusions The connectedness of PHC workers in social networks influenced their job burnout. Thus, organizations should establish an informal communication platform and information feedback mechanism, promote and manage friendship networks, and help PHC workers overcome emotional exhaustion. Managers should also encourage individuals with a high level of connectedness in advisory networks play the role of “opinion leader” so that they can help others mitigate burnout.

As a cutting-edge technique for denoising and feature extraction, singular spectrum analysis (SSA) has been applied successfully for feature mining in hyperspectral images (HSI). However, when applying SSA for in situ feature extraction in HSI, conventional pixel-based 1-D SSA fails to produce satisfactory results, while the band-image-based 2D-SSA is also infeasible especially for the popularly used line-scan mode. To tackle these challenges, in this article, a novel 1.5D-SSA approach is proposed for in situ spectral-spatial feature extraction in HSI, where pixels from a small window are used as spatial information. For each sequentially acquired pixel, similar pixels are located from a window centered at the pixel to form an extended trajectory matrix for feature extraction. Classification results on two well-known benchmark HSI datasets and an actual urban scene dataset have demonstrated that the proposed 1.5D-SSA achieves the superior performance compared with several state-of-the-art spectral and spatial methods. In addition, the near real-time implementation in aligning to the HSI acquisition process can meet the requirement of online image analysis for more efficient feature extraction than the conventional offline workflow.

Accurately monitoring the quantity and quality of urban vegetation contributes to regional greening efforts and improves the understanding of vegetation's impact on the environment. However, factors such as building shadows and synthetic materials can greatly obstruct vegetation estimates. Additionally, vegetation indices (VIs) saturate quickly in high biomass conditions, complicating vegetation quality assessments. To address these issues, we propose a new vegetation index, namely the hyperspectral image-based vegetation index (HSVI). HSVI is built in three steps: band selection, saturable band reconstruction, and index structure redefinition. Firstly, we select four representative bands and construct an enhanced vegetation index (EVI) to eliminate the interference of complex urban surface factors. Secondly, we reconstruct the easily saturable band (760 nm) through an exponential function to form an optimized enhanced vegetation index (OEVI). Finally, the index structure is redefined by adding the denominator of the sum of the red edge (689 nm) and green (520 nm) bands to OEVI to further enhance the spectral information of vegetation and eliminate the saturation problem typical of VIs. Three datasets with different geomorphological features (Shanghai Theatre Academy, Dazhu Mountain, and the University of Houston) are used to compare the performance of HSVI with six VIs widely adopted in urban ecological research, i.e., the difference vegetation index (DVI), the normalized difference vegetation index (NDVI), the simple ratio (SR), the optimized soil-adjusted vegetation index (OSVAI), the modified transformed vegetation index (MTVI2) and the wide-dynamic-range vegetation index (WDRVI). The results show that the vegetation extraction accuracy of HSVI is more than 90%, which is significantly higher than those of the other VIs. Additionally, HSVI also solves the VIs saturation issue. Therefore, HSVI shows high potential usefulness for urban ecological research applications.

Cardiac complications are common in antiretroviral therapy-treated (ART-treated) acquired immune deficiency syndrome (AIDS) patients, and the incidence increases with age. Myocardial injury in ART-treated AIDS patients with a relatively longer disease duration has been evaluated. However, there is no relevant study on whether patients with a short AIDS duration have cardiac dysfunction. Thirty-seven ART-treated males with AIDS and eighteen healthy controls (HCs) were prospectively included for CMR scanning. Clinical data and laboratory examination results were collected. The ART-treated males with AIDS did not have significantly reduced biventricular ejection fraction, myocardial edema, or late gadolinium enhancement. Compared with the HCs, the biventricular volume parameters and left ventricle myocardial strain indices in ART-treated males with AIDS were not significantly reduced (all p > 0.05). ART-treated males with AIDS were divided into subgroups according to their CD4+ T-cell counts (p > 0.05). In Pearson correlation analysis, CD4+ T-cell counts were not significantly correlated with biventricular volume parameters or left ventricular myocardial strain indices. In conclusion, ART-treated males with AIDS receiving ART therapy with a short disease duration (less than 3 years) might not develop obvious cardiac dysfunction as evaluated by routine CMR, so it is reasonable to appropriately extend the interval between cardiovascular follow-ups to more than 3 years.

In this article, the networked filtering problem for a class of robotic manipulators with semi-Markov type parameters is investigated under the passivity framework. In particular, the mode-dependent quantization and event-triggered communication scheme are both proposed for increasing the network transmission efficiency. Sufficient stability conditions are first derived by choosing mode-dependent Lyapunov–Krasovskii functionals. Then, the mode-dependent filter gains and the event-triggering parameters are further designed with the help of matrix convex optimization. In the end, a simulation example is provided such that the effectiveness of the proposed filtering method can be well demonstrated.

The monoclonal antibody against CTLA-4, Ipilimumab, is a first-in-class immune-checkpoint inhibitor approved for treatment of advanced melanoma in adults but not extensively studied in children. In light of the fact that the immune response early in life differs from that of adults, we have applied a human in vitro model stimulating CD4+ T-cells from neonates, children (1–5 years), and adults antigen-specifically with Staphylococcus aureus (S. aureus) for assessment of CTLA-4 blockade early in life. We show that T-cell proliferation as well as frequencies of antigen-specific T-cells (CD40L+CD4+) were enhanced in neonatal T-cells upon CTLA-4 blockade showing a larger variance within the group (F-test p

Joint sparse representation classification (JSRC) is a representative spectral–spatial classifier for hyperspectral images (HSIs). However, the JSRC is inappropriate for highly heterogeneous areas due to the spatial information being extracted from a fixed-sized neighborhood block, which is often unable to conform to the naturally irregular structure of land cover. To address this problem, a superpixel-based JSRC with nonlocal weighting, i.e., superpixel-based nonlocal weighted JSRC (SNLW-JSRC), is proposed in this paper. In SNLW-JSRC, the superpixel representation of an HSI is first constructed based on an entropy rate segmentation method. This strategy forms homogeneous neighborhoods with naturally irregular structures and alleviates the inclusion of pixels from different classes in the process of spatial information extraction. Afterwards, the superpixel-based nonlocal weighting (SNLW) scheme is built to weigh the superpixel based on its structural and spectral information. In this way, the weight of one specific neighboring pixel is determined by the local structural similarity between the neighboring pixel and the central test pixel. Then, the obtained local weights are used to generate the weighted mean data for each superpixel. Finally, JSRC is used to produce the superpixel-level classification. This speeds up the sparse representation and makes the spatial content more centralized and compact. To verify the proposed SNLW-JSRC method, we conducted experiments on four benchmark hyperspectral datasets, namely Indian Pines, Pavia University, Salinas, and DFC2013. The experimental results suggest that the SNLW-JSRC can achieve better classification results than the other four SRC-based algorithms and the classical support vector machine algorithm. Moreover, the SNLW-JSRC can also outperform the other SRC-based algorithms, even with a small number of training samples.

The effect of intercritical tempering temperature (TT) on the microstructure evolution and mechanical properties of 3.6Mn medium manganese steel, which contained martensite and austenite, was investigated by X-ray diffraction, electron backscattering diffraction and transmission electron microscopy, as well as Thermo-Calc calculation. The results showed that the volume fraction of reversed austenite (RA) increased firstly and then decreased with the increasing TT in the range of 550~650 °C. When the TT was below 620 °C, lath-like RA with good stability was mainly displayed between martensite laths and its size is about 100 nm. When the TT was higher than 650 °C, larger-size and block RA was formed in the martensite block boundaries, and part of the RA transformed into fresh martensite during cooling. The yield strength and tensile strength of the experimental steels decreased gradually as the TT increased, but the tensile strength increased gradually with the formation of block RA and fresh martensite. Lath-like RA could significantly improve the toughness and plasticity with slight loss of yield strength, but block RA decreased slightly them.

Background Increasing studies demonstrated that the cardiac involvements are related to coronavirus disease 2019 (COVID‐19). Thus, we investigated the clinical characteristics of patients with COVID‐19 and further determined the risk factors for cardiac involvement in them. Methods and Results We analyzed data from 102 consecutive laboratory‐confirmed and hospitalized patients with COVID‐19 (52 women aged 19–87 years). Epidemiologic and demographic characteristics, clinical features, routine laboratory tests (including cardiac injury biomarkers), echocardiography, electrocardiography, chest imaging findings, management methods, and clinical outcomes were collected. Patients were divided into acute cardiac injury, with and without cardiac marker abnormities groups according to different level of cardiac markers. In this research, cardiac involvement was found in 72 of the 102 (70.6%) patients: tachycardia (n=20), electrocardiography abnormalities (n=23), echocardiography abnormalities (n=59), elevated myocardial enzymes (n=55), and acute cardiac injury (n=9). Eight patients with acute cardiac injury were aged >60 years; seven of them had ≥2 underlying comorbidities (hypertension, diabetes mellitus, cardiovascular diseases, chronic obstructive pulmonary disease, and chronic kidney disease). Novel coronavirus pneumonia was much more severe in the patients with acute cardiac injury than in patients with nondefinite acute cardiac injury (P

Background: Despite an increase in the familiarity of the medical community with the epidemiological and clinical characteristics of coronavirus disease 2019 (COVID-19), there is presently a lack of rapid and effective risk stratification indicators to predict the poor clinical outcomes of COVID-19 especially in severe patients.Methods: In this retrospective single-center study, we included 117 cases confirmed with COVID-19. The clinical, laboratory, and imaging features were collected and analyzed during admission. The Multi-lobular infiltration, hypo-Lymphocytosis, Bacterial coinfection, Smoking history, hyper-Tension and Age (MuLBSTA) Score and Confusion, Urea, Respiratory rate, Blood pressure, Age 65 (CURB65) score were used to assess the death and intensive care unit (ICU) risks in all patients.Results: Among of all 117 hospitalized patients, 21 (17.9%) patients were admitted to the ICU care, and 5 (4.3%) patients were died. The median hospital stay was 12 (10–15) days. There were 18 patients with MuLBSTA score ≥ 12 points and were all of severe type. In severe type, ICU care and death patients, the proportion with MuLBSTA ≥ 12 points were greater than that of CURB65 score ≥ 3 points (severe type patients, 50 vs. 27.8%; ICU care, 61.9 vs. 19.0%; death, 100 vs. 40%). For the MuLBSTA score, the ROC curve showed good efficiency of diagnosis death (area under the curve [AUC], 0.956; cutoff value, 12; specificity, 89.5%; sensitivity, 100%) and ICU care (AUC, 0.875; cutoff value, 11; specificity, 91.7%; sensitivity, 71.4%). The K–M survival analysis showed that patients with MuLBSTA score ≥ 12 had higher risk of ICU (log-rank, P = 0.001) and high risk of death (log-rank, P = 0.000).Conclusions: The MuLBSTA score is valuable for risk stratification and could effectively screen high-risk patients at admission. The higher score at admission have higher risk of ICU care and death in patients infected with COVID.

The aim of this manuscript is to tackle the tracking problem for uncertain semi-Markov systems. More precisely, the mode-dependent event-triggering communication approach is introduced for networked controller design procedure, which can considerably increase the signal transmission efficiency. Based on the Lyapunov–Krasovski method, mode-dependent sufficient conditions are derived and the tracking errors could achieve the asymptotic mean-square stability, and mode-dependent controllers could be further calculated by convex optimization. A numerical simulation with application to vertical take-off and landing helicopter would be performed for verifying the availability and usefulness.

Precision glass molding (PGM) technology is a cost-efficient process for the production of micro/nanostructured glass components with complex surface geometries. The stress distribution, surface profile, and reduced refractive index of the molded lens are based on the lens being fully formed. The process of the deformation of the glass preform is rarely discussed, especially in the case of multi-machining parameters in the experiment. The finite element method (FEM) was adopted to analyze the glass preform deformation. Due to the phenomenon of incomplete deformation of the glass preforms in the experiments, two groups of finite element simulations with different boundary conditions were carried out with MSC.Marc software, to reveal the relationship between the deformation progress and the parameters settings. Based on the simulation results, a glass preform deformation model was established. The error between the model result and the simulation result was less than 0.16. The establishment method of the glass preform deformation model and the established model can be used as a reference in efficiently optimizing PGM processing parameters when the designed lens has two different base radii of curvature.

In this paper, the characteristics of water pollution in Yitong River were analyzed by the comprehensive pollution index method. Combined with the pore water concentration gradient method and Fick’s first law, the release characteristics of nutrients at the sediment–water interface of Yitong River (Jilin Province, China) were studied. The results showed that the distribution trend of nitrogen and phosphorus content in the overlying and interstitial water of the Yitong River was the same, and the highest values appeared at the S3 and S5 points in the urban section. The water quality was mainly affected by nitrogen pollutants in domestic sewage. The evaluation results of the water quality comprehensive pollution index showed that the pollution degree of interstitial water in urban areas was much higher than that of the overlying water, and the endogenous nitrogen and phosphorus pollutants had the risk of diffusion to the overlying water. The exchange flux analysis of ammonia nitrogen (NH4+-N), total dissolved nitrogen (TDN), and total dissolved phosphorus (TDP) in water showed that the diffusion flux of NH4+-N ranged from 0.03 to 6.52 mg·(m2·d)−1, and the sediment was the “source” of ammonia nitrogen pollutants. The range of TDN diffusion flux was −1.57 to 11.6 mg·(m2·d) −1, and the difference between points was large. The sediment was both the “source” and “sink” of nitrogen pollutants. The range of TDP diffusion flux was −0.05 to 0.22 mg·(m2·d) −1. Except for point S8, the TDP diffused from sediment into the water body. Among all the sampling points, the diffusion fluxes of NH4+-N, TDN, and TDP at the S3 point were the largest, the release rate of endogenous pollutants was the most rapid, and the pollution to the water quality was the most serious. The results are of great significance to the exchange flux of nutrients at the sediment–water interface of rivers and the prevention and control of water eutrophication. It also provides a reference for the study of nutrient exchange flux at the sediment–water interface of rivers and other surface water bodies worldwide.

Micro/nano- BN co-doped epoxy composites were prepared and their thermal conductivity, breakdown strength at power frequency and voltage endurance time under high frequency bipolar square wave voltage were investigated. The thermal conductivity and breakdown performance were enhanced simultaneously in the composite with a loading concentration of 20 wt% BN at a micro/nano proportion of 95/5. The breakdown strength of 132 kV/mm at power frequency, the thermal conductivity of 0.81 W·m−1·K−1 and voltage endurance time of 166 s were obtained in the composites, which were approximately 28%, 286% and 349% higher than that of pristine epoxy resin. It is proposed that thermal conductive pathways are mainly constructed by micro-BN, leading to improved thermal conductivity and voltage endurance time. A model was introduced to illustrate the enhancement of the breakdown strength. The epoxy composites with high thermal conductivity and excellent breakdown performance could be feasible for insulating materials in high-frequency devices.

Abstract Background Apart from its direct impact on public health and well-being, malaria had placed significant socioeconomic burden on both individuals and whole health systems. This study was conducted to investigate the hospitalization cost of malaria and explore the inter-province variation during the National Malaria Elimination Programme in China. Methods Information on medical expenditure for malaria treatment was extracted from inpatient medical records in Henan, Hainan and Guangxi Province. The costs were adjusted to the price in 2014 and converted to USD (United States Dollars). Non-parametric and parametric methods were employed to estimate hospitalization costs and non-parametric bootstrap method was used for the comparison of hospitalization costs among sample provinces and to estimate the uncertainty of differences in inter-province hospitalization costs. Results The hospitalization cost and daily cost of 426 malaria inpatients were 929.8 USD and 143.12 USD respectively. The average length of stay was 11.95 days. The highest cost of hospitalization services occurred in tertiary hospitals (956 USD per episode). Whereas the lowest ones occurred in internal departments (424 USD). Medications, laboratory tests and supportive resources for treatment were the most important components of hospitalization costs, respectively responsible for 45.31, 24.70, and 20.09% of the total hospitalization costs. The hospitalization cost per episode in Henan Province was significantly higher than that in Hainan an in Guangxi Province, with incremental costs of 713 USD (95% confidence interval 419.70, 942.50) and of 735.58 USD (95% CI 606.50, 878.00), respectively. The differences in the daily costs between Henan and Hainan along with Guangxi provinces were 75.33 USD (95% CI 40.33, 96.67) and 93.56 USD (95% CI 83.58, 105.28), respectively. Conclusions Although the prevalence of malaria cases has considerably declined, the direct hospitalization costs of malaria in the household remain high and the inter-province variations need to be seriously considered in the formulation the further interventions regarding hospitalization cost control. This study suggests that economic risk protection mechanisms targeting at malaria inpatients should be redesigned. The drug price addition policy in public hospitals should be gradually reformed or abolished coupling with increasing government subsidies along with the charges for treatment services to reduce the hospitalization cost. The policy for cost control in the provincial hospitals should be implemented in comparison with the policy in other provinces, where the status of economic and geography are similar.

Abstract Background The current stage of malaria elimination in China requires experienced local health workers with sufficient knowledge of malaria who help to keep the public health system vigilant about a possible resurgence. However, the influencing factors of local health workers’ knowledge level are not fully comprehended. This study aims to explore the factors with heavy impact on local health worker’s knowledge of malaria and propose corresponding suggestions. Methods Underpinned by stratified sampling method, a cross-sectional survey was carried out between November 2014 and April 2016. Chi square test was performed to identify the factors with potential influence on health workers’ knowledge level of malaria. Bivariate logistic regression was employed to explore the relationship between the predictors and local health workers’ knowledge level of malaria. Layered Chi square test was used to calculate the homogeneity of the interaction between training approaches and the percentage of participants with high-level knowledge. Results The endemic type of county and type of organization played the most significant role in influencing local health workers’ knowledge level regarding malaria in the sample population. The participants from Type 1 and Type 2 counties were 4.3 times (4.336 and 4.328, respectively) more likely to have high-level knowledge of malaria than those who work in Type 3 counties. The probability of having high-level knowledge amongst the participants from county-level facilities (county hospitals and CDCs) were more than 2.2 times higher than those who work in villages. Other socio-demographic factors, such as education and work experience, also affected one’s knowledge regarding malaria. Amongst the six most-used training approaches, electronic material (OR = 2.356, 95% CI 1.112–4.989), thematic series (OR = 1.784, 95% CI 0.907–3.508) and supervision (OR = 2.788, 95% CI 1.018–7.632) were proven with significant positive impact on local health workers’ knowledge of malaria. Conclusion Village doctors and who served in Type 3 counties were identified as the ones in urgent need of effective training. Three types of training approaches, including electronic material, thematic series and supervision, were proven to be effective in improving local health workers’ knowledge. Nevertheless, the coverage of these training approaches was still limited. This study suggests expanding the coverage of training, especially the three particular types of training, to local health workers, particularly to the target populations (village doctors and who served in Type 3 counties). Online training, small group discussion and targeted skill development may be the directions for the future development of training programmes.

Abstract Background Men’s active involvement in reproductive healthcare has shown to be positively associated with maternal and child health outcomes. Bangladesh has made appreciable progress in its pursuance of maternal mortality related goals in the framework of the MDGs. However, there remains a lot to be accomplished to realise the long-term goals for which active participation of male counterparts in reproductive care is crucial. Therefore, the objective of the present study was to investigate factors associated with male involvement in reproductive health among Bangladeshi men. Methods We used data from Bangladesh Demographic and Health Survey (BDHS) conducted in 2011. Study participants were 1196 married men, aged between 15 and 69 years and living in both urban and rural households. Level of male involvement (outcome variable) was measured based on the responses on knowledge, awareness and practice regarding reproductive health. Chi-square tests and multivariable logistic regression models were performed for data analysis. Results Out of 1196 participants, only 40% were found to be active about partners’ reproductive healthcare. Chi-square test showed significant association between active involvement and ever hearing about family planning (FP) in television, learning about FP through community health events, community health workers and poster/billboard. Results from logistic regression analysis revealed that type of residency [p = 0.004, AOR = 0.666, 95% CI = 0.504–0.879], literacy [secondary/higher education- p = 0.006. AOR = 0.579, 95% CI = 0.165–0.509], learning about family planning from Newspaper [p

Insulation fails quickly under high-frequency AC high voltage, especially bipolar square-wave voltage with a high dV/dt. It is of great significance to study the failure mechanism of epoxy casting insulation under such kind of voltage. In this paper, pin-plane epoxy casting insulation samples with air gaps were prepared, and the relation between the electrical trees under the high frequency bipolar square-wave voltage and the air gap conditions and voltage frequencies (1~20 kHz) were studied. Results indicated that, with the presence of air gaps, the electrical trees were bush-type and had a relatively slow growth rate, which was different from the fast-growing branch-type trees in the samples without air gap. The electrical tree characteristics related with the size of air gap and voltage frequency were also studied. The electrical tree grew faster under higher voltage frequency or with a smaller air gap. Results proved that discharge introduced a lot of defects for the surface layer of the epoxy resin samples and hence induced the possibility of multi-directional expansion of electrical trees. In addition, the resulting heat accumulation and unique charge transport synergistically affected the electrical tree characteristics under the high frequency bipolar square-wave voltage.

Active flow control of surface dielectric barrier discharge (SDBD) plasma is a technology that converts electrical energy into kinetic energy to achieve flow control. Its main application areas are concentrated in the aviation field. Undoubtedly, few studies have applied it in the field of automobile flow control. Meanwhile, during high-speed driving, there is a serious airflow separation phenomenon at the rear of notch-back cars, which brings a large area of negative pressure to the back of the cars. Due to the huge pressure difference between the front and end of the cars, it will increase the driving drag and fuel cost of the car. In this context, we seek to discuss the control effect on the airflow separation at the rear of the notch-back by using the phenomenological numerical simulation method of plasma flow control. Firstly, the plasma actuator is arranged separately on the rear end of the roof, c-pillar, upper and side of the trunk to study the control effect of airflow separation. After that, the plasma actuators at each position are combined and actuated simultaneously. We try to observe the control effect of airflow separation and select the combination with the best drag reduction effect. In the third stage, an efficient global optimization (EGO) algorithm based on kriging response surface is applied to optimize the supply voltage of the best combination that has been obtained before and obtain the driving voltage parameter of each actuator optimized under this combination. The results show that when plasma actuation is applied at four locations, only the actuation applied to the side of the luggage compartment has a significant drag reduction effect, while in other cases, the drag coefficient will increase. Specifically, drag reduction is better when the actuation is applied at four positions simultaneously. The maximum drag reduction coefficient of the car is reduced by 13.17%.

Through analyzing coring well observation and in combination with drilling data log sheet and the analysis of the test data, combined with the regional sedimentary tectonic evolution background of the second member of Tengger formation in Jiergalangtu of Erlian basin, the results show that lithic arkose and feldspathic lithic sandstone are developed in the study area. There are abundant sedimentary structures, mainly including parallel bedding, laminated bedding and massive bedding, etc. According to the analysis of sedimentary characteristics, nine lithofacies types and four vertical assemblages are summarized, which respectively reflect different microfacies environments: subaqueous distributary channel subaqueous distributary channel interestuarine bar sheet sand.

The high interior heterogeneity of land surface covers in high-resolution image of coastal cities makes classification challenging. To meet this challenge, a Multi-Scale Superpixels-based Classification method using Optimized Spectral−Spatial features, denoted as OSS-MSSC, is proposed in this paper. In the proposed method, the multi-scale superpixels are firstly generated to capture the local spatial structures of the ground objects with various sizes. Then, the normalized difference vegetation index and extend multi-attribute profiles are introduced to extract the spectral−spatial features from the multi-spectral bands of the image. To reduce the redundancy of the spectral−spatial features, the crossover-based search algorithm is utilized for feature optimization. The pre-classification results at each single scale are, therefore, obtained based on the optimized spectral−spatial features and random forest classifier. Finally, the ultimate classification is generated via the majority voting of those pre-classification results in each scale. Experimental results on the Gaofen-2 image of Qingdao and WorldView-2 image of Hong Kong, China confirmed the effectiveness of the proposed method. The experiments verify that the OSS-MSSC method not only works effectively on the homogeneous regions, but also is able to preserve the small local spatial structures in the high-resolution remote sensing images of coastal cities.

Extracting buildings from very high resolution (VHR) images has attracted much attention but is still challenging due to their large varieties in appearance and scale. Convolutional neural networks (CNNs) have shown effective and superior performance in automatically learning high-level and discriminative features in extracting buildings. However, the fixed receptive fields make conventional CNNs insufficient to tolerate large scale changes. Multiscale CNN (MCNN) is a promising structure to meet this challenge. Unfortunately, the multiscale features extracted by MCNN are always stacked and fed into one classifier, which make it difficult to recognize objects with different scales. Besides, the repeated sub-sampling processes lead to a blurred boundary of the extracted features. In this study, we proposed a novel parallel support vector mechanism (SVM)-based fusion strategy to take full use of deep features at different scales as extracted by the MCNN structure. We firstly designed a MCNN structure with different sizes of input patches and kernels, to learn multiscale deep features. After that, features at different scales were individually fed into different support vector machine (SVM) classifiers to produce rule images for pre-classification. A decision fusion strategy is then applied on the pre-classification results based on another SVM classifier. Finally, superpixels are applied to refine the boundary of the fused results using region-based maximum voting. For performance evaluation, the well-known International Society for Photogrammetry and Remote Sensing (ISPRS) Potsdam dataset was used in comparison with several state-of-the-art algorithms. Experimental results have demonstrated the superior performance of the proposed methodology in extracting complex buildings in urban districts.