How Belief in a Just World Benefits Mental Health: The Effects of Optimism and Gratitude

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Past research suggests that individuals’ belief in a just world (BJW) is closely connected with their mental health. To clarify the underlying mechanism, the current study proposes that BJW encourages optimism and gratitude which then mediates the relation- ship between BJW and mental health as indicated by subjective well-being (SWB) and depression. A sample of 1,200 undergraduates yields results indicating that (a) BJW influences optimism, gratitude, SWB, and depression after controlling for gender, age, income, and personality; (b) optimism and gratitude mediate BJW effects by increasing SWB and decreasing depression. The issues of BJW’s adaptive functions are discussed

慢性心力衰竭患者心率减速力与心率变异性检测的临床意义

Objective: To study the change of heart rate deceleration capacity ( DC ) and heart rate variability in patients with chronic heart failure (CHF) and its relationship with left ventricular ejection fraction (LVEF). Methods: DC, LVEF, time and frequency domain parameters of HRV were measured in 66 patients with CHF and 34 healthy adults (control group) by using 24h Holter recordings and Echocardiography. The standard deviation of normal R-R intervals( SDNN), squares of differences between adjacent NN intervals ( RMSSD)，low frequency power( LFn ) and high frequency power( HFn ) and the changes of LVEF were compared between  the two groups，the relationship between DC，LVEF and HRV were studied in patients with CHF. Results: The median value of DC in the patients with CHF was significantly lower than that in control group( 3.1 ± 2.4 ms vs 7.2 ± 1.3 ms，P <0.01)．Incidence of abnormal DC in the CHF group was 57.5%，which was significantly higher than that in the control group (P <0.01)．The HRV index, including SDNN、RMSSD、LFn、HFn, in the CHF group was significantly lower than that in normal control group (P < 0.01). Significant positive correlation between HRV index and LVEF were confirmed (P < 0.01). Conclusions: DC and HRV index are lower in patients with CHF and have a good correlation with the left ventricular ejection fraction.目的 探讨心率减速力与心率变异性在慢性心力衰竭和健康者变化的临床意义及其与左室射血分数之间的关系。方法 66例慢性心力衰竭患者和34 例健康者接受24 h 动态心电图检查和超声心动图检查，分别测定两组患者的DC、HRV时域指标( SDNN，RMSSD ) 与标化的频域指标( LFn、HFn ) 及LVEF；比较两组患者的DC、SDNN，RMSSD、LFn 、HFn及LVEF的变化，比较DC 与LVEF 及HRV各指标之间的关系。结果 CHF患者的DC 值明显小于正常对照组( 3.1±2.4 ms vs 7.2±1.3 ms，P＜0.05)，其DC异常患者的比率高达57.5%，明显高于正常对照组( P＜0.05 )；HRV指标(SDNN、RMSSD、LFn、HFn)，CHF组明显低于正常对照组( P＜0.05)。CHF 组HRV指标与LVEF之间具有相关性( P＜0.05)。结论 CHF患者的DC值及HRV值明显降低,与左室射血分数之间具有一定相关性

Modeling and Optimal Control of Atmospheric Pollution Hazard in Nuclear and Chemical Disasters

AbstractNuclear and chemical disasters can cause heavy atmospheric pollution hazard and threat people's lives and health. In this paper, theory and application for modeling and optimal control of such hazard is studied. The modeling is based on the simulation and visualization of atmospheric dispersion of pollutants, the source term estimation of nuclear and chemical disasters, and the risk evaluation of hazardous substances. The optimal control is based on Natural Cybernetics theory, effective and economic cost evaluation of control techniques, and optimization methods. Some applications and illustrations of modeling and optimal control are reported

Review of photoacoustic imaging plus X

Photoacoustic imaging (PAI) is a novel modality in biomedical imaging technology that combines the rich optical contrast with the deep penetration of ultrasound. To date, PAI technology has found applications in various biomedical fields. In this review, we present an overview of the emerging research frontiers on PAI plus other advanced technologies, named as PAI plus X, which includes but not limited to PAI plus treatment, PAI plus new circuits design, PAI plus accurate positioning system, PAI plus fast scanning systems, PAI plus novel ultrasound sensors, PAI plus advanced laser sources, PAI plus deep learning, and PAI plus other imaging modalities. We will discuss each technology's current state, technical advantages, and prospects for application, reported mostly in recent three years. Lastly, we discuss and summarize the challenges and potential future work in PAI plus X area