ABSTRACT
This paper presents a study on the mechanical properties of cement-stabilized steel-slag-based materials under freeze-thaw cycles for a highway project in Xinjiang. Using 3D scanning technology the specimen model conforming to the real steel slag shape was established. The objectives of the study are as follows: to explore the sensitivity between the macro- and micro-parameters of the specimen and to establish a non-linear regression equation; and to study the changes in mechanical properties of materials under freeze-thaw cycles, fatigue loading, and coupled freeze-thaw cycle-fatigue loading. The results show that there are three stages of compression damage of the specimen, namely, linear elasticity, peak plasticity, and post-peak decline. Maximum contact forces between cracks and particles occur mainly in the shear zone region within the specimen. The compression damage of the specimen is a mixed tensile-shear damage dominated by shear damage. When freeze-thaw cycles or fatigue loads are applied alone, the flexural strength and fatigue life of the specimens show a linear relationship of decline. The decrease in flexural modulus at low stress is divided into the following: a period of rapid decline, a relatively smooth period, and a period of fracture, with a tendency to change towards linear decay with increasing stress. In the case of freeze-thaw-fatigue coupling, the flexural modulus of the specimen decreases drastically by about 50% in the first 2 years, and then enters a period of steady decrease in flexural modulus in the 3rd-5th years.
ABSTRACT
BACKGROUND: Studies have shown that sleep disorders are closely related to anxiety and depression, and the quality of life (QoL) of patients with sleep disorders is generally poor. AIM: To examine the occurrence of sleep disorders in people with coronary heart disease (CHD) and their relationships with QoL, depression, and anxiety. METHODS: As per the sleep condition, 240 CHD individuals were separated into two groups: non-sleep disorder group (n = 128) and sleep disorder group (n = 112). The self-rating anxiety scale (SAS), self-rating depression scale (SDS), and World Health Organization criteria for the Quality of Life Brief scale (WHOQOL-BREF) scores of the two groups were compared. Logistic regression method was used to analyze the independent risk factors of CHD patients with sleep disorders. Multivariate logistic regression analysis was employed to develop the risk prediction model. The association among the Pittsburgh Sleep Quality Index, SAS, and SDS was examined using Spearman's correlation analysis. RESULTS: The incidence of sleep disorder was 46.67% in 240 patients. The scores of SAS and SDS in the sleep disorder group were higher than those in the non-sleep disorder group, and the WHOQOL-BREF scores were lower than those in the non-sleep disorder group (P < 0.05). The risk prediction model of sleep disturbances in CHD patients was constructed using the outcomes of multivariate logistic regression analysis, P = 1/[1 + e (-2.160 + 0.989 × (female) + 0.001 × (new rural cooperative medical insurance) + 2.219 × (anxiety) + 2.157 × depression)]. The results of a Spearman's correlation study revealed that sleep quality was strongly adversely connected with the physiological field, psychological field, and social relation scores in QoL, and was considerably positively correlated with SAS and SDS (P < 0.05). CONCLUSION: A multivariate logistic regression model can better predict the occurrence of sleep disorders in CHD patients. Sleep disorders in CHD patients are significantly correlated with QoL, depression, and anxiety.
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We present an erratum to our Letter [Opt. Lett.47, 3688 (2022)10.1364/OL.463637]. This erratum corrects subscript errors in Eq. (1), H1 and H2. These errors could confuse readers when they perform the derivation processes, but the errors do not affect our experimental results. Therefore, these corrections do not affect the results and conclusions of the original Letter.
ABSTRACT
This Letter proposes a novel, to the best of our knowledge, intensity-modulation transmitter equipped with an optical intensity feedback (OIF) loop, which mitigates the holistic nonlinearity on both sides of intensity modulation and direct detection (IM/DD) transceivers from solely the transmitter side. In contrast to the recent effort on pre-distortion, we construct a negative feedback loop bridging the optical intensity of light-emitting diodes (LEDs) toward a sensor for nonlinearity perception to suppress the nonlinearity among all physical devices. In the meantime, we propose an analytical model for the feedback loop and an implementation scheme. The experimental results demonstrate a significant linearity improvement in the total harmonic distortion (THD) and the power gain flatness. More specifically, the average THD of the bipolar junction transistor (BJT)-based OIF transceiver is -49.4 dB (0.37%) and the minimum power gain variance is 0.0005, 0.0025% of the control group. As for the transceiver using a metal-oxide-semiconductor field-effect transistor (MOSFET), its average THD is -52.42 dB (0.25%) and the minimum power gain variance can reach 0.0026. Not only that, since the method only takes advantage of the negative feedback feature and dose not rely on any particular module, it has lower complexity and better applicability.
ABSTRACT
Although epidemiology and toxicology studies have demonstrated that exposure to ambient air particles could result in a variety of lung diseases, but the pulmonary toxicological mechanism remains obscure. In this study, the toxicity of PM2.5 particles in different concentrations was investigated by toxicological methods, including the luminescent bacteria acute toxicity test and genotoxicity performed by SOS chromogenic reaction. The results indicated that, the acute toxicity and genotoxicity were low and negative, respectively. In addition, rats were treated with PM2.5 suspension through intratracheal instillation, and the pathologic changes and expression of different genes in their lungs were carried out. We found that PM2.5 exposure resulted in fibrotic changes and inflammation in the lung with the increase in PM2.5 concentration. Pathway analysis indicated that PM2.5 can induce pulmonary toxicity through disturbing the function of ribosomal protein, fatty acids, and cholesterol metabolism, suggesting an inflammatory reaction in the lung is caused by genetic damage and is irreversible. A gene ontology analysis revealed that abnormal expression of related genes in the immune response could be the specific pathway of lung inflammation. These findings improve our understanding of the toxicological pathway and mechanism of PM2.5 exposure.
