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Abstract In the mechanical cutting industry, trial production is used for predicting and evaluating the quality of product processes before batch production, and it can be expressed through the qualification rate. However, it cannot objectively and comprehensively evaluate the quality of product processes. This study optimizes the analysis of outliers and stability in mathematical statistics to better apply it in the mechanical cutting industry; then, it combines them with process capability analysis. Simultaneously, considering the non-normal distribution of process parameters, a batch production-prediction model is proposed. The reliability of batch production-prediction model is verified by the diameter, roundness and roughness of structural common samples. Meanwhile, for other mechanical parts in the mechanical cutting industry, the model proposed in this paper can be used to quickly and accurately predict and evaluate batch production.

Stems are prone to bending or lodging due to inadequate stem strength, which seriously reduces the cut-flower ornamental quality of herbaceous peony (Paeonia lactiflora Pall.). Plant LACCASE (LAC), a copper-containing polyphenol oxidase, has been shown to participate in the polymerization process of monolignols; however, the role of LAC in regulating the stem strength of P. lactiflora remains unclear. Here, the full-length cDNA of PlLAC15, which demonstrated a positive association with stem strength, was isolated. It consisted of 1790 nucleotides, encoding 565 amino acids that had four typical laccase copper ion-binding domains. Moreover, PlLAC15 was highly expressed in the stem, and its expression level gradually significantly increased during stem development. Furthermore, PlLAC15 was found to be localized specifically to the cell wall, and its recombinant protein exhibited laccase activity. Additionally, the role of PlLAC15 in regulating the stem strength of P. lactiflora was confirmed by transgenic studies. When PlLAC15 was overexpressed in tobacco, stem strength increased by more than 50%, S-lignin was significantly deposited, and the lignification degree of stem xylem fiber cells increased. These results suggested that PlLAC15 facilitated S-lignin deposition to enhance stem strength in P. lactiflora, which would provide precious information that benefits future exploration of stem bending or lodging resistance in plants.

The blockchain provides a reliable and scalable method for enabling source-tracing functionality in large-scale Internet of Things (IoT) systems. Traditional blockchain-based source tracing applications are generally based on the hypothesis that the raw data collected by each IoT node are credible and consistent, which however may not always be the truth. As no mechanism ensures the reliability of the original data collected from the IoT devices, these data may be accidently screwed up or maliciously tampered with before they are uploaded on-chain. To address this issue, we propose the Multi-dimensional Certificates of Origin (MCO) method to filter out the potentially incredible data-till all the data uploaded to the chain are credible. To achieve this, we devise the Multi-dimensional Information Cross-Verification (MICV) and Multi-source Data Matching Calculation (MDMC) methods. MICV verifies whether a to-be-uploaded datum is consistent or credible, and MDMC determines which data should be discarded and which data should be kept to retain the most likely credible/untampered ones in the circumstance when data inconsistency appears. Large-scale experiments show that our scheme ensures on the credibility of data and off the chain with an affordable overhead.

Abstract Background The stress hyperglycemia ratio (SHR) has demonstrated a noteworthy association with unfavorable cardiovascular clinical outcomes and heightened in-hospital mortality. Nonetheless, this relationship in critically ill patients remains uncertain. This study aims to elucidate the correlation between SHR and patient prognosis within the critical care setting. Methods A total of 8978 patients admitted in intensive care unit (ICU) were included in this study. We categorized SHR into uniform groups and assessed its relationship with mortality using logistic or Cox regression analysis. Additionally, we employed the restricted cubic spline (RCS) analysis method to further evaluate the correlation between SHR as a continuous variable and mortality. The outcomes of interest in this study were in-hospital and 1-year all-cause mortality. Results In this investigation, a total of 825 (9.2%) patients experienced in-hospital mortality, while 3,130 (34.9%) individuals died within the 1-year follow-up period. After adjusting for confounding variables, we identified a U-shaped correlation between SHR and both in-hospital and 1-year mortality. Specifically, within the SHR range of 0.75–0.99, the incidence of adverse events was minimized. For each 0.25 increase in the SHR level within this range, the risk of in-hospital mortality rose by 1.34-fold (odds ratio [OR]: 1.34, 95% CI: 1.25–1.44), while a 0.25 decrease in SHR within 0.75–0.99 range increased risk by 1.38-fold (OR: 1.38, 95% CI: 1.10–1.75). Conclusion There was a U-shaped association between SHR and short- and long-term mortality in critical ill patients, and the inflection point of SHR for poor prognosis was identified at an SHR value of 0.96.

Pyroelectric materials, with piezoelectricity and pyroelectricity, have been widely used in infrared thermal detectors. In this paper, a modified first-order plate theory is extended to analyze a pyroelectric sensitive element structure. The displacement, temperature, and electric potential expand along the thickness direction. The governing equation of the pyroelectric plate is built up. The potential distributions with upper and lower electrodes are obtained under different supported boundary conditions. The corresponding numerical results of electric potential are consistent with those obtained by the three-dimensional finite element method. Meanwhile, the theoretical results of electric potential are close to that of experiments. The influence of supported boundary conditions, piezoelectric effect, and plate thickness are analyzed. Numerical results show that the piezoelectric effect reduces the electric potential. The thickness of the pyroelectric plate enhances the electric potential but reduces the response speed of the detector. It is anticipated that the pyroelectric plate theory can provide a theoretical approach for the structural design of pyroelectric sensitive elements.

The microstructural evolution and hardening mechanism caused by carburizing heat treatment must be determined to improve the in-service functional performance of components used in advanced equipment for aerospace and other industrial applications. Carburizing heat treatment causes the microstructure to exhibit heterogeneous characteristics in the depth direction. In this study, the effects of carburizing heat treatment on the microstructure and hardening mechanism of 18CrNiMo7-6 steel were investigated. The experimental results show the residual austenite (RA) content in the carburized surface reached 56.2% and the RA content in the core was 0.1% after carburizing heat treatment. The kernel average misorientation (KAM) value, grain size, low angle grain boundaries (LAGBs) content, and dislocation density caused by carburizing heat treatment increased with increasing depth. After the carburizing heat treatment, considerable grain refinement occurred, and the minimum grain size of the carburized surface was 3.19 μm. The microhardness of the carburized layer first rose and then reduced, achieving a maximum of 686 HV, which was 57.7% higher than that of the quenching and tempering (uncarburized) samples. In addition, it was found that grain boundary and solution strengthening played a prominent position in the hardening mechanism of the carburized layer. This study has deepened the current understanding of the hardening mechanism of 18CrNiMo7-6 steel during carburizing heat treatment.

Summary:. The displacement of a lost contact lens into the upper fornix is an uncommon occurrence. This case report presents a rare incidence wherein a patient diagnosed with hemifacial atrophy was found to have concealed five soft contact lenses within the left upper fornix during autologous fat injection into the retrobulbar space.

Titanium alloys are widely used in aviation, marine, automotive, offshore, and medical fields. However, their poor wear resistance reduces the safety and reliability of components during service. Few study has been previously conducted on the wear resistance enhancement of titanium alloys (including Ti–6Al–4V alloy) processed by mechanical cutting. High-speed ultrasonic vibration cutting (HUVC) is an effective approach for improving the machinability of titanium alloys. In this study, we attempted to utilize HUVC improving the wear resistance of titanium alloys. After conducting high-speed turning (cutting speed within the range of 200–300 m/min), the surface integrities (surface roughness, microstructure, in-depth micro-hardness, and residual stress) of conventional cutting (CC)- and HUVC-machined samples were characterized. Experimental results demonstrated that, compared with CC, HUVC achieved a thicker plastic deformation layer (greater than 46.93 μm), lower surface roughness, higher surface micro-hardness (greater than 433 HV0.05), and higher compressive residual stress (up to −840 MPa). Moreover, surface nanocrystallization and gradient nanostructured layer were observed in HUVC-machined Ti–6Al–4V samples. In addition, compared with CC, HUVC effectively further reduced the friction coefficient and worn volume loss (decreased by 20.98%–25.59%) and ultimately improved the wear resistance. The hardness has a higher influence on the wear resistance of the machined Ti–6Al–4V alloy than the other surface integrity factors. Therefore, the proposed mechanical cutting operation was confirmed to improve the wear resistance of titanium alloys.

As global warming progresses, heat waves are becoming increasingly frequent and intense, meanwhile the incidence of heat stroke (HS) has increased sharply during the past decades. HS is typically associated with significant morbidity and mortality, and there is an urgent need for further research to solve this difficult issue. There currently exists difficulties regarding on-site emergency treatment methods and limited in-hospital treatment approaches, and better treatments are required as soon as possible. Theories and therapies from various traditional Chinese medicine (TCM) academic groups have been widely reported. Therefore, an exploration of prevention and protection methods should consider TCM experiences as an alternative. This article primarily reviews TCM herbal therapies and external therapies that have been described in various clinical reports and demonstrated in relevant studies. Herbal therapies, including herbal formulas, Chinese patent medicines (CPMs), single Chinese herbs, and associated extracts or monomers, are summarized based on the shared perspectives of the underlying mechanisms from TCM. In addition, external therapies including acupuncture, bloodletting, cupping, Gua sha and Tui na that have rarely been rarely mentioned and considered in most cases, are introduced and discussed to offer a unique perspective in the search for novel interventions for HS. In summary, TCM may provide abundant potential clinical benefits and research directions in the fight against HS.

In typical alteration extraction methods, e.g., band math and principal component analysis (PCA), the bands or band combinations unitized to extract altered minerals are usually selected based on empirical models or previous rules. This results in significant differences in the alteration of mineral mapping even in the same area, thus greatly increasing the uncertainty of mineral resource prediction. In this paper, an intelligent alteration extraction approach was proposed in which an optimization algorithm, i.e., a genetic algorithm (GA), was introduced into the PCA; this approach is termed GA-PCA and is used for selecting the optimized band combinations of mineralized alterations. The proposed GA-PCA was employed to map iron oxides and hydroxyl minerals using the most commonly adopted multispectral data, i.e., Landsat-8 OLI data, at the Lalingzaohuo polymetallic deposits, China. The results showed that the spectral characteristics of GA-PCA-selected OLI band combinations in the research area were beneficial for enhancing alteration information and were more capable of suppressing the interference of vegetation information. The mapping alteration zones using the GA-PCA approach had a higher agreement with known ore spots, i.e., 25% and 33.3% in ferrous-bearing and hydroxyl-bearing deposits, compared to the classical PCA. Furthermore, two predicted targets (not shown in the classical PCA results) were precisely obtained via analyzing the GA-PCA alteration maps combined with the ore-forming geological conditions of the mine and its tectonic characteristics. This indicated that the intelligent selection of mineral alteration band combinations increased the reliability of remote sensing-based mineral exploration.

This work considers the analytical solution of the contact problem between a conical indenter and a transversely isotropic material, and uses a finite element method to determine the correction coefficient to implement in the analytical solution involving a Vickers indenter. Meanwhile, an indentation characterization method was established to determine the elastic modulus of the transversely isotropic material. By applying the finite element model of indentation to evaluate transversely isotropic materials, the dimensionless functions used to compute the yield strength, strain-hardening exponent, and yield strength ratio could be established based on the sensitivity analysis of the plastic parameters. The anisotropic elastic–plastic properties of surface-modified layers (SMLs) were characterized by treating the SML as several layers of transversely isotropic material. Indentation tests were carried out to study the SMLs at different depths, and their elastic–plastic parameters were obtained using the proposed method. The results indicate that the elastic modulus in the longitudinal direction and the isotropic plane at the same depth are distinct, and there is a small difference between the yield strengths in the longitudinal and vertical directions of the heat-treated 18CrNiMo7-6 alloy steel. However, the yield strength ratios in both directions are generally constant along the depth of the SML. As the depth of the SML increases, the yield strength and hardening index also decrease gradually.

In this paper, we systematically investigate the synergistic regulation of ultraviolet and mechanical loading on the electromechanical behavior of a GaN nanowire. The distributions of polarization charge, potential, carriers, and electric field in the GaN nanowire are analytically represented by using a one-dimensional model that combines pyro-phototronic and piezo-phototronic properties, and then, the electrical transmission characteristics are analyzed. The results suggest that, due to the pyro-phototronic effect and ultraviolet photoexcited non-equilibrium carriers, the electrical behavior of a nano-Schottky junction can be modulate by ultraviolet light. This provides a new method for the function improvement and performance regulation of intelligent optoelectronic nano-Schottky devices.

Abstract Background The 15-item Geriatric Depression Scale (GDS-15) shows good performance in detecting depression among older persons, but its applicability has not been well studied in non-Western oldest-old adults and centenarians. This study aimed to evaluate the psychometric property of the GDS-15 and a simplified version among a large representative longevous population in China. Methods A total of 1624 individuals (786 oldest-old persons aged from 80 to 99 years; 838 centenarians aged 100+ years) participated in this study. Home interviews with structured questionnaires were conducted to collect sociodemographic data. Depressive symptoms were measured using the Chinese GDS-15 version. We implemented mixed methods for the psychometric evaluation of the GDS-15. Cronbach’s α coefficient and item-total correlation coefficients were used to evaluate the internal consistency. A standard expert consultation was conducted to test the content validity of each item. Multiple factor analyses were used to explore the optimal factor structure and measurement invariance. Results The α coefficient of the GDS-15 was 0.745, while two items impaired the overall consistency reliability. Nineteen experts rated the applicability for each item and provided removal suggestion. Five items with less validity were removed, and a simplified 10-item GDS model with three-factor structure was proposed as an optimal solution. The GDS-10 model showed factorial equivalence across age, sex, residence, and education in multi-group confirmatory factor analyses. Conclusions The original GDS-15 has acceptable internal reliability, known-group validity, and concurrent validity among Chinese community-dwelling oldest-old and centenarians; however we provided preliminary evidence indicating that individual items related to somatic function or social activities may not be applicable for this population. The modified GDS-10 can be proposed as a potentially more practical and comprehensible instrument for depression screening.

Carburizing heat treatment is widely used in the fabrication of gears to improve their fatigue performance. The effects of carburizing process on the material properties surface hardness, residual stresses, retained austenite of case-hardened 18CrNiMo7-6 and the consequential fatigue strength have not been studied in detail. In this research, the high-cycle fatigue performance of uncarburized and carburized 18CrNiMo7-6 gear steel were studied. In addition, the evolution processes of hardness, microstructure and residual stress of carburized specimens during the fatigue test were observed quasi-in situ. The initiation of fatigue cracks was also analyzed by SEM and the transformation of retained austenite during the fatigue test was observed by TEM. The results showed that the fatigue strength of carburized specimens has an increase-decrease trend with the increase of effective case depth. Besides, the fatigue failure mode of steel changes from surface failure to internal failure after being carburized, during which retained austenite plays an important part. In addition, if a large amount of retained austenite exists in the specimen with internal failure, the high-density twin martensite region formed by the retained austenite transformation can act as the crack initiation site, which is harmful to fatigue performance.

GaN is an excellent material choice for power devices due to its excellent properties such as super wide bandgap width and high electron mobility. However, the problem of temperature affects the thermo reliability and hinders the potential of GaN devices. In this paper, the electrical properties of GaN under temperature have been studied by the combination of numerical simulation and experimental research. The electric current change and electrical resistivity of polarized and depolarized GaN semiconductor samples were tested in an environment-test cabinet. Based on the influence of temperature, the expression of the resistivity curve vs temperature was established for polarized and depolarized GaN samples. It is shown that the resistivity model predictions are consistent with experimental results. The I–V characteristic curves under different temperatures were also measured. Thus, such a model is instructive to the reliable design of GaN high-temperature devices. The findings will be instructive to the optimal design of GaN electronic components.

A surface-modified layer (SML) can play an important role in the durability and in-service behavior of key components, but characterization of the mechanical properties of SML is complex. In this paper, an indentation method to characterize the plastic parameters of the SML is proposed. The method combines indentation tests and finite element simulation to analyze the plastic parameters of the SML. The yield strength and hardening index of the SML for 18CrNiMo7-6 alloy steel, before and after heat treatment, were characterized using the proposed method. After heat treatment, the yield strength and hardening index decreased gradually along the depth. The results obtained agree with the tensile test results.

ABSTRACT: Background: Infection is a relevant complication of tissue expander surgery that may compromise the flap. The effects of meteorological variables on surgical site infection have been observed in many surgeries; however, their influence on tissue expander infection is unknown. Methods: We identified tissue expander implantation and infection based on their International Classification of Diseases, 10th revision, codes in electronic hospitalization summary reports of 26 cities from January 1, 2014 to December 31, 2015. The data of the present study were collected for administrative purposes without any personal identifiers. The Cox proportional hazard model was used to investigate the association between meteorological variables and tissue expander-related major infection with six covariates. Results: A total of 3,089 patients were enrolled. Of them, 8.7% experienced a major infection during the study period. The optimal daily average temperature was between 22.9 °C and 26.8 °C, and the risk of major infection was significantly decreased in this range. The minimal infection temperature was 24.4 °C, with a hazard ratio of 0.85. When the average relative humidity was 37%, the infection risk was minimal with a hazard ratio of 0.86; however, a relative humidity of ≥ 79% significantly increased the risk of infection. Conclusions: This is the first study to investigate the impact of temperature and relative humidity on tissue expander-related major infection. Our study suggests that there may be an optimal range of both temperature (22.9 °C–26.8 °C) and relative humidity (< 79%) that can lower the risk of major infection after tissue expander implantation.

Hypertrophic scar causes serious functional and cosmetic problem, but no treatment method is known to achieve a satisfactory therapeutic effect. However, mesenchymal stem cells show a possible cure prospect. Here, we investigated the effect of interleukin-10-modified adipose-derived mesenchymal stem cells (IL-10-ADMSC) on the formation of hypertrophic scar. In vitro, IL-10-ADMSC could highly express IL-10 and exhibited stronger inhibition of hypertrophic scar fibroblasts (HSFs) proliferation, migration, and extracellular matrix synthesis (the expression of collagen I, collagen III, FN, and α-SMA protein) than ADMSC. In vivo, we found that IL-10-ADMSC speeded up wound healing time and reduced scar area and scar outstanding height. Same as in vitro, IL-10-ADMSC also exhibited stronger inhibition of extracellular matrix synthesis (the expression of collagen I, collagen III protein) in wound than ADMSC. In addition, we also found that IL-10-ADMSC is also a stronger inhibitory effect on inflammation in wound than ADMSC, and IL-10-ADMSC inhibited TGF-β/Smads and NF-κB pathway. In conclusion, IL-10-ADMSC demonstrated the ability to prevent hypertrophic scar formation. And its possible molecular mechanism might be related to IL-10-ADMSC inhibiting the proliferation and migration of the synthesis of extracellular matrix of HSFs, and IL-10-ADMSC inhibited the inflammation during the wound healing.

In this paper, we propose a one-dimensional model that combines photoelectricity, piezoelectricity, and photothermal effects. The influence of ultraviolet light on the electromechanical coupling properties of GaN nanowires is investigated. It is shown that, since the ultraviolet photon energy is larger than the forbidden gap of GaN, the physical fields in a GaN nanowire are sensitive to ultraviolet. The light-induced polarization can change the magnitude and direction of a piezoelectric polarization field caused by a mechanical load. Moreover, a large number of photogenerated carriers under photoexcitation enhance the current density, whilst they shield the Schottky barrier and reduce rectifying characteristics. This provides a new theoretical nanoarchitectonics approach for the contactless performance regulation of nano-GaN devices such as photoelectric sensors and ultraviolet detectors, which can further release their great application potential.

The marine environment presents a unique set of challenges for human–robot interaction. Communicating with gestures is a common way for interacting between the diver and autonomous underwater vehicles (AUVs). However, underwater gesture recognition is a challenging visual task for AUVs due to light refraction and wavelength color attenuation issues. Current gesture recognition methods classify the whole image directly or locate the hand position first and then classify the hand features. Among these purely visual approaches, textual information is largely ignored. This paper proposes a visual–textual model for underwater hand gesture recognition (VT-UHGR). The VT-UHGR model encodes the underwater diver’s image as visual features, the category text as textual features, and generates visual–textual features through multimodal interactions. We guide AUVs to use image–text matching for learning and inference. The proposed method achieves better performance than most existing purely visual methods on the dataset CADDY, demonstrating the effectiveness of using textual patterns for underwater gesture recognition.

Background: The COVID-19 pandemic brought about great transformation to medical education mode. Although mobile communication devices played a crucial role in online learning among quarantined university students, the potential smartphone addition problems, negative health behaviors, and psychological symptoms need considerable attention. This study examined the relationship of problematic smartphone use (PSU), sleep quality, and daytime fatigue among medical students.Methods: A web-based survey was conducted in six polyclinic hospitals in Beijing between February and May 2020. 1016 participants (26.01 ± 2.46 years, 65.16% female) completed self-report measurements including Short Version Smartphone Addiction Scale (SAS-SV), Athens Insomnia Scale (AIS), and Subjective Fatigue Scale (FS). Spearman correlation coefficients and multiple regression models were used to analyze the association among PSU, sleep quality, and daytime fatigue. We used structural equation modeling to test the mediating effect of sleep quality between PSU and daytime fatigue.Results: 49.70% of the participants had PSU. Significant positive correlations were found among SAS-SV, AIS, and FS scores (r = 0.35–0.61, PS < 0.001). Subjects with PSU were more likely to report sleep disturbance (β = 1.07, P < 0.001, OR = 2.91, 95%CI = 2.17–3.91), physical fatigue (β = 1.16, P < 0.001, OR = 3.18, 95%CI = 2.45–4.15), and mental fatigue (β = 0.88, P < 0.001, OR = 2.42, 95%CI = 1.86–3.14). The indirect effect of PSU on physical fatigue and mental fatigue mediated by sleep quality accounted for 50.03 and 45.43% of the total effect, respectively.Conclusions: PSU was significantly associated with sleep disturbance and fatigue among medical students during the COVID-19 pandemic. Sleep quality mediated the relationship between PSU and daytime fatigue. Our results provide valuable information for maintaining medical students' health status and constructing online education structures.

Target search for moving and invisible objects has always been considered a challenge, as the floating objects drift with the flows. This study focuses on target search by multiple autonomous underwater vehicles (AUV) and investigates a multi-agent target search method (MATSMI) for moving and invisible objects. In the MATSMI algorithm, based on the multi-agent deep deterministic policy gradient (MADDPG) method, we add spatial and temporal information to the reinforcement learning state and set up specialized rewards in conjunction with a maritime target search scenario. Additionally, we construct a simulation environment to simulate a multi-AUV search for the floating object. The simulation results show that the MATSMI method has about 20% higher search success rate and about 70 steps shorter search time than the traditional search method. In addition, the MATSMI method converges faster than the MADDPG method. This paper provides a novel and effective method for solving the maritime target search problem.

The Internet of Medical Things (IoMT) is one of the most promising applications of the newly emerging wearable devices and body-area networks. Generally, the IoMT devices are composed of lightweight facilities, which collect the health data (i.e., heart rate, body temperature, and respiratory rate) and upload them to the cloud. As the medical information is sensitive for the data owners (DOs), it is critical to ensure the integrity and confidentiality of these outsourced data. Normally, blinding (or encryption) and auditing are classical methods for achieving these goals. However, until to now, quite a few batch auditing schemes have been proposed, and they all share the following two shortcomings: 1) lacking of an efficient mechanism to identify the corrupted data files once the batch auditing task fails and 2) the communication overhead of audit phase increases linearly with the number of data files being audited or the number of data blocks being challenged. In order to overcome the above issues, in this paper, we propose an efficient batch auditing scheme based on the Lucas sequence for IoMT. To be specific, utilizing the self-query technique and polynomial commitment technique, we reduce the communication complexity of the batch auditing phase from linear to a constant scale. In addition, according to the recursion of the Lucas sequence, we design a novel search method for efficiently identifying the corrupted data files when the batch auditing task fails. The security of our scheme ensures that curious third-party auditor and cloud service provider cannot gain any real-data contents of the DO files. The detailed experiments show that our scheme is more efficient than the existing batch auditing schemes in terms of the communication overhead of the audit phase and the efficiency in identifying the corrupted files when the batch auditing task fails.

It is always difficult to evacuate crowds in public places like subway stations. The traditional crowd behavior simulation models often ignore two important issues in crowd evacuation: pedestrian tracking and individual differences. To solve the problem, this paper combines social force model (SFM) with deep learning into a novel pedestrian detection method. Firstly, several deep learning algorithms for pedestrian detection were compared, and the best ones for sparse and dense crowds were determined. Next, the pedestrian positions in a real video were acquired by the selected algorithms, and converted into actual coordinates in the scene. Then, the evacuation process was simulated with our method and the SFM based on these coordinates. The results show that our model output closer-to-reality results than the SFM. The research findings shed important new light on evacuation in crowded areas.

Background: Medical students are affected by high levels of general anxiety disorder. However, few studies have specifically focused on the applicability of universal anxiety screening tools in this sample. This study was aimed to evaluate the psychometric property of the 7-item Generalized Anxiety Disorder Scale (GAD-7) among Chinese medical university students.Methods: A questionnaire survey was conducted among 1,021 medical postgraduates from six polyclinic hospitals. Internal consistency and convergent validity of the GAD-7 were evaluated. Factor analyses were used to test the construct validity of the scale. An item response theory (IRT) framework was used to estimate the parameters of each item. Multi-group confirmatory analyses and differential item function analyses were used to evaluate the measurement equivalence of the GAD-7 across age, gender, educational status, and residence.Results: Cronbach's α coefficient was 0.93 and the intraclass correlation coefficients ranged from 0.71 to 0.87. The GAD-7 summed score was significantly correlated with measures of depression symptoms, perceived stress, sleep disorders, and life satisfaction. Parallel analysis and confirmatory factor analysis supported the one-factor structure of the GAD-7. Seven items showed appropriate discrimination and difficulty parameters. The GAD-7 showed good measurement equivalence across demographic characteristics. The total test information of the scale was 22.85, but the test information within the range of mild symptoms was relatively low.Conclusions: The GAD-7 has good reliability, validity, and measurement invariance among Chinese medical postgraduate students, but its measurement precision for mild anxiety symptoms is insufficient.

BackgroundThe Pittsburgh Sleep Quality Index (PSQI) is a widely used self-report questionnaire that measures general sleep quality in general populations. However, its psychometric properties have yet to be thoroughly examined in longevous persons.ObjectivesThis study aimed to explore the reliability, validity and factor structure of the Chinese-language version of the PSQI in community-dwelling centenarians.MethodsA total of 958 centenarians (mean age = 102.8 years; 81.8% females) recruited from 18 regions in Hainan, China, completed the PSQI scale. Cronbach’s alpha coefficient was used to measure the internal consistency. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were performed to explore the validity and factor structure of the PSQI in this sample. Correlations between the global PSQI score and physical function, depression symptoms, self-reported health status and subjective well-being were used to assess divergent validity.ResultsThe Cronbach’s α coefficient of the PSQI was 0.68, and it increased to 0.78 after two components (medication use and daytime dysfunction) were removed. The Spearman correlation coefficients of the PSQI score with each component were statistically significant (P0.05).ConclusionsThe original PSQI showed acceptable applicability in Chinese community-dwelling centenarians, and its psychometric characteristics moderately improved after sleeping medication and daytime dysfunction were removed. Further validation studies on PSQI are needed among centenarians from varied backgrounds.

Background: Vitamin D and complement components shared some common pathophysiological pathways in the musculoskeletal system, circulation, and metabolism, which were linked to physical function. It is hypothesized that serum complement components may interact with vitamin D in respect of the physical activities of daily living (PADLs).Objective: To investigate if serum complement components 3 (C3), complement components 4 (C4), and 25-hydroxyvitamin D [25(OH)D] associate with PADLs, and to examine whether the association between 25(OH)D levels and PADLs varies at different complement component levels among Chinese centenarians.Methods: This study was conducted in a group of population-based centenarians. PADLs were evaluated using the Barthel Index. Multiple regressions were used to analyze the associations among 25(OH)D, complements C3 and C4, and PADLs.Results: Among 943 participants, 672 (71.3%) had physical dependence (PD). After adjusting for potential confounders, serum 25(OH)D and C3 levels were positively correlated with PADLs, while C4 levels were negatively correlated with PADLs (Ps < 0.05). Serum 25(OH)D levels significantly interacted with both C3 (P for interaction = 0.033) and C4 (P for interaction = 0.006) levels on PADLs. At lower complement component levels, the multivariate odds ratios (ORs) of the upper tertile of vitamin D for PD were 0.32 (95% CI: 0.18–0.55) in the C3 group and 0.29 (95% CI: 0.16–0.50) in the C4 group. At higher complement component levels, the ORs in the C3 and C4 groups were not statistically significant.Conclusions: In a group of population-based Chinese centenarians, we observed that serum complement C3 and 25(OH)D levels were positively associated with PADLs, while C4 was negatively associated with PADLs. The associations between 25(OH)D levels and PADLs were more pronounced in groups with lower serum complement component levels.

Copper antimony sulfide (CuSbS2) has attracted significant interest as an earth-abundant photovoltaic absorber. However, the efficiency of the current CuSbS2 photovoltaic device is too low to meet the requirement of a large-scale application. In this study, selenylation was introduced to optimize the band structure and improve the device performance. Selenized CuSbS2 [CuSbS2(Se)] films were realized using porous CuSbS2 films prepared by spray deposition with a post-treatment in Se vapor. The as-prepared CuSbS2(Se) films exhibited a compact structure. X-ray diffraction and elemental analysis confirmed the effective doping of Se into the lattice by substituting a part of S in CuSbS2. Elemental analysis revealed a gradient distribution for Se from the top surface to the deeper regions, and the substitution rate was very high (>39%). Dark J–V characteristics and AC impedance spectroscopy analysis showed that selenylation significantly reduced the carrier recombination center. As a result, the selenized CuSbS2 device exhibited a significant efficiency improvement from 0.12% to 0.90%, which is much higher than that of the simply annealed device (0.46%), indicating this technique is a promising approach to improve the performance of CuSbS2 solar cells.

The performance of devices fabricated from piezoelectric semiconductors, such as sensors and actuators in microelectromechanical systems, is superior; furthermore, plate structures are the core components of these smart devices. It is thus important to analyze the electromechanical coupling properties of piezoelectric semiconductor nanoplates. We established a nanoplate model for the piezoelectric semiconductor plate structure by extending the first-order shear deformation theory. The flexural vibrations of nanoplates subjected to a transversely time-harmonic force were investigated. The vibrational modes and natural frequencies were obtained by using the matrix eigenvalue solver in COMSOL Multiphysics 5.3a, and the convergence analysis was carried out to guarantee accurate results. In numerical cases, the tuning effect of the initial electron concentration on mechanics and electric properties is deeply discussed. The numerical results show that the initial electron concentration greatly affects the natural frequency and electromechanical fields of piezoelectric semiconductors, and a high initial electron concentration can reduce the electromechanical fields and the stiffness of piezoelectric semiconductors due to the electron screening effect. We analyzed the flexural vibration of typical piezoelectric semiconductor plate structures, which provide theoretical guidance for the development of new piezotronic devices.

Based on dimensional analysis and finite element analysis (FEA), a test method was developed to determine the layer thickness of the surface residual stress using instrumented indentation testing. The relative loading curvatures of the stressed and stress-free P-h curves were obtained from the FEA results. The platform region of the curve of the relative loading curvature versus the indentation depth was used to estimate the residual stress, and the residual stress layer thickness was obtained by considering the turning point of the curve. According to the error analysis results, the proposed method is valid for estimating the residual stress layer thickness by carefully considering the material properties. The proposed method was reduced to the instrumented indentation testing method to determine the uniform residual stress when the indentation depth was far smaller than the layer thickness.

The underwater environment is still unknown for humans, so the high definition camera is an important tool for data acquisition at short distances underwater. Due to insufficient power, the image data collected by underwater submersible devices cannot be analyzed in real time. Based on the characteristics of Field-Programmable Gate Array (FPGA), low power consumption, strong computing capability, and high flexibility, we design an embedded FPGA image recognition system on Convolutional Neural Network (CNN). By using two technologies of FPGA, parallelism and pipeline, the parallelization of multi-depth convolution operations is realized. In the experimental phase, we collect and segment the images from underwater video recorded by the submersible. Next, we join the tags with the images to build the training set. The test results show that the proposed FPGA system achieves the same accuracy as the workstation, and we get a frame rate at 25 FPS with the resolution of 1920 × 1080. This meets our needs for underwater identification tasks.

In this paper, the fracture behavior of GaN piezoelectric semiconductor ceramics was investigated under combined mechanical and electric loading by using three-point bending tests and numerical analysis. The experimental results demonstrate that, in contrast to traditional insulating piezoelectric ceramics, electric current is a key factor in affecting the fracture characteristics of GaN ceramics. The stress, electric displacement, and electric current intensity factors were numerically calculated and then a set of empirical formulae was obtained. By fitting the experimental data, a fracture criterion under combined mechanical and electrical loading was obtained in the form of an ellipsoid function of intensity factors. Such a fracture criterion can be extended to predict the failure behavior of other piezoelectric semiconductors or devices with a crack, which are useful in their reliability design and applications.