Research on improved YOLOV7-SSWD digital meter reading recognition algorithms.

Meter reading recognition is an important link for robots to complete inspection tasks. To solve the problems of low detection accuracy and inaccurate localization of current meter reading recognition algorithms, the YOLOV7-SSWD (YOLOV7-SiLU-SimAM-Wise-IoU-DyHeads) model is proposed, a novel detection model based on the multi-head attention mechanism, which is improved on the YOLOV7-Tiny model. First, the Wise-IoU loss function is used to solve the problem of sample quality imbalance and improve the model's detection accuracy.

N/O-Codoped Ultrathin Porous Biochar Derived from Casein for Fast Adsorption of Iodine.

The release of radioactive iodine into the environment poses a significant threat, as it can contaminate soil, water, and food chains, leading to detrimental effects on ecosystems and biodiversity. Hence, employing the adsorption method proves to be a simple yet effective approach for treating radioactive waste. N/O-codoped ultrathin porous biochar, synthesized from casein using NaHCO activation, emerges as a potential candidate for adsorption materials.

In-situ confining selenium within bubble - like carbon nanoshells for ultra-stable Li-Se batteries.

Lithium-selenium (Li-Se) batteries are promising energy storage devices. However, the long-term durability and high-rate performance of the Se cathode have been limited by significant volume expansion and the troublesome shuttle effect of polyselenides during repeated charging/discharging processes. To revolutionize these issues, we applied a top-down strategy through the in-situ trapping of amorphous Se within bubble-like carbon (BLC) frameworks, which can radically minimize the presence of surface-absorbed Se while enhancing Se loading capacity.

Inverted U-shaped association between bacillary dysentery and temperature: A new finding using a novel two-stage strategy in multi-region studies.

Background: Bacillary dysentery (BD) has brought a significant public health concern in China. Temperature is one of the main factors affecting BD incidence. Due to the largely different temperature ranges between regions, the classic multi-region time series studies could only explore the relative temperature-BD association and showed that BD incidence is positively associated with relative temperature (i.

Using a novel strategy to identify the clustered regions of associations between short-term exposure to temperature and mortality and evaluate the inequality of heat- and cold-attributable burdens: A case study in the Sichuan Basin, China.

Background: Few studies have focused on the spatially clustered regions in the association between short-term exposure to temperature and mortality, which is important for identifying high-susceptibility population and enhancing the prevention of high/low temperatures. Previous studies have explored the association inequality, but no study has evaluated the inequalities of temperature-attributable burdens, which may be more meaningful for reducing temperature-related regional inequality.

Methods: Taking the Sichuan Basin (SCB), an economically imbalanced area with high humidity and four distinctive seasons, as an example, we used a novel multi-stage strategy to investigate the two issues.

Self-sacrificed BiOBr template-assisted synthesis of α-BiO/BiOBr heterojunctions with oxygen vacancies for enhanced photocatalytic nitrogen fixation.

The catalytic conversion of nitrogen to ammonia is one of the most significant processes in nature and the chemical industry. However, the traditional Haber-Bosch process of ammonia synthesis consumes substantial energy and emits a large amount of carbon dioxide. The efficiency of photocatalytic N activation is severely limited by the lack of N adsorption sites and poor carrier utilization.

Using a novel strategy to investigate the spatially autocorrelated and clustered associations between short-term exposure to PM and mortality and the attributable burden: A case study in the Sichuan Basin, China.

Due to the lack of statistical methods, few studies have investigated the spatial autocorrelated distribution in the association between short-term exposure to PM and mortality and used a statistical manner to explore the association-clustered regions, which play important roles in identifying high-sensitivity/susceptibility regions. The Sichuan Basin (SCB) is one of the most PM-polluted areas, and the extreme economic imbalance may cause considerable spatial heterogeneity and clustering in PM-mortality association. In this work, we used a recently proposed strategy by us to investigate the spatially autocorrelated and clustered association between daily PM and cardiorespiratory mortality from 2015 to 2019 in 130 counties of the SCB.

Facile Synthesis Hyper-Crosslinked PdFe Bimetallic Polymer as Highly Active Catalyst for Ullmann Coupling Reaction of Chlorobenzene.

The synthesis of efficient and sustainable heterogeneous Pd-based catalysts has been an active field of research due to their crucial role in carbon-carbon coupling reactions. In this study, we developed a facile and eco-friendly in situ assembly technique to produce a PdFe bimetallic hyper-crosslinked polymer (HCP@Pd/Fe) to use as a highly active and durable catalyst in the Ullmann reaction. The HCP@Pd/Fe catalyst exhibits a hierarchical pore structure, high specific surface area, and uniform distribution of active sites, which promote catalytic activity and stability.

Multi-scale detection of pulmonary nodules by integrating attention mechanism.

The detection of pulmonary nodules has a low accuracy due to the various shapes and sizes of pulmonary nodules. In this paper, a multi-scale detection network for pulmonary nodules based on the attention mechanism is proposed to accurately predict pulmonary nodules. During data processing, the pseudo-color processing strategy is designed to enhance the gray image and introduce more contextual semantic information.

Mapping the long-term associations between air pollutants and COVID-19 risks and the attributable burdens in the continental United States.

Numerous studies have investigated the associations between COVID-19 risks and long-term exposure to air pollutants, revealing considerable heterogeneity and even contradictory regional results. Studying the spatial heterogeneity of the associations is essential for developing region-specific and cost-effective air-pollutant-related public health policies for the prevention and control of COVID-19. However, few studies have investigated this issue.

Epidemiological characteristics and risk factors of obstetric infection after the Universal Two-Child Policy in North China: a 5-year retrospective study based on 268,311 cases.

Background: Obstetrical infection is one of the causes of maternal death and a difficult problem for many clinicians. Changes in the demographic and obstetric background of pregnant women following the Universal Two-Child Policy may have an impact on some fertility phenomena. And with the increase in the number of deliveries, the limited medical resources become more scarce.

Therapeutic experience of a pancreatic mixed serous neuroendocrine neoplasm invading peripancreatic vessels: A case report.

Rationale: Pancreatic mixed serous neuroendocrine neoplasm (PMSNN) is an extremely rare disease. Only a few cases on the surgical treatment of PMSNN have been reported in the literature, and it is unclear whether there is invasion of important peripancreatic vessels.

Patient Concerns: We report the case of a 39-year-old female patient with PMSNN accompanied by invasion of important peripancreatic vessels.

A deep learning-based model predicts survival for patients with laryngeal squamous cell carcinoma: a large population-based study.

Objectives: To assess the performance of DeepSurv, a deep learning-based model in the survival prediction of laryngeal squamous cell carcinoma (LSCC) using the Surveillance, Epidemiology, and End Results (SEER) database.

Methods: In this large population-based study, we developed and validated a deep learning survival neural network using pathologically diagnosed patients with LSCC from the SEER database between January 2010 and December 2018. Totally 13 variables were included in this network, including patients baseline characteristics, stage, grade, site, tumor extension and treatment details.

Longer depressive duration reduces sleep duration more: A longitudinal study in the middle-aged and elderly Chinese.

Background: Quantifying the effect of depression on sleep duration is of great importance to the diagnosis, control, prevention of sleep-related diseases and understanding related biological mechanisms. However, existing studies explored the effect without considering depressive duration, which may cause inaccurate results.

Methods: Accessing the data from the China Health and Retirement Longitudinal Study in 2011, 2013, 2015 and 2018, we used the interval between two interviews with persistent depression status to approximate depressive duration.

Using a novel two-stage strategy to characterize the spatial distribution of associations between temperature and COVID-19: A case study in the continental United States.

Background: Numerous studies have studied the association between daily average temperature (DAT) and daily COVID-19 confirmed cases, which show considerable heterogeneity, even opposite results, among different regions. Such heterogeneity suggests that characterizing the association on a large area scale would ignore the local variation, even obtain false results in some local regions. So, characterizing the spatial distribution of heterogeneous DAT-COVID-19 associations and exploring the causes plays an important role on making temperature-related region-specific intervention measures and early-warning systems.

A machine learning model predicting candidates for surgical treatment modality in patients with distant metastatic esophageal adenocarcinoma: A propensity score-matched analysis.

Objective: To explore the role of surgical treatment modality on prognosis of metastatic esophageal adenocarcinoma (mEAC), as well as to construct a machine learning model to predict suitable candidates.

Method: All mEAC patients pathologically diagnosed between January 2010 and December 2018 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. A 1:4 propensity score-matched analysis and a multivariate Cox analysis were performed to verify the prognostic value of surgical treatment modality.

Regulation of endothelial nitric oxide synthase in cardiac remodeling.

Objectives: Our previous study demonstrated that endothelial nitric oxide synthase (eNOS) gene serves as a candidate for modifiers of hypertrophic cardiomyopathy (HCM), which alters severity of HCM phenotypes. Herein, we sought to further elucidate the role of eNOS on cardiac myocyte hypertrophy and fibrosis, the major phenotypes of HCM.

Methods: Male eNOS-deficient mice (eNOS-/-) and wild type control mice (eNOS+/+, C57B1/6 J) were used in this study.

A novel peptide-based fluorescent probe for highly selective detection of mercury (II) ions in real water samples and living cells based on aggregation-induced emission effect.

A new fluorescent probe TPE-GHK was synthesized containing a tetrastyrene (TPE) derivative as fluorophore and classical tripeptide (Gly-His-Lys-NH) as a receptor based on the aggregation-induced emission (AIE) mechanism. TPE-GHK displayed high selectivity and rapid fluorescent "turn-on" response to Hg among other competitive metal ions. The 2:1 complex binding mechanism of TPE-GHK toward Hg was verified by fluorometric titration, Job's plots, and ESI-HRMS spectra.

Genetic diversity of the cultivated Salvia miltiorrhiza populations revealed by four intergenic spacers.

For better understanding the genetic diversity and phylogeny of the cultivated Salvia miltiorrhiza populations, four intergenic spacer sequences, ETS, psbA-trnH, trnL-trnF, and ycf1-rps15 of the 40 populations collected from China were Polymerase Chain Reaction (PCR) amplified, analyzed both individually and in combination. Haplotype diversity analysis showed that the cultivated S. miltiorrhiza populations had a very rich genetic diversity and an excellent capacity to resist environmental pressure.

Reclaiming independence in spatial-clustering datasets: A series of data-driven spatial weights matrices.

Most spatial models include a spatial weights matrix (W) derived from the first law of geography to adjust the spatial dependence to fulfill the independence assumption. In various fields such as epidemiological and environmental studies, the spatial dependence often shows clustering (or geographic discontinuity) due to natural or social factors. In such cases, adjustment using the first-law-of-geography-based W might be inappropriate and leads to inaccuracy estimations and loss of statistical power.

Effects of internet-based cognitive behavioral therapy on postpartum depression: A protocol for systematic review and meta-analysis.

Background: Postpartum depression is one of the most common complications during the postpartum period. In recent years, internet-based psychological interventions have made significant progress and provided a new psychotherapy model. Internet-based cognitive behavioral therapy (ICBT) for postpartum depression has achieved good results.

[Longitudinal Cohort Study of the Relationship between Sleep Duration and Depressive Symptoms in Older People in China].

Objective: To investigate the relationship between sleep duration and depressive symptoms in older people in China, and to explore whether there are gender differences in the relationship.

Methods: Accessing the data from China Health and Retirement Longitudinal Study (CHARLS) for 2015 and 2018, we covered in the study a total of 2898 respondents, including 1684 males (58.1%) and 1214 females (41.