The association between socioeconomic status perception and mental health among Chinese older adults: the mediating roles of social trust and justice.

BACKGROUND: Mental health is a matter of quality of life among older adults. This study aimed to explore the association between the socioeconomic status (SES) perception and mental health of older adults using data from 2017 Chinese General Social Survey (CGSS). METHODS: Ordinary least squares (OLS) regression was used to analyse the association between SES perception and mental health, and the substitution model and variable methods were used to check the robustness of the results. Moreover, we adopted the Sobel model to analyse the mediating roles of social trust and justice. RESULTS: SES perception was positively associated with mental health, and this association was mediated by social trust and justice. This kind of positive association was mainly embodied in those groups with the highest or lowest objective SES. In other words, this study confirmed the phenomenon of "a contented mind is a perpetual feast" in Chinese society. CONCLUSIONS: Higher SES perception is associated with improved mental health for Chinese older adults. It is imperative to prioritize efforts to enhance the perceptual abilities of older adults, particularly those with the highest or lowest objective SES, to promote their overall subjective well-being.

Fully automated assessment of the future liver remnant in a blood-free setting via CT before major hepatectomy via deep learning.

OBJECTIVES: To develop and validate a deep learning (DL) model for automated segmentation of hepatic and portal veins, and apply the model in blood-free future liver remnant (FLR) assessments via CT before major hepatectomy. METHODS: 3-dimensional 3D U-Net models were developed for the automatic segmentation of hepatic veins and portal veins on contrast-enhanced CT images. A total of 170 patients treated from January 2018 to March 2019 were included. 3D U-Net models were trained and tested under various liver conditions. The Dice similarity coefficient (DSC) and volumetric similarity (VS) were used to evaluate the segmentation accuracy. The use of quantitative volumetry for evaluating resection was compared between blood-filled and blood-free settings and between manual and automated segmentation. RESULTS: The DSC values in the test dataset for hepatic veins and portal veins were 0.66 ± 0.08 (95% CI: (0.65, 0.68)) and 0.67 ± 0.07 (95% CI: (0.66, 0.69)), the VS values were 0.80 ± 0.10 (95% CI: (0.79, 0.84)) and 0.74 ± 0.08 (95% CI: (0.73, 0.76)), respectively No significant differences in FLR, FLR% assessments, or the percentage of major hepatectomy patients were noted between the blood-filled and blood-free settings (p = 0.67, 0.59 and 0.99 for manual methods, p = 0.66, 0.99 and 0.99 for automated methods, respectively) according to the use of manual and automated segmentation methods. CONCLUSION: Fully automated segmentation of hepatic veins and portal veins and FLR assessment via blood-free CT before major hepatectomy are accurate and applicable in clinical cases involving the use of DL. CRITICAL RELEVANCE STATEMENT: Our fully automatic models could segment hepatic veins, portal veins, and future liver remnant in blood-free setting on CT images before major hepatectomy with reliable outcomes. KEY POINTS: Fully automatic segmentation of hepatic veins and portal veins was feasible in clinical practice. Fully automatic volumetry of future liver remnant (FLR)% in a blood-free setting was robust. No significant differences in FLR% assessments were noted between the blood-filled and blood-free settings.

The impact of physical activity on household out-of-pocket medical expenditure among adults aged 45 and over in urban China: The mediating role of spousal health behaviour.

Background: Increasing medical expenditure is viewed as one of the critical challenges in the context of population ageing. Physical activity (PA), as a primary prevention strategy for promoting health, is considered as an effective way to curb the excessive growth in medical expenditure. This study aimed to analyze the association between PA and the household out-of-pocket medical expenditure (HOPME) among Chinese urban adults aged 45 and over, and to explore the mediating role of spousal health behaviour. Methods: This study analyzed a nationally longitudinal survey: 2014-2018 China Family Panel Studies (CFPS). Fixed effects regression model was applied to estimate the association between PA and annual HOPME. Sobel model was utilized to test the mediating effect. Results: (1) PA was negatively associated with the annual HOPME among urban resident aged 45 and over in China. Exercising 1-5 times per week and maintaining the duration of each exercise session at 31-60 min were effective in reducing annual HOPME. (2) Spousal PA played a significant mediating role in the relationship between respondent's PA and annual HOPME. (3) The negative association between the respondent's PA and HOPME were found among women and those aged between 45 and 65, so was the mediating effect of spouse's PA. Conclusion: Individual PA not only directly reduces HOPME but also indirectly contributes to this reduction by enhancing the PA levels of their spouses. To capitalize on these benefits, more actions should be taken to increase the availability of PA facilities, enhance the public awareness of PA's benefits, and encourage residents to consistently engage in regular PA.

Fiscal agricultural expenditures' impact on sustainable agricultural economic development: Dynamic marginal effects and impact mechanism.

Sustainable agricultural economic development is the core task for achieving the objective of rural revitalization strategy in China, which cannot be separated from the support and guidance of fiscal policy, and agricultural industry integration is a key path for the fiscal promotion of sustainable agricultural economic development. This paper systematically examines the interaction mechanism between fiscal agricultural expenditures and sustainable agricultural economic development by using 31 provincial panel data in China from 2008 to 2020 and adopting a two-way fixed effect model, a panel quantile model, and a mediating effect model, respectively. The results show that the impact of fiscal agricultural expenditures on sustainable agricultural economic development is significantly positive, and appears a dynamic increasing trend with the agricultural development stage upgrading. Moreover, heterogeneity analysis shows that the effect of fiscal agricultural expenditures is more obvious for the samples in the central region and with a high share of primary industry. Further, a mediating effect test finds that agricultural industry integration plays a mediating mechanism between fiscal agricultural expenditures and sustainable agricultural economic development. Therefore, this paper proposes constructing a long-term investment mechanism for fiscal agricultural expenditures, formulating differentiated fiscal support policies for agriculture, and prioritizing support for agricultural industry integration, which provides theoretical support and policy inspiration for promoting sustainable agricultural economic development.

The disparity in hesitancy toward COVID-19 vaccination between older individuals in nursing homes and those in the community in Taizhou, China.

PURPOSE: Older individuals are priority coronavirus disease 2019 (COVID-19) vaccine recipients. Our aim was to investigate the prevalence of and factors influencing vaccine hesitancy in older individuals living in nursing homes and communities. METHODS: A self-administered COVID-19 vaccine hesitancy survey was conducted from September 2021 to December 2021 among people aged ≥ 60 years in eight nursing homes (382 participants) and the community (112 participants) in Taizhou, China. The response rate was 72.1% (382/530) for older adults in nursing homes and 68.7% (112/163) for older adults in the community. RESULTS: We found that 58.1% of the older individuals in nursing homes and 36.6% of those in the community were hesitant to receive the COVID-19 vaccine and that there was a statistically significant difference (P < 0.001). Multiple logistic regression results indicated that the main factors influencing hesitation among the older individuals in nursing homes were being male (Odds Ratio (OR) = 1.67, 95% Confidence Interval (CI): 1.01-2.76); their cognitive level, including having a high perceived risk of COVID-19 infection (OR = 3.06, 95% CI: 1.73-5.43) or the perception of low vaccine safety (OR = 3.08, 95% CI: 1.545- 6.145); anxiety (OR = 3.43, 95% CI: 1.96-5.99); and no previous influenza vaccination (OR = 1.82, 95% CI: 1.13-2.93); whereas those for older individuals in the community were comorbid chronic diseases (OR = 3.13, 95% CI: 1.11- 8.78) and community workers not recommending the vaccine (OR = 8.223, 95% CI: 1.77-38.27). CONCLUSION: The proportion of older individuals in nursing homes who were hesitant to receive the COVID-19 vaccine was significantly higher than for older individuals in the community. Targeted measures should be implemented to reduce vaccine hesitancy and improve vaccination rates in response to the special environment of nursing homes and the characteristics of this population.

[Pollution Characteristics, Source Analysis, and Risk Assessment of Heavy Metals in the Surrounding Farmlands of Manganese Mining Area].

In order to understand the status of heavy metal pollution and the resulting ecological risk of farmland soil surrounding the manganese mining area, 174 soil samples were collected, and the heavy metals(Cu, Zn, Pb, Cr, Ni, Mn, As, and Hg) were analyzed. Principal component analysis (PCA) and the positive matrix factorization (PMF) model were used to determine the source of heavy metals in the soils. The single-factor pollution index method, geo-accumulation index method, potential ecological risk assessment method, and US EPA health risk assessment model were used to evaluate the ecological environment risk of heavy metals. The results showed that the average values of Cu, Zn, Cr, Ni, Mn, and Hg exceeded the background value of Guizhou. 100% of Zn samples and 38.86% of Cu samples exceeded the risk screening value for agricultural land soil pollution. Source analysis revealed that the main sources of soil heavy metals were mining emission, mixed agricultural activity and transportation, nature, and agricultural activities. The risk evaluation showed that Ni, Cr, Pb, and As belonged to the clean level, Hg and Cu were in a light pollution stage, Zn fell into the category of moderate contamination, and Mn reached the heavy pollution level. Cu, Zn, Pb, Cr, Ni, Mn, As, and Cd posed low potential ecological risk, while Hg caused a considerable potential ecological risk. In total, the integrated potential ecological risk of heavy metals was ranked "strong", eight types of heavy metals had carcinogenic risks and non-carcinogenic risks for children aged 0-5 years, and the main contributing factors were Cr and Mn, respectively.

Phage resistance formation and fitness costs of hypervirulent Klebsiella pneumoniae mediated by K2 capsule-specific phage and the corresponding mechanisms.

Introduction: Phage is promising for the treatment of hypervirulent Klebsiella pneumoniae (hvKP) infections. Although phage resistance seems inevitable, we found that there still was optimization space in phage therapy for hvKP infection. Methods: The clinical isolate K. pneumoniae FK1979 was used to recover the lysis phage ΦFK1979 from hospital sewage. Phage-resistant bacteria were obtained on LB agar and used to isolate phages from sewage. The plaque assay, transmission electron microscopy (TEM), multiplicity of infection test, one-step growth curve assay, and genome analysis were performed to characterize the phages. Colony morphology, precipitation test and scanning electron microscope were used to characterize the bacteria. The absorption test, spot test and efficiency of plating (EOP) assay were used to identify the sensitivity of bacteria to phages. Whole genome sequencing (WGS) was used to identify gene mutations of phage-resistant bacteria. The gene expression levels were detected by RT-qPCR. Genes knockout and complementation of the mutant genes were performed. The change of capsules was detected by capsule quantification and TEM. The growth kinetics, serum resistance, biofilm formation, adhesion and invasion to A549 and RAW 264.7 cells, as well as G. mellonella and mice infection models, were used to evaluate the fitness and virulence of bacteria. Results and discussion: Here, we demonstrated that K2 capsule type sequence type 86 hvKP FK1979, one of the main pandemic lineages of hvKP with thick capsule, rapidly developed resistance to a K2-specific lysis phage ΦFK1979 which was well-studied in this work to possess polysaccharide depolymerase. The phage-resistant mutants showed a marked decrease in capsule expression. WGS revealed single nucleotide polymorphism (SNP) in genes encoding RfaH, galU, sugar glycosyltransferase, and polysaccharide deacetylase family protein in the mutants. RfaH and galU were further identified as being required for capsule production and phage sensitivity. Expressions of genes involved in the biosynthesis or regulation of capsule and/or lipopolysaccharide significantly decreased in the mutants. Despite the rapid and frequent development of phage resistance being a disadvantage, the attenuation of virulence and fitness in vitro and in vivo indicated that phage-resistant mutants of hvKP were more susceptible to the immunity system. Interestingly, the newly isolated phages targeting mutants changed significantly in their plaque and virus particle morphology. Their genomes were much larger than and significantly different from that of ΦFK1979. They possessed much more functional proteins and strikingly broader host spectrums than ΦFK1979. Our study suggests that K2-specific phage has the potential to function as an antivirulence agent, or a part of phage cocktails combined with phages targeting phage-resistant bacteria, against hvKP-relevant infections.

Automatic segmentation of hepatic metastases on DWI images based on a deep learning method: assessment of tumor treatment response according to the RECIST 1.1 criteria.

BACKGROUND: Evaluation of treated tumors according to Response Evaluation Criteria in Solid Tumors (RECIST) criteria is an important but time-consuming task in medical imaging. Deep learning methods are expected to automate the evaluation process and improve the efficiency of imaging interpretation. OBJECTIVE: To develop an automated algorithm for segmentation of liver metastases based on a deep learning method and assess its efficacy for treatment response assessment according to the RECIST 1.1 criteria. METHODS: One hundred and sixteen treated patients with clinically confirmed liver metastases were enrolled. All patients had baseline and post-treatment MR images. They were divided into an initial (n = 86) and validation cohort (n = 30) according to the examined time. The metastatic foci on DWI images were annotated by two researchers in consensus. Then the treatment responses were assessed by the two researchers according to RECIST 1.1 criteria. A 3D U-Net algorithm was trained for automated liver metastases segmentation using the initial cohort. Based on the segmentation of liver metastases, the treatment response was assessed automatically with a rule-based program according to the RECIST 1.1 criteria. The segmentation performance was evaluated using the Dice similarity coefficient (DSC), volumetric similarity (VS), and Hausdorff distance (HD). The area under the curve (AUC) and Kappa statistics were used to assess the accuracy and consistency of the treatment response assessment by the deep learning model and compared with two radiologists [attending radiologist (R1) and fellow radiologist (R2)] in the validation cohort. RESULTS: In the validation cohort, the mean DSC, VS, and HD were 0.85 ± 0.08, 0.89 ± 0.09, and 25.53 ± 12.11 mm for the liver metastases segmentation. The accuracies of R1, R2 and automated segmentation-based assessment were 0.77, 0.65, and 0.74, respectively, and the AUC values were 0.81, 0.73, and 0.83, respectively. The consistency of treatment response assessment based on automated segmentation and manual annotation was moderate [K value: 0.60 (0.34-0.84)]. CONCLUSION: The deep learning-based liver metastases segmentation was capable of evaluating treatment response according to RECIST 1.1 criteria, with comparable results to the junior radiologist and superior to that of the fellow radiologist.

Atom-Economical Synthesis of Dimethyl Carbonate from CO2 : Engineering Reactive Frustrated Lewis Pairs on Ceria with Vacancy Clusters.

The chemical conversion of CO2 to long-chain chemicals is considered as a highly attractive method to produce value-added organics, while the underlying reaction mechanism remains unclear. By constructing surface vacancy-cluster-mediated solid frustrated Lewis pairs (FLPs), the 100 % atom-economical, efficient chemical conversion of CO2 to dimethyl carbonate (DMC) was realized. By taking CeO2 as a model system, we illustrate that FLP sites can efficiently accelerate the coupling and conversion of key intermediates. As demonstrated, CeO2 with rich FLP sites shows improved reaction activity and achieves a high yield of DMC up to 15.3 mmol g-1 . In addition, by means of synchrotron radiation in situ diffuse reflectance infrared Fourier-transform spectroscopy, combined with density functional theory calculations, the reaction mechanism on the FLP site was investigated systematically and in-depth, providing pioneering insights into the underlying pathway for CO2 chemical conversion to long-chain chemicals.

Preoperative prediction of pelvic lymph nodes metastasis in prostate cancer using an ADC-based radiomics model: comparison with clinical nomograms and PI-RADS assessment.

PURPOSE: To develop and test radiomics models based on manually corrected or automatically gained masks on ADC maps for pelvic lymph node metastasis (PLNM) prediction in patients with prostate cancer (PCa). METHODS: A primary cohort of 474 patients with PCa who underwent prostate mpMRI were retrospectively enrolled for PLNM prediction between January 2017 and January 2020. They were then randomly split into training/validation (n = 332) and test (n = 142) groups for model development and internal testing. Four radiomics models were developed using four masks (manually corrected/automatic prostate gland and PCa lesion segmentation) based on the ADC maps using the primary cohort. Another cohort of 128 patients who underwent radical prostatectomy (RP) with extended pelvic lymph node dissection (ePLND) for PCa was used as the testing cohort between February 2020 and October 2021. The performance of the models was evaluated in terms of discrimination and clinical usefulness using the area under the curve (AUC) and decision curve analysis (DCA). The optimal radiomics model was further compared with Memorial Sloan Kettering Cancer Center (MSKCC) and Briganti 2017 nomograms, and PI-RADS assessment. RESULTS: 17 (13.28%) Patients with PLNM were included in the testing cohort. The radiomics model based on the mask of automatically segmented prostate obtained the highest AUC among the four radiomics models (0.73 vs. 0.63 vs. 0.70 vs. 0.56). Briganti 2017, MSKCC nomograms, and PI-RADS assessment-yielded AUCs of 0.69, 0.71, and 0.70, respectively, and no significant differences were found compared with the optimal radiomics model (P = 0.605-0.955). CONCLUSION: The radiomics model based on the mask of automatically segmented prostate offers a non-invasive method to predict PLNM for patients with PCa. It shows comparable accuracy to the current MKSCC and Briganti nomograms.

The Impact of Instant Reimbursement of Cross-Regional Medical Services on Hospitalization Costs Incurred by the Floating Population-Evidence from China.

BACKGROUND: The medical cost reimbursement function of medical insurance can reduce the medical burden of individuals and thus improve their medical service utilization level. This study aimed to explore the impact of different cross-regional reimbursement types of medical insurance (instant reimbursement and manual reimbursement) on the hospitalization costs incurred by the floating population. METHODS: The data used in this study was from the 2018 China Migrants Dynamic Survey (CMDS) conducted by the National Health Commission of China. The multiple linear regression model and Propensity Score Matching method (PSM) were used to analyze the impact of instant and manual reimbursement on hospitalization costs. RESULTS: (1) Instant reimbursement and manual reimbursement could significantly reduce the floating population's out-of-pocket proportion of hospitalization costs by 33.2% and 26.9%, respectively; (2) the average proportion and amounts of out-of-pocket hospital costs of instant reimbursement for the floating population were lower than those of manual reimbursement by 6.35% and 19.6%, respectively, and this impact would gradually increase as the flow distance expanded; (3) there was no significant impact of instant reimbursement on the total hospitalization costs relative to manual reimbursement. CONCLUSIONS: Our study suggests that instant reimbursement can effectively reduce the out-of-pocket medical burden of the floating population at the individual level, but it will not have an obvious impact on the total hospitalization costs at the social level.

A simulation-optimization approach for supporting conservative water allocation under uncertainties.

In this paper, a hybrid method integrated unbiased grey model (UGM) and artificial neural network (ANN) into an interval two-stage fuzzy credibility-constrained programming (ITFCP) framework is proposed for water resources allocation of the Yalong River research area. Through the grey correlation analysis and the eXtreme Gradient Boosting (XGboost) algorithm, the economic and social indicators are related to the water demands of different water sectors in different regions can be obtained for building water demand prediction model. According to the unbiased grey prediction of the socio-economic development data of each region in the Yalong River Basin (YRB), water demand prediction models are constructed by using neural network. The establishment of a hybrid two-stage interval fuzzy credibility-constrained programming model can analyze the uncertainties existing in the process of water resources allocation. Taking 2020, 2025, and 2030 as the planning years, the developed model studies and reveals the system benefits at different credibility levels, the water shortage of each user in sub-regions and the water resources allocation situation to provide suggestion for managers to optimize the allocation of water resources. Compared to the previous methods, this integrated model can help decision-makers set management policies more sustainably and profitably.

Analysis on the causes of the change in the north-south gap of industrial pollution discharge in China.

What are the causes of the change in the north-south gap of industrial pollution discharge in 2008 and 2016? In order to solve this problem, this paper makes theoretical and empirical research. The results show that (1) the difference in economic growth pattern transformation is the root cause of the change in the north-south gap of industrial pollution discharge.(2) The international financial crisis is the direct cause of the change in the north-south gap of industrial pollution discharge in 2008. The international financial crisis forced the industrial transformation and upgrading of the southern region, which made the TFP of the southern region relatively improve, and then led to the relative reduction of industrial pollution discharge in the southern region. (3) The supply-side structural reform is the direct cause of the change in the north-south gap of industrial pollution discharge in 2016. However, the supply-side structural reform proposed by the central government in 2016 is essentially a further continuation of the policy of "resolving overcapacity" implemented in 2013. In fact, the north-south gap in the growth rate of industrial discharge has changed since 2013.

Design and validation of a synchrotron proton beam line for FLASH radiotherapy preclinical research experiments.

PURPOSE: The main purpose of this work was to generate and validate the dosimetric accuracy of proton beams of dimensions that are appropriate for in vivo small animal and in vitro ultrahigh dose rate (FLASH) radiotherapy experiments using a synchrotron-based treatment delivery system. This study was performed to enable future investigations of the relevance of a spread-out Bragg peak (SOBP) under FLASH conditions. METHODS: The spill characteristics of the small field fixed horizontal beam line were modified to deliver accelerated protons in times as short as 2 ms and to control the dose delivered. A Gaussian-like transverse beam profile was transformed into a square uniform one at FLASH dose rates, while avoiding low-dose regions, a crucial requirement to protect normal tissue during FLASH irradiation. Novel beam-shaping devices were designed using Monte Carlo techniques to produce up to about 6 cm3 of uniform dose in SOBPs while maximizing the dose rate. These included a scattering foil, a conical flattening filter to maximize the flux of protons into the region of interest, energy filters, range compensators, and collimators. The shapes, sizes, and positions of the components were varied to provide the required field sizes and SOBPs. RESULTS: The designed and fabricated devices were used to produce 10-, 15-, and 20-mm diameter, circular field sizes and 10-, 15-, and 20-mm SOBP modulation widths at uniform physical dose rates of up to 375 Gy/s at the center of the SOBP and a minimum dose rate of about 255 Gy/s at the entrance, respectively, in cylindrical volumes. The flatness of lateral dose profiles at the center could be adjusted to within ±1.5% at the center of the SOBP. Assessment of systematic uncertainties, such as impact of misalignments and positioning uncertainties, was performed using simulations, and the results were used to provide appropriate adjustments to ensure high-accuracy FLASH beam delivery for both in vitro and in vivo preclinical experiments. CONCLUSIONS: It is feasible to use synchrotron-generated proton beams of sufficient dimensions for FLASH radiobiology experiments. We expect to use the system we developed to acquire in vitro and in vivo small animal FLASH radiobiology data as a function of dose, dose rate, oxygen content, and linear energy transfer to help us understand the underlying mechanisms of the FLASH phenomenon.

One-stop preoperative assessment of renal vessels for living donors with 3.0 T non-contrast-enhanced magnetic resonance angiography: compared with computerized tomography angiography and surgical results.

OBJECTIVE: The study was to investigate the feasibility and accuracy of assessment for living renal donors before transplantation by using 3.0 T non-contrast-enhanced magnetic resonance angiography (NCE-MRA). METHODS: 30 renal donors were investigated and underwent computed tomography angiography (CTA) and 3.0 T NCE-MRA before nephrectomy. Two radiologists independently assessed arterial and venous anatomy and potential kidney lesions. The image quality score, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), diameters and lengths of renal arteries and veins were compared between CTA and NCE-MRA. Imaging findings were compared with the surgical results served as reference standard. Agreement was assessed using κ test. The Wilcoxon test and paired sample t test were used for statistically significant differences. RESULTS: The results of image quality score for renal arteries and veins were highly consistent between the two radiologists in NCE-MRA (p < 0.001). There was no significant difference in the scores of renal arterial and venous branches between NCE-MRA and CTA (p > 0.05). The SNR and CNR of renal vessels were higher than CTA (p < 0.001). There were no statistically significant differences in the length of renal vessels measured by the two methods (p > 0.05), and the diameter was smaller than that of CTA (p < 0.05). The detection of normal renal arteries and early branches by both examination techniques was consistent with intraoperative findings. Both methods showed good consistency between the anatomical variation of renal vein and the intraoperative diagnosis (p < 0.001). CONCLUSION: 3.0 T NCE-MRA can be used for evaluation of main renal arteries and veins with high accuracy for anatomy and variation classification, and can be used for pre-operative vascular evaluation of living donor kidney transplantation. ADVANCES IN KNOWLEDGE: 3.0 T NCE-MRA can be used for evaluation of main renal arteries and veins with high accuracy for anatomy and variation classification, and can be used for pre-operative vascular evaluation of living donor kidney transplantation.

A Review of the Robust Optimization Process and Advances with Monte Carlo in the Proton Therapy Management of Head and Neck Tumors.

In intensity-modulated proton therapy, robust optimization processes have been developed to manage uncertainties associated with (1) range, (2) setup, (3) anatomic changes, (4) dose calculation, and (5) biological effects. Here we review our experience using a robust optimization technique that directly incorporates range and setup uncertainties into the optimization process to manage those sources of uncertainty. We also review procedures for implementing adaptive planning to manage the anatomic uncertainties. Finally, we share some early experiences regarding the impact of uncertainties in dose calculation and biological effects, along with techniques to manage and potentially reduce these uncertainties.

Application of 3D-Printed Orthopedic Cast for the Treatment of Forearm Fractures: Finite Element Analysis and Comparative Clinical Assessment.

OBJECTIVE: This pilot study is aimed at investigating the mechanical characteristics of a cast-wrapped fractured forearm and performing a clinical comparative study of our own developed 3D-printed orthopedic cast. METHODS: An integrated finite element (FE) model including a forearm and a 3D-printed cast wrapping the forearm was created. The distal radial ulna in this model was cut through to mimic the bone fracture. A 400 N force and 1 Nm rotation moment, which were much larger than the loading conditions encountered in daily life for a human being, were applied on the palm. We conducted a comparative clinical study by using statistical assessment. 60 patients with forearm fractures were selected and treated with manual reduction and external fixation cast. All patients were divided into three groups with equal members (20): (a) 3D-printed external cast group, (b) traditional plaster external fixation group, and (c) splint external fixation group. The clinical efficacy, wrist function, and patient satisfaction were scored and compared. RESULTS: In the condition of 400 N loading, the fracture displacements in anterior-posterior (AP), posterior-anterior (PA), medial to lateral (ML), and lateral to medial (LM) compression directions were 1.2648, 1.3253, 0.8503, and 0.8957 (mm), respectively, and the corresponding fracture stresses were 4.5986, 3.9129, and 5.0334, 7.9197 (MPa), respectively. In the inward (IR) and outward (OR) rotations, the fracture displacements were both 0.02628 (mm), and the corresponding fracture surface stresses were 0.1733 and 0.1723 (MPa), respectively. In the clinical efficacy, wrist function, and patient comfort evaluation, the total scores of group A were both higher than those in groups B and C (P < 0.05). CONCLUSION: A 3D-printed orthopedic cast was capable of exerting appropriate mechanical correction loads on specific areas to maintain optimal alignment of a fractured forearm and thus could achieve the favorable clinical efficacy and patient comfort.

Recurrent convolutional neural kernel model for stock price movement prediction.

Stock price movement prediction plays important roles in decision making for investors. It was usually regarded as a binary classification task. In this paper, a recurrent convolutional neural kernel (RCNK) model was proposed, which learned complementary features from different sources of data, namely, historical price data and text data in the message board, to predict the stock price movement. It integrated the advantage of technical analysis and sentiment analysis. Different from previous studies, the text data was treated as sequential data and utilized the RCNK model to train sentiment embeddings with the temporal features. Besides, in the classification section of the model, the explicit kernel mapping layer was used to replace several full-connected layers. This operation reduced the parameters of the model and the risk of overfitting. In order to test the impact of treating the sentiment data as sequential data, the effectiveness of explicit kernel mapping layer and the usefulness integrating the technical analysis and sentiment analysis, the proposed model was compared with the other two deep learning models (recurrent convolutional neural network model and convolutional neural kernel model) and the models with only one source of data as input. The result showed that the proposed model outperformed the other models.

Influence of FDI on environmental pollution in selected Arab countries: a spatial econometric analysis perspective.

This study investigates the spatial influence and spillover effects of foreign direct investment (FDI) on environmental pollution (EP) by using panel spatial data in 1970-2016 for 12 selected Arab countries. It employs the STochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model. The spatial econometric approach is applied to examine the validity of the pollution haven hypothesis (PHH) and the pollution halo hypothesis (P-HH) (from now on, we will use the acronyms PHH and P-HH to denote the pollution haven hypothesis and pollution halo hypothesis, respectively). The Sustainable Development Goals (SDGs) are linked to the study results with a focus on cleaner production practices. The global Moran's I, local Moran's I, and Lagrange multiplier (LM) tests are used to ascertain the existence of spatial autocorrelation (SAR) and determine its trend. We also apply the spatial lag model (SLM), the spatial error model (SEM), and the spatial Durbin model (SDM) to achieve the study objectives. Data are analyzed by using the SDM on the basis of the results of the Wald and likelihood ratio tests. The results of the LM and global and local Moran's I tests confirm the existence of SAR. The SDM results reveal that a slight increase in CO2 is an influence of the FDI on EP. Findings support the existence of PHH in the Arab countries. The direct effect of the FDI is increased CO2 and environmental degradation, and the spatial spillover effects are statistically insignificant. This study suggests a set of policies for managing and directing FDI toward clean technology-based industries and reduced CO2 emissions. Such policies may contribute to the achievement of some SDGs and balancing economic development and environmental sustainability according to the cleaner production practice perspective in the Arab countries and other states with similar conditions.

The Impact of Internet Medical Information Overflow on Residents' Medical Expenditure Based on China's Observations.

Background: The rapid rise of medical expenditure is a common problem in the field of public health around the world, but the challenges for the Chinese government are even greater. How to control the rapid rise in medical expenditure and reduce individuals' economic burden when receiving medical treatment has become one of the core issues that the Chinese government urgently needs to solve. The aim of this study was to evaluate the impact of Internet use on individuals' medical expenditure and further discuss the potential impact mechanism. Methods: The data used in this study were from the 2018 China Family Panel Studies (CFPS) conducted by Peking University. The Heckman sample selection model was used to analyse the impact of Internet use on individuals' medical expenditure. Results: Internet use reduced the medical expenditure of individuals by 6.19%; high frequency Internet use reduced the medical expenditure of individuals by 15.1%, while low frequency Internet use had no impact. In addition, Internet use had different impacts on individuals' medical expenditure at different levels of hospitals. Specifically, Internet use reduced the medical expenditure of individuals who received medical treatment at general hospitals by 9.63%, and high frequency Internet use reduced the medical expenditure of individuals by 22.2%. However, Internet use had no impact on the medical expenditure of individuals who received medical treatment at primary hospitals. Conclusions: Findings from this study underscore the importance of Internet use as an important role in reducing individuals' medical expenditure. The use of the Internet can significantly reduce the level of individuals' medical expenditure, and high frequency Internet use has a greater effect. However, Internet use has different impacts on individuals' medical expenditure among different levels of hospitals. The reduction effect of Internet use on individuals' medical expenditure is mainly concentrated in general hospitals but has no effect in primary hospitals.