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Child influenza is an acute infectious disease that places substantial burden on children and their families. Real-time accurate prediction of child influenza epidemics can aid scientific and timely decision-making that may reduce the harm done to children infected with influenza. Several models have been proposed to predict influenza epidemics. However, most existing studies focus on adult influenza prediction. This study demonstrates the feasibility of using the LASSO (least absolute shrinkage and selection operator) model to predict influenza-like illness (ILI) levels in children between 2017 and 2020 in Shanghai, China. The performance of the LASSO model was compared with that of other statistical influenza-prediction techniques, including autoregressive integrated moving average (ARIMA), random forest (RF), ordinary least squares (OLS), and long short-term memory (LSTM). The LASSO model was observed to exhibit superior performance compared to the other candidate models. Owing to the variable shrinkage and low-variance properties of LASSO, it eliminated unimportant features and avoided overfitting. The experimental results suggest that the LASSO model can provide useful guidance for short-term child influenza prevention and control for schools, hospitals, and governments.

To explore the evolution mechanism of multistage machining processes and torsional fatigue behaviour based on strain energy for the first time and provide process optimization of axis parts of low-alloy medium-carbon steel for service performance, four multistage machining processes were applied to the 45CrNiMoVA steel, including the rough turning process (RT), RT + the finish turning process (FRT), FRT+ the grinding process (GFRT) and RT+ the finish turning process on dry cutting condition (FRT0). The result showed that the FRT process’s average low-cycle torsional fatigue life increased by 50% when it evolved from the RT process. The lower surface roughness of Ra 1.3 μm caused the total strain energy to increase by 163.8 Pa mm/mm instead of the unchanged strain energy density, and the crack feature evolved from some specific bulges to flat shear plane characteristics. When the GFRT process evolved from the FRT process, its average fatigue life increased by 1.45 times, compared with the RT process. Plastic strain amplitude decreased by 21%, and the strain energy density decreased by 4% due to more considerable compressive residual stress (-249 MPa). Plastic deformation layer depth had a consistent tendency with surface roughness. In this paper, surface integrity evolutions on cyclic characteristics and fatigue behaviour have also been explained. A fatigue life prediction model based on the energy method for machined surface integrity is proposed.

Fused silica is an optical material with excellent performance, and it is widely used in the fabrication of optics in various high-power laser systems. With the gradual improvement of laser systems, the quality of optics becomes crucial. Taking magnetorheological finishing (MRF), ion beam sputtering etching (IBSE), and advanced mitigation processing (AMP) as the means, this work focuses on exploring the damage characteristics evolution of fused silica under different techniques. In this work, IBSE technique was used to determinedly polish the optical surface after removing damage layer by MRF technique, and AMP technique was applied to etch the surface with a certain depth. Then, 10 J/cm2 (355 nm, 5 ns) laser was used to irradiate the optical surface, and the damage density of optics maintained at a low level, about 0.001/mm2, which proves that MRF, IBSE, and AMP techniques can effectively improve the laser damage resistance of optics.

BackgroundThe causal relevance of polyunsaturated fatty acids (PUFAs) for risk of site-specific cancers remains uncertain.MethodsUsing a Mendelian randomization (MR) framework, we assessed the causal relevance of PUFAs for risk of cancer in European and East Asian ancestry individuals. We defined the primary exposure as PUFA desaturase activity, proxied by rs174546 at the FADS locus. Secondary exposures were defined as omega 3 and omega 6 PUFAs that could be proxied by genetic polymorphisms outside the FADS region. Our study used summary genetic data on 10 PUFAs and 67 cancers, corresponding to 562,871 cases and 1,619,465 controls, collected by the Fatty Acids in Cancer Mendelian Randomization Collaboration. We estimated odds ratios (ORs) for cancer per standard deviation increase in genetically proxied PUFA exposures.FindingsGenetically elevated PUFA desaturase activity was associated (P < 0.0007) with higher risk (OR [95% confidence interval]) of colorectal cancer (1.09 [1.07–1.11]), esophageal squamous cell carcinoma (1.16 [1.06–1.26]), lung cancer (1.06 [1.03–1.08]) and basal cell carcinoma (1.05 [1.02–1.07]). There was little evidence for associations with reproductive cancers (OR = 1.00 [95% CI: 0.99–1.01]; Pheterogeneity = 0.25), urinary system cancers (1.03 [0.99–1.06], Pheterogeneity = 0.51), nervous system cancers (0.99 [0.95–1.03], Pheterogeneity = 0.92) or blood cancers (1.01 [0.98–1.04], Pheterogeneity = 0.09). Findings for colorectal cancer and esophageal squamous cell carcinoma remained compatible with causality in sensitivity analyses for violations of assumptions. Secondary MR analyses highlighted higher omega 6 PUFAs (arachidonic acid, gamma-linolenic acid and dihomo-gamma-linolenic acid) as potential mediators. PUFA biosynthesis is known to interact with aspirin, which increases risk of bleeding and inflammatory bowel disease. In a phenome-wide MR study of non-neoplastic diseases, we found that genetic lowering of PUFA desaturase activity, mimicking a hypothetical intervention to reduce cancer risk, was associated (P < 0.0006) with increased risk of inflammatory bowel disease but not bleeding.InterpretationThe PUFA biosynthesis pathway may be an intervention target for prevention of colorectal cancer and esophageal squamous cell carcinoma but with potential for increased risk of inflammatory bowel disease.FundingCancer Resesrch UK (C52724/A20138, C18281/A19169). UK Medical Research Council (MR/P014054/1). National Institute for Health Research (NIHR202411). UK Medical Research Council (MC_UU_00011/1, MC_UU_00011/3, MC_UU_00011/6, and MC_UU_00011/4). National Cancer Institute (R00 CA215360). National Institutes of Health (U01 CA164973, R01 CA60987, R01 CA72520, U01 CA74806, R01 CA55874, U01 CA164973 and U01 CA164973).

Programmed death receptor-1 (PD-1) is a suppressor-like receptor located on T cells that interacts with programmed death ligand-1 (PD-L1) to suppress T cell expression, resulting in tumor immune escape. The way to achieve immunotherapy by inhibiting PD-1 and PD-L1 pathways and blocking PD-1 and PD-L1 binding, thereby achieving T-cell upregulation, has been validated by the FDA to enter clinical practice. To date, natural components from herbal medicine such as paclitaxel and camptothecin have been shown to play a role in oncological treatment either alone or in combination with currently known therapies. Meanwhile, many animal experimental studies have shown that natural ingredients from traditional Chinese medicine or traditional Chinese herbal compounds can play a positive role in gastric and colon cancer by inhibiting the PD-L1 pathway. This review focuses on the mechanism of PD-L1 and the modulation of PD-L1 pathway by some traditional Chinese medicines in two common types of digestive cancers, gastric cancer and rectal colon cancer, with the aim to open up new ideas for the development of novel drugs against digestive cancers.

BackgroundThe relative risk of smoking on lung cancer have been reported to be much higher in white population than that in East Asians. However, it’s unknown whether genetic background underlies this disparity between ethnic groups. To assess the role of ethnic differences in genetic factors associated with this phenomenon.MethodsWe first constructed ethnic-specific polygenic risk scores (PRSs) to quantify individual genetic risk of lung cancer in Chinese and white populations. Then, we compared genetic risk and smoking as well as their interactions on lung cancer between two cohorts, including the China Kadoorie Biobank (CKB) and the UK Biobank (UKB). We also evaluated the absolute risk reduction over a 5-year period.Results19 SNPs and 23 SNPs were identified to construct the PRSs in Chinese and white populations, and smoking-related loci were only included in white populations. The PRSs were consistently associated with lung cancer risk respectively, but stronger associations were observed in smokers of the UKB (HR 1.26versus1.15,P=0.028). A significant interaction between genetic risk and smoking on lung cancer was observed in the UKB (RERI, 11.39 [95% CI, 7.01-17.94]), but not in the CKB. By comparing heavy smokers with nonsmokers, a greater absolute risk reduction was found in the UKB (10.95versus7.12 per 1000 person-years,PConclusionsIn China, tobacco control alone is not enough to reduce the burden of lung cancer, and comprehensive policies should be made to lower its high incidence.

A geographical flow (hereafter flow) is defined as a movement between locations at two different times. A group of spatiotemporal flows can be viewed as a cluster if their origins and destinations are both spatiotemporally concentrated. Identifying spatiotemporal flow clusters may help reveal underlying spatiotemporal mobility trends or intensive relationships between regions. Despite recent advances in flow clustering methods, most only consider spatial attributes and ignore temporal information, and may fail to differentiate space-close but time-separated clusters. To this end, we derive global and local versions of the Spatiotemporal Flow L-function, extended from the classical L-function for points, and thereby construct a clustering method. First, the global version is utilized to check whether flow data contain clusters and estimate the spatial and temporal scales of the clusters. The local version is then employed to extract the clusters with the estimated scales. Experiments of simulated data demonstrate that our method outperforms three state-of-the-art methods in identifying spatiotemporal flow clusters with arbitrary shapes and different densities and reducing subjectivity in the parameter selection process. A case study with taxi data shows that our method reveals residents’ spatiotemporal moving patterns, including rush-hour commuting and whole-daytime transferring among railway stations.

Autistic children (AC) show less audiovisual speech integration in the McGurk task, which correlates with their reduced mouth-looking time. The present study examined whether AC's less audiovisual speech integration in the McGurk task could be increased by increasing their mouth-looking time. We recruited 4- to 8-year-old AC and nonautistic children (NAC). In two experiments, we manipulated children's mouth-looking time, measured their audiovisual speech integration by employing the McGurk effect paradigm, and tracked their eye movements. In Experiment 1, we blurred the eyes in McGurk stimuli and compared children's performances in blurred-eyes and clear-eyes conditions. In Experiment 2, we cued children's attention to either the mouth or eyes of McGurk stimuli or asked them to view the McGurk stimuli freely. We found that both blurring the speaker's eyes and cuing to the speaker's mouth increased mouth-looking time and increased audiovisual speech integration in the McGurk task in AC. In addition, we found that blurring the speaker's eyes and cuing to the speaker's mouth also increased mouth-looking time in NAC, but neither blurring the speaker's eyes nor cuing to the speaker's mouth increased their audiovisual speech integration in the McGurk task. Our findings suggest that audiovisual speech integration in the McGurk task in AC could be increased by increasing their attention to the mouth. Our findings contribute to a deeper understanding of relations between face attention and audiovisual speech integration, and provide insights for the development of professional supports to increase audiovisual speech integration in AC. HIGHLIGHTS: The present study examined whether audiovisual speech integration in the McGurk task in AC could be increased by increasing their attention to the speaker's mouth. Blurring the speaker's eyes increased mouth-looking time and audiovisual speech integration in the McGurk task in AC. Cuing to the speaker's mouth also increased mouth-looking time and audiovisual speech integration in the McGurk task in AC. Audiovisual speech integration in the McGurk task in AC could be increased by increasing their attention to the speaker's mouth.

Accurate estimates of forest aboveground biomass (AGB) are critical for supporting strategies of ecosystem conservation and climate change mitigation. The Jiuzhaigou National Nature Reserve, located in Eastern Tibet Plateau, has rich forest resources on steep slopes and is very sensitive to climate change but plays an important role in the regulation of regional carbon cycles. However, an estimation of AGB of subalpine forests in the Nature Reserve has not been carried out and whether a global biomass model is available has not been determined. To provide this information, Landsat 8 OLI and Sentinel-2B data were combined to estimate subalpine forest AGB using linear regression, and two machine learning approaches–random forest and extreme gradient boosting, with 54 inventory plots. Regardless of forest type, Observed AGB of the Reserve varied from 61.7 to 475.1 Mg ha−1 with an average of 180.6 Mg ha−1. Results indicate that integrating the Landsat 8 OLI and Sentinel-2B imagery significantly improved model efficiency regardless of modelling approaches. The results highlight a potential way to improve the prediction of forest AGB in mountainous regions. Modelled AGB indicated a strong spatial variability. However, the modelled biomass varied greatly with global biomass products, indicating that global biomass products should be evaluated in regional AGB estimates and more field observations are required, particularly for areas with complex terrain to improve model accuracy.

Geographic information science (GIScience) and remote sensing have long provided essential data and methodological support for natural resource challenges and environmental problems research. With increasing advances in information technology, natural resource and environmental science research faces the dual challenges of data and computational intensiveness. Therefore, the role of remote sensing and GIScience in the fields of natural resources and environmental science in this new information era is a key concern of researchers. This study clarifies the definition and frameworks of these two disciplines and discusses their role in natural resource and environmental research. GIScience is the discipline that studies the abstract and formal expressions of the basic concepts and laws of geography, and its research framework mainly consists of geo-modeling, geo-analysis, and geo-computation. Remote sensing is a comprehensive technology that deals with the mechanisms of human effects on the natural ecological environment system by observing the earth surface system. Its main areas include sensors and platforms, information processing and interpretation, and natural resource and environmental applications. GIScience and remote sensing provide data and methodological support for resource and environmental science research. They play essential roles in promoting the development of resource and environmental science and other related technologies. This paper provides forecasts of ten future directions for GIScience and eight future directions for remote sensing, which aim to solve issues related to natural resources and the environment.

In this paper, a single degree of freedom (DOF) anthropomorphic gait rehabilitation mechanism with passive branch chain is proposed and optimized. First, the dimension parameters of the mechanism are designed. Taking the normal gait trajectory as the target, 1-DOF Watt-I six-bar mechanism driven by a uniform motor is adopted as the motion executer, and its path synthesis is carried out. Then, the lightweight design of the lower limb rehabilitation mechanism is implemented. A three-dimensional design model of the six-bar linkage is established, which is imported into ANSYS Workbench for static force analysis and topology optimization. Then, a 2-DOF passive chain is designed and imposed into the mechanism for a better dynamic and kinematic performance. In the end, a prototype of the 1-DOF six-bar gait rehab device with passive chain is built, and experiments are conducted using motion capture system to obtain the trajectory. The results show that the optimized mechanism can well simulate the motion of normal human gait trajectory, which verifies the effectiveness of the mechanism and the optimization method.