Search

The issue of missing data is common in a bike-sharing system due to various reasons, such as the failure of data collection devices. To better utilize the bike-sharing data and guide the operation and planning of the public transportation system, missing data need to be imputed. When data are missing to a rate as high as 50%, or when the training set to calibrate a model is incomplete, many commonly used methods dealing with missing data may fail. Our concerns are how to incorporate the temporal-spatial relations from counts from a bike-sharing system and ensure a stable performance when the training set is incomplete. To solve these issues, a method is proposed using the strengths of a Generative Adversarial Network (GAN), which learns the distribution of missingness and generates data close to ground-truth values to impute the missing counts from a bike-sharing system. Traffic counts data are collected from Bluebikes, Boston. With limited available observations, the proposed method imputes missing traffic counts when concerning two scenarios: not missing at random (NMAR) problem and MCAR (Missing Completely at Random problem). The proposed method shows robustness with increasing missingness ratios in the dataset. In our experiment, the RMSE values used to measure the missing data imputation accuracy are smaller than 0.15, while the missingness ratio raises from 20% to 80%. Compared to other baseline methods, the method is robust and efficient for the missing data imputation problem for a bike-sharing system.

Atrial fibrillation (AF) is a major complication of type 2 diabetes mellitus (T2DM) and plays critical roles in the pathogenesis of atrial remodeling. However, the differentially expressed genes in atria during the development of AF induced by hyperglycemia have rarely been reported. Here, we showed time-dependent increased AF incidence and duration, atrial enlargement, inflammation, fibrosis, conduction time and action potential duration in db/db mice, a model of T2DM. RNA sequencing analysis showed that 2256 genes were differentially expressed in the atria at 12, 14 and 16 weeks. Gene Ontology analysis showed that these genes participate primarily in cell adhesion, cellular response to interferon-beta, immune system process, positive regulation of cell migration, ion transport and cellular response to interferon-gamma. Analysis of significant pathways revealed the IL-17 signaling pathway, TNF signaling pathway, MAPK signaling pathway, chemokine signaling pathway, and cAMP receptor signaling. Additionally, these differentially expressed genes were classified into 50 profiles by hierarchical clustering analysis. Twelve of these profiles were significant and comprised 1115 genes. Gene coexpression network analysis identified that mitogen-activated protein kinase 10 (MAPK10) was localized in the core of the gene network and was the most highly expressed gene at different time points. Knockdown of MAPK10 markedly attenuated DM-induced AF incidence, atrial inflammation, fibrosis, electrical disorder and apoptosis in db/db mice. In summary, the present findings revealed that many genes are involved in DM-induced AF and that MAPK10 plays a central role in this disease, indicating that strategies targeting MAPK10 may represent a potential therapeutic approach to treat DM-induced AF.

Conventional traffic crash analysis methods often use highly aggregated data, making it difficult to understand the effects of time-varying factors on crash occurrence. In this study, the combined effect of roadway geometry, speed distribution, and weather conditions on crash occurrence and severity was investigated on short duration daily level crash data. This study collected data from four different sources on rural two-lane roadways in Texas. A machine learning method, XGBoost (eXtreme Gradient Boosting), was applied to train the data. To mitigate imbalanced data problems, a synthetic minority oversampling technique (SMOTE) was applied. The XGBoost model was trained separately on all crash occurrences and severe crash occurrences. Finally, an explainable artificial intelligence (AI) technique, SHAP (SHapley Additive exPlanation), was applied to investigate the contribution of all variables to the model’s output. The results show that annual average daily traffic has a significant impact on all crash occurrences and severe crash (fatal and incapacitating injury) occurrences on rural two-lane roadways. Moreover, weather condition factors including daily precipitation, average visibility, and the standard deviation of visibility show association with high crash occurrences. The short duration crash prediction models of this study can provide more insights into the relationships between crash, geometric variables, traffic exposure, weather, and operating speed.

With support from United States Department of Transportation and state policies and regulations, in recent years manufacturers have initiated automated vehicle (AV) testing on public roads. Vehicle autonomy has grown from simulations and controlled environments to real-world driving environments with normal traffic. California is one of the states with an autonomous vehicle tester (AVT) program. It was established as early as 2014 for authorized manufacturers to test their AVs on public roads. This review examines permit holder information, autonomous mileage reports, autonomous vehicle disengagement reports, and autonomous vehicle collision reports over a six-year period. In addition to reviewing operating experience and the growth of AV testing, this study conducted in-depth analysis to evaluate maturity in automated driving technology and reported disengagement causes. It shows that a state-run AVT program boosts maturity in automated driving technology. At the same time, by participating in the AVT program, AV manufacturers showed a trend toward improvement in their AV technologies (e.g., an 8% fall in disengagements caused by hardware and software discrepancies and a 12% fall in those caused by perception discrepancies). States are encouraged to initiate or continue their AVT programs for the benefit of autonomous driving on public roads.

The study was to probe into the application of ultrasound technique in gestational diabetes mellitus (GDM) and research the progress of PEG-PCL nano micelle and ultrasound technique.210 patients with a singleton pregnancy fetus, who received the fetal echocardiography in Yuhang District First People's Hospital from March 2019 to March 2020, were selected as the subjects, including 101 fetuses who were confirmed as gestational diabetes mellitus(GDM), and 109 normal fetuses (control group). The ultrasound cardiogram technique was employed to detect the thickness of the fetus ventricle septum, mitral/tricuspid annular displacement, left/right TEI indexes, and so on. The mean value of three cardiac cycles was taken as the test results. Finally, SPSS17.0 software was applied to the analysis of data. The nano micelle was made from the amphiphilic block copolymers (PEG-PCL) using the dialysis method/solvent evaporation method. The nanoscale ultrasound contrast agent was prepared from Decafluoropentane which was imaging gas. The characterizations were studied using the optical microscope, and transmission electron microscopy (TEM). The temperature sensitivity and ultrasound sensitivity of the nano-ultrasound contrast agent were analyzed with the particle size as the evaluation index. The in-vitro ultrasound contrast experiment was conducted to study the contrast-enhanced effect.The fetal Tei index of the case group was higher than that of the control group, of which P0.05 had statistical significance. However, the thickness of the fetus ventricle septum, Em, Am, and Em/Am of mitral/tricuspid annular were not significantly different from those of the control group (P0.05). The nano ultrasonic contrast agent prepared through the ultrasonic injection method had a uniform particle size and a hollow shell-core structure under an electron projection microscope. The particle size of the nano-ultrasound contrast agent varied with temperature, and its microbubbles were generated under ultrasonic conditions. As compared with the blank degassed water group, a real linear echo appeared inside the contrast agent group, with small and even echo spots. The back echo remained with no obvious attenuation and lasted for a longer period. However, the blank degassed group had no distinct echo intensity and spot.PEG-PCL nano-ultrasound contrast agent achieved an excellent imaging effect; there was no obvious change to heart function and structure of the fetus, when gestational diabetes pregnant had blood sugar perfectly controlled, however, the fetus's heart function may change in the last trimester.

Polypropylene fibers are added to concrete to improve the toughness of the material. Manufactured sand and fly ash with high content are used to reduce the impact on the environment and cost. The response surface method (RSM) was used to design the test and study the mechanical and bending properties of polypropylene-fiber-reinforced high-performance concrete (PPFHPC). Three process variables, including the content of polypropylene fiber (1%, 1.5%, and 2%), content of fly ash (45%, 60%, and 75%), and water-binder (W/B) ratio (0.27, 0.3, and 0.33), were considered as factors. The compressive strength, flexural strength, flexural-compressive ratio, splitting tensile strength, and first-crack strength and bending strength of thin plate were evaluated. The prediction model established by the RSM showed the correlation and predictability between the response and the factors, and the corresponding relationship equation between the factors and the response was obtained. Results of multiobjective optimization indicated that the optimal three factors (content of PPF, FA, and W/B) were 2%, 62%, and 0.27. The established model can be used to predict the basic mechanical properties and bending properties of materials. This test laid a theoretical foundation for the development of PPFHPC materials.

The deck condition of bridges is one of the most important factors impacting the connectivity and efficiency of transportation networks. Bridges with quickly deteriorating deck conditions are a huge financial burden for transportation agencies and can downgrade the efficiency of the whole transportation network. This study utilizes an interpretable machine learning framework, Shapley additive explanation (SHAP), to investigate the associations between various factors, such as wearing surface, deck structure, and so forth, and bridges with quickly deteriorating deck conditions nationwide. An XGBoost model is trained to perform the binary classification task on a heavily imbalanced dataset and classify relatively young bridges (less than 20 years old) with poor/fair deck conditions and relatively old bridges (30–40 years old) with good deck conditions in the National Bridge Inventory (NBI) database. The accuracy of the predictive model is 0.91, and the AUC score is about 0.83. After applying this well-performed predictive model on the interpretable machine learning framework, the results revealed that without wearing surface, corrugated steel deck structure, wide bridge structure, and long span are highly associated with bridges with quickly deteriorating decks. The results also show that bridges with a relatively low average daily traffic (ADT) or truck percentage of ADT are in a dilemma zone, where the overall traffic or truck volume of the bridge is not low enough to prevent fast deterioration, but not high enough for eligibility for the funding required for more durable materials during construction or appropriate maintenance.

The electrochemical carbon dioxide reduction reaction (CRR) to formic acid has shown great potential in carbon capture, utilization and storage (CCUS).

Understanding soil water dynamics and their influencing factors is an important basis for formulating efficient water-use strategies aimed at alleviating water stress, especially in areas with water shortages. In this research, six plots with different densities were designed to systematically analyze the influences of Phragmites australis density and groundwater level on soil water in a semiarid wetland. (1) The Phragmites australis density had a negative influence on the soil water in the 0-40 cm profile and from April to August. (2) The Phragmites australis density had a positive effect on the annual variation degree of the soil water storage. The water replenishment could be implemented in April and June for low and high Phragmites australis densities, respectively. (3) The groundwater level had a significant influence on the soil water content of the 0-50 cm layer, and the change was positively correlated with the Phragmites australis density. The influence of groundwater level on soil water was more influential than that of Phragmites australis density. (4) The suitable average groundwater depth for the 0%, 20%, 40%, 60%, 80% and 100% densities were 76 cm, 63 cm, 50 cm, 37 cm, 23 cm and 10 cm, respectively. The suitable average densities of Phragmites australis for the groundwater depth of 35 cm, 40 cm, 45 cm and 50 cm were 62%, 55%, 47% and 40%, respectively. This research can provide a theoretical support for the management of Phragmites australis density and groundwater level in the Baiyangdian wetland.

This work reports that via confining high density of 16 wt% single Mo atoms into the lattice of CoOOH nanosheets and simultaneously fabricating robust nanoframes of the nanosheets, an unprecedented large-current-density OER activity is achieved.

An asymmetric electrolyte design has been proposed for lithium-ion capacitors which was enabled by a metal–organic framework modified separator because of the physical obstruction and chemical interactions toward the soluble redox mediators.

The BDS multipath delay error is highly related to the surrounding monitoring environment, which cannot be eliminated or mitigated by establishing the double difference observation model. In the actual monitoring environment, due to the complexity of the BDS constellation, it is difficult for existing algorithms to consider GEO, IGSO, MEO and other different orbital types of satellites for real-time and efficient multipath error reduction. Therefore, this paper proposes a novel BDS dual-frequency multipath error reduction method for real deformation monitoring for BDS considering various satellite orbit types. This method extracts the single error residual of each satellite based on the assumption of "zero mean", and divides the appropriate grid density of GEO and IGSO\MEO respectively, to construct the dual-frequency multi-path hemispherical map model suitable for BDS satellites with different orbital types. This method can realize the multi-path error elimination of the observed values of different orbits and different frequencies. The results of simulation experiments and real deformation monitoring data demonstrate that this method can effectively eliminate low-frequency multipath delay errors in the observation domain and coordinate domain. After multipath correction, the precision of the horizontal coordinates and height coordinates is 1.7mm and 4.6mm. The precision of the horizontal coordinate and height coordinate is increased by 50% and 60% respectively. The fixed rate of ambiguity increased by 5%~7%.

Super Tau-Charm Facility (STCF) is a next-generation high luminosity electron-positron collider facility and is currently one of the major options for accelerator-based particle physics experiment in China. The crystal-based electromagnetic calorimeter (EMC) with undoped CsI is a major sub-system of the STCF spectrometer. To fulfill the increasing physics requirements on measurement precision and the suffering of radiation, improving the detected light yield is an important task of STCF EMC R&D. This paper studies a "wavelength shifting in propagation" scheme for STCF EMC using the nanostructured organosilicon luminophore (NOL). The studies are performed by both Monte Carlo simulation and experimental tests. The light yield is proved to be improved by a factor of 1.59 in the experiment. Meanwhile, a study of the NOL's radiation hardness is carried out to verify the reliability of the NOL. No obvious degradation in the performance is observed with the total ionization does up to 100 krad, far beyond the total radiation dose of STCF with ten years of operation., 18 pages, 8 figures

Glycogen synthase kinase 3 beta (GSK3β) has emerged as a therapeutic target for breast cancer. As inhibitors of GSK-3β, 1,2,4-thiadiazole-3,5-dione (TDZD) family members have been reported as potential candidates for cancer treatment. In this study, the anticancer effects of ethiadin (ETD-174), one of the chemical synthesis compounds of TDZD, were investigated in MCF-7 human breast cancer cells. MCF-7 cells incubated with different doses of ETD-174 for different time periods. CCK-8 assays were carried out to test the effect of ETD-174 on the proliferation of MCF-7 cells. The occurrence of apoptosis was detected by Hoechst 33258 staining and flow cytometry. ETD-174 on cell migration and colony formation were examined by wound healing experiments and soft agar assays. Relative protein expressions were conducted with immunoblot assay. ETD-174 demonstrated a higher degree of cytotoxicity in MCF-7 cells. Topical morphological changes of apoptotic body formation after ETD-174 treatment were observed. Meanwhile, apoptosis was elicited by ETD-174. Also, ETD-174 could inhibit the migration and clonality of MCF-7 cells. After the treatment with ETD-174, the level of phosphorylation of GSK3β

Background The underlying circular RNAs (circRNAs)-related competitive endogenous RNA (ceRNA) mechanisms of pathogenesis and prognosis in non-small cell lung cancer (NSCLC) remain unclear. Methods Differentially expressed circRNAs (DECs) in two Gene Expression Omnibus datasets (GSE101684 and GSE112214) were identified by utilizing R package (Limma). Circinteractome and StarBase databases were used to predict circRNA associated-miRNAs and mRNAs, respectively. Then, protein–protein interaction (PPI) network of hub genes and ceRNA network were constructed by STRING and Cytoscape. Also, analyses of functional enrichment, genomic mutation and diagnostic ROC were performed. TIMER database was used to analyze the association between immune infiltration and target genes. Kaplan–Meier analysis, cox regression and the nomogram prediction model were used to evaluate the prognostic value of target genes. Finally, the expression of potential circRNAs and target genes was validated in cell lines and tissues by quantitative real-time PCR (qRT-PCR) and Human Protein Atlas (HPA) database. Results In this study, 15 DECs were identified between NSCLC tissues and adjacent-normal tissues in two GEO datasets. Following the qRT-PCR corroboration, 7 DECs (hsa_circ_0002017, hsa_circ_0069244, hsa_circ_026337, hsa_circ_0002346, hsa_circ_0007386, hsa_circ_0008234, hsa_circ_0006857) were dramatically downregulated in A549 and SK-MES-1 compared with HFL-1 cells. Then, 12 circRNA-sponged miRNAs were screened by Circinteractome and StarBase, especially, hsa-miR-767-3p and hsa-miR-767-5p were significantly up-regulated and relevant to the prognosis. Utilizing the miRDB and Cytoscape, 12 miRNA-target genes were found. Functional enrichment, genomic mutation and diagnostic analyses were also performed. Among them, FNBP1, AKT3, HERC1, COL4A1, TOLLIP, ARRB1, FZD4 and PIK3R1 were related to the immune infiltration via TIMER database. The expression of ARRB1, FNBP1, FZD4, and HERC1 was correlated with poor overall survival (OS) in NSCLC patients by cox regression and nomogram. Furthermore, the hub-mRNAs were validated in cell lines and tissues. Conclusion We constructed the circRNA-miRNA-mRNA network that might provide novel insights into the pathogenesis of NSCLC and reveal promising immune infiltration and prognostic biomarkers.

Objective: To test the efficacy and safety of modified hysterosalpingography (HSG) for infertile patients.Altogether 110 infertile cases from March 2018 to July 2020 were grouped into the observation group (OG, 58 cases) and the control group (CG, 52 cases) according to different therapies. The OG was treated with modified HSG, while the CG was treated with conventional HSG. The tubal patency after treatment, sex hormone levels before and after therapy [including luteinizing hormone (LH), follicle stimulating hormone (FSH), estradiol (E2)], changes in uterine volume and endometrial thickness before and after therapy were tested and compared between the CG and the OG. The individuals were followed up for one year, and the pregnancy success rate was recorded. Finally, the adverse reactions of the CG and the OG after treatment were recorded and compared.After treatment, the sex hormone level, tubal patency, uterine volume and endometrial thickness of the CG and the OG were markedly elevated, but the improvement of the OG was more obvious than that of the CG. Follow-up analysis revealed that the pregnancy success rate of theOG was markedly higher than that of theCG, and the incidence of adverse reactions in OG was markedly lower than that in CG.The modified HSG can effectively improve the pregnancy situation of patients and has higher safety compared with the traditional HSG, so it is worth popularizing in clinic.