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Objective With the rapid growth of urban rail transit scale, the application of information-based intelligent vehicle operation and maintenance system becomes increasingly extensive, and the information security problem of the intelligent vehicle operation and maintenance system for urban rail transit becomes prominent gradually and needs to be solved urgently. Method Based on the information security risks and problems that the intelligent operation and maintenance system for urban rail transit vehicles may face, such as software vulnerabilities, systematic protection missing, network transmission security, etc., and with reference to a number of national and industrial information security standards, the technical solutions to information security protection are systematically proposed, including security zoning, boundary isolation, vertical authentication, and centralized supervision. The device host security is safeguarded by software hardening, access control, security audit and intrusion prevention.The network transmission security is safeguarded by secure partition, boundary isolation, secure transmission and robust network of the communication networks between vehicle-mounted, vehicle-ground and ground communication networks.The business data security is improved by controlling and protecting the processing steps including storage, transmission, application and destruction.The security of application platform is safeguarded by identity authentication, session management, access control, security audit and intrusion prevention. The security of the whole system management center is implemented through decentralized management and centralized control. Result & Conclusion A systematic, unified and comprehensive information security protection technology system is constructed to prevent the vehicle intelligent operation and maintenance system from malicious attacks and illegal intrusions, and protect the system, so as to achieve safe, efficient and reliable vehicle operation and maintenance in urban rail transit.

Background and Objectives: The coronavirus disease 2019 (COVID-19) pandemic originated in Wuhan, China, in December 2019, the first case diagnosed since January 2020 in Taiwan. The study about the potential impact of the COVID-19 pandemic on event, location, food source, and pathogens of foodborne disease (FBD) is limited in Taiwan. Our aim in this study is to investigate FBD in the context of the COVID-19 pandemic. Materials and Methods: We collected publicly available annual summary data from the FBD dataset in the Taiwan Food and Drug Administration and Certifiable Disease on reported FBD in Taiwan from 2019 to 2020. We used logistic regression to evaluate changes in the occurrence or likelihood of FBD cases and Poisson regression to examine the relative risk (RR) between FBD and climate factors. Results: Similar events occurred in 2019 and 2020, but the total number of FBD cases decreased from 6935 in 2019 to 4920 in 2020. The places where FBD decreased were in schools, hospitals, outdoors, vendors, and exteriors. The top place in FBD shifted from schools to restaurants. The top food source for FBD has changed from boxed food to compound food. Bacillus cereus and Salmonella emerged as the top two observed bacterial pathogens causing FBD. The risk of FBD cases increased with a higher air temperature, with an RR of 1.055 (1.05–1.061, p < 0.001) every 1 °C. Conclusion: The incidence of FBD decreased significantly during the COVID-19 pandemic in Taiwan. This decline may be attributed to protective measures implemented to control the spread of the virus. This shift in locations could be influenced by changes in public behavior, regulations, or other external factors. The study emphasizes the importance of understanding the sources and effectiveness of severe infection prevention policies. The government can use these findings to formulate evidence-based policies aimed at reducing FBD cases and promoting public health. Consumers can reduce the risk of FBD by following safe food handling and preparation recommendations.

Objective: Improve the detection accuracy and efficiency of apple surface defects. Methods: An detection method for apple surface defects was established based on an improved convolutional neural network (CNN) and data augmentation method. Firstly, the classical CNN was improved to detect apple surface defects. Then, using the conditional generation adversarial network, the image data of surface defect free and defective apples was augmented with synthetic apple images to improve the detection performance of the improved CNN for apple surface defects. Finally, by pruning the CNN model, the detection accuracy, detection speed and energy saving limits of apple surface defects were balanced reasonably to improve the practicability of the proposed method. Results: When 2 048 interpretive neurons were selected in the interpretation layer of the improved CNN, the average detection accuracy was the highest among the interpretive neuron number situations. Additionally, the diversity of the apple image data sets was enhanced with the synthetic apple images produced by the conditional generation adversarial network. In addition, the accuracy of the proposed method for detecting apple surface defects increased continuously with the increase of the proportion of the enhanced images in the test data set. When the ratio of the pruned model size to the original model size decreased from 100% to 50%, the detection efficiency of apple surface defects was doubled with 6.96% detection accuracy decreasing. Conclusion: This method is expected to realize the automatic defect detection in apple production and processing, and provide a reference for the developing of other fruit surface defect detection methods.

(1) Background: An asthma exacerbation that is not relieved with medication typically requires an emergency room visit (ERV). The coronavirus disease 2019 (COVID-19) pandemic began in Taiwan in January of 2020. The influence of the COVID-19 pandemic on pediatric ERVs in Taiwan was limited. Our aim was to survey pediatric asthma ERVs in the COVID-19 era; (2) Methods: Data were collected from the health quality database of the Taiwanese National Health Insurance Administration from 2019 to 2021. Air pollution and climatic factors in Taipei were used to evaluate these relationships. Changes in the rates of pediatric asthma ERVs were assessed using logistic regression analysis. Poisson regression was used to evaluate the impact of air pollution and climate change; (3) Results: The rate of pediatric asthma ERVs declined in different areas and at different hospital levels including medical centers, regional and local hospitals. Some air pollutants (particulate matter ≤ 2.5 µm, particulate matter ≤ 10 µm, nitrogen dioxide, and carbon monoxide) reduced during the COVID-19 lockdown. Ozone increased the relative risk (RR) of pediatric asthma ERVs during the COVID-19 period by 1.094 (95% CI: 1.095–1.12) per 1 ppb increase; (4) Conclusions: The rate of pediatric asthma ERVs declined during the COVID-19 pandemic and ozone has harmful effects. Based on these results, the government could reduce the number of pediatric asthma ERVs through healthcare programs, thereby promoting children’s health.

Background and Objectives: Hearing loss after septicemia has been found in mice; the long-term risk increased 50-fold in young adults in a previous study. Hearing loss after septicemia has not received much attention. The aim of this study was to assess the relationship between septicemia and subsequent hearing loss. Materials and Methods: Inpatient data were obtained from the Taiwan Insurance Database. We defined patients with sensorineural hearing loss and excluded patients under 18 years of age. Patients without hearing loss were selected as controls at a frequency of 1:5. The date of admission was defined as the date of diagnosis. Comorbidities in the 3 years preceding the date of diagnosis were retrieved retrospectively. Associations with hearing loss were established by multiple logistic regression and forward stepwise selection. Results: The odds ratio (OR) for the association between sepsis and hearing loss was 3.052 (95% CI: 1.583–5.884). Autoimmune disease (OR: 5.828 (95% CI: 1.906–17.816)), brain injury (OR: 2.264 (95% CI: 1.212–4.229)) and ischemic stroke (OR: 1.47 (95% CI: 1.087–1.988)) were associated with hearing loss. Conclusions: Our study shows that hearing loss occurred after septicemia. Apoptosis caused by sepsis and ischemia can lead to hair cell damage, leading to hearing loss. Clinicians should be aware of possible subsequent complications of septicemia and provide appropriate treatment and prevention strategies for complications.

Although autologous nerve transplantation is the gold standard for treating peripheral nerve defects, it has many clinical limitations. As an alternative, various tissue-engineered nerve grafts have been developed to substitute for autologous nerves. In this study, a novel nerve graft composed of chitin scaffolds and a small autologous nerve was used to repair sciatic nerve defects in rats. The novel nerve graft greatly facilitated regeneration of the sciatic nerve and myelin sheath, reduced atrophy of the target muscle, and effectively restored neurological function. When the epineurium of the small autogenous nerve was removed, the degree of nerve regeneration was similar to that which occurs after autogenous nerve transplantation. These findings suggest that our novel nerve graft might eventually be a new option for the construction of tissue-engineered nerve scaffolds. The study was approved by the Research Ethics Committee of Peking University People’s Hospital (approval No. 2019PHE27) on October 18, 2019.

Abstract Background SCL/TAL1 interrupting locus (STIL) is associated with the progression of several tumors; however, the biological role of STIL in osteosarcoma remains poorly understood. Methods In this study, the clinical significance of STIL in osteosarcoma was analyzed by gene chip data recorded in public databases. STIL expression was silenced in osteosarcoma cell lines to observe the effects on proliferation, apoptosis, invasion, and migration. Differentially expressed genes (DEGs) in the osteosarcoma chip were analyzed using The Limma package, and STIL co-expressed genes were obtained via the Pearson correlation coefficient. The potential molecular mechanism of STIL in osteosarcoma was further explored by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Results Osteosarcoma was associated with higher STIL expression compared to the control samples, and the standardized mean difference (SMD) was 1.52. STIL also had a good ability to distinguish osteosarcoma from non-osteosarcoma samples [area under the curve (AUC) = 0.96]. After silencing STIL, osteosarcoma cell proliferation decreased, apoptosis increased, and the migratory and invasion ability decreased. A total of 294 STIL differentially co-expressed genes were screened, and a bioinformatics analysis found that differentially co-expressed genes were primarily enriched in the cell signaling pathways. The protein-protein interaction (PPI) network indicated that the hub differentially co-expressed genes of STIL were CDK1, CCNB2, CDC20, CCNA2, BUB1, and AURKB. Conclusions STIL is associated with osteosarcoma proliferation and invasion, and may be promote the progression of osteosarcoma by regulating the expression of CDK1, CCNB2, CDC20, CCNA2, BUB1 and AURKB.

By collecting the magnetic field information of each spatial point, we can build a magnetic field fingerprint map. When the user is positioning, the magnetic field measured by the sensor is matched with the magnetic field fingerprint map to identify the user’s location. However, since the magnetic field is easily affected by external magnetic fields and magnetic storms, which can lead to “local temporal-spatial variation”, it is difficult to construct a stable and accurate magnetic field fingerprint map for indoor positioning. This research proposes a new magnetic indoor positioning method, which combines a magnetic sensor array composed of three magnetic sensors and a recurrent probabilistic neural network (RPNN) to realize a high-precision indoor positioning system. The magnetic sensor array can detect subtle magnetic anomalies and spatial variations to improve the stability and accuracy of magnetic field fingerprint maps, and the RPNN model is built for recognizing magnetic field fingerprint. We implement an embedded magnetic sensor array positioning system, which is evaluated in an experimental environment. Our method can reduce the noise caused by the spatial-temporal variation of the magnetic field, thus greatly improving the indoor positioning accuracy, reaching an average positioning accuracy of 0.78 m.

To control the solar power, reliability and stability are two main challenges. In addition, the total harmonic distortion (THD) must be within limits for optimal operation. In an inverter, the harmonics are produced during the conversion of DC power to AC power, which will affect the power electronic devices. Therefore, to overcome such challenges in high voltage and high power systems multilevel inverter (MLI) topology is more useful. Such type of inverters uses various DC voltage levels to generate the stepped AC at its output, approaching the sinusoidal shape. The cascaded H-bridge, capacitor-clamped, and diode-clamped are the most commonly used multilevel inverters topologies. For photovoltaic (PV) usage, cascaded H-bridge (CHB) MLI is more adaptive among the three topologies, where for each H-bridge unit; each PV model behaves as an isolated DC source. This paper specifically focused on the simulation of PV power as a source to the system and displayed the potential of a single-phase 11-level CHB inverter. For switching the IGBT devices, sinusoidal pulse width modulation (SPWM) is applied. Moreover, the fuzzy logic control (FLC) is introduced to improve the power quality. FLC reduce the THD via finding the appropriate set of IGBT switch signals. To show the improvement in the operation and reduction in the complex harmony signal effects of the CHB 11-level inverter, the proposed system is designed in Matlab/Simulink software. Finally, the results show that the dynamic behavior of the FLC is much better than the traditional proportional integral derivative (PID) controller.