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Mechanical stirring can promote uniform distribution of crude oil temperature and increase the heating rate, but the effect is different for different heating methods in crude oil storage tank. In this paper, jet heating and tubular heating are used as the heating methods in the tank, the physical and mathematical models under the synergy of two heating methods and mechanical stirring are established, FVM and SIMPLE algorithm are used to numerical calculate. The results show that mechanical stirring can enhance the flow of crude oil in the tank, affect greatly the temperature and velocity fields of crude oil and improve uniformity of the temperature field. Mechanical stirring has more significant effect on tubular heating for the 1000 m3 actual oil storage tank. For tubular heating, mechanical stirring can increase the crude oil average velocity 13.8 times, heating rate by 0.123 °C/h, heating efficiency by 8.37 % and reduce the temperature variance by 92.03 % during 2h of heating. At the same time, the indicators of economic benefits for different heating methods are put forward, and the order of energy consumption per unit temperature rise is obtained: Tubular heating > Jet heating > Jet heating and stirring > Tubular heating and stirring.

Abstract Cities play a fundamental role in policy decision-making processes, necessitating the availability of city-level population projections to better understand future population dynamics and facilitate research across various domains, including urban planning, shrinking cities, GHG emission projections, GDP projections, disaster risk mitigation, and public health risk assessment. However, the current absence of city-level population projections for China is a significant gap in knowledge. Moreover, aggregating grid-level projections to the city level introduces substantial errors of approximately 30%, leading to discrepancies with actual population trends. The unique circumstances of China, characterized by comprehensive poverty reduction, compulsory education policies, and carbon neutrality goals, render scenarios like SSP4(Shared Socioeconomic Pathways) and SSP5 less applicable. To address the aforementioned limitations, this study made three key enhancements, which significantly refines and augments our previous investigation. Firstly, we refined the model, incorporating granular demographic data at the city level. Secondly, we redesigned the migration module to consider both regional and city-level population attractiveness. Lastly, we explored diverse fertility and migration scenarios.

The electric bus is an extremely important part of urban public transportation and has a huge impact on the ecosystem. However, the battery capacity is still a tough problem, and electric buses often face a booming demand for charging during peak periods. This paper focuses on the problem of electric bus battery swapping station (BSS) location. Based on the traffic flow assignment theory, this paper proposes a hybrid traffic assignment method based on GA and Frank–Wolfe algorithm, which has proved to be closer to the global optimum than the traditional method. This paper proposes a BSS selection model considering service quality as an evaluating indicator and a simulation is made based on a virtual road network. Compared with the traditional method, the result from the hybrid method is more suitable for electric buses when considering the situation at peak hours.

There is a growing interest in developing and implementing adaptive instructional systems to improve, automate, and personalize student education. A necessary part of any such adaptive instructional system is a student model used to predict or analyze learner behavior and inform adaptation. To help inform researchers in this area, this paper presents a state-of-the-art review of 11 years of research (2010-2021) in student modeling, focusing on learner characteristics, learning indicators, and foundational aspects of dissimilar models. We mainly emphasize increased prediction accuracy when using multidimensional learner data to create multimodal models in real-world adaptive instructional systems. In addition, we discuss challenges inherent in real-world multimodal modeling, such as uncontrolled data collection environments leading to noisy data and data sync issues. Finally, we reinforce our findings and conclusions through an industry case study of an adaptive instructional system. In our study, we verify that adding multiple data modalities increases our model prediction accuracy from 53.3% to 69%. At the same time, the challenges encountered with our real-world case study, including uncontrolled data collection environment with inevitably noisy data, calls for synchronization and noise control strategies for data quality and usability.

AbstractIn 2018, successive large-scale landslides occurred near the village of Baige in the Jinshajiang suture zone on the Qinghai–Tibet Plateau, posing substantial threat both to the lives and property of residents and to the engineering facilities along the upper and lower reaches of the Jinsha River. In this study, field investigation data, remote sensing images, aerial photography, microanalysis of rocks, and mechanical experiments were considered to ascertain the material and geomorphic conditions of the landslides and to explore the failure mechanism and process of evolution of the landslides under the coupled effect of exogenic and endogenic factors. Located in the Jinshajiang suture zone, the Baige landslides occurred close to the western boundary fault zone. The geological structure of the slope and the formation of landslides are controlled by the specific environmental tectonic dynamics of the suture zone. Tectonic damage has dramatically influenced the strength and hydraulic characteristics of the rock mass, and the rock’s uniaxial compressive strength and resistance to water disintegration have deteriorated markedly as a result. Strong weathering of the plateau and repeated groundwater infiltration have further reduced the mechanical properties of the unique rock and soil with inferior original strength characteristics. The intensive crustal uplift and the rapid river erosion have markedly altered the free face of the damaged rock mass, thereby increasing the gravitational potential energy of the rock mass. The long-term cumulative coupled effect of tectonic movement and surface denudation represents the fundamental mechanism of the Baige landslides. The Jinshajiang suture zone continues to face the risk of further massive landslides similar to those that occurred in Baige.

Understanding the causality between energy consumption, carbon emissions and economic growth is helpful for policymakers to formulate energy, environmental and economic policies. For the first time, based on nonlinear dynamics, this paper employs multispatial convergent cross mapping (CCM) to revisit the energy-carbon-economy causation for China, India and the G7 countries using both aggregate data and per capita data. The findings indicate that there are significant differences between developing countries and developed countries. A bidirectional nexus between energy consumption, carbon emissions and economic growth is found in China and India, but various causal relationships are identified in the G7 countries, including bidirectional, unidirectional and neutral nexus. The results confirm that the decoupling phenomenon is common in most G7 countries. By leveraging a variety of samples and a new approach, this study provides new evidence for policy authorities to formulate country-specific policies to obtain better environmental quality while achieving sustainable economic growth.

Background: To be aware of infection combining the avian influenza H9N2 virus with human immunodeficiency virus (HIV) increases the risk of the disease. Through epidemiological investigation, a better grasp of the pathogenetic process and possible sources of infection. Diagnostic criteria and laboratory tests were used to confirm the pathogen. Case Description: This patient was diagnosed with avian influenza H9N2 subtype and HIV infection according to diagnostic criteria. Environmental daub swab of two live poultry markets showed H9 positive. His family members were not detected with HIV and H9 subtype. The patient died from an H9N2 virus infection with HIV under specialists' consultation. Conclusion: The diagnostic capability of H9N2 and Acquired Immune Deficiency Syndrome in primary care should be noticed and improved. Infection with the H9N2 virus and HIV should be paid more attention to prevent public health events. [ABSTRACT FROM AUTHOR]

Introduction: At the end of 2019, the COVID-19 broke out, and spread to Guizhou province in January of 2020. Methodology: To acquire the epidemiologic characteristics of COVID-19 in Guizhou province, we collected data from 169 laboratoryconfirmed COVID-19 related cases. We described the demographic characteristics of the cases and estimated the incubation period, serial interval and the effective reproduction number. We also presented two representative case studies in Guizhou province: Case Study 1 was an example of the asymptomatic carrier; while Case Study 2 was an example of a large and complex infection chain that involved four different regions, spanning three provinces and eight families. Results: Two peaks in the incidence distribution associated with COVID-19 in Guizhou province were related to the 6.04 days (95% CI: 5.00 - 7.10) of incubation period and 6.14±2.21 days of serial interval. We also discussed the effectiveness of the control measures based on the instantaneous effective reproduction number that was a constantly declining curve. Conclusions: As of February 2, 2020, the estimated effective reproduction number was below 1, and no new cases were reported since February 26. These showed that Guizhou Province had achieved significant progress in preventing the spread of the epidemic. The medical isolation of close contacts was consequential. Meanwhile, the asymptomatic carriers and the super-spreaders must be isolated in time, who would cause a widespread infection. [ABSTRACT FROM AUTHOR]

Introduction: Coronavirus disease 2019 (COVID-19) has caused an outbreak around the world. Early detection of severe illness is crucial for patients' survival. We analysed initial clinical characteristics of 146 patients with COVID-19 reported in Guizhou province, China to explore risk factors for transforming mild illness to severe. Methodology: Data of 146 laboratory-confirmed cases were collected and evaluated by the survival analysis of univariate and multivariate Cox proportional hazards model. Results: On initial presentation, patients had fever (51.05%), dry cough (45.45%), headache (16.08%), shortness of breath (7.75%) and gastrointestinal symptoms (13.99%). Among 146 laboratory-confirmed cases, 30 patients (20.55%) had severe illness and needed Intensive Care Unit care for supportive treatment. The remaining patients (116, 79.45%) were non-severe cases. Nineteen (19/146, 13.01%) of 30 patients in the Intensive Care Unit had comorbidities, including hypertension (12, 40.00%), diabetes (5, 16.67%), cardiovascular disease (5, 16.67%) and pulmonary disease (4, 13.33%). For survival analysis, patients who had fever (HR = 3.30, 95% CI = 1.31, 8.29) and comorbidities (HR = 9.76, 95% CI = 4.28, 22.23) at baseline were more likely to be admitted into the Intensive Care Unit. Few variables were not related to the survival time of discharge from baseline to discharge and from Intensive Care Unit care to discharge. Conclusions: Severe patients with COVID-19 should be paid more attention. On initial symptoms, many patients did not have fever, but those with fever were more likely to be admitted to the Intensive Care Unit. Comorbidities were likewise a risk factor of severe COVID-19. [ABSTRACT FROM AUTHOR]