Wuhan Research Articles

Pathway analysis of clinical nurse educator’s intention to use virtual reality technology based on the UTAUT model

PurposeThis study aims to investigate the willingness of clinical nurse educator to adopt virtual reality technology, while also examining the underlying mechanisms that influence this willingness through the lens of the Unified Theory of Acceptance and Use of Technology (UTAUT).MethodsA convenience sampling method was employed to select 225 clinical nurse educator, all of whom possess a professional qualification certificate as nurse practitioners, from a tertiary hospital in Wuhan City, Hubei Province. The study utilized an adapted UTAUT model theory-based design to develop several questionnaires: the performance expectancy questionnaire (11 items), the effort expectancy questionnaire (4 items), the social influence questionnaire (6 items), the facilitating conditions questionnaire (7 items), and the behavioral intention questionnaire (4 items). These instruments were designed to assess the clinical nurse educators’ willingness to adopt VR technology. Furthermore, a regression model was established to analyze the factors influencing this willingness, utilizing SPSS 26.0 for statistical analysis and validating the model through path analysis with AMOS 24.0, where a p-value of less than 0.05 was considered statistically significant.ResultsThe questionnaire demonstrated strong reliability and validity, yielding a total of 222 valid samples, comprising 209 females (94.14%) and 13 males (5.86%). Among the clinical nurse educators, 163 (73.42%) reported a willingness to use virtual reality technology, with scores of 4 or higher. Pearson correlation analysis revealed positive correlations between performance expectancy, effort expectancy, social influence, and facilitating conditions with behavioral intention (p < 0.05). Furthermore, regression analysis indicated that performance expectancy, effort expectancy, social influence, and facilitating conditions had a positive impact on behavioral intention (p < 0.05). The path model exhibited a good fit, and the results were consistent with the regression analysis, showing that the effects of performance expectancy, effort expectancy, and social influence on the behavioral intention to use virtual reality technology were 0.231, 0.150, 0.236, and 0.247, respectively.ConclusionClinical nurse educators exhibit a robust willingness to engage with VR technology. Moreover, improving factors such as performance expectancy, effort expectancy, social influence, and facilitating conditions can substantially enhance their readiness to adopt this technology.

Characterization of Disinfection By-Products Originating from Residual Chlorine-Based Disinfectants in Drinking Water Sources

In this study, samples from the Yangtze River, Han River, and Liangzi Lake in Wuhan City were utilized to characterize the formation of disinfection by-products (DBPs) from chlorine-based disinfection residues in drinking water sources. The results indicated that the main DBPs in drinking water sources were trichloromethane (TCM) and trichloroacetic acid (TCAA). The generation of DBPs was significantly positively correlated with oxidative substances, aromatic compounds, pH, and ammonia nitrogen (NH3-N) content in the water. The concentration of TCAA increased from 0 to 2.45 ± 0.31 mg/L when the reaction time increased to 72 h. As the NaClO concentration increased from 5 mg/L to 15 mg/L, the concentrations of TCAA, TBM, and DCAN increased from 2.03 ± 0.04 mg/L, 0 mg/L, and 0 mg/L to 2.49 ± 0.34 mg/L, 0.21 ± 0.07 mg/L, and 0.10 ± 0.04 mg/L before decreasing to 1.75 ± 0.19 mg/L, 0.17 ± 0.07 mg/L, and 0.04 ± 0.05 mg/L, respectively. The orthogonal experimental results showed that Br−, NH3-N, and pH all had significant influences on the TCM generation, whereas temperature affected the formation of TCAA in the Han River. This work reveals the factors influencing the generation of DBPs from chlorine-based disinfection residues, offering a prevention and control method for DBPs in drinking water sources from a theoretical perspective.

First Report of Lelliottia amnigena Causing Soft Rot on Purple Stem Mustards in China.

The purple stem mustards (Brassica rapa subsp. chinensis var. purpuraria) (Govaerts R, 2003) are widely cultivated along Yangtze River Valley in China, which is famous for its flavorful and nutritious edible stalks (Wang et al., 2022). In February 2023, a disease of soft rot was observed in multiple purple stem mustards planting fields in Wuhan city, Hubei province, China (30.41°N, 114.22°E). Disease incidence rates were almost 20 to 30% in the planting area (5 ha in size), causing severe economic loss. Infected plants displayed water-soaked symptoms at the base of the petioles, emitting a foul soft rot odor. The severely infected petioles, stems and roots exhibit pus symptoms leading to plant death. To identify the causal agent, small pieces of soft rot symptomatic tissue were cut from the margin of necrotic lesions and surface disinfected with 75% (v/v) ethanol for 30 seconds, followed by three successive rinses with sterile distilled water. The exudates from the clipped tissues were serially diluted and then incubated onto nutrient agar (NA) plates to obtain purified strains at 28°C for 48 hours (Koike et al., 2002). After incubation, 15 strains were obtained and the colonies of all strains were Gram-negative, aerobic, small, round, convex, whitish to dull white, and had smooth slimy edges. Three single bacterial strains CT020801 - CT020803, which were individually isolated from three different diseased samples, were selected as representative strains for further study. Biochemical tests using the BIOLOG GENIII microplate system (Biolog, Hayward, CA, USA) revealed that these strains were positive for methyl red, pectin, dextrin, D-Cellobiose, β-galactosidase, citrate, and maltose, but negative for indole, arginine dihydrolase, urease, ornithine decarboxylase, and gelatinase tests. The 16S ribosomal RNA gene and the three housekeeping genes, atpD, rpoB, and recN were amplified using genomic DNA of Lelliottia amnigena NCTC12124T as the template, with specially designed primers. All amplified fragments were sequenced and deposited in GenBank with accession numbers OQ954706-OQ954707, OQ954713, and OQ953873-OQ953881. BLAST alignments of the 16S rRNA, atpD, rpoB and recN sequences revealed that the sequences of Strain CT020801-03 exhibited the highest identity (100%, ≥97.97%, ≥98.85% and ≥94.52%, respectively) with L. amnigena （Figure S2）. Phylogenetic tree analysis based on multilocus sequence joint 16S rRNA - atpD - rpoB - recN revealed that CT020801 - CT020803 and L. amnigena clustered together in the same clade (Carrie et al., 2013). These results were consistent with those reported for Lelliottia amnigena (Osei et al., 2022). To confirm pathogenicity, healthy base petioles of three-week-old purple stem mustards seedlings were stab inoculated with 20 μL bacterial suspensions (approximately 108 CFU/mL) and then incubated at 28°C and 80% relative humidity in a growth chamber. A sterile liquid NB medium served as the negative control. The test was repeated thrice with each test consisting of five seedlings per treatment. After three days, soft rot symptoms appeared on the stem bases of the inoculated plants, consistent with the initial symptoms observed in the field. Control plants showed no symptoms. The strains were successfully re-isolated from symptomatic plants and identified as L. amnigena, fulfilling Koch's postulates. L. amnigena, a member of the Enterobacter genus (Birlutiu et al., 2023; Brady et al., 2013; Izard et al., 1981), is commonly found in soil and has been identified as an opportunistic pathogen responsible for plant soft rot disease (Reyes-García et al., 2020; Schroeder et al., 2009; Wu et al., 2023). Previous studies have linked L. amnigena to soft rot disease in potato tubers in China. However, this study marks the first documented case of L. amnigena causing soft rot disease in purple stem mustards in China. This discovery expands the known host range of the pathogenic bacteria and will help to provide essential information for making effective measures to manage this disease.

Deciphering the new governance experiment of dilapidated neighborhoods in China: A case of Xi'ma New Village, Wuhan

Approximately 100 million residents in Chinese cities inhabit former work-unit neighborhoods and municipal housing areas. Since the 1990s, the state has retreated from the direct provision of neighborhood services. However, as the alternative approach, commercialized property management has largely failed in these neighborhoods, leading to their gradual decline into “dilapidated neighborhoods.” Consequently, the poor living conditions and inadequate services severely constrained the well-being of these residents. Recently, new governance experiments have emerged in dilapidated neighborhoods across Chinese cities, warranting significant attention and exploration. Drawing on fieldwork and interviews conducted from 2019 to 2023 in Xi'ma New Village, Wuhan City, this research investigates the evolving governance shaped by affordable property management. Our findings indicate that, first, when sponsoring dilapidated neighbourhoods for affordable property management, the state's rationale is to address the crisis and alleviate social tensions; second, state leadership is reinforced through a multi-scalar governance network surrounding property management; third, in this case, the process of how the state achieved the above goals through deploying and mobilizing market and society exemplifies “state entrepreneurialism” in Chinese cities. Thus, the study offers nuanced insights, particularly at the neighborhood level, enabling readers to understand the evolving governance modalities in Chinese cities, especially in the context of (re)increasing state control and leadership.

The challenges of frontline health managers during the COVID-19 pandemic in India: A framework analysis study

ABSTRACT Background: Coronavirus was first officially reported in Wuhan city of China in December 2019. As this novel coronavirus spread rapidly throughout the world, health care workers faced many difficulties addressing the pandemic. In the present study, we explored the challenges faced by front-line health managers on human resource management, execution of the central policies, and training and in formulating innovative approaches during the coronavirus disease 2019 (COVID-19) pandemic in India. Methods: A qualitative study was conducted using framework analysis among front-line health managers concerning COVID-19 management at the district level. We conducted 120 in-depth interviews among eight states with the use of an interview guide. Results: The results are described under five sections: ‘challenges of front-line managers in policymaking and its execution’, ‘human resource management’, ‘gaps in local execution of central policies’, ‘challenges in training workforce and data management’, and ‘innovative approaches adopted during COVID 19’. Conclusions: We observed that a centre-down approach was not appreciated much. Many participants felt that there was a need to understand the local context and appropriate amendment. The private system is a part of the Indian health system and can never be ignored; thus, all guidelines should include the private system.

FASTER AND COST-EFFECTIVE EXTRACTION FREE METHOD FOR SARS-COV2 DETECTION BY RT-PCR

Background: The World Health Organization (WHO) declared an outbreak of febrile respiratory illness caused by Severe Acute Respiratory Syndrome Corona Virus-2 (SARS-CoV-2) in Wuhan City, China in December 2019. Within the immediate outbreak of three months, the global community was challenged with a devastating pandemic that caused heavy morbidities and mortalities around the globe. The expeditious spread of the virus, challenged the diagnostic laboratories to rapidly develop the accurate molecular diagnostic methods. As SARS CoV-2 assays became available for testing on existing molecular platforms, laboratories devoted unprecedented energy and resources to evaluating the analytical performance of the new tests and in some cases developed their diagnostic assays under FDA-EUA guidance. Aim: This study aims to compare the diagnostic efficacy of the extraction-free method of COVID-19 PCR and the conventional RT-PCR with extraction. Method: To get an accurate view of how an omission of RNA extraction step would perform in a real-world setting, a comparative study was performed using TATA MD CHECK RT-PCR DIRECT (Direct PCR) and LabGun Genomics for Conventional RT-PCR method. Result: From this study, direct RT-PCR correctly identified 92.3% of samples (n = 50) identified positive for SARS-CoV-2 RNA by conventional RT-PCR featuring an RNA extraction. Conclusion: Direct methods may represent a reasonable alternative to meet higher testing demands with low turnaround time as reverse transcription PCR includes traditionally time-consuming RNA extraction and purification procedures.

Attitude, Behavior, and Practices of Infection Control (Hand Washing, Social Distancing and Wearing Mask) among Communities During COVID-19 Outbreak in Areas, (Orangi, Baldia, Movach, Site, Garden, Nazimabad, Qayyumabad) of Karachi, Pakistan

Background Novel corona virus infectious disease covid-19 was first time reported in Wuhan city of China at the end of December 2019.[1] Which proliferated rapidly in China and then around the globe in 209 countries of USA, Europe, Australia, and Asia as well as Pakistan. The death toll around the world has been reached to more than 42 million and 2 billion have been affected so far,[3] in Pakistan the death toll reached to 23 thousand and affected population reached to 10 million and still numbers increasing rapidly.[5] Government taken Various measures in Pakistan for the control of covid-19. Despite of having insufficient funds Pakistan also taken accurate quantify like planned special hospitals, laboratories for testing, isolation facilities, mindfulness drive and lock down to minimize spread virus. Despite the government strict policy towards COVID-19 there are many people who are unable to follow the measures which add into the rapid spread of virus. the aim of the study is to assess the attitude, behavior, and practice among the resident of Karachi specifically those who are residing in SITE area, Orangi Town, Baldia Town, Movach Goth, Nazimabad, Garden, Qayyumabad and Gulshan-e-Iqbal to know the public response towards following SOPs.  Method A self-administered questionnaire was designed, based on determined attitude, behavior, and practices among the resident of Karachi during COVID-19 outbreak. Questionnaire were prepared at google form and accessible online for the participants. The questionnaire was processed to the residents of Karachi, between the duration from 12, June to 10, July 2021. The collected data was analyzed with help of SPSS version 26.0 (IBM) to identify the attitude behavior and practices of people during COVID-19 outbreak. The responses were analyzed based on age, gender, level of education, and income, to identify statistical correlation by utilizing chi square test.  Results The study included 318 participants, out of which 193(61%) males and 125(39%) were female. The majority (291;92%) of the participant was familiar with the covid 19, (94%; 299) of the participant were concerned about the health of their families, (95%;303) agreed that self- care and protection can reduce the possibility to get infected by COVID-19 infection, a vast majority (98%; 313) participants were following cough etiquettes.  Conclusion All of the study participants were from Karachi and they have reasonably good attitude, behavior and practices towards COVID-19 precautions, but still there must be given further awareness to cope with the social and psychological impact of the COVID-19 on public health, and also awareness session should be taken into account to reduce the spread of the infection COVID-19.

A Study on the Influence Mechanisms of Neighborhood Vitality and the Characteristics of Spatial and Temporal Differentiation in the Urban Fringe Areas of Wuhan City

Achieving effective integration of urban–rural relationships and promoting the flow of resources between urban and rural areas in megacities are a key priority in the development of China’s new urbanization efforts. As a transitional zone between urban and rural areas, the urban fringe is the frontier of urban–rural integration. The specific research object of this paper is the urban fringe areas of Wuhan City. This paper quantifies the neighborhood vitality of the fringe areas by the short-stay visitors in the fringe areas and selects the 5D elements of the built environment and social media data from multiple sources to construct the indicator system assessing the neighborhood vitality of the urban fringe areas. This paper analyzes the spatial distribution characteristics of neighborhood vitality and its influencing factors in urban fringe areas and investigates the connection between neighborhood vitality and its influencing factors through the application of the multi-scale geographically weighted regression (MGWR) model. Based on the regression results, relevant planning recommendations are made on how to enhance the vitality of neighborhoods in urban fringe areas. The results show that the index system constructed by “5D” elements of built environment and social media data can well explain the spatial distribution of neighborhood vitality in urban fringe areas. Among the influencing factors, the absolute value of the correlation coefficient of network exposure is the largest, followed by road density and functional density. Thanks to the different bandwidths given by MGWR to the influencing factors, the global influencing factors are only two indicators—development intensity and functional mixing degree—while the other influencing factors are all local, and the influence degree of different regions is different, so it is necessary to analyze and put forward different planning suggestions accordingly.

The Effects of Air Quality and the Impact of Climate Conditions on the First COVID-19 Wave in Wuhan and Four European Metropolitan Regions

This paper investigates the impact of air quality and climate variability during the first wave of COVID-19 associated with accelerated transmission and lethality in Wuhan in China and four European metropolises (Milan, Madrid, London, and Bucharest). For the period 1 January–15 June 2020, including the COVID-19 pre-lockdown, lockdown, and beyond periods, this study used a synergy of in situ and derived satellite time-series data analyses, investigating the daily average inhalable gaseous pollutants ozone (O3), nitrogen dioxide (NO2), and particulate matter in two size fractions (PM2.5 and PM10) together with the Air Quality Index (AQI), total Aerosol Optical Depth (AOD) at 550 nm, and climate variables (air temperature at 2 m height, relative humidity, wind speed, and Planetary Boundary Layer height). Applied statistical methods and cross-correlation tests involving multiple datasets of the main air pollutants (inhalable PM2.5 and PM10 and NO2), AQI, and aerosol loading AOD revealed a direct positive correlation with the spread and severity of COVID-19. Like in other cities worldwide, during the first-wave COVID-19 lockdown, due to the implemented restrictions on human-related emissions, there was a significant decrease in most air pollutant concentrations (PM2.5, PM10, and NO2), AQI, and AOD but a high increase in ground-level O3 in all selected metropolises. Also, this study found negative correlations of daily new COVID-19 cases (DNCs) with surface ozone level, air temperature at 2 m height, Planetary Boundary PBL heights, and wind speed intensity and positive correlations with relative humidity. The findings highlight the differential impacts of pandemic lockdowns on air quality in the investigated metropolises.

Wetland Landscape Dynamics and Multi-Functional Assessment of Wuhan City, China

Under the dual pressures of rapid urbanization and intensifying global climate change, China has proposed governance policies aimed at promoting ecological urban construction. Wetland landscapes play a key role in sustaining human and social well-being. As a significant city in the middle reaches of the Yangtze River, Wuhan’s wetland resources play an irreplaceable role in maintaining the regional ecological balance and promoting sustainable economic and social development. However, urbanization poses a severe challenge to the ecological service functions of wetlands. Consequently, in this study, we analyzed the spatial–temporal evolution patterns of the sub-functional systems of carbon sequestration, biodiversity conservation, water yield, and water purification in five wetland types in Wuhan City from 2000 to 2020 by using the CASA model and InVEST model. Then, a wetland multi-functional assessment framework was constructed to quantify the comprehensive multi-function score. It is imperative to unravel the underlying mechanisms driving the changes in wetland functions and to explore the equilibrium point between wetland conservation and urban sustainable development. Our results show that the wetland area of Wuhan City decreased from 5077.33 km2 in 2000 to 4696.60 km2 in 2020, and the wetland multi-functions exhibited significant spatial heterogeneity from 2000 to 2020. Wetland carbon sequestration increased from 0.94 Tg in 2000 to 1.11 Tg in 2020. The wetland habitat quality declined from 0.13 in 2000 to 0.11 in 2020. The water production of the wetlands increased from 5.43 × 109 t in 2000 to 22.59 × 109 t in 2020. The wetland N loss decreased from 55,850.58 t in 2000 to 49,209.93 t in 2020. The highest multi-function score was in paddy fields, which increased from 0.41 ± 0.12 to 0.51 ± 0.12, followed by tidal flats, which increased from 0.39 ± 0.14 to 0.50 ± 0.16, and the lowest was rivers, which also increased from 0.33 ± 0.12 to 0.41 ± 0.14. The multi-function score was closely related to the wetland type and urban development direction over the past two decades, and it was negatively correlated with production and living density, providing new ideas for wetland ecological protection and construction in Wuhan City.

Integrating street-view imagery and points of interest for refining population spatialization: A case study in Wuhan City

Fine-scale population spatialization is the frontier of geosciences, it is essential for sustainable urban planning and effective resource allocation. Various approaches have been proposed to enhance population estimation accuracy using multi-source geospatial data. However, the approaches based on remote sensing data usually suffer from the problem of spatial homogeneity, while the social-sensing-based approach such as point of interest (POI) data cannot distinguish the population distribution around POIs with the same category but different scales. Thus, this study proposes a novel method that incorporates street view imagery (SVI) with POI, to enrich the semantic landscape of street-level objects and provide a visual representation of spatial heterogeneity within an urban environment. Specifically, we extract POI and SVI features at grid-, street-, and community-level, respectively, and then select modelling features based on cross-scale consistency analysis with population. After that, grid-level SVI features are adjusted by community-level SVI features to alleviate its sparsity and transiency. Finally, we train random forest (RF) at the street-level and estimate grid-level population weight for population allocation. Experiments in Wuhan City at a grid size of 100 × 100m show that our method yields higher accuracy compared to WorldPop, GPW datasets, Ye's method, and heterogeneous population attraction of POI modelling (HPA-POI), demonstrating its effectiveness in fine-scale population spatialization.

Optimalisasi Kandungan Al-Qur’an Dalam Menghadapi Wabah Penyakit

This article is the result of research based on the current reality regarding the handling of disease outbreaks, and linking it to the verses of the Qur'an. In the Qur'an, disease outbreaks are mentioned several times, which shows the potential for science that can be explored to be applied in the present era. Since early 2019, the world has been hit by a major outbreak caused by a small creature called a virus. Coronavirus Disease (COVID-19) has become a major threat that has an impact on life without discrimination; anyone is at risk of contracting this infectious disease. The COVID-19 outbreak was first detected in Wuhan City, China, at the end of 2019 and has spread to almost 200 countries around the world, including Indonesia. The Qur'an is a source of knowledge that contains various aspects of life, such as history, health, and exemplary behavior. Methods for dealing with various problems can also be taken from the information contained in the Qur'an. Therefore, as Muslims, we have an obligation to explore and understand how the knowledge contained in the Qur'an can be implemented in the current context.

Epidemiological study of human papillomavirus infection in 105,679 women in Wuhan, China

BackgroundQuality assessment of the prevalence and distribution of human papillomavirus (HPV) genotypes could support additional targeted HPV vaccinations. However, the characteristics of HPV infection in Wuhan city are limited in the past decade. We aimed to assess the epidemiology of HPV infection among women and provide a reference for the prevention and treatment of cervical cancer in this region.MethodsA retrospective study employing 105,679 women attending Wuhan Medical and Health Center for Women and Children for cervical cancer screening from January 2015 to December 2022 was conducted. The HPV genotype was detected by polymerase chain reaction (PCR) and diversion hybridization. The overall incidence and age-specific type distribution of HPV infection and the relationship between HPV infection and cervical cytology were analyzed.ResultsThe overall HPV infection rate was 16.87% in Wuhan city, and the prevalence rates of high-risk, low-risk and mixed high- and low-risk HPV infections were 13.64%, 1.77% and 1.46%, respectively. The five most prevalent genotypes were HPV52 (4.24%), HPV58 (2.42%), HPV16 (2.34%), HPV53 (1.87%), and HPV39 (1.66%). The prevalence of HPV in women exhibited a “two-peak” pattern, the peaks of which were observed in the < 21 years group (37.4%) and the 61–65 years group (41.72%). Logistic regression analysis revealed no significant difference in the rate of high-grade lesion positivity between single and multiple high-risk HPV infections. Among patients with a high-grade squamous intraepithelial lesion+ (HSIL+) ThinPrep cytologic test (TCT) diagnosis, HPV58 was the most common type, followed by HPV52, HPV16, HPV39 and HPV53.ConclusionsHPV types 52, 58, 16, 53, and 39 were the most common types in the general female population in Wuhan, and the prevalence of HPV infection varied among different age groups. This study provides a comprehensive overview of the epidemiological characteristics of HPV infection in women, which could support the development of targeted prevention and control strategies for cervical cancer in the region.

Delineating Ecological Functional Zones and Grades for Multi-Scale Ecosystem Management

Integrating ecosystem services (ESs) to delineate ecological functional zones (EFZs) is fundamental in terrestrial spatial planning and ecosystem management. However, existing studies have largely overlooked the refinement of EFZs at local scales, which hinders targeted and multi-scale ecosystem management. This study introduced a “two-step refinement zoning method” to address this gap, first using a self-organizing feature mapping method to delineate EFZs at a township scale, and then applying a hotspot overlay analysis to refine the resulting EFZs by designating them with different grades at the village scale. The proposed method was applied in Wuhan City, dividing it into five types of EFZs with different ES combinations and land use compositions. Furthermore, 5.23% of villages were identified as level I areas of EFZs, serving as advantageous areas of dominant ESs in the study area. On this basis, diversified management strategies and conservation priorities were proposed. This study provides a theoretical and methodological reference for terrestrial spatial planning and sustainable ecosystem management.

Preface

2024 4th International Conference on Fluid and Chemical Engineering (ICFCE 2024) has been successfully held on July 26-27, 2024, in Wuhan China as a virtual event. Organized by Hubei Zhongke Institute of Geology and Environment Technology, ICFCE 2024 intends to invite worldwide famous scientists, experts, scholars, and researchers for academic presentations. ICFCE 2024 proceeding is a collection of outstanding submissions in the field of biofluid mechanics, chemically reacting fluids and combustion, computational fluid dynamics (CFD), experimental fluid mechanics, flow through porous media, fluid–solid interactions (FSI), geophysical fluid dynamics, granular/suspension flows, heat and mass transfer, hydrodynamics, physical, theoretical and computational chemistry, chemical engineering fundamentals, chemical reaction engineering, chemical engineering equipment design and process design, thermodynamics, catalysis &amp; reaction engineering, particulate systems, crystallization, etc. Around 65 articles were selected from 146 submissions after peer-review, and authors and guests participated in ICFCE 2024 with keynote speeches, oral presentations and posters, promoting the communication among researchers and experts from institutes and universities, including University of Sharjah, The University of Manchester, Harbin Engineering University, China University of Petroleum (East China), Shanghai Maritime University, Jiangxi University of Science and Technology, Nagoya University, Marine Design &amp; Research Institute of China, Tianjin Transportation Technical College, Okayama University, etc. Cordial gratitude is delivered to Technical Program Committee of ICFCE 2024 for the professional work on guarantying the high standard of conference as well as the proceedings. We believe the proceedings will enhance the exchange of ideas and state-of-art knowledge on Fluid and Chemical Engineering. Finally, we thank all the staff members at IOP Publishing for their valuable editorial support. Professor Omid Mahian Xian Jiaotong University, China Associate Professor Sébastien Déon University of Bourgogne-Franche-Comté, France List of Technical Committee is available in the pdf

Matching analysis between the heating/cooling capacity of PVT heat pumps and the heating/cooling demand of residential buildings across various regions in China

PVT-HP (Photovoltaic-Thermal Heat Pump) is a novel type of energy saving technology. Existing researches on PVT-HP technology focuses only on its operating performance under some specific conditions, ignoring the matching of its energy supply capacity with the energy demand of buildings, which is very important for its engineering design and application. In this paper, the matching relationship between the heating/cooling capacity of the PVT-HP system and the heating/cooling demand of residential buildings in major cities of China has been analyzed. To achieve this goal, a novel prediction model used to calculate the heating/cooling performance of the PVT-HP system has been proposed. And the daily heating guarantee rate and daily cooling guarantee rate have been put forward to evaluate the matching relationship. Based on the evaluation indexes, the applicable matching relationship between the installed capacity of the PVT-HP system and the heating/cooling area of residential buildings has been analyzed. The result of case study shows that for the selected cities of Shenyang, Beijing and Wuhan, the heating/cooling area of residential building for PVT-HP system with installed capacity of 1hp should not exceed 17m2, 31m2 and 25m2, respectively. Further matching analysis of major cities in China shows that the PVT-HP system is more suitable for application in hot summer and cold winter zones of China, in where the suggested heating/cooling area for the PVT-HP system with installed capacity of one horse power is within the range of 30m2 to 37m2.

Vaccination subsidy allocation under budget constraints considering the human interpersonal contact pattern and vaccine protection effect in epidemics

Vaccination subsidy is one of the most important measures to increase the willingness of people to be vaccinated for epidemic prevention and control. Given the budget constraint of vaccination subsidy and the different roles of various age groups population in the epidemic transmission process, a novel approach is proposed to optimize the utilization of the limited vaccination subsidy budget. First, an age-structured SIR model that integrates the human interpersonal contact pattern and vaccine protection effect is developed to simulate the epidemic trend under a certain vaccination state. Then, a decision model is constructed to determine the optimal vaccination subsidy allocation scheme for various age groups based on the age-structured SIR model. A case study of Wuhan City is used to verify the decision approach, and a series of sensitivity analyses are conducted. The result shows that the peak time of an epidemic is positively related to the total treatment cost for all the infections, and more subsidies should be allocated to the populations with higher interpersonal contact frequencies for epidemic prevention and control.

YOLO-V4 Based Real-Time Face Mask Detection via Unmanned Aerial Vehicle

COVID-19, which started in Wuhan city of China's Hubei province and then affected the whole world, continues to spread despite the measures taken. One of the most important of these measures is to use a mask. In some countries, while wearing a mask is mandatory in crowded environments, it is just as difficult to control it. Failure to detect individuals violating the mask causes the virus to spread, resulting in an increase in the number of cases and an increase in the number of deaths. Therefore, detecting the mask and taking action against it is an extremely important issue. In this study, in addition to making mask detection easily and quickly, mask detection is made by using unmanned aerial vehicles (UAVs) using images taken from different angles and different heights. For mask detection from UAV images, training and validation processes were applied using the YOLO-v4 algorithm on a public dataset containing 1510 masked and unmasked human face images. As a result of the training on this dataset, mean-average precision (mAP) was achieved with a success rate of 92.06%. Then, real-time mask detection was performed on the images taken with the DJI Ryze Tello quadcopter using the trained network. The results showed that the UAV is applicable in crowded environments required for autonomous mask detection and gives successful results.

Dynamic simulation of street-level carbon emissions in megacities: A case study of Wuhan City, China (2015–2030)

Dynamic simulation of carbon emissions (CE) in megacities is crucial for regional carbon reduction management, however, limited simulation accuracy hinders its application in carbon reduction policies. An integrated modeling framework was developed based on high-resolution multi-source data to analyze the street-level carbon emissions in Wuhan from 2015 to 2030. First, we conducted principal components analysis on the 5 driving factors of carbon emissions (including point of interests, electricity consumption, gross domestic product, population, and nighttime light) to delineate single carbon emission character region (CECR). Then, a machine learning method was used to simulating CE and explaining the contributions of different CECRs. Multi-scenarios CE accountings also were conducted with CECR simulations and an improved cellular automata model. Results shows that: (1) CE in Wuhan showed strong aggregation during the historical period. The five CECRs formed a near-concentric circle. The changes of CECR reflected the enhancement of human activity. (2) CE gradually shifted from the central urban areas to the surrounding regions during the scenario period, showing significant spatial spillover effects. Administrative districts with lower CE density exhibited greater scenario variation in total carbon emissions, indicating a higher potential for carbon reductions. (3) The total CE of Wuhan (148.11 Mt) in 2030 is projected to increase by 42.6 % compared to 2015 in the baseline scenario, representing 105 % of the low scenario and 91 % of the high scenario. The growth rate of total CE in Wuhan significantly slows down (<1 %) under all scenarios. The high-resolution dynamic simulation of CE will provide an important scientific basis for low-carbon city management in China.

Assessment of Urban Environmental Quality by Socioeconomic and Environmental Variables Using Open‐Source Datasets

ABSTRACTIn this era of rapid development, environmental quality is an essential aspect of sustainable development. A healthy urban environment supports, regulates, and provides livable conditions. In urban areas, environmental quality is considerably affected by socioeconomic factors such as population expansion and economic development. For decision‐making, it is also significant for stakeholders and policymakers to understand the impact of urban expansion on environmental quality. While previous studies have examined urban environmental quality, they often focused on single cities or limited environmental parameters. This research addresses these limitations by conducting a comparative analysis of two major Asian cities with similar demographic features, utilizing a comprehensive set of socioeconomic and environmental variables. Our innovative approach combines open‐source datasets with advanced remote sensing techniques to provide a more holistic assessment of urban environmental quality over two decades. We analyzed urban environmental quality for last two decades with the selected urban environmental quality parameters: surface greenness, surface moisture, and land surface temperature. Lahore (Pakistan) and Wuhan (China) cities were selected for having approximately same demographic features. Correlation matrix has been used to assess the relationship between these environmental variables and social‐economic variables: urban expansion and carbon emission. Correlation coefficient indicated that urban expansion correlates negatively with surface greenness and surface moisture for both Lahore (−0.67 and −0.71) and Wuhan District (−0.5 and −0.75), respectively, while it had a positive relation with land surface temperature: 0.65 and 0.57 for Lahore and Wuhan District, respectively. These effects are more prominent within 10 km distance from the city center, where a substantial urban expansion is observed during the time window.