Characteristics Of Region Research Articles

Alzheimer's disease diagnosis by applying Shannon entropy to Ricci flow-based surface indexing and extreme gradient boosting

Geometric surface models are extensively utilized in brain imaging to analyze and compare three-dimensional anatomical shapes. Due to the intricate nature of the brain surface, rather than examining the entire cortical surface, we are introducing a new set of signatures focused on characteristics of the hippocampal region, which is linked to aspects of Alzheimer's disease. Our approach focuses on Ricci flow as a conformal parameterization method, permitting us to calculate the conformal factor and mean curvature as conformal surface representations to identify distinct regions within a three-dimensional mesh. For the first time for such settings, we propose a simple while elegant formulation by employing the well-established concept of Shannon entropy on these well-known features. This compact while rich feature formulation turns out to lead to an efficient local surface encoding. We are validating its effectiveness through a series of preliminary experiments on 3D MRI data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), with the aim of diagnosing Alzheimer's disease. The feature vectors generated and inputted into the XGBoost classifier demonstrate a remarkable level of accuracy, further emphasizing their potential as a valuable additional measure for surface-based cortical morphometry in Alzheimer's disease research.

Effectiveness of spatial measurement model based on SDM-STIRPAT in measuring carbon emissions from transportation facilities

To gain a deeper understanding of the carbon emission mechanism from transportation facilities, all system elements affecting carbon emissions from regional transportation facilities are identified and analyzed according to panel data from 30 regions in China. A spatial econometric model for carbon emissions from transportation facilities is constructed using the Spatial Dolbin model from 2004 to 2022 as the research period. From the results, the carbon dioxide emissions from transportation facilities added from 318 million tons in 2004 to 752 million tons in 2022, with an average annual growth rate of 4.9%. The global spatial auto-correlation coefficient was significant at the 5%, with an obvious spatial correlation between carbon dioxide emissions within a geographical range. In addition, through stability testing, the model showed high stability in both spatial lag testing and spatial error testing, demonstrating strong ability to interpret data. The research shows that the carbon emission is affected by independent variables, including population, economy, technology, and transportation, and exhibit significant spatial distribution characteristics in different regions and years, providing a basis for policy formulation and carbon emission management.

Radiomics in oncology: A mini-review of principles, applications and challenges

Radiomics, a quantitative approach to medical imaging, employs computational methods to extract features from the images, revealing hidden characteristics of specific regions. This emerging field leverages advanced techniques to analyze a spectrum of features from modalities, including computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET) scans, aiming to decode tissue characteristics, disease progression, and treatment responses. The radiomics workflow integrates image acquisition, segmentation, feature selection, and data integration, utilizing advanced techniques such as deep learning, machine learning, and data mining. Radiomics demonstrates considerable potential in cancer detection and management, exhibiting high sensitivity and specificity in distinguishing between benign and malignant tumors and predicting outcomes. However, challenges such as imaging protocol variability, overfitting, and standardization requirements impede its broad clinical adoption. Innovations in multi-modal radiomics, deep learning, and genomics integration strive to mitigate these constraints. This review elucidates radiomics’ capabilities, current applications, benefits, challenges, and future directions in oncology.

Оценка перспектив вовлечения территорий упраздненных поселений в туристско-рекреационное хозяйство (на примере Республики Карелия)

This article emphasizes the relevance of exploring import substitution strategies in the Russian tourism and recreational market. Special attention is given to the need to satisfy the demand for unique travel experiences. As it is necessary to integrate unused territories into the economy, the article proposes to increase the involvement of abandoned settlements in the tourism and recreational sector. To identify the most promising villages, a goal was set to develop and test a scoring scale based on the system of indicators proposed by the authors. The Republic of Karelia was chosen as the research site. Criteria were identified to determine the attractiveness and feasibility of including abandoned settlements in tour itineraries. Based on these criteria, villages such as Keret, Loushki, Pulozero, Pegrema, Kashalilamba, Lagilamba, Kharitonova Gora, Gafostrof Rebolskoy, and Kolodozero were selected. Using the assessment system presented in the article, these villages were assigned points, and the integral indicator was calculated. The results show that Keret, Gafostrof Rebolskoy, Kashalilamba, Kakkarovo, and Pegrema are the most promising ones, which is confirmed by practice: Keret, Gafostrof Rebolskoy, and Pegrema have already been included in tour itineraries. Future research prospects involve improving the presented methodology, as it requires adaptation to factor in individual socio-economic and natural characteristics of other regions. It is also possible to expand the list of factors influencing the attractiveness of abandoned settlements. Theoretical developments in this direction can serve as a basis for the successful integration of abandoned villages in the tourism and recreational market in the Russian North.

The functional and structural alterations in brain regions related to the fear network model in panic disorder: A resting-state fMRI and T1-weighted imaging study

Abnormal functional connectivity (FC) within the fear network model (FNM) has been identified in panic disorder (PD) patients, but the specific local structural and functional properties, as well as effective connectivity (EC), remain poorly understood in PD. The purpose of this study was to investigate the structural and functional patterns of the FNM in PD. Magnetic resonance imaging data were collected from 33 PD patients and 35 healthy controls (HCs). Gray matter volume (GMV), degree centrality (DC), regional homogeneity (ReHo), and amplitude of low-frequency fluctuation (ALFF) were used to identify the structural and functional characteristics of brain regions within the FNM in PD. Subsequently, FC and EC of abnormal regions, based on local structural and functional features, and their correlation with clinical features were further examined. PD patients exhibited preserved GMV, ReHo, and ALFF in the brain regions of the FNM compared with HCs. However, increased DC in the bilateral amygdala was observed in PD patients. The amygdala and its subnuclei exhibited altered EC with rolandic operculum, insula, medial superior frontal gyrus, supramarginal gyrus, opercular part of inferior frontal gyrus, and superior temporal gyrus. Additionally, Hamilton Anxiety Scale score was positively correlated with EC from left lateral nuclei (dorsal portion) of amygdala to right rolandic operculum and left superior temporal gyrus. Our findings revealed a reorganized functional network in PD involving brain regions regulating exteroceptive-interoceptive signals, mood, and somatic symptoms. These results enhance our understanding of the neurobiological underpinnings of PD, suggesting potential biomarkers for diagnosis and targets for therapeutic intervention.

Uncertainty quantification of turbine endwall aero-thermal performance under combustor-turbine interface louver coolant and cavity

The uncertainty characteristics have a significant influence on turbine cooling performance and its reliability, especially for the combustor-turbine interface region which faces more complicated flow interactions. Previous researches under the certainty framework are not able to reflect the realistic cooling characteristics of the interface region under real operation circumstances. Considering the random fluctuations of the major structure and flow parameters, uncertainty quantification of turbine endwall cooling performance under realistic combustor-turbine interface conditions is conducted in this paper using the polynomial chaos expansion method. The mix characteristic of combustor louver coolant and interface cavity leakage in the turbine endwall region is investigated, and the influences of parameter uncertainties on endwall cooling, vane phantom cooling, and cascade aerodynamic characteristics are analyzed. The results indicate that the uncertainties at the combustor-turbine interface largely influence the endwall cooling by modifying the strength and position of the secondary flows. Under the random fluctuations of interface geometry parameters, the local mean value of endwall cooling effectiveness can reach up to 0.25, and the standard deviation of endwall cooling effectiveness can reach 0.1. The geometrical parameters of interface width and misalignment height are the decisive factors for endwall cooling uncertainty. The random fluctuations of interface width and misalignment height separately cause great cooling effectiveness uncertainties on the pressure side endwall and suction side hot ring. The uncertainties in mainstream and structure parameters exhibit a reduced propensity to propagate onto vane phantom cooling. The decisive factors for vane phantom cooling uncertainty are interface width and misalignment height, and the major influenced area is the vane middle part. Four mainstream and structure parameters all make great contributions to the aerodynamic uncertainty at the strong secondary flow region and vane wake flow region. This paper can provide a theoretical basis for the design of combustor-turbine interface cooling structures to accommodate the actual turbine operation uncertainty conditions.

Assessing greywater characteristics in the sahel region and perception of the local population on its reuse in agriculture

Research on greywater reuse in water stressed areas is in full swing. However, the perception of greywater reuse is one of the least researched areas in West Africa, particularly in Sahelian countries. This study aimed to fills a significant gap in the existing literature, which has largely ignored the specific socio-demographic contexts of developing countries in the Sahelian regions. The study involved in-depth interviews with 240 rural households and the collection of 40 greywater samples in four locations for laboratory analysis. The survey focused on greywater management and household perceptions of greywater reuse in agriculture. The analyses focused on determining the physico-chemical and microbiological parameters of greywater collected from households. The results showed that over 80 % of households discharged greywater into the natural environment without prior treatment. The majority of respondents were aware that poor greywater management poses a health risk. The results also showed an association between locality, gender, education level and perceptions of poor grey water management. Respondents were willing to accept the reuse of greywater in agriculture, to consume irrigated vegetables and to install a greywater treatment system. The quality analysis showed that the greywater was not in compliance with the legal discharge limits. This study highlights that in order to promote sustainable greywater management practices within households, it is important to design effective greywater treatment systems that meet the needs of the target population. Awareness campaigns, education and training programmes on wastewater management could also be established.

Local thermal resistance delamination method for precise analysis and optimization of heat transfer processes

Excessive carbon emissions are one of the global challenges. Promoting the optimization of high-efficiency heat transfer systems and improving the analysis and evaluation methods of heat exchangers is one of the effective ways to save energy and reduce carbon emissions. The traditional thermal resistance analysis method treats the fluid domain as a uniform whole, which makes it difficult to regulate the heat transfer characteristics in local regions, especially in the near-wall region. To address this problem, this paper obtained the thermal resistance mathematical equation for different regions in the flow field by magnitude analysis. The thermal resistance delamination method for dividing the thermal resistance field is proposed from the channel flow, and the conduction, mixing and advection zones in the flow field are identified. The delamination factor (α) is defined to determine the boundaries of thermal resistance zones. The α values which meet the delamination factor independence under forced convection and natural convection conditions are investigated. By studying the mechanism of the thermal resistance in conduction zone of the enhanced heat transfer structure, the critical value of fin height to achieve maximum enhancement efficiency is determined. The thermal resistance delamination facilitates a comprehensive analysis of heat transfer processes and structure optimization in the near-wall region.

Прогнозирование характеристик половодья 2024 года на реках Ишим, Тобол и Урал

The Hydrometeorological Center of Russia has developed a system of methods for forecasting spring flood characteristics, which was implemented for eight stations on the Ishim, Tobol, and Ural rivers in 2024. Specific features of the methods are the simplicity of their obtaining and implementation for a particular river reach and a possibility of the fast correction of forecasts as the current information is available. The peak water level at the station was predicted based on its dependence on the peak water level at the upstream station. The date of the flood peak was predicted with account of the data of the peak at the upstream station and probable values of the travel time from the upstream gauge to the predicted downstream one. The date of the water level drop to the level of a severe event was forecasted taking into account the height and date of the flood peak using the calculated recession curve obtained by the statistical analysis of flood recessions in the previous years. The date of the water level drop to the level of an adverse event was predicted by extrapolating the flood recession observed during 10–15 days after the flood peak. The mean forecast lead time is 9 days. The forecasts were issued in a deterministic and probabilistic form and gave quite satisfactory results, which were used in the organization and implementation of measures to protect the population and economic facilities from the floods observed in 2024. The efficiency of the developed methods allows recommending them for use in predicting flood characteristics in various regions of Russia.

Tieboutian clubs revisited

This paper examines the evolution of Tieboutian clubs over time and across metropolitan regions. We address this topic by examining a large set of socioeconomic characteristics of metropolitan regions to assess empirically whether and how those member attributes may figure into a Tiebout sorting process. The method entails factor analysis to reduce an initial set of forty-nine variables to a much smaller number of factors that represent groups of intercorrelated variables. An analysis of variance is then undertaken on the corresponding factor scores to assess whether census tracts within municipalities are more alike than those between municipalities. We do this for the Los Angeles metropolitan region using census data from 1970, 1990 and 2020, and we repeat the process for the twenty largest metropolitan regions (core-based statistical areas) in the USA for 2020. Several key results emerge from this analysis. While in most cases seven or eight factors emerge repeatedly, four are most persistent and ubiquitous; these pertain to economic class, race, age cohort and immigration status. These are, in effect, the most enduring fundamental aspects of the socioeconomic landscape in metropolitan regions in the USA. The final question addressed by our work links back to the original motivation, which is to assess the role of municipalities in the formation of these clubs. We do so for the twenty largest metropolitan regions in the USA. The results from our analyses of variance are compelling. With very few exceptions we find that census tracts with similar club characteristics have a strong tendency to be co-located within the same municipalities. This strong result holds regardless of which metropolitan region we examined, or which decade. This affirms that municipalities are indeed Tieboutian clubs.

Evaluating the Effects of the ‘Pilot Zone’ Policy on China’s Agricultural Green Development

Green agriculture is a new sustainable agricultural development model that coordinates agricultural development with the environment which has been vigorously promoted in China in recent years. With the support of national policies, China has set up 130 pilot zones for green agricultural development. Taking these pilot zones as quasi-natural experimental areas, the difference-in-differences (DID) method and agricultural green total factor productivity are used to evaluate the effect of the policy in the pilot zones. The findings indicate that the pilot zones notably diminish non-point source agricultural pollution without affecting agricultural added value and improve agricultural green total factor productivity by improving technical efficiency. Heterogeneity analysis shows that the effectiveness of this policy varies regionally. The eastern region of China, the main agricultural producing areas, and the regions with higher initial environmental pollution levels and abundant educational resources experience more pronounced benefits. Based on the regional characteristics of different regions, this study considers the factors such as agricultural resource endowment and development basis and explores how the policy effects of agricultural green development in different regions, which has certain guiding significance for the continuous improvement in China’s agricultural green development policies.

Regional heterogeneity of sustainable wastewater sludge management in China

In various regions of China, the sludge characteristics, available sludge treatment and disposal routes, and economic and environmental concerns exhibit significant variations. This makes it challenging for regions to select appropriate technologies for sustainable sludge management. This study proposed a universal framework that integrates carbon emissions, economic cost, and environmental risk potential to assess sustainability of diverse sludge treatment and disposal routes in different regions of China. An up-to-date database of sludge characteristics in different regions of China has also been created. Depending on sludge characteristics, co-incineration in coal-fired plants or cement kilns and thermal hydrolysis-anaerobic digestion routes demonstrate outstanding sustainability for most regions in China. Moreover, the current carbon trading price in China is low and does not significantly influence the technical selection. The created sludge characteristics database and the sustainability assessment framework could help sludge managers make better in process selection, technological improvement, and future policy formulation.

Why does the courtyard spaces of same ethnic group present diverse characteristics in different regions： evidence based on ENVI-met climate modeling

The rapid urbanization in developing countries like China has led to a heightened challenge of climate degradation and the erosion of traditional ecological knowledge worldwide. The widespread distribution of Yi traditional settlements across various climatic zones in southwest China offers a unique opportunity to investigate the diverse courtyard spaces within the same ethnic group, influenced by distinct climatic environments. Through comprehensive field investigation, meticulous field measurement, and rigorous ENVI-met simulation, this study conducts a comparative analysis of microclimates in Yi typical courtyards across diverse climatic conditions. The results show that: 1) Courtyard plays a pivotal role in regulating microclimate dynamics across cold, temperate, and hot climatic conditions. 2) The microclimate regulation mechanism of a courtyard varies across different climatic environments. 3) The climate regulation efficacy of courtyards will diminish as the climate environment undergoes changes. 4) The aspect ratio (AR) is a key spatial factor which plays a crucial role in determining the efficiency of regulating courtyard microclimate. Concluded this study, the research findings not only provide valuable guidance for the protection planning and design of traditional Yi settlements in southwest China, but also offer significant insights for courtyard construction in other regions with extreme climates worldwide. In addition, this study constructs a new research framework for traditional settlements, which is of great significance for scientifically and accurately identifying the spatial value of traditional settlements and improving the theoretical system of traditional settlement protection and activation.

Machine learning approach to predict flow fields induced by internal solitary waves acting on mid-water structures based on particle image velocimetry experiments

Mid-water structures (MWSs) have important applications in the ocean to minimize the effects of environmental factors in the surface ocean and to avoid the effects of high pressure on the seabed. However, their operational positions are vulnerable to internal solitary waves (ISWs), which poses a significant challenge to the safe functioning of MWSs. Consequently, there is a pressing need to explore the flow field characteristics surrounding MWSs under the action of ISWs to establish a reliable foundation for structural design. In this study, experimental investigations were conducted to analyze the flow fields induced by ISWs acting on MWSs, employing the particle image velocimetry (PIV) method. The intricate details of the flow fields around the structure were thoroughly analyzed, and the impact of the structure's submerged depth on the ISW-induced flow fields was discussed. A machine learning approach is utilized to develop an Artificial Neural Network (ANN) model aimed at predicting the flow fields of ISWs. The experimental results are compared and analyzed alongside the predicted outcomes, focusing on the anomaly region, the tail field region, and the occluded region. The results show that the presence of the structure complicates the flow characteristics in the tail flow regions, and the flow patterns are constantly changing. The characteristics of the ISW flow fields around the structure vary with the different submerged depths of the MWS. Positioning the MWS above the wave trough results in an ascending trend followed by a descending trend in the strength of the surrounding flow field with increasing submerged depth. The ANN predictions for different types of regions of the flow fields show satisfactory accuracy. The model closely matches the PIV results in predicting the extremes and positions of horizontal velocities in the tail flow fields at different stages of ISW trough propagation. The ANN model can be recommended for predicting the flow fields of ISWs acting on MWSs. This study offers comprehensive insights into the characteristics of the flow fields induced by ISWs acting on MWSs, emphasizing the valuable contribution of machine learning methods to the field of fluid dynamics.

Analysis of rare mutations associated with Thalassemia and their hematological characteristics in Chenzhou region of Hunan Province

To explore the distribution and hematological characteristics of rare thalassemia-associated mutations in Chenzhou region of Hunan Province with an aim to provide a basis for genetic counseling and effective prevention. A total of 37 370 individuals enrolled from January 2015 to December 2021 were screened by routine blood test and hemoglobin electrophoresis. The genotypes were determined with high-throughput sequencing. A total of 8 455 thalassemia mutations (including 185 rare ones) were detected, which had involved 27 mutational types. Rare type α-Thalassemia --THAI and CD31 (AGG>AAG) have the typical microcytic hypochromic hematological features, whilst SEA-HPFH, CD14 (CTG>-TG), CD37 (TGG>TAG), -90(C>T), Codon 15 (G>A), IVS-I-128 (T>G), CD86 (GCC>GC-) and Chinese Gγ+(Aγδβ)0 had typical microcytic hypochromic and β-thalassemia-associated hematological features of elevated HbA2 or HbF. In addition, the -50（G>A）heterozygotes of β-thalassemia had normal or slightly decreased MCV and MCH without an increase in HbA2. Various forms of thalassemia-associated mutations have been identified in the Chenzhou region of Hunan Province. Above finding has facilitated development of preventive and control strategies for thalassemia as well as birth health programs.

Analysis and prediction of epidemiological characteristics of tuberculosis deaths among Chinese residents from 2006 to 2021

Objective: The epidemiological characteristics of tuberculosis deaths among Chinese residents from 2006 to 2021 were analyzed, and the tuberculosis mortality rate from 2022 to 2027 was predicted to provide a reference for tuberculosis prevention and control in China. Methods: The data set of tuberculosis deaths from 2006 to 2021 was published regularly by the China CDC, and the crude mortality rate (CMR) and age-standardized mortality rates (ASMR) were calculated according to the population structure of China in 2000. The distribution characteristics of age, sex, region, and time of tuberculosis deaths were analyzed, the Joinpoint regression analysis model was used to analyze the changing trend, and the grey model was applied to predict CMR and ASMR from 2022 to 2027. Results: From 2006 to 2021, the CMR and ASMR of tuberculosis showed a downward trend among males and females, urban and rural areas, and all age groups, in a word, all the Chinese residents. Except for the age group ≥85 years old, the mortality trend was insignificant. In the eastern, central, or western regions. CMR and ASMR were significantly higher in males than in females.CMR and ASMR were significantly lower in urban areas than in rural areas. In general, active tuberculosis patients present a higher mortality rate. The CMR and ASMR in the western region were higher than those in the eastern and central regions and lower in the eastern region than in the central region, but the differences were less obvious. The ASMR of the eastern cities was lower than that of the central and western regions, and the ASMR of the central cities was higher than that of the western region from 2006 to 2009 and 2012 and lower than that of the western region in other years. The ASMR in the western countryside was higher than that in the eastern and central regions and lower in the eastern part than in the central region, but the difference was not obvious. The grey model prediction results show that the CMR (/100 000) of Chinese residents from 2022 to 2027 is 1.585, 1.471, 1.360, 1.250, 1.143, and 1.038, and the ASMR (/100 000) is 0.779, 0.653, 0.531, 0.411, 0.295 and 0.181, respectively. Conclusions: The CMR and ASMR of tuberculosis will continue to decline, and extraordinary achievements have been made in tuberculosis prevention and control in Chinese residents from 2006 to 2021 and, presumably, from 2022 to 2027. However, tuberculosis screening and treatment programs in the western region, men, the elderly population, and rural areas should be further strengthened, and targeted prevention and control measures should be formulated to reduce mortality.

Molecular epidemiology and strain diversity of circulating feline Calicivirus in Thai cats.

Feline calicivirus (FCV) is a significant viral pathogen causing upper respiratory tract and oral diseases in cats. The emergence of the virulent systemic FCV variant (VS-FCV) has raised global concern in the past decade. This study aims to explore the epidemiology, genetic characterization, and diversity of FCV strains circulating among Thai cats. Various sample types, including nasal, oral, and oropharyngeal swabs and fresh tissues, were collected from 184 cats across different regions of Thailand from 2016 to 2021. Using reverse transcription real-time polymerase chain reaction (RT-qPCR), FCV infection was investigated, with additional screening for feline herpesvirus-1 (FHV-1) by qPCR. The detection rates for FCV, FHV-1, and co-infection were 46.7, 65.8, and 31.5%, respectively. Significantly, the odds ratio (OR) revealed a strong association between the detection of a single FCV and the presence of gingivostomatitis lesions (OR: 7.15, 95% CI: 1.89-26.99, p = 0.004). In addition, FCV detection is notably less likely in vaccinated cats (OR: 0.22, 95% CI: 0.07-0.75, p = 0.015). Amino acid sequence analysis based on the VP1 major capsid protein gene of the 14 FCV-Thai (FCV-TH) strains revealed genetic diversity compared to the other 43 global strains (0 to 86.6%). Intriguingly, a vaccine-like FCV variant was detected in one cat. In summary, this study provides insights into the epidemiology and molecular characteristics of FCV diversity within the Thai cat population for the first time. The identification of unique physicochemical characteristics in the capsid hypervariable region of some FCV-TH strains challenges previous hypotheses. Therefore, further exploration of vaccine-like FCV variants is crucial for a comprehensive understanding and to improve viral prevention and control strategies.

The Impact of Different Catalysts on Heterogeneous Hydrogenation of Hydroxyl‐Terminated Polybutadiene

AbstractHydroxyl‐terminated polybutadiene (HTPB) is hydrogenated using catalytic hydrogenation with HTPB as a precursor using various catalysts. The hydrogenation is carried out using iso‐propyl alcohol (IPA) and toluene as an active solvent media. The present paper used (a) charcoal, (b) palladium supported by charcoal (Pd−C), (c) palladium supported by zirconium oxide (Pd‐ZrO2), and (d) copper chromite (CC) as catalysts for hydrogenation of HTPB to study the influence on the degree of hydrogenation with respect to each catalyst. The experimental data shows that hydrogenated HTPB (HHTPB) formation is predominantly controlled by physisorption and chemical reaction with a catalyst. Various techniques like NMR, FTIR and chemical analysis are used to characterize HTPB and HHTPB. Degree of hydrogenation of HTPB is found to be higher with copper chromite when compared to other catalysts in this work. Post‐hydrogenation, no significant change in hydroxyl value and a marginal increase in molecular weight is noticed with all catalysts. HTPB and HHTPB samples are analyzed using FTIR, 1H‐NMR, and 13C‐NMR and TG‐DSC studies, and inferences are derived with respect to the change in the olefinic region, microstructural changes, molecular weight, and thermal decomposition characteristics.

First year of COVID-19 in Brazil: Factors associated with the spread of COVID-19 in small and large cities.

To test the association between sociodemographic and social characteristics with COVID-19 cases and deaths in small and large Brazilian cities. This ecological study included COVID-19 data available in State Health Secretaries (managed by brasil.io API) and three national databases (IBGE, DATASUS and Embrapa). Temporal spread of COVID-19 in Brazil during the first year considered as outcome: a) days until 1st case in each city since 1st in the country; b) days until 1,000 cases/100,000 inhabitants since 1st case in each city; c) days until 1st death until 50 deaths/100,000 inhabitants. Covariates included geographic region, city social and environmental characteristics, housing conditions, job characteristics, socioeconomic and inequalities characteristics, and health services and coverage. The analysis were stratified by city size into small (<100,000 inhabitants) and large cities (≥100,00 inhabitants). Multiple linear regressions were performed to test associations of all covariates to adjust to potential confounders. In small cities, the first cases were reported after 82.2 days and 1,000 cases/100,000 were reported after 117.8 days, whereas in large cities these milestones were reported after 32.1 and 127.7 days, respectively. For first death, small and large cities took 121.6 and 36.0 days, respectively. However, small cities were associated with more vulnerability factors to first case arrival in 1,000 cases/100,000 inhabitants, first death and 50 deaths/100,000 inhabitants. North and Northeast regions positively associated with faster COVID-19 incidence, whereas South and Southeast were least. Social and built environment characteristics and inequalities were associated with COVID-19 cases spread and mortality incidence in Brazilian cities.

Direct numerical simulation of shock wave/boundary layer interaction controlled by steady microjet in a compression ramp

Shock wave/boundary layer interaction in a 24° turning angle of the compression ramp at Mach number 2.9 controlled by steady microjet is investigated using direct numerical simulation. Three different jet spacings which are termed as sparse, moderate and dense are considered, and the induced vortex system and shock structures are compared. A moderate jet spacing configuration is found to generate counter-rotating vortex pairs that transport high-momentum fluid towards the vicinity of wall and strengthen the boundary layer to resist separation, reducing the separation region. The dense jet spacing configuration creates a larger momentum deficit region, reducing the friction downstream of the corner. Analysis of pressure and pressure gradient reveals that dense jet spacing configuration reduces the intensity of separation shock. The impact of varying jet spacings on the turbulent kinetic energy transport mechanism is also investigated by decomposing the budget terms in the transport equation. Furthermore, the spectral characteristics of the separation region are studied using power spectral density and dynamic mode decomposition methods, revealing that moderate jet spacing configuration suppresses low-frequency fluctuations in the separation region.