Spatial inequalities in skilled birth attendance in India: a spatial-regional model approach

Background Despite a significant increase in the skilled birth assisted (SBA) deliveries in India, there are huge gaps in availing maternity care services across social gradients - particularly across states and regions. Therefore, this study applies the spatial-regression model to examine the spatial distribution of SBA across districts of India. Furthermore, the study tries to understand the spatially associated population characteristics that influence the low coverage of SBA across districts of India and its regions. Methods The study used national representative cross-sectional survey data obtained from the fourth round of National Family Health Survey, conducted in 2015-16. The effective sample size was 259,469 for the analysis. Moran’s I statistics and bivariate Local Indicator for Spatial Association maps were used to understand spatial dependence and clustering of deliveries conducted by SBA coverage in districts of India. Ordinary least square, spatial lag and spatial error models were used to examine the correlates of deliveries conducted by SBA. Results Moran’s I value for SBA among women was 0.54, which represents a high spatial auto-correlation of deliveries conducted by SBA over 640 districts of India. There were 145 hotspots for deliveries conducted by SBA among women in India, which includes almost the entire southern part of India. The spatial error model revealed that with a 10% increase in exposure to mass media in a particular district, the deliveries conducted by SBA increased significantly by 2.5%. Interestingly, also with the 10% increase in the four or more antenatal care (ANC) in a particular district, the deliveries conducted by SBA increased significantly by 2.5%. Again, if there was a 10% increase of women with first birth order in a particular district, then the deliveries conducted by SBA significantly increased by 6.1%. If the district experienced an increase of 10% household as female-headed, then the deliveries conducted by SBA significantly increased by 1.4%. Conclusion The present study highlights the important role of ANC visits, mass media exposure, education, female household headship that augment the use of an SBA for delivery. Attention should be given in promoting regular ANC visits and strengthening women’s education.

Convolutional Neural Network-based Reconstruction for Positronium Annihilation Localization

A hermetic novel detector composed of 200 Bismuth germanium oxide crystal scintillators and 393 channel silicon photomultipliers has been developed for positronium (Ps) annihilation study. This compact 4π detector is capable of simultaneously detecting γ-ray decay in all directions, enabling not only the study of visible and invisible exotic decay processes but also tumor localization in positron emission tomography for small animals. In this study, we investigate the use of a convolutional neural network (CNN) for the localization of the Ps annihilation synonymous with tumor localization. The 2-γ decay systems of the Ps annihilation from the 22Na and 18F radioactive sources are simulated using GEANT4. The simulated data sets are preprocessed by applying energy cuts. The spatial error in the XY plane from CNN is compared to that from the classical centroiding, weighted k-means algorithm. The feasibility of the CNN-based Ps an-nihilation reconstruction with tumor localization is discussed.

Backstepping sliding mode control strategy of non-contact 6-DOF Lorentz force platform

With the development of aerospace technology, more and more scientific activities are carried out in the universe. Due to the microgravity environment of space, the control of the 6-DOF platform is different from those on the earth. First, a virtual prototype model of the 6-DOF non-contact platform was built in ADAMS. The dynamics model was developed based on the Newton–Euler method. Then, the 6-DOF backstepping sliding mode controller and disturbance observer were designed in MATLAB/Simulink. Finally, by combining the virtual prototype model in ADAMS and the control system in MATLAB, the co-simulation model was proposed. According to the simulation results, the 6-DOF backstepping sliding mode controller can well complete the positioning, 3D trajectory tracking, and vibration isolation tasks of non-contact 6-DOF platform. Quantitatively, the spatial error of backstepping sliding mode controller’s 3D trajectory tracking is only 50% of the ordinary sliding mode control and it is 20% of the nonlinear propotional-derivative-integral.

High-precision modeling of CNCs’ spatial errors based on screw theory

A method for establishing machine tool’s spatial error model is put forward based on screw theory, which is different from the traditional error modeling method. By analyzing the position relationship between the ideal coordinate vector and the actual coordinate vector jointly affected by linear errors and angular errors, a single-axis screw conversion matrix error expression is brought up based on screw theory. Meanwhile, the comprehensive spatial error model of the CNC machine tool is derived by considering the influence of the workpiece motion chain and the tool motion chain on the model. Further, to compensating spatial errors of CNCs, such screw theory-based model is embedded in the error compensation system by means of integration of a few specific application examples. And in order to evaluate the compensation effects, an integrated evaluation method of quantitative spatial diagonal calculation and MATLAB simulation is proposed. Application results show that the screw theory-based spatial error model of tool has a very substantial compensation effect, which makes the position error of the machine tool decreased by about 80%.

Pemodelan Data Kemiskinan di Provinsi Jawa Barat Menggunakan Regresi Spasial Data Panel

Persentase kemiskinan di Provinsi Jawa Barat masih tergolong cukup tinggi dan masih menjadi fokus perhatian pemerintah. Faktor-faktor yang memengaruhi kemiskinan penting untuk diketahui agar pemerintah mampu membuat suatu kebijakan yang tepat untuk menekan angka kemiskinan. Oleh karena itu, pada penelitian ini, dilakukan suatu analisis untuk mengetahui faktor-faktor yang memengaruhi tingkat kemiskinan di Provinsi Jawa Barat. Analisis pada penelitian ini menggunakan metode regresi spasial data panel karena diduga pada data kemiskinan di Provinsi Jawa Barat terdapat efek spasial dan unit amatan diamati pada jangka waktu tertentu. Model yang terbentuk dari analisis ini adalah Fixed Effect Spatial Error Model karena interaksi spasial yang terbentuk pada data kemiskinan di Provinsi Jawa Barat nyata pada error. Model ini juga berhasil menjadi model terbaik dibandingkan model lainnya berdasarkan kriteria nilai R-square terbesar. Analisis data kemiskinan di Provinsi Jawa Barat menggunakan metode regresi spasial data panel memperoleh hasil bahwa usia harapan hidup, pengeluaran per kapita disesuaikan, dan rata-rata lama sekolah berpengaruh secara signifikan terhadap persentase penduduk miskin di Provinsi Jawa Barat.

Does Urbanization Increase the Risk of Emerging Infectious Diseases in China? A Spatial Econometric Analysis

The current COVID-19 pandemic has inspired more and more discussion about the relationship between urbanization and emerging infectious diseases (EID). This paper aims to examine the spatial effect of urbanization on EID incidence, such as hepatitis, syphilis and gonorrhea in China. Taking into account geographical and economic factors, the estimation results of the Spatial Error Model (SEM) show that urbanization has increased the risks of EID transmission from 2003 to 2019 in China. The spatial effects of urbanization are slightly different due to different types of infectious diseases, with a larger effect on syphilis comparing with hepatitis and gonorrhea. The regional heterogeneity test shows that the impact of urbanization on EID in eastern China is stronger than that in the Midwest especially when considering spatial correlation. Policy implications that include health must be integrated into urban planning, attaching more importance to ecological construction, improving regional joint prevention and control mechanisms, and more attention being paid to vulnerable groups. Considering the frequent occurrence of COVID-19 among cities in China, we emphasize the importance of enhancing the coordinated anti-crisis capacity of urban clusters and highlight the leading role of central cities.

Gambling Outlets Location in Urban Areas: A Case Study of Madrid

Cities are certainly a key factor in the location of gambling facilities. This paper aims to map the location of gambling outlets in urban areas and to examine potential links between neighborhoods socioeconomic and demographic characteristics and gambling supply, taking into account spatial dependencies of neighboring areas. This correlation is of interest because neighborhood characteristics may attract sellers, and because the presence of gambling sellers may cause changes in neighborhood demographics. Using detailed official data from the city of Madrid for the year 2017, three spatial econometric approaches are considered: spatial autoregressive (SAR) model, spatial error model (SEM) and spatial lag of X (explicative variables) model (SLX). Empirical analysis finds a strong correlation between neighborhoods characteristics and co-location of gambling outlets, highlighting a specific geographic patterning of distribution within more disadvantaged urban areas. This may have interesting implications for gambling stakeholders and for local governments when it comes to the introduction and/or increase of gambling availability.

Touchscreen-based finger tapping: Repeatability and configuration effects on tapping performance

Parkinson’s disease (PD) is a progressive neurodegenerative disease that affects almost 2% of the population above the age of 65. To better quantify the effects of new medications, fast and objective methods are needed. Touchscreen-based tapping tasks are simple yet effective tools for quantifying drug effects on PD-related motor symptoms, especially bradykinesia. However, there is no consensus on the optimal task set-up. The present study compares four tapping tasks in 14 healthy participants. In alternate finger tapping (AFT), tapping occurred with the index and middle finger with 2.5 cm between targets, whereas in alternate side tapping (AST) the index finger with 20 cm between targets was used. Both configurations were tested with or without the presence of a visual cue. Moreover, for each tapping task, within- and between-day repeatability and (potential) sensitivity of the calculated parameters were assessed. Visual cueing reduced tapping speed and rhythm, and improved accuracy. This effect was most pronounced for AST. On average, AST had a lower tapping speed with impaired accuracy and improved rhythm compared to AFT. Of all parameters, the total number of taps and mean spatial error had the highest repeatability and sensitivity. The findings suggest against the use of visual cueing because it is crucial that parameters can vary freely to accurately capture medication effects. The choice for AFT or AST depends on the research question, as these tasks assess different aspects of movement. These results encourage further validation of non-cued AFT and AST in PD patients.

Relationship between Urban Floating Population Distribution and Livability Environment: Evidence from Guangzhou’s Urban District, China

The livability environment is an important aspect of urban sustainable development. The floating population refers to people without local hukou (also called ‘non-hukou migrants’). The floating population distribution is influenced by livability environment, but few studies have investigated this relationship. Especially, the influence of social environment on floating population distribution is rarely studied. Therefore, we study 1054 communities in Guangzhou’s urban district to explore the relationship between livability environment and floating population distribution. The purpose of this article is to study how livability environment affects floating population distribution. We develop a conceptual framework of livability environment, which consists of physical environment, social environment and life convenience. A cross-sectional dataset of the impact of livability environment on the floating population distribution is developed covering the proportion of floating population in the community as the dependent variable, eight factors of livability environment as the explanatory variables, and two factors of architectural characteristics and one factor of location characteristics as the control variables. We use spatial regression models to explore the degree of influence and direction of physical environment, social environment and life convenience on the floating population distribution in livability environment. The results show that the spatial error model is more effective than ordinary least squares and spatial lag model models. The five factors of the livability environment have statistical significance regarding floating population distribution, including four social environment factors (proportion of middle- and high-class occupation population, proportion of highly educated people in the population, proportion of rental households, and unemployment rate) and regarding life convenience factors (work and shopping convenience). The conclusion has value for understanding how the social environment affects the residential choice of the floating population. This study will help city administrators reasonably guide the residential pattern of the floating population and formulate reasonable management policies, thereby improving the city’s livability, attractiveness and sustainable development.