Miracle-dz/UniFAR-FTUs huggingface dataset:
Detecting Spatiotemporal Features and Rationalities of Urban Expansions within the Guangdong-Hong Kong-Macau Greater Bay Area of China from 1987 to 2017 Using Time-Series Landsat Images and Socioeconomic Data

The Guangdong–Hong Kong–Macau Greater Bay Area (GBA) of China is one of the major bay areas in the world. However, the spatiotemporal characteristics and rationalities of urban expansions within this region over a relatively long period of time are not well-understood. This study explored the spatiotemporal evolution of 11 cities within the GBA in 1987–2017 by integrating remote sensing, landscape analysis, and geographic information system (GIS) techniques, and further evaluated the rationalities of their expansion using the urban area population elastic coefficient (UPEC) and the urban area gross domestic product (GDP) elastic coefficient (UGEC). The results showed the following: (1) Guangzhou, Shenzhen, Foshan, Dongguan, Zhongshan, and Zhuhai experienced unprecedented urbanization compared with the other cities, and from 1987 to 2017, their urban areas expanded by 10.12, 11.48, 14.21, 24.90, 37.07, and 30.15 times, respectively; (2) several expansion patterns were observed in the 11 cities, including a mononuclear polygon radiation pattern (Guangzhou and Foshan), a double-nucleated polygon pattern (Macau and Zhongshan), and a multi-nuclear urbanization pattern (Shenzhen, Hong Kong, Dongguan, Jiangmen, Huizhou, Zhaoqing, and Zhuhai); (3) with regard to the proportion of area, the edge-expansion and outlying growth types were the predominant types for all 11 cities, and the infilling growth type was the one of the important types during 2007–2017 for Shenzhen, Hong Kong, Dongguan, Zhongshan, and Foshan; (4) the expansion of most cities took on an urban-to-rural landscape gradient, especially for Guangzhou, Shenzhen, Foshan, Zhongshan, Dongguan, and Zhuhai; and (5) the rationalities of expansion in several time periods were rational for Guangzhou (1997–2007), Hong Kong (2007–2017), Foshan (1987–2007), Huizhou (1987–1997), and Dongguan (1997–2007), and the rationalities of expansion in the other cities and time periods were found to be irrational. These findings may help policy- and decision-makers to maintain the sustainable development of the Guangdong–Hong Kong–Macau Greater Bay Area.
A Numerical Approach for Buildings Reduced Thermal Model Parameters Evaluation

This paper introduces an efficient PSO-based optimization method to identify parametric values of buildings reduced thermal RC network models. A high order reference model representing energy flow through building envelope is developed based on Crank-Nicolson finite difference method. Thermal network models performance with random resistance and capacitance values are compared with a reference model then PSO is used for parameters identification to match the actual reference model thermal dynamics. The accuracy and computational cost of these optimized models are validated against reference model for different construction classes. The proposed methodology presents an effective way to develop a reliable thermal network model representing realistic thermal dynamics in building that can be used to improve efficiency of controlling techniques.
Assessment of Water Resources Management Strategy under Different Evolutionary Optimization Techniques

Competitive optimization techniques have been developed to address the complexity of integrated water resources management (IWRM) modelling; however, model adaptation due to changing environments is still a challenge. In this paper we employ multi-variable techniques to increase confidence in model-driven decision-making scenarios. Here, water reservoir management was assessed using two evolutionary algorithm (EA) techniques, the epsilon-dominance-driven self-adaptive evolutionary algorithm (-DSEA) and the Borg multi-objective evolutionary algorithm (MOEA). Many objective scenarios were evaluated to manage flood risk, hydropower generation, water supply, and release sequences over three decades. Computationally, the -DSEA’s results are generally reliable, robust, effective and efficient when compared directly with the Borg MOEA but both provide decision support model outputs of value.
Low-rank matrix decomposition method for potential field data separation

Separation of potential field data forms the basis of inversion and interpretation. The low-rank matrix theory is used for the separation of potential field data. A theoretical analysis led to the approximate equation that demonstrates the relation between the amplitudes of the wavenumber components of potential field data and the singular values of the trajectory matrix embedded from the potential field data matrix. Therefore, the low-rank feature of the trajectory matrix of regional field data and the sparse feature of the trajectory matrix of residual field data can be obtained based on the features of the power spectrum of the potential field data. Based on this, we have developed a low-rank matrix decomposition model for the separation of the trajectory matrix of the potential field data. Minimizing the rank of the trajectory matrix of the regional field data and the [Formula: see text]-norm of the trajectory matrix of the residual field data is a double-objective optimization task, and this optimization task can be solved by the inexact augmented Lagrange multiplier algorithm. The weighting parameter is robust and easy to set. Numerical experiment results indicate that our method is robust, and the separation errors of the method are smaller compared to the matched filtering and wavelet analysis methods. In addition, our method can be easily implemented and has clear geophysical significance. Finally, our method is applied on real data sets in the Daye area, Hubei Province, China. The separated gravity and magnetic fields coincide well with target geologic sources.
Ka-band return link for UAVs using adaptive spreading factor for DSSS in a DVB-RCS2 context

This paper evaluates the potential performances of a Direct Sequence Spread Spectrum (DSSS) satellite communication for Unmanned Aerial Vehicles (UAVs) in Ka-band using low directional antenna. The need to comply with the interference templates established by ITU enforces a bound to the signal power emitted toward adjacent satellites and greatly limits the accessible data rate. That prevents the UAVs communications to use a dedicated repeater for the return link. Instead, simultaneous transmission with return link communications in accordance to DVB-RCS2 standard is investigated. The proposed system is thus based on simultaneous transmission of narrow-band carriers (DVB-RCS2 primary system) and spread spectrum carriers (secondary system dedicated to UAVs). Mutual interferences are evaluated, it is shown that secondary transmissions do not affect primary systems availability, but conversely DVB-RCS2 carriers forces the secondary systems to use a high spreading factor, typically between 28 and 214 which can be updated as the number of primary active carriers changes within the beam. A compromise between secondary burst length and speed of adaptation for spreading factor is also discussed. Typically, if the targeted Packet Error Rate (PER) of the secondary link is 10e-5 and modulation is QPSK with a code rate 1/3, SNIR has to be held over 0 dB. This objective is reached with a spreading factor switching from 2e10 to 2e14 as the number of active primary carriers changes with a maximum bandwidth occupation of 90%, resulting in a data rate varying between 8 kbps and 34 kbps for the secondary system and a SNIR maintained between 1.5 dB and 4.5 dB.
An Assessment of Changes in Ecological Stability and Landscape Management Practices over the Last Centuries: A Case Study from Vrbovce, Slovakia

The landscape is an open system influenced by natural and anthropogenic factors that in a long-run fundamentally affect its state and development. A comprehensive understanding and assessment of the anthropogenic impacts on the environment is a key prerequisite to maintain its good ecological state. However, as the impacts of anthropogenic activities on the environment are omnipresent, necessary measures for their mitigation should be addressed to improve the landscape ecological stability. In Slovakia, agricultural activities on large blocks of land are considered as one of the main anthropogenic factors negatively influencing the landscape ecological stability, which however could be eliminated by effective landscape management activities. This study assesses the ecological stability of the cadastral area of the village of Vrbovce in both historical and current contexts and suggests several “green” measures aiming at improving its ecological stability. The information about the land types and structures were obtained by manual vectorization of historical and current topographical maps. Based on this information analysis of land utilization and its development was carried out for a period of more than 250 years. For each historical period, a coefficient of ecological stability was evaluated to assign a degree of ecological stability for each period. Moreover, an analysis of positive and negative landscape-ecological impacts was also performed to identify the problematic areas within the cadastral area that need to be addressed by mitigation measures. Based on these analyses several mitigation measures were suggested to improve the ecological stability of the area. Most of them were related to the agricultural land, which makes up a significant part of the area and represents its less ecologically stable part. The proposed measures respect the original rural character of the area and its specific scenery which is a result of centuries of man-land interaction. The measures are mostly focused on transforming some of the less ecologically stable areas into natural grasslands which would be used for ecological cattle and sheep breeding as these activities were historically the primary source of living in this area.
Spatio-temporal Distribution Characteristics of Water Quality in Miju River and Erhai Lake

Liu, J.; Xu, J.; Chen, J.; Hong, X. , and Zhou, M. , 2019. Spatio-temporal distribution characteristics of water quality in Miju River and Erhai Lake. In: Guido-Aldana, P.A. and Mulahasan, S. (eds.), Advances in Water Resources and Exploration. Journal of Coastal Research, Special Issue No. 93, pp. 31–38. Coconut Creek (Florida), ISSN 0749-0208.In the research related to the water resources management and prevention of pollution, it is of great practical significance to analyze the spatial and temporal distribution characteristics of the water quality. The present work deals with the study on the actual water quality monitoring data obtained from the Miju River monitoring sections in the Erhai Lake during 2011-2016. Six water quality indicators were selected for investigation using the comprehensive pollution index method and the principal component analysis method, in order to analyze the spatial and temporal distribution characteristics of water quality in the Miju River Basin. The results of the comprehensive pollution index method showed that the water quality of the Miju River has not changed much in the past 6 years, and the water body has only been slightly polluted. Additionally, the water quality of the Jiangweiqiao section was slightly inferior to that of the Yinqiaocun section. Principal component analysis method showed that the nitrogen pollution was the dominant factor in the wet season, followed by phosphorus, pH and dissolved oxygen. In the normal season, the dissolved oxygen and pH of the water were the main factors, followed by phosphorus and ammonia nitrogen. In the dry season, the dissolved oxygen, ammonia nitrogen and organic matter pollution were the main influencing factors followed by phosphorus and pH. The water quality of the Miju River in the past 3 years was slightly worse than that in the initial 3 years, and the overall performance of the water quality of the Miju River was relatively best during the dry season followed by the normal season, while the water quality was worst during the wet season. Furthermore, the water quality variation trends of Yinqiaocun and the Jiangweiqiao sections were observed to be similar.
SOCIOECONOMIC DETERMINANTS OF WOMEN’S CHOICE OF PLACE OF DELIVERY IN CROSS RIVER STATE, NIGERIA

To increase women’s utilisation ofskilled attendants during pregnancy and childbirth, the government of Cross River State, Nigeria, in 2009, introduced a cost-free maternal health programme. The project was intended to help reduce the high maternal mortality rate in the state, which occurs mainly because of the utilisation of unskilled attendants by women during pregnancy and childbirth. However, the patronage of unskilled attendants by pregnant women in the state has persisted. Thisstudy thus examinesthe factors that influence women’s choices when it comes to where they choose to get care during pregnancy and childbirth. Cross River State, Nigeria, was the study area, and the mixed method was the study design. Women of childbearing age in the state constituted the study population, while a total of 613 respondents were selected purposively to form the subjects for the study. Quantitative data for the study was obtained using a structured questionnaire, while the Focus Group Discussion and interviews were utilised to generate the qualitative data. Two hypotheses were formulated and tested using the ChiSquare and Multiple Regression Analysis as statistical tools. Findings based on the test of the Hypothesis I revealed that delivery demands significantly influence women’s choice of place of delivery. The analysis of the second hypothesis using the multiple regression further revealed that religious belief and income level both had statistically significant p-values of 0.000, which is less than the 0.05 alpha levels of significance; meaning that both religious belief and income level significantly influence women’s choice of place of delivery. Educational status, however, had a p-value (0.078)> 0.05 alpha levels of significance. This is not statistically significant, implying that educational status does not significantly influence women’s choice of place of delivery. The study recommends that beyond making delivery cost-free, the government of Cross River State should adequately equip hospitals to prevent the demands placed on women at the time of birth, which scares a number of them, forcing some to opt for unskilled attendants. Also, the study recommends increased effort towards the empowerment of women to curb the difficulties created by income as well as the intensification of awareness campaigns, among other measures.
A minimum-volume oriented bounding box strategy for improving the performance of urban cellular automata based on vectorization and parallel computing technology

ABSTRACT As an effective tool for simulating spatiotemporal urban processes in the real world, urban cellular automata (CA) models involve multiple data layers and complicated calibration algorithms, which make their computational capability become a bottleneck. Numerous approaches and techniques have been applied to the development of high-performance urban CA models, among which the integration of vectorization and parallel computing has broad application prospects due to its powerful computational ability and scalability. Unfortunately, this hybrid algorithm becomes inefficient when the axis-aligned bounding box (AABB) of study areas contains many unavailable cells. This paper presents a minimum-volume oriented bounding box (OBB) strategy to solve the above problem. Specifically, geometric transformation (i.e. translation and rotation) is applied to find the OBB of the study area before implementing the hybrid algorithm, and a set of functions are established to describe the spatial coordinate relationship between the AABB and OBB layers. Experiments conducted in this study demonstrate that the OBB strategy can further reduce the computational time of urban CA models after vectorization and parallelism. For example, when the cell size is 15 m and the neighborhood size is 3 × 3, an approximately 10-fold speedup in computational time can result from vectorization in the MATLAB environment, followed by an 18-fold speedup after implementing parallel computing in a quad-core processor and, finally, a speedup of 25-fold by further using an OBB strategy. We thus argue that OBB strategy can make the integration of vectorization and parallel computing more efficient and may provide scalable solutions for significantly improving the applicability of urban CA models.
Probing into the Recent Occurrence of Scrub Typhus Cases in and around Kolkata

Scrub typhus is endemic in India. Right now scrub typhus is enjoying its status as a re-emerging disease and is often causing trouble in diagnosis due to absence of specific rash or eschar. In our institution, we observed a seasonal rise of febrile illnesses that coincided with monsoon rain, and decided to investigate the probable etiological role of scrub typhus among the undiagnosed fever cases. This prospective study was conducted from the middle of May to the end of August in 2019. All febrile patients who tested negative for malaria, dengue, urinary tract infections, enteric fever and other pyogenic infections were included in this study. Those who became serologically reactive for Scrub typhus IgM antibody by ELISA were considered as established cases of scrub typhus. The seroprevalence of scrub typhus among undiagnosed fever cases was 33.9% with a resultant mortality of 11.8%. Fever (100%), headache (92%) and myalgia (62%) were the commonest symptoms followed by lymphadenopathy, vomiting, diarrhea, pain abdomen, rash and rarely eschar. Meningoencephalitis (12%) was the commonest complication followed by acute kidney injury which along with hepatitis often led to fatal multi organ failure. Thus, scrub typhus should be considered at the earliest in the differential diagnoses for acute undiagnosed fever with nonspecific features in endemic countries like ours.
Dam Effects on Downstream Riparian Wetlands: The Nenjiang River, Northeast China

Many studies have found that damming a river can change downstream hydrology, sediment transport, channel morphology, and fish habitat. However, little is known about river dam effects on downstream riparian wetland dynamics and their quantitative relationship with hydrological alterations. In this study, hydrological time series and wetland distribution data spanning nearly 40 years (1978–2016) before and after the construction of a large dam in 2005 across the Nenjiang River in Northeast China were used to reveal the impact of dam on the downstream discharge regime and wetland degradation. Hydro-statistical and stepwise multiple regression analyses were performed to quantify the relationship of riparian wetland area with a metrics of 33 hydrological indicators. Dam construction caused decline in peak discharge, flood frequency, and magnitude. Moreover, 150 km riparian wetlands along the downstream of the dam was largely reduced. The count and duration of high flow pulses, 1-day maximum, and date of maximum discharge changed significantly after the dam construction. The hydrological changes have made a significant contribution to the 44% reduction in riparian wetlands following the dam construction. Our results indicated that hydrological alterations caused by dam regulation led to the area reduction of downstream riparian wetlands. The findings provide relevant information for developing best dam operation practices to protect and restore downstream wetland ecosystems.
Finding a Relatively Flat Archaeological Site with Minimal Ceramics: A Case Study from Iraqi Kurdistan

ABSTRACT We present a new technique to detect flat archaeological sites with minimal ceramics using an unmanned aerial vehicle that maps surface stone concentrations. Methods deployed include point pattern analysis of stone concentrations and a machine-learning technique using unsupervised classification of visible stone signature qualities, which are used in simple linear regressions to compare with geophysical and ceramic surface survey results of a site in Iraqi Kurdistan. There is a stronger fit (r2 = 0.77) between surface stone concentrations and architecture identified by geophysical measurement, while surveyed ceramics show a weaker fit to defined architecture (r2 = 0.31). Surface stone concentrations are potentially a better proxy than ceramics for determining the presence of past settlement in regions where stone was commonly used, sites are relatively flat, and ceramics are found in low concentrations. The methods advanced here can be scaled to wider areas, particularly in mountainous regions, where surface stone features are present.
Design of a Tendon Driven Soft Continuum Robotic Arm Using Proprioceptive Sensors

In this thesis the use of proprioceptive sensors in elephant trunk inspired soft continuum robots was explored. After presenting the basics for this project, a review of existing soft continuum robots is given. The sensors used are off-the-shelf stretch senors. Those sensors are carbon black impregnated rubber cords. The design and the fabrication of the robot are described. Using material characteristics a calibration process was developed to improve the sensor’s consistency. The robot is then tested in open-loop as well as a closed-loop experiment. Results of those experiments are presented and discussed.
Mapping Languages and Demographics with Georeferenced Corpora

This paper evaluates large georeferenced corpora, taken from both web-crawled and social media sources, against ground-truth population and language-census datasets. The goal is to determine (i) which dataset best represents population demographics; (ii) in what parts of the world the datasets are most representative of actual populations; and (iii) how to weight the datasets to provide more accurate representations of underlying populations. The paper finds that the two datasets represent very different populations and that they correlate with actual populations with values of r=0.60 (social media) and r=0.49 (web-crawled). Further, Twitter data makes better predictions about the inventory of languages used in each country.
Mining Entities from Events

Nowaday Wikipedia is becoming the main source of data for analyzing, researching and finding insights from it. Many researchers are for this reason interested about the Wikipedia data. Understand the relationship between entities according to a given set of entities which we called seed entities. Finding insights from them, it is also very important to obtain more related entities and analyze them. Entity resolution is a problem that arises in many information integration scenarios [1]. To fulfilling this purpose visualizing entities through graph has an increasing demand and interest among researchers. To analyzing this data as a source our main goal objective is mining entities from events and study how to effectively use crowdsourcing techniques to generate an automated trustable entity graph. Based on this foundation we develop a model for generating entities and inside the page based on the link entity it extends the input seed entity. We develop models and methods that find out the co-occurrences between entities based on their events and automatically generate the entity graph. Also this produces a word cloud representation according to user’s given input.