Miracle-dz/UniFAR-FTUs huggingface dataset:
An Integrated Approach of Spatial Justice and Structure to Detect Spatial Conflicts in Yazd City

According to several types of research, one of the most important issues and principles of sustainable development that urban professionals pay attention to it recently is Just City. One aspect of Justice in cities, spatial justice, has particular significance by Unequal and discordant Expanding in cities regarding creating unequal areas. On the other hand, the urban spatial structure affects the equal distribution of elements and services. If this structure is devoid of justice ideology will lead to a complex social crisis and spatial issues as spatial conflict. Accordingly, this study aims to analyse the spatial justice and structure in the case of Yazd city to know how they influence each other. Spatial justice is examined from the view of "Equality of opportunity". Involved criteria are "equality", "Physical diversity", "human diversity" and "urban spaces", and spatial structure based on “Space Syntax” technique with "integration", "control", "connect" and " intelligibility " parameters. These criteria are Scored and analysed by FDAHP techniques and GIS. The result shows favourable status in the Central District, and as getting away from the disadvantaged downtown District increased. On the other hand, the spatial structure analysis reveals the most spatial coherent analogue the north-south axis with a little depth and isolated District (Spatial segregations) have located in the corners and edges of the city. Results from the superposition of these two analysis layers show a compatibility relation between the spatial structure of Yazd and the pattern of justice distribution except in the central and historical centre.
A Multi-Mode Data-Driven Volt/Var Control Strategy With Conservation Voltage Reduction in Active Distribution Networks

This paper proposes a two-stage multi-mode data-driven Volt/Var optimization-based conservation voltage reduction (VVO/CVR) strategy to reduce total energy consumption while mitigating fast voltage violations in distribution networks. In the first stage, optimal power flow (OPF) is performed in the central controller (CC) to obtain day-ahead dispatch results of on-load tap changers (OLTC) and capacitor banks (CBs) based forecasting data of PV and load. In the second stage, a multi-mode data-driven local control strategy is designed in real-time Volt/Var control (VVC) with three operation modes, which are energy saving mode, reactive power reservation mode and security operation mode respectively. The coordination and transition among different control modes allow system operators to achieve both energy savings and voltage security under various conditions. The flexible reactive power margin of PVs can also be adaptively improved through cooperation with CBs. Moreover, a data-driven deep convolution neural network (CNN) is developed and trained as a local controller (LC) to regulate the reactive power of PVs based on local measurements. The influence of input selections on training losses is analyzed in detail, and a clustering-based data preprocessing method is also proposed to simplify the training process without compromising the training performance. The proposed approach is tested on the IEEE 33-bus distribution system and simulation results verify the effectiveness both in saving energy and addressing voltage problems.
Separable functions: symmetry, monotonicity, and applications

In this paper, we introduce concepts of separable functions in balls and in the whole space, and develop a new method to investigate the qualitative properties of separable functions. We first study the axial symmetry and monotonicity of separable functions in unit circles by geometry analysis, and we prove the uniqueness of the symmetry axis for nontrivial separable functions. Then by using reduction dimension and convex analysis, we get the axial symmetry and monotonicity of separable functions in high dimensional spheres. Based on the above results on unit circles and spheres, we deduce the axial symmetry and monotonicity of separable functions in balls and the radial symmetry and monotonicity of separable functions in the whole space. Conversely, the function with axial symmetry and monotonicity in the ball domain is separable function, and the function with radial symmetry and monotonicity in the whole space is also separable function. These enable us to provide easily some examples that separable functions in balls may be just axially symmetric not radially symmetric. Finally, as applications, we obtain the axial symmetry and monotonicity of all the positive ground states to the Choquard equation in a ball as well as the radial symmetry and monotonicity of all the positive ground states in the whole space.
Influence of Temperature and Pentacene Thickness on the Electrical Parameters in Top Gate Organic Thin Film Transistor

In this contribution, we report on the effect of pentacene thickness and temperature on the performance of top gate transistors. We first investigated the temperature dependence of the transport properties in the temperature range of 258 K - 353 K. The electrical characteristics showed that the threshold voltage (VT) and the onset voltage (Von) remain unchanged. However, the subthreshold current (Ioff), the on-current (Ion) and the field effect mobility (μ) are highly affected with a slight deterioration of subthreshold slope. We observed Arrhenius-like behavior suggesting a thermally activated mobility with an activation energy EA = 68 meV. Moreover the dependence of the charge carrier mobility on the organic semiconductor thickness has also been studied. The mobility decreased as the pentacene thickness increases whereas the threshold voltage and Ioff current remain minimally affected. In order to understand the transport properties and in view to put in light morphology peculiarities of pentacene, AFM images were performed. It turns out that the pentacene grain sizes are smaller and disorganized as the film thickness increases, and charge carriers are more prone to be trapped, leading to decrease the field effect mobility and the Ion current. The devices were also tested under bias stress and the transistors with low thicknesses exhibited a relatively good electrical stability compared to those with high pentacene thicknesses. This work points out the influence of temperature, semiconductor thickness and bias stress effect on the device performance and stability of transistor using top gate configuration.
ITCZ Width Controls on Hadley Cell Extent and Eddy-Driven Jet Position and Their Response to Warming

The impact of global warming–induced intertropical convergence zone (ITCZ) narrowing onto the higher-latitude circulation is examined in the GFDL Atmospheric Model, version 2.1 (AM2.1), run over zonally symmetric aquaplanet boundary conditions. A striking reconfiguration of the deep tropical precipitation from double-peaked, off-equatorial ascent to a single peak at the equator occurs under a globally uniform +4 K sea surface temperature (SST) perturbation. This response is found to be highly sensitive to the SST profile used to force the model. By making small (≤1 K) perturbations to the surface temperature in the deep tropics, varying control simulation precipitation patterns with both single and double ITCZs are generated. Across the climatologies, narrower regions of ascent correspond to more equatorward Hadley cell edges and eddy-driven jets. Under the global warming perturbation, the experiments in which there is narrowing of the ITCZ show significantly less expansion of the Hadley cell and somewhat less poleward shift of the eddy-driven jet than those without ITCZ narrowing. With a narrower ITCZ, the ascending air has larger zonal momentum, causing more westerly upper-tropospheric subtropical wind. In turn, this implies 1) the subtropical jet will become baroclinically unstable at a lower latitude and 2) the critical (zero wind) line will shift equatorward, allowing midlatitude eddies to propagate farther equatorward. Both of these mechanisms modify the Hadley cell edge position, and the latter affects the jet position.
FSMS: An Enhanced Polynomial Sampling Fusion Method for Audio-Visual Speech Recognition

In recent years, end-to-end audio-visual speech recognition (AVSR) has been proposed with great success. However, due to the heterogeneity between different modal data, an effective audio-visual fusion strategy is in need to learn the correlation between the audio and the video information. In this paper, we propose a fusion strategy in which the high-level features output from audio and video encoders are fed into a siamese neural network with shared weights, and then feature-level masking and polynomial sampling are incorporated to train the fusion of the high-dimensional features of audio and video, achieving inter-modality information alignment. In comparison with the traditional fusion methods as concatenation, it results in improvement of performance. We experimentally demonstrate the effectiveness of this approach on the word-level AVSR task.
UvA-DARE ( Digital Academic Repository ) Tracking Real-Time Changes in Working Memory Updating and Gating with the Event-Based EyeBlink Rate

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Use of Acorn Leaves as a Natural Coagulant in a Drinking Water Treatment Plant

In this study, the use of acorn leaves as a natural coagulant to reduce raw water turbidity and globally improve drinking water quality was investigated. The raw water was collected from a drinking water treatment plant located in Mila (Algeria) with an initial turbidity of 13.0 ± 0.1 NTU. To obtain acorn leaf powder as a coagulant, the acorn leaves were previously cleaned, washed with tap water, dried, ground and then finely sieved. To improve the coagulant activity and, consequently, the turbidity removal efficiency, the fine powder was also preliminarily treated with different solvents, as follows, in order to extract the coagulant agent: (i) distilled water; (ii) solutions of NaCl (0.25; 0.5 and 1 M); (iii) solutions of NaOH (0.025; 0.05 and 0.1 M); and (iv) solutions of HCl (0.025; 0.05 and 0.1 M). Standard Jar Test assays were conducted to evaluate the performance of the coagulant in the different considered operational conditions. Results of the study indicated that at low turbidity (e.g., 13.0 ± 0.1 NTU), the raw acorn leaf powder and those treated with distilled water (DW) were able to decrease the turbidity to 3.69 ± 0.06 and 1.97 ± 0.03 NTU, respectively. The use of sodium chloride solution (AC-NaCl) at 0.5 M resulted in a high turbidity removal efficiency (91.07%) compared to solutions with different concentrations (0.25 and 1 M). Concerning solutions of sodium hydroxide (AC-NaOH) and hydrogen chloride (AC-HCl), the lowest final turbidities of 1.83 ± 0.13 and 0.92 ± 0.02 NTU were obtained when the concentrations of the solutions were set at 0.05 and 0.1 M, respectively. Finally, in this study, other water quality parameters, such as total alkalinity hardness, pH, electrical conductivity and organic matters content, were measured to assess the coagulant performance on drinking water treatment.
Assessment on different digital camera calibration software for photogrammetric applications

Article history: Received 11 February 2017 Received in revised form 16 March 2017 Accepted 26 March 2017 Available online 4 April 2017 Camera calibration has always been an essential component in photogrammetric measurement. Nowadays, self-calibration is being integral and routinely applied operations within photogrammetric triangulation, especially in high accuracy close range measurement. This study is to compare the accuracy of different types of software in order to determine the correct technique based on two different calibrations software. The objective of this study is to analyze the accuracy based on different resolution, to assess the calibration result based on two different software and to evaluate the best technique in camera calibration. Based on this study, the data involves are image of calibration sheet from different camera resolutions, good and bad light conditions and different flash conditions. This is the three types of data needed in this study before next process can be done. After all the data has been acquired, it undergoes data processing to assess the RMSE value for each result. This process used PhotoModeler software and GML C++ Camera Calibration Toolbox. The result shows the Olympus camera has better result than the other two camera used. In conclusion, the self–calibration method is easy to perform and save time compare to other method that required cost and more complex.
Variable Inertias of Wind Turbines in Interconnected Power System for Transient Stability Enhancement

The virtual energy generated by the variable speed wind turbine with virtual inertia control not only changes the frequency response of the system, but also has a significant effect on the transient stability of rotor angle. In this paper, the equivalent model of interconnected system with wind turbines is derived. According to the extended equal area criterion, the conversion between the virtual energy of wind turbine and the transient energy of synchronous generator (SG) is calculated, and the first swing stability of rotor angle is evaluated. The integral manifold method is then adopted to reduce the order of the system model, and the influence of variable inertia control on system damping is analyzed. A variable inertia optimization control strategy is proposed to reduce rotor angle variation by exchanging transient energy with SG while providing rapid inertia response. Finally, a two-area interconnected power system with high wind power penetration is established. The results demonstrate that under the proposed control strategy, the transient stability of system frequency and rotor angle can be both significantly improved.
Power Set-Point Tracking of a Wave Energy Converter With Multiple Power Take-Off Units in Irregular Waves

Ocean wave energy has been regarded as a promising and sustainable power source for offshore power system. In order to handle the uncertainty and fluctuation of the wave power, the power system is generally designed to be highly dependent on short-time energy storage facilities such as battery packs. This means the cost of energy storage facility tends to dramatically increase when a large wave farm is deployed. This paper proposes a model predictive control algorithm to realise the continuous power set-point tracking of a single six-of-freedom point absorber with multiple power take-off units, to mitigate the dependence of the energy storage in offshore power supply. The key controller settings that determine the power quality of the wave energy converter are analysed over various power set-points. Furthermore, the performance of power set-point tracking is assessed over significant wave heights and peak periods. It is found that although the power set-point tracking algorithm only achieves 10-27% of power generation capacity at the expense of reducing power fluctuation, the controlled point absorber is still capable to serve as a high-quality power source in some of offshore scenarios.
Sources of High Sulfate Aerosol Concentration Observed at Cape 1 Hedo in Spring 2012 2 3

23  Corresponding author. Tel: 81-70-5080-1394; Fax: 81-4-7183-2966 E-mail address: isyuichi@criepi.denken. or.jp; sitahas@ncsu.edu AC CE PT ED M AN US CR IP T 2 Intensive observation campaigns approximately 1 week long were conducted periodically 24 from March 2010 to November 2015 at Cape Hedo, Okinawa, Japan. The maximum daily 25 mean sulfate aerosol (SO4) concentrations surpassed 15 μg m in springtime 2012. In this 26 study, the sources of the high SO4 concentrations were estimated by using the air quality 27 model with the tagged tracer method. The main source of the high SO4 concentrations in 28 March was volcanoes and that in April was anthropogenic emissions from China. In March, 29 the prevailing northerly wind transported a volcanic SO2 plume with a low conversion ratio to 30 Cape Hedo. The impacts of 15 volcanoes in Japan were estimated in this study, and a 31 substantial impact of Sakurajima, which accounted for more SO2 than anthropogenic 32 emissions from Japan, was found. Because the model had difficulty capturing the highest 33 concentration, three sensitivity simulations were performed to consider the uncertainty of 34 volcanic SO2 emission amounts and injection heights, revealing the importance of the 35 injection height in addition to SO2 emission amount. Throughout April, source 36 apportionments from anthropogenic emissions from China were found; hence, the source was 37 further divided into 31 provincial scales. Shandong and Jiangsu provinces, which are the first 38 and seventh largest emission sources in China, were identified as important sources at Cape 39 Hedo. These sources showed day-to-day variation, and the highest contribution from 40 Shandong province was on April 23, whereas that from Jiangsu province was on April 22. 41
Research and Implementation of Wireless TDOA Positioning Station Synchronization Based on RTL-SDR

Aiming at the problems of high precision time synchronization between station signals and high hardware cost in wireless TDOA positioning, a method of high precision time synchronization between station signals with low cost was proposed by using RTL-SDR TV stick as station signal receiver. Chengdu FM 102.6 Mhz radio station was taken as the synchronization time standard, and the synchronization error of the radiation source signal and the radio signal was estimated by two TV sticks. The GCC correlation algorithm was used to carry out the composite signal correlation calculation, and then the integer and decimal delay filtering was used to carry out the precision synchronization of the signals between the stations. In the proposed time synchro-nization implementation method, when using 100 ppm and 1 ppm built-in crystal oscillator receiving equipment, the accuracy of time synchronization error calculated by the station is 400 ns and 200 ns respectively. The 1 ppm equipment has a better synchronization accuracy range, which meets the synchronization accuracy requirements in general scenarios. The experimental results show that the RTL-SDR device can achieve the synchronization accuracy of wireless TDOA positioning time and frequency, and the hardware cost is much lower than the market synchronization equipment.
An Adversarial Model of Network Disruption: Maximizing Disagreement and Polarization in Social Networks

The spread of misinformation has increased markedly in recent years, a phenomenon which has been accelerated and amplified by social media such as Facebook and Twitter. While some actors spread misinformation to push a specific agenda, it has also been widely documented that others aim to simply disrupt the network by increasing disagreement and polarization across the network, thereby destabilizing society. Popular social networks are also vulnerable to large-scale attacks. Motivated by this reality, we introduce a simple model of network disruption to capture this phenomenon, where an adversary can take over a limited number of user profiles in a social network with the aim of maximizing disagreement and/or polarization in the network. We investigate this model both theoretically and empirically. We show that the adversary will always change the opinion of a taken-over profile to an extreme in order to maximize disruption. We also prove that an adversary can increase disagreement/polarization at most linearly in the number of user profiles it takes over. Furthermore, we present a detailed empirical study of several natural algorithms for the adversary on both synthetic networks and real world (Reddit and Twitter) data sets. These show that even simple, unsophisticated heuristics, such as targeting centrists, can disrupt a network effectively, causing a large increase in disagreement / polarization. Studying the problem of network disruption through the lens of an adversary thus highlights the severity of the problem.
Research and Application of Ultrasonic Stress Detection Method for Insulation Defects of High Voltage Switchgear

Aiming at the problems of single technical means and difficult quantitative analysis in the process of insulation defect detection of high voltage switchgear, in this paper, the effects of bubble and crack on the stress distribution of insulation diaphragm under electric field were studied by finite element method. On this basis, an ultrasonic stress detection method for insulation defects of high voltage switchgear was proposed. A detection system in this study was constructed, and the artificial simulated defect samples placed in the high voltage switchgear were also tested. Our study show that the average error of defect size was 0.24mm. The experimental results show that this method can effectively detect and quantitatively analyze the insulation defects in high voltage switchgear, and the detection results have high accuracy.
A comparative analysis of Graph Neural Networks and commonly used machine learning algorithms on fake news detection

Fake news on social media is increasingly regarded as one of the most concerning issues. Low cost, simple accessibility via social platforms, and a plethora of low-budget online news sources are some of the factors that contribute to the spread of false news. Most of the existing fake news detection algorithms are solely focused on the news content only but engaged users' prior posts or social activities provide a wealth of information about their views on news and have significant ability to improve fake news identification. Graph Neural Networks are a form of deep learning approach that conducts prediction on graph-described data. Social media platforms are followed graph structure in their representation, Graph Neural Network are special types of neural networks that could be usually applied to graphs, making it much easier to execute edge, node and graph-level prediction. Therefore, in this paper, we present a comparative analysis among some commonly used machine learning algorithms and Graph Neural Networks for detecting the spread of false news on social media platforms. In this study, we take the UPFD dataset and implement several existing machine learning algorithms on text data only. Besides this, we create different GNN layers for fusing graph-structured news propagation data and the text data as the node feature in our GNN models. GNNs provide the best solutions to the dilemma of identifying false news in our research.
Corrected analytical solution of the generalized Woods–Saxon potential for arbitrary ℓ ?> states

The bound state solution of the radial Schrödinger equation with the generalized Woods–Saxon potential is carefully examined using the Pekeris approximation for arbitrary ℓ ? > states. The energy eigenvalues and the corresponding eigenfunctions are analytically obtained for different n and ℓ ? > quantum numbers. The closed forms obtained are applied to calculate the single particle energy levels of a neutron orbiting around 56Fe nucleus in order to check the consistency between the analytical and the Gamow code results. The analytical results are in good agreement with the results obtained using Gamow code for ℓ = 0 ? > .