Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhanced Thermal Properties of Zirconia Nanoparticles and Chitosan-Based Intumescent Flame Retardant Coatings

Zirconia (ZrO2)-based flame retardant coatings were synthesized through the process of grinding, mixing, and curing. The flame retardant coatings reinforced with zirconia nanoparticles (ZrO2 NPs) were prepared at four different formulation levels marked by F0 (without adding ZrO2 NPs), F1 (1% w/w ZrO2 NPs), F2 (2% w/w ZrO2 NPs), and F3 (3% w/w ZrO2 NPs) in combination with epoxy resin, ammonium polyphosphate, boric acid, chitosan, and melamine. The prepared formulated coatings were characterized by flammability tests, combustion tests, and thermogravimetric analysis. Finally, char residues were examined with scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS). The peak heat release rate (PHRR) of the controlled sample filled with functionalized ZrO2 NPs was observed to decrease dramatically with increasing functionalized ZrO2 NPs loadings. There was an increase in the limit of oxygen index (LOI) value with the increase in the weight percentage of ZrO2 NPs. The UL-94V data clearly revealed a V-1 rating for the F0 sample; however, with the addition of ZrO2 NPs, the samples showed enhanced properties with a V-0 rating. Thermal gravimetric analysis (TGA) results revealed that addition of ZrO2 NPs Improved composite coating thermal stability at 800 °C by forming high residual char. The results obtained here reveal that the addition of ZrO2 NPs in the formulated coatings has shown the excellent impact as flame retardant coatings.
Optimal Frequency-Flat Precoding for Frequency-Selective Millimeter Wave Channels

The two key features of millimeter wave-(mmWave) based MIMO communication are the use of large antenna arrays at the transceivers and large bandwidth. The former complicates the design of optimal beamformers, while the latter makes the system frequency-selective and, thus, requires equalization. Conventionally, for wideband mmWave channels, choosing the precoders/combiners have involved frequency-selective designs that are based on channel state information. In this paper, we show that under some assumptions, semi-unitary frequency-flat precoding and combining are sufficient for low-scattering millimeter wave channels. To show this, we evaluate the conditions and practical settings under which the dominant subspaces of the frequency-domain channel matrices are similar. We model the frequency-dependence of uniform linear antenna arrays, which leads to what is known as beam-squint, for two different practical setting to analyze the optimality of frequency-flat beamforming designs under practical hardware impairments. For the cases when the optimality conditions hold, we propose novel techniques based on compressive subspace estimation to design the optimal frequency-flat, semi-unitary precoders and combiners. Simulation results show that the system achieves near-digital spectral efficiencies at very small implementation cost of beamformers and channel training overhead.
CLIMATE CHANGE IMPACTS AND ADAPTATION FOR CROP MANAGEMENT OF WINTER WHEAT AND MAIZE IN THE SEMI‐ARID REGION OF IRAN

Climate change is expected to lead to declining crop yields in semi‐arid regions due to higher temperatures and more severe droughts, which calls for adaptations in crop management. We used the WOFOST and AquaCrop crop simulation models to examine the response of crop yield in winter wheat and maize to a set of climate change scenarios up to 2040 in the semi‐arid climate of Mashhad in north‐east Iran. Modelled climate change from six AOGCMs including GFCM21, HADCM3, INCM3, IPCM4, MPEH5 and NCCCSM under IPCC SRES A2 and B1 emission scenarios was used. The crop models were calibrated and validated against 7 years of observed crop yield data, confirming that the models adequately simulated yields of wheat and maize in the study area. The bootstrap method was used to estimate the uncertainty of crop yield projections. The results showed a mean yield decrease of 10–34% for winter wheat and 8–18% for maize, depending on the crop model and climate change scenario. The period of flowering to maturity of winter wheat and maize would be shortened on average by 9 and 5 days, respectively. Changes in crop management were considered for adaptation to climate change. Simulation results indicated that early sowing of winter wheat and late sowing of maize enhanced yield and water productivity across all climate change scenarios and that late‐maturity cultivars of winter wheat and early‐maturity hybrids of maize generally have higher productivity than standard cultivars. Increasing heat tolerance of the crops and changing irrigation management of winter wheat were also found to be beneficial adaptation options. © 2019 John Wiley & Sons, Ltd. © 2019 John Wiley & Sons, Ltd.
Reply to “Comments on ‘Traffic Sign Recognition Using Kernel Extreme Learning Machines With Deep Perceptual Features”’

This paper addresses the questions and concerns raised in the comment paper entitled “Comments on ‘Traffic Sign Recognition Using Kernel Extreme Leaning Machines With Deep Perceptual Features”’. It is analyzed that the major questions and concerns in the comment paper are due to some misunderstanding on the statements and the main contributions of the original paper by Zeng et al. The main clarifications are as follows: (1) The weight update rule used by Zeng et al. is a standard form of kernel extreme learning machine (KELM) but not the rule of reduced KELM mentioned by the comment paper. (2) The aim and main contribution of the original paper by Zeng et al. are to improve the classification precision of traffic sign recognition (TSR) based on convolutional neural networks without dramatically increasing the scale or complexity of the deep neural network model, which leads to a relatively less training cost. The authors of the comment paper focused on the reduction of KELM’s computational costs but it is beyond the topic of the original paper. In addition, the reduction of KELM’s computational costs has been well studied in the literature. (3) The supplementary experiment is provided to show that the TSR method proposed by Zeng et al. is valid whether or not the training samples are much more than the needed kernels.
High-Precision 13CO2/12CO2 Isotopic Ratio Measurement Using Tunable Diode Laser Absorption Spectroscopy at 4.3 μm for Deep-Sea Natural Gas Hydrate Exploration

For the detection of deep-sea natural gas hydrates, it is very important to accurately detect the 13CO2/12CO2 isotope ratio of dissolved gas in seawater. In this paper, a 13CO2/12CO2 isotope ratio sensor is investigated, which uses a tunable diode laser absorption spectroscopy (TDLAS) technique at 4.3 μm. The proposed sensor consists of a mid-infrared interband cascade laser (ICL) operating in continuous wave mode, a long optical path multi-pass gas cell (MPGC) of 24 m, and a mid-infrared mercury cadmium telluride (MCT) detector. Aiming at the problem of the strong absorption intensity of the two absorption lines of 13CO2 and 12CO2 being affected by temperature, a high-precision temperature control system for the MPGC was fabricated. Five different concentrations of CO2 gas were configured to calibrate the sensor, and the response linearity could reach 0.9992 for 12CO2 and 0.9996 for 13CO2. The data show that the carbon isotope measurement precision was assessed to be 0.0139‰ when the integration time was 92 s and the optical path length was 24 m. The sensor is combined with a gas–liquid separator to detect the 13CO2/12CO2 isotope ratio of CO2 gas extracted from water. Results validate the reported sensor system’s potential application in deep-sea natural gas hydrate exploration.
Inherited thrombophilia and its relation with obstetric complications

The purpose of this study was to investigate the relationship between maternal thrombophilia and several obstetric complications. Ninety-four pregnant women delivered at 24-42 gestational weeks at our clinic from February 2006 to March 2007 were included. Patients were divided into two groups. Group 1 consisted of 54 patients with complications of preeclampsia, intrauterine growth restriction and intrauterine fetal death. Group 2 consisted of 40 healthy pregnant women as control. The most commonly detected thrombophilic defect in two groups was Factor V Leiden mutation. It was detected in 15 patients (27.7%) in group 1 and in 4 patients (10%) in group 2 (p=0.019). Protein S. protein C and antithrombin-III deficiencies were detected only in group 1. There was no statistical significance between two groups for protein S. protein C and antithrombin-III deficiencies. Factor-V Leiden mutation can be a component of a genetic screening test for obstetric complications, but further detailed studies are needed for protein C, protein S and antithrombin-III.
Automatic targetless camera–LIDAR calibration by aligning edge with Gaussian mixture model

This paper presents a calibration algorithm that does not require an artificial target object to precisely estimate a rigid‐body transformation between a camera and a light detection and ranging (LIDAR) sensor. The proposed algorithm estimates calibration parameters by minimizing a cost function that evaluates the edge alignment between two sensor measurements. In particular, the proposed cost function is constructed using a projection model‐based many‐to‐many correspondence of the edges to fully exploit measurements with different densities (dense photometry and sparse geometry). The alignment of the many‐to‐many correspondence is represented using the Gaussian mixture model (GMM) framework. Here, each component of the GMM, including weight, displacement, and standard deviation, is derived to suitably capture the intensity, location, and influential range of the edge measurements, respectively. The derived cost function is optimized by the gradient descent method with an analytical derivative. A coarse‐to‐fine scheme is also applied by gradually decreasing the standard deviation of the GMM to enhance the robustness of the algorithm. Extensive indoor and outdoor experiments validate the claim that the proposed GMM strategy improves the performance of the proposed algorithm. The experimental results also show that the proposed algorithm outperforms previous methods in terms of precision and accuracy by providing calibration parameters of standard deviations less than 0.6° and 2.1 cm with a reprojection error of 1.78 for a 2.1‐megapixel image (2,048 × 1,024) in the best case.
Road rage in China: An exploratory study

Abstract This study consisted of a stated-preference questionnaire survey to investigate road rage among Chinese drivers. A total of 5157 Chinese drivers completed the survey. The Driving Anger Scale (DAS) and Driving Anger Expression Inventory (DAX) were used to measure road rage under various anger-provoking situations. Meanwhile, the theory of planned behavior (TPB) was adopted to explore respondents’ attitudinal perception towards road rage behaviors. Three TPB variables, i.e., behavioral attitude (BA), subjective norm (SN), and perceived behavioral control (PBC), were used to describe drivers’ perceived anger levels, driving habits, self-efficacy, and perceived controllability of road rage, respectively. Additionally, aggressive reaction (AR) was introduced to describe drivers’ inclination to express road rage. Then, descriptive analyses were performed to examine the connection between individual characteristics on road rage. Results exhibited these variables have different between-group correlation and significant relationships with gender, age group, education, driving years, professional or not, daily driving hours, and vehicle type. Also, outcomes from structural equation models (SEMs) demonstrated that the above four descriptive variables in the modified TPB model could be linked to drivers’ intention to exhibit road rage behaviors. Finally, countermeasures for controlling and curing road rage were proposed based on the findings.
Effect of Location and Distribution of Insulation Layers on the Dynamic Thermal Performance of Chinese Solar Greenhouse Walls

Chinese solar greenhouses (CSG) are fully passive solar greenhouses. The dynamic thermal characteristics of 15 wall configurations with one or two insulation layers were investigated numerically during clear winter days for a typical CSG design using computational fluid dynamics (CFD) models. The total wall thickness of 0.6 m and the total insulation layer thickness of 0.12 m were kept constant for all cases. For the case of a single layer of insulation, the optimum wall design consisted of (from inside to outside): 0.12 m of brick, 0.12 m of insulation, and 0.36 m of brick. For the case of two layers of insulation, the optimum wall design consisted of (from the inside to the outside): 0.12 m of brick, 0.06 m of insulation, 0.36 m of brick, and 0.06 m of insulation. This study also showed that the wall configuration having the maximum time lag and the minimum decrement factor was similar to the configurations reported by other studies, but that the maximum time lag and the minimum decrement usually used to optimize the design of insulated building walls did not result in the optimum configuration of the insulation layers in Chinese solar greenhouse walls.
Understanding the determinants of mobile banking continuance usage intention

Purpose The quality of people life and efficiency of banks can be improved by mobile banking (m-banking). The long-term success of m-banking depends on its constant use. The purpose of this paper is to investigate the determinants of m-banking continuance intention to use, using the technology continuance theory (TCT) by including the self-efficacy and channel preference. Design/methodology/approach Empirical data from 369 Malaysian users who had prior experience with mobile banking were analysed, using partial least squares technique. Findings The results confirmed that the TCT model had a high exploratory power in explaining users’ perceived usefulness (PU), satisfaction, attitude and intentions to continue to use m-banking. Furthermore, self-efficacy and channel importance were important drivers of continuance intention in the context of m-banking. According to the results, perceived ease of use has no effect on PU and attitude in the post-adoption stage. Practical implications The findings help bank managers to understand the importance of meeting customers’ needs and expectations as a prerequisite in enhancing their satisfaction and favourable attitude towards m-banking and consequently their continuance intention. Originality/value Based on the TCT model, this study contributes to the limited body of research on continuance intention to use m-banking. Furthermore, self-efficacy and channel preferences were added to the TCT model and the results confirmed the importance of enriching the TCT model to explain continuance intention to use information systems by adding contextual factors.
Mapping Themes in the Study of New Work Practices

Both shaping and shaped by technological, economic and social facets, the world of work has witnessed a wide array of changes. This review article sets out to provide a synthesis of some of the main directions and insights of existing research connected to the new world of work. In particular, we approached the topic of new work practices through four key dimensions: (1) Conceptual and methodological dimensions in the study of new work practices; (2) Spatial and temporal manifestations of new work practices in the collaborative economy; (3) Individuals, organizations and new work configurations; (4) Power and control. The review article critically discusses the future of work and argues that the ‘new’ world of work simply repeats asymmetrical power relations and inequalities that characterise work activities, with the potential of exacerbating even further disparities, inequalities and precarity.
Enhancing Stability of Microalgae Biocathode by a Partially Submerged Carbon Cloth Electrode for Bioenergy Production from Wastewater

The electricity output from microbial fuel cell (MFC) with a microalgae assisted cathode is usually higher than that with an air cathode. The output of electricity from a photosynthetic microalgae MFC was positively correlated with the dissolved oxygen (DO) level in the microalgae assisted biocathode. However, DO is highly affected by the photosynthesis of microalgae, leading to the low stability in the electricity output that easily varies with the change in microalgae growth. In this study, to improve the electricity output stability of the MFC, a partially submerged carbon cloth cathode electrode was first investigated to use oxygen from both microalgae and air, with synthetic piggery wastewater used as the anolyte and anaerobically digested swine wastewater as the catholyte. When the DO levels dropped from 13.6–14.8 to 1.0–1.6 mg/L, the working voltages in the MFCs with partially submerged electrodes remained high (256–239 mV), whereas that for the conventional completely submerged electrodes dropped from 259 to 102 mV. The working voltages (average, 297 ± 26 mV) of the MFCs with the 50% submerged electrodes were significantly (p < 0.05) higher than with other partially or completely submerged electrodes. The associated maximum lipid production from wastewater was 250 ± 42 mg/L with lipid content of 41 ± 6% dry biomass. Although the partially submerged electrode had no significant effects on lipid production or nitrogen removal in wastewater, there was significant improvement in the stability of the electricity generated under variable conditions.
Robust Calibration Procedure of a Manipulator and a 2D Laser Scanner using a 1D Calibration Target

An accurate extrinsic calibration between a robots’ exteroceptive sensors and its manipulator is essential for tasks such as mobile manipulation and tactile exploration. Especially for extrinsic calibration of a manipulators’ end effector and 2D laser scanner, state-of-the-art approaches often require complex calibration targets or sensors which need to be mounted to the end effector. Therefore, such approaches are only suitable to a limited extent for use in mobile robotics. In this paper, we present a simple but effective approach to determine the six degrees of freedom transformation between the end effector of a serial manipulator and the center of a 2D laser scanner. In contrast to other approaches, our approach requires only a 1D target for calibration. Whereas complex calibration geometries often require a tool change for calibration, our approach is also applicable using practical objects like a drill mounted to the end effector. As a consequence, a tool change is not required for recalibration for many applications anymore. To evaluate the performance of our approach, we perform the calibration based on simulated as well as real data. We compare our results against the ground truth of a physically closed transformation chain using the lidars’ CAD data.
Implications of Future Natural Gas Demand on Sugarcane Production, Land Use Change and Related Emissions in Brazil

Due to its low share of energy-related emissions, energy systems models have overlooked the implications of technological transition in the agricultural sector and its interaction in the wider energy system. This paper explores the role of agriculture intensification by using a novel agricultural-based energy systems model. The aim is to explore the future role of Brazil’s agriculture and its dynamics with other energy sectors under two carbon constraint scenarios. The main focus has been to study resource competition between sugarcane and natural gas at a country level. Results show that in order to meet the future food and bioenergy demand, the agricultural sector would start intensifying by 2030, improving productivity at the expense of higher energy demand; however, land-related emissions would be minimised due to freed-up pasture land and reduction in deforestation rates. Additionally, the development of balanced bioenergy and natural gas markets may help limit the sugarcane expansion rates, preserving up to 12.6 million hectares of forest land, with significant emissions benefits.
Energy savings due to internal façade insulation in historic buildings

– Historic buildings contribute heavily to the energy consumption of the existing European building stock. Application of internal insulation offers a possibility to improve the historic buildings’ energy performance, without compromising the buildings’ architectural appearance. The paper presents desktop analyses of potential energy savings in historic buildings, carried out using standard boundary conditions for calculation of energy savings, as prescribed in the European building energy performance certification schemes. Internal insulation of the building’s façades can potentially reduce the theoretical energy demand for space heating by 9 to 43 % compared to the energy demand of the original building if installed moisture-safe. Combined with other commonly used energy saving measures, 43–78 % reduction of the energy demand was estimated. This shows that internal insulation of external walls have the potential of contributing considerable to the overall energy savings in historic buildings and highlights the need for such measures.
Assessment of the antibacterial activity of Some traditional medicinal plants on some food-borne pathogens

Abstract: Crude preparations of four types of traditional medicinal plants used in Ethiopia, collected from local markets, were assessed for their antimicrobial activity against some food-borne pathogens. The growth or inhibition of Bacillus cereus, Staphylococcus aureus, Shigella boydii, Shigella flexineri, Salmonella typhimurium, and Escherichia coli was determined in growth media separately containing Artemisia afra (5%), Vernonia amygdalina (7%), Lepidium sativum ((2%) and Carum copticum (10%). None of the test organisms was affected by Lepidium sativum in 24 hours. B. cereus and Staph. aureus had markedly lower final counts in media containing crude preparations of Vernonia amygdalina, Carum copticum, and Artemisia afra when compared to control. Retarding effect was noted on Sh. Flexineri and Sh. Boydii in the initial stages by Vernonia amygdalina and Artemisia afra. Counts of S. typhimurium in all crude preparations were lower by about one log unit than the control until eight hours. None of the crude preparations had any effect on E. coli. The antimicrobial effect of some of the crude preparations may be considerably enhanced in traditional treatment if they are taken at four hour intervals. [Ethiop. J. Health Dev. 1999;13(3):211-216]
Mitigating the Impacts of Covert Cyber Attacks in Smart Grids Via Reconstruction of Measurement Data Utilizing Deep Denoising Autoencoders

As one of the most diversified cyber-physical systems, the smart grid has become more decumbent to cyber vulnerabilities. An intelligently crafted, covert, data-integrity assault can insert biased values into the measurements collected by a sensor network, to elude the bad data detector in the state estimator, resulting in fallacious control decisions. Thus, such an attack can compromise the secure and reliable operations of smart grids, leading to power network disruptions, economic loss, or a combination of both. To this end, in this paper, we propose a novel idea for the reconstruction of sensor-collected measurement data from power networks, by removing the impacts of the covert data-integrity attack. The proposed reconstruction scheme is based on a latterly developed, unsupervised learning algorithm called a denoising autoencoder, which learns about the robust nonlinear representations from the data to root out the bias added into the sensor measurements by a smart attacker. For a robust, multivariate reconstruction of the attacked measurements from multiple sensors, the denoising autoencoder is used. The proposed scheme was evaluated utilizing standard IEEE 14-bus, 39-bus, 57-bus, and 118-bus systems. Simulation results confirm that the proposed scheme can handle labeled and non-labeled historical measurement data and results in a reasonably good reconstruction of the measurements affected by attacks.