Miracle-dz/UniFAR-FTUs huggingface dataset:
Behind the Scenes: What is Parliamentary Performance and How Can We Measure It?

Although evaluations of members of parliaments’ (MPs) parliamentary work have gained increasing public popularity, the academic literature on the concept and measurement of parliamentary performance is surprisingly scarce. Most studies analysing (aspects of) MPs’ parliamentary performance focus on quantitative parliamentary activity indicators only, thereby neglecting the quality and effectiveness of parliamentary work, and the importance of less visible parliamentary activities. This article introduces a conceptual framework of parliamentary performance as well as a more encompassing measurement approach, and provides a first empirical test of theoretically expected underlying dimensions on 325 Belgian MPs. This study proposes an innovative method relying on the collective expertise of MPs through peer assessment while controlling for potential rater effects. I demonstrate that parliamentary performance cannot be captured by parliamentary activity indicators alone. Exploratory and confirmatory factor analyses show that apart from three factors of parliamentary activity, two more qualitative factors (content and policy-making effectiveness) can be identified. The results suggest that future evaluations of MPs’ parliamentary work may need to include more qualitative elements.
Preliminary Screening of Maize Accessions Against Common Rust Disease (Puccinia sorghi Schw) in Arsi Negele District, Ethiopia

Maize is one of the most important crops in Ethiopia. The production of the crop is threatened by a number of biotic and a biotic factor. Among biotic factors, common rust caused by Puccinia sorghi Schw, is one of destructive foliar diseases of maize in Ethiopia. A study was conducted during the main cropping season (April to November, 2016) in the field at Arsi Negele research farm, Ethiopia with the objective of screening 92 maize accessions and 2 farmer’s verities checks against common rust disease. The experiment was laid out in augmented design with no replications. Disease assessment was done as percentage of leaf area infected on individual plant at 15 days intervals starting from 55 days after planting to cropping season for 5 times. The mean values of disease incidence, severity and AUDPC were calculated and yield recorded. The higher disease percent severity and AUDPC, least yield and thousand seed weight were observed from accessions, AN-239620, AN-9195, AN-9988, AN-9991, AN-15459, AN-15460, AN-16021, AN-18121, AN-18122 and Check-1 with mean values (63.94%, 1694.5%-in days, 3.04 to 3.69 t/ha and 240 to 297g) respectively and categorized in moderately susceptible group. Conversely, the minimum percent disease severity, AUDPC, higher yield and thousand seed weight were recorded from accessions, AN-16559, AN-9987, AN-16571, AN-18104, AN-18106, AN-18121, AN2-4297, AN-913, AN-15325 AN-15326, AN-15461, AN-16276, AN-16278, AN-241584 and AN-162383, with mean values of (31.01%, 720.4%-in days, 4.81 to 5.59 t/ha and 380 to 442g) respectively and grouped in resistant category. Therefore, accessions recorded low percent disease severity and AUDPC values could be used as the resistant varieties and source of resistance to common rust for varietal development of maize.
Accounting for Sources of Information in Trade Fairs: Evidence from Portuguese Exhibitors

Trade fairs are important sources of information for decision making in marketing management. Currently, trade fairs are places where participants share useful data and information, while creating relationships between customers (visitors) and suppliers (exhibitors). However, only a limited number of studies have focused on the identification of the sources of information that exhibitors can provide for marketing managers at trade fairs. This study examines the importance of the different types of information resources that can be delivered by exhibitors to managers in order to transfer information about product and market trends. Based on the data from a survey of 172 Portuguese executives from different industries, the theoretical hypotheses are tested, using CFA (Confirmatory Factor Analysis). Consistent with our hypotheses, the results show that Direct Marketing techniques, such as face-to-face contacts and product/service demonstrations, are often used by exhibitors. Information in digital formats and demonstration in digital equipment (Digital Marketing) are also used in trade fairs to display information to potential customers. Additionally, the organization of parallel events (Event Marketing) during a trade fair supplements the package of activities developed by exhibitors to transmit and capture information for their companies. These results provide certain support for the importance of trade fairs in view of being a rich source of market information about not only new technological developments of products, but also major strengths and weaknesses of competitors, and future market trends, among other types of information needed for the marketing planning.
Simulation of flood hydrographs in urban channels: a tool for urban planning

Floods caused by extreme hydrological events and their consequences are one of the major challenges faced by local government authorities about urban planning. In this context, we studied the urban cross channel sections behaviour located in the Jatobá stream catchment, in the city of Belo Horizonte, Brazil. Different precipitation scenarios were used as input parameters for the hydraulic simulation. For this purpose, the accumulated rainfall was disaggregated and a frequency analysis was performed to compute different duration times (from 10 to 120 minutes) and return periods (from 2 to 100 years). Then, hydrological and hydraulic simulations were carried out using HEC-HMS and HEC-RAS models, respectively. The results showed that the average time until the channel overflows was 58 minutes and the average duration time for the overflow was 28 minutes. The channel overflowed in 77.14% of the simulated scenarios. The simulations were carried out for different rainfall return periods and time duration to characterize extreme events for this catchment, aiding the decision- making process and assisting in the development of strategies to improve the drainage system.
Evaluate the Optimal Future Demand of Water Consumption in Al-Anbar Province in the West of Iraq

Water is an essential source of sustaining life and used in generating electricity, agriculture, industry, and the daily domestic uses. This study was prepared to determine the water consumption of Anbar Province in the west of Iraq according to agricultural, industrial, and domestic demand. In addition, the study is evaluating the expected future water consumption by demand sites within study area. The results showed the domestic water demand will increases by 32% from 267.30 million m 3 /year in 2021 to 352.70 million m 3 per year in 2035, with a deficit of 24.5% in the year 2035. Furthermore, the study had appeared the agricultural demand was 1404.38 million m 3 /year according to the limited cultivated area, which equals 42.93% from the total available area of 221,250 hectares. The agricultural demand increases to 2611 million m 3 /year when uses all available area, and this cause occurs deficit in water demand reach to 1591 and 1715 million m 3 /year in the years 2030 and 2035 respectively. In contrast, the study referred to necessary apply other irrigation methods as drip and sprinkler irrigation, which has high irrigation efficiency. In addition, using lined channels and pipes to transport water to reduce losses by leaching and evaporation.
Metal-free or transition-metal-catalyzed one-pot synthesis of 2-aminobenzothiazoles

A series of 2-aminobenzothiazoles were synthesized by using 2-halogen-substituted anilines (halogen = Cl, Br, I) and dithiocarbamates in the presence of KOt-Bu. This simple and efficient protocol lets the reactions undergo in a smooth and rapid way to afford the corresponding 2-aminobenzothiazoles in good yields. It is noteworthy that the present process allows the construction of 2-aminobenzothiazoles from a wide range of 2-halogen-substituted aniline derivatives, including substituted 2-iodoanilines, 2-bromoanilines and 2-chloroanilines. GRAPHICAL ABSTRACT
Flow Analysis of Regenerated Silk Fibroin/Cellulose Nanofiber Suspensions via a Bioinspired Microfluidic Chip

Microfluidic spinning has been used to mimic and discover the natural spinning process of silk. However, it is still challenging to understand the orientation and alignment of silk‐spinning through microfluidic chips. Here, flow analysis is performed for a bioinspired microfluidic chip mimicking the shape of a spider's major ampullate gland and spinning duct by in situ small angle X‐ray scattering and simulations using the finite element method. A composite suspension of regenerated silk fibroin and cellulose nanofibers show higher orientation and alignment after flowing through the microfluidic chip. This confinement can be attributed to the drop in the extrusion pressure of the silk proteins and the shear and elongation forces from the anisotropic microchannel. This work reveals the microstructure−property relationship of fibers obtained through the microfluidic chip. Hence, it paves the way to uncover the mystery behind the natural spinning process and further provides comprehensive and systematic insights into preparing highly oriented artificial fibers for biomedical applications.
Analysis of Signal Processing for Gigabit Rate Wireline Communication

In this paper we mainly focus on achieving higher speed data which is about 1Gb/s over short copper loops using G.Fast technology. The use of TDD and higher bandwidth are two key features in G.Fast. Short twisted pair cable models are used to operate at relatively wider bandwidth. At higher frequencies, the problem of FEXT crosstalk becomes dominant. So to overcome these issues we are using different crosstalk cancellation techniques using various cables which provide different data rates at different frequencies and distances. Performance analysis of various crosstalk cancelation techniques has been done in this paper.
Fourier neural networks as function approximators and differential equation solvers

We present a Fourier neural network (FNN) that can be mapped directly to the Fourier decomposition. The choice of activation and loss function yields results that replicate a Fourier series expansion closely while preserving a straightforward architecture with a single hidden layer. The simplicity of this network architecture facilitates the integration with any other higher‐complexity networks, at a data pre‐ or postprocessing stage. We validate this FNN on naturally periodic smooth functions and on piecewise continuous periodic functions. We showcase the use of this FNN for modeling or solving partial differential equations with periodic boundary conditions. The main advantages of the current approach are the validity of the solution outside the training region, interpretability of the trained model, and simplicity of use.
Heroes and Hooligans: The Heterogeneity of Video Game Modders

Video games are hugely popular, generating more than twice the revenue of global movie and music industries combined. Whilst technically illegal and often carrying negative connotations, modding constitutes a moral grey area that is commonly accepted, often encouraged by proprietary owners and forum-centred gaming communities. Literature reflects a disparity between outsider and insider perceptions of modding, with a paucity of studies reflecting insider perspectives. Using Reddit forum data, this study contributes insight into perceptions of modding held by gamers and ‘modders’, as described in their words and their territory. Thematic analysis revealed four main themes relating to unfairness in the vendor community, modders as antagonists, differences between modders and modding as forms of self-defence. Conclusions include that modding appears to have both pro- and antisocial applications, but many people and organisations demonise modders as a homogeneous group, which may encourage antisocial behaviours.
Novel Authentication and Secure Trust based RPL Routing in Mobile sink supported Internet of Things

ABSTRACT In the modern era, prevalence of the Internet of Things (IoT) devices that have de facto protocol as IPv6 routing protocol for low power and lossy networks (RPL). Yet, RPL protocol is vulnerable to many attacks such as rank attack, password spoofing and more. To this end, most of the works have focused their research on securing the RPL-based IoT network. However, still there exist downsides such as high energy consumption, lack of effective authentication and high packet losses. Motivated by these preceding defects, this paper proposes the Novel Authentication and Secure Trust-based RPL Routing in Mobile sink-supported Internet of Things (SecRPL-MS). At first, SecRPL-MS performs a registration process where all IoT nodes in the network register themselves in the security entity. In this work, the frequent death of IoT nodes is alleviated through deploying mobile sink in the network. If any grid member (GM) node wants to transmit their data to the grid head (GH) node, then it must undergo authentication process. Secure routing is adopted in RPL by utilising the sail fish optimisation algorithm. Each GM node encrypts its sensed data using the prince algorithm before transmitting it to the GH node. The moving points are selected for the mobile sink using the Quantum Inspired Neural Network (QINN) algorithm. This proposed SecRPL-MS performance is evaluated using the Network Simulator 3 (NS3) in terms of the Packet Delivery Ratio (%), Delay (ms), Energy Consumption (mJ), Key Generation Time (ms) and Malicious Node Detection Accuracy (%). The proposed SecRPL-Ms outperforms 23% of malicious node detection accuracy when compared to existing systems, which represent the proposed SecRPL-MS system providing high security by mitigating the following attacks such as rank attack, Sybil attack, blackhole attack and man in the middle attack.
Aperiodic Sampled-Data Takagi–Sugeno Fuzzy Extended State Observer for a Class of Uncertain Nonlinear Systems With External Disturbance and Unmodeled Dynamics

For the extended state observer (ESO) design, the most challenging issue is to exploit efficient nonlinear observation performance, while maintaining desirable linear numerical tractability under noncontinuous transmission. In this article, in order to address this issue, the sampled-data ESO design is investigated for a class of uncertain nonlinear systems. First, based on the fuzzy modeling approach with reasonable fuzzy rules and sets, the nonlinear functions of the ESO are suitably approximated by several local linear models weighted by membership functions. Then, a novel methodology of Takagi–Sugeno fuzzy extended state observer (TSFESO) is developed for the first time. By virtue of fuzzy membership functions, the estimating action is implemented in a nonlinear pattern, while taking advantages of Takagi–Sugeno fuzzy formulation, the observer gains can be calculated in a linear manner. As a result, the nonlinear estimating efficiency and linear numerical tractability are integrated in a unified framework. Second, for the aperiodic sampling case, the exponential convergence criterion for the TSFESO is presented by constructing a sampling- and time-dependent Lyapunov functional, in which the information on sampling action is taken into full consideration for desirable feasibility. Moreover, the observer design approach is also put forward. Finally, the superiorities and effectiveness of the proposed approaches are demonstrated by numerical examples.
Multi-Touch Interaction Generation Device by Spatiotemporally Switching Electrodes

With the spread of devices equipped with touch panels, such as smartphones, tablets, and laptops, the opportunity for users to perform touch interaction has increased. In this paper, we constructed a device that generates multi-touch interactions to realize high-speed, continuous, or hands-free touch input on a touch panel. The proposed device consists of an electrode sheet printed with multiple electrodes using conductive ink and a voltage control board, and generates eight multi-touch interactions: tap, double-tap, long-press, press-and-tap, swipe, pinch-in, pinch-out, and rotation, by changing the capacitance of the touch panel in time and space. In preliminary experiments, we investigated the appropriate electrode size and spacing for generating multi-touch interactions, and then implemented the device. From the evaluation experiments, it was confirmed that the proposed device can generate multi-touch interactions with high accuracy. As a result, tap, press-and-tap, swipe, pinch-in, pinch-out, and rotation can be generated with a success rate of 100%. It was confirmed that all the multi-touch interactions evaluated by the proposed device could be generated with high accuracy and acceptable speed.
TDMA scheduling schemes targeting high channel utilization for energy-harvesting wireless sensor networks

As a contention-free channel access protocol, Time Division Multiple Access (TDMA) is widely applied in Energy Harvesting Wireless Sensor Networks (EH-WSNs) due to ease of implementation. TDMA scheduling in EH-WSNs faces the problem of low channel utilization since time slots assigned to some nodes may not be used by them due to short-age of energy or data. It is important to design TDMA scheduling schemes that enhance channel utilization. In this paper, the Fixed Frame Size Scheme (FFSS) and the Adaptive Frame Size Scheme (AFSS) are proposed to improve channel utilization of EH-WSNs. The FFSS aims at the optimal TDMA slot assignment for the TDMA scheduling with ﬁxed frame size, and the AFSS considers the TDMA with variable frame size and targets both the optimal frame size and the optimal slot assignment. The optimization problems maximizing channel utilization are formulated for the FFSS and the AFSS, respectively, which take the upcoming energy and data into account. The optimization problems are transformed into assignment-like problems and solved by the Hungarian-based algorithm in polynomial time. Simulation results indicate that the proposed FFSS and AFSS can considerably improve channel utilization in the EH-WSNs compared with the existing TDMA scheduling schemes.
Automated Probabilistic Analysis and Parametric Modelling of the Seasonal-Diurnal Wind Vector

A refined and extended version of the Offset Elliptical Normal mixture model has been developed to parameterise the seasonal diurnal wind vector automatically. Automated using R scripts, the method eliminates any potential risk of confirmation bias posed by the manual supervision in the original method. Refinements to the method include the latest algorithms for clustering of Gaussian mixtures, with Bayesian regularisation to set the number of components and to limit the predisposition to overfit. A new extension uses fuzzy logic to evaluate the probability distributions, autocovariances and spectra of the random perturbations around the mean seasonal-diurnal variations for each component of the mixture. These additional parameters allow the predictions of the OEN model to be validated and its automated application demonstrated using the hourly METAR reports of mean wind speeds at Adelaide, South Australia, showing significant improvements over the previously published analysis. The OEN mixture model is directly applicable to a wide range of wind engineering applications where seasonal and diurnal variation is of importance.
Mineral enrichment in carrot with different sources and doses of zinc

A deficiência de zinco (Zn) no solo e plantas e seu baixo estado nutricional na população estimulam estudos sobre enriquecimento de produtos agrícolas. A cenoura tem potencial para o enriquecimento, pois é um vegetal comumente consumido. O objetivo deste estudo foi avaliar as fontes de Zn (ZnO, ZnSO 4 ou ZnEDTA) e a dose (0, 5, 10, 20 and 30 mg dm) aplicadas no solo a fim de aumentar a concentração do mineral na parte comestível da cenoura. ZnSO 4 foi mais adequado para esse papel, porque apresentou maior acúmulo com o aumento da dose de tratamento. A melhor dose foi 19,45 mg dm de ZnSO 4, a qual apresentou maior teor de Zn nas cenouras. Além disso, este tratamento aumentou o teor de Zn na raiz em 7 vezes comparado com o controle. O baixo custo da produção de cenouras enriquecidas com Zn as torna uma hortaliça potencial para a redução da deficiência deste micronutriente na nutrição populacional.
3-D Gabor Convolutional Neural Network for Hyperspectral Image Classification

Due to the detailed spectral information through hundreds of narrow spectral bands provided by hyperspectral image (HSI) data, it can be employed to accurately classify diverse materials of interest, which is one of the core applications of hyperspectral remote sensing technology. In recent years, with the rapid development of deep learning, convolutional neural networks (CNNs) have been successfully applied in many fields, including HSI classification. However, the random gradient descent-based parameter updating scheme is too general and leading to the inefficiency of CNN models. Moreover, the high dimensionality and limited training samples of HSI data also exacerbate the overfitting problem. To tackle these issues, in this article, a novel deep network with multilayer and multibranch architecture, named 3-D Gabor CNN (3DG-CNN), is proposed for HSI classification. More precisely, since the predefined 3-D Gabor filters in multiple scales and orientations could well characterize the internal spatial–spectral structure of HSI data from various perspectives, the 3-D Gabor-modulated kernels (3-D GMKs) are employed to replace the random initialization kernels. Moreover, the specially designed multibranch architecture enables the network to better integrating the scalable property of 3-D Gabor filters; thus, the representative ability and robustness of the extracted features can be greatly improved. Alternatively, the number of network parameters is substantially reduced due to the incorporation of 3-D Gabor modulation, relieving the training complexity and also alleviating the training process from overfitting. Experimental results on four real HSI datasets (including two newly released ones in the literature) have demonstrated that the proposed 3DG-CNN model can achieve better performance than several widely used machine-learning-based and deep-learning-based approaches. For the sake of reproducibility, the codes of the proposed 3DG-CNN model are available at http://jiasen.tech/papers/.
Magnesium-induced biofilm development in Arthrobacter sp. SUK 1201 and removal of hexavalent chromium

Abstract This study reports the influence of Mg ions on the development and architecture of biofilms by a chromium resistant and reducing bacterium Arthrobacter sp. SUK 1201 and their utilization in the removal of toxic hexavalent chromium. Among the different metal ions tested, Mg(II) greatly influenced the biofilm growth in peptone yeast extract glucose medium. Both Scanning and Confocal Laser Scanning Microscopy revealed that biofilms formed under the induction of Mg(II) had characteristic higher cell densities. The cells remain embedded in thick porous layers of extracellular polymeric substances as evident from the fluorescein isothiocyanate labeled lectin concanavalin A and 4, 6- diamino-2-phenylindole staining. COMSTAT analysis also indicated maximum thickness and roughness coefficient of the biofilm grown in presence of Mg(II). Biofilms of Arthrobacter sp. SUK 1201 developed under such Mg (II) influenced condition showed complete removal of 0.5 mM Cr(VI) in mineral salts medium. The biofilm of this isolate grown in presence of Mg(II) was also able to remove 60µM Cr(VI) from mine seepage water suggesting its possible implication in effective bioremediation of chromium polluted environments.