Miracle-dz/UniFAR-FTUs huggingface dataset:
The ability of young learners to construct word meaning in context

This study examines young English readers’ ability to infer word meanings in context and to use metacognitive knowledge for constructing word meanings in relation to their reading performance. The participants were 61 fourth-grade students in the United States, comprising 24 monolingual English-speaking (ME) students and 37 English-as-a-second-language (L2) students; each group was also divided into strong and emergent readers in English. Participants were asked to read aloud paragraphs containing words unfamiliar to them in two different contextual conditions (i.e., explicit and implicit conditions), to guess the unfamiliar word meanings, and to tell a teacher how they arrived at the inferred meanings. Quantitative analyses found significant differences between strong and emergent readers in their oral fluency as well as in their ability to infer word meanings and articulate their use of metacognitive knowledge. Although significant differences were found in the ability to infer word meanings and the use of metacognitive reasoning between ME and L2 students, such differences disappeared after controlling for the size of students’ receptive vocabulary. Qualitative analyses also revealed differences in the kinds of knowledge and strategies that strong and emergent readers relied on when constructing the meaning of unknown words in both explicit and implicit contexts.
Studying the Effects of Peer-to-Peer Sharing Economy Platforms on Society

Peer-to-peer sharing economy platforms potentially have big effects on values in society. Policymakers need to develop governance arrangements to benefit from the positive effects, while simultaneously mitigate the negative effects. This requires having a structured overview of the effects of these platforms on the diversity of values that are involved. Currently no theoretical overview of these effects on values is available. The objective of this article is to structure the research into the effects of sharing economy platforms. We use a theoretical mapping that was developed by using a Grounded Theory approach. By positioning the literature onto the map, we derived an overview of the extend in which each effected value has been studied so far. Based on this mapping, we propose five research themes into specific effects of peer-to-peer sharing economy platforms: social values, consumer and societal risks, working conditions and labor market dynamics, environmental sustainability and innovation.
ePubWU Institutional Repository

Purpose: Advertisers setting up search engine advertising campaigns for the first time need to place bids on keywords, but typically lack experience and data to determine ranks that maximize a keyword’s profit (generally referred to as a cold-start problem). This article aims at solving the problem of bidding on keywords in newly set-up search engine advertising campaigns. Approach: We suggest that advertisers collect data from the Google Keyword Planner to obtain precise estimates of the percentage increases in prices per click and clickthrough rates, which are needed to calculate optimal bids (exact approach). Together with the profit contribution per conversion and the conversion rate, the advertiser might then set bids that maximize profit. In case advertisers cannot afford to collect the required data, we suggest two proxy approaches and evaluate their performance using the exact approach as a benchmark. Findings: The empirical study shows that both proxy approaches perform reasonably well―the easier approach to implement (proxy 2) sometimes performs even better than the more sophisticated one (proxy 1). As a consequence, advertisers might just use this very simple proxy when bidding on keywords in newly set-up SEA campaigns. Originality/value: This research extends the stream of literature on how to determine optimal bids, which so far focuses on campaigns that are already running and where the required data to calculate bids is already available. This research offers a novel approach of determining bids when advertisers lack the aforementioned information.
Facile Fabrication of Cellulosic Paper- based Composites with Temperature- controlled Hydrophobicity and Excellent Mechanical Strength

In this paper, we presented a novel strategy to employ a plantderived carbohydrate polymer, i. e. , cellulose, to prepare a hydrophobic composite. Cellulose was used as a scaffold, and ethylene-propylene side by side (ES) fiber was thermally melted and then coated on the cellulose surface to achieve hydrophobicity. Experimental results revealed that the thermocoating ES fibers greatly increased the water contact angle of the cellulose scaffold from 25° to 153° while simultaneously enhanced the wet tensile strength of the composite approximately 6.7-fold (drying temperature of 170°C) compared with the pure cellulose paper. In particular, compared with other related research, the prepared cellulose-based composite possessed excellent hydrophobicity and superior mechanical strength, which introduces a new chemical engineering approach to prepare hydrophobic cellulose-based functional materials.
TurboNet: Faithfully Emulating Networks with Programmable Switches

Faithfully emulating networks is critical for verifying the correctness and effectiveness of new networking-related designs. Existing network experiment platforms either cannot faithfully emulate functionality and performance of production networks or cannot scale well because of cost limitations. In this paper, we propose TurboNet, a new network emulator that leverages one programmable switch to enable faithful emulation of both network data plane and control plane. For data plane emulation, we present a series of key designs such as port mapper, queue mapper, and delayed queue to emulate network topologies and performance metrics with high flexibility and accuracy. For control plane emulation, we support static routing configurations, distributed routing agents, and the centralized routing controller. Meanwhile, we provide API for operators to simplify network emulation tasks. We implement TurboNet on a Tofino switch. The evaluation results show that: (1) TurboNet can flexibly emulate various topologies such as the 8-ary fat-tree on the data plane and support about 200 BGP agents with 25% CPU usage on the control plane; (2) TurboNet can accurately emulate different network performance metrics, including 400Gbps linerate background traffic injection, as small as 10–8 link loss, and microsecond-level to millisecond-level link delay.
STUDY THE BLDC MOTORS AND ITS USAGE OF VARIOUS ORGANIZATIONS FOR BETTER EFFECTIVENESS BanavathVenkateswarlu

The modern approach of static frequency transformation has freed the enlistment motor from its authentic part as a rigid speed machine. The inalienable gifts of movable frequency operation can't be finished unless a suitable management technique is used. The choice of technology is essential in pivotal the attributes and execution of the driving framework. Furthermore this paper presents that the office device has almost no abundance current ability; all through ordinary operation the management technique should ensure that motor operation is confined to the locales of high torsion per ampere, in this manner coordinating the electrical converter appraisals and limiting the framework loses. Over-burden or fault conditions ought to be taken care of by inconspicuous management rather than over style.
A New Resonant Capacitor Diode Voltage Multiplier Topology for Pulsed Power Application

Today, the pulsed power systems have been employed in many applications. To meet the requirement of user, the pulse generator should enjoy the advantages of compactness, high flexibility, high pulse repetition rate and cost efficiency. Among all of converters that can be used to generate high voltage pulses, capacitance diode voltage multiplier (CDVM) is a good candidate to meet the mentioned requirements. In this paper a new converter that is combination of full-bridge inverter, CDVM and resonant circuit is proposed. The performance of developed converter is compared with the conventional circuits and is demonstrated via simulation in MATLAB/SIMULINK. Experimental tests on a prototype setup have verified the capability of this topology.
Improving the Performance of Block-based DRAM Caches Via Tag-Data Decoupling

In-package DRAM-based Last-Level-Caches (LLCs) that cache data in small chunks (i.e., blocks) are promising for improving system performance due to their efficient main memory bandwidth utilization. However, in these high-capacity DRAM caches, managing metadata (i.e., tags) at low cost is challenging. Storing the tags in SRAM has the advantage of quick tag access but is impractical due to a large area overhead. Storing the tags in DRAM reduces the area overhead but incurs tag serialization latency for an associative LLC design, which is inevitable for achieving high cache hit rate. To address the area and latency overhead problem, we propose a block-based DRAM LLC design that decouples tag and data into two regions in DRAM. Our design stores the tags in a latency-optimized DRAM region as the tags are accessed more often than the data. In contrast, we optimize the data region for area efficiency and map spatially-adjacent cache blocks to the same DRAM row to exploit spatial locality. Our design mitigates the tag serialization latency of existing associative DRAM LLCs via selective in-DRAM tag comparison, which overlaps the latency of tag and data accesses. This efficiently enables LLC bypassing via a novel DRAM Absence Table (DAT) that not only provides fast LLC miss detection but also reduces in-package bandwidth requirements. Our evaluation using SPEC2006 benchmarks shows that our tag-data decoupled LLC improves system performance by 11.7 percent compared to a state-of-the-art direct-mapped LLC design and by 7.2 percent compared to an existing associative LLC design.
Ascorbic Acid Reduces the Phytotoxic Effects of Selenium on Rice (Oryza Sativa L.) by Up-Regulation of Antioxidative and Metal-Tolerance Mechanisms

Selenium (Se) in trace concentrations (<1mg/kg) is proved to be beneficial for many plant species, but is considered toxic at higher concentrations and adversely affects the potential growth and yield of plants. Hence, measures are needed to minimise the phyto-toxicity of Se on plants. Ascorbic acid (Asc) has vital roles as a redox buffer, a strong antioxidant, regulator of enzymes of photosynthesis, phytohormones, cell division and growth in plants. In the present study, rice, which is a sensitive to Se-stress, was grown under controlled laboratory conditions (30/25; 15/9h, light/ dark; light intensity: 350 umol m-2 s-1, RH: 65-70%) with selenium (as sodium selenate; 1, 2.5 and 5 ppm) in the absence or presence of 50 μM Asc for ten days in half-strength Hoagland solution. Se at 2.5 ppm concentration resulted in 22.6 and 30% inhibition of roots and shoots, respectively, which increased markedly at 5.0 ppm (47% for roots 60% for shoots). Addition of Asc to the rice plants treated with 2.5 and 5.0 ppm Se resulted in 36 and 21% improvement in root growth and 28 and 38% increase in shoot growth, respectively, over the plants growing without Se. The uptake of Se increased with rise in its exogenous concentration but it was not affected by Asc application. Asc-supplemented plants showed significant prevention of damage caused by Se to membranes, chlorophyll and PSII function. A significant reduction in oxidative stress, measured as malondialdehyde and hydrogen peroxide content, was observed in the presence of Asc in Se-stressed plants, which was found to be associated with improvement in activities of enzymatic (pertinently, ascorbate peroxidase, glutathione peroxidase) and non-enzymatic (ascorbic acid, reduced glutathione) antioxidants. Furthermore, Se-stressed plants supplemented with Asc showed significant up-regulation of metallothioneins, total thiols and glutathione-stransferase (GST) activity to reduce the toxic effects of Se.
The study evolution of the structure formation of the foil workpiece during rolling screw rollers and longitudinal-wedge mill (LWM)

S. A. Mashekov, (mashekov.1957@mail.ru), Satbayev University, Almaty, Kazakhstan G. A. Smailova, Kazakh Agrarian University, Almaty, Kazakhstan M. S. Kulgildinov, Kazakh Academy of Transport and Communications named after M. Tynyshpayev, Almaty, Kazakhstan A. Zhauyt, K. S. Chezhimbayeva, K. T. Tergemes, Almaty University of Power Engineering and Telecommunications, Almaty, Kazakhstan T. M. Buzauova, Karaganda State Technical University, Kazakhstan The article presents the results of studies of the influence number of passes and single crimps during rolling strips, respectively, in helical rolls and longitudinal-wedge mill on the parameters of the microstructure of aluminum alloy 2017. Comparative assessment grain sizes of ultrafine-grained structure after rolling strips with different passes in the helical rolls and deformation of the longitudinal-wedge mill at a deformation temperature of 400 °C. It is shown that the aluminum alloy sheet material 2017 provides the formation of a homogeneous ultrafine grain structure with a grain size of about 240 nm, which leads to an increase strength and plastic properties of the alloy.
In vitro clonal propagation and evaluation of antibacterial activity of Benghal dayflower-Commelina benghalensis L.

An efficient protocol for in vitro propagation of Commelina benghalensis was developed. Nodal segments were showed the superb explants in performance for shoot proliferation than other explants. On the other hand, BAP with auxin was better combination. The maximum (90.52) number of explants response and the highest (23.25) number of shoots per plant were obtained from nodal segments on MS medium fortified with 3.0 mg/l BAP+0.1 mg/l IBA. The highest shoot length (17.25 cm) was achieved on MS medium containing 3.0mg/l BAP+0.5mg/l IBA. In vitro proliferated shoots were transferred to full and half strength of MS media where 1.5 mg/l IBA on full strength of MS media was the best to fit for the maximum number (12.69) of roots formation per micro-shoot. Well rooted plantlets were transferred to soil and successfully acclimatized with 97% survival rate. Three extracts i.e. methanol, ethanol, Petroleum ether of C. benghalensis L and four concentrations of each extracts were used against five gram (+ve) and five gram (-ve) bacterial species for the screening of antibacterial activity. Ethanol extracts was the superior in performance. The susceptibility of tested pathogenic bacterial species was increasing compare with increasing of extracts concentration with few exceptions. The highest zone of inhibition was obtained against S. aureus (17.50 mm) and P. aeruginosa (17.44 mm) at 800 mg/l dose level of extracts. It was also noticed that Gram (+ve) bacterial species are more susceptible to Benghal dayflower crude extracts than Gram (-ve) bacterial species.
Study on the transient conjugated heat transfer

This paper presents the succession of heat and/or mass driven natural convection processes along a uniform temperature and concentration vertical wall embedded in a Darcy doubly stratified porous medium. Using the scale analysis of the governing equations, three possible heat transfer regimes are discovered, presented and quantified through the temperature, concentration and velocity boundary layer thickness, magnitude and location. If ST and SC are the porous medium thermal and concentration stratification coefficients and if N is the buoyancy ratio, then we can encounter these possibilities: a heat driven convection regime (HDC) along the wall if T C S S  ; a mass driven convection regime (MDC) along the wall if 1 N S S C T    ; a HDC−MDC succession in all the other cases. The finite difference method is used to solve the governing equations and to verify the results on the heat transfer regimes succession for one particular case.
Driving behavior classification for Heavy-Duty vehicles using LSTM Networks

Despite growing autonomous driving trend, human is still a major factor in the current vehicle technology. Drivers have a great impact on both fuel economy and accident prevention. Therefore, identi cation and evaluation of driving behaviors are crucial to improve the performance, safety and energy management of vehicle technologies, particularly for heavy-duty vehicles. In this thesis, several driving behaviors with di erent acceleration and car following characteristics are generated on a realistic truck model in IPG's TruckMaker simulation environment. A Long Short Term Memory (LSTM) classi er is then utilized to recognize driving behaviors. First, six drivers are de ned based on their longitudinal and lateral acceleration limits. The classi er is trained using driving signals acquired from the simulated truck which follows an arti cial training road with di erent trailer loads. The training road is designed to cover possible road curves that can be seen in highways. The model is tested with driving signals that are collected from a realistic road using the same method. Then, three drivers (calm, normal and aggressive) are de ned based on their longitudinal acceleration pro les in car following and the classi er is trained and tested using driving signals of these drivers in di erent tra c scenarios. Results show that the proposed LSTM classi er is capable of successfully capturing the dynamic relations encoded in driving signals and recognizing di erent driving behaviors in small time samples
Weld Defect Radiographic Image Segmentation with Finite Mixture Model (FMM)

— Image segmentation is an important task in computer vision. This paper aims at studying two image segmentation methods based on the mixture of two probability density functions. We explore here the exploitation of a Finite Mixture Model (FMM), particularly Gaussian and Student’s t - mixtures models (GMM, SMM) in histogram classification-based image segmentation. The expectation maximization (EM) algorithm is used to estimate the parameters of each model that maximize the log-likelihood function. Experiments have been conducted to segment real industrial radiography images. Comparison of results is achieved for GMM and SMM image segmentation. The obtained results show that the SMM is more robust that the GMM when segmenting real industrial radiography images.
Approaches to Understanding the Roles of Insect Defoliators in Forest Ecosystems

Forest insect defoliators have traditionally been viewed as pests because they damage their host plants, causing reduced growth and reproduction or even mortality. However, many forest insect defoliators are endemic species; they have coevolved with their hosts over thousands of years, ancl they are important components of the forest ecosystem. We need to develop a better understanding of the roles that insect herbivores playas recyclers of nutrients, agents of disturbance,: members of food chains, and regulators of the productivity, diversity and density of plants. I review some of the empirical approaches that have been used by other scientists to investigate the roles of insect defoliators as recyclers of nutrients and regulators of primary production. These include: 1) Simulating the effects of herbivory on forest biomass production; 2) Estimating bioelement transfers by insect herbivores; and 3) Testing the effects of herbivore density on primary production, nutrient turnover, and litter decomposition in forest ecosystems. I also present some ideas I have on using greenhouse experiments to investigate these roles for the western spruce budworm (Choristoneura occidentalis)/Douglas-fir (Psuedotsuga menziesiJ) model system I am working with. The strengths and weaknesses of the various research approaches are compared.
Translation Invariant Wavelet Based Noise Reduction Using a New Smooth Nonlinear Improved Thresholding Function

In this paper, a new type of thresholding function is introduced for wavelet based image de-noising. Here we combined the new smooth nonlinear improved thresholding function with translation invariant wavelet transform (TIWT). Unlike the common thresholding functions (hard and soft thresholding), the new proposed function is smooth and nonlinear. Applying this thresholding function on wavelet transform provides us with better resolution and higher peak signal to noise ratio (PSNR) in comparison with some other available techniques in image de-noising. The proposed method achieves up to 2.45 dB improvement over the state-of-the-art for de-noising ‘Boat’ image.
Forecasting the Final Ranking in Competitions with a Premature Ending due to COVID-19

We study an alternative approach to determine the final league table in football competitions with a premature ending. For several countries, a premature ending of the 2019/2020 football season has occurred due to the COVID-19 pandemic. We propose a model-based method as a possible alternative to the use of the incomplete standings to determine the final table. This method measures the performance of the teams in the matches of the season that have been played and predicts the remaining non-played matches through a paired-comparison model. The main advantage of the method compared to the incomplete standings is that it takes account of the bias in the performance measure due to the schedule of the matches in a season. Therefore, the resulting ranking of the teams based on our proposed method can be regarded as more fair in this respect. A forecasting study based on historical data of seven of the main European competitions is used to validate the method. The empirical results suggest that the model-based approach produces more accurate predictions of the true final standings than those based on the incomplete standings.
Why Are Open Ascending Auctions Popular? The Role of Information Aggregation and Behavioral Biases

The popularity of open ascending auctions is often attributed to the fact that openly observable bidding allows to aggregate dispersed information. Another reason behind the frequent utilization of open auction formats may be that they activate revenue enhancing biases. In an experiment, we compare three auctions that differ in how much information is revealed and in the potential activation of behavioral biases: (i) the ascending Vickrey auction, a closed format; and two open formats, (ii) the Japanese–English auction, and (iii) the Oral Outcry auction. Even though bidders react to information conveyed in others' bids, information aggregation fails in both open formats. In contrast, the Oral Outcry raises higher revenue than the other two formats by stimulating bidders to submit unprofitable jump bids and triggering a quasi‐endowment effect.