Miracle-dz/UniFAR-FTUs huggingface dataset:
Studying attitudes to English usage1

Attitudes to English Usage is the title of a book published in 1970 by W. H. Mittins, Mary Salu, Mary Edminson and Sheila Coyne from the University of Newcastle upon Tyne that reported on an enquiry held among some 450 informants concerning the acceptability of 55 usage items. These items had been selected because they were at the time ‘subject to variation in practice and dispute in theory’ (Mittins et al., 1970: 4), and they include sentences like He refused to even think about it, It looked like it will rain and Everyone has their off-days. In each case the offensive feature had been highlighted so that informants would know what they had to comment on: to even think (a split infinitive), the use of like for as if, and of their with a singular antecedent (everyone). For fifty sentences the informants had to indicate acceptability in informal speech, informal writing, formal speech and formal writing, and for the remaining five only for informal and formal writing, since usage of these items was believed to be restricted to writing (1970: 4). The sentences were subsequently ranged from highest general acceptability (did not do as well as) to lowest (veryunique), and correlations were calculated with the occupation of the informants (students, teachers, lecturers, examiners and non-educationists), while the items were also classified as colloquial (pretty reliable), etymological (data is), grammatical (did it quicker) and lexical/semantic (inferred/implied), or as language myths, ‘where the censorious tend to invoke a prescription of dubious authority’ (dangling participles) (1970: 15). The main part of the book dealt with the individual constructions, analysing the reasons for their status as debated usage items and providing further historical context in the process.
Trials for Alleviating The Problems of Poor Setting, Uneven Colouration of Berries and Fruit Quality Impaired of Crimson Seedless Grapevines

This study was carried out during 2011 and 2012 seasons to examine the effect of spraying ethrel at 300 ppm either alone or in combinations with potassin at 0.1 %, orthophosphoric acid at 0.1 %, magnesium sulphate at 0.1 %, boric acid at 0.05 % and potassium silicate (Si) at 0.05 % on alleviating yield decline, uneven berries colouration and impaired fruit quality problems in Crimson seedless grapevines grown under Minia region conditions. Using ethrel alone had no effect on berry setting %, yield, cluster weight as well as berry weight and dimensions, while it was very effective in enhancing red berries %, T.S. S %, total sugars %, T.S. S/ acid and berries peel content of anthocyanins in relative to the check treatment. Maturation date was also greatly advanced with ethrel treatments. Total acidity %, percentages of pink and green berries, chlorophylls a & b and total carotenoids in the peels tended to reduce with ethrel application. Using K, P, Mg, B or Si fertilizers along with ethrel effectively enhanced yield, berries colouration as well as physical and chemical characteristics of the berries comparing with using ethrel alone. The promoting effect of these nutrients on yield and quality could be arranged as follows in ascending order K, P, Mg, B and Si. Four sprays of a mixture containing potassin at 0.1 %, orthophosphoric acid at 0.1 %, magnesium sulphate at 0.1 %, boric acid at 0.05 % and potassium silicate at 0.05 % in addition to one spray of ethrel at 300 ppm applied only with the fourth spray of nutrients was responsible for improving yield quantitively and qualitatively and at the same time for reducing the problems of poor setting and uneven colouration of berries of Crimson seedless grapevines.
REJOINDER

We feel privileged that a number of renowned researchers in the field of unit root testing have commented on our paper. It is the valuable contributions of researchers such as these that have supplied the stimulation and motivation for the current paper, and we gratefully acknowledge this debt. The five sets of comments not only address those matters concerning unit root testing under uncertainty regarding linear trends and initial conditions, as are directly dealt with in the paper, but also suggest thought-provoking directions in which analyses of these issues might be taken forward. Here, we attempt to respond to some of the issues raised.
ReviewHPMA Copolymer-Based Nanomedicines in Controlled Drug DeliveryPetr Chytil

Recently, numerous polymer materials have been employed as drug carrier systems in medicinal research, and their detailed properties have been thoroughly evaluated. Water-soluble polymer carriers play a significant role between these studied polymer systems as they are advantageously applied as carriers of low-molecular-weight drugs and compounds, e.g., cytostatic agents, anti-inflammatory drugs, antimicrobial molecules, or multidrug resistance inhibitors. Covalent attachment of carried molecules using a biodegradable spacer is strongly preferred, as such design ensures the controlled release of the drug in the place of a desired pharmacological effect in a reasonable time-dependent manner. Importantly, the synthetic polymer biomaterials based on N-(2hydroxypropyl) methacrylamide (HPMA) copolymers are recognized drug carriers with unique properties that nominate them among the most serious nanomedicines candidates for human clinical trials. This review focuses on advances in the development of HPMA copolymer-based nanomedicines within the passive and active targeting into the place of desired pharmacological effect, tumors, inflammation or bacterial infection sites. Specifically, this review highlights the safety issues of HPMA polymer-based drug carriers concerning the structure of nanomedicines. The main impact consists of the improvement of targeting ability, especially concerning the enhanced and permeability retention (EPR) effect.
A Comprehensive Review on Secure Routing in Internet of Things: Mitigation Methods and Trust-Based Approaches

Internet of Things (IoT) is a network of “things,” connected via Internet, to collect and exchange data. These “things” can be sensors, actuators, smartphones, wearables, computers, or any object that is interconnected to provide specific services. Similarly, wireless sensor network (WSN), as a part of IoT, forwards the gathered data after sensing any event. The scalability and heterogeneity of IoT offer limited protection and is prone to diverse attacks, including WSN-inherited attacks. Moreover, IPv6 routing protocol for low power and lossy networks (RPL), a de facto routing protocol for IoT networks, also suffers from certain vulnerabilities based on its features and functionalities. Researchers have proposed various mitigation mechanisms for secure networks and routing in IoT. Recently, trust-based approaches have gained tremendous interest from the research community to embed security in IoT networks and routing protocols. In the existing literature, several trust models have been introduced according to the security needs of the IoT system, such as SecTrust, DCTM-IoT, CTRUST, etc. In this research, security issues and requirements of IoT networks and RPL routing protocol are studied with respect to various attacks, such as Blackhole, Spoofing, Rank, etc. Additionally, various mitigation methods and significance of trust models in IoT for secure routing are analyzed. Further, trust metrics in IoT environments, including the open issues and research challenges, as well as the implication of trust as a security paradigm in IoT networks and routing protocols are discussed.
A Home Charging System for EVs Using Vienna Based Modified Cuk Converter and LLC Resonant Converter

This paper presents home charging system for e-rickshaw with two stage power conversion. The charging system has AC-DC and DC-DC power conversion stage with an isolation transformer. The AC-DC power conversion is made by modified Cuk converter based on Vienna rectification, which is used to maintain power quality according to IEC 61000-3-2 international standard and to maintain constant DC-link with the variation in AC power supply. The output of primary stage is fed to split DC-link. The second stage has half bridge isolated converter with passive rectification on secondary side. This DC-DC power stage is used to control the charging of battery of EV, the charging control is made through frequency modulation. The change in switching frequency changes the power transfer with the variation in effective value in transfer inductance. In order to determine performance of front end converter, the state space model is developed and its frequency response Bode plot is determined with designed parameters under both open and closed loop conditions. For this, a 1.5 kW EV charging system is designed and simulated on MATLAB/Simulink and simulation results at different input and output conditions show the effectiveness of charging system.
UNet++-Based Multi-Channel Speech Dereverberation and Distant Speech Recognition

We propose a novel approach of using a newly appeared fully convolutional network (FCN) architecture, UNet++, for multichannel speech dereverberation and distant speech recognition (DSR). While the previous FCN architecture UNet is good at utilizing time-frequency structures of speech, UNet++ offers better robustness in network depths and skip connections. For DSR, UNet++ serves as a feature enhancement front-end, and the enhanced speech features are used for acoustic model training and recognition. We also propose a frequency-dependent convolution scheme (FDCS), resulting in new variants of UNet and UNet++. We present DSR results from the multiple distant microphone (MDM) datasets of AMI meeting corpus, and compare the performance of UNet++ with UNet and weighted prediction error (WPE). Our results demonstrate that for DSR, the UNet++-based approaches provide large word error rate (WER) reductions over its UNetand WPE-based counterparts. The UNet++ with WPE preprocessing and 4-channel input achieves the lowest WERs. The dereverberation results are also measured by speech-to-dereverberation modulation energy ratio (SRMR), from which large gains of UNet++ over UNet and WPE are also observed.
Chemical Absorption of Carbon Dioxide into Glycidyl Methacrylate Solution with Tetrabutylammonium Bromide

Abstract Absorption of carbon dioxide was carried out in a semi‐batch stirred tank of glycidyl methacrylate solution with tetrabutylammonium bromide as a catalyst at 101.3 kPa. The measured rate of absorption of carbon dioxide was used to obtain the reaction kinetics by the mass transfer mechanism accompanied by the chemical reaction, which was consisted of two elementary reactions. An empirical correlation formula between the reaction rate constants and the solubility parameters of the solvents, such as toluene, N‐methyl‐2‐pirrolidinone, and dimethyl sulfoxide, was presented.
The intensity of the 1602 cm-1 band in human cells is related to mitochondrial activity

We report a Raman band at 1602 cm−1 in the spectra of human cells, which previously had only been observed in mitochondria of yeast cells. This band, which has not yet been assigned to a particular molecular species, was found to occur in HeLa cells, peripheral blood lymphocytes, human mesenchymal stem cells and bovine chondrocytes. The band is proposed as an indicator of the activity of mitochondria in cells. Cells were cultured with and without serum or temporarily deprived of serum. The band can be observed for all these variations in cell culture methodology. The band intensity decreases under the influence of an increase of the calcium ion concentration in the surrounding medium.
ADMM-based Optimum Power Flow in Nested Microgrids

Nested microgrids is an emerging configuration of microgrids where one microgrid can operate as part of a bigger microgrid to ensure supply and increase reliability. Each microgrid contains dispatchable and non-dispatchable distributed generators (DGs) from renewable energy sources (RES), and loads so it can be optimized to be self-sufficient. Yet, it is given the option to buy power from the upper level to meet its deficit or sell its surplus of power to the lower level. This paper proposed a method to optimize DGs output power and the power trading between upper and lower microgrids with the distributed optimization technique. Using the alternating direction method of multipliers (ADMM) algorithm, each level is optimized in parallel for a day-ahead energy management system (EMS). Then the boundary variables are checked until convergence criteria are met. A case study was executed on IEEE 33-bus system to evaluate the performance of the proposed technique.
SAHAR-LSTM: An enhanced Model for Sentiment Analysis of Hotels’Arabic Reviews based on LSTM

Over the last few years, many scientists have paid special attention to the Sentiment analysis (SA) area of research, thanks to its interesting uses in different domains. The most popular studies have tackled the issue of SA in the English language; however, those dealing with SA in the Arabic language are, up to now, limited due to the complexity of the computational processing of this Morphologically Rich Language (MRL). As a matter of fact, Deep learning and especially the use of Recurrent Neural networks (RNN) has recently proved to be an efficient tool for handling SA challenges. The recourse to some approaches, based on the long short-term memory (LSTM) architecture, has provided adequate solutions to the problems of SA in Arabic language. In our paper, we conduct a study on SA in the Arabic language. Therefore, we propose an enhanced LSTM based model for performing SA of Hotels’ Arabic reviews, called SAHAR-LSTM. This model is evaluated on a dataset containing Hotels’ reviews written in Modern Standard Arabic (MSA), and it is implemented together with two Dimensionality reduction techniques: Latent Semantic Analysis (LSA) and Chi-Square. The experimental results obtained in this work are promising, and demonstrate that our proposed approaches achieve an accuracy of 83.6% on LSA and Chi-Square methods and 92% on LSTM classification Model.
Analysis of Reverse-Saliency PMSM with Multiple Flux-Barriers for SWPS

A reverse-saliency permanent magnet synchronous motor (RS-PMSM) with multiple flux-barriers is presented in this paper. The RS-PMSM produces a positive reluctance torque with flux-intensifying current which thereby reduces the permanent magnet (PM) demagnetization possibility and increases the operating speed range. The presented motor is compared with its conventional counterparts and the electromagnetic performances of both the motors in terms of inductance curves, average-torque contours, torque-ripple profiles, torque-speed characteristics and efficiency maps are obtained by using finite element methods. Meanwhile, the utility of designed motor for applications like solar water pump system (SWPS) is demonstrated. A prototype of the presented motor is also manufactured and the test performances are obtained to verify the effectiveness of developed prototype.
Analysis of Product Value Based on NLP and Time Sequence Model

In most instances, necessity is the mother of invention. For example, the generation of B2C business mode enables the business company to capture data such as star ratings, reviews, and helpful votes from online customers. Therefore, the company can have an insight into the market conditions and explore prospective customer demands. In this paper, we aim to take advantage of innovative algorithms and models to conduct scientific analysis and data mining. Original data are provided by Sunshine Company, including star ratings, reviews, helpful votes, and more. Our solution is composed of three main sections. In order to reduce errors from original data, we use Python to pre-process the provided data. It will significantly improve the credibility and efficiency of the data. The data pre-processing includes three steps: Text Deduplication, Mechanical Compression and Tag Filtration. In terms of model construction, we use different algorithms in multiple-dimensions to analyze the data. For instance, Factor Analysis, Grey Relational Analysis, and Cluster Analysis are proposed to process reviews and obtain text-based product information like meaningful quantitative patterns, and relationships between star ratings and reviews. We use the LDA algorithm to visualize the word frequency. Then the Sentiment Word Analysis is performed to quantify the comments, and the user's comprehensive evaluation of the product is obtained by linear weighting of comments and ratings. In order to solve problems in multiple dimensions, we develop a brand-new kind of Time Sequence Model which can obtain the best relevant combination of the products. Specific analysis processes are: Assume each day as a measurement, Weight the customer reviews to obtain overall reviews for that day, and Visualize the date of reviews. We creatively use Time Characteristics Analysis to analyze whether customer reviews are affected by others at the end. In order to ensure the stability and credibility of the Time Sequence Model, we conduct a sensitivity analysis, and results of the test are good. Generally speaking, the results of the data analysis can basically answer the questions raised by Sunshine Company. We put forward some innovative ideas and suggestions for reference.
2.1 mm-Wave 5G Radios: Baseband to Waves

There are many challenges in building millimeter-Wave (mmW) 5G radios [1] –[3]. Some of the key challenges are the cost, heat dissipation, and array calibration. This paper describes ADI’s full line-up of mmW 5G radios used today, with a focus on the millimeter wave front-end portion, and how it addresses some of these challenges. The radio block diagram, shown in Fig. 2.1. 1, is an example of a dual-polarized 24-to-30GHz band mmW radio. All ICs in this radio cover 24 to 30GHz, allowing the same chips to be used in n257, n258, and n261 radios, which reduces the development cost. The radio consists of two domains: BB-IF and mmW. The BB-IF domain contains either an IF transceiver utilizing quadrature baseband data converters and mixers to generate the IF, or data converters (MxFE) to directly synthesize the IF. The former is optimal for narrower bandwidth applications while the latter consumes more power but can support higher bandwidths. The mmW domain consists of a mmW Up/Down converter and a 16-channel, (2 polarizations $\times 8$ channels per pol) high-performance beamformer (BF). The mmW chips utilize a 45nm RF SOI process, which is optimized for RF performance at the mmW 5G bands. The SOI process is a 12-inch process, hence economically suitable for large-volume applications. The BF linear output power is 12dBm/channel @ 3% EVM using a 400MHz 5G NR waveform. The channel P1dB is 20dBm. Two mmW BFs, cover 24-to-30 and 37-to-44GHz bands, respectively. An implementation of the mmW front-end, consisting of 128 dual-polarized antenna elements, 16 BFs, 4 Up/Down frequency converters (UDCs), and the power-management circuitry has been fabricated and is shown in Fig. 2.1. 2. Over-the-air (OTA) measurement results of the fabricated array are presented below. The measurements include the radiation pattern, EIRP, linearity, and combined throughput of four streams. The paper also discusses the following: OTA Performance of ADI’s mmW 5G radios, antenna performance and design aspects, thermal aspects and heat dissipation modelling, and calibration of mmW radios.
An Approach for Optimal Pre-Conditioning of the Analytical Field Solution of Slotless PM Machines

Analytical modeling of electrical machines has the advantage of remarkable computational efficiency when compared with finite element analysis (FEA). This is especially important for slotless topologies, as they are well suited for 2-D analytical field solutions. Nevertheless, the analytical techniques are doubtlessly non-trivial; besides, the ill-conditioned nature of the problem comes along with the mathematical complexity. The numerical issues are shown to be loosely assessed or even ignored in some parts of the literature, which causes a lack of replicability and low practical usability of analytical approaches. Although researchers often adopt a numerically optimized formulation in their works, the mathematical manipulations that make the solutions to be well-posed and efficiently exploitable are often hidden from the reader since the focus is rather on the theoretical derivation and the exact solutions. This paper shows how the direct field solution of the magnetic field problem, named the raw field formulation (RFF), can lead to significant errors throughout the domain of slotless SPM machines, which vary significantly with the machine geometry. Then, an approach to reach the numerically optimal form of the field solution, named optimized field formulation (OFF), is proposed, comprehensibly described, and discussed. Finally, the closed-form expression and the optimal pre-conditioner underneath are explicitly presented and shown to outperform the accuracy of other pre-conditioned formulations used in the literature (including RFF). The OFF’s performance is significant, especially at higher harmonic orders.
Investigation of Robustness of IMC Controller for a Paper Mill Sub-Process

This work is centered on IMC (Internal Model Control) control system design and its robustness analysis for controlling the basis weight of the paper produced by the paper milll. The headbox has a significant role in a paper mill. It maintains the pressure inside the box and discharges stock at an optimum required speed. In this paper, the robustness of the IMC based controllers will be investigated for the two parameters, setpoint tracking and disturbance rejection. The MATLAB software is used for carrying out all simulations done in this paper.
Space Matching for Highly Efficient Microwave Wireless Power Transmission Systems: Theory, Prototype, and Experiments

Microwave wireless power transmission (MWPT) via radio waves has been an important research topic of the WPT systems, where the overall power transfer and conversion efficiency is a key factor to evaluate the system performance. The state-of-the-art work on MWPT has only taken the end-to-end power transfer efficiency in free space or the power conversion efficiency of the receiver (rectenna) into consideration separately when optimizing the power transfer efficiency of the overall system. To comprehensively consider the system-level matching of the entire MWPT system, a novel space matching concept, including aperture field matching, power matching, and impedance matching, is proposed for optimizing the overall power transfer efficiency. By using the space matching method in this work, the optimal designs of the subsystem components such as the transmitting antenna, receiving antenna, and rectifying circuit can be separately obtained to avoid the complex systematic optimization of the large-scale and complicated MWPT system, therefore, significantly improving the overall power transfer efficiency by 19.4% compared with the traditional methods, and reducing the complexity in large-scale system-level design. This work will have valuable implications in the system design of MWPT applications.
Chip defect detection based on deep learning method

With the rapid development of deep learning theory and computing resources, defect detection based on deep learning has been increasingly used. Compared with traditional machine learning methods, detection methods based on deep learning can achieve end-to-end detection methods, with high flexibility and accuracy, strong network expression capabilities, and no manual design features. This paper focuses on the use of deep learning-based methods to detect chip defects: make data sets according to the types of chip defects, detect chip defect based on the YOLOv3 network and fine-tuning it. The final mAP reached 86.36%.