Miracle-dz/UniFAR-FTUs huggingface dataset:
Research Study Exploring the Primary Teachers’ Knowledge About ADHD and their Attitude Towards the Inclusion of ADHD learners in the Mainstream Classrooms in an American Private School in Sharjah

The chief intent of this study was to explore the issues around including the attitudes and knowledge of teachers towards children with ADHD and their inclusion into mainstream classrooms in the UAE. It also sought to assess the impact of the attitudes held by teachers as well as their awareness on ADHD children’s academic achievement. Furthermore, this study includes an overview of the main characteristics of children with ADHD in the impact the disorder has on their academic, social and emotional well-being. The tools utilized in this study were drawn from the qualitative approach and used to obtain the data required for this research. Semi-structured interviews were conducted with special educators, subject teachers, parents and the child, called Ali for the purpose of this study, which is not his real name. This pseudonym was adopted in order to protect the child’s identity and maintain ethical standards of child privacy. Furthermore, observations in and out of the classroom were used to gather further data to support the analysis. The semi-structured interviews were specifically used to identify the levels of knowledge and awareness in the UAE in relation to ADHD, and to assess the level of impact on an affected child’s learning in a mainstream classroom that results from the teacher’s knowledge of ADHD. ADHD is known to be associated with academic challenges and behavioural issues and is a relatively common disorder. There are a number of options for interventions available to affected children, which include behavioural therapy and medication. These treatments and approaches have been widely researched; however, far less is known and evidenced regarding the effect on a child’s development of their teacher’s attitudes towards and knowledge of ADHD and how these impact on the child’s learning outcomes. This study found that the majority of teachers in a primary setting appeared to have limited knowledge and understanding of ADHD and consequently raising awareness was found to be needed. In the UAE, ADHD remains underexplored and little understood; this increases the importance of early intervention services and improving teacher knowledge in relation to ADHD. By building a greater understanding of ADHD amongst education professionals and other stakeholders, the academic achievement, the social skills and the general well-being of children with ADHD can be significantly improved.
Determination of chlorinated furanones, hydroxyfuranones, and butenedioic acids in chlorine-treated water and in pulp bleaching liquor

Compounds with structural similarities to the potent bacterial mutagen 3-chloro-4-(dichloromethyl)-5-hydroxy-2(5H)-furanone, MX, have been synthesized and quantitatively determined in extracts of chlorination-stage bleaching liquors (CBL) from pulp mills, chlorine:treated aqueous solution of fulvic acids, chlorinated natural humic water, and chlorine-disinfected drinking water. In addition, a preliminary screening of the mutagenic potency of the compounds was performed. The compounds were found in the extracts with the exception of a few compounds not detected in the drinking water extracts. The compounds induced mutagenicity in Ames tester strain TA100 in tests performed without metabolic activation
A Multi-Sensor Approach to Classify Tillage Practices in Mexico

To minimize soil disturbance, there has been an increased adoption of reduced or zero tillage (ZT) technologies among farmers in different regions across the globe. Yet, to date, the scale of adoption remains unclear because it is difficult to collect adoption data on-the-ground at large spatial and temporal scales. Remote sensing can offer a way to map such technology adoption at large scales and at low cost. This study uses Sentinel-2, Landsat 7 & 8, and Sentinel-1 satellites to map tillage practices in Guanajuato, Mexico, a region where the use of zero-tillage has been promoted by national and international agencies over the last decade. We specifically compared accuracy scores of different sensors and sensor combinations, and different timing of imagery in a random forest classification. The results indicate that when considering the accuracy of a single sensor, Sentinel-2 has the highest classification accuracy. However, using a combination of all three sensors dramatically outperformed all single sensor analyses, with an overall classification accuracy of 85.96%. Considering image timing, we find that using imagery from only the sowing season performs almost as well as using imagery throughout the growing season. We conclude that using freely-available satellite images is effective in classifying tillage practices in Mexico at large spatio-temporal scales.
Comparative study of the preparation of negative electron affinity GaAs photocathodes with O2 and with NF3

We discuss the possibility of replacing oxygen with nitrogen trifluoride in the preparation of stable GaAs negative electron affinity (NEA) photocathodes. The different role of O2 versus NF3 exposure during the activation is examined by means of quantum yield and photocurrent lifetime measurements. Quantum yield results clearly demonstrate that NEA conditions can be attained also with NF3. Measurements performed on the same samples and in the same experimental conditions, show a remarkably different time evolution of the activation process in the two cases. However, as a result of a huge number of activations, no evidence of significantly larger lifetimes for NF3 prepared photocathodes can be deduced.
Interfacial energy and strength of multiwalled-carbon-nanotube-based dry adhesive

Vertically aligned multiwalled carbon nanotube (MWCNT) arrays can mimic the hairs on a gecko’s foot and act as a dry adhesive. We demonstrate the van der Waals interactions originated dry adhesion between MWCNT array surfaces and various target surfaces over millimeter-sized contact areas. The adhesive strengths were measured over 10N∕cm2 in the normal direction and about 8N∕cm2 in the shear direction with glass surface. The adhesion strength over repeated cycles is limited by the relatively poor adhesion of MWCNTs to their growth substrate, which was improved significantly by adding molybdenum to the catalyst underlayer. We also measured the interfacial work of adhesion as a fundamental adhesion property at the interface. Our measured values of a few tens of mJ∕m2, which falls in the range of typical van der Waals interactions energies, provide a direct proof of the van der Waals dry adhesion mechanism. Furthermore, in contrast to other dry adhesives, we show that MWCNT adhesives are electrically and the.
Identification of co-expressed modules of cotton genes responding to Verticillium dahliae infection by WGCNA

Weighted gene co-expression network analysis (WGCNA) is a classic systematic biological method, which can be used to identify co-expressed modules, investigate relationships between modules and specific traits, and screen hub genes in the networks. Verticillium wilt, caused by the fungal pathogen Verticillium dahliae, can cause severe fibre quality reduction and yield loss of cotton. Studying on cotton genes and molecular mechanisms related to defense responses against V. dahliae can shed light on cotton breeding. In this study, 21 transcriptome data of Gossypium barbadense seedling roots infected by V. dahliae were used to investigate differentially expressed genes (DEGs). By filtering out the genes with low variation, 35,647 genes were selected for WGCNA. In total, 22,850 DEGs were identified under V. dahliae infection, with 4685 in common at all inoculated time points. Co-expression network analysis identified 18 modules, in which five modules significantly associated with V. dahliae infection (black, mediumpurple3, darkolivegreen, plum3 positively correlated with the 2 h, 6 h, 48 h, and 72 h inoculated time points, respectively; mediumpurple2 negatively correlated with the 2 h inoculated time point). GO and KEGG enrichment analysis were performed on these five specific modules, which could be enriched in GO terms and metabolic pathways, such as cellular response to stimulus, calcium ion binding and flavonoid biosynthesis. The hub genes were screened by calculating gene connectivity in the corresponding networks, and they may play important roles in the resistance against biotic/abiotic stresses. In summary, by WGCNA, a few defense-related co-expressed modules and hub genes were identified. The results of this study would be beneficial for further understanding of the molecular mechanisms of pathogen resistance in cotton, and provide new gene resources for https://engine.scichina. com/doi/10.3724/SP.J.1006.2020. 94124 第 5期 傅明川等: 利用 WGCNA鉴定棉花抗黄萎病相关基因共表达网络 669 cotton breeding in the future.
ISLAMIC VS CONVENTIONAL FUNDS WITHIN THE FAMILY: SELECTIVITY SKILLS AND MARKET TIMING ABILITY

ABSTRACT The aim of the study is to compare the performance of Islamic mutual fund (IMF) and conventional mutual fund (CMF) within the same family, in addition, to examine the performance of fund family in Malaysia for the period from 2007 to 2018. The study used eight measures of performance, raw returns, excess returns, Sharpe ratio, Treynor ratio, Jensen alpha, Carhart four-factor model as selectivity models, In addition to Treynor & Mazuy (TM) and Hendrickson & Merton (HM) as market timing models. The study contributes by investigating and compares the performance at the family level. The results reported that IMFs exhibited some fund selection ability over CMFs. However, both types of funds displayed poor market timing ability. At a fund family level, the results show the fund families exhibited good fund selections skills, at the same time, fund family still exhibited poor market timing ability. The novel result of this study that the difference in performance between Islamic and conventional funds shrank compared to the results of previous studies. Due to the common advantages offered by the families for both types of funds. The findings are important to investors because the results provide new evidence about the fund families' performance. Most investors follow the top-down approach, where mutual fund investors initially choose fund families before deciding which funds to hold. In addition, the results are important for managers to decide which types of funds that they may issue in their own families, so that they can perform well in the future.
Extracting and Cleaning RDF Data

The RDF data model has become a prevalent format to represent heterogeneous data because of its versatility. The capability of dismantling information from its native formats and representing it in triple format offers a simple yet powerful way of modelling data that is obtained from multiple sources. In addition, the triple format and schema constraints of the RDF model make the RDF data easy to process as labeled, directed graphs. This graph representation of RDF data supports higher-level analytics by enabling querying using different techniques and querying languages, e.g., SPARQL. Anlaytics that require structured data are supported by transforming the graph data on-the-fly to populate the target schema that is needed for downstream analysis. These target schemas are defined by downstream applications according to their information need. The flexibility of RDF data brings two main challenges. First, the extraction of RDF data is a complex task that may involve domain expertise about the information required to be extracted for different applications. Another significant aspect of analyzing RDF data is its quality, which depends on multiple factors including the reliability of data sources and the accuracy of the extraction systems. The quality of the analysis depends mainly on the quality of the underlying data. Therefore, evaluating and improving the quality of RDF data has a direct effect on the correctness of downstream analytics. This work presents multiple approaches related to the extraction and quality evaluation of RDF data. To cope with the large amounts of data that needs to be extracted, we present DSTLR, a scalable framework to extract RDF triples from semi-structured and unstructured data sources. For rare entities that fall on the long tail of information, there may not be enough signals to support high-confidence extraction. Towards this problem, we present an approach to estimate property values for long tail entities. We also present multiple algorithms and approaches that focus on the quality of RDF data. These include discovering quality constraints from RDF data, and utilizing machine learning techniques to repair errors in RDF data.
Optimization of sample deposition for plasma-desorption mass spectrometry of peptidoglycan monomers

Three selected peptidogycan monomers isolated from muramidase-digested Escherichia coli-sacculus were characterized by positive- and negative-ion 252Cf plasma-desorption mass spectrometry (PDMS). Dut to the high affinity of sugar moieties towards alkali cations multiple alkali attachment in PDMS can be a problem. Electrospray, nitrocellulose, nitrocellulose sandwich anthracene-9-carboxylic acid 3-(3-Pyridyl)acrylic acid deposition techniques were evaluated for the degree of (de)proltonation and cationization of the molecular species by sodium and/or potassium. Electrosprayed and nitrocellulose-deposited samples mainly exhibited intense cationized molecular ion species whereas anthracene-9-caboxylic acid-deposition sample show a similar pattern but with much lower intensity. An extension of the nitrocellulose deposition technique, the so-called nitrocellulose sandwich sample preparation reduced the aallkali attachment problem for these hydrophilic compounds. Application of the small molecule matrix 3-(3-pyridyl)acrylic acid yielded mass spectra with abundant [M+H]+ and [MH]− ions in the positive- and in the negative-ion modes, respectively.
Ab initio study of transition state spectroscopy: ClHCl - photodetachment spectrum

Ab initio CASSCF‐MRCI calculations with the [7s6p3d1f/4s3p1d] contracted Gaussian basis sets are performed to investigate the photodetachment spectrum of ClCHl− observed experimentally by Neumark et al. [J. Chem. Phys. 88, 1463 (1988); J. Phys. Chem. 94, 1377 (1990)]. The theoretical assignments for the ClHCl− and ClDCl− spectra based on one‐dimensional Franck–Condon calculations are qualitatively in good agreement with the experiment. It is found by calculations that some peaks in the experimental spectra are assignable to transitions to the vibrational states of the first electronically excited 2Π state in addition to those of the ground 2Σ+ state in the transition state region of the neutral complex.
Nonisothermal Crystallization Behaviors of Poly(butylene terephthalate) Nucleated with Elastomer-Modified Nano-SiO2, a Commercial Nucleating Agent (P250), and Talc

The nonisothermal crystallization of poly(butylene terephthalate) (PBT) nucleated with elastomer-modified nano-SiO2 [SiO2-(E-MA-GMA)], a commercial nucleating agent (P250), and talc were investigated by differential scanning calorimetry (DSC) under different cooling rates. It was observed that P250, talc, and SiO2-(E-MA-GMA) act as heterogeneous nuclei in PBT; PBT-P250 and PBT-NE [PBT/SiO2-(E-MA-GMA)] blends, in particular, take a shorter time to crystallize. The Avrami, Ozawa, and Mo models were used to analyze the nonisothermal crystallization kinetics. The Avrami-Jeziorny model failed to describe the nonisothermal crystallization of PBT samples. The Ozawa analysis showed that P250, talc, and SiO2-(E-MA-GMA) change the nucleation mechanism and crystal growth of PBT. The crystallization activation energies of all the PBT samples were determined by the Kissinger model. The results show that the crystallization activation energy of PBT-P250 was lower than that of the others, and the nucleating efficiency of SiO2-(E-MA-GMA) on PBT was close to that of P250, while better than that of talc.
A Novel Random Forest Implementation of Sentiment Analysis

-------------------------------------------------------------------***---------------------------------------------------------------------- Abstract - In today’s world, we humans have been communicating with each other through calls, social media applications like WhatsApp, Facebook, Twitter, etc. From the social media apps, we get social media data from those applications and check what sentences are positive and negative sentiment using sentiment analysis and using deep learning methods like deep neural networks for classifying them under positive or negative sentiment polarity from twitter accounts. The data that we get from these social sites are being used for many social problems and used in government to analyze the opinion about social media users. This technique is called sentiment analysis. The main purpose of this sentiment analysis for this project will be to comparatively determine the writings made by user and check if they are going towards positive or negative. Only one technique will be used her – Machine Learning Algorithms – Random Forest. This paper uses the machine learning algorithm-Random Forest. The scope of this project will be widely used in classifying the text in terms of positive and negative polarity and help the government to handle social and threats due to the text classification.
Clinical use of orthodontic mini-implants for intrusion and retraction: a systematic review

Abstract Background Bimaxillary dental protrusion is common in many ethnic groups and is generally treated by the extraction of all first premolars. However, temporary anchorage devices (TADs) are currently gaining popularity and most studies have focused on anchorage loss, treatment duration, mini-implant success and failure rates, pain, discomfort and root resorption. Few studies have focused on the clinical effectiveness of implants for the intrusion and retraction of anterior teeth. Objectives To assess the clinical use of orthodontic mini-implants for the intrusion and retraction of anterior teeth. Methods A systematic review of articles selected from PUBMED and Google Scholar was carried out to determine the clinical use of orthodontic mini-implants for anterior tooth intrusion and retraction. Additional studies were hand searched to identify and include clinical trials, prospective and retrospective studies, while excluding finite element method (FEM) studies and case reports. A total of 598 articles were identified, of which 37 papers met the inclusion criteria and, following the elimination of duplicates, 20 articles were selected. Results Orthodontic mini-implants are more efficient for intrusion and retraction when compared to conventional intraoral and extra-oral anchorage devices. A greater amount of intrusion and retraction is achieved when mini-implants are placed between the first and second premolars without using any specific intrusive mechanics. Conclusion The present review highlights the clinical effectiveness of orthodontic mini-implants for anterior tooth intrusion and retraction and the results suggest that orthodontic mini-implants are more effective than other conventional methods of anchorage reinforcement.
Fabrication of Nanosized Antireflection Patterns on Surface of Aspheric Lens Substrate by Nanoimprint Lithography

Currently, various techniques are being explored for fabricating nano- or microsized patterns on flat and curved substrates. However, there are only a few techniques that can be used to fabricate nano- to microsized patterns on the surface of aspheric lenses. In this study, nanoimprint lithography (NIL) was used to obtain nanosized antireflection structures on the surface of aspheric lenses. In order to ensure conformal contact between the imprint mould and the aspheric lens substrate, a highly flexible poly(urethane acrylate) (PUA)-based film mould was used. As a result, various nanosized patterns were uniformly fabricated on the surface of the aspheric lens with high fidelity.
In-situ measurement of conducting polymers on evaporated and electrochemically deposited Au surfaces

By utilizing strain gage technology it is possible to directly and continuously measure the electrochemically induced strain response of EAP actuators. Strain sensitive actuators were constructed by directly vapor depositing gold (EvAu) on polyimide strain gages which are capable of measuring strain with an accuracy of +/- 1(mu) (epsilon) . Strain sensitive actuators were used to evaluate the strain response of polypyrrole (PPy), poly(3,4-ethylenedioxypyrrole) (PEDOP) and poly(3,6-bis(2-(3,4-ethylenedioxy)thienyl)-N-carbazole) (PBEDOT-Cz). PPy was shown to produce significantly higher strain when compared to PEDOP and PBEDOT-Cz. The resulting overall strain for the materials was: 236, 33, and 35 (mu) (epsilon) respectively. From the initial investigation, adhesion of the EAP to the EvAu layer was identified as a major factor in the resulting lifetime and strain response of these actuators. Therefore an electrochemically deposited Au layer (EcAu) was deposited on top of the EvAu layer to improve the adhesion of the EAP to the working electrode. By changing the surface roughness from requals3.43 (EvAu) to requals8.26 and 18.00 (EcAu) the normalized strain response after 2000 cycles increases from 45% to 60% and 68% respectively. Also by changing the surface roughness from 5 to 23, the resulting strain response increases from ~100 (mu) (epsilon) to 600-800 (mu) (epsilon) for Ppy.
Suspension Polymerization of Styrene Monomer without Emulsifier and Initiator

Ultrasonic waves were used to perform suspension polymerization of styrene monomer in the absence of both emulsifier (surfactant) and polymerization initiator. Styrene monomer was ultrasonically dispersed as oil droplets at 40 kHz after being added dropwise into water. Polymerization of the monomer in the droplets was initiated with the radical species from water as the polymerization initiator generated by irradiation with a high frequency ultrasonic wave at 200 kHz on the surfactant-free (styrene monomer/water) emulsion. The particles thus prepared were confirmed to be polystyrene particles by FT-IR measurements and the particle size was found to be several tens nanometers through TEM observation and dynamic light scattering measurement.
Convective Drying of Apples: Kinetic Study, Evaluation of Mass Transfer Properties and Data Analysis using Artificial Neural Networks

Abstract In the present work, the effect of drying was evaluated on some chemical and physical properties of apples, and the functions were modelled using feed-forward artificial neural networks. The drying kinetics and the mass transfer properties were also studied. The results indicated that acidity and sugars were significantly reduced by drying. Regarding colour lightness decreases, whereas redness and yellowness increased. As for texture, the dried samples were softer and less cohesive as compared to the fresh ones. Mass diffusivity increased with temperature, from 4.4×10−10 m2/s at 30°C to 1.4×10−9 m2/s at 60°C, and so did the mass transfer coefficient, increasing from 3.7×10−10 m/s at 30°C to 7.4×10−9 m/s at 60°C. As to the activation energy, it was found to be 34 kJ/mol. Neural network modelling showed that all properties can be correctly predicted by feed-forward neural networks. The analysis of the networks’ behaviours input layer weight values also shows which properties are more affected by dehydration or more dependent on variety.
Synthesis and characterization of thiol-stabilized CdTe nanocrystals

In order to expand the range of high-quality nanosized semiconductor materials that can be obtained as quantum dots through a wet chemical route a series of oxidize-stable CdTe nanoclusters with narrow size distributions and extremely small particle sizes ranging from 1.3 to 2.4 nm has been prepared in aqueous solution using 2-mercaptoethanol and 1-thioglycerol as stabilizers. It has been investigated by means of UV-vis absorption and photoluminescence spectroscopy, X-ray diffraction (XRD), high resolution transmission electron microscopy (HRTEM) and energy dispersive x-ray analysis (EDX).