The level of creativity in English writing among Jordanian secondary school students

The aim of this study is to explore the level of creativity in English writing among Jordanian secondary school students.The researchers have used a random sample of 100 students of secondary school students in Irbid and Amman cities in Jordan.Adapetd Torrance Test of Creative Thinking (TTCT) was used to measure their creativity in English writing.TTCT test is thought to be the best test to evaluate the creativity dimensions of students in writing.TTCT assesses fluency or the number of ideas; flexibility, the variety of categories in the answers; and originality, which consists in considering innovative answers, neither familiar nor inappropriate.The results of the study showed that the respondents fall in the moderate level of creativity

Kinetic study of copper (II) removal from aqueous solution onto unmodified kenaf fibre

Adsorption has been proven as an excellent method for industrial wastewater treatment. Therefore, there is a need to explore new sources of alternative and inexpensive adsorbent for elimination of heavy metals. In this study, a series of batch experiments was conducted to study the adsorption potential of kenaf as an adsorbent for Cu (II) removal from aqueous solutions. The specific objectives are to obtain kinetics determination and measure the adsorption capacity in batch system. The single adsorption kinetics was carried out at a constant temperature of 30±1°C using an incubator shaker operated at 200 rpm. The results showed that the equilibrium time for removal of Cu (II) was 3 h at pH 5.0. The pseudo first-order and pseudo second-order models were used to describe adsorption kinetics of Cu (II). It was observed that the adsorption kinetics of Cu (II) ions onto kenaf followed pseudo second-order model. This suggests that the chemisorption mechanism is the rate-limiting step in the adsorption uptake. This study established the feasibility of kenaf as an effective adsorbent for removing Cu (II) from aqueous solution

Optimization of torrefaction conditions for high energy density solid biofuel from oil palm biomass and fast growing species available in Malaysia

Without appropriate treatment, lignocellulosic biomass is not suitable to be fed into existing combustion systems because of its high moisture content, low bulk energy density and difficulties in transport, handling and storage. The aim of this study was to investigate the effects of torrefaction treatment on the weight loss and energy properties of fast growing species in Malaysia (Acacia spp., and Macaranga spp.) as well as oil palm biomass (oil palm trunk and empty fruit bunch). The lignocellulosic biomass was torrefied at three different temperatures 200, 250 and 300 °C for 15, 30 and 45 min. Response surface methodology was used for optimization of torrefaction conditions, so that biofuel of high energy density, maximized energy properties and minimum weight loss could be manufactured. The analyses showed that increase in heating values was affected by treatment severity (cumulated effect of temperature and time). Our results clearly demonstrated an increased degradation of the material due to the combined effects of temperature and treatment time. While the reaction time had less impact on the energy density of torrefied biomass, the effect of reaction temperature was considerably stronger under the torrefaction conditions used in this study. It was demonstrated that each biomass type had its own unique set of operating conditions to achieve the same product quality. The optimized torrefaction conditions were verified empirically and applicability of the model was confirmed. The torrefied biomass occurred more suitable than raw biomass in terms of calorific value, physical and chemical properties. The results of this study could be used as a guide for the production of high energy density solid biofuel from lignocellulosic biomass available in Malaysia

Improving compatibility of Recycled Nitrile Rubber (rNBR) and Ethylene Vinyl Acetate (EVA) blends by electron beam irradiation

Blends of ethylene vinyl acetate (EVA) copolymer and recycled nitrile rubber (rNBR) were prepared using an internal mixer. N,N’-m-phenylenedimaleimide (HVA-2) was added into the blend composed of 70 wt % of EVA and 30 wt % of rNBR, and served as a crosslinking agent. The HVA-2 concentration was varied from 0 to 5 phr. The changes in the compatibility of the blends were investigated before and after electron beam irradiation by means of physical and morphological tests. The results obtained from these tests were then analysed, namely tensile strength (TS), modulus 100 (M100), elongation at break, gel content and scanning electron microscopy (SEM). The results showed that the TS and elongation at break had decreased with increasing in HVA-2 concentration and electron beam irradiation dose, while the M100 had increased. It is believed that the blends had undergone early crosslinking reaction during mixing. Hence, the brittleness of the materials had increased upon exposure to electron beam irradiation due to the excessive crosslinking bonds. This observation was supported by the gel content and SEM micrographs

MIDV-2020: a comprehensive benchmark dataset for identity document analysis

Identity documents recognition is an important sub-field of document analysis, which deals with tasks of robust document detection, type identification, text fields recognition, as well as identity fraud prevention and document authenticity validation given photos, scans, or video frames of an identity document capture. Significant amount of research has been published on this topic in recent years, however a chief difficulty for such research is scarcity of datasets, due to the subject matter being protected by security requirements. A few datasets of identity documents which are available lack diversity of document types, capturing conditions, or variability of document field values. In this paper, we present a dataset MIDV-2020 which consists of 1000 video clips, 2000 scanned images, and 1000 photos of 1000 unique mock identity documents, each with unique text field values and unique artificially generated faces, with rich annotation. The dataset contains 72409 annotated images in total, making it the largest publicly available identity document dataset to the date of publication. We describe the structure of the dataset, its content and annotations, and present baseline experimental results to serve as a basis for future research. For the task of document location and identification content-independent, feature-based, and semantic segmentation-based methods were evaluated. For the task of document text field recognition, the Tesseract system was evaluated on field and character levels with grouping by field alphabets and document types. For the task of face detection, the performance of Multi Task Cascaded Convolutional Neural Networks-based method was evaluated separately for different types of image input modes. The baseline evaluations show that the existing methods of identity document analysis have a lot of room for improvement given modern challenges. We believe that the proposed dataset will prove invaluable for advancement of the field of document analysis and recognition.This work is partially supported by Russian Foundation for Basic Research (projects 19-29-09066 and 19-29-09092). All source images for MIDV-2020 dataset were obtained from Wikimedia Commons. Author attributions for each source images are listed in the original MIDV-500 description table (ftp://smartengines.com/midv-500/documents.pdf). Face images by Generated Photos (https://generated.photos)

Resveratrol Targeting of Carcinogen-Induced Brain Endothelial Cell Inflammation Biomarkers MMP-9 and COX-2 is Sirt1-Independent

The occurrence of a functional relationship between the release of metalloproteinases (MMPs) and the expression of cyclooxygenase (COX)-2, two inducible pro-inflammatory biomarkers with important pro-angiogenic effects, has recently been inferred. While brain endothelial cells play an essential role as structural and functional components of the blood-brain barrier (BBB), increased BBB breakdown is thought to be linked to neuroinflammation. Chemopreventive mechanisms targeting both MMPs and COX-2 however remain poorly investigated. In this study, we evaluated the pharmacological targeting of Sirt1 by the diet-derived and antiinflammatory polyphenol resveratrol. Total RNA, cell lysates, and conditioned culture media from human brain microvascular endothelial cells (HBMEC) were analyzed using qRT-PCR, immunoblotting, and zymography respectively. Tissue scan microarray analysis of grade I–IV brain tumours cDNA revealed increased gene expression of Sirt-1 from grade I–III but surprisingly not in grade IV brain tumours. HBMEC were treated with a combination of resveratrol and phorbol 12-myristate 13-acetate (PMA), a carcinogen known to increase MMP-9 and COX-2 through NF-κB. We found that resveratrol efficiently reversed the PMA-induced MMP-9 secretion and COX-2 expression. Gene silencing of Sirt1, a critical modulator of angiogenesis and putative target of resveratrol, did not lead to significant reversal of MMP-9 and COX-2 inhibition. Decreased resveratrol inhibitory potential of carcinogen-induced IκB phosphorylation in siSirt1-transfected HBMEC was however observed. Our results suggest that resveratrol may prevent BBB disruption during neuroinflammation by inhibiting MMP-9 and COX-2 and act as a pharmacological NF-κB signal transduction inhibitor independent of Sirt1

Multi-Platform Next-Generation Sequencing of the Domestic Turkey (Meleagris gallopavo): Genome Assembly and Analysis

The combined application of next-generation sequencing platforms has provided an economical approach to unlocking the potential of the turkey genome