Miracle-dz/UniFAR-FTUs huggingface dataset:
Proposed Teacher Competencies to Support Effective Nature of Science Instruction: A Meta-Synthesis of the Literature

ABSTRACT Enhancing students’ understanding of aspects of the nature of science (NOS) recommended by the science education community is an important goal of science instruction. This can occur only when teachers are adequately prepared for teaching NOS. However, the science education community is still considering what is needed to enhance the efficiency of NOS instruction with respect to the preparation of NOS teachers. Based on a qualitative meta-synthesis of recent literature (2009–2018), we propose a framework of competencies for what teachers need to know to be an effective NOS instructor. Fifty-eight peer-reviewed journal articles targeting NOS instruction for, and related classroom practices of, preservice and inservice teachers were analyzed. This evaluation resulted in the identification of 20 specific competencies clustered in seven categories deemed necessary in the support of effective NOS instruction, generally divided into those that are NOS specific and those directed at more general pedagogical issues. These include (1) general NOS knowledge, (2) subject matter knowledge, (3) knowledge of learners with respect to NOS, (4) knowledge about NOS instructional strategies, (5) knowledge about NOS assessment, (6) general pedagogical knowledge, and (7) teachers’ motivations and beliefs about teaching NOS. The proposed competencies can be used as a guide for science educators preparing teachers who, in turn, are able to demonstrate NOS competencies and enhance the quality and depth of their students’ learning.
Impact of Temperature and Discharge Rate on the Aging of a LiCoO2/LiNi0.8Co0.15Al0.05O2 Lithium-Ion Pouch Cell

This paper presents a lithium-ion battery aging study in which pouch cells comprising a LiCoO 2 /LiNi 0.8 Co 0.15 Al 0.05 O 2 blended cathode and a graphite anode are examined. The study focuses on the impact of temperature and discharge rate on the cycle life of the tested cells. Compared to the aging behavior of other lithium-ion cells in the literature, the cells tested here are less sensitive to the discharge rate but more vulnerable to low temperature cycling. The vulnerability to low temperature mainly comes from cathode degradation, especially of the LiCoO 2 component. This is identiﬁed by electrochemical impedance spectroscopy, differential voltage analysis and incremental capacity analysis. The cells are able to achieve 3000–5000 cycles before reaching a capacity fade of 20%, also at higher discharge rates up to 5C. All in all, the high discharge rate capability could be a general advantage of pouch cells due to less mechanical and thermal stress in their geometry. Furthermore, more attention should be paid to the cathode health in low temperature applications of lithium-ion cells containing layered oxides. This paper focuses mainly on non-invasive aging detection methods for lithium-ion cells. Post-mortem results will be published in a following paper. ©
Detection rate of common intestinal parasites in end stage renal disease patients under maintenance hemodialysis in Benha University Hospital, Egypt

Background: Several parasites are responsible for life threatening infections in immunocompromised patients including those with chronic renal diseases. Determination of enteroparasitosis prevalence in patients with end stage renal disease (ESRD) experiencing hemodialysis (HD) showed elevated rates of infection, primarily by protozoa. Objectives: To investigate the common intestinal parasites among patients with ESRD undergoing HD in Benha University Hospital. Subjects and Methods: This case-control research was performed on 57 patients subjected to HD and 60 apparently healthy people as control group with no history of kidney disorders or other immunosuppressive conditions in the control group. Age of participants ranged from 20-70 years in both groups. Three consecutive fresh fecal samples from all participants were obtained after completion of the questionnaire and examined macroscopically and microscopically to identify various stages of common pathogenic intestinal parasites using iodine and modified Ziehl-Neelsen stains to detect protozoa. Results: The total rate of parasite infection was 68.4% and 48.3% in ESRD patients and control group, respectively. The discrepancies between the two groups were statistically significant. E. histolytica/E. dispar was the commonest parasite compared to other parasites in the two groups. Conclusion: In ESRD patients, a high detection rate of intestinal parasites was reported which can lead to severe complications in these patients being immunocompromised individuals. Hence, stool examination
L-arginine Metabolism Regulates Airways Responsiveness in Asthma and Exacerbation by Air Pollution

The enzyme, arginase, converts L-arginine into L-ornithine and urea, and has been implicated in the pathogenesis of lung diseases, related to dysregulation of L-arginine metabolism and remodeling. Allergic asthma is a chronic condition characterized by inflammation, lung remodeling and airways hyperresponsiveness (AHR). Increased expression of arginase may contribute to AHR in asthma by reducing L-arginine bioavailability for the nitric oxide synthase (NOS) isozymes, thus, limiting the production of the endogenous bronchodilator, nitric oxide (NO). Reduction of intracellular L-arginine concentrations as a consequence of augmented arginase expression and activity may also promote NOS uncoupling, resulting in increased formation of peroxynitrite, a powerful oxidant that promotes bronchoconstriction and inflammation. In chronic asthma, increased arginase expression may also contribute to airways remodeling, through increased synthesis of L-ornithine, and hence the production of polyamines and L-proline, which are involved in cell proliferation and collagen deposition, respectively. New drugs targeting the arginase pathway could have therapeutic benefits in asthma. This review focuses on recent developments in our understanding of the role of arginase in AHR, inflammation and remodeling, highlighting studies that advance our knowledge of L-arginine dysregulation in human asthma and animal studies that explore the therapeutic potential of arginase inhibition.
How online news headlines and accompanying images ‘translate’ a violent event: a cross-cultural case study

ABSTRACT In this article, I examine UK, Swiss and Spanish online news articles that report on a violent event (Nice, France, 14 July 2016) and that were published on the first day of the news cycle. I focus in particular on the language of the headlines, and on accompanying visual material, as this would have been likely to be ‘read’ with each headline. These textual and visual elements translate the event as newsworthy and as a terrorist act. Differences across the news cultures represented are discussed, and the case is made for extending cross-cultural research on stylistic and visual features of news texts.
Prevalence and Phylogenetic Diversity of Pathogenic Fusarium Species in Genotypes of Wheat Seeds in Three Rift Valley Regions, Kenya

Wheat is a source of nutrients for around 40% world’s population and the second most important cereal crop in Kenya. However, Fusarium head blight (FHB) hinders sustainable sufficient production of the crop, causing both economic and health losses. With the emerging unfavorable climatic changes, effective disease management strategies and adequate seed system are necessary to meet the deficiency. Current information on prevalence of the causative pathogens in varieties of wheat genotypes is a critical prerequisite to such strategies. This study aimed at determining the prevalence of pathogenic Fusarium species in seeds of developed varieties of wheat genotypes in three major wheat-producing regions in Kenya. A total of 260 samples of 18 wheat genotypes from 123 farms were collected. Peptone pentachloronitrobenze agar was used for fungal isolation, while identification of Fusarium spp. was based on the gene encoding translation elongation factor 1-α (tef1-alpha) sequence analysis. Fusarium spp. isolated include Fusarium poae, F. tricinctum, F. heterosporum, F. culmorum, F. equiseti, Fusarium sp. , F. verticillioides, and F. oxysporum. There was no significant difference in prevalence of Fusarium spp. pathogens among the three regions studied. Fusarium spp. diversity index for Nakuru was 2.008, Narok was 1.4603, and Uasin Gishu was 1.2337. Wheat produce from farm-saved seeds yielded 66.25% of the isolates, while the produce from certified commercial wheat seeds yielded 33.75% of the isolates. The significant finding of the study is that Fusarium spp. associated with mycotoxins that contaminate the wheat food chain seem to be flourishing in all the sampled wheat seed genotypes from the regions studied. Information on the prevalence and diversity of the pathogens on persistence of the disease in the crop is critical in advancing integrative FHB control measures.
Factors influence the housing price in Kuala Lumpur by using AHP

The housing affordability issue was bothered the B40 and M40 buyers where the income level of the buyers cannot afford the higher housing price in Kuala Lumpur. To understand the factors that contribute to the housing price can improve the planning for the buyers. The planning for purchasing the residential property should be construct by the buyers to analyze the financial ability. Analytical Hierarchical Process can show the hierarchical diagram for the factors interested which have the higher priority is define as the important factor towards the housing price.
Implementation of Digital Games in Advancing Students’ Higher-Order Thinking Skills: A Review

The 4.0 industrial revolution transformed life remarkably. Dependence on technology is notable and influences the learning system in our country. In fact, its weight becomes more visible in the post-COVID-19 situation that strikes the world today. Online learning compels educators to be more creative in designing the learning process. One of them is to employ a digital game strategy in learning that utilises the elements of the game intending to motivate students, maximise positive feelings and engagement with the learning process. Furthermore, the application of this media can help to improve students’ higher-order thinking skills because through the digital game, students can explore innovative things as well as test their level of acceptance of the topics discussed in the lecture. Nonetheless, to what extent is the approach victorious in helping to overcome various problems in learning and able to improve students’ higher-order thinking skills? Therefore, this paper identified the implementation of digital games in learning and its implications for the advancement of higher-order thinking skills of students either at the secondary or tertiary education level. Extensive literature review methods were administred to identify and present data relevant to the current situation, especially in the learning atmosphere in this epoch of COVID-19 pandemic. In particular, this research addressed the fundamental concepts of digital games, its implementation and function in enhancing students’ higher-order thinking skills. Further, the researchers proposed that this study would contribute to educators, particularly in improving the efficiency of technology. Ergo, it would be supporting students to explore novel ideas.
Quantification of Non-Exhaust Particulate Matter Traffic Emissions and the Impact of COVID-19 Lockdown at London Marylebone Road

This research quantifies current sources of non-exhaust particulate matter traffic emissions in London using simultaneous, highly time-resolved, atmospheric particulate matter mass and chemical composition measurements. The measurement campaign ran at Marylebone Road (roadside) and Honor Oak Park (background) urban monitoring sites over a 12-month period between 1 September 2019 and 31 August 2020. The measurement data were used to determine the traffic increment (roadside–background) and covered a range of meteorological conditions, seasons, and driving styles, as well as the influence of the COVID-19 “lockdown” on non-exhaust concentrations. Non-exhaust particulate matter (PM)10 concentrations were calculated using chemical tracer scaling factors for brake wear (barium), tyre wear (zinc), and resuspension (silicon) and as average vehicle fleet non-exhaust emission factors, using a CO2 “dilution approach”. The effect of lockdown, which saw a 32% reduction in traffic volume and a 15% increase in average speed on Marylebone Road, resulted in lower PM10 and PM2.5 traffic increments and brake wear concentrations but similar tyre and resuspension concentrations, confirming that factors that determine non-exhaust emissions are complex. Brake wear was found to be the highest average non-exhaust emission source. In addition, results indicate that non-exhaust emission factors were dependent upon speed and road surface wetness conditions. Further statistical analysis incorporating a wider variability in vehicle mix, speeds, and meteorological conditions, as well as advanced source apportionment of the PM measurement data, were undertaken to enhance our understanding of these important vehicle sources.
University Professors' Level Of Technological Skills And Its Relationship To The Orientation Towards E-Learning

The aim of this research is to determine the level of university professors’ technological skills and its relationship to the orientation towards electronic education. To achieve the objectives of this research, five null hypotheses were formulated. We used the descriptive method and chose a random sample of university professors totalling around (200) professors distributed among (14) colleges of Dhi Qar University. In order to achieve the research objectives, we prepared two tools: the first is a technological skills questionnaire consisting of (45) constructs which included six main skills (preparation and planning skill, implementation skill, mastery of scientific material, skill of using pedagogical techniques, evaluation skill, classroom management skill). The validity and robustness of the questionnaire were verified. The second tool is a scale to measure the orientation towards e-learning that included five areas (university professors' vision of e-learning, motivation in e-learning, the desired benefit of e-learning in society, fun in e-learning, self-concept in e-learning). The scale consisted of of (54) constructs the validity and robustness of which were also verified. The research tools were applied to the research sample of (200) professors and the research results were statistically treated using the Statistical Package for Social Sciences (SPSS) program. The results showed that the sampled professors have a higher-than-average level of technological skills as well as statistically significant positive orientation towards electronic education. Results also showed that there is a positive relationship between the level of university professors' mastery of technological skills and their orientation towards electronic learning. In light of the research results, we presented a number recommendations and proposals.
2D Detection Model of Defect on the Surface of Ceramic Tile by an Artificial Neural Network

The ceramic tile visual inspection process is divided into three parts: texture classification, color classification, and surface defect detection. In its application in the industry is a difficult process, because it is done manually involving many workers and done in a noisy environment with differences in temperature and humidity. This study emphasized the quality control based on the visual inspection automation system on the detection of a defective type of ceramic surface. The process performed is capturing an image, image processing, feature extraction, training, testing, and classification. In the preprocessing process are image resizing, RGB color conversion, segmentation and feature extraction. Features extraction using Gray Level Co-occurrence Matric (GLCM). The generated feature will be an artificial neural network (ANN) input in training and testing using Matlab 2013a to detect more than one type of surface defect with good accuracy. The artificial neural network training uses backpropagation with network architectures 14 input features, 27 hidden layers, 1 output. The learning rate used 0.001, 75 data training, and 23 data testing. The position and type of defect can be detected with 83% accuracy and error rate of 17%. Maximum time detection 1,06 seconds and minimum time detection 0,1 seconds. therefore by using automation system inspection, inspection error caused humans could be ignored and increased quality and productivity in production.
Dynamical Analysis on A Model of Cholera Epidemic with Quarantine, Vaccination, and Two Path of Transmissions

This research focus on dynamical analysis of a SIQRVB (Susceptible-Infectious-Quarantined-Recovered-Vaccinated-Bacterial) model. It describe the spread of cholerae with quarantine, vaccination and two transmission paths. As is well-known, there mainly exist two transmission paths for cholerae: environment-to-human transmission and human-to-human transmission. This model has two equilibrium points, that is disease-free equilibrium point which always exists and an endemic equilibrium point that exists with some conditions. The local stability of the equilibrium points is investigated by using Routh-Hurwitz criteria. The method of Next Generation Matrix is applied to get the basic reproduction number R0 . It can be shown numerically that disease-free equilibrium point is locally asymptotic stable when R0 < 1, while the endemic equilibrium point exist and locally asymptotic stable when satisfy Routh-Hurwitz criteria. Numerical simulations are given to illustrate the theoretical results.
Ethylene and its inhibitors affect the quality of processed sweet potatoes

Sweet potatoes roots (Ipomoea batatas Lam) have become the focus of research in recent years due to their unique nutritional and functional properties (Wang et al., 2016). Sweet potato has been identified as an important nutritious food, because contains reasonable amounts of bioactive compounds such as b-carotene, ascorbic acid, polyphenols, dietary fibre as well as vitamins, minerals, and proteins (Motsa et al., 2015).
Standardless Semi-quantitative Elemental Analysis of Steel Using Laser Ablation Time-of-flight Mass Spectrometry

A small high irradiance laser ablation and ionization time-of-flight mass spectrometer with orthogonal sample introduction was described. Nearly uniform relative sensitivity coefficients as well as satisfactory resolving power(~2200) were achieved for most of metal elements. Fairly good signal stability was obtained by automated step moving of the sample stage in short time intervals. Interferences of multiply charged ions and polyatomic ions were nearly eliminated in the spectrum by utilizing helium as the buffer gas in the ion source,which resulted in a relative clean background. Standardless semi-quantitative analysis of steel was realized and the limits of detection are about 10-6 g/g for most of metal elements.
Foliar Application of Ulva rigida Water Extracts Improves Salinity Tolerance in Wheat (Triticum durum L.)

This study investigated the effect of seaweed extract (SWE) sprays obtained from Ulva rigida on wheat plants (Triticum durum L., variety Karim) grown under salt stress conditions for six weeks. Three levels of NaCl (0, 34.22, 68.44 mM) and four different concentrations (0, 12.5, 25 and 50%) of Ulva rigida as a water extract were applied. The obtained results indicated that seaweed treated plants showed higher ability to tolerate salt stress (34.22 or 68.44 mM of NaCl) by a significant (p < 0.05) increase of plant growth and the photosynthetic pigment contents, compared to those of control (non-treated plants). Furthermore, there was a significant improvement in antioxidant enzyme activity, such as superoxide dismutase (SOD), isocitrate dehydrogenase (ICDH), glutathione peroxidase (GPx), glutathione reductase (GR) activities in the stressed plants, especially in those treated with 12.5% of SWE. Overall, our results suggest that the application of the Ulva rigida water extract could be used as a promising plant growth biostimulant for treating wheat plants under salinity stress.
Performance Analysis of Wi-Fi and LoRa Technology and its Implementation in Farm Monitoring System

One of the most interesting technology named Internet of Things made the world to move in smarter way. IoT is an idea of associating devices to internet which works automatically without human presence. Along with IoT different wireless technologies greatly supports in communication. Wide range communication and short range communication are made possible using IoT. These communications through IoT is done via technologies like Wi-Fi, Bluetooth, ZigBee, LoRa, NB-IoT, etc. In agriculture sector, these technologies helps in monitoring environmental factors in smarter way which yields more efficient crops but it works for only certain range. Some of the long range communicating technologies are NB-IoT, LoRa. Low Power wide area network will provide long range communication at low power consumption. LoRa is used to monitor the environmental factors in two different areas. Data from different areas is collected using LoRa device. Here, the comparisons in features of Wi-Fiand LoRa is graphically presented. Features like power, time, data rate for both Wi-Fi and LoRa has been analysed in this project. The data collected here is environmental factors such as moisture, temperature, humidity, motion and light. This project describes the features of Wi-Fi vs LoRa in agriculture for communication.
Optimal Management of Mobile Battery Energy Storage as a Self-Driving, Self-Powered and Movable Charging Station to Promote Electric Vehicle Adoption

The high share of electric vehicles (EVs) in the transportation sector is one of the main pillars of sustainable development. Availability of a suitable charging infrastructure and an affordable electricity cost for battery charging are the main factors affecting the increased adoption of EVs. The installation location of fixed charging stations (FCSs) may not be completely compatible with the changing pattern of EV accumulation. Besides, their power withdrawal location in the network is fixed, and also, the time of receiving the power follows the EVs’ charging demand. The EV charging demand pattern conflicts with the network peak period and causes several technical challenges besides high electricity prices for charging. A mobile battery energy storage (MBES) equipped with charging piles can constitute a mobile charging station (MCS). The MCS has the potential to target the challenges mentioned above through a spatio-temporal transfer in the required energy for EV charging. Accordingly, in this paper, a new method for modeling and optimal management of mobile charging stations in power distribution networks in the presence of fixed stations is presented. The MCS is powered through its internal battery utilizing a self-powered mechanism. Besides, it employs a self-driving mechanism for lowering transportation costs. The MCS battery can receive the required energy at a different time and location regarding EVs accumulation and charging demand pattern. In other words, the mobile station will be charged at the most appropriate location and time by moving between the network buses. The stored energy will then be used to charge the EVs in the fixed stations’ vicinity at peak EV charging periods. In this way, the energy required for EV charging will be stored during off-peak periods, without stress on the network and at the lowest cost. Implementing the proposed method on a test case demonstrates its benefits for both EV owners and network operator.