Miracle-dz/UniFAR-FTUs huggingface dataset:
If You Can Program, You Can Write: Learning Introductory Programming Across Literacy Levels

Aim/Purpose: This paper presents findings on a curricular intervention aimed at integrating computer programming with reading and writing in early elementary school. The purpose of this research was to explore the relation between students’ varying literacy levels and their level of success in mastering an introductory programming language. Methodology: This curricular intervention study was implemented in a single school district in southeastern Virginia. Of the district’s 33 elementary schools, eight schools received an external grant from the U.S. Department of Defense to introduce computer science in early elementary education. Standardized literacy test scores were correlated with internally developed, and age appropriate programming assessment scores from N = 132 second grade students. Contribution: This study is the first of its kind to look at how students at varying literacy levels succeed in mastering an introductory programming language when introduced through a literacy lens. Findings: The findings indicated that there was strong evidence for a weak, positive correlation between students’ literacy levels, as determined by the PALS assessment, and their programming mastery, as determined by the curricular programming assessments. The positive correlation suggests that there may indeed be underlying constructs that overlap between literacy and programming. Recommendations for Practitioners: Consider integrating computer programming as a foundational component of the literacy curriculum, especially in the early grades, where the two skill sets can mutually support one another. Recommendation for Researchers: Additional research is necessary, using a variety of literacy and programming measures, to continue to understand the relationship between emerging literacy and emerging computer programming skills. Impact on Society: Reimagining computer programming as a language has significant implications for how we teach programming in schools and how students then use programming out in the workforce. Future Research: Future work will repeat this curricular intervention with younger students: the district’s first grade and kindergarten classrooms. Introducing programming through the Coding as Literacy (CAL) approach even earlier in students’ literacy trajectories, we believe, will allow the positive impact of programming knowledge to influence students’ literacy development. In this next phase of our research agenda, we will collect pre and post literacy scores, both standardized and internally developed, to see the myriad ways that programming knowledge impacts literacy.
IMPACT OF SOME IMPROVED SURFACE IRRIGATION SYSTEM AND NITROGEN FERTILIZATION ON SOME WATER RELATIONS AND PRODUCTIVITY OF MAIZE CROP AT NORTH DELTA

To evaluate some modern surface irrigation systems and their effects on some water relations and nitrogen use efficiency on maize crop, a field experiment was conducted at El-Hamoul District, Kafr Elshiekh Governorate at North Delta. The experiment included traditional surface irrigation, alternative surface furrow irrigation, gated pipes and alternative gated pipes furrow, with three nitrogen treatments (0,101 and 135 Kg fed -1 ). The main obtained results could be summarized as follows:  Using gated pipes method for irrigating maize crop resulted in less amount of water applied compared to traditional surface method. On the other hand, gated pipes technique saved irrigation water by 19.5 and 31.4 % for alternative gated pipe technique and gated pipe technique, respectively compared to traditional surface irrigation. This method realized the lowest value of actual water consumptive use ,improved water application efficiency and water distribution efficiency compared to traditional irrigation method  There is no effect on maize yield due to different irrigation systems used in this study. Whereas, grain yield was increased by 110.9 % and 85.5% for the N recommended dose and 75% of the recommended dose, respectively over control treatment (0 Kg N Fed -1 ). It can be observed that alternative furrow irrigation by gated pipe achieved the highest grain and stalk yield followed by gated pipes under the highest nitrogen application rate.  Nitrogen use efficiency and N recovery % was increased with increasing N level. The highest value of N recovery % was found under alternative gated pipe system and the N recommended dose.
Digital Elevation Model from raw CoSSC TanDEM-X data (2015) in the area of Trail Valley Creek, Northwest Territories, Canada Metadata Documentation – 2019-05-28

Digital Elevation Model from raw CoSSC TanDEM-X data (2015) in the area of Trail Valley Creek, Northwest Territories, Canada Metadata Documentation – 2019-05-28 Sofia Antonova, Katharina Anders, Inga Beck, Julia Boike, Bernhard Höfle, Sabrina Marx Institute of Geography, Heidelberg University, Heidelberg, Germany Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Potsdam, Germany Umweltforschungsstation Schneefernerhaus, Garmisch-Partenkirchen, Germany Humboldt University, Geography Department, Berlin, Germany
An Effective Model for SMS Spam Detection Using Content-based Features and Averaged Neural Network

In recent years, there has been considerable interest among people to use short message service (SMS) as one of the essential and straightforward communications services on mobile devices. The increased popularity of this service also increased the number of mobile devices attacks such as SMS spam messages. SMS spam messages constitute a real problem to mobile subscribers; this worries telecommunication service providers as it disturbs their customers and causes them to lose business. Therefore, in this paper, we proposed a novel machine learning method for detection of SMS spam messages. The proposed model contains two main stages: feature extraction and decision making. In the first stage, we have extracted relevant features from the dataset based on the characteristics of spam and legitimate messages to reduce the complexity and improve performance of the model. Then, an averaged neural network model was applied on extracted features to classify messages into either spam or legitimate classes. The method is evaluated in terms of accuracy and F-measure metrics on a real-world SMS dataset with over 5000 messages. Moreover, the achieved results were compared against three recently published works. Our results show that the proposed approach achieved successfully high detection rates in terms of F-measure and classification accuracy, compared with other considered researches. Moreover, the achieved results were compared against three recently published works. The results show that the proposed approach achieved high detection rate, which was successful in terms of the F-measure and classification accuracy compared with other considered researches.
INFLUENCE OF IN OVO INOCULATION OF BIFIDOBACTERIA ON PRODUCTIVE PERFORMANCE, ANTIOXIDANT AND IMMUNE STATUS AND GUT MICROFLORAOF BROILER CHICKENS

This study was conducted to assess the potential effect of Bifidobacterium bifidum ATTC 29521(B. bifidum ) and Bifidobacterium longum ATTC 15707(B. longum) inoculated in yolk sac of developing embryo of broilers at 18 days of incubation on growth parameters, antioxidant and immunological status and gut microflora. Three hundred broiler breeder eggs (Cobb-500) obtained from maternal flock aged 49 weeks were individually weighed at day 18th of incubation then divided into six equal treatment groups as follow; C- (non-inoculated, negative control); C+ ( (inoculated with sterile distilled water (vehicle), positive control); B.bifidum H (inoculated with 5x109cfu/ ml); B. bifidum L (inoculated with 1x107cfu/ml); B. longum H (inoculated with 2x109cfu/ ml); and B. longum L (inoculated with 7x107cfu/ ml). Results showed that, at 35 days of age live body weight (LBW), average daily weight gain (ADWG) and feed conversion ratio (FCR) were significantly improved in bacterial inoculation groups compared with control groups. Improvement in antioxidant status was noted at 35 days of age in bacterial injected groups. Serum GSH content was insignificant increased while MDA content was significantly decreased in B. bifidum H and B. longum H groups. Moreover, SOD activity was significantly increased in B. bifidum H and B. longum L groups. Immunological parameters were also enhanced with inoculation of bifidobacteria strains. Serum concentration of total immunoglobulins, IgG and IgM were significantly increased with bifidobacteria inoculation compared with control groups. Furthermore, antibody titer against NDV was increased during the secondary response in injected groups than control groups. All examined microbiological parameters were also significantly affected by in ovo inoculation with bifidobacteria strains. A significant reduction was recorded for total bacteria, total coliform, fecal coliform and Salmonella spp. counts, however, bifidobacteria and total lactic acid bacteria were significantly increased in inoculation groups than controls. It is concluded that injection of B. bifidum and B. longum enhances growth, antioxidant and Immunological status, activities of gut microflora and reducing the pathogenic bacteria of Cobb-500 broiler chickens. The recommended dose of in ovo inoculation is 5x109cfu / ml of B. bifidum and 7x107cfu / ml of B. longum.
Robust H∞ Control for Path Tracking of Network-Based Autonomous Vehicles

This paper investigates the robust H∞ path-tracking control problem of network-based autonomous vehicles (AVs) with delay and packet dropout. Generally, both network-induced delay and packet dropout bring negative effects on the system stability and performance. A robust H∞ control scheme is proposed to realize the desired path tracking and lateral stability. The closed-loop system is asymptotically stable with the prescribed H∞ disturbance attention level if there exist some matrices satisfying certain linear matrix inequality (LMI) conditions. Furthermore, the proposed controller is robust to the parameter uncertainties and external disturbances. Simulation results are presented to verify the effectiveness of the proposed control scheme.
Variable Synthetic Depth of Field with Mobile Stereo Cameras

We implement a pipeline to perform variable depth of ﬁeld simulation for mobile devices based on common camera parameters. Overall, our pipeline given good depth information works well at adjusting focal distance, aperture size, and bokeh shape with minor artifacts. Though our local-block disparity matching algorithm performs poorly on the KITTI stereo challenge with 68% error, it is decent enough to estimate depth for synthetic depth of ﬁeld in large baseline, well-calibrated cameras. Estimating this information from a mobile smartphone camera proves to be a challenge for our disparity method due to differing lens parameters, asynchronous shots, and small baseline.
A State-of-Art on Cloud Load Balancing Algorithms

The cloud computing is alarmingly getting into mainstream for the booming companies and the research organizations as; they seek to gain benefits from its on-demand access, service models and deployment models. It provides unique features like ondemand access to shared pool of resources over internet in a self-accessible, dynamically scalable and metered manner. It is widely accepted because of its “pay-as-you-go” model. These features make this paradigm a buzzword in the area of high-performance distributed computing (HPDC). Though, this domain is widely accepted still it demands enhancements to bring out the optimized performance. The load balancing among the virtual machines (VMs) belongs to NP-hard problem as far as the equilibrium load distribution is concerned. The hardness of this problem can be defined by considering two factors such as: large solution space and polynomial bounded computation. One of the major issues in cloud computing which, needs serious attention is load balancing for its efficient performance. In the present work, a deep literature study has been carried out by considering the state of art algorithms for cloud load balancing. The algorithm includes traditional methods, heuristic, meta-heuristic, and hybrid approach. From the analysis and study of the methods presented in the deep literature survey, it has been observed that the existing heuristic algorithms are not generating near to optimal solution within polynomial time. The amalgamation of meta-heuristics, and hybrid-heuristics techniques have been proved to produce suboptimal solutions within reasonable time. This paper provides an extensive historical survey and comparative analysis on various existing load balancing (LB) literature. The presented work will be a help hand tool for researchers to design new efficient load balancing algorithms in the Cloud computing domain.
Modeling the evolution of pulse-like perturbations in atmospheric carbon and carbon isotopes: the role of weathering–sedimentation imbalances

Abstract. Measurements of carbon isotope variations in climate archives and isotope-enabled climate modeling advance the understanding of the carbon cycle. Perturbations in atmospheric CO2 and in its isotopic ratios (δ13C, Δ14C) are removed by different processes acting on different timescales. We investigate these differences on timescales of up to 100 000 years in pulse-release experiments with the Bern3D-LPX Earth system model of intermediate complexity and by analytical solutions from a box model. On timescales from years to many centuries, the atmospheric perturbations in CO2 and δ13CO2 are reduced by air–sea gas exchange, physical transport from the surface to the deep ocean, and by the land biosphere. Isotopic perturbations are initially removed much faster from the atmosphere than perturbations in CO2 as explained by aquatic carbonate chemistry. On multimillennial timescales, the CO2 perturbation is removed by carbonate compensation and silicate rock weathering. In contrast, the δ13C perturbation is removed by the relentless flux of organic and calcium carbonate particles buried in sediments. The associated removal rate is significantly modified by spatial δ13C gradients within the ocean, influencing the isotopic perturbation of the burial flux. Space-time variations in ocean δ13C perturbations are captured by principal components and empirical orthogonal functions. Analytical impulse response functions for atmospheric CO2 and δ13CO2 are provided. Results suggest that changes in terrestrial carbon storage were not the sole cause for the abrupt, centennial-scale CO2 and δ13CO2 variations recorded in ice during Heinrich stadials HS1 and HS4, though model and data uncertainties prevent a firm conclusion. The δ13C offset between the Penultimate Glacial Maximum and Last Glacial Maximum reconstructed for the ocean and atmosphere is most likely caused by imbalances between weathering, volcanism, and burial fluxes. Our study highlights the importance of isotopic fluxes connected to weathering–sedimentation imbalances, which so far have been often neglected on glacial–interglacial timescales.
Availability of Play Materials and Their Influence on Children Acquisition of Physical Skills in Koibatek Sub-County, Baringo County, Kenya

Play contributes to learners developing physical skills, their understanding of different concepts, their ability to solve problems, their self-confidence and motivation, and an awareness of the needs of others. The study was guided by this objective: To determine the availability of play materials and their influence on children acquisition of physical skills in Koibatek Sub-County, Baringo County. The study was guided by experiential learning theory by Kolb. The researcher adopted descriptive research design. The researcher targeted all the 250 ECDE centers in Koibatek Sub-county. Simple random sampling was used to select 152 ECDE centers and purposively selected 152 ECDE teachers, one teacher from each selected ECDE centers. Validity of the research tools were established by use of education experts at the university, while reliability of the instruments was tested using pilot data and a co-efficient threshold of more than 0.70 accepted. The data was collected using a questionnaire. Data findings were analyzed with the help of a Statistical Package for Social Sciences (SPSS) and the results presented using tables, graphs and narrative. The study findings indicated that there were adequate play materials in the ECDE centers. In addition, availability of play materials, significantly influenced acquisition of physical skills (p=0.000), with the later contributing to 34.0% of the physical skills. The study recommended enforcing the ECDE standard guidelines and deploying adequate, trained and qualified ECDE teachers to implement curriculum. The researcher paid keen attention to research ethical issues and got the informed consent of the respondents and guarded against plagiarism and ensured confidentiality.
Path Loss Modelling of UHF Radio Wave Propagation in Ado-Ekiti, Nigeria

In order to achieve optimal performance of a wireless communication system in any given environment, empirical path loss models are used to predict the received signal strength and power. We present an assessment of the quality of UHF signal reception and development of path loss model in the UHF range for the city of Ado-Ekiti in Nigeria, using the signal field strength of the broadcast signal of Ekiti State Television (EKTV). Measurements of received signal field strength within and around the city were carried out and analyzed, from which path loss models in the UHF range were developed for Ado-Ekiti using linear regression model – one being a general model, and the other is for the western region of Ado-Ekiti with irregular terrain. The result of the field strength measurements from EKTV in comparison with ITU recommendation for analogue terrestrial television service in band V shows that the quality of reception within Ado-Ekiti metropolis is good. Also, path loss prediction for Ado-Ekiti using three conventional empirical models in literature: Okumura-Hata model, COST-Hata model, and Egli model were performed, and the results obtained were compared with results from the developed models. Comparison shows that COST-Hata model has the highest standard deviation value of 24.11 from the general model while Okumura-Hata and Egli model has lower values of 22.76 and 22.30 respectively. For the model of the western region with irregular terrain, COST-Hata model also has the highest standard deviation value of 26.61 while Okumura-Hata and Egli each has a value of 25.29 and 21.85 respectively.
Blind Text Deblurring with Flutter Shutter

Photos taken from handheld devices often have some sort of motion blur; natural handshake and taking photos from a moving vehicle make it hard to take clear photos. In addition, being able to extract text from blurry photos is very beneﬁcial to those who are visually impaired. In this paper, we propose a method to perform blind text deblurring: deblurring without knowledge of the exact blur kernel, or point spread function (PSF), on both motion blurred images and images that are captured using the ﬂutter shutter technique. The blur kernel is learned from the given image using a least squares minimization approach, and the kernel is then processed to make it cleaner. We use the estimated kernel for deconvolution, using ADMM with a total variation prior. We show that images that are captured us-ing ﬂutter shutter and deblurred using our approach have higher quality than regular motion blurred images.
Detecting Bursts of Activity in Telecommunications

The high asymmetry of international termination rates, where calls are charged with higher values, are fertile ground for the appearance of frauds in Telecom Companies. In this paper, we present a solution for a real problem called Interconnect Bypass Fraud. This problem is one of the most expressive in the telecommunication domain and can be detected by the occurrence of burst of calls from speciﬁc numbers. Based on this assumption, we propose the adoption of a new fast forgetting technique that works together with the Lossy Counting algorithm. Our goal is to detect as soon as possible items with abnormal behaviours, e.g. bursts of calls, repetitions and mirror behaviours. The results shows that our technique not only complements the techniques used by the telecom company but also improves the performance of the Lossy Counting algorithm in terms of runtime, memory used and sensibility to detect the abnormal behaviours.
Corrosion Behavior of TiN/CrN Nanoscale Multi-layered Coating in Ringer's Solution

In this article, corrosion behavior of the single-layered TiN, single-layered CrN and multi-layered TiN/CrN coatings have been fabricated on 420C stainless steel (SS) by Cathodic Arc Evaporation (CAE) method in Ringer's solution was studied. The electrochemical appraisal was done by the Potentiodynamic Polarization (PDP) and Electrochemical Impedance Spectroscopy (EIS) tests. Results of PDP test revealed that all coated specimens have an increment in the polarization resistance (Rp) values (ranges from 438.2 to 593.6Ω.cm2) compared to bare SS (268.1Ω.cm2). Corrosion rate values for bare 420C SS and CrN, TiN and multi-layered TiN/CrN coatings were measured 0.086, 0.042, 0.050 and 0.068mpy, respectively. Furthermore, EIS results were showed that the single-layer CrN coating well depicted by an equivalent circuit with three time constants and has larger impedance and maximum logarithmic variation of C2. Finally, the corrosion performance results confirmed that single-layered CrN coating is an appropriate choice for deposition on 420C SS with the aim of application in general surgical instruments.
The adaptive value of developmental plasticity in response to individually variable cues

Developmental plasticity is one important way that organisms manage the risk created by a constantly changing environment. Information collected during development, if it helps predict environmental changes, can be used to guide development towards a suitable phenotype. This kind of predictive plasticity can be quite successful. On the other hand, if the environment is completely unpredictable, a last-ditch strategy is bet-hedging—randomizing the phenotype so that at least some offspring will get it right by chance. In situations where only partially reliable information is available, a well-adapted developmental strategy may strike a balance between predictive plasticity and bet-hedging, depending on how well developmental conditions predict environmental change. In this article, we develop a theoretical model which shows that it is not just the predictive value of developmental cues that matters, but also the correlation between those cues within and between generations. For example, an early spring rain may prompt many seeds to germinate early, with potentially disastrous results for the parent plant’s lineage if that year’s growing conditions turn out to be poor. However, if there are subtle differences in microclimate that affect the timing of germination, even if some seeds germinate early, others are likely to germinate late. In such circumstances a strongly differentiated response to individually variable developmental conditions can achieve two goals at once: it helps match the phenotype to the predicted environment, and at the same time creates phenotypic diversity—hedging bets in case that prediction is wrong.