Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning Design – creative design to visualise learning activities

Abstract The focus on quality improvements by institutions for better online and blended teaching can be delivered in different ways. This article reports on the implementation of this process and the approaches taken first, in terms of the design of new learning materials, and second, when reviewing the existing curriculum. The study aims to ascertain whether the combination of a collaborative, networked approach at the initial design stage, augmented with visualisations, has changed the way educators design their courses at The Open University, UK. Analysis of 148 learning designs shows both before and after the introduction of Learning Design, which of the pedagogic decisions that educators made substantially changed. Courses that were designed after the introduction of Learning Design were more focused on the development of a range of skills and included fewer assimilative activities (reading, watching videos and listening to audio). Our findings suggest that by visualising the design upfront, educators focused less on traditional teaching patterns, such as the ‘teach, practice, apply’ model. Remarkably, just by visualising initial decisions and working in collaborative workshops, educators created more student-centred and creative designs aimed to develop a range of skills which support students in both their studies and the workplace. Further studies are needed to establish whether these pedagogic decisions have an impact on student outcomes and whether these findings can be replicated in different institutions.
The Impact of Knowledge Generating Investment on GDP Growth

The article analyzes the impact of knowledge generating investments on the economic growth. It was found that the main investment cash flows are intangible, education, research and development costs. Since in Lithuania the core capital is mainly formed from tangible assets and intangible assets constitute only a small part of an emerging capital, the largest part of investment goes to education, research and development, while the smallest one – to intangible assets. The research is intended to support the impact of knowledge generating investments impact on GDP growth, interconnection and level of significance.
Towards building a similarity video search engine for the World-Wide-Web

We define similar video content as video sequences with almost identical content but possibly compressed at different qualities, reformatted to different sizes and frame-rates, undergone minor editing in either spatial or temporal domain, or even summarized into keyframe sequences. Building a search engine to identify such similar content in the World-Wide Web requires robust video similarity measurements, fast similarity search techniques on large databases, and intuitive organization of search results. We have proposed in [1] a randomized technique called the video signature (ViSig) method for video similarity measurement. In this paper, we present the design of a search engine that uses the ViSig method in finding similar video content on the web. Similar to many other content-based methods, the ViSig method uses high-dimensional feature vectors to represent video. To warrant a fast response time for similarity searches on high dimensional vectors, we propose a novel dimension reduction scheme on metric spaces that combines the triangle inequality with the classical Principal Component Analysis (PCA). We show experimentally that the proposed technique outperforms PCA, Fastmap, Triangle-Inequality Pruning, and Haar wavelet on signature data. Due to the randomness of the ViSig method and the distortion imposed by dimension reduction techniques, signature distances cannot always be measured accurately. Such errors can be mitigated by using a clustering algorithm to capture distance relationship between all pairs of signatures in the database. As such, we propose a robust clustering method based on minimum spanning tree. This algorithm achieves better retrieval performance on a ground-truth set than simple thresholding, single-link and complete-link clustering. The clustering structure can also be used to better organize search results, which is demonstrated by a prototype web search engine accessed through our web-site.
Nitrogen leaching and residual effect of barley/field bean intercropping

Cereal/legume intercropping may improve resource use efficiency in agroecosystems and increase yield per unit surface area and yield stability. Two field bean ( Vicia faba L.) and four barley ( Hordeum vulgare L.) cultivars were mono- and intercropped (additive design) in a 2-year lysimeter experiment on a sandy loam soil. The aim was to test the effect of the cropping system on dry matter and N yield of forage, the residual effect on the subsequent ryegrass crop ( Lolium multiflorum Lam. westerwoldicum ), and NO 3 -N leaching in the rotation. Land equivalent ratios were 1.65 for dry matter and 1.67 for N yield, indicating a clear advantage of the intercrop over sole crops. Both species suffered from competition, especially in terms of N resources, but barley was less affected. Nitrate leaching was the lowest from intercrop. Preceding crop significantly affected dry matter, N content and NO 3 -N leaching of ryegrass. Field bean sole crop gave the highest benefits to ryegrass in terms of forage dry matter and N content, but also the highest NO 3 -N leaching, followed by the intercrop and the barley sole crop. Barley/field bean intercropping may be an effective strategy to reduce land requirements, N leaching losses and fertilizer inputs, thereby increasing the sustainability of farming systems.
Empêcher la Détection Criminalistique de Filtrage Médian en Images

For median filtering anti-forensic purposes, this paper proposes an image variational deconvolution optimization framework, which is composed of a convolution term, an image fidelity term, and a prior term. The median filtering process is approximated using a spatially homogenous convolution kernel, which is reflected in the first convolution term. The second fidelity term keeps the processed image still similar to the median filtered image. The last image prior term regularizes the pixel value derivative of the obtained image so that its distribution is close to that of the original image. With an additional pixel value perturbation, the proposed median filtering anti-forensic method outperforms the state-of-the-art methods, with a better forensic undetectability against detectors and a higher visual quality of the processed image.
AC Ship Microgrids: Control and Power Management Optimization

At sea, the electrical power system of a ship can be considered as an islanded microgrid. When connected to shore power at berth, the same power system acts as a grid connected microgrid or an extension of the grid. Therefore, ship microgrids show some resemblance to terrestrial microgrids. Nevertheless, due to the presence of large dynamic loads, such as electric propulsion loads, keeping the voltage and frequency within a permissible range and ensuring the continuity of supply are more challenging in ship microgrids. Moreover, with the growing demand for emission reductions and fuel efficiency improvements, alternative energy sources and energy storage technologies are becoming popular in ship microgrids. In this context, the integration of multiple energy sources and storage systems in ship microgrids requires an efficient power management system (PMS). These challenging environments and trends demand advanced control and power management solutions that are customized for ship microgrids. This paper presents a review on recent developments of control technologies and power management strategies proposed for AC ship microgrids.
Supernova-regulated ISM. V. Space and Time Correlations

We apply correlation analysis to random fields in numerical simulations of the supernova-driven interstellar medium (ISM) with the magnetic field produced by dynamo action. We solve the magnetohydrodynamic (MHD) equations in a shearing Cartesian box representing a local region of the ISM, subject to thermal and kinetic energy injection by supernova explosions, and parameterized, optically thin radiative cooling. We consider the cold, warm, and hot phases of the ISM separately; the analysis mostly considers the warm gas, which occupies the bulk of the domain. Various physical variables have different correlation lengths in the warm phase: 40 , 50 , and 60 pc for the random magnetic field, density, and velocity, respectively, in the midplane. The correlation time of the random velocity is comparable to the eddy turnover time, about 10 7 year , although it may be shorter in regions with a higher star formation rate. The random magnetic field is anisotropic, with the standard deviations of its components b x / b y / b z having approximate ratios 0.5 / 0.6 / 0.6 in the midplane. The anisotropy is attributed to the global velocity shear from galactic differential rotation and locally inhomogeneous outflow to the galactic halo. The correlation length of Faraday depth along the z axis, 120 pc , is greater than for electron density, 60 – 90 pc , and the vertical magnetic field, 60 pc . Such comparisons may be sensitive to the orientation of the line of sight. Uncertainties of the structure functions of synchrotron intensity rapidly increase with the scale. This feature is hidden in a power spectrum analysis, which can undermine the usefulness of power spectra for detailed studies of interstellar turbulence.
Towards Spatial Knowledge Infrastructure ( SKI ) : Technological Understanding

Nowadays, a growing attention has been paid to extracting knowledge from voluminous and distributed spatial data. In this regard, a number of spatial data mining methods and algorithms have been developed, but there are a number of challenges for applying these methods in spatial knowledge extraction process. Like early years of GIS development, collecting data on a repository is still applied for knowledge extraction. In adaption, interoperability and usability are two important issues that have been neglected in traditional knowledge extraction methods. To respond the requirements from knowledge perspective a set of Web service-based geographical knowledge extraction is necessary. The services required a technological infrastructure or framework to extract useful knowledge from the different and geographically distributed data sources. In order to overcome this challenges, a general Spatial Knowledge Infrastructure (SKI) proposed to facilitate knowledge extraction in distributed scenarios. The SKI is a widespread interoperable framework through which geographical/spatial knowledge is created, organized, shared, managed and used in many domains. It creates a mechanism to make the necessary processes of geographic knowledge with the highest efficiency and usability. SKI's primary goal is to combine Spatial Data Infrastructure (SDI), Spatial Web Services (SWS) and Spatial Data Mining (SDM) concepts to facilitate geographical knowledge extraction as a collection of services. With a combination of SDI, SWS and SDM concepts this study presents the nature of SKI, including definition, levels, components, and architecture.
Baby, it's cold outside: Climate model simulations of the effects of the asteroid impact at the end of the Cretaceous

Sixty‐six million years ago, the end‐Cretaceous mass extinction ended the reign of the dinosaurs. Flood basalt eruptions and an asteroid impact are widely discussed causes, yet their contributions remain debated. Modeling the environmental changes after the Chicxulub impact can shed light on this question. Existing studies, however, focused on the effect of dust or used one‐dimensional, noncoupled atmosphere models. Here we explore the longer‐lasting cooling due to sulfate aerosols using a coupled climate model. Depending on aerosol stratospheric residence time, global annual mean surface air temperature decreased by at least 26°C, with 3 to 16 years subfreezing temperatures and a recovery time larger than 30 years. The surface cooling triggered vigorous ocean mixing which could have resulted in a plankton bloom due to upwelling of nutrients. These dramatic environmental changes suggest a pivotal role of the impact in the end‐Cretaceous extinction.
Validation of a measure of perceived environmental restorativeness.

Hartig, T. , Korpela, K. , Evans, G.W. , & Garling, T. Validation of a measure of perceived environmental restorativeness. Goteborg Psychological Reports, 1996, 26, No. 7. Restorative environments help renew psychological resources depleted in environments that do not fully support intended functions. The design of restorative environments can be aided and the understanding of underlying theory improved with an instrument for measuring psychological factors thought to work in restorative experiences. This paper reports four studies carried out to develop such a measure, the Perceived Restorativeness Scale (PRS). Each study used a variety of reliability and validity assessment strategies. Factor analysis was used to examine the stability of the measure’s factor structure across different sites and studies. To assess criterion, convergent, and discriminant validities, measures of emotional states and other environmental qualities were also completed for each site. The sites selected for evaluation differed on theoretically relevant dimensions so that the PRS’s sensitivity to meaningful differences among environments could be tested. The results were consistent across the studies, which also involved different subject populations (American, Swedish, Finnish) and presentation modes (on-site, video, photographic slides, remembered/imagined). Although factor analytic results indicate qualifications to keep in mind when interpreting PRS data, some
Analysis of White Matter Fiber Tracts via Fiber Clustering and Parametrization

White matter fiber bundles of the human brain form a spatial pattern defined by the anatomical and functional architecture. Tractography applied to the tensor field in diffusion tensor imaging (DTI) results in sets of streamlines which can be associated with major fiber tracts. Comparison of fiber tract properties across subjects requires comparison at corresponding anatomical locations. Clinical analysis studying fiber tract disruption and connectivity requires analysis along tracts and within cross-sections, which is hard to accomplish by conventional region of interest and voxel-based analysis. We propose a new framework via tractography, fiber clustering and parametrization. The resulting fiber tract models are parametrized with arc length and carry local properties derived from diffusion tensors, e.g. fractional anisotropy FA and apparent diffusion coefficient ADC, local shape characteristics derived from the Frénet frame (curvature, torsion) and area and shape of cross-sections. Comparison of transversal tracts and projection tracts between adults and neonates are shown. This extended set of features might lead to an improved understanding of diffusion properties and its association to brain development and eventually changes due to pathology.
Clinical Modalities and TherapeuticOutcomes; Between Ever-Smokers Versus Never-Smokers of Tuberculosis Patients in Penang, Malaysia

Aim: There is consistent evidence that tobacco smoking has been implicated as a risk factor for tuberculosis infection, disease and death. Study was aimed to identify the impact of smoking on Tuberculosis (TB) clinical characteristics and treatment outcome and to emphasize this association thus may be useful in the management of TB cases. Method: The retrospective, observational and cross-sectional cohort survey was done to compare disease characteristic and clinical presentation during treatment of TB. Result: Five hundred twenty four TB patients were consecutively recruited during the period of the study. Of this, 250 [47.7%] were never smokers. Ever smoking TB patients accounted for 274 [52.3%]. There were significant relationships between smoking status of TB patient with race and initial Mantoux test. But there were no significant as sociation between smoking habit and marital status, patients’ identities, history of chronic disease, history of contact to pulmonary TB patients and BCG scar. Ever smoker TB patients’ were four times more likely to have slower smear conversion at two months compared to non-smoker tuberculosis patients’. Conclusion: We found a high risk of death from smoking induce tuberculosis. Treatment outcomes were not statistically significant with/ without smoking. It was seen that smoking is consider as a risk factor for unfavorable outcomes among TB patients registered in DOTS program in term of therapeutic compliance.
Identification and promoter analysis of some important storage protein genes from wheat (Triticum aestivum L.).

A cDNA library was constructed using wheat seeds from a cultivar PH82-2-2 with superior bread-making quality, and differential hybridization was conducted by using RNA probes of unpollinated ovary, embryo and endosperm with 10, 000 clones from the cDNA library. 99 out of 800 clones, representing 22 unique genes, were identified as storage protein genes through sequencing blast. These 22 genes encode low molecular weight glutenin subunits (LMW-GS), high molecular weight glutenin subunits (HMW-GS), gliadin and avenins. Three clones 6A4, 6H11 and 8G17 encoding storage proteins were confirmed to express specifically in endosperm via Northern blot analysis. Southern blot result indicated there are at least three copies of 6A4 in wheat genome. A 2- kb promoter of 8G17 was isolated by Universal GenomeWalker Kit. The analysis of cis-acting elements revealed 8G17 promoter contained endosperm related transcriptional elements. The functional genomics data in this paper will provide valuable information for improvement of wheat flour quality.
Ceftazidime-Resistant Salmonella enterica, Morocco

To the Editor: Nontyphoidal salmonellosis (NTS) is a major food-borne illness worldwide. Extended-spectrum cephalosporins (ESCs) are currently preferred drugs for treatment of children with NTS. However, resistance to ESCs has emerged worldwide and has become a serious public health problem. This resistance is caused by production of various class A extended-spectrum β-lactamases (ESBLs) and class C cephalosporinases in Salmonella enterica (1).
Global Trade Models and Economic Policy Analyzes: Relevance, Risks and Repercussions for Africa

Computable general equilibrium models are widely used for trade policy analyses and recommendations. There is, however, increasing discomfort with the use of these models, especially in Africa. This article demonstrates that the results of several such studies of the impact of trade reforms in Africa differ drastically in terms of both magnitude and direction, failing to take account of key features of African economies. It also outlines potential consequences of the misuse of CGE models for policy evaluation and suggests pitfalls to be avoided. Copyright (c) The Authors 2008. Journal compilation (c) 2008 Overseas Development Institute.
ECRU: An Encoder-Decoder Based Convolution Neural Network (CNN) for Road-Scene Understanding

This research presents the idea of a novel fully-Convolutional Neural Network (CNN)-based model for probabilistic pixel-wise segmentation, titled Encoder-decoder-based CNN for Road-Scene Understanding (ECRU). Lately, scene understanding has become an evolving research area, and semantic segmentation is the most recent method for visual recognition. Among vision-based smart systems, the driving assistance system turns out to be a much preferred research topic. The proposed model is an encoder-decoder that performs pixel-wise class predictions. The encoder network is composed of a VGG-19 layer model, while the decoder network uses 16 upsampling and deconvolution units. The encoder of the network has a very flexible architecture that can be altered and trained for any size and resolution of images. The decoder network upsamples and maps the low-resolution encoder’s features. Consequently, there is a substantial reduction in the trainable parameters, as the network recycles the encoder’s pooling indices for pixel-wise classification and segmentation. The proposed model is intended to offer a simplified CNN model with less overhead and higher performance. The network is trained and tested on the famous road scenes dataset CamVid and offers outstanding outcomes in comparison to similar early approaches like FCN and VGG16 in terms of performance vs. trainable parameters.
Evaluating Pro-Poor Transfers When Targeting is Weak: The Albanian Ndihma Ekonomike Program Revisited

The Albanian Ndihma Ekonomike is one of the first poverty reduction programs launched in transitional economies. Its record has been judged positively during the recession period of the 1990s and negatively during the more recent growth phase. This paper reconsiders the program using a regression-adjusted matching estimator rst suggested by Heckman et al. (1997, 1998) and exploiting discontinuities in program design and targeting failures. We nd the program to have a weak targeting capacity and a negative and signi cant impact on welfare. We also nd that recent changes introduced to the program have not improved its performance. An analysis of the distributional impact of treatment based on stochastic dominance theory suggests that our results are robust.
Growth Hormone in Athletes

4 List of papers.5 Table of contents.6 Abbreviations.8 Introduction.9 Doping in sports.9 GH historical background.10 Physiology of GH secretion. 11 GH and muscles. 11 Lipolytic effects of GH. 12 Anti-natriuretic effects of GH. 12 GH effects on bone. 13 Doping with GH. 13 GH and exercise.14 Variability. 14 Supraphysiological doses of GH effects on muscles, power, exercise capacity and body composition.15 GH effects on IGFBP-4 and IGFBP-5. 16 Aims of the thesis. 17 Subjects and methods. 18 Subjects. 18 Study protocols. 18 Ethical aspects. 20 Methods. 20 Laboratory methods. 22 Statistical methods. 23 Summary of main results . 25 Paper I. 25 Paper II. 27 Paper III. 29 Paper IV. 32 Paper V. 34 General discussion. 37 Paper I. 37 Maximum exercise test. 37 Paper II. 39 Resting values. 39 Resting values versus post competition values.40 Paper III-V. 40 Side-effects. 40 IGF-I. 41
Standardized Procedures for Use of Nucleic Acid-Based Tools

Abstract : Groundwater and soil samples are frequently analyzed by academic and commercial organizations using molecular biological tools (MBTs) to detect unique genetic biomarkers associated with Dehalococcoides (Dhc) and other environmentally relevant microorganisms. The results of these analyses are increasingly used by site owners, consultants, and regulators to design and evaluate natural degradation and enhanced bioremediation systems. Despite the widespread use and importance of MBTs, there are currently no standardized methods for collecting, preserving, transporting, storing, or processing groundwater samples for analysis. More importantly, the lack of standardized reference materials: a) is a barrier to comparison of MBT results between laboratories and over time, b) makes confident assessment of the relationship between biodegradative microorganisms, such as Dhc, and remediation success a challenge and c) obscures the impacts of sampling methodologies, detection of procedural errors, and other biases that affect the accuracy, precision and reproducibility of MBT analysis. Currently, there is little understanding of how biomarker integrity is affected throughout sample collection to quantification process.