Miracle-dz/UniFAR-FTUs huggingface dataset:
State of the Art of Learning Analytics in Higher Education

One of the characteristics of our world today is that it is continuously changing. Every aspect of our world has been transformed by the emerging technologies, ranging from our day to day activities to scientific and industrial developments. This progress has been made in the last few decades. It is also true for all aspects of education. The use of emerging technologies at all levels of education, such as intelligent tutoring systems, learning management systems, interactive learning environments, and online learning, gives access to vast volumes of data of the students. Student data collected automatically in online learning environments are usually not converted into useful information for teaching, although it is a good source of information. It is poorly used throughout the educational domain. A new concept has emerged to capture this educational big data called “Learning Analytics”. LA is about discovering hidden patterns in the educational process, assess student learning, and make predictions, which in turn provide a better understanding of teaching, learning, and interpretation of student’s data. Higher education institutes are adapting to the evolving concept of LA. It would help HEI’s to facilitates students to improve academic performance and enable teachers to keep track of individual students, identify student at-risk, and provide timely interventions. This paper provides the bird’s eye view of the research evidence on the usage of learning analytics in higher education across the world by reviewing the leading publications, research studies, and case studies in this area.
A Review of Ontological Models Applied for the Assistance of Persons with Disabilities

At least 15% of the population in the world has some type of disability. Unfortunately, this population has the problem of facing various accessibility barriers, to which technological barriers are also added. One of the most relevant obstacles is the one that arises as a result of the development of the technology itself when using the Information and Communication Technologies (ICT). Therefore, the objective of this article is to review the main uses of the Semantic Web tools and to group them together in order to be able to propose the design and construction of more personalized and flexible systems, which allows to help people with disabilities to perform some type of activity using ICT, in this way, knowledge can be modeled in different domains related to people who have some type of disability, using ontologies, and some ontological models can be reused for various types of disability depending on the case study. The usefulness of this study is to reveal that with the models presented, it is possible to construct a Meta ontology that includes some or all areas of disability.
Bridging Cultural Holes in Organizations: The Dynamic Structure of Social Networks and Organizational Vocabularies Within and Across Subunits

The mechanisms by which social networks and organizational vocabularies combine jointly to affect communication patterns across organizational boundaries remain largely unexplored. In this paper, we examine the mutually constitutive relation between the network ties through which organizational members communicate with each other and the vocabularies that they use to describe their organization. We suggest that the dynamic structure of social networks and organizational vocabularies is contingent on the formal design of organizational subunits. Within subunit boundaries, members who interact with each other are more likely to develop similar vocabularies over time. Interestingly, between subunits, the more two members share similar organizational vocabularies, the more likely they are to form a tie over time. We find empirical evidence for these arguments in a longitudinal study conducted among the managers of a multiunit organization. Organizational vocabularies, we suggest, may sustain communication patterns across organizational boundaries, thus bridging cultural holes within organizations.
Gα and Gβγ Require Distinct Src-dependent Pathways to Activate Rap1 and Ras*

The Src tyrosine kinase is necessary for activation of extracellular signal-regulated kinases (ERKs) by the β-adrenergic receptor agonist, isoproterenol. In this study, we examined the role of Src in the stimulation of two small G proteins, Ras and Rap1, that have been implicated in isoproterenol's signaling to ERKs. We demonstrate that the activation of isoproterenol of both Rap1 and Ras requires Src. In HEK293 cells, isoproterenol activates Rap1, stimulates Rap1 association with B-Raf, and activates ERKs, all via PKA. In contrast, the activation by isoproterenol of Ras requires Gβγ subunits, is independent of PKA, and results in the phosphoinositol 3-kinase-dependent activation of AKT. Interestingly, β-adrenergic stimulation of both Rap1 and ERKs, but not Ras and AKT, can be blocked by a Src mutant (SrcS17A) that is incapable of being phosphorylated and activated by PKA. Furthermore, a Src mutant (SrcS17D), which mimics PKA phosphorylation at serine 17, stimulates Rap1 activation, Rap1/B-Raf association, and ERK activation but does not stimulate Ras or AKT. These data suggest that Rap1 activation, but not that of Ras, is mediated through the direct phosphorylation of Src by PKA. We propose that the β2-adrenergic receptor activates Src via two independent mechanisms to mediate distinct signaling pathways, one through Gαs to Rap1 and ERKs and the other through Gβγ to Ras and AKT.
A Logical Framework of the Evidence Function Approximation Associated with Relevance Vector Machine

Relevance vector machine (RVM) is a Bayesian sparse kernel method for regression in statistical learning theory, which can avoid principal limitations of the support vector machine (SVM) and result in faster performance on test data while maintaining comparable generalization error. In this paper, we develop a logic framework of the evidence function approximation associated with RVM based on Taylor expansion instead of traditional technology called “completing the square. ” While constructing the term of completing the square, we have to find the term of completing the square by making use of some skill, which in practice increases the difficulty in dealing with the evidence function approximation associated with RVM. The logical framework in this paper based on Taylor expansion shows some advantages compared with the conventional method of completing the square, which is easier to be enforced due to the clear logical framework and avoids the difficulty in looking for the term of completing the square intentionally. From symmetry of covariance in a multivariate Gaussian distribution and algebraic knowledge, we derive approximation and maximization of the evidence function associated with RVM, which is consistent with the previous result using the novel logical framework. Finally, we derive the EM algorithm for RVM, which is also consistent with the previous result except that we use the precision matrix as the covariance.
A comprehensive study on face recognition: methods and challenges

ABSTRACT Face Recognition is the process of identifying and verifying the faces. Face recognition has vast importance in the field of Security, Healthcare, Banking, Criminal Identification, Payment, and Advertising. In this paper, we have reviewed various techniques and challenges for the face recognition. Illumination, pose variation, facial expressions, occlusions, aging, etc. are the key challenges to the success of face recognition. Pre-processing, Face Detection, Feature Extraction, Optimal Feature Selection, and Classification are primary steps in any face recognition system. This paper provides a detailed review of each. Feature extraction techniques can be classified as appearance-based methods or geometry-based methods, such method may be local or global. Feature extraction is the most crucial stage for the success of the face recognition system. However, deep learning methods have freed the user from handcrafting the features. In this article, we have surveyed state-of-the-art methods of last few decades and the comparative study of various feature extraction methods is provided. Article also describes the current challenges in the area.
Exploring direct citations between citing publications

This article defines and explores the direct citations between citing publications (DCCPs) of a publication. We construct an ego-centred citation network for each paper that contains all of its citing papers and itself, as well as the citation relationships among them. By utilising a large-scale scholarly dataset from the computer science field in the Microsoft Academic Graph (MAG-CS) dataset, we find that DCCPs exist universally in medium and highly cited papers. For those papers that have DCCPs, DCCPs do occur frequently; highly cited papers tend to contain more DCCPs than others. Meanwhile, the number of DCCPs of papers published in different years does not vary dramatically. This paper also discusses the relationship between DCCPs and some indirect citation relationships (e.g. co-citation and bibliographic coupling).
Changes in physico-chemical properties of wild date palm (Phoenix sylvestris) sap over its peak production period

Phoenix sylvestris Roxb. sap plays an important role in the diet of inhabitants of tribal area of West Bengal. In the present study the sap of 15 to 20 years old trees was collected separately during December to February, 2012-13 and 2013-14 from Haringhata block in Nadia district of West Bengal (India). The results indicated that the specific gravity of the sap changed little from 1.041 to 1.052 during December to February while the total soluble solids (TSS) were found maximum during February (14.33%). Chemical composition analysis revealed that a sap with highest pH (6.75) and lowest acidity (0.04%) was found during January while the sugar/acid ratio decreased from 325.47 during January to 42.93 during February. The sap of wild date palm had the maximum ascorbic acid content (18.75 mg/100 ml) during December while it decreased to 14.58 mg/100 ml during January and 13.75 mg/100 ml during February. Alcohol content was highest during February, whereas it decreased gradually during January and December. The sap also contained ample amount of phenol ranging from 67.90 mg/100 ml to 81.47 mg/100 ml. Total sugar content was greater during February (12.50%) than during January (11.72%) and December (11.37%). The overall results revealed that the wild date palm sap is a good nutrient supplement and is opulent in TSS, vitamin C and carbohydrate. So the sap can be used as a good alternative source of health drink and to alleviate malnutrition of poor tribal population of West Bengal (India).
Complex topographic configuration in the Hengduan Mountains shaped the phylogeographic structure of Chinese white-bellied rats

Several studies indicated that the Hengduan Mountains acted as refugia during the Pleistocene. Complex topographic configuration in this area might have played an important role in shaping the genetic divergence. Here, we investigated the phylogeography of the Chinese white-bellied rats, Niviventer confucianus, to test the role of mountain ranges in the Hengduan Mountains. Our results revealed that N. confucianus populations were clustered into three geographic lineages, which were consistent with the geographic origin, where, the Daxueshan Mountains but not the Daocheng Ice Cap regions contributed to the genetic divergence of N. confucianus populations. The Daxueshan Mountains separated N. confucianus populations into two distinct evolutionary lineages (clade A and clade B) and Motuo population formed monophyletic group (clade C). Results from the mismatch distribution and neutrality test analysis suggested a range expansion of the two clades (clade A and clade B). Divergence time estimation indicated that all splits within each clade occurred after the mid-Pleistocene. All results revealed that the complex topographic configuration in the Hengduan Mountains contributed to the genetic divergence of N. confucianus.
C. elegans Atlas

SECTION I. HANDBOOK1. Introduction to C. elegans Anatomy2. Epithelial SystemPart I. HypodermisPart II. Seam CellsPart III. Interfacial Epithelial CellsPart IV. Atypical Epithelial Cells3. Nervous SystemPart I. General DescriptionPart II. Neuronal Support Cells4. Excretory System5. Muscular SystemPart I. Musclea. Overviewb. Somatic Musclec. Nonstriated MusclePart II. GLR CellsPart III. Head Mesodermal Cell6. Coelomocyte System7. Alimentary SystemPart I. The Pharynxa. General Descriptionb. Pharyngeal NervousSystemPart II. The IntestinePart III. The Rectum and Anus8. Reproductive SystemPart I. OverviewPart II. The Somatic GonadPart III. The Germ LinePart IV. The Egg-laying Apparatus9. Cuticle10. Subcellular Organelles and Cytoskeletal ElementsSECTION II: ELECTRON MICROSCOPY CROSSSECTIONS OF THE WORM(50-75 sections each with an annotated and colored [opaque] version on the opposite page)SECTION III: INDIVIDUAL NEURONSSECTION IV: GLOSSARYIndex
A Novel Assorted Nonlinear Stabilizer for DC–DC Multilevel Boost Converter With Constant Power Load in DC Microgrid

The multilevel boost converter (MBC) has been widely adopted in the dc microgrid systems due to its high voltage gain and simple structure. In recent years, the power electronic loads, which usually behave as constant power loads (CPLs), are penetrating in microgrids. The incremental negative impedance of CPLs degrades the stability of microgrid systems. To ensure effective power flow and guarantee system stability, eliminating the undesired effects of CPLs is a necessity. In this article, a novel assorted nonlinear stabilizer, which is integrated with an extended nonlinear disturbance observer (NDO) and an adaptive backstepping controller, is proposed for stabilizing the MBC-fed microgrid system with CPLs. First, the reduced-order MBC model is transformed into the Brunovsky's canonical form using the exact feedback linearization technique. Second, owing to the NDO, fast system dynamic responses are achieved. Using the estimations of NDO, an adaptive backstepping controller is developed to strictly guarantee the microgrid bus voltage stability in the sense of a large signal. Simulation and experiment results are presented to verify the effectiveness and feasibility of the proposed stabilizer.
Bit Error Rate Performance of In-vivo Radio Channel Using Maximum Likelihood Sequence Estimation

In this paper we present the Bit Error Rate (BER) performance of equalizers using in-vivo channel response measured using Vector Network Analyzer (VNA). Including the use of a Bandwidth (BW) of 50 MHz in the simulations, the results are compared with multiple equalizers and it is shown that Maximum Likelihood Sequence Estimation (MLSE) equalizer outperformed the rest of the equalizers including linear equalizers Least Mean Square (LMS) and Recursive least sequence (RLS) and non-linear equalizer Decision Feedback Equalizer (DFE). The BER performance using MLSE showed significant improvement by improving the BER and outperforming the linear equalizer from 10−2 to 10−6 and DFE from 10−4 to 10−6 at $\text{Eb}/\text{No}= 14$ dB for in vivo radio communication channel at ultra wideband (UWB) frequencies. Furthermore, the un-equalized and equalized channel frequency response spectrum is also part of this article which presents the overall improvement between the two spectrums.
Policy and the structure of roll call voting in the US house

Abstract Competition in the US Congress has been characterised along a single, left-right ideological dimension. We challenge this characterisation by showing that the content of legislation has far more predictive power than alternative measures, most notably legislators’ ideological positions derived from scaling roll call votes. Using a machine learning approach, we identify a topic model for final passage votes in the 111th through the 113th House of Representatives and conduct out-of-sample tests to evaluate the predictive power of bill topics relative to other measures. We find that bill topics and congressional committees are important for predicting roll call votes but that other variables, including member ideology, lack predictive power. These findings raise serious doubts about the claim that congressional politics can be boiled down to competition along a single left-right continuum and shed new light on the debate about levels of polarisation in Congress.
Wideband tapered slot antenna for applications in ground penetrating radar

A planar slotted patch antenna is proposed for ground penetrating radar (GPR). The proposed antenna has a wide bandwidth ranging from 600 MHz to 4 GHz. Tapered slot feeding, curved ground plane, and slot loading are used for a wideband operation, whereas resistive loading is utilized for removal of notch band. Current loops made by slots are bifurcated with the use of 50 Ω resistors. The antenna is designed and optimized to achieve good performance, especially at lower frequencies while keeping the antenna's physical dimension relatively small. The time‐domain analysis of the antenna is performed, and the comparative graph is added after analysis to validate its performance in the impulse‐based radar. Furthermore, a sandbox test is conducted; the experimental results show the significance of the proposed antenna toward GPR application.
Baltic cyanobacteria – a source of biologically active compounds

Cyanobacteria are effective producers of bioactive metabolites, including both acute toxins and potential pharmaceuticals. In the current work, the biological activity of 27 strains of Baltic cyanobacteria representing different taxonomic groups and chemotypes were tested in a wide variety of assays. The cyanobacteria showed strain-specific differences in the induced effects. The extracts from Nodularia spumigena CCNP1401 were active in the highest number of tests, including protease and phosphatase inhibition assays. Four strains from Nostocales and four from Oscillatoriales increased proliferation of mitogen-stimulated human T cells. In antimicrobial assays, Phormidium sp. CCNP1317 (Oscillatoriales) strongly inhibited the growth of six fouling Gammaproteobacteria. The growth of monocotyl Sorghum saccharatum was inhibited by both toxin-producing and ‘non-toxic’ strains. The Baltic cyanobacteria were also found to be a rich source of commercially important enzymes. Among the 19 enzymatic activities tested, alkaline phosphatase, acid phosphatase, esterase (C4 and C8), and naphthol-AS-BI-phosphohydrolase were particularly common. In the cyanobacterial extracts, different peptides which may have been responsible for the observed effects were identified using LC-MS/MS. Their structures were classified to microcystins, nodularins, anabaenopeptins, cyanopeptolins, aeruginosins, spumigins and nostocyclopeptides.
Desempenho dos descendentes de clones de Eucalyptus spp. autofecundados e cruzados

Inbred and outbred Eucalyptus clone were assessed aiming to check the possible loss of vigor in the initial germination phases and growing in nursery and in t field conditions. Offsprings from two commercial clones were assessed as inbreds (C01 and C02) and as hybrids (C01 x C03 and C02 x C03). The work consisted of two phases. The first one was in the nursery, in a completely random design, with 4 treatments and 6 reps, in plots with 30 tubes with only one seed. The second one, in the field, used a randomized complete block design, with 4 treatments and 6 reps, with 18 plants per plots. The percentage of germination, germination speed index, survival and plant height were assessed at 35, 50, 65 and 80 days in the nursery and, in the field, the percentage of survival with 6 months and plant height with 2, 4 and 6 months. It was concluded that the germination, survival and the growing of plants resulted from inbred were similar to the hybrid, showing that the loss of vigor is not expressive for those characters in initial developmental phases of Eucalyptus spp
Fitness landscapes of gene regulation in variable environments

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Biostratigraphy and Paleoecological Inferences Based on Oligocene Calcareous Nannofossils
 from the Ceará
 Rise (ODP Leg 154, Site 929A): Equatorial Atlantic Ocean

The Ceará Rise is an aseismic feature located in the Equatorial Atlantic Ocean, between the Amazon Cone, Demerara Abyssal Plain and the Ceará Abyssal Plain, which represents a key area for the understanding of deep ocean facies. In the oil and gas field, the identification of calcareous nannofossil-based biozones is important for the age modeling and comprehension of depositional evolution of the sedimentary strata. The study of Oligocene calcareous nannofossil-based succession at the Ceará Rise helped to detect paleoecological trends during the Oligocene. Using a polarized light optical microscope, forty-four species were observed, described and accounted in fifteen samples. The biostratigraphic model includes the standard biozones NP23, NP24 and NP25, as well as the recently proposed biozone NP26 Clausicoccus fenestratus. Among the species found, Sphenolithus ciperoensis, Sphenolithus distentus and Sphenolithus predistentus were the most important biostratigraphic markers for the section. The quantification of the nannofossils, enabled the division of the studied section into eight distinct intervals according to the fluctuation in paleoproxies values and diversity indices: Interval A (CP17: Rupelian): oligotrophic assemblage of warmer surface waters; Interval B (CP18: Rupelian): temperate assemblage of mesotrophic/eutrophic surface waters; Interval C (CP18 and CP19a: Rupelian/Chattian): oligotrophic assemblage of warmer surface waters; Interval D (CP19a and CP19b: Chattian): temperate assemblage of mesotrophic/eutrophic surface waters; Interval E (CP19b: Chattian): oligotrophic assemblage of warmer surface waters; Interval F (CP19b: Chattian): temperate assemblage of oligotrophic surface waters; Interval G (CP19b: Chattian): temperate assemblage of oligotrophic surface waters; and Interval H (CN1a: Chattian): temperate assemblage of eutrophic surface waters.
Investigations on adaptive connectivity and shape prior based fuzzy graph‐cut colour image segmentation

Image segmentation is a challenging problem in computer vision with wide application. It is a process which considers the similarity criterion required to separate an image into different homogenous connected regions. First, an Optimized Adaptive Connectivity and Shape Prior in Modified Graph Cut Segmentation method has been applied to handle the structural irregularities in images. Second, an Optimized Adaptive Connectivity and Shape Prior in Modified Fuzzy Graph Cut Segmentation (Opac‐MFGseg) is proposed to partition the images based on feature values. In this method, a fuzzy rule based system is used with optimization algorithm to provide the information on how much a specific feature is involved in image boundaries. The graph obtained from this fuzzy approach is further used in adaptive shape prior in modified graph cuts framework. Moreover, this method supports moving images (videos). In such a situation, a fully dynamic method called Optimized Adaptive Connectivity and Shape Prior in Dynamic Fuzzy Graph Cut Segmentation (Opac‐DFGseg) method is proposed for the image segmentation. The effectiveness of the Opac‐MFGseg and Opac‐DFGseg methods is tested in terms of average sensitivity, precision, area overlap measure, relative error, and accuracy and computation time.