Miracle-dz/UniFAR-FTUs huggingface dataset:
Experiences from Blended Learning, Net-based Learning and Mind Tools

My experiences described in this article are based on lecturing at the intermediate level at Department of Computer and Information Science (IDI) at NTNU. The primary cause for initiating the research projects, which lasted several years and with a gradual increase in the use of ICT, was the tenfold increase in number of students over only a few years, from barely 20 to more than 250. Two positive results were a significant improvement in grades and a large increase in the proportion of students completing the course compared to earlier years, despite a strong increase in number of students and a decline of resources. Seventy percent of the students registered for the course completed and passed the exam, compared to forty nine percent the year before. For two other similar courses the completion percentages for this pilot year were thirty two percent and forty five percent, respectively. The average final grade improved from 3.2 to 2.5, where 1 is the highest grade in a scale from 1 to 6. The course was structured applying blended learning, net-based learning, and mind tools. The course was comprehensively evaluated with an external examiner and the results were compared to corresponding courses within the program with more traditional formats, and also to a more traditional format within the course itself. A traditional format includes lectures in an auditorium and approved/not approved when it comes to exercises in an obligatory exercise arrangement. The course was organized with a subject teacher, an exercise teacher (assistant teacher), and student assistants. There was one student assistant for each exercise group of 30 students.
A study on pre-competitive and post-competitive anxiety and stress of national level yoga performers

The purpose of the present study was to find out the difference between pre-competitive anxiety and stress and post-competitive anxiety and stress in national level male and female yoga performers. Total sixty (N=60) national level yogic practitioners i.e. thirty male performers (Gr. M) and thirty female performers (Gr. F) were randomly selected from National level School Yogasanas Competition, held at Delhi, 2016. Data were collected from performers using a Sports Competitive Anxiety Test (SCAT) consists of fifteen items which include 5 spurious items, 8 positive items and 2 negative items. Stress Questionnaire designed by The International Stress Management Association (ISMAUK) and it was employed to all the performers of Gr. M and Gr. F. The t-test was used to compare the mean of the anxiety and stress level between pre and post competition. The level significance was set at p<0.05. The result of the study reveals that:i) Precompetitive anxiety and stress of national level for both male and female yogic performers was higher than post competitive anxiety and stress levels. ii) Significant improvement was observed between pre and post competitive anxiety and stress of both national level male and female yogic performers. iii) Female yogic performers were significantly higher level of anxiety and stress than male yogic performers.
Sensory and cortical activation of distinct glial cell subtypes in the somatosensory thalamus of young rats

The rodent ventrobasal (VB) thalamus receives sensory inputs from the whiskers and projects to the cortex, from which it receives reciprocal excitatory afferents. Much is known about the properties and functional roles of these glutamatergic inputs to thalamocortical neurons in the VB, but no data are available on how these afferents can affect thalamic glial cells. In this study, we used combined electrophysiological recordings and intracellular calcium ([Ca2+]i) imaging to investigate glial cell responses to synaptic afferent stimulation. VB thalamus glial cells can be divided into two groups based on their [Ca2+]i and electrophysiological responses to sensory and corticothalamic stimulation. One group consists of astrocytes, which stain positively for S100B and preferentially load with SR101, have linear current–voltage relations and low input resistance, show no voltage‐dependent [Ca2+]i responses, but express mGluR5‐dependent [Ca2+]i transients following stimulation of the sensory and/or corticothalamic excitatory afferent pathways. Cells of the other glial group, by contrast, stain positively for NG2, and are characterized by high input resistance, the presence of voltage‐dependent [Ca2+]i elevations and voltage‐gated inward currents. There were no synaptically induced [Ca2+]i elevations in these cells under control conditions. These results show that thalamic glial cell responses to synaptic input exhibit different properties to those of thalamocortical neurons. As VB astrocytes can respond to synaptic stimulation and signal to neighbouring neurons, this glial cell organization may have functional implications for the processing of somatosensory information and modulation of behavioural state‐dependent thalamocortical network activities.
A Resolution of the Mutation Load Paradox in Humans

Current information on the rate of mutation and the fraction of sites in the genome that are subject to selection suggests that each human has received, on average, at least two new harmful mutations from its parents. These mutations were subsequently removed by natural selection through reduced survival or fertility. It has been argued that the mutation load, the proportional reduction in population mean fitness relative to the fitness of an idealized mutation-free individual, allows a theoretical prediction of the proportion of individuals in the population that fail to reproduce as a consequence of these harmful mutations. Application of this theory to humans implies that at least 88% of individuals should fail to reproduce and that each female would need to have more than 16 offspring to maintain population size. This prediction is clearly at odds with the low reproductive excess of human populations. Here, we derive expressions for the fraction of individuals that fail to reproduce as a consequence of recurrent deleterious mutation (ϕ) for a model in which selection occurs via differences in relative fitness, such as would occur through competition between individuals. We show that ϕ is much smaller than the value predicted by comparing fitness to that of a mutation-free genotype. Under the relative fitness model, we show that ϕ depends jointly on U and the selective effects of new deleterious mutations and that a species could tolerate 10’s or even 100’s of new deleterious mutations per genome each generation.
Serving the readers of scholarly documents: A grand challenge for the introspective digital library

The scholarly literature produced by human civilization will soon be considered small data, able to be portably conveyed by the network and carried on personal machines. This semi-structured text centric knowledge base is a focus of attention for scholars, as the wealth of facts, facets and connections in scholarly documents are large. Such machine analysis can derive insights that can inform policy makers, academic and industrial management, as well as scholars as authors themselves. There is another underserved community of scholarly document users that has been overlooked: the readers themselves. I call for the community to put more efforts towards supporting our own scholars (especially beginning scholars, new to the research process) with automation from information retrieval and natural language processing. Techniques that mine information from within the full text of a document could be used to introspect a digital library's materials, inferring better search metadata, improving scholarly document recommendation, and aiding the understanding of the text, figures, presentations and citations of our scholarly literature. Such an introspective digital library will enable scholars to assemble an understanding of other scholars' work more efficiently, and provide downstream machine reading applications with input for their analytics.
Conduction latency along CA3 hippocampal axons from rat

Relatively few physiological studies have been carried out on intrahippocampal axons. We have recorded compound potentials from fiber groups and the activity of individual axons at 22–25°C to characterize the conduction in subsets of the broad fan‐shaped CA3 pyramidal axonal tree, including the Schaffer collaterals and longitudinal branches. The same wide axonal branching was indicated by antidromic activation of individual CA3 pyramidal cells. The average compound action potential latency from the CA3 to the CA1 area (Schaffer collaterals) increased by 4.16 ± 0.06 ms/mm separation between the stimulation and registration electrodes. The impulses spread 31% faster in the 45‐degree oblique temporal than in the transverse direction across CA1. The latency of the longitudinal axons in the CA3 area increased by 6.19 ± 0.19 ms/mm. More impressive than these direction‐dependent differences in latency were the large differences between individual axons running in the same direction. For both the longitudinal axons and the Schaffer collaterals, there was a broad distribution of antidromic latencies for a given distance between the stimulation and recording points. Typically, the fastest impulses arrived in half the time of the slowest. The distribution of compound action potential latencies between two points in the tissue could be made narrower by surgical restriction of the thickness and width of the preparation. By comparison, the cerebellar parallel fibers showed a narrower distribution of their latencies than the Schaffer collaterals. Because the cerebellar fibers run more straight than Schaffer collaterals, this suggested that some of the latency differences of the latter were due to differences in the path length of the axons. One consequence of our findings is that synchronous firing of neighboring CA3 pyramidal cells does not necessarily give synchronous inputs to common target CA1 neurons. © 2003 Wiley‐Liss, Inc.
Generation of Con ict Resolution Maneuvers for Air Tra cManagement

We explore the use of distributed on-line motion planning algorithms for multiple mobile agents, in Air Traf-c Management Systems (ATMS). The work is motivated by current trends in ATMS to move towards decentralized air traac management, in which the aircraft operate in \free ight" mode instead of following prespeciied \sky freeways". Connict resolution strategies are an integral part of the free ight setting. In TPS96], a set of predeened coordination maneuvers has been proposed. The purpose of this paper is to extend this set of maneuvers to cover all possible connict scenarios involving multiple agents. A distributed motion planning algorithm based on potential and vortex elds is used. While the algorithm is not always guaranteed to generate yable trajectories, the obtained trajectories can serve as qualitative prototypes for coordination maneuvers between multiple aircraft. The actual maneuvers are generated by approximating these prototypes with trajectories made up of straight lines and arcs of circles.
Linear Programming Heuristics for the Graph Isomorphism Problem

An isomorphism between two graphs is a bijection between their vertices that preserves the edges. We consider the problem of determining whether two finite undirected weighted graphs are isomorphic, and finding an isomorphism relating them if the answer is positive. In this paper we introduce effective probabilistic linear programming (LP) heuristics to solve the graph isomorphism problem. We motivate our heuristics by showing guarantees under some conditions, and present numerical experiments that show effectiveness of these heuristics in the general case.
AN IMPROVED MODEL FOR SYMBOL RATE ESTIMATION BASED ON WAVELET TRANSFORM

In non-cooperative communication system, symbol rate is a crucial part of parameter estimation. Based on the wavelet transform, an improved symbol rate estimation model is proposed. Without a prior knowledge, we raised a better symbol rate pre-estimation method in view of corrected average periodogram’s smoothing power spectrum. By choosing the optimal wavelet scale and fast Fourier transform, we adopted a multi-synchronous reference algorithm to extract the symbol rate. Simulation demonstrates that the performance of accuracy and anti-noise is improved than traditional algorithms. The normalized mean square is lower than 10 at SNR=0dB and reached 10 when SNR=10dB, which is approaching more closely to CRLB.
Permutation Entropy and Its Main Biomedical and Econophysics Applications: A Review

Entropy is a powerful tool for the analysis of time series, as it allows describing the probability distributions of the possible state of a system, and therefore the information encoded in it. Nevertheless, important information may be codified also in the temporal dynamics, an aspect which is not usually taken into account. The idea of calculating entropy based on permutation patterns (that is, permutations defined by the order relations among values of a time series) has received a lot of attention in the last years, especially for the understanding of complex and chaotic systems. Permutation entropy directly accounts for the temporal information contained in the time series; furthermore, it has the quality of simplicity, robustness and very low computational cost. To celebrate the tenth anniversary of the original work, here we analyze the theoretical foundations of the permutation entropy, as well as the main recent applications to the analysis of economical markets and to the understanding of biomedical systems.
A NEURAL COMPUTATION APPROACH TO THE MODELLING ON GLUCOSE FUEL CELLS

The direct oxidation, in a fuel cell, of organic compounds derived from biomass is a very attractive way of converting chemical energy into electrical energy. Unlike electricity production by conventional heat cycles, a Carnot type relation does not limit the efficiency of energy production by fuel cells and efficiencies of 80% have been obtained in practice at useful power levels. Recently, the electrooxidation of D.glucose has become the subject of many investigations in connection with the problem of devising both electrochemical sensors for determining sugar concentration in blood and implantable glucose fuel cells indented for artificial hearts and heart pacers. In this study, the modelling of the electrooxidation of D.glucose on palladium electrode in alkaline medium was realised by using a three layer feed-forward ANN with error propagation learning algorithm which is the most widely and effectively used technique in ANN applications.
Detection of Android ad library focusing on HTTP connections and view object redraw behaviors

In recent years, the smart phone application market has expanded rapidly. One of reasons is the popularity of free applications. A developer acquires his revenues by including advertising libraries in his own application. However, some problems about these advertising libraries become clear from recent researches. Especially in the leakage of privacy information is known as a typical problem which advertising libraries cause. In order to solve this problem, the technology which detects advertisement libraries is important. In this paper, we propose a method for detection of Android ad library. We focus on the acquisition and redraw of advertising image operation which are the basic operations of mobile advertisement. Firstly, we tried running some applications with advertisements. Then, It turned out that mobile advertisements acquire advertising images from server and set that image on the screen at a fixed interval. By modifying AndroidOS, logging HTTP connections and View object redraw behaviors, we confirmed the ad image acquisition behavior. Moreover, to take advantage of the periodicity of this behavior, we carried out Fourier-transform the invocation time data of HTTP connections and redraw of View objects. Then, we extracted the periodicity by calculating correlation coefficient for these two data. From the value of correlation coefficient, it is possible to judge whether advertisement library is incorporated into an application or not. As a result, our proposal method results in a output of about 76 % detection rate.
Evaluating acoustic distance measures for template based recognition

In this paper we investigate the behaviour of different acoustic distance measures for template based speech recognition in light of the combination of acoustic distances, linguistic knowledge and template concatenation fluency costs. To that end, different acoustic distance measures are compared on tasks with varying levels of fluency/linguistic constraints. We show that the adoption of those constraints invariably results in an acoustically clearly suboptimal template sequence being chosen as the winning hypothesis. There are strong implications for the design of acoustic distance measures: distance measures that are optimal for frame based classification may prove to be suboptimal for full sentence recognition. In particular, we show this is the case when comparing the Euclidean and the recently introduced adaptive kernel local Mahalanobis distance measures.
Automated synthesis and deployment of cloud applications

Complex networked applications are assembled by connecting software components distributed across multiple machines. Building and deploying such systems is a challenging problem which requires a significant amount of expertise: the system architect must ensure that all component dependencies are satisfied, avoid conflicting components, and add the right amount of component replicas to account for quality of service and fault-tolerance. In a cloud environment, one also needs to minimize the virtual resources provisioned upfront, to reduce the cost of operation. Once the full architecture is designed, it is necessary to correctly orchestrate the deployment phase, to ensure all components are started and connected in the right order. We present a toolchain that automates the assembly and deployment of such complex distributed applications. Given as input a high-level specification of the desired system, the set of available components together with their requirements, and the maximal amount of virtual resources to be committed, it synthesizes the full architecture of the system, placing components in an optimal manner using the minimal number of available machines, and automatically deploys the complete system in a cloud environment.
Learning Linguistic Descriptors of User Roles in Online Communities

Understanding the ways in which users interact with different online communities is crucial to social network analysis and community maintenance. We present an unsupervised neural model to learn linguistic descriptors for a user’s behavior over time within an online community. We show that the descriptors learned by our model capture the functional roles that users occupy in communities, in contrast to those learned via a standard topic-modeling algorithm, which simply reﬂect topical content. Experiments on the social media forum Reddit show how the model can provide interpretable insights into user behavior. Our model uncovers linguistic differences that correlate with user activity levels and community clustering.
Loss of flight in the Galapagos cormorant mirrors human skeletal ciliopathies

Changes in the size and proportion of limbs and other structures have played a key role in the adaptive evolution of species. However, despite the ubiquity of these modifications, we have a very limited idea of how these changes occur on the genetic and molecular levels. To fill this gap, we studied a recent and extreme case of wing and pectoral skeleton size reduction leading to flightlessness in the Galapagos cormorant (Phalacrocorax harrisi). We sequenced and de novo assembled the genomes of four closely related cormorant species and applied a joint predictive and comparative genomics approach to find candidate variants. Here we report that function-altering variants in genes necessary for both the correct transcriptional regulation and function of the primary cilium contributed to the evolution of loss of flight in P. harrisi. Cilia are essential for Hedgehog signaling, and humans affected by skeletal ciliopathies suffer from premature arrest of bone growth, mirroring the skeletal features associated with loss of flight.
3,5-Dihydroxybenzoic Acid, a Specific Agonist for Hydroxycarboxylic Acid 1, Inhibits Lipolysis in Adipocytes

Niacin raises high-density lipoprotein and lowers low-density lipoprotein through the activation of the β-hydroxybutyrate receptor hydroxycarboxylic acid 2 (HCA2) (aka GPR109a) but with an unwanted side effect of cutaneous flushing caused by vascular dilation because of the stimulation of HCA2 receptors in Langerhans cells in skin. HCA1 (aka GPR81), predominantly expressed in adipocytes, was recently identified as a receptor for lactate. Activation of HCA1 in adipocytes by lactate results in the inhibition of lipolysis, suggesting that agonists for HCA1 may be useful for the treatment of dyslipidemia. Lactate is a metabolite of glucose, suggesting that HCA1 may also be involved in the regulation of glucose metabolism. The low potency of lactate to activate HCA1, coupled with its fast turnover rate in vivo, render it an inadequate tool for studying the biological role of lactate/HCA1 in vivo. In this article, we demonstrate the identification of 3-hydroxybenzoic acid (3-HBA) as an agonist for both HCA2 and HCA1, whereas 3,5-dihydroxybenzoic acid (3,5-DHBA) is a specific agonist for only HCA1 (EC50 ∼150 μM). 3,5-DHBA inhibits lipolysis in wild-type mouse adipocytes but not in HCA1-deficient adipocytes. Therefore, 3,5-DHBA is a useful tool for the in vivo study of HCA1 function and offers a base for further HCA1 agonist design. Because 3-HBA and 3,5-DHBA are polyphenolic acids found in many natural products, such as fruits, berries, and coffee, it is intriguing to speculate that other heretofore undiscovered natural substances may have therapeutic benefits.
Speeding Up Dynamic Shortest-Path Algorithms

Dynamic shortest-path algorithms update the shortest paths taking into account a change in an arc weight. This paper describes a new generic technique that allows the reduction of heap sizes used by several dynamic single-destination shortest-path algorithms. For unit weight changes, the updates can be done without heaps. These reductions almost always reduce the computational times for these algorithms. In computational testing, several dynamic shortest-path algorithms with and without the heap-reduction technique are compared. Speedups of up to a factor of 1.8 were observed using the heap-reduction technique on random weight changes and of over a factor of five on unit weight changes. We compare as well with Dijkstra's algorithm, which recomputes the paths from scratch. With respect to Dijkstra's algorithm, speedups of up to five orders of magnitude are observed.