Miracle-dz/UniFAR-FTUs huggingface dataset:
Designing Generic Visualisations for Activity Log Data

Especially in lifelong or professional learning, the picture of a continuous learning analytics process emerges. In this process, heterogeneous and changing data source applications provide data relevant to learning, at the same time as questions of learners to data change. This reality challenges designers of analytics tools, as it requires analytics tools to deal with data and analytics tasks that are unknown at application design time. In this paper, we describe a generic visualization tool that addresses these challenges by enabling the visualization of any activity log data. Furthermore, we evaluate how well participants can answer questions about underlying data given such generic versus custom visualizations. Study participants performed better in 5 out of 10 tasks with the generic visualization tool, worse in 1 out of 10 tasks, and without significant difference when compared to the visualizations within the data-source applications in the remaining 4 of 10 tasks. The experiment clearly showcases that overall, generic, standalone visualization tools have the potential to support analytical tasks sufficiently well.
Decision making from economic and signal detection perspectives: development of an integrated framework

Behavior is comprised of decisions made from moment to moment (i.e., to respond one way or another). Often, the decision maker cannot be certain of the value to be accrued from the decision (i.e., the outcome value). Decisions made under outcome value uncertainty form the basis of the economic framework of decision making. Behavior is also based on perception—perception of the external physical world and of the internal bodily milieu, which both provide cues that guide decision making. These perceptual signals are also often uncertain: another person's scowling facial expression may indicate threat or intense concentration, alternatives that require different responses from the perceiver. Decisions made under perceptual uncertainty form the basis of the signals framework of decision making. Traditional behavioral economic approaches to decision making focus on the uncertainty that comes from variability in possible outcome values, and typically ignore the influence of perceptual uncertainty. Conversely, traditional signal detection approaches to decision making focus on the uncertainty that arises from variability in perceptual signals and typically ignore the influence of outcome value uncertainty. Here, we compare and contrast the economic and signals frameworks that guide research in decision making, with the aim of promoting their integration. We show that an integrated framework can expand our ability to understand a wider variety of decision-making behaviors, in particular the complexly determined real-world decisions we all make every day.
Implementing decision trees in hardware

In this paper several hardware implementations of decision trees (axis-parallel, oblique and non-linear) based on the concept of universal node and sequence of universal nodes are presented. Proposed hardware architectures are suitable for the implementation in both Field Programmable Gate Arrays (FPGA) and Application Specific Integrated Circuits (ASIC). Proposed architectures can be easily customized in order to fit a wide variety of application requirements, fulfilling their role as general purpose building blocks for System on Chip designs. Experimental results obtained on 23 datasets of standard University of California Irvine (UCI) Machine Learning Repository database suggest that the proposed architecture based on the sequence of universal nodes requires on average 56% less hardware resources compared with the previously proposed architectures, having the same throughput.
Speeding up mobile multimedia applications

Mobile devices are becoming ubiquitous multimedia computing platforms. However, due to limited computational power on these devices, a good mobile application requires far more considerations in algorithm design and optimization than for desktop systems. This demo shows two multimedia applications on a mobile phone: mobile visual search and panorama. The innovative components of the system include hybrid tracking and visual matching, optimal region classification and feature selection for faster and more reliable image-related applications, and an optimized image processing pipeline for multimedia applications on a mobile phone.
Evolving robots able to self-localize in the environment: the importance of viewing cognition as the result of processes occurring at different time-scales

In this paper we address the problem of synthesizing mobile robots able to solve problems in which they cannot merely react to sensory input, but have to maintain an internal state as well. More precisely, we shall show how autonomous robots synthesized through an evolutionary process can solve problems that necessarily require an ability to integrate sensorimotor information over time. By presenting the result of a set of experiments in which evolving robots are asked to navigate and self-localize in the environment, we shall show that successful results can be achieved by providing evolving individuals with neural controllers with neurons that: (a) vary their activity at different rates to detect regularities at different time-scales in the sensorimotor flow; and (b) use thresholded activation functions to detect events extending over time.
Stratospheric and mesospheric HO 2 observations from the Aura Microwave Limb Sounder

Abstract. This study introduces stratospheric and mesospheric hydroperoxyl radical (HO2) estimates from the Aura Microwave Limb Sounder (MLS) using an offline retrieval (i.e. run separately from the standard MLS algorithm). This new data set provides two daily zonal averages, one during daytime from 10 to 0.0032 hPa (using day-minus-night differences between 10 and 1 hPa to ameliorate systematic biases) and one during nighttime from 1 to 0.0032 hPa. The vertical resolution of this new data set varies from about 4 km at 10 hPa to around 14 km at 0.0032 hPa. A description of the methodology and an error analysis are presented. Comparisons against the Whole Atmosphere Community Climate Model (WACCM), the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) and the Far Infrared Spectrometer (FIRS-2) measurements, as well as photochemical simulations, demonstrate the robustness of the retrieval and indicate that the retrieval is sensitive enough to detect mesospheric HO2 layers during both day and night. This new data set is the first long-term HO2 stratospheric and mesospheric satellite record and it provides needed constraints to help resolve the O3 deficit problem and the "HOx dilemma".
Touch TV : Adding Feeling to Broadcast Media

In this paper, we discuss the potential role haptic, or touch, feedback might play in supporting a greater sense of immersion in broadcast content and describe some preliminary scenarios we have developed to explore how haptic content might be created and delivered within the context of a broadcast programme. In particular, this work has looked at two potential programme scenarios the creation of authored haptic effects for children’s' cartoons and the automatic capture of motion data to be streamed and displayed in the context of a sports broadcast. We believe that the interactive nature of this touch media has the potential to greatly enrich interactive TV by physically engaging the viewer in the programmed experience.
Endothelium-dependent relaxation of collateral microvessels after intramuscular gene transfer of vascular endothelial growth factor in a rat model of hindlimb ischemia.

BACKGROUND Recent investigations have demonstrated the ability of vascular endothelial growth factor (VEGF) to augment the development of collateral arteries in vivo. In vitro studies have suggested that the use of VEGF also improves the endothelium-dependent relaxation of collaterals at the microvascular level. The purpose of this study was to determine in vivo the extent to which vasomotor responses of collateral microvessels are altered after VEGF treatment. METHODS AND RESULTS Ischemia was induced in the hindlimb of 35 rats by excision of the femoral artery. Immediately thereafter, 400 microg of a plasmid encoding VEGF or ss-galactosidase (control) was transfected into limb muscles. Four weeks later, synchrotron radiation microangiography, with a spatial resolution of 30 microm, was performed to document the reactivity of collateral microvessels. Administration of the endothelium-dependent vasodilator acetylcholine failed to induce dilation of collateral microvessels in control animals. By contrast, profound dilation of collaterals was observed after acetylcholine in VEGF-treated animals. This response was evident in vessels with a linear appearance but not in those with an undulating appearance. The resulting blood flow in the ischemic limb after administration of acetylcholine in the control animals was only 64.6+/-17.0% of that of the contralateral normal limb, whereas blood flow was augmented to 106.1+/-8.4% in VEGF-treated animals (P<0.05). CONCLUSIONS These results demonstrate in vivo that the use of VEGF restores impaired vasomotor responses in some types of collateral microvessels, which may help to provide a basis for understanding the microcirculation after therapeutic angiogenesis with VEGF.
Random access for massive MIMO systems with intra-cell pilot contamination

Massive MIMO systems, where the base stations are equipped with hundreds of antenna elements, are an attractive way to attain unprecedented spectral efficiency in future wireless networks. In the "classical" massive MIMO setting, the terminals are assumed fully loaded and a main impairment to the performance comes from the inter-cell pilot contamination, i.e., interference from terminals in neighboring cells using the same pilots as in the home cell. However, when the terminals are active intermittently, it is viable to avoid inter-cell contamination by pre-allocation of pilots, while same-cell terminals use random access to select the allocated pilot sequences. This leads to the problem of intra-cell pilot contamination. We propose a framework for random access in massive MIMO networks and derive new uplink sum rate expressions that take intra-cell pilot collisions, intermittent terminal activity, and interference into account. We use these expressions to optimize the terminal activation probability and pilot length.
Temporal regulation of HIF-1 and NF-κB in hypoxic hepatocarcinoma cells

Regulations between NF-κB and HIF-1 have not been adequately addressed in previous research. Here, we report that hypoxia increased NF-κB in hepatocellular carcinoma cells. The HIF-1 protein level was rapidly induced by protein stabilization (by 2 hours) and then moderately decreased, whereas mRNA levels were reciprocally increased. We also found that NF-κB p50 and p65 (RelA), but not c-Rel, bound the HIF-1a promoter, thus increasing its transcription. In contrast, miR-199a-5p and miR-93, c-Rel downstream targets, decreased HIF-1α at both the mRNA and protein levels. Dicer1, a key enzyme in miRNA biogenesis, was decreased by acute hypoxia but was later increased by HIF-1, rather than by the above-mentioned NF-κB subunits. Thus, NF-κB both positively and negatively fine-tuned HIF-1 in hypoxic hepatocarcinoma cells.
From event-labeled gene trees with horizontal gene transfer to species trees

Evolutionary event relations such as orthology, paralogy and xenology provide important information on the evolutionary history of the investigated genes. It has recently been shown that there is an event-labeled gene tree that displays estimated event relations if and only if the (graph-representation of these) relations are so-called cographs, resp. , uniformly non-prime 2-structures. In particular, the respective event-labeled gene trees can then be constructed in polynomial time by utilizing solely the information of these event relations. In this contribution, we are concerned with the next conceptual step: the derivation of a species tree from an event-labeled gene tree $T$ that contains horizontal gene transfer, speciation and duplication events. We show that there is a species tree $S$ for $T$ if and only if certain triples that are displayed in $T$ are also displayed in $S$. To this end, a reconciliation map from $T$ to $S$ is provided that is consistent with so-called DTL-scenarios. Moreover, we provide a polynomial-time algorithm to decide whether there is a species tree for a given gene tree, and in the positive case, to construct the species tree and the respective reconciliation map.
A new non-liner correlation measure

To overcome the disadvantage which the traditional nonlinear correlation measure values do not range in [0, 1], in this paper, we propose the concept of the nonlinear correlation co-efficient (NCC), which indicate 0 and 1 denotes the weakest and the strongest relationship. We also develop a complete mathematical theory for the effects of variables distribution changes on nonlinear correlation coefficient. For multivariable data set, the nonlinear correlation information entropy (NCIE) is proposed for measuring the general relationship of a multivariable data set, which also ranges in the closed interval [0, 1]. Data sets generated from a logistic function are analyzed using the proposed NCIE. The results testify the suitableness and correctness of the proposed concepts as nonlinear correlation measure.
Contagion Effect Among Crude Oil and Food Prices in India

This paper examines the contagion effect among crude oil and wheat, soybean and maize spot prices in India using the daily prices data for 2010-2013. Using correlation, we find comovement among spot as well as among futures prices of commodities. The causality is present among spot prices of commodities. There is unidirectional contagion effect running from crude oil to soybean spot and, from maize spot and soybean spot to wheat spot. In the recent period, we find the movement of contagion effect from crude oil prices to food prices. The VAR model shows that commodities spot prices are influenced by its past prices and futures prices and also by the spot and futures prices of other commodities. The contagion effect among the crude oil and food prices as well as within the food market has been witnessed among wheat, soybean and maize spot prices even after controlling for futures prices in the Indian commodities market.
Whole Mitochondrial Genome Sequence of an Indian Plasmodium falciparum Field Isolate

Mitochondrial genome sequence of malaria parasites has served as a potential marker for inferring evolutionary history of the Plasmodium genus. In Plasmodium falciparum, the mitochondrial genome sequences from around the globe have provided important evolutionary understanding, but no Indian sequence has yet been utilized. We have sequenced the whole mitochondrial genome of a single P. falciparum field isolate from India using novel primers and compared with the 3D7 reference sequence and 1 previously reported Indian sequence. While the 2 Indian sequences were highly divergent from each other, the presently sequenced isolate was highly similar to the reference 3D7 strain.
A practical method for the software fault-prediction

In the paper, a novel machine learning method, SimBoost, is proposed to handle the software fault-prediction problem when highly skewed datasets are used. Although the method, proved by empirical results, can make the datasets much more balanced, the accuracy of the prediction is still not satisfactory. Therefore, a fuzzy-based representation of the software module fault state has been presented instead of the original faulty/non-faulty one. Several experiments were conducted using datasets from NASA Metrics Data Program. The discussion of the results of experiments is provided.
Department of Economics Working Paper Series a Search Cost Perspective on Duration of Trade a Search Cost Perspective on Duration of Trade

More than half of all US import relationships begin with less than $10,000 annually. The median relationship is observed to last just one year. The incidence and duration of these relationships are consistent with a matching model of international trade. The preponderance of small starting relationships reveals uncertainty present in formation of trade relationships. Initial size, reliability, and search costs matter and play an important role. Larger initial purchase results in longer relationships. Higher reliability and lower search costs lead to larger initial purchases and longer relationships.
Review of Relational Algebra for Dynamic Distributed Federated Databases

This paper reviews the coverage of formal Relational Algebra as it applies to distributed, federated databases in varying network topologies. The review shows that a number of Relational Algebra extensions allow distributed relations and federation of heterogeneous database schema. More concrete physical Relational Algebra extensions support access plans for multi-database query processing but lack cost functions dealing with specific network topologies such as scale-free networks, hyper-cubes and Kautz graphs. Statistic gathering techniques are highlighted which allow efficient distribution of database metrics, with the aim of providing optimized query processing. Keywords— Relational Algebra, Databases, Query Processing, Distributed, Federated, GaianDB, Network Topology
In-silico , in-vitro antibacterial activity and toxicity profile of new quinoline derivatives

The new substituted quinoline derivatives have been synthesized and characterized by various spectroscopic techniques. A prediction of activity spectra for substances (PASS) of synthesized quinoline compounds showed their probabilities of being active for the antibacterial activities. Therefore, all the newly synthesized compounds have been evaluated for their in-vitro antibacterial activity against Staphylococcus aureus and Escherichia coli. It has been observed that 6-chloro-4-phenylquinoline-2,3-dicarboxylic acid 4a selectively active against Gram (-)ve E. coli and 8-chloro-10phenyl-2,3-dihydropyridazino[4,5-b]quinoline-1,4-dione 5a showed selectivity against Gram (+)ve S. aureus. PASS prediction study indicates that the compound 5a as a potential candidate with a Pa 0.671, maximum from the series. According to the results obtained from brine shrimp (Artemia salina) lethality bioassay the compounds prove to be non toxic. The computer aided results are in good agreement with experimental results.
Up by their bootstraps: Online learning in Artificial Neural Networks for CMP uncore power management

With increasing core counts in Chip Multi-Processor (CMP) designs, the size of the on-chip communication fabric and shared Last-Level Caches (LLC), which we term uncore here, is also growing, consuming as much as 30% of die area and a significant portion of chip power budget. In this work, we focus on improving the uncore energy-efficiency using dynamic voltage and frequency scaling. Previous approaches are mostly restricted to reactive techniques, which may respond poorly to abrupt workload and uncore utility changes. We find, however, there are predictable patterns in uncore utility which point towards the potential of a proactive approach to uncore power management. In this work, we utilize artificial intelligence principles to proactively leverage uncore utility pattern prediction via an Artificial Neural Network (ANN). ANNs, however, require training to produce accurate predictions. Architecting an efficient training mechanism without a priori knowledge of the workload is a major challenge. We propose a novel technique in which a simple Proportional Integral (PI) controller is used as a secondary classifier during ANN training, dynamically pulling the ANN up by its bootstraps to achieve accurate predictions. Both the ANN and the PI controller, then, work in tandem once the ANN training phase is complete. The advantage of using a PI controller to initially train the ANN is a dramatic acceleration of the ANN's initial learning phase. Thus, in a real system, this scenario allows quick power-control adaptation to rapid application phase changes and context switches during execution. We show that the proposed technique produces results comparable to those of pure offline training without a need for prerecorded training sets. Full system simulations using the PARSEC benchmark suite show that the bootstrapped ANN improves the energy-delay product of the uncore system by 27% versus existing state-of-the-art methodologies.
Expectation-maximization (em) Software Algorithm: Procedure 1. Estimating Mean Concentrations for Potentially Toxic Pollutants When Certain Numbers of Observations Fall below an Established Detection Limit

A computer algorithm and software package in order to calculate maximum likelihood estimates using the EM algorithm (with or without bootstrapping on the sample) is provided. The programs are set up to read the complete-data log-likelihood for pollutant samples with certain numbers falling below an established detection limit. The programs can be changed to read the complete-data log-likelihood for estimating HIV transmission and pediatric AIDS incubation. In the case when all concentration values are found to be above the detection limit, there will be a closed form solution for µ and σ 2 for each given λ. The likelihood can be scanned to find the λ that maximizes the log likelihood and, hence, the likelihood. In the case when the sample contains values below the detection limit, the log-likelihood is non-linear in the parameters µ and σ 2 so that some modified procedure such as the Expectation-Maximization (EM) Algorithm, of Dempster et al. (1977), is necessary. Assuming all values in the sample are observed the complete-data log-likelihood is: λ µ σ σ σ µ λ) ln () () ln 2 2 2 1. The EM Algorithm is an iterative procedure which maximizes the expectation of ln L (, ,) ′ λ µ σ conditioned on the censoring pattern at each step.
Towards Cross-Lingual Information Retrieval using Random Indexing

We propose a new method for cross-lingual information retrieval that avoids direct translation of queries by implicit encoding of translations in a Random Indexing vector space model. It relies solely on a translation dictionary and source/target language text corpora, without the need for aligned multilingual text. Initial experiments show promising results for retrieval of related terms in Norwegian-English cross-lingual information retrieval. A number of possible improvements and extensions to the model are discussed.
GEN-R: Genetic Algorithm Based Model for Rubik's Cube Solution Generator

Evolutionary algorithm's implementation has solved problems in various disciplines including combinatorial optimization. Genetic algorithms especially have been able to provide more robust support for such problems. This work describes a model for generating solutions for a Rubik's cube based on genetic algorithm. Rubik's cube is a problem pertaining to discrete optimization. The proposed model named Gen-R takes scrambled state of a Rubik's cube as input. After implementation of a refined genetic algorithm and performing suitable optimization, the steps required to obtain the solved state are provided to the user. The model is flexible enough to adjust parameters of the algorithm as per the requirement. The experimental results obtained using Gen-R clearly establish relationships between parameters used in this model. Also the implementation of the model developed shows that it can effectively solve scrambled cubes and provide correct sequence of maneuvers.