Miracle-dz/UniFAR-FTUs huggingface dataset:
MDA5 complements TLR3 in suppression of neuroblastoma

Toll-like receptor3 (TLR3) has been confirmed to be differentially expressed in neuroblastoma (NB), and predicts a favorable prognosis with a high expression in tumor tissues. Treatment with TLR3 agonist - polyinosinic-polycytidylic acid [poly(I:C)] could induce significant but limited apoptosis in TLR3-expressing NB cells, suggesting that other viral RNA sensors, including melanoma differentiation-associated gene 5 (MDA5) and retinoic acid-inducible gene-I (RIG-I) in the cytosolic compartment might also be implicated in poly(I:C)-induced NB cell death. MDA5 and RIG-I were induced by poly(I:C) to express in two of six NB cell lines, SK-N-AS (AS) and SK-N-FI, which were associated with up-regulation of caspase9 and active caspase3. While knockdown of either MDA5 or RIG-I alone is ineffective to decrease caspase9 and active caspase3, simultaneously targeting MDA5 and TLR3 showed the best effect to rescue poly(I:C) induced up-regulation of mitochondrial antiviral signaling protein (MAVS), caspase9, active caspase3, and apoptosis in AS cells. Over-expression of MDA5 in FaDu cells resulted in significantly less colony formation and more poly(I:C)-induced cell death. Further studies in human NB tissue samples revealed that MDA5 expression in NB tissues predicted a favorable prognosis synergistically with TLR3. Our findings indicate that MDA5 may serve as a complementary role in the TLR3 activated suppression of NB.
Computational mechanisms of mechanosensory processing in the cricket

SUMMARY Crickets and many other orthopteran insects face the challenge of gathering sensory information from the environment from a set of multi-modal sensory organs and transforming these stimuli into patterns of neural activity that can encode behaviorally relevant stimuli. The cercal mechanosensory system transduces low frequency air movements near the animal's body and is involved in many behaviors including escape from predators, orientation with respect to gravity, flight steering, aggression and mating behaviors. Three populations of neurons are sensitive to both the direction and dynamics of air currents: an array of mechanoreceptor-coupled sensory neurons, identified local interneurons and identified projection interneurons. The sensory neurons form a functional map of air current direction within the central nervous system that represents the direction of air currents as three-dimensional spatio-temporal activity patterns. These dynamic activity patterns provide excitatory input to interneurons whose sensitivity and spiking output depend on the location of the neuronal arbors within the sensory map and the biophysical and electronic properties of the cell structure. Sets of bilaterally symmetric interneurons can encode the direction of an air current stimulus by their ensemble activity patterns, functioning much like a Cartesian coordinate system. These interneurons are capable of responding to specific dynamic stimuli with precise temporal patterns of action potentials that may encode these stimuli using temporal encoding schemes. Thus, a relatively simple mechanosensory system employs a variety of complex computational mechanisms to provide the animal with relevant information about its environment.
3D MULTIMEDIA PRESENTATIONS - INTEGRATING REMOTE SENSING, PHOTOGRAMMETRIC MODELLING AND CARTOGRAPHIC VISUALISATION

Recent developments in computer science have influenced the use of Geo-imagery by expert groups and the general public. The processing methods of remote sensing results and photogrammetric recording have became more accurate, effective and the work flow is accelerated. The results, in general, are often used for engineering, documentation purposes and for the communication of environmental systems. By this, is meant that the understanding of the system plus its internal coherence is improved by the use of new digital presentation methods. Cartography, as the communication interface of different user groups, tries to find and use more effectivly methods for communicating spatial information, by integrating the results of remote sensing and photogrammetry. With the use of multimedia, in the field of multimedia cartography, a new integrative communication form that uses interactivity, multitasking and different ways of coding information, can be explored. It has created a new paradigm for the visualisation of natural and cultural information related to topography. Within the cartographic communication process 3D multimedia cartography uses both symbolisation and generalisation to build communication models. In addition, for very large scales, elements of the data management model, like photogrammetric models of objects, may be directly included in these types of cartographic presentations. The focus is to understand relationships between spatial objects using the techniques of Geo-communication. This paper results from the integration of Geo-imagery and products from photogrammetry into the cartographic communication process using 3D multimedia cartography. It shows the effects on common understanding in terms of information and highlights the possibilities of software implementation methods.
Intelligent decision strategy for adaptive resource management in wireless cognitive network

With the development of cognitive radio technology, more surrounding cognition information is available to make wireless cognitive network self-adaptive to dynamic conditions of wireless networks. However, due to increasing cognition information, it is an interesting problem to achieve optimal strategies in numbers of adjustable parameters for relatively wide adjustable capacity in resource management of wireless cognitive networks. In this paper, an intelligent decision strategy with learning-reasoning mechanism and decision-evaluation process is proposed to classify, select and optimize the large adjustable parameters for network traffic end-to-end QoS requirements in wireless cognitive networks. Non-Dominated Sorting Genetic Algorithm and Fuzzy Decision Making are introduced in learning-reasoning strategy to abstract cognition information to “knowledge”, and save the “knowledge” into history-case database. Complex Combinatorial Optimization Probability method is used in decision-evaluation process to search for optimal solution of resource management in wireless cognitive networks. By simulations, the performances show that the proposed intelligent decision strategy can guarantee end-to-end QoS in dynamic conditions of wireless cognitive networks.
Supervised Classification and Unsupervised Classification

This project use migrating means clustering unsupervised classification (MMC), maximum likelihood classification (MLC) trained by picked training samples and trained by the results of unsupervised classification (Hybrid Classification) to classify a 512 pixels by 512 lines NOAA-14 AVHRR Local Area Coverage (LAC) image. All the channels including ch3 and ch3t are used in this project. The image is classified to six classes including water, vegetation, thin partial clouds over ground, thin clouds, low/middle thick clouds and high thick clouds plus unknown class for supervised classification. In total, the results using these three methods are very consistent with the original three-band overlay color composite image and the statistical mean vectors for each class are consistent using different methods and are reasonable. We also note that the ch3t temperature is usually much larger than the thermal channel-measured temperature for clouds, the colder the thermal temperature, the larger their difference. The ch3 reflectance is anti-correlated with the ch1 and ch2 reflectance, which is due to that high reflectance ice clouds can absorb most of the energy in this channel. Look carefully, the results of MMC and MLC trained by the results of MMC are better than that of the MMC trained by picked samples. The MLC trained by picked samples produces more unknown classes than that trained by MMC, which is probably due to that the standard deviation (multivariate spreads) for each class generated by MMC is usually larger than that of picked training samples. It takes more computation time to run MMC (5 iterations) than MLC if the classes are the same, but take more time to pick samples over and over to get comparable results. The results of MLC trained by picking samples is worse than the other two methods due to the difficulty of picking representative training samples. The hybrid supervised/unsupervised classification combines the advantages of both supervised classification and unsupervised classification. It doesn’t require the user have the foreknowledge of each classes, and can still consider the multivariate spreads and obtain accurate mean vectors and covariance matrixes` for each spectral class by using all the pixels image as training samples. Class Project Report: Supervised Classification and Unsupervised Classification 2
State-ofthe-art in utilizing Living Labs approach to user-centric ICT innovation-a European approach

Europe (and the rest of the western world) faces many challenges in the future: integration of the new member states, continued competition in important business sectors, solving the healthcare issues of an ageing population, to name but a few. Probably the most important challenge is increasing the overall productivity and job creation in the society in general. It is wellknown that developing the ability to be creative and innovative in a society influenced by stress, lack of time, and other factors, is perhaps the most important key towards increasing the overall productivity of a future European society. Rather than the ability to produce low cost products or creating new knowledge more efficient, innovation and creativity is the key to the future. Mathijs van Zupthen [1] outlines some of the new paradigms in a society more focused on innovation. This includes changing some of the underlying fundamentals of the overall economic system of today, which is based on that knowledge is scarce, owning properties and controlling rights is the means of controlling the economical system of today’s society. Technology enables new value-chains, often without its chain attributes, becoming more network-like and the user/citizen/consumer is given new tools and relations to participate in those value networks thereby becoming as much producer as consumer. This paper examines the state-of-the art in involving the user and organisations into the innovation process in various initiatives ongoing, examines the key practices that needs to be in place and gives examples on how those have been deployed. The proposed systemic innovation approach presented under the name of Living Labs contributes to the coming challenges of massdeployment of ICT solutions as a mean to further develop the society involving the citizens. It brings the users/consumers/citizens into the system of innovation, thereby leveraging on a larger mass of ideas, knowledge and experiences etc and substantially boosting the innovation capability.
Deep Learning Based Computer Vision Technique for Automatic Heat Detection in Cows

This paper presents a novel deep learning based computer vision technique for automatically monitoring the heat in cows by detecting the heat detector device such as Kamar and its colour. The proposed technique learns the device characteristics and colour properties. It extracts heat detectors from the back of the cow and classifies the device into colour change and no colour change. The main purpose of the technique is to identify the color change in heat detectors on the back of the cow body so that a camera can be installed around a water point or walk over weighing machine. The image data of cows with heat detectors have been collected. The technique has been evaluated on the collected data. The experimental results on a small data showed that the technique can automatically and accurately detect the colour change.
Dynamical behaviour on the parameter space: New populational growth models proportional to beta densities

We present new populational growth models, generalized logistic models which are proportional to beta densities with shape parameters p and 2, where p ≫ 1, with Malthusian parameter r. The complex dynamical behaviour of these models is investigated in the parameter space (r, p), in terms of topological entropy, using explicit methods, when the Malthusian parameter r increases. This parameter space is split into different regions, according to the chaotic behaviour of the models.
Scaffolding students' learning using test my code

As programming is the basis of many CS courses, meaningful activities in supporting students on their journey towards being better programmers is a matter of utmost importance. Programming is not only about learning simple syntax constructs and their applications, but about honing practical problem-solving skills in meaningful contexts. In this article, we describe our current work on an automated assessment system called Test My Code (TMC), which is one of the feedback and support mechanisms that we use in our programming courses. TMC is an assessment service that (1) enables building of scaffolding into programming exercises; (2) retrieves and updates tasks into the students' programming environment as students work on them, and (3) causes no additional overhead to students' programming process. Instructors benefit from TMC as it can be used to perform code reviews, and collect and send feedback even on fully on-line courses.
Empirical Distributions of F ST from Large-Scale Human Polymorphism Data

Studies of the apportionment of human genetic variation have long established that most human variation is within population groups and that the additional variation between population groups is small but greatest when comparing different continental populations. These studies often used Wright’s F ST that apportions the standardized variance in allele frequencies within and between population groups. Because local adaptations increase population differentiation, high-F ST may be found at closely linked loci under selection and used to identify genes undergoing directional or heterotic selection. We re-examined these processes using HapMap data. We analyzed 3 million SNPs on 602 samples from eight worldwide populations and a consensus subset of 1 million SNPs found in all populations. We identified four major features of the data: First, a hierarchically F ST analysis showed that only a paucity (12%) of the total genetic variation is distributed between continental populations and even a lesser genetic variation (1%) is found between intra-continental populations. Second, the global F ST distribution closely follows an exponential distribution. Third, although the overall F ST distribution is similarly shaped (inverse J), F ST distributions varies markedly by allele frequency when divided into non-overlapping groups by allele frequency range. Because the mean allele frequency is a crude indicator of allele age, these distributions mark the time-dependent change in genetic differentiation. Finally, the change in mean-F ST of these groups is linear in allele frequency. These results suggest that investigating the extremes of the F ST distribution for each allele frequency group is more efficient for detecting selection. Consequently, we demonstrate that such extreme SNPs are more clustered along the chromosomes than expected from linkage disequilibrium for each allele frequency group. These genomic regions are therefore likely candidates for natural selection.
A Robust Assessment of the Romanian Business Cycle

The paper provides potential output and output gap estimates for the Romanian economy in the period 1998 - 2008. Our approach consists in combining the structural method of the production function with several non-structural statistical detrending methods: Hodrick-Prescott, Kalman, band-pass, and wavelet transform filters. In this way, the obtained results benefit both from the economic foundations the production function method is relying on, as well as from the flexibility of the detrending techniques. The contribution of our analysis to the scarce literature dealing with the estimation of the cyclical position of the Romanian economy is twofold. First, we identify the contribution of the production factors to the potential output growth. Second, we aggregate the results obtained through filtering techniques in a consensus estimate ascribing to each method a weight inversely related to its revision stability. Our results suggest for the period 2000-2008 an average annual growth rate of the potential output equal to 5.8%, but on a descendant slope at the end of the analyzed period, due to the adverse developments in the macroeconomic context.
Reusable framework for Web-based teleoperation

The advent of the WWW presents an opportunity for a wide audience to make use of telemanipulation. Unfortunately, current efforts in Web-based telemanipulation are primarily undertaken by individual groups and lead to a plethora of specific solutions, instead of a general, reusable framework. Because of this, any groups seeking to enter into this field must spend a large amount of time building the interfaces necessary for remote monitoring and manipulation. Our proposed solution to this problem is to build a general framework of Java-based components that allow researchers to focus on their particular applications instead of building the infrastructure for Web interaction themselves. These components only require researchers to build an interface to our framework, instead of implementing a complete end-to-end solutions. This framework is designed to enable the manipulation of simple to medium complexity devices via the WWW. Example application domains include small robotic vehicles and robotic arms.
THE VISUAL ORBIT OF THE 1.1 DAY SPECTROSCOPIC BINARY σ2 CORONAE BOREALIS FROM INTERFEROMETRY AT THE CHARA ARRAY

We present an updated spectroscopic orbit and a new visual orbit for the double-lined spectroscopic binary σ2 Coronae Borealis (CrB) based on radial velocity measurements at the Oak Ridge Observatory in Harvard, MA and interferometric visibility measurements at the Center for High Angular Resolution Astronomy (CHARA) Array on Mount Wilson in California. σ2 CrB is composed of two Sun-like stars of roughly equal mass in a circularized orbit with a period of 1.14 days. The long baselines of the CHARA Array have allowed us to resolve the visual orbit for this pair, the shortest-period binary yet resolved interferometrically, enabling us to determine component masses of 1.137 ± 0.037 M☉ and 1.090 ± 0.036 M☉. We have also estimated absolute V-band magnitudes of MV(primary) = 4.35 ± 0.02 and MV(secondary) = 4.74 ± 0.02. A comparison with stellar evolution models indicates a relatively young age of 0.1–3 Gyr, consistent with the high-Li abundance measured previously. This pair is the central component of a quintuple system, along with another similar-mass star, σ1 CrB, in a ∼730-year visual orbit, and a distant M-dwarf binary, σ CrB C, at a projected separation of ∼10′. We also present differential proper motion evidence to show that components C & D (ADS 9979C & D) listed for this system in the Washington Double Star Catalog are optical alignments that are not gravitationally bound to the σ CrB system.
Keyword question answering system with report generation for linked data

We introduce a question-answering system that responds to a keywords-query by extracting information from linked data and generating reports in natural language (NL). Using entity disambiguation and distributed word similarity, we matched each keyword to a related entity and property in linked data. To extract keyword-related information, we used the entity and property to generate a SPARQL query. NL generation was performed using a NL generation template database. In our experiment, our system answered 95.1% of the user keyword questions in reasonable NL report.
Homogenization of Interfaces Between Rapidly Oscillating Fine Elastic Structures and Fluids

The paper studies the interaction of a periodic solid bristle structure with a fluid. Such problems arise, for example, when modelling biotechnological devices operating in liquids or when simulating epithelium surfaces of blood vessels. The fluid is described by the linearized Navier--Stokes equation whereas the solid part is governed by equations of linear elasticity. The interface conditions are accounted. A homogenized model of the structure is derived by employing the two-scale convergence technique. The model describes a new material which possesses some interesting properties.
Self-supervised bootstrapping of a movement primitive library from complex trajectories

Recent approaches have been advocated to learn a movement primitive library from demonstrations by using predefined motion features to identify and extract new movement primitives. In this paper, a new bootstrapping cycle is proposed which builds a suitable movement primitive library by (i) perceiving known primitives in complex trajectories, (ii) learn either new primitives or refines old ones, and (iii) consolidate the library by deleting unused primitives. The main contribution is that the movement primitives are in the center of the bootstrapping cycle and are learned self-supervised based on the notion of co-articulation. We evaluate the learning behavior of this bootstrapping cycle in a toy example and with complex handwriting trajectories. Finally, we demonstrate the bootstrapping cycle of movement primitives in a full skill learning example, where a human tutor teaches the humanoid robot iCub how to perform "fishing" motions with a fishing rod.
Cytoplasmic Tail Phosphorylation of the α-Factor Receptor Is Required for Its Ubiquitination and Internalization

G protein–coupled (GPC) receptors are phosphorylated in response to ligand binding, a modification that promotes receptor desensitization or downregulation. The α-factor pheromone receptor (Ste2p) of Saccharomyces cerevisiae is a GPC receptor that is hyperphosphorylated and ubiquitinated upon binding α-factor. Ubiquitination triggers Ste2p internalization into the endocytic pathway. Here we demonstrate that phosphorylation of Ste2p promotes downregulation by positively regulating ubiquitination and internalization. Serines and a lysine are essential elements of the Ste2p SINNDAKSS internalization signal that can mediate both constitutive and ligand-stimulated endocytosis. The SINNDAKSS serines are required for receptor phosphorylation which, in turn, facilitates ubiquitination of the neighboring lysine. Constitutive phosphorylation is required to promote constitutive internalization, and is also a prerequisite for ligand-induced phosphorylation at or near the SINNDAKSS sequence. Mutants defective in yeast casein kinase I homologues are unable to internalize α-factor, and do not phosphorylate or ubiquitinate the receptor, indicating that these kinases play a direct or indirect role in phosphorylating the receptor. Finally, we provide evidence that the primary function of phosphorylation controlled by the SINNDAKSS sequence is to trigger receptor internalization, demonstrating that phosphorylation-dependent endocytosis is an important mechanism for the downregulation of GPC receptor activity.