Miracle-dz/UniFAR-FTUs huggingface dataset:
Evolution of vortex knots

For the first time since Lord Kelvin's original conjectures of 1875 we address and study the time evolution of vortex knots in the context of the Euler equations. The vortex knot is given by a thin vortex filament in the shape of a torus knot [Tscr ]p,q (p>1, q>1; p, q co-prime integers). The time evolution is studied numerically by using the Biot–Savart (BS) induction law and the localized induction approximation (LIA) equation. Results obtained using the two methods are compared to each other and to the analytic stability analysis of Ricca (1993, 1995). The most interesting finding is that thin vortex knots which are unstable under the LIA have a greatly extended lifetime when the BS law is used. These results provide useful information for modelling complex structures by using elementary vortex knots.
Carcinoma Metastases Activating Cell Motility and Invasion Oncogene in Human MET Novel Somatic Mutations of the Updated Version

Several gene mutations responsible for human cancer initiation have been discovered, whereas only a few have been identified in association with the progression to metastasis. In this study, we screened a large panel of human sporadic cancers, metastases, and tumor cell lines for mutations in the tyrosine kinase domain of the MET receptor, crucially involved in invasive cell growth and motility during embryogenesis. MET activating mutations have been described previously in hereditary papillary renal cell carcinoma and in a few sporadic tumors. Summarizing results of this and our previous studies, we did not detect mutations in the MET kinase domain from 153 sporadic human cancers and 25 cancer cell lines, whereas we found somatic MET mutations in 10 of 46 lymph nodal and 2 of 14 pulmonary metastases. We identified four MET mutations in metastases. Two were known as MET germ-line mutations (H1112R and Y1248C), which predispose to hereditary renal cell carcinoma. One of the two novel mutations (N1118Y) changed an asparagine in the region of the glycine-rich ATP binding site, which is highly conserved in all of the kinases. The other (Y1253D) changed a critical tyrosine, known to regulate MET kinase activity, to a negatively charged residue. The MET receptors carrying either the N1118Y or the Y1253D mutation were constitutively active and conferred a motile-invasive phenotype on transduced carcinoma cells. The latter phenotype was additionally stimulated by the MET receptor ligand scatter factor/hepatocyte growth factor. These data suggest that MET might be one of the long sought oncogenes controlling progression of primary cancers to metastasis.
New Non-Linear Color Look-Up Table for Visualization of Brain Fractional Anisotropy Based on Normative Measurements – Principals and First Clinical Use

Fractional anisotropy (FA) is the most commonly used quantitative measure of diffusion in the brain. Changes in FA have been reported in many neurological disorders, but the implementation of diffusion tensor imaging (DTI) in daily clinical practice remains challenging. We propose a novel color look-up table (LUT) based on normative data as a tool for screening FA changes. FA was calculated for 76 healthy volunteers using 12 motion-probing gradient directions (MPG), a subset of 59 subjects was additionally scanned using 30 MPG. Population means and 95% prediction intervals for FA in the corpus callosum, frontal gray matter, thalamus and basal ganglia were used to create the LUT. Unique colors were assigned to inflection points with continuous ramps between them. Clinical use was demonstrated on 17 multiple system atrophy (MSA) patients compared to 13 patients with Parkinson disease (PD) and 17 healthy subjects. Four blinded radiologists classified subjects as MSA/non-MSA. Using only the LUT, high sensitivity (80%) and specificity (84%) were achieved in differentiating MSA subjects from PD subjects and controls. The LUTs generated from 12 and 30 MPG were comparable and accentuate FA abnormalities.
Enabling Virtual Sensing as a Service

In many situations, placing a physical sensor in the ideal position in or on the human body to acquire sensing data is incredibly difficult. Virtual sensors, in contrast to physical sensors, can provide indirect measurements by making use of other available sensor data. In this paper, we demonstrate a virtual sensing application developed as a service on top of a cloud-based health sensor data management platform called Wiki-Health. The proposed application “implants” virtual sensors in the human body by integrating environmental, geographic and personal sensor data with physiological models to compute temperature estimations of various parts of the body. The feasibility of the proposed virtual sensing service is supported by a case study. The ability to share computational models relevant to do calculations on measured data on the go is also discussed.
Distributed generation of state space for timed Petri nets

Development of complex systems is usually preceded by detailed studies of their models. For concurrent systems, Petri nets have proved to be a convenient modeling formalism because of their ability to express concurrency, synchronization, precedence constraints and nondeterminism. Timed Petri nets also take into account the durations of modeled activities, facilitating qualitative as well as quantitative analysis of models. The behavior of Petri nets is represented by their state spaces, which are Markov (or embedded Markov) chains. For large models these state spaces easily exceed the resources of a single computer system. Readily available networks of computers provide an attractive alternative to complex methods of state space reduction or aggregation. -- The main objective of this project is to use a cluster of PC's or workstations for the state space generation of timed Petri nets. The distributed algorithm uses a divide and conquer technique: disjoint regions of the state graph are constructed on different machines. On each machine the communication is separated from the computation part, and is performed by two specialized concurrent processes: one receiving, and one sending messages. The implementation is based on PVM (Parallel Virtual Machine) using a modified version of TPN-tools, a software package for the analysis of timed Petri nets. Experiments performed on a cluster of 32 PC's connected via a 100 Mbps Ethernet show almost linear speedup for some classes of timed Petri nets.
Putting adaptive granularity and rich context into learning objects

The content granularity and context information are two important factors to the efficiency and reusability of learning objects. The context information is necessary to facilitate the discovery and reuse of learning objects stored in global and/or local repositories. However, traditional learning objects are generally not conceived to incorporate with enough context information. Users have to do some extension of the description item set to fit their special use. In this paper, in order to deal with the issue mentioned above, we firstly introduce a context-rich paradigm, the related service driven tagging strategy, and a context model of learning objects. We further explain how to use the context information to realize the adaptive granularity of the content object. Finally, we show a simple concept model for online authoring systems that support the evolution from resource objects to learning objects.
Provisional chapter Stereo Vision and Scene Segmentation

Scene segmentation is the well-known task of identifying the image regions corresponding to the different scene elements or segments Sk , k = 1, 2. , N belonging to a predefined set S par‐ titioning the scene in N subsets, each one corresponding to a scene object or to a region of interest. Beside being an important problem by itself, segmentation is also employed as a preliminary step in many other computer vision tasks, e.g. object recognition or stereo vi‐ sion. A closely related problem, very relevant for the television and movie industries, is vid‐ eo-matting which consists in separating the background from the foreground.
The RRI Co-Authorship Network Analysis: 1965-2014

The year 2015 marked the fiftieth anniversary of West Virginia University’s (WVU) Regional Research Institute (RRI), which has played an important role in many scientific collaboration networks. Through social network analysis (SNA) focusing on the RRI research community since its inception in 1965, this paper illustrates the role that organizations and the networks they promote can play in scientific problem domains, promoting scholarly collaborations and co-authorship in the field of regional science. We analyzed an evolving WVU RRI co-authorship network that has grown and gained in complexity over time, in terms of (1) global metrics, (2) components and cluster analysis, (3) centrality and (4) PageRank and AuthorRank. The results of these analyses depict a well-developed and influential scientific collaboration structure within both WVU and the regional science research community.
Interallelic Transcriptional Enhancement as an in Vivo Measure of Transvection in Drosophila melanogaster

Transvection—pairing-dependent interallelic regulation resulting from enhancer action in trans—occurs throughout the Drosophila melanogaster genome, likely as a result of the extensive somatic homolog pairing seen in Dipteran species. Recent studies of transvection in Drosophila have demonstrated important qualitative differences between enhancer action in cis vs. in trans, as well as a modest synergistic effect of cis- and trans-acting enhancers on total tissue transcript levels at a given locus. In the present study, we identify a system in which cis- and trans-acting GAL4-UAS enhancer synergism has an unexpectedly large quantitative influence on gene expression, boosting total tissue transcript levels at least fourfold relative to those seen in the absence of transvection. We exploit this strong quantitative effect by using publicly available UAS-shRNA constructs from the TRiP library to assay candidate genes for transvection activity in vivo. The results of the present study, which demonstrate that in trans activation by simple UAS enhancers can have large quantitative effects on gene expression in Drosophila, have important new implications for experimental design utilizing the GAL4-UAS system.
A Scheme of Streaming Media Digital Rights Management in Cloud Conditions

It has been a widely concerned problem for the video producers and copyright business that how their digital content can be stored, retrieved and disseminated securely and effectively. Using the ability of cloud computing is an effective and convenient way to achieve processing a large number of video data. Aiming at how to protect the video content storage, distribution and using, meanwhile protecting the users' privacy, a DRM framework(VOD/LIVE) capable of supporting main streaming media service in cloud conditions has been proposed in this paper. The framework can provide rapid and variable granularity encryption module, real-time and efficient key distribution module and lightweight, transmission security authentication and authorization module three parts. The security, efficiency, scalability and access control granularity are compared in this paper with the traditional DRM system in the cloud-based streaming media service framework.
Diffusion limited aggregation and the fractal evolution of gene promoter networks

Gene promoter networks (GPNs) are systems-level representations of the base pair-sharing relationships (graph edges) among promoters (graph nodes). It has been shown in the bacterium E. coli that these networks can contain a fractal nucleus of strong associations suggesting a self-organizing complexity. Here I report results of twenty seven in silico simulations for a diffusion limited aggregation model which accounts for much of the fractal structure previously observed in GPNs. Parameters varied in the model included (a) the frequency of gene duplication events, and the extent of (b) attraction and (c) repulsion presented by the DNAprotein binding chemistry. Both duplication and attraction had significant effects on fractal topology of the GPN nucleus, whereas repulsion due to DNA-protein binding chemistry did not, at least for the levels explored in these simulations. Since repulsion is thought to be a key feature of fractal networks, it is likely that the repulsion in GPNs arises from the sparseness of the promoter space. The generation of a finite random set of promoters leads to sparse occupancy of promoter space which itself presents a considerable repulsion away from the consensus motif, working against the DNA-binding protein’s efforts to organize the system of promoters over evolutionary time. This interplay between attractive and repulsive forces in a GPN is sufficient to generate a fractal topology.
A concise review of the Space Time premise and its impact on modern wireless communication theory

In mid 90(s) researches of A. Paulraj\S. Kailath et al, E. Telatar and the historical research of G. Foschini\J. Gans “On Limits of Wireless Communications in a Fading Environment when Using Multiple Antennas”; instigated a new era in the modern wireless communication. The research of G. Foschini\J. Gans led to what became defined as Space Time (ST) premise. Their study depicted mathematical models for optimizing spatial sharing of the physical link (channel capacity) through use of multi-element antenna MEA (space dimension). Use of space dimension opened new avenues to produce efficient coding and modulation techniques by exploring various combinations between spatial and the established time\frequency techniques. It has become a part of todays WCT necessities, that wireless designers acquire a profound understanding of this premise. This paper reviews the capacity limits in MEA channel, as expressed by G. Foschini\J. Gans and E. Telatar and the impact of their findings on succeeding developments in WCT field. The paper includes a brief description of two selected ST schemes; Multi-Input-Multi-Output with Orthogonal-Frequency-Division-Multiplexing (MIMO-OFDM) and a method to exploit the location diversity of Multiple Antenna Sites (MAS) for spatial multiplexing “SFN-MAP-TDD-MIMO- OFDM technique”. Finally, paper predicts and discusses the next probable development roots in WCT.
Adapting Decision Tree-Based Method to Index Large DNA-Protein Sequence Datasets

Currently, the size of biological databases has increased significantly with the growing number of users and the rate of queries where some databases are of terabyte size. Hence, there is an increasing need to access databases at the fastest possible rate. Where biologists are concerned, the need is more of a means to fast, scalable and accuracy searching in biological databases. This may seem to be a simple task, given the speed of current available gigabytes processors. However, this is far from the truth as the growing number of data which are deposited into the database are ever increasing. Hence, searching the database becomes a difficult and time-consuming task. Here, the computer scientist can help to organize data in a way that allows biologists to quickly search existing information. In this paper, a decision tree indexing model for DNA and protein sequence datasets is proposed. This method of indexing can effectively and rapidly retrieve all the similar proteins from a large database for a given protein query. A theoretical and conceptual proposed framework is derived, based on published works using indexing techniques for different applications. After this, the methodology was proved by extensive experiments using 10 data sets with variant sizes for DNA and protein. The experimental results show that the proposed method reduced the searching space to an average of 97.9% for DNA and 98% for protein, compared to the Top Down Disk-based suffix tree methods currently in use. Furthermore, the proposed method was about 2.35 times faster for DNA and 29 times for protein compared to the BLAST+ algorithm, in respect of query processing time.
Approximate optimal control for reaching and trajectory planning in a humanoid robot

Online optimal planning of robotic arm movement is addressed. Optimality is inspired by computational models, where a “cost function” is used to describe limb motions according to different criteria. A method is proposed to implement optimal planning in Cartesian space, minimizing some cost function, by means of numerical approximation to a generalized nonlinear model predictive control problem. The Extended RItz Method is applied as a functional approximation technique. Differently from other approaches, the proposed technique can be applied on platforms with strict control temporal constraints and limited processing capability, since the computational burden is completely concentrated in an off-line phase. The trajectory generation on-line is therefore computationally efficient. Task to joint space conversion is implemented on-line by a closed loop inverse kinematics algorithm, taking into account the robot's physical limits. Experimental results, where a 4DOF arm moves according to a particular nonlinear cost, show the effectiveness of the proposed approach, and suggest interesting future developments.
Efficient method of collecting routing tables based on OSPF/iBGP monitoring

If a problem with IP communication occurs, IP network operators refer to the routing tables of the affected routers to check the routes to the destinations. There are a number of methods currently used for referring to routing tables. However, operators cannot refer to past routing tables using existing methods. The past routing tables are useful for IP network operation. For example, operators can find out how the influence of a network problem on routes spreads to the network by checking fluctuations in each routerpsilas routing table. In this paper, we propose a method of collecting every routerpsilas routing table within a domain based on the monitoring of routing protocols. In our method, we collect routing protocol messages and calculate all routerspsila routing tables within a domain in a concentrated manner using the same way where each router within a domain calculates its routing table. Routing tables are calculated whenever route status in IP networks changes, and calculated routing tables are stored so that operators can refer to them at any time in the future.
An Intelligent Environment Must Be Adaptive

Michael C. Mozer, University of Colorado What will the home of the future look like? One popular vision is that household devices-appliances, entertainment centers, phones, thermostats, lights-will be endowed with microprocessors that allow the devices to communicate with one another and with the home’s inhabitants. The dishwasher can ask the water heater whether the water temperature is adequate; inhabitants can telephone home and remotely instruct the VCR to record a favonte show; the TV could select news stones of special interest to the inhabitant; the stereo might lower its volume when the phone rings; and the clothes dryer might make an announcement over an intercom system when it has completed its cycle.
A Model Predictive Approach to Emergency Maneuvers in Critical Traffic Situations

Advanced Driver Assistance Systems (ADAS) that support drivers during emergency maneuvers have been considered in research and development projects before. It is commonplace that the two problems trajectory planning and vehicle control are solved in two different steps. The paper at hand proposes a real time capable method that solves the planning and control problem in one step. This is achieved by using a scheme similar to model predictive control combined with an environmental model to avoid the necessity of a precalculated reference signal, i.e. a trajectory. The real time capability is achieved by a rough discretization of the inputs, which yields the possibility to predict the plant's state trajectory for all possible combinations of discretized input values. Compared to an iterative minimization the computational burden is lower and can be determined deterministically. This contribution contains collision avoidance maneuvers in different traffic situations evaluated in simulation and a fixed base driving simulator.
Toward A Multidimensional Framework: Exploring The Constructed Identities And Pedagogical Styles Of Black Male Kindergarten Teachers In The South

Given the one-dimensional, essentialist view of Black male teachers as social change agents (i.e., role models and father-figures) (Brown, 2012; Rezai-Rashti, 2008), the purpose of this study was to examine the identities, the ability to support Black male students' success, and pedagogical styles of Black male kindergarten teachers in the South. Using a multidimensional conceptual framework including Black masculinity, study captured counterstories of culturally relevant Black male kindergarten teachers. The counterstories were used as a methodological tool to convey major themes which demonstrated Black male kindergarten teachers' ability to positively influence Black male kindergarteners academically using culturally relevant teaching. Findings revealed that Black male kindergarten teachers perceived themselves to be fictive brothers/fathers who fostered collaboration and built solidarity with the Black community to academically and socially support Black male kindergarteners in early childhood classrooms. Black male kindergarten teachers were also found to be pedagogues of culturally relevant classroom management practices. Black male kindergartners reported that their Black male teachers used hip-hop, sports, and mathematics literacies as instructional approaches. Black family members perceived Black male kindergarten teachers as Role Models who represented positive images of Black manhood for their Black male kindergarteners. They also regarded Black male
Penalized Maximum Likelihood Estimation of Multi-layered Gaussian Graphical Models

Analyzing multi-layered graphical models provides insight into understanding the conditional relationships among nodes within layers after adjusting for and quantifying the effects of nodes from other layers. We obtain the penalized maximum likelihood estimator for Gaussian multi-layered graphical models, based on a computational approach involving screening of variables, iterative estimation of the directed edges between layers and undirected edges within layers and a final refitting and stability selection step that provides improved performance in finite sample settings. We establish the consistency of the estimator in a high-dimensional setting. To obtain this result, we develop a strategy that leverages the biconvexity of the likelihood function to ensure convergence of the developed iterative algorithm to a stationary point, as well as careful uniform error control of the estimates over iterations. The performance of the maximum likelihood estimator is illustrated on synthetic data.