Miracle-dz/UniFAR-FTUs huggingface dataset:
Ringtail: Feature Selection For Easier Nowcasting

In recent years, social media “nowcasting”—the use of online user activity to predict various ongoing real-world social phenomena—has become a popular research topic; yet, this popularity has not led to widespread actual practice. We believe a major obstacle to widespread adoption is the feature selection problem. Typical nowcasting systems require the user to choose a set of relevant social media objects, which is difficult, time-consuming, and can imply a statistical background that users may not have. We propose Ringtail, which helps the user choose relevant social media signals. It takes a single user input string (e.g., unemployment) and yields a number of relevant signals the user can use to build a nowcasting model. We evaluate Ringtail on six different topics using a corpus of almost 6 billion tweets, showing that features chosen by Ringtail in a wholly-automated way are better or as good as those from a human and substantially better if Ringtail receives some human assistance. In all cases, Ringtail reduces the burden on the user.
Operative and Technical Complications of Vagus Nerve Stimulator Implantation

BACKGROUND: The treatment of refractory epilepsy by vagus nerve stimulation (VNS) is a well-established therapy option for patients not suitable for epilepsy surgery and therapy refractory depressions. OBJECTIVE: To analyze surgical and technical complications after implantation of left-sided VNS in patients with therapy-refractory epilepsy and depression. METHODS: One hundred five patients receiving a VNS or VNS-related operations (n = 118) from 1999 to 2008 were investigated retrospectively. RESULTS: At the time of operation, 84 patients were younger than 18 years, with a mean age of 10.5 years. Twenty (19%) patients had technical problems or complications. In 6 (5.7%) patients these problems were caused by the operation. The device was removed in 8 cases. The range of surgically and technically induced complications included electrode fractures, early and late onset of deep wound infections, transient vocal cord palsy, cardiac arrhythmia under test stimulation, electrode malfunction, and posttraumatic dysfunction of the stimulator. CONCLUSION: VNS therapy is combined with a wide spread of possible complications. Technical problems are to be expected, including electrode fracture, dislocation, and generator malfunction. The major complication in younger patients is the electrode fracture, which might be induced by growth during adolescence. Surgically induced complications of VNS implantation are comparably low. Cardiac symptoms and recurrent nerve palsy need to be taken into consideration.
Fractional quantum Hall effect via holography: Chern-Simons, edge states and hierarchy

We present three holographic constructions of fractional quantum Hall effect (FQHE) via string theory. The first model studies edge states in FQHE using supersymmetric domain walls in = 6 Chern-Simons theory. We show that D4-branes wrapped on 1 or D8-branes wrapped on 3 create edge states that shift the rank or the level of the gauge group, respectively. These holographic edge states correctly reproduce the Hall conductivity. The second model presents a holographic dual to the pure U(N)k (Yang-Mills-)Chern-Simons theory based on a D3-D7 system. Its holography is equivalent to the level-rank duality, which enables us to compute the Hall conductivity and the topological entanglement entropy. The third model introduces the first string theory embedding of hierarchical FQHEs, using IIA string on 2/Zn.
Structure and Synaptic Function of Metal Binding to the Amyloid Precursor Protein and its Proteolytic Fragments

Alzheimer’s disease (AD) is ultimately linked to the amyloid precursor protein (APP). However, current research reveals an important synaptic function of APP and APP-like proteins (APLP1 and 2). In this context various neurotrophic and neuroprotective functions have been reported for the APP proteolytic fragments sAPPα, sAPPβ and the monomeric amyloid-beta peptide (Aβ). APP is a metalloprotein and binds copper and zinc ions. Synaptic activity correlates with a release of these ions into the synaptic cleft and dysregulation of their homeostasis is linked to different neurodegenerative diseases. Metal binding to APP or its fragments affects its structure and its proteolytic cleavage and therefore its physiological function at the synapse. Here, we summarize the current data supporting this hypothesis and provide a model of how these different mechanisms might be intertwined with each other.
Microstrip phase shifter using ground-plane reconfiguration

In this paper, a new reconfigurable microstrip structure is presented where line impedance can be actively controlled to induce phase shift on a transmission-line signal. Micromachining is used to fabricate thin-film copper membranes in the ground plane below the transmission line. Actuation of these membranes enables control of transmission-line to ground-plane spacing and, thus, the line capacitance. The performance of this reconfigurable microstrip transmission line as a phase shifter is investigated between 5-32 GHz for a variety of membrane geometries. A phase shift of up to -32.1/spl deg/ at 15.00 GHz is achieved by actuating an array of five 4.3-mm-diameter membranes beneath a 30-/spl Omega/ microstrip line. A single 10.0-mm-diameter membrane achieved a phase shift of -25.57/spl deg/ at 15.05 GHz on a 50-/spl Omega/ line, while a 10.4-mm membrane achieved a phase shift of -55.5/spl deg/ at 14.25 GHz on a 30-/spl Omega/ line. Both single and multiple series ground-plane membranes are possible, and they can be activated with discrete or continuous control signals, individually or together. Discrete and continuous phased array beam steering are, therefore, feasible.
Research on sentiment analysis technology and polarity computation of sentiment words

With the rapid development of E-Commerce, customer reviews on a product grows rapidly. This makes it difficult for a potential customer to make an informed decision on purchasing the product, as well as for the manufacturer of the product to keep track and to manage customer opinions. All these works strongly depend on polarity analysis of sentiment words. This paper proposes a novel approach to realize polarity analysis of new words, in addition implement quantitative computation of sentiment words and automatic expansion of polarity lexicon. Experimental results show the feasibility and effectiveness of our approach.
Open Innovation and Firm's Survival: An empirical investigation by using a linked dataset of patent and enterprise census

This paper uses patent filings as an indicator of innovation and investigates the relationship between innovation and firms' survival, based on the linked dataset of the Census of Establishment and Enterprise and the Institute of Intellectual Property (IIP) Patent Database for Japanese firms. We have constructed the indicators on the organization of innovative activities, such as external collaboration in inventions and the type of collaborative partners, and disentangle two competing factors, i.e., technological capability (positive influence on firms' survival) and commercial risk (negative influence on firms' survival). We found that the risk factor surpasses the capability factor, thus the impact of patenting on survival has a negative correlation with firms' survival at the end.
Quantifying the Hurricane Catastrophe Risk to Offshore Wind Power

The U.S. Department of Energy has estimated that over 50 GW of offshore wind power will be required for the United States to generate 20% of its electricity from wind. Developers are actively planning offshore wind farms along the U.S. Atlantic and Gulf coasts and several leases have been signed for offshore sites. These planned projects are in areas that are sometimes struck by hurricanes. We present a method to estimate the catastrophe risk to offshore wind power using simulated hurricanes. Using this method, we estimate the fraction of offshore wind power simultaneously offline and the cumulative damage in a region. In Texas, the most vulnerable region we studied, 10% of offshore wind power could be offline simultaneously because of hurricane damage with a 100‐year return period and 6% could be destroyed in any 10‐year period. We also estimate the risks to single wind farms in four representative locations; we find the risks are significant but lower than those estimated in previously published results. Much of the hurricane risk to offshore wind turbines can be mitigated by designing turbines for higher maximum wind speeds, ensuring that turbine nacelles can turn quickly to track the wind direction even when grid power is lost, and building in areas with lower risk.
MODELING AND OPTIMIZATION OF G-PROTEIN COUPLED RECEPTOR SIGNAL TRANSDUCTION

Signal transduction is the process by which a cell converts one kind of signal or stimulus into another. In this process, G-protein coupled receptors (GPCRs) are considered a major class of membrane protein receptors. GPCRs play a critical role in signal transduction, and they are important pharmacological drug targets. Motivated by some specific experimental data, we construct a mathematical model to investigate a signaling system of interest. The model is composed of mass-action ordinary differential equations that describe ligand-receptor and receptorG-protein interactions. Because the kinetic reaction rates in the signaling processes previously gathered in reliable in vivo and in vitro experiments are limited to a small number of known values, we apply a genetic algorithm (GA) to estimate the parameter values in our model. In order to carry out the parameter estimation, we use the Augmented Lagrangian Genetic Algorithm (ALGA) with help from the mathematical theorem of infinite norm. This method ensures a faster parameter estimation speed in the modeled system. In addition, mathematical analyses are also performed. Some good agreement between analytic, numerical and experimental data was found. The simulation results of the model are extensively discussed and compared with the experimental data. G-PROTEIN COUPLED RECEPTOR SIGNAL TRANSDUCTION 19
Annotating Learning Materials on Moodle LMS

Learning management system (LMS) plays a critical role in current pedagogy. Along with the concept of WEB 2.0, web has become an interactive platform for contribution and collaboration. Moodle open source LMS is one of the most popular learning management systems currently. It will be valuable for the learners to view the teaching materials online and perform annotating operations on them which are traditionally executed on printed materials. To meet these requirements, a Moodle module: Learning Annotation for Moodle (LAM) was built. With this module, students can see both their own annotations and different thoughts in other students’ mind. Instructors can promote teaching by viewing students’ annotations.
Modeling Steering Using the Queueing Network — Model Human Processor (QN-MHP)

The Queueing Network — Model Human Processor (QN-MHP) is a computational architecture that combines the mathematical theories and simulation methods of queueing networks (QN) with the symbolic and procedure methods of a GOMS-style task description and the Model Human Processor (MHP). Using QN-MHP, a steering model was created to represent the concurrent perceptual, cognitive, and motor activities involved in vehicle steering as truly concurrent processes. The model was compared with driving performance of human subjects and demonstrated realistic steering behavior. It steered a simulated vehicle at a fixed speed within the lane boundaries of straight sections and curves of different radii. In a quantitative validation of several basic measures of driving performance, the steering model yielded steering angle and lateral position similar to the human subject data. This work showed the strength of QN-MHP as a model of driving behavior. Ongoing work further develops the model by expanding the scope of the driving task and by adding a concurrent secondary in-vehicle task.
Grothendieck Classes and Chern Classes of Hyperplane Arrangements

We show that the characteristic polynomial of a hyperplane arrangement can be recovered from the class in the Grothendieck group of varieties of the complement of the arrangement. This gives a quick proof of a theorem of Orlik and Solomon relating the characteristic polynomial with the ranks of the cohomology of the complement of the arrangement. We also show that the characteristic polynomial can be computed from the total Chern class of the complement of the arrangement; this has also been observed by Huh. In the case of free arrangements, we prove that this Chern class agrees with the Chern class of the dual of a bundle of differential forms with logarithmic poles along the hyperplanes in the arrangement; this follows from work of Mustata and Schenck. We conjecture that this relation holds for all free divisors. We give an explicit relation between the characteristic polynomial of an arrangement and the Segre class of its singularity (`Jacobian') subscheme. This gives a variant of a recent result of Wakefield and Yoshinaga, and shows that the Segre class of the singularity subscheme of an arrangement together with the degree of the arrangement determine the ranks of the cohomology of its complement. We also discuss the positivity of the Chern classes of hyperplane arrangements: we give a combinatorial interpretation of this phenomenon, and we discuss the cases of generic and free arrangements.
Unknown Malicious Codes Detection Based on Rough Set Theory and Support Vector Machine

For detecting malicious codes, a classification method of support vector machine (SVM) based on rough set theory (RST) is proposed. The original sample data is preprocessed with the knowledge reduction algorithm of RST, and the redundant features and conflicting samples are eliminated from the working sample dataset to reduce space dimension of sample data. Then the preprocessed sample data is used as training sample data of SVM. By utilizing SVM, the generalizing ability of detection system is still good even the sample dataset size is small. Experiment results show that the proposed detection system needs few priori knowledge and can improve the training speed and precision of classification.
Efficient particle filtering for multiple target tracking with application to tracking in structured images

For many dynamic estimation problems involving nonlinear and/or non-Gaussian models, particle filtering offers improved performance at the expense of computational effort. This paper describes a scheme for efficiently tracking multiple targets using particle filters. The tracking of the individual targets is made efficient through the use of Rao-Blackwellisation. The tracking of multiple targets is made practicable using Quasi-Monte Carlo integration. The efficiency of the approach is illustrated on synthetic data.
The brush border cytoskeleton is not static: in vivo turnover of proteins

The shape and stability of intestinal epithelial cell microvilli are maintained by a cytoskeletal core composed of a bundle of actin filaments with several associated proteins. The core filaments are intimately associated with the overlying plasma membrane, in which there occur rapid turnover of proteins and constant incorporation of new membrane. Previous work has shown that starvation or inhibition of protein synthesis results in modulation of microvillar length, which indicates that there may be cytoskeletal protein turnover. We demonstrate herein, by means of in vivo pulse labeling with radioactive amino acids, that turnover of brush border cytoskeletal proteins occurs in mature absorptive cells. Turnover of cytoskeletal proteins appears to be quite slow relative to membrane protein turnover, which suggests that the turnover of these two microvillar compartments is not coupled. We thus conclude that cytoskeletal protein turnover may be a factor used to maintain normal length and stability of microvilli and that the cytoskeleton cannot be considered a static structure.
to appear in Mathematical Modelling and Numerical Analysis ANALYSIS OF A FORCE-BASED QUASICONTINUUM APPROXIMATION

Abstract. We analyze a force-based quasicontinuum approximation to a one-dimensional system of atoms that interact by a classical atomistic potential. This force-based quasicontinuum approximation can be derived as the modification of an energy-based quasicontinuum approximation by the addition of nonconservative forces to correct nonphysical “ghost” forces that occur in the atomistic to continuum interface during constant strain. The algorithmic simplicity and consistency with the purely atomistic model at constant strain has made the force-based quasicontinuum approximation popular for large-scale quasicontinuum computations. We prove that the force-based quasicontinuum equations have a unique solution when the magnitude of the external forces satisfy explicit bounds. For Lennard-Jones next-nearest-neighbor interactions, we show that unique solutions exist for external forces that extend the system nearly to its tensile limit. We give an analysis of the convergence of the ghost force iteration method to solve the equilibrium equations for the force-based quasicontinuum approximation. We show that the ghost force iteration is a contraction and give an analysis for its convergence rate.
An error correcting neural network

The behavior of a particular class of neural networks and their application to error control coding are discussed. It is proved that the net is able to perform analog error correction without hanging up at some undesired states-an annoying event that occurs occasionally in Hopfield (1982) nets. The corresponding code is a balanced code which has a significantly higher rate than Hopfield's 1-in-N code. Accordingly, the product of balanced code has a higher rate and better error correcting ability than Hopfield's permutation N*N code. The application of the code to combined modulation and channel coding for a 4-ary channel is discussed. <<ETX>>
A self-organized growing network for on-line unsupervised learning

An on-line unsupervised learning mechanism is proposed for unlabeled data which is polluted by noises. By using a similarity threshold and local error based insertion criterion, the system is able to grow incrementally and to accommodate input patterns of on-line non-stationary data distribution. The definition of a utility parameter - "error-radius" enables this system to learn the number of nodes needed to solve a current task. The usage of a new technique for removing nodes in low probability density regions can separate the clusters with low-density overlaps and dynamically eliminate the noise in the input data. The design of two-layer neural network makes it possible for this system to represent the topological structure of unsupervised on-line data, report the reasonable number of clusters and give typical prototype patterns of every cluster without any priori conditions such as suitable number of nodes or a good initial codebook.
Atherosclerotic Plaque Smooth Muscle Cells Have a Distinct Phenotype

Objective—The present study addresses the question, “Are plaque smooth muscles cells (SMCs) genetically distinct from medial SMCs as reflected by the ability to maintain a distinctive expression phenotype in vitro? ” Methods and Results—Multiple cell strains were developed from carotid endarcterectomy specimens, and quadruplicate array hybridizations were completed for each sample. A new normalization protocol was developed and used to analyze the data. Permutation analysis suggests that most of the significant differences in expression could not have occurred by chance. A broad pattern of significant expression differences, consisting of almost 5% of the genes probed, was detected. Quantitative polymerase chain reaction (QPCR) confirmation was found in 70% of a subset of genes selected for validation. Conclusions—The SMC cultures were nearly indistinguishable by morphological features, population doubling time, and sensitivity to cell death induced by Fas cross-linking. Surprisingly, array expression analysis identified differences so extensive that we conclude that plaque and medial SMCs are distinctly different SMC cell types.
Preventing Cooperative Black Hole Attacks in Mobile Ad Hoc Networks: Simulation Implementation and Evaluation

A black hole attack is a severe attack that can be easily employed against routing in mobile ad hoc networks. A black hole is a malicious node that falsely replies for any route requests without having active route to specified destination and drops all the receiving packets. If these malicious nodes work together as a group then the damage will be very serious. This type of attack is called cooperative black hole attack. In S. Ramaswamy et al. (2003), we proposed a solution to identifying and preventing the cooperative black hole attack. Our solution discovers the secure route between source and destination by identifying and isolating cooperative black hole nodes. In this paper, via simulation, we evaluate the proposed solution and compare it with other existing solutions in terms of throughput, packet loss percentage, average end-to-end delay and route request overhead. The experiments show that (1) the AODV greatly suffers from cooperative black holes in terms of throughput and packet losses, and (2) our solution proposed in S. Ramaswamy et al. (2003) presents good performance in terms of better throughput rate and minimum packet loss percentage over other solutions, and (3) our solution can accurately prevent the cooperative black hole attacks. The example findings are: (1) the proposed scheme presents 5 - 8% more communication overhead of route request; and (2) The secure route discovery delay slightly increases the packet loss percentage.
LAGRANGEAN BASED HEURISTIC FOR INTEGRATED PLANNING PRODUCTION AND MAINTENANCE PROBLEM WITH TIME WINDOWS AND SHORTAGE COST

In this paper, we deal with a problem of integrating production and maintenance. The integrated problem is a combining problem of two problems largely studied in literature: the problem of determining the cycle of preventive maintenance actions, and the main production planning problem known as multi items capacitated lot sizing problem with shortage cost. Preventive maintenance is carried out in time windows to restore the production line to an "as-good-as-new" status, and when a production line fails, a minimal repair is carried out to restore it to an "as-bad-as- old" status. The resulting problem is modelled as a linear mixed-integer program. It takes into account demand shortage and the reliability of the production line. We will solve the problem with a Langrangean heuristic, the computational results show that the heuristic provide a good feasible solution quality in short execution time.
Response Gradient Estimation using Mathematical Programming Models of Discrete-Event System Sample Paths

This paper illustrates the use of mathematical programming in computing gradient estimators. Consistency property of these estimators is established under the usual assumptions for IPA gradient estimator consistency. A finite difference tolerance limit is introduced. For complex discrete-event systems, more concise linear programming representations are developed. These new representations provide a direct way of calculating gradient estimates