Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic Load Balancing Algorithm for MPI Parallel Computing

MPI is the most important parallel programming tool in cluster currently. It implements communication in parallel program by message. Implementing load balance in MPI parallel program is very important. It may reduce running time and improve performance of MPI parallel program, aiming at solving the dynamic balancing problem in homogeneous cluster system. This paper proposes an implementing method in MPI parallel program that can transfer tasks between nodes effectively by node’s load. The experiments prove the availability and practicability of the algorithm in parallel computing task.
Navigation and Interaction in Graph Visualizations

Graphs are widely utilized in many fields and several applications require their visualization. Graph visualization is based on techniques for graph drawing, interaction and navigation in such a way that helps the user in finding and manipulating information efficiently. These techniques, which can be two or three-dimensional, depending on the spatial metaphor used to represent the graph, can be combined in many different ways in order to fit a particular application's needs. This paper presents an overview of the field of graph visualization.
Reinforcement Learning Applied to an Electric Water Heater: From Theory to Practice

Electric water heaters have the ability to store energy in their water buffer without impacting the comfort of the end user. This feature makes them a prime candidate for residential demand response. However, the stochastic and nonlinear dynamics of electric water heaters, makes it challenging to harness their flexibility. Driven by this challenge, this paper formulates the underlying sequential decision-making problem as a Markov decision process and uses techniques from reinforcement learning. Specifically, we apply an auto-encoder network to find a compact feature representation of the sensor measurements, which helps to mitigate the curse of dimensionality. A well-known batch reinforcement learning technique, fitted <inline-formula> <tex-math notation="LaTeX">${Q}$ </tex-math></inline-formula>-iteration, is used to find a control policy, given this feature representation. In a simulation-based experiment using an electric water heater with 50 temperature sensors, the proposed method was able to achieve good policies much faster than when using the full state information. In a laboratory experiment, we apply fitted <inline-formula> <tex-math notation="LaTeX">${Q}$ </tex-math></inline-formula>-iteration to an electric water heater with eight temperature sensors. Further reducing the state vector did not improve the results of fitted <inline-formula> <tex-math notation="LaTeX">${Q}$ </tex-math></inline-formula>-iteration. The results of the laboratory experiment, spanning 40 days, indicate that compared to a thermostat controller, the presented approach was able to reduce the total cost of energy consumption of the electric water heater by 15%.
A Lexical Normalisation for Social Media Text

Twitter provides access to large volumes of data in real time, but is notoriously noisy, hampering its utility for NLP. In this paper, we target out-of-vocabulary words in short text messages and propose a method for identifying and normalising lexical variants. Our method uses a classifier to detect lexical variants, and generates correction candidates based on morphophonemic similarity. Both word similarity and context are then exploited to select the most probable correction candidate for the word. The proposed method doesn’t require any annotations, and achieves state-of-the-art performance over an SMS corpus and a novel dataset based on Twitter. This paper is an extension of Han and Baldwin [2011] and Han et al. [2012], with significantly expanded experimentation over the original paper.
Applying Reinforcement Learning for the AI in a Tank-Battle Game

Reinforcement learning is an unsupervised machine learning method in the field of Artificial Intelligence and offers high performance in simulating the thinking ability of a human. However, it requires a trial-and-error process to achieve this goal. In the research field of game AIs, it is a good approach that can give the non-player-characters (NPCs) in digital games more human-like qualities. In this paper, we try to build a Tank-battle computer game and use the methodology of reinforcement learning for the NPCs (the tanks). The goal of this paper is to make this game become more interesting due to the enhanced interactions with the more intelligent NPCs.
Capital-Labour Substitution and Banking Sector Performance in Nigeria ( 1960-2008 )

This study examines productivity in the banking sector by way of estimating two major production functions known in the economic literature. The result obtained from the ordinary least square (OLS) estimates shows that substitution parameters α and β (substitution parameters for capital and labour, respectively) confirms the a priori expectation that the duo of α and β are positive values of less than one. The addition of the values of α and β is greater than one, which indicates that as the banking sector doubles its inputs in terms of capital and labour, the output in terms of deposit will be more than doubled. The substitution parameters in the Constant Elasticity of Substitution Production Function were equally positive, which supports the theory. The speed of adjustment for the two models are reasonably good as any deviation from equilibrium is to be adjusted back in the long run. In the final analysis, the study supports economic theory on the specification of both Cobb-Douglas and Constant Elasticity of Substitution production functions.
Identification of a Cryptic Prokaryotic Promoter within the cDNA Encoding the 5′ End of Dengue Virus RNA Genome

Infectious cDNA clones of RNA viruses are important research tools, but flavivirus cDNA clones have proven difficult to assemble and propagate in bacteria. This has been attributed to genetic instability and/or host cell toxicity, however the mechanism leading to these difficulties has not been fully elucidated. Here we identify and characterize an efficient cryptic bacterial promoter in the cDNA encoding the dengue virus (DENV) 5′ UTR. Following cryptic transcription in E. coli, protein expression initiated at a conserved in-frame AUG that is downstream from the authentic DENV initiation codon, yielding a DENV polyprotein fragment that was truncated at the N-terminus. A more complete understanding of constitutive viral protein expression in E. coli might help explain the cloning and propagation difficulties generally observed with flavivirus cDNA.
Analysis of the Retinal Nerve Fiber Layer in Retinitis Pigmentosa Using Optic Coherence Tomography

Aim. To evaluate the peripapillary retinal nerve fiber layer (RNFL) changes in retinitis pigmentosa (RP) patients using spectral domain optic coherence tomography (Sd-OCT). Methods. We retrospectively examined medical records of forty-four eyes of twenty-two RP patients. The results were also compared with those of previously reported forty-four eyes of twenty-two normal subjects (controls). Records of average and four quadrants peripapillary RNFL thickness measurements using Sd-OCT were assessed. Results. In RP patients the mean RNFL thickness was 97.57 ± 3.21 μm. The RNFL in the superior, temporal, nasal, and inferior quadrants was 119.18 ± 4.47 μm, 84.68 ± 2.31 μm, 75.09 ± 3.34 μm, and 113.88 ± 4.25 μm, respectively. While the thinning of RNFL was predominantly observed in the inferior quadrant, the thickening was mostly noted in temporal quadrant. The differences between mean, superior, and nasal quadrant RNFL thicknesses were not statistically significant when compared with control group. The RP patients had thinner inferior quadrant and thicker temporal quadrant than control group (p < 0.05). Conclusion. Sd-OCT is highly sensitive and effective instrument to detect RNFL changes in RP patients. RNFL measurements can provide information about the progression of retinitis pigmentosa and may provide prognostic indices for future treatment modalities.
Topic Detection and Tracking for News Web Pages

This paper proposes a new approach to observe, summarize and track events from a collection of news Web pages. Given a set of temporal Web pages, we obtain valid times-tamp from Web pages and detect events by means of clustering. Then we track events by using KeyGraph based on the clusters and abstract the clusters by using SuffixTree. We examine some experimental results and show the usefulness of our approach
Title: Ancestral Relationships Using Metafounders: Finite Ancestral Populations and across Population Relationships. 2 3 Running Title: Metafounders in Pedigrees

23 Recent use of genomic (marker-based) relationships shows that relationships exist within 24 and across base population (breeds or lines). However, current treatment of pedigree 25 relationships is unable to consider relationships within or across base populations, although 26 such relationships must exist due to finite size of the ancestral population and connections 27 between populations. This complicates the conciliation of both approaches and, in 28 particular, combining pedigree with genomic relationships. We present a coherent 29 theoretical framework to consider base population in pedigree relationships. We suggest a 30 conceptual framework that considers each ancestral population as a finite-sized pool of 31 gametes. This generates across-individual relationships and contrasts with the classical view 32 where each population is considered as an infinite, unrelated pool. Several ancestral 33 populations may be connected and therefore related. Each ancestral population can be 34 represented as a “metafounder”, a pseudo-individual included as founder of the pedigree 35 and similar to an “unknown parent group”. Metafounders have selfand across36 relationships according to a set of parameters, which measure ancestral relationships, i.e. 37 homozygozities within populations and relationships across populations. These parameters 38 can be estimated from existing pedigree and marker genotypes using maximum likelihood or 39 a method based on summary statistics, for arbitrarily complex pedigrees. Equivalences of 40 genetic variance and variance components between the classical and this new 41 parameterization are shown. Segregation variance on crosses of populations is modeled. 42 Efficient algorithms for computation of relationship matrices, their inverses, and inbreeding 43 coefficients are presented. Use of metafounders leads to compatibility of genomic and 44
On the use of random neural networks for traffic matrix estimation in large-scale IP networks

Despite a large body of literature and methods devoted to the Traffic Matrix (TM) estimation problem, the inference of traffic flows volume from aggregated data still represents a major issue for network operators. Directly and frequently measuring a complete TM in a large-scale network is costly and difficult to perform due to routers limited capacities. In this paper we introduce and evaluate a new method to estimate a TM from easily available link load measurements. The method uses a novel statistical learning technique to unveil the relation between links traffic volume and origin-destination flows volume. By training a system based on Random Neural Networks, we provide a fast and accurate TM estimation tool that attains proper results without assuming any traffic model or particular behavior. Using real data from an operational backbone network, we compare this new method to the most well known and accepted TM estimation techniques, including in the evaluation some more accurate and up-to-date methods developed in recent works. Results show that current TM estimation techniques can still be improved.
Distributed investigations of intrusion detection data on the grid

In this paper we demonstrate the use of grid-based computing in revealing aspects of intrusion detection data which were difficult to reveal some years ago due to constrained computing resources. Exploiting the grids for their computing resources can rapidly turn into a tedious task, entailing solid technical knowledge about the grid. Grid application (and) frameworks are the category of tools that make the use of the grid much simplified for the scientist with interest solely on the computing resources. Mining security data is a task, we believe, that can be better served using the grid. Here, we attempt to reveal new insights in intrusion detection data, such as the well known KDDCUP'99 data set.
In vitro antioxidant activity and potential inhibitory action against α-glucosidase of polysaccharides from fruit peel of tea (Camellia sinensis L.)

The conditions for extracting polysaccharides from tea (Camellia sinensis L.) fruit peel (TFPPs) were studied. Three parameters (temperature, time, and liquid/solid ratio) affecting the extraction of TFPP were optimized using response surface methodology (RSM). Under the optimized conditions, the yield of TFPP was predicted to be 4.98%. The physicochemical properties, in vitro antioxidant activities, and inhibitory effects on α-glucosidase of fractionated TFPPs (TFPP-0, TFPP-20, TFPP-40, and TFPP-60) were investigated. We found that the TFPPs were all acid protein-bound heteropolysaccharides, although with different chemical compositions. They had not only remarkable scavenging activity on 2,2’-azinobis(3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS) and reducing activity, but also excellent inhibitory potential against α-glucosidase in vitro. Our results suggest that tea fruit peel could be treated as a potential bioresource for the development of polysaccharide antioxidants.
From the Owl to the Eskimo: the Radiation-Gasdynamics of Planetary Nebulae IV

We present the results of two-dimensional radiation-gasdynamic simulations of aspherical Planetary Nebulae (PNe) evolution. These simulations were constructed using the Generalized Interacting Stellar Winds (GISW) scenario of Balick (1987) where a fast, tenuous wind from the central star expands into a toroidal, slow, dense wind. We demonstrate that the GISW model can produce a wide range of aspherical flow patterns. We have constructed self-consistent synthetic observations of the models from forbidden line emissivities used in the energy loss term. We present integrated intensity and long-slit spectrum, (Position-Velocity) maps of the models projected at different angles on the sky. These synthetic observations are compared with real intensity and Position-Velocity maps of PNe. We find that there is a very good match between the synthetic and real observations in terms of morphologies, kinematics, and physical conditions. From the results of these simulations we conclude that the GISW scenario can account for most, if not all, PNe morphologies, thus confirming Balick's (1987) conjecture.
X-RAY IMAGING MODALITIES FOR NUCLEAR WASTE

: X-ray imaging is a suitable technique for nuclear waste drums inspection, especially large and highly attenuating ones. It requires an energy source greater than 6MeV and dose rate over 0.1Gy/s. Controlling waste drums calls for a multi-level strategy: from systematic and fast controls to specific or detailed examinations. Using a high energy (8MeV) experimental set-up, we have studied and validated different modalities for X-ray inspection of these drums: radiography, radioscopy, tomosynthesis, and tomography. Various types of detectors can be used, all of them dedicated to high energy: large screen imager, CdTe-unit detector, linear array. They differ on induced geometry acquisition, global acquisition time, resolution, and possible modalities. Data collection therefore also differs from one device to another.
Kidney paired donation and optimizing the use of live donor organs.

CONTEXT Blood type and crossmatch incompatibility will exclude at least one third of patients in need from receiving a live donor kidney transplant. Kidney paired donation (KPD) offers incompatible donor/recipient pairs the opportunity to match for compatible transplants. Despite its increasing popularity, very few transplants have resulted from KPD. OBJECTIVE To determine the potential impact of improved matching schemes on the number and quality of transplants achievable with KPD. DESIGN, SETTING, AND POPULATION We developed a model that simulates pools of incompatible donor/recipient pairs. We designed a mathematically verifiable optimized matching algorithm and compared it with the scheme currently used in some centers and regions. Simulated patients from the general community with characteristics drawn from distributions describing end-stage renal disease patients eligible for renal transplantation and their willing and eligible live donors. MAIN OUTCOME MEASURES Number of kidneys matched, HLA mismatch of matched kidneys, and number of grafts surviving 5 years after transplantation. RESULTS A national optimized matching algorithm would result in more transplants (47.7% vs 42.0%, P<.001), better HLA concordance (3.0 vs 4.5 mismatched antigens; P<.001), more grafts surviving at 5 years (34.9% vs 28.7%; P<.001), and a reduction in the number of pairs required to travel (2.9% vs 18.4%; P<.001) when compared with an extension of the currently used first-accept scheme to a national level. Furthermore, highly sensitized patients would benefit 6-fold from a national optimized scheme (2.3% vs 14.1% successfully matched; P<.001). Even if only 7% of patients awaiting kidney transplantation participated in an optimized national KPD program, the health care system could save as much as $750 million. CONCLUSIONS The combination of a national KPD program and a mathematically optimized matching algorithm yields more matches with lower HLA disparity. Optimized matching affords patients the flexibility of customizing their matching priorities and the security of knowing that the greatest number of high-quality matches will be found and distributed equitably.
Nutritional Capability of and Substrate Suitability for Pseudogymnoascus destructans, the Causal Agent of Bat White-Nose Syndrome

Pseudogymnoascus destructans, the causal agent of bat white-nose syndrome, has caused nearly six million deaths in North American bats since its introduction into the United States in 2006. Current research has shown that caves can harbor P. destructans even after the infected bats are removed and bats no longer visit or inhabit previously infected caves. Our research focuses on elucidating reservoir requirements by investigating the nutritional capabilities of and substrate suitability requirements for six different P. destructans isolates from various localities including Illinois, Indiana, New York (Type specimen), and Pennsylvania. Enzyme assays implicate that both urease and b-glucosidase appear to be constitutive, lipase and esterase activity were more rapid than proteinase activity on 6% gelatin, gelatin degradation was accompanied by medium alkalinization, the reduction of thiosulfate generated hydrogen sulfide gas, chitinase and manganese dependent peroxidase activity were not visually demonstrated within eight weeks, and keratinase activity was not evident at pH 8 within eight weeks. We demonstrate that all P. destructans isolates are capable of growth and sporulation on dead fish, insect, and mushroom tissues. Sole nitrogen source assays demonstrated that all P. destructans isolates exhibit Class 2 nitrogen utilization and that growth-dependent interactions occur among different pH and nitrogen sources. Substrate suitability assays demonstrated that all isolates could grow and sporulate on media ranging from pH 5–11 and tolerated media supplemented with 2000 mg/L of calcium and 700 mg/L of three separated sulfur compounds: thiosulfate L-cysteine, and sulfite. All isolates were intolerant to PEG-induced matric potential with delayed germination and growth at −2.5 MPa with no visible germination at −5 MPa. Interestingly, decreasing the surface tension with Tween 80 permitted germination and growth of P. destructans in −5 MPa PEG medium within 14 days suggesting a link between substrate suitability and aqueous surface tension altering substances.
Minimum energy probabilistic reliable data delivery in wireless sensor networks

Many sensor network applications only require probabilistic data delivery, as they can tolerate some missing data samples. For example, in environmental monitoring, missing temperature, pressure and humidity level samples can often be inferred by spatial and/or temporal interpolations. In this paper we propose and study an adaptive p-persistent CSMA-based media access control protocol that supports end-to-end probabilistic reliability for sensor networks on a hop-by-hop basis. In an effort to reduce the probability of packet collisions, first we tune the carrier sensing range of the nodes; then given an end-to-end reliability requirement, we determine the optimal allocation of per-hop reliability requirements on each route to minimize the expected total number of transmissions needed; finally, our adaptive p-persistent CSMA protocol tunes its link persistence probability to further reduce the expected total number of transmissions, and thereby minimizes the energy consumption in the network. We formulate this latter problem as a constrained optimization problem, and then derive an algorithm to adapt the link persistence probabilities using the Lagrangian dual decomposition method.
On the Relationship Between Robust Minimum Variance Beamformers With Probabilistic and Worst-Case Distortionless Response Constraints

An interesting relationship between the probability-constrained and worst-case optimization based robust minimum variance (MV) beamformers has been discovered. It is shown that both in the cases of circularly symmetric Gaussian and worst-case distributions of the steering vector mismatch, the probability-constrained robust MV beamforming problem can be tightly approximated as a convex second-order cone programming (SOCP) problem. The latter problem is mathematically equivalent to that resulting from the deterministic worst-case approach and, therefore, probability-constrained beamformers can be interpreted and implemented using their deterministic worst-case counterparts. However, an important advantage of the developed probability-constrained MV beamformers with respect to their standard worst-case counterparts is that the former approaches enable to explicitly quantify the parameters of the uncertainty region in terms of the beamformer outage probability.
Channel estimation for the downlink of 3GPP-LTE systems

In this paper, we study the channel estimation algorithms for the downlink of 3GPP LTE systems. By using computer simulation, the pilot signal assisted channel estimation algorithms based on least square (LS) and linear minimum mean square error (LMMSE) criteria, together with channel interpolation based on piecewise-linear interpolation and DFT based interpolation are studied. By analyzing simulation results in terms of Mean Square Error (MSE) and un-coded Bit Error Rate (BER), we conclude that the channel frequency responses of pilot tones are estimated by using LS estimator, and the channel frequency responses of data tones are interpolated by DFT based interpolation method is appropriate for the downlink of 3GPP LTE systems.