Miracle-dz/UniFAR-FTUs huggingface dataset:
Embedding Cuts in a Branch & Cut Framework : a Computational Study with { 0 , 12 }-Cuts

Embedding cuts into a Branch&Cut framework is a delicate task, the main so when the implemented separation procedures are very successful and do produce a large set of violated cuts. In this case, it is of crucial importance to balance between the benefits deriving from a tighter (but larger) LP relaxation, and the overhead introduced for its solution. In this paper we describe a separation heuristic for {0, 1 2 }-cuts, special cases of Chvátal-Gomory cuts which play an important role in combinatorial problems formulated as Integer Linear Programming (ILP) problems [4]. Our separation procedure is embedded within ILOG-Cplex 8.1, a widely-used commercial
Consensual Qualitative Research and Its Application to Counseling Research

Consensual Qualitative Research(CQR) is one of the well-developed and popular methods of qualitative research,a commonly used paradigm in the western counseling field.This paper first introduced the procedures of applying CQR,and then reviewed the main topics of the studies using this method.Based on previous illustration,the authors finally discussed the strengths and limitations in doing research with CQR.
Iterative projector calibration using multi-frequency phase-shifting method

In this paper, an iterative projector calibration method is proposed using multi-frequency phase-shifting methods. With the help of the multi-frequency phase shifting, the projector can `see' the 3D control point from the correspondence between the camera image and the projector image. The 3D control point information is directly adopted instead of computing them from the calibrated camera. Thus, the error propagation from the camera calibration is avoided. To diminish the influence of the lens distortion and the projective transformation, an iterative refining method is adopted to approach the real canonical fronto-parallel image from the camera image instead of the projector image. Because the canonical fronto-parallel image is determined by the virtual camera and the pose of calibration board, they are same from the camera image and the projector image to generate the canonical fronto-parallel image. However, it is complicated and time-consuming to obtain it from the projector image, because the projector image has to be created from the correspondence at first. The proposed method is conducted in our portable structured light system. It is compared with the non-iterative method. The results confirm that the proposed method has higher accuracy.
Transcription factor p53 influences microglial activation phenotype

Several neurodegenerative diseases are influenced by the innate immune response in the central nervous system (CNS). Microglia have proinflammatory and subsequently neurotoxic actions as well as anti‐inflammatory functions that promote recovery and repair. Very little is known about the transcriptional control of these specific microglial behaviors. We have previously shown that in HIV‐associated neurocognitive disorders (HAND), the transcription factor p53 accumulates in microglia and that microglial p53 expression is required for the in vitro neurotoxicity of the HIV coat glycoprotein gp120. These findings suggested a novel function for p53 in regulating microglial activation. Here, we report that in the absence of p53, microglia demonstrate a blunted response to interferon‐γ, failing to increase expression of genes associated with classical macrophage activation or secrete proinflammatory cytokines. Microarray analysis of global gene expression profiles revealed increased expression of genes associated with anti‐inflammatory functions, phagocytosis, and tissue repair in p53 knockout (p53−/−) microglia compared with those cultured from strain matched p53 expressing (p53+/+) mice. We further observed that p53−/− microglia demonstrate increased phagocytic activity in vitro and expression of markers for alternative macrophage activation both in vitro and in vivo. In HAND brain tissue, the alternative activation marker CD163 was expressed in a separate subset of microglia than those demonstrating p53 accumulation. These data suggest that p53 influences microglial behavior, supporting the adoption of a proinflammatory phenotype, while p53 deficiency promotes phagocytosis and gene expression associated with alternative activation and anti‐inflammatory functions. © 2011 Wiley‐Liss, Inc.
Colour-basedImageRetrieval fr om VideoSequences

Themultimodalneighbourhoodsignature(MNS) algorithmrepresentslocalobjectappearance by stablecolour-based invariantsefficiently computedfrom imageneighbourhoodswith multimodalcolour densityfunction. Local featureextractionfacilitatesregion-basedinteracti ve queryspecificationandcomputationof illumination invariantfeatures.Themethodallows for fastsignaturematchingandsupportsretrieval of objectscoveringonly a fractionof the databaseimage.MNS signaturesaregenerallycompactandstoragerequirementsaretypically a few hundredbytes perimage. In this paper , theproposedalgorithmis testedon a challengingregion-basedimageretrieval task,searchingfor objectsin a sportsvideo sequence.Imageregionsdepictingobjectsof typical interestin a sportsimagedatabase aredelineatedby the usersandusedasqueries. Acceptableretrieval resultsarepresentedfor a numberof experiments. Relevant imageswere retrieved regardlessof backgroundclutter dominatingthe scene,partial occlusion and/ornon-rigid objectdeformation. Finally, the suitability of the approachis investigatedin the context of webbasedapplicationswhereefficient signaturecreation,goodmatchingspeedandminimal storagerequirementsare required.
Kernel parameter selection by gap maximization between intra and inter-class samples

By maximizing the gap between classes in the reproducing kernel Hilbert space (RKHS), our method optimizes for the sigma values of radial basis function (RBF) or gaussian kernels. For each sample, we try to ensure the distance gap between intra-class and inter-class in RKHS to be large. Unlike previous methods of multiple kernel learning, our method does not need large amount of computations, which allows us to apply the proposed method to a larger set of data. Our method is compared with the method of kernel target alignment which is one of the most popular methods in multiple kernel learning to prove its efficiency of finding the optimal kernel parameter for the Face vs Non-face dataset.
A multi-functional dynamic state estimator for error validation: measurement and parameter errors and sudden load changes

We propose a new and efficient algorithm to detect, identify, and correct measurement errors and branch parameter errors of power systems. A dynamic state estimation algorithm is used based on the Kalman filter theory. The proposed algorithm also successfully detects and identifies sudden load changes in power systems. The method uses three normalized vectors to process errors at each sampling time: normalized measurement residual, normalized Lagrange multiplier, and normalized innovation vector. An IEEE 14-bus test system was used to verify and demonstrate the effectiveness of the proposed method. Numerical results are presented and discussed to show the accuracy of the method.
Structural, electronic, and dielectric properties of ultrathin zirconia films on silicon

As high-permittivity dielectrics approach use in metal-oxide-semiconductor field-effect transistor production, an atomic level understanding of their dielectric properties and the capacitance of structures made from them is being rigorously pursued. We and others have shown that crystal structure of ZrO2 films have considerable effects on permittivity as well as band gap. The as-deposited films reported here appear amorphous below a critical thickness (∼5.4nm) and transform to a predominantly tetragonal phase upon annealing. At much higher thickness the stable monoclinic phase will be favored. These phase changes may have a significant effect on channel mobility.
Oxygen desaturation during a 4-minute step test: predicting survival in idiopathic pulmonary fibrosis.

BACKGROUND AND AIM PaO2 during exertion is a significant predictor of IPF survival. The aim of study was to assess oxygen desaturation for predicting survival in IPF patients at the end of a 4-minute step test. METHODS A longitudinal study was done in 59 patients with IPF from February 1998 to January 2005. Upon initial examination, lung function testing was performed, as were 4-minute step tests, in which patients stepped up and down on a 20-cm single step at a self-paced rate. In the final minute, oxygen saturation by pulse oximetry (SpO2) was measured. RESULTS Median survival was 58 months. SpO2 at rest and during stepping, dyspnea score, as well as FVC% and DLCO% were found to be significant predictors of mortality. Desaturation to 89% or less,correlated with a hazard ratio of 2.39 for IPF mortality (95% CI, 1.16-3.63; p < 0.0001). In patients with such desaturation, four-year survival was 39%, compared to 96% in those with no desaturation. In a multivariate Cox analysis, only SpO2 during stepping remained significant (p < 0.0001). A DLco < 45% of predicted (n=40 patients) correlated with a hazard ratio of 2.23 for mortality (95% CI, 0.73-3.71; p < 0.0001). When the analysis was repeated including DLco, SpO2 and DLco remained significant (p < 0.05). CONCLUSION Desaturation to 89% or less in a 4-min step test is a strong predictor of mortality in IPF patients.
Thermal adaptation generates a diversity of thermal limits in a rainforest ant community

The Thermal Adaptation Hypothesis posits that the warmer, aseasonal tropics generates populations with higher and narrower thermal limits. It has largely been tested among populations across latitudes. However, considerable thermal heterogeneity exists within ecosystems: across 31 trees in a Panama rainforest, surfaces exposed to sun were 8 °C warmer and varied more in temperature than surfaces in the litter below. Tiny ectotherms are confined to surfaces and are variously submerged in these superheated boundary layer environments. We quantified the surface CTmin and CTmaxs (surface temperatures at which individuals grew torpid and lost motor control, respectively) of 88 ant species from this forest; they ranged in average mass from 0.01 to 57 mg. Larger ants had broader thermal tolerances. Then, for 26 of these species we again tested body CTmaxs using a thermal dry bath to eliminate boundary layer effects: body size correlations observed previously disappeared. In both experiments, consistent with Thermal Adaptation, CTmaxs of canopy ants averaged 3.5–5 °C higher than populations that nested in the shade of the understory. We impaled thermocouples in taxidermy mounts to further quantify the factors shaping operative temperatures for four ant species representing the top third (1–30 mg) of the size distribution. Extrapolations suggest the smallest 2/3rds of species reach thermal equilibrium in <10s. Moreover, the large ants that walk above the convective superheated surface air also showed more net heating by solar radiation, with operative temperatures up to 4 °C higher than surrounding air. The thermal environments of this Panama rainforest generate a range of CTmax subsuming 74% of those previously recorded for ant populations worldwide. The Thermal Adaptation Hypothesis can be a powerful tool in predicting diversity of thermal limits within communities. Boundary layer temperatures are likely key to predicting the future of Earth's tiny terrestrial ectotherm populations.
Building Reactive Characters for Dynamic Gaming Environments

Interactive computer games are widely seen as a killer application domain for Artificial Intelligence (AI) [8]. Quite apart from the significant size of the games market in terms of revenue [3], computer games provide complex, dynamic, uncertain and competitive environments that are perfect for developing, testing and deploying AI technologies. While many researchers currently focus on enhancing games with sophisticated AI, most overlook the role that AI has to play in the development of the games themselves. In this paper we present an approach to building non-player characters (NPCs) for a well-known computer game, Unreal Tournament1. Specifically, we use decision trees induced from human player strategies to define how an NPC in the game performs in a highly dynamic environment. The benefits of this approach are twofold. Firstly, it provides a basis for building competitive AI-based NPCs for interactive computer games. Secondly, this approach eases the development overhead of such characters. Our empirical evaluation demonstrates that the NPCs we create are very competitive against hand-crafted ones in a number of simulated gaming sessions.
Simulation-Based Approach to General Game Playing

The aim of General Game Playing (GGP) is to create intelligent agents that automatically learn how to play many different games at an expert level without any human intervention. The most successful GGP agents in the past have used traditional game-tree search combined with an automatically learned heuristic function for evaluating game states. In this paper we describe a GGP agent that instead uses a Monte Carlo/UCT simulation technique for action selection, an approach recently popularized in computer Go. Our GGP agent has proven its effectiveness by winning last year s AAAI GGP Competition. Furthermore, we introduce and empirically evaluate a new scheme for automatically learning search-control knowledge for guiding the simulation playouts, showing that it offers significant benefits for a variety of games.
GrIDS A Graph-Based Intrusion Detection System for Large Networks

There is widespread concern that large-scale malicious attacks on computer networks could cause serious disruption to network services. We present the design of GrIDS (Graph-Based Intrusion Detection System). GrIDS collects data about activity on computers and network tra c between them. It aggregates this information into activity graphs which reveal the causal structure of network activity. This allows large-scale automated or co-ordinated attacks to be detected in near real-time. In addition, GrIDS allows network administrators to state policies specifying which users may use particular services of individual hosts or groups of hosts. By analyzing the characteristics of the activity graphs, GrIDS detects and reports violations of the stated policy. GrIDS uses a hierarchical reduction scheme for the graph construction, which allows it to scale to large networks. An early prototype of GrIDS has successfully detected a worm attack.
Enhanced Restricted Boltzmann Machine With Prognosability Regularization for Prognostics and Health Assessment

In the Internet-of-Things environment, it is critical to bridge the gap between business decision-making and real-time factory data to let companies transfer from condition-based maintenance service to predictive maintenance service. Condition monitoring systems have been widely applied to many industries to acquire operation and equipment related data, through which machine health state can be evaluated. One of the challenges of predicting future machine health lies in extracting the right features that are correlated well with the fault progression/degradation. We propose an enhanced restricted Boltzmann machine with a novel regularization term to automatically generate features that are suitable for remaining useful life prediction. The regularization term tries to maximize the trendability of the output features, which potentially better represent the degradation pattern of a system. The proposed method is benchmarked with regular restricted Boltzmann machine algorithm and principal component analysis. The generated features are used as input to a similarity-based method for life prediction. Run-to-failure datasets collected from two rotating systems are used for validation.
Determination of Corresponding Trunks in a Pair of Terrestrial Images and Airborne Laser Scanner Data

A method based on extracted trunks is proposed for automatic determination of corresponding trees between a georeferenced pair of terrestrial images and airborne laser scanner data in a wooded area. Trunks in the terrestrial images are obtained by region growing segmentation between left and right edges of trunks detected within a region of interest. Trunks in a digital tree height model generated from the laser scanner data are estimated as straight vertical lines through the weighted centers of canopy points of single trees. Corresponding trunks in the left and right images are found with the help of trunks in the laser scanner data and additional attributive information. A piece of 3-D line reconstructed from the trunks in the images verifies the corresponding trunk in the laser scanner data. An experiment illustrates the performance of the method. Potential applications include augmenting a 3-D forest model derived from laser scanner data with complementary information from terrestrial images.
Parallel Sorted Neighborhood Blocking with MapReduce

Cloud infrastructures enable the efficient parallel execution of data-intensive tasks such as entity resolution on large datasets. We investigate challenges and possible solutions of using the MapReduce programming model for parallel entity resolution. In particular, we propose and evaluate two MapReduce-based implementations for Sorted Neighborhood blocking that either use multiple MapReduce jobs or apply a tailored data replication.
Iron Accumulation Is Not Homogenous among Patients with Parkinson's Disease

Background. Iron is considered to lead to neurodegeneration and has been hypothesized as a possible cause of Parkinson's disease (PD). Susceptibility-weighted imaging (SWI) is a powerful tool to measure phase related iron content of brain. Methods. Twelve de novo patients with PD were recruited from the Movement Disorders Clinic, Department of Neurology, Loma Linda University. Twelve age- and sex-matched non-PD subjects were recruited from neurology clinic as controls. Using SWI, the phase related iron content was estimated from different brain regions of interest (ROIs). Results. There was a trend between increasing age and iron accumulation in the globus pallidus and putamen in all subjects. Iron accumulation was not significant in different ROIs in PD patients compared to controls after adjustment for age. Our data revealed heterogeneity of phase values in different brain ROIs among all subjects with an exaggerated trend at SN in PD patients. Conclusions. Our data suggest a nonhomogeneous pattern of iron accumulation in different brain regions among PD patients. Further studies are needed to explore whether this may correlate to the progression of PD. To our knowledge, this is the first study demonstrating the heterogeneity of iron accumulation in the brain, among patients with PD.
Construction of a Super-Competent Bacillus subtilis 168 Using the PmtlA-comKS Inducible Cassette

Competence is a physiological state that enables Bacillus subtilis 168 to take up and internalize extracellular DNA. In practice, only a small subpopulation of B. subtilis 168 cells becomes competent when they enter stationary phase. In this study, we developed a new transformation method to improve the transformation efficiency of B. subtilis 168, specially in rich media. At first, different competence genes, namely comK, comS, and dprA, were alone or together integrated into the chromosome of B. subtilis 168 under control of mannitol-inducible PmtlA promoter. Overexpression of both comK and comS increased the transformation efficiency of B. subtilis REG19 with plasmid DNA by 6.7-fold compared to the wild type strain 168. This transformation efficiency reached its maximal level after 1.5 h of induction by mannitol. Besides, transformability of the REG19 cells was saturated in the presence of 100 ng dimeric plasmid or 3000 ng chromosomal DNA. Studying the influence of global regulators on the development of competence pointed out that important competence development factors, such as Spo0A, ComQXPA, and DegU, could be removed in REG19. On the other hand, efficient REG19 transformation remained highly dependent on the original copies of comK and comS regardless of the presence of PmtlA-comKS. Finally, novel plasmid-free strategies were used for transformation of REG19 based on Gibson assembly.
The use of morphokinetics as a predictor of embryo implantation.

BACKGROUND Time-lapse observation presents an opportunity for optimizing embryo selection based on morphological grading as well as providing novel kinetic parameters, which may further improve accurate selection of viable embryos. The objective of this retrospective study was to identify the morphokinetic parameters specific to embryos that were capable of implanting. In order to compare a large number of embryos, with minimal variation in culture conditions, we have used an automatic embryo monitoring system. METHODS Using a tri-gas IVF incubator with a built-in camera designed to automatically acquire images at defined time points, we have simultaneously monitored up to 72 individual embryos without removing the embryos from the controlled environment. Images were acquired every 15 min in five different focal planes for at least 64 h for each embryo. We have monitored the development of transferred embryos from 285 couples undergoing their first ICSI cycle. The total number of transferred embryos was 522, of which 247 either failed to implant or fully implanted, with full implantation meaning that all transferred embryos in a treatment implanted. RESULTS A detailed retrospective analysis of cleavage times, blastomere size and multinucleation was made for the 247 transferred embryos with either failed or full implantation. We found that several parameters were significantly correlated with subsequent implantation (e.g. time of first and subsequent cleavages as well as the time between cleavages). The most predictive parameters were: (i) time of division to 5 cells, t5 (48.8-56.6 h after ICSI); (ii) time between division to 3 cells and subsequent division to 4 cells, s2 (≤ 0.76 h) and (iii) duration of cell cycle two, i.e. time between division to 2 cells and division to 3 cells, cc2 (≤ 11.9 h). We also observed aberrant behavior such as multinucleation at the 4 cell stage, uneven blastomere size at the 2 cell stage and abrupt cell division to three or more cells, which appeared to largely preclude implantation. CONCLUSIONS The image acquisition and time-lapse analysis system makes it possible to determine exact timing of embryo cleavages in a clinical setting. We propose a multivariable model based on our findings to classify embryos according to their probability of implantation. The efficacy of this classification will be evaluated in a prospective randomized study that ultimately will determine if implantation rates can be improved by time-lapse analysis.