Miracle-dz/UniFAR-FTUs huggingface dataset:
Convergence of Weighted Min-Sum Decoding Via Dynamic Programming on Trees

Applying the max-product (and sum-product) algorithms to loopy graphs is now quite popular for best assignment problems. This is largely due to their low computational complexity and impressive performance in practice. Still, there is no general understanding of the conditions required for convergence or optimality of converged solutions or both. This paper presents an analysis of both attenuated max-product decoding and weighted min-sum decoding for low-density parity-check (LDPC) codes, which guarantees convergence to a fixed point when a weight factor, β, is sufficiently small. It also shows that, if the fixed point satisfies some consistency conditions, then it must be both a linear-programming (LP) and maximum-likelihood (ML) decoding solution. For (dv, dc)-regular LDPC codes, the weight factor must satisfy β(dv-1) <; 1 to guarantee convergence to a fixed point, whereas the results proposed by Frey and Koetter require instead that β(dv-1)(dc-1) ≤ 1. In addition, the range of the weight factor for a provable ML decoding solution is extended to 0 <; β(dv-1) 1. In addition, counterexamples that show a fixed point might not be the ML decoding solution if β(dv-1) > 1 are given. Finally, connections are explored with recent work on the threshold of LP decoding.
Deformetrica: a software for statistical analysis of anatomical shapes

We present Deformetrica, which is a C++ software for the statistical analysis of 2D and 3D shape data. Data can be surface meshes, polygonal lines, labeled points or unstructured point sets. It is therefore of particular interest for the statistical analysis of multi-object anatomical data including surfaces meshes of cortical or sub-cortical structures and white matter fiber tracts.
Graded Entailment for Compositional Distributional Semantics

The categorical compositional distributional model of natural language provides a conceptually motivated procedure to compute the meaning of sentences, given grammatical structure and the meanings of its words. This approach has outperformed other models in mainstream empirical language processing tasks. However, until recently it has lacked the crucial feature of lexical entailment -- as do other distributional models of meaning. In this paper we solve the problem of entailment for categorical compositional distributional semantics. Taking advantage of the abstract categorical framework allows us to vary our choice of model. This enables the introduction of a notion of entailment, exploiting ideas from the categorical semantics of partial knowledge in quantum computation. The new model of language uses density matrices, on which we introduce a novel robust graded order capturing the entailment strength between concepts. This graded measure emerges from a general framework for approximate entailment, induced by any commutative monoid. Quantum logic embeds in our graded order. Our main theorem shows that entailment strength lifts compositionally to the sentence level, giving a lower bound on sentence entailment. We describe the essential properties of graded entailment such as continuity, and provide a procedure for calculating entailment strength.
Developing Social Network Propositions to Explain Large-Group Intervention Theory and Practice

The problem and the solution . In response to turbulent business environments, organizations are increasingly calling on the human resource development (HRD) function to facilitate organizational change.Thus, HRD professionals are looking to new forms of organization development that promise more rapid, whole-system change. One approach is large-group interventions. Although practitioners and researchers recognize the efficacy of large-group interventions, many researchers contend that the underlying theoretical mechanisms by which these interventions operate are poorly understood, resulting in a gap between research and practice that makes it difficult to say with certainty how large-group interventions operate, when they are appropriate, or how they might be integrated with other approaches.This article suggests that a social network perspective can inform our understanding of how large-group interventions work. Drawing on the social network and organizational change literature, the article develops four propositions for future empirical research. These propositions may ground large-group intervention methods in social network theory.
Distributed Spectrum Sensing With Sequential Ordered Transmissions to a Cognitive Fusion Center

Cooperative spectrum sensing is a robust strategy that enhances the detection probability of primary licensed users. However, a large number of detectors reporting to a fusion center for a final decision causes significant delay and also presumes the availability of unreasonable communication resources at the disposal of a network searching for spectral opportunities. In this paper, we employ the idea of sequential detection to obtain a quick, yet reliable, decision regarding primary activity. Local detectors take measurements, and only a few of them transmit the log likelihood ratios (LLR) to a fusion center in descending order of LLR magnitude. The fusion center runs a sequential test with a maximum imposed on the number of sensors that can report their LLR measurements. We calculate the detection thresholds using two methods. The first achieves the same probability of error as the optimal block detector. In the second, an objective function is constructed and decision thresholds are obtained via backward induction to optimize this function. The objective function is related directly to the primary and secondary throughputs with possible privilege for primary operation. Simulation results demonstrate the enhanced performance of the approaches proposed in this paper. We also investigate the case of fading/shadowing channels between the local sensors and the fusion center, and the situation in which the sensing cost is negligible.
Defect-Oriented Testing and Defective-Part-Level Prediction

After an integrated circuit (IC) design is complete, but before first silicon arrives from the manufacturing facility, the design team prepares a set of test patterns to isolate defective parts. Applying this test pattern set to every manufactured part reduces the fraction of defective parts erroneously sold to customers as defect-free parts. This fraction is referred to as the defect level (DL). However, many IC manufacturers quote defective part level, which is obtained by multiplying the defect level by one million to give the number of defective parts per million. Ideally, we could accurately estimate the defective part level by analyzing the circuit structure, the applied test-pattern set, and the manufacturing yield. If the expected defective part level exceeded some specified value, then either the test pattern set or (in extreme cases) the design could be modified to achieve adequate quality. Although the IC industry widely accepts stuck-at fault detection as a key test-quality figure of merit, it is nevertheless necessary to detect other defect types seen in real manufacturing environments. A defective-part-level model combined with a method for choosing test patterns that use site observation can predict defect levels in submicron ICs more accurately than simple stuck-at fault analysis.
Lossless Compression for Sources with Two-Sided Geometric Distributions

LosslessCompressionforSourceswithTwo-SidedGeometricDistributionsNeriMerhavyElectricalEngineeringDepartmentTechnionHaifa32000,IsraelGadielSeroussiandMarceloJ.WeinbergerHewlett-PackardLab oratories1501PageMillRoadPaloAlto,CA94304,USA.AbstractLosslesscompressionisstudiedforacountablyin nitealphab etsourcewithano -centered,two-sidedgeometric(TSG)distribution,whichisacommonlyusedstatisticalmo delforimagepredictionresiduals.Inthe rstpartofthispap er,wedemonstratethatarithmeticco dingbasedonasimplestrategyofmo deladaptation,essentiallyattainsthetheoreticallowerb oundtotheuniversalco dingredundancyasso ciatedwiththismo del.Inthesecondpart,wefo cusonmorepracticalco desforTSG,thatop erateasymb ol-by-symb olbasis.Sp eci cally,wepresentacompletecharacterizationofminimumexp ected-lengthpre xco desforTSGsources.Thefamilyofoptimalintro ducedhereisanextensionoftheGolombco des,whichareoptimalforone-sidedgeometricdistributionsnonnegativeintegers.Astheone-sidedcase,resultingoptimumHu mantreehasastructurethatenablessimplecalculationoftheco dewordeverygivensourcesymb ol.Ourcharacterizationavoidstheheuristicapproximationsfrequentlyusedwhenmo difyingGolombco dessoastoapplytwo-sidedsources.Finally,eprovideadaptationcriteriaforafurthersimpli ed,sub-optimalfamilyofco desusedinpractice.IndexTerms:Losslessimagecompression,Hu manco de,in nitealphab et,geometricdistri-bution,exp onentialdistribution,Golombco des,predictionresidual,universalco ding,sequenco ding,universalmo deling.Partsofthispap erwerepresentedinthe1996InternationalConferenceonImagePro cessing,Lausanne,Switzerland,andinthe1997InternationalSymp osiumonInformationTheory,Ulm,Germany.yThisworkasdonewhiletheauthoronsabbaticalleaveatHewlett-PackardLab oratories,PaloAlto,California.TheauthorisalsowithHewlett-PackardLab oratories{IsraelinHaifa,Israel.
INTEGRATING AND PRESERVING A DIFFERENT CULTURE AFTER ACQUISITION

When organizations with disparate cultures are merged, the culture of the acquired organization often represents a counterculture for the acquiring firm. Scholars and consultants frequently recommend avoiding integration of an acquired company if it has a sharply different culture. This paper presents a case study of a recent hostile takeover that disproves the conventional wisdom and shows that careful implementation processes enable the company, not only to overcome post‐merger integration barriers due to culture clash, but also to maximize strategic benefits from those cultural differences. It shows that integration can be achieved through a process in which only some specific cultural dimensions are integrated while others are preserved.
Mislocalization of centromeric histone H3 variant CENP-A contributes to chromosomal instability (CIN) in human cells

Chromosomal instability (CIN) is a hallmark of many cancers and a major contributor to tumorigenesis. Centromere and kinetochore associated proteins such as the evolutionarily conserved centromeric histone H3 variant CENP-A, associate with centromeric DNA for centromere function and chromosomal stability. Stringent regulation of cellular CENP-A levels prevents its mislocalization in yeast and flies to maintain genome stability. CENP-A overexpression and mislocalization are observed in several cancers and reported to be associated with increased invasiveness and poor prognosis. We examined whether there is a direct relationship between mislocalization of overexpressed CENP-A and CIN using HeLa and chromosomally stable diploid RPE1 cell lines as model systems. Our results show that mislocalization of overexpressed CENP-A to chromosome arms leads to chromosome congression defects, lagging chromosomes, micronuclei formation and a delay in mitotic exit. CENP-A overexpressing cells showed altered localization of centromere and kinetochore associated proteins such as CENP-C, CENP-T and Nuf2 leading to weakened native kinetochores as shown by reduced interkinetochore distance and CIN. Importantly, our results show that mislocalization of CENP-A to chromosome arms is one of the major contributors for CIN as depletion of histone chaperone DAXX prevents CENP-A mislocalization and rescues the reduced interkinetochore distance and CIN phenotype in CENP-A overexpressing cells. In summary, our results establish that CENP-A overexpression and mislocalization result in a CIN phenotype in human cells. This study provides insights into how overexpression of CENP-A may contribute to CIN in cancers and underscore the importance of understanding the pathways that prevent CENP-A mislocalization for genome stability.
Obstacle detection technique using multi sensor integration for small unmanned aerial vehicle

Achieving a robust obstacle detection system for small UAV is very challenging. Due to size and weight constraints, very limited detection sensors can be equipped in the system. Prior works focused on a single sensing device which is either camera or range sensors based. However, these sensors have their own advantages and disadvantages in detecting the appearance of the obstacles. In this paper, combination of both sensors based is proposed for a small UAV obstacle detection system. A small Lidar sensor is used as the initial detector and queue for image capturing by the camera. Next, SURF algorithm is applied to find the obstacle sizes estimation by searching the connecting feature points in the image frame. Finally, safe avoidance path for UAV is determined through the exterior feature points from the estimated width of the obstacle. The proposed method was evaluated by conducting experiments in real time with indoor environment. In the experiment conducted, we successfully detect and determine a safe avoidance path for the UAV on 6 different sizes and textures of the obstacles including textureless obstacles.
ChIP-BIT: Bayesian inference of target genes using a novel joint probabilistic model of ChIP-seq profiles

Chromatin immunoprecipitation with massively parallel DNA sequencing (ChIP-seq) has greatly improved the reliability with which transcription factor binding sites (TFBSs) can be identified from genome-wide profiling studies. Many computational tools are developed to detect binding events or peaks, however the robust detection of weak binding events remains a challenge for current peak calling tools. We have developed a novel Bayesian approach (ChIP-BIT) to reliably detect TFBSs and their target genes by jointly modeling binding signal intensities and binding locations of TFBSs. Specifically, a Gaussian mixture model is used to capture both binding and background signals in sample data. As a unique feature of ChIP-BIT, background signals are modeled by a local Gaussian distribution that is accurately estimated from the input data. Extensive simulation studies showed a significantly improved performance of ChIP-BIT in target gene prediction, particularly for detecting weak binding signals at gene promoter regions. We applied ChIP-BIT to find target genes from NOTCH3 and PBX1 ChIP-seq data acquired from MCF-7 breast cancer cells. TF knockdown experiments have initially validated about 30% of co-regulated target genes identified by ChIP-BIT as being differentially expressed in MCF-7 cells. Functional analysis on these genes further revealed the existence of crosstalk between Notch and Wnt signaling pathways.
Density matrix formulation for quantum renormalization groups.

A generalization of the numerical renormalization-group procedure used first by Wilson for the Kondo problem is presented. It is shown that this formulation is optimal in a certain sense. As a demonstration of the effectiveness of this approach, results from numerical real-space renormalization-group calculations for Heisenberg chains are presented.
A Critical Review Of Emergency Evacuation Simulation Models

The paper presents a critical review of selected simulation models including (1) flow based, (2) cellular automata, (3) agent-based, and (4) activity-based models, as well as of three simulation models that incorporate social scientific processes--FIRESCAP, EXODUS, and the Multi-Agent Simulation for Crisis Management. It concludes by pointing out the so far ignored insights that could be derived from the fields of social psychology and social organization. A number of predictions regarding the effects of social organizational variables on the timing and movement of evacuating groups are presented. Proceeding of Conference “Building Occupant Movement During Fire Emergencies,” June 10-11, 2004. Gaithersburg, Maryland: National Institute of Standards and Technology, (forthcoming).
Lithium chloride prevents interleukin‐1β induced cartilage degradation and loss of mechanical properties

Osteoarthritis is a chronic degenerative disease that affects the articular cartilage. Recent studies have demonstrated that lithium chloride exhibits significant efficacy as a chondroprotective agent, blocking cartilage degradation in response to inflammatory cytokines. However, conflicting literature suggests lithium may affect the physicochemical properties of articular cartilage and thus long‐term exposure may negatively affect the mechanical functionality of this tissue. This study aims to investigate the effect of lithium chloride on the biomechanical properties of healthy and interleukin‐1β treated cartilage in vitro and examines the consequences of long‐term exposure to lithium on cartilage health in vivo. Bovine cartilage explants were treated with lithium chloride for 12 days. Chondrocyte viability, matrix catabolism and the biomechanical properties of bovine cartilage explants were not significantly altered following treatment. Consistent with these findings, long term‐exposure (9 months) to dietary lithium did not induce osteoarthritis in rats, as determined by histological staining. Moreover, lithium chloride did not induce the expression of catabolic enzymes in human articular chondrocytes. In an inflammatory model of cartilage destruction, lithium chloride blocked interleukin‐1β signaling in the form of nitric oxide and prostaglandin E2 release and prevented matrix catabolism such that the loss of mechanical integrity observed with interleukin‐1β alone was inhibited. This study provides further support for lithium chloride as a novel compound for the treatment of osteoarthritis. © 2015 The Authors. Journal of Orthopaedic Research published by Wiley Periodicals, Inc. J Orthop Res 33:1552–1559, 2015.
Lycium Barbarum Polysaccharides Decrease Hyperglycemia-Aggravated Ischemic Brain Injury through Maintaining Mitochondrial Fission and Fusion Balance

Although it has been reported that polysaccharides found in Lycium barbarum possess neuroprotective effects, little is known of their ability to ameliorate hyperglycemia-aggravated ischemia/reperfusion brain injury. In this study, normoglycemic (NG) and hyperglycemic (HG) rats were compared after 30 minutes of middle cerebral artery occlusion (MCAO), followed by 24 or 27 hours of reperfusion, with HG rats pretreated with lyceum barbarum polysaccharides (LBP) or insulin. In each group, the neurological deficit, infarct volume, pathohistology, and expression of proteins, Opa1 and Drp1, were assessed to determine the efficacy of LBP in alleviating hyperglycemia-aggravated ischemia/reperfusion brain injury. Our results show that, compared to the NG group, the HG group had increases in neurological deficits, infarct volume, and evidence of neuronal pyknosis at 24- and/or 72-h of reperfusion (P<0.05) and that pre-treatment with LBP decreased these effects (P<0.05). In addition, immunohistochemistry revealed an increase of Drp1 and a decrease of Opa1 positive neurons in the HG group after 24 and 72 hours of reperfusion when compared to the NG group. LBP treatment prevented the HG-induced alterations in Drp-1 and Opa1 expression. Western blots further confirmed these findings showing that HG caused an increase in phospho-Drp1 and a decrease in Opa1 which were subsequently reversed by LBP addition. These results suggest that hyperglycemia-aggravated ischemic brain damage is associated with an alteration of mitochondrial dynamics and that pre-treatment with LBP ameliorates the hyperglycemia-enhanced ischemic brain damage through maintaining mitochondrial dynamic balance.
Electrospinning of fibrous polymer scaffolds using positive voltage or negative voltage: a comparative study

Electrospinning of fibrous tissue engineering scaffolds has been traditionally conducted using positive voltages. In the current study, positive voltage (PV) electrospinning and negative voltage (NV) electrospinning were investigated for forming fibrous membranes of poly(hydroxybutyrate-co-hydroxyvalerate) (PHBV). In both PV-electrospinning and NV-electrospinning, the fiber diameter generally increased with increasing needle inner diameter and PHBV concentration but decreased with increasing working distance. The use of a conductivity-enhancing surfactant, benzyl triethylammonium chloride (BTEAC), significantly reduced PHBV fiber diameters from the micron scale to the sub-micron scale. Interestingly, with increasing applied voltage, the fiber diameter increased for PV-electrospinning but decreased for NV-electrospinning. The PV-electrospun fibrous membranes from solutions without BTEAC (PVEfm) and with BTEAC (PVEfm-B) and NV-electrospun membranes from solutions without BTEAC (NVEfm) and with BTEAC (NVEfm-B) were characterized in terms of their structure, wettability, thermal properties and tensile properties. Both PVEfm and NVEfm exhibited similar water contact angles (∼104°) but the contact angle of PVEfm-B or NVEfm-B was not measurable. The elongation at break of PVEfm-B or NVEfm-B was significantly higher than that of PVEfm or NVEfm. Using NV-electrospinning or a combination of NV- and PV-electrospinning may be very useful for developing suitable scaffolds for tissue engineering applications.
The Effect Of Stock Splits On Liquidity And Excess Returns: Evidence From Shareholder Ownership Composition

We examine the influence of firm ownership composition on both the abnormal returns at the announcement of a stock split and liquidity changes following a stock split. We find three results. First, the largest post-split increase in institutional ownership occurs for firms that had low institutional ownership before the split. Second, changes in liquidity are negatively related to the level of institutional ownership before the split. Last, the abnormal return following a split is negatively related to the level of institutional ownership before the split. These findings are important as they shed new light on the source of stock split announcement returns. 2003 The Southern Finance Association and the Southwestern Finance Association.
Effect of Television Viewing at Mealtime on Food Intake After a Glucose Preload in Boys

Television viewing (TVV) is considered a contributing factor to the development of childhood obesity yet it is unclear whether obesity results, in part, from increased energy intake during TVV. The objective of this study was to determine the effect of TVV on food intake (FI) of boys at a meal and its effect on caloric compensation at the test meal after a premeal glucose drink. On four separate mornings and in random order, boys received equally sweetened preloads containing Splenda sucralose or glucose [1.0 g/kg body weight (BW)] in 250 mL of water 2 h after a standard breakfast. Food intake from a pizza meal was measured 30 min later with or without TVV. Both preload treatment (p < 0.01) and TVV (p < 0.001) affected FI (kcal). TVV increased lunchtime FI by an average of 228 kcal. Glucose suppressed FI in the no TVV condition compared with control, but the effect was not statistically significant during TVV. Body composition and subjective appetite scores were positively associated with FI at the test lunch. In conclusion, TVV while eating a meal contributes to increased energy intake by delaying normal mealtime satiation and reducing satiety signals from previously consumed foods.