Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast Rate Analysis of Some Stochastic Optimization Algorithms

In this paper, we revisit three fundamental and popular stochastic optimization algorithms (namely, Online Proximal Gradient, Regularized Dual Averaging method and ADMM with online proximal gradient) and analyze their convergence speed under conditions weaker than those in literature. In particular, previous works showed that these algorithms converge at a rate of O(ln T/T) when the loss function is strongly convex, and O(1/√T) in the weakly convex case. In contrast, we relax the strong convexity assumption of the loss function, and show that the algorithms converge at a rate O(ln T/T) if the expectation of the loss function is locally strongly convex. This is a much weaker assumption and is satisfied by many practical formulations including Lasso and Logistic Regression. Our analysis thus extends the applicability of these three methods, as well as provides a general recipe for improving analysis of convergence rate for stochastic and online optimization algorithms.
Lipolysis of LDL by Human Secretory Phospholipase A2 Induces Particle Fusion and Enhances the Retention of LDL to Human Aortic Proteoglycans

Abstract—The first morphological sign of atherogenesis is the accumulation of extracellular lipid droplets in the proteoglycan-rich subendothelial layer of the arterial intima. Secretory nonpancreatic phospholipase A2 (snpPLA2), an enzyme capable of lipolyzing LDL particles, is found in the arterial extracellular matrix and in contact with the extracellular lipid droplets. We have recently shown that in the presence of heparin, lipolysis of LDL with bee venom PLA2 induces aggregation and fusion of the particles. Here, we studied the effect of human snpPLA2 on the integrity of LDL particles and on their interaction with human aortic proteoglycans. In addition, the capacity of the proteoglycans to retain PLA2-lipolyzed LDL particles was tested in a microtiter well assay. We found that lipolysis of LDL induced fusion of proteoglycan-bound LDL particles, which increased their binding strength to the proteoglycans. Moreover, lipolysis of LDL with snpPLA2 under physiological salt and albumin concentrations induced a 3-fold increase in the amount of LDL bound to proteoglycans. The results imply a role for PLA2 in the retention and accumulation of LDL to the proteoglycan matrix in atherosclerosis.
Policy gradient methods

A policy gradient method is a reinforcement learning approach that directly optimizes a parametrized control policy by gradient descent. It belongs to the class of policy search techniques that maximize the expected return of a policy in a fixed policy class while traditional value function approximation approaches derive policies from a value function. Policy gradient approaches have various advantages: they allow the straightforward incorporation of domain knowledge in the policy parametrization and often significantly fewer parameters are needed for representing the optimal policy than the corresponding value function. They are guaranteed to converge to at least a locally optimal policy and can handle continuous states and action, and often even imperfect state information. Their major drawbags are the difficult use in off-policy settings, their slow convergence in discrete problems and that global optima are not attained.
Isolation and characterization of plaque-forming lambdadnaZ+ transducing bacteriophages

The Escherichia coli dnaZ gene, a deoxyribonucleic acid (DNA) polymerization gene, is located 1.2 min counterclockwise from purE, at approximately min 10.5 on the E. coli map. From a lysogen with lamdacI857 integrated at a secondary attachment site near purE, transducing phages (lambdadnaS+) that transduced a dnaZts (lambda+) recipient to temperature insensitivity (TS+) were discovered. Three different plaque-forming transducing phages were isolated from seven primary heterogenotes. Genetic tests and heteroduplex mapping were used to determine the length and position of E. coli DNA within the lambda DNA. Complementation tests demonstrated that the deletions in all three strains removed both att P and the int gene, i,e. , DNA from both prophage ends. Heteroduplex mapping confirmed this result by demonstrating that all three strains had deletions of lambda DNA that covered the b2 to red region, thereby removing both prophage ends. Specifically, the deletions removed lambda DNA between the points 39.3 to 66.5% of lambda length (measured in percent length from the left and of lambda phage DNA) in all three strains. The three strains are distinct, however, because they had differing lengths of host DNA insertions. These phages must have been formed by an anomalous procedure, because standard lambda transducing phages are deleted for one prophage end only. In lambdagal and lambdabio strains, the deletions of lambda DNA begin at the union of prophage ends (i.e., position 57.3% of lambda length) and extend leftward or rightward, respectively (Davidson and Szybalski, in A, D. Hershey [ed.], The Bacteriophage Lambda, p. 45-82, 1971). Models for formation of the lambdadnaZ+ phages are discussed.
Can Thread Priorities be Used to Provide Difierentiated Quality of Service for Web Applications

Resumen|The e-commerce web sites receive a great and varied number of visitors every day. These visitors share the application server’s limited resources and when there are too many clients connecting to the web site, it is possible that they hinder between them, even to overload the application server. These visitors can be divided in difierent categories, depending on their importance from site viewpoint. Considering the importance that in these web sites some client connections (e.g. buyers’ connections) flnish successfully before other connections, in this paper we propose a mechanism to provide difierent quality of service to the difierent client categories by assigning difierent priorities to the threads attending the connections. After observing that Java Thread Priorities are only applied within the JVM, and moreover, these priorities do not reach the O.S. threads, we propose to schedule threads using the Linux Real Time priorities. Our results demonstrate that difierent quality of service classes can be supported using this mechanism. Palabras clave| SSL, Threads, Priority, QoS, Linux, JVM, Operating System
Glutamatergic Targets for Enhancing Extinction Learning in Drug Addiction

The persistence of the motivational salience of drug-related environmental cues and contexts is one of the most problematic obstacles to successful treatment of drug addiction. Behavioral approaches to extinguishing the salience of drug-associated cues, such as cue exposure therapy, have generally produced disappointing results which have been attributed to, among other things, the context specificity of extinction and inadequate consolidation of extinction learning. Extinction of any behavior or conditioned response is a process of new and active learning, and increasing evidence suggests that glutamatergic neurotransmission, a key component of the neural plasticity that underlies normal learning and memory, is also involved in extinction learning. This review will summarize findings from both animal and human studies that suggest that pharmacological enhancement of glutamatergic neurotransmission facilitates extinction learning in the context of drug addiction. Pharmacological agents that have shown potential efficacy include NMDA partial agonists, mGluR5 receptor positive allosteric modulators, inhibitors of the GlyT1 glycine transporter, AMPA receptor potentiators, and activators of the cystine-glutamate exchanger. These classes of cognition-enhancing compounds could potentially serve as novel pharmacological adjuncts to cue exposure therapy to increase success rates in attenuating cue-induced drug craving and relapse.
Learning Data Manifolds with a Cutting Plane Method

Abstract We consider the problem of classifying data manifolds where each manifold represents invariances that are parameterized by continuous degrees of freedom. Conventional data augmentation methods rely on sampling large numbers of training examples from these manifolds. Instead, we propose an iterative algorithm, MCP, based on a cutting plane approach that efficiently solves a quadratic semi-infinite programming problem to find the maximum margin solution. We provide a proof of convergence as well as a polynomial bound on the number of iterations required for a desired tolerance in the objective function. The efficiency and performance of MCP are demonstrated in high-dimensional simulations and on image manifolds generated from the ImageNet data set. Our results indicate that MCP is able to rapidly learn good classifiers and shows superior generalization performance compared with conventional maximum margin methods using data augmentation methods.
Pitch synchronous spectral analysis scheme for voiced speech

The problem of spectrum analysis of harmonic signals which are periodic or at least quasi-periodic, such as human voice, is addressed. An efficient and accurate pitch-synchronized spectral analysis scheme for obtaining the Fourier coefficients of a harmonic signal, sampled at an arbitrary rate above the Nyquist critical rate, is outlined. The pitch is derived from the sampled signal prior to the spectral analysis. The rationale behind the scheme is based on an interpolation of the signal with an upsampling rate that is synchronized with the pitch period of the signal. It is shown that the resulting unsampled sequence is aperiodic, but nevertheless can be decomposed into a periodic signal corrupted by a small, aperiodic, high-frequency noise. The fact that this noise is correlated with the signal is used to obtain a closed-form solution for the desired Fourier coefficients from the noisy values, using the computationally superior fast Fourier transform (FFT) algorithm. The accuracy of the scheme is demonstrated for synthetic speech for which the spectrum is known a priori. The results obtained for real speech signals show better consistency across adjacent frames as compared to conventional methods. >
A versatile software package for inter-subject correlation based analyses of fMRI

In the inter-subject correlation (ISC) based analysis of the functional magnetic resonance imaging (fMRI) data, the extent of shared processing across subjects during the experiment is determined by calculating correlation coefficients between the fMRI time series of the subjects in the corresponding brain locations. This implies that ISC can be used to analyze fMRI data without explicitly modeling the stimulus and thus ISC is a potential method to analyze fMRI data acquired under complex naturalistic stimuli. Despite of the suitability of ISC based approach to analyze complex fMRI data, no generic software tools have been made available for this purpose, limiting a widespread use of ISC based analysis techniques among neuroimaging community. In this paper, we present a graphical user interface (GUI) based software package, ISC Toolbox, implemented in Matlab for computing various ISC based analyses. Many advanced computations such as comparison of ISCs between different stimuli, time window ISC, and inter-subject phase synchronization are supported by the toolbox. The analyses are coupled with re-sampling based statistical inference. The ISC based analyses are data and computation intensive and the ISC toolbox is equipped with mechanisms to execute the parallel computations in a cluster environment automatically and with an automatic detection of the cluster environment in use. Currently, SGE-based (Oracle Grid Engine, Son of a Grid Engine, or Open Grid Scheduler) and Slurm environments are supported. In this paper, we present a detailed account on the methods behind the ISC Toolbox, the implementation of the toolbox and demonstrate the possible use of the toolbox by summarizing selected example applications. We also report the computation time experiments both using a single desktop computer and two grid environments demonstrating that parallelization effectively reduces the computing time. The ISC Toolbox is available in https://code.google. com/p/isc-toolbox/
Automatic performance evaluation for video text detection

We propose an objective, comprehensive and difficulty-independent performance evaluation protocol for video text detection algorithms. The protocol includes a positive set and a negative set of indices at textbox level, which evaluate the detection quality in terms of both location accuracy and fragmentation of the detected textboxes. In the protocol, we assign a detection difficulty (DD) level to each ground truth textbox. The performance indices can then be normalized with respect to the textbox DD level and are therefore independent of the ground truth difficulty. We also assign a detection importance (DI) level to each ground truth textbox. The overall detection rate is the DI-weighted average of the detection qualities of all ground truth textboxes, which makes the detection rate more accurate to reveal the real performance. The automatic performance evaluation scheme has been applied on a text detection approach to determine the best parameters that can yield the best detection results.
Increased Expression of Colonic Wnt9A through Sp1-mediated Transcriptional Effects involving Arylsulfatase B, Chondroitin 4-Sulfate, and Galectin-3

Background: Mechanism by which Wnt expression was increased by carrageenan exposure was unknown. Results: Sp1 activated Wnt9A transcription through changes in arylsulfatase B, chondroitin 4-sulfation, and galectin-3. Conclusion: Decline in arylsulfatase B leads to transcriptional effects mediated by Sp1 and galectin-3. Significance: Extracellular events can regulate transcription through changes in arylsulfatase B and chondroitin 4-sulfation. In cultured human colonic epithelial cells and mouse colonic tissue, exposure to the common food additive carrageenan leads to inflammation, activation of Wnt signaling, increased Wnt9A expression, and decline in the activity of the enzyme arylsulfatase B (ARSB; N-acetylgalactosamine-4-sulfatase). In this study, the novel transcriptional mechanism by which carrageenan and decline in ARSB increase Wnt9A expression in NCM460 and HT-29 human colonic epithelial cells and in mouse colon is presented. Increased expression of Wnt9A has been associated with multiple malignancies, including colon carcinoma, and with ectodermal and mesoendodermal morphogenesis. When ARSB activity was reduced by siRNA or by exposure to carrageenan (1 μg/ml for 24 h), degradation of chondroitin 4-sulfate (C4S) was inhibited, leading to accumulation of more highly sulfated C4S, which binds less galectin-3, a β-galactoside-binding protein. Nuclear galectin-3 increased and mediated increased binding of Sp1 to the Sp1 consensus sequence in the Wnt9A promoter, shown by oligonucleotide-binding assay and by chromatin immunoprecipitation assay. When galectin-3 was silenced, the increases in Sp1 binding to the Wnt9A promoter and in Wnt9A expression, which followed carrageenan or ARSB silencing, were inhibited. Mithramycin A, a specific inhibitor of Sp1 oligonucleotide binding, and Sp1 siRNA blocked the carrageenan- and ARSB siRNA-induced increases in Wnt9A expression. These studies reveal how carrageenan exposure can lead to transcriptional events in colonic epithelial cells through decline in arylsulfatase B activity, with subsequent impact on C4S, galectin-3, Sp1, and Wnt9A and can exert significant effects on Wnt-initiated signaling and related vital cell processes.
Frontal Eye Field Neurons with Spatial Representations Predicted by Their Subcortical Input

The frontal eye field (FEF) is a cortical structure involved in cognitive aspects of eye movement control. Neurons in the FEF, as in most of cerebral cortex, primarily represent contralateral space. They fire for visual stimuli in the contralateral field and for saccadic eye movements made to those stimuli. Yet many FEF neurons engage in sophisticated functions that require flexible spatial representations such as shifting receptive fields and vector subtraction. Such functions require knowledge about all of space, including the ipsilateral hemifield. How does the FEF gain access to ipsilateral information? Here, we provide evidence that one source of ipsilateral information may be the opposite superior colliculus (SC) in the midbrain. We physiologically identified neurons in the FEF that receive input from the opposite SC, same-side SC, or both. We found a striking structure–function relationship: the laterality of the response field of an FEF neuron was predicted by the laterality of its SC inputs. FEF neurons with input from the opposite SC had ipsilateral fields, whereas neurons with input from the same-side SC had contralateral fields. FEF neurons with input from both SCs had lateralized fields that could point in any direction. The results suggest that signals from the two SCs provide each FEF with information about all of visual space, a prerequisite for higher level sensorimotor computations.
A future of traffic management: toward a hybrid system of roadside and personal mobile devices

In the last few decades, increasing traffic has led to serious problems in urban areas. Travel times for travellers have increased and the liveability in residential areas has declined due to pollution and issues concerning safety. Whereas new road and rail infrastructure in densely populated areas is costly, a better utilisation of existing infrastructure appears to be more attractive. This becomes increasingly possible due to huge developments in the world of Information and Communication Technology (ICT). However, implementing ICT solutions for the purpose of traffic management remains challenging. First, it is quite a task to set up a system in which infrastructure, travel vehicles and travellers can communicate with each other. Secondly, it is quite difficult to gather and exchange traffic and travel information in such a way that the traffic situation improves significantly. This paper deals with the latter issue, and it provides an outline for the possible architecture of a future traffic management system. It concludes that in such a system both mobile devices, like smartphones and navigation systems, and roadside devices, like loop detectors and cameras, need to be included to arrive at optimal results.
Recapturing What Was Lost : Re-emphasizing Locality in Social Interactions on the Net

Locality, the impact of geography in physical space on social interactions in virtual space, is resurfacing as an important attribute in the successful design and maintenance of Web sites and online communities. This paper briefly traces the history of this attribute in computer-mediated communication system experience over the past 15 years and offers a critical survey of contemporary localization efforts online. A set of fundamental design dimensions and a preliminary framework for examining locality on the Web are developed from real examples. This exploratory work forms the foundation for future empirical work to better understand and support locality for Net users’ online interactions.
Pattern-preserving-based motion imitation for robots

This paper presents a new algorithm of encoding dynamic movements through pattern-preserving optimization by a physical robot. This research follows a recent robot programming approach called learning from demonstration in which the motion trajectory is learned from human demonstrations. The motivation of this work is to deal with major challenges in learning from demonstration such as embodiment mapping, generalization, adaptation, robustness to perturbations, stability, pattern-preserving, and parameter tuning. We propose a new method that can deal with those problems and present empirical results to support our insistence.
Efficient dual-scale flow and thermo-chemo-rheological coupling simulation during on-line mixing resin transfer molding process

Simulation tools are required to ease the determination of the optimal process parameters and injection strategy of short cycle resin transfer molding (RTM). The developed finite element method/volume of fluid numerical tool aims to simulate accurately and efficiently the flow of a reactive resin mixed on-line in a dual-scale porous reinforcement during the resin transfer molding process. A macroscopic mesh deals with the flow inside of the channels of the reinforcement while a representative microstructure associated to each element allows reproducing both the unsaturated area and the intra-tow resin storage. Degree of cure, temperature, and viscosity are updated and transported at each time step, both in the channels and in the tows of the fabric using advection equations and sink and source terms for inter-scale exchanges. A new flexible approach based on the textile’s geometry defines automatically the representative microstructure associated to each macroscopic element depending on its size and shape. Additionally, tow saturation is simplified under the assumption of high-speed injection to a sum of one-dimensional transverse tow saturation problems, which reduces the computational cost of the simulation. Convergence tests have highlighted the ability for the simulation tool to treat with an equivalent degree of accuracy a saturation problem with elements exhibiting element sizes three times smaller to three times bigger than the length of the unsaturated area. Significant computation time reductions have also been noticed when large elements were used. Finally thermo-chemo-rheological coupled simulations have been conducted, highlighting the importance of taking the dual-scale effect into account when simulating reactive injections with on-line mixing.
A randomized-controlled trial of low-dose doxycycline for periodontitis in smokers.

BACKGROUND/AIM Tobacco use reduces the effect of non-surgical periodontal therapy. Host-modulation with low-dose doxycycline (LDD) might favour repair and promote an improved treatment response. The aim of this study was to investigate the effect of LDD in smokers on non-surgical periodontal therapy. MATERIAL AND METHODS This was a parallel arm, randomized, identical placebo-controlled trial with masking of examiner, care-giver, participant and statistician and 6 months of follow-up. Patients received non-surgical therapy and 3 months of test or control drug. Statistical analysis used both conventional methods and multilevel modelling. RESULTS Eighteen control and 16 test patients completed the study. The velocity of change was statistically greater for the test group for clinical attachment level -0.19 mm/month (95% CI=-0.34, 0.04; p=0.012) and probing depth 0.30 mm/month (95% CI=-0.42, -0.17; p<0.001). However, no differences were observed for absolute change in clinical or biochemical markers at 6 months. CONCLUSIONS This study does not provide evidence of a benefit of using LDD as an adjunct to non-surgical periodontal therapy in smokers.