Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimization for Speculative Execution in Big Data Processing Clusters

A big parallel processing job can be delayed substantially as long as one of its many tasks is being assigned to an unreliable or congested machine. To tackle this so-called straggler problem, most parallel processing frameworks such as MapReduce have adopted various strategies under which the system may speculatively launch additional copies of the same task if its progress is abnormally slow when extra idling resource is available. In this paper, we focus on the design of speculative execution schemes for parallel processing clusters from an optimization perspective under different loading conditions. For the lightly loaded case, we analyze and propose one cloning scheme, namely, the Smart Cloning Algorithm (SCA) which is based on maximizing the overall system utility. We also derive the workload threshold under which SCA should be used for speculative execution. For the heavily loaded case, we propose the Enhanced Speculative Execution (ESE) algorithm which is an extension of the Microsoft Mantri scheme to mitigate stragglers. Our simulation results show SCA reduces the total job flowtime, i.e., the job delay/ response time by nearly <inline-formula><tex-math notation="LaTeX">$6$</tex-math><alternatives> <inline-graphic xlink:href="xu-ieq1-2564962.gif"/></alternatives></inline-formula> percent comparing to the speculative execution strategy of Microsoft Mantri. In addition, we show that the ESE Algorithm outperforms the Mantri baseline scheme by <inline-formula><tex-math notation="LaTeX">$71$</tex-math><alternatives> <inline-graphic xlink:href="xu-ieq2-2564962.gif"/></alternatives></inline-formula> percent in terms of the job flowtime while consuming the same amount of computation resource.
Fragment retransmission scheme with enhanced collision avoidance for energy-efficient IEEE 802.11 WLANs

In IEEE 802.11 based wireless local area networks (WLANs), channel induced errors and collisions cause transmission failures which waste bandwidth and energy. To improve the energy efficiency of battery powered mobile devices we propose a scheme which mitigates channel induced errors and collisions by using two ideas namely, backoff-free fragment retransmission and collision-free transmission schedules, respectively. Performance evaluation using ns-3 showed that the proposed scheme outperforms existing schemes in energy efficiency, throughput and delay.
Tight Bounds for Set Disjointness in the Message Passing Model

In a multiparty message-passing model of communication, there are $k$ players. Each player has a private input, and they communicate by sending messages to one another over private channels. While this model has been used extensively in distributed computing and in multiparty computation, lower bounds on communication complexity in this model and related models have been somewhat scarce. In recent work \cite{phillips12,woodruff12,woodruff13}, strong lower bounds of the form $\Omega(n \cdot k)$ were obtained for several functions in the message-passing model; however, a lower bound on the classical Set Disjointness problem remained elusive. In this paper, we prove tight lower bounds of the form $\Omega(n \cdot k)$ for the Set Disjointness problem in the message passing model. Our bounds are obtained by developing information complexity tools in the message-passing model, and then proving an information complexity lower bound for Set Disjointness. As a corollary, we show a tight lower bound for the task allocation problem \cite{DruckerKuhnOshman} via a reduction from Set Disjointness.
Bioactive Cembranoids from the Dongsha Atoll Soft Coral Sarcophyton crassocaule

Seven new cembranoids, sarcocrassocolides F–L (1–7), have been isolated from a soft coral Sarcophyton crassocaule. Their structures were determined by extensive spectroscopic analysis. Most new compounds exhibited significant cytotoxic activity against a limited panel of cancer cell lines, and the structure–activity relationship was studied. Compounds 1–7 were found to display significant in vitro anti-inflammatory activity in LPS-stimulated RAW264.7 macrophage cells by inhibiting the expression of the iNOS protein. Compound 4 was also found to effectively reduce the level of COX-2 protein.
Ageing of Cadmium Telluride Radiation Detectors and its Diagnostics with Low Frequency Noise

Samples of CdTe single crystals which are used as radiation detectors were periodically measured during a long time interval with different values of an applied voltage. The samples were also periodically exposed during long time periods to high temperatures of 390 K and to rapid changes of temperature from 300 K to 390 K. After 1.5 years of measurements we observed ageing of the samples which resulted in deterioration of their transport characteristics. The resistance of the samples increased significantly and current-voltage characteristics were unstable in time. Noise spectroscopy showed that low frequency noise can be used for detection of CdTe sample ageing as its spectral density increases significantly comparing to the 1/f noise of a high quality sample.
Universal Enumerative Coding for Tree Models

Efficient enumerative coding for tree sources is, in general, surprisingly intricate-a simple uniform encoding of type classes, which is asymptotically optimal in expectation for many classical models, such as FSMs, turns out not to be so in this case. We describe an efficiently computable enumerative code that is universal in the family of tree models in the sense that, for a string emitted by an unknown source whose model is supported on a known tree, the expected normalized code length of the encoding approaches the entropy rate of the source with a convergence rate (K/2)(log n)/n, where K is the number of free parameters of the model family. Based on recent results characterizing type classes of context trees, the code consists of the index of the sequence in the tree type class, and an efficient description of the class itself using a nonuniform encoding of selected string counts. The results are extended to a twice-universal setting, where the tree underlying the source model is unknown.
Polymorphonuclear Leukocytes

Complete protection of Staphylococcus aureus Wood 46 from gentamicin bactericidal activity was documented for microorganisms located within polymorphonuclear leukocytes. The highest, still ineffective gentamicin concentration tested in the phagocytic assay was 80 times higher than the minimal concentration required to kill uningested organisms. Extracellular gentamicin activity was unaffected by the phagocytic process as demonstrated by microbiological and enzymatic assays, and liberation of intracellular S. aureus by lysis of neutrophils showed the bacteria to be fully susceptible to the antibiotic. These results were corroborated by studies performed with ['4C]gentamicin; binding of the labeled antibiotic by resting neutrophils, or by neutrophils ingesting live, killed S. aureus or endotoxin-coated paraffin particles, showed no statistical differences and never exceeded 20% of the extracellular concentration. These results show that intraleukocytic S. aureus are protected from the bactericidal action of gentamicin and suggest that this protection can be explained by poor intracellular penetration of the antibiotic.
Local deformation models for monocular 3D shape recovery

Without a deformation model, monocular 3D shape recovery of deformable surfaces is severely under-constrained. Even when the image information is rich enough, prior knowledge of the feasible deformations is required to overcome the ambiguities. This is further accentuated when such information is poor, which is a key issue that has not yet been addressed. In this paper, we propose an approach to learning shape priors to solve this problem. By contrast with typical statistical learning methods that build models for specific object shapes, we learn local deformation models, and combine them to reconstruct surfaces of arbitrary global shapes. Not only does this improve the generality of our deformation models, but it also facilitates learning since the space of local deformations is much smaller than that of global ones. While using a texture-based approach, we show that our models are effective to reconstruct from single videos poorly-textured surfaces of arbitrary shape, made of materials as different as cardboard, that deforms smoothly, and much lighter tissue paper whose deformations may be far more complex.
Stopping eyes and hands: evidence for non-independence of stop and go processes and for a separation of central and peripheral inhibition

In the stop-signal paradigm, participants perform a primary reaction task, for example a visual or auditory discrimination task, and have to react to a go stimulus as quickly as possible with a specified motor response. In a certain percentage of trials, after presentation of the stimulus (go signal), another stimulus (stop signal) is presented with a variable stop-signal delay. Whenever a stop signal occurs, the participant is asked to inhibit the execution of the response. Here, an extended test of the popular horse race model for this task (Logan and Cowan, 1984) is presented. Responses for eye and hand movements in both single-task and dual-task conditions were collected. Saccadic reaction times revealed some significant violations of the model's basic assumption of independent go and inhibition processes for all six participants. Saccades that escaped an early stop signal were systematically slower and had smaller amplitudes compared to saccades without a stop signal. Moreover, the analysis of concomitant electromyographic responses recorded from the upper arm suggests the existence of two separate inhibitory mechanisms: a slow, selective, central inhibitory mechanism and a faster, highly efficient, peripheral one, which is probably ineffective for saccades.
Elaboration versus Suppression of Cued Memories: Influence of Memory Recall Instruction and Success on Parietal Lobe, Default Network, and Hippocampal Activity

Functional imaging studies of episodic memory retrieval consistently report task-evoked and memory-related activity in the medial temporal lobe, default network and parietal lobe subregions. Associated components of memory retrieval, such as attention-shifts, search, retrieval success, and post-retrieval processing also influence regional activity, but these influences remain ill-defined. To better understand how top-down control affects the neural bases of memory retrieval, we examined how regional activity responses were modulated by task goals during recall success or failure. Specifically, activity was examined during memory suppression, recall, and elaborative recall of paired-associates. Parietal lobe was subdivided into dorsal (BA 7), posterior ventral (BA 39), and anterior ventral (BA 40) regions, which were investigated separately to examine hypothesized distinctions in sub-regional functional responses related to differential attention-to-memory and memory strength. Top-down suppression of recall abolished memory strength effects in BA 39, which showed a task-negative response, and BA 40, which showed a task-positive response. The task-negative response in default network showed greater negatively-deflected signal for forgotten pairs when task goals required recall. Hippocampal activity was task-positive and was influenced by memory strength only when task goals required recall. As in previous studies, we show a memory strength effect in parietal lobe and hippocampus, but we show that this effect is top-down controlled and sensitive to whether the subject is trying to suppress or retrieve a memory. These regions are all implicated in memory recall, but their individual activity patterns show distinct memory-strength-related responses when task goals are varied. In parietal lobe, default network, and hippocampus, top-down control can override the commonly identified effects of memory strength.
A Unifying Framework for Marginalised Random‐Intercept Models of Correlated Binary Outcomes

We demonstrate that many current approaches for marginal modelling of correlated binary outcomes produce likelihoods that are equivalent to the copula‐based models herein. These general copula models of underlying latent threshold random variables yield likelihood‐based models for marginal fixed effects estimation and interpretation in the analysis of correlated binary data with exchangeable correlation structures. Moreover, we propose a nomenclature and set of model relationships that substantially elucidates the complex area of marginalised random‐intercept models for binary data. A diverse collection of didactic mathematical and numerical examples are given to illustrate concepts. Copyright © 2013 John Wiley & Sons, Ltd.
Information extraction from sound for medical telemonitoring

Today, the growth of the aging population in Europe needs an increasing number of health care professionals and facilities for aged persons. Medical telemonitoring at home (and, more generally, telemedicine) improves the patient's comfort and reduces hospitalization costs. Using sound surveillance as an alternative solution to video telemonitoring, this paper deals with the detection and classification of alarming sounds in a noisy environment. The proposed sound analysis system can detect distress or everyday sounds everywhere in the monitored apartment, and is connected to classical medical telemonitoring sensors through a data fusion process. The sound analysis system is divided in two stages: sound detection and classification. The first analysis stage (sound detection) must extract significant sounds from a continuous signal flow. A new detection algorithm based on discrete wavelet transform is proposed in this paper, which leads to accurate results when applied to nonstationary signals (such as impulsive sounds). The algorithm presented in this paper was evaluated in a noisy environment and is favorably compared to the state of the art algorithms in the field. The second stage of the system is sound classification, which uses a statistical approach to identify unknown sounds. A statistical study was done to find out the most discriminant acoustical parameters in the input of the classification module. New wavelet based parameters, better adapted to noise, are proposed in this paper. The telemonitoring system validation is presented through various real and simulated test sets. The global sound based system leads to a 3% missed alarm rate and could be fused with other medical sensors to improve performance
Pearl Nuts and Plasma Lipids : An Almond-Based Diet Lowers LDL-C while Preserving HDLC Gene

Objective: To compare lipid-altering effects of an almond-based diet with an olive oil-based diet, against a cheese and butter-based control diet. Methods: Forty-five free-living hyperlipidemic men (n 512) and women (n 533) with a mean plasma total cholesterol (TC) of 251 630 mg/dL followed one of three diets; almond-based, olive oil-based, or dairy-based for 4 weeks. Total fat in each diet was matched, and the study-provided sources of fat comprised the major portion of fat intake. Results:Reductions in TC and low-density lipoprotein-cholesterol (LDL-C) between the three groups were significantly different from the almond group (both p ,0.001). Within group analysis revealed that the almond-based diet induced significant reductions in TC (p ,0.05), LDL-C (p,0.001), and the TC:HDL ratio (p,0.001), while HDL-C levels were preserved. TC and HDL-C in the control diet were significantly increased from baseline (both p ,0.05), while the olive oil-based diet resulted in no significant changes over the study period. Weight did not change significantly. Conclusion: Results suggest that the more favorable lipid-altering effects induced by the almond group may be due to interactive or additive effects of the numerous bioactive constituents found in almonds.
FlowFence: Practical Data Protection for Emerging IoT Application Frameworks

Emerging IoT programming frameworks enable building apps that compute on sensitive data produced by smart homes and wearables. However, these frameworks only support permission-based access control on sensitive data, which is ineffective at controlling how apps use data once they gain access. To address this limitation, we present FlowFence, a system that requires consumers of sensitive data to declare their intended data flow patterns, which it enforces with low overhead, while blocking all other undeclared flows. FlowFence achieves this by explicitly embedding data flows and the related control flows within app structure. Developers use Flow-Fence support to split their apps into two components: (1) A set of Quarantined Modules that operate on sensitive data in sandboxes, and (2) Code that does not operate on sensitive data but orchestrates execution by chaining Quarantined Modules together via taint-tracked opaque handles-references to data that can only be dereferenced inside sandboxes. We studied three existing IoT frameworks to derive key functionality goals for Flow-Fence, and we then ported three existing IoT apps. Securing these apps using FlowFence resulted in an average increase in size from 232 lines to 332 lines of source code. Performance results on ported apps indicate that FlowFence is practical: A face-recognition based door-controller app incurred a 4.9% latency overhead to recognize a face and unlock a door.
Prenatal Famine and Genetic Variation Are Independently and Additively Associated with DNA Methylation at Regulatory Loci within IGF2/H19

Both the early environment and genetic variation may affect DNA methylation, which is one of the major molecular marks of the epigenome. The combined effect of these factors on a well-defined locus has not been studied to date. We evaluated the association of periconceptional exposure to the Dutch Famine of 1944–45, as an example of an early environmental exposure, and single nucleotide polymorphisms covering the genetic variation (tagging SNPs) with DNA methylation at the imprinted IGF2/H19 region, a model for an epigenetically regulated genomic region. DNA methylation was measured at five differentially methylated regions (DMRs) that regulate the imprinted status of the IGF2/H19 region. Small but consistent differences in DNA methylation were observed comparing 60 individuals with periconceptional famine exposure with unexposed same-sex siblings at all IGF2 DMRs (PBH<0.05 after adjustment for multiple testing), but not at the H19 DMR. IGF2 DMR0 methylation was associated with IGF2 SNP rs2239681 (PBH = 0.027) and INS promoter methylation with INS SNPs, including rs689, which tags the INS VNTR, suggesting a mechanism for the reported effect of the VNTR on INS expression (PBH = 3.4×10−3). Prenatal famine and genetic variation showed similar associations with IGF2/H19 methylation and their contributions were additive. They were small in absolute terms (<3%), but on average 0.5 standard deviations relative to the variation in the population. Our analyses suggest that environmental and genetic factors could have independent and additive similarly sized effects on DNA methylation at the same regulatory site.
Helicobacter pylori seropositivity and subsite-specific gastric cancer risks in Linxian, China.

BACKGROUND Helicobacter pylori carriage (i.e., persistent exposure to the organism without gastric epithelial cell invasion) is an established risk factor for noncardia gastric cancer. However, its association with the risk of cancer of the gastric cardia is controversial. Consequently, we designed this prospective, nested case-control study to further explore the subsite-specific gastric cancer risks associated with H. pylori seropositivity (a surrogate marker for persistent exposure). METHODS A total of 99 patients with gastric cardia cancer, 82 patients with noncardia gastric cancer, and 192 cancer-free subjects were selected from among the participants (n = 29 584) of a nutrition intervention trial previously conducted in Linxian, China. H. pylori seropositivity was determined by assaying for the presence of H. pylori whole cell and CagA antibodies in baseline serum samples from all subjects. Seropositivity was defined as one or both serum assays being positive. Odds ratios (ORs) for subsite-specific gastric cancer were estimated by multivariate logistic regression analyses. All statistical comparisons were two-sided (alpha =.05). RESULTS H. pylori seropositivity rates for subjects with gastric cardia cancer, noncardia gastric cancer, and gastric cardia and noncardia cancers combined were 70% (P =.02), 72% (P: =.01), and 71% (P =.003) compared with 56% for cancer-free control subjects. OR estimates for H. pylori seropositivity were 1.87 (95% confidence interval [CI] = 1.10 to 3.17) for gastric cardia cancer, 2.29 (95% CI = 1.26 to 4.14) for noncardia gastric cancer, and 2.04 (95% CI = 1.31 to 3.18) for gastric cardia and noncardia cancers combined. CONCLUSIONS H. pylori seropositivity was associated with increased risks for both gastric cardia cancer and noncardia gastric cancer in this well-characterized cohort. Thus, H. pylori carriage may increase the risk of cancer throughout the stomach.
Study on residual resist layer thickness measurement for Nanoimprint Lithography based on near-field optics

To realise Nanoimprint Lithography (NIL) as a highly reliable lithography technique for the next-generation semiconductor fabrication process, it is seriously necessary to measure the thickness of the residual resin layer of several 10 nm remaining between the imprinted patterns and the substrate. In this paper, we propose a novel optical measurement method for the
Speech Dereverberation Based on Integrated Deep and Ensemble Learning Algorithm

Reverberation, which is generally caused by sound reflections from walls, ceilings, and floors, can result in severe performance degradation of acoustic applications. Due to a complicated combination of attenuation and time-delay effects, the reverberation property is difficult to characterize, and it remains a challenging task to effectively retrieve the anechoic speech signals from reverberation ones. In the present study, we proposed a novel integrated deep and ensemble learning algorithm (IDEA) for speech dereverberation. The IDEA consists of offline and online phases. In the offline phase, we train multiple dereverberation models, each aiming to precisely dereverb speech signals in a particular acoustic environment; then a unified fusion function is estimated that aims to integrate the information of multiple dereverberation models. In the online phase, an input utterance is first processed by each of the dereverberation models. The outputs of all models are integrated accordingly to generate the final anechoic signal. We evaluated the IDEA on designed acoustic environments, including both matched and mismatched conditions of the training and testing data. Experimental results confirm that the proposed IDEA outperforms single deep-neural-network-based dereverberation model with the same model architecture and training data.