Miracle-dz/UniFAR-FTUs huggingface dataset:
Convergence Rate Analysis of Primal-Dual Splitting Schemes

Primal-dual splitting schemes are a class of powerful algorithms that solve complicated monotone inclusions and convex optimization problems that are built from many simpler pieces. They decompose problems that are built from sums, linear compositions, and infimal convolutions of simple functions so that each simple term is processed individually via proximal mappings, gradient mappings, and multiplications by the linear maps. This leads to easily implementable and highly parallelizable or distributed algorithms, which often obtain nearly state-of-the-art performance. In this paper, we analyze a monotone inclusion problem that captures a large class of primal-dual splittings as a special case. We introduce a unifying scheme and use some abstract analysis of the algorithm to prove convergence rates of the proximal point algorithm, forward-backward splitting, Peaceman--Rachford splitting, and forward-backward-forward splitting applied to the model problem. Our ergodic convergence rates are deduced under var.
SIMD Ray Stream Tracing - SIMD Ray Traversal with Generalized Ray Packets and On-the-fly Re-Ordering -

Achieving high performance on modern CPUs requires ecient utilization of SIMD units. Doing so requires that algorithms are able to take full advantage of the SIMD width oered and to not waste SIMD instructions on low utilization cases. Ray tracers exploit SIMD extensions through packet tracing. This re-casts the ray tracing algorithm into a SIMD framework, but high SIMD eciency is only achieved for moderately complex scenes, and highly coherent packets. In this paper, we present a stream programming oriented traversal algorithm that processes streams of rays in SIMD fashion; the algorithm is motivated by breadth-first ray traversal and implicitly re-orders streams of rays on the fly by removing deactivated rays after each traversal step using a stream compaction step. This improves SIMD eciency in the presence of complex scenes and
Short and Long-Term Outcomes of Epidural or Intravenous Analgesia after Esophagectomy: A Propensity-Matched Cohort Study

Background and Objectives As a well-established technique for postoperative pain relief, the benefits of epidural analgesia (EDA) have been under debate recently. This study aimed to determine whether EDA could improve perioperative outcomes and survival in patients undergoing esophagectomy. Methods From January 2010 to December 2012, 587 consecutive cases undergoing McKeown-type esohpageactomy were retrospectively identified from a prospectively maintained database. Results After propensity-matching, incorporating baseline characteristics, 178 cases were included in each group, and patients characteristics distributions were well-balanced between two groups. Compared with intravenous analgesia, the use of EDA significantly decreased the incidence of pneumonia from 32% to 19.7% (P = 0.008), and anastomotic leakage from 23.0% to 14.0% (P = 0.029). The change in CRP level of EDA group was significantly decreased (preoperative, 6.2 vs. 6.2; POD 1, 108.1 vs. 121.3; POD 3, 131.5 vs. 137.8; POD 7, 69.3 vs. 82.1 mg/L; P = 0.044). EDA patients had a significantly longer duration of indwelling urinary catheter (P<0.001), and lower levels in both systolic (P = 0.001) and diastolic blood pressure (P<0.001). There weren't significant differences in overall survival (log-rank P = 0.47) and recurrence (Gray-test P = 0.46) between two groups. Conclusions These findings revealed that EDA could attenuate inflammatory response and reduce the incidence of pneumonia and anastomotic leakage after esophagectomy, at the price of delayed urinary catheter removal and lower blood pressure. EDA remains an important component of multimodal perioperative management after esophagectomy.
Secure Modular Hashing

In many situations, such as in biometric applications, there is need to encrypt and “hide” data, while simultaneously permitting restricted computations on them. We present a method to securely determine the ℓ2 distance between two signals if they are close enough. This method relies on a locality sensitive hashing scheme based on a secure modular embedding, computed using quantized random projections, being a generalization of previous work in the area. Secure Modular Hashes (SMH) extracted from the signals preserve information about the distance between the signals, hiding other characteristic from the signals. Theoretical properties state that the described scheme provides a mechanism to threshold how much information to reveal, and is also information theoretically secure above this threshold. Finally, experimental results reveal that distances computed from SMH vectors can effectively replace the actual Euclidean distances with minimal degradation.
Extrapolating abundance curves has no predictive power for estimating microbial biodiversity

Locey and Lennon (1) recently conducted an analysis of microbial and macrobial communities to investigate the effect of sample size (N, number of individuals or reads observed) on community species richness (S), species evenness (Simpson), frequency distribution skew, and frequency count of most abundant taxa. They argue that log–log linear models fit these relationships, specifically claiming that the index of the power law between sample size and species richness is consistent across macro- and microorganisms. Furthermore, they use the “lognormal model of biodiversity” to estimate global microbial biodiversity around 1011 to 1012 taxa. Although their claims are appealing and elegant, I argue (from a statistical perspective) …
Controllability Modulates the Anticipatory Response in the Human Ventromedial Prefrontal Cortex

Research has consistently shown that control is critical to psychological functioning, with perceived lack of control considered to play a crucial role in the manifestation of symptoms in psychiatric disorders. In a model of behavioral control based on non-human animal work, Maier et al. (2006) posited that the presence of control activates areas of the ventromedial prefrontal cortex (vmPFC), which in turn inhibit the normative stress response in the dorsal raphe nucleus and amygdala. To test Maier’s model in humans, we investigated the effects of control over potent aversive stimuli by presenting video clips of snakes to 21 snake phobics who were otherwise healthy with no comorbid psychopathologies. Based on prior research documenting that disrupted neural processing during the anticipation of adverse events can be influenced by different forms of cognitive processing such as perceptions of control, analyses focused on the anticipatory activity preceding the videos. We found that phobics exhibited greater vmPFC activity during the anticipation of snake videos when they had control over whether the videos were presented as compared to when they had no control over the presentation of the videos. In addition, observed functional connectivity between the vmPFC and the amygdala is consistent with previous work documenting vmPFC inhibition of the amygdala. Our results provide evidence to support the extension of Maier’s model of behavioral control to include anticipatory function in humans.
Wireless Internet Technology to Support Learning in the University of Jordan: Students Voices

This study aimed to determine the obstacles that face the students in The University of Jordan while using wireless Internet technology. In addition, the study aimed to determine any statistical significant differences in students estimates of the obstacles in use with regard to their (gender, and the university educational level). A stratified random sample (500) students (male, female) were selected from the University of Jordan during the academic year 2013-2014. A questionnaire with three sections was developed for collecting data to answer the research questions of the study. First section was for demographic information; second section consisted of (11) items, and third section with an open-ended question. The results showed that students’ estimates of the obstacles they encounter during their use of wireless Internet technology in learning was very high. There were statistical significant differences with the means of the students’ estimates for the obstacles in their use with regard to gender in favor of females. In addition, there were no statistical significant differences with the means of students’ estimates for the obstacles in their use with regard to university educational level. The most important obstacles faced the students were: the weakness of Internet wireless coverage for all the buildings in the University of Jordan, and lack of sufficient power switches for charging portable devices on campus.
Signaling mechanisms underlying strain-dependent brain natriuretic peptide gene transcription.

Activation of brain natriuretic peptide (BNP) gene promoter activity represents one of the earliest and most reliable markers of ventricular cardiac myocyte hypertrophy. We recently demonstrated that mechanical strain increases immunoreactive BNP secretion, steady-state BNP mRNA levels and BNP gene transcriptional activity in neonatal rat myocyte cultures. We have also shown that strain-dependent BNP gene transcription is critically dependent on the functional integrity of a number of integrins (specfically beta1, beta3, and alpha(v)beta5 integrins) present on the surface of cardiac myocytes. When used alone, each of these antibodies resulted in a significant reduction in strain-dependent activation of a transfected hBNP-luciferase reporter and inhibition of a number of signaling pathways that have been linked to stimulation of this reporter (e.g., extracellular signal regulated kinase and c-Jun amino terminal kinase). The present study shows that combinations of these antibodies resulted in further reductions in hBNP gene promoter activity and inhibition of the relevant signaling cascades. These studies provide further support for the importance of integrin-matrix interactions in promoting strain-dependent changes in cardiac myocyte gene transcription.
Quantitative Analysis of Intercellular Connections by Immunohistochemistry of the Cardiac Gap Junction Protein Connexin43

Polyclonal antisera directed against epltopes in the cytoplasmic domain of rat connexin43, the predominant cardiac gap junction protein, were used to delineate immunohistochemically the distribution of gap junctions in sections of canine left ventricle. Antigen-antibody binding and tissue structure were preserved after paraformaldehyde fixation and paraffin embedment of canine myocardium. Specific binding of antibody to the cytoplasmic surfaces of uitrastructurally identified gap junctions was confirmed with electron microscopy. Light microscopic morphometric analysis of immunostained sections in five separate experiments revealed a mean gap junction surface density of 0.0052 μm2/μm3 myocyte volume, which is consistent with previously reported values determined by use of quantitative electron microscopy. This new method permits quantitative determinations of gap junction surface density and distribution in relatively large heterogeneous areas of myocardium in which ultrastructural morphometry would be impractical. This approach should facilitate analysis of the relation between potential alterations in electrical coupling of myocytes and abnormalities of myocardial conduction occurring at the macroscopic scale in regions such as structurally heterogeneous infarct border zones. {Circulation Research 1989;65:1450-1457)
Laser proton accelerator with improved repeatability at Peking University

The repeatability of laser proton accelerator is mainly limited by laser plasma interaction, laser target coupling and laser parameter variation. In our recent experiments performed on the Compact Laser Plasma Accelerator at Peking University, gain of proton beams with improved repeatability is demonstrated. In order to control the laser plasma interaction in pre-plasma, cross polarized-wave generation technique is employed to provide a laser pulse with an ultrahigh contrast of 10−10 A semi-automatic laser and target alignment system with a sensitivity of few microns is employed. The repetition rate of the laser pro-ton accelerator is at the level of 0.1 Hz which is beneficial to decrease laser parameter variation. The shot-to-shot variation of proton energies is about 9% for a level of confidence of 0.95.
Antibacterial Substances Separated from Plants

Interest is arising in the possible use of higher plants as the source of naturally occurring antibiotic substances. The use of higher plants in the treatment of disease is as old as the art of healing itself. Isaiah of Biblical times suggested that a plaster of figs be placed on boils as a treatment of this form of infection. Hyssop and cedarwood were used in the cleansing of lepers. The Orientals (Hume, 1940) have used plants and herbs for centuries in the treatment of many diseases. Preliminary surveys (Osborn, 1943; Lucas and Lewis, 1944; Huddleson et al., 1944) of large numbers of plants suggest that many contain potential antibiotic materials. Further work by several investigators (Irving, Fontaine, and Doolittle, 1946; Cavallito, Bailey, and Kirchner, 1945; Heatley, 1944; Cavallito, Buck, and Suter, 1945; Seegal and Holden, 1945) on individual plants or parts of plants indicated that these substances can be purified and remain active in this form against microorganisms in vitro. Recently (Carlson, Bissell, and Mueller, 1946) it was demonstrated that partially purified extracts of plants are active in vivo against the malaria parasites and against gram-positive bacteria. During the spring and summer of 1946 it was possible to collect 550 plants in regions of Ohio and Oregon. From these plants, 2,115 extracts were prepared and tested. The object of the study here reported was to determine which plants of those collected from these regions contain active substances which would inhibit the growth of microorganisms in vitro.
Systematic protein–protein interaction mapping for clinically relevant human GPCRs

G‐protein‐coupled receptors (GPCRs) are the largest family of integral membrane receptors with key roles in regulating signaling pathways targeted by therapeutics, but are difficult to study using existing proteomics technologies due to their complex biochemical features. To obtain a global view of GPCR‐mediated signaling and to identify novel components of their pathways, we used a modified membrane yeast two‐hybrid (MYTH) approach and identified interacting partners for 48 selected full‐length human ligand‐unoccupied GPCRs in their native membrane environment. The resulting GPCR interactome connects 686 proteins by 987 unique interactions, including 299 membrane proteins involved in a diverse range of cellular functions. To demonstrate the biological relevance of the GPCR interactome, we validated novel interactions of the GPR37, serotonin 5‐HT4d, and adenosine ADORA2A receptors. Our data represent the first large‐scale interactome mapping for human GPCRs and provide a valuable resource for the analysis of signaling pathways involving this druggable family of integral membrane proteins.
RDF(S) and SPARQL Expressiveness in Engineering Design Patterns

In engineering product design, using RDF(s) semantic Web (SW) language, the number of instances to handle is usually large. We want to easily put additional information on property values and metadata over selected instances. Moreover, we want to use standard SPARQL in order to query the RDF graph. We have designed solutions to address a family of problems related to instance property values in engineering design patterns (order, metadata, etc.).
Using wavelet decomposition to support progressive and approximate range-sum queries over data cubes

Data cubes are designed to pro vide aggregate information that can be used to analyze the contents of databases and data w arehouses. A range query applies an aggregation operation (e.g., SUM, A VERAGE) over all selected cells in a data cube, where the selection is speci ed by providing ranges of values on di erent dimensions. Previous approaches to process the range sum query on data cubes (e.g., pre x sum) have low query costs but have high update costs. We use the discrete wavelet transformation to decompose a data cube into w avelet coe cients of di erent resolutions. The resulting decomposed data cube can be used for progressiv eand appro ximatequery processing. This new approach can handle clustered and sparse data gracefully and can provide e cient performance for both queries and updates, which makes the wavelet decomposition technique suitable for dynamic data cube environments.
An Architecture for Orchestrating Hadoop Applications in Hybrid Cloud

MapReduce is a programming model for processing and generating large data sets, and Hadoop, a MapReduce implementation, is a good tool to handle Big Data. Cloud computing with its ubiquitous characteristic, on demand and dynamic resource provisioning at low cost has potential to be the environment to treat big data. However, using Hadoop on the cloud spends time and requires technical knowledge from users. The hybrid cloud leverages these requirements, because it's necessary to evaluate the resources in private cloud and, if necessary, obtain and prepare on-demand resources in the public cloud. Moreover, the simultaneous management of private and public domains requires an appropriate model that combines performance with minimal cost. In this paper we propose an architecture to make the orchestration of Hadoop applications in hybrid clouds. The core of the model consists of a web portal for submissions, an orchestration engine and an execution services factory. Through these three components it's possible to automate the preparation of a cross-domain cluster, performing the provisioning of files involved, managing the execution of the application, and making the results available to the user.
Robust CSI-Based Soft Decision for COFDM Systems with Co-Channel Interference

In this paper, we propose a robust soft decision method based on channel state information (CSI) for coded orthogonal frequency division multiplexing (COFDM) systems. In the presence of co-channel interference (CCI), conventional soft decision decoding is performed by a simple erasing method for frequency selective CCI. But the conventional method cannot obtain sufficient performance gain because the CCI power varies and a considerable number of bits are affected by the CCI. For this reason, we consider a novel weighting method based on the specific CSI such as statistical location and instantaneous power of the CCI as well as typical frequency-selective fading channel. Simulation results verify that the proposed CSI estimation is sufficiently reliable for digital video broadcasting-terrestrial (DVB-T) system with analog TV signals as the CCI. In addition, the proposed soft decision method guarantees superior coded bit error rate (BER) performance compared to the conventional method.
Chitosan‐graphene oxide nanocomposites: Effect of graphene oxide nanosheets and glycerol plasticizer on thermal and mechanical properties

In this study, graphite oxide (GO) is synthesized from natural graphite flakes by the modified Hummers method. Characterization by Fourier Transform Infrared (FTIR), X-ray photoelectron (XPS), Raman and Ultraviolet-visible (UV–Vis) spectroscopies, X-ray diffraction (XRD), and thermogravimetric analysis (TGA) is conducted on GO to confirm the oxidation of graphite. Unplasticized and glycerol plasticized chitosan/graphene oxide nanosheets (CS/GO) nanocomposites with different GO loadings are prepared by solution casting. The combined effect of GO and glycerol on structure, thermal and mechanical properties of nanocomposite films is studied. GO nanosheets are well dispersed throughout the CS matrix due to the hydrogen bonding and electrostatic interactions between CS and GO nanosheets. The incorporation of GO within the CS matrix results in a decrease of the crystallinity, an improvement of thermal stability, and a significant enhancement of the stiffness and tensile strength that is emphasized by the glycerol. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017, 134, 45092.
An optimisation algorithm for minimising energy dissipation in NoC-based hard real-time embedded systems

This paper introduces an evolutionary multi-objective optimisation algorithm to facilitate fast and efficient task allocation of hard real-time embedded systems with Networks-On-Chip (NoC) as the interconnection at the early design stage, where evaluating as many as possible solutions is crucial. Our approach uses analytical fitness functions to provide fast evaluation of large number of solutions; a contrast to simulation-based optimisation technique, whereby it tends to be not only impractical when the design space is very large but also unfeasible as far as hard real-time systems are concerned. The proposed algorithm guarantees the predictability in timing behaviour of the systems whilst minimising energy dissipation whenever tasks are reallocated and their packets are rerouted, which differs from the state-of-the-art approaches. In addition, not only it can explore the allocation of tasks but also the encoding of the data packets. The evidence gathered from case studies shows that the proposed algorithm is able to find schedulable allocation of tasks, preserving it whilst further minimising energy dissipation.
Challenges in measuring the effects of pharmacological interventions on cognitive and adaptive functioning in individuals with Down syndrome: A systematic review

We systematically reviewed the measures used in pharmaceutical trials in children/adults with Down syndrome without dementia. Our purpose was to identify developmentally appropriate outcome measures capable of detecting changes in cognitive and adaptive functioning in this population. Eleven studies were included and used diverse outcome measures across the domains of language, memory, attention, behavior, and executive/adaptive functioning. Our results highlight the challenges in selecting measures capable of capturing improvements in pharmaceutical trials in individuals with DS. We offer suggestions to enhance future research, including: conducting studies with larger samples of participants with a range of developmental abilities; modifying existing/developing novel outcome measures; incorporating advances from related areas and DS observational studies; and considering alternative analytic techniques to characterize treatment effects.
Redundant roles of PRDM family members in zebrafish craniofacial development

Background: PRDM proteins are evolutionary conserved Zn‐Finger transcription factors that share a characteristic protein domain organization. Previous studies have shown that prdm1a is required for the specification and differentiation of neural crest cells in the zebrafish. Results: Here we examine other members of this family, specifically prdm3, 5, and 16, in the differentiation of the zebrafish craniofacial skeleton. prdm3 and prdm16 are strongly expressed in the pharyngeal arches, while prdm5 is expressed specifically in the area of the forming neurocranium. Knockdown of prdm3 and prdm16 results in a reduction in the neural crest markers dlx2a and barx1 and defects in both the viscerocranium and the neurocranium. The knockdown of prdm3 and prdm16 in combination is additive in the neurocranium, but not in the viscerocranium. Injection of sub‐optimal doses of prdm1a with prdm3 or prdm16 Morpholinos together leads to more severe phenotypes in the viscerocranium and neurocranium. prdm5 mutants have defects in the neurocranium and prdm1a and prdm5 double mutants also show more severe phenotypes. Conclusions: Overall, our data reveal that prdm3, 5, and 16 are involved in the zebrafish craniofacial development and that prdm1a may interact with prdm3, 5, and 16 in the formation of the craniofacial skeleton in zebrafish. Developmental Dynamics 242:67–79, 2013. © 2012 Wiley Periodicals, Inc.