Miracle-dz/UniFAR-FTUs huggingface dataset:
Fracture and fatigue in graphene nanocomposites.

Graphene, a single-atom-thick sheet of sp-bonded carbon atoms, has generatedmuch interest due to its high specific area and novel mechanical, electrical, and thermal properties. Recent advances in the production of bulk quantities of exfoliated graphene sheets from graphite have enabled the fabrication of graphene–polymer composites. Such composites show tremendous potential for mechanical-property enhancement due to their combination of high specific surface area, strong nanofiller–matrix adhesion and the outstanding mechanical properties of the sp carbon bonding network in graphene. Graphene fillers have been successfully dispersed in poly(styrene), poly(acrylonitrile) and poly(methyl methacrylate) matrices and the responses of their Young’s modulus, ultimate tensile strength, andglass-transition temperaturehave been characterized. However, to the best of our knowledge there is no report on the fracture toughness and fatigue properties of graphene–polymer composites. Fracture toughness describes the ability of a material containing a crack to resist fracture and it is a critically important material property for design applications. Fatigue involves dynamic propagation of cracks under cyclic loading and it is one of the primary causes of catastrophic failure in structural materials. Consequently, the material’s resistance to fracture and fatigue crack propagation are of paramount importance to prevent failure. Herein we report the fracture toughness, fracture energy, and fatigue properties of an epoxy polymer reinforced with various weight fractions of functionalized graphene sheets. Remarkably, only 0.125% weight of functionalized graphene sheets was observed to increase the fracture toughness of the pristine (unfilled) epoxy by 65% and the fracture energy by 115%. Toachievecomparableenhancement,carbonnanotube (CNT) and nanoparticle epoxy composites require one to two orders of magnitude larger weight fraction of nanofillers. Under fatigue conditions, incorporation of 0.125% weight of functionalized graphene sheets drastically reduced the rate of crack propagation in the epoxy 25-fold. Fractography analysis
Whole-exome sequencing identifies a polymorphism in the BMP5 gene associated with SSRI treatment response in major depression

Although antidepressants are widely used in the pharmacotherapy of major depressive disorder (MDD), their efficacy is still insufficient as approximately one-third of the patients do not fully recover even after several treatment trials. Inter-individual genetic differences are thought to contribute to the variability in antidepressant response; however, current findings from pharmacogenetic studies are uncertain or not clearly replicated. Here we report the first application of full exome sequencing for the analysis of pharmacogenomics on antidepressant treatment. After 12 weeks of treatment with the selective serotonin re-uptake inhibitor escitalopram, we selected five clear responders and five clear non-responders for exome sequencing. By comparing the allele counts of previously known single nucleotide polymorphisms and novel polymorphisms we selected 38 markers for further genotyping in two independent patient samples treated with escitalopram (n=116 and n=394). The A allele, carried by approximately 30% of the patients with MDD, of rs41271330 in the bone morphogenetic protein (BMP5) gene showed strong association with worse treatment response in both sample sets (p=0.001), indicating that this is an promising pharmacogenetic marker for prediction of antidepressant therapeutic outcome.
Utilization of Fuzzy Theory in the Modeling of Users of Adaptive Hypermedia Systems

Most of the software systems are not developed taking into account the heterogeneous needs of users. It is known that each user has different levels of knowledge, goals, abilities, and preferences. This fact emphasizes the need of developing systems which can adapt themselves to different types of user, or stereotypes. Since the description of the knowledge and features of the user involves uncertainness and imprecise sense, the fuzzy theory can be applied in order to deal with this vagueness. This paper proposes a user model for adaptive hypermedia systems using a structure, based on fuzzy theory. This model is able to properly reflect some of the user characteristics in the model, and adapt its own navigation and the content of hypermedia nodes for the user needs.
Bacterial Cellulose as a Supersoft Neural Interfacing Substrate.

Biocompatible neural interfaces hold great promise for treating neurological disorders and enhancing the mental and physical ability of human beings. Most of the currently available neural interfaces are made from rigid, dense inorganic materials that cause tissue damage. We present supersoft multichannel electrodes by depositing gold layers on thin bacterial cellulose (BC) (Au-BC electrodes). The Young's modulus of BC ( EBC = 120 kPa) is between those of the brain tissue ( Ebrain = 2.7-3.1 kPa) and the peripheral neural tissues ( Eperipheral nerve = 580-840 kPa). The bending stiffness of the Au-BC electrodes corresponds to 1/5200 of Au-polyimide electrodes with the same layout. Furthermore, the Au-BC electrodes are highly durable (conductivity >95% after 100 cycles of 180° bending). In vivo recording of brain electric activity demonstrates the great potential of the Au-BC electrodes for neural interfacing applications.
Small upconverting fluorescent nanoparticles for biomedical applications.

Fluorescent labels have been widely used for biological applications, primarily in imaging and assays. Traditional fluorophores such as fluorescent dyes are mainly based on downconversion fluorescence, which have several drawbacks such as photobleaching, high background noise from autofluorescence, and considerable photodamage to biological materials. Upconverting fluorescent nanoparticles emit detectable photons of higher energy in the near-infrared (NIR) or visible range upon irradiation with an NIR light in a process termed 'upconversion. ' They overcome some of the disadvantages faced by conventional downconversion labels, thus making them an ideal fluorescent label for biological applications. This review looks at the development of these particles, critically examines the reported applications, and discusses their future in biomedicine.
Pharmacokinetic and pharmacodynamic characterisation of JNJ-40411813, a positive allosteric modulator of mGluR2, in two randomised, double-blind phase-I studies

Metabotropic glutamate receptor-2 positive allosteric modulator, JNJ-40411813 (ADX71149), was characterised for clinical effects in healthy volunteers in two phase-1 studies. In study 1, healthy men received 50-, 100-, 150- or 225 mg and women received 100 mg JNJ-40411813 (n=6, each cohort) or placebo (n=2, each cohort) twice daily for seven days; smoking men (n=30) received placebo twice daily on days 1−7, 100 mg JNJ-40411813 (n=20) or placebo (n=10) on days 8−14. In study 2, healthy men received intravenous 0.005 mg/kg S(+) ketamine over 60 min at 3 (n=24; cohort 1), 12 h (n=8; cohort 3), and 24 h (n=8; cohort 2) after a single oral dose of 500 mg JNJ-40411813 or placebo. The pharmacokinetics and effects of JNJ-40411813 on cognition and subjective awareness were evaluated. Plasma JNJ-40411813 exposure was dose-dependent, tmax ranged from 3−4 h and t1/2 19.4−34.2 h across the dose levels. JNJ-40411813 significantly (p=0.02) reduced continuity of attention score (150 mg dose) and ameliorated smoking withdrawal-induced changes in power of attention and quality of episodic memory versus placebo. A modest reduction in alertness was observed at 150–225 mg doses, JNJ-40411813 (500 mg) reduced S(+) ketamine-induced negative symptoms by approximately 43% and 30% in cohorts 1 and 3, respectively. JNJ-40411813 was generally well-tolerated.
Tianeptine in an experimental medicine model of antidepressant action

Changes in emotional processing have been shown following acute administration of a range of monoaminergic antidepressants, and may represent an important common neuropsychological mechanism underpinning their therapeutic effects. Tianeptine is an agent that challenges the traditional monoaminergic hypothesis of antidepressant action, though its exact mode of action remains controversial. Healthy volunteers were randomised to receive a single dose of tianeptine (12.5 mg) or placebo, and subsequently completed a battery of tasks measuring emotional processing, including facial expression recognition, emotional memory and attentional vigilance, as well as working and verbal memory. Tianeptine-treated subjects were less accurate at identifying facial expressions, though this was not valence specific. The tianeptine group also showed reduced positive affective memory and reduced attentional vigilance to positive stimuli. There were no effects on emotional categorization or non-emotional cognition. The negative biases in aspects of emotional processing observed following acute tianeptine administration are at variance with the positive biases generally seen after acute administration of conventional antidepressant drugs, despite tianeptine’s putative antidepressant efficacy. This is an intriguing finding in the context of the lack of consensus regarding tianeptine’s mechanism of action; however, it may be consistent with the reported ability of acute tianeptine to increase the re-uptake of serotonin.
A Parallel Memory System Model for Multi-core Processor

Modern multi-core processors are predominant in improving performance of parallel applications. This paper discusses a triple-based multi-core architecture which provides native support for object-oriented methodology and applications in hardware level. The model explicitly represents objects and supports messaging-based communication, which maps well to the standard style of interaction in object oriented languages. However, the Memory Wall is still the bottleneck which should be resolved to decrease the disparity between how fast a CPU can operate on data and how fast it can get data. A hierarchy shared memory system (HSM) working with the partially-inclusive cache mapping policy is proposed. And a new object management model is presented, which use object table and recycle stack scheme to supports explicit dynamic object management. Our cache design presents an innovative solution to handling the costs of cache coherence by allowing applications to control the amount of sharing between cores. Experimental analysis based on comparisons between our objects management and other common link structured object organization methods shows that our method is predominant in spatial and temporal aspects on memory parallel access efficiency and costs less storage space to organize objects.
Recognizing human interaction by multiple features

In this paper, we address the problem of recognizing human interaction of two persons from videos. We fuse global and local features to build a more expressive and discriminative action representation. The representation based on multiple features is robust to motion ambiguity and partial occlusion in interactions. Moreover, action context information is utilized to capture the interdependencies between interaction class and individual action classes of two persons. We introduce a hierarchical random field model which integrates large-scale global feature, local spatial-temporal feature and action context information into a unified framework. Results on UT-Interaction dataset show that our method is quite effective in recognizing human interaction.
Immunodetection and subcellular distribution of imidazoline receptor proteins with three antibodies in mouse and human brains: Effects of treatments with I1- and I2-imidazoline drugs

Various imidazoline receptor (IR) proteins have been proposed to mediate the effects of selective I1- and I2-IR drugs. However, the association of these IR-binding proteins with classic I1- and I2-radioligand binding sites remains somewhat controversial. In this study, three IR antibodies (anti-NISCH and anti-nischarin for I1-IRs; and anti-IRBP for I1/I2-IRs) were used to immunodetect, characterize and compare IR protein patterns in brain (mouse and human; total homogenate, subcellular fractionation, grey and white matter) and some cell systems (neurones, astrocytes, human platelets). Various immunoreactive IRs (specific molecular weight bands coincidently detected with the different antibodies) were related to I1-IR (167 kDa, 105/115 kDa and 85 kDa proteins) or I2-IR (66 kDa, 45 kDa and 30 kDa proteins) types. The biochemical characterization of cortical 167 kDa protein, localized in the membrane/cytosol but not in the nucleus, indicated that this I1-IR also forms part of higher order nischarin-related complexes. The contents of I1-IR (167 kDa, 105/115 kDa, and 85 kDa) proteins in mouse brain cortex were upregulated by treatment with I1-drugs (moxonidine, efaroxan) but not with I2-drugs (BU-224, LSL 61122). Conversely, the contents of I2-IR (66 kDa, 45 kDa and 30 kDa) proteins in mouse brain cortex were modulated by treatment with I2-drugs (decreases after BU-224 and LSL 61122, and increases after idazoxan) but not with I1-drugs (with the exception of moxonidine). These findings further indicate that brain immunoreactive IR proteins exist in multiple forms that can be grouped in the already known I1- and I2-IR types, which are expressed both in neurones and astrocytes.
The role of circadian rhythm on the pharmacokinetic of methotrexate in streptozotocin-induced diabetes mellitus rats

Abstract Chronopharmacokinetic studies have been conducted both in animals and humans. Anticancer agents are of great interest due to their narrow therapeutic range and large pharmacokinetic variability. It was reported that the pharmacokinetics of MTX showed a circadian rhythm in rats and humans. Since diabetes-induced physiological changes can affect pharmacokinetics of drugs, it was reported that MTX blood concentration in diabetic rats was higher than that of the control groups. The present study was designed to elucidate whether these diabetes-induced changes in pharmacokinetics occurred during the day and thus administered MTX at four different times in streptozotocin-induced diabetes mellitus (SIDM) rats. Blood samples were drawn at 5, 15, 30, and 60 min after IV infusion of MTX in both the SIDM and control groups. Control and SIDM Area under the concentration – time curve (AUC) values showed a significant circadian rhythm with a peak located in mid-dark phase at 14:00. Clearance values were significantly low at 14:00 in the diabetic group when compared to other periods and the control group. The MTX AUC was increased when treatment with dexamethasone was given to suppress the endogenous production of corticosterone in both control and SIDM rats. These results suggest that the extent of MTX pharmacokinetics varies with the time of day in the SIDM rats and these variations might be related to changes in corticosterone concentrations.
NASA: A Novel System Architecture for Ad Hoc Networks

A novel architecture used in the Ad Hoc networks is designed for building a well communication network quickly and reliably without any support of base installation. The system including hardware and software, called NASA, is also designed for high data rate transmission. The system architecture of NASA takes collaborative design of hardware and software. Therefore, it is completely open and doesn’t base on any operating system. NASA is designed for distributed networks and every NASA node could communicate with each other coequally. The paper discusses how to build the hardware platform of NASA, the cross layer implementation of the MAC and routing protocol. It has been proved that the proposed system is quite efficient and has low data transmission delay. In our experiments, the highest data transfer rate of NASA can be up to 1Mbps with 120 meters.
OCR from Video Stream of Book Flipping

Optical Character Recognition (OCR) in video stream of flipping pages is a challenging task because flipping at random speed cause difficulties to identify frames that contain the open page image (OPI) for better readability. Also, low resolution, blurring effect shadows add significant noise in selection of proper frames for OCR. In this work, we focus on the problem of identifying the set of optimal representative frames for the OPI from a video stream of flipping pages and then perform OCR without using any explicit hardware. To the best of our knowledge this is the first work in this area. We present an algorithm that exploits cues from edge information of flipping pages. These cues, extracted from the region of interest (ROI) of the frame, determine the flipping or open state of a page. Then a SVM classifier is trained with the edge cue information for this determination. For each OPI we obtain a set of frames. Next we choose the central frame from that set of frames as the representative frame of the corresponding OPI and perform OCR. Experiments are performed on video documents recorded using a standard resolution camera to validate the frame selection algorithm and we have obtained 88% accuracy. Also, we have obtained character recognition accuracy of 82% and word recognition accuracy of 77% from such book flipping OCR.
Determining Relation Semantics by Mapping Relation Phrases to Knowledge Base

Open Information Extraction (Open IE) recognizes domain-independent relational triples from natural language texts but does not recognize the exact semantics of the triples. Nevertheless, relations in existing knowledge bases, like manually edited attributes in Wikipedia Info boxes, have provided the semantic meaning of open relations. Therefore, our goal is to bridge the gap between open relation phrases extracted by an Open IE system and a pre-defined attributes in knowledge base. This task is important for Information Extraction. In this paper, we proposed a novel approach to map relation phrases to attributes in knowledge base. We matched relational triples extracted from Wikipedia articles with attribute triples generated from Wikipedia Info boxes. Finally, our system expanded 509 Wikipedia attributes with a total of 2,527 phrases. Experiments show that the proposed approach can achieve an average precision of 0.88±0.02 over all mapped relation pairs.
A Regional Popularity-Aware Cache replacement algorithm to improve the performance and lifetime of SSD-based disk cache

Flash-based Solid State Drive (SSD) has limitations in terms of cost and lifetime. It is used as a second-level cache between main memory and traditional HDD-based storage widely. Adopting traditional cache algorithms, which are designed primarily depending on temporal locality and popular blocks, to SSD-based second-level disk cache can cause unnecessary cache replacements, which not only degrade the cache performance but also shorten the lifetime of SSD. To overcome this problem, this paper proposes a performance-effective Regional Popularity-Aware Cache replacement algorithm (RPAC). Instead of a single block, the popularity of a region which is constituted by many adjacent disk blocks is recorded and used to determine replacing a block or not. In this way, the spatial locality of disk access is completely leveraged and sequential I/O blocks are gathered in SSD cache. Furthermore, it reduces the number of unnecessary cache replacement and erasure operation on SSD, prolonging its lifetime. We have implemented RPAC in real system and evaluated it by many workloads. Compared to traditional cache algorithms, it improve I/O throughput by up to 53% and reduce cache replacements of SSD up to 98.5%.
ITS4: a static vulnerability scanner for C and C++ code

We describe ITS4, a tool for statically scanning security-critical C source code for vulnerabilities. Compared to other approaches, our scanning technique stakes out a new middle ground between accuracy and efficiency. This method is efficient enough to offer real-time feedback to developers during coding while producing few false negatives. Unlike other techniques, our method is also simple enough to scan C++ code despite the complexities inherent in the language. Using ITS4 we found new remotely-exploitable vulnerabilities in a widely distributed software package as well as in a major piece of e-commerce software. The ITS4 source distribution is available at http://www.rstcorp. com/its4.
Expression of toll-like receptor-2 and -4 in amniochorion membranes of preterm delivery in the presence of histologic chorioamnionitis

Expression of Toll-like receptors at the maternal-fetal interface during normal and complicated pregnancies has aroused interest in the last few years. However, despite the importance of TLR-2 and TLR-4, which recognizes most microorganisms presenting in the amniotic cavity infections associated with prematurity, comparison of the expressions of these receptors is rare in the literature. Thus, the purpose of this study was to compare the gene expression between TLR-2 and TLR-4 in amniochorion membranes of pregnant women with preterm delivery in the presence of histologic chorioamnionitis (HCA). Amniochorion membranes were collected from 40 pregnant women with preterm delivery; 20 presented HCA and 20 did not. Fragments of the membranes were submitted to total RNA extraction, followed by cDNA production by reverse transcription. Real time quantitative PCR was used to quantify the gene expression of the TLRs. mRNA concentrations between TLR-2 and TLR-4 were compared using the nonparametric Mann-Whitney test. TLR-2 expression was higher than TLR-4 expression in the presence of HCA. No difference was observed between TLR-2 and TLR-4 expression in membranes in the absence of inflammatory infiltrate. In conclusion, amniochorion membranes express TLR-2 and TLR-4 and higher TLR-2 expression in the presence of histologic chorioamnionitis suggests that microorganisms recognizable by TLR-2 play an important role in the physiopathology of preterm labor.
Chasing the Weakest Failure Detector for k-Set Agreement in Message-Passing Systems

This paper continues our quest for the weakest failure detector which allows the k-set agreement problem to be solved in asynchronous message-passing systems prone to process failures. It has two main contributions which will be instrumental to complete this quest. The first contribution is a new failure detector (denoted PiSigma(x, y)) that has several noteworthy properties. (a) It is stronger than Sigma(k) which has been shown to be necessary. (b) It is equivalent to the pair (Sigma, Omega) when x=y=1 (optimal to solve consensus). (c) It is equivalent to the pair (Sigma(n-1), Omega(n-1)) when x=y=n-1 (optimal for (n-1)-set agreement). (d) It is strictly weaker than the pair (Sigma(x), anti-Omega(y)) (which has been investigated in previous works). (e) It is operational: the paper presents a PiSigma(x, y)-based algorithm that solves k-set agreement for k greater or equal to xy (intuitively, x refers to the maximum number of isolated groups of processes and y to the number of leaders in each of these groups). The second contribution of the paper is a proof that, for k strictly between 1 and n-1, the eventual leaders failure detector Omega(k) (which eventually provides each process with the same set of k process identities, this set including at least one correct process) is not necessary to solve k-set agreement problem.