Miracle-dz/UniFAR-FTUs huggingface dataset:
Hopcount in the NICE Application Layer Multicast Protocol

Application layer (AL) multicast protocols emerged, and in large number, as a response to the slow deployment of IP multicast. However, the gain of different AL multicast mechanisms, in terms of resources consumption over uni-cast, is questionable. In this paper, we investigate the efficiency of AL multicast protocol NICE, in terms of the number of hops a packet traverses on its path toward the destinations. We propose four alternative algorithms for the creation of NICE overlay and compare their efficiency to the efficiency of unicast, IP multicast, and another two previously evaluated AL multicast protocols (MCAN and Scribe). Further, we investigate the influence of the underlying topology awareness on the efficiency. Our analysis has been performed via simulations, as well as via measurements on the PlanetLab network. We show that the NICE structure achieves better results than MCAN and scribe
Mutations in the rpoB Gene of Multidrug-Resistant Mycobacterium tuberculosis Isolates from China

ABSTRACT Mutations in the 81-bp rifampin resistance determining region (RRDR) and mutation V176F locating at the beginning of the ropB gene were analyzed by DNA sequencing of 86 Mycobacterium tuberculosis clinical isolates (72 resistant and 14 sensitive) from different parts of China. Sixty-five mutations of 22 distinct kinds, 21 point mutations, and 1 insertion were found in 65 of 72 resistant isolates. The most common mutations were in codons 531 (41%), 526 (40%), and 516 (4%). Mutations were not found in seven (10%) of the resistant isolates. Six new alleles within the RRDR, along with five novel mutations outside the RRDR, are reported. None of isolates contained the V176 mutation.
Explaining Sentiment Spikes in Twitter

Tracking public opinion in social media provides important information to enterprises or governments during a decision making process. In addition, identifying and extracting the causes of sentiment spikes allows interested parties to redesign and adjust strategies with the aim to attract more positive sentiments. In this paper, we focus on the problem of tracking sentiment towards different entities, detecting sentiment spikes and on the problem of extracting and ranking the causes of a sentiment spike. Our approach combines LDA topic model with Relative Entropy. The former is used for extracting the topics discussed in the time window before the sentiment spike. The latter allows to rank the detected topics based on their contribution to the sentiment spike.
RAS signalling is abnormal in a c-raf1 MEK1 double mutant

A mutant rat cell clone that suppresses the transformation defects of RAS effector loop substitutions is heterozygous for mutations in c-raf1 and MEK1. The mutant cells can be transformed by many otherwise defective RAS effector mutants, including RAS genes with the effector regions of distantly related GTPases, even though the encoded RAS proteins do not interact with either the mutant or wild-type RAF in Saccharomyces cerevisiae. While the significance of the c-raf1 mutation is unclear, the MEK1 mutation increases MEK1 activity and leads to activation of mitogen-activated protein kinase. The mutant MEK1 is coupled to the epidermal growth factor pathway but exhibits decreased physical interaction with RAF. When overexpressed, the MEK1 mutation is transforming and causes hyperphosphorylation of RAF. Signalling from RAS to MEK1 may be mediated by something other than RAF alone, but signalling through MEK1 is probably sufficient for RAS transformation.
Endothelial Dysfunction as a Target for Prevention of Cardiovascular Disease

The endothelium, once considered a mere selectively permeable barrier between the bloodstream and the outer vascular wall, is now recognized to be a crucial homeostatic organ, fundamental for the regulation of the vascular tone and structure. Indeed, endothelial cells are able to synthesize and secrete a broad spectrum of anti-atherosclerotic substances, the most characterized of which is nitric oxide (NO), a gas that is generated from the metabolism of l-arginine by endothelial NO synthase (eNOS), constitutively expressed in endothelial cells (1). Under physiologic conditions, endothelial stimulation induces the production and release of NO, which diffuses to surrounding tissue and cells and exerts its cardiovascular protective role by relaxing media-smooth muscle cells, preventing leukocyte adhesion and migration into the arterial wall, muscle cell proliferation, platelet adhesion and aggregation, and adhesion molecule expression (1,2). In disease conditions, including the presence of cardiovascular risk factors, the endothelium undergoes functional and structural alterations, thus losing its protective role and becoming a proatherosclerotic structure (1). In the earliest stages, the principal endothelial alteration is merely functional and addressed as “endothelial dysfunction. ” The fundamental feature of this condition is the impaired NO bioavailability. This can be the consequence of either a reduced production by eNOS or, more frequently, of an increased breakdown by reactive oxygen species (ROS) (1,2). In the presence of impaired NO bioavailability, the endothelium implements various physiological pathways in the attempt to compensate for NO deficiency. For instance, endothelium-dependent vasodilation is warranted, although impaired, also in the presence of cardiovascular risk factors by the production and release of endothelium-derived vasodilators other than NO, such as prostanoids and other endothelium-derived hyperpolarizing factors. Along with NO deficiency, a dysfunctioning endothelium also becomes the source of other substances and mediators that are detrimental to the arterial wall, including endothelin-1, tromboxane A …
Pharmacokinetic Evaluation of Guar Gum-Based Colon-Targeted Drug Delivery Systems of Tinidazole in Healthy Human Volunteers

The aim of the present investigation was to determine the in vivo availability of guar gum-based colon-targeted tablets of tinidazole in comparison with immediate release tablets of tinidazole in human volunteers. Six healthy volunteers participated in the study, and a cross-over design was used. The plasma concentration of tinidazole was estimated by HPLC. The pharmacokinetic parameters were calculated from the plasma concentration of tinidazole versus time data. The immediate release tablets of tinidazole produced a peak plasma concentration (Cmax of 3239 ± 428 ng/ml) at 1.04 ± 0.32 hr (Tmax), whereas colon-targeted tablets produced peak plasma concentration (Cmax of 2158 ± 78 ng/ml) at 14.9 ± 1.6 hr. The delayed Tmax, decreased Cmax, and Ka, and unaltered bioavailability and elimination half-life of tinidazole from guar gum-based colon-targeted tinidazole tablets, in comparison with the immediate tablets, indicated that the drug was not released in the stomach and small intestine but delivered to the colon. Slow absorption of the drug from the less absorptive colon might result in the availability of the drug for local action in the colon. The guar gum-based colon-targeted tablets of tinidazole may be useful in providing an effective and safe therapy of intestinal amoebiasis.
Contributors to the Challenge Task

is the fourth in a series of LLL workshops. Previous workshops took place in Bled (LLL99), Lisbon (LLL00) and Strasbourg (LLL01). This year LLL takes place as part of the 22 nd International Conference on Machine Learning (ICML 2005) in Bonn, Germany. We would like to thank the ICML organisers, particularly Hendrik Blockeel, for their help in publicising and organising LLL05. The purpose of the workshop is to provide a focus for work which applies machine learning using logical representations to natural language. Much existing work in this area uses techniques from inductive logic programming (ILP), and increasingly statistical relational learning. There is currently much interest in applying logic-based machine learning to the problem of Information Extraction from biomedical texts, so the major innovation this year was to have an associated Genic Interaction Extraction Challenge (http://genome.jouy. inra.fr/texte/LLLchallenge/) organised by the Mathématique, Informatique et Génome (MIG) laboratory at the French National Institute for Agronomics Research (INRA). The challenge organisers made available data consisting of sentences describing interactions between genes and proteins, where proteins are the agents of interaction and genes are the targets. The goal of the challenge was to use this data to induce rules for extracting gene/protein interactions, and a test set was provided by the organisers to evaluate performance on this task. Significantly, the training data contained considerable linguistic annotation. Basic annotation consisted of word segmentation plus the identification of agents, targets and their interactions. Enriched annotation added lemmas (using a named-entity dictionary) and syntactic dependencies, both manually-checked. Extracting relational events (e.g. an interaction) from text requires this sort of linguistically structured data. We would like to thank all those at MIG-INRA and LIPN-Université Paris 13 who contributed to creating this data and running the challenge competition. This work would not have been possible without funding from the following four projects: the French Caderige project, the French ExtraPloDocs project, the FP6 Alvis project and the FP6 Pascal Network of Excellence. Six research groups, coming from Germany, the UK, the Netherlands, the Czech Republic and the USA, took up the LLL genic IE challenge and the results of their endeavours can be found in Part II of these proceedings. We would like to thank the scientific committee and additional reviewers for the challenge task who reviewed these papers to a very tight deadline. One of us (CN) has provided an overview of the IE challenge, and the reader is …
Judgment frequency effects in generative andpreventative causal learning

The frequency of judgment effect is a special case of Response Mode effect in human covariation and causal learning. Judgment adjustment -to ΔP-, depends on the trial type preceding that judgment, but that effect is restricted to situations in which participants are asked to make their judgments with a high frequency. Two experiments further demonstrated the reliability and the generality of this effect in positive and negative causal learning tasks. Experiment 1 yielded similar judgment frequency effects with a higher positive contingency (ΔP= 0.71) and a larger block size (n=16) than in previous studies. Experiment 2 showed that judgment frequency also modulates the detection of negative contingency (ΔP= -0.5), as far as judgment accuracy was shown to be a function of the type of trial just preceding that judgment in the high frequency group. Associative and statistical models of covariation learning cannot easily explain these results without incorporating relevant post-hoc assumptions. These findings add new-evidence to the growing body of data showing that human causal learning depends on the action of several mechanisms, as proposed by the Belief Revision Model.
InterAKTions with FKBPs - Mutational and Pharmacological Exploration

The FK506-binding protein 51 (FKBP51) is an Hsp90-associated co-chaperone which regulates steroid receptors and kinases. In pancreatic cancer cell lines, FKBP51 was shown to recruit the phosphatase PHLPP to facilitate dephosphorylation of the kinase Akt, which was associated with reduced chemoresistance. Here we show that in addition to FKBP51 several other members of the FKBP family bind directly to Akt. FKBP51 can also form complexes with other AGC kinases and mapping studies revealed that FKBP51 interacts with Akt via multiple domains independent of their activation or phosphorylation status. The FKBP51-Akt1 interaction was not affected by FK506 analogs or Akt active site inhibitors, but was abolished by the allosteric Akt inhibitor VIII. None of the FKBP51 inhibitors affected AktS473 phosphorylation or downstream targets of Akt. In summary, we show that FKBP51 binds to Akt directly as well as via Hsp90. The FKBP51-Akt interaction is sensitive to the conformation of Akt1, but does not depend on the FK506-binding pocket of FKBP51. Therefore, FKBP inhibitors are unlikely to inhibit the Akt-FKBP-PHLPP network.
Design of pin-constrained general-purpose digital microfluidic biochips

Digital microfluidic biochips are being increasingly used for biotechnology applications. The number of control pins used to drive electrodes is a major contributor to fabrication cost for disposable biochips in a highly cost-sensitive market. Most prior work on pin-constrained biochip design determines the mapping of a small number of control pins to a larger number of electrodes according to the specific schedule of fluid-handling operations and routing paths of droplets. Such designs are therefore specific to the bioassay application, hence sacrificing some of the flexibility associated with digital microfluidics. We propose a design method to generate an application-independent pin-assignment configuration with a minimum number of control pins. Layouts of a commercial biochip and laboratory prototypes are used as case studies to evaluate the proposed design method for determining a suitable pin-assignment configuration. Compared with previous pin-assignment algorithms, the proposed method can reduce the number of control pins and facilitate the “general-purpose” use of digital microfluidic biochips for a wide range of applications.
An Inference and Integration Approach for the Consolidation of Ranked Lists

In this article, we describe a new approach that combines the estimation of the lengths of highly conforming sublists with their stochastic aggregation, to deal with two or more rankings of the same set of objects. The goal is to obtain a much smaller set of informative common objects in a new rank order. The input lists can be of large or huge size, their rankings irregular and incomplete due to random and missing assignments. A moderate deviation-based inference procedure and a cross-entropy Monte Carlo technique are used to handle the combinatorial complexity of the task. Two alternative distance measures are considered that can accommodate truncated list information. Finally, the outlined approach is applied to simulated data that was motivated by microarray meta-analysis, an important field of application.
A concept for MIMO antennas on small terminals based on characteristic modes

In this paper, we present a concept for a MIMO antenna system on a small terminal platform. The concept is based on the selective excitation of different orthogonal characteristic modes on the chassis of the small terminal. Thereby the chassis of the mobile terminal itself can be effectively used as the MIMO antenna similar to the concept commonly applied to single port (single mode) antennas on mobile terminals. The different modes generate orthogonal radiation patters and are therefore suited to radiate de-correlated signals fed to the different antenna ports. Such modes can be excited selectively by certain sets of couplers distributed around the outer edges of the chassis. First stage numerical investigations show that coupling between the modes is low.
Using a CNN ensemble for detecting pornographic and upskirt images

The recent popularity of smartphones causes significant increase of upskirt filming cases in many countries and regions. To search upskirt images in suspects' IT devices and block them on social media, an effective detector is demanded, but it is neglected by both academic and commercial communities. Three commercial pornographic image detectors and one detector distributed by the U.S. National Institute of Justice are first examined on upskirt images. They classify 24.56%-41.90% of the testing upskirt images as pornographic images and the rest as normal images. These results imply that the detectors cannot be used to search upskirt images. To effectively use unbalanced training data, a convolution neural network (CNN) ensemble is proposed for classifying pornographic, upskirt and normal images. Training images for this classification problem are always unbalanced, because pornographic and normal images are numerous on the Internet, but upskirt images are significantly fewer. In this study, the ensemble is formed by multiple CNNs, which are trained on balanced datasets with different pornographic and normal images, but the same upskirt images. The probabilities from the CNNs are fused as the ensemble outputs. To train and test the CNN ensemble, 10,997 pornographic images, 1,673 upskirt images and 38,832 normal images are collected from the Internet. Experimental results show that the ensemble with six CNNs outperforms a single CNN by 2.93% and achieves detection accuracy of 90.23%. Comparing with the four pornographic image detectors, the ensemble also performs better in classifying pornographic images from normal images, with a significant margin of over 10%.
Fuzzy event tree analysis for quantified risk assessment due to oil and gas leakage in offshore installations

Accidental oil and gas leak is a critical concern for the offshore industry because it can lead to severe consequences and as a result, it is imperative to evaluate the probabilities of occurrence of the consequences of the leakage in order to assess the risk. Event Tree Analysis (ETA) is a technique to identify the consequences that can result from the occurrence of a hazardous event. The probability of occurrence of the consequences is evaluated by the ETA, based on the failure probabilities of the sequential events. Conventional ETA deals with events with crisp failure probabilities. In offshore applications, it is often difficult to arrive at a single probability measure due to lack of data or imprecision in data. In such a scenario, fuzzy set theory can be applied to handle imprecision and data uncertainty. This paper presents fuzzy ETA (FETA) methodology to compute the probability of the outcomes initiated due to oil/gas leak in an actual offshore-onshore installation. Post FETA, sensitivity analysis by Fuzzy Weighted Index (FWI) method is performed to find the event that has the maximum contribution to the severe sequences. It is found that events of „ignition‟, spreading of fire to „equipment‟ and „other areas‟ are the highest contributors to the severe consequences, followed by failure of „leak detection‟ and „fire detection‟ and „fire water not being effective‟. It is also found that the frequency of severe consequences that are catastrophic in nature obtained by ETA is one order less than that obtained by FETA, thereby implying that in ETA, the uncertainty does not propagate through the event tree. The ranking of severe sequences based on their probability, however, are identical in both ETA and FETA.
Writing Styles of a Korean Sample by Age: An Exploratory Study

This descriptive study concerned whether language use differs across age groups of Korean participants. Language use by Koreans in their 20s, 40s, and 60s were compared using the Korean Linguistic Inquiry and Word Count. Analysis showed that Koreans in their 60s used as many phrases and morphemes per sentence as younger people, which reflects similar complexity of language. In addition, those in their 40s showed the strongest use of words related to emotion, cognition, work, and leisure. These results show interesting differences from studies conducted with Western subjects.
A low power IC to enable optical communications in a robotic swarm

In this paper a low power transceiver for short-range IR-communications between robots is described. The mm3- sized robots will be deployed in an arena of A4 sheet size with controlled illumination conditions. The transceiver can manage variations of background light from point to point in the arena, interferences induced by other robots and deals with the inter-robot distance, i.e., the amplitude of the signal to be detected.
Implementation of a High-Efficiency, High-Lifetime, and Low-Cost Converter for an Autonomous Photovoltaic Water Pumping System

This paper proposes a new converter for photovoltaic (PV) water pumping or treatment systems without the use of chemical storage elements, such as batteries. The converter is designed to drive a three-phase induction motor directly from PV energy. The use of a three-phase induction motor presents a better solution to the commercial dc motor water pumping system. The development is oriented to achieve a more efficient, reliable, maintenance-free, and cheaper solution than the standard ones that use dc motors or low-voltage synchronous motors. The developed system is based on a current-fed multiresonant converter also known as resonant two-inductor boost converter (TIBC) and a full-bridge three-phase voltage source inverter (VSI). The classic topology of the TIBC has features like high voltage gain and low input current ripple. In this paper, it is further improved with the use of a nonisolated recovery snubber along with a hysteresis controller and the use of a constant duty cycle control to improve its efficiency. Experimental results show a peak efficiency of 91% at a rated power of 210 W for the dc/dc converter plus the three-phase VSI and a peak efficiency of 93.64% just for the dc/dc converter. The system is expected to have a high lifetime due to the inexistence of electrolytic capacitors, and the total cost of the converter is below 0.43 U$/Wp. As a result, the system is a promising solution to be used in isolated locations and to deliver water to poor communities.
OS Support for Virtualizing Hardware Transactional Memory

Transactional memory promises to simplify multithreaded programming. Hardware TM (HTM) implementations promise better performance by augmenting processors with transactional state. However, HTMs interact poorly with the operating system or virtual machine monitor. For example, they often do not tolerate OS actions that virtualize processors and memory, such as context switching and paging. Without support for these actions, an HTM may not execute programs correctly or guarantee forward progress. We investigate virtualizing transactional memory in the context of LogTM-SE. First, we describe an implementation of a kernel module in OpenSolaris that implements transactional virtualization and requires only 1120 lines of code. Second, we find that LogTMSE interacts poorly with virtual machine monitors due to a reliance on physical addresses. We propose an extension to LogTM-SE, called LogTM-VSE, that addresses these problems and improves context-switching performance. Third, through application tracing on real hardware and full system simulation, we show virtualizing transactions can be necessary for system stability and to support code that voluntarily context switches. However, we find that aborting a transaction is generally faster than virtualizing it, and hence preferable in some cases.
The impact of starch-powdered gloves on the formation of adhesions in rats.

OBJECTIVE To assess the influence of starch powdered surgical gloves on the postoperative formation of adhesions in a standard rat model. DESIGN Prospective, randomised, double-blind study. MATERIAL 197 rats. INTERVENTIONS Abdominal cavity was exposed to gloves during the induction of adhesions and for an additional two minutes. Animals were operated on with the operator wearing either starch-powdered or powder-free gloves. MAIN OUTCOME MEASURES Formation of adhesions and starch particles present in the adhesions after one, three, 12, or 24 weeks. RESULTS When powdered gloves were worn the percentage of adhesions formed was significantly greater (n = 197, p < 0.01) than when powder-free gloves were worn. Starch particles were found in biopsy specimens from rats operated on with powdered gloves, but not when powder-free gloves were used. CONCLUSION Even the small amount of starch that settles in the abdominal cavity during an operation increases the amount of adhesions formed.