Miracle-dz/UniFAR-FTUs huggingface dataset:
Content retrieval model for information-center MANETs: 2-dimensional case

Information-Centric Networking (ICN) is a cleanslate networking architecture that puts information in focus instead of addressed hosts. Construction of content retrieval model to estimate the delivery performance is challenging in this ICN-based Mobile Ad hoc Networks (MANETs). In this paper, we propose a novel content retrieval model (PRCRM) for Information-Centric MANETs (ICMs) in 2-dimensional case. By investigating the distribution of content popularity, receiverdriven mechanism, content caching and replacement mechanism and generalized mobility model in 2-dimensional space, PRCRM constructs a novel content retrieval model based on the content hit/miss probability to estimate the content retrieval-related performance. We evaluate PRCRM by comparing its performance with another state of the art solution in terms of RTT and throughput. Simulation results demonstrate PRCRM's rationality and validity and it is shown that PRCRM is available to analyze content retrieval in ICMs.
Allergic disease in infants up to 2 years of age in relation to plasma omega‐3 fatty acids and maternal fish oil supplementation in pregnancy and lactation

To cite this article: Furuhjelm C, Warstedt K, Fagerås M, Fälth‐Magnusson K, Larsson J, Fredriksson M, Duchén K. Allergic disease in infants up to 2 years of age in relation to plasma omega‐3 fatty acids and maternal fish oil supplementation in pregnancy and lactation. Pediatr Allergy Immunol 2011; 22: 505–514.
1 ICT , Training and Effective Selling Skills in Marketing Education in Nigeria

The 21st century marketing environment is characterized by e-encounter. This phenomenon has tremendous implication for selling, which is now competitive than ever. It is important that sales personnel should acquire relevant skills like the use of computer-based multi-media and interface network connections and this requires training and retraining in order to excel in all e-permeated market environment. With the internet, people can access information, buy and sell in any part of the world by means of e-commerce. Without specific relevant skills acquired vigorously through training, sales personnel will be left behind the voyage of competition. This paper focused on training, and effective selling skills acquired through ICT which are important element in Marketing Education in Nigeria. It looked at the basic concepts and highlighted specific selling skills that sales personnel should acquire. As an empirical study, it had used the statistical tool of pearson product moment correlation analysis to ascertain the relationship between ICT training and retraining package in offering sellers the necessary selling skills for marketing. The following two hypotheses were formulated that: (1) There is no significant relationship between ICT training and retraining package in offering sellers the necessary selling skills in marketing. (2) There is no significant relationship between the use of ICT and marketing education in Nigeria. The hypotheses were tested at 0.05 level of significance. The findings were as follows: (i) Skills acquired through ICT for selling were valuable which motivated sellers to be more proactive and professional (ii) The use of ICT helped sales personnel to accept marketing education in the area of training and retraining (iii) Minority respondents, that is, twenty percent of sales personnel had initial problems of understanding the use of ICT therefore they did not see any relationship between ICT skills and sales. The study made some conclusion, and recommended that sales personnel should be exposed more to interface networking.
Magneto-Optical Investigation of the Critical State in Coated Conductors: Peculiarities of the Magnetic Field Distribution and the Determination of the Critical Current Density

In this paper, we present a detailed analysis of the results of the magneto-optical measurements of the field's topography in the coated conductor (CC) tapes at various temperatures in order to study the distribution of the field and develop a simple method for determining the critical current density. It is shown that the fitting of calculated field profiles to the results of the magneto-optical measurements gives a satisfactory agreement between the model and the experiment. In addition, we proposed a method for the determination of the critical current density from measurements of the topography of the transverse field that is insensitive to the precise form of the current lines. Furthermore, it is shown that the experimentally observed asymmetry of the field profile is probably due to a slight misalignment between the MOI film and the CC tape, which is possibly due to the presence of a small transverse curvature of actual CC tapes.
Synaptic Functions of Invertebrate Varicosities: What Molecular Mechanisms Lie Beneath

In mammalian brain, the cellular and molecular events occurring in both synapse formation and plasticity are difficult to study due to the large number of factors involved in these processes and because the contribution of each component is not well defined. Invertebrates, such as Drosophila, Aplysia, Helix, Lymnaea, and Helisoma, have proven to be useful models for studying synaptic assembly and elementary forms of learning. Simple nervous system, cellular accessibility, and genetic simplicity are some examples of the invertebrate advantages that allowed to improve our knowledge about evolutionary neuronal conserved mechanisms. In this paper, we present an overview of progresses that elucidates cellular and molecular mechanisms underlying synaptogenesis and synapse plasticity in invertebrate varicosities and their validation in vertebrates. In particular, the role of invertebrate synapsin in the formation of presynaptic terminals and the cell-to-cell interactions that induce specific structural and functional changes in their respective targets will be analyzed.
A Preliminary Study on the Preparation of Monoclonal Antibody with Umbilical Cord Blood Cell

Objective: We conducted a preliminary study on the feasibility of preparing monoclonal antibody by umbilical cord blood cells systems. Methods: Collected umbilical cord blood cells and stimulated by Rubella virus, then incubated them and collected cell supernatant. By using Caprylic acid- saturated Ammonium sulfate method, monoclonal antibody was purified, and IgG subtype identification was conducted by their subtype classification kit of sigma. In traditional way, the preparation of monoclonal antibody cannot do without BABL/C mice and SP2/0 hybridoma cells. Consider this kinds of monoclonal antibody as a positive control, the reactivity and specificity of monoclonal antibodies were identified by Dot-ELISA. Results: By ELISA, we obtained four strains of positive umbilical cord blood cells. After subculture, cryopreservation and resuscitation in vitro, three of them were confirmed to secrete monoclonal antibody against rubella virus stably. The result of monoclonal antibody subtype classification showed that, both IgG1 and IgG2 types were detected. However, the quantity of monoclonal antibody prepared by umbilical cord blood cells was less than that from traditional method. Conclusions: The method of prepare monoclonal antibody using umbilical cord blood cells is feasible.
A comparison of Foursquare and Instagram to the study of city dynamics and urban social behavior

Social media systems allow a user connected to the Internet to provide useful data about the context in which they are at any given moment, such as Instagram and Foursquare, which are called participatory sensing systems. Location sharing services are examples of participatory sensing systems. The sensed data is a check-in of a particular place that indicates, for instance, a restaurant in a specific location, and also a signal from a user expressing his/her preference. From a participatory sensing system we can derive a participatory sensor network. In this work we compare two different participatory sensor networks, one derived from Instagram, and another one derived from Foursquare. In Instagram, the sensed data is a picture of a specific place. On the other hand, in Foursquare the sensed data is the actual location associated with a specific category of place (e.g., restaurant). Using those social networks we can extract information in many ways. In this work we are interested in comparing two datasets of Foursquare and two datasets of Instagram. We analyze those datasets to investigate whether we can observe the same users' movement pattern, the popularity of regions in cities, the activities of users who use those social networks, and how users share their content along the time. In answering those questions, we want to better understand location-related information, which is an important aspect of the urban phenomena.
Atrial Fibrillation Ablation Outcome Is Predicted by Left Atrial Remodeling on MRI

Background—Although catheter ablation therapy for atrial fibrillation (AF) is becoming more common, results vary widely, and patient selection criteria remain poorly defined. We hypothesized that late gadolinium enhancement MRI (LGE-MRI) can identify left atrial (LA) wall structural remodeling (SRM) and stratify patients who are likely or not to benefit from ablation therapy. Methods and Results—LGE-MRI was performed on 426 consecutive patients with AF without contraindications to MRI before undergoing their first ablation procedure and on 21 non-AF control subjects. Patients were categorized by SRM stage (I–IV) based on the percentage of LA wall enhancement for correlation with procedure outcomes. Histological validation of SRM was performed comparing LGE-MRI with surgical biopsy. A total of 386 patients (91%) with adequate LGE-MRI scans were included in the study. After ablation, 123 patients (31.9%) experienced recurrent atrial arrhythmias during the 1-year follow-up. Recurrent arrhythmias (failed ablations) occurred at higher SRM stages with 28 of 133 (21.0%) in stage I, 40 of 140 (29.3%) in stage II, 24 of 71 (33.8%) in stage III, and 30 of 42 (71.4%) in stage IV. In multivariate analysis, ablation outcome was best predicted by advanced SRM stage (hazard ratio, 4.89; P<0.0001) and diabetes mellitus (hazard ratio, 1.64; P=0.036), whereas increased LA volume and persistent AF were not significant predictors. LA wall enhancement was significantly greater in patients with AF versus non-AF controls (16.6±11.2% versus 3.1±1.9%; P<0.0001). Histological evidence of remodeling from surgical biopsy specimens correlated with SRM on LGE-MRI. Conclusions—Atrial SRM is identified on LGE-MRI, and extensive LGE (≥30% LA wall enhancement) predicts poor response to catheter ablation therapy for AF.
A Programming Language Extension for Probabilistic Robot Programming Sebastian Thrun

In recent years, probabilistic techniques have led to improved solutions for many robotics problems. However, no general tools are currently available to aid the development of probabilistic robotic software. This paper presents a programming language extension to C++ that integrates probabilistic computation and learning. Its two main ideas are to make probability distributions as usable as ﬂoating-point numbers, and to smoothly integrate function approximators into C++ code. These innovations facilitate the development of robust, probabilistic robot software, as illustrated by a proto-type program for a mail delivery robot.
Head pose tracking based on optimizing normalized cross-correlation

This paper proposes an efficient algorithm for head pose tracking. The most preexisting head pose tracking method usually consists of high cost computing algorithm. Therefore, it is difficult to implement head pose tracking in a mobile system with low performance hardware such as smartphone. In this paper, we propose a low cost computing algorithm for fast head pose tracking method. The proposed method consists of two stages: rough tracking and precise tracking stages. Especially, this paper discusses the efficient design of precise tracking stage. According to the experimental results, we demonstrate that our method increases the tracking performance using the proposed coarse-to-fine random sampling algorithm.
Surface chemical modification of carbon nanowalls for wide-range control of surface wettability

Carbon nanowalls (CNWs) are self-assembled, free-standing, few-layered graphenenano-structures with large surface area, and thin graphene edges. For their application to nanobiotechnology, the effects of chemisorbed species on surface wettability were investigated. The surfaces of as-grown CNWs obtained using CH4/H2 mixture were hydrophilic. After Ar atmospheric pressure plasma treatments for up to 30 s, the contact angles of water droplets on the CNWs decreased from 51° to 5°, owing to a result of oxidation only at edges and surface defects. They increased up to 147° by CF4 plasma treatment at low pressure. The wide-range control of surface wettability of CNWs was realized by post-growth plasma treatments. We also demonstrated detection of bovine serum albumin using surface-modified CNWs as electrodes.
MR_predictor: a simulation engine for Mendelian Randomization studies

UNLABELLED I present MR_predictor, a simulation engine designed to guide the development and interpretation of statistical tests of causality between phenotypes using genetic instruments. MR_predictor provides a framework to model either individual traits or complex scenarios where multiple phenotypes are correlated or dependent on each other. Crucially, MR_predictor can incorporate the effects of multiple biallelic loci (linked or unlinked) contributing genotypic variability to one or more simulated phenotypes. The software has a range of options for sample generation, and output files generated by MR_predictor port into commonly used analysis tools (e.g. PLINK, R), facilitating analyses germane for Mendelian Randomization studies. Benchmarks for speed and power calculations for summary statistic-based Mendelian Randomization analyses are presented and compared with analytical expectation. AVAILABILITY AND IMPLEMENTATION The simulation engine is implemented in PERL, and the associated scripts can be downloaded from github.com, and online documentation, tutorial and example datasets are available at http://coruscant.itmat. upenn.edu/mr_predictor.
Effect of some treatments on emission of volatile organic compounds (VOC) from chips used in pellets making processes

Emission of volatile organic compounds (VOC) from wood during processing to pellets – significance of wood extractives. Cellulose, hemicelluloses and lignin are the main components of the cell wall in wood. Moreover, wood contains different amounts of extractives, depending on the wood species. Extractives in softwoods play an important role during processing of wood to different wood products. This work studies the influence of storage on the change of extractives as well as on the emission of monoterpenes (primary emission) and aliphatic aldehydes, as degradation products of fats and fatty acids (secondary emission). In case of pine wood storage for 2 days at 80°C proved to be more efficient in the reduction of emissions of terpenes and aldehydes than 4 weeks at 40°C. Quantitative differences between pine (Pinus sylvestris) and spruce (Picea abies) wood chips in the emission were evaluated and discussed. Pinewood emits about 10 times higher amounts of terpenes and aldehydes than spruce wood. The results indicate that the intense of change in primary and secondary emissions due to storage depends on the wood species as well as on the boundary conditions under which storage is carried out. In general, storage at high temperature (80°C) is much more effective than at low temperature (40°C). The results also reveal that removal of wood extractives from pine wood by extraction with ethanol-cyclohexane or treatment with sodium hydroxide decreases the emission of primary and secondary volatile organic compounds drastically. Nevertheless, after such treatments minute amounts of volatile organic compounds are still detectable.
Analysis of correlation based dimension reduction methods

Analysis of correlation based dimension reduction methods Dimension reduction is an important topic in data mining and machine learning. Especially dimension reduction combined with feature fusion is an effective preprocessing step when the data are described by multiple feature sets. Canonical Correlation Analysis (CCA) and Discriminative Canonical Correlation Analysis (DCCA) are feature fusion methods based on correlation. However, they are different in that DCCA is a supervised method utilizing class label information, while CCA is an unsupervised method. It has been shown that the classification performance of DCCA is superior to that of CCA due to the discriminative power using class label information. On the other hand, Linear Discriminant Analysis (LDA) is a supervised dimension reduction method and it is known as a special case of CCA. In this paper, we analyze the relationship between DCCA and LDA, showing that the projective directions by DCCA are equal to the ones obtained from LDA with respect to an orthogonal transformation. Using the relation with LDA, we propose a new method that can enhance the performance of DCCA. The experimental results show that the proposed method exhibits better classification performance than the original DCCA.
On-line Scheduling via Sampling

We consider the problem of scheduling an unknown sequence of tasks for a single server as the tasks arrive with the goal off maximizing the total weighted value of the tasks served before their deadline is reached. This problem is faced for example by schedulers in packet communication networks when packets have deadlines and rewards associated with them. We make the simplifying assumptions that every task takes the same fixed amount of time to serve, that every task arrives with the same initial latency to its deadline. We also assume that future task arrivals are stochastically described by a Hidden Markov Model (HMM). The resulting decision problem can be formally modelled as a Partially Observable Markov Decision Process (POMDP). We first present and analyze a new optimal off-line scheduling algorithm called Prescient Minloss scheduling for the problem just described, but with "prescient" foreknowledge of the future task arrivals. We then discuss heuristically adapting this off-line algorithm into an on-line algorithm by sampling possible future task sequences from the HMM. We discuss and empirically compare scheduling methods for this on-line problem, including previously proposed sampling-based POMDP solution methods. Our heuristic approach can be used to adapt any off-line scheduler into an on-line scheduler.
A dynamically reconfigurable hardware-based cipher chip

A cipher core has been implemented, which is dedicated to a 64-bit block, 128-bit key, dynamically reconfigurable hardware-based cipher, called "Chameleon", in which two 32-cell, 8-context dynamically reconfigurable hardware units are employed to generate new subkeys for each of the 16 iterations in the encryption/decryption process. The proposed architecture has been implemented by 0.6 nm CMOS 3LM technology, using 65.6 K transistors and attaining a maximum throughput of 317.5 Mbps. The new approach demonstrates distinctive features of enhanced complexity and flexibility dedicatedly for embedded encryption/decryption applications in mobile computing.
Power Consumption Estimation Models for Processors, Virtual Machines, and Servers

The power consumption of presently available Internet servers and data centers is not proportional to the work they accomplish. The scientific community is attempting to address this problem in a number of ways, for example, by employing dynamic voltage and frequency scaling, selectively switching off idle or underutilized servers, and employing energy-aware task scheduling. Central to these approaches is the accurate estimation of the power consumption of the various subsystems of a server, particularly, the processor. We distinguish between power consumption measurement techniques and power consumption estimation models. The techniques refer to the art of instrumenting a system to measure its actual power consumption whereas the estimation models deal with indirect evidences (such as information pertaining to CPU utilization or events captured by hardware performance counters) to reason about the power consumption of a system under consideration. The paper provides a comprehensive survey of existing or proposed approaches to estimate the power consumption of single-core as well as multicore processors, virtual machines, and an entire server.
Effects of propafenone on calcium currents in single ventricular myocytes of guinea‐pig

1 The effects of propafenone on the inward calcium current (ICa) were investigated in isolated single ventricular myocytes of the guinea‐pig by the whole‐cell clamp method. Propafenone inhibited ICa in a dose‐dependent manner at concentrations of propafenone ranging from 1 × 10−8 to 1 × 10−3 m and half maximal block of ICa occurred at a propafenone concentration of 1.5 × 10−6 m. Propafenone did not change the current‐voltage relation of ICa other than a reduction in amplitude and showed no clear use‐ or frequency‐dependent effects upon ICa (stimulation frequencies from 0.03 to 2 Hz). Propafenone did not alter the steady‐state inactivation process: the half maximal activation potentials were 18.5 ± 2.2 mV in the control state and 20.9 ± 5.0 mV in the presence of 1×10−6 m propafenone (n = 12, NS). Propafenone (1 × 10−6 m) increased the half‐time of reactivation by 73.9% (n = 6, 212.3 ± 1.2 ms vs 369.2 ± 1.5 ms, P < 0.05). 2 We conclude that propafenone blocks ICa in a concentration‐dependent and a channel state‐, use‐ or frequency‐independent manner. The ICa, blockade elicited by propafenone at clinically therapeutic plasma concentration is significant and may be involved in its anti‐arrhythmic effects.
Transmission techniques for relay-interference networks

In this paper we study the relay-interference wireless network, in which relay (helper) nodes are to facilitate competing information flows over a wireless network. We examine this in the context of a deterministic wireless interaction model, which eliminates the channel noise and focuses on the signal interactions. Using this model, we show that almost all the known schemes such as interference suppression, interference alignment and interference separation are necessary for relay-interference networks. In addition, we discover a new interference management technique, which we call interference neutralization, which allows for over-the-air interference removal, without the transmitters having complete access the interfering signals. We show that interference separation, suppression, and neutralization arise in a fundamental manner, since we show complete characterizations for special configurations of the relay-interference network.
A random-based fractional-N frequency divider for spurious tones cancellation

A new fractional frequency divider is presented. It is based on a random dithering of the phase error. The divider output spectrum is cleaned from any fractional spurious tone. Moreover, as no noise shaping is applied, the proposed solution can be implemented in frequency synthesizers like Phase Locked Loops (PLL) without implication on the loop filter.