Miracle-dz/UniFAR-FTUs huggingface dataset:
End-to-End Loss Differentiation Algorithm Based on Estimation of Queue Usage in Multi-Hop Wireless Networks

When TCP operates in multi-hop wireless networks, it suffers from severe performance degradation. This is because TCP reacts to wireless packet losses by unnecessarily decreasing its sending rate. Although previous loss differentiation algorithms (LDAs) can identify some of the packet losses due to wireless transmission errors as wireless losses, their accuracy is not high as much as we expect, and these schemes cannot avoid sacrificing the accuracy of congestion loss discrimination by misclassifying congestion losses as wireless losses. In this paper, we suggest a new end-to-end loss differentiation scheme which has high accuracy in both wireless loss discrimination and congestion loss discrimination. Our scheme estimates the rate of queue usage using information available to TCP. If the estimated queue usage is larger than 50% when a packet is lost, our scheme diagnoses the packet loss as congestion losses. Otherwise, it diagnoses the packet loss as wireless losses. Because the estimated queue usage is highly correlated to congestion, our scheme has an advantage to more exactly identify packet losses related to congestion and those unrelated to congestion. Through extensive simulations, we compare and evaluate our scheme with previous LDAs in terms of correlation, accuracy, and stability. And the results show that our scheme has the highest accuracy as well as its accuracy is more reliable than the other LDAs.
Dose-finding studies, MCP-Mod, model selection, and model averaging: Two applications in the real world

Background Phase II clinical trials are important milestones to determine whether a dose-effect exists and to decide on future doses to use in confirmatory studies. To take into account the overall shape of the dose–response curve, modeling the relationship by linear or non-linear models is preferable to the classical pair-wise comparisons of the effect of each dose versus the placebo or the comparator. The multiple comparisons and modeling approach has been developed within the last 10 years to address this important question in the clinical development of drugs. Despite some recent publications referring to this methodology, few detailed applications have been shown so far and several practical questions remain to be addressed. Methods Starting from a set of candidate models, model selection using classical methods criteria is possible. However, it suffers some limitations, not taking into account the uncertainty of the selection process itself. An attractive solution is to use model averaging, which applies appropriate weights to the parameters (e.g., the minimum effective dose) obtained from each model. Results A discussion of the selection criteria is first presented. Through two real examples, how to proceed with model selection and model averaging is presented and discussed. Limitations The first multiple comparisons and modeling approach papers addressed normal responses. More recently, an extension of this methodology has been proposed to deal with other types of responses, in particular binary, time-to-event and longitudinal data. Questions that remain are concerned with the choice of the candidate models and of their parameters’ guesstimates. Conclusions The analysis of clinical dose-finding studies using a modeling of the entire curve offers a promising alternative as compared with the classical multiple comparisons methods, while not compromising the necessary rigor of the analysis.
Motility, viability, and calcium in the sperm cells

Abstract Sperm cells are complicated in vitro models. Their viability is limited, and physiology is complex. The study of their properties is of great application in the animal production as viable and functional gametes are essential. It has been shown that the decrease of sperm cell viability parallels an increase of the reactive oxygen species (ROS). Reactive oxygen species is secondary to normal metabolic processes of the cell-like flagellar movement. There is evidence of strategies that reduce ROS levels by using exogenous or endogenous antioxidants with the intention that seminal plasma protects the sperm cells and increases viability. Perhaps viability can increase by reducing that flagellar movement which is regulated by calcium. The phenomenon has not been fully characterized, but it is established that in certain mammalian models, the entrance of calcium via specific channels such as CATsper or voltage-dependent channels, signals flagellar movement. Previous reports have indicated that a change in the concentration of calcium or if the temperature is altered, the function of mammal sperm cells is reduced or blocked and viability prolonged. Fish sperm can remain immobile for several weeks but when activated the number of mobile and viable sperm is reduced at a faster rate. However, if the cells are not mobilized the semen can be preserved for longer periods. As presented in this paper, this supports the notion that by modulating calcium channels to reduce motility the viability of these cells can increase.
A Survey on Virtual Machine Migration: Challenges, Techniques, and Open Issues

When users flood in cloud data centers, how to efficiently manage hardware resources and virtual machines (VMs) in a data center to both lower economical cost and ensure a high service quality becomes an inevitable work for cloud providers. VM migration is a cornerstone technology for the majority of cloud management tasks. It frees a VM from the underlying hardware. This feature brings a plenty of benefits to cloud providers and users. Many researchers are focusing on pushing its cutting edge. In this paper, we first give an overview of VM migration and discuss both its benefits and challenges. VM migration schemes are classified from three perspectives: 1) manner; 2) distance; and 3) granularity. The studies on non-live migration are simply reviewed, and then those on live migration are comprehensively surveyed based on the three main challenges it faces: 1) memory data migration; 2) storage data migration; and 3) network connection continuity. The works on quantitative analysis of VM migration performance are also elaborated. With the development and evolution of cloud computing, user mobility becomes an important motivation for live VM migration in some scenarios (e.g., fog computing). Thus, the studies regarding linking VM migration to user mobility are summarized as well. At last, we list the open issues which are waiting for solutions or further optimizations on live VM migration.
Prediction of Best Weld Quality Using Artificial Neural Network

The aim of the proposed work is to use an artificial neural network(ANN) to predict the best weld made of two dissimilar metals i.e. MS (AISI 1040) and SS (AISI3014) fabricated by Gas tungsten arc welding (GTAW), also known as tungsten inert gas (TIG) welding. The process parameters used are weld travel speed, current, gas flow rate, and inclination. Experiments are designed and conducted as per the Taguchi method. Further MOORA method is used to find the best combination of input process parameters. The results of experiments are used to model the process using for artificial neural network. The performance ANN models is compared with experimental results and found the good correlation between the experimental results and the results provided by ANN.
Toward 6 DOF Object Pose Estimation with Minimum Dataset

In this research, we propose a method for estimating 6 DOF object pose (3D orientation and position), based on convolutional neural networks (CNN). We propose RotationCNN that predicts 3D orientation of the object. The position of the object is estimated using an object detection CNN that predicts the class of the object and bounding box around it. Unlike the method that trains CNNs using a largescale database, the proposed system is trained with minimum dataset obtained in a local environment that is similar to where the robot is used. With the proposed semi-automated dataset collection techniques based on a web camera and AR markers, users in different environment will be able to train the network suited for their own environment relatively easily and quickly. We believe that this approach is suitable for a practical robotic application. The results on 3D orientation prediction using RotationCNN show the average error of 18.9 degrees, which we empirically found that it is low enough as an initial solution to successfully run the iterative closest point (ICP) algorithm that uses depth data to refine the pose obtained with CNNs. The effectiveness of the proposed method is validated by applying the method to object grasping by a robot manipulator.
Clustering System Group Customers through Fuzzy C-Means Clustering

Like other economic sectors, it is important to identify, satisfy, and attract profitable customers in the software industry. Organizations have decided to analyze customer behavior and keep the most valuable customers satisfied due to competitive conditions and customer attraction costs. This applied-descriptive study was conducted on the dataset of System Group customers, including 26620 records in 2017. The dataset was analyzed to extract key factors such as the quality of being strategic, the number of software systems, contract sum and customer lifetime. For this purpose, the cross-industry standard process for data mining (CRISP-DM) was employed along with the fuzzy C-means (FCM) clustering algorithm to classify customers and identify profitable and loyal ones. Then the existing data were clustered, and the resultant clusters were evaluated. Finally, the dataset was divided into four major clusters. The first, second, third, and fourth clusters included the special customers (140 members), loyal customers (1800 members), ordinary customers (8960 members), and low-value customers (15720 members), respectively.
Numbers of copy-number variations and false-negative rates will be underestimated if we do not account for the dependence between repeated experiments.

To the Editor: We read with interest the recent publication of Wong et al.1 that uses six repeat experiments to provide estimates of copy-number variation (CNV) numbers and false-positive and false-negative rates in the absence of a “gold-standard” set of data. With acceptance of the obvious limitation that such an approach is not making inference about the true CNV population but only that subset that might be detected via this technology, this appears to be an ingenious idea (with echoes of capture-recapture schemes) and is itself worthy of replication.
A Proposed Model for Preventing the spread of misinformation on Online Social Media using Machine Learning

With more than 71% of internet users using Online Social Media (OSM), it has become an important platform for people to share ideas, information and various forms of expressions. However, there is no guarantee about the credibility of the information i.e. how legitimate is the information due to the use of crowd sourcing and absence of any central moderation. This makes it easier for malicious users and some anti-social elements to circulate rumors and create panic among the public, particularly during any real time incident or a disaster by generating fake content. Among the OSMs, the most popular micro-blogging website, Twitter, becomes an easy target for malicious users to spread misinformation having a wide variety of crowd from general public to celebrities, politicians and even large organizations. The system aims to detect such misleading information on Twitter and provide possible measures that can be adopted by the social media company to prevent the spread of misinformation and by the users who contribute to the spread without verifying the veracity of the content.
"Two-Photon" coincidence imaging with a classical source.

Coincidence imaging is a technique that extracts an image of a test system from the statistics of photons transmitted by a reference system when the two systems are illuminated by a source possessing appropriate correlations. It has recently been argued that quantum entangled sources are necessary for the implementation of this technique. We show that this technique does not require entanglement, and we provide an experimental demonstration of coincidence imaging using a classical source. We further find that any kind of coincidence imaging technique which uses a "bucket" detector in the test arm is incapable of imaging phase-only objects, whether a classical or quantum source is employed.
A Novel Two-Layer Low-Profile 23-GHz Microstrip Array Fed by Slots in an SIW for Wireless Backhauling Applications

This paper proposes a robust option for developing a new class of efficient and cheap antenna array based on patch array fed by substrate-integrated waveguide (SIW) through slot apertures for wireless backhauling applications. It consists in performing the feed network in SIW and the radiating structure in microstrip technology. The microstrip lines are coupled to the slots on the top wall of the SIW. Hence, it is demonstrated that the best alternative of the costly, heavy, and bulky rectangular waveguide feeder is SIW, which provides miniaturization, cost reductions, performance enhancements, and easy integration with patch array antennas. The experimental prototype presented in this paper demonstrates the efficiency of the design method and the feasibility of creating low-cost moderate-bandwidth millimeter-wave planar $8\times 8$ patch antenna array configurations in two stacked substrates to get ultracompact antenna module. The principle of achieving such high-quality antenna array is presented in detail along with experimental verification of theoretical results to validate the design procedure and demonstration of the feasibility of implementing the array by means of relatively inexpensive compact structures. The maximum gain is around 23 dBi at 22.4 GHz, the measured impedance bandwidth is 5%, and the efficiency is around 70%.
Intra-patient Registration Methods for Thoracic CT Exams

Now-a-days CT scanners provide detailed morphological information of pulmonary structures, with great importance to the diagnostic and follow-up of oncological diseases. When a patient with lung cancer is submitted to several CT exams during a period of time; these exams need an appropriate registration to quantify or visualize the tumour’s evolution. We propose a new method for 3D intra-patient registration of thoracic CT exams and compare its results with several 3D registration methods. The performance of these registration methods is analysed, computing several normalized figures of merit; we also explore these metrics to check which is more sensible to changes in CT exams due to the presence of lung tumours. The results with several cases of intra-patient, intra-modality registration show that the proposed method provides an accurate registration which is needed for the quantitative tracking of lesions that may effectively assist the follow-up process of oncological patients.
Initial Reactivity of Linkages and Monomer Rings in Lignin Pyrolysis Revealed by ReaxFF Molecular Dynamics.

The initial conversion pathways of linkages and their linked monomer units in lignin pyrolysis were investigated comprehensively by ReaxFF MD simulations facilitated by the unique VARxMD for reaction analysis. The simulated molecular model contains 15 920 atoms and was constructed on the basis of Adler's softwood lignin model. The simulations uncover the initial conversion ratio of various linkages and their linked aryl monomers. For linkages and their linked monomer aryl rings of α-O-4, β-O-4 and α-O-4 & β-5, the Cα/Cβ ether bond cracking dominates the initial pathway accounting for at least up to 80% of their consumption. For the linkage of β-β & γ-O-α, both the Cα-O ether bond cracking and its linked monomer aryl ring opening are equally important. Ring-opening reactions dominate the initial consumption of other 4-O-5, 5-5, β-1, β-2, and β-5 linkages and their linked monomers. The ether bond cracking of Cα-O and Cβ-O occurs at low temperature, and the aryl ring-opening reactions take place at relatively high temperature. The important intermediates leading to the stable aryl ring opening are the phenoxy radicals, the bridged five-membered and three-membered rings and the bridged six-membered and three-membered rings. In addition, the reactivity of a linkage and its monomer aryl ring may be affected by other linkages. The ether bond cracking of α-O-4 and β-O-4 linkages can activate its neighboring linkage or monomer ring through the formed phenoxy radicals as intermediates. The important intermediates revealed in this article should be of help in deepening the understanding of the controlling mechanism for producing aromatic chemicals from lignin pyrolysis.
X-ray scatter tomography using coded apertures

Kenneth P. MacCabe: X-ray scatter tomography using coded apertures (Under the direction of David Brady and Otto Zhou) This work proposes and studies a new eld of x-ray tomography which combines the principles of scatter imaging and coded apertures, termed coded aperture x-ray scatter imaging (CAXSI). Conventional x-ray tomography reconstructs an object's electron density distribution by measuring a set of line integrals known as the x-ray transform, based physically on the attenuation of incident rays. More recently, scatter imaging has emerged as an alternative to attenuation imaging by measuring radiation from coherent and incoherent scattering. The information-rich scatter signal may be used to infer density as well as molecular structure throughout a volume. Some scatter modalities use collimators at the source and detector, resulting in long scan times due to the low e ciency of scattering mechanisms combined with a high degree of spatial ltering. CAXSI comes to the rescue by employing coded apertures. Coded apertures transmit a larger fraction of the scattered rays than collimators while also imposing structure to the scatter signal. In a coded aperture system each detector is sensitive to multiple ray paths, producing multiplexed measurements. The coding problem is then to design an aperture which enables de-multiplexing to reconstruct the desired physical properties and spatial distribution of the target. In this work, a number of CAXSI systems are proposed, analyzed, and demonstrated. One-dimensional pencil beams, two-dimensional fan beams, and three-dimensional cone beams are considered for the illumination. Pencil beam and fan beam CAXSI systems are demonstrated experimentally. The utility of energy-integrating (scintillation) detectors and energy-sensitive (photon counting) detectors are evaluated theoretically, and new coded aperture designs are presented for each beam geometry. Physical models are developed for each coded aperture system, from which resolution metrics are derived. Systems employing di erent combinations of beam geometry, coded apertures, and detectors are analyzed by constructing linear measurement operators and comparing their singular value decompositions. Since x-ray measurements are typically dominated by photon shot noise, iterative algorithms based on Poisson statistics are used to perform the reconstructions. This dissertation includes previously published and unpublished co-authored material.
Influence of the Epstein-Barr virus nuclear antigen EBNA 2 on the growth phenotype of virus-transformed B cells

Epstein-Barr virus (EBV) isolates show sequence divergence in the BamHI YH region of the genome which encodes the nuclear antigen EBNA 2, a protein thought to be involved in the initiation of virus-induced B-cell transformation; type A isolates (such as B95-8 EBV) encode a 82- to 87-kilodalton EBNA 2A protein, whereas type B isolates (such as AG876 EBV) encode an antigenically distinct 75-kilodalton EBNA 2B protein. In the present work 12 type A isolates and 8 type B isolates have been compared for their ability to transform resting human B cells in vitro into permanent lymphoblastoid cell lines. Although the kinetics of initial focus formation was not markedly dependent upon the EBNA 2 type of the transforming virus, on subsequent passage type A virus-transformed cells (type A transformants) yielded cell lines much more readily than did type B transformants. Direct comparison between the two types of transformant revealed clear differences in several aspects of growth phenotype. Compared with type A transformants, cell lines established with type B virus isolates consistently displayed an unusual growth pattern with poor survival of individual cells shed from lymphoblastoid clumps, a lower growth rate and a greater sensitivity to seeding at limiting dilutions, and a significantly lower saturation density that could not be corrected by supplementation of the medium with culture supernatant containing B-cell growth factors. This is the first direct evidence that, in EBV-transformed B-cell lines, the EBNA 2 protein plays a continuing role in determining the cellular growth phenotype.
Presence of monoterpene synthase in four Labiatae species and Solid-Phase Microextraction- Gas chromatography-Mass Spectroscopy analysis of their aroma profiles

Background: The family Lamiaceae (Labiatae) has included some medicinal plants. some monoterpene synthases, including linalool and limonene synthases, have been cloned and functionally characterized from several plants of Labiatae family. Materials and Methods: In this study, presence of linalool and limonene synthases, in four species of Labiatae family including Nepeta cataria, Lavandula angustifolia, Hyssopus officinalis and Salvia sclarea has been determined by molecular biological techniques together with the Head space SPME – GC-MS analysis of the aroma profile of these species. Results: Indicated that none of the plant species produced distinguishable bands with primer pairs related to d-limonene synthase. Distinguishable bands around 1800 bp in cDNA samples of L. angustifolia, H. officinalis and S. sclarea were observed regarding to the presence of linalool synthase. Head space SPME-GC-MS analysis of the aroma profiles of the above-mentioned plants showed that linalool (31.0%), linalyl acetate (18.2%), were found as the major compounds of L. angustifolia, while geraniol (5.5%), nerol (34.0%) and α- citral (52.0%) were identified as the main compounds of the N. cataria. The major components of H. officinalis and S. sclarea oils were determined as cis-pinocamphone (57.3%), and linalool (19.0%), linalyl acetate (51.5%), respectively. Conclusion: H. officinalis was rich of cyclic monoterpenes, L. angustifolia, N. cataria and S. sclarea showed considerable amount of linear monoterpenes. The aroma profile of the above-mentioned plants contained low concentration of sesquiterpenes except N. cataria, which indicated no sesquiterpene. The profiles of the main components of these plants are in agreement with molecular assays.
Different mechanisms underlying changes in excitability of peripheral nerve sensory and motor axons in multiple sclerosis

Introduction: Subtle involvement of peripheral nerves may occur in multiple sclerosis. Motor excitability studies have suggested upregulation of slow K+ currents, probably secondary to altered motoneuron properties resulting from the central lesion. This study concentrates on sensory axons. Methods: Excitability of median nerve axons at the wrist was studied in 26 patients. Results: Sensory recordings were possible in 22 patients, and reduced superexcitability was the sole abnormality. There was no evidence for changes in membrane potential or demyelination. The decrease was significant in patients taking immunomodulatory therapy. These findings could be reproduced in a computer model by changing the gating of fast K+ channels. Motor axon findings were consistent with previously reported increased slow K+ current. Conclusions: The sensory findings differ from motor findings. They can be explained by a humoral factor, possibly cytokines, which can penetrate the paranode and have been documented to alter the gating of K+ channels. Muscle Nerve, 2013