Miracle-dz/UniFAR-FTUs huggingface dataset:
Ieee Transactions on Wireless Communications 1 Dynamic User Grouping and Joint Resource Allocation with Multi-cell Cooperation for Uplink Virtual Mimo Systems

—This paper proposes a novel joint resource allocation algorithm combining dynamic user grouping, multi-cell cooperation and resource block (RB) allocation for single carrier-frequency division multiple access (SC-FDMA) uplink in multi-cell virtual MIMO systems. We first develop the dynamic multi-cell user grouping criteria using minimum mean square error (MMSE) equalization and adaptive modulation (AM) with bit error rate (BER) constraint. Then, we formulate and solve a new throughput maximization problem whose resource allocation includes cell selection, dynamic user grouping and RB pattern assignment. Furthermore, to reduce the computational complexity significantly, especially in the case of large numbers of users and RBs, we present an efficient iterative Hungarian algorithm based on user and resource partitions (IHA URP) to solve the problem by decomposing the large scale problem into a series of small scale sub-problems, which can obtain close-to-optimal solution with much lower complexity. The simulation results show that our proposed joint resource allocation algorithm with dynamic multi-cell user grouping scheme achieves better system throughput with BER guarantee than fixed user grouping algorithm and other proposed schemes in the literature.
Metagenomic Insights Into the Microbial Community and Nutrient Cycling in the Western Subarctic Pacific Ocean

The composition and metabolic functions of prokaryotic communities in the western subarctic Pacific (WSP), where strong mixing of waters from the Sea of Okhotsk and the East Kamchatka Current result in transfer to the Oyashio Current, were investigated using a shotgun metagenome sequencing approach. Functional metabolic genes related to nutrient cycling of nitrogen, sulfur, carbohydrates, iron and amino acids were differently distributed between the surface and deep waters of the WSP. Genes related to nitrogen metabolism were mainly found in deep waters, where Thaumarchaeaota, Sphingomonadales, and Pseudomonadales were closely associated and performing important roles in ammonia oxidation, assimilatory nitrate reduction, and dissimilatory nitrate reduction processes, respectively. In addition, orders affiliated to Spingobacteria and Alphaproteobacteria were crucial for sulfate reduction and abundant at 3000 m, whereas orders affiliated to Gammaproteobacteria, which harbored the most sulfate reduction genes, were abundant at 1000 m. Additionally, when compared with the East Kamchatka Current, the prokaryotes in the Oyashio Current were likely to consume more energy for synthesizing cellular components. Also, genes encoding iron transport and siderophore biosynthesis proteins were in low abundance, indicating that the iron was not a limiting factor in the Oyashio current. In contrast, in the East Kamchatka Current, prokaryotes were more likely to directly utilize the amino acids and absorb iron from the environment. Overall, our data indicated that the transformation from the East Kamchatka Current to the Oyashio Current reshapes not only the composition of microbial community, but also the function of the metabolic processes. These results extended our knowledge of the microbial composition and potential metabolism in the WSP.
Rapid Engineering of Foot-and-Mouth Disease Vaccine and Challenge Viruses

ABSTRACT There are seven antigenically distinct serotypes of foot-and-mouth disease virus (FMDV), each of which has intratypic variants. In the present study, we have developed methods to efficiently generate promising vaccines against seven serotypes or subtypes. The capsid-encoding gene (P1) of the vaccine strain O1/Manisa/Turkey/69 was replaced with the amplified or synthetic genes from the O, A, Asia1, C, SAT1, SAT2, and SAT3 serotypes. Viruses of the seven serotype were rescued successfully. Each chimeric FMDV with a replacement of P1 showed serotype-specific antigenicity and varied in terms of pathogenesis in pigs and mice. Vaccination of pigs with an experimental trivalent vaccine containing the inactivated recombinants based on the main serotypes O, A, and Asia1 effectively protected them from virus challenge. This technology could be a potential strategy for a customized vaccine with challenge tools to protect against epizootic disease caused by specific serotypes or subtypes of FMDV. IMPORTANCE Foot-and-mouth disease (FMD) virus (FMDV) causes significant economic losses. For vaccine preparation, the selection of vaccine strains was complicated by high antigenic variation. In the present study, we suggested an effective strategy to rapidly prepare and evaluate mass-produced customized vaccines against epidemic strains. The P1 gene encoding the structural proteins of the well-known vaccine virus was replaced by the synthetic or amplified genes of viruses of seven representative serotypes. These chimeric viruses generally replicated readily in cell culture and had a particle size similar to that of the original vaccine strain. Their antigenicity mirrored that of the original serotype from which their P1 gene was derived. Animal infection experiments revealed that the recombinants varied in terms of pathogenicity. This strategy will be a useful tool for rapidly generating customized FMD vaccines or challenge viruses for all serotypes, especially for FMD-free countries, which have prohibited the import of FMDVs.
Detecting duplicate examples in behaviour driven development specifications

In Behaviour-Driven Development (BDD), the behaviour of the software to be built is specified as a set of example interactions with the system, expressed using a “Given-When-Then” structure. The examples are written using customer language, and are readable by end-users. They are also executable, and act as tests that determine whether the implementation matches the desired behaviour or not. This approach can be effective in building a common understanding of the requirements, but it can also face problems. When the suites of examples grow large, they can be difficult and expensive to change. Duplication can creep in, and can be challenging to detect manually. Current tools for detecting duplication in code are also not effective for BDD examples. Moreover, human concerns of readability and clarity can rise. We present an approach for detecting duplication in BDD suites that is based around dynamic tracing, and describe an evaluation based on three open source systems.
Parallel Implementation of Local Similarity Search for Unstructured Text Using Prefix Filtering

Identifying partially duplicated text segments among documents is an important research problem with applications in plagiarism detection and near-duplicate web page detection. We investigate the problem of local similarity search for finding partially replicated text, focusing on its parallel implementation. Our aim is to find text windows that are approximately similar in two documents, using a filter verification framework. We present various parallel approaches to the problem, of which input data partitioning along with the reduction of individual index maps was found to be most suitable. We analyzed the effect of varying similarity threshold and number of processes on speedup, and also performed cost analysis. Experimental results show that the proposed method achieves up to 13x speedup on a 24-core processor.
Nonlinear Discriminant Analysis on Embedded Manifold

Traditional manifold learning algorithms, such as ISOMAP, LLE, and Laplacian Eigenmap, mainly focus on uncovering the latent low-dimensional geometry structure of the training samples in an unsupervised manner where useful class information is ignored. Therefore, the derived low-dimensional representations are not necessarily optimal in discriminative capability. In this paper, we study the discriminant analysis problem by considering the nonlinear manifold structure of data space. To this end, firstly, a new clustering algorithm, called Intra-Cluster Balanced K-Means (ICBKM), is proposed to partition the samples into multiple clusters while ensure that there are balanced samples for the classes within each cluster; approximately, each cluster can be considered as a local patch on the embedded manifold. Then, the local discriminative projections for different clusters are simultaneously calculated by optimizing the global Fisher Criterion based on the cluster weighted data representation. Compared with traditional linear/kernel discriminant analysis (KDA) algorithms, our proposed algorithm has the following characteristics: 1) it essentially is a KDA algorithm with specific geometry-adaptive-kernel tailored to the specific data structure, in contrast to traditional KDA in which the kernel is fixed and independent to the data set; 2) it is approximately a locally linear while globally nonlinear discriminant analyzer; 3) it does not need to store the original samples for computing the low-dimensional representation of a new data; and 4) it is computationally efficient compared with traditional KDA when the sample number is large. The toy problem on artificial data demonstrates the effectiveness of our proposed algorithm in deriving discriminative representations for problems with nonlinear classification hyperplane. The face recognition experiments on YALE and CMU PIE databases show that our proposed algorithm significantly outperforms linear discriminant analysis (LDA) as well as Mixture LDA, and has higher accuracy than KDA with traditional kernels
Evaluating Consistency Algorithms for Temporal Metric Constraints

We study the performance of some known algorithms for solving the Simple Temporal Problem (STP) and the Temporal Constraint Satisfaction Problem (TCSP). In particular, we empirically compare the Bellman-Ford (BF) algorithm and its incremental version (incBF) by (Cesta & Oddi 1996) to the ΔSTP of (Xu & Choueiry 2003a). Among the tested algorithms, we show that ΔSTP is the most efficient for determining the consistency of an STP, and that incBF combined with the heuristics of (Xu & Choueiry 2003b) is the most efficient for solving the TCSP. We plan to improve ΔSTP by exploiting incrementality as in incBF and other new incremental algorithms.
Mutating the CX3C Motif in the G Protein Should Make a Live Respiratory Syncytial Virus Vaccine Safer and More Effective

ABSTRACT Respiratory syncytial virus (RSV) belongs to the family Paramyxoviridae and is the single most important cause of serious lower respiratory tract infections in young children, yet no highly effective treatment or vaccine is available. Through a CX3C chemokine motif (182CWAIC186) in the G protein, RSV binds to the corresponding chemokine receptor, CX3CR1. Since RSV binding to CX3CR1 contributes to disease pathogenesis, we investigated whether a mutation in the CX3C motif by insertion of an alanine, A186, within the CX3C motif, mutating it to CX4C (182CWAIAC187), which is known to block binding to CX3CR1, might decrease disease. We studied the effect of the CX4C mutation in two strains of RSV (A2 and r19F) in a mouse challenge model. We included RSV r19F because it induces mucus production and airway resistance, two manifestations of RSV infection in humans, in mice. Compared to wild-type (wt) virus, mice infected with CX4C had a 0.7 to 1.2 log10-fold lower virus titer in the lung at 5 days postinfection (p.i.) and had markedly reduced weight loss, pulmonary inflammatory cell infiltration, mucus production, and airway resistance after challenge. This decrease in disease was not dependent on decrease in virus replication but did correspond to a decrease in pulmonary Th2 and inflammatory cytokines. Mice infected with CX4C viruses also had higher antibody titers and a Th1-biased T cell memory response at 75 days p.i. These results suggest that the CX4C mutation in the G protein could improve the safety and efficacy of a live attenuated RSV vaccine. IMPORTANCE RSV binds to the corresponding chemokine receptor, CX3CR1, through a CX3C chemokine motif (182CWAIC186) in the G protein. RSV binding to CX3CR1 contributes to disease pathogenesis; therefore, we investigated whether a mutation in the CX3C motif by insertion of an alanine, A186, within the CX3C motif, mutating it to CX4C (182CWAIAC187), known to block binding to CX3CR1, might decrease disease. The effect of this mutation and treatment with the F(ab′)2 form of the anti-RSV G 131-2G monoclonal antibody (MAb) show that mutating the CX3C motif to CX4C blocks much of the disease and immune modulation associated with the G protein and should improve the safety and efficacy of a live attenuated RSV vaccine.
Spoken Language Digital Libraries : The Million Hour Speech Project

The Center for Innovations in Speech and Language (CISL) at Carnegie Mellon University has launched a grand challenge project to collect and annotate at least one million hours of recorded speech. To collect and analyze such a large corpus, CISL is seeking the help and cooperation of affiliated research centers in many countries. The Million-Hour Corpus is designed to support research into innovative methodologies in knowledge representation and knowledge acquisition applied to speech recognition and synthesis, for which current data corpora have been inadequate. The new methodologies and the strong international cooperation will in turn enable the analysis and utilization of large corpora in ways that heretofore have not been possible. If this joint effort is successful, not only will it lead to improvements in speech systems, but it will make such systems available in many more languages and may even provide the catalyst for a paradigm shift in acoustic modeling. Index Terms — Socratic Agents, Knowledge Acquisition, Multiple Classifiers, Modular Architecture, Speech Manifold, Hidden Phonetic Sequences, Multi-Stage Recognition, Distributed Learning.
Platelets in Alzheimer’s Disease

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that gradually leads to severe cognitive impairment. The neuropathological hallmarks of AD include beta-amyloid plaques, tau neurofibrillary tangles, inflammation and glial responses, vascular dysfunction, synapse loss and cholinergic neurodegeneration. Currently, the diagnosis of possible or probable AD is based on a time consuming combination of clinical and psychological testing, imaging, and the analysis of three well-established biomarkers (beta-amyloid(42), total tau and phospho-tau-181) in cerebrospinal fluid. The search for biomarkers in blood is of high importance to avoid invasive lumbar puncture and to allow fast and easy analysis of a high number of patients. Biomarkers have been screened in blood of AD patients in plasma/serum, peripheral blood mononuclear cells (PBMCs), monocytes or also in platelets.
Simulation framework for improved UI/UX of AR-HUD display

The AR-HUD (Augmented Reality-Head Up Display) overlays the ADAS (Autonomous Driver Assistant System) information to real world objects on the windshield unlike the normal HUD. This projected ADAS information on the windshield usually occurs the irregularity between the objects and the ADAS information because of the difference between driver and AR-HUD's view plane. To overcome this problem, we present a simulation framework for the improved AR-HUD in ADAS by means of a homographie registration with inference outputs from a region based deep learning model. In order to build this simulation framework, we set up a simulation test bed to mimic on-road driving environment in a darkroom, and use the inference model based on region-based fully convolutional network to obtain on-road ADAS information. And then we apply the homographie registration method to minimize the irregularity between object and ADAS information in terms of driver's perception. We tested the proposed simulation framework with real world driving recordings, and it showed better display results for improved UI/UX with inference outputs from region-based deep learning model.
Socioeconomic differences in children’s growth trajectories from infancy to early adulthood: evidence from four European countries

Background Height is regarded as a marker of early-life illness, adversity, nutrition and psychosocial stress, but the extent to which differences in height are determined by early-life socioeconomic circumstances, particularly in contemporary populations, is unclear. This study examined socioeconomic differences in children’s height trajectories from birth through to 21 years of age in four European countries. Methods Data were from six prospective cohort studies—Generation XXI, Growing Up in Ireland (infant and child cohorts), Millennium Cohort Study, EPITeen and Cardiovascular Risk in Young Finns Study—comprising a total of 49 492 children with growth measured repeatedly from 1980 to 2014. We modelled differences in children’s growth trajectories over time by maternal educational level using hierarchical models with fixed and random components for each cohort study. Results Across most cohorts at practically all ages, children from lower educated mothers were shorter on average. The gradient in height was consistently observed at 3 years of age with the difference in expected height between maternal education groups ranging between −0.55 and −1.53 cm for boys and −0.42 to −1.50 cm for girls across the different studies and widening across childhood. The height deficit persists into adolescence and early adulthood. By age 21, boys from primary educated maternal backgrounds lag the tertiary educated by −0.67 cm (Portugal) and −2.15 cm (Finland). The comparable figures for girls were −2.49 cm (Portugal) and −2.93 cm (Finland). Conclusions Significant differences in children’s height by maternal education persist in modern child populations in Europe.
Historical and Modern Image-to-Image Translation with Generative Adversarial Networks

We investigate the use of Cycle-Consistent Adversarial Networks (CycleGANs) for the translation of historical images to their modern color equivalents. CycleGANs have previously been used for a variety of geometric and colorbased image-to-image transformation tasks, but here we face the particular challenge of complete colorization of a historical photograph using an unpaired training dataset. We hypothesize that due to differences between modern and historical grayscale photographs, ordinary approaches for translating grayscale to color with paired datsets will be insufficient.
Hyperglycemia and Cancer: An algorithm to guide oncology nurses

BACKGROUND: A dual diagnosis of cancer and hyperglycemia has demonstrated untoward effects on patients' cancer treatment, prognosis, and survival. OBJECTIVES: The purpose of this evidence‐based project is to improve knowledge and awareness of the consequences of hyperglycemia in patients with cancer, increasing nurses' capability to effectively intervene. In addition, a clinical algorithm based on current evidence was developed and is presented. METHODS: An educational program was developed and pilot tested. The program addressed the etiology of hyperglycemia and its effects on patients with cancer. Knowledge of hyperglycemia in patients with cancer was assessed with a pre‐ and post‐test. FINDINGS: All participants found the educational program effective and deemed the clinical algorithm useful. Results improved significantly after participation in the educational intervention.
Pedestrian Detection by Feature Selected Self-Similarity Features

This paper is concerned with the pedestrian detection problem. In this area, boosted decision tree (BDT) methods are highly successful and very efficient. However, to achieve the best performance, most BDT methods require a large number of input features, which make the algorithm scale poorly to large-scale data. Inspired by the effectiveness of self-similarity (SS) features, we use linear discriminant analysis to select features in the SS features according to their generalized Rayleigh quotient, leading to a small number but most discriminative features. These features are called feature selected self-similarity (FSSS) features. The FSSS features are only used for the late stages of the BDT cascade, making the training and detecting much more efficient. Extensive experiments on four well-known data sets demonstrate that the FSSS features are highly effective and the trained pedestrian detector achieves state-of-the-art performance among all existing non-deep-learning methods on several benchmarks. We also compare our method with deep learning methods and show its superiority in high-quality localization and will be a good complement to deep learning methods.
Design and Characterization of a 43.2-ps and PVT-Resilient TDC for Single-Photon Imaging Arrays

This brief describes the design and characterization of a ring oscillator-based time-to-digital converter (TDC) with down to 43.2 ps of time resolution and high tolerance to process, voltage and temperature variations. By employing a compact architecture, it is therefore suitable for inclusion in imaging arrays for time-stamping functions. The proposed TDC has been fabricated in a 0.13-<inline-formula> <tex-math notation="LaTeX">${\mu }\text{m}$ </tex-math></inline-formula> CMOS technology in a <inline-formula> <tex-math notation="LaTeX">${16\times 8}$ </tex-math></inline-formula> array of single-photon avalanche diode-based pixels for positron emission tomography applications and thoroughly characterized.
Design of CPW fed hexagonal sierpinski fractal antenna for UWB band applications

In this paper, a novel hexagonal sierpinski fractal antenna has been designed for ultra wideband (UWB) applications. Coplanar Waveguide (CPW) fed fractal antenna is to be designed with the design parameters of the size is 30 × 28 × 1.6 mm<sup>3</sup> and the substrate is FR<inf>4</inf> ε<inf>r</inf>=4.4 and tanδ= 0.002. The proposed antenna resonates at 3.1 to 10.8 GHz with a return loss of above −10 dB. The antenna has a better gain of 7 dBi at the UWB band frequency. The antenna is used for variety of applications like defence, secure communication and biomedical applications. The software used for simulation is IE3D simulator.
Scc2/Nipbl hops between chromosomal cohesin rings after loading

The cohesin complex mediates DNA-DNA interactions both between (sister chromatid cohesion) and within chromosomes (DNA looping) via a process thought to involve entrapment of DNAs within its tripartite ring. It has been suggested that intra- chromosome loops are generated through processive extrusion of DNAs through the lumen of cohesin’s ring. Scc2 (Nipbl) is essential for loading cohesin onto chromosomes but not for maintaining sister chromatid cohesion following DNA replication. It has therefore been assumed that Scc2 is involved exclusively in the cohesin loading process. However, it is possible that the stimulation of cohesin’s ABC-like ATPase by Scc2 also has a post-loading function, for example driving loop extrusion. Using fluorescence recovery after photobleaching (FRAP) and single-molecule tracking, we show that Scc2 binds dynamically to chromatin, principally through an association with cohesin. Scc2’s movement within chromatin is consistent with a “stop-and-go” or “hopping” motion. We suggest that a low diffusion coefficient, a low stoichiometry relative to cohesin, and a high affinity for chromosomal cohesin enables Scc2 to move rapidly from one chromosomal cohesin complex to another, performing a function distinct from loading.