Miracle-dz/UniFAR-FTUs huggingface dataset:
A Chain-Based Data Gathering Protocol Under Compressive Sensing Framework for Wireless Sensor Networks

This paper proposes an efficient data gathering protocol for large scale wireless sensor networks by using the compressive sensing technology. All sensor nodes construct a chain by a greedy algorithm. Data packets are transmitted through this chain from one node to another and till the end node of the chain. This end node, namely chain leader, then relays all packets to the base station. By using compressive sensing technology, all sensing data can be simultaneously transmitted and aggregated to a few packets by relaying nodes. The base station is responsible for recovering every node's data according to these few packets. Simulation results show that this method can reduce the energy consumption of large scale wireless sensor network.
The role of vertical chemical fractionation in controlling late Quaternary atmospheric carbon dioxide

The 30% decrease in atmospheric carbon dioxide during glacial maxima must be driven by some change in the chemical circulation of the ocean. Here, a new model for late Quaternary CO2 variability is presented which resolves some problems occurring in previous models (including the timing of carbon dioxide response and changes in the oxygen content of the deep ocean). The primary driving factor in this model is a rearrangement of chemical distributions in the ocean whereby labile nutrients and metabolic CO2 are concentrated in deep waters rather than in intermediate waters as observed in the modern ocean. This new “bottom-heavy” chemical structure does not affect atmospheric carbon dioxide directly. Instead, CO2-induced acidity lowers the deep ocean carbonate ion concentration and temporarily increases carbonate dissolution rates. Oceanic alkalinity then rises until the deep ocean carbonate ion is restored to its steady state value. The resulting increase in oceanic alkalinity draws CO2 out of the atmosphere into the ocean. Alkalinity and atmospheric CO2 lag several thousand years behind the change in oceanic chemical structure; this delayed response is determined by the limited rate of continental weathering and deep ocean carbonate dissolution relative to the oceanic alkalinity inventory. It is proposed that characteristic deglacial and preglacial states of the ocean are leading factors driving glacial-interglacial climate changes. This concept reinterprets the carbon isotope contrast between surface water and deep waters [Δδ13C(P-B)] as due to a shift of light metabolic carbon from intermediate waters into deep waters. The process is illustrated here by a simple equilibrium five box ocean model. The observed intermediate-depth nutrient depletion is not sufficient in itself to determine which of several possible mechanisms are operating, and some mechanisms are not as effective in changing atmospheric CO2 as others. The largest response is seen from deepening the regeneration cycle of organic carbon; the least response is seen from converting North Atlantic Deep Water into intermediate water.
Propagation characteristics of intra-body communications for body area networks

Body area networks (BAN) will become increasingly important in the future personal communication systems. We believe that intra-body communications (IBC) based on near field electromagnetic waves is a suitable solution for BAN. This paper presents experimental measurements of the frequency and time domain responses in order to investigate the transmission characteristics of the human body as a conductor of low power high frequency radio signals (up to 3GHz). In the measurements, several distances between transmitter and receiver (up to a long distance from the head to the foot) and six test people (to study the possible variation results due to physiological body effects) have been considered. Besides analyzing the intra-body channel response, we also aim to define a suitable frequency range for IBC. Finally, this paper also presents an initial evaluation study of several digital modulation schemes in order to investigate the optimal technique for IBC.
Differential contribution of two Ppd-1 homoeoalleles to early-flowering phenotype in Nepalese and Japanese varieties of common wheat

Wheat landraces carry abundant genetic variation in heading and flowering times. Here, we studied flowering-related traits of two Nepalese varieties, KU-4770 and KU-180 and a Japanese wheat cultivar, Shiroganekomugi (SGK). These three wheat varieties showed similar flowering time in a common garden experiment. In total, five significant quantitative trait loci (QTLs) for three examined traits, the heading, flowering and maturation times, were detected using an F2 population of SGK/KU-4770. The QTLs were found at the Ppd-1 loci on chromosomes 2B and 2D and the 2B QTL was also confirmed in another F2 population of SGK/KU-180. The Ppd-D1 allele from SGK and the Ppd-B1 alleles from the two Nepalese varieties might be causal for early-flowering phenotype. The SGK Ppd-D1 allele contained a 2-kb deletion in the 5′ upstream region, indicating a photoperiod-insensitive Ppd-D1a allele. Real-time PCR analysis estimating the Ppd-B1 copy number revealed that the two Nepalese varieties included two intact Ppd-B1 copies, putatively resulting in photoperiod insensitivity and an early-flowering phenotype. The two photoperiod-insensitive Ppd-1 homoeoalleles could independently contribute to segregation of early-flowering individuals in the two F2 populations. Therefore, wheat landraces are genetic resources for discovery of alleles useful for improving wheat heading or flowering times.
Human Coronavirus NL63 Infection and Other Coronavirus Infections in Children Hospitalized with Acute Respiratory Disease in Hong Kong, China

Abstract Background. Human coronavirus NL63 (HCoV-NL63) is a recently discovered human coronavirus found to cause respiratory illness in children and adults that is distinct from the severe acute respiratory syndrome (SARS) coronavirus and human coronaviruses 229E (HCoV-229E) and OC43 (HCoV-OC43). Methods. We investigated the role that HCoV-NL63, HCoV-OC43, and HCoV-229E played in children hospitalized with fever and acute respiratory symptoms in Hong Kong during the period from August 2001 through August 2002. Results. Coronavirus infections were detected in 26 (4.4%) of 587 children studied; 15 (2.6%) were positive for HCoV-NL63, 9 (1.5%) were positive for HCoV-OC43, and 2 (0.3%) were positive for HCoV-229E. In addition to causing upper respiratory disease, we found that HCoV-NL63 can present as croup, asthma exacerbation, febrile seizures, and high fever. The mean age (± standard deviation [SD]) of the infected children was 30.7 ± 19.8 months (range, 6–57 months). The mean maximum temperature (±SD) for the 12 children who were febrile was 39.3°C ± 0.9°C, and the mean total duration of fever (±SD) for all children was 2.6 ± 1.2 days (range, 1–5 days). HCoV-NL63 infections were noted in the spring and summer months of 2002, whereas HCoV-OC43 infection mainly occurred in the fall and winter months of 2001. HCoV-NL63 viruses appeared to cluster into 2 evolutionary lineages, and viruses from both lineages cocirculated in the same season. Conclusions. HCoV-NL63 is a significant pathogen that contributes to the hospitalization of children, and it was estimated to have caused 224 hospital admissions per 100,000 population aged ⩽6 years each year in Hong Kong.
An algorithm for determining the regulator and the fundamental unit of hyperelliptic congruence function field

Let K be an algebraic function field in one indeterminate X over a finite field of constants k = IFq of characteristic p. Hence K/k is a congruence function field of transcendence degree one. Suppose that K/k is elliptic or hyperelliptic and that k has characteristic p ~ 2. Then K is a quadratic extension of the rational subfield K. k(X). In fact there IS a square-free polynomial D c k[X] such that K = KO(~D ), and the integral closure of the polynomial ring k[X~ in K is R = k[X ,<D ]. Suppose moreover, that K/KO is a real quadratic extension, i.e. that the place at infinity pm of K. with respect to X splits in K: pa = plpz. ln analogy to the case of a real quadratic number field, the unit group U of the real quadratic function field K/k is the direct product of the finite cyclic group kx of non-zero constants and an infinite cyclic group <E> generated by the fundamental unit E of K: U = k’ x <E> . The absolute value of the normalized additive valuation Vp of E associated with pi, i.e. r =
Use of Single Nucleotide Polymorphism Array Technology to Improve the Identification of Chromosomal Lesions in Leukemia

Acute leukemias are characterized by recurring chromosomal and genetic abnormalities that disrupt normal development and drive aberrant cell proliferation and survival. Identification of these abnormalities plays important role in diagnosis, risk assessment and patient classification. Until the last decade methods to detect these aberrations have included genome wide approaches, such as conventional cytogenetics, but with a low sensitivity (5-10%), or gene candidate approaches, such as fluorescent in situ hybridization, having a greater sensitivity but being limited to only known regions of the genome. Single nucleotide polymorphism (SNP) technology is a screening method that has revolutionized our way to find genetic alterations, enabling linkage and association studies between SNP genotype and disease as well as the identification of alterations in DNA content on a whole genome scale. The adoption of this approach for the study of lymphoid and myeloid leukemias contributed to the identification of novel genetic alterations, such as losses/gains/uniparental disomy not visible by cytogenetics and implicated in pathogenesis, improving risk assessment and patient classification and in some cases working as targets for tailored therapies. In this review, we reported recent advances obtained in the knowledge of the genomic complexity of chronic myeloid leukemia and acute leukemias thanks to the use of high-throughput technologies, such as SNP array.
Stability and optimization of the golden-section adaptive control

The stability of the characteristic model-based golden-section adaptive control is discussed and the relationship between the controller parameters l1, l2 and the closed-loop dynamic performance is analyzed. It is shown that l1, l2 are closely related to the parameters bounds in the characteristic model. For the typical case of a second order linear system with a pair of stable eigenvalues, it is proved that l2 ≈ 0.618 corresponds to the smallest spectral radius in the worst case. By describing the slowly time-varying property in an explicit inequality form, a bridge is built between the instantaneous stability and the time-varying stability. A numerical example is given to show the advantage of the golden-section adaptive controller over that of the classical model reference adaptive control law.
Automatic Service Composition via Model Checking

Web service composition is the process of constructing a set of Web services which, when invoked with some user input in a particular order, can produce the output to the user's requirements. This paper proposes a novel model checking based approach for automated service composition. Modeling services as a set of interleaved processes in a class of process algebra, we formulate service composition as model checking asserted on a specific type of property on the model. We show that, under this formulation, correct composition workflows can be constructed from the counter-examples provided by model checking. With a case study on online hotel booking services, we demonstrate that the proposed approach can support directed a cyclic composition graphs and the generated composition graphs are automatically verified.
Pan-Arctic Trends in Terrestrial Dissolved Organic Matter from Optical Measurements

Climate change is causing extensive warming across arctic regions resulting in permafrost degradation, alterations to regional hydrology, and shifting amounts and composition of dissolved organic matter (DOM) transported by streams and rivers. Here, we characterize the DOM composition and optical properties of the six largest arctic rivers draining into the Arctic Ocean to examine the ability of optical measurements to provide meaningful insights into terrigenous carbon export patterns and biogeochemical cycling. The chemical composition of aquatic DOM varied with season, spring months were typified by highest lignin phenol and dissolved organic carbon (DOC) concentrations with greater hydrophobic acid content, and lower proportions of hydrophilic compounds, relative to summer and winter months. Chromophoric DOM (CDOM) spectral slope (S275-295) tracked seasonal shifts in DOM composition across river basins. Fluorescence and parallel factor analysis identified seven components across the six Arctic rivers. The ratios of ‘terrestrial humic-like’ versus ‘marine humic-like’ fluorescent components co-varied with lignin monomer ratios over summer and winter months, suggesting fluorescence may provide information on the age and degradation state of riverine DOM. CDOM absorbance (a350) proved a sensitive proxy for lignin phenol concentrations across all six river basins and over the hydrograph, enabling for the first time the development of a single pan-arctic relationship between a350 and terrigenous DOC (R2 = 0.93). Combining this lignin proxy with high-resolution monitoring of a350, pan-arctic estimates of annual lignin flux were calculated to range from 156 to 185 Gg, resulting in shorter and more constrained estimates of terrigenous DOM residence times in the Arctic Ocean (spanning 7 months to 2½ years). Furthermore, multiple linear regression models incorporating both absorbance and fluorescence variables proved capable of explaining much of the variability in lignin composition across rivers and seasons. Our findings suggest that synoptic, high-resolution optical measurements can provide improved understanding of northern high-latitude organic matter cycling and flux, and prove an important technique for capturing future climate-driven changes.
Spatiotemporal Reconfiguration of Large-Scale Brain Functional Networks during Propofol-Induced Loss of Consciousness

Applying graph theoretical analysis of spontaneous BOLD fluctuations in functional magnetic resonance imaging (fMRI), we investigated whole-brain functional connectivity of 11 healthy volunteers during wakefulness and propofol-induced loss of consciousness (PI-LOC). After extraction of regional fMRI time series from 110 cortical and subcortical regions, we applied a maximum overlap discrete wavelet transformation and investigated changes in the brain's intrinsic spatiotemporal organization. During PI-LOC, we observed a breakdown of subcortico-cortical and corticocortical connectivity. Decrease of connectivity was pronounced in thalamocortical connections, whereas no changes were found for connectivity within primary sensory cortices. Graph theoretical analyses revealed significant changes in the degree distribution and local organization metrics of brain functional networks during PI-LOC: compared with a random network, normalized clustering was significantly increased, as was small-worldness. Furthermore we observed a profound decline in long-range connections and a reduction in whole-brain spatiotemporal integration, supporting a topological reconfiguration during PI-LOC. Our findings shed light on the functional significance of intrinsic brain activity as measured by spontaneous BOLD signal fluctuations and help to understand propofol-induced loss of consciousness.
(Not) Talking Politics: Motivations and Strategies for Avoiding the Expression of Political Opinions

The notion that a healthy democracy requires a public who discusses politics is based on the assumption that discussions expose members of the public to the perspectives of others. The contentious nature of politics, and the propensity for political conversations to arouse emotions, however, suggest that people may prefer to withhold their true opinions during such encounters. Combining interpersonal and political communication theories, this study details the motivations and strategies used in avoiding the expression of political opinions. The sharing of political points of view is essential to democracy. This work uses qualitative and quantitative analyses to uncover how and why people avoid it.
A genealogy of control structures

The issue of program control structures has had a history of heated controversy. To put this issue on a solid footing, this paper reviews numerous theoretical results on control structures and explores their practical implications. The classic result of Böhm and Jacopini on the theoretical completeness of if-then-else and while-do is discussed. Several recent ideas on control structures are then explored. These include a review of various other control structures, results on time/space limitations, and theorems relating the relative power of control structures under several notions of equivalence. In conclusion, the impact of theoretical results on the practicing programmer and the importance of one-in, one-out control structures as operational abstractions are discussed. It is argued further that there is insufficient evidence to warrant more than if-then-else, while-do, and their variants.
Model Predictive Control for Dynamic Resource Allocation Dragos

The present paper develops a simple, easy to interpret algorithm for a large class of dynamic allocation problems with unknown, volatile demand. Potential applications include ad display problems and network revenue management problems. The algorithm operates in an online fashion and relies on reoptimization and forecast updates. The algorithm is robust (as witnessed by uniform worst-case guarantees for arbitrarily volatile demand) and in the event that demand volatility (or equivalently deviations in realized demand from forecasts) is not large, the method is simultaneously optimal. Computational experiments, including experiments with data from real-world problem instances, demonstrate the practicality and value of the approach. From a theoretical perspective, we introduce a new device—a balancing property—that allows us to understand the impact of changing bases in our scheme. 1. Introduction. The present paper considers an archetypal dynamic allocation problem that captures a swathe of disparate applications in revenue management and e-commerce. Informally, the class of problems we consider can be described as follows: we are given a bipartite graph consisting of a set of I sources and A sinks, together with E edges from the sources to the sinks. Every source node i receives " demand " over time. The rate at which demand arrives is described by a general stochastic process. An allocation is an assignment of the demand arriving at each of the source nodes to the sinks they are connected with. This allocation may change over time; hence the dynamic moniker. For every unit of demand allocated along edge e (connecting some source iï¿¿eï¿¿ to some sink aï¿¿eï¿¿), we receive a reward of p e. In addition, this unit allocation will consume varying quantities of each of K distinct resources described by a vector A e ∈ ï¿¿ K +. We begin with an initial allocation of each of the K resources and must allocate demand over time in a manner that maximizes revenues while consuming no more than the initial allocation of resources. The key source of uncertainty in this model comes from the stochastic demand rate processes; in practical settings even specifying such a process is a potentially nontrivial task. The abstract allocation model we describe can capture a number of applications of broad interest. Two examples that are of particular interest in revenue management (RM) are the following: (i) The network revenue management (NRM) problem. This is a generic high-dimensional allocation problem encountered in industries ranging from …
On Interoperation among User-driven and System-driven Parallel Languages

Modern parallel codes are often written as a collection of several diverse modules. Different programming languages might be the best or natural fit for each of these modules or for different libraries that are used together in an application. For such applications, the restriction of implementing the entire application in a single parallel language may impact the application’s performance and programmer’s productivity negatively. This paper studies interoperation among parallel languages that differ with respect to the driver of program execution. We describe the challenges in enabling interoperation among userdriven and system-driven languages, and present techniques for managing important attributes of a program, such as the control flow, resource sharing, and data sharing, in an interoperable environment. We also present a generalized framework that enables interoperation between two production languages, MPI and Charm++. Finally, we study the application of the presented techniques and demonstrate the benefits of interoperation through several case studies using production codes including CHARM, EpiSimdemics, NAMD, FFTW, MPI-IO and ParMETIS, executed on IBM Blue Gene/Q and Cray XE6.
A Parallel Implementation of the 2D Wavelet Transform Using CUDA

There is a multicore platform that is currently concentrating an enormous attention due to its tremendous potential in terms of sustained performance: the NVIDIA Tesla boards. These cards intended for general-purpose computing on graphic processing units (GPGPUs) are used as data-parallel computing devices. They are based on the Computed Unified Device Architecture (CUDA) which is common to the latest NVIDIA GPUs. The bottom line is a multicore platform which provides an enormous potential performance benefit driven by a non-traditional programming model. In this paper we try to provide some insight into the peculiarities of CUDA in order to target scientific computing by means of a specific example. In particular, we show that the parallelization of the two-dimensional fast wavelet transform for the NVIDIA Tesla C870 achieves a speedup of 20.8 for an image size of 8192x8192, when compared with the fastest host-only version implementation using OpenMP and including the data transfers between main memory and device memory.
2-10 KeV luminosity of high - mass binaries as a gauge of ongoing star - formation rate

Based on recent work on spectral decomposition of the emission of star-forming galaxies, we assess whether the inte- grated 2−10 keV emission from high-mass X-ray binaries (HMXBs), L HMXB−10 , can be used as a reliable estimator of ongoing star formation rate (SFR). Using a sample of 46 local (z < 0.1) star-forming galaxies, and spectral modeling of ASCA, BeppoSAX, and XMM-Newton data, we demonstrate the existence of a linear SFR -L HMXB−10 relation which holds over ∼5 decades in X-ray luminosity and SFR. The total 2−10 keV luminosity is not a precise SFR indicator because at low SFR (i.e., in normal and moderately-starbursting galaxies) it is substantially affected by the emission of low-mass X-ray binaries, which do not trace the current SFR due to their long evolution lifetimes, while at very high SFR (i.e., for very luminous FIR-selected galaxies) it is frequently affected by the presence of strongly obscured AGNs. The availability of purely SB-powered galaxies - whose 2−10 keV emission is mainly due to HMXBs - allows us to properly calibrate the SFR -L HMXB−10 relation. The SFR -L HMXB−10 relation holds also for distant (z ∼ 1) galaxies in the Hubble Deep Field North sample, for which we lack spectral information, but whose SFR can be estimated from deep radio data. If confirmed by more detailed observations, it may be possible to use the deduced relation to identify distant galaxies that are X-ray overluminous for their (independently estimated) SFR ,a nd are therefore likely to hide strongly absorbed AGNs.