Miracle-dz/UniFAR-FTUs huggingface dataset:
Notice of RetractionIdentifying the Key ways of Organizational Learning for Enhancing Logistic Capability

To identify effective ways of organizational learning, this paper makes a case study of the material delivery center in a Chinese large-scale steel enterprise. And three key ways of organizational learning for enhancing logistics capability for manufacturing enterprise are summarized on the basis of resource-based view and organizational learning theory. The result of case study shows that successfully implementing systematic thinking, innovative experiment, and organizational memory can efficiently help enhance logistics capability, which contributes to better efficiency and effectiveness of exploiting logistic resources, thus significantly improving organizational logistic performance.
Collecting Protein Biomarkers in Breath Using Electret Filters: A Preliminary Method on New Technical Model and Human Study

Biomarkers in exhaled breath are useful for respiratory disease diagnosis in human volunteers. Conventional methods that collect non-volatile biomarkers, however, necessitate an extensive dilution and sanitation processes that lowers collection efficiencies and convenience of use. Electret filter emerged in recent decade to collect virus biomarkers in exhaled breath given its simplicity and effectiveness. To investigate the capability of electret filters to collect protein biomarkers, a model that consists of an atomizer that produces protein aerosol and an electret filter that collects albumin and carcinoembryonic antigen-a typical biomarker in lung cancer development- from the atomizer is developed. A device using electret filter as the collecting medium is designed to collect human albumin from exhaled breath of 6 volunteers. Comparison of the collecting ability between the electret filter method and other 2 reported methods is finally performed based on the amounts of albumin collected from human exhaled breath. In conclusion, a decreasing collection efficiency ranging from 17.6% to 2.3% for atomized albumin aerosol and 42% to 12.5% for atomized carcinoembryonic antigen particles is found; moreover, an optimum volume of sampling human exhaled breath ranging from 100 L to 200 L is also observed; finally, the self-designed collecting device shows a significantly better performance in collecting albumin from human exhaled breath than the exhaled breath condensate method (p<0.05) but is not significantly more effective than reported 3-stage impactor method (p>0.05). In summary, electret filters are potential in collecting non-volatile biomarkers in human exhaled breath not only because it was simpler, cheaper and easier to use than traditional methods but also for its better collecting performance.
On the Formation of Extended Galactic Disks by Tidally Disrupted Dwarf Galaxies

We explore the possibility that extended disks, such as that recently discovered in M31, are the result of a single dwarf (109-1010 M☉) satellite merger. We conduct N-body simulations of dwarf NFW halos with embedded spheroidal stellar components on coplanar, prograde orbits in an M31-like host galaxy. As the orbit decays due to dynamical friction and the system is disrupted, the stellar particles relax to form an extended, exponential-disk-like structure that spans the radial range 30-200 kpc. The disk scale length Rd correlates with the initial extent of the stellar component within the satellite halo: the more embedded the stars, the smaller the resulting disk scale length. If the progenitors start on circular orbits, the kinematics of the stars that make up the extended disk have an average rotational motion that is 30-50 km s-1 lower than the host's circular velocity. For dwarf galaxies moving on highly eccentric orbits (e ≃ 0.7), the stellar debris exhibits a much lower rotational velocity. Our results imply that extended galactic disks might be a generic feature of the hierarchical formation of spiral galaxies such as M31 and the Milky Way.
CONTINUOUS DIAGNOSIS OF DISCRETE-EVENT SYSTEMS

This paper presents a diagnostic technique that subsumes two complementary approaches to diagnosis of discrete-event systems (DESs), namely the diagnoser approach and the active system approach. The more significant shortcomings of such approaches are, on the one side, the need for the generation of the global system model and, on the other, the completion of the system observation before starting the diagnostic task. The former makes the application of the diagnoser approach prohibitive in real contexts, where the system model is too large to be generated, even off-line. The latter makes it impossible to the active system approach to perform diagnosis while monitoring. The proposed technique, which overcomes such limitations, copes with a generalized class of DESs that integrate both synchronous and asynchronous behavior.
Vision feature image retrieval using Daubechies wavelet

his paper proposed an image retrieval method using the Daubechies wavelet and stage treatment. This algorithm decomposes the color information of the image using Daubechies wavelet and constructs the eigenvector using both the low frequency component and the high frequency component. Three features: variance, invariant moment and angle of the eigenvector are used to compare the similarity between the retrieval image and the images in the database. The experiment demonstrates the effectiveness of this method and its time efficiency.
A Model-based Self-tuning Controller forThermoacoustic Instability

Abstract Active Control of thermoacoustic instabilities in continuous premixed combustion processes is being increasingly investigated for operating at lean low NOx conditions. Recently, we have developed a model-based approach for active control design which accounts for the underlying acoustics, heat release dynamics, and sensor and actuator dynamics. While this model captures a number of the dominant dynamic features of a premixed laminar combustor, there are a number of uncertainties associated with it as well. In this paper, we study the sensitivity of this model with respect to parametric uncertainties, and the efficacy of a fixed control design for suppressing pressure oscillations. We show that under certain conditions, the fixed controller is inadequate and present a self-tuning controller which is capable of delivering the desired performance in the presence of these uncertainties. The controller proposed is based on a rigorous analytical foundation, and is shown through simulation results to le.
Introducing a Distributed Cloud Architecture with Efficient Resource Discovery and Optimal Resource Allocation

Cloud computing is an emerging field in computer science. Users are utilizing less of their own existing resources, while increasing usage of cloud resources. With the emergence of new technologies such as mobile devices, these devices are usually under-utilized, and can provide similar functionality to a cloud provided they are properly configured and managed. This paper proposes a Distributed Cloud Architecture to make use of independent resources provided by the devices/users. Resource discovery and allocation is critical in designing an efficient and practical distributed cloud. We propose using multi-valued distributed hash tables for efficient resource discovery. Leveraging the fact that there are many users providing resources such as CPU and memory, we define these resources under one key to easily locate devices with equivalent resources. We then propose a new auction mechanism, using a reserve bid formulated rationally by each user for the optimal allocation of discovered resources. Then we discuss how the Nash Equilibrium is achieved based on user requirements.
Quantifying uncertainty in genotype calls

MOTIVATION Genome-wide association studies (GWAS) are used to discover genes underlying complex, heritable disorders for which less powerful study designs have failed in the past. The number of GWAS has skyrocketed recently with findings reported in top journals and the mainstream media. Microarrays are the genotype calling technology of choice in GWAS as they permit exploration of more than a million single nucleotide polymorphisms (SNPs) simultaneously. The starting point for the statistical analyses used by GWAS to determine association between loci and disease is making genotype calls (AA, AB or BB). However, the raw data, microarray probe intensities, are heavily processed before arriving at these calls. Various sophisticated statistical procedures have been proposed for transforming raw data into genotype calls. We find that variability in microarray output quality across different SNPs, different arrays and different sample batches have substantial influence on the accuracy of genotype calls made by existing algorithms. Failure to account for these sources of variability can adversely affect the quality of findings reported by the GWAS. RESULTS We developed a method based on an enhanced version of the multi-level model used by CRLMM version 1. Two key differences are that we now account for variability across batches and improve the call-specific assessment of each call. The new model permits the development of quality metrics for SNPs, samples and batches of samples. Using three independent datasets, we demonstrate that the CRLMM version 2 outperforms CRLMM version 1 and the algorithm provided by Affymetrix, Birdseed. The main advantage of the new approach is that it enables the identification of low-quality SNPs, samples and batches. AVAILABILITY Software implementing of the method described in this article is available as free and open source code in the crlmm R/BioConductor package. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Accuracy and performance of linear unmixing techniques for detecting minerals on OMEGA/MEx

Detecting minerals on a huge hyperspectral dataset (> To) is a difficult task that we proposed to address using linear unmixing techniques. We test different algorithms with positivity constrains on a typical Martian hyperspectral image of the Syrtis Major volcanic complex. The usefulness of additional constraints, such as sparsity and sum-to-one constrains are discussed. We compare the results with a supervised detection technique based on band ratio.
Using UML to Model Educational Games

There has been a constant increase in the number of serious games. In recent years, they have become extremely important within the scientific community and their repercussions on industry have been reflected in exponential growth in terms of their economic impact. The term serious game covers an extremely wide range of video games all with very different purposes and with many different areas of application. One of the most prolific areas is the field of education and many research papers have highlighted the benefits of video games in the classroom. Despite the complexity of educational game development, however, mainly because of the communication difficulties that exist between the technical team and the teaching team, very little research has been conducted to find a suitable design language for both parties. This article proposes the use of formall software planning within the educational games community, concretely an adaptation of UML (Unified Modeling Language) to educational games. This proposal is illustrated with a graphic adventure that the authors are developing to help second grade primary school students with their reading comprehension.
Calculations of B1 distribution, SNR, and SAR for a surface coil adjacent to an anatomically‐accurate human body model

Calculations of the radiofrequency magnetic (B1) field, SAR, and SNR as functions of frequency between 64 and 345 MHz for a surface coil against an anatomically‐accurate human chest are presented. Calculated B1 field distributions are in good agreement with previously‐published experimental results up to 175 MHz, especially considering the dependence of field behavior on subject anatomy. Calculated SNR in the heart agrees well with theory for low frequencies (nearly linear increase with B0 field strength). Above 175 MHz, the trend in SNR with frequency begins to depend largely on location in the heart. At all frequencies, present limits on local (1 g) SAR levels are exceeded before limits on whole‐body average limits. At frequencies above 175 MHz, limits on SAR begin to be an issue in some common imaging sequences. These results are relevant for coils and subjects similar to those modeled here. Magn Reson Med 45:692–699, 2001. © 2001 Wiley‐Liss, Inc.
A Distributed Heuristic for Energy-Efficient Multirobot Multiplace Rendezvous

We consider the problem of finding a set of trajectories for a heterogeneous group of mobile robots, such that a single service robot can rendezvous with every other member of the team in a prescribed order, and the total travel cost is minimized. We present a simple heuristic controller that runs independently on each robot, yet is guaranteed to achieve an approximation to global solution in bounded time linear in population size. Simulation experiments empirically show that the method finds approximated solutions of near-optimal quality on average.
A New Chaos-Based Cryptosystem for Secure Transmitted Images

This paper presents a novel and robust chaos-based cryptosystem for secure transmitted images and four other versions. In the proposed block encryption/decryption algorithm, a 2D chaotic map is used to shuffle the image pixel positions. Then, substitution (confusion) and permutation (diffusion) operations on every block, with multiple rounds, are combined using two perturbed chaotic PWLCM maps. The perturbing orbit technique improves the statistical properties of encrypted images. The obtained error propagation in various standard cipher block modes demonstrates that the proposed cryptosystem is suitable to transmit cipher data over a corrupted digital channel. Finally, to quantify the security level of the proposed cryptosystem, many tests are performed and experimental results show that the suggested cryptosystem has a high security level.
Indirect Genetic Effects for Survival in Domestic Chickens (Gallus gallus) Are Magnified in Crossbred Genotypes and Show a Parent-of-Origin Effect

Through social interactions, individuals can affect one another’s phenotype. The heritable effect of an individual on the phenotype of a conspecific is known as an indirect genetic effect (IGE). Although IGEs can have a substantial impact on heritable variation and response to selection, little is known about the genetic architecture of traits affected by IGEs. We studied IGEs for survival in domestic chickens (Gallus gallus), using data on two purebred lines and their reciprocal cross. Birds were kept in groups of four. Feather pecking and cannibalism caused mortality, as beaks were kept intact. Survival time was shorter in crossbreds than in purebreds, indicating outbreeding depression and the presence of nonadditive genetic effects. IGEs contributed the majority of heritable variation in crossbreds (87 and 72%) and around half of heritable variation in purebreds (65 and 44%). There was no evidence of dominance variance, neither direct nor indirect. Absence of dominance variance in combination with considerable outbreeding depression suggests that survival is affected by many loci. Direct–indirect genetic correlations were moderately to highly negative in crossbreds (−0.37 ± 0.17 and −0.83 ± 0.10), but low and not significantly different from zero in purebreds (0.20 ± 0.21 and −0.28 ± 0.18). Consequently, unlike purebreds, crossbreds would fail to respond positively to mass selection. The direct genetic correlation between both crosses was high (0.95 ± 0.23), whereas the indirect genetic correlation was moderate (0.41 ± 0.26). Thus, for IGEs, it mattered which parental line provided the sire and which provided the dam. This indirect parent-of-origin effect appeared to be paternally transmitted and is probably Z chromosome linked.
A robust sequential CO 2 emissions strategy based on optimal control of atmospheric CO 2 concentrations

This paper formally introduces the concept of mitigation as a stochastic control problem. This is illustrated by applying a digital state variable feedback control approach known as Non-Minimum State Space (NMSS) control to the problem of specifying carbon emissions to control atmospheric CO2 concentrations in the presence of uncertainty. It is shown that the control approach naturally lends itself to integrating both anticipatory and reflexive mitigation strategies within a single unified framework. The framework explicitly considers the closed-loop nature of climate mitigation, and employs a policy orientated optimisation procedure to specify the properties of this closed-loop system. The product of this exercise is a control law that is suitably conditioned to regulate atmospheric CO2 concentrations through assimilating online information within a 25-year review cycle framework. It is shown that the optimal control law is also robust when faced with significant levels of uncertainty about the functioning of the global carbon cycle.
Spectral mapping of the spiral structures in IP Pegasi on the decline from an outburst

We report eclipse mapping of time-resolved spectroscopy of the dwarf nova IP Pegasi on the late decline from the 1993 May outburst. The continuum light curves exhibit an asymmetric 'V' shape with broad bulges and results in eclipse maps with two asymmetric arcs extended both in radius [R(0.2–0.6)RL1, where RL1 is the distance from the disc centre to the inner Lagrangian point] and in azimuth (by 90°), interpreted as a two-armed spiral shock. The spiral arms are thus still visible some 8 d after the onset of the outburst. Their fractional contribution to the continuum emission, 12 per cent of the total light, is similar to that measured close to outburst maximum, whereas their orientation is rotated by 58° with respect to the spirals seen in the eclipse map at outburst maximum. The radial temperature distribution computed from the spiral-free disc regions is flat, with temperatures of 5000 K at all disc radii. Velocity-resolved light curves across the Hα and the He i lines show the classical rotational disturbance, with the blue side of the line being eclipsed earlier than the red side. The differences between the Hα and the He i maps are significant. The spiral arms are clearly seen in the He i maps, with the receding arm being stronger on the red side, while the approaching arm is stronger on the blue side of the line. The analysis of the Hα maps suggests that this emission arises mainly from a large and vertically extended region that we interpret as an outflowing (and spiralling) disc wind. The Hα emission-line surface brightness is flat in the inner disc regions (IR-0.3 for R 0.3RL1). The spectrum of the uneclipsed light is dominated by a strong, blueshifted and narrow Hα emission line superimposed on a red continuum and can be understood as a combination of emission from an M5V secondary star plus optically thin emission from the outer parts of the vertically extended disc wind. The inner disc regions show an emission-line spectrum with a strong [equivalent width EW=(100±2) A] and broad (fullwidth zero intensity3000 km s-1) Hα component superimposed on a flat continuum. This is in marked contrast with the results from the spectral mapping of nova-like variables of comparable inclination and mass ratio and suggests that intrinsically different physical conditions hold in the inner disc regions of outbursting dwarf novae and nova-like systems.
Parallel UPGMA Algorithm on Graphics Processing Units Using CUDA

The construction of phylogenetic trees is important for the computational biology, especially for the development of biological taxonomies. UPGMA is one of the most popular heuristic algorithms for constructing ultrametric trees (UT). Although the UT constructed by the UPGMA often is not a true tree unless the molecular clock assumption holds, the UT is still useful for the clocklike data. However, a fundamental problem with the previous implementations of this method is its limitation to handle large tax a sets within a reasonable time. In this paper, we present GPU-UPGMA which can provide a fast construction of very large datasets for biologists. Experimental results show that GPU-UPGMA obtains about 95 times speedup on NVIDIA Tesla C2050 GPU over the 2.13 GHz CPU implementation.
Better ARP handling with InSPired SDN switches

SDN research is moving towards enabling the delegation of parts of control functions to the network elements. In recent work we analytically evaluated the benefit in terms of ARP data traffic load reduction as well as control channel interaction reduction when delegating the generation of ARP replies. In this paper we describe the corresponding control program and network configuration to handle ARP traffic in a software-defined network leveraging programmable in-switch packet generation capabilities. We also discuss potential optimizations and implementation options.
Divergent evolutions of trinucleotide polymerization revealed by an archaeal CCA‐adding enzyme structure

CCA‐adding enzyme [ATP(CTP):tRNA nucleotidyltransferase], a template‐independent RNA polymerase, adds the defined ‘cytidine–cytidine–adenosine’ sequence onto the 3′ end of tRNA. The archaeal CCA‐adding enzyme (class I) and eubacterial/eukaryotic CCA‐adding enzyme (class II) show little amino acid sequence homology, but catalyze the same reaction in a defined fashion. Here, we present the crystal structures of the class I archaeal CCA‐adding enzyme from Archaeoglobus fulgidus, and its complexes with CTP and ATP at 2.0, 2.0 and 2.7 Å resolutions, respectively. The geometry of the catalytic carboxylates and the relative positions of CTP and ATP to a single catalytic site are well conserved in both classes of CCA‐adding enzymes, whereas the overall architectures, except for the catalytic core, of the class I and class II CCA‐adding enzymes are fundamentally different. Furthermore, the recognition mechanisms of substrate nucleotides and tRNA molecules are distinct between these two classes, suggesting that the catalytic domains of class I and class II enzymes share a common origin, and distinct substrate recognition domains have been appended to form the two presently divergent classes.
E-ITRC Protocol with Long & Adjustable Range on Underwater Acoustic Sensor Network

The underwater sensor network environment differs substantially from a terrestrial sensor network in the aspect of the communication medium so Acoustic communication is alternative, which is relatively very slow and narrow bandwidth compared with Radio Frequency. In this paper, we propose an underwater sensor network architecture and then present the essential routing algorithm focused on minimum response time as well as energy efficiency. The characteristic of our proposed underwater sensor network is that there are a long-range communication node on the surface of the water and adjustable transmission range on underwater nodes. The surface station equipped with solar panels may request queries to underwater sensor nodes with long-range transmission. In order to gather messages from underwater sensor node, we use underwater relay nodes in the midst of water using Energy efficiency & Innovative Time Reduction Communication (E-ITRC) protocol. Our proposed E-ITRC protocol can find the optimal path to save energy and minimize response time. The simulation results clearly show that our protocol is a fast, energy efficient and fault-tolerant method in an underwater environment.