Miracle-dz/UniFAR-FTUs huggingface dataset:
Hyperspectral image classification by Multi-Scale Vector Tunnel

The spectral matching, statistical and kernel based methods are the most widely known classification algorithms for hyperspectral imaging. Spectral matching algorithms try to identify the similarity of the unknown spectral signature of test pixels with the expected signature. In this study, an efficient spectral similarity method employing Multi-Scale Vector Tunnel Algorithm (MS-VTA) for supervised classification of the materials in hyperspectral imagery is introduced. With the proposed algorithm, a simple spectral similarity based decision rule using some reference data or spectral signature is formed and compared with the Euclidian Distance (ED) and the Spectral Angle Map (SAM) classifiers. The prediction of multi-level upper and lower spectral boundaries of spectral signatures for all classes across spectral bands constitutes the basic principle of the proposed algorithm.
Towards multidimensional subspace skyline analysis

The skyline operator is important for multicriteria decision-making applications. Although many recent studies developed efficient methods to compute skyline objects in a given space, none of them considers skylines in multiple subspaces simultaneously. More importantly, the fundamental problem on the semantics of skylines remains open: Why and in which subspaces is (or is not) an object in the skyline? Practically, users may also be interested in the skylines in any subspaces. Then, what is the relationship between the skylines in the subspaces and those in the super-spaces? How can we effectively analyze the subspace skylines? Can we efficiently compute skylines in various subspaces and answer various analytical queries? In this article, we tackle the problem of multidimensional subspace skyline computation and analysis. We explore skylines in subspaces. First, we propose the concept of Skycube, which consists of skylines of all possible nonempty subspaces of a given full space. Once a Skycube is materialized, any subspace skyline queries can be answered online. However, Skycube cannot fully address the semantic concerns and may contain redundant information. To tackle the problem, we introduce a novel notion of skyline group which essentially is a group of objects that coincide in the skylines of some subspaces. We identify the decisive subspaces that qualify skyline groups in the subspace skylines. The new notions concisely capture the semantics and the structures of skylines in various subspaces. Multidimensional roll-up and drill-down analysis is introduced. We also develop efficient algorithms to compute Skycube, skyline groups and their decisive subspaces. A systematic performance study using both real data sets and synthetic data sets is reported to evaluate our approach.
HYBRIDIZATION OF PARTICLE SWARM OPTIMIZATION AND ANT COLONY OPTIMIZATION TECHNIQUE TO SOLVE THE DISTRIBUTION PLANNING PROBLEM OF THE CROSS-DOCKING NETWORK

Cross-docking is a logistic technique in which distribution centers are the transfer points to coordinate the continuous physical flow through supply chain with no storage. The harmonization of this system in a network of cross-docks with customers and suppliers requires a effective planning. This paper addresses the distribution planning problem of cross-docking network considering the transportation cost and the operation cost that are incurred in the consolidation process at the cross-docking center. Hybridization of Ant Colony Optimization and Discrete Particle Swarm Optimization technique is proposed to solve the problem. Experimental results demonstrate the potency of the proposed algorithm achieving remarkable results .
An intelligent nondestructive detection method based on wavelet processing and principal component analysis

To improve the performance of the acoustic nondestructive detection, an intelligent method was put forward. By using the wavelet transform (WT) with the optimal basis, the original acoustic resonance spectroscopy (ARS) signal was projected to the wavelet subspace at first, and then the signal was represented by a matrix of wavelet coefficients. To reduce the amount of calculation, the principal component analysis (PCA) was performed: The feature vector was obtained by Karhunen-Loeve transformation (K-L transformation), serving as the input of the neural network. Finally, a radial basis function (RBF) neural network was developed as a classifier using the recursive localized least square method. Simulation and experimental results showed that the proposed method is accurate and have good generalization ability.
An Optimal Temporally Expressive Planner: Initial Results and Application to P2P Network Optimization

Temporally expressive planning, an important class of temporal planning, has attracted much attention lately. Temporally expressive planning is difficult; few existing planners can solve them, as they have highly concurrent actions. We propose an optimal approach to temporally expressive planning based on a SAT formulation of the problem, finding solutions with the shortest time spans. Our experiments on several temporally expressive domains showed that our planner is able to optimally solve many instances in a reasonable amount of time, comparing favorably to existing temporally expressive planners. Our second result is a temporally expressive planning problem formulation of the Peer-to-Peer (P2P) network communications. In addition to demonstrating a better performance of our new method than the only existing temporally expressive planners on several temporally expressive problem domains, we apply our new planner to find optimal communication schedules for P2P networks. Our results will be potentially useful for designing efficient communication protocols in P2P networks.
BMM-Based Chinese Word Segmentor with Word Support Model for the SIGHAN Bakeoff 2006

This paper describes a Chinese word segmentor (CWS) for the third International Chinese Language Processing Bakeoff (SIGHAN Bakeoff 2006). We participate in the word segmentation task at the Microsoft Research (MSR) closed testing track. Our CWS is based on backward maximum matching with word support model (WSM) and contextual-based Chinese unknown word identification. From the scored results and our experimental results, it shows WSM can improve our previous CWS, which was reported at the SIGHAN Bakeoff 2005, about 1% of F-measure.
Prevalence and Risk Factors of HIV, Syphilis, Hepatitis B and C Among Female Prisoners in Isfahan, Iran

Background Female prisoners are at risk of acquiring sexually transmitted infections (STIs). There has been no previous study regarding the epidemiological status of STIs among female prisoners in Isfahan, central Iran. Objectives The aim of this study was to investigate the prevalence and risk factors of the aforementioned infections among women incarcerated in the central prison, Isfahan, to determine appropriate prevention measures. Patients and Methods In a cross-sectional study, all of the 163 women incarcerated in the central prison, Isfahan in 2009, were voluntarily enrolled by the census method. After completing a checklist consisting of demographic, social, and risk factors, a 5ml blood sample was taken from each individual. The sera were analyzed for markers of the hepatitis B virus (HBV; HBsAg, HBsAb, HBcAb), hepatitis C virus (HCV; HCV antibodies), human immunodeficiency virus (HIV; HIV antibodies), and syphilis (RPR). Confirmatory tests were performed on HCV antibody-positive cases. Results The mean age of the participants in the study was 34.54 ± 11.2 years old, 94.3% of these women were Iranian, and many of them had only a primary level of education. The prevalence of HBsAg, HBcAb, HBsAb, and HCV antibodies were; 1.2%, 7.4%, 12.9% and 7.4% respectively. No positive RPR or HIV antibodies were detected. Conclusions A significant relationship was seen between the HCV antibody, drug injection and illegal sex in the women, and also between HBc-Ab and drug injection. Regular screening, educational programs, and facilitation of access to suitable treatment care should be widely implemented in the prison population. Testing for immunity against HBV should be considered on admission, and afterwards vaccination of all prisoners and an appropriate preventative approach should be applied.
Intershell Conductance of Multiwalled Carbon Nanotubes

Multiprobe electrical transport measurements on individual multiwalled carbon nanotubes (MWNTs) are described. Using a method by which single carbon shells can be removed from a MWNT [1,2], the intershell contributions to the conductance can be separated from the intrashell contributions. This measurement directly probes the electronic coupling between shells, and clearly demonstrates the Arrhenius temperature dependence of this coupling.
Myocardial infarction in an urban population: worse long term prognosis for patients from less affluent residential areas

Study objective: The objective in this follow up study from the Malmö myocardial infarction register has been to assess whether long term survival following discharge after first myocardial infarction has any relation with the socioeconomic environment and to assess to what extent intra-urban differences in mortality from ischaemic heart disease can be accounted for by covariance with long term survival following discharge after acute myocardial infarction. Design: Register based surveillance study. Setting: Seventeen residential areas in the city of Malmö, Sweden. Participants: The cohort contains all 2931 male and 2083 female patients with myocardial infarction who were discharged for the first time between 1986–95 from Malmö University Hospital. Main results: During the on average 4.9 years of follow up 55% of the patients died. The sex adjusted and age adjusted all cause mortality rate/1000 patient years ranged between residential areas from 85.5 to 163.6. The area specific relative risk of death after discharge was associated with a low socioeconomic score, r=−0.56, p=0.018. Major risk factors for cardiovascular disease were more prevalent in areas with low socioeconomic score and low rates of survival. Of the intra-urban differences in mortality from ischaemic heart disease, 41% could be accounted for by differences with regard to the survival rate after discharge. Conclusions: The results are compatible with the hypothesis that the socioeconomic environment plays an important part in the survival rate of patients with myocardial infarction. To assess the preventive potential, the extent to which socioeconomic circumstances covary with severity of disease, respectively with the use and compliance with secondary preventive measures, needs to be evaluated.
Algorithm xxx: Padua2D: Lagrange Interpolation at Padua Points on Bivariate Domains

We present a stable and efficient Fortran implementation of polynomial interpolation at the “Padua points” on the square [−1, 1]. These points are unisolvent and their Lebesgue constant has minimal order of growth (log square of the degree). The algorithm is based on the representation of the Lagrange interpolation formula in a suitable orthogonal basis, and takes advantage of a new matrix formulation together with the machine-specific optimized BLAS subroutine DGEMM for the matrix-matrix product. Extension to interpolation on rectangles, triangles and ellipses is also described.
Generation of Peanut Drought Tolerant Plants by Pingyangmycin-Mediated In Vitro Mutagenesis and Hydroxyproline-Resistance Screening

In order to enlarge the potential resources of drought-tolerant peanuts, we conducted in vitro mutagenesis with Pingyangmycin (PYM) as the mutagen as well as directed screening on a medium supplemented with Hydroxyproline (HYP). After being extracted from mature seeds (cv. Huayu 20), the embryonic leaflets were cultured on somatic embryogenesis-induction medium with 4 mg/L PYM and the generated embryos were successively transferred to a germination medium with 4 and then 8 mmol/L HYP to screen HYP-tolerant plantlets. After that, these plantlets were grafted and transplanted to the experimental field. In the next generation, all seeds were sown in the field, and phenotype variation and trait segregation can be observed in most of the offspring (M2 generation). The M3 generation individuals were subjected to drought stress at the seedling stages. The activities of SOD and POD were substantially increased in eight offspring of 11 HYP-tolerant, regenerated plants than in their mutagenic parents. To determine the correlation between mutant phenotypes and genomic modification, we carried out a comparison of the DNA polymorphisms between the mutagenic parents and 13 M3 generation individuals from different HYP-tolerant, regenerated plants with SSR primers. Results showed that most mutants and parent plants had signs of polymorphisms. Under drought stress, some M3 generation individuals of 10 original HYP-tolerant, regenerated plants produced more pods than the mutagenic parent; twenty individuals among them produced >60 g pods/plant. M4-generation seeds were tested for quality characteristics by Near Infrared Spectroscopy (NIS) and nine individuals with higher protein content (>30%) and 21 individuals with higher oil content (>58%) were screened. We concluded that the use of PYM-based in vitro mutagenesis in combination with directed screening with HYP is effective for the creation of potential drought-tolerant mutants of peanut.
Clinical and Pathologic Features of Multifocal and Multicentric Breast Cancer in Chinese Women: A Retrospective Cohort Study

Purpose This study aims to analyze the clinical-pathological characteristics of multifocal and multicentric breast cancer (MMBC) in Chinese women. Methods Sixty-seven cases with MMBC were randomly collected and reviewed at seven hospitals in representative districts of China during 1999 to 2008. Results The incidence of MMBC in breast cancer in China was 1.75%. Compared to those with unifocal breast cancer, women with MMBC were more likely to have larger tumor size, lymph node metastasis (59.70% vs. 45.62%) and stage III to IV (46.26% vs. 21.10%). The peak age at onset of MMBC was 40 to 49 years old and has been gradually increasing during 1999 to 2008. Most of the MMBC women were treated with surgery and adjuvant therapy. Conclusion In China, the incidence of MMBC in breast cancer is significantly lower than that in Western countries. Compared to unifocal breast cancer, MMBC is biologically more aggressive. Most MMBC women underwent mastectomy, instead of breast conservation surgery.
Caenorhabditits elegans LRK-1 and PINK-1 Act Antagonistically in Stress Response and Neurite Outgrowth*

Mutations in two genes encoding the putative kinases LRRK2 and PINK1 have been associated with inherited variants of Parkinson disease. The physiological role of both proteins is not known at present, but studies in model organisms have linked their mutants to distinct aspects of mitochondrial dysfunction, increased vulnerability to oxidative and endoplasmic reticulum stress, and intracellular protein sorting. Here, we show that a mutation in the Caenorhabditits elegans homologue of the PTEN-induced kinase pink-1 gene resulted in reduced mitochondrial cristae length and increased paraquat sensitivity of the nematode. Moreover, the mutants also displayed defects in axonal outgrowth of a pair of canal-associated neurons. We demonstrate that in the absence of lrk-1, the C. elegans homologue of human LRRK2, all phenotypic aspects of pink-1 loss-of-function mutants were suppressed. Conversely, the hypersensitivity of lrk-1 mutant animals to the endoplasmic reticulum stressor tunicamycin was reduced in a pink-1 mutant background. These results provide the first evidence of an antagonistic role of PINK-1 and LRK-1. Due to the similarity of the C. elegans proteins to human LRRK2 and PINK1, we suggest a common role of both factors in cellular functions including stress response and regulation of neurite outgrowth. This study might help to link pink-1/PINK1 and lrk-1/LRRK2 function to the pathological processes resulting from Parkinson disease-related mutants in both genes, the first manifestations of which are cytoskeletal defects in affected neurons.
A Novel Radio Mode Identification Approach for Spectrum Sensing in Cognitive Radios

The paper suggests a radio mode identification algorithm for spectrum sensing that utilizes time frequency analysis and digital image processing techniques to identify various transmission parameters of the primary user. The classical spectrum sensing techniques only provide information about existence of spectrum holes in the spectrum band of interest. However the proposed approach enables the cognitive radio to identify spectral behavior of the primary users in addition to identifying the spectrum holes with greater accuracy. These parameters can be utilized to decide the suitability of the identified spectrum holes and predict pattern of spectrum usage in near future.
Estimation of Two-axis Synchronous Machine Parameters using Non-Deterministic Tools

Optimization is employed in this work to obtain the two-axis parameters of a typical solid-rotor synchronous machine. SSFR data is used to set-up the identification problem, leading to a fitness function that must be minimized. However, the function is plagued with local minima, making the parameter identification impossible with deterministic methods. Genetic algorithms have become an important tool to deal with local minima and software codes are readily available. Determination of the global/true minimum is not easy though since big computational resources are required even for relatively small problems. Moreover, the final minimum may not be found in spite of proper tuning of the genetic algorithm. Some tuning aspects are addressed in this work.
Structure of the DNA-binding domain of NgTRF1 reveals unique features of plant telomere-binding proteins

Telomeres are protein–DNA elements that are located at the ends of linear eukaryotic chromosomes. In concert with various telomere-binding proteins, they play an essential role in genome stability. We determined the structure of the DNA-binding domain of NgTRF1, a double-stranded telomere-binding protein of tobacco, using multidimensional NMR spectroscopy and X-ray crystallography. The DNA-binding domain of NgTRF1 contained the Myb-like domain and C-terminal Myb-extension that is characteristic of plant double-stranded telomere-binding proteins. It encompassed amino acids 561–681 (NgTRF1561–681), and was composed of 4 α-helices. We also determined the structure of NgTRF1561–681 bound to plant telomeric DNA. We identified several amino acid residues that interacted directly with DNA, and confirmed their role in the binding of NgTRF1 to telomere using site-directed mutagenesis. Based on a structural comparison of the DNA-binding domains of NgTRF1 and human TRF1 (hTRF1), NgTRF1 has both common and unique DNA-binding properties. Interaction of Myb-like domain with telomeric sequences is almost identical in NgTRF1561–681 with the DNA-binding domain of hTRF1. The interaction of Arg-638 with the telomeric DNA, which is unique in NgTRF1561–681, may provide the structural explanation for the specificity of NgTRF1 to the plant telomere sequences, (TTTAGGG)n.
Perforation Behavior of Balloon Fabric under Impact Load

A new composite fabric has been developed for a balloon envelope possessing both excellent strength and gas barrier as well as low density, and perforation behavior under impact load is presently focused. The perforation test was experimentally conducted to clarify the effect of loading rate on the fracture behavior, together with the tensile test to evaluate the strain rate effect on the strength of the present material. Rate dependence of the stress strain relation of the material was clearly identified; the strength is significantly increased while the strain at fracture is decreased with a rise of strain rate. This fact well explains the experimental results where perforation strength is almost independent of loading rate, but the behavior is much more brittle due to localized deformation around perforated region at impact loading. It is also found that delamination of inter-laminar fibers in the composite fabric is able to relieve stress concentration and will be served to prevent a brittle fracturing independent of loading rate.
Exploiting Causality for Selective Belief Filtering in Dynamic Bayesian Networks (Extended Abstract)

Dynamic Bayesian networks (DBNs) are a general model for stochastic processes with partially observed states. Belief filtering in DBNs is the task of inferring the belief state (i.e. the probability distribution over process states) based on incomplete and noisy observations. This can be a hard problem in complex processes with large state spaces. In this article, we explore the idea of accelerating the filtering task by automatically exploiting causality in the process. We consider a specific type of causal relation, called passivity, which pertains to how state variables cause changes in other variables. We present the Passivity-based Selective Belief Filtering (PSBF) method, which maintains a factored belief representation and exploits passivity to perform selective updates over the belief factors. PSBF produces exact belief states under certain assumptions and approximate belief states otherwise, where the approximation error is bounded by the degree of uncertainty in the process. We show empirically, in synthetic processes with varying sizes and degrees of passivity, that PSBF is faster than several alternative methods while achieving competitive accuracy. Furthermore, we demonstrate how passivity occurs naturally in a complex system such as a multi-robot warehouse, and how PSBF can exploit this to accelerate the filtering task.
Computing Accurate Performance Bounds for Best Effort Networks-on-Chip

Real-time (RT) communication support is a critical requirement for many complex embedded applications which are currently targeted to Network-on-chip (NoC) platforms. In this paper, we present novel methods to efficiently calculate worst case bandwidth and latency bounds for RT traffic streams on wormhole-switched NoCs with arbitrary topology. The proposed methods apply to best-effort NoC architectures, with no extra hardware dedicated to RT traffic support. By applying our methods to several realistic NoC designs, we show substantial improvements (more than 30 percent in bandwidth and 50 percent in latency, on average) in bound tightness with respect to existing approaches.
MECHANICAL PROPERTIES OF CONCRETE INCORPORATING HIGH VOLUMES OF FLY ASH FROM SOURCES IN THE U.S.

This paper presents the results of studies to determine the properties of fresh and hardened high volume fly ash concretes using 8 fly ashes and 2 portland cements from the U.S. The details of the studies are described. The anslysis of the test results lead to the conclusion that high performance air entrained high volume fly ash concrete can be produced with the fly ashes and cements used in this investigation. The concretes so produced have low bleeding, satisfactory slump and setting characteristics and low autogenous temperature rise. These concretes also have excellent mechanical properties at both early and late ages with compressive strengths reaching as high as 50 MPa at 91 days. The creep and drying shrinkage of the concretes investigated are relatively low.