Miracle-dz/UniFAR-FTUs huggingface dataset:
A comparative study of the anomalous fading effects of TL and OSL signals of Durango apatite

The Thermoluminescence (TL), Blue Stimulated Luminescence (BSL) and Infrared Stimulated Luminescence (IRSL) properties of apatite (originating from Durango, Mexico) are studied. The TL dose response of Durango apatite is linear to an extended dose region whereas the BSL and IRSL dose responses are sublinear. The TL, BSL and IRSL signals are found to exhibit strong anomalous fading (AF). All experimentally obtained BSL and IRSL decay curves were transformed into pseudo‐linear modulated (pseudo‐LM) ones. The resulting glow‐curve shaped pseudo‐LM curves were analyzed using a deconvolution analysis, similar to that used for the glow‐curve deconvolution (GCD) of TL glow‐curves. It was found that the pseudo‐LM BSL and IRSL decay curves consist of two components termed fast and slow and their individual contributions were estimated. The AF of the remnant TL, BSL and IRSL signals as a function of storage time were fitted to the tunneling model equations and the fading rate g, in terms of percentage per decade was evaluated. According to the g values found the AF properties are ordered as following: The AF of the BSL and IRSL signals is stronger than that of the TL. The AF of the fast components of BSL and IRSL signals is almost the same. The stimulation by blue light causes strong bleaching of the TL signal and alterations in the glow‐curve shape, whereas the IR light causes, only, a slight bleaching of the TL signal without changes in the glow‐curve shape. (© 2006 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Research on Modeling Method Based on Least Squares Support Vector Machine

dkwine@163.com Abstract - A method of support vector machine based on particle swarm optimization was proposed for the question of parameter selecting difficult of least square support vector machine in modeling of gas sensor. Least square support vector machine is used to build the model of gas sensor. Particle swarm optimization arithmetic was introduced to optimize the parameters of support vector machine. The sensor model is tested with the data measured reality. The results prove the accuracy of the model. Index Terms - Particle swarm optimization algorithm, Support vector machine, Gas sensor, Mathematical modeling
Diversity study analysis of Leptin gene in some ruminant and non-ruminant selected animal species

The key element of the system regulating food intake has proven to be the Leptin. It act as hunger centre in the hypothalamus and affects the regulation of appetite. It has also been shown that Leptin gene influence milk performance in sheep, cattle and reproduction performance in beef cattle. Genetic characterization to assess the existing biodiversity and differences among the important livestock breeds is an essential pre-requisite to facilitate the conservation program in an effective and meaningful way. This paper sought to study the diversity analysis of Leptin gene in some ruminant and non-ruminant animal species. A total of twenty three (23) Leptin gene sequences belonging to eight (8) species: Cattle (3), Sheep (3), Goat (3), Swine (3), Horse (2), Camel (3), Mouse (3) and Rabbit (3) were retrieved from Genbank (www.ncbi.nlm.nih.gov). Sequences alignment, translation and comparison were done using ClustalW of the MEGA 6.0. The minimum distance matrix (Dxy) value (0.02) was observed between the sequence of cattle and goat while the maximum Dxy value (2.72) was seen between cattle and sheep in ruminant species. In non-ruminant species the highest Dxy value (17.61) was seen between rabbit and camel while the minimum Dxy value (0.18) was observed between mouse and camel respectively. The smaller the distance matrix value, the closer the sequence of the species and the lesser the genetic distance among or between species whereas the larger the Dxy value, the higher the genetic distance among and between species investigated. This finding could provide basis for selection when considering evolution and differentiation among species.
How satisfaction modifies the strength of the influence of perceived service quality on behavioral intentions

Purpose – The existence and form of interaction effects between service quality and satisfaction are still uncertain. The main purpose of this study is to examine whether satisfaction moderates the relationship between service quality and behavioral intentions.Design/methodology/approach – A structured questionnaire was distributed to the out‐patients of 12 regional hospitals (the middle level) in Taiwan.Findings – The findings show that the forms of moderators played by satisfaction are not always the same under different dimensions of service quality (i.e. reliability, responsiveness, assurance, and empathy). Satisfaction positively moderates the influence of reliability/empathy on behavioral intentions, but negatively moderates the relationships between responsiveness/assurance and behavioral intentions.Originality/value – This study reveals the moderating role of satisfaction in the translation from service quality to behavioral intentions in health care services. Moreover, the natures of the moderati.
Malaysian Journal of Civil Engineering 25 Special Issue(1):1-12 (2013)

Objective of this paper is comparison of results of numerical analysis of headed studs with different head size and CCD (Concrete Capacity Design) approach which is used for design of anchoring in Eurocode 2. The breakout simulation tests of six different head diameters with four different effective embedment depths were investigated. The concrete properties were kept constant for all of them. It was found that the capacity of anchor is affected by the head size significantly. The approximately 25% decrease of capacity for small heads and about 30% capacity increase for large heads were observed in comparison to the CCD method.
Data-Driven Clustering of P300 EEG Data Using Coupled Tensor Decompositions

Recently, it was shown that auditory brain-computerinterface (BCI) classifications can be performed in real life environments. However, the need for initial training of existing supervised classifiers on large parts of that data discourages practical application. Reducing calibration time of BCI analyses would benefit short-term interactions. The current paper presents a carefully simulated study of P300 Event-Related-Potential (ERP) data to illustrate the performance of tensor decompositions for data-driven classification of the P300 effect. The aim of this study was to investigate whether coupling of a highand low-noise dataset can enhance data-driven clustering of the P300. Imposing structure and linking the decompositions of higher dimensional data arrays called tensors was hypothesized to increase the classification accuracy. For the highest noise dataset (SNR=0.60), we demonstrated that imposing a coupling to datasets with a lower noise level can significantly improve the extracted clusters to classify target from non-target trials to achieve equal accuracy to the widely used supervised regularized Linear-DiscriminantAnalysis (rLDA). We evaluated the performance of Canonical Polyadic Decomposition (CPD) and decomposition in multilinear rank Lr,Lr,1 terms (LL1). These structured models do not need a training phase or label information, although they require additional data. Finally, we illustrated the potential of the tensor approach for the analysis of simultaneous EEG recordings in which the trial mode is shared between subjects. Without a priori knowledge of the signal of interest, the tensor-based models successfully separated the two stimuli classes in the highest noise scenario up to 100% for coupling of five simulated subjects. These results highlight the benefits of exploiting structure in the stimuli and experimental setup (e.g., conditions or subjects).
Head-Related Transfer Functions of Human Subjects

Head-related transfer functions (HRTFs) were measured on 40 human subjects for 97 directions of sound incidence, covering the entire sphere. Individual HRTF data for the median, horizontal, and frontal planes are presented in the frequency domain. Measurements were made synchronously at both ears, thus making the time representations, that is, the head-related impulse responses (HRIRs), valid also when interaural time differences are considered. The measurements were made at the entrance to the blocked ear canal. Sound at this point contains full spatial information, and the interindividual variation is lower than at the open ear canal
Possibilities and constraints in the use of very high spatial resolution UltraCamX airborne imagery and digital surface models for classification in densely built-up areas: a case study of Berlin

With the availability of large digital frame cameras like the UltraCamX (UCX) additional benefits through a combination of high-resolution multispectral aerial images with highly accurate digital surface models emerge. This ongoing study examines the level of detail of urban information that can be extracted. High resolution and the unprecedented geometric accuracy of the multispectral and the 2.5D object information enable the derivation of detailed and characteristic object features. The method of object-based classification is not only used to extract meaningful objects, even more important is a detailed assessment of semantic relationships. Our study shows the explicit advantage of high geometric resolution to increase the stability of classification and the number of classes in a representative area of Berlin.
Sol-Gel Applications in Textile Finishing Processes

In the chapter, sol‐gel applications in textile finishing process such as flame retardancy, water, oil repellency, ultraviolet (UV) protection, self‐cleaning, and antibacterial and anti‐ wrinkle processes are reviewed. Sol‐gel technology is well known in materials, metallurgy, ceramic, and glass industry since 1960 and has been researched in textile industry in the last decade. Sol‐gel technology has some advantages when compared to conventional textile finishing process. Sol‐gel technology, which is a method applied to the inorganic metal alk‐ oxide or metal salts to organic textile materials, could impart the high, durable activity and multifunctional properties to different textile materials in the same bath at one step using low concentration of precursors. In addition, sol‐gel technology presents alternatively eco‐ nomical, ecological, and environmental friendly process due to one‐step application, using low concentration of chemicals, nonhalogenated chemicals, and nonformaldehyde release when compared to conventional processes.
The Linkage Between Work Unit Performance Perceptions of U.S. Federal Employees and Their Job Satisfaction: An Expectancy Theory

Public organizations are interested in how to improve their performance. Performance in a work unit can also influence employee job satisfaction due to positive expectations based on higher performance. Thus, our study attempts to investigate if organizational performance has an impact on employee motivation under the premise that employees who perform better in a work unit expect greater professional recognition and rewards. By using data from the 2013 Federal Employee Viewpoint Survey (FEVS), we find that employees who perceive higher levels of performance in a work unit have a higher level of job satisfaction. This paper further shows that performance perception based on rewards is also positively related to job satisfaction. However, underrepresented groups (female and non-white), older employees and mid-level (work experience from 6 to 14 years) employees are less satisfied with higher work unit performance. Finally, employees in the distributive agency category are more satisfied with work unit performance while those in the regulatory agency category are less satisfied with work unit performance. In conclusion, organizations should recognize particular characteristics of employees to develop the policies related to performance management, and effectively utilize these policies in order to attract and retain proficient workers.
Inferring Advisor-Student Relationships from Publication Networks Based on Approximate MaxConfidence Measure

A publication network contains abundant knowledge about advisor-student relationships. However, these relationship labels are not explicitly shown and need to be identified based on the hidden knowledge. The exploration of such relationships can benefit many interesting applications such as expert finding and research community analysis and has already drawn many scholars’ attention. In this paper, based on the common knowledge that a student usually coauthors his papers with his advisor, we propose an approximate MaxConfidence measure and present an advisor-student relationship identification algorithm based on the proposed measure. Based on the comparison of two authors’ publication list, we first employ the proposed measure to determine the time interval that a potential advising relationship lasts and then infer the likelihood of this potential advising relationship. Our algorithm suggests an advisor for each student based on the inference results. The experiment results show that our algorithm can infer advisor-student relationships efficiently and achieve a better accuracy than the time-constrained probabilistic factor graph (TPFG) model without any supervised information. Also, we apply some reasonable restrictions on the dataset to reduce the search space significantly.
Compositional compression of deep image features using stacked quantizers

In computer vision, it is common for image representations to be stored as highdimensional real-valued vectors. In many computer vision applications, such as retrieval, classification, registration and reconstruction, the computational bottleneck arises in a process known as feature matching, where, given a query vector, a similarity score has to be computed to many vectors in a (potentially very large) database. For example, it is not uncommon for object retrieval and classification to be performed by matching global representations in collections with thousands [27] or millions [10, 32] of images. A popular approach to reduce the computational and memory requirements of this process is vector quantization. In this work, we first analyze several vector compression methods typically used in the computer vision literature in terms of their computational trade-offs. In particular, we observe that Product Quantization (PQ) and Additive Quantization (AQ) lie on the extremes of a compositional vector compression design choice, where the former assumes complete codebook independence and the latter assumes full codebook dependence. We explore an intermediate approach that exploits a hierarchical structure in the codebooks. This results in a method that is largely competitive with AQ in structured vectors, and outperforms AQ in unstructured vectors while being several orders of magnitude faster. We also perform an extensive evaluation of our method on standard benchmarks of Scale Invariant Feature Transform (SIFT), and GIST descriptors, as well as on new datasets of features obtained from state-of-the-art convolutional neural networks. In benchmarks of low-dimensional deep features, our approach obtains the best known-to-date results, often requiring less than half the memory of PQ to achieve the same performance.
Studying the Regional Cyberspace by Exploiting Internet Sequential Information Flows

The study of cyberspace is faced with the challenge of the data shortage and model verification. This paper proposed a method to explore the regional cyberspace by employing Internet sequential information flows crawled from social network platforms. Compared with previous studies which only use one type of data sources for analysis, the main contribution of this manuscript is adopting the scheme that uses one kind of Internet information flow to extract cyberspace feature while relevant data collected from the other network platform is used for verification. Moreover, starting from measuring the informatization level of a region, a modified gravity model is designed by adding the value of informatization level to the traditional method. Then, an information association matrix based on the improved gravity model is constructed for analyzing the characteristics of cyberspace. To demonstrate the efficiency, Fuzhou city is considered as an interesting regional sample in this paper. The reasonable results indicate that the proposed approach is practical for regional cyberspace.
Structure of genetic diversity of Bemisia tabaci (Genn.) (Hemiptera: Aleyrodidae) populations in Brazilian crops and locations

Bemisia tabaci (Genn.) represents a complex of cryptic species that causes losses of many valuable crops. Even though there are differences in their ability to colonize hosts, transmit phytovirus and develop resistance to insecticides, the genetic differentiation of the insect populations is important for the adoption of control measures. Therefore, the genetic diversity of B. tabaci populations in economically important crops in Brazilian locations was characterized through a microsatellite analysis. Eight microsatellite markers were used for the analysis of eight populations, three in Solanum tuberosum (States of Sao Paulo, Minas Gerais and Bahia), two in Glycine max (States of Sao Paulo and Mato Grosso), one in Phaseolus vulgaris and Brassica oleracea var. acephala (States of Sao Paulo and Distrito Federal, respectively) and a cabbage population from Florida (USA). The number of alleles varied between two and 13 and the average value of FST was 0.13. The population occurring in beans was genetically different, suggesting that the excessive use of insecticide or the host itself may have caused the modification of its allele frequency. The American population presented a large diversity and small differentiation compared to the Brazilian populations, especially from the Southeast, supporting the hypothesis that the B biotype was probably introduced into Brazil by the trade of plant material between the USA and the State of Sao Paulo. The genetic diversity found within and among the populations is geographically structured, and the insects from the central region of Brazil had superior genetic divergence when compared to the others Brazilian locations.
Absence of scale dependence in dolphin-habitat models for the eastern tropical Pacific Ocean

Research into the effects of scale on cetacean-habitat relationships is limited and has produced ambiguous results. We explored the effects of spatial resolution (a component of scale) on dolphin- habitat models using 4 yr of data collected in the eastern tropical Pacific Ocean (ETP). We developed generalized additive models of dolphin-habitat rela- tionships for 4 species at 6 spatial resolutions using oceanographic and geographic habitat variables. For all species, the ecological patterns in the models built at the different resolutions were similar: the same vari- ables frequently occurred at multiple resolutions and had similar functional forms, and maps of predicted distributions identified similar high and low density regions. Additionally, interannual habitat variability, which is most likely related to the El Nino-Southern Oscillation, had a greater impact on the predictive power of dolphin-habitat models than spatial resolu- tion. Although it is common to find scale dependence in species-habitat relationships, domains of scale exist in which ecological patterns do not change. The absence of scale dependence in the models for the 4 dolphin species suggests that resolutions from 2 to 120 km occur within a single domain of scale in the ETP. This domain of scale may be determined by the physical oceanography of the ETP, which is generally defined by large-scale processes. Although resolutions from 2 to 120 km appear to occur within a domain of scale, building models at the larger resolutions we investigated may reduce the noise in the data due to false absences.
Gamma rays from cosmic radioactivities

Abstract— Gamma rays from radioactive byproducts of cosmic nucleosynthesis are direct messengers from nuclear processes taking place in various cosmic sites, and can be measured with telescopes operated in space. Due to low detector sensitivity, up until now, only a handful of sources have been detected in that electromagnetic window. Cobalt lines from SN1987A and 44Ti lines from the Cassiopeia A (Cas A) supernova remnant offer unique constraints on the properties of the innermost regions of core collapse supernovae. Diffuse gamma‐ray lines from the decay of radioactive 26Al and the annihilation of positrons are bright enough for mapping the Milky Way in the MeV regime, and are both measured by recent spaceborne spectrometers with unprecedented precision. This constrains the sources of Al production and the state of interstellar gas in the vicinity of these sites: the total mass of 26Al produced by stellar sources throughout the Galaxy is estimated to be ∼3 M⊙ per Myr, and the interstellar medium near those sources appears to be characterized by velocities of ∼100 km s−1. Positron annihilation must occur in a modestly ionized, warm phase of the interstellar medium, but at present the major positron production site(s) remain unknown. The spatial distribution of the annihilation gamma‐ray emission constrains positron production sites and positron propagation in the Galaxy. 60Fe radioactivity has been clearly detected recently; the flux ratio relative to 26Al of about 15% is on the lower side of predictions from massive star and supernova nucleosynthesis models. Those views at nuclear and astrophysical processes in and around cosmic sources by space‐based gamma‐ray telescopes offer invaluable information on cosmic nucleosynthesis.
The Nature of Corporate Income Tax Under a Full Imputation Tax Regime: A Test of Functional Fixation

This paper tests two competing hypotheses describing investors' behavior: the efficient market hypothesis and the functional fixation hypothesis. In particular, this study examines how Taiwan's stock market interprets the nature of corporate income tax after the 1998 Tax Reform, which switches from the "classical" tax system to the "integrated" tax system. This Tax Reform changes the nature of corporate income tax from a pure operating expense to an individual shareholder's tax credit, but current GAAP still treats it as an operating expense in the income statement. The empirical results show that Taiwan's stock market perceives the change in nature of corporate income tax and responds accordingly. Copyright Blackwell Publishers Ltd, 2002.