Miracle-dz/UniFAR-FTUs huggingface dataset:
The spectral energy distribution of PKS 2004–447: a compact steep-spectrum source and possible radio-loud narrow-line Seyfert 1 galaxy

An investigation of the spectral energy distribution (SED) of the compact steep-spectrum (CSS) source and possible radio-loud narrow-line Seyfert 1 galaxy (NLS1), PKS 2004‐447, is presented. Five out of six well-studied radio-loud NLS1 share this dual classification (optically defined as a NLS1 with radio definition of a CSS or giga-he rtz peaked spectrum (GPS) source), suggesting that the connection could have a physical origin. The SED is created from simultaneous observations (within 24 hours) at radio (from ATCA), optical/NIR (from Siding Spring) and UV/X-ray (from XMM-Newton) wavelengths. The X-ray data show evidence of short-term variability (primarily a � 30 per cent increase in the final 4 ks of the observation), a possible soft excess, and negligible absorption. Togethe r with the rest of the SED, the Xray emission is excessive in comparison to synchrotron plus synchrotron self-Compton (SSC) models. The SED can be described with a two component model consisting of extended synchrotron/SSC emission with Comptonisation in the X-rays, though SSC models with a very high electron-to-magnetic energy density ratio cannot be excluded either. The peak emission in the SED appears to be in the near infrared, which can be attributed to thermal emission (T � 1000 K) from a dusty torus. Analysis of a non-contemporaneous, low-resolution optical spectrum suggests that the narrow-line region (NLR) is much more reddened than the X-ray emitting region suggesting that the gas-to-dust rati o in PKS 2004‐447 may be very different than in our own Galaxy. This could be achieved if the radio jets in PKS 2004‐447 deposits material from the nucleus into the NLR. Long-term radio monitoring of PKS 2004‐ 447 shows a rather constant light curve over nearly a six month period with the exception of one outburst when the 6.65 GHz flux increased by � 35 per cent over 19 days. It is not possible to differentiate between intrinsic or extrinsic (i.e., interstellar scintillation) origins for this outburst, but the detection of the rare event demonstrates t he importance of intensive monitoring campaigns. In comparison to general samples of GPS sources, which appear to be X-ray weak, NLS1-CSS/GPS sources possess stronger X-ray emission relative to radio (comparable to normal radio-loud AGN). In addition, NLS1-CSS/GPS sources also exhibit lower intrinsic absorption than GPS sources of similar X-ray luminosity. This is consistent with the additional X-ray component required for PKS 2004‐447, but larger samples of NLS1-CSS/GPS are needed before any conclusive remarks can be made.
Discussion: The Dantzig selector: Statistical estimation when p is much larger than n

1. Computational considerations. When Lasso [11] was proposed, it was a computational challenge to solve the associated quadratic program min β 1 � y − Xβ � 2 s.t. � β� 1 ≤ t Lasso(t) given just a single parameter t. Two active-set methods were described in [11], with some concern about efficiency if p were large, where X is n × p . Later when basis pursuit de-noising (BPDN) was introduced [2], the intention was to deal with p very large and to allow X to be a sparse matrix or a fast operator. A primal–dual interior method was used to solve the associated quadratic program, but it remained a challenge to deal with a single parameter. The authors’ new Dantzig Selector (DS) also assumes a specific parameter. It is helpful to state the BPDN and DS models together: min β,r λ� β� 1 + 1 � r� 2 s.t. r = y − Xβ, BPDN(λ) min β,r � β� 1 s.t. � X T r� ∞ ≤ λ, r = y − Xβ. DS(λ) For reference purposes we also state the corresponding dual problems: min r −y T r + 1 � r� 2 s.t. � X T r� ∞ ≤ λ, BPdual(λ) min r,z −y T r + λ� z� 1 s.t. � X T r� ∞ ≤ λ, r = Xz.
Quality Assessment of Web Services Using Multivariate Adaptive Regression Splines

The need to chose a suitable web service in the present scenario, due to the high growth in number of web services that provide similar types of functionalities is a critical task. To select a suitable web service, quality of service (QoS) parameters are efficient to use. In this paper, nine parameters of QoS have been considered as input for design a model using multivariate adaptive regression splines (MARS) to select suitable web service. The performance parameters of MARS model are evaluated and compared with those obtained using models such as: Multivariate Linear Regression, Multivariate Polynomial Regression, Naives Bayes Classifier, Artificial Neural Network. It is observed that the proposed model designed using MARS technique achieved better results as compared to the other three techniques. This paper also focuses on the effectiveness of feature selection techniques to find a small subset of QoS parameters. These may be able to classify the web services with higher accuracy and also reduced the value of misclassification errors.
In Search of Glacial Refuges of the Land Snail Orcula dolium (Pulmonata, Orculidae) - An Integrative Approach Using DNA Sequence and Fossil Data

Harboring a large number of endemic species, the Alps and the Western Carpathians are considered as major centers of biodiversity. Nonetheless, the general opinion until the turn of the millennium was that both Central European mountain regions did not provide suitable habitat during the Last Glacial Maximum, but were colonized later from southern refuges. However, recent molecular genetic studies provide new evidence for peripheral Alpine refuges. We studied the phylogeography of the calciphilous land snail O. dolium across its distribution in the Alps and the Western Carpathians to assess the amount of intraspecific differentiation and to detect potential glacial refuges. A partial sequence of the mitochondrial COI was analyzed in 373 specimens from 135 sampling sites, and for a subset of individuals, partial sequences of the mitochondrial 16S and the nuclear histone H3 and H4 were sequenced. A molecular clock analysis was combined with a reconstruction of the species’ geographic range history to estimate how its lineages spread in the course of time. In order to obtain further information on the species’ past distribution, we also screened its extensive Pleistocene fossil record. The reconstruction of geographic range history suggests that O. dolium is of Western Carpathian origin and diversified already around the Miocene-Pliocene boundary. The fossil record supports the species’ presence at more than 40 sites during the last glacial and earlier cold periods, most of them in the Western Carpathians and the Pannonian Basin. The populations of O. dolium display a high genetic diversity with maximum intraspecific p-distances of 18.4% (COI) and 14.4% (16S). The existence of various diverged clades suggests the survival in several geographically separated refuges. Moreover, the sequence patterns provide evidence of multiple migrations between the Alps and the Western Carpathians. The results indicate that the Southern Calcareous Alps were probably colonized only during the Holocene.
Feature classification for the satellite modulation based on sparse coding algorithm

In order to improve the characteristics for satellite data expression ability, it is proposed sparse coding with over complete bases, to induce the high dimensional feature vectors form down to up pattern, then to accurately express the original high-dimensional features with very few over complete basis vectors. From top-down semi supervised learning characteristics, to project high dimensional feature to low dimensional space, in order to verify the similarity of coding of the training data, then to express the characteristics of input satellite data. The encoder needs as much as possible reconstruction for the input multi dimensional, and the find the main ingredients for representing the original information about input data. Therefore, the over complete is not only by the coefficient of input data to determine characteristics, but also by the dimensional space. In order to verify the performance of the sparse coding algorithm, using the sparse coding algorithm is to identify the 6 kinds of commonly used digital modulation signal: 4ASK, 4FSK, 4PSK, MSK, 16QAM, π/4QPSK. The performance of correct modulation recognition rate is higher stability. The overall recognition of 6 kinds of modulation rate of SNR is higher, not less than 0dB 99%. Keywordssparse; extraction; feature; modulation; satellite;
Towards Enhancing Quality in Education through Information and Communication Technologies (ICTs) in Higher Educational Institutions (HEIs)

Teaching and Learning through ICT in Higher Educational Institutions (HEIs) has attracted global ICT investments of various Governments. However the results of these investments in ICT, that has a target to enhance quality of education remains to be seen and realized. Various factors such as ICT adoption and penetration, ICT infrastructure and equipment and professional development to enhance education using ICT have been limited. Using Wollo University in Ethiopia and Accra Polytechnic in Ghana as case studies, this article reviews institutional, personal and technological factors that can encourage stakeholders, teachers and students to use ICT to enhance the quality of education in these HEIs. The article reviews these factors and concludes that knowing the extent to which the enumerated barriers affect teachers and students of Wollo University and Accra Polytechnic, decisions concerning enhancing ICT quality of education through ICT can be made to the benefit of these HEIs as well as other ones.
The Century’s Giant: An Obituary of Economist Kenneth Arrow

Kenneth Arrow was arguably the leading figure of mainstream economics in the post-World War II era. His contributions to microeconomic theory were monumental. But his precision of thinking always shone through, and he carefully delineated the many limitations of free market solutions. The social, real-world aspects of his work were highly influential. The author, an eminent economic historian, was a colleague of his at Stanford University.
Architecture and Performance Potential of STICS S CSI-T oI P C ache S torage

Data storage plays an essential role in today’s fast-growing data-intensive network services. New standards and products emerge very rapidly for networked data storages. Given the mature Internet infrastructure, overwhelming preference among IT community recently is using IP for storage networking because of economy and convenience. iSCSI is one of the most recent standards that allows SCSI protocols to be carried out over IP networks. However, there are many disparities between SCSI and IP in terms of speeds, bandwidths, data unit size, and design considerations that prevent fast and efficient deployment of SAN (Storage Area Network) over IP. This paper introduces STICS (SCSI-To-IP Cache Storage), a novel storage architecture that couples reliable and highspeed data caching with low-overhead conversion between SCSI and IP protocols. A STICS block consists of one or several storage devices such as disks or RAID, and an intelligent processing unit with CPU and RAM. The storage devices are used to cache and store data while the intelligent processing unit carries out caching algorithm, protocol conversion, and self-management functions. Through efficient caching algorithm and localization of certain unnecessary protocol overheads, STICS can significantly improve performance, reliability, manageability, and scalability over current iSCSI systems. Furthermore, STICS can be used as a basic plug-and-play building block for data storage over IP. Analogous to “cache memory” invented several decades ago for bridging the speed gap between CPU and memory, STICS is the first-ever “cache storage” for bridging the gap between SCSI and IP making it possible to build efficient SAN over IP. We have carried out a partial implementation and simulation experiments to study the performance potential of STICS. Numerical results using popular PostMark benchmark program and EMC’s trace have shown dramatic performance gain over the iSCSI implementation.
Novel Approaches to Speaker Clustering for Speaker Diarization in Audio Broadcast News Data

The growing demand to shift content-based information retrieval from text to various multimedia sources means there is an increasing need to deal with large amounts of multimedia information. The data provided from television and radio broadcast news (BN) programs are just one example of such a source of information. In our research we focus on the processing and analysis of audio BN data, where the main information source is represented by speech data. The main issues in our work relate to the preparation and organization of BN audio data for further processing in information audio-retrieval systems based on speech technologies. This chapter addresses the problem of structuring the audio data in terms of speakers, i.e., finding the regions in the audio streams that belong to a single speaker and then joining each region of the same speaker together. The task of organizing the audio data in this way is known as speaker diarization and was first introduced in the NIST project of Rich Transcription in the “Who spoke when” evaluations (Fiscus et al., 2004; Tranter & Reynolds, 2006). The speaker-diarization problem is composed of several stages, in which the three main tasks are performed: speech detection, speakerand background-change detection, and speaker clustering. While the aim of the speech detection and the speakerand acousticsegmentation procedures is to provide the proper segmentation of the audio data streams, the purpose of the speaker clustering is to join or connect together segments that belong to the same speakers, and this is usually applied in the last stage of the speaker-diarization process. In this chapter we focus on speaker-clustering methods, concentrating on developing proper representations of the speaker segments for clustering, and research different similarity measures for joining the speaker segments and explore different stopping criteria for the clustering that result in a minimization of the overall diarization error of such systems. The chapter is organized as follows: In Section 2, two baseline speaker-clustering approaches are presented. The first is a standard approach using a bottom-up agglomerative clustering principle with the Bayesian information criterion as the merging criterion. In the second system an alternative approach is applied, also using bottom-up clustering, but the representations of the speaker segments are modeled by Gaussian mixture models, and for O pe n A cc es s D at ab as e w w w . in te ch w eb . o rg
Quadratic-programming based self-motion planning with no target-configuration assigned for planar robot arms

For better manipulability, a criterion in the form of a quadratic function is presented for the self-motion planning (SMP) of redundant manipulators with no target-configuration assigned. Such SMP scheme could automatically select the desirable configuration so that the manipulator could be more flexible and maneuverable. As physical limits generally exist in actual redundant manipulators, both joint limits and joint velocity limits are taken into consideration in the presented SMP scheme for practical purposes. Computer simulations based on two types of multi-link planar robot arms substantiate the efficiency and reliability of the presented scheme. Moreover, theoretical analysis of the presented quadratic performance index is conducted and proved via two different approaches, i.e., gradient-descent and Zhang et al's neural-dynamic methods.
A Wind Driven Approach Using Lévy Flights for Global Continuous Optimization

Recently, the metaheuristics have drawn a great attention to researchers. The drawbacks of existing derivative-based numerical methods have forced the researchers to rely on metaheuristics founded on simulations to solve scientific computation and engineering optimization problems. A common feature shared by the metaheuristics is that they combine rules and randomness to imitate some natural phenomena. Wind driven optimization (WDO) belongs to optimization metaheuristic algorithm. It is a stochastic nature-inspired global optimization method based on atmospheric motion. In this paper, we focus our study on an enhanced WDO using Lévy flights (WDOLE) applied to global optimization in the continuous domain. To evaluate the performance of the proposed WDOLE, well-known unconstrained benchmark functions in the literature are optimized using the proposed WDOLE, and provides comparisons with the standard WDO.
Triple Gene Analysis Using Samples Obtained by Endobronchial Ultrasound-guided Transbronchial Needle Aspiration

Objective A mutational analysis of tumor tissue samples is an important part of advanced lung cancer treatment strategies. This study evaluated the efficacy of a triple gene analysis using samples obtained via endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA). Methods Either metastatic lymph nodes or primary lung mass samples obtained by EBUS-TBNA were collected between May 2011 and May 2013. We consecutively analyzed epidermal growth factor receptor (EGFR), V-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS), and anaplastic lymphoma kinase (ALK) fusion genes using remnant tissue samples. Results A total of 109 patients were diagnosed with non-small cell lung cancer (NSCLC). Of these, 70% were adenocarcinoma, 27% squamous cell carcinoma with NSCLC, and 3% were related to other types of lung cancer. EGFR mutations were detected in 23 cases (21.1%), KRAS mutations in 13 cases (11.9%), and ALK fusion genes in 5 cases (4.9%). The ALK fusion genes could not be analyzed in four cases because of insufficient tissue samples remaining after routine histochemistry and an EGFR/KRAS mutation analysis. We found that small biopsy samples from EBUS-TBNA were adequate for performing a triple gene analysis in 97 patients (96%). ALK fusion protein immunohistochemistry (IHC) was 100% consistent with fluorescence in situ hybridization (FISH). Conclusion Small samples obtained by EBUS-TBNA were found to be sufficient for performing a triple gene analysis following routine histology and IHC. ALK IHC showed a very good concordance with FISH for detecting ALK fusion genes.
What Drives the Current Account in Commodity Exporting Countries? The Cases of Chile and New Zealand

This paper uses an open economy DSGE model with a commodity sector and nominal and real rigidities to ask what factors account for current account developments in two small commodity exporting countries. We estimate the model, using Bayesian techniques, on Chilean and on New Zealand data, and investigate the structural factors that explain the behaviour of the two countries’ current accounts. We find that foreign financial conditions, investment-specific shocks, and foreign demand shocks account for the bulk of the variation of the current accounts of the two countries. In the case of New Zealand, fluctuations in commodity export prices have also been important. Counterfactual experiments indicate that (i) a peso denomination of the Chilean external debt would reduce the impact of external shocks on the exchange rate and domestic variables, and the influence of monetary policy on the current account; and (ii) more or less aggressive monetary policy in New Zealand offers little scope for stabilizing the exchange rate and the current account.
Redundancy in Collaborative DialogueAppeared in Coling 92

In dialogues in which both agents are autonomous, each agent deliberates whether to accept or reject the contributions of the current speaker. A speaker cannot simply assume that a proposal or an assertion will be accepted. However, an examination of a corpus of naturally-occurring problem-solving dialogues shows that agents often do not explicitly indicate acceptance or rejection. Rather the speaker must infer whether the hearer understands and accepts the current contribution based on indirect evidence provided by the hearer's next dialogue contribution. In this paper, I propose a model of the role of informationally redundant utterances in providing evidence to support inferences about mutual understanding and acceptance. The model (1) requires a theory of mutual belief that supports mutual beliefs of various strengths; (2) explains the function of a class of informationally redundant utterances that cannot be explained by other accounts; and (3) contributes to a theory of dialogue by showing how mutual beliefs can be inferred in the absence of the master-slave assumption.
Neurochemical effect of neuromuscular electrical stimulation in brain after stroke : A microdialysis study using rats with focal cerebral ischemia – A pilot study

Neuromuscular electrical stimulation (NMES) is commonly used for producing repetitive active muscular contraction, which is believed that one of the outcomes is to promote plastic reorganisation after stroke. Previous microdialysis studies showed that motor activity triggered the increase in the levels of several amino acids/ neurotransmitters such as glutamate. Massive release of glutamate during cerebral ischemia is the main pathway leading to neuronal death. The objective of this study is to investigate the effect of NMES on the levels of neurotransmitters released by the hippocampal neurons after ischemic damage. The levels were monitored by microdialysis for two weeks. Basal percentage of glutamate was found to be increased after NMES intervention and then dropped gradually. This trend persisted throughout a week (Day 1 to Day 7 after stroke), whereas the levels remained steady in control group. The increase in glutamate may lead to additional excitotoxic damage in hippocampus following the intervention. Taurine level was increased after NMES on Day 1, but this pattern did not persisted afterwards. Its basal concentration kept increasing throughout 2 weeks while glutamate basal concentration exhibited an opposite trend. Taurine may act as an inhibitor to the excitotoxicity by excessive glutamate.
Wireless Sensor Networks for Life Science Automation

This paper identifies life science automation (LSA) as a predestinated field of application for wireless sensor networks (WSN). We are presenting a variety of environmental and process parameters which are measured in LSA using wired sensors today, but are best candidates to be replaced by wireless sensors. We show how they can be used and what kind of additional information can be derived from the parameters. In various examples we show the applicability of WSN in LSA and sketch a laboratory environment which is augmented with various sensor nodes. Additionally, we propose to use WSN for localization of equipment as well as persons carrying a sensor node beside the measurement of physical phenomena. Thereafter, we have a closer look at localization in WSN and present our experimental results. The use of localization in LSA is presented with the help of a scenario. A WSN with multi purpose abilities provides the flexibility to adjust laboratory installation to LSA.