Miracle-dz/UniFAR-FTUs huggingface dataset:
Spectrum sensing of correlated subbands with colored noise in cognitive radios

In this paper, we consider the problem of wideband spectrum sensing by using the correlation among the observation samples in different subbands. The Primary User (PU) signal samples in occupied subbands are assumed to be zero-mean correlated Gaussian random variables and additive noise is modeled as colored zero-mean Gaussian random variables independent of the PU signal. It is also assumed that there is at least a minimum given number of subbands that are vacant of PU signals. First we derive the optimal detector and the Generalized Likelihood Ratio (GLR) detector for the case that the covariance matrix of PUs signal samples is unknown and the noise variance in the different subbands is known. Then, we propose an iterative algorithm for GLR test when both the covariance matrix of the PUs signal samples and the noise variances in the different subbands, are unknown. For analytical performance evaluation, we derive some closed-form expressions for detection and false alarm probabilities of the proposed detectors in low Signal to Noise Ratio (SNR) regime. The simulation results are further presented to compare the performance of the proposed detectors.
Blockade of Nucleoside Transport Is Required for Delivery of Intraarterial Adenosine Into the Interstitium: Relevance to Therapeutic Preconditioning in Humans

Background—Adenosine, a known mediator of preconditioning, has been infused into the coronary circulation to induce therapeutic preconditioning, eg, in preparation for angioplasty. However, results have been disappointing. We tested the hypothesis that endothelial nucleoside transporter acts as a barrier impeding the delivery of intravascular adenosine into the underlying myocardium and that this can be overcome with dipyridamole, a nucleoside transporter blocker. Methods and Results—We infused saline or adenosine (0.125 and 0.5 mg/min) into the brachial artery while monitoring forearm blood flow (FBF) and interstitial adenosine levels with microdialysis probes implanted in the flexor digitorum superficialis of the forearm in 7 healthy volunteers during intravenous administration of saline or dipyridamole (loading dose, 0.142 mg/kg per min for 5 minutes followed by 0.004 mg/kg per min). Adenosine produced near maximal forearm vasodilation, increasing FBF from 4.0±0.7 to 10.4±1.9 and 13.1±1.6 mL/100 mL per min for the low and high doses, respectively, but did not increase muscle dialysate adenosine concentration (from 88±21 to 65±23 and 85±26 nmol/L). Intravenous dipyridamole enhanced resting muscle dialysate adenosine (from 77±25 to 147±50 nmol/L), adenosine-induced increase in FBF (from 4.1±0.8 to 12.6±3 and 15.1±3 mL/100 mL per min for the low and high dose, respectively), and the delivery of adenosine into the interstitium (to 290±80 and 299±143 nmol/L for the low and high dose, respectively, P =0.04). Conclusions—Intravascular adenosine is likely ineffective in inducing myocardial preconditioning because of poor interstitial delivery. This can be overcome by blocking the nucleoside transporter with dipyridamole.
A pattern-based SVM for protein remote homology detection

One key element in understanding the molecular machinery of the cell is to understand the structure and function of each protein encoded in the genome. A very successful means of inferring the structure or function of a previously un-annotated protein is via sequence homology with one or more protein whose structure or function is already known. In this paper, a novel method for protein remote homology detection has been presented. The technologies of text categorization from natural language processing have been used in protein classification. Patterns are discovered by TEIRESIAS algorithm and can be viewed as the "words" of "protein sequence language". The patterns are then filtered by an efficient feature selection algorithm called chi-square algorithm. Each protein sequence is mapped into a high dimensional vector by the occurrence times of the selected patterns. This presentation, combined with a discriminative classification algorithm known as the support vector machine (SVM), provides a powerful means for protein remote homology detection. The method, called SVM-pattern, is tested on the SCOP database and compared with other state-of-the-art methods. The performance of SVM-pattern is better than that of BLAST method and comparable with other SVM-based methods such as SVM-k-spectrum and SVM-pairwise.
LUCApedia: a database for the study of ancient life

Organisms represented by the root of the universal evolutionary tree were most likely complex cells with a sophisticated protein translation system and a DNA genome encoding hundreds of genes. The growth of bioinformatics data from taxonomically diverse organisms has made it possible to infer the likely properties of early life in greater detail. Here we present LUCApedia, (http://eeb.princeton.edu/lucapedia), a unified framework for simultaneously evaluating multiple data sets related to the Last Universal Common Ancestor (LUCA) and its predecessors. This unification is achieved by mapping eleven such data sets onto UniProt, KEGG and BioCyc IDs. LUCApedia may be used to rapidly acquire evidence that a certain gene or set of genes is ancient, to examine the early evolution of metabolic pathways, or to test specific hypotheses related to ancient life by corroborating them against the rest of the database.
Willingness to Pay for Irradiated Food: A Non Hypothetical Market Experiment

This paper focuses on estimating consumers' willingness to pay for and willingness to accept irradiated food using a non-hypothetical experiment utilizing real food products (i.e., irradiated ground beef), real cash, and actual exchange in a market setting. Single-bounded and one and one-half bounded models are developed using dichotomous choice contingent valuation experiments. Our results indicate that average willingness to pay values range from 75.43 to 78.51 cents per pound while average willingness to accept values range from 69.49 to 81.63 cents per pound of irradiated ground beef.
Color Lie algebras and Lie algebras of order F

The notion of color algebras is generalized to the class of F-ary algebras, and corresponding decoloration theorems are established. This is used to give a construction of colored structures by means of tensor products with Cli ord-like algebras. It is, moreover, shown that color algebras admit realizations as q = 0 quon algebras.
Clustering-based automatic generation of extraction patterns

Most information extraction (IE) systems adopt a pattern-matching approach. As a result, how to generate extraction patterns has become an essential step. Using single-link clustering, examples of patterns can be clustered into various categories, each of which represents a pattern. We applied the method to Chinese agricultural texts, and achieved a plausible performance.
Summarizing Rushes Videos by Motion, Object, and Event Understanding

Rushes footages are considered as cheap gold mine with the potential for reuse in broadcasting and filmmaking industries. However, mining “gold” from unedited videos such as rushes is challenging as the reusable segments are buried in a large set of redundant information. In this paper, we propose a unified framework for stock footage classification and summarization to support video editors in navigating and organizing rushes videos. Our approach is composed of two steps. First, we employ motion features to filter the undesired camera motion and locate the stock footage. A hierarchical hidden Markov model (HHMM) is proposed to model the motion feature distribution and classify video segments into different categories to decide their potential for reuse. Second, we generate a short video summary to facilitate quick browsing of the stock footages by including the objects and events that are important for storytelling. For objects, we detect the presence of persons and moving objects. For events, we extract a set of features to detect and describe visual (motion activities and scene changes) and audio events (speech clips). A representability measure is then proposed to select the most representative video clips for video summarization. Our experiments show that the proposed HHMM significantly outperforms other methods based on SVM, FSM, and HMM. The automatically generated rushes summaries are also demonstrated to be easy-to-understand, containing little redundancy, and capable of including ground-truth objects and events with shorter durations and relatively pleasant rhythm based on the TRECVID 2007, 2008, and our subjective evaluations.
Integration of Enterprise Application Based on SOA

Globalisation, business process outsourcing and ever increasing regulatory environments are forcing the large enterprises to transform the way they provide their business and services. Businesses are required to be more agile and flexible, and IT managers are being asked to deliver improved functionality while leveraging existing IT investment. Service-oriented Architectures (SOA) has a major impact on the development of software systems because of its potential for increased business agility, adaptability of applications, integration and interoperability between systems, and reuse of legacy assets. This paper will briefly introduce SOA and analyzes integration of enterprise application based on SOA through a case of Marine Emergency Auxiliary Command System.
Information Geometric Approach to Recursive Update in Nonlinear Filtering

The measurement update stage in the nonlinear filtering is considered in the viewpoint of information geometry, and the filtered state is considered as an optimization estimation in parameter space has been corresponded with the iteration in the statistical manifold, then a recursive method is proposed in this paper. This method is derived based on the natural gradient descent on the statistical manifold, which constructed by the posterior probability density function (PDF) of state conditional on the measurement. The derivation procedure is processing in the geometric viewpoint, and gives a geometric interpretation for the iteration update. Besides, the proposed method can be seen as an extended for the Kalman filter and its variants. For the one step in our proposed method, it is identical to the Extended Kalman filter (EKF) in the nonlinear case, while traditional Kalman filter in the linear case. Benefited from the natural gradient descent used in the update stage, our proposed method performs better than the existing methods, and the results have showed in the numerical experiments.
Fuzzy PID control of lower limb exoskeleton for elderly mobility

This paper presents investigations into the development of an assistive device for elderly mobility. An exoskeleton is designed as an assistive device, to enhance the lower extremity and provide supporting torque to augment the torque of hip and knee during the walking cycle. A humanoid and actuated exoskeleton frame are designed in solid works and then imported to Visual Nastran 4D virtual environment. Fuzzy PID Control algorithm uses to control the actuated exoskeleton. Simulated walking tasks are performed with a humanoid wearing the exoskeleton. It is assumed that the humanoid representing an elderly person, is able to provide 60% of the whole torque required to complete the gait cycle, and the assistive device providing 40% of the overall torque.
The Unemployment Subsidy Program in Colombia: An Assessment

This paper assesses the effects of the Colombian Unemployment Subsidy (US), which includes benefits as well as training for some recipients. Using regression discontinuity and matching differences-in-differences estimators, the study finds that participation in the labor market, earnings of beneficiaries, and household income do not increase, and for some populations decrease during the 18 months after leaving the US program. Enrollment in formal health insurance falls. Effects on male heads of household include reductions in their earnings, decreases in their labor participation, and increases in their unemployment rates. The study also finds a small though statistically significant positive effect on beneficiaries¿ school attendance, but none on their children¿s weight or height at birth. The results are sensitive to the type of training that beneficiaries receive. Overall, the program serves more as a mechanism for smoothing consumption and providing social assistance than for increasing labor market efficiency.
Open Innovation within Business Ecosystems: A Tale from Amazon.Com

Open innovation refers to the ability of firms to open themselves up to external networks and relationships in order to gain the full potential of their investments in innovation. The development of ICTs has opened up new markets and ways of innovating. Today, platforms and Web services are supportive instruments of relations between firms. This paper analyzes how Amazon managed openness thanks to ICT infrastructure. In this paper, we address the challenge of managing open innovation within business ecosystems, especially those abetted by a new generation of technologies called Web services. We will draw lessons from Amazon.com to understand how this keystone organization is becoming nimble at open innovation, leveraging the power of its platform thanks to its Web services package. The case study shows that by using Web services to enhance collaboration in business ecosystems, some companies could support open innovation and expand the value of the goods and services they deliver to customers. The paper concludes with a suggested research agenda dealing with the significant implications for both strategy and policy.
Work shifts and disability: a national view

More than one-fifth of employed persons with disabilities work late or rotating shifts, about the same percentage as nondisabled workers; in general, day workers with disabilities receive lower hourly wages than nondisabled day workers, but, except for men with severe disabilities, nonday workers with disabilities receive wages similar to those of their nondisabled counterparts Work shifts and disability: a national view
Machine Learning and keyword-matching integrated Protocol Identification

Identifying the underlying protocol carried in the data traffic (i.e., Protocol Identification) is of fundamental important to QoS, Security, Network management and many other purposes. Port-based, content-based and behavior-based are commonly used identification methods in today's networks. However, all of these methods have their own shortcomings. In this paper, a new Machine Learning and Keyword-matching Integrated (MALKI) protocol identification method is proposed to overcome the shortcomings brought by these existing methods. The proposed method combines the content and behavior-based technologies together to identify the underlying protocol in the data flow. A prototype is implemented on a high performance multi-core processor platform. From the experimental results, we can see the proposed method is effective and efficient when applied into the protocol identification.
Send Orders of Reprints at Reprints@benthamscience.org Why Confidence Intervals Should Be Used in Reporting Studies of Complete Populations

Public-health reports sometimes leave out confidence intervals when data are presented for an entire population. A rationale cited for this practice is that population statistics are measurements rather than estimates; hence there is no need to consider random error because the statistics show exactly what occurred. We argue that this reason does not justify leaving out interval estimates. Targeting intervention in areas with high disease rates can be justified only on the assumption that the excess would continue in those areas; in that case, at the very least, we need to allow for random fluctuations over time. Thus, we recommend that interval estimates be reported even when the entire population is observed. INTERVAL ESTIMATES FOR POPULATIONS Confidence intervals are used in public-health practice to indicate the degree of uncertainty in estimates due to random error. This makes intuitive sense when estimates are based on data taken from a sample of a larger population, because relations in the sample are unlikely to mirror relations in the true population exactly, even when sampling is random [1]. Some error – random error, at the very least – is likely to occur. However, official reports sometimes leave out confidence intervals when data are presented for an entire population. This can be justified when case numbers are so large that random error is negligible (e.g., as in large national summaries [2, 3]). With smaller numbers, however, they are sometimes omitted on the grounds that the observed rates are measurements rather than estimates for the population; hence there is no need to consider random error because the statistics show exactly what occurred in the population. [4] We argue that this reason does not justify leaving out interval estimates. For example, targeting intervention in areas with high disease rates can be justified only on the assumption that the excess would continue in those areas; in that case, at the very least, we need to allow for random fluctuations over time. Those fluctuations can be considerable even when the number of cases seems large, and confidence intervals show the minimum uncertainty needed for applications. We thus recommend interval estimates be reported even if the entire population is observed without selectivity or error. Existence of the latter problems only underscores the need for interval estimation. WHY CONFIDENCE INTERVALS SHOULD BE A MINIMAL REQUIREMENT Suppose we knew the exact population size of an administrative region, and the exact number of …
Bringing the “right to request” flexible working arrangements to life: from policies to practices

Purpose – The purpose of this paper is to understand how the “right to request” flexible working arrangements (FWAs), located in national policy and in organisational policy contexts, are brought to life in the workplace by employees and their managers. The authors seek to understand the nature and content of requests, the process followed in attending to requests, the scope of the arrangements which resulted and the implications for the work of both employees and managers. Design/methodology/approach – The authors employ a case study method, investigating how formal “right to request” FWAs policies translate to practice within two large companies in Australia. The primary data focuses on 66 in-depth interviews with line managers, employees and key organisational informants. These interviews are triangulated with legislative, company and union policy documents. Findings – Most requests were made by mothers returning from maternity leave. Typically their requests involved an attempt to move from full-time .
Exploring the Security Capabilities of Physical Layer Network Coding

In wireless networks, the bandwidth is considered one of the most scarce and valuable resources. The physical layer network coding (PNC) technique encourages strategically picked senders to interfere so that the destination nodes can leverage the network level information to recover the signals. PNC can yield higher capacity than network layer network coding when applied to wireless networks. However, before PNC can be widely deployed so that we can fully capture its advantages, we must have a thorough understanding and evaluation of the safety of the technique. Previous research on physical layer network coding focuses on the separation of the interfered signals [1, 2]. For the network layer coding technique, the research on its security focuses on the prevention of the malicious activities such as pollution attacks [3].
THE IMPACT OF DIRECT BENEFITS OF CONTROL ON THE PRICE INFORMATIVE VALUE OF VOLUNTARY INFORMATION DISCLOSURE: AN EMPIRICAL STUDY OF THE IRANIAN PUBLIC LISTED COMPANIES

This paper seeks whether the voluntarily information disclosed by public companies listed on the TSE where the institutional blockholders possess the Direct Benefit of Control (DBC) is useful and relevant information as a proxy for presenting true financial picture. We assumed that the relevant voluntary disclosure indicates more transparency. We chose the annual reports of all public companies listed on the main board of TSE in 2009. Two types of indices were constructed, an index for the extent of voluntary disclosure (VD), and an index for the price informative voluntary disclosure (PID). The results show that the institutional blockholders meet the needs of market for information by disclosing a lot of information (VD) but with less-relevant content in order to cover up their perks’ consumptions. The blockholders would like to show the market is efficient with no information asymmetry however such transparency is not genuine. This paper may contribute to the literature whereas the presence of blockholders shall increase the extent of voluntary disclosure (VD) but the transparency may decline.
Wi-Sh: A Simple, Robust Credit Based Wi-Fi Community Network

Wireless community networks, where users share wireless bandwidth is attracting tremendous interest from academia and industry. Companies such as FON have been successful in attracting large communities of users. However, solutions such as FON either require users to buy specialized FON routers or firmware modifications to existing routers. In this paper we propose a solution which requires no such sophisticated hardware. An alternative is to provide a solution which requires users to download a client software on to their PCs. While the solution appears simple it raises several issues of incentivizing users to share their bandwidth and also issues of preventing users from cheating behaviors which give them an unfair advantage. In this paper, we propose a system and solution which (i) requires only software downloads on PCs, (ii) is robust to tampering of the software, and intermittent monitoring of an access point by the owner, (iii) a credit based mechanism whereby users earn credits for sharing bandwidth and punishment and pricing mechanism whereby users are charged at a higher price whenever they are caught misbehaving. By making simple but plausible assumptions about user behavior, we show via analysis and extensive simulations that the system converges to a Pareto optimal Nash equilibrium. We further validate our system model, by running trace driven simulations on real world data. We believe that the solution provided by Wi-Sh is an attractive and more credible alternative to solutions such as FON.
Optimal order execution for algorithmic trading: A CVaR approach

Order execution for algorithmic trading has been studied in the literature as a means of determine the optimal strategy by minimizing a trade-off between expected execution cost and risk. Usually, the variance of the execution cost is taken as a proxy of risk. The problem of this approach is that variance being a symmetric measure of risk disregard the fact that investors only considered as risky cost realizations that are higher than an expected target value. This fact becomes even more sensitive when the return distribution is nonnormal, negatively skewed, or leptokurtic. In this paper, we propose the use of the conditional value-at-risk of the execution cost as risk measure, which allows for taking only the unfavorable part of the return distribution, or equivalently unwanted high cost, into consideration.