Miracle-dz/UniFAR-FTUs huggingface dataset:
Using passage-based language model for opinion detection in blogs

In this work, we evaluate the importance of Passages in blogs especially when we are dealing with the task of Opinion Detection. We argue that passages are basic building blocks of blogs. Therefore, we use Passage-Based Language Modeling approach as our approach for Opinion Finding in Blogs. Our decision to use Language Modeling (LM) in this work is totally based on the performance LM has given in various Opinion Detection Approaches. In addition to this, we propose a novel method for bi-dimensional Query Expansion with relevant and opinionated terms using Wikipedia and Relevance-Feedback mechanism respectively. We also compare the impacts of two different query terms weighting (and ranking) approaches on final results. Besides all this, we also compare the performance of three Passage-based document ranking functions (Linear, Avg, Max). For evaluation purposes, we use the data collection of TREC Blog06 with 50 topics of TREC 2006 over TREC provided best baseline with opinion finding MAP of 0.3022. Our approach gives a MAP improvement of almost 9.29% over best TREC provided baseline (baseline4).
Ethnic and Mouse Strain Differences in Central Corneal Thickness and Association with Pigmentation Phenotype

The cornea is a transparent structure that permits the refraction of light into the eye. Evidence from a range of studies indicates that central corneal thickness (CCT) is strongly genetically determined. Support for a genetic component comes from data showing significant variation in CCT between different human ethnic groups. Interestingly, these studies also appear to show that skin pigmentation may influence CCT. To validate these observations, we undertook the first analysis of CCT in an oculocutaneous albinism (OCA) and Ugandan cohort, populations with distinct skin pigmentation phenotypes. There was a significant difference in the mean CCT of the OCA, Ugandan and Australian-Caucasian cohorts (Ugandan: 517.3±37 µm; Caucasian: 539.7±32.8 µm, OCA: 563.3±37.2 µm; p<0.001). A meta-analysis of 53 studies investigating the CCT of different ethnic groups was then performed and demonstrated that darker skin pigmentation is associated with a thinner CCT (p<0.001). To further verify these observations, we measured CCT in 13 different inbred mouse strains and found a significant difference between the albino and pigmented strains (p = 0.008). Specific mutations within the melanin synthesis pathway were then investigated in mice for an association with CCT. Significant differences between mutant and wild type strains were seen with the nonagouti (p<0.001), myosin VA (p<0.001), tyrosinase (p = 0.025) and tyrosinase related protein (p = 0.001) genes. These findings provide support for our hypothesis that pigmentation is associated with CCT and identifies pigment-related genes as candidates for developmental determination of a non-pigmented structure.
WISE: Efficient Wireless Access Point SElection for Large-Scale Cooperative System

Cooperative design is becoming especially import for loosely coupled MIMO system. Cooperative AP selection is one of the most important issue need to be addressed. In this study, we investigate the efficient AP selection for cooperative MIMO system. The major concern in this work is to reduce the coordinative overhead in network. Two key challenges need to be formally addressed before achieving aforementioned goal. First, the decoding symbols in network is moderately large, which will lead to considerably high network traffic. Second, the decoding performances are highly correlated with the decoding symbols. Reducing symbol transfer will inevitably lead to low decoding rate. Thus, high quality decoding data, say, selecting the appropriate AP for decoding and performing efficient symbol transfer would be a possible solution to tackle aforementioned difficulties. In our design, we fully evaluate the performance of symbol level decoding for cooperative MIMO system, and explore the relationship between the cooperative AP selection with overall decoding. We propose WISE: a simple but effective scheme for AP selection, which is almost optimal and aggressive with moderately low complexity. Our algorithm is implemented and evaluated with USRP, an open software radio network design platform, which enable us to evaluate and validate our scheme more effectively. Experimental results show that, ours could significantly reduce the network overhead, and maintain relatively high decoding rate for cooperative MIMO system.
Lightly supervised GMM VAD to use audiobook for speech synthesiser

Audiobooks have been focused on as promising data for training Text-to-Speech (TTS) systems. However, they usually do not have a correspondence between audio and text data. Moreover, they are usually divided only into chapter units. In practice, we have to make a correspondence of audio and text data before we use them for building TTS synthesisers. However aligning audio and text data is time-consuming and involves manual labor. It also requires persons skilled in speech processing. Previously, we have proposed to use graphemes for automatically aligning speech and text data. This paper further integrates a lightly supervised voice activity detection (VAD) technique to detect sentence boundaries as a pre-processing step before the grapheme approach. This lightly supervised technique requires time stamps of speech and silence only for the first fifty sentences. Combining those, we can semi-automatically build TTS systems from audiobooks with minimum manual intervention. From subjective evaluations we analyse how the grapheme-based aligner and/or the proposed VAD technique impact the quality of HMM-based speech synthesisers trained on audiobooks.
Detecting sound objects in audio recordings

In this paper we explore the idea of defining sound objects and how they may be detected. We try to define sound objects and demonstrate by our experiments the existence of these objects. Most of current works on acoustic event detection focus on detecting a finite set of audio events and the detection of a generic object in sound is not done. The major reason for proposing the idea of sound objects is to work with a generic sound concept instead of working with a small set of acoustic events for detection as is the norm. Our definition tries to conform to notions present in human auditory perception. Our experimental results are promising, and show that the idea of sound objects is worth pursuing and that it could give a new direction to semi-supervised or unsupervised learning of acoustic event detection mechanisms.
ENHANCED CREDIT BASED LOAD BALANCING IN CLOUD ENVIRONMENT

Cloud computing is one of the latest and upcoming paradigm that offers huge benefits such as reduced time to market, unlimited computing power and flexible computing capabilities. It is a model that provides an on-demand network access to a shared pool of computing resources It comprises a large number of concepts primarily Load Balancing, Scheduling, etc. This paper discusses load balancing as a mechanism to distribute the workload evenly to all nodes in the system to achieve a higher resource utilization and user satisfaction. It helps in allocation and de-allocation of instances of applications without failure. This paper reports a new load balancing technique using modified credit based system using task length, task priority and its cost. The proposed algorithm has been implemented in cloudsim toolkit and its comparison with existing algorithm has been discussed in the paper.
Asymptomatic Preclinical Rheumatoid Arthritis-Associated Interstitial Lung Disease

Objective. Interstitial lung disease (ILD) is a common extra-articular manifestation of rheumatoid arthritis (RA) and a significant cause of morbidity and mortality. The objective of this study was to define high-resolution chest CT (HRCT) and pulmonary function test (PFT) abnormalities capable of identifying asymptomatic, preclinical forms of RA-ILD that may represent precursors to more severe fibrotic lung disease. Methods. We analyzed chest HRCTs in consecutively enrolled RA patients and subsequently classified these individuals as RA-ILD or RA-no ILD based on the presence/absence of ground glass opacification, septal thickening, reticulation, traction bronchiectasis, and/or honeycombing. Coexisting PFT abnormalities (reductions in percent predicted FEV1, FVC, TLC, and/or DLCO) were also used to further characterize occult respiratory defects. Results. 61% (63/103) of RA patients were classified as RA-ILD based on HRCT and PFT abnormalities, while 39% (40/103) were designated as RA-no ILD. 57/63 RA-ILD patients lacked symptoms of significant dyspnea or cough at the time of HRCT and PFT assessment. Compared with RA-no ILD, RA-ILD patients were older and had longer disease duration, higher articular disease activity, and more significant PFT abnormalities. Conclusion. HRCT represents an effective tool to detect occult/asymptomatic ILD that is highly prevalent in our unselected, university-based cohort of RA patients.
Minimum Latency Aggregation Scheduling in Interference-Aware 3-Dimensional WSNs

In this paper, we study the Minimum Latency Aggregation Scheduling (MLAS) problem in Wireless Sensor Networks (WSNs) adopting the two interference models: the graph model and the more realistic physical interference model known as Signal-to-Interference-Noise-Ratio (SINR). The main issue of the MLAS problem is to compute schedules with the minimum number of timeslots, that is, to compute the minimum latency schedules, such that data can be aggregated without any collision or interference. While existing works studied the problem in 2-dimensional (2D) WSNs only, we investigate the problem in the more general 3-dimensional (3D) WSNs, and introduce two approximation algorithms with O(1)-approximation ratios that yield schedules whose latency is bounded by O(∆ + R), where ∆ is the maximum node degree and R is the network radius. To the best known of our knowledge, our results are the first results of the MLAS problem in 3D WSNs. Keywords-Data Aggregation, Interference-Aware, Signal-toInterference-Noise-Ratio, 3-dimensional Network, Approximation Algorithm
Data visualization sliders

Computer sliders are a generic user input mechanism for specifying a numeric value from a range. For data visualization, the effectiveness of sliders may be increased by using the space inside the slider as • an interactive color scale, • a barplot for discrete data, and • a density plot for continuous data. The idea is to show the selected values in relation to the data and its distribution. Furthermore, the selection mechanism may be generalized using a painting metaphor to specify arbitrary, disconnected intervals while maintaining an intuitive user-interface.
Genetic diversity and population structure of an important wild berry crop

Bilberry (Vaccinium myrtillus L.) fruits are perceived by consumers to be a health-promoting food, conferred by their high content of phenolic compounds and carotenoids. The health properties of these molecules have raised commercial interest in these berries globally, and caught the attention of breeders. Bilberry is a wild crop and represents an important source of genetic variability for blueberry breeding. Our study presents information related to the genetic diversity and structure of bilberry populations derived from Northern Europe, providing new knowledge for the development of genetic studies and for breeding purposes.
Patterns and Trends in Racial Academic Achievement Gaps Among States, 1999-2011

In this paper we combine National Assessment of Educational Progress and state accountability test data to examine variation among states in achievement gap levels and trends. Although national trends in gaps have been well studied, little research has examined variation in gaps across states or the extent to which differences in state demographics or policies account for these differences. We find that white-black and white-Hispanic achievement gaps are large and have been closing very slowly over the last two decades, but the sizes and rates of change of these gaps vary considerably across states. Much of the variation in gap levels, but none of the variation in gap trends, can be explained by differences across states in the socioeconomic status of minority children and school racial segregation.
Molecular Computations Using Self-Assembled DNA Nanostructures and Autonomous Motors

Self-assembly is the spontaneous self-ordering of substructures into superstructures driven by the selective affinity of the substructures. DNA provides a molecular scale material for programmable self-assembly, using the selective affinity of pairs of DNA strands to form DNA nanostructures. DNA self-assembly is the most advanced and versatile system that has been experimentally demonstrated for programmable construction of patterned systems on the molecular scale. The methodology of DNA self-assembly begins with the synthesis of single-strand DNA molecules that self-assemble into macromolecular building blocks called DNA tiles. These tiles have sticky ends that match the sticky ends of other DNA tiles, facilitating further assembly into larger structures known as DNA tiling lattices. In principle, DNA tiling assemblies can form any computable two or three-dimensional pattern, however complex, with the appropriate choice of the tiles’ component DNA. Two-dimensional DNA tiling lattices composed of hundreds of thousands of tiles have been demonstrated experimentally. These assemblies can be used as scaffolding on which to position molecular electronics and robotics components with precision and specificity. This programmability renders the scaffolding have the patterning required for fabricating complex devices made of these components. We overview the evolution of DNA self-assembly techniques from pure theory, through simulation and design, and then to experimental practice. We will begin with an overview of theoretical models and algorithms for DNA lattice self-assembly. Then we describe our software for the simulation and design of DNA tiling assemblies and DNA nanomechanical devices. As an example, we discuss models and algorithms for the key problem of error control in DNA lattice self-assembly, as well as the computer simulation of these methods for error control. We will then briefly discuss our experimental laboratory demonstrations, including those using the designs derived by our software. These experimental demonstrations of DNA self-assemblies include the assembly of patterned objects at the molecular scale, the execution of molecular computations, and freely running autonomous DNA motors. ∗Contact address: Department of Computer Science, Duke University, Box 90129, Durham, NC 27708-0129. E-mail: reif@cs.duke. edu.
Incremental Peritoneal Dialysis Favourably Compares with Hemodialysis as a Bridge to Renal Transplantation

Background. The value of incremental peritoneal dialysis (PD) as a bridge to renal transplantation (Tx) has not been specifically addressed. Methods. All consecutive Stage 5 CKD patients with at least 1 year predialysis followup, starting incremental PD or HD under our care and subsequently receiving their first renal Tx were included in this observational cohort study. Age, gender, BMI, underlying nephropathy, residual renal function (RRF) loss rate before dialysis and RRF at RRT start, comorbidity, RRT schedules and adequacy measures, dialysis-related morbidity, Tx waiting time, RRF at Tx, incidence of delayed graft function (DGF), in-hospital stay for Tx, serum creatinine at discharge and one year later were collected and compared between patients on incremental PD or HD before Tx. Results. Seventeen patients on incremental PD and 24 on HD received their first renal Tx during the study period. Age, underlying nephropathy, RRF loss rate in predialysis, RRF at the start of RRT and comorbidity did not differ significantly. While on dialysis, patients on PD had significantly lower epoetin requirements, serum phosphate, calciumxphosphate product and better RRF preservation. Delayed graft function (DGF) occurred in 12 patients (29%), 1 on incremental PD and 11 on HD. Serum creatinine at discharge and 1 year later was significantly higher in patients who had been on HD. Conclusions. In patients receiving their first renal Tx, previous incremental PD was associated with low morbidity, excellent preservation of RRF, easier attainment of adequacy targets and significantly better immediate and 1-year graft function than those observed in otherwise well-matched patients previously treated with HD.
Loss and Gain of Natural Killer Cell Receptor Function in an African Hunter-Gatherer Population

Modulating natural killer cell functions in human immunity and reproduction are diverse interactions between the killer cell immunoglobulin-like receptors (KIR) of Natural Killer (NK) cells and HLA class I ligands on the surface of tissue cells. Dominant interactions are between KIR2DL1 and the C2 epitope of HLA-C and between KIR2DL2/3 and the C1 epitope of HLA-C. KhoeSan hunter-gatherers of Southern Africa represent the earliest population divergence known and are the most genetically diverse indigenous people, qualities reflected in their KIR and HLA genes. Of the ten KhoeSan KIR2DL1 alleles, KIR2DL1*022 and KIR2DL1*026 likely originated in the KhoeSan, and later were transmitted at low frequency to the neighboring Zulus through gene flow. These alleles arose by point mutation from other KhoeSan KIR2DL1 alleles that are more widespread globally. Mutation of KIR2DL1*001 gave rise to KIR2DL1*022, causing loss of C2 recognition and gain of C1 recognition. This makes KIR2DL1*022 a more avid and specific C1 receptor than any KIR2DL2/3 allotype. Mutation of KIR2DL1*012 gave rise to KIR2DL1*026, causing premature termination of translation at the end of the transmembrane domain. This makes KIR2DL1*026 a membrane-associated receptor that lacks both a cytoplasmic tail and signaling function. At higher frequencies than their parental allotypes, the combined effect of the KhoeSan-specific KIR2DL1*022 and KIR2DL1*026 is to reduce the frequency of strong inhibitory C2 receptors and increase the frequency of strong inhibitory C1 receptors. Because interaction of KIR2DL1 with C2 is associated with risk of pregnancy disorder, these functional changes are potentially advantageous. Whereas all other KhoeSan KIR2DL1 alleles are present on a wide diversity of centromeric KIR haplotypes, KIR2DL1*026 is present on a single KIR haplotype and KIR2DL1*022 is present on two very similar haplotypes. The high linkage disequilibrium across their haplotypes is consistent with a recent emergence for these KIR2DL1 alleles that have distinctive functions.
Distributed Reputation Management for Electronic Commerce

One of the major challenges for electronic commerce is how to establish a relationship of trust between different parties. Establishing trust is nontrivial, because the traditional physical or social means of trust cannot apply directly in virtual settings. In many cases, the parties involved may not ever have interacted before. Reputation systems seek to address the development of trust by recording the reputations of different parties. However, most existing reputation systems are restricted to individual market websites. Further, relevant information about a party may come from several websites and from interactions that were not mediated by any website.
Lifetime holes aware register allocation for clustered VLIW processors

This paper presents an on-the-fly register allocator which dynamically detects and utilises lifetime holes for clustered VLIW processors. A lifetime hole is an interval in which a variable does not contain a valid value. A register holding a lifetime hole can be allocated to another variable whose live range fits in the lifetime hole, leading to more efficient utilisation of registers. We propose efficient techniques for dynamically utilising lifetime holes and incorporate these techniques into our on-the-fly register allocator. We have simulated our register allocator and a linear scan register allocator without considering lifetime holes by using the MediaBench II benchmark suite. Our simulation results show that our register allocator reduces the number of spills by 12.5%, 11.7%, 12.7%, for three different processor models, respectively.
On Optimality of Myopic Policy for Restless Multi-Armed Bandit Problem: An Axiomatic Approach

Due to its application in numerous engineering problems, the restless multi-armed bandit (RMAB) problem is of fundamental importance in stochastic decision theory. However, solving the RMAB problem is well known to be PSPACE-hard, with the optimal policy usually intractable due to the exponential computation complexity. A natural alternative approach is to seek simple myopic policies which are easy to implement. This paper presents a generic study on the optimality of the myopic policy for the RMAB problem. More specifically, we develop three axioms characterizing a family of generic and practically important functions termed as regular functions. By performing a mathematical analysis based on the developed axioms, we establish the closed-form conditions under which the myopic policy is guaranteed to be optimal. The axiomatic analysis also illuminates important engineering implications of the myopic policy including the intrinsic tradeoff between exploration and exploitation. A case study is then presented to illustrate the application of the derived results in analyzing a class of RMAB problems arising from multi-channel opportunistic access.
Active learning with direct query construction

Active learning may hold the key for solving the data scarcity problem in supervised learning, i.e., the lack of labeled data. Indeed, labeling data is a costly process, yet an active learner may request labels of only selected instances, thus reducing labeling work dramatically. Most previous works of active learning are, however, pool-based; that is, a pool of unlabeled examples is given and the learner can only select examples from the pool to query for their labels. This type of active learning has several weaknesses. In this paper we propose novel active learning algorithms that construct examples directly to query for labels. We study both a specific active learner based on the decision tree algorithm, and a general active learner that can work with any base learning algorithm. As there is no restriction on what examples to be queried, our methods are shown to often query fewer examples to reduce the predictive error quickly. This casts doubt on the usefulness of the pool in pool-based active learning. Nevertheless, our methods can be easily adapted to work with a given pool of unlabeled examples.
Venture Capital and Corporate Governance in the Newly Public Firm

I examine the effects of venture capital backing on the corporate governance of the entrepreneurial firm at the time of transition from private to public ownership. Using a selection model framework that instruments for venture backing with variations in the supply of venture capital, I conduct three sets of tests comparing corporate governance in venture- and non--venture-backed initial public offering (IPO) firms. Venture-backed firms have lower levels of earnings management, more positive reactions to the adoption of shareholder rights agreements, and more independent board structures than similar non--venture-backed firms, consistent with better governance. These effects are not common to all pre-IPO large shareholders. Copyright 2011, Oxford University Press.