Miracle-dz/UniFAR-FTUs huggingface dataset:
Integrating MapReduce and RDBMSs

Data processing needs are changing with the ever increasing amounts of both structured and unstructured data. While the processing of structured data typically relies on the well-developed field of relational database management systems (RDBMSs), MapReduce is a programming model developed to cope with processing immense amounts of unstructured data. MapReduce, however, offers features and advantages that can be exploited to process structured data. Several database vendors and researchers have already turned to MapReduce to aid in processing relational data, thus requiring integration of MapReduce and RDBMS technologies. In this paper, we provide a taxonomy to characterize several existing integration methods. Further, we take a detailed look at DBInputFormat which is an interface between Hadoop's MapReduce and a relational database. The challenges posed by such an interface are identified and we provide suggestions for improvement.
Maximal respiratory pressures in myasthenia gravisRelation to single fiber electromyography*

Objectives– The respiratory muscle weakness was evaluated in mild forms of myasthenia gravis (MG) and was compared with single fiber electromyography results (SFEMG) in the extensor digitorum communis muscle. Material and methods– We assessed 61 treated MG patients without clinical respiratory involvement (13 ocular forms, 28 form IIa and 20 form IIb patients) by maximal respiratory pressure (MRP) to ascertain whether they were consistent with SFEMG results. Results– Maximal expiratory pressure (MEP) and maximal inspiratory pressure (MIP) were reduced below the lower limit for healthy subjects in 85% and 77% of ocular patients; in 93% and 89% of form IIa, respectively; and in 95% of form IIb. The highest percentage of MEP and MIP reduction showed a positive correlation with increased jitter (r=0.45, P<0.001; r=0.27; P<0.05 respectively) and impulse blocking (r=0.35, P<0.01; r=0.28, P<0.05 respectively). Conclusion– We consider MRP measure useful for assessing respiratory muscle weakness in MG patients with subclinical respiratory involvement.
Wind disturbance rejection for an insect-scale flapping-wing robot

Despite having achieved unconstrained stable flight, the insect-scale flapping-wing robot is still tethered for power and control. Towards the goal of operating a biologically-inspired robot autonomously outside of laboratory conditions. In this paper, we simulate outdoor disturbances in the laboratory setting and investigate the effects of wind gusts on the flight dynamics of a millimeter-scale flapping wing robot. Simplified models describing the disturbance effects on the robot's dynamics are proposed, together with two disturbance rejection schemes capable of estimating and compensating for the disturbances. The proposed methods are experimentally verified. The results show that they reduced the root mean square position errors by approximately 50% when the robot was subject to 60 cm·s-1 horizontal wind.
GeoProof: Proofs of Geographic Location for Cloud Computing Environment

Cloud computing has emerged as a major ICT trend and has been acknowledged as a key theme of industry by prominent ICT organisations. However, one of the major challenges that face the cloud computing concept and its global acceptance is how to secure and protect the data that is the property of the user. The geographic location of cloud data storage centres is an important issue for many organisations and individuals due to the regulations and laws that require data and operations to reside in specific geographic locations. Thus, data owners may need to ensure that their cloud providers do not compromise the SLA contract and move their data into another geographic location. This paper introduces an architecture for a new approach for geographic location assurance, which combines the proof of storage protocol (POS) and the distance-bounding protocol. This allows the client to check where their stored data is located, without relying on the word of the cloud provider. This architecture aims to achieve better security and more flexible geographic assurance within the environment of cloud computing.
Seismicity at the Northern Hikurangi Margin, New Zealand, and Investigation of the Potential Spatial and Temporal Relationships With a Shallow Slow Slip Event

In 2014–2015, the Hikurangi Ocean Bottom Investigation of Tremor and Slow Slip experiment deployed seafloor absolute pressure gauges and ocean bottom seismometers directly above a large slow slip event, allowing examination of the relationship between slow slip and earthquakes in detail. Hikurangi Ocean Bottom Investigation of Tremor and Slow Slip data were combined with nearby existing land stations to create a catalog of microseismicity consisting of 2,300 earthquakes ranging in magnitude between 0.5 and 4.7 that is complete to magnitude 1.5, yielding almost twice as many events as detected by the onshore networks alone. This greatly improves the seismicity catalog for this active subduction zone margin, especially in the offshore portion that was difficult to study using only the inland permanent seismic network. The new locations for the events within the footprint of the offshore network show that earthquakes near the trench are systematically shallower than and NW (landward) of their locations using only land‐based stations. Our results indicate that Hikurangi seismicity is concentrated in two NE‐SW bands, one offshore beneath the outer forearc wedge, one onshore beneath the eastern Raukumara Peninsula, and the majority of earthquakes are within the subducting Pacific plate with a smaller percent at the plate interface. We find a 20‐km wide northeast trending gap in microseismicity between the two bands and beneath the inner forearc wedge and this gap in seismicity borders the downdip edge of a slow slip patch.
Decentralized linear time-varying model predictive control of a formation of unmanned aerial vehicles

This paper proposes a hierarchical MPC approach to stabilization and autonomous navigation of a formation of unmanned aerial vehicles (UAVs), under constraints on motor thrusts, angles and positions, and under collision avoidance constraints. Each vehicle is of quadcopter type and is stabilized by a local linear time-invariant (LTI) MPC controller at the lower level of the control hierarchy around commanded desired set-points. These are generated at the higher level and at a slower sampling rate by a linear time-varying (LTV) MPC controller per vehicle, based on an a simplified dynamical model of the stabilized UAV and a novel algorithm for convex under-approximation of the feasible space. Formation flying is obtained by running the above decentralized scheme in accordance with a leader-follower approach. The performance of the hierarchical control scheme is assessed through simulations, and compared to previous work in which a hybrid MPC scheme is used for planning paths on-line.
Analysing the behaviour of distributed software architectures: a case study

A software architecture is the overall structure of a system in terms of its constituent components and their interconnections. We describe work to associate behavioural specifications with the components of a distributed software architecture and an approach to analysing the behaviour of systems composed from these components. The approach is based on the use of labelled transition systems to specify behaviour and compositional reachability analysis to check composite system models. The architecture description of a system is used directly to generate the model used for analysis. Analysis allows a designer to check whether an architecture satisfies the properties required of it. The approach is illustrated using a case study of an active badge system.
Blind Adaptive Constrained Constant-Modulus Reduced-Rank Interference Suppression Algorithms Based on Interpolation, Switched Decimation and Filtering

This work proposes a blind adaptive reduced-rank scheme and constrained constant-modulus (CCM) adaptive algorithms for interference suppression in wireless communications systems. The proposed scheme and algorithms are based on a two-stage processing framework that consists of a transformation matrix that performs dimensionality reduction followed by a reduced-rank estimator. The complex structure of the transformation matrix of existing methods motivates the development of a blind adaptive reduced-rank constrained (BARC) scheme along with a low-complexity reduced-rank decomposition. The proposed BARC scheme and a reduced-rank decomposition based on the concept of joint interpolation, switched decimation and reduced-rank estimation subject to a set of constraints are then detailed. The proposed set of constraints ensures that the multi-path components of the channel are combined prior to dimensionality reduction. In order to cost-effectively design the BARC scheme, we develop low-complexity decimation techniques, stochastic gradient and recursive least squares reduced-rank estimation algorithms. A model-order selection algorithm for adjusting the length of the estimators is devised along with techniques for determining the required number of switching branches to attain a predefined performance. An analysis of the convergence properties and issues of the proposed optimization and algorithms is carried out, and the key features of the optimization problem are discussed. We consider the application of the proposed algorithms to interference suppression in DS-CDMA systems. The results show that the proposed algorithms outperform the best known reduced-rank schemes, while requiring lower complexity.
Automatic text extraction from video for content-based annotation and retrieval

Efficient content-based retrieval of image and video databases is an important application due to rapid proliferation of digital video data on the Internet and corporate intranets. Text either embedded or superimposed within video frames is very useful for describing the contents of the frames, as it enables both keyword and free-text based search, automatic video logging, and video cataloging. We have developed a scheme for automatically extracting text from digital images and videos for content annotation and retrieval. We present our approach to robust text extraction from video frames, which can handle complex image backgrounds, deal with different font sizes, font styles, and font appearances such as normal and inverse video. Our algorithm results in segmented characters that can be directly processed by an OCR system to produce ASCII text. Results from our experiments with over 5000 frames obtained from twelve MPEG video streams demonstrate the good performance of our system in terms of text identification accuracy and computational efficiency.
Lower-Bounding of Dynamic Time Warping Distances for Multivariate Time Series

A tight lower-bounding measure for dynamic time warping (DTW) distances for univariate time series was introduced in [Keogh 2002] and a proof for its lower-bounding property was presented. Here we extend these findings to allow lower-bounding of DTW distances for multivariate time series.
Determination of the chelatable iron pool of single intact cells by laser scanning microscopy.

We have previously established a method of detecting intracellular chelatable iron in viable cells based on digital fluorescence microscopy. To quantify cellular chelatable iron, it was crucial to determine the intracellular indicator concentration. In the present study, we therefore adapted the method to confocal laser scanning microscopy, which should allow the determination of the indicator concentration on the single-cell level. The fluorescent heavy-metal indicator phen green SK (PG SK), the fluorescence of which is quenched by iron, was loaded into cultured rat hepatocytes. The hepatocellular fluorescence increased when cellular chelatable iron available to PG SK was removed from the probe by an excess of the membrane-permeable transition metal chelator 2,2'-dipyridyl (2, 2'-DPD, 5 mM). We optimized the scanning parameters for quantitatively recording changes in fluorescence and determined individual intracellular PG SK concentrations from the unquenched cellular fluorescence (after 2,2'-DPD) compared with PG SK standards in a "cytosolic" medium. An ex situ calibration method based on laser scanning microscopy was set up to determine the concentration of cellular chelatable iron from the increase of PG SK fluorescence after addition of 2,2'-DPD (5 mM). As the stoichiometry of the PG SK:Fe(2+) complex was 3:1 as long as PG SK was not limiting, cellular chelatable iron was calculated directly from absolute changes in cellular fluorescence. Using this method, we found 2.5 +/- 2.2 microM chelatable iron in hepatocytes. This method makes it possible to determine the pool of chelatable iron in single vital cells independently of cellular differences (e.g., dye loading, cell volume) in heterogeneous cell populations.
Discourse and Dialogue 6.1.1 beyond Sentence Interpretation 6.1.2 Interpretation and Generation in Context 6.2 Discourse Modeling 6.2.1 Overview: Discourse and Dialogue 6.2.2 Discourse Representation Theory

Computational work in discourse has focused on two di erent types of discourse: extended texts and dialogues, both spoken and written. Although there are clear overlaps between these|dialogues contain text-like sequences spoken by a single individual and texts may contain dialogues|the current state of the art leads research to focus on di erent questions for each. In addition, application opportunities and needs are di erent. Work on text is of direct relevance to document analysis and retrieval applications whereas work on dialogue is of import for human-computer interfaces regardless of the modality of interaction. A good sense of the current state of research in text interpretation can be gained from reading the papers on text interpretation in a recent special issue of Arti cial Intelligence (hereafter, AIJ-SI ), (Hobbs, Stickel, et al., 1994; Jacobs & Rau, 1994; Palmer, Passonneau, et al., 1994).
Biomarker genes highlight intraspecific and interspecific variations in the responses of Pinus taeda L. and Pinus radiata D. Don to Sirex noctilio F. acid gland secretions.

Sirex noctilio F. , a Eurasian horntail woodwasp recently introduced into North America, oviposits in pines and other conifers and in the process spreads a phytopathogenic fungus that serves as a food source for its larvae. During oviposition the woodwasp also deposits mucus produced in its acid (venom) gland that alters pine defense responses and facilitates infection by the fungus. A 26,496-feature loblolly pine cDNA microarray was used to survey gene expression of pine tissue responding to S. noctilio venom. Six genes were selected for further assessment by quantitative real-time polymerase chain reaction (qRT-PCR), including one that encoded an apparent PR-4 protein and another that encoded a thaumatin-like protein. Expression of both was strongly induced in response to venom, while expression of an apparent actin gene (ACT1) was stable in response to the venom. The pattern of gene response was similar in Pinus taeda L. and Pinus radiata D. Don, but the magnitude of response in P. radiata was significantly stronger for each of the induced genes. The magnitude of the biomarker gene response to venom also varied according to genotype within these two species. The qRT-PCR assay was used to demonstrate that the primary bioactive component in S. noctilio venom is a polypeptide.
Random Walk Distributed Dual Averaging Method For Decentralized Consensus Optimization

In this paper, we address the problem of distributed learning over a decentralized network, arising from scenarios including distributed sensors or geographically separated data centers. We propose a fully distributed algorithm called random walk distributed dual averaging (RW-DDA) that only requires local updates. Our RW-DDA method, improves the existing distributed dual averaging (DDA) method, making it robust to changes in network topology and amenable to asynchronous implementations. Our theoretical analysis shows the algorithm has O(1/ √ t) convergence for non-smooth convex problems. Various and valuable practical acceleration tricks are also introduced in the implementation. Experimental results show that our algorithm outperforms competing methods, especially in the presence of communication link failures.
Exploratory Landscape Analysis of Continuous Space Optimization Problems Using Information Content

Data-driven analysis methods, such as the information content of a fitness sequence, characterize a discrete fitness landscape by quantifying its smoothness, ruggedness, or neutrality. However, enhancements to the information content method are required when dealing with continuous fitness landscapes. One typically employed adaptation is to sample the fitness landscape using random walks with variable step size. However, this adaptation has significant limitations: random walks may produce biased samples, and uncertainty is added because the distance between observations is not accounted for. In this paper, we introduce a robust information content-based method for continuous fitness landscapes, which addresses these limitations. Our method generates four measures related to the landscape features. Numerical simulations are used to evaluate the efficacy of the proposed method. We calculate the Pearson correlation coefficient between the new measures and other well-known exploratory landscape analysis measures. Significant differences on the measures between benchmark functions are subsequently identified. We then demonstrate the practical relevance of the new measures using them as class predictors on a machine learning model, which classifies the benchmark functions into five groups. Classification accuracy greater than 90% was obtained, with computational costs bounded between 1% and 10% of the maximum function evaluation budget. The results demonstrate that our method provides relevant information, at a low cost in terms of function evaluations.
Novel Techniques to Derive Capacity Results for Multi-User Interference Channels

The Interference Channels (ICs) represent fundamental building blocks of wireless communication networks. Despite considerable progress in network information theory, available capacity results for ICs, specifically those with more than two users, are still very limited. One of the main difficulties in the analysis of these networks is how to establish useful capacity outer bounds for them. In this paper, novel techniques requiring subtle sequential application of Csiszar-Korner identity are developed to establish efficient single-letter outer bounds on the sum-rate capacity of interference networks. By using the outer bounds, a full characterization of the sum-rate capacity is then derived for various multi-user ICs under specific conditions. Our capacity results hold for both discrete and Gaussian networks.
HRS/EHRA/APHRS Expert Consensus Statement on the Diagnosis and Management of Patients with Inherited Primary Arrhythmia Syndromes

Class IIb 6. LCSD may be considered in patients with a diagnosis of CPVT who experience recurrent syncope or polymorphic/bidirectional VT/several appropriate ICD shocks while on beta-blockers and in patients who are intolerant or with contraindication to beta-blockers. Class III 7. ICD as a standalone therapy is not indicated in an asymptomatic patient with a diagnosis of CPVT. 8. Programmed electrical stimulation is not indicated in CPVT patients. ICD implantation may be considered in asymptomatic individuals who demonstrate a high-risk ER ECG pattern (high J-wave amplitude, horizontal/descending ST segment) in the presence of a strong family history of juvenile unexplained sudden death with or without a pathogenic mutation.
Rendering and Modeling of Stratus Cloud Using Weather Forecast Data

This paper presents a method for physically plausible modeling and real-time rendering of large scale cloud scene from weather forecast data which includes stratus clouds and cumulus clouds. Our method uses particles as primitives, but differs from existing methods, the particles are generated from the data using a new optical model, and then are splatted onto multi-resolution axis-aligned slices for rendering at interactive frame rates. In the cloud optics model, multiple light sources are used and multiple anisotropic Mie scattering and Rayleigh scattering are employed according to the particle optical depth. After particles are generated from weather forecast data, multi-resolution axis-aligned slices are generated. The rendering process can use these slices and be easily implemented on graphics hardware. The experiment results show that realistic cloud can be modeled and rendered at interactive frame rates.
Understanding consumers’ moral consciousness

The issue driving this paper is ‘Why don’t people, in their consumer role, have a well developed moral conscience? ’ To address this compelling question, the paper explores the moral consciousness of consumption behaviour (or lack thereof). The first part of the paper provides brief overviews of: (1) moral consciousness applied to consumption, (2) the essence of morality and ethics, (3) four facets of the field of ethics, (4) two moral development models, and (5) the affective domain of learning. The intent is to prepare the reader for a discussion of an approach to understanding the moral consciousness of consumption that integrates particular concepts drawn from the theory of ethics and morality with the moral development models and the affective domain of learning.
Epidemiological Interactions between Urogenital and Intestinal Human Schistosomiasis in the Context of Praziquantel Treatment across Three West African Countries

Background In many parts of sub-Saharan Africa, urogenital and intestinal schistosomiasis co-occur, and mixed species infections containing both Schistosoma haematobium and S. mansoni can be common. During co-infection, interactions between these two species are possible, yet the extent to which such interactions influence disease dynamics or the outcome of control efforts remains poorly understood. Methodology/Principal Findings Here we analyse epidemiological data from three West African countries co-endemic for urogenital and intestinal schistosomiasis (Senegal, Niger and Mali) to test whether the impact of praziquantel (PZQ) treatment, subsequent levels of re-infection or long-term infection dynamics are altered by co-infection. In all countries, positive associations between the two species prevailed at baseline: infection by one species tended to predict infection intensity for the other, with the strength of association varying across sites. Encouragingly, we found little evidence that co-infection influenced PZQ efficacy: species-specific egg reduction rates (ERR) and cure rates (CR) did not differ significantly with co-infection, and variation in treatment success was largely geographical. In Senegal, despite positive associations at baseline, children with S. mansoni co-infection at the time of treatment were less intensely re-infected by S. haematobium than those with single infections, suggesting competition between the species may occur post-treatment. Furthermore, the proportion of schistosome infections attributable to S. mansoni increased over time in all three countries examined. Conclusions/Significance These findings suggest that while co-infection between urinary and intestinal schistosomes may not directly affect PZQ treatment efficacy, competitive interspecific interactions may influence epidemiological patterns of re-infection post-treatment. While re-infection patterns differed most strongly according to geographic location, interspecific interactions also seem to play a role, and could cause the community composition in mixed species settings to shift as disease control efforts intensify, a situation with implications for future disease management in this multi-species system.