Miracle-dz/UniFAR-FTUs huggingface dataset:
Space-round tradeoffs for MapReduce computations

This work explores fundamental modeling and algorithmic issues arising in the well-established MapReduce framework. First, we formally specify a computational model for MapReduce which captures the functional flavor of the paradigm by allowing for a flexible use of parallelism. Indeed, the model diverges from a traditional processor-centric view by featuring parameters which embody only global and local memory constraints, thus favoring a more data-centric view. Second, we apply the model to the fundamental computation task of matrix multiplication presenting upper and lower bounds for both dense and sparse matrix multiplication, which highlight interesting tradeoffs between space and round complexity. Finally, building on the matrix multiplication results, we derive further space-round tradeoffs on matrix inversion and matching.
Validation of MODIS gross primary productivity for a subtropical coniferous plantation in Southern China

Terrestrial carbon cycle plays an important role in global climate change. As a key component of terrestrial carbon cycle, gross primary productivity (GPP) is a major determinant of the exchange of carbon between the atmosphere and terrestrial ecosystems. 8-day global GPP estimated from ground meteorological data and remotely sensed fraction of photosynthetic active radiation (fPAR) by MODIS using the light use efficiency approach is currently provided as MOD17 product. Previous studies indicated that MODIS GPP has large uncertainties in some ecosystems. In this study, GPP of a subtropical coniferous plantation at Qianyanzhou Experimental Station in southern China was firstly calculated using the MODIS GPP algorithm (MOD17 algorithm) driven by MODIS fPAR and measured meteorological data. Calculated GPP was validated using GPP measured during 2003 and 2004 with the eddy covariance technique. Then the potential to better MODIS GPP was investigated through comparing GPP calculated using the MOD17 algorithm and improved fPAR or/and maximum light use efficiency (εmax) calibrated with measured GPP. The results indicated that the MODIS GPP product significantly underestimated measured GPP at this planted forest. The R2 of MODIS GPP with measured GPP was 0.72 and 0.67 in 2003 and 2004, respectively. And the calculated annual GPP was 33% and 47% lower than measured values in these two years. The improvement on fPAR through using LAI data estimated with photosynthetic active radiation (PAR) measured above and below canopy can definitely remedy underestimation of annual GPP. The application of εmax determined through model calibration improved annual GPP more significantly, indicating that the errors in MODIS GPP at this site can be mainly attributed to the underestimation of fPAR and εmax. When the improved fPAR and εmax were used, the agreement between calculated and measured 8-day GPP improved significantly, with R2 equals to 0.78 and 0.85 for years 2003 and 2004, respectively. And the calculated annual GPP was only 3.5% lower and 1.3% higher than measured values in these two years. Through this study, it can be concluded that accurate εmax and LAI from which fPAR is calculated are required for reliably calculating regional/global GPP with the MOD17 algorithm. The fusion of flux data with remote sensing data can provide the accurate estimate of εmax andhas a great potential to control uncertainties in calculated regional/global GPP.
Supporting the professional development of teacher educators in a productive way

This study reports on what 13 teacher educators going through a procedure to become registered as a teacher educator in 2011–2012 learned, what goals they formulated for their further professional development and what activities they planned to achieve these goals. The methods used in this study are mainly the same as were used at the time the first cohort went through the registration procedure in 2002. The 2012 cohort participated in a supportive programme, whereas the 2002 cohort did not. This enables a comparison of the results of both studies and thus some insight into the possible benefits of integrating a registration procedure with a supportive programme for the professional development of teacher educators.
An improved z-buffer CSG rendering algorithm

We present an improved z-buffer based CSG rendering algorithm, based on previous techniques using z-buffer parity based surface clipping. We show that while this type of algorithm has been reported as requiring O( ), (where is the number of primitives), an O( ) (where is depth complexity) algorithm may be substituted. For cases where is less than this translates into a significant performance gain. CR Categories: I.3. 5 [Computing Methodologies]: Computer Graphics—Constructive solid geometry (CSG) I.3. 3 [Computing Methodologies]: Computer Graphics—Display Algorithms I.3. 1 [Computing Methodologies]: Computer Graphics—Hardware Architecture
Experimental investigations into the role of passive variable compliant legs for dynamic robotic locomotion

Biomechanical studies suggest that animals' abilities to tune their effective leg compliance in response to changing terrain conditions plays an important role in their agile, robust locomotion. However, despite growing interest in leg compliance within the robotics literature, little experimental work has been reported on tunable passive leg compliance in running machines. In this paper we present an empirical study into the role of leg compliance using a composite tunable leg design implemented on our dynamic hexapod, EduBot, with gaits optimized for running speed using a range of leg stiffnesses, on two different surface stiffnesses, and with two different payload configurations (0 kg and 0.91 kg). We found that leg stiffness, surface compliance, and payload had a significant impact on the robot's final optimized speed and efficiency. These results document the value and efficacy of what we believe is the first autonomous dynamic legged robot capable of runtime leg stiffness adjustment.
Severe B cell deficiency and disrupted splenic architecture in transgenic mice expressing the E41K mutated form of Bruton's tyrosine kinase

To identify B‐cell signaling pathways activated by Bruton's tyrosine kinase (Btk) in vivo, we generated transgenic mice in which Btk expression is driven by the MHC class II Ea gene locus control region. Btk overexpression did not have significant adverse effects on B cell function, and essentially corrected the X‐linked immunodeficiency (xid) phenotype in Btk− mice. In contrast, expression of a constitutively activated form of Btk carrying the E41K gain‐of‐function mutation resulted in a B cell defect that was more severe than xid. The mice showed a marked reduction of the B cell compartment in spleen, lymph nodes, peripheral blood and peritoneal cavity. The levels in the serum of most immunoglobulin subclasses decreased with age, and B cell responses to both T cell‐independent type II and T cell‐dependent antigens were essentially absent. Expression of the E41K Btk mutant enhanced blast formation of splenic B cells in vitro in response to anti‐IgM stimulation. Furthermore, the mice manifested a disorganization of B cell areas and marginal zones in the spleen. Our findings demonstrate that expression of constitutively activated Btk blocks the development of follicular recirculating B cells.
The quanser DC motor control trainer individual or team learning for hands-on control education - Product Review

ing is well aware of the economic demands of a laboratory course versus a lecture course. A lecture course can grow in size (at least to a reasonable extent) with minimal effect on the students and little marginal expense to the educational institution. A lab course, on the other hand, requires facilities in terms of benchtop equipment and lab space. One solution for accommodating a large lab class is to have students work in teams. In fact, in recent years there has been a widespread effort to promote “team projects” in engineering curricula based on the belief that team experiences build skills that are important for a professional career.
The use of ICTs and mobilisation in the age of parallel media – an emerging fifth estate? A case study of Nafeer's flood campaign in the Sudan

Abstract The fourth estate's power, in many African countries, has been restricted and its role as a catalyst of change in civil society curtailed. The ensuing information gap provided fertile ground for alternative forms of communication, to take centre stage. A parallel market of information has been facilitated by new technologies that circumvent government censorship. On 1 August 2013, heavy rains in the Sudan triggered flash floods that affected more than 530 000 citizens. The government failed to aid those affected and created a media blackout. More than 12 000 Sudanese volunteers created a horizontal network of citizens participating in a community-led initiative. The Nafeer campaign united the fragmented discourse, demonstrating that using ICTs to mobilise citizens is not contingent on the number of people with access, but on how access is channeled.
Analyzing the potential of mobile opportunistic networks for big data applications

The advantages brought by opportunistic data delivery make mobile opportunistic networking a promising technology for big data computing. Thus, it is important to study the potential of mobile opportunistic networks in supporting big data applications by analyzing their fundamental data dissemination properties. However, such an analysis is nontrivial as a large dimension of elements may affect the data spreading behavior in mobile opportunistic networks. In this article, we first outline the challenges of analyzing the potential of mobile opportunistic networks for big data applications. Then we survey the state-of-the-art analytical results on data dissemination properties in mobile opportunistic networks. Finally, we summarize our analytical results and present a few open research issues that may foster future research endeavors on mobile opportunistic networks to support big data applications.
Challenges in Requirements Engineering for Mobile Games Development: The Meantime Case Study

The development of new market-driven software products involves several challenges for the requirements engineering process. The challenges are deeper in the case these products are mobile video games. In particular, the mobile games must satisfy a number of critical non-functional requirements (e.g. portability, gameplay, emotional issues). In addition to that, mobile games are developed for mass market, demanding from the development team to understand the requirements of very diverse and sometimes unknown groups of stakeholders. This paper presents the experience of meantime, a global mobile game developing company, in conducting requirements engineering activities during the development of the Frogman game. It also presents some lessons learned in the process.
Automatic algorithm selection for MeSH Heading indexing based on meta-learning

We present a methodology that automati-cally selects indexing algorithms for each heading in MeSH, NLM’s vocabulary for indexing MEDLINE. While manually comparing indexing methods is manageable with a limited number of MeSH headings, a large number of them makes automation of this selection desirable. Results show that this process can be automated based on previously indexed MEDLINE records. We ﬁnd that AdaBoostM1 is better suited to index a group of MeSH headings named Check Tags and helps improve the micro F-measure from 0.5385 to 0.7157 and the macro F-measure from 0.4123 to 0.5387 (both p < 0 . 01 ).
How is visual salience computed in the brain? Insights from behaviour, neurobiology and modelling

Inherent in visual scene analysis is a bottleneck associated with the need to sequentially sample locations with foveating eye movements. The concept of a ‘saliency map’ topographically encoding stimulus conspicuity over the visual scene has proven to be an efficient predictor of eye movements. Our work reviews insights into the neurobiological implementation of visual salience computation. We start by summarizing the role that different visual brain areas play in salience computation, whether at the level of feature analysis for bottom-up salience or at the level of goal-directed priority maps for output behaviour. We then delve into how a subcortical structure, the superior colliculus (SC), participates in salience computation. The SC represents a visual saliency map via a centre-surround inhibition mechanism in the superficial layers, which feeds into priority selection mechanisms in the deeper layers, thereby affecting saccadic and microsaccadic eye movements. Lateral interactions in the local SC circuit are particularly important for controlling active populations of neurons. This, in turn, might help explain long-range effects, such as those of peripheral cues on tiny microsaccades. Finally, we show how a combination of in vitro neurophysiology and large-scale computational modelling is able to clarify how salience computation is implemented in the local circuit of the SC. This article is part of the themed issue ‘Auditory and visual scene analysis’.
MAGIC detection of short-term variability of the high-peaked BL Lac object 1ES 0806+524

The high-frequency-peaked BL Lac (HBL) 1ES 0806+524 (z = 0.138) was discovered in VHEγ rays in 2008. Until now, the broad-band spectrum of 1ES 0806+524 has been only poorly characterized, in particular at high energies. We analysed multiwavelength observations fromγ rays to radio performed from 2011 January to March, which were triggered by the high activity detected at optical frequencies. These observations constitute the most precise determination of the broad-band emission of 1ES 0806+524 to date. The stereoscopic MAGIC observations yielded aγ-ray signal above 250 GeV of (3.7± 0.7) per cent of the Crab Nebula flux with a statistical significa nce of 9. 9σ. The multiwavelength observations showed significant vari ability in essentially all energy bands, including a VHEγ-ray flare that lasted less than one night, which provided unp recedented evidence for short-term variability in 1ES 0806+524. The spectrum of this flare is well described by a power law with a photon index of 2.97± 0.29 between∼150 GeV and 1 TeV and an integral flux of (9.3± 1.9) per cent of the Crab Nebula flux above 250 GeV. The spectrum during the non-flaring VHE activity is compatible w ith the only available VHE observation performed in 2008 with VERITAS when the source was in a low optical state. The broad-band spectral energy distribution can be described with a one-zone Synchrotron Self Compton model with parameters typical for HBLs, indicating that 1ES 0806+524 is not substantially different from the HBLs previously detected.
Serial activation of distinct cytoarchitectonic areas of the human S1 cortex after posterior tibial nerve stimulation

MEG recordings visualized non-invasively a dynamic anterior–posterior activation in the pyramidal cell population of the human primary somatosensory cortex (S1) after posterior tibial nerve stimulation. Somatosensory evoked fields (SEFs) were recorded over the foot area in response to right posterior tibial nerve stimulation at the ankle in six normal subjects. A newly developed MEG vector beamformer technique applied to the SEFs revealed two distinct sources in the mesial wall of the left hemisphere around the primary P37m response typically separated by 1.3 cm. The first source was located in area 3b and oriented toward the contralateral hemisphere. The second source was assumed to be in an area near the marginal sulcus and the source orientation was directed posteriorly. The first source began to be active during the initial slope of the P37m. The second source was active after the P37m peak and the signal intensities of the first and second sources were equal at a mean latency of 2.6 ms after the peak of P37m. Then the first source became inactive and the second source was dominant after about 5 ms post-P37m peak. These findings suggest that a single peaked posterior tibial nerve P37m consists of partially overlapping two subcomponents generated in area 3b and an area near the marginal sulcus.
Theranostic Value of Multimers: Lessons Learned from Trimerization of Neurotensin Receptor Ligands and Other Targeting Vectors

Neurotensin receptor 1 (NTS1) is overexpressed on a variety of cancer entities; for example, prostate cancer, ductal pancreatic adenocarcinoma, and breast cancer. Therefore, it represents an interesting target for the diagnosis of these cancers types by positron emission tomography (PET). The metabolically-stabilized neurotensin (NT) derivative peptide Nlys8-Lys9-Pro10-Tyr11-Tle12-Leu13-OH was elongated at the N-terminus with 6-azido norleucine and coupled with the 1,4,7-triazacyclononane-1,4,7-tris[(2-carboxyethyl)methylenephosphinic acid] (TRAP) chelator TRAP(alkyne)3 in order to synthesize a NT trimer with subnanomolar affinity and high stability. The 68Ga-labeled peptide [68Ga]Ga-TRAP(NT4)3 was characterized in vitro using the NTS1-expressing human colorectal adenocarcinoma cell line HT29. It displayed fast and high internalization rates of >90%, but also fast efflux rates of 50% over 15 min. In vivo, [68Ga]Ga-TRAP(NT4)3 showed moderate HT29 tumor uptake values of 1.7 %ID/g at 60 min post-injection (p.i.), but also high uptake and retention in the kidneys and liver. A comparison of data for trimer/monomer pairs of NT ligands and other targeting vectors (peptides and peptoids targeting integrins αvβ3, α5β1, and αvβ6, the PSMA-ligand DUPA (2-[3-(1,3-dicarboxypropyl)-ureido]pentanedioic acid), and nitroimidazoles targeting hypoxia) revealed that multimers always exhibit higher target affinities and tumor uptake, but not necessarily improved tumor-to-tissue ratios. Thus, although in vitro data are not suitable for prediction of in vivo performance, multimers are potentially superior to monomers, particularly for applications where high tumor accumulation is crucial.
The Significance of Electronic Commerce to Firms' Operations in Relation to Business Location: an empirical investigation

Globalization of production and increasing competition spurs greater business use of innovative information systems. As globalization extends its reach over cities and regions, the positions of those places within the emerging global paradigms of regional economies is changing. Only those regions and cities that can mobilize assets for local advantage would succeed. This research examines the implications of location for electronic commerce (EC) role in firm operations through the lens of managerial perceptions of EC systems, EC activities, agglomeration economies, firm-specific features and outputs relative to industry. The input-based view and industrial development frameworks provide the theoretical underpinning for this research. Fully completed instruments from 106 firms in Singapore and Lagos financial services sector, respectively, are the basis of our analysis. Our findings reveal varying results between industries across the two cities, supporting our propositions. Firms with well-configured EC systems are more likely to experience efficiency in EC activities and outputs, given conducive operational conditions. However, firm-specific features were not linked to output, a finding inconsistent with prior studies. Finally, EC business models that focus on operational efficiency strongly complement the historically relevant location variable in industrial operations. These findings provide basis for recommendations to policymakers, practitioners, and researchers.
Image Texture Classification Based on Finite Gaussian Mixture Models

A novel image texture classification method based on finite Gaussian mixture models of sub-band coefficients is proposed in this paper. In the method, an image texture is first decomposed into several sub-bands, then the marginal density distribution of coefficients in each sub-band is approximated by Gaussian mixtures. The Gaussian component parameters are estimated by an “EM+MML” algorithm which performs parameter estimation and model selection automatically. The Earth Mover’s Distance (EMD) is used to measure the distributional similarity based on the Gaussian components. Thus, classification can be done by matching the marginal density distributions. Extensive experiments show that the proposed method achieved an overall improved classification accuracy compared to nonparametric representation of sub-band distributions.
Named Entity Disambiguation for little known referents: a topic-based approach

We propose an approach to Named Entity Disambiguation that avoids a problem of standard work on the task (likewise affecting fully supervised, weakly supervised, or distantly supervised machine learning techniques): the treatment of name mentions referring to people with no (or very little) coverage in the textual training data is systematically incorrect. We propose to indirectly take into account the property information for the “non-prominent” name bearers, such as nationality and profession (e.g., for a Canadian law professor named Michael Jackson, with no Wikipedia article, it is very hard to obtain reliable textual training data). The target property information for the entities is directly available from name authority files, or inferrable, e.g., from listings of sportspeople etc. Our proposed approach employs topic modeling to exploit textual training data based on entities sharing the relevant properties. In experiments with a pilot implementation of the general approach, we show that the approach does indeed work well for name/referent pairs with limited textual coverage in the training data.
B lymphocytes may escape tolerance by revising their antigen receptors

To explore mechanisms that prevent autoreactivity in nonautoimmune mice, endogenous immunoglobulin (Ig) light (L) chains that associate with a transgenic anti-DNA heavy chain were analyzed. The antibodies from splenic B cell hybridomas of such mice did not bind double- stranded DNA (dsDNA) and their L chain sequences showed a biased use of V kappa and J kappa gene segments. The 44 L chains in this survey were coded for by just 18 germline genes. Six of the genes, each belonging to a different V kappa group, were used more than once and accounted for three fourths of all sequences. Based on the distribution of V kappa genes, the L chain repertoire in this line of transgenic mice was estimated at 37 V kappa genes. The most frequently observed gene, a member of the V kappa 12/13 group, was identified in 16 hybrids. In addition, the majority of V kappa genes used J kappa 5. We interpret the skewed representation of V kappa and J kappa gene segments to result from negative selection. Based on the data, we suggest that V kappa rearrangements giving rise to anti-dsDNA reactivity are removed from the repertoire by a corrective mechanism capable of editing self- reactive Ig.
Detection of Urban Damage Using Remote Sensing and Machine Learning Algorithms: Revisiting the 2010 Haiti Earthquake

Remote sensing continues to be an invaluable tool in earthquake damage assessments and emergency response. This study evaluates the effectiveness of multilayer feedforward neural networks, radial basis neural networks, and Random Forests in detecting earthquake damage caused by the 2010 Port-au-Prince, Haiti 7.0 moment magnitude (Mw) event. Additionally, textural and structural features including entropy, dissimilarity, Laplacian of Gaussian, and rectangular fit are investigated as key variables for high spatial resolution imagery classification. Our findings show that each of the algorithms achieved nearly a 90% kernel density match using the United Nations Operational Satellite Applications Programme (UNITAR/UNOSAT) dataset as validation. The multilayer feedforward network was able to achieve an error rate below 40% in detecting damaged buildings. Spatial features of texture and structure were far more important in algorithmic classification than spectral information, highlighting the potential for future implementation of machine learning algorithms which use panchromatic or pansharpened imagery alone.