Miracle-dz/UniFAR-FTUs huggingface dataset:
Integrating remotely sensed lai with epic model based on global optimization algorithm for regional crop yield assessment

Assimilating external data into crop growth model to improve accuracy of crop growth monitoring and yield estimation has been being a research hotspot in recent years. In this paper, the global optimization algorithm SCE-UA (Shuffled Complex Evolution method - University of Arizona) was used to integrate remotely sensed leaf area index (LAI) with crop growth model EPIC to simulate regional yield, sowing date, plant density and net nitrogen fertilizer application rate of summer maize in Huanghuaihai Plain. The final results showed that average relative error of estimated summer maize yield was 4.37% and RMSE was 0.44t/ha. Meanwhile, compared with actual observation and investigation data, average relative error of simulated sowing date, plant density and net N fertilization application rate was 1.85%, −7.78% and −10.60% respectively. These above accuracy of simulated results could meet the need of crop monitoring at regional scale. It was proved that integrating remotely sensed LAI with EPIC model based on global optimization algorithm SCE-UA for simulation of crop growth condition and crop yield was feasible.
Design of titanium alloy for efficient sintering to low porosity

Few Ti alloys have been designed for ease of sintering. This paper considers the design of alloys for processing using the mixed elemental technique, in which powders are mixed, cold pressed in a die to near net shape and sintered under vacuum at high temperature. The authors describe steps in the process of developing a Ti–Ni–Sn alloy, able to be sintered to near full density at a sintering temperature as low as 1100°C without requiring unusually fine powder or high compaction pressure. Higher sintering temperature allows the Ni content of the alloy to be reduced, but swelling of the alloy probably imposes an upper limit on practical sintering temperature. The increase in green density, and hence sintered density, conferred by Sn in Ti–Sn alloys, and the increase in sintered density due to the high diffusivity of Ni in Ti–Ni alloys, are combined in Ti–Ni–Sn alloys.
Infrared-transparent polymer solar cells

Transparent solar cells are very useful in making transparent electrical power supplies and tandem devices. We report the fabrication of semi-transparent polymer solar cells by replacing conventional metal electrode with a carbon nanotube film. The solar cells can be illuminated at both front and back sides, with power conversion efficiencies (up to 2.5%) comparable to cells using metal electrodes. The solar cells are highly transparent in near-infrared region, with an optical transmittance of nearly 80% in the range of 670 nm to 1.2 μm, and maintain a transmittance of above 60% through 1.2 to 2.5 μm. We further constructed a tandem structure with two subcells operating separately, in which the back cell receives infrared light transmitted through the front cell. Our infrared-transparent solar cells possess multiple functions such as serving as a light filter to drive a CdSe nanobelt photo-sensor with enhanced wavelength selectivity.
Effective Capacity and Randomness of Closed Sets

We investigate the connection between measure and capacity for the space of nonempty closed subsets of {0,1}*. For any computable measure, a computable capacity T may be defined by letting T(Q) be the measure of the family of closed sets which have nonempty intersection with Q. We prove an effective version of Choquet's capacity theorem by showing that every computable capacity may be obtained from a computable measure in this way. We establish conditions that characterize when the capacity of a random closed set equals zero or is >0. We construct for certain measures an effectively closed set with positive capacity and with Lebesgue measure zero.
Topology and Differential Geometry-based Three-dimensional Characterization of Pearlite Spheroidization

1) National Institute for Materials Science, Innovative Materials Engineering Laboratory, 1-2-1 Sengen, Tsukuba, Ibaraki, 305-0047 Japan. 2) Foremerly at National Institute for Materials Science, Innovative Materials Engineering Laboratory. Nowat Department of Mechanical Engineering, Graduate School of Science and Engineering, Kagoshima University, Korimoto 1-21-24, Kagoshima, 890-8580 Japan. E-mail: adachi@mech.kagoshima-u.ac. jp(
Human?Robot Interaction and Neuroprosthetics: A review of new technologies.

New technologies in the field of neuroprosthetics and robotics are leading to the development of innovative commercial products based on user-centered, functional processes of cognitive neuroscience and perceptron studies. The aim of this review is to analyze this innovative path through the description of some of the latest neuroprosthetics and human-robot interaction applications, in particular the brain-computer interface (BCI) linked to haptic systems, interactive robotics, and autonomous systems. These issues will be addressed by analyzing developmental robotics and examples of neurorobotics research. These new devices show the benefits of using an interdisciplinary approach based on cognitive neuroscience, embodied and situated cognition, neural network, and deep learning. All of these products share the capability to adapt, online, to the dynamic environment and to the user's actions. As the role of the human tutor is key in this learning process, these systems permit a natural and dynamic approach to interaction among people, neuroprosthetics, and robotics self-extensions.
Reliability Estimation of Three Single-Phase Topologies in Grid-Connected PV Systems

This paper presents the reliability estimation of the power stages in three grid-connected photovoltaic systems. The circuits analyzed are an integrated topology, a two-stage configuration, and a three-stage one, all commutating in the hard-switching mode. The reliability-related parameters, such as the failure rate, are calculated following the procedure outlined in MIL-HDBK 217. A comparison between the topologies is performed, and both the components and the stress factor with the highest contribution to the failure rate are identified. The methods to calculate junction temperature variations are included.
Learning responsive robot behavior by imitation

In this paper we present a new approach for learning responsive robot behavior by imitation of human interaction partners. Extending previous work on robot imitation learning, that has so far mostly concentrated on learning from demonstrations by a single actor, we simultaneously record the movements of two humans engaged in on-going interaction tasks and learn compact models of the interaction. Extracted interaction models can thereafter be used by a robot to engage in a similar interaction with a human partner. We present two algorithms for deriving interaction models from motion capture data as well as experimental results on a humanoid robot.
DC-110GHz continuous variable attenuator based on 65nm CMOS process

Continuous variable attenuator with wide bandwidth has been designed and fabricated in a 65nm CMOS process. This π-type with three shunt FETs in one side demonstrates state-of-the art performance showing a minimum insertion loss of 0.13–2.48 dB and good matching across the whole band. The attenuator has a continuous controllability from DC-110GHz with an attenuation range more than 16 dB as voltage bias changed constantly varies from 0 to 1.2V. Measurements also show return loss is greater than −22dB from 10 to 110GHz. The chip size is 340×280um2 and the core area is 26×109um2.
NexusVIS: A distributed visualization toolkit for mobile applications

Many mobile pervasive applications need to visualize information about the user's geographic surroundings combined with data from sensors, which determine the user's context. We demonstrate NexusVIS, a distributed visualization toolkit for mobile applications. By building upon an existing data stream processing system we enable applications to define distributed visualization processes as continuous queries. This allows applications to define visualization semantics descriptively. Moreover, NexusVIS is capable of adapting the visual query at runtime, and thus allows to navigate in the visualized scene both automatically and manually through user control.
Exact Expressions for the Condition Number Distribution of Complex Wishart Matrices

The standard condition number (SCN) is a fundamental metric in the context of multiple-input multiple-output communication systems, linear detection and classical linear algebra. Hence, in this paper we propose a novel generic framework for the SCN distribution of three different classes of Wishart matrices which leads to new results and insights. In particular, our analysis covers both central and non-central Wishart distributions of arbitrary dimension and therefore is applicable to uncorrelated/semi-correlated Rayleigh fading and Ricean fading scenarios. For the special case of dual semi-correlated central Wishart matrices, we derive exact and asymptotic polynomial expressions for the SCN distributions. All analytical results are validated via Monte-Carlo simulations with the attained accuracy being excellent in all cases. The impact of the model parameters on channel conditioning is also investigated in detail.
Online The Open University ’ s repository of research publications and other research outputs Semantic learning narratives Conference Item

In this paper we highlight the importance of an interpretation of the learning process from a narrative perspective and show how Semantic Web technologies, in particular ontologies, can serve to represent the key dimensions of this approach and to support an intelligent navigation of learning resources. Here we introduce our initial work in order to formalize the structure of these “learning narratives” in the domain of philosophy.
Sparse group factor analysis for biclustering of multiple data sources

MOTIVATION Modelling methods that find structure in data are necessary with the current large volumes of genomic data, and there have been various efforts to find subsets of genes exhibiting consistent patterns over subsets of treatments. These biclustering techniques have focused on one data source, often gene expression data. We present a Bayesian approach for joint biclustering of multiple data sources, extending a recent method Group Factor Analysis to have a biclustering interpretation with additional sparsity assumptions. The resulting method enables data-driven detection of linear structure present in parts of the data sources. RESULTS Our simulation studies show that the proposed method reliably infers biclusters from heterogeneous data sources. We tested the method on data from the NCI-DREAM drug sensitivity prediction challenge, resulting in an excellent prediction accuracy. Moreover, the predictions are based on several biclusters which provide insight into the data sources, in this case on gene expression, DNA methylation, protein abundance, exome sequence, functional connectivity fingerprints and drug sensitivity. AVAILABILITY AND IMPLEMENTATION http://research.cs. aalto.fi/pml/software/GFAsparse/ CONTACTS : kerstin.bunte@googlemail.com or samuel.kaski@aalto.fi.
The contribution of parasitism to selection on floral traits in Heuchera grossulariifolia

Parasites are ubiquitous and have well‐documented ecological consequences. In contrast, the extent to which parasites drive phenotypic evolution in hosts remains obscure. We use a recently developed statistical technique – selective source analysis – to analyse the strength of phenotypic selection acting on floral traits in the plant Heuchera grossulariifolia attributable to attack by the seed‐parasitic moth, Greya politella. This analysis spanned 3 years and included two sympatric populations of the host plant H. grossulariifolia that differ in ploidy. Our analyses revealed that attack by G. politella contributed to phenotypic selection for flowering time and floral display size, favouring earlier flowering in the polyploid population, later flowering in the diploid population and increased floral display size in the polyploid population. Although selection imposed by parasite attack was generally quite weak, in one of the 3 years parasites generated a modestly strong selection gradient (β = −0.059) that explained 38.6% of total observed phenotypic selection for earlier flowering in the polyploid population. Together, our results demonstrate parasites can generate significant phenotypic selection, but that such selection may be sporadic across populations and time.
1 2 Ju l 2 01 7 Cooperative Game Theory Approaches for Network Partitioning

The paper is devoted to game-theoretic methods for community detection in networks. The traditional methods for detecting community structure are based on selecting denser subgraphs inside the network. Here we propose to use the methods of cooperative game theory that highlight not only the link density but also the mechanisms of cluster formation. Specifically, we suggest two approaches from cooperative game theory: the first approach is based on the Myerson value, whereas the second approach is based on hedonic games. Both approaches allow to detect clusters with various resolution. However, the tuning of the resolution parameter in the hedonic games approach is particularly intuitive. Furthermore, the modularity based approach and its generalizations can be viewed as particular cases of the hedonic games.
Identification of Powdery Mildew Responsive Genes in Hevea brasiliensis through mRNA Differential Display

Powdery mildew is an important disease of rubber trees caused by Oidium heveae B. A. Steinmann. As far as we know, none of the resistance genes related to powdery mildew have been isolated from the rubber tree. There is little information available at the molecular level regarding how a rubber tree develops defense mechanisms against this pathogen. We have studied rubber tree mRNA transcripts from the resistant RRIC52 cultivar by differential display analysis. Leaves inoculated with the spores of O. heveae were collected from 0 to 120 hpi in order to identify pathogen-regulated genes at different infection stages. We identified 78 rubber tree genes that were differentially expressed during the plant–pathogen interaction. BLAST analysis for these 78 ESTs classified them into seven functional groups: cell wall and membrane pathways, transcription factor and regulatory proteins, transporters, signal transduction, phytoalexin biosynthesis, other metabolism functions, and unknown functions. The gene expression for eight of these genes was validated by qRT-PCR in both RRIC52 and the partially susceptible Reyan 7-33-97 cultivars, revealing the similar or differential changes of gene expressions between these two cultivars. This study has improved our overall understanding of the molecular mechanisms of rubber tree resistance to powdery mildew.
Discerning Tactical Patterns for Professional Soccer Teams: An Enhanced Topic Model with Applications

Analyzing team tactics plays an important role in the professional soccer industry. Recently, the progressing ability to track the mobility of ball and players makes it possible to accumulate extensive match logs, which open a venue for better tactical analysis. However, traditional methods for tactical analysis largely rely on the knowledge and manual labor of domain experts. To this end, in this paper we propose an unsupervised approach to automatically discerning the typical tactics, i.e., tactical patterns, of soccer teams through mining the historical match logs. To be specific, we first develop a novel model named Team Tactic Topic Model (T3M) for learning the latent tactical patterns, which can model the locations and passing relations of players simultaneously. Furthermore, we demonstrate several potential applications enabled by the proposed T3M, such as automatic tactical pattern discovery, pass segment annotation, and spatial analysis of player roles. Finally, we implement an intelligent demo system to empirically evaluate our approach based on the data collected from La Liga 2013-2014. Indeed, by visualizing the results obtained from T3M, we can successfully observe many meaningful tactical patterns and interesting discoveries, such as using which tactics a team is more likely to score a goal and how a team's playing tactic changes in sequential matches across a season.
Mechanisms of the Shape Memory Effect in Polymeric Materials

This review paper summarizes the recent research progress in the underlying mechanisms behind the shape memory effect (SME) and some newly discovered shape memory phenomena in polymeric materials. It is revealed that most polymeric materials, if not all, intrinsically have the thermo/chemo-responsive SME. It is demonstrated that a good understanding of the fundamentals behind various types of shape memory phenomena in polymeric materials is not only useful in design/synthesis of new polymeric shape memory materials (SMMs) with tailored performance, but also helpful in optimization of the existing ones, and thus remarkably widens the application field of polymeric SMMs.
Tasks for assessment of the episodic buffer: a systematic review

aim of the present study was to review the tasks that have been used to assess the functioning of the episodic buffer in Baddeley's multicomponent model of working memory. A systematic review of studies published from January 2000 to February 2013 was conducted. The search term "episodic buffer" was used in the Web of Knowledge, PsycINFO, PubMed, Embase, and BVS-Psi databases. The selected articles consisted of empirical studies that used tasks to assess the episodic buffer. Theoretical and review papers and studies with animals were excluded. The final sample comprised 36 papers. The tasks were categorized as experimental tasks or standardized tests. The experimental tasks were grouped by modality (unimodal or crossmodal) and described according to four criteria: task to be performed, type of stimulus used, secondary task employed, if any, and retention interval. The standardized tests included classical measures of working memory. Some tasks were found to not meet the experimental criteria that were needed to evaluate the episodic buffer. Moreover, some of the standardized tests did not provide theoretical arguments or empirical evidence that the episodic buffer is recruited to perform them. The results are discussed in the context of the multicomponent model of working memory. Keywords: working memory, episodic buffer, binding, experimental task, standardized test.
An Interactive Framework Based on Geometry Driven Data Distribution and Parallelisation

In this paper, we present an interactive framework, which is capable of delivering access to huge amounts of data from Building Information Models (BIM) and digital terrain data by using hierarchical data structures and elaborate algorithms in an efficient multi-level fashion. This framework bridges the gap between big datasets and accurate numerical simulations by exploiting parallelisation and data distribution techniques based on the geometric information existing at various levels. By having such a framework at hand, results of numerical simulations become applicable, which take on the one hand side multi-level geometric information from a global to a fine detailed level into account, and on the other hand side can make use of auxiliary information. These auxiliary information result from the underlying product model data and give the input for simulation relevant details, such as part specific material parameters e.g. As applications of the framework, besides a scalable parallel immersive visualisation, we present the integration of a massive parallel CFD simulation following the Lattice-BoltzmannMethod, a multi-scale extension of a spatial version of the Structured-Query-Language(SQL), and the coupling to a grid generation framework.
An Empirical Analysis of the Pricing of Collateralized Debt Obligations

We study the pricing of collateralized debt obligations (CDOs) using an extensive new data set for the actively-traded CDX credit index and its tranches. We find that a three-factor portfolio credit model allowing for firm-specific, industry, and economywide default events explains virtually all of the time-series and crosssectional variation in CDX index tranche prices. These tranches are priced as if losses of 0.4, 6, and 35 percent of the portfolio occur with expected frequencies of 1.2, 41.5, and 763 years, respectively. On average, 65 percent of the CDX spread is due to firm-specific default risk, 27 percent to clustered industry or sector default risk, and 8 percent to catastrophic or systemic default risk. Recently, however, firm-specific default risk has begun to play a larger role.
Atomic force microscopy with carbon nanotube tip for critical dimension measurement

Since the carbon nanotube (CNT) tip was first reported in 1996, its application to CD metrology has been an interest because of its unique properties. It is needle-like, which is the ideal shape as the scanning probe. In addition it elastically buckles, and therefore is robust and does not produce damage to the surface. It is also hydrophobic. The conventional AFM tip has the pyramidal or conical shape, so that either the steep side wall or high aspect ratio pattern like deep and narrow trench is difficult to measure, although the obtained image tends to be more stable than with the other kinds of tips. Recently, FIB(focused ion beam) tip or HDC(high dense carbon) tip with high aspect ratio structure became commercially available, improving the measurement capability of AFM. They are, however, weaker compared with the conventional tip, and still subject to the wear and contamination. In spite of the theoretical advantages, more researches seem to be needed either to make the CNT tip practicable for the precision CD measurement or even to examine its usefulness as a routine metrology tool. At KRISS, the geometry of the CNT tip is being improved by using the 3D manipulator in SEM for better performance, while commercial CNT tips are already available. Two kinds of patterns, groove and dot, have been measured with the three kinds of tips(conventional, HDC, and CNT as home-made). The AFM measurement results are compared, and the characteristics of CNT tips at the current stage, are discussed from the practical point of view.
Educational expansion and inequalities in mortality—A fixed-effects analysis using longitudinal data from 18 European populations

Objective The aim of this paper is to empirically evaluate whether widening educational inequalities in mortality are related to the substantive shifts that have occurred in the educational distribution. Materials and methods Data on education and mortality from 18 European populations across several decades were collected and harmonized as part of the Demetriq project. Using a fixed-effects approach to account for time trends and national variation in mortality, we formally test whether the magnitude of relative inequalities in mortality by education is associated with the gender and age-group specific proportion of high and low educated respectively. Results The results suggest that in populations with larger proportions of high educated and smaller proportions of low educated, the excess mortality among intermediate and low educated is larger, all other things being equal. Conclusion We conclude that the widening educational inequalities in mortality being observed in recent decades may in part be attributed to educational expansion.