Miracle-dz/UniFAR-FTUs huggingface dataset:
The genetical theory of kin selection

Natural selection operates both directly, via the impact of a trait upon the individual’s own fitness, and indirectly, via the impact of the trait upon the fitness of the individual’s genetically related social partners. These effects are often framed in terms of Hamilton’s rule, rb − c > 0, which provides the central result of social‐evolution theory. However, a number of studies have questioned the generality of Hamilton’s rule, suggesting that it requires restrictive assumptions. Here, we use Fisher’s genetical paradigm to demonstrate the generality of Hamilton’s rule and to clarify links between different studies. We show that confusion has arisen owing to researchers misidentifying model parameters with the b and c terms in Hamilton’s rule, and misidentifying measures of genotypic similarity or genealogical relationship with the coefficient of genetic relatedness, r. More generally, we emphasize the need to distinguish between general kin‐selection theory that forms the foundations of social evolution, and streamlined kin‐selection methodology that is used to solve specific problems.
Computer-Aided Plant Species Identification (CAPSI) Based on Leaf Shape Matching Technique

In this paper, an efficient computer-aided plant species identification (CAPSI) approach is proposed, which is based on plant leaf images using a shape matching technique. Firstly, a Douglas - Peucker approximation algorithm is adopted to the original leaf shapes and a new shape representation is used to form the sequence of invariant attributes. Then a modified dynamic programming (MDP) algorithm for shape matching is proposed for the plant leaf recognition. Finally, the superiority of our proposed method over traditional approaches to plant species identification is demonstrated by experiment. The experimental result showed that our proposed algorithm for leaf shape matching is very suitable for the recognition of not only intact but also partial, distorted and overlapped plant leaves due to its robustness.
Influencing support of charitable objectives in the near and distant future: delay discounting and the moderating influence of construal level

Abstract Two studies investigated the delay discounting effect in charitable giving situations, and whether construal level moderates this effect. In both studies, construal level was manipulated by inducing a concrete vs. an abstract mindset. Participants were asked how much time (Experiment 1) or how much money (Experiment 2) they would be willing to volunteer or donate, respectively, to a self-chosen charitable organization in either the near or distant future. Participants committed themselves to contributing more time and money in the distant than in the near future. Additionally, an abstract (vs. concrete) mindset reduced this delay discounting effect, particularly for monetary donations. Delay discounting of costs associated with altruistic behavior and the role of construal level in increasing donations and volunteering are discussed.
The Alzheimer Aβ Peptide : Identification of Properties Distinctive for Toxic Prefibrillar Species

The formation of soluble prefibrillar oligomeric species of the amyloid β peptide (Aβ) has been implicated as a causative agent in the development of Alzheimer’s disease (AD). It is therefore important to characterize the properties of these aggregates, which precede the formation of amyloid fibrils. We studied the in vitro aggregation process of two Aβ40 peptide variants through the combined use of four different fluorescent probes and transmission electron microscopy. Previous studies have shown that these two studied Aβ40 variants exhibit different levels of neurodegeneration when expressed in the central nervous system of Drosophila melanogaster. In the present study, we demonstrate distinct differences in aggregate morphology and their binding properties to different fluorescent probes during in vitro fibrillation of these Aβ peptides. Our results indicate a potential link between the observed neurodegenerative properties and the biophysical properties of distinct aggregated Aβ species.
A simulation study on the stability-oriented routing protocols for mobile ad hoc networks

We present an extensive ns-2 (K. Fall and K. Varadhan) simulation-based performance comparison of three widely known stability-oriented mobile ad hoc network routing protocols: associativity-based routing (ABR) protocol (C-K Toh, 1997), flow-oriented routing protocol (FORP) (W. Su et al., 2001) and route assessment based routing (RABR) protocol (S. Agarwal et al., 2000). The order of the ranking of the protocols in terms of the packet delivery ratio and the number of route transitions is as follows: FORP, RABR, and ABR. The order of ranking in terms of the average hop count per route and end-to-end delay per packet is: ABR, RABR, and FORP. Thus, we see a stability-delay tradeoff within the class of stability-oriented routing protocols
Investigation of link layer algorithms and play-out buffer requirements for efficient multicast services in 3G cellular systems

The success of 3G networks depends on the possibility to attract customers to this new technology. Therefore, new services using the spectrum in an efficient manner while satisfying the customers are needed. We introduce link layer algorithms that are suitable for multicast transmission in 3G cellular systems and we present their impact on video application in terms of play-out buffer requirements. By our approach we show that hybrid ARQ solutions can be successfully employed to perform error control in the multicast transmission case. Using these schemes, performance can be increased thereby increasing system capacity and lowering the cost per served user. In the final part of the paper, these solutions are extended for the important multicast video streaming case, where new schemes are devised to avoid the throughput inefficiencies of fully reliable error recovery algorithms.
IMPACT ON STUDENT CHANGE IN SCIENTIFIC CREATIVITY AND SOCIO-SCIENTIFIC REASONING SKILLS FROM TEACHER COLLABORATION AND GAINS FROM PROFESSIONAL IN-SERVICE

This study examines the impact on 9 grade students’ change in socio-scientific reasoning and scientific creativity skills as a result of their science teachers’ professional change, as a result of participating in longitudinal in-service courses. Eight chemistry and four biology teachers participated in two consecutive intervention studies, each running for 8 months, both designed to guide teachers on promoting the level of scientific literacy in their students. During the in-service courses, the teachers created teaching materials for 4 integrative teaching modules and taught their students using a designed STL teaching approach. The students’ development was determined in terms of scientific creativity and socioscientific reasoning skills, as indicators of scientific literacy gains, with an initial pre-test in the fall of the school year and a post-test in the spring after the STL intervention. The results of the study revealed that the degree of teachers’ professional level in promoting problem solving and decision making teaching and its impact on student gains, as well as the number of teachers collaborating together in the teaching within a school, had a significant impact on their students’ improvement in skills associated with socio-scientific reasoning and scientific creativity.
Strategies for Searching Video Content with Text Queries or Video Examples

The large number of user-generated videos uploaded on to the Internet everyday has led to many commercial video search engines, which mainly rely on text metadata for search. However, metadata is often lacking for user-generated videos, thus these videos are unsearchable by current search engines. Therefore, content-based video retrieval (CBVR) tackles this metadata-scarcity problem by directly analyzing the visual and audio streams of each video. CBVR encompasses multiple research topics, including low-level feature design, feature fusion, semantic detector training and video search/reranking. We present novel strategies in these topics to enhance CBVR in both accuracy and speed under different query inputs, including pure textual queries and query by video examples. Our proposed strategies have been incorporated into our submission for the TRECVID 2014 Multimedia Event Detection evaluation, where our system outperformed other submissions in both text queries and video example queries, thus demonstrating the effectiveness of our proposed approaches.
Surface-roughness-scattering in non-planar channels — The role of band anisotropy

In this work, we investigate the effect of band structure anisotropy and channel orientation on SRS in non-planar channels such as tri-gate and GAA structures. A new formalism is introduced for calculating SRS rates for non-planar structures. The formalism is an extension of the theory by Prange and Nee for planar structures, which has been widely used for calculating the conductivity of inversion layers and thin films. We derive matrix elements for open and closed surfaces of arbitrary shape taking anisotropy of the band structure fully into account. Numerical experiments performed on tri-gate and GAA cross-sections indicate that SRS is greatly influenced by band anisotropy and channel orientation.
Investment in Telecommunications Markets: Evidence from OECD Countries

Recent studies provide strong evidence that the quality of telecommunications infrastructure has strong impacts on economic growth. Especially in Germany there is a controversial debate if we have a so called "infrastructure gap", because per capita investment in telecommunications infrastructure lags behind most of the levels in other OECD countries. To …nd appropriate policies to enhance infrastructure investment one has to get a thorough understanding of the determinants of infrastructure investment. Using a panel consisting of 30 OECD countries for the period 1990 to 2003 and taking account of possible non-stationarities in aggregate data, we investigate the main drivers of telecommunications investment on an aggregate level apply
Rapid object indexing using locality sensitive hashing and joint 3D-signature space estimation

We propose a new method for rapid 3D object indexing that combines feature-based methods with coarse alignment-based matching techniques. Our approach achieves a sublinear complexity on the number of models, maintaining at the same time a high degree of performance for real 3D sensed data that is acquired in largely uncontrolled settings. The key component of our method is to first index surface descriptors computed at salient locations from the scene into the whole model database using the locality sensitive hashing (LSH), a probabilistic approximate nearest neighbor method. Progressively complex geometric constraints are subsequently enforced to further prune the initial candidates and eliminate false correspondences due to inaccuracies in the surface descriptors and the errors of the LSH algorithm. The indexed models are selected based on the MAP rule using posterior probability of the models estimated in the joint 3D-signature space. Experiments with real 3D data employing a large database of vehicles, most of them very similar in shape, containing 1,000,000 features from more than 365 models demonstrate a high degree of performance in the presence of occlusion and obscuration, unmodeled vehicle interiors and part articulations, with an average processing time between 50 and 100 seconds per query
Social emergence in organisational contexts: benefits from multi-agent simulations

The paper at hand highlights how multi-agent simulations may help analyse meaningful organisational questions. This article relies on a model addressing Organisational Change based on empirical data put forth by Oreg in 2006. A bottom-up multi-agent model is derived. Simulations show that important details of social interdependence may be missing in the mainstream scientific examination of organisations, which only considers organisations at a systemic and/or macroscopic level. With our multi-agent model, we present a case in which the consideration of the micro-level and the simulation of individual interaction-processes grow meaningful emergent properties at the macro-level of the organisation. A series of simple experiments serves to exemplify the necessity of a more in-depth consideration of emergent macro-social processes.
Tomographic velocity images by radial basis function artificial neural network

The seismic tomography can be used to constrain estimates of the Earth's velocity structure. This kind of problem is usually known to be non-linear, high-dimensional, with a complex search space which may be riddled with many local minima, and results in irregular objective functions. We investigate here the performance and the application of a radial basis function artificial neural network (RBF-ANN) type, in the tomographic velocity reconstruction. The proposed structure has the advantage of being easily trained by means of a back-propagation algorithm without getting stuck in local minima. An adequate cross-validation test is run to ensure the performance of the network on new data sets. The application of such a network to synthetic data shows that the inverted seismic velocity section was efficient. A comparative reconstruction with tow classical methods was performed using Algebraic Reconstruction Technique (ART) Conjugate Gradient (CG). The results clearly show improvements of the quality of the reconstruction obtained by radial basis function artificial neural network.
TRECVID 2006 Rushes Exploitation By CAS MCG

In our rushes exploitation task of TRECVID 2006, we propose a novel and interactive rushes video selection and editing method based on hierarchical browsing of key frames, where high level features of each key frame such as face, interview, person, crowd, building, outdoor, waterbody, and other information about redundancy and repetition are displayed at same time for helping editors to select what they really want. During high level feature extraction, we propose a multi-modal interview detection method based on audio classification and face detection, and a new repetition detection method based on spatio-temporal slice. We also detect some concepts such as crowd, building, outdoor, waterbody based on SVM classifiers. Additionally, we characterize rushes by categorizing camera motion for inferring intention. Due to the difficulty of high level feature extraction and the diversity of editor’s requirements, our hierarchical browsing method along with extracted information may be a good choice for rushes exploitation.
Bridging the gap: Integrating cellular and functional magnetic resonance imaging studies of the hippocampus

The importance of the medial temporal lobe in memory has been studied extensively at the neuronal, neural ensemble, and systems level. In this report, we discuss recent systems level neuroimaging results in relation to neurophysiological studies of the hippocampus and related structures within the medial temporal lobe. By combining our knowledge across the cellular and systems levels we sought to gain theoretical insight and a better understanding of the function of the hippocampus and related medial temporal lobe structures. The integration of information from studies carried out at the cellular and neural ensemble level with studies at the systems level is difficult because of the vast differences in spatial and temporal resolution of the different research methodologies, differences in neuroanatomy across species, and differences in the types of behavioral and cognitive paradigms used in rat, nonhuman primate, and human studies. Despite these methodological and species‐related differences, the neurophysiological studies offer insight into many of the questions raised by recent neuroimaging studies. For instance, there is physiological evidence that suggests that the hippocampal memory system is functionally heterogeneous, which may explain some of the discrepancies in the location and extent of activation reported by different imaging studies of the medial temporal lobe. In addition, we describe recent computational models of the hippocampus which may be useful for bridging the gap between neurophysiological and neuroimaging data. Hippocampus 1999;9:45–53. © 1999 Wiley‐Liss, Inc.
Predictive Current Control of an Induction Machine Fed by a Matrix Converter With Reactive Power Control

A different approach to perform the control of an induction machine fed by a matrix converter (MC) is presented in this paper. The proposed technique is based on predictive control and effectively controls input and output variables to the power converter, as expected from an MC. The method allows the use of all valid switching states, including rotating vectors that are not considered in most control techniques, as space vector modulation or direct torque control for induction machines fed by MCs. Experimental results show the excellent performance of the proposed approach, with low-distortion input currents, adjustable power factor, sinusoidal output currents with smooth frequency transitions, and good speed control in motoring and regeneration conditions, even working under an unbalanced power supply. The implementation and comprehension of the method should be considered simple compared to other control strategies with similar features. The high computational effort required should not be a problem considering recent progresses in digital signal processors-and even less in years to come.
Molecular Cloning and Characterisation of Farnesyl Pyrophosphate Synthase from Tripterygium wilfordii

Farnesylpyrophosphate synthase (FPS) catalyzes the biosynthesis of farnesyl pyrophosphate (FPP), which is an important precursor of sesquiterpenoids such as artemisinin and wilfordine. In the present study, we report the molecular cloning and characterization of two full-length cDNAs encoding FPSs from Tripterygium wilfordii (TwFPSs). TwFPSs maintained their capability to synthesise FPP in vitro when purified as recombinant proteins from E. coli. Consistent with the endogenous role of FPS in FPP biosynthesis, TwFPSs were highly expressed in T. wilfordii roots, and were up-regulated upon methyl jasmonate (MeJA) treatment. The global gene expression profiles suggested that the TwFPSs might play an important regulatory role interpenoid biosynthesis in T. wilfordii, laying the groundwork for the future study of the synthetic biology of natural terpene products.
Hot Dust Close to the Young Massive StarHerschel 36

The O7 star Herschel 36 is responsible for the ionisation of the \hourglass" region in M 8. Adaptive optics near-infrared observations with ADONIS connrmed its association with compact diiuse emission. This feature is most likely due to scattered light and thermal radiation from dust grains which are situated very close to the massive star. Mid-infrared and radio continuum observations strongly support this view. These ndings are discussed in the framework of possible explanations:-Another proplyd-type object close to Herschel 36,-A deeply embedded massive protostar close to the line of sight towards Herschel 36,-Disk debris left from the formation of the high-mass star,-An evaporating gaseous globule close to the O star.
Stroke level HMMs for on-line handwriting recognition

The recent development of new terminals such as phones, mobile computers, e-books, etc, raises the needs for new interface modalities, in order to replace or complement the traditional mouse/keyboard interface. Ideally, these new interfaces should use limited computing resources and should be easy to adapt to a specific user and to a large variety of user needs. We propose here a new handwriting recognition system that is an attempt to handle these constraints. We evaluate its performances and ability to adapt to new users on a part of the Unipen database.
Using Paraphrases of Deep Semantic Representions to Support Regression Testing in Spoken Dialogue Systems

Rule-based spoken dialogue systems require a good regression testing framework if they are to be maintainable. We argue that there is a tension between two extreme positions when constructing the database of test examples. On the one hand, if the examples consist of input/output tuples representing many levels of internal processing, they are fine-grained enough to catch most processing errors, but unstable under most system modifications. If the examples are pairs of user input and final system output, they are much more stable, but too coarse-grained to catch many errors. In either case, there are fairly severe difficulties in judging examples correctly. We claim that a good compromise can be reached by implementing a paraphrasing mechanism which maps internal semantic representations into surface forms, and carrying out regression testing using paraphrases of semantic forms rather than the semantic forms themselves. We describe an implementation of the idea using the Open Source Regulus toolkit, where paraphrases are produced using Regulus grammars compiled in generation mode. Paraphrases can also be used at run-time to produce confirmations. By compiling the paraphrase grammar a second time, as a recogniser, it is possible in a simple and natural way to guarantee that confirmations are always within system coverage.
Locality based discriminative measure for multiple-shot person re-identification

Multiple-shot person re-identification tackles the problem to build the correspondences between sets of human images obtained from distributed cameras. It is challenging due to large within-class variations and small between-class differences, caused by the changing of human appearance and environment. Existing methods for addressing this issue include designing the representation to capture the within-set correlation, or crafting the measure to explore the between-set separation. This paper proposes a novel set based matching model called “Locality Based Discriminative Measure (LBDM)”, in which the discriminative potentiality of a new set-to-set distance is exploited by using the learned local metric field. As experimentally demonstrated, the proposal remarkably outperforms state-of-the-art schemes on public benchmark datasets.
A broadband beamforming method based on microphone array for the speech enhancement

A broadband beamforming method based on wavelet filterbanks and adaptive beamforming is proposed for speech enhancement in this paper. First, using the wavelet analysis filterbanks, noisy speech signals are transformed into wavelet domain with wavelet coefficients as output. Then the beamforming based on generalized sidelobe canceller (GSC) operates on the wavelet coefficients. Finally, the enhanced full-band speech signals were finally reconstructed by synthesizing the enhanced subband speech signals by used of the wavelet synthesis filterbanks. Simulation results demonstrate its effect.