Miracle-dz/UniFAR-FTUs huggingface dataset:
A strategy to escape from local traps for sparse A* algorithm

in this paper the sparse A* algorithm (SAS) has been studied from the aspect of handling local traps. Firstly, SAS is briefly introduced and differences between the standard A* algorithm and SAS has been analyzed. The comparison shows that SAS is serious deficient in dealing with local traps, however it is very important for SAS to work in practical applications. Thirdly, a method to measure local traps is proposed. Based on this method, the efficiency of using different step lengths has been studied. Forth, a combined strategy to improve the performance of SAS is proposed, two simulation closed to real applications have proven the effectiveness of the proposed strategy.
DistanceADaptive ( DAD ) Broadcastingfor Ad Hoc Networks

In mobile ad hocnetworks, it is often necessaryto broadcast control information to all the constituent nodesin the network. Possible applications include searching for a destinationnode(asa part of routing) or a particular service suchasDNS look-up. Flooding, which is often deployed to achieve the above objective, is expensi ve in terms of overhead and wastesvaluableresourcessuchasbandwidth and power. An improvement to flooding is to chooseprobabilistically a subsetof nodesto rebroadcast. In this paper, we proposeto usethe signal-strength to improve the efficiencyof broadcasting. We proposea protocol to selecta set of nodes for rebroadcastingon the basisof their relative distancefr om the previous broadcast. We show how we can use the signal strength as an estimate of the relative nodedistance.Our simulations indicate that our approach can increasethe efficiencyof broadcastingsignificantly. Our simulations show that wecanachieve the samecoveragewith approximately 20% less rebroadcasts. In addition, the time taken by the global broadcastis also reducedby more than 20%.
Design implications for end-user debugging tools : a strategy-based view

End-user programmers‟ code (e.g., accountants‟ spreadsheet formulas) is fraught with errors. To help mitigate this problem, end-user software engineering research is becoming established. However, most of this work has focused on feature usage, rather than debugging strategies. If a debugging tool were to support end-user programmers‟ specific debugging strategy needs, what should it take into account and how? To consider the design of such tools, this work contributes a comprehensive overview of end-user debugging strategies at four strategy levels. An example empirical study in Microsoft Excel demonstrates that this view of debugging provides useful insights, and we argue that many of these insights generalize to other environments. Our results include end-user debugging tactics and the effective and ineffective moves employed to achieve them, ten end-user debugging strategems applied to a new environment, and how these strategems were used within three contexts: by strategy used, by sensemaking step, and by debugging phase. These findings coalesce into a comprehensive overview of end-user debugging strategies and detailed implications for the design of strategy-based end-user debugging tools.
ZebraRecognizer: Efficient and Precise Localization of Pedestrian Crossings

Autonomous mobility is a challenge for visually impaired people. In the last years, a number of solutions have been proposed in the scientific literature to support visually impaired people during road crossing. In our previous work we presented ZebraLocalizer a mobile application that detects zebra crossings and guides the user to safely cross. In this paper we present the ZebraRecognizer algorithm that improves the detection module of our solution and that applies innovative solutions in the field of zebra crossings recognition. The major contribution resides in the fact that ZebraRecognizer rectifies the ground plane hence removing the projection distortion of the extracted features. This leads to two major advantages: first, it possible to compute the relative distance between the user and the zebra crossing in meters. Second, the grouping and validation criteria specifically designed for the rectified line segments are much more effective, hence improving the accuracy of the recognition. An additional contribution consists in a significantly improved computation time. Indeed, ZebraRecognizer is 3 time faster than our previous solution, thanks to the adoption of a personalized version of the EDLines algorithm to detect the line segments.
Analysis of Synaptic Growth and Function in Drosophila with an Extended Larval Stage

The Drosophila larval neuromuscular junction (NMJ) is a powerful system for the genetic and molecular analysis of neuronal excitability, synaptic transmission, and synaptic development. However, its use for studying age-dependent processes, such as maintenance of neuronal viability and synaptic stability, are temporally limited by the onset of pupariation and metamorphosis. Here we characterize larval NMJ growth, growth regulation, structure, and function in a developmental variant with an extended third instar (ETI). RNAi-knockdown of the prothoracicotropic hormone receptor, torso, in the ring gland of developing larvae leaves the timing of first and second instar molts largely unchanged, but triples duration of the third instar from 3 to 9.5 d (McBrayer et al., 2007; Rewitz et al., 2009). During this ETI period, NMJs undergo additional growth (adding >50 boutons/NMJ), and this growth remains under the control of the canonical regulators Highwire and the TGFβ/BMP pathway. NMJ growth during the ETI period occurs via addition of new branches, satellite boutons, and interstitial boutons, and continues even after muscle growth levels off. Throughout the ETI, organization of synapses and active zones remains normal, and synaptic transmission is unchanged. These results establish the ETI larval system as a viable model for studying motor neuron diseases and for investigating time-dependent effects of perturbations that impair mechanisms of neuroprotection, synaptic maintenance, and response to neural injury.
Universal Interventions: Fully Exploring Their Impacts and Potential to Produce Population-Level Impacts

ABSTRACT In this article we seek to promote a deeper understanding of the value of universal intervention research in education as well as other fields and to call for greater interdisciplinary learning and discourse. Our goal is to deepen the conversation regarding how to build a stronger research orientation toward longitudinal, population-level outcomes in education and mental health. After highlighting the value of universal approaches targeting entire populations and their relevance to education, we raise issues regarding the traditional benchmarks of efficacy when applied to universal intervention trials and suggest alternative metrics for judging the impact of universal approaches. We conclude with lessons based on exemplar studies to help shape future research and policy regarding universal interventions.
Chilean Pitavia more closely related to Oceania and Old World Rutaceae than to Neotropical groups: evidence from two cpDNA non-coding regions, with a new subfamilial classification of the family

Abstract The position of the plant genus Pitavia within an infrafamilial phylogeny of Rutaceae (rue, or orange family) was investigated with the use of two non-coding regions from cpDNA, the trnL-trnF region and the rps16 intron. The only species of the genus, Pitavia punctata Molina, is restricted to the temperate forests of the Coastal Cordillera of Central-Southern Chile and threatened by loss of habitat. The genus traditionally has been treated as part of tribe Zanthoxyleae (subfamily Rutoideae) where it constitutes the monogeneric tribe Pitaviinae. This tribe and genus are characterized by fruits of 1 to 4 fleshy drupelets, unlike the dehiscent fruits typical of the subfamily. Fifty-five taxa of Rutaceae, representing 53 genera (nearly one-third of those in the family) and all subfamilies, tribes, and almost all subtribes of the family were included. Parsimony and Bayesian inference were used to infer the phylogeny; six taxa of Meliaceae, Sapindaceae, and Simaroubaceae, all members of Sapindales, were also used as out-groups. Results from both analyses were congruent and showed Pitavia as sister to Flindersia and Lunasia, both genera with species scattered through Australia, Philippines, Moluccas, New Guinea and the Malayan region, and phylogenetically far from other Neotropical Rutaceae, such as the Galipeinae (Galipeeae, Rutoideae) and Pteleinae (Toddalieae, former Toddalioideae). Additionally, a new circumscription of the subfamilies of Rutaceae is presented and discussed. Only two subfamilies (both monophyletic) are recognized: Cneoroideae (including Dictyolomatoideae, Spathelioideae, Cneoraceae, and Ptaeroxylaceae) and Rutoideae (including not only traditional Rutoideae but also Aurantioideae, Flindersioideae, and Toddalioideae). As a consequence, Aurantioideae (Citrus and allies) is reduced to tribal rank as Aurantieae.
On Farm Conservation of Rice Biodiversity in Nepal : a Simultaneous Estimation Approach

Sections of this material may be reproduced for personal and not-for profit use without the express written permission of but with acknowledgment to IFPRI. To reproduce the material contained herein for profit or commercial use requires express written permission. To obtain permission, contact the Communications Division at ifpri-copyright@cgiar.org. ABSTRACT This paper presents an empirical case study about farmer management of rice genetic resources in two communities of Nepal, drawing on interdisciplinary, participatory research that involved farmers, rice geneticists, and social scientists. The decision-making process of farm households is modelled and estimated in order to provide information for the design of community-based conservation programs. A bivariate model with sample selection treats the simultaneous process of whether farmers decide to plant landraces or modern varieties, and whether the landraces they choose to plant constitute genetic diversity of interest for future crop improvement. Findings show that the two landrace choices are affected by different social and economic factors. The estimation procedure demonstrates that in certain cases, however, the decision processes are interrelated. Policies to promote the conservation of local rice diversity will need to take both processes into account. Fitted equations are then used to compare the likelihood that households targeted for conservation according to one set of conservation criteria also meet other conservation criteria. Households most likely to plant landraces identified as important for crop improvement also grow richer, more spatially diverse rice varieties. In these communities, few policy trade-offs would result from employing one set of criteria instead of the other.
MOBILE ROBOT TRAJECTORY TRACKING USING MODEL PREDICTIVE CONTROL

This work focus on the application of model-based predictive control (MPC) to the trajectory tracking problem of nonholonomic wheeled mobile robots (WMR). The main motivation of the use of MPC in this case relies on its ability in considering, in a straightforward way, control a nd state constraints that naturally arise in practical proble ms. Furthermore, MPC techniques consider an explicit performance criterion to be minimized during the computation of the control law. The trajectory tracking problem is solved using two approaches: (1) nonlinear MPC and (2) linear MPC. Simulation results are provided in order to show the effectiveness of both schemes. Considerations regarding the computational effort of the MPC are developed with the purpose of analyzing the real-time implementation viability of the proposed techniques.
University of Calgary Feature Selection for Cancer Classification Using Microarray Gene Expression Data

The rapid development of DNA microarray technology enables researchers to measure the expression levels of thousands of genes simultaneously and allows biologists easily gain insight into the complex interaction in tumours on gene expression levels. Its application in cancer studies has been shown great success in both diagnosis and elucidating the pathological mechanism. However, DNA microarray data usually contains thousands of genes and most of them are proved to be uninformative and redundant. Meanwhile, small size of samples of microarray data undermines the diagnosis accuracy of statistical models. Thereby, selecting highly discriminative genes from raw gene expression data can improve the performance of cancer classification and cut down the cost of medical diagnosis. This M.Sc. thesis proposes and investigates a new method of selecting highly discriminative genes for cancer classification based on DNA microarray data. For two-group classification problem, the Bhattacharyya distance is proposed to measure the dissimilarity in gene expression levels between the two groups. For any particular gene, we calculate the Bhattacharrya distance between the two groups based on the expression levels of that particular gene. We use the calculated distances, one for each gene, as a criteria to rank all the genes. Finally, support vector machine is utilized to obtain the optimal subset of genes achieving the lowest misclassification rate. Compared with the other two methods, SWKC (supervised weighted kernel clustering) (Shim et al., 2009) and SVM-RFE (support vector machine with recursive feature elimination) (Guyon et al., 2002), the proposed method is shown to be more effective and sensitive to differentially expressed genes. In the simulation study, the proposed method has much higher recovery rate than the other two methods. Comparisons among these three gene selection methods are also made through two real DNA microarray datasets, the colon dataset and the leukemia dataset, that are publicly available. Based on three classification performance indexes, i.e. average number of genes selected, average number of classification errors in test set and misclassification rate, the proposed method gets slightly better classification results than SVM-RFE for the colon dataset while at a much less computation cost. It also achieves better classification results than the SWKC methods in both datasets. Finally, we discuss that in future work improvement in performance could be achieved by introducing kernel density estimators and replacing Bhattacharyya distance with Hellinger distance as a feature selection criteria. Since kernel density estimation is free of distribution assumptions, under which the classification results would be more robust than that obtained by the Bhattacharyya distance under normal assumption.
High Frequency Component Matching Motion Estimation : A Revolutionary Improvement for Real-Time Telemedicine Applications

In Telemedicine applications, for diagnostic purposes, it is essential that the video compression process causes no tangible loss of detail and introduces no noticeable artifacts which could be otherwise misinterpreted as being pathological in nature. On the other hand, due to the limitation of storage and transmission and the huge amount of medical video, high compression ratio is often required. Video coding exploits the high correlation between successive image frames to improve coding efficiency, which is achieved by motion estimation and motion compensation techniques. This paper demonstrates the feasibility of incorporating the high frequency component matching block motion estimation in H.264 in order to improve video compression performance in telemedicine applications. Implementation using the H.264 codec and thereby facilitating performance analysis, the experimental result indicates that high frequency component matching introduces a revolutionary improvement as a matching criterion for motion compensated predictive coding in real-time telemedicine applications.
PTSD and Psychological Debriefing

Following a personal, community or national crisis or disaster there is a need to provide some form of early intervention and crisis support. The essential components of successful early interventions include planning, education, training and support for those affected. The goal of all early interventions should be to maximize the likelihood of a positive mental health outcome using the person’s own adaptive coping mechanisms and support structures. Psychological debriefing (PD) has been described as an intervention conducted by trained professionals shortly after a catastrophe, allowing victims to talk about their experience and receive information on “normal” types of reactions to such an event. Psychological debriefing has been developed and has been at the centre of significant levels of controversy during the past 15 years. Talking through traumatic or stressful events may help the psychological recovery of those who have suffered psychological insults.
Light-Response Quantitative Trait Loci Identified with Composite Interval and eXtreme Array Mapping in Arabidopsis thaliana Sequence data from this article have been deposited with the EMBL/GenBank Data Libraries under accession nos. AY394847 and AY466496.

Genetic analysis of natural variation in ecotypes of Arabidopsis thaliana can facilitate the discovery of new genes or of allelic variants of previously identified genes controlling physiological processes in plants. We mapped quantitative trait loci (QTL) for light response in recombinant inbred lines (RILs) derived from the Columbia and Kashmir accessions via two methods: composite interval mapping and eXtreme array mapping (XAM). After measuring seedling hypocotyl lengths in blue, red, far-red, and white light, and in darkness, eight QTL were identified by composite interval mapping and five localized near photoreceptor loci. Two QTL in blue light were associated with CRY1 and CRY2, two in red light were near PHYB and PHYC, and one in far-red light localized near PHYA. The RED2 and RED5 QTL were verified in segregating lines. XAM was tested for the identification of QTL in red light with pools of RILs selected for extreme phenotypes. Thousands of single feature polymorphisms detected by differential DNA hybridized to high-density oligo-nucleotide arrays were used to estimate allele frequency differences between the pools. The RED2 QTL was identified clearly; differences exceeded a threshold of significance determined by simulations. The sensitivities of XAM to population type and size and genetic models were also determined by simulation analysis.
Joint optimization of carrier sensing threshold and transmission rate in wireless ad hoc networks

The ever-increasing demands of wireless traffic call for continuously growing the wireless network capacity or throughput. Carrier sensing threshold adaptation and transmission rate adaptation, two efficient mechanisms improving the capacity of ad hoc network, have attracted much attention in recent years. However, simply adopting either mechanism can hardly meet the expectation that optimizing the network capacity. In this paper, we investigate the joint optimization of carrier sensing threshold and transmission rate to improve the network capacity or throughput. The area capacity (throughput), which is defined as the network capacity (throughput) per unit area, is theoretically analyzed. Meanwhile, the relationship between carrier sensing threshold and transmission rate is theoretically revealed. Furthermore, the optimal area capacity is obtained by jointly optimizing the carrier sensing threshold and the transmission rate. Simulation results validate our analysis and derived results, and show that the throughput is significantly improved by the joint optimization.
Chain of Trust Testing Based on Model Checking

In 1998, Blaze, Bleumer, and Strauss proposed a kind of cryptographic primitive called proxy re-encryption. In proxy re-encryption, a proxy can transform a cipher text computed under Alice’s public key into one that can be opened under Bob’s decryption key. In this paper, with the help of the PKG, we construct a CCA-secure identity based proxy reencryption scheme based on a variant of BB1 identity based encryption (IBE), we also prove its security in the random oracle model.
Joint link-and-user scheduling for buffer-aided relaying system with adaptive rate transmission

In this paper, we consider a relaying system which consists of a multiple-antenna source node (SN), M single-antenna destination nodes (DNs) and a multiple-antenna relay node (RN). The RN possesses a buffer and it is able to store the decoded message before retransmitting the message to the DNs. We use the joint link-and-user scheduling method to maximize the long term average achievable rate of a multiple-input multiple-output (MIMO) relaying system. The optimal scheduling criteria is obtained and a two-step approach is proposed to implement it. In addition, we propose a rate allocation scheme of the source-relay (S-R) link to preserve the flow conservation constraint of each individual user. Furthermore, two reduced complexity joint link-and-user scheduling methods which use the zero forcing (ZF) beamforming in the relay-destination (RD) link are investigated. It is shown that joint link-and-user scheduling can significantly increase the average achievable rate of the system.
Mate choice for genetic quality when environments vary : suggestions for 2 empirical progress 3 4

23 Mate choice for good-genes remains one of the most controversial evolutionary 24 processes ever proposed. This is partly because strong directional choice should 25 theoretically deplete the genetic variation that explains the evolution of this type of 26 female mating preferences (the so-called lek paradox). Moreover, good-genes benefits 27 are generally assumed to be too small to outweigh opposing direct selection on 28 females. Here, we review recent progress in the study of mate choice for genetic 29 quality, focussing particularly on the potential for genotype by environment 30 interactions (GEIs) to rescue additive genetic variation for quality, and thereby 31 resolve the lek paradox. We raise five questions that we think will stimulate empirical 32 progress in this field, and suggest directions for research in each area: 1) How is 33 condition-dependence affected by environmental variation? 2) How important are 34 GEIs for maintaining additive genetic variance in condition? 3) How much do GEIs 35 reduce the signalling value of male condition? 4) How does GEI affect the 36 multivariate version of the lek paradox? 5) Have mating biases for high-condition 37 males evolved because of indirect benefits? 38 39