Miracle-dz/UniFAR-FTUs huggingface dataset:
Insect eggs induce a systemic acquired resistance in Arabidopsis.

Although they constitute an inert stage of the insect's life, eggs trigger plant defences that lead to egg mortality or attraction of egg parasitoids. We recently found that salicylic acid (SA) accumulates in response to oviposition by the Large White butterfly Pieris brassicae, both in local and systemic leaves, and that plants activate a response that is similar to the recognition of pathogen-associated molecular patterns (PAMPs), which are involved in PAMP-triggered immunity (PTI). Here we discovered that natural oviposition by P. brassicae or treatment with egg extract inhibit growth of different Pseudomonas syringae strains in Arabidopsis through the activation of a systemic acquired resistance (SAR). This egg-induced SAR involves the metabolic SAR signal pipecolic acid, depends on ALD1 and FMO1, and is accompanied by a stronger induction of defence genes upon secondary infection. Although P. brassicae larvae showed a reduced performance when feeding on Pseudomonas syringae-infected plants, this effect was less pronounced when infected plants had been previously oviposited. Altogether, our results indicate that egg-induced SAR might have evolved as a strategy to prevent the detrimental effect of bacterial pathogens on feeding larvae.
Hierarchical Mesh Segmentation Based on Quadric Surface Fitting

In this paper we introduce a hierarchical region decomposition algorithm for triangle meshes segmentation based on quadric surface fitting. Initially, the whole mesh represents a single cluster. At every iteration, the region with largest error is divided and Lloyd iteration clustering is executed following, which make sure the segmentation has the minimum error in each hierarchical level. An error control strategy is used to get finally result automatically. Besides, users also can interpose this process by specifying the segmentation level. Each segmentation region after this process has a best fitting proxy of quadric surface. We propose an improved L2,1 distance into a hybrid error, which is used in least square fit of quadric function. By comparing with the state-of-the art methods, our method is testified to be insensitive to noise. Model optimization and hole filling based on our algorithm are demonstrated in the last.
Fast Microwave Medical Imaging Based on Iterative Smoothed Adaptive Thresholding

This letter presents a fast microwave imaging technique based on the concept of smoothed minimization and adaptive thresholding. The distorted Born iterative method (DBIM) is used to solve the electromagnetic (EM) inverse scattering problem. We propose to solve the set of underdetermined equations at each iteration of the DBIM algorithm using an L2 regularized iterative smoothed adaptive thresholding ( L2-ISATCS) technique. Our simulation results confirm that this technique can reduce considerably the required reconstruction times for the DBIM method relative to previously suggested compressed sensing (CS)-based approaches .
Experimental Placebo Analgesia Changes Resting-State Alpha Oscillations

The lack of clear understanding of the pathophysiology of chronic pain could explain why we currently have only a few effective treatments. Understanding how pain relief is realised during placebo analgesia could help develop improved treatments for chronic pain. Here, we tested whether experimental placebo analgesia was associated with altered resting-state cortical activity in the alpha frequency band of the electroencephalogram (EEG). Alpha oscillations have been shown to be influenced by top-down processes, which are thought to underpin the placebo response. Seventy-three healthy volunteers, split into placebo or control groups, took part in a well-established experimental placebo procedure involving treatment with a sham analgesic cream. We recorded ongoing (resting) EEG activity before, during, and after the sham treatment. We show that resting alpha activity is modified by placebo analgesia. Post-treatment, alpha activity increased significantly in the placebo group only (p < 0.001). Source analysis suggested that this alpha activity might have been generated in medial components of the pain network, including dorsal anterior cingulate cortex, medial prefrontal cortex, and left insula. These changes are consistent with a cognitive state of pain expectancy, a key driver of the placebo analgesic response. The manipulation of alpha activity may therefore present an exciting avenue for the development of treatments that directly alter endogenous processes to better control pain.
A cloud computing approach to complex robot vision tasks using smart camera systems

In this paper we show our work on enabling service robot systems to distribute parts of the image processing functions to different off-board computer systems in the working environment of the robot. Thus complex algorithms can be carried out on high performance systems circumventing the restrictions considering space and power consumption that a mobile platform imposes. As high resolution cameras provide a huge amount of image data and the bandwidth of a wireless network connection is strongly limited, we are using intelligent camera systems on the mobile robot platform to execute parts of the image processing functions directly on the robot. This way only preprocessed image information will be transmitted instead of raw image data. We are using a flexible modular software framework that allows us to split image processing tasks into a pipeline of modular functions that can run on different systems. We show how our approach can be used to enable a service robot system to speed up high resolution SIFT-based object detection.
How do online social networks support decision making? A pluralistic research agenda

Recently Online Social Communities and Networks (OSNs) have become widely popular as a source of data or reference for those seeking advice. Using an OSN can potentially enhance or degrade the DM process for both individuals and communities through the accessing of data from multiple sources. While ample independent research into OSN and DM exists, there is a lack of research into how online technology affects the making of decisions that have an impact on our lives. The synergy of these themes provides a unique perspective for research into DM in OSN. This paper proposes a pluralistic research agenda that interviews qualitative (exploratory) and quantitative (explanatory) approaches. In particular, we propose using netnography, surveys and interviews to discover the potential utilisation of OSNs as a support tool for the DM process.
The central role of thrombin in hemostasis

Summary Following vascular injury, blood loss is controlled by the mechanisms of hemostasis. During this process, the serine proteinase, thrombin, is generated both locally and rapidly at sites of vessel damage. It plays a pivotal role in clot promotion and inhibition, and cell signaling, as well as additional processes that influence fibrinolysis and inflammation. These functions involve numerous cleavage reactions, which must be tightly coordinated. Failure to do so can lead to either bleeding or thrombosis. The crystal structures of thrombin, in combination with biochemical analyses of thrombin mutants, have provided insight into the ways in which thrombin functions, and how its different activities are modulated. Many of the interactions of thrombin are facilitated by exosites on its surface that bind to its substrates and/or cofactors. The use of cofactors not only extends the range of thrombin specificity, but also enhances its catalytic efficiency for different substrates. This explains a paradox (i.e. thrombin is a specific proteinase, and yet one that has multiple, and sometimes opposing, substrate reactions). In this review, we describe the context in which thrombin acts during hemostasis and explain the roles that its exosites and cofactors play in directing thrombin function. Thereafter, we develop the concept of cofactor competition as a means by which the activities of thrombin are controlled.
An approximation algorithm for conflict-aware broadcast scheduling in wireless ad hoc networks

Broadcast scheduling is a fundamental problem in wireless ad hoc networks. The objective of a broadcast schedule is to deliver a message from a given source to all other nodes in a minimum amount of time. At the same time, in order for the broadcast to proceed as predicted in the schedule, it must not contain parallel transmissions which can be conflicting based on the collision and interference parameters in the wireless network. Most existing work on this problem use a limited network model which accounts only for conflicts occurring inside the transmission ranges of the nodes. The broadcast schedules produced by these algorithms are likely to experience unpredictable delays when deployed in the network. This is because they do not take into consideration other important sources of conflict in parallel transmissions, namely the interference range and the carrier sensing range. In this paper we develop a conflict-aware network model, which uses these parameters to increase the probability of scheduling conflict-free transmissions, and thereby improve the reliability of the broadcast schedule. We present and prove correctness of a constant approximation algorithm for minimum-latency broadcast scheduling under this network model. We also present a greedy heuristic algorithm for the same problem. Experimental results are provided to evaluate the performance of our algorithms. In addition, the algorithms are analyzed to justify their performance trends.
A Signal Processing Perspective on Hyperspectral Unmixing: Insights from Remote Sensing

Blind hyperspectral unmixing (HU), also known as unsupervised HU, is one of the most prominent research topics in signal processing (SP) for hyperspectral remote sensing [1], [2]. Blind HU aims at identifying materials present in a captured scene, as well as their compositions, by using high spectral resolution of hyperspectral images. It is a blind source separation (BSS) problem from a SP viewpoint. Research on this topic started in the 1990s in geoscience and remote sensing [3]-[7], enabled by technological advances in hyperspectral sensing at the time. In recent years, blind HU has attracted much interest from other fields such as SP, machine learning, and optimization, and the subsequent cross-disciplinary research activities have made blind HU a vibrant topic. The resulting impact is not just on remote sensing - blind HU has provided a unique problem scenario that inspired researchers from different fields to devise novel blind SP methods. In fact, one may say that blind HU has established a new branch of BSS approaches not seen in classical BSS studies. In particular, the convex geometry concepts - discovered by early remote sensing researchers through empirical observations [3]-[7] and refined by later research - are elegant and very different from statistical independence-based BSS approaches established in the SP field. Moreover, the latest research on blind HU is rapidly adopting advanced techniques, such as those in sparse SP and optimization. The present development of blind HU seems to be converging to a point where the lines between remote sensing-originated ideas and advanced SP and optimization concepts are no longer clear, and insights from both sides would be used to establish better methods.
Matrix Metalloproteinase-7 and ADAM-12 (a Disintegrin and Metalloproteinase-12) Define a Signaling Axis in Agonist-Induced Hypertension and Cardiac Hypertrophy

Background— Excessive stimulation of Gq protein–coupled receptors by cognate vasoconstrictor agonists induces a variety of cardiovascular processes, including hypertension and hypertrophy. Here, we report that matrix metalloproteinase-7 (MMP-7) and a disintegrin and metalloproteinase-12 (ADAM-12) form a novel signaling axis in these processes. Methods and Results— In functional studies, we targeted MMP-7 in rodent models of acute, long-term, and spontaneous hypertension by 3 complementary approaches: (1) Pharmacological inhibition of activity, (2) expression knockdown (by antisense oligodeoxynucleotides and RNA interference), and (3) gene knockout. We observed that induction of acute hypertension by vasoconstrictors (ie, catecholamines, angiotensin II, and the nitric oxide synthase inhibitor NG-nitro-l-arginine methyl ester) required the posttranscriptional activation of vascular MMP-7. In spontaneously hypertensive rats, knockdown of MMP-7 (by RNA interference) resulted in attenuation of hypertension and stopped development of cardiac hypertrophy. Quantitative reverse-transcription polymerase chain reaction studies in mouse models of MMP-7 knockdown (by RNA interference) and gene knockout revealed that MMP-7 controlled the transcription of ADAM-12, the major metalloproteinase implicated in cardiac hypertrophy. In mice with angiotensin II–induced hypertension and cardiac hypertrophy, myocardial ADAM-12 and downstream hypertrophy marker genes were overexpressed. Knockdown of MMP-7 attenuated hypertension, inhibited ADAM-12 overexpression, and prevented cardiac hypertrophy. Conclusions— Agonist signaling of both hypertension and hypertrophy depends on posttranscriptional and transcriptional mechanisms that involve MMP-7, which is transcriptionally connected with ADAM-12. Approaches targeting this novel MMP-7/ADAM-12 signaling axis could have generic therapeutic potential in hypertensive disorders caused by multiple or unknown agonists.
Feature analysis of groundwater discharge points in coastal regions around Mt. Chokaisan, Japan by using alos palsar data

Submarine groundwater discharges exist in the Japan Sea around Mt. Chokaisan, Japan. However, in the coastal regions, the details regarding their properties have not yet been clarified. In our previous study, we have detected groundwater discharge points arising due to the difference in freshwater and seawater by using the Landsat ETM+ and the ALOS AVNIR-2 signals. The ETM+ and AVNIR-2 are passive sensors, and the data taken by the above sensors will be affected by clouds, the limited data are available. In order to understand features of the groundwater discharge points regardless of the weather conditions, this paper analyzes textures obtained from the ALOS PALSAR data. Our experimental results were in considerable agreement with the results obtained from the AVNIR-2 data, and the realities in the study area.
Dynamics modelling, performance evaluation and stability analysis of an autonomous underwater vehicle

This paper describes the viability of applying non-linear controllers and line of guidance methods to manipulate different motion regimes of an autonomous underwater vehicle (AUV) without any assumptions. The modelling component includes vehicle dynamics, external forces acting on the vehicle and environment. So far, diving dynamics of an AUV have often been derived under various postulations on the motion of the vehicle. However, these kinds of assumptions may induce large modelling errors and may cause further severe problems in many practical applications. A position and attitude tracking control law for (AUVs) in six degrees of freedom is decoupled into longitudinal and lateral motions such that autopilots for speed, depth/diving and heading control can be designed. A numerical simulation demonstrates that the proposed controllers make the system stable and maintain the desired depth and heading angle with sufficient accuracy. Phase plane analysis is used to study the stability of the whole system.
Design of the detuned accelerator structure

This is a summary of the design procedure for the detuned accelerator structure for SLAC's Next Linear Collider program. The 11.424 GHz accelerating mode of each cavity must be synchronous with the beam. The distribution of the disk thicknesses and lowest synchronous dipole mode frequencies of the cavities in the structure is Gaussian in order to reduce the effect of wake fields. The finite element field solver YAP calculated the accelerating mode frequency and the lowest synchronous dipole mode frequency for various cavity diameters, aperture diameters and disk thicknesses. Polynomial 3-parameter fits are used to calculate the dimensions for a 1.8 m detuned structure. The program SUPERFISH was used to calculate the shunt impedances, quality factors and group velocities. The RF parameters of the section like filling time, attenuation factor, accelerating gradient and maximum surface field along the section are evaluated. Error estimates are discussed and comparisons with conventional constant gradient and constant impedance structures are be presented. <<ETX>>
Estimating Selection on Nonsynonymous Mutations

The distribution of mutational effects on fitness is of fundamental importance for many aspects of evolution. We develop two methods for characterizing the fitness effects of deleterious, nonsynonymous mutations, using polymorphism data from two related species. These methods also provide estimates of the proportion of amino acid substitutions that are selectively favorable, when combined with data on between-species sequence divergence. The methods are applicable to species with different effective population sizes, but that share the same distribution of mutational effects. The first, simpler, method assumes that diversity for all nonneutral mutations is given by the value under mutation-selection balance, while the second method allows for stronger effects of genetic drift and yields estimates of the parameters of the probability distribution of mutational effects. We apply these methods to data on populations of Drosophila miranda and D. pseudoobscura and find evidence for the presence of deleterious nonsynonymous mutations, mostly with small heterozygous selection coefficients (a mean of the order of 10−5 for segregating variants). A leptokurtic gamma distribution of mutational effects with a shape parameter between 0.1 and 1 can explain observed diversities, in the absence of a separate class of completely neutral nonsynonymous mutations. We also describe a simple approximate method for estimating the harmonic mean selection coefficient from diversity data on a single species.
Feedback Gesture Generation for Embodied Conversational Agents

This Master’s Project is carried out in the context of the NECA project. The NECA project develops a system that generates multi-modal dialogues for embodied conversational agents. The aim of this project is to develop and implement an algorithm that generates feedback gestures for the characters in the dialogue. Subsequently the effects feedback gestures might have on the general impression of the dialogue are evaluated. Feedback gestures are performed by a person involved in a conversation but not having the speaking turn at the moment. This person supplies the speaker with feedback so that the speaker knows if s/he has understood or not. The effects were measured in terms of entertainment, naturalness, liveliness and ability to remember the dialogue content. The algorithm was developed and implemented and an evaluation was carried out. The evaluation results show no big differences in the subjects’ apprehension of the dialogue with feedback gestures compared to the dialogue without feedback gestures. The subjects judged the dialogue without feedback gestures as slightly more entertaining and natural but the one with feedback gestures was judged as livelier. The memory test shows that the subjects remembered the content of the dialogue without feedback gestures better than the content of the dialogue with feedback gestures. Generering av återkopplingsgester för konverserande agenter Sammanfattning Detta examensarbete utfördes som en del av NECA-projektet. NECA-projektet utvecklar multimodala dialoger för konverserande agenter. Syftet med detta examensarbete var att utveckla och implementera en algoritm som genererar återkopplingsgester åt de karaktärer som agerar i dialogen. Därefter skulle också de eventuella effekter som återkopplingsgesterna hade på dialogen vad gäller underhållningsvärde, naturlighet, livlighet och förmåga att minnas dialogens innehåll fastställas. Algoritmen utvecklades och implementerades och därefter gjordes en utvärdering av det förändrade systemet. Utvärderingen visar inga stora skillnader beträffande hur försökspersonerna uppfattade dialogen utan återkopplingsgester jämfört med den med återkopplingsgester. Utefter försökspersonernas bedömningar var dialogen utan återkopplingsgester något mer underhållande och naturlig medan dialogen med återkopplingsgester var livligare. Minnestestet visar att försökspersonerna kom ihåg innehållet i dialogen utan återkopplingsgester något bättre än innehållet i dialogen med återkopplingsgester.
CNplot: visualizing pre-clustered networks.

SUMMARY CNplot is a simple technique for the visualization of global connectivity within pre-clustered network data. CNplot is easy to implement and in most cases produces informative and satisfactory summary of the data. AVAILABILITY A Java implementation is available that allows users to modify graphics parameters and produces a LaTeX output. This software is free and is available at http://csb.stanford. edu/nbatada/VCN.html
The Role of Gammaherpesviruses in Cancer Pathogenesis

Worldwide, one fifth of cancers in the population are associated with viral infections. Among them, gammaherpesvirus, specifically HHV4 (EBV) and HHV8 (KSHV), are two oncogenic viral agents associated with a large number of human malignancies. In this review, we summarize the current understanding of the molecular mechanisms related to EBV and KSHV infection and their ability to induce cellular transformation. We describe their strategies for manipulating major cellular systems through the utilization of cell cycle, apoptosis, immune modulation, epigenetic modification, and altered signal transduction pathways, including NF-kB, Notch, Wnt, MAPK, TLR, etc. We also discuss the important EBV latent antigens, namely EBNA1, EBNA2, EBNA3’s and LMP’s, which are important for targeting these major cellular pathways. KSHV infection progresses through the engagement of the activities of the major latent proteins LANA, v-FLIP and v-Cyclin, and the lytic replication and transcription activator (RTA). This review is a current, comprehensive approach that describes an in-depth understanding of gammaherpes viral encoded gene manipulation of the host system through targeting important biological processes in viral-associated cancers.
Measuring Source Credibility of Social Engineering Attackers on Facebook

Past research has suggested that social networking sites are the most common source for social engineering-based attacks. Persuasion research shows that people are more likely to obey and accept a message when the source's presentation appears to be credible. However, many factors can impact the perceived credibility of a source, depending on its type and the characteristics of the environment. Our previous research showed that there are four dimensions of source credibility in terms of social engineering on Facebook: perceived sincerity, perceived competence, perceived attraction, and perceived worthiness. Because the dimensionalities of source credibility as well as their measurement scales can fluctuate from one type of source to another and from one type of context to another, our aim in this study includes validating the existence of those four dimensions toward the credibility of social engineering attackers on Facebook and developing a valid measurement scale for every dimension of them.