Miracle-dz/UniFAR-FTUs huggingface dataset:
Origin and development of the germ line in sea stars

This review summarizes and integrates our current understanding of how sea stars make gametes. Although little is known of the mechanism of germ line formation in these animals, recent results point to specific cells and to cohorts of molecules in the embryos and larvae that may lay the ground work for future research efforts. A coelomic outpocketing forms in the posterior of the gut in larvae, referred to as the posterior enterocoel (PE), that when removed, significantly reduces the number of germ cell later in larval growth. This same PE structure also selectively accumulates several germ‐line associated factors—vasa, nanos, piwi—and excludes factors involved in somatic cell fate. Since its formation is relatively late in development, these germ cells may form by inductive mechanisms. When integrated into the morphological observations of germ cells and gonad development in larvae, juveniles, and adults, the field of germ line determination appears to have a good model system to study inductive germ line determination to complement the recent work on the molecular mechanisms in mice. We hope this review will also guide investigators interested in germ line determination and regulation of the germ line into how these animals can help in this research field. The review is not intended to be comprehensive—sea star reproduction has been studied for over 100 years and many reviews are comprehensive in their coverage of, for example, seasonal growth of the gonads in response to light, nutrient, and temperature. Rather the intent of this review is to help the reader focus on new experimental results attached to the historical underpinnings of how the germ cell functions in sea stars with particular emphasis to clarify the important areas of priority for future research. genesis 52:367–377, 2014. © 2014 Wiley Periodicals, Inc.
Supporting Multiplayer Online Ball Passing at a Distance with Multiple Sets of Kinect

We present Alone Together, a collaborative virtual ball playing environment augmented with three sets of Microsoft Kinect. The play environment fulfills a 'sport over the distance' them via the attempt to mimic the real world ball-passing exercise (or rehabilitation sessions) except that the players can be miles away from each other, and they interact without a physical ball. Moreover, our system allows each player to see the other two and their physical environment respectively, which is a combination of the physical world where players are situated and the virtual world where they play with each other. Kinect sensors are used to map players' action into a virtual world including the passing of the virtual ball.
SVM-based video segmentation and annotation of lectures and conferences

This paper presents a classification system for video lectures and conferences based on Support Vector Machines (SVM). The aim is to classify videos into four different classes (talk, presentation, blackboard, mix). On top of this, the system further analyses presentation segments to detect slide transitions, animations and dynamic content such as video inside the presentation. The developed approach uses various colour and facial features from two different datasets of several hundred hours of video to train an SVM classifier. The system performs the classification on frame-by-frame basis and does not require precomputed shotcut information. To avoid over-segmentation and to take advantage of the temporal correlation of succeeding frames, the results are merged every 50 frames into a single class. The presented results prove the robustness and accuracy of the algorithm. Given the generality of the approach, the system can be easily adapted to other lecture datasets.
A Survey on the Flexibility Requirements Related to Business Processes and Modeling Artifacts

In competitive and evolving environments only organizations which can manage complexity and can respond to rapid change in an informed manner can gain a competitive advantage During the early 90's, workflow technologies offered a transversal integration capacity to the enterprise applications. Today, to "integrate " enterprise applications -and the activities they support- into business processes is not sufficient. The architecture of this integration should also be flexible. Enterprise requirements highlight flexible and adaptive processes whose execution can evolve (i) according to situations that cannot always be prescribed, and/or (ii) according to business changes (organizational, process improvement, strategic .). More recent works highlight requirements in term of flexible and adaptive workflows, whose execution can evolve according to situations that cannot always be prescribed. This paper presents the state of the art for flexible business process management systems and criteria for comparing them.
Optimal Power Allocation for Hybrid Distributed Beamforming in Wireless Relay Networks

In this paper, the optimal power allocation problems are solved for hybrid distributed beamforming in wireless relay networks. The capacity of the source-destination link is maxi- mized and the total transmit power of the source and the relays is minimized. The hybrid relaying which adapts relaying strategies such as amplify-and-forward (AF) and decode-and-forward (DF) to the channel condition can enhance the signal reliability. Three policies are used to determine the ordering of the relays for switching the relaying mode from AF to DF. Simulation results show that the performance of the proposed scheme is nearly optimal for both capacity maximization and power minimization with a few iterations. I. INTRODUCTION Multiple-input multiple-output (MIMO) techniques can in- crease the spectral efficiency and the signal reliability. Mobile station may have one antenna due to the cost and size of the device. However, distributed relays equipped with single antenna can form a virtual antenna array and use conventional transmission schemes of MIMO channels, and hence the signal reliability can be enhanced. When the channel state informa-
Fluid Limits of G/G/1+G Queues Under the Nonpreemptive Earliest-Deadline-First Discipline

A single-server queueing model is considered with customers that have deadlines. If a customer’s deadline elapses before service is offered, the customer abandons the system (customers do not abandon while being served). When the server becomes available, it offers service to the customer having the earliest deadline among those that are in the queue. We obtain a fluid limit of the queue length and abandonment processes and for the occupation measure of deadlines, in the form of measure-valued processes. We characterize the limit by means of a Skorohod problem in a time-varying domain that has an explicit solution. The fluid limits also describe a certain process called the frontier that is well known to play a key role in systems operating under this scheduling policy.
Community response to enrichment is highly sensitive to model structure

Biologists use mathematical functions to model, understand and predict nature. For most biological processes, however, the exact analytical form is not known. This is also true for one of the most basic life processes: the uptake of food or resources. We show that the use of several nearly indistinguishable functions, which can serve as phenomenological descriptors of resource uptake, may lead to alarmingly different dynamical behaviour in a simple community model. More specifically, we demonstrate that the degree of resource enrichment needed to destabilize the community dynamics depends critically on the mathematical nature of the uptake function.
Two Methods for Classifying Bloggers’ Sentiment

—On lots of commercial blogs, bloggers’ negative comments about enterprisers’ images or harmful evaluations of products spread quickly in the cyber space. Moreover, an exposure of an inside story in the blogosphere may influence a company’s reputation. Therefore, to identify bloggers’ sentiment effectively is extremely important for enterprisers. These negative comments often bring great damage to enterprises. Recently, researchers proposed lots of machine learning techniques to efficiently detect customers’ negative emotions for helping companies to carefully response customers’ comments. However, they don’t consider the class imbalance problem which lots of bloggers’ comments are positive and far fewer comments are negative. A classifier induced from an imbalanced data set has high classification accuracy for the majority class, but an unacceptable error rate for the minority class. Therefore, this study proposed two new methods, MCBS and VS to provide a possible solution. Finally, a real case of bloggers’ comments regarding MP3 products will be employed to illustrate the effectiveness of our proposed methods.
Characterization-free behavioral power modeling

We propose a new approach to RT-level power modeling for combinational macros, that does not require simulation-based characterization. A pattern-dependent power model for a macro is analytically constructed using only structural information about its gate-level implementation. The approach has three main advantages over traditional techniques: (i) it provides models whose accuracy does not depend on input statistics, (ii) it offers a wide range of tradeoff between accuracy and complexity, and (iii) it enables the construction of pattern-dependent conservative upper bounds.
Autonomic Data Center Thermal Management

Data centers play the critical role of hosting company data. As data centers have increased in size and scope, they have also started to generate increasing amounts of heat, thus requiring increasing amounts of power for self-cooling. Data center cooling now demands increased efficiency and autonomy in order to better protect the environment, improve server stability, and minimize costs. Autonomic computing provides a viable solution: by programming computers to self-manage and self-optimize their processes, they can maximize their own efficiency without human intervention. To explore autonomic approaches to data center environmental management, we simulated a workload on a cluster of eight servers. We developed an autonomic scheduler in Perl to manage these servers and distribute the simulated tasks to minimize heat production. Our scheduler averted dangerous temperature increases on our servers, improving the reliability of these systems.
DEM estimation from multi-Baseline ENVISAT- ASAR interferometric data through maximum likelihood techniques

In this paper, two techniques for estimating accurate height profiles of the ground, using multi-baselines interferometric synthetic aperture radar (In-SAR) data and an a-priori inaccurate digital elevation model (DEM) of the observed scene, are analyzed. The methods are both based on maximum likelihood (ML) estimation: the first estimates directly the quota of each pixel of the image, independently from the other pixels, while the latter estimates the parameters of the local planes which best approximate, in the ML sense, the height profile in a small neighborhood of each pixel. The inclusion of this contextual information allows improving the estimation accuracy. Results on simulated and real ENVISAT-ASAR data are presented.
Intracellular calcium activates TRPM2 and its alternative spliced isoforms

Melastatin-related transient receptor potential channel 2 (TRPM2) is a Ca2+-permeable, nonselective cation channel that is involved in oxidative stress-induced cell death and inflammation processes. Although TRPM2 can be activated by ADP-ribose (ADPR) in vitro, it was unknown how TRPM2 is gated in vivo. Moreover, several alternative spliced isoforms of TRPM2 identified recently are insensitive to ADPR, and their gating mechanisms remain unclear. Here, we report that intracellular Ca2+ ([Ca2+]i) can activate TRPM2 as well as its spliced isoforms. We demonstrate that TRPM2 mutants with disrupted ADPR-binding sites can be activated readily by [Ca2+]i, indicating that [Ca2+]i gating of TRPM2 is independent of ADPR. The mechanism by which [Ca2+]i activates TRPM2 is via a calmodulin (CaM)-binding domain in the N terminus of TRPM2. Whereas Ca2+-mediated TRPM2 activation is independent of ADPR and ADPR-binding sites, both [Ca2+]i and the CaM-binding motif are required for ADPR-mediated TRPM2 gating. Importantly, we demonstrate that intracellular Ca2+ release activates both recombinant and endogenous TRPM2 in intact cells. Moreover, receptor activation-induced Ca2+ release is capable of activating TRPM2. These results indicate that [Ca2+]i is a key activator of TRPM2 and the only known activator of the spliced isoforms of TRPM2. Our findings suggest that [Ca2+]i-mediated activation of TRPM2 and its alternative spliced isoforms may represent a major gating mechanism in vivo, therefore conferring important physiological and pathological functions of TRPM2 and its spliced isoforms in response to elevation of [Ca2+]i.
Query relaxation using malleable schemas

In contrast to classical databases and IR systems, real-world information systems have to deal increasingly with very vague and diverse structures for information management and storage that cannot be adequately handled yet. While current object-relational database systems require clear and unified data schemas, IR systems usually ignore the structured information completely. Malleable schemas, as recently introduced, provide a novel way to deal with vagueness, ambiguity and diversity by incorporating imprecise and overlapping definitions of data structures. In this paper, we propose a novel query relaxation scheme that enables users to find best matching information by exploiting malleable schemas to effectively query vaguely structured information. Our scheme utilizes duplicates in differently described data sets to discover the correlations within a malleable schema, and then uses these correlations to appropriately relax the users' queries. In addition, it ranks results of the relaxed query according to their respective probability of satisfying the original query's intent. We have implemented the scheme and conducted extensive experiments with real-world data to confirm its performance and practicality.
On Two Measures of Problem Instance Complexity and their Correlation with the Performance of SeDuMi on Second-Order Cone Problems

We evaluate the practical relevance of two measures of conic convex problem complexity as applied to second-order cone problems solved using the homogeneous self-dual (HSD) embedding model in the software SeDuMi. The first measure we evaluate is Renegar's data-based condition measure C(d), and the second measure is a combined measure of the optimal solution size and the initial infeasibility/optimality residuals denoted by S (where the solution size is measured in a norm that is naturally associated with the HSD model). We constructed a set of 144 second-order cone test problems with widely distributed values of C(d) and S and solved these problems using SeDuMi. For each problem instance in the test set, we also computed estimates of C(d) (using Peña’s method) and computed S directly. Our computational experience indicates that SeDuMi iteration counts and log (C(d)) are fairly highly correlated (sample correlation R = 0.675), whereas SeDuMi iteration counts are not quite as highly correlated with S (R = 0.600). Furthermore, the experimental evidence indicates that the average rate of convergence of SeDuMi iterations is affected by the condition number C(d) of the problem instance, a phenomenon that makes some intuitive sense yet is not directly implied by existing theory.
Linear transformation-based asymmetric watermarking scheme

We propose a new asymmetric watermarking scheme. In the proposed scheme, two linear transformation matrices are constructed. One matrix is secret and applied to a secret watermark to form a public asymmetric watermark. The other matrix is public and non-full rank, which is used to perform a public (asymmetric) detection using a correlation test. Theory analysis and simulation results show that the proposed scheme not only can provide a reliable asymmetric detection, but also ensures that the embedded watermark can be detected even if the asymmetric detection is disabled.
Bignoniaceae Metabolites as Semiochemicals

Members of the family Bignoniaceae are mostly found in tropical and neo-tropical regions in America, Asia and Africa, although some of them are cultivated in other regions as ornamentals. Species belonging to this family have been extensively studied in regard to their pharmacological properties (as extracts and isolated compounds). The aim of this review is to summarize the reported scientific evidence about the chemical properties as well as that of the extracts and isolated compounds from species of this family, focusing mainly in insect-plant interactions. As it is known, this family is recognized for the presence of iridoids which are markers of oviposition and feeding preference to species which have became specialist feeders. Some herbivore species have also evolved to the point of been able to sequester iridoids and use them as defenses against their predators. However, iridoids also exhibit anti-insect properties, and therefore they may be good lead molecules to develop botanical pesticides. Other secondary metabolites, such as quinones, and whole extracts have also shown potential as anti-insect agents.
Very large G protein-coupled receptor 1 regulates myelin-associated glycoprotein via Gαs/Gαq-mediated protein kinases A/C

Significance Although most known Mendelian genes causing nonsymptomatic epilepsies encode ion channels, Mass1 (monogenic audiogenic seizure susceptible 1) is among the few known epilepsy genes that do not encode channels, suggesting that membrane hyperexcitability can arise indirectly. Here we found that the MASS1 protein is highly expressed in the colliculi of the adult brain, where MASS1 senses extracellular calcium and activates PKA and PKC signaling via Gαs and Gαq to regulate stability of MAG in myelin-forming cells. These data provide us with a unique working model where MASS1 regulates MAG in response to calcium in myelinated regions of critical sites for the initiation and propagation of audiogenic epilepsy. VLGR1 (very large G protein-coupled receptor 1), also known as MASS1 (monogenic audiogenic seizure susceptible 1), is an orphan G protein-coupled receptor that contains a large extracellular N terminus with 35 calcium-binding domains. A truncating mutation in the Mass1 gene causes autosomal recessive, sound-induced seizures in the Frings mouse. However, the function of MASS1 and the mechanism underlying Frings mouse epilepsy are not known. Here, we found that MASS1 protein is enriched in the myelinated regions of the superior and inferior colliculi, critical areas for the initiation and propagation of audiogenic seizures. Using a panel of myelin antibodies, we discovered that myelin-associated glycoprotein (MAG) expression is dramatically decreased in Frings mice. MASS1 inhibits the ubiquitylation of MAG, thus enhancing the stability of this protein, and the calcium-binding domains of MASS1 are essential for this regulation. Furthermore, MASS1 interacts with Gαs/Gαq and activates PKA and PKC in response to extracellular calcium. Suppression of signaling by MASS1 RNAi or a specific inhibitor abrogates MAG up-regulation. We postulate that MASS1 senses extracellular calcium and activates cytosolic PKA/PKC pathways to regulate myelination by means of MAG protein stability in myelin-forming cells of the auditory pathway. Further work is required to determine whether MAG dysregulation is a cause or consequence of audiogenic epilepsy and whether there are other pathways regulated by MASS1.
Improving the prediction of users ’ disclosure behavior ... by making them disclose more predictably ?

Taking a step beyond segmentation, privacy researchers have recently proposed privacy personalization or adaptation as an approach to assist users in their privacy decision making. Analyzing a number of datasets of users’ personal information disclosure behavior, we find an interesting phenomenon regarding privacy personalization: the order in which information is requested has an impact on prediction accuracy. We provide evidence that this happens because certain request orders cause people’s disclosure behavior to be less variable and thus more predictable. This is an important phenomenon to study, because if request orders indeed influence the variability and predictability of subsequent requests, then adapting the request order to the user may result in positive feedback loops that promote prediction accuracy. We address several possible explanations for this phenomenon, and we propose a study that will help us find out which of these explanations is correct.
Real-time adaptive kinematic model estimation of concentric tube robots

Kinematic models of concentric tube robots have matured from considering only tube bending to considering tube twisting as well as external loading. While these models have been demonstrated to approximate actual behavior, modeling error can be significant for medical applications that often call for positioning accuracy of 1-2mm. As an alternative to moving to more complex models, this paper proposes using sensing to adaptively update model parameters during robot operation. Advantages of this method are that the model is constantly tuning itself to provide high accuracy in the region of the workspace where it is currently operating. It also adapts automatically to changes in robot shape and compliance associated with the insertion and removal of tools through its lumen. As an initial exploration of this approach, a recursive on-line estimator is proposed and evaluated experimentally.
Resistance of Entamoeba histolytica to the Cysteine Proteinase Inhibitor E64 Is Associated with Secretion of Pro-enzymes and Reduced Pathogenicity*

Cysteine proteinases (CPs) have been considered suitable targets for the development of antiparasitic drugs. To assess the importance of CPs for the growth and pathogenicity of the protozoan parasite Entamoeba histolytica we have cultured amoebae in the presence of various cysteine proteinase inhibitors (CPIs). It was found that broad range CPIs, which are membrane permeable and rapidly enter the cell, are highly toxic at micromolar concentrations, and all attempts to generate E. histolytica mutants resistant to these CPIs were unsuccessful. In contrast, the broad range CPI E64, which does not permeate membranes as well, was deleterious at much higher concentrations, and amoebae rapidly developed resistance to this inhibitor. Compared with sensitive wild-type cells, E64-resistant E. histolytica were substantially reduced in the expression of various CP genes and were able to secrete unprocessed enzyme into the culture medium. Moreover, E64 resistance was associated with a significant reduction in virulence, because these cells were greatly impaired in the ability to generate liver abscesses in experimentally infected gerbils.