Miracle-dz/UniFAR-FTUs huggingface dataset:
Hyperlinking digital libraries on the web

In the academic field almost all scholarly documents have a references section that supports the ideas and positions they take. This section creates a connection between documents to help the reader find the article in case they want to know more about the topic. Creating a method of navigating through these connections and finding articles from which the scholar document is based on is a task that has been done by several applications in many ways. This paper explains a research made on how to automate the manual process involved to find scholar documents using a search engine and bibliographic information. The tool had a accuracy of 42% locating 42 references of the 100 cited works.
92–96 GHz GaN power amplifiers

We report the test results of a family of 92-96 GHz GaN power amplifiers (PA) with increasing gate peripheries (150 µm to 1200 µm). The 1200 µm, 3-stage PA produces 2.138 W output power (Pout) with an associated PAE of 19% at 93.5 GHz (VD=14V). The amplifier offers Pout over 1.5W with associated PAE over 17.8% in the 92–96 GHz bandwidth. The measured data show that the maximum Pout scales linearly with increasing gate periphery at an almost constant PAE around 20%. This demonstrates the high efficiency of on-chip power combining and enables W-band high power single chip solid state power amplifiers.
Analysis of the disturbance rejection ability of a passive dynamic walker with hip spring

In numerous passive dynamic walking experiments, we found a spring added between walker's two legs increase its walking success rate dramatically. To explore the inherent nature of this phenomenon, we make a simulation comparison between the method to add hip springs and the method to change leg mass center position and foot radius, on the extent how much walking disturbance rejection ability can be improved. We find that the hip springs placed between leg's center of mass have an enlarged basin of attraction of the walking cycle as well as a strengthened walking ability on irregular slope. Further, parameters study is performed by simulating the influence of hip spring, mass distribution and foot radius on the walker's disturbance rejection ability. The results show that hip springs can increase the walker's disturbance rejection ability while keeping the existence of stable equilibrium state unchanged, and arc foot can only obtain the same performance when the radius ia large, and the mass center position has little contribution to the disturbance rejection ability.
Edgelens: an interactive method for managing edge congestion in graphs

An increasing number of tasks require people to explore, navigate and search extremely complex data sets visualized as graphs. Examples include electrical and telecommunication networks, Web structures, and airline routes. The problem is that graphs of these real world data sets have many interconnected nodes, ultimately leading to edge congestion: the density of edges is so great that they obscure nodes, individual edges, and even the visual information beneath the graph. To address this problem we developed an interactive technique called EdgeLens. An EdgeLens interactively curves graph edges away for a person's focus attention without changing the node positions. This opens up sufficient space to disambiguate node and edge relationships and to see underlying information while still preserving node layout. Initially two methods of creating this interaction were developed and compared in a user study. The results of this study were used in the selection of a basic approach and the subsequent development of the EdgeLens. We then improved the EdgeLens through use of transparency and colour and by allowing multiple lenses to appear on the graph.
An RNAi strategy for treatment of amyotrophic lateral sclerosis caused by mutant Cu,Zn superoxide dismutase

Amyotrophic lateral sclerosis (ALS or Lou Gehrig's disease) is a neurodegenerative disease characterized by motor neuron degeneration, paralysis and death. One cause of this disease is mutations in the Cu,Zn superoxide dismutase (SOD1) gene. As mutant SOD1 acquires a toxic property that kills motor neurons, by reducing the mutant protein the disease progression may be slowed or prevented. While mutant SOD1 is toxic, the wild‐type SOD1 is indispensable for motor neuron health. Therefore, the ideal therapeutic strategy would be to inhibit selectively the mutant protein expression. Previously we have demonstrated that RNA interference (RNAi) can selectively inhibit some mutant SOD1 expression. However, more than 100 SOD1 mutants can cause ALS and all mutants cannot be inhibited selectively by RNAi. To overcome this obstacle, we have designed a replacement RNAi strategy. Using this strategy, all mutants and wild‐type genes are inhibited by RNAi. The wild‐type SOD1 function is then replaced by designed wild‐type SOD1 genes that are resistant to the RNAi. Here we demonstrate the concept of this strategy.
Patterns of Phylogenetic Diversity of Subtropical Rainforest of the Great Sandy Region, Australia Indicate Long Term Climatic Refugia

Australia’s Great Sandy Region is of international significance containing two World Heritage areas and patches of rainforest growing on white sand. Previous broad-scale analysis found the Great Sandy biogeographic subregion contained a significantly more phylogenetically even subset of species than expected by chance contrasting with rainforest on white sand in Peru. This study aimed to test the patterns of rainforest diversity and relatedness at a finer scale and to investigate why we may find different patterns of phylogenetic evenness compared with rainforests on white sands in other parts of the world. This study focussed on rainforest sites within the Great Sandy and surrounding areas in South East Queensland (SEQ), Australia. We undertook field collections, expanded our three-marker DNA barcode library of SEQ rainforest plants and updated the phylogeny to 95% of the SEQ rainforest flora. We sampled species composition of rainforest in fixed area plots from 100 sites. We calculated phylogenetic diversity (PD) measures as well as species richness (SR) for each rainforest community. These combined with site variables such as geology, were used to evaluate patterns and relatedness. We found that many rainforest communities in the Great Sandy area were significantly phylogenetically even at the individual site level consistent with a broader subregion analysis. Sites from adjacent areas were either not significant or were significantly phylogenetically clustered. Some results in the neighbouring areas were consistent with historic range expansions. In contrast with expectations, sites located on the oldest substrates had significantly lower phylogenetic diversity (PD). Fraser Island was once connected to mainland Australia, our results are consistent with a region geologically old enough to have continuously supported rainforest in refugia. The interface of tropical and temperate floras in part also explains the significant phylogenetic evenness and higher than expected phylogenetic diversity.
kGuard: Lightweight Kernel Protection

interests are mainly in software and systems security, with a focus on automated software Georgios Portokalidis is a postdoctoral researcher in the department of computer Science at columbia University. He obtained his doctorate from the Vrije Universiteit in Amsterdam. His research interests are mainly around the area of systems security, but extend to network monitoring, operating systems, and virtualization elias Athanasopoulos holds a bS in physics from the University of Athens, and an mS and Phd from the University of crete. He is currently a marie curie postdoctoral fellow with columbia University. interests revolve around systems and software security and reliability. He received his Phd in 2001 from the University of Pennsylvania. Kernel exploits have become increasingly popular over the past several years. We have developed kGuard, a cross-platform system that defends the operating system (OS) against a widespread class of kernel attacks. We describe how these attacks work and how kGuard protects the kernel with only a small decrease in performance. The OS kernel is becoming an attractive target for attackers. The rising number of kernel vulnerabilities discovered and reported attest to this (see Figure 1). The reasons behind this trend are numerous. First, the number of applications running (continuously) with administrative privileges has significantly decreased, meaning that an attacker compromising such programs remotely gains only limited power over the underlying system. Additionally, programs have become harder to exploit due to the various defense mechanisms already adopted by modern OSes, such as address space layout randomization and stack smashing protection. The most interesting reason is probably that vulnerabilities such as NULL pointer dereference bugs, which were thought to be impractical, hard to exploit, and had not received significant attention by the security community, can be used with ease against the kernel to gain elevated privileges. In fact, some researchers proclaimed 2009 as " the year of the kernel NULL pointer dereference flaw " [2]. Last, exploiting kernel bugs has the added benefit of allowing attackers to mask their presence on the compromised systems (e.g., by hiding processes or files). Figure 1: Kernel vulnerabilities (per year) reported to NIST. Over the past decade, the distinct number of cVe identifiers assigned to kernel vulnerabilities has increased by a factor of 5. Kernel attacks are facilitated by the fact that user and kernel space (i.e., the memory area where user applications and the kernel reside, respectively), are weakly separated in modern OSes. …
Controlling Exploration , Diversity and Escaping Local Optima in GP : Adapting Weights of Training Sets to Model Resource Consumption

A common problem in evolutionary computation, and in particular in GA and GP, is the loss of diversity due both to ‘lock-in’ and early convergence of a population to ‘deceptive’ high scoring partial solutions. As the run proceeds, such individuals constitute a larger and larger segment of the population, eliminate diversity and stop the progress of the run. This paper will present a method for the automatic detection of such lock-in and impasse, as well as explore a fitness function which uses this information to reward diversity and innovation and increasingly penalize the locked-in individuals. This method can be applied to essentially any problem, and can be successful in preventing a run from locking-in on an easily obtainable local optimum and in preserving diversity. We present an analysis, discussion, and preliminary results on its application to the boolean 11-multiplexer problem.
Adaptive joint scheduling of spectrum sensing and data transmission in cognitive radio networks

We consider a cognitive radio (CR) network that makes opportunistic use of a set of channels licensed to a primary network. During operation, the CR network is required to carry out spectrum sensing to detect active primary users, thereby avoiding interfering with them. However, spectrum sensing may cause negative effect on the performance of the CR network, as all CR communications has to be postponed during channel sensing. This paper focuses on adaptively scheduling spectrum sensing and data transmission so that negative impacts to the performance of the CR network are minimized. We first consider the case when CR nodes always have data to transmit and experience time-varying channels. Based on knowledge of channel conditions, the sensing periods are adaptively scheduled to maximize the spectrum efficiency of the CR operation. We show how optimal sensing/transmission scheduling policies can be obtained and prove some important structural properties of such optimal policies. We then consider the case when CR nodes experience both stochastic data arrival and time-varying channels. By treating each sensing period as a 'virtual sensing packet'', we convert the problem of joint spectrum-sensing/datatransmission scheduling into a standard queueing model. Based on that, an efficient scheduling algorithm that takes into account channel and queue conditions of the CR network is proposed.
Non-Expert Correction of Automatically Generated Relation Annotations

We explore a new way to collect human annotated relations in text using Amazon Mechanical Turk. Given a knowledge base of relations and a corpus, we identify sentences which mention both an entity and an attribute that have some relation in the knowledge base. Each noisy sentence/relation pair is presented to multiple turkers, who are asked whether the sentence expresses the relation. We describe a design which encourages user efficiency and aids discovery of cheating. We also present results on inter-annotator agreement.
Goal-oriented and map-based people tracking using virtual force field

Estimation of people tracking may become divergent in the presence of occlusion. Since the interactions between people and environments can be mathematically modeled and probabilistically estimated, stream field based tracking provides the solution where the state of the occluded people is estimated by inferring the interactive force between the virtual goal of a person and environmental features. Such tracker suffers from high computation complexity because of the multi-hypotheses of the person's goal and feature-based map. Therefore, this paper proposes a novel virtual force field (VFF) based tracking algorithm that can be realized with a single hypothesis for the person's goal and grid-based map. The occupied grids generate repulsive forces while the person's goal generates attractive force in the virtual force field. Since the virtual force field based tracking integrates map, person, and the person's goal, the position of the person sheltered by the environment can be accurately estimated in unknown environments. Compared with the Kalman filter with constant acceleration (CA) model and stream field based algorithms, our proposed scheme significantly improves the tracking accuracy in case of occlusion.
Tendon-Based Stiffening for a Pneumatically Actuated Soft Manipulator

There is an emerging trend toward soft robotics due to its extended manipulation capabilities compared to traditionally rigid robot links, showing promise for an extended applicability to new areas. However, as a result of the inherent property of soft robotics being less rigid, the ability to control/obtain higher overall stiffness when required is yet to be further explored. In this letter, an innovative design is introduced which allows varying the stiffness of a continuum silicon-based manipulator and proves to have potential for applications in Minimally Invasive Surgery. Inspired by muscular structures occurring in animals such as the octopus, we propose a hybrid and inherently antagonistic actuation scheme. In particular, the octopus makes use of this principle activating two sets of muscles-longitudinal and transverse muscles-thus, being capable of controlling the stiffness of parts of its arm in an antagonistic fashion. Our designed manipulator is pneumatically actuated employing chambers embedded within the robot's silicone structure. Tendons incorporated in the structure complement the pneumatic actuation placed inside the manipulator's wall to allow variation of overall stiffness. Experiments are carried out by applying an external force in different configurations while changing the stiffness by means of the two actuation mechanisms. Our test results show that dual, antagonistic actuation increases the load bearing capabilities for soft continuum manipulators and thus their range of applications.
Similarity in Approximate Reasoning

This paper presents an approach to similarity based approximate reasoning that elucidates the connection between similarity and existing approaches to inference in approximate reasoning methodology. A set of axioms is proposed to compute a reasonable measure of similarity between two fuzzy sets. Such a measure of similarity is then used at different stages to derive a conclusion in approximate reasoning methodology. In the process, Zadeh's compositional rule of inference and existing similarity based reasoning are integrated to produce the proposed mechanism of inference. As an illustration of its effectiveness the proposed mechanism is used to develop a multi-rule based fuzzy system. Based on the specificity measure of fuzzy sets, a new defuzzification scheme for similarity based fuzzy systems is proposed. Simulation results are presented for the well-known d.c. shunt motor. Copyright c ∞ 2006 Yang's Scientific Research Institute, LLC. All rights reserved.
TanDEM-X for Large-Area Modeling of Urban Vegetation Height: Evidence from Berlin, Germany

Large-area urban ecology studies often miss information on vertical parameters of vegetation, even though they represent important constituting properties of complex urban ecosystems. The new globally available digital elevation model (DEM) of the spaceborne TanDEM-X mission has an unprecedented spatial resolution (12 × 12 m) that allows us to derive such relevant information. So far, suitable approaches using a TanDEM-X DEM for the derivation of a normalized canopy model (nCM) are largely absent. Therefore, this paper aims to obtain digital terrain models (DTMs) for the subsequent computation of two nCMs for urban-like vegetation (e.g., street trees) and forest-like vegetation (e.g., parks), respectively, in Berlin, Germany, using a TanDEM-X DEM and a vegetation mask derived from UltraCam-X data. Initial comparisons between morphological DTM-filter confirm the superior performance of a novel disaggregated progressive morphological filter (DPMF). For improved assessment of a DTM for urban-like vegetation, a modified DPMF and image enhancement methods were applied. For forest-like vegetation, an interpolation and a weighted DPMF approach were compared. Finally, all DTMs were used for nCM calculation. The nCM for urban-like vegetation revealed a mean height of 4.17 m compared to 9.61 m of a validation nCM. For forest-like vegetation, the mean height for the nCM of the weighted filtering approach (9.16 m) produced the best results (validation nCM: 13.55 m). It is concluded that an nCM from TanDEM-X can capture vegetation heights in their appropriate dimension, which can be beneficial for automated height-related vegetation analysis such as comparisons of vegetation carbon storage between several cities.
Wnt5a controls neurite development in olfactory bulb interneurons

Neurons born in the postnatal SVZ (subventricular zone) must migrate a great distance before becoming mature interneurons of the OB (olfactory bulb). During migration immature OB neurons maintain an immature morphology until they reach their destination. While the morphological development of these cells must be tightly regulated, the cellular pathways responsible are still largely unknown. Our results show that the non-canonical Wnt pathway induced by Wnt5a is important for the morphological development of OB interneurons both in vitro and in vivo. Additionally, we demonstrate that non-canonical Wnt signalling works in opposition to canonical Wnt signalling in neural precursors from the SVZ in vitro. This represents a novel role for Wnt5a in the development of OB interneurons and suggests that canonical and non-canonical Wnt pathways dynamically oppose each other in the regulation of dendrite maturation.
Corticosterone and exogenous glucose alter blood glucose levels, neurotoxicity, and vascular toxicity produced by methamphetamine

Our previous studies have raised the possibility that altered blood glucose levels may influence and/or be predictive of methamphetamine (METH) neurotoxicity. This study evaluated the effects of exogenous glucose and corticosterone (CORT) pretreatment alone or in combination with METH on blood glucose levels and the neural and vascular toxicity produced. METH exposure consisted of four sequential injections of 5, 7.5, 10, and 10 mg/kg (2 h between injections) D‐METH. The three groups given METH in combination with saline, glucose (METH+Glucose), or CORT (METH+CORT) had significantly higher glucose levels compared to the corresponding treatment groups without METH except at 3 h after the last injection. At this last time point, the METH and METH+Glucose groups had lower levels than the non‐METH groups, while the METH+CORT group did not. CORT alone or glucose alone did not significantly increase blood glucose. Mortality rates for the METH+CORT (40%) and METH+Glucose (44%) groups were substantially higher than the METH (< 10%) group. Additionally, METH+CORT significantly increased neurodegeneration above the other three METH treatment groups (≈ 2.5‐fold in the parietal cortex). Thus, maintaining elevated levels of glucose during METH exposure increases lethality and may exacerbate neurodegeneration. Neuroinflammation, specifically microglial activation, was associated with degenerating neurons in the parietal cortex and thalamus after METH exposure. The activated microglia in the parietal cortex were surrounding vasculature in most cases and the extent of microglial activation was exacerbated by CORT pretreatment. Our findings show that acute CORT exposure and elevated blood glucose levels can exacerbate METH‐induced vascular damage, neuroinflammation, neurodegeneration and lethality.
Uncovering Physiologic Mechanisms of Circadian Rhythms and Sleep/Wake Regulation through Mathematical Modeling

Mathematical models of neurobehavioral function are useful both for understanding the underlying physiology and for predicting the effects of rest-activity-work schedules and interventions on neurobehavioral function. In a symposium titled “Modeling Human Neurobehavioral Performance I: Uncovering Physiologic Mechanisms” at the 2006 Society for Industrial and Applied Mathematics/Society for Mathematical Biology (SIAM/SMB) Conference on the Life Sciences, different approaches to modeling the physiology of human circadian rhythms, sleep, and neurobehavioral performance and their usefulness in understanding the underlying physiology were examined. The topics included key elements of the physiology that should be included in mathematical models, a computational model developed within a cognitive architecture that has begun to include the effects of extended wake on information-processing mechanisms that influence neurobehavioral function, how to deal with interindividual differences in the prediction of neurobehavioral function, the applications of systems biology and control theory to the study of circadian rhythms, and comparisons of these methods in approaching the overarching questions of the underlying physiology and mathematical models of circadian rhythms and neurobehavioral function. A unifying theme was that it is important to have strong collaborative ties between experimental investigators and mathematical modelers, both for the design and conduct of experiments and for continued development of the models.
Supervised nonlinear dimensionality reduction by Neighbor Retrieval

Many recent works have combined two machine learning topics, learning of supervised distance metrics and manifold embedding methods, into supervised nonlinear dimensionality reduction methods. We show that a combination of an early metric learning method and a recent unsupervised dimensionality reduction method empirically outperforms previous methods. In our method, the Riemannian distance metric measures local change of class distributions, and the dimensionality reduction method makes a rigorous tradeoff between precision and recall in retrieving similar data points based on the reduced-dimensional display. The resulting supervised visualizations are good for finding (sets of) similar data samples that have similar class distributions.