Miracle-dz/UniFAR-FTUs huggingface dataset:
Contour Line Tracing Algorithm for Digital Topographic Maps

Topographic maps contain information related to roads, contours, landmarks, land covers and rivers etc. For any Remote sensing and GIS based project, creating a database using digitization techniques is a tedious and time consuming process especially for contour tracing. Contour line is very important information that these maps provide. They are mainly used for determining slope of the landforms or rivers. These contour lines are also used for generating Digital Elevation Model (DEM) for 3D surface generation from any satellite imagery or aerial photographs. This paper suggests an algorithm that can be used for tracing contour lines automatically from contour maps extracted from the topographical sheets and creating a database. In our approach, we have proposed a modified Moore’s Neighbor contour tracing algorithm to trace all contours in the given topographic maps. The proposed approach is tested on several topographic maps and provides satisfactory results and takes less time to trace the contour lines compared with other existing algorithms.
Recent Segmental Duplications in the Human Genome

Primate-specific segmental duplications are considered important in human disease and evolution. The inability to distinguish between allelic and duplication sequence overlap has hampered their characterization as well as assembly and annotation of our genome. We developed a method whereby each public sequence is analyzed at the clone level for overrepresentation within a whole-genome shotgun sequence. This test has the ability to detect duplications larger than 15 kilobases irrespective of copy number, location, or high sequence similarity. We mapped 169 large regions flanked by highly similar duplications. Twenty-four of these hot spots of genomic instability have been associated with genetic disease. Our analysis indicates a highly nonrandom chromosomal and genic distribution of recent segmental duplications, with a likely role in expanding protein diversity.
In-network cache simulations based on a YouTube traffic analysis at the edge network

Recently, with the advent of YouTube and similar video streaming websites, online video playback has gained popularity. Further, video traffic, represents the largest portion of Internet traffic. However, online video traffic contains redundant traffic due to identical video accesses. Network virtualization has been studied and developed, which makes it possible to deploy different protocols and new functionalities over the same physical network. in-network processing, the execution of calculation processes on routers, is one of the new features enabled by network virtualization. Further, since YouTube is the largest video publishing service in the world, we analyze YouTube video playbacks at the edge network and investigate redundant traffic and its locality. Based on these recent developments and technology, we propose to reduce redundant video traffic using in-network caching by positing video caches on routers. This cache could be moved to other routers according to users' access. In this paper, we analyze redundant YouTube video accesses and perform in-network cache simulations. According to these simulations, in-network caching can be optimized to reduce not only incoming traffic to the edge network by 42.2%, but also download traffic inside the network by up to 18.9%, with the only cost being an increase of 6.6% additional upload traffic inside the network. The result also demonstrates the presence of the locality of video accesses at the edge network.
Brain Activity in the Evaluation of the Impression of Robot Bodily Expressions

Controlling devices using physiological signals is an increasingly active research field in human-robot interaction. Using brain signals, or Electroencephalograms (EEG), to control devices is widely known as Brain-Computer Interfacing (BCI). In a BCI system, brain signals are used to directly control devices and not as a communication channel, so target applications are restricted to handicapped and aged people. On the other hand, it is possible for healthy people to simply control devices using voice and body movements. In this paper, quantifying human's state of mind and emotions is investigated by analyzing changes in brain activity. The existence of a relation between robots' bodily expressions and their impressions on the observer is demonstrated. We also show a correlation between the nature of the expression and the power of the low-alpha channel in brain signals. Robots can make use of this quantification as an extra channel of information to achieve smoother and more human-like adaptive interaction
Evaluation of a face recognition system performance's variation on a citizen passports database

Face recognition systems (FRS) have been widely studied and the performances reported are very high in the standard databases used for comparison. In this work we present a FRS that achieves state of the art results in these databases and show its performance's variation when tested in a field trial using a citizen identification database. To accomplish this, a set of experiments are proposed. These include increasing the size of the database, using subsets that include a time difference of one to ten years between the query samples and those enrolled in the system and finally using different subsets of the same database. Discussion on these experiments and conclusions are presented.
The expression of heterologous Fe (III) phytosiderophore transporter HvYS1 in rice increases Fe uptake, translocation and seed loading and excludes heavy metals by selective Fe transport

Summary Many metal transporters in plants are promiscuous, accommodating multiple divalent cations including some which are toxic to humans. Previous attempts to increase the iron (Fe) and zinc (Zn) content of rice endosperm by overexpressing different metal transporters have therefore led unintentionally to the accumulation of copper (Cu), manganese (Mn) and cadmium (Cd). Unlike other metal transporters, barley Yellow Stripe 1 (HvYS1) is specific for Fe. We investigated the mechanistic basis of this preference by constitutively expressing HvYS1 in rice under the control of the maize ubiquitin1 promoter and comparing the mobilization and loading of different metals. Plants expressing HvYS1 showed modest increases in Fe uptake, root‐to‐shoot translocation, seed accumulation and endosperm loading, but without any change in the uptake and root‐to‐shoot translocation of Zn, Mn or Cu, confirming the selective transport of Fe. The concentrations of Zn and Mn in the endosperm did not differ significantly between the wild‐type and HvYS1 lines, but the transgenic endosperm contained significantly lower concentrations of Cu. Furthermore, the transgenic lines showed a significantly reduced Cd uptake, root‐to‐shoot translocation and accumulation in the seeds. The underlying mechanism of metal uptake and translocation reflects the down‐regulation of promiscuous endogenous metal transporters revealing an internal feedback mechanism that limits seed loading with Fe. This promotes the preferential mobilization and loading of Fe, therefore displacing Cu and Cd in the seed.
Impact of aggregation level on the performance of dynamic lightpath adaptation under time-varying traffic

In this article we focus on lightpath adaptation under time-varying traffic in a dynamic elastic optical network (EON) implementing flexgrid optical technology. In the considered scenario, a number of IP/MPLS metro area networks performing traffic aggregation are connected through a core EON. We explore the elastic spectrum allocation (SA) capability of EON and, in this context, we study the effectiveness of three alternative SA policies, namely Fixed, Semi-Elastic and Elastic. For each elastic SA policy, we develop a dedicated algorithm which is responsible for adaptation of spectrum allocated to lightpath connections in response to traffic changes. The evaluation is performed for a set of network scenarios, each one characterized by a different level of traffic aggregation, and hence different traffic variability. As simulation results show, the effectiveness of SA policies highly depends on both the aggregation level and maximum lightpath capacity. In particular, in our experiments up to 21% more traffic is served with the proposed elastic SA than with the fixed SA in a network with low aggregation and high lightpath capacity.
Minimax Trees in Linear Time

A minimax tree is similar to a Huffman tree except that, instead of minimizing the weighted average of the leaves' depths, it minimizes the maximum of any leaf's weight plus its depth. Golumbic (1976) introduced minimax trees and gave a Huffman-like, $\Oh{n \log n}$-time algorithm for building them. Drmota and Szpankowski (2002) gave another $\Oh{n \log n}$-time algorithm, which checks the Kraft Inequality in each step of a binary search. In this paper we show how Drmota and Szpankowski's algorithm can be made to run in linear time on a word RAM with (\Omega (\log n))-bit words. We also discuss how our solution applies to problems in data compression, group testing and circuit design.
Optimal thicknesses determination in a multilayer structure to improve the SPP efficiency for photovoltaic devices by an hybrid FEM — Cascade Neural Network based approach

As the global energy needs to grow, there is increasing interest in the electricity generation by photovoltaics (PVs) devices or solar cells. Analytical and numerical methods are used in literature to study the propagation of surface plasmon polaritons (SPP) but the optimal thicknesses in a multilayer structure can't be established for an optimal propagation by these. In this paper a new method based on cascade Neural Network (NN) is used to predict the propagation characteristics of a multilayer plasmonic structure and coupling FEM analysis of the involved electromagnetic field. The trained NNs are able to provide the required optimal values of the SPP propagation with good accuracy at different value of thicknesses in the multilayer structure.
Development of an optimized backbone of FRET biosensors for kinases and GTPases

We report an optimized backbone for the rapid development of a highly sensitive intramolecular fluorescence resonance energy transfer (FRET) biosensor, which includes an optimized pair of fluorescent proteins and a long flexible linker ranging from 116 to 244 amino acids in length. With this backbone system, we developed FRET biosensors of PKA, ERK, JNK, EGFR, RSK, S6K, Akt, PKC, Ras, and Rac1.
Eye movement evidence that readers maintain and act on uncertainty about past linguistic input

In prevailing approaches to human sentence comprehension, the outcome of the word recognition process is assumed to be a categorical representation with no residual uncertainty. Yet perception is inevitably uncertain, and a system making optimal use of available information might retain this uncertainty and interactively recruit grammatical analysis and subsequent perceptual input to help resolve it. To test for the possibility of such an interaction, we tracked readers' eye movements as they read sentences constructed to vary in (i) whether an early word had near neighbors of a different grammatical category, and (ii) how strongly another word further downstream cohered grammatically with these potential near neighbors. Eye movements indicated that readers maintain uncertain beliefs about previously read word identities, revise these beliefs on the basis of relative grammatical consistency with subsequent input, and use these changing beliefs to guide saccadic behavior in ways consistent with principles of rational probabilistic inference.
Semipolar GaInN/GaN light- emitting diodes grown on honeycomb patterned substrates

Excellent semipolar GaN material quality can be obtained by growing inverse GaN pyramids on full 2 inch c-plane sapphire when combining the advantages of defect reduction via FACELO and selective area growth for faceted surfaces. The nearly defect free material is obtained by structuring the mask into a honeycomb pattern. When realizing full GaInN/GaN LED structures on those templates a relatively broad emission is observed during electroluminescence measurements. Furthermore, the dominant wavelength is found to be dependent on the applied current density. The pronounced shift is in good agreement with the wavelength shift along one single facet. Gas phase diffusion during the active area growth is believed to be the main reason for the varying indium content. The homogeneity could be influenced by changing the reactor pressure during the active area growth (© 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)
Earnings Management and the Long-Run Market Performance of Initial Public Offerings

Issuers of initial public offerings ~IPOs! can report earnings in excess of cash f lows by taking positive accruals. This paper provides evidence that issuers with unusually high accruals in the IPO year experience poor stock return performance in the three years thereafter. IPO issuers in the most “aggressive” quartile of earnings managers have a three-year aftermarket stock return of approximately 20 percent less than IPO issuers in the most “conservative” quartile. They also issue about 20 percent fewer seasoned equity offerings. These differences are statistically and economically significant in a variety of specifications.
Comparison of Testing Methods for the Detection of BRAF V600E Mutations in Malignant Melanoma: Pre-Approval Validation Study of the Companion Diagnostic Test for Vemurafenib

Background The cobas 4800 BRAF V600 Mutation Test is a CE-marked and FDA-approved in vitro diagnostic assay used to select patients with metastatic melanoma for treatment with the selective BRAF inhibitor vemurafenib. We describe the pre-approval validation of this test in two external laboratories. Methods Melanoma specimens were tested for BRAF V600 mutations at two laboratories with the: cobas BRAF Mutation Test; ABI BRAF test; and bidirectional direct sequencing. Positive (PPA) and negative (NPA) percent agreements were determined between the cobas test and the other assays. Specimens with discordant results were tested with massively parallel pyrosequencing (454). DNA blends with 5% mutant alleles were tested to assess detection rates. Results Invalid results were observed in 8/116 specimens (6·9%) with Sanger, 10/116 (8·6%) with ABI BRAF, and 0/232 (0%) with the cobas BRAF test. PPA was 97·7% for V600E mutation for the cobas BRAF test and Sanger, and NPA was 95·3%. For the cobas BRAF test and ABI BRAF, PPA was 71·9% and NPA 83·7%. For 16 cobas BRAF test-negative/ABI BRAF-positive specimens, 454 sequencing detected no codon 600 mutations in 12 and variant codon 600 mutations in four. For eight cobas BRAF test-positive/ABI BRAF-negative specimens, four were V600E and four V600K by 454 sequencing. Detection rates for 5% mutation blends were 100% for the cobas BRAF test, 33% for Sanger, and 21% for the ABI BRAF. Reproducibility of the cobas BRAF test was 111/116 (96%) between the two sites. Conclusions It is feasible to evaluate potential companion diagnostic tests in external laboratories simultaneously to the pivotal clinical trial validation. The health authority approved assay had substantially better performance characteristics than the two other methods. The overall success of the cobas BRAF test is a proof of concept for future biomarker development.
BLANDFORD , A . ( 2004 ) Information Handling in Dynamic Decision Making Environments .

In this paper we describe our observations about information handling in the complex and dynamic decision making environment of ambulance control, more formally known as Emergency Medical Dispatch. Our findings suggest that the information handling capacity of individual dispatchers and of the system as a whole is affected by the difficulties they face in handling information, and this is exhibited in an increase in the time taken to activate ambulances as workload levels increase. We identified 18 information handling difficulties from which we extracted 12 information design features that are expected to improve the information handling ability of the dispatchers in this study.
Strategic Oscillation in Heuristic Local Search Strategic Oscillation in Heuristic Local Search

Main area: search techniques. Abstract This paper describes a local search algorithm for combinatorial optimization problems. It is centered on strategic oscillation. This means that breaking some constraints is allowed so that the search oscillates between feasible and unfeasible elements. It includes global search principles too. In particular heuristic evaluation inspired from A* is used to guide the search. Performance is tested on the multidi-mensional knapsack problem. Experience prooves that the algorithm is very eecient, as well according to the quality of the found solutions as according to the search speed.
An improved k-means clustering algorithm based on dissimilarity

K-means clustering algorithm is one of the most widely used clustering algorithms and has been applied in many fields of science and technology. A major problem of the original k-means clustering algorithm is that the cluster results depend on the initial centroids which choose at random. At the same time, the similarity measure on the algorithm based on distance is not suitable for big high- dimensional dataset. They all lead to severe degradation in performance. In this paper, an improved k-means clustering algorithm based on dissimilarity is proposed. It selects the initial centriods using the Huffman tree which uses dissimilarity matrix to construct. Many experiments confirm that the proposed algorithm is an efficient algorithm with better clustering accuracy on the same algorithm time complexity.
Nonlinear pricing beyond the demand profile approach

Wilson [16] introduced a general methodology to deal with monopolistic pricing in situations where customers have private information on their tastes (‘types’). It is based on the demand profile of customers: For each nonlinear tariff by the monopolist the demand at a given level of product (or quality) is the measure of customers’ types whose marginal utility is at least the marginal tariff (‘price’). When the customers’ marginal utility has a natural ordering (i.e., the Spence and Mirrlees Condition), such demand profile is very easy to perform. In this paper we will present a particular model with one-dimensional type where the Spence and Mirrlees condition (SMC) fails and the demand profile approach results in a suboptimal solution for the monopolist. Moreover, we will suggest a generalization of the demand profile procedure that improves the monopolist’s profit when the SMC does not hold.
Product Review Information Extraction Based on Adjective Opinion Words

Product review mining can provide effective help for manufacturers, retailers and potential customers. We propose a framework of product review information extraction based on adjective opinion words. Firstly, we extract the web page information with web page template features. Secondly, we manually label seed adjective opinion word set, and expanded it to a set with words coverage reaching 90%. We also identify comparative sentence, word match and negation patterns. Finally, we summarize the product reviews from the various perspectives. In order to demonstrate our methods of the framework, we conduct the experiment with the product reviews of digital camera from www. Epinions.com. The experiment shows that the methods can provide the number of emotion polarity for the products and features.
Nephroprotective Effect of Heparanase in Experimental Nephrotic Syndrome

Background Heparanase, an endoglycosidase that cleaves heparan sulfate (HS), is involved in various biologic processes. Recently, an association between heparanase and glomerular injury was suggested. The present study examines the involvement of heparanase in the pathogenesis of Adriamycin-induced nephrotic syndrome (ADR-NS) in a mouse model. Methods BALB/c wild-type (wt) mice and heparanase overexpressing transgenic mice (hpa-TG) were tail-vein injected with either Adriamycin (ADR, 10 mg/kg) or vehicle. Albuminuria was investigated at days 0, 7, and 14 thereafter. Mice were sacrificed at day 15, and kidneys were harvested for various analyses: structure and ultrastructure alterations, podocyte proteins expression, and heparanase enzymatic activity. Results ADR-injected wt mice developed severe albuminuria, while ADR-hpa-TG mice showed only a mild elevation in urinary albumin excretion. In parallel, light microscopy of stained cross sections of kidneys from ADR-injected wt mice, but not hpa-TG mice, showed mild to severe glomerular and tubular damage. Western blot and immunofluorescence analyses revealed significant reduction in nephrin and podocin protein expression in ADR-wt mice, but not in ADR-hpa-TG mice. These results were substantiated by electron-microscopy findings showing massive foot process effacement in injected ADR-wt mice, in contrast to largely preserved integrity of podocyte architecture in ADR-hpa-TG mice. Conclusions Our results suggest that heparanase may play a nephroprotective role in ADR-NS, most likely independently of HS degradation. Moreover, hpa-TG mice comprise an invaluable in vivo platform to investigate the interplay between heparanase and glomerular injury.
The origin recognition complex: from simple origins to complex functions.

Eukaryotic DNA replication is an intricate process that requires the coordinate and tightly regulated action of numerous molecular machines. Eukaryotic cells must choose hundreds if not thousands of origins of replication and assemble multiple proteins or protein complexes at these sites. During S phase, these complexes are activated in a reproducible, temporal program to generate twice this number of replication fork machines dedicated to DNA synthesis. Moreover, these machines must overcome the highly packaged nature of the eukaryotic genome to access all DNA sites, without excep
A GPU-Based Multiple-Pattern Matching Algorithm for Network Intrusion Detection Systems

By the development of network applications, network security issues are getting more and more important. This paper proposes a multiple-pattern matching algorithm for the network intrusion detection systems based on the GPU (Graphics Processing Units). The highly parallelism of the GPU computation power is used to inspect the packet content in parallel. The performance of the proposed approach is analyzed through evaluations such as using various texture formats and different implementations. Experimental results indicate that the performance of the proposed approach is twice of that of the modified Wu-Manber algorithm used in Snort. The proposed approach makes a commodity and cheap GPU card as a high performance pattern matching co-processor.
Landslide Monitoring with Sensor Networks: a Case for Autonomic Communication Services

Wireless sensor networks can be a very useful technology for monitoring remote and hostile environments. In this paper, we firstly report on our experience with landslide monitoring, and analyze the issues and the challenges we had to face in programming and deploying a suitable and useful wireless sensor network infrastructure. Following, we discuss how, within the CASCADAS project, we are contributing to the development of a novel component-based framework to facilitate the design and development of autonomic and situation-aware communication services for the use in modern network scenarios. Such a framework can become a useful tool to facilitate the development of easy-to-deploy, robust, and flexible sensor-network-based monitoring systems and, in particular, of landslide monitoring systems.