Miracle-dz/UniFAR-FTUs huggingface dataset:
Mobile Robot Path Planning with Complex Constraints Based on the Second-Order Oscillating Particle Swarm Optimization Algorithm

According to the low efficiency of Particle Swarm Optimization algorithm applied in mobile robot path planning with complex constraints, a novel boundary constraints handling mechanism was put forward through analyzing the type of constraints. In addition, the path planning method based on Second-order Oscillating Particle Swarm Optimization (SOPSO) was proposed to improve the properties of solutions, in which the searching ability of particles was enhanced by controlling the process of oscillating convergence and asymptotic convergence. A comparison of the results was made by simple PSO, standard PSO, Chaotic particle swarm optimization (CPSO) and SOPSO, which showed that SOPSO has the highest efficiency and accuracy. SOPSO is much more suitable for solving this kind of problem.
Dual-band Class-ABJ AlGaN/GaN high power amplifier

This paper presents a dual-band multiharmonic Class-ABJ high power amplifier (PA) realized in AlGaN/GaN technology. In the Class-ABJ theory power and efficiency are theoretically maintained constant for the wide band spectrum frequency due to the ability to accommodate simultaneous fundamental and harmonic reactive terminations. Here it will be shown that by using the Class-ABJ theory, it is possible to optimize power, gain and efficiency for different frequency bands in a high PA design. The realized Class-ABJ power amplifier delivers drain efficiency greater than 55% with output power and gain greater than 42.4-44.4 dBm and 10-11 dB respectively for the two frequency bands 2.05-2.22 GHz and 2.45-2.58 GHz at around 2-3 dB of compression level.
TransportDB: a comprehensive database resource for cytoplasmic membrane transport systems and outer membrane channels

TransportDB () is a comprehensive database resource of information on cytoplasmic membrane transporters and outer membrane channels in organisms whose complete genome sequences are available. The complete set of membrane transport systems and outer membrane channels of each organism are annotated based on a series of experimental and bioinformatic evidence and classified into different types and families according to their mode of transport, bioenergetics, molecular phylogeny and substrate specificities. User-friendly web interfaces are designed for easy access, query and download of the data. Features of the TransportDB website include text-based and BLAST search tools against known transporter and outer membrane channel proteins; comparison of transporter and outer membrane channel contents from different organisms; known 3D structures of transporters, and phylogenetic trees of transporter families. On individual protein pages, users can find detailed functional annotation, supporting bioinformatic evidence, protein/DNA sequences, publications and cross-referenced external online resource links. TransportDB has now been in existence for over 10 years and continues to be regularly updated with new evidence and data from newly sequenced genomes, as well as having new features added periodically.
Present Status and Future Direction of BSIM SOI Model for High- Performance/Low-Power/RF Application

The recent progress of BSIM (Berkeley Short-channel IGFET Model) SPICE models extended for SOI transistors are reviewed. The models cover partially depleted (PD), fully depleted (FD) and dynamic depletion (FD) (automatically transition between PD and FD). The key concept of dynamic depletion will be discussed.
Stereotyping and Bias in the Flickr30K Dataset

An untested assumption behind the crowdsourced descriptions of the images in the Flickr30K dataset (Young et al., 2014) is that they "focus only on the information that can be obtained from the image alone" (Hodosh et al., 2013, p. 859). This paper presents some evidence against this assumption, and provides a list of biases and unwarranted inferences that can be found in the Flickr30K dataset. Finally, it considers methods to find examples of these, and discusses how we should deal with stereotype-driven descriptions in future applications.
A Novel GBM Saliency Detection Model Using Multi-Channel MRI

The automatic computerized detection of regions of interest (ROI) is an important step in the process of medical image processing and analysis. The reasons are many, and include an increasing amount of available medical imaging data, existence of inter-observer and inter-scanner variability, and to improve the accuracy in automatic detection in order to assist doctors in diagnosing faster and on time. A novel algorithm, based on visual saliency, is developed here for the identification of tumor regions from MR images of the brain. The GBM saliency detection model is designed by taking cue from the concept of visual saliency in natural scenes. A visually salient region is typically rare in an image, and contains highly discriminating information, with attention getting immediately focused upon it. Although color is typically considered as the most important feature in a bottom-up saliency detection model, we circumvent this issue in the inherently gray scale MR framework. We develop a novel pseudo-coloring scheme, based on the three MRI sequences, viz. FLAIR, T2 and T1C (contrast enhanced with Gadolinium). A bottom-up strategy, based on a new pseudo-color distance and spatial distance between image patches, is defined for highlighting the salient regions in the image. This multi-channel representation of the image and saliency detection model help in automatically and quickly isolating the tumor region, for subsequent delineation, as is necessary in medical diagnosis. The effectiveness of the proposed model is evaluated on MRI of 80 subjects from the BRATS database in terms of the saliency map values. Using ground truth of the tumor regions for both high- and low- grade gliomas, the results are compared with four highly referred saliency detection models from literature. In all cases the AUC scores from the ROC analysis are found to be more than 0.999 ± 0.001 over different tumor grades, sizes and positions.
Statistically adaptive learning for a general class of cost functions (SA L-BFGS)

We present a system that enables rapid model experimentation for tera-scale machine learning with trillions of non-zero features, billions of training examples, and millions of parameters. Our contribution to the literature is a new method (SA L-BFGS) for changing batch L-BFGS to perform in near real-time by using statistical tools to balance the contributions of previous weights, old training examples, and new training examples to achieve fast convergence with few iterations. The result is, to our knowledge, the most scalable and flexible linear learning system reported in the literature, beating standard practice with the current best system (Vowpal Wabbit and AllReduce). Using the KDD Cup 2012 data set from Tencent, Inc. we provide experimental results to verify the performance of this method.
Improving Cooperative Caching Using Importance-Aware Bloom Filter

This paper describes the working of existing cooperative caching algorithms like Greedy Forwarding, N-Chance and Robinhood algorithms. In this paper, a comparison of these three algorithms is shown and the reasons for an algorithm to work better than other algorithms is presented with results. A drawback of the existing algorithm which could make the cooperative caching process slow has been discussed in this paper and a solution using Importance-Aware Bloom Filter has been proposed. The global cache that lets the clients collaborate could lead to a performance bottleneck and this paper proposes an idea using which the tasks performed by the global cache could be distributed using an Importance-Aware Bloom Filter.
Coevolution and Hierarchical Interactions of Tomato mosaic virus and the Resistance Gene Tm-1

During antagonistic coevolution between viruses and their hosts, viruses have a major advantage by evolving more rapidly. Nevertheless, viruses and their hosts coexist and have coevolved, although the processes remain largely unknown. We previously identified Tm-1 that confers resistance to Tomato mosaic virus (ToMV), and revealed that it encodes a protein that binds ToMV replication proteins and inhibits RNA replication. Tm-1 was introgressed from a wild tomato species Solanum habrochaites into the cultivated tomato species Solanum lycopersicum. In this study, we analyzed Tm-1 alleles in S. habrochaites. Although most part of this gene was under purifying selection, a cluster of nonsynonymous substitutions in a small region important for inhibitory activity was identified, suggesting that the region is under positive selection. We then examined the resistance of S. habrochaites plants to ToMV. Approximately 60% of 149 individuals from 24 accessions were resistant to ToMV, while the others accumulated detectable levels of coat protein after inoculation. Unexpectedly, many S. habrochaites plants were observed in which even multiplication of the Tm-1-resistance-breaking ToMV mutant LT1 was inhibited. An amino acid change in the positively selected region of the Tm-1 protein was responsible for the inhibition of LT1 multiplication. This amino acid change allowed Tm-1 to bind LT1 replication proteins without losing the ability to bind replication proteins of wild-type ToMV. The antiviral spectra and biochemical properties suggest that Tm-1 has evolved by changing the strengths of its inhibitory activity rather than diversifying the recognition spectra. In the LT1-resistant S. habrochaites plants inoculated with LT1, mutant viruses emerged whose multiplication was not inhibited by the Tm-1 allele that confers resistance to LT1. However, the resistance-breaking mutants were less competitive than the parental strains in the absence of Tm-1. Based on these results, we discuss possible coevolutionary processes of ToMV and Tm-1.
A New Method For Indoor SLAM Based On Artificial Landmark

A mobile robot must be capable of localizing itself in unknown environments and constructing a map of the environments at the same time. Simultaneous localization and mapping (SLAM) is a challenging problem in indoor envi- ronments because GPS information isn't available. An algorithm is proposed in this paper for SLAM with vision sensors, which is designed by utilizing the artificial landmark MR code and integrating the FastSLAM algorithm, the method can decrease the time cost compared with particle filter and improve the accuracy of localization and mapping compared with natural landmarks. Experiments show the effectiveness and robustness of this algorithm.
Stability Analysis of Sampled-Data Systems Using Sum of Squares

This technical brief proposes a new approach to stability analysis of linear systems with sampled-data inputs or channels. The method, based on a variation of the discrete-time Lyapunov approach, provides stability conditions using functional variables subject to convex constraints. These stability conditions can be solved using the sum of squares methodology with little or no conservatism in both the case of synchronous and asynchronous sampling. Numerical examples are included to show convergence.
Economic Benefits Associated with the Visa Waiver Program - A Difference-in-Differences Approach

This study evaluates the economic benefit that the Visa Waiver Program, VWP, brings to the United States, including decreased spending on administration and increased tourism. To capture the net effect of VWP due to increased tourism, this study conducts a semi-experimental evaluation by introducing a control group â€“ it pairs a VWP member country with a non-member country. The results show a net increase of 3-4.5 tourism/business trips per thousand population for a VWP participating country. It concludes that in 2010, because the VWP was in place, the U.S. government has saved from 1.9 billion to 3.2 billion for the cost of interviewing visitors. In sum, this research provides more concrete evidence to the discussion of VWPâ€™s future expansion.
Regulation of partitioned sterol biosynthesis in Saccharomyces cerevisiae

Using yeast strains with null mutations in structural genes which encode delta-aminolevulinic acid synthetase (HEM1), isozymes of 3-hydroxy-3-methylglutaryl coenzyme A (HMG1 and HMG2), squalene epoxidase (ERG1), and fatty acid delta 9-desaturase (OLE1), we were able to determine the effect of hemes, sterols, and unsaturated fatty acids on both sterol production and the specific activity of 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGR) in Saccharomyces cerevisiae. We found that the HMGR isozymes direct essentially equal amounts of carbon to the biosynthesis of sterols under heme-competent conditions, despite a huge disparity (57-fold) in the specific activities of the reductases. Our results demonstrate that palmitoleic acid (16:1) acts as a rate-limiting positive regulator and that ergosterol acts as a potent inhibitor of sterol production in strains which possess only the HMGR1 isozyme (HMG1 hmg2). In strains which contain only the HMGR2 isozyme (hmg1 HMG2), sterol production was inhibited by oleic acid (18:1) and to a lesser degree by ergosterol. The specific activities of the two reductases (HMGR1 and HMGR2) were found to be differentially regulated by hemes but not by ergosterol, palmitoleic acid, or oleic acid. The disparate effects of unsaturated fatty acids and sterols on these strains lead us to consider the possibility of separate, compartmentalized isoprenoid pathways in S. cerevisiae.
A note on pearson correlation coefficient as a metric of similarity in recommender system

Recommender systems help users to find information that best fits their preferences and needs in an overloaded search space. Most recommender systems researches have been focused on the accuracy improvement of recommendation algorithms. Choosing appropriate similarity measure is a key to the recommender system success for this target. Pearson Correlation Coefficient (PCC) is one of the most popular similarity measures for Collaborative filtering recommender system, to evaluate how much two users are correlated. While Correlation-based prediction schemes were shown to perform well, they suffer from some limitations. In This paper we present an extension toward Pearson Correlation Coefficient measure for cases which does not exist similarity between users by using it. Experimental result on the film trust data set demonstrate via our proposed measure and PCC we can achieve better result for similarity measure than traditional PCC.
TL1A Increases Expression of CD25, LFA-1, CD134 and CD154, and Induces IL-22 and GM-CSF Production from Effector CD4 T-Cells

Elevated levels of the cytokine TL1A is associated with several autoimmune diseases e.g. rheumatoid arthritis and inflammatory bowel disease. However, the exact role of TL1A remains elusive. In this study, we investigated the function of TL1A in a pro-inflammatory setting. We show that TL1A together with IL-12, IL-15 and IL-18 increases expression of the co-stimulatory molecules CD154 (CD40 ligand) and CD134 (OX40) on previously activated CD4+ T cells. This indicates that TL1A functions as a co-stimulatory molecule, decreasing the activation threshold of T-cells. We have previously shown that TL1A co-stimulation strongly induces IL-6 in human healthy leukocytes. Interestingly, the cytokine-activated effector T-cells did not produce IL-6 in response to TL1A, indicating distinct effects of TL1A on different cell populations. We further show that this co-stimulation increases the expression of CD25 (IL-2Rα) and CD11a (α-chain of LFA-1) on CD4 T-cells, likely governing increased IL-2/IL-15 sensitivity and cell-cell contact. Along with this, TL1A co-stimulation caused a specific induction of IL-22 and GM-CSF from the activated T-cells. These results substantially contribute to the explanation of TL1A's role in inflammation. Our results suggest that TL1A should be considered as a target for immunotherapeutic treatment of rheumatoid arthritis and inflammatory bowel disease.
Multiple introductions and recombination in Cryphonectria hypovirus 1: perspective for a sustainable biological control of chestnut blight

Cryphonectria hypovirus 1 (CHV1) is a mycovirus which decreases the virulence of its fungal host Cryphonectria parasitica, the causal agent of chestnut blight recently introduced in Europe. The understanding of the evolutionary processes which have shaped CHV1 populations in Europe is required to develop a sustainable biocontrol strategy targeting chestnut blight and effective in European chestnut forests. To retrace the evolutionary history of CHV1, we analyzed sequences from two genomic regions on a collection of 55 CHV1 strains from France and northern Spain, two countries where multiple introductions of C. parasitica occurred. Several recombination events and variable selection pressures contributed to CHV1 evolution, agreeing with a non‐clock‐like diversification rate. These two mechanisms may be at the origin of CHV1 population diversity observed in western Europe. Considering the actual prevalence of CHV1 and its association with host genotypes, multiple introductions of CHV1 may have occurred in Europe, some of them directly from Asia and some of them through North America. Although some viral strains remained with low frequency in their introduction area, multiple infections might have allowed homologous recombination within parental sequences. Some of these recombinant lineages are associated with the spread of CHV1 in European regions.
Study on a multi-robot cooperative wireless communication control system for the spherical amphibious robot

In multi-robot cooperative control system where robots will complete a common task, it is significant to have a better communication among robots. This paper proposed a multi-robot cooperative control system for the spherical amphibious robot. The aim of this method is to set up a point to multipoint network which supports multiple robots link in. Moreover, Multi-robot cooperative control system is given to achieve master-slave approaches, where leader robot guides the slave robots. Multi-robot cooperative control system is a novel approach to the coordination of large numbers of relatively team robots which takes its inspiration from many aspects. We carried out some experiments, and experimental results indicated that using XBee modules with ZigBee protocol to transmit control signal to the robot is an efficiency way. ZigBee communication mode is very suitable for low power consumption, and low data transmission applications, which can be taken into consideration about the communication constraints among amphibious robots. The experimental results indicated that signals are transmitted efficiently in the low power environment by using XBee communications module, and proposed communication control system has excellent performance in low SNR environments. This communication system is very suitable in the low power environment, and the multi-robot cooperative wireless communication system can be used to underwater detection and environmental reconnaissance and military defense, etc.
Visualization of Police Intelligence Data Based on Word Clouds

This paper studies the method of using word clouds to visualize 110 incidents data. It has been reported that word clouds have become a simple and visual appeal of the visualization method for text. Lots of data are stored in the police intelligence system without a novel visualization method. In this study, we therefore explore the possibility of using word clouds to visualize 110 incidents data. After processing the data, we construct a word cloud of incident type and a key word cloud of the incident information. The combination of the word clouds techniques and 110 incidents data promote the analyst to explore the deep insights.
Status and Results from the Cryogenic Dark Matter Search (CDMS)

The Cryogenic Dark Matter Search (CDMS) experiment utilizes novel cryogenic particle detectors for a direct search of dark matter particles in the form of WIMPs in our galaxy. The detectors are able to discriminate between nuclear and electron recoils through the simultaneous measurement of ionization and phonons. We report on the latest results from several kg-day exposure of Ge and Si detectors. Despite exposure times that are 100 times smaller than previous experiments, our sensitivity is comparable to the currently reported dark matter limits.
Automatic generation of standard cell library in VDSM technologies

We developed standard cell libraries for three technologies (130, 180 and 350 nm) using an automatic layout generation tool that we have developed. The automatic layout generation tool is improved so as to cope with phase shift mask and mismatch between transistor pitch and wire pitch, which appear commonly in VDSM technologies. The developed libraries are as competitive as manually-designed libraries in layout density and speed. The libraries are currently public to educational organizations in Japan after we verified the functionalities of all cells and the speed of basic combinational cells on the fabricated chips.
Sensor-based online trajectory generation for smoothly grasping moving objects

Presents a new approach to online trajectory planning for target tracking, dynamic grasping and catching. The robot executes a geometric controller-it simply evaluates a nonlinear function which maps the currently measured position and velocity of the object to be grasped into a current desired robot pose. If the robot tracks these setpoints, it is guaranteed to match the object's velocity and acceleration on a specified grasp surface. The authors develop a geometric controller which specifies the full 6DOF position and orientation of the robot's end effector. A planar simulation demonstrates that this paradigm performs favorably when compared with the traditional planning approach. Since it does not depend on future object measurements, no object model is needed for trajectory prediction. Without trajectory prediction, the computational effort is drastically reduced, allowing for higher controller speed and tracking feedback gains. At the same time this approach provides a framework for general sensor based control of robotic tasks. <<ETX>>
Automated Acquisition and Visualization of Texturized 3-D Models with scalable Resolution

This case study presents an automated method for digitizing complex free-form surfaces. Hardware and software components developed at the Fraunhofer IFF allow generating texturized virtual models from physical objects. Both the 3-D geometry and the surface texture (color information) are measured with high spatial resolution. The method can be applied to a variety of object measurements, for instance, in the fields of quality control, cultural heritage and medical imaging. Selected results for different real-world objects are also presented.
Testing TCP Westwood + over Transatlantic Links at 10 Gigabit / Second rate

Recent introduction of 10 Gigabit Routers and 10 Gigabit Ethernet cards makes of great interest the issue of designing and testing new protocols capable of efficient utilization of 10 gigabit Internet paths. In this work we report a first investigation of the performance of Westwood+ TCP over large delay paths at 10 gigabit/second rates. The investigation has been conducted at the CERN–IT division using the implementation of Westwood+ we have recently made available in the Linux 2.6 stack. The main feature of Westwood+ TCP is its adaptive setting of the control windows after a congestion episode obtained by estimating the bandwidth available along the connection path. The “Westwood+ feature” has been proven to be particularly effective over lossy channels, where packet losses are not due to congestion, and to improve fairness. Experiment results reported in this work show that remarkable throughput and fairness improvements are also present in the presence of very high bandwidth delay product paths. In the future, we plan to combine the way Westwood+ sets the control window after congestion with modifications of standard TCP probing phase. A first try in this direction is also reported in this paper.