Miracle-dz/UniFAR-FTUs huggingface dataset:
Constructing Drivability Maps from 3 D Laser Range Data for Autonomous Vehicles

The field of robotics is making successful progress towards endowing robots with human-like capabilities. One example is the well-known DARPA Urban Challenge, which demonstrated an autonomous ground vehicle with sophisticated software that could drive itself while preparing for interaction with other vehicles, human beings, and obstacles on the road. In the recent DARPA Urban Challenge, road blockage locations were unknown to contestants but pre-specified routes were provided that included all accessible road segments and other information such as waypoints, stop sign locations, and lane width. When driving a car in real life, human beings may not have knowledge of drivable road segments in advance. Instead, they make decisions on how to drive based on what they see at the moment. Hence, it is necessary for the autonomous vehicles to have the same capability to recognize the drivable roads at their current positions. Murarka and Kuipers presented a real-time stereo vision based mapping algorithm for identifying and modeling various hazards in urban environments by constructing a 3D model and segmenting it into distinct traversable ground regions [1]. However, their algorithm works in real-time for the robot's immediate vicinity of 10 x 10 meters. This is a relatively small space compared to our vehicle's immediate vicinity of 120 x 120 meters. The goal of this thesis is to present a revision of their algorithm that will allow the vehicle to discover accessible road segments along its path without relying on pre-specified routes. This will be particularly important in off-road situations where accessible road segments may not be pre-defined. This algorithm is expected to significantly improve the vehicle's performance in detecting and avoiding obstacles as well as navigating safely to the destination.
SHREC '11 Track: Shape Retrieval on Non-rigid 3D Watertight Meshes

Non-rigid 3D shape retrieval has become an important research topic in content-based 3D object retrieval. The aim of this track is to measure and compare the performance of non-rigid 3D shape retrieval methods implemented by different participants around the world. The track is based on a new non-rigid 3D shape benchmark, which contains 600 watertight triangle meshes that are equally classified into 30 categories. In this track, 25 runs have been submitted by 9 groups and their retrieval accuracies were evaluated using 6 commonly-utilized measures.
Design of Computing Circuits using Spatially Localized DNA Majority Logic Gates

DNA is considered as a good computing device because of the predictability of the double helical structure and the Watson-Crick binding thermodynamics associated with them. DNA circuits can be considered as a possible replacement of silicon transistor based circuits, in implantable medical devices, bio-nanorobots, SMART drugs etc. In this paper, we are proposing a novel five input majority logic gate using DNA strands. A spatially localized architecture is used for implementing the majority logic in an Origami substrate. The localization of the strands, give the advantage of re-using the same strands repeatedly in the circuit without causing any spurious reactions. The proposed majority gate is tested using Visual DSD software. The addition of a five input majority gate into the set of DNA logic gates family will give more flexibility for the designer while developing the complex digital computing circuits. We also implemented a full adder circuit using majority gates. A general condition for obtaining n-input majority gate is also discussed.
Estimation of Rapidly Time-Varying Sparse Channels

The estimation of sparse shallow-water acoustic communication channels and the impact of estimation performance on the equalization of phase coherent communication signals are investigated. Given sufficiently wide transmission bandwidth, the impulse response of the shallow-water acoustic channel is often sparse as the multipath arrivals become resolvable. In the presence of significant surface waves, the multipath arrivals associated with surface scattering fluctuate rapidly over time, in the sense that the complex gain, the arrival time, and the Dopplers of each arrival all change dynamically. A sparse channel estimation technique is developed based on the delay-Doppler-spread function representation of the channel. The delay-Doppler-spread function may be considered as a first-order approximation to the rapidly time-varying channel in which each channel component is associated with Doppler shifts that are assumed constant over an averaging interval. The sparse structure of the delay-Doppler-spread function is then exploited by sequentially choosing the dominant components that minimize a least squares error. The advantage of this approach is that it captures both the channel structure as well as its dynamics without the need of explicit dynamic channel modeling. As the symbols are populated with the sample Dopplers, the increase in complexity depends on the channel Doppler spread and can be significant for a severely Doppler-spread channel. Comparison is made between nonsparse recursive least squares (RLS) channel estimation, sparse channel impulse response estimation, and estimation using the proposed approach. The results are demonstrated using experimental data. In training mode, the proposed approach shows a 3-dB reduction in signal prediction error. In decision-directed mode, it improves significantly the robustness of the performance of the channel-estimate-based equalizer against rapid channel fluctuations.
Towards Trusted Semantic Service Computing

This paper describes a new prototype of a semantic Service Oriented Architecture (SOA) called Spec Services. Instead of publishing their API through a protocol like SOAP, as Web Services do, services can register to a service manager a powerful syntactic description or even semantic description of their functional capabilities. The client entity will then send a syntactic or semantic description of its requirements to the service manager, which will try to find an appropriate formerly registered service and to bind them together. Today our service manager can deal with two languages: regular expressions, which is probably the most powerful syntactic-only description language; and Prolog, which is purely semantic. This implementation is made, since its beginning, with evolution in mind, i.e. to easily support integration of new additional formal languages and to provide support for non-functional properties of services. This paper proposes also a trust-based extension of our architecture in order to deploy effectively these self-describing services in an uncertain environment.
Race/ethnicity and the receipt of watchful waiting for the initial management of prostate cancer

AbstractINTRODUCTION: Several recent studies have noted that African Americans disproportionately receive “watchful waiting” for the initial management of their prostate cancer. To determine whether racial/ethnic differences in the receipt of watchful waiting are explained by differences in clinical presentation and life expectancy at the time of diagnosis, we examined Surveillance, Epidemiology, and End Results (SEER)-Medicare data for men diagnosed with prostate cancer in 1994 to 1996. METHODS: Race/ethnicity, comorbidity, stage, grade, age, and expected lifespan and their association with the receipt of watchful waiting were examined in multivariate logistic regression analyses. Race-stratified logistic regression analyses were also used to examine racial/ethnic variation in the association of clinical and demographic factors with the receipt of watchful waiting among African-American, Hispanic, and non-Hispanic white men. RESULTS: African-American (odds ratio [OR], 1.4; 95% confidence interval [CI], 1.3 to 1.6) and Hispanic men (OR, 1.3; 95% CI, 1.1 to 1.5) were significantly more likely than non-Hispanic white men to receive watchful waiting in a multivariate model adjusted for age, comorbidity, stage, grade, and life expectancy. Advanced stage and grade, lower life expectancy, older age, and high comorbidity indices were also significantly associated with an increase in the odds of receipt of watchful waiting in multivariate analyses. In general, the association between the receipt of watchful waiting and the clinical characteristics (i.e., stage, grade, and age) were similar for the three racial/ethnic groups. In race-stratified logistic regression analyses, life expectancy was associated with an increase in the odds of receiving watchful waiting but results were statistically significant for whites only. There was also a statistically significant increase in the odds of receiving watchful waiting for African-American and white men with high comorbidity indices but not Hispanic men. The odds of receiving watchful waiting were also higher for African-American and Hispanic men who resided in census tracts where a large percentage of residents had not completed high school than for white men who resided in similar census tracts. CONCLUSION: The disproportionate receipt of watchful waiting among African Americans and Hispanics is not completely explained by racial/ethnic variation in clinical characteristics or life expectancy as measured in this study. These data suggest that there are other factors that contribute to racial/ethnic differences in receipt of watchful waiting that warrant investigation.
Recent advances on the development and regulation of flower color in ornamental plants

Flower color is one of the most important features of ornamental plants. Its development and regulation are influenced by many internal and external factors. Therefore, understanding the mechanism of color development and its regulation provides an important theoretical basis and premise for the cultivation and improvement of new color varieties of ornamental plants. This paper outlines the functions of petal tissue structure, as well as the distribution and type of pigments, especially anthocyanins, in color development. The progress of research on flower color regulation with a focus on physical factors, chemical factors, and genetic engineering is introduced. The shortcomings of flower color research and the potential directions for future development are explored to provide a broad background for flower color improvements in ornamental plants.
Small Molecule Inhibitor of Type Three Secretion Suppresses Acute and Chronic Chlamydia trachomatis Infection in a Novel Urogenital Chlamydia Model

Previously, we reported that a compound from a group of thiohydrazides of oxamic acids, CL-55, possessed antichlamydial activity in vitro that was accompanied by a decreased translocation of the type three secretion effector, IncA, into the host cell. In this study, the antichlamydial activity of CL-55 was tested in vivo in DBA/2 mice infected with C. trachomatis serovar D. We found that intravaginal inoculation of DBA/2 mice with the clinically relevant strain, C. trachomatis serovar D, results in a course of infection and pathology similar to that observed in humans. The early stage of infection in this model was characterized by a shedding of Chlamydia in vaginal secretions followed by an ascending infection and inflammation in the upper genital tract. We found that CL-55 possessed antibacterial activity in vivo and was able to control C. trachomatis vaginal shedding, ascending infection, and inflammation in the upper genital organs in DBA/2 mice. Our data provide a proof of concept for the protective effect of the thiadiazinon, CL-55, against chlamydial infection in vivo and support the feasibility of further studies of its potential therapeutic applications.
Distance-Vector Algorithms for Distributed Shortest Paths on Dynamic Power-Law Networks

Efficiently solving the problem of computing, in a distributed fashion, the shortest paths of a graph whose topology dynamically changes over time is a core functionality of many today’s digital infrastructures, probably the most prominent example being communication networks. Many solutions have been proposed over the years for this problem that can be broadly classified into two categories, namely Distance-Vector and Link-State algorithms. Distance-Vector algorithms are widely adopted solutions when scalability and reliability are key issues or when nodes have either limited hardware resources, as they result in being very competitive approaches in terms of both the memory and the computational point of view. In this paper, we first survey some of the most established solutions of the Distance-Vector category. Then, we discuss some recent algorithmic developments in this area. Finally, we propose a new experimental study, conducted on a prominent category of network instances, namely generalized linear preference (GLP) power-law networks, to rank the performance of such solutions.
Association between sodium intakes with the risk of chronic kidney disease: evidence from a meta-analysis.

OBJECTIVE Inconsistent results regarding the association between sodium intake and the risk of chronic kidney disease (CKD) have been reported. Thus, we conducted a meta-analysis to summarize the evidence from epidemiological studies of sodium with the risk of CKD. METHODS Pertinent studies were identified by searching of PubMed and Web of Science. The random effect model was used to combine the results. Meta-regression and subgroups analyses were used to explore potential sources of between-study heterogeneity. Publication bias was estimated using Egger's regression asymmetry test. RESULTS Finally, 9 articles involving 5638 CKD cases were included in this meta-analysis. Pooled results suggested that highest sodium intake level versus lowest level was significantly associated with the risk of CKD [summary relative risk (RR) = 1.088, 95% CI = 1.009-1.193, I(2) = 78.1%], especially among Europe [summary RR = 1.097, 95% CI = 1.009-1.205], but not in the America. The association was also found in the prospective studies [summary RR = 1.096, 95% CI = 1.007-1.192], but not in the cross-sectional studies. No evidence of significant publication bias was found. CONCLUSIONS Higher sodium intake might increase the risk of CKD.
Morphological and Genetic Variation in the Endemic Sea Grass Halophila hawaiiana (Hydrocharitaceae) in the Hawaiian Archipelago

The endemic seagrass Halophila hawaiiana Doty & Stone is found in discrete populations throughout the Hawaiian Archipelago. Morphological characteristics of plants from Midway Atoll, Pearl and Hermes Reef, KauaÔi, OÔahu, MolokaÔi, and Maui were measured and compared. Striking variation in leaf length, leaf width, leaf length to width ratio, and internode length was evident among the 18 collection sites sampled at depths ranging from 0.32 to 18 m. DNA sequence analyses of a chloroplast-genome, single-base repeat locus in ramets from nine different collections found only two repeat haplotypes. Repeat haplotypes were fixed at all collection sites and for all islands except O'ahu.
A Novel Probability Binary Particle Swarm Optimization Algorithm and Its Application

Particle swarm optimization (PSO), an intelligent optimization algorithm inspired by the flocking behavior of birds, has been shown to perform well and widely used to solve the continuous problem. But the traditional PSO and most of its variants are developed for optimization problems in continuous space, which are not able to solve the binary combinational optimization problem. To tackle this problem, Kennedy extended the PSO and proposed a discrete binary PSO. But its performance is not ideal and just few further works were conducted based on it. In this paper, we propose a novel probability binary particle swarm optimization (PBPSO) algorithm for discrete binary optimization problems. In PBPSO, a novel updating strategy is adopted to update the swarm and search the global solution, which further simplify the computations and improve the optimization ability. To investigate the performance of the proposed PBPSO, the multidimensional knapsack problems are used as the test benchmarks. The experimental results demonstrate that PBPSO has a better performance for solving the multidimensional knapsack problem in terms of convergent speed and global search ability.
Living analytics methods for the web observatory

The collective effervescence of social media production has been enjoying a great deal of success in recent years. The hundred of millions of users who are actively participating in the Social Web are exposed to ever-growing amounts of sites, relationships, and information. In this paper, we report part of the efforts towards the realization of a Web Observatory at the L3S Research Center (www.L3S.de). In particular, we present our approach based on Living Analytics methods, whose main goal is to capture people interactions in real-time and to analyze multidimensional relationships, metadata, and other data becoming ubiquitous in the social web, in order to discover the most relevant and attractive information to support observation, understanding and analysis of the Web. We center the discussion on two areas: (i) Recommender Systems for Big Fast Data and (ii) Collective Intelligence, both key components towards an analytics toolbox for our Web Observatory.
‘Don’t push me aside, Doctor’: Suicide attempters talk about their support needs, service delivery and suicide prevention in South Africa

Few studies have explored the expressed support needs of suicide attempters in developing countries. Data, collected via in-depth interviews with suicide attempters admitted to a South African hospital, were analysed using thematic content analysis. Participants explicitly asked for integrated psycho-social services at a primary health care level and say they require assistance with alleviating psychiatric symptoms, establishing connectedness, interpersonal conflict and solving socio-economic problems. Findings highlight the importance for suicide prevention of (1) considering interpersonal and contextual socio-economic factors in addition to the psychiatric causes of suicidal behaviour; and (2) multilevel strategies, intersectoral collaboration and integrated person-centred primary health care.
An evaluation of feature sets and sampling techniques for de-identification of medical records

De-identification of text medical records is of critical importance in any health informatics system in order to facilitate research and sharing of medical records. While statistical learning based techniques have shown promising results for de-identification purposes, few such systems are publicly available. It remains a challenge for practitioners to build an accurate and efficient system as it involves a significant amount of feature engineering, i.e. creation and examination of new features used in the system. A comprehensive evaluation is needed to thoroughly understand the effects of different feature sets and potential impacts of sampling and their trade-offs between the often conflicting goals of precision (or positive predictive value), recall (or sensitivity), and efficiency. In this paper, we present the Health Information DE-identification (HIDE) framework and evaluate the open- source software. We present an evaluation of various types of features used in HIDE, and introduce a window sampling technique (only the terms within a specified distance from personal health information are used to train the classifier) and evaluate its effect on both quality and efficiency. Our results show that the context features (previous and next terms) are particularly important and the sampling technique can be used to increase recall with minimal impact on precision. We obtained token-level label precision of 0.967, recall of 0.986 and F-Score of 0.977 when not including true negatives. The overall HIDE system achieves token-level precision of . 998, recall of . 999, and f-score of . 999 on the previous i2b2 challenge task.
VGuard: A distributed denial of service attack mitigation method using network function virtualization

Distributed denial of service (DDoS) attacks have caused tremendous damage to ISPs and online services. They can be divided into attacks using spoofed IPs and attacks using real IPs (botnet). Among them the attacks from real IPs are much harder to mitigate since the attack traffic can be fabricated to be similar to legitimate traffic. The corresponding DDoS defence strategies proposed in past few years have not been proven to be highly effective due to the limitation of participating devices. However, the emergence of the next generation networking technologies such a network function virtualization (NFV) provide a new opportunity for researchers to design DDoS mitigation solutions. In this paper we propose VGuard, a dynamic traffic engineering solution based on prioritization, which is implemented on a DDoS virtual network function (VNF). The flows from the external zone are directed to different tunnels based on their priority levels. This way trusted legitimate flows are served with guaranteed quality of service, while attack flows and suspicious flows compete for resources with each other. We propose two methods for flow direction: the static method and the dynamic method. We evaluated the performance of both methods through simulation. Our results show that both methods can effectively provide satisfying service to trusted flows under DDoS attacks, and both methods have their pros and cons under different situations.
Composition of complex V of the mitochondrial oxidative phosphorylation system.

Complex V isolated from bovine heart mitochondria (Stiggall, D. L., Galante, Y. M., and Hatefi, Y. (1978) J. Biol. Chem. 253, 956-964) was further purified to remove minor respiratory chain contaminants. The purified preparation exhibited an oligomycin-sensitive ATPase activity of 15 to 20 pmol/min/mg of protein, and an uncouplerand oligomycin-sensitive ATP-33Pi exchange activity of about 190 nmol/min/mg of protein, both at 30°C. Upon electrophoresis on three different gel systems in the presence of sodium dodecyl sulfate, purified Complex V exhibits 12 to 13 polypeptide bands. The only known impurity is 2 to 3% of an iron-sulfur flavoprotein with a composition and M, characteristic of ETF dehydrogenase. Using purified coupling factors for comparison of M, values and coelectrophoresis with Complex V, photoaffinity labeling with the uncoupler [3H]2-azido-4-nitrophenol, labeling with [‘4C]dicyclohexylcarbodiimide, and direct isolation from Complex V, the following components have been identified in the purified complex: the five subunits of F1-ATPase, oligomycin sensitivity-conferring protein, uncoupler-binding protein, dicyclohexylcarbodiimide-binding protein, a membrane sector protein corresponding in M, to subunit 6 of the yeast oligomytin-sensitive ATPase complex, and coupling factor F+ In addition, there is a polypeptide band with M, (-11,000) similar to those of the ATPase inhibitor protein and purified coupling factor B (You, K. S., and Hatefi, Y. (19’76) Biochim. Biophys. Acta 423, 398-412). Small amounts of the ATPase inhibitor protein are present in Complex V.
Integrating Rules in Term Subsumption Knowledge Representation Servers

This paper addresses the integration of services for rule-based reasoning in knowledge representation servers based on term subsumption languages. As an alternative to previous constructions of rules as concept→concept links. a mechanism is proposed based on intensional roles implementing the axiom of comprehension in set theory. This has the benefit of providing both rules as previously defined. and set aggregation. using a simple mechanism that is of identical computational complexity to that for rules alone. The extensions proposed have been implemented as part of KRS. a knowledge representation server written as a class library in C++. The paper gives an example of their application to the ripple-down rule technique for large-scale knowledge base operation. acquisition and maintenance.