Miracle-dz/UniFAR-FTUs huggingface dataset:
An elastic path controller for a collaborative wheelchair assistant

In this paper, we propose a new type of Elastic Path Controller (EPC), which is used to control and manipulate the Collaborative Wheelchair Assistant (CWA). The EPC is built on the basis of Brent's path planner and the control force is generated by balance between the internal restoring force and external normal force. Simulation results show that the new EPC can not only follow an arbitrary curve as a guideway but also deviate from the guideway with a normal force to avoid obstacles. This EPC can also work in the singularity area, which was not solved ever before.
Evaluation of the Performance of the Distributed Phased-MIMO Sonar

A broadband signal model is proposed for a distributed multiple-input multiple-output (MIMO) sonar system consisting of two transmitters and a receiving linear array. Transmitters are widely separated to illuminate the different aspects of an extended target of interest. The beamforming technique is utilized at the reception ends for enhancement of weak target echoes. A MIMO detector is designed with the estimated target position parameters within the general likelihood rate test (GLRT) framework. For the high signal-to-noise ratio case, the detection performance of the MIMO system is better than that of the phased-array system in the numerical simulations and the tank experiments. The robustness of the distributed phased-MIMO sonar system is further demonstrated in localization of a target in at-lake experiments.
Design of Management System of Hainan Li Brocade Pattern Gene Database Based on JSP

The research background of management system of Hainan Li brocade pattern gene database and the meaning of Li ethnic cultural inheritance were introduced in the paper. And the overall structure of management system of Hainan Li brocade pattern gene database was introduced also. The functional implementation of modules in the system was elaborated, such as: the design of the data table structure, add, modify and delete management of Li brocade pattern gene data, storage of pattern gene data, user information management, and other functions. The implementation technology of main functions in the system was presented in the paper. Finally, the test condition of the system was explained. The paper was finished on the basis of "The design of management system of Hainan Li brocade pattern gene database ". It was illustrated the management of Li brocade pattern gene data implemented by using JSP technology is a completely feasible new method.
The S-HOCK dataset: Analyzing crowds at the stadium

The topic of crowd modeling in computer vision usually assumes a single generic typology of crowd, which is very simplistic. In this paper we adopt a taxonomy that is widely accepted in sociology, focusing on a particular category, the spectator crowd, which is formed by people “interested in watching something specific that they came to see” [6]. This can be found at the stadiums, amphitheaters, cinema, etc. In particular, we propose a novel dataset, the Spectators Hockey (S-HOCK), which deals with 4 hockey matches during an international tournament. In the dataset, a massive annotation has been carried out, focusing on the spectators at different levels of details: at a higher level, people have been labeled depending on the team they are supporting and the fact that they know the people close to them; going to the lower levels, standard pose information has been considered (regarding the head, the body) but also fine grained actions such as hands on hips, clapping hands etc. The labeling focused on the game field also, permitting to relate what is going on in the match with the crowd behavior. This brought to more than 100 millions of annotations, useful for standard applications as people counting and head pose estimation but also for novel tasks as spectator categorization. For all of these we provide protocols and baseline results, encouraging further research.
The New Immortalized Uroepithelial Cell Line HBLAK Contains Defined Genetic Aberrations Typical of Early Stage Urothelial Tumors

Background: Cell culture models of normal urothelial cells are important for studying differentiation, disease mechanisms and anticancer drug development. Beyond primary cultures with their limitations in lifespan, interindividual heterogeneity and supply, few conditionally immortalized cell lines with limited applicability due to partial transformation or impaired differentiation capacity are available. We describe characteristics of the new spontaneously immortalized cell line HBLAK derived from a primary culture of uroepithelial cells. Objective: To characterize utility and limitations of HBLAK cells as an urothelial cell culture model. Methods: Differentiation markers were investigated by immunofluorescence and RT-PCR, genetic changes by standard karyotyping, array-CGH, PCR, RT-PCR and exome sequencing; expression of p53 and p21 by Western blotting. Results: HBLAK cells proliferated for >50 passages without senescing. They expressed cytokeratins of basal urothelial cells. Terminal differentiation markers appeared only after induction of differentiation by specific protocols. The karyotype was stable, with few chromosomal changes, especially gains of chromosomes 5 and 20 and a chromosome 9p21 deletion resulting in p16INK4A loss. A C228T TERT promoter mutation was present, but no other mutation typical of urothelial carcinoma. TP53 was wild-type and the cell cycle was arrested in response to genomic stress. Conclusions: HBLAK cells retain some differentiation potential and respond to cytotoxic agents similar to normal urothelial cells, but contain genetic changes contributing to immortalization in urothelial tumors. HBLAK may be valuable for evaluating the tumor specificity of novel cancer drugs, but may also be applied as an urothelial in vitro carcinogenesis model.
Citation handling: Processing citation texts in scientific documents

Title of thesis: CITATION HANDLING: PROCESSING CITATION TEXTS IN SCIENTIFIC DOCUMENTS Michael Alan Whidby Master of Science, 2012 Thesis directed by: Professor Bonnie Dorr Dr. David Zajic Department of Computer Science Citation sentences (sentences that cite other papers) play a key role in the summarization of scientific articles. However, a citation-based summarization system that depends on generic natural language processing components, such as parsers or sentence compressors, will perform poorly if those components cannot handle citations correctly. In this thesis, I examine the effect of citation handling on parsing, sentence compression, and multi-document summarization. There are two types of citations that occur in citation sentences: constituent citations and parenthetical citations. I propose an automatic citation classifier based on training data created through Mechanical Turk tasks. I demonstrate that the use of type-specific citation handling as pre-processing improves the performance of a state-of-the-art generic parser, both for quality of the parse trees and running time. Extrinsic evaluations demonstrate that improving the performance of a parser on citation sentences in turn improves the performance of a sentence compressor, Trimmer Zajic et al. (2007), and a multidocument summarization system, MASCS, according to several summarization measures.
Origin Cookies : Session Integrity for Web Applications

Virtually every web site on the Internet uses cookies to maintain session state between HTTP requests. Unfortunately, cookies have a serious design flaw which limits their security. In particular, cookies can not provide session integrity against an attacker who can host content on a related domain. This type of attacker is surprisingly common and problematic, yet existing proposals and best practices do not address this vulnerability. A lack of session integrity can result in session hijacking and session substitution that seriously compromise the security of web sites. In this paper, we demonstrate the possibility of achieving session integrity in existing browsers, but this requires the use of techniques that many existing web sites would have difficulty implementing. Therefore, we propose a lightweight extension to cookies that is secure against related-domain and network attackers, and illustrate how it facilitates session integrity.
Signals of Opportunity Aided Inertial Navigation

A signal of opportunity (SOP)-aided inertial navigation system (INS) framework provides various technical solutions to technical problems facing GNSS implementations. A mobile receiver, whether handheld or vehicle-mounted, has access to Global Navigation Satellite System (GNSS) signals, multiple unknown terrestrial SOPs, and IMU measurements, which are used to estimate receiver states. When GNSS signals become unreliable, the mobile receiver continues to navigate using the SOP-aided INS. The SOP-aided INS produces bounded estimation errors in the absence of GNSS signals, and the bounds are dependent on the quantity and quality of exploited SOPs.
Harnessing the power of fantastic attempts: Kindergarten teacher perspectives on student mistakes

Abstract Now, more than ever, American students at all grade levels face intense pressure to increase academic performance—including kindergarteners. Given that prior research has well established that mistakes and corrective feedback are key elements of the learning endeavor, it is critical to closely examine teachers’ mistake-related experiences within the current educational context. The author reports on an interview study of 25 public school kindergarten teachers, who articulate in their own words how they perceive and respond to student mistakes in practice. Five central themes drawn from thematic analysis reflect commonly reported ways that teachers strive to respond to mistakes in their real-world classrooms: differentiating responses to the learner, building a positive classroom culture, facilitating student self-correction, adjusting instruction, and considering outside factors. The author concludes with a discussion connecting these themes to existing research and considering implications for research, policy, and classroom teaching.
Potential Capacity of Aptamers to Trigger Immune Activation in Human Blood

Target specific short single-stranded DNA (ssDNA) molecules, called aptamers, are auspicious ligands for numerous in vivo applications. However, aptamers are synthetic molecules, which might be recognized by the immune cells in vivo and induce an activation of the innate immune system. Thus, immune activation potential of synthetic ssDNA oligonucleotides (ODNs) was determined using a well established closed-loop circulation model. Fresh human blood was incubated at 37°C for 2 or 4 hours with ssDNA ODNs (SB_ODN) or CpG ODN as positive control. Transcriptional changes were determined by microarray analyses. Blood samples containing SB_ODN demonstrated after 4 hours a significant regulation of 295 transcripts. Amongst others, CCL8, CXCL10, CCL7 and CXCL11 were highest regulated genes. Gene Ontology terms and KEGG pathway analyses exhibited that the differentially expressed genes belong to the transcripts that are regulated during an immune and inflammatory response, and were overrepresented in TLR signaling pathway. This study shows for the first time the potential of aptamers to activate immune system after systemic application into the human blood. Thus, we highly recommend performing of these preclinical tests with potential aptamer-based therapeutics.
Transport in granular systems

There are many situations in which a continuum view of granular systems does not fully capture the relevant mechanics. In order for engineers to be able to design systems for transporting granular materials, there needs to be an understanding of the mechanics of granular systems and how their non-continuous behavior affects their dynamics. This thesis takes an example of a granular system from nature and uses this system to analyze the way granular materials interact with flexible boundaries. This thesis focuses on digging in granular materials. Pinto bean plant roots were used as a model biological system, and experiments using photoelastic grains were performed to quantify the effect of the inhomogeneous forces in the substrate on the root growth. It was determined that the pinto bean roots grew between grains when the force between those grains was less than 0.5 N. This value was time-dependent and showed a previously-unquantified strengthening of the roots over time. Also, while the roots were growing in the granular substrate, they altered the forces between grains by an average of 110 mN. An analytical model of digging energy was developed to investigate the differences between diggers that are much larger than the grain size and diggers that are much smaller than the grain size. Based on this model, a design tool was created so that designers could quickly identify promising technologies for digging based on the size scale of the grains and the desired size of the digger. Finally, two elements of the plant roots, mechanical flexibility and an actuated tip, were used to create robotic diggers to quantify the associated savings in digging energy. Increasing the mechanical flexibility of the digger was shown to result in energy savings of more than 50% when decreasing the bending modulus by one order of magnitude. However, large variations in the data were observed as a result of the inhomogeneity of the granular system. These variations were quantified and were consistent with previous literature regarding forces in granular systems. Also, a numerical model was created that demonstrates that the increase in digging efficiency can be attributed to the flexibility of the digger. Experiments with diggers whose tip orientation cycled from side to side show that it is more energy-efficient to dig with this active tip only if the energy used to create the changing tip orientation is less than 2.5 x 10-5 J per mm dug. Thesis Supervisor: Anette (Peko) Hosoi Title: Associate Professor
A user-centred evaluation of ranking algorithms for interactive query expansion

The evaluation of 6 ranking algorithms for the ranking of terms for query expansion is discussed within the context of an investigation of interactive query expansion and relevance feedback in a real operational environment. The yardstick for the evaluation was provided by the user relevance judgements on the lists of the candidate terms for query expansion. The evaluation focuses on the similarities in the performance of the different algorithms and how the algorithms with similar performance treat terms.
Comorbidity of alcohol and substance dependence with attention-deficit/hyperactivity disorder (ADHD).

AIMS Attention-deficit/hyperactivity disorder (ADHD) is of great clinical importance not only because of its high prevalence but also due to the frequent comorbid illnesses that are connected with this disorder. Several studies were able to demonstrate that ADHD constitutes a significant risk factor for the exacerbation of habit-forming illnesses, i.e. addictions. METHODS We conducted a study on 152 adult patients with alcohol dependence (n = 91) or multiple substance addiction (n = 61) to determine whether or not these patients were affected by ADHD. For retrospective assessment of childhood ADHD, the WURS-k was used as well as the DSM-IV symptom checklist for ADHD. The CAARS was used to assess the persisting symptoms of ADHD in adults. RESULTS 20.9% (WURS-k) or 23.1% (DSM-IV diagnostic criteria) of the alcohol-dependent patients showed evidence of retrospective ADHD affliction in childhood. With the help of CAARS, ADHD was proved to be persistent in 33.3% of the adult patients. In the group of substance-addicted patients 50.8% (WURS-k) and 54.1% (DSM-IV) presented with diagnostic criteria for ADHD in childhood and 65.5% (CAARS) showed evidence of ADHD persisting in adulthood. CONCLUSIONS These results reveal that habit-forming illnesses can be associated with a high comorbidity with ADHD, expressed in the form of alcohol abuse and also in consumption of illegal drugs. The results underline the great importance of early and adequate diagnostics and therapy of ADHD for the prevention of habit-forming illnesses.
CfA3: 185 TYPE Ia SUPERNOVA LIGHT CURVES FROM THE CfA

We present multiband photometry of 185 type-Ia supernovae (SNe Ia), with over 11,500 observations. These were acquired between 2001 and 2008 at the F. L. Whipple Observatory of the Harvard-Smithsonian Center for Astrophysics (CfA). This sample contains the largest number of homogeneously observed and reduced nearby SNe Ia (z ≲ 0.08) published to date. It more than doubles the nearby sample, bringing SN Ia cosmology to the point where systematic uncertainties dominate. Our natural system photometry has a precision of ≲0.02 mag in BVRIr′i′ and ≲0.04 mag in U for points brighter than 17.5 mag. We also estimate a systematic uncertainty of 0.03 mag in our SN Ia standard system BVRIr′i′ photometry and 0.07 mag for U. Comparisons of our standard system photometry with published SN Ia light curves and comparison stars, where available for the same SN, reveal agreement at the level of a few hundredths mag in most cases. We find that 1991bg-like SNe Ia are sufficiently distinct from other SNe Ia in their color and light-curve-shape/luminosity relation that they should be treated separately in light-curve/distance fitter training samples. The CfA3 sample will contribute to the development of better light-curve/distance fitters, particularly in the few dozen cases where near-infrared photometry has been obtained and, together, can help disentangle host-galaxy reddening from intrinsic supernova color, reducing the systematic uncertainty in SN Ia distances due to dust.
Ensemble systems and incremental learning

Classification of the unknown dataset can be obtained by several methods. Ensemble classifier methods are proved to be the better for classification. Learn++, An incremental learning algorithm, which allows supervised classification algorithms to learn from new data without forgetting previously acquired knowledge even when the previously used data is no longer available. Learn++ suffers from inherent “out-voting problem when asked to learn new classes, which causes it to generate an unnecessarily large number of classifiers. Also, in Learn++, distribution update rule based on performance of compound hypothesis, for selecting training set of the next weak classifier, it allows an efficient incremental learning capability when new classes are introduced. Whereas, in AdaBoost distribution update rule based on individual hypothesis guarantees robustness and prevents performance deterioration. In proposed algorithm, it combines the advantages of both the methods. It provides weight updating rule based on a combination of individual hypothesis and compound hypothesis which provide optimum performance level.
An updated theoretical scenario for globular cluster stars

In the rst part of this paper we revisit the history of theoretical predictions for HB luminosities in old Population II stellar clusters, starting from the results of \old" evolutionary computations to introduce in vari- ous steps all the available \new" physics. We discuss the influence of physical ingredients on selected evolutionary parameters, nally presenting models which incorporate all the most recent updating of the relevant physics. The evolutionary behavior of such models is extensively inves- tigated for selected choices about the cluster metallicity, discussing theoretical predictions concerning both cluster isochrones and the calibration of the parameterR in terms of the original amount of He in stellar matter. One nds that the \new" physics has a relevant influence on both these parameters, moving cluster ages into a much bet- ter agreement with current cosmological evaluations. This scenario is implemented by a further set of stellar models where element diusion is taken into account. The com- parison between theoretical scenarios with or without dif- fusion is presented and discussed. A discussion of current observational constraints in the light of the updated the- ory closes the paper.
Modeling of an anti-interference spherical robot for polar region scientific research

In most research work, the steering process has been ignored when considering the ability to move quickly from point to point. Being under control when suffering from Coriolis force or external disturbance in various types of terrain is also essential for spherical robots in hazardous locations such as the Antarctic ice shelf. In this paper, we has a spherical robot with deformable structure, which has two steering engines to control the dip angle between the ground and mid body. The deformable parts on either side of the robot were designed not only to stabilize itself using the method of limiting the degree of freedom with the ground but also to increase the reaction torque from the ground in the steering process. An experiment was set to investigate the relationship between the curvature radius of steering motion and driving angular velocity of the shell. The designed robot was proved to be well under control in test cases with external disturbances like driven by wind power.
Solving Multi-objective Reinforcement Learning Problems by EDA-RL - Acquisition of Various Strategies

EDA-RL, Estimation of Distribution Algorithms for Reinforcement Learning Problems, have been proposed by us recently. The EDA-RL can improve policies by EDA scheme: First, select better episodes. Secondly, estimate probabilistic models, i.e., policies, and finally, interact with the environment for generating new episodes. In this paper, the EDA-RL is extended for Multi-Objective Reinforcement Learning Problems, where reward is given by several criteria. By incorporating the notions in Evolutionary Multi-Objective Optimization, the proposed method is enable to acquire various strategies by a single run.
Author's Personal Copy Computational Statistics and Data Analysis Alternating Imputation Posterior Estimation of Models with Crossed Random Effects

Keywords: Adaptive quadrature Crossed random effects Generalized linear mixed model Item response theory Laplace approximation Random cross-classification Salamander mating data Two-way error components a b s t r a c t Generalized linear mixed models or latent variable models for categorical data are difficult to estimate if the random effects or latent variables vary at non-nested levels, such as persons and test items. Clayton and Rasbash (1999) suggested an Alternating Imputation Posterior (AIP) algorithm for approximate maximum likelihood estimation. For item response models with random item effects, the algorithm iterates between an item wing in which the item mean and variance are estimated for given person effects and a person wing in which the person mean and variance are estimated for given item effects. The person effects used for the item wing are sampled from the conditional posterior distribution estimated in the person wing and vice versa. Clayton and Rasbash (1999) used marginal quasi-likelihood (MQL) and penalized quasi-likelihood (PQL) estimation within the AIP algorithm, but this method has been shown to produce biased estimates in many situations, so we use maximum likelihood estimation with adaptive quadrature. We apply the proposed algorithm to the famous salamander mating data, comparing the estimates with many other methods, and to an educational testing dataset. We also present a simulation study to assess performance of the AIP algorithm and the Laplace approximation with different numbers of items and persons and a range of item and person variances.