Miracle-dz/UniFAR-FTUs huggingface dataset:
Time-Invariant Motion Planner in Discretized C-Spacetime for MRS

In this work, a new class of planners for MRS is introduced: Time-invariant Motion Planners, a class of planners that operate indifferently in forward or in backward planningtime direction. Thanks to the specular symmetry (with respect to the timeline) of the motion operators, the planning algorithm can operate both in top-down way (from the goal to the starting pose) or vice versa bottom-up (from the starting pose to the goal) addressing different types of problems. The planner underlying mechanism is an artificial field over a lattice (CAs), where the robots are shrunk to points subjected to attractive and repulsive forces (Lagrangian mechanics). Building a regular manifold of potential values and following its minimum valleys, a trajectory in the spacetime is extracted, corresponding to a robot movement (geometrization of the motion). The potential manifold is constructed on the base of the motion operators. These are the atomic (non interruptible) moves over the space and the time lattice and the set of all of them represents the entire kinematics of a robot. Every robot has its own set and there are contemporarily robots with different kinematics. The manifold emerges from the interaction of the set of operators, the world model and the representation of the robots’ shapes. Using a discretized C-Spacetime, the definition of velocity of a robot becomes an intrinsical (geometrical) property emerging from the interaction between the motion operators and the spacetime. It is fundamental for the correctness of the planning to take care of the actual robot occupancy during an atomic move to avoid collisions with other robots/obstacles. It derives the definition of Motion Silhouette, a conceptual evolution of the Sweeping Silhouette (2002), which is itself an evolution of the Obstacles Enlargement concept by Lozano-Perez in 1983. To avoid the problem of the swapping of two robots, it is important to take in consideration of the well-known Shannon’s Theorem in the discretization phase of the C-Spacetime and consequently in the definition of Motion Silhouette.
Floor Texture Visual Servo Using Multiple Cameras for Mobile Robot Localization

The study of mobile robot localization techniques has been of increasing interest to many researchers and hobbyists as accessibility to mobile robot platforms and sensors have improved dramatically. The field is often divided into two categories, local and global localization, where the former is concerned with the pose of the robot with respect to the immediate surroundings, while the latter deals with the relationship to the complete environment the robot considers. Although the ideal capability for localization algorithms is the derivation of the global pose, the majority of global localization approaches make use of local localization information as the foundation. The use of simple kinematic models or internal sensors, such as rotational encoders, often have limitations in accuracy and adaptability in different environments due to the lack of feed back information to correct any discrepancies between the motion model and the actual motion. Closed loop approaches, on the other hand, allow for more robust pose calculations using various sensors to observe the changes in the environment as the robot moves around. One of these sensors of increasing interest is the camera, which has become more affordable and precise in being able to capture the structure of the scene. The proposed techniques include the investigation of the issues in using multiple off-theshelf webcams mounted on a mobile robot platform to achieve a high precision local localization in an indoor environment (Jensfelt, 2001). This is achieved through synchronizing the floor texture tracker from two cameras mounted on the robot. The approach comprises of three distinct phases; configuration, feature tracking, and the multicamera fusion in the context of pose maintenance. The configuration phase involves the analysis of the capabilities of both the hardware and software components that are integrated together while considering the environments in which the robot will be deployed. Since the coupling between the algorithm and the domain knowledge limits the adaptability of the technique in other domains, only the commonly observed characteristics of the environment are used. The second phase deals with the analyses of the streaming images to identify and track key features for visual servo (Marchand & Chaumette, 2005). Although this area is a well studied in the field of image processing, the performance of the algorithms are heavily influenced by the environment. The last phase involves the techniques for the synchronizing multiple trackers and cameras. 17
Phylogenetic diveristy of marine cyanophages as revealed by sequences of viral capsid assembly protein gene g20

In order to characterize the genetic diversity and phylogenetic affiliations of marine cyanophage isolates and natural cyanophage assemblages, oligonucleotide primers CPS1/CPS8 were designed to specifically amplify ca. 592 bp fragments of the viral capsid assembly protein gene g20. Phylogenetic analysis of isolated cyanophages revealed that marine cyanophages were highly diverse yet more closely related to each other than to enteric coliphage T4. Genetically related marine cyanophage isolates were widely distributed without significant geographical segregation (i.e. no correlation between genetic variation and geographic distance). Cloning and sequencing analysis of 6 natural virus concentrates from estuarine and oligotrophic offshore environments revealed 9 phylogenetic groups in a total of 114 different g20 homologs, with up to 6 clusters and 29 genotypes encountered in a single sample. The composition and structure of natural cyanophage communities in the estuary and the open ocean samples were different from each other, with unique phylogenetic clusters found for each environment. Changes in clonal diversity were also observed from the surface waters to the deep chlorophyll maximum (DCM) layer in the open ocean. Only three clusters contained known cyanophage isolates, while the identity of the other six clusters remain unknown. Whether or not these unidentified groups are comprised of bacteriophages that infect different groups of Synechococcus or other closely related cyanobacteria remains to be answered. The high genetic diversity of marine cyanophage assemblages revealed by the g20 sequences suggests that marine viruses can potentially play important roles in regulating microbial genetic diversity.
Sound Localization for Robot Navigation

Localization and mapping are the essence of successful navigation in mobile platform technology. Localization is a fundamental task in order to achieve high levels of autonomy in robot navigation and robustness in vehicle positioning. Robot localization and mapping is commonly related to cartography, combining science, technique and computation to build a trajectory map that reality can be modelled in ways that communicate spatial information effectively. This book describes comprehensive introduction, theories and applications related to localization, positioning and map building in mobile robot and autonomous vehicle platforms. It is organized in twenty seven chapters. Each chapter is rich with different degrees of details and approaches, supported by unique and actual resources that make it possible for readers to explore and learn the up to date knowledge in robot navigation technology. Understanding the theory and principles described in this book requires a multidisciplinary background of robotics, nonlinear system, sensor network, network engineering, computer science, physics, etc.
Objects Localization and Differentiation Using Ultrasonic Sensors

The most crucial problem for the mobile robot navigation is obstacles detection and their localization. The determination of obstacle position should be as accurate as possible in order to support robot self-localization procedures. In order to increase its efficiency the recognition of some feature of obstacles shapes should be done. The most advanced systems use laser range-finder and vision to solve this task. They allow to obtain a lot of data of a robot environment and the delivered information is quite precise. Unfortunately these devices have some important drawbacks. Laser scanning range-finders are still expensive. Their another drawback is that they scan only in a single plain. It causes that some obstacle cannot be detected. There are also available 3D laser range-finders. But measurements performed by them are time consuming. Therefore it is rather difficult to use them for on-line mobile robot navigation when a robot moves during a measurement execution. Considering vision systems the main disadvantages are computation consuming methods and a price of the system. In this sense ultrasonic range-finders seems still to be very useful equipment for a mobile robot. Their important advantage is low price and simplicity. Considering robotics applications they seem to be very attractive comparing especially with laser range-finders and vision systems. But in current mobile robots the ultrasonic sensors are rather used as an auxiliary equipment allowing to obtain rough information of the environment. The main reason of this situation is that the obtained data from commercial ultrasonic range-finders are very difficult to interprete. In this chapter two methods are presented which makes possible to overcome some difficulties combined with ultrasonic sensing. The first one is dedicated to the problem of object differentiation. The second method addresses the problem of an object localization and simplification of necessary computations.
Pictorial Pattern Recognition Applied To Morphometric Cytology

This paper discusses algorithms for an interactive picture-processing system which would gather quantitative morphological information on four organelles (mitochondria, glycogen, smooth endoplasmic reticulum and rough endoplasmic reticulum) from electron micrographs of liver cells. Many investigations have shown that quantitative data is more indicative of an alteration of function than qualitative data. Unfortunately, the techniques to obtain quantitative data currently in use are slow and sometimes unreliable. The algorithm is a ladder-structured decision tree in which processing technique image resolution is a function of the depth in the decision tree. The algorithm will generate chain-encoded descriptions of each organelle discovered in the current image from which both quantitative and qualitative data may be extracted.
LOW R&D EFFICIENCY IN LARGE PHARMACEUTICAL COMPANIES

Large pharmaceutical companies will face serious challenges in the future when several of their blockbuster drugs run out of patents, and meanwhile a growing political pressure to stop the fast increase in health care expenditures has emerged. The recent wave of mergers and acquisitions (M&A) within the industry can be seen as an effective means to reduce costs and compensate for the reduced earnings from patented drugs. The paper examines the main development in expenditure on research and development (R&D) and number of patents in the industry with a focus on the role of company size. The analysis builds on a data set containing information of both patents and R&D expenditure from the world’s top 90 largest pharmaceutical companies, as well as their account data from 2002 to 2013. The empirical part estimates the firm size effect on R&D efficiency and the amount of investment allocated to R&D. Fixed effects estimation models have been applied to control for differences in firm characteristics. We find significantly lower innovation activities in large companies with low innovation productivity as well. The M&A strategy of the large pharmaceutical companies may have been their wise move to catch up on new drugs and revenues.
Shape transitions in a soft incompressible sphere with residual stresses

Residual stresses may appear in elastic bodies, owing to the formation of misfits in the microstructure, driven by plastic deformations or thermal or growth processes. They are especially widespread in living matter, resulting from dynamic remodelling processes aimed at optimizing the overall structural response to environmental physical forces. From a mechanical viewpoint, residual stresses are classically modelled through the introduction of a virtual incompatible state that collects the local relaxed states around each material point. In this work, we employ an alternative approach based on a strain energy function that constitutively depends only on the deformation gradient and the residual stress tensor. In particular, our objective is to study the morphological stability of an incompressible sphere, made of a neo-Hookean material, and subjected to given distributions of residual stresses. The boundary value elastic problem is studied with analytic and numerical tools. Firstly, we perform a linear stability analysis on the prestressed solid sphere using the method of incremental deformations. The marginal stability conditions are given as a function of a control parameter, which is the dimensionless variable that represents the characteristic intensity of the residual stresses. Secondly, we perform finite-element simulations using a mixed formulation in order to investigate the postbuckling morphology in the fully nonlinear regime. Considering different initial distributions of the residual stresses, we find that different morphological transitions occur around the material domain, where the hoop residual stress reaches its maximum compressive value. The loss of spherical symmetry is found to be controlled by the mechanical and geometrical properties of the sphere, as well as the spatial distribution of the residual stress. The results provide useful guidelines for designing morphable soft spheres, for example by controlling residual stresses through active deformations. They finally suggest a viable solution for the nondestructive characterization of residual stresses in soft tissues, such as solid tumours.
Houghton, Stephen and Hunter, Simon C. and Khan, Umneea and Tan, Carol (2013) Interpersonal and affective dimensions of psychopathic traits in adolescents : development and validation of a self-report

We report the development and psychometric evaluations of a self-report instrument designed to screen for psychopathic traits among mainstream community adolescents. Tests of item functioning were initially conducted with 26 adolescents. In a second study the new instrument was administered to 150 high school adolescents, 73 of who had school records of suspension for antisocial behavior. Exploratory factor analysis yielded a 4-factor structure (Impulsivity g = .73, Self-Centredness g = .70, Callous-Unemotional g = .69, and Manipulativeness g = .83). In a third study involving 328 high school adolescents, 130 with records of suspension for antisocial behaviour, competing measurement models were evaluated using confirmatory factor analysis. The superiority of a first-order model represented by four correlated factors that was invariant across gender and age was confirmed. The findings provide researchers and clinicians with a psychometrically strong, self-report instrument and a greater understanding of psychopathic traits in mainstream adolescents.
Directly imaging damped Lyα galaxies at z > 2 – II. Imaging and spectroscopic observations of 32 quasar fields

Damped Lyα absorbers (DLAs) are a well-studied class of absorption line systems, and yet the properties of their host galaxies remain largely unknown. To investigate the origin of these systems, we have conducted an imaging survey of 32 quasar fields with intervening DLAs between z ∼ 1.9 and 3.8, leveraging a technique that allows us to image galaxies at any small angular separation from the background quasars. In this paper, we present the properties of the targeted DLA sample, new imaging observations of the quasar fields, and the analysis of new and archival spectra of the background quasars.
MOBILITY AND ENVIRONMENTAL EQUITY: DO HOUSING CHOICES DETERMINE EXPOSURE TO AIR POLLUTION?

U.S. Census data show that approximately 40 million Americans move each year, raising questions about the role of mobility in determining observed environmental risk exposure patterns. The literature in this area continues to be contested, and the relationship between household sorting and exposure is still not well understood. We offer a new assessment of this question with respect to the criteria air pollutants (focusing on ozone and particulate matter) using a unique data set that combines information from repeat real estate transactions by the same San Francisco Bay area homebuyers. Our hedonic results suggest a trade-off does exist between housing services and pollution (i.e., households can get more housing services for the same price by moving to a neighborhood with more pollution). Our results show poor/minority households are more likely to make this trade-off and that wealth taken from appreciating housing stocks increases their ability to avoid the conventional sorting induced-exposure story.
On the design of human-safe robot manipulators

Bringing robot manipulators in the same environment as humans seems a natural evolution in the path towards more advanced robotics. This upcoming co-existence will offer a tremendous potential to improve many industrial applications such as manufacturing and assembly. In this paradigm, an efficient synergy between human and robot can be obtained by combining the human’s reasoning ability and adaptability in unstructured environments with the inexhaustible strength of robots. The current generation of commercially available robot manipulators is not designed to fit the specific needs required by this novel collaboration. Indeed, control algorithms that enable an intuitive and efficient interaction between humans and robots are still missing to industrial robots. At an even more fundamental level, the way they are currently designed presents significant risks in the proximity of humans. Many studies have investigated this last aspect to demonstrate the potential danger of a robot Zinn, Khatib, Roth & Salisbury (2004a) and to understand and provide metrics to characterize to the level of this threat Haddadin, AlbuSchaffer, Frommberger & Hirzinger (2008); Haddadin, Albu-Schaffer & Hirzinger (2008); Yamada et al. (1997). The next step for robot designers should focus on increasing human safety to an acceptable level according to the conclusion of these studies. The aim of this chapter is to present how, at the conceptual level, robot manipulators should be mechanically designed to be harmless for humans. Both established and novel concepts will be reviewed to provide actual guidelines to the robot designer. Serial elastic actuators (SAE), distributed macro-mini (DM2) and variable stiffness joints will be reviewed whereas more emphasis will be placed on force limiting devices (FLD), robot soft covering and a method for efficiently coupling robot joint actuators for reducing their potential of transferring energy to the surrounding environment.
DC resistivity at the onset of spin density wave order in two-dimensional metals

The theory for the onset of spin density wave order in a metal in two dimensions flows to strong coupling, with strong interactions not only at the “hot spots,” but on the entire Fermi surface. We advocate the computation of dc transport in a regime where there is rapid relaxation to local equilibrium around the Fermi surface by processes which conserve total momentum. The dc resistivity is then controlled by weaker perturbations which do not conserve momentum. We consider variations in the local position of the quantum-critical point, induced by long-wavelength disorder, and find a contribution to the resistivity which is linear in temperature (up to logarithmic corrections) at low temperature. Scattering of fermions between hot spots, by short-wavelength disorder, leads to a residual resistivity and a correction which is linear in temperature.
Conscience 1 Running head: Conscience Eysenck’s Theory of Conscience: Antisocial Behavior and Moral Reasoning

Hans Eysenck’s hypothesis about the acquisition of behavioral inhibitions and good behavior was evaluated. The hypothesis suggests that what is often described as morality or conscience is acquired through learning experiences to which individuals respond differently according to their temperament-based personality traits. Eysenck’s theory of personality has three temperament-based traits: Psychoticism (P), Extraversion (E), and Neuroticism (N). He suggests that individuals who are low on both the E and N traits are more likely to acquire behavioral inhibitions than individuals who are high on both traits. Further, the E trait is known to affect susceptibility to reinforcement and punishment and therefore learning. Thus, it was hypothesized that individuals low on E and N should have higher scores on an assessment of moral reasoning. The study employed 60 participants between 11 and 15 years of age. The participants were placed in either a high group (n = 30) or a low group (n = 30) based on their E and N trait scores. Participants in the two groups were matched for age and gender. Scores on the P trait were controlled to allow a better test of the E and N trait combination. Differences between the groups on self-reported externalizing conduct problems were examined. Participants’ who scored low on the E and N traits scored significantly lower (p < .001) on self-reported behavior problems than those scoring high on the two traits. In a regression analysis, the interaction of EN accounted for the most variance. Likewise there was a significantly higher moral reasoning score (p < .001) for the participants from the low E and N group. In a regression analysis, the E alone accounted for the most variance. The authors discuss the results, limitations of the study, and suggestions for future research.