Constraints on the near-Earth asteroid obliquity distribution from the Yarkovsky effect

Aims. From lightcurve and radar data we know the spin axis of only 43 near-Earth asteroids. In this paper we attempt to constrain the spin axis obliquity distribution of near-Earth asteroids by leveraging the Yarkovsky effect and its dependence on an asteroid’s obliquity. Methods. By modeling the physical parameters driving the Yarkovsky effect, we solve an inverse problem where we test different simple parametric obliquity distributions. Each distribution results in a predicted Yarkovsky effect distribution that we compare with a X2 test to a dataset of 125 Yarkovsky estimates. Results. We find different obliquity distributions that are statistically satisfactory. In particular, among the considered models, the best-fit solution is a quadratic function, which only depends on two parameters, favors extreme obliquities, consistent with the expected outcomes from the YORP effect, has a 2:1 ratio between retrograde and direct rotators, which is in agreement with theoretical predictions, and is statistically consistent with the distribution of known spin axes of near-Earth asteroids

Equitable persistent coverage of non-convex environments with graph-based planning

In this article, we tackle the problem of persistently covering a complex non-convex environment with a team of robots. We consider scenarios where the coverage quality of the environment deteriorates with time, requiring every point to be constantly revisited. As a first step, our solution finds a partition of the environment where the amount of work for each robot, weighted by the importance of each point, is equal. This is achieved using a power diagram and finding an equitable partition through a provably correct distributed control law on the power weights. Compared with other existing partitioning methods, our solution considers a continuous environment formulation with non-convex obstacles. In the second step, each robot computes a graph that gathers sweep-like paths and covers its entire partition. At each planning time, the coverage error at the graph vertices is assigned as weights of the corresponding edges. Then, our solution is capable of efficiently finding the optimal open coverage path through the graph with respect to the coverage error per distance traversed. Simulation and experimental results are presented to support our proposal

Enzyme production of d-gluconic acid and glucose oxidase: successful tales of cascade reactions

This review mainly focuses on the use of glucose oxidase in the production of D-gluconic acid, which is a reactant of undoubtable interest in different industrial areas. The enzyme has been used in numerous instances as a model reaction to study the problems of oxygen supply in bioreactors. One of the main topics in this review is the problem of the generated side product, hydrogen peroxide, as it is an enzyme-inactivating reagent. Different ways to remove hydrogen peroxide have been used, such as metal catalysts and use of whole cells; however, the preferred method is the coupling glucose oxidase with catalase. The different possibilities of combining these enzymes have been discussed (use of free enzymes, independently immobilized enzymes or co-immobilized enzymes). Curiously, some studies propose the addition of hydrogen peroxide to this co-immobilized enzyme system to produce oxygen in situ. Other cascade reactions directed toward the production of gluconic acid from polymeric substrates will be presented; these will mainly involve the transformation of polysaccharides (amylases, cellulases, etc.) but will not be limited to those (e.g., gluconolactonase). In fact, glucose oxidase is perhaps one of most successful enzymes, and it is involved in a wide range of cascade reactions. Finally, other applications of the enzyme have been reviewed, always based on the production of D-gluconic acid, which produces a decrease in the pH, a decrease in the oxygen availability or the production of hydrogen peroxide; in many instances, cascade reactions are also utilized. Thus, this review presents many different cascade reactions and discusses the advantages/drawbacks of the use of co-immobilized enzymes.We gratefully recognize the financial support from Ministerio de Ciencia e Innovación-Spanish Government and FEDER funds (project number CTQ2017-86170-R, RTI2018-095291-BI00, MAT2017-87579-R) and Generalitat Valenciana (PROMETEO/2018/076). DC thank to Ministerio de Ciencia e Innovacion-Spanish Government by a FPI. PWT thanks to the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES) – Finance Code 001

The role of immune PSA complex (iXip) in the prediction of prostate cancer

Purpose: To analyse the performance of iXip in the prediction of prostate cancer (PCa) and high-grade PCa. Methods: A consecutive series of men undergoing MRI/FUSION prostate biopsies were enrolled in one centre. Indications for prostate biopsy included abnormal prostate-specific antigen (PSA) levels (PSA>4 ng/ml) and/or abnormal digital rectal examination (DRE) and/or abnormal MRI. All patients underwent the evaluation of serum PSA-IgM concentration and the iXip ratio was calculated. Accuracy iXip for the prediction of PCa was evaluated using multivariable binary regression analysis and receiver operator characteristics (ROC) curves. Results: Overall 160 patients with a median age of 65 (62/73) years were enrolled. Overall, 42% patients were diagnosed with PCa and 75% of them had high-grade cancer (Epstein ≥ 3). Patients with PCa were older and presented higher PSA levels, higher PIRADS scores and lower prostate volumes (PVs). On ROC analysis iXip presented an area under the curve (AUC) of 0.57 in the prediction of PCa and of 0.54 for the prediction of high-grade PCa. Conclusions: In our experience, immune PSA complexes are not predictors of PCa. iXip analysis should not be included in the diagnostic pathway of patients at increased risk of PCa

Patients with chronic migraine without history of medication overuse are characterized by a peculiar white matter fiber bundle profile

Background: We investigated intracerebral fiber bundles using a tract-based spatial statistics (TBSS) analysis of diffusion tensor imaging (DTI) data to verify microstructural integrity in patients with episodic (MO) and chronic migraine (CM). Methods: We performed DTI in 19 patients with MO within interictal periods, 18 patients with CM without any history of drug abuse, and 18 healthy controls (HCs) using a 3 T magnetic resonance imaging scanner. We calculated diffusion metrics, including fractional anisotropy (FA), axial diffusion (AD), radial diffusion (RD), and mean diffusion (MD). Results: TBSS revealed no significant differences in the FA, MD, RD, and AD maps between the MO and HC groups. In comparison to the HC group, the CM group exhibited widespread increased RD (bilateral superior [SCR] and posterior corona radiata [PCR], bilateral genu of the corpus callosum [CC], bilateral posterior limb of internal capsule [IC], bilateral superior longitudinal fasciculus [LF]) and MD values (tracts of the right SCR and PCR, right superior LF, and right splenium of the CC). In comparison to the MO group, the CM group showed decreased FA (bilateral SCR and PCR, bilateral body of CC, right superior LF, right forceps minor) and increased MD values (bilateral SCR and right PCR, right body of CC, right superior LF, right splenium of CC, and right posterior limb of IC). Conclusion: Our results suggest that chronic migraine can be associated with the widespread disruption of normal white matter integrity in the brain

KINETIC MODEL FOR WHEY PROTEIN HYDROLYSIS BY ALCALASE MULTIPOINT- IMMOBILIZED ON AGAROSE GEL PARTICLES

Abstract -Partial hydrolysis of whey proteins by enzymes immobilized on an inert support can either change or evidence functional properties of the produced peptides, thereby increasing their applications. The hydrolysis of sweet cheese whey proteins by alcalase, which is multipoint-immobilized on agarose gel, is studied here. A MichaelisMenten model that takes into account competitive inhibition by the product was fitted to experimental data. The influence of pH on the kinetic parameters in the range 6.0 to 11.0 was assessed, at 50 o C. Initial reaction-rate assays in a pHstat at different concentrations of substrate were used to estimate kinetic and Michaelis-Menten parameters, k and K M . Experimental data from long-term batch assays were used to quantify the inhibition parameter, K I . The fitting of the model to the experimental data was accurate in the entire pH range

Robotic Wireless Sensor Networks

In this chapter, we present a literature survey of an emerging, cutting-edge, and multi-disciplinary field of research at the intersection of Robotics and Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system that aims to achieve certain sensing goals while meeting and maintaining certain communication performance requirements, through cooperative control, learning and adaptation. While both of the component areas, i.e., Robotics and WSN, are very well-known and well-explored, there exist a whole set of new opportunities and research directions at the intersection of these two fields which are relatively or even completely unexplored. One such example would be the use of a set of robotic routers to set up a temporary communication path between a sender and a receiver that uses the controlled mobility to the advantage of packet routing. We find that there exist only a limited number of articles to be directly categorized as RWSN related works whereas there exist a range of articles in the robotics and the WSN literature that are also relevant to this new field of research. To connect the dots, we first identify the core problems and research trends related to RWSN such as connectivity, localization, routing, and robust flow of information. Next, we classify the existing research on RWSN as well as the relevant state-of-the-arts from robotics and WSN community according to the problems and trends identified in the first step. Lastly, we analyze what is missing in the existing literature, and identify topics that require more research attention in the future

Space debris collision avoidance using a three-filter sequence

In the last few decades, the amount of space debris has dramatically increased, and this trend is expected to continue in the near future. Thus, there is a real risk that two objects in space orbiting about the Earth might collide. Consequently, an effective method for the detection of collisions is required in order to systematically prevent the creation of new space debris, or to study the evolution of the population of space debris after a collision occurs. This research is focused on objects orbiting in the exosphere - in low Earth orbits (LEOs) - because in the past decades these have produced the most serious damage. The methodology proposed in this paper consists of reducing the number of possible pairs of pieces of space debris into a shortlist of possible pairs at real risk of collision, using a filter sequence. This method is achieved by the following two procedures. First, an interpolation ephemerides table is built to compute the state of all the objects at several instants of time. Secondly, using the interpolation ephemerides table, the number of pairs at risk of collision is reduced by three filters. The first two filters are based on the geometry of the orbits and try to exclude pairs not undergoing orbit crossings, while the third filter searches for a time of coincidence. As a result, we have designed a powerful tool that can be used to avoid collisions between pieces of space debris