Identifying and understanding urban sport areas using Nokia Sports Tracker

Current advancements in pervasive technologies allow users to create and share an increasing amount of whereabouts data. Thus, some rich datasets on human mobility are becoming available on the web. In this paper we extracted approximately 790,000 mobility traces from a web-based repository of GPS tracks—the Nokia Sports Tracker Service. Using data mining mechanisms, we show that this data can be analyzed to uncover daily routines and interesting schemes in the use of public spaces. We first show that our approach supports large-scale analysis of people’s whereabouts by comparing behavioral patterns across cities. Then, using Kernel Density Estimation, we present a mechanism to identify popular sport areas in individual cities. This kind of analysis allows us to highlight human-centered geographies that can support a wide range of applications ranging from location-based services to urban planning.     

Information-Driven Sensor Path Planning by Approximate Cell Decomposition

A methodology is developed for planning the sensing strategy of a robotic sensor deployed for the purpose of classifying multiple fixed targets located in an obstacle-populated workspace. Existing path planning techniques are not directly applicable to robots whose primary objective is to gather sensor measurements using a bounded field of view (FOV). This paper develops a novel approximate cell-decomposition method in which obstacles, targets, sensor's platform, and FOV are represented as closed and bounded subsets of an Euclidean workspace. The method constructs a connectivity graph with observation cells that is pruned and transformed into a decision tree from which an optimal sensing strategy can be computed. The effectiveness of the optimal sensing strategies obtained by this methodology is demonstrated through a mine-hunting application. Numerical experiments show that these strategies outperform shortest path, complete coverage, random, and grid search strategies, and are applicable to nonoverpass capable robots that must avoid targets as well as obstacles.     

Akhet Khufu: Archaeo-astronomical Hints at a Common Project of the Two Main Pyramids of Giza, Egypt

The architectural complexes composed by the two main pyramids of Giza together with their temples are investigated from an interdisciplinary point of view, taking into account their astronomical alignments as well as their relationships with the visible landscape. Combining already known facts together with new clues, the work strongly supports the idea that the two complexes were conceived as parts of a common project.     

Proposal for the measurement of backward and total scattering by mineral particles suspended in water

An experimental procedure for the determination of the specific backscattering and total scattering coefficients of mineral particles suspended in water is described. The procedure combines measurements performed on samples of particles retained in glass-fiber filters and suspended in water, using a dual-beam spectrophotometer provided with an integrating-sphere attachment.     

A heuristic approach to automatic grasp planning for a 3-fingered hand

This paper presents the core of a software system able to determine a good grasp configuration on 3D objects for a three-fingered hand. The grasp planning problem has been studied considering both the constraints due to the stability and accessibility conditions, and the ones related to functionality. Physical, geometrical, spatial and task-related knowledge for solving the grasp planning problem have been properly modelled to support a heuristic-based reasoning process. A series of heuristic rules and geometric tests are used to scan the solution space, searching for a good grasp. In fact, when considering the three-dimensional case, a purely analytical and exhaustive approach appears too complex because of the dimension of the search space. This approach results in an incremental and modular model of grasp reasoning, that has been implemented using the Flex expert system shell. This work has been developed and demonstrated within the Esprit 2 project CIM-PLATO No. 2202.     

Indirect Exciton–Phonon Dynamics in MoS2 Revealed by Ultrafast Electron Diffraction

Transition metal dichalcogenides layered nano-crystals are emerging as promising candidates for next-generation optoelectronic and quantum devices. In such systems, the interaction between excitonic states and atomic vibrations is crucial for many fundamental properties, such as carrier mobilities, quantum coherence loss, and heat dissipation. In particular, to fully exploit their valley-selective excitations, one has to understand the many-body exciton physics of zone-edge states. So far, theoretical and experimental studies have mainly focused on the exciton–phonon dynamics in high-energy direct excitons involving zone-center phonons. Here, ultrafast electron diffraction and ab initio calculations are used to investigate the many-body structural dynamics following nearly- resonant excitation of low-energy indirect excitons in MoS₂. By exploiting the large momentum carried by scattered electrons, the excitation of in-plane K- and Q- phonon modes are identified with 𝑬^′ symmetry as key for the stabilization of indirect excitons generated via near-infrared light at 1.55 eV, and light is shed on the role of phonon anharmonicity and the ensuing structural evolution of the MoS₂ crystal lattice. The results highlight the strong selectivity of phononic excitations directly associated with the specific indirect- exciton nature of the wavelength-dependent electronic transitions triggered in the system.     

Cell-protection mechanism through autophagy in HGFs/<Emphasis Type="Italic">S. mitis</Emphasis> co-culture treated with Chitlac-nAg

Silver-based products have been proven to be effective in retarding and preventing bacterial growth since ancient times. In the field of restorative dentistry, the use of silver ions/nanoparticles has been explored to counteract bacterial infections, as silver can destroy bacterial cell walls by reacting with membrane proteins. However, it is also cytotoxic towards eukaryotic cells, which are capable of internalizing nanoparticles. In this work, we investigated the biological effects of Chitlac-nAg, a colloidal system based on a modified chitosan (Chitlac), administered for 24–48?h to a co-culture of primary human gingival fibroblasts and Streptococcus mitis in the presence of saliva, developed to mimic the microenvironment of the oral cavity. We sought to determine its efficiency to combat oral hygiene-related diseases without affecting eukaryotic cells. Cytotoxicity, reactive oxygen species production, apoptosis induction, nanoparticles uptake, and lysosome and autophagosome metabolism were evaluated. In vitro results show that Chitlac-nAg does not exert cytotoxic effects on human gingival fibroblasts, which seem to survive through a homoeostasis mechanism involving autophagy. That suggests that the novel biomaterial Chitlac-nAg could be a promising tool in the field of dentistry.     

Editorial: Special issue on approximate dynamic programming and reinforcement learning

We are extremely pleased to present this special issue of the Journal of Control Theory and Applications.Approximate dynamic programming (ADP) is a general and effective approach for solving optimal control and estimation problems by adapting to uncertain environments over time.ADP optimizes the sensing objectives accrued over a future time interval with respect to an adaptive control law,conditioned on prior knowledge of the system,its state,and uncertainties.A numerical search over the present value of the control minimizes a Hamilton-Jacobi-Bellman (HJB) equation providing a basis for real-time,approximate optimal control.     

From Images to Shape Models for Object Detection

We present an object class detection approach which fully integrates the complementary strengths offered by shape matchers. Like an object detector, it can learn class models directly from images, and can localize novel instances in the presence of intra-class variations, clutter, and scale changes. Like a shape matcher, it finds the boundaries of objects, rather than just their bounding-boxes. This is achieved by a novel technique for learning a shape model of an object class given images of example instances. Furthermore, we also integrate Hough-style voting with a non-rigid point matching algorithm to localize the model in cluttered images. As demonstrated by an extensive evaluation, our method can localize object boundaries accurately and does not need segmented examples for training (only bounding-boxes).