Multi bin energy-sensitive micro-CT using large area photon-counting detectors Timepix

X-ray micro-CT has become a popular and widely used tool for the purposes of scientific research. Although the current state-of-the-art micro-CT is on a high technology level, it still has some known limitations. One of the relevant issues is an inability to clearly identify and quantify specific materials. The mentioned drawback can be solved by the energy-sensitive CT approach. Dual-energy CT, which is already frequently used in human medicine, offers the identification of two different materials; for example, it differentiates an intravenous contrast agent from bone or it can indicate the composition of urinary stones. Resolving a larger number of material components within a single object is beyond the capabilities of dual-energy CT. Such an approach requires a higher number of measurements using different photon energies. A possible solution for multi bin, or so-called spectral CT, is the application of photon-counting detectors. Photon counting technology offers an integrated circuitry capable of resolving the energy of incoming photons in each pixel. Therefore, it is possible to collect data in user-defined energy windows. This contribution evaluates the applicability of the large-area photon-counting detector Timepix for multi bin energy-sensitive micro-CT. It presents an experimental phantom study focused on the simultaneous K-edge-based identification and quantification of multiple contrast agents within a single object. The paper describes the collection of multiple energy bins using the Timepix detector operated in the photon counting mode, explains the data processing, and demonstrates the results obtained from an in-house implemented basis material decomposition algorithm.

Optical encryption using phase modulation generated by thermal lens effect

We present the implementation of an experimental optical encryption configuration in the Fresnel domain using the thermal lens effect to modulate the phase of the illumination beam. We corroborate the basic performance of our cryptosystem by performing the encryption-decryption procedure of a single object. Then, we test the tolerance of the proposed scheme to decrypt decryption with keys registered for different modulations of the illumination beam induced by the phase generated due to thermal lens effect. These different phase modulations are obtained by introducing axial displacements of a sample, where the thermal lens effect is induced by an excitation beam. Considering the phase modulation changes in the illumination due to sample displacements, we propose an undercover procedure to further protect the target information using decoy data. The key associated with the target information is obtained when the probe and excitation beams are focused on the same point of the sample, while the decoy object key is registered when the beams are not focused on the same region of the sample. Finally, we analyzed the resistance of the undercover ciphertext to some of the attacks reported in the literature. All experimental results presented in this work demonstrate the basic capabilities, viability, and versatility of our proposals.

The Short-Term Retention of Depth

We review research on the visual working memory for information portrayed by items arranged in depth (i.e., distance to the observer) within peri-personal space. Most items lose their metric depths within half a second, even though their identities and spatial positions are retained. The paradoxical loss of depth information may arise because visual working memory retains the depth of a single object for the purpose of actions such as pointing or grasping which usually apply to only one thing at a time.

A MEDICAL SERVICE OF IMPROPER QUALITY: SOME ASPECTS OF THE INVESTIGATION METHODOLOGY

В статье рассматриваются преступления против здоровья населения и в сфере охраны жизни и здоровья человека, совершаемые медицинскими работниками. Обосновывается необходимость объединения этих преступлений в качестве единого объекта криминалистического исследования. Приводятся примеры фактов привлечения работников системы здравоохранения к уголовной ответственности за оказание услуг, не отвечающих требованиям безопасности. Определяются законодательные пробелы, связанные с отсутствием уголовно-правовой охраны человеческого плода в процессе родового акта, а также с невозможностью применения квалифицирующих признаков указанных преступлений в случае виновного причинения гибели плоду. The article considers crimes against public health and in the sphere of protection of life and health committed by medical workers. The necessity of combining these crimes as a single object of forensic investigation is substantiated. Examples of bringing of health care workers to criminal liability for the provision of services that do not meet the safety requirements are given. The legislative gaps associated with the lack of criminal law protection of human fetus in the process of delivery, as well as the inability to apply the qualifying signs of these crimes in the case of culpable causing the death of a human fetus are identified.

Single object tracking algorithm in occlusion scene based on improved ECO

To alleviate the occlusion problem in a single object tracking scene, this paper proposes an ECO-MHDU object tracking algorithm with a more powerful anti-occlusion performance based on the ECO tracker. The algorithm first uses the pre-trained MobileNetV3 lightweight backbone network on the ImageNet dataset to replace the ResNet network in the ECO to increase the speed of the algorithm to obtain the shallow and deep feature information of the image, while effectively using the attention mechanism in the MobileNetV3 network to strengthen the algorithm’s ability to extract target features; secondly, use the DropBlock operation on the acquired feature map to generate a random continuous mask on the feature map channel to improve the algorithm’s learning of the global robust spatial structure information; finally, a confidence update strategy is introduced into the GMM sample generation space. To improve the quality of training samples, unreliable tracking states such as confidence detection and occlusion are designed to avoid updating the sample space with damaging information. Compared with the ECO algorithm, the ECO-MHDU algorithm proposed in this paper has a success rate of 68.0% on the occlusion attributes of the OTB100 dataset, which is 2.3% higher than the ECO algorithm, and the ECO-MHDU algorithm also showed the best performance on the entire dataset sequence, with a success rate of 69.3%.

IBOA-Based Optimization of Cross-Sectional Dimension of Rods for a 3-RRR PPM to Minimize Energy Consumption

For obtaining optimal cross-sectional dimensions of rods for a 3-RRR planar parallel manipulator (PPM) to minimize energy consumption, the inverse dynamics of the manipulator is modeled based on the Newton–Euler method, after which the coefficient matrix of the inverse dynamics equation is decomposed based on matrix theory. Hence, the objective function, that is, the logical relationship between the energy consumption of the manipulator and the cross-sectional dimension of each rod, is established. However, in solving the multidimensional constrained single-object optimization problem, there are difficulties such as the penalty function’s sensitivity to the penalty factors if the problem is transformed into the one of unconstrained multiobjective optimization. Therefore, to properly handle the constraints, an improved butterfly optimization algorithm (IBOA) is presented to ensure that the new iterated point always falls into the feasible region according to the butterfly optimization algorithm (BOA). Finally, the comparisons among the IBOA, particle swarm optimization (PSO), and BOA and further experiments of the physical prototype are implemented to validate the effectiveness of the proposed theoretical model and numerical algorithm. Results indicate that the proposed IBOA is more suitable for solving the constrained single-object optimization problem with better convergence speed and accuracy.

Data Citation and the Citation Graph

The citation graph is a computational artifact that is widely used to represent the domain of published literature. It represents connections between published works, such as citations and authorship. Among other things, the graph supports the computation of bibliometric measures such as h-indexes and impact factors. There is now an increasing demand that we should treat the publication of data in the same way that we treat conventional publications. In particular, we should cite data for the same reasons that we cite other publications. In this paper we discuss what is needed for the citation graph to represent data citation. We identify two challenges: (i) to model the evolution of credit appropriately (through references) over time and (ii) to model data citation not only to a dataset treated as a single object but also to parts of it. We describe an extension of the current citation graph model that addresses these challenges. It is built on two central concepts: citable units and reference subsumption. We discuss how this extension would enable data citation to be represented within the citation graph and how it allows for improvements in current practices for bibliometric computations both for scientific publications and for data.

Three-Dimensional Outdoor Analysis of Single Synthetic Building Structures by an Unmanned Flying Agent Using Monocular Vision

An algorithm designed for analysis and understanding a 3D urban-type environment by an autonomous flying agent, equipped only with a monocular vision, is presented. The algorithm is hierarchical and is based on the structural representation of the analyzed scene. Firstly, the robot observes the scene from a high altitude to build a 2D representation of a single object and a graph representation of the 2D scene. The 3D representation of each object arises as a consequence of the robot’s actions, as a result of which it projects the object’s solid on different planes. The robot assigns the obtained representations to the corresponding vertex of the created graph. The algorithm was tested by using the embodied robot operating on the real scene. The tests showed that the robot equipped with the algorithm was able not only to localize the predefined object, but also to perform safe, collision-free maneuvers close to the structures in the scene.

Planning for grasping cluttered objects based on obstruction degree

Grasping objects in clutter is more difficult than grasping a separated single object. An important issue is that unsafe grasps may occur, in case, one object sits or leans on another, which could cause the collapse of objects. In addition, reachability of each object surrounded by other obstacles also has to be considered. So the order of multiple objects for grasping and the grasp configuration of each object must be planned simultaneously. This article combines grasp order and grasp configuration planning to perform fast and safe multiobject grasping in cluttered scenes. First, a comprehensive grasp configuration database is built to provide enough feasible grasp configurations for the objects. Then, we propose an obstruction degree to estimate the likelihood of reachability of each grasp configuration as well as each object. This measurement also implicitly infers object interactions. Finally, grasp order and grasp configurations are planned together to deal with the constraints caused by reachability and object interaction. Simulations and experiments in a series of cluttered scenes demonstrate that our method can grasp objects efficiently and can greatly reduce unsafe grasps.