Springer Science and Business Media LLC

The purpose of this research is to provide a framework for the analysis and comparison of contact detection algorithms for pairs of ellipses and ellipsoids. This work focuses primarily on the category of algorithms that are the most computationally efficient and can produce estimates of the separation and the penetration distance between ellipses and ellipsoids. Specifically, only analytic representations of the ellipses and ellipsoids are considered and contact detection for moving pairs of ellipsoids is not treated. The first contribution is a mathematical framework for the study of these algorithms, most notably with existence and uniqueness proofs for classes of contact detection algorithms, formal descriptions of the asymptotics of pairs of ellipses in close contact (or overlap), and a global analysis of constraints on the normals. The framework highlights the key role played by the different definitions of contact found in the literature, independent of the numerical strategies deployed to estimate the separation/penetration distance. Specifically, it is shown that all the studied algorithms can be expressed as minimization problems, with or without non-binding constraints on the normal(s) at the contact point(s), and that the constraints can be used to identify the global minima among the critical points in the minimization problem. Another contribution of this research, based on the mathematical framework introduced, is a better classification of the known algorithms. These algorithms are compared on established test problems, and their strengths and weaknesses are highlighted and explained in terms of their classification. Furthermore, this research provides comparisons in speed and stability between the most efficient algorithms in each category over a large sample size of test problems. Among the other contributions, this research describes inexpensive but effective initial estimates of the contact to be used in iterative algorithms. Finally, the usefulness of the new framework is illustrated with the introduction of a fast algorithm combining some new and old ideas.

The paper deals with a compilation of several of our modelling studies on particle methods used for simulation of wound healing and tumor growth processes. The paper serves as an introduction of our modelling approaches to researchers with interest in biological cell-based models that use particle-based modelling approaches. The particles that we consider in the present models mimic either cells or points on cell boundaries that are allowed to migrate as a result of several chemical and mechanical factors. A distinct feature of our modelling frameworks with respect to conventional particle models, is that cells, mimicked by particles, are allowed to divide, differentiate and to die as a result of apoptosis or any causes for cell death. The paper is merely descriptive, rather than written in full mathematical rigor, and will show some of the potentials of the applied modelling.

Fine particles of ash and sand can deposit on the surfaces of cooling ducts, diminishing heat transfer efficiency and threatening the operation of turbine engines. The surface roughness of deposits can alter the nearby flow dynamics, and result in changes of subsequent particle collision and deposition. In this work, the effects of rib turbulence on particle deposition in cooling duct are numerically studied based on the wall modeled shear stress transport k–ω model with a UDF code correction for particle–wall impacts and the discrete particle model. A Gaussian probability density function is adopted to give the topology of deposited particles on the surface impacted by micron particles. We investigate how variables such as particle diameter and temperature impact collision and deposition processes. Additionally, the impact of ribbed turbulence on particle deposition is also discussed. The findings indicate that the impact ratio increases with particle diameter while exhibiting less sensitivity to temperature. Deposition ratios experience a significant decrease when particle size exceeds 1 μm. The temperature of the particles has a noteworthy influence on surface profile of deposits. Specifically, deposits on the wall surface, where particles are introduced by fluid injection, tend to assume a crane-like shape as the temperature rises. Notably, a more uniform deposition pattern is achieved when the particle temperature is low. In terms of particle distribution, low-velocity particles are more likely to accumulate in the windward region of the rib, especially at the junction of the rib wall, where the maximum deposition height is observed. Furthermore, deposits on the rib surface tend to grow, and the gap between the peak and valley widens as the particle temperature increases, as evident from the roughened rib surface features.

Human endotoxemia is a well-accepted surrogate model for studying the acute inflammatory responses. In order to discover the complex underlying dynamics, identifying biologically relevant transcriptional regulators as well as their putative regulatory interactions with target genes is an essential step. However, prediction of relevant transcriptional regulators in higher eukaryotes remains a challenge both in silico and in vivo. In this study, we analyzed gene expression data from human blood leukocytes to extract four significant patterns of highly coexpressed genes that capture the essence of inflammatory phases. Upon identification of these patterns, a number of inflammation-specific pathways are selected by evaluating the enrichment of the corresponding subsets. Subsequently, statistically significant cis-regulatory modules (CRMs) are selected and decomposed into a list of relevant transcription factors (34 TFs) which are further validated from prior experiments and computational studies in literature. Additionally, our analysis also allows for the construction of a putative dynamic representation of the transcriptional regulatory program, making it become a critical enabler for unraveling regulatory interactions which is an essential step towards a quantification of dynamic transcriptional regulatory networks.

Money laundering poses a pervasive threat to the stability and integrity of global financial systems. Since traditional anti-money laundering (AML) methods predominantly rely on rule-based systems and statistical approaches, it has limitations to capture the intricate and interconnected relationships that is inherent in money laundering networks. In response to this challenge, this paper proposes an innovative approach to enhance money laundering detection through transactions. We begin by constructing network graphs from a large dataset of bank transactions. Drawing insights from language modeling and supervised learning, we transform these graphs into directed node representations that effectively encode these intricate relationships and community structures within the transaction network. Subsequently, we utilize Random Forest (RF) to predict suspicious behavior associated with money laundering. Additionally, we address the specific challenges posed by highly imbalanced classes in the context of money laundering detection through both oversampling and undersampling experiments to overcome these challenges. The predictive performance of the RF model with oversampling yielded an accuracy of 86%, whereas when undersampling was applied, the accuracy increased to 92%.

We have fabricated simple bottom-SOT film stacks using doped BiSbX TI materials as the SOT layer with novel high resistance nucleation/growth and migration barrier layers. The thin buffer layer produces a very strong fiber axis (012) texture (rocking curve ~ 7 degs. FWHM). The migration barrier between the FM and The SOT layers significantly reduces both Bi,Sb migration out of the SOT and electrical shunting across the FM. The seed and capping layers have high resistivities (~ 250 uohm-cm), as do the thin migration and nucleation/growth layers (resistivities ~ > 300 uohm-cm). The migration barrier layer is critical to reduce intermixing between SOT and FM layer reducing SOT surface roughness, sharpening the SOT-interlayer interface, and to reduce FM shunting effects. Cross Hall-bar patterns 20umX60um (WxL) were fabricated from the simple film stacks shown schematically in figure 1. Very high SHA values of about 24 (see figs. 4b., and 5b.) were measured on two differently doped BiSbX SOT materials.

A simple and low-power-based discrete-time chaotic oscillator based on Carbon Nanotube Field-Effect Transistors (CNFETs) is presented in this paper. The CNFET is built in SPICE using Wong and Deng's well-known model. The chaotic circuit is composed of a nonlinear circuit that creates an adjustable chaos map, two sample and hold cells for capture and delay functions, and a voltage shifter that works as a buffer and adjusts the output voltage for feedback. The operation of the chaotic circuit was verified via time series and power spectra in the SPICE with a supply voltage of 0.9 V and a frequency of 20 kHz conditions. The CNT-based chaotic circuit design is better at thermal reliability and power consumption in comparing with presented MOS-based design making it suitable for systems where many chaos-signal generators are required on a single chip.

The Topological Insulator (TI) BiSb, grown with a (012) film texture using molecular beam epitaxy, and coupled with a FM layer has been shown to have a very high Spin Hall Angle (SHA) > 2 and high electrical conductivity (>10 5 Ohm -1 m -1 ) in thin film stacks 1 . This makes the TI material ideally suited for spin transfer devices requiring several orders of magnitude less power consumption to operate than other traditional devices 2 . However, the practical implementation of this TI material into devices using PVD requires you overcome many severe material challenges. The BiSb material is very soft, easily damaged in ion milling or by subsequent depositions, it has a very low melting point ~ 280C, and hence possesses a very large in-plane grain size as deposited at room temperature, ~6X the targeted thickness in devices. Thermal Migration of Sb out of the TI material is also a severe problem, which is exacerbated by film roughness and large grain sizes, and all of this must be solved while growing and maintaining a non-prismatic (012) texture of BiSb with low roughness, good interfacial TI properties, at reasonable operating temperatures > 180C in actual device stacks, non-epitaxially on SiOx or ceramic substrates. We discuss here how we addressed these challenges through appropriate selection of epitaxial and non-epitaxial materials for buffer layer(s) (bottom interface), and (top interface) interlayer(s), and by using a non-uniform thickness doping of the BiSb(X) material to stabilize and grow a BiSbX(012) textured layer with low roughness, good TI properties, at elevated temperatures in FM thin film stacks.

Conventional four-switch buck-boost converter (FBBC) has been widely used for battery-powered portable devices when a voltage between the min and max voltages of the battery is needed. However, its power efficiency is limited because of high conduction and switching losses. In this paper, a power-efficient hybrid buck-boost converter (HBUBOC) is presented. The proposed HBUBOC reduces RON and DRC conduction loss, and switching loss simultaneously, thus, achieving high efficiency in both the buck and boost modes, over a wide range of conversion. The proposed HBUBOC achieved a max/min efficiency up to 97/85.43 % over a load current of 0.1-1 A and input voltage of 2.5-5.5 V at 3.3 V output voltage. This performance can be considered as the highest over both buck and boost modes compared to the most recent reported state-of-the-art counterparts if same switches and low-profile high-DCR inductor are used.