Path Space Research Articles

Multi-Objective Safety-Enhanced Path Planning for the Anterior Part of a Flexible Ureteroscope in Robot-Assisted Surgery.

In robot-assisted flexible ureteroscopy, planning a safety-enhanced path facilitates ureteroscope reaching the target safely and quickly. However, current methods rarely consider the safety impact caused by body motion of the anterior part, such as impingement on the lumen wall and sweeping motion risk, or the method can only be used in collision-free situations. The kinematic model of the anterior part under C-shaped and S-shaped collision bending is first analysed. Considering the newly defined impingement cost and sweeping area, the differential evolution algorithm is adopted to optimise the path in the configuration space. Experiments were performed to verify the effectiveness of the method. Compared with the competing algorithm, the proposed algorithm reduced impingement cost and sweeping area by an average of 31.0% and 8.64%. Force measurement experiments verified the rationality of the impingement cost expression. The experimental results proved the feasibility of the proposed path planning algorithm.

Differentiable Photon Mapping using Generalized Path Gradients

Photon mapping is a fundamental and practical Monte Carlo rendering technique for efficiently simulating global illumination effects, especially for caustics and specular-diffuse-specular (SDS) paths. In this paper, we present the first differentiable rendering method for photon mapping. The core of our method is a newly introduced concept named generalized path gradients. Based on the extended path space manifolds (EPSMs) [Xing et al. 2023], the generalized path gradients define the derivatives of the vertex positions and color contributions of a path with respect to scene parameters under given geometric constraints. By formalizing photon mapping as a path sampling technique through vertex merging [Georgiev et al. 2012] and incorporating a smooth differentiable density estimation kernel, we enable the differentiation of the photon mapping algorithms based on the theoretical results of generalized path gradients. Experiments demonstrate that our method is more effective than state-of-the-art physics-based differentiable rendering methods in inverse rendering applications involving difficult illumination paths, especially SDS paths.

Comparative Analysis of the Signal Strength of Two Radio Stations in Okene, Kogi State, Nigeria

There are significant concerns for the citizens of Okene and its surroundings; regarding the distortions experienced in radio signals due to increased attenuation, which have resulted in poor signal quality. This study carried out a comparative analysis of the signal strength of two radio broadcast stations in Okene, Kogi State, Nigeria, using a field strength meter. The study involved measuring the signal strength for each radio stations at six selected locations in Okene and surrounding area. The wavelength and free space path-loss was calculated at sixteen different locations. The results indicated an inverse relationship between the measured signal strengths and the path-loss, as well as the approximate distance amid antennas. The transmitting signal strength was 100.9dBµV (KA) and 102.2dBµV (KB). Distance from station where signal can be receive was 72.0km (KA) and 69.0km (KB). The free space path loss experienced was 109.01dB (KA) and 109.39dB (KB). Even though KA has a lower transmitting signal strength, its longer wavelength 3.21m and lower frequency 93.5MHz gives it an age over KB with higher frequency 109.5MHz and shorter wavelength 2.94m. However, it is recommended that the FM stations should strategically enhance their network infrastructure to improve service delivery, particularly where performance lags. Booster stations at approximately 69km away from the main stations can effectively enhance the signal, leading to better signal quality and improved customer satisfaction.

Extracting fiber paths from the optimized lamination parameters of variable-stiffness laminated shells based on physic-informed neural network

This paper presents a novel approach for extracting fiber paths from the optimized lamination parameters (LPs) of variable stiffness laminated shells, utilizing the framework of physics-informed neural network (PINN). In this methodology, each fiber layer is associated with a specific stream function, which is approximated by an independent neural network. The stream function is governed by a partial differential equation (PDE) derived from the fiber orientation field in the parameter space. Moreover, the isocontours of the stream function are transformed into the actual fiber paths in the physical space. To account for manufacturing constraints, Riemannian geometry serves as a computational tool to determine the intrinsic distance between adjacent fiber paths and the geodesic curvature of the isocontours. By incorporating regularization terms into the loss function based on the physical relationships, the constrained optimization problem is converted into an unconstrained one, making it more suitable for neural network training. Meanwhile, a fiber path extraction (FPE) algorithm is used to minimize the loss function at randomly sampled points through gradient descent. The numerical results suggest that the extraction of fiber paths using PINN can achieve satisfactory levels of accuracy while effectively satisfying the imposed constraints.

Optimizing ironing parameters in material extrusion (MEX) technology: enhancing efficiency and performance

This study explores the optimization of ironing parameters in Material Extrusion (MEX) technology, specifically targeting improvements in the mechanical properties of polylactic acid (PLA) printed objects, with a focus on enhancing Ultimate Tensile Strength (UTS) and minimizing printing time. To achieve this, we employed a systematic experimental approach that varied flow rate, path speed, and spacing between passes, followed by a comprehensive statistical analysis using Analysis of Variance (ANOVA). Our findings indicate that path speed and spacing between passes significantly influence both UTS and printing time, while flow rate has a minor effect within the tested range. Optimal parameters were determined to be a flow rate of 14.34%, path speed of 30 mm/s, and spacing between passes of 0.3 mm, achieving a composite desirability of 0.970537. Validation using the response optimizer feature in Minitab software confirmed a strong correlation between predicted and experimental results. This research provides practical insights for optimizing MEX parameters, contributing to enhanced mechanical properties and efficiency in additive manufacturing processes.

El valor de la educación familiar. Una aproximación desde la obra La vanagloria, la educación de los hijos y el matrimonio de Juan Crisóstomo

The following writing is the result of the interest in identifying elements that contribute to the deepening of the essential values that concern the Christian family. To this end, this writing seeks to approach the practical life of Christians and answer the question: What function did education in the family serve for Christians in the 4th century and what echo does it have for Christian life today? In this logic we focus on the Christianity of Antioch, led by John Chrysostom, in his work: Vainglory, the Education of Children and Marriage, a work written between the years 393-394. In this work it is possible to find various themes in relation to family education, Christian formation and its impact on daily life, showing in it the possibility of witnessing to Christ and conceiving a virtuous life. Finally, this work presents in a general way the vision of marriage as an opportunity to fully live the Christian faith, and a necessary pedagogical place for every Christian. With this we will present a contextual outline of the work, followed by an analysis of the work, presentation of constitutive elements of marriage, family education and some conclusions regarding the current reality of the Christian family. From the exercise of reviewing this style of Christian life, some lines of inspiration will be identified to contribute to the renewal of Christian life today, particularly in the family orbit as a space and formative path to live the Christian faith in particular societies.

Rapidly Screening the Correlation between the Rotational Mobility and the Hydrogen Bonding Strength of Confined Water.

Automated Deuterium Relaxation-Ordered SpectroscopY in solution (ADROSYS), an automated two-dimensional deuterium NMR methodology, discriminates between D2O populations (as well as deuterium-labeled alcohol groups) whose properties differ as a result of being confined inside nanoscale volumes. In this contribution, a proof-of-principle demonstration on reverse micelles (RMs) yields the insight that as the length scale of the confinement decreases from several nanometers down to less than a nanometer, the position of the signal peak migrates through the two-dimensional (2D) spectrum, tracing out a distinctive path in the 2D space (of relaxation time vs chemical shift). The signals typically follow a relatively gentle linear path for water confined on the scale of several nanometers, before curving once the surfactants confine the water molecules to length scales smaller than 1-2 nm. The qualitative shape of this path, especially in the regime of strong confinement, can change with different choices of surfactants, i.e., a different choice of chemistry at the edges of the confining environment. An important facet of this research was to demonstrate the relatively wide applicability of these techniques by showing that both: (1) Standard modern NMR instrumentation is capable of deploying an automated measurement, even though the choice of a deuterium nucleus is nonstandard and frequently requires companion proton spectra in order to reference the chemical shifts; and (2) well-established (though underutilized) modern techniques can process the resulting signal even though it involves the somewhat unusual combination of chemical shifts along one dimension and a distribution of relaxation times along another dimension. In addition to demonstrating that this technique can be deployed across many samples of interest, detailed facts pertaining to the broadening or shifting of resulting signals upon inclusion of various guest molecules are also discussed.

Spin waves and orbital contribution to ferromagnetism in a topological metal

Honeycomb and kagome lattices can host propagating excitations with non-trivial topology as defined by their evolution along closed paths in momentum space. Excitations on such lattices can also be momentum-independent, and the associated flat bands are of interest due to strong interactions between heavy quasiparticles. Here, we report the discovery — using circularly polarized X-rays for the unambiguous isolation of magnetic signals — of a nearly flat spin-wave band and large (compared to elemental iron) orbital moment in the metallic ferromagnet Fe3Sn2 with compact AB-stacked kagome bilayers. As a function of out-of-plane momentum, the nearly flat optical mode and the global rotation symmetry-restoring acoustic mode are out of phase, consistent with a bilayer exchange coupling that is larger than the already large in-plane couplings. The defining units of this topological metal are therefore triangular lattices of octahedral iron clusters rather than weakly coupled kagome planes. The spin waves are strongly damped when compared to elemental iron, opening the topic of topological boson–fermion interactions for deeper exploration within this material platform.

Parameter estimation and singularity of laws on the path space for SDEs driven by Rosenblatt processes

In this paper, we study parameter identification for solutions to (possibly non-linear) SDEs driven by additive Rosenblatt process and singularity of the induced laws on the path space. We propose a joint estimator for the drift parameter, diffusion intensity, and Hurst index that can be computed from discrete-time observations with a bounded time horizon and we prove its strong consistency under in-fill asymptotics with a fixed time horizon. As a consequence of this strong consistency, singularity of measures generated by the solutions with different drifts is shown. This results in the invalidity of a Girsanov-type theorem for Rosenblatt processes.

Risk measures based on weak optimal transport

In this paper, we study convex risk measures with weak optimal transport penalties. In a first step, we show that these risk measures allow for an explicit representation via a nonlinear transform of the loss function. In a second step, we discuss computational aspects related to the nonlinear transform as well as approximations of the risk measures using, for example, neural networks. Our setup comprises a variety of examples, such as classical optimal transport penalties, parametric families of models, divergence risk measures, uncertainty on path spaces, moment constraints, and martingale constraints. In a last step, we show how to use the theoretical results for the numerical computation of worst-case losses in an insurance context and no-arbitrage prices of European contingent claims after quoted maturities in a model-free setting.

Engineering flexible machine learning systems by traversing functionally invariant paths

Contemporary machine learning algorithms train artificial neural networks by setting network weights to a single optimized configuration through gradient descent on task-specific training data. The resulting networks can achieve human-level performance on natural language processing, image analysis and agent-based tasks, but lack the flexibility and robustness characteristic of human intelligence. Here we introduce a differential geometry framework—functionally invariant paths—that provides flexible and continuous adaptation of trained neural networks so that secondary tasks can be achieved beyond the main machine learning goal, including increased network sparsification and adversarial robustness. We formulate the weight space of a neural network as a curved Riemannian manifold equipped with a metric tensor whose spectrum defines low-rank subspaces in weight space that accommodate network adaptation without loss of prior knowledge. We formalize adaptation as movement along a geodesic path in weight space while searching for networks that accommodate secondary objectives. With modest computational resources, the functionally invariant path algorithm achieves performance comparable with or exceeding state-of-the-art methods including low-rank adaptation on continual learning, sparsification and adversarial robustness tasks for large language models (bidirectional encoder representations from transformers), vision transformers (ViT and DeIT) and convolutional neural networks.

Self-induced Bose glass phase in quantum quasicrystals

We study the emergence of Bose glass phases in self sustained bosonic quasicrystals induced by a pair interaction between particles of Lifshitz–Petrich type. By using a mean-field variational method designed in momentum space as well as Gross–Pitaevskii simulations we determine the phase diagram of the model. The study of the local and global superfluid fraction allows the identification of supersolid, super quasicrystal, Bose glass and insulating phases. The Bose glass phase emerges as a quasicrystal phase in which the global superfluidity is essentially zero, while the local superfluidity remains finite in certain ring structures of the quasicrystalline pattern. Furthermore, we perform continuous space Path Integral Monte Carlo simulations for a case in which the interaction between particles stabilizes a quasicrystal phase. Our results show that as the strength of the interaction between particles is increased the system undergoes a sequence of states consistent with the super quasicrystal, Bose glass, and quasicrystal insulator thermodynamic phases.

Optimal Trajectory Planning for Wheeled Robots (OTPWR): A Globally and Dynamically Optimal Trajectory Planning Method for Wheeled Mobile Robots

In recent years, with the widespread application of indoor inspection robots, efficient motion planning has become crucial. Addressing the issue of discontinuous and suboptimal robot trajectories resulting from the independent nature of global and local planning, we propose a novel optimal path-planning method for wheeled mobile robots. This method leverages differential flatness to reduce dimensionality and decouple the problem, achieving globally optimal, collision-free paths in a two-dimensional flat output space through diagonal search and polynomial trajectory optimization. Comparative experiments in a simulated environment demonstrate that the proposed improved path search algorithm reduces search time by 46.6% and decreases the number of visited nodes by 43.1% compared to the original algorithm. This method not only ensures the optimal path and efficient planning but also ensures that the robot’s motion trajectory satisfies the dynamic constraints, verifying the effectiveness of the proposed optimal path planning algorithm for wheeled mobile robots.

EMPIRICAL STUDY OF SIGNAL STRENGTH PATH LOSS IN A UNIVERSITY CAMPUS ENVIRONMENT

Conducting performance analysis can be a valuable tool for mobile network operators (MNO) in optimizing network performance, improving user experience, and ensuring services, such as voice calls, data transmission, and video streaming, as well as to adhere to quality standards. This approach facilitates capacity planning, resource allocation, and the prompt identification and resolution of network congestion, hardware failures, or security breaches. In this paper, the performance of three MNOs around Papua New Guinea University of Technology (PNGUoT) is examined. The downlink frequency signal was measured and collected using the MST207T spectrum analyzer. The allocated frequency spectrum for each mobile network evolution from 3G to 4G-LTE was analyzed and calculated for signal strength path loss utilizing Free Space Path Loss (FSPL) and the Cost 231 Hata Model methods. 5G is not discussed in this paper as the technology is awaiting PNG market entry approval. The findings indicate that Digicel towers exhibit a decrease in downlink signal intensity and quality in areas with poor signal reception. Certain technical issues were observed to be responsible for the identified poor performances, including overcrowding of base stations (BS). The signal strength qualities of Bmobile Vodafone and Telikom exhibit variations, suggesting a moderate to poor level of quality. The data results from the path loss calculation also show an increase in fading signal strength quality. The findings of this empirical study would provide valuable insights for enhancing the efficiency and coverage of mobile communication networks around PNGUoT.

FF-RRT*: A Sampling-Based Planner for Multirobot Global Formation Path Planning

Abstract This article presents a collision-free global path planning approach for multirobot systems called flexible formation—rapidly exploring randomized trees* (FF-RRT*). The algorithm is based on RRT* and provides a flexible and efficient representation of the formation geometry independent of the number of robots. It is designed to generate optimal paths for multirobot systems in a five-dimensional configuration space comprising the formation centroid, orientation, and scaling. An affine transformation is used to convert the path in the configuration space to the workspace of the robots. The proposed method employs a new distance function that eliminates the need for tuning weights and a sampling scheme for scaling factors to avoid inter-robot collisions. FF-RRT* is experimentally demonstrated using nonholonomic wheeled mobile robots and is effective in planning the collective motion of the robots. Robots could collectively reach goals by squeezing through narrow gaps and splitting and merging around large obstacles.

Sub-terahertz near field channel measurements and analysis with beamforming and Bessel beams

Sub-terahertz communications (100–300 GHz) are explored today as a candidate technology to enable extremely high-rate, low-latency data services and high-resolution sensing in beyond-fifth-generation (beyond-5G) wireless networks. However, these sub-terahertz wireless systems will often have to operate in the near field, where the signal propagation does not follow canonical far-field models, including the commonly used free space path loss equation. Instead, the signal propagation in the near field follows more complex patterns that are not well-captured with analytical far-field models standardized for 5G research. Moreover, state-of-the-art beamforming solutions exploited heavily in fourth-generation (4G) and 5G networks are notably less efficient in the near field. In this article, the near-field sub-terahertz channel is accurately measured and analyzed. In addition to state-of-the-art beamforming, the article also analyzes the sub-terahertz channel measurements when using near-field-specific Bessel beams that demonstrate fewer power fluctuations in the near field in addition to higher focusing gain. Novel distance-centric and angle-centric dependencies reported in this article may serve as a reference when developing next-generation channel models for sixth-generation (6G) and beyond-6G near-field sub-terahertz wireless systems.

On the path of spin-[formula omitted] Berry phase

This paper investigates the relation between the Berry phase of a spinor accumulated along a path corresponding to an adiabatically varying magnetic field and the conformal deformation along the path in the parameter space. The first part demonstrates that the accumulated phase can be controlled by continuous deformation characterized by a single conformal parameter. The source of the corresponding field strength responsible for the deformed phase path is shown to be a conformally deformed monopole located at the origin in the parameter space with the fundamental strength g=±1/2. In the second part, we model a rotating magnetic field coupled to a charged spinor with a time-varying amplitude subjected to the conformal deformation, realizing a single-variable deformation of the evolution process of the phase path.

Impact of Antenna Orientation on Localization Accuracy Using RSSI-based Trilateration

The goal of the indoor localization is to determine the position and orientation of people, devices, and mobile robots. With the rise of Industry 4.0, wireless communication technologies have emerged as a rapidly evolving and crucial area for achieving this goal. Various radiocommunication-based technologies, including Bluetooth, Bluetooth Low Energy (BLE), Wi-Fi, Ultra-Wideband (UWB), and ZigBee offer means to indirectly estimate distance. These methods leverage diverse principles such as time-based measurements, signal strength, and angle of arrival. Indoor positioning systems can be categorized into two approaches: distance-based and distance-independent techniques. The Free Space Path Loss (FSPL) model describes the connection between distance and Received Signal Strength Indicator (RSSI). The parameters within this model significantly impact distance estimation and localization accuracy. Therefore, a method that accurately characterizes the model is critical. This work proposes an orientation-based localization technique utilizing RSSI and trilateration. Measurements were conducted between two ESP32 units in various orientations to obtain optimal parameters for each specific scenario. To assess the effectiveness of this approach, two scenarios were evaluated: one considering orientation and another neglecting it. The results show that incorporating orientation information leads to significantly more accurate positioning compared to the orientation-agnostic approach.

A strain acceleration method to identify the onset of diffuse necking

This paper presents an innovative ‘strain acceleration method’ for determining the onset of diffuse necking in sheet forming tests using data obtained from digital image correlation (DIC). The method identifies the onset time of diffuse necking and provides the corresponding in-plane principal strain values by detecting a local extreme in the second derivative of the minor principal in-plane strain with respect to time at the edges of the sheet surface region where diffuse necking occurs. Results obtained from applying the method to tensile testing on two different materials and comparisons with available methods based on force-time or principal strain rate evolutions confirm its accuracy and validity. The new method was implemented in a computer software to be used for research and education that also enables determination of localized necking and fracture and plotting the strain loading paths in principal strain space.

Application of Artificial Intelligence in the Design of 2D Escape From Pirates Game with A Star Algorithm Search Method

This research is designed to provide a challenging gaming experience by integrating strategy and problem-solving elements. The A* algorithm was chosen due to its efficient ability to find the shortest path in a complex search space. The implementation of this algorithm allows the main character to dynamically avoid obstacles and pirate threats and reach the destination in an optimal way. The test results show that the A* algorithm not only improves game performance but also provides a more realistic and challenging experience for the player. For testing this application, using obstacles and measured based on the value of nodes on the game map. Based on the test results, the A Star algorithm was successfully applied when comparing the computations in the game and manual calculations in the Escape from Pirates game in the test. Thus, this research contributes to the development of artificial intelligence-based games and opens opportunities for further innovation in interactive game design.