Directional Path Research Articles

The Aerial Guide Dog: A Low-Cognitive-Load Indoor Electronic Travel Aid for Visually Impaired Individuals.

Most navigation aids for visually impaired individuals require users to pay close attention and actively understand the instructions or feedback of guidance, which impose considerable cognitive loads in long-term usage. To tackle the issue, this study proposes a cognitive burden-free electronic travel aid for individuals with visual impairments. Utilizing human instinctive compliance in response to external force, we introduce the "Aerial Guide Dog", a helium balloon aerostat drone designed for indoor guidance, which leverages gentle tugs in real time for directional guidance, ensuring a seamless and intuitive guiding experience. The introduced Aerial Guide Dog has been evaluated in terms of directional guidance and path following in the pilot study, focusing on assessing its accuracy in orientation and the overall performance in navigation. Preliminary results show that the Aerial Guide Dog, utilizing Ultra-Wideband (UWB) spatial positioning and Measurement Unit (IMU) angle sensors, consistently maintained minimal deviation from the targeting direction and designated path, while imposing negligible cognitive burdens on users while completing the guidance tasks.

Bridging Effect of Carbon Nitride with More Negative Conduction Potential and Halogens Promotes the Liquid-Phase Oxidation of Aromatic C-H Bonds.

The selective oxidation of benzyl C-H bonds of alkyl aromatic hydrocarbons under solvent-free conditions by using heterogeneous catalysis is a challenging task. In this work, we designed a carbon nitride photocatalyst with a high charge separation efficiency and a directed charge transfer path, which was doped with Ni and Br in the carbon nitride skeleton. Br was deposited directionally onto the electron-rich Ni surface traps to form a bond with Ni, which acted as a charge transfer bridge connecting CN and Br, resulting in a bridging effect. Photogenerated electrons were transferred from Ni target to Br, and electrons were aggregated to form a directional charge transfer path, thereby enhancing the photocatalytic performance of CN. The photocatalyst was utilized for the selective oxidation of ethylbenzene at room temperature, atmospheric pressure, and solvent-free conditions. Under batch conditions simulating solar irradiation, the conversion of ethylbenzene was 43.3% and the selectivity of the product acetophenone was up to 92.0%. With the continuous flow strategy, the conversion of ethylbenzene was increased to 52.4 and 48.1%, respectively, while the selectivity reached 92.7 and 91.0%, and the reaction time was reduced from 24 to 2.1 h. The catalyst was also found to be broadly applicable for the selective oxidation of C-H bonds in the benzyl position of alkyl aromatic hydrocarbons.

A novel directional sampling-based path planning algorithm for ambient intelligence navigation scheme in autonomous mobile robots

Path planning algorithms determine the performance of the ambient intelligence navigation schemes in autonomous mobile robots. Sampling-based path planning algorithms are widely employed in autonomous mobile robot applications. RRT*, or Optimal Rapidly Exploring Random Trees, is a very effective sampling-based path planning algorithm. However, the RRT* solution converges slowly. This study proposes a directional random sampling-based RRT* path planning algorithm known as DR-RRT* to address the slow convergence issue. The novelty of the proposed method is that it reduces the search space by combining directional non-uniform sampling with uniform sampling. It employs a random selection approach to combine the non-uniform directional sampling method with uniform sampling. The proposed path planning algorithm is validated in three different environments with a map size of 384*384, and its performance is compared to two existing algorithms: RRT* and Informed RRT*. Validation is carried out utilizing a TurtleBot3 robot with the Gazebo Simulator and the Robotics Operating System (ROS) Melodic. The proposed DR-RRT* path planning algorithm is better than both RRT* and Informed RRT* in four performance measures: the number of nodes visited, the length of the path, the amount of time it takes, and the rate at which the path converges. The proposed DR-RRT* global path planning algorithm achieves a success rate of 100% in all three environments, and it is suited for use in all kinds of environments.

An Effective Method for Computing the Least-Cost Path Using a Multi-Resolution Raster Cost Surface Model

Calculating the least-cost path (LCP) is a fundamental operation in raster-based geographic information systems (GIS). The LCP is applied to raster cost surfaces, in which it determines the most cost-effective path. Increasing the raster resolution results in a longer computation time to obtain LCP. This paper proposes a method for calculating the LCP using a multi-resolution raster cost surface model to enhance computational performance for large-scale grids. The original raster cost surface is progressively downsampled to generate grids of decreasing resolutions. Subsequently, the path is determined on the low-resolution raster. By performing operations such as filtering directional points and mapping path points, the final path on the high-resolution raster can be obtained. The method enables a parallel computation of paths. Therefore, it significantly improves the efficiency for synthetic raster cost surfaces with continuous or discrete characteristics, as well as for raster cost surfaces generated from real terrain datasets, while also providing an end-to-end path output. The experiments show that 80% of the results are very close to the original LCP, and the accuracy of the remaining paths falls within an acceptable range. At the same time, our method greatly improves the efficiency of path solving on a large-scale raster, fulfilling practical application requirements.

Infiltration of C-ring into crystalline carbon nitride S-scheme homojunction for photocatalytic hydrogen evolution

Enhancing the carrier separation in graphitized carbon nitride (g-C3N4) is advantageous for improving its photocatalytic activity. Herein, we propose a feasible method for preparing CN-C by thermal polymerization to gradually infiltrate carbon rings (C-rings) into the surface of crystalline carbon nitride (CN), enabling photogenerated electrons to be transferred rapidly between the CN inner layers and the CN/C outer layer. Successful penetration and distribution of carbon rings into carbon nitride were confirmed by secondary ion mass spectroscopy using ratio analysis of C and N elements at various depths of the prepared photocatalyst. Theoretical calculations indicated that CN and CN/C in the molecule generated different Fermi levels to form an S-scheme homojunction, establishing appropriate built-in electric fields and thus enabling interlayer charge migration. Moreover, the overlap of the conjugate plane of C-rings with carbon nitride led to the formation of photogenerated in-plane charge transfer tunnels. The two-electron transfer tunnels greatly improved the dissociation efficiency of photogenerated electrons. The prepared sample loaded with 3 wt% Pt as a co-catalyst for hydrogen production under visible light irradiation, and the prepared optimal sample CN-C showed a maximum quantum efficiency of 15.56% for photocatalytic H2 evolution at 385 nm. This research introduces a new idea for constructing a directional transfer path for charge carriers in-plane and intralayer.

Temporal order of diagnosis between gambling disorder and substance use disorders: Longitudinal results from the Norwegian Patient Registry

IntroductionPrevious research has established co-occurrence between substance use disorders (SUDs) and gambling disorder (GD). Less well understood is the temporal sequencing of onset between these disorders, and in particular whether SUD is a risk factor for GD. The present study examined the temporal order between registered diagnoses of SUD and GD, stratified by sex. MethodsA study with a longitudinal design using objective registry data drawn from the Norwegian Patient Registry was carried out. Among the patients with a registered diagnosis of GD between 2008 and 2018 (N = 5,131; males = 81.8%), those (who in addition) had a registered diagnosis of any SUD (n = 1,196; males = 82.1%) were included. The measures included a registered diagnosis using the ICD-10 of both GD (code F63.0) and SUDs (codes F10-F19) by a health care professional. Binomial tests were used to identify the temporal order between SUD(s) and GD. Co-occurring cases (i.e., cases diagnosed within the same month) were removed in the main analyses. ResultsResults showed a significant directional path from SUD to GD but no support for the reversed path (i.e., from GD to SUD). This finding was similar overall for (i) both males and females, (ii) when different SUDs (alcohol, cannabis, sedatives, and polysubstance) were examined individually, and (iii) when specifying a 12-month time-lag between diagnoses. ConclusionsThe findings suggest that experiencing SUD(s) is a risk marker for GD given the temporal precedence observed for patients in specialised healthcare services seeking treatment. These results should be considered alongside screening and prevention efforts for GD.

Robust Beamforming Design for RIS-Aided Integrated Sensing and Communication System

It is expected that the future intelligent transportation system will be endowed with the sensing ability to cope with the complex road environment. Therefore, the integrated sensing and communications (ISAC) system can complement the development of intelligent transportation. In this work, a novel reconfigurable intelligent surface (RIS)-aided ISAC system is investigated, in which an RIS reflects signals to the vehicle target and user by creating a directional path to enhance sensing and communication performance. We are interested in the joint robust design of transmitted beamformer at the dual-functional radar-communication (DFRC) base station and phase-shift at the RIS to maximize the radar mutual information subject to user achievable rate constraint under imperfect angles knowledge and channel state information (CSI). Specifically, two CSI error models, namely, the bounded and the mixed bounded-moment error models, are considered. Then, a worst-case robust (WCR) beamforming problem, as well as a mixed chance-constrained and worst-case robust (MCWR) beamforming problem, are separately formulated. Furthermore, we develop two efficient methods to convert the formulated semi-infinite constraint problems into feasibility ones, and an alternate optimization framework is proposed to obtain stationary points of the original problems. Simulation results are provided to validate the effectiveness of the proposed transformation methods and solution.

Hollow bi-Janus hetero-nanofibers as a bi-functional photoreforming catalyst for prominently boosting hydrogen evolution from water-pollutant system

Bi-functional photoreforming catalysts are promising for synergetic hydrogen evolution and pollutant removal through a water-pollutant system. The rational energy band and interface engineering are crucial in promoting their performance but are still challenging due to finely regulating nanoscale interface difficulties. Herein, single to bi-Janus interface engineering is adopted to develop hollow bi-Janus SrTiO3/ZnO/TiO2 hetero-nanofibers with gradient energy band and spatially separated redox surfaces via electrospinning married atomic layer deposition methods. The simulations indicate that these novel structures have a stronger internal electric field (5.72 ×106 V/m) than SrTiO3/ZnO (1.84 ×106 V/m) and ZnO/TiO2 (3.98 ×106 V/m) single-Janus hetero-nanofibers (SJ-HNFs), and more ordered electric field distribution than mixed hetero-nanofibers (MHNFs). Experimentally, they have better charge separation and directional carriers transfer path, as evidenced by photoluminescence, photovoltage, and photoelectrochemical investigations, along with photo-deposition probe experiments. The gradient energy band, directional charge transfer path, and spatially separated redox surfaces promote their photoreforming performance effectively, presenting a high photoreforming hydrogen evolution rate of 104.6 μmol g−1 h−1 in 10,000 ppm propranolol (corresponding degradation of 33.1% after 5 h), about 3.62, 4.27, and 3.11 times of ZnO/TiO2 SJ-HNFs, SrTiO3/ZnO SJ-HNFs and SrTiO3/ZnO/TiO2 MHNFs. This work provides a promising interfacial engineering strategy for designing photoreforming catalyst to simultaneously achieve energy conversion and environmental pollution treatment.

Microstructure and hardness evolution induced by annealing of ion irradiated LiTaO3

The evolution of the microstructure and mechanical properties of low-energy heavy-ion-irradiated LiTaO3 crystals annealed at various temperatures was investigated by transmission electron microscopy (TEM) observations and nanoindentation tests to extend the applications of irradiated LiTaO3 crystals. Before annealing, randomly distributed voids formed in an approximately 200 nm thick region at the end of the ion irradiation range, which was attributed to preferential absorption of interstitials by the amorphous-crystalline interface. After annealing, a new directional diffusion path of defects was identified, resulting in a void string. Furthermore, void string diffusion to the free surface was also found during the annealing temperature increase process, which offers a potential application in designing custom sized-thickness exfoliation at the nanoscale. Meanwhile, two competing processes were identified during the annealing process: epitaxial recrystallization from the amorphous-crystalline interface and grain nucleation process in the amorphous region, which formed phases different from the matrix crystal structure, resulting in an interaction between them. Furthermore, the hardness of irradiated samples was also found to be affected by the annealing process; in particular, a hardness decrease induced by the interstitial Fe ions in the recrystallized region was also confirmed, which can improve the processability of samples for further application.

Our Fire Stories

The directional learning path our Indigenous Knowloegde (IK) reveals, is happening and emerging in a way that is based in our lore and systems. What I refer to here in Australia is over 60, 000 years of continuous cultural knowledge connected around 60,000 years’ worth of campfires. The pattern which we gather and sit around these campfires is in circle. And the circle pattern we have gathered around these times creates a distinct flow of energy and knowledge transfer. The distinct pattern of IK transfer at Deakin’s Indigenous Knowledge System Lab (IKSL) now, can be understood in four ways, IK in Production; Transmission; Application and Regeneration. We see emergence through the patterns and stories that are brought through following the whisps of smoke from the fire – the unseen made known through the form of smoke - dgumge. To pay homage to our beginnings in shares and development of knowledge’s we write together as part of the ‘IK pattern’ of yarning (Yunkaporta, 2019), we use in Labs – us/only, us/twos and us/all ways of communicating. This paper is a way for us/two, Dr. Rhonda Coopes – palawa and Dr. John Davis – Cobble Cobble, as fellow countrywomen and men, camped around these IKSL fires, to give some markers, lay some tracks, make sense of the paths we take through the ever-emerging patterns of IKSL yarns, actions, and project activities.

The Role of Dual Vacancies in TiO2 for Enhanced Photocatalytic Hydrogen Generation and Pollutants Removal

AbstractThe mechanism of TiO2 with Ti vacancy and O vacancy in photocatalytic hydrogen production is unknown. Herein, TiO2 with three types of vacancies was constructed. It was found that DV‐Ti‐3O containing both O vacancies and Ti vacancies had the highest photocatalytic hydrogen production of 12.42 mmol ⋅ g−1 ⋅ h−1 twice that of SV‐Ti, where the O vacancy acted as an emitter providing a directional path for the migration of photogenerated electrons and provided the adsorption sites for water molecules, while the introduction of Ti vacancies took the role as electron traps to collect more electrons for hydrogen proton reduction. DV‐Ti‐3O achieved ultra‐fast migration of electronics from O vacancies to Ti vacancies and created ideas for defective engineering of non‐precious metal catalysts for photocatalytic hydrogen production and organic pollutants removal.

Insight into postural control in unilateral sensorineural hearing loss and vestibular hypofunction.

This pilot study aimed to identify postural strategies in response to sensory perturbations (visual, auditory, somatosensory) in adults with and without sensory loss. We tested people with unilateral peripheral vestibular hypofunction (N = 12, mean age 62 range 23-78), or with Unilateral Sensorineural Hearing Loss (USNHL, N = 9, 48, 22-82), or healthy controls (N = 21, 52, 28-80). Postural sway and head kinematics parameters (Directional Path in the anterior-posterior and medio-lateral directions (sway & head); pitch, yaw and roll (head) were analyzed in response to 2 levels of auditory (none, rhythmic sounds via headphones), visual (static, dynamic) and somatosensory cues (floor, foam) within a simulated, virtual 3-wall display of stars. We found no differences with the rhythmic auditory cues. The effect of foam was magnified in the vestibular group compared with controls for anterior-posterior and medio-lateral postural sway, and all head direction except for medio-lateral. The vestibular group had significantly larger anterior-posterior and medio-lateral postural sway and head movement on the static scene compared with controls. Differences in pitch, yaw and roll emerged between vestibular and controls only with sensory perturbations. The USNHL group did not increase their postural sway and head movement with the increased visual load as much as controls did, particularly when standing on the foam. They did not increase their medio-lateral sway with the foam as much as controls did. These findings suggest that individuals with USNHL employ a compensatory strategy of conscious control of balance, the functional implications of which need to be tested in future research.

A Predicting Model for Near-Horizontal Directional Drilling Path Based on BP Neural Network in Underground Coal Mine

This study establishes a prediction model based on the back propagation (BP) neural network for controlling the underground directional drilling path in a coal mine. The four-layer BP neural network model chooses 11 trajectory parameters (dip angles and azimuths from 12 m after the measurement while drilling (MWD)) and two control parameters as inputs. Two parameters, the dip angle and azimuth at bit, are the outputs. Trained with data from 502 groups, the model was used to forecast 12 test data groups. The results were then compared with the prediction results of artificial experience from 24 technicians. The study shows that the mean absolute error of the dip angle and azimuth at bit are only 0.51° and 0.68°, respectively, as predicted by the prediction model, which uses the logsig activation function and has a double-hidden-layer with a point structure of 9×6. The prediction error also follows a normal distribution. Compared with technicians who have worked for more than five years, the accuracy of prediction results from the BP neural network model is reduced by 33.9% and meets the needs of drilling path control.

A CdS/MnS p–n heterojunction with a directional carrier diffusion path for efficient photocatalytic H2 production

A CdS/MnS p–n heterojunction is prepared. The H2 production rate is 5.92 mmol g−1 h−1 with the apparent quantum efficiency of 5.63% at 420 nm, which is 10.57 times and 49.33 times higher than that of CdS nanorods and MnS, respectively.

Optimum directional well path design considering collapse and fracture pressures

Optimum directional well path design considering collapse and fracture pressures

Optimum directional well path design considering collapse and fracture pressures

Optimum directional well path design considering collapse and fracture pressures

Decision Making and Machine Learning Algorithms’ Selection with Artificial Intelligent Rule-Based Expert System

Everybody is confronted daily with cluster of decisions that must be appropriately taken in the process of making accurate decision; individuals are faced with and most often fall prey to series of common biases, fallacies, and many other decision making odds. In determining which algorithm to apply for analysis (with machine learning algorithms/models) open to critical steps to be taken and also highly depend on many factors ranging from the type of problem at hand, the condition to choose a model and to the expected outcomes. The study looks at how artificial intelligent approach with expert system would be helpful in making timely decision on which type of algorithm(s) is/are capable to be applied and implemented to have desired results. The study also uses VisiRule software to model series of successful channels to arrive at a good decision making means. The use of VisiRule (Artificial Intelligent Based Expert System) was employed to give directional path ways to the selection of appropriate algorithms from supervised and unsupervised machine learning to different classification methods, regression methods, clustering approaches, dimensionality reduction methods, and association rules. The outcome of this study demonstrates the easy way through paths to select relevant and most appropriate model or algorithm that best fit the analysis at hand with detailed explanation of each alternative option. The use of VisiRule software has proven the easy way to achieve decision making problems without any codes requirement for such actions. Decision making challenges could be resolved by just implementing artificial intelligent rule-based expert system which require less time, coding free, and highly achievable accurate outcomes.

Propuesta de interacción entre el verbo y la preposición en la codificación de los eventos de desplazamiento. Estudio contrastivo entre el español y el chino mandarín

Spanish and Mandarin Chinese have been classified as verb-framed language and satellite-framed language respectively (Talmy: 1991, 2000). However, in Spanish, manner verbs are compatible with hacia and hasta, and a small group of them can do so with a. The typological discussion on Mandarin Chinese focuses on the serial verb construction of “manner verb + path word”, in which the second constituent lacking morphological variation can also function independently as path verb. To try to shed light on these discussions, we propose that the core scheme —the directional path— of the motion event is generated through the interaction between the verb and the preposition, in which the manner verb with external movement implies a non- directional path which plays a primary role, while the preposition and the second constituent of the Chinese serial verb construction are only direction indicators that do not contribute any path. The analysis of the combinatory between manner verbs and hacia, hasta, a, as well as their equivalent Chinese expressions, support our hypothesis and they let conclude that: a is locative; Chinese serial verb construction belongs to the satellite-framed language type; the extensive value of hasta does not favor the generation of the directional path, but that of its Chinese equivalent can do so.

PARP: A Parallel Traffic Condition Driven Route Planning Model on Dynamic Road Networks

The problem of route planning on road network is essential to many Location-Based Services (LBSs). Road networks are dynamic in the sense that the weights of the edges in the corresponding graph constantly change over time, representing evolving traffic conditions. Thus, a practical route planning strategy is required to supply the continuous route optimization considering the historic, current, and future traffic condition. However, few existing works comprehensively take into account these various traffic conditions during the route planning. Moreover, the LBSs usually suffer from extensive concurrent route planning requests in rush hours, which imposes a pressing need to handle numerous queries in parallel for reducing the response time of each query. However, this issue is also not involved by most existing solutions. We therefore investigate a parallel traffic condition driven route planning model on a cluster of processors. To embed the future traffic condition into the route planning, we employ a GCN model to periodically predict the travel costs of roads within a specified time period, which facilitates the robustness of the route planning model against the varying traffic condition. To reduce the response time, a Dual-Level Path (DLP) index is proposed to support a parallel route planning algorithm with the filter-and-refine principle. The bottom level of DLP partitions the entire graph into different subgraphs, and the top level is a skeleton graph that consists of all border vertices in all subgraphs. The filter step identifies a global directional path for a given query based on the skeleton graph. In the refine step, the overall route planning for this query is decomposed into multiple sub-optimizations in the subgraphs passed through by the directional path. Since the subgraphs are independently maintained by different processors, the sub-optimizations of extensive queries can be operated in parallel. Finally, extensive evaluations are conducted to confirm the effectiveness and superiority of the proposal.

Research on resilience assessment and disaster prevention strategy of active distribution network

Since Chinese government work report in 2010 put forward the content of strengthening the construction of smart grids, the construction of smart grids has become one of the important contents of the national development strategy. In the in-depth study of smart grids, the issue of security defense systems and disaster prevention frameworks has always been Research hotspots by scholars at home and abroad, but most of my country’s existing security defenses are aimed at large-scale interconnected systems such as transmission grids, and there is a lack of research on disaster prevention of distribution networks. Therefore, in this research context, this article starts from the perspective of multi-source information fusion, takes into account the uncertainty of distribution network information and other factors, constructs a distribution network disaster response resilience index system and a distribution network resilience assessment model, and uses accidents at the same time. The scenario optimization method improves the disaster warning capability of the distribution network, and provides a scientific basis for the distribution network to take active defense measures. Then, a coordinated defense evolution strategy for the distribution network considering the optimization of accident scenarios was established. This strategy takes limited resources as the constraint, takes the minimum load loss as the objective function, and considers the economics of strategy conversion. Power supply equipment output, load transfer, and switching linkage mechanism between the three load is established, forming islands of security, and network transfer, emergency coordination of the three islands of the distribution network evolution strategy of active defense. This strategy looks for a directional evolution path from real-time accident scenarios to defense strategies from both horizontal and vertical perspectives, and realizes the coordinated control of the distribution network’s active defense strategy locally and globally. Finally, this paper takes the ice disaster climate as an example for simulation verification to prove the comprehensiveness of the risk assessment model and the rationality of the security defense method, and prove that the defense strategy can meet the online adaptive evolution requirements of the active defense of the distribution network, while taking into account The local autonomy and global optimal coordinated control of the active defense of the distribution network make up for the shortcomings of the current active defense strategy and are of great significance to further improve the security defense level of the active distribution network.