Path Extension Research Articles

Structural and functional design of CTAB-geopolymer adsorbents for rapid removal of tetracycline: A comparative study

A powder, inorganic membrane and 3D printing cetyltrimethylammonium bromide (CTAB)-geopolymer adsorbents system for adsorbing tetracycline (TC) was developed. And the adsorption properties, adsorption mechanism, adsorption cycle application based on the dynamic pH of adsorption system were systematically investigated by experiment, characterization and density functional theory (DFT) calculation. The introduction of CTAB significantly increased the adsorption response to TC in the high alkaline environment caused by spontaneous alkali release of geopolymer. The adsorption of CTAB-geopolymer for TC was most efficient in the dynamic pH range corresponding to TC- species. The predominant influencing mechanism between CTAB-geopolymer with TC was electrostatic interaction assisted by the hydrogen bonding and n-π interaction. The powder adsorbent with 11 wt% CTAB can capture 92.38 % TC at 2 min and fitted the pseudo-second-order model, and was also suitable for adsorption of trace TC. Although the extension of the diffusion path of the monolithic adsorbents limited the adsorption rate, the 3D printed adsorbent showed an adsorption efficiency of 84.20 % at 302 min. The outstanding adsorption (4 times)-desorption (3 times) cycle properties of 11 %CT-GA (81.15 % at 24 min, 4th adsorption) and cycle cumulative adsorption efficiency of 11 %CT-3DP (59.23 % at 120 min, 4th adsorption) adsorbent were exhibited. Furthermore, a high accuracy performance prediction model with the mean R2 value tended to 1 and the low root mean square error (0.0747) was provided, which can provide theoretical and technical reference for the subsequent industrial application of CTAB-geopolymer adsorbents.

Application of improved grey wolf model in collaborative trajectory optimization of unmanned aerial vehicle swarm

With the development of science and technology and economy, UAV is used more and more widely. However, the existing UAV trajectory planning methods have the limitations of high cost and low intelligence. In view of this, grey Wolf algorithm is being used to achieve collaborative trajectory optimization of UAV groups. However, it is found that the Grey Wolf optimization algorithm (GWO) has the problem of weak cooperation. In this study, based on the traditional GWO pheromone factor is introduced to improve it.. Aiming at the problem of unstable performance of swarm intelligence optimization algorithm under dynamic threat, deep reinforcement learning is used to optimize the model. An unmanned aerial vehicle swarm trajectory planning model was constructed based on the improved grey wolf algorithm. Through experimental analysis, the optimal fitness value of the improved grey wolf algorithm was lower than 0.43 of the grey wolf algorithm. Compared with other algorithms, the fitness value of this algorithm is significantly reduced and the stability is higher. In complex scenarios, the improved grey wolf algorithm had a trajectory length of 70.51 km and a planning time of 5.92 s, which was clearly superior to other algorithms. The path length planned by the research and design model was 58.476 km, which was significantly smaller than the other three models. The planning time was 5.33 s and the number of path extension points was 46. The indicator values of the Unmanned Aerial Vehicle swarm trajectory planning model designed by this research were all smaller than the other three models. By analyzing the results, the model can achieve low-cost trajectory optimization, providing more reasonable technical support for unmanned aerial vehicle mission execution.

Obstacle Avoidance Path Planning of a 4-DOF Weapon Arm Based on Improved RRT (RRT-H) Algorithm

To improve soldiers’ combat capability, weapon arms have a good development prospect. However, due to special work scenarios and tasks, new requirements are exerted on. Based on the fast-expanding random tree algorithm (RRT), path algorithm optimization (RRT-H) is proposed for the path planning of weapon arms. Overall path optimization is achieved by reducing the local path length with a closer path point planning to the obstacle. In a complex environment, the RRT-H algorithm can avoid local traps by guiding the new path extension direction and exploring multiple different paths in the map. The superiority of this algorithm is verified with 2D plane obstacle avoidance and pathfinding simulation experiments. Compared to RRT∗, RRT∗ smart, and information RRT∗, the RRT-H can obtain high-quality calculation results in a shorter time. After setting degrees of freedom (DOF) as that of variables, the algorithm is applied to the 4-DOF weapon arm, which confirms an effective reduction to the 4-DOF weapon arm’s motion costs.

Crack modeling via minimum-weight surfaces in 3d Voronoi diagrams

As the number one building material, concrete is of fundamental importance in civil engineering. Understanding its failure mechanisms is essential for designing sustainable buildings and infrastructure. Micro-computed tomography (μCT) is a well-established tool for virtually assessing crack initiation and propagation in concrete. The reconstructed 3d images can be examined via techniques from the fields of classical image processing and machine learning. Ground truths are a prerequisite for an objective evaluation of crack segmentation methods. Furthermore, they are necessary for training machine learning models. However, manual annotation of large 3d concrete images is not feasible. To tackle the problem of data scarcity, the image pairs of cracked concrete and corresponding ground truth can be synthesized. In this work we propose a novel approach to stochastically model crack structures via Voronoi diagrams. The method is based on minimum-weight surfaces, an extension of shortest paths to 3d. Within a dedicated image processing pipeline, the surfaces are then discretized and embedded into real μCT images of concrete. The method is flexible and fast, such that a variety of different crack structures can be generated in a short amount of time.

Miniaturized broadband upward-folded dipole for base station applications

This paper proposes a compact and broadband dual-polarized base station antenna based on current path extension for 2G/3G/LTE base stations. The antenna is miniaturized by bending the end of the radiator to extend the current path. By bending the antenna, a new resonant mode is introduced to increase the bandwidth. In addition, a parasitic patch is placed above the antenna to improve impedance matching, and the introduction of artificial magnetic conductors reduces the profile of the antenna and significantly improves the radiation characteristics. The antenna radiator has a compact size of only 0.207×0.207λL2 at the lowest frequency with a total profile of 0.136 λL. The measured results indicate that the proposed antenna has a substantial bandwidth of 45.5% and more than 34 dB of high port isolation with a gain of 7.9 ± 0.5 dBi.

Simultaneous waveform inversion of seismic-while-drilling data for P-wave velocity, density, and source parameters

Full-waveform inversion (FWI), as an optimization-based approach to estimating subsurface models, is limited by incomplete acquisition and illumination of the subsurface. The incorporation of additional data from new and independent raypaths should be expected to result in significant increase in the accuracy of FWI models. In principle, seismic-while-drilling (SWD) technology can supply these additional raypaths; however, it introduces a new suite of unknowns, namely precise source locations (i.e., drilling path), source signature, and radiation characteristics. A new FWI algorithm is formulated in which the source radiation patterns and positions join the velocity and density values of the grid cells as unknowns to be determined. Several numerical inversion experiments are then conducted with different source settings using a synthetic model. The SWD sources are supplemented by explosive sources and multicomponent receivers at the surface, simulating a conventional surface acquisition geometry. The subsurface model and SWD source properties are recovered and analyzed. The analysis is suggestive that SWD involvement can enhance the accuracy of FWI models, with varying degrees of enhancement depending on factors such as trajectory inclination, source density, and drill path extension. The impact of SWD-FWI over standard FWI is reduced when low-frequency data are missing, but improvements over the models constructed with no subsurface sources remain. This formulation permits general source information, such as position and moment tensor components, to be independently obtained. This inversion scheme may lead to a range of potential applications for which medium properties and source information are required.

Enhanced electromagnetic wave absorption performance of pompon-shaped Nb2O5/CNTs composite microspheres prepared via spraying technique

The pompon-shaped Nb2O5/carbon nanotubes composite microspheres (NCM) were successfully synthesized via a spraying technique as electromagnetic wave (EMW) absorption materials. The comprehensive investigation process involved the microstructure, phase composition, EMW absorption property, and corresponding mechanisms of the as-fabricated NCM. The combination of CNTs and Nb2O5 not only provides multiple attenuation mechanisms but also promotes impedance matching. Furthermore, substantial newly-formed heterogeneous interfaces in NCM enhance the relaxation polarization process. Additionally, the distinctive pompon-shaped morphology of NCM enhances multiple reflection and scattering of the EMW, thereby facilitating the extension of transmission paths for charge. NCM-3 demonstrated significantly superior EMW absorption performance, with an effective absorption bandwidth (EAB) of 5.28 GHz and a minimum reflection loss (RLmin) of −30.52 dB at a mere thickness of 1.97 mm. This work could provide critical guidance for the exploration of new binary materials for EMW absorption.

Local station correlation: large N-arrays and DAS

The use of cross-correlation between seismic stations has had widespread applications particularly in the exploitation of ambient seismic noise. We here show how the effects of a non-ideal noise distribution can be understood by looking directly at correlation properties and show how the behaviour can be readily visualised for both seismometer and DAS configurations, taking into account directivity effects. For sources lying in a relatively narrow cone around the extension of the inter-station path, the dispersion properties of the correlation relate directly to the zone between the stations. We illustrate the successful use of correlation analysis for both a large-N array perpendicular to a major highway and DAS cable along a busy road. For correlation work, the co-array consisting of the ensemble of inter-station vectors provides an effective means of assessing the behaviour of array layouts, supplementing the standard plane-wave array response. When combined with knowledge of the suitable correlation zones for noise sources, the co-array concept provides a useful way to design array configurations for both seismometer arrays and DAS.

Hyporheic exchange and nitrogen cycle processes under the dual effects of flooding and heterogeneous streambed

In this study, we investigated the effects of media heterogeneity and flood processes on hyporheic exchange and nitrogen cycle processes in hyporheic zone adjacent to a natural in-stream gravel bar. We conducted field experiments and set a reactive transport model of surface-groundwater exchange based on the monitoring results. The flood process is obtained based on field monitoring, and the heterogeneous medium field is constructed using the SAR3DC method based on in-site experiment results. The results showed that both the heterogeneity of the medium and the flood process can enhance the spatial variability of velocity distribution, resulting in an increase of exchange flux, a decrease in lag time, and an extension of the migration path. For heterogeneous media, it is easier to form specific channels for high velocity flow, and the flow velocity within them is more sensitive to changes in media and hydrodynamic conditions, the direction of hyporheic exchange can be reversed in some specific channels. For the nitrogen cycle processes, the heterogeneous medium condition determines the source-sink functions and the direction of nitrate nitrogen reduction in hyporheic zone by providing a wider reaction space for reactants, reducing the lag time to 1/40 and increasing the migration path by 4 times. The flood process can increase the infiltration amounts of reactants by 5 times and reduce the lag time (time of particle entry into the hyporheic zone to migrate out) to 1/6. In general, under the effects of media heterogeneity and flood processes, the reaction rates and nitrate nitrogen reduction rates during the nitrogen cycle processes are decreasing and the hyporheic zone will face greater pollution risks.

Multitarget Real-Time Path Planning Using Double Adaptive A Algorithm

Multi-target real-time path planning (MTRT) is an extension of path planning that aims to traverse multiple targets in an unknown environment at the lowest cost. The MTRT is gov-erned by the “multi-target” demand leading to a rather extensive search space and the “real-time” requirement that imposes fast planning. However, the traditional path planning algorithm A* is notoriously inefficient in large spaces. Therefore, spurred by the low efficiency of A* for MTRT, this paper proposes the double adaptive A algorithm (DAA), which implements an adaptive multi-target heuristic function and an adaptive node expansion method to accelerate planning. The suggested method is evaluated utilizing two approaches to establishing the search space, i.e., decompose MTRT into traditional path planning problems and involve one target at a time, and consider all unsearched targets while planning. Simulations in discrete grid maps demonstrate that DAA provides at least equivalent searching paths to A* and other algorithms, but at much less running time.

Understanding Node Localizability in Barycentric Linear Localization

The barycentric linear localization (BLL) methods provide a lightweight, distributed way to calculate locations for resource-limited IoT devices. A crucial requirement for BLL is that the nodes participating in the iterative location propagation are localizable. Otherwise, the unlocalizable nodes will continuously pose error information in the location propagation process, making even the theoretically localizable nodes converge to the wrong locations. However, the research on node localizability in BLL is much lacked, greatly limiting the application scope of BLL. In specific, BLL node localizability is detected on a generated graph <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathcal{G^A}$</tex-math> </inline-formula> . For any node, its neighbors appear in <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathcal{G^A}$</tex-math> </inline-formula> only when the neighbors can form triangle(s), so that <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathcal{G^A}$</tex-math> </inline-formula> is much sparser than the original <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathcal G$</tex-math> </inline-formula> . Thus, the node localizability condition in BLL is harder to be satisfied than that in traditional localization methods. Moreover, the distributed algorithm to detect BLL localizable nodes is still open. This paper thoroughly investigates the node localizability conditions and distributed localizable node detection algorithms in BLL. At first, an efficient and fully distributed Negative Edge Inference (NEI) algorithm is proposed for each node to infer implicit edges in its neighborhood. NEI strengthens the distance graph by revealing more distance constraints so that enables more neighboring triangles. Then a new sufficient condition, i.e., the recursive three disjoint path condition (Recursive-3DP) on the strengthened distance graph is proposed to identify BLL localizable nodes much more accurately. Secondly, a distributed Path Extension and Pruning (PEP) algorithm is proposed for distributed localizable node detection. PEP is proved to detect all the theoretically Recursive-3DP nodes in the strengthened distance graph. A Fast-PEP algorithm is further proposed, which misses very limited Recursive-3DP nodes while bringing significant improvement in efficiency. PEP and Fast-PEP guarantee to identify BLL localizable nodes in <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2H$</tex-math> </inline-formula> rounds, where <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H$</tex-math> </inline-formula> is the maximum hop number of the node disjoint paths. Finally, by using NEI and PEP (Fast-PEP), a localizability-aware BLL (LABEL) method is proposed, which correctly identifies localizable nodes and guarantees their correct location convergence. Extensive analysis and experiments show the advantages in localizability and location accuracy of the proposed schemes over the state-of-the-art methods.

Dual-Band Shared-Aperture Base Station Antenna Array Based on 3-D Chokes

A novel structure for suppressing cross-band scattering interference in dual-band dual-polarized base station antenna arrays has been proposed. To alleviate the radiation pattern distortion of the high-band (HB) element caused by the low-band (LB) element, the LB radiator was loaded with 3-D chokes to suppress its scattering in the HB. In addition, when the LB element is excited, the resonance interference of the HB element to the LB element can be solved by the method of path extension. The array structure is composed of an LB element operating at 0.69–0.96 GHz (| <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">S</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">11</sub> | < −14 dB) and two columns of HB elements operating at 1.7–2.7 GHz. The simulation and experimental results of the array show that the loading of the 3-D chokes effectively suppresses the scattering interference in the LB element and restores the radiation patterns of the HB subarray, proving the effectiveness of this novel structure.

Shortest Path Finding in Quantum Networks With Quasi-Linear Complexity

A fully-quantum network implies the creation of quantum entanglement between a given source node and some other destination node, with a number of quantum repeaters in between. This paper tackles the problem of quantum entanglement distribution by solving the routing problem over an infrastructure based on quantum repeaters and with a finite number of pairs of entangled qubits available in each link. The network model considers that link purification is available such that a nested purification protocol can be applied at each link to generate entangled qubits with higher fidelity than the original ones. A low-complexity multi-objective routing algorithm to find the shortest path between any two given nodes is proposed and assessed for random networks, using a fairly general path extension mechanism that can fit a large family of particular technological requirements. Different types of quantum protocols require different levels of fidelity for the entangled qubit pairs. For that reason, the proposed algorithm identifies the shortest path between two nodes that assures an end-to-end fidelity above a specified threshold. The minimum requirements for the end-to-end entanglement fidelity depend on the whole extension of the paths, and cannot be looked at as a local property of each link. Moreover, one needs to keep track not only of the shortest path, but also of longer paths holding more entangled qubits than the shorter paths in order to satisfy the fidelity criterion. Thus, standard single parameter shortest-path algorithms do not necessarily converge to the optimal solution. The problem of finding the best path in a network subject to multiple criteria (known as multi-objective routing) is, in general, an NP-hard problem due to the rapid growth of the number of stored paths. This work proposes a metric that identifies and discards paths that are objectively worse than others. By doing so, the time complexity of the proposed algorithm scales near-to-linearly with respect to the number of nodes in the network, showing that the shortest-path problem in quantum networks can be solved with a complexity very close to the one of the classical counterparts. That is analytically proved for the case where all the links of a path have the same fidelity (homogeneous model). The algorithm is also adapted to a particular type of path extension, where different links along a path can be purified to different degrees, asserting its flexibility and near-to-linearity even when heterogeneous fidelities along the sections of a path are considered.

A Sobolev rough path extension theorem via regularity structures

We show that every ℝd-valued Sobolev path with regularity a and integrability p can be lifted to a Sobolev rough path provided 1/2 &gt; α &gt; 1/p&gt; ⋁ 1/3. The novelty of our approach is its use of ideas underlying Hairer’s reconstruction theorem generalized to a framework allowing for Sobolev models and Sobolev modelled distributions. Moreover, we show that the corresponding lifting map is locally Lipschitz continuous with respect to the inhomogeneous Sobolev metric.

Impact of Worker’s Remittances, Financial Development, and Economic Growth on Living Standard of Pakistan

Plethora of studies have drawn conflicting conclusions about the relationships between workers’ remittances, financial development and growth, and living standards in different setups but partially. For this purpose, the capital conduit effect and threshold conduit effect are frequently utilized to trace out the transmission channels for causal linkages. This study extends the capital conduit and threshold channels to look at how worker remittances affect living standards. The data is taken from 1980 to 2020. The augmented Dickey-Fuller test was used to look at the stationarity of the data series. For both short-run and long-run consequences, ARDL-bound testing is employed. The study's findings suggest that, when taking into account the effects of financial development and GDP growth, there is a direct and indirect, short-term and long-term relationship between worker remittances and living standards. Additionally, it is confirmed that the path's extension has made a considerable contribution. These results may help policymakers comprehend the part that worker remittances play in the creation of financially sound plans.

The deployment of snowmaking in the French ski tourism industry: a path development approach

ABSTRACT Many mountainous regions in Europe, including their tourism sectors, show a high degree of economic specialization. The ski tourism industry forms part of the long-standing economic success of the French Alps. Over the past 20 years, snowmaking has become a key feature of ski tourism, but future climate change will decrease its effectiveness as an adaptation solution to natural snow cover reduction. However, the ski tourism industry does not seem to be intent on stopping its investment in snowmaking, which raises the question of its dependence on this technology. In this study, we employ the path development framework to examine how snowmaking development has oriented decision-making to ensure the future of the French ski tourism industry. We analysed 38 in-depth semi-directive interviews and key financial figures from the French alpine ski tourism industry. Our results show that technical progress and specific investments in snowmaking have deeply transformed the management of ski resorts. Our finding is that snowmaking spurred ski lift operators to pursue specialization in the ski tourism industry. However, because of its ambivalent effects on the ski tourism industry, we view snowmaking development both as path extension and as path contraction.

Frequency Division Multiplexing and Normalized Harmonic Method for WMS Detection System in Multi-gas Detection

A frequency division multiplexing (FDM) WMS system for multi-gas detection is reported in this paper. The distributed feedback lasers with different wavelengths adopt different modulation frequencies to achieve multi-components gas detection by the FDM technology. Combining optical path extension, normalized harmonic detection and wavelength modulation spectroscopy technology, the highly self-made system realized high sensitivity, high precision and short response time. The performance of this system was evaluated through the mixed gas of methane and hydrogen chloride. Experimental results show great linear response between gas concentration and normalized second harmonic (2f/1f) signal, the minimum detection limit (MDL) of the system is calculated to be 30.16 ppb for CH4 and 31.6 ppb for HCl with the integration time of 15 s. The MDL could be further enhanced to 11 ppb for CH4 and 13.1 ppb for HCl with an extended integration time. The maximum relative error is 2.16% and 3.19% for CH4 and HCl respectively.

Three-Dimensional Dubins-Path-Guided Continuous Curvature Path Smoothing

This paper presents an efficient three-dimensional (3D) Dubins path design and a new continuous curvature path-smoothing algorithm. The proposed 3D Dubins path is a simple extension of the 2D path and serves as a reference path generator to guide the proposed smoothing algorithm. In the smoothing algorithm, the reference path is approximated by several cubic Bezier curves to generate a parametric path that simultaneously satisfies curvature continuity and maximum curvature requirements. The algorithm also provides a criterion to select a required number of Bezier curves to strictly meet the maximum curvature constraint. Therefore, our algorithm can be used for 3D path-following applications in many areas such as aerospace and robotics. The numerical simulation results show that the proposed algorithm produces a continuous curvature path that passes through all waypoints with a slight increase in path length compared with the original 3D Dubins reference path.

Influence of tooth asymmetry and mating gear material on the tooth deflection characteristics of polymer gears

Transmission error (TE) in polymer gears is significantly affected by the elastic deflection of meshing teeth. The present work describes the deflection characteristics of the asymmetric Nylon 66 spur gears under similar and dissimilar engagements. The load sharing and deflection behavior were estimated numerically using a linear viscoelastic material model. Experimental determination of mesh deflection was carried out through static load tests. The peak mesh deflection in a cycle for the 20°/34° configuration was found to be 8% and 12% smaller as compared to 34°/20° and 20°/20° configurations, respectively. The peak tooth deflection was found to be highest for the 34°/20° configuration and lowest for the 20°/34° configuration, with the deviation between their peak deflections being 15% in metal-polymer pairs and 17% in polymer-polymer pairs. In the 34°/20° configuration, the higher drive side pressure angle increased the single tooth contact period, causing greater peak-to-valley amplitude in a cycle. The negligible tooth compliance of steel gear caused unsymmetrical load sharing in the double tooth contact zones of metal-polymer engagements. The greater compliance of driver gear in polymer-polymer engagements increased the mesh deflections of 20°/20° and 20°/34° configurations by 45% and that of 34°/20° configuration by 37%. Also, gear pairs with similar material stiffness balanced the load sharing in the addendum and dedendum double tooth contact zones. The large tooth deflection extended the contact duration of all configurations for both the similar as well as for the dissimilar engagements, respectively. This was signified by the contact path extension at the peripheries of the mesh cycle.

Improved Belief Propagation List Decoding for Polar Codes

Polar codes have become the channel coding scheme for control channel of enhanced mobile broadband in the 5G communication systems. Belief propagation (BP) decoding of polar codes has advantages of low decoding latency and high parallelism but achieves worse bit error ratio (BER) performance compared with the successive cancellation list (SCL) decoding scheme. In this paper, an improved BP list (IBPL) decoding algorithm is proposed with comparable BER performance to SCL algoritm. Firstly, the optimal permuted factor graph is analyzed for polar codes, which improves the performance of the BP decoder without path extension. Furthermore, based on the optimal graph, the bit metric and decoding path metric are proposed to extend and prune the decoding path. The proposed IBPL decoder is focused on not only the permutation of polar codes but also the reliabilities of decoded codewords during each iteration of BP decoding, which has a more accurate decoding path list. The simulation results show that the proposed IBPL decoder improves the BER performance compared with the original BP decoder significantly, and can approach the performance of the SCL decoder at low signal to noise ratio regions.