Local Vector Research Articles

Plasmon-Mediated Chiroptical Second Harmonic Generation from Seemingly Achiral Gold Nanorods.

Throughout nature, simple rules explain complex phenomena, such as the selective interaction of chiral objects with circularly polarized light. Here, we demonstrate chiroptical signals from gold nanorods, which are seemingly achiral structures. Shape anisotropy due to atomic-level faceting and rounding at the tips of nanorods, which are free of chiral surface ligands, induces linear-to-circular polarization modulation during second harmonic generation. The intrinsic nanorod chiroptical response is increased by plasmon-resonant excitation, which preferentially amplifies circularly polarized harmonic signals. This structure-plasmon interplay is uniquely resolved by polarization-resolved second harmonic generation measurements. The material's second-order polarizability is the product of the structure-dependent lattice-normal susceptibility and local surface plasmon field vectors. Synthetically scalable plasmon-supporting nanorods that amplify small circular dichroism signals provide a simple, assembly-free platform for chiroptical transduction.

Malaria Transmission, Vector Diversity, and Insecticide Resistance at a Peri-Urban Site in the Forest Zone of Ghana

IntroductionRecent surge ofAnophelesresistance to major classes of World Health Organization (WHO)-approved insecticides globally necessitates the need for information about local malaria vector populations. It is believed that insecticide efficacy loss may lead to operational failure of control interventions and an increase in malaria infection transmission. We investigated the susceptibility levels of malaria vectors to all classes of WHO-approved vector control insecticides and described the dynamics of malaria transmission in a peri-urban setting.MethodsFit 3–5-day-old adults that emerged fromAnopheleslarvae collected from several different sites in the study area were subjected to the WHO bioassay for detecting insecticide resistance. The knockdown resistance gene (kdr) mutations within the vector populations were detected using PCR. Entomological inoculation rates were determined using the human landing catch technique andPlasmodium falciparumcircumsporozoite ELISA.ResultsThe malaria vectors from the study area were resistant to all classes of insecticides tested. Out of the 284Anophelescomplex specimen assayed for the resistance study, 265 (93.30%) were identified asAnopheles gambiae s.s.The kdr gene was detected in 90% of theAnopheles gambiae s.s.assayed. In an area whereAnopheles coluzziiresistance to insecticides had never been reported, the kdr gene was detected in 78% of theAnopheles coluzziisampled. The entomological inoculation rate (EIR) for the dry season was 1.44 ib/m/n, whereas the EIR for the rainy season was 2.69 ib/m/n.ConclusionsThis study provides information on the high parasite inoculation rate and insecticide resistance of malaria vectors in a peri-urban community, which is critical in the development of an insecticide resistance management program for the community.

Rock mass deterioration model of bank slope based on high-precision 3D multiperiod point clouds in the Three Gorges Reservoir, China

Karst bank slopes are widely developed in the Three Gorges Reservoir area. Potential bank slope instability caused by the deterioration of rock masses has aroused considerable attention. This paper describes an attempt to use high-precision 3D laser scanning point cloud technology to reveal the deterioration law of a rock mass from a meso-/macroscale perspective and to preliminarily establish the relationship between the characteristics of the rock mass deterioration and 3D point cloud response. The main conclusions are as follows. The point cloud response characteristics of rock mass deterioration can be divided into three types: crack manifestation–extension, collapse-block falling, and translation-rotation. The crack manifestation–extension type can be further subdivided into three subcategories: crack extension, crack widening and crack deepening. These three subclasses of point cloud response characteristics of crack manifestation–extension all exhibit strip-like erosion-induced extensions, but the deformation forms and locations are slightly different. The point cloud response of collapse-block falling shows irregular sheet erosion. The point cloud response characteristics of translational rotation are similar, but associated erosion deformation often presents regular isosurface deformation characteristics. The C2C and M3C2 algorithms are used to calculate the deterioration and deformation, and the difference between recording points at the same location is small, except where the local normal vector N → changes greatly or the point cloud is sparse, where there are large differences. Based on 3D point clouds, the deterioration rate formula D e = n / N for a rock mass is proposed for the first time, where n is the number of degraded and deformed point clouds, and N is the total number of point clouds in the test area. According to the deterioration rates D e corresponding to different deformation thresholds, the deterioration degree and state of a rock mass can be described and judged.

Early warning systems (EWSs) for chikungunya, dengue, malaria, yellow fever, and Zika outbreaks: What is the evidence? A scoping review.

BackgroundEarly warning systems (EWSs) are of increasing importance in the context of outbreak-prone diseases such as chikungunya, dengue, malaria, yellow fever, and Zika. A scoping review has been undertaken for all 5 diseases to summarize existing evidence of EWS tools in terms of their structural and statistical designs, feasibility of integration and implementation into national surveillance programs, and the users’ perspective of their applications.MethodsData were extracted from Cochrane Database of Systematic Reviews (CDSR), Google Scholar, Latin American and Caribbean Health Sciences Literature (LILACS), PubMed, Web of Science, and WHO Library Database (WHOLIS) databases until August 2019. Included were studies reporting on (a) experiences with existing EWS, including implemented tools; and (b) the development or implementation of EWS in a particular setting. No restrictions were applied regarding year of publication, language or geographical area.FindingsThrough the first screening, 11,710 documents for dengue, 2,757 for Zika, 2,706 for chikungunya, 24,611 for malaria, and 4,963 for yellow fever were identified. After applying the selection criteria, a total of 37 studies were included in this review. Key findings were the following: (1) a large number of studies showed the quality performance of their prediction models but except for dengue outbreaks, only few presented statistical prediction validity of EWS; (2) while entomological, epidemiological, and social media alarm indicators are potentially useful for outbreak warning, almost all studies focus primarily or exclusively on meteorological indicators, which tends to limit the prediction capacity; (3) no assessment of the integration of the EWS into a routine surveillance system could be found, and only few studies addressed the users’ perspective of the tool; (4) almost all EWS tools require highly skilled users with advanced statistics; and (5) spatial prediction remains a limitation with no tool currently able to map high transmission areas at small spatial level.ConclusionsIn view of the escalating infectious diseases as global threats, gaps and challenges are significantly present within the EWS applications. While some advanced EWS showed high prediction abilities, the scarcity of tool assessments in terms of integration into existing national surveillance systems as well as of the feasibility of transforming model outputs into local vector control or action plans tends to limit in most cases the support of countries in controlling disease outbreaks.

A Satellite Incipient Fault Detection Method Based on Decomposed Kullback-Leibler Divergence.

Detection of faults at the incipient stage is critical to improving the availability and continuity of satellite services. The application of a local optimum projection vector and the Kullback–Leibler (KL) divergence can improve the detection rate of incipient faults. However, this suffers from the problem of high time complexity. We propose decomposing the KL divergence in the original optimization model and applying the property of the generalized Rayleigh quotient to reduce time complexity. Additionally, we establish two distribution models for subfunctions and to detect the slight anomalous behavior of the mean and covariance. The effectiveness of the proposed method was verified through a numerical simulation case and a real satellite fault case. The results demonstrate the advantages of low computational complexity and high sensitivity to incipient faults.

Decentralization of Phasor-Aided State Estimation Using Local State Vector Extension

Distributed state estimation (DSE) and bad data (BD) processing have become increasingly important for the analysis and operation of large-scale power networks. This paper develops a new strategy for decentralized phasor-aided state estimation (DPHASE) to improve the performance of BD processing and, hence, the accuracy of DSE results. Given the recent availability of PMUs, the DPHASE strategy is developed using a parallel multi-stage hybrid approach. The practical challenges in the approach are identified and attributed to the difference between the sets of buses for SCADA- and PMU-based state estimates in sub-areas. Phasor-aided normalized residuals are locally unobtainable and the fusion of local state estimates is unattainable. These challenges are effectively resolved by extending local state vectors. Comparative case studies are performed using the proposed and conventional DSE strategies. The study results confirm that the proposed DPHASE strategy improves the accuracy and robustness of the DSE results under various test network and data measurement conditions.

Theory and application of the vector pair correlation function for real-space crystallographic analysis of order/disorder correlations from STEM images

Deviations of local structure and chemistry from the average crystalline unit cell are increasingly recognized to have a significant influence on the properties of many technologically important materials. Here, we present the vector pair correlation function (vPCF) as a new real-space crystallographic analysis method, which can be applied to atomic-resolution scanning transmission electron microscopy (STEM) images to quantify and analyze structural order/disorder correlations. Our STEM-based vPCFs have several advantages over radial PCFs and/or 3D pair distribution functions from x-ray total scattering: vPCFs explicitly retain crystallographic orientation information, are spatially resolved, can be applied directly on a sublattice basis, and are suitable for any material that can be imaged with STEM. To show the utility of our approach, we measure partial vPCFs in Ba5SmSn3Nb7O30 (BSSN), a tetragonal tungsten bronze (TTB) structured complex oxide. Many TTBs are known to be classical or relaxor ferroelectrics, and these properties have been correlated with the presence of superlattice ordering. BSSN, specifically, exhibits relaxor behavior and an incommensurate structural modulation. From the vPCF data, we observe that, of the cation sites, only the Ba (A2) sublattice is structurally modulated. We then infer the local modulation vector and reveal a marked anisotropy in its correlation length. Finally, short-range correlated polar displacements on the B2 cation sites are observed. This work introduces the vPCF as a powerful real-space crystallography technique, which enables direct, robust quantification of short-to-long range order on a sublattice-specific basis and is applicable to a wide range of complex material types.

Malaria vector dynamics and utilization of insecticide-treated nets in low-transmission setting in Southwest Ethiopia: implications for residual transmission

BackgroundUnderstanding the behaviour of local malaria vectors is essential as effectiveness of the commonly used vector-targeted malaria control tools heavily relies on behaviour of the major malaria vectors. This study was conducted to determine species composition, biting behaviour, host preference and infectivity of anopheline mosquitoes, and assess utilization of insecticide-treated nets (ITNs) in a low transmission setting in Southwest Ethiopia.MethodsAdult anopheline mosquitoes were collected using human landing catches (HLCs), Centers for Disease Control and Prevention (CDC) light traps (LTs) and Pyrethrum Spray Catches (PSCs) from June 2016 to May 2018 in Kishe, Jimma Zone, Southwest Ethiopia. The anopheline mosquitoes were morphologically identified. Moreover, sub-sample of An. gambiae s.l. was identified to species using polymerase chain reaction (PCR). Circum-sporozoite proteins (CSPs) and blood meal sources of the anopheline mosquitoes were tested using enzyme-linked immunosorbent assay (ELISA). In addition, a cross-sectional survey was conducted to assess ITN utilization by the inhabitants.ResultsA total of 3659 anopheline mosquitoes comprising An. coustani complex (84.4%), An. gambiae s.l. (11.3%), and An. pharoensis and An. squamosus comprising less than 5% were collected. The anopheline mosquitoes showed marked outdoor (67%) and early evening (63%) biting behaviour. An. coustani complex and An. gambiae s.l. were predominantly zoophilic and anthropophilic, respectively. None of the sampled anopheline were CSP-positive. Most of the households (97.8%) owned at least one ITN, with modest usage by the inhabitants (73.4%). ITN usage was significantly higher among under-five children (AOR = 7.9, 95% CI: 4.41–14.03), household heads and spouses (AOR = 4.8, 95% CI: 3.0–7.59), those with sufficient access to ITNs (AOR = 1.8, 95% CI: 1.39–2.35), and who were not utilizing alternative mosquito repellents (AOR = 2.2, 95% CI: 1.58–2.99).ConclusionThe anopheline mosquito species exhibited predominantly outdoor and early evening biting activity. Household ITN coverage was high with slight gap in usage. Vector control interventions should target outdoor and early biting vectors to further suppress the local mosquito population. Moreover, sensitization of the community on consistent use of ITNs is required.

Visual perceptual learning of a primitive feature in human V1/V2 as a result of unconscious processing, revealed by decoded functional MRI neurofeedback (DecNef).

Although numerous studies have shown that visual perceptual learning (VPL) occurs as a result of exposure to a visual feature in a task-irrelevant manner, the underlying neural mechanism is poorly understood. In a previous psychophysical study (Watanabe et al., 2002), subjects were repeatedly exposed to a task-irrelevant Sekuler motion display that induced the perception of not only the local motions, but also a global motionmoving in the direction of the spatiotemporal average of the local motion vectors. As a result of this exposure, subjects enhanced their sensitivity only to the local moving directions, suggesting that early visual areas (V1/V2) that process local motions are involved in task-irrelevant VPL. However, this hypothesis has never been tested directly using neuronal recordings. Here, we employed a decoded neurofeedback technique (DecNef) using functional magnetic resonance imaging in human subjects to examine the involvement of early visual areas (V1/V2) in task-irrelevant VPL of local motion within a Sekuler motion display. During the DecNef training, subjects were trained to induce the activity patterns in V1/V2 that were similar to those evoked by the actual presentation of the Sekuler motion display. The DecNef training was conducted with neither the actual presentation of the display nor the subjects’ awareness of the purpose of the experiment. After the experiment, subjects reported that they neither perceived nor imagined the trained motion during the DecNef training. As a result of DecNef training, subjects increased their sensitivity to the local motion directions, but not specifically to the global motion direction. Neuronal changes related to DecNef training were confined to V1/V2. These results suggest that V1/V2 are involved in exposure-based task-irrelevant VPL of local motion.

Susceptibility of Anopheles sinensis to insecticides in Puyang City, Henan Province

To investigate the susceptibility of Anopheles sinensis to malathion, deltamethrin and lambda-cyhalothrin in Puyang City, Henan Province, so as to provide the scientific basis for local malaria vector control. An. sinensis was captured from Puyang County, Puyang City of Henan Province in September 2018 and July 2020, and the susceptibility of field captured An. sinensis to malathion, deltamethrin and lambda-cyhalothrin was tested using the filter-paper bioassay recommended by WHO. The insecticide resistance level was assessed based on the WHO criteria. In 2018 and 2010, the half knock-down times (KT50) of malathion were 91.08 min and 40.95 min for An. sinensis, with knock-down rates of 37.50% and 60.87% 60 min post-exposure to malathion and 24-hour mortality rates of 90.91% and 100%, respectively, and the insecticide resistance levels were moderately resistant (M) and susceptible (S). The KT50 of deltamethrin were 415.56 min and 341.19 min for An. sinensis in 2018 and 2020, with knock-down rates of 22.92% and 16.98% 60 min post-exposure to malathion and 24-hour mortality rates of 22.92% and 16.98%, and the insecticide resistance levels were all resistant (R). The KT50 of lambda-cyhalothrin were 164.22 min and 236.22 min for An. sinensis in 2018 and 2020, with knock-down rates of 30.39% and 38.30% 60 min postexposure to malathion and 24 h mortality rates of 19.60% and 21.28%, respectively, and the insecticide resistance levels were all R. An. sinensis is relatively susceptible to malathion but has developed high-level resistance to deltamethrin and lambda-cyhalothrin in Puyang City, Henan Province..

Evaluating 9 m of near-surface transpressional displacement during the Mw 7.8 2016 Kaikōura earthquake: re-excavation of a pre-earthquake paleoseismic trench, Kekerengu Fault, New Zealand

ABSTRACT During the Kaikōura earthquake, a paleoseismic trench was dextrally displaced ∼9 m and shortened by 1.3 ± 0.4 m – the largest globally recorded displacement of a trench. Analysis showed that two processes accommodated subequal amounts of slip at the surface: (1) discrete dextral-slip on two steeply-dipping faults bounding a <3.5 m wide central deformation zone; and (2) coseismic clockwise rotation of turf rafts and pervasive sediment deformation in that zone. The second (successive) process resulted in upward (<1 m) and outward (<2 m) bulging along low-angle thrusts, creating horizontal fault-perpendicular shortening that exceeds the heave (∼1.3 m). This discrepancy results from coseismic rotation of rafts, that shorten upon approaching perpendicularity with the fault – creating extra apparent shortening (in fault-orthogonal view). Comparison of pre- and post-earthquake trench logs indicates that strike-slip ruptures at the same site can be expressed differently over time; fault strands carrying major displacement in 2016 were not the locus of deformation in the previous earthquake(s), suggesting temporal unpredictability is important in defining fault zones. The last several paleoearthquakes at the trench produced cm-dm scale normal-sense dip separations across faults; however, the 2016 earthquake created compressive structures including up-bulging and low-angle reverse faulting, as well as fissuring. This contrast in deformation style likely resulted from an >8° clockwise rotation of the local slip vector in 2016 (becoming transpressive), highlighting that small changes in slip kinematics may affect rupture zone structures.

Applications of Particle Tracking Velocimetry to severe nuclear accident experimentation

Experimental research into severe nuclear accidents may entail the discharge of a very high-temperature lava-like molten fuel mixture, corium, either into a pool of less-dense, more-volatile coolant or onto a solid substrate where the corium will spread and cool. In both instances, remote, high-speed video imaging is usually required to interpret these transient interactions and PTV represents a powerful tool for the characterisation of the dynamic properties of discrete melt fragments or distinctive features in the surface of the melt during spreading. Nuclear fuel-coolant interactions present particular challenges for PTV analysis as a molten jet and its fragments can exhibit high rates of inter-frame deformation and undergo fragmentation with a relatively high frequency. A PTV algorithm, adapted to these challenges, is presented whereby a user-defined tolerance in the evolution of certain particle properties is used to refine the potential candidate particles prior to particle matching. This candidate refinement step is used to distinguish between acceptable levels of deformation between successive sightings of a given particle, and more substantial changes consistent with fragmentation or coalescence, requiring the tracking of a new particle. Implementation of the PTV algorithm is presented for (1) an X-ray video from the FCINA-30-1 experiment between a jet of molten stainless steel and liquid sodium, conducted at the JAEA’s MELT facility, and (2) video imaging of the VE-U9-ceramic experiment of a molten corium-thermite mixture spreading on a zirconium substrate, conducted at the CEA’s VULCANO facility. The latter case-study enabled the characterization of &gt; 70,000 local velocity vectors at locations corresponding to distinctive temperature heterogeneities in the surface of the spreading melt, providing extensive insight into the spreading dynamics for the validation of corium spreading models.

The economic effects of government spending: using expectations data to control for information

AbstractWe present a new methodology that uses professional forecasts to estimate the effects of fiscal policy. We use short-term forecasts to better identify exogenous shocks to government spending by controlling for anticipatory information already in the public domain. We use longer-term forecasts to net out expectations from the future path of other variables, which improves accuracy and efficiency by focusing on more precise measures of the impact of shocks. We show that this improves the statistical fit relative to both local projection methods and vector autoregression-based analyses that do not control for the entire future path of expectations.

A Characterization of a Local Vector Valued Bollob\xe1s Theorem

In this paper, we are interested in giving two characterizations for the so-called property L_{o,o}, a local vector valued Bollobás type theorem. We say that (X, Y) has this property whenever given varepsilon > 0 and an operador T: X rightarrow Y, there is eta = eta (varepsilon , T) such that if x satisfies Vert T(x)Vert > 1 - eta , then there exists x_0 in S_X such that x_0 approx x and T itself attains its norm at x_0. This can be seen as a strong (although local) Bollobás theorem for operators. We prove that the pair (X, Y) has the L_{o,o} for compact operators if and only if so does (X, mathbb {K}) for linear functionals. This generalizes at once some results due to D. Sain and J. Talponen. Moreover, we present a complete characterization for when (X widehat{otimes }_pi Y, mathbb {K}) satisfies the L_{o,o} for linear functionals under strict convexity or Kadec–Klee property assumptions in one of the spaces. As a consequence, we generalize some results in the literature related to the strongly subdifferentiability of the projective tensor product and show that (L_p(mu ) times L_q(nu ); mathbb {K}) cannot satisfy the L_{o,o} for bilinear forms.

Symmetry‐Protected Photonic Chiral Spin Textures by Spin–Orbit Coupling

AbstractChiral spin textures are widely researched in condensed matter systems and have shown potential for use in spintronics and storage applications. Photonic counterparts of these textures are observed in various optical systems with broken inversion symmetry. Unfortunately, the resemblances are only phenomenological. This work proposes a theoretical framework based on the variational theorem to show that the photonic chiral spin textures in an optical interface originate from the system's symmetry and relativity. Analysis of the rotational symmetry in optical systems indicates that the conservation of the total angular momentum is preserved from the local variations of spin vectors. Specifically, although the integral spin momentum does not carry net energy, the local spin momentum distribution, which determines the local subluminal energy transport and minimization variation of the square of the total angular momentum, results in the chiral twisting of the local spin vectors. The findings of this study deepen the understanding of the symmetries, conservative laws, and energy transport in optical systems, reveal the similarities in the formation mechanisms and the geometries of photonic and condensed‐matter chiral spin textures, and have potential applications in chiral and spin photonics.

An Improved Fractional-Order Variational Optical Flow Model Combining Structure Tensor

Dealing with problems of illumination changes in optical flow estimation, an improved variational optical flow model is proposed in this paper. The local structure constancy constraint (LSCC) is applied in the data term of the traditional HS (Horn &amp; Schunck) optical flow model to substitute the brightness constancy constraint. The fractional-order smoothness constraint (FSC) is applied in the smoothness term of the HS model. Then, the detailed calculation processes from the optical flow model to the optical flow value are explained. The structure tensor in LSCC is an image feature that is constant in the illumination changes scene. The fractional differential coefficient in FSC can fuse the local neighborhood optical flow vector into the optical flow vector of the target pixel, which can improve the integrity of the motion region with the same motion speed. Combining LSCC with FSC, our improved optical flow model can obtain an accurate optical flow field with clear outline in the illumination abnormity scene. The experimental results show that, compared with other optical flow models, our model is more suitable for the illumination changes scene and can be employed in outdoor motion detection projects.

The burden of skin disease and eye disease due to onchocerciasis in countries formerly under the African Programme for Onchocerciasis Control mandate for 1990, 2020, and 2030.

Onchocerciasis ("river blindness") can cause severe morbidity, including vision loss and various skin manifestations, and is targeted for elimination using ivermectin mass drug administration (MDA). We calculated the number of people with Onchocerca volvulus infection and onchocercal skin and eye disease as well as disability-adjusted life years (DALYs) lost from 1990 through to 2030 in areas formerly covered by the African Programme for Onchocerciasis Control. Per MDA implementation unit, we collated data on the pre-control distribution of microfilariae (mf) prevalence and the history of control. Next, we predicted trends in infection and morbidity over time using the ONCHOSIM simulation model. DALY estimates were calculated using disability weights from the Global Burden of Disease Study. In 1990, prior to MDA implementation, the total population at risk was 79.8 million with 26.0 million (32.5%) mf-positive individuals, of whom 17.5 million (21.9%) had some form of onchocercal skin or eye disease (2.5 million DALYs lost). By 2030, the total population was predicted to increase to 236.1 million, while the number of mf-positive cases (about 6.8 million, 2.9%), people with skin or eye morbidity (4.2 million, 1.8%), and DALYs lost (0.7 million) were predicted to decline. MDA has had a remarkable impact on the onchocerciasis burden in countries previously under the APOC mandate. In the few countries where we predict continued transmission between now and 2030, intensified MDA could be combined with local vector control efforts, or the introduction of new drugs for mopping up residual cases of infection and morbidity.

A CNN model embedded with local feature knowledge and its application to time-varying signal classification

A novel convolutional neural network is proposed for local prior feature embedding and imbalanced dataset modeling for multi-channel time-varying signal classification. This model consists of a single-channel signal feature parallel extraction unit, a multi-channel signal feature integration unit, a local feature embedding and feature similarity measurement unit, a full connection layer, and a Softmax classifier. An algorithm combining dynamic clustering and sliding window was used to select segments signals with typical local features in each pattern class, forming a typical local feature set. The one-dimensional CNNs were used to extract features from the single-channel signal in parallel, a comprehensive feature matrix of the multi-channel signal and the local feature matrix templates were produced. Using the method of external embedding, based on the sliding window and dynamic time warping (DTW) algorithm, the local feature similarities between the local feature template of each pattern class and the comprehensive feature sub-matrix of the input signal were measured, and the maximum values were selected to construct a local feature similarity vector in order. The information fusion was realized through a full connection layer. The proposed methodology can extract and represent both global and local signals features, strengthen the role of prior local feature in classification and improve the modeling properties of imbalanced datasets. A comprehensive learning algorithm is presented in this paper. The classification diagnosis of cardiovascular disease based on 12-lead ECG signals was used as a verification experiment. Results showed that the accuracy and generalization for the proposed technique were significantly improved.

Feasibility of Fiber Reinforcement Within Magnetically Actuated Soft Continuum Robots.

Soft continuum manipulators have the potential to replace traditional surgical catheters; offering greater dexterity with access to previously unfeasible locations for a wide range of interventions including neurological and cardiovascular. Magnetically actuated catheters are of particular interest due to their potential for miniaturization and remote control. Challenges around the operation of these catheters exist however, and one of these occurs when the angle between the actuating field and the local magnetization vector of the catheter exceeds 90°. In this arrangement, deformation generated by the resultant magnetic moment acts to increase magnetic torque, leading to potential instability. This phenomenon can cause unpredictable responses to actuation, particularly for soft, flexible materials. When coupled with the inherent challenges of sensing and localization inside living tissue, this behavior represents a barrier to progress. In this feasibility study we propose and investigate the use of helical fiber reinforcement within magnetically actuated soft continuum manipulators. Using numerical simulation to explore the design space, we optimize fiber parameters to enhance the ratio of torsional to bending stiffness. Through bespoke fabrication of an optimized helix design we validate a single, prototypical two-segment, 40 mm × 6 mm continuum manipulator demonstrating a reduction of 67% in unwanted twisting under actuation.

Research on Classification Method of 3D Point Cloud Model Based on KE-PointVNet

With the popularization and use of three-dimensional data acquisition equipment, the acquisition of three-dimensional data is more convenient. Three-dimensional data contains rich shape and scale information. How to effectively and accurately classify, segment and identify three-dimensional data is a research hotspot in the field of computer vision. Aiming at the particularity of 3D point cloud data and the neglect of local correlation between points, this paper proposes a new end-to-end depth network framework, namely KE-PointVNet. KE-PointVNet can directly deal with point cloud and construct deep convolutional network. KE-PointVNet extracts local geometric features of each point based on the EdgeConv module. By using the KNN proximity algorithm to construct local neighborhood of the point cloud, it can avoid its non-local diffusion, and finally obtain the high-level semantics of the point cloud through the local aggregation vector VLAD layer. The experimental results show that this method has a higher classification accuracy than most of the existing point cloud classification methods.