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The Miura-ori pattern possesses intriguing mechanical features, namely, the one Degree Of Freedom mobility, auxetic in-plane behavior and energy absorption capability, for applications such as core to sandwich structure, shock absorber, airless tire, etc. To realize the folding mechanism of Miura-ori, in this paper a Miura-ori patterned sheet was made from copolymer Elvaloy by compression molding, and then its deformation behavior was investigated experimentally and by using finite element analysis. The intrinsic mechanical properties of Elvaloy were obtained by tensile and four-point-bending tests, respectively, and subsequently used in the finite element (FE) simulation. For utilizing the sheet in all the principal directions, three types of tests were conducted: out-of-plane compression, three-point-bending and in-plane compressions. FE simulations using Abaqus/Explicit were carried out to analyze the deformations of the patterned sheet under the same loading as that in the tests. The simulation results were then compared with the tests, which show good agreements. Based on the simulation results, the deformation patterns of the patterned sheet under different loading conditions were examined, as well as the energy absorption capacity. [ABSTRACT FROM AUTHOR]

Abstract: With the development of the GIS and computer technology, it is necessary to use sampling data for spatial analysis in their researches. However, the emergence of spatial data interpolation algorithms makes it possible for us to get continuous spatial data that satisfy certain accurate requirement. These traditional methods are suffering some limitations, such as strong subjectivity, numerous assumptions, poor adaptive variation, etc. This paper presents a noval approach by using the establishment of integrated radial basis function (RBF) neural network for improving the spatial interpolation performance. Based on the experimental results on the lead element content in the soil in Kunming and its extensional areas through spatial interpolation by RBF network, it can be concluded that the proposed approach provide the more detail spatial distribution than that by using the traditional methods. [Copyright &y& Elsevier]

• A new urban-growth CA model using the firefly algorithm can enhance the simulation accuracy. • The model was applied to simulate the past and future urban patterns of Xi-xian. • The land transition probability indicates that the traffic facilities have a significant impact. • The FOM in the calibration and validation are respectively increased by 4.84% and 8.10%. • The model can improve CA-based simulation methods and enhance our understanding. Optimization of cellular automata (CA) using swarm intelligence is an effective approach to establish optimal models for urban growth modeling. This study builds a new CA model (CA FFA) using the firefly algorithm through optimizing transition rules, aiming to enhance the simulation accuracy. We applied CA FFA to reproduce historical urban growth (2009-2014 and 2014-2019) and simulate future scenarios (2024 and 2029) of the Xi-xian metropolitan area in 2009, 2014 and 2019. The retrieved CA FFA parameters and land transition probability maps indicate that the traffic facilities have more significant impacts on urban growth in Xi-xian than the socio-economic and other proximity factors. The overall accuracy of CA FFA is 90.2% in 2014 and 94.6% in 2019, both better than the logistic CA model (88.9% and 92.2%). The figure-of-merits of CA FFA in calibration and validation are respectively increased by 4.84% and 8.10% compared with the logistic CA model. With the increasing distance to the city center, new urban areas will first increase and then decrease, and be mainly distributed in the northern part, which are consistent with the local development planning and have strong practical significance. The proposed model can improve CA-based modeling methods and enhance our understanding of Chinese western cities. [ABSTRACT FROM AUTHOR]

Mercury ions (Hg2+) owing to excessive discharge cause serious damage to human health and the water ecosystem via bioaccumulation in food chains. Novel materials employed for the high-performance monitoring of Hg2+ are urgently required. Herein, using sucrose, boric acid, and melamine as raw materials, a new nanomaterial sensor, namely boron and nitrogen co-doped carbon dots (B, N-CDs), was designed for fluorescent and colorimetric dual-mode detection of Hg2+. Because of the occurrence of both dynamic and static quenching, B, N-CDs were utilized to function as fluorescent sensors for detecting Hg2+ with a limit of detection (LOD) of 5.3 nM. B, N-CDs performed an action for catalytic oxidation of 3,3′,5,5′-Tetramethylbenzidine (TMB) to a blue cationic radical via peroxidase mimetic activity. By sequentially adding cysteine and Hg2+ to control the emergence of the TMB cation radical, a sensor for the Hg2+ assay was established through the colorimetric "on-off-on" signal and the LOD was as low as 7.8 nM. Moreover, the application potential of B, N-CDs for complex water environments was demonstrated to be excellent. In summary, the dual-mode detection method delivers some valid strategies for the detection of mercury in aqueous solutions employing the functional nanomaterials mentioned, and opens new avenues in tackling the problem of heavy metal ion pollution for environmental monitoring and remediation. [Display omitted] • The B, N-CDs exhibited favorable optical properties and catalase activity. • Fluorescent and colorimetric dual-mode was applied to detect mercury ions. • The method achieved high sensitivity and visible monitoring of Hg2+ in wastewater. [ABSTRACT FROM AUTHOR]

A growing body of evidence demonstrates visual, perceptual, and oculomotor abilities contribute to batting performance in baseball and there is interest in whether training such abilities can transfer positively to batting performance. The current study tested this question through a pre-registered, randomized, and placebo-controlled intervention, conducted with 24 collegiate baseball players at two NCAA Division 1 universities. Athletes were randomized to receive either dynamic vision training consisting of stroboscopic, anticipatory timing, and eye quickness drills, or placebo drills stylized after control procedures in previous vision therapy studies. Generalized near-transfer was tested via a digital visual-motor task battery (n = 20), while sports-specific intermediate and far transfer of training were evaluated through instrumented batting practice metrics (n = 14) and box score performance in NCAA-sanctioned games (n = 12), respectively. The effects of training group were tested on these outcome measures while controlling for covariates such as pre-training expectations and site. Participants averaged 8.50 hours of training with no significant group differences in training adherence, expectations, or baseline assessments. ANCOVA revealed no group differences in measures of visual-motor skills or NCAA game statistics. However, batting practice demonstrated significant improvements in launch angle (p = 0.002, Cohen's d = 0.74) and hit distance (p < 0.001, Cohen's d = 0.70) for the active training cohort relative to the placebo control. This controlled and pre-registered pilot study therefore provides preliminary evidence that vision training may improve batting practice performance, creating new opportunities for the transfer of skill training and warranting further study. • Conducted pre-registered, randomized, placebo-controlled training study with baseball batters. • Training design guided by the modified perceptual training framework. • 24 batters on two college teams received either dynamic or placebo vision training. • Causal evidence of training transfer observed in instrumented batting performance. • Several alternative explanations for the transfer evidence were ruled out. [ABSTRACT FROM AUTHOR]

Abstract Recent years have seen a rapid surge in the use of remote sensing technologies for characterizing the structure, composition and function of forested landscapes. Yet with few exceptions these studies have only provided snapshots of the ecosystem at one point in time, thereby limiting our ability to understand how forests are responding to global change. New approaches for characterizing forest dynamics using multi-temporal remotely sensed data are therefore urgently needed if we are to integrate these new technologies into conservation and management decision making processes. By combining data from a network of forest plots with repeat airborne lidar, here we develop an approach to (i) map fine-scale variation in aboveground carbon density (ACD) and its change over time across the landscape, and (ii) link these changes in ACD to forest structural attributes, species composition, disturbance regimes and local topography. We tested this framework on a temperate forest in the Alps characterized by the presence of three dominant species: spruce (Picea abies), silver fir (Abies alba) and beech (Fagus sylvatica). We found that between 2007 and 2011 the majority of the landscape (61.0%) increased in ACD, with a much smaller fraction of the study area exhibiting evidence of small-scale natural disturbances (3.7%) or ACD loss as a result of logging activities (13.7%). On average, areas of the landscape that actively sequestered carbon did so at a rate of 3.6% per year. However, rates of ACD accumulation varied considerably across the landscape, being greatest in forest stands characterized by multi-layered heterogeneous canopies, in ones dominated by spruce and at lower elevations. We demonstrated the potential of repeat lidar for characterizing not only the structure, but also the composition and aboveground carbon dynamics of forests. In doing so we open the door to monitor forests across large and inaccessible landscapes in order to better understand how they are responding to rapid global change and refine how we manage and conserve these critical ecosystems. Highlights • Bi-temporal lidar data are used to map forest disturbances and changes in ACD. • Lidar data are used to map forest structure, species composition, and topography. • ACD changes are linked to forest structure, species composition, and topography. • Lidar allows objective prediction of ACD, species composition, and forest structure. [ABSTRACT FROM AUTHOR]

Due to the limitation of labeled training samples, computational complexity, and other difficulties, active learning (AL) algorithms aiming at finding the most informative training samples have been an active topic of research in remote sensing image classification in the last few years. Usually, AL follows an iterative scheme, and the search of new samples relies on the whole image, resulting in that an approach may turn out to be prohibitive when the data sets are huge, e.g., hyperspectral data. Large amounts of unlabeled samples are easy to collect indeed, with respect to the cost of labeled sample collection. However, algorithm complexity, data storage capacity and processing times are also limited. Therefore, a sample set smaller in size, and consisting of the most valuable information, is preferable. In this work, we propose a design protocol to generate a more significant candidate sample set for active learning, aiming at reducing the unlabeled sample search complexity, and eventually improving the classification performance. The basic idea is providing the initial labeled and unlabeled samples that are composed of mixed or pure samples for AL heuristics, to find out which one is better for AL from the low-cost sample design point of view. For comparison and validation purposes, six state-of-the-art AL methods (including breaking ties, margin sampling, margin sampling by closest support vectors, normalized entropy query-by-committee, multi-class level uncertainty and multi view adaptive maximum disagreement based active learning) were tested on real hyperspectral images with different resolution both with and without the proposed sample design protocol. Experimental results confirmed the advantages of the proposed technique. [ABSTRACT FROM AUTHOR]

Wind represents a primary source of disturbances in forests, necessitating an assessment of the resulting damage to ensure appropriate forest management. Remote sensing, encompassing both active and passive techniques, offers a valuable and efficient approach for this purpose, enabling coverage of large areas while being cost-effective. Passive remote sensing data could be affected by the presence of clouds, unlike active systems such as Synthetic Aperture Radar (SAR) which are relatively less affected. Therefore, this study aims to explore the utilization of bitemporal SAR data for windthrow detection in mountainous regions. Specifically, we investigated how the detection outcomes vary based on three factors: i) the SAR wavelength (X-band or C-band), ii) the acquisition period of the pre- and post-event images (summer, autumn, or winter), and iii) the forest type (evergreen vs. deciduous). Our analysis considers two SAR satellite constellations: COSMO-SkyMed (band-X, with a pixel spacing of 2.5 m and 10 m) and Sentinel-1 (band-C, with a pixel spacing of 10 m). We focused on three study sites located in the Trentino-South Tyrol region of Italy, which experienced significant forest damage during the Vaia storm from 27th to 30th October 2018. To accomplish our objectives, we employed a detail-preserving, scale-driven approach for change detection in bitemporal SAR data. The results demonstrate that: i) the algorithm exhibits notably better performance when utilizing X-band data, achieving a highest kappa accuracy of 0.473 and a balanced accuracy of 76.1%; ii) the pixel spacing has an influence on the accuracy, with COSMO-SkyMed data achieving kappa values of 0.473 and 0.394 at pixel spacings of 2.5 m and 10 m, respectively; iii) the post-event image acquisition season significantly affects the algorithm's performance, with summer imagery yielding superior results compared to winter imagery; and iv) the forest type (evergreen vs. deciduous) has a noticeable impact on the results, particularly when considering autumn/winter data. • SAR band, and season of the acquisition conditioned mapping accuracy. • COSMO-SkyMed data overcome Sentinel-1 data with the adopted methodology. • Pixel spacing had a small effect on the mapping accuracy. • Images acquired in optimal conditions provide the highest detection accuracies. • Detection accuracies are influenced by leaf-on leaf-off conditions of trees. [ABSTRACT FROM AUTHOR]

• Alluvial-fan to delta-coastal environments in an initial stage of basin-fill. • Depositional breaks occurred in the late Meso- to Neoproterozoic caused by uplifts. • Depocenter migrated from the north to the south in the late Meso- to Neoproterozoic. • Detrital zircon ages in the Mesoproterozoic and Paleozoic show variable provenances. • The North China Craton was involved in the assembly of the Rodinia Supercontinent. The North China Craton (NCC) is thought to experience multi-stage extensional events after the breakup of the Columbia (Nuna) Supercontinent, and even during the assembly of the Rodinia Supercontinent. In recent years, volcanic and detrital zircon U-Pb dating ages provided new insights into the Mesoproterozoic to Neoproterozoic tectonic framework in the NCC. As the Mesoproterozoic Xiong'er Group in the southern NCC is regarded as the oldest volcanic-sedimentary succession after the final amalgamation of the NCC, we reviewed the sedimentary environments and provenances of Mesoproterozoic to Neoproterozoic sedimentary sequences above the strata in order to understand tectono-sedimentary evolution of the southern NCC during this period. The early Mesoproterozoic sedimentary rocks were deposited in alluvial-fan to fluvial and (fan-) delta-coastal environments suggesting an initial stage of basin development. Fine-grained clastic sedimentary rocks interlayered with carbonate deposition formed on the southern NCC later, and implied a broad subsidence before ca. 1611 Ma. After that, depositional breaks caused by regional tectonic uplifts led to different sedimentary sequences and lateral migration of the depocenter from the north to the south (to the current co-ordinates). The unconformably overlying sedimentary rocks in the north of the southern NCC were deposited in restricted marine basins during late Mesoproterozoic to Neoproterozoic as a whole. However, the enlargement of shallow-marine shelf led to the thick accumulation of carbonates in the southernmost NCC characterized by a deepening-upward trend from the late Mesoproterozoic sequence. The Neoproterozoic sedimentary sequence is typified by sharp increasing terrigenous supplies and frequent changes in environment, and could be deposited in a tectonically active basin in consideration of its close association with volcanism. Detrital zircon grains from the oldest clastic sequence (i.e., the Bingmagou Formation) overlying the Xiong'er volcanic-sedimentary rocks and from the earliest Paleozoic sedimentary rocks (i.e., the Xinji Formation) are used to track changes of provenances. Detrital zircon grains from the Bingmagou Formation display two dominant age peaks at ca. 1850 and 2500 Ma and three secondary peaks at ca. 2100, 2350 and 2700 Ma. In contrast, detrital zircon grains from the Xinji Formation have three major age peaks at ca. 1850, 2200 and 2500 Ma and three subordinate populations of 950, 1100 and 1450 Ma. In combination with the uplifts during the Mesoproterozoic to Neoproterozoic, Neoproterozoic magmatism, and a large amount of detrital zircon derived from Rodinia-related orogenesis in the southern NCC, it is very likely that the major changes of basin configuration could be related to significant tectonic readjustment along with the evolution of the Rodinia Supercontinent. [ABSTRACT FROM AUTHOR]

Highlights • The iron oxide nanoparticles is synthesized via chemical co-precipitation method. • The self-Q-switched operation can be presented with the absence of polarizer controller. • The shortest pulse duration is 896 ns. Abstract All fiber Q-switched laser with its advantages of high energy, compact structure and high stability boosted the growing demand in many applications. We synthesized the regular iron oxide nanoparticles (IONP) in size of 12–15 nm via the chemical co-precipitation method. Using the IONP-PVA film as SA, high stable polarization-insensitive Er-doped Q-switched fiber laser was demonstrated. The prepared IONP SA exhibits saturation intensity of 13.44 MW/cm2. The shortest pulse duration was achieved to be 896 ns and the single pulse energy was up to 100 nJ with the maximum pump power of 500 mW. In particular, the polarization controller is unnecessary in our experiments, so the ring cavity can be compacted into a smaller size with 80 dB signal-to-noise ratio for the output pulse sequence. Such a compact, low cost and high stability Q-switched laser maybe expected to have the more extensive application prospect. [ABSTRACT FROM AUTHOR]

The study presents the dark solitons generation in Er-doped mode-locked fiber laser based on ferroferric-oxide (Fe 3 O 4 ) nanoparticles. The D-shaped fiber deposited with Fe 3 O 4 nanoparticles is used as the birefringence and nonlinearity device. The dark solitons with repetition rate of 13.5 MHz are obtained in the pump power of 350 mW. The bright-dark soliton pairs are also observed by properly adjusting the polarization state at the pump power of 400 mW. The results in this paper demonstrate that Fe 3 O 4 nanoparticles are the promising materials for generating dark solitons in fiber lasers. [ABSTRACT FROM AUTHOR]

Despite the widespread use of transcranial magnetic stimulation (TMS) in research and clinical care, the dose–response relations and neurophysiological correlates of modulatory effects remain relatively unexplored. To fill this gap, we studied modulation of visual processing as a function of TMS parameters. Our approach combined electroencephalography (EEG) with application of single pulse TMS to visual cortex as participants performed a motion perception task. During each participants' first visit, motion coherence thresholds, 64-channel visual evoked potentials (VEPs), and TMS resting motor thresholds (RMT) were measured. In second and third visits, single pulse TMS was delivered at one of two latencies, either 30 ms before the onset of motion or at the onset latency of the N2 VEP component derived from the first session. TMS was delivered at 0%, 80%, 100%, or 120% of RMT over the site of N2 peak activity, or at 120% over vertex. Behavioral results demonstrated a significant main effect of TMS timing on accuracy, with better performance when TMS was applied at the N2-Onset timing versus Pre-Onset, as well as a significant interaction, indicating that 80% intensity produced higher accuracy than other conditions at the N2-Onset. TMS effects on the P3 VEP showed reduced amplitudes in the 80% Pre-Onset condition, an increase for the 120% N2-Onset condition, and monotonic amplitude scaling with stimulation intensity. The N2 component was not affected by TMS. These findings reveal the influence of TMS intensity and timing on visual perception and electrophysiological responses, with optimal facilitation at stimulation intensities below RMT. • Studied modulation of visual perception and EEG due to single-pulse TMS. • Delivered spTMS at two latencies and five intensities to either visual cortex or vertex. • Found a significant effect of timing and an interaction with intensity on accuracy. • P3 VEP showed monotonic amplitude scaling with stimulation intensity. • Findings generally indicate facilitation at stimulation intensities below RMT. [ABSTRACT FROM AUTHOR]

• Long-interval paired-pulse TMS was applied to visual cortex during a motion perception task. • The ppTMS was delivered according to scalp and meta-analytic coordinates, as well as sham. • No effects of active-versus-sham stimulation were observed on motion perception performance. The perception of visual motion is dependent on a set of occipitotemporal regions that are readily accessible to neuromodulation. The current study tested if paired-pulse Transcranial Magnetic Stimulation (ppTMS) could modulate motion perception by stimulating the occipital cortex as participants viewed near-threshold motion dot stimuli. In this sham-controlled study, fifteen subjects completed two sessions. On the first visit, resting motor threshold (RMT) was assessed, and participants performed an adaptive direction discrimination task to determine individual motion sensitivity. During the second visit, subjects performed the task with three difficulty levels as TMS pulses were delivered 150 and 50 ms prior to motion stimulus onset at 120% RMT, under the logic that the cumulative inhibitory effect of these pulses would alter motion sensitivity. ppTMS was delivered at one of two locations: 3 cm dorsal and 5 cm lateral to inion (scalp-based coordinate), or at the site of peak activation for "motion" according to the NeuroSynth fMRI database (meta-analytic coordinate). Sham stimulation was delivered on one-third of trials by tilting the coil 90°. Analyses showed no significant active-versus-sham effects of ppTMS when stimulation was delivered to the meta-analytic (p = 0.15) or scalp-based coordinates (p = 0.17), which were separated by 29 mm on average. Active-versus-sham stimulation differences did not interact with either stimulation location (p = 0.12) or difficulty (p = 0.33). These findings fail to support the hypothesis that long-interval ppTMS recruits inhibitory processes in motion-sensitive cortex but must be considered within the limited parameters used in this design. [ABSTRACT FROM AUTHOR]