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The locomotion performance of the current legged miniature robots remains inferior compared to even the most simple insects. The inferiority has led researchers to utilize biological principles and control in their designs, often resulting in improved performance and robot capabilities. Additionally, optimizing the locomotion patterns compatible with the robot's limitations (such as the gaits achievable by the robot) improves the performance significantly and results in a robot operating with its maximum capabilities. This paper studies the locomotion characteristics of running/walkingn-legged modular miniature robots with soft or rigid module connections. The locomotion study is done using the presented dynamic model, and the results are verified using a legged modular miniature robot with soft and rigid backbones (SMoLBot). The optimum foot contact sequences for ann-legged robot with different compliance values between the modules are derived using the locomotion analyses and the dynamic and kinematic formulations. Our investigations determine unique optimum foot contact sequences for multi-legged robots with different body compliances and module numbers. Locomotion analyses of a multi-legged robot with different backbones operating with optimum gaits show two main motion characteristics; the rigid robots minimize the number of leg-ground contacts to increase velocity, whereas soft-backbone robots use a lift-jump-fall motion sequence to maximize the translational speeds. These two behaviors are similar between different soft-backbone and rigid-backbone robots; however, the optimal foot contact sequences are different and unpredictable.The crystal structures of Sb2Te3-ySey(y= 0.6 andy= 1.2) at 0-24 GPa were investigated by synchrotron x-ray diffraction. The stoichiometry of Sb2Te3-ySeyused in this study was determined to be Sb2Te2.19(9)Se0.7(2)fory= 0.6 and Sb2Te1.7(1)Se1.3(3)fory= 1.2, on the basis of energy-dispersive x-ray spectroscopy. The sample of Sb2Te2.19(9)Se0.7(2)showed a structural phase transition from a rhombohedral structure (space group No. 166,R3¯m) (phase I) to a monoclinic structure (space group No. 12,C2/m) (phase II), with increasing pressure up to ∼9 GPa. A new structural phase (phase II') emerged at 17.7 GPa, a monoclinic structure with the space groupC2/c(No. 15). Finally, a 9/10-fold monoclinic structure (space group No. 12,C2/m) (phase III) was observed at 21.8 GPa. In contrast, the sample of Sb2Te1.7(1)Se1.3(3)provided only phase I (space group No. 166,R3¯m) and phase II (space group No. 12,C2/m), showing one structural phase transition from 0-19.5 GPa. These samples were not superconductors at ambient pressure, but superconductivity suddenly appeared with increasing pressure. Superconductivity with superconducting transition temperatures (Tc's) of 2 and 4 K was observed above 6 GPa in phase I of Sb2Te2.19(9)Se0.7(2). In this sample, theTcvalues of 6 and 9 K were observed in phase II and phase II' or III of Sb2Te2.19(9)Se0.7(2), respectively. Superconductivity withTc's of 4 and 5 K suddenly emerged in Sb2Te1.7(1)Se1.3(3)at 13.6 GPa, which corresponds to phase II, and it evolved to 6.0 K under further increased pressure. ATcvalue of 9 K was finally found above 15 GPa. The magnetic field dependence ofTcin phase II of Sb2Te2.19(9)Se0.7(2)and Sb2Te1.7(1)Se1.3(3)followed ap-wave polar model, suggesting topologically nontrivial superconductivity.Objective. X-ray luminescence computed tomography (XLCT) has played a crucial role in pre-clinical research and effective diagnosis of disease. However, due to the ill-posed of the XLCT inverse problem, the generalization of reconstruction methods and the selection of appropriate regularization parameters are still challenging in practical applications. In this research, an robust Elastic net-ℓ1ℓ2reconstruction method is proposed aiming to the challenge.Approach. Firstly, our approach consists of ℓ1and ℓ2regularization to enhance the sparsity and suppress the smoothness. Secondly, through optimal approximation of the optimization problem, double modification of Landweber algorithm is adopted to solve the Elastic net-ℓ1ℓ2regulazation. Thirdly, drawing on the ideal of supervised learning, multi-parameter K-fold cross validation strategy is proposed to determin the optimal parameters adaptively.Main results. To evaluate the performance of the Elastic net-ℓ1ℓ2method, numerical simulations, phantom and in vivo experiments were conducted. In these experiments, the Elastic net-ℓ1ℓ2method achieved the minimum reconstruction error (with smallest location error, fluorescent yield relative error, normalized root-mean-square error) and the best image reconstruction quality (with largest contrast-to-noise ratio and Dice similarity) among all methods. The results demonstrated that Elastic net-ℓ1ℓ2can obtain superior reconstruction performance in terms of location accuracy, dual source resolution, robustness and in vivo practicability.Significance. It is believed that this study will further benefit preclinical applications with a view to provide a more reliable reference for the later researches on XLCT.Nanoimprint lithography is an emerging technology to form patterns and features in the nanoscale. Production of nanoscale patterns is challenging particularly in the sub-50 nm range. Pre-stressed polymer films with embedded microscale pattern can be miniaturized by shrinking induced due to thermal stress release. However, when pre-stressed films are thermally nanoimprinted with sub-micron features and shruken, they lose all the topographical features due to material recovery. Here we report a new approach that prevents recovery and allows retention of shrunken patterns even at the scale of less then 50 nm. We have discovered that when the shrinking process is mechanically constrained in one direction, the thermal treatment only relieves the stress in the orthogonal direction leading to a uniaxial shrinkage in that direction while preserving the topographical features. A second step, with the constraint in the orthogonal direction leads to biaxial shrinkage and preservation of all of the topographical features. This new technique can produce well defined and high resolution nanostructures at dimensions below 50 nm. The process is programmable and the thermal treatment can be tuned to shrink features to various dimension below the original imprint which we use to produce tunable and gradient plasmonic structures.SPECT imaging with123I-FP-CIT is used for diagnosis of neurodegenerative disorders like Parkinson's disease. Attenuation correction (AC) can be useful for quantitative analysis of123I-FP-CIT SPECT. Ideally, AC would be performed based on attenuation maps (μ-maps) derived from perfectly registered CT scans. Suchμ-maps, however, are most times not available and possible errors in image registration can induce quantitative inaccuracies in AC corrected SPECT images. Earlier, we showed that a convolutional neural network (CNN) based approach allows to estimate SPECT-alignedμ-maps for full brain perfusion imaging using only emission data. Here we investigate the feasibility of similar CNN methods for axially focused123I-FP-CIT scans. We tested our approach on a high-resolution multi-pinhole prototype clinical SPECT system in a Monte Carlo simulation study. Three CNNs that estimateμ-maps in a voxel-wise, patch-wise and image-wise manner were investigated. selleck products As the added value of AC on clinical123I-FP-CIT scans is still debatable, the impact of AC was also reported to check in which cases CNN based AC could be beneficial. AC using the ground truthμ-maps (GT-AC) and CNN estimatedμ-maps (CNN-AC) were compared with the case when no AC was done (No-AC). Results show that the effect of using GT-AC versus CNN-AC or No-AC on striatal shape and symmetry is minimal. Specific binding ratios (SBRs) from localized regions show a deviation from GT-AC≤2.5% for all three CNN-ACs while No-AC systematically underestimates SBRs by 13.1%. A strong correlation (r≥0.99) was obtained between GT-AC based SBRs and SBRs from CNN-ACs and No-AC. Absolute quantification (in kBq ml-1) shows a deviation from GT-AC within 2.2% for all three CNN-ACs and of 71.7% for No-AC. To conclude, all three CNNs show comparable performance in accurateμ-map estimation and123I-FP-CIT quantification. CNN-estimatedμ-map can be a promising substitute for CT-basedμ-map.Hydrogel crosslinking by external stimuli is a versatile strategy to control and modulate hydrogel properties. Besides photonic energy, thermal energy is one of the most accessible external stimuli and widely applicable for many biomedical applications. However, conventional thermal crosslinking systems require a relatively high temperature (over 100°C) to initiate covalent bond formation. To our knowledge, there has not been a thermally tunable hydrogel crosslinking system suitable for biological applications. This work demonstrates a unique approach to utilize temperature sensitive liposomes to control and modulate hydrogel crosslinking over mild temperature range (below 50°C). Temperature sensitive liposomes were used to control the release of chemical crosslinkers by moderate temperature changes. The thermally controlled crosslinker release resulted in tunable mechanical and transport properties of the hydrogel. No significant inflammable response observed in the histology results ensured the biocompatibility of the liposome-mediated crosslinkable hydrogel. This work opens new opportunities to implement thermal energy system for control and modulate hydrogel properties.Objective.There is a growing interest in the use of carbon and its allotropes for microelectrodes in neural probes because of their inertness, long-term electrical and electrochemical stability, and versatility. Building on this interest, we introduce a new electrode material system consisting of an ultra-thin monoatomic layer of graphene (Gr) mechanically supported by a relatively thicker layer of glassy carbon (GC).Approach.Due to its high electrical conductivity and high double-layer capacitance, Gr has impressive electrical and electrochemical properties, two key properties that are useful for neural recording and stimulation applications. However, because of its two-dimensional nature, Gr exhibits a lack of stiffness in the transverse direction and hence almost non-existent flexural and out-of-plane rigidity that will severely limit its wider use. On the other hand, GC is one of carbon's important allotropes and consists of three-dimensional microstructures of Gr fragments with a natural molecular simila18 weeks)in vivostudy of the use of theseGr on GCmicroelectrodes assessed the quality of the electrocorticography-based neural signal recording and stimulation through electrophysiological measurements. The probes were demonstrated to be functionally and structurally stable over the 18 week period with minimal glial response-the longest reported so far for Gr-based microelectrodes.Significance.TheGr on GCmicroelectrodes presented here offers a compelling case for expanding the potentials of Gr-based technology in the broad areas of neural probes.In this work, the growth and stability towards O2exposure of two dimensional (2D) TaS2on a Cu(111) substrate is investigated. Large area (∼1 cm2) crystalline 2D-TaS2films with a metallic character are prepared on a single crystal Cu(111) substrate via a multistep approach based on physical vapor deposition. Analytical techniques such as Auger electron spectroscopy, low energy electron diffraction, and photoemission spectroscopy are used to characterize the composition, crystallinity, and electronic structure of the surface. At coverages below one monolayer equivalent (ML), misoriented TaS2domains are formed, which are rotated up to±13orelative to the Cu(111) crystallographic directions. The TaS2domains misorientation decreases as the film thickness approaches 1 ML, at which the crystallographic directions of TaS2and Cu(111) are aligned. The TaS2film is found to grow epitaxially on Cu(111). As revealed by low energy electron diffraction in conjunction with an atomic model simulation, the (3 × 3) unit cells of TaS2match the (4 × 4) supercell of Cu(111).