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Alzheimer's disease (AD) is a neurodegenerative disorder that is beginning with amyloidosis, followed by neuronal loss and deterioration in structure, function, and cognition. The accumulation of amyloid-beta in the brain, measured through 18F-florbetapir (AV45) positron emission tomography (PET) imaging, has been widely used for early diagnosis of AD. However, the relationship between amyloid-beta accumulation and AD pathophysiology remains unclear, and causal inference approaches are needed to uncover how amyloid-beta levels can impact AD development. In this paper, we propose a graph varying coefficient neural network (GVCNet) for estimating the individual treatment effect with continuous treatment levels using a graph convolutional neural network. We highlight the potential of causal inference approaches, including GVCNet, for measuring the regional causal connections between amyloid-beta accumulation and AD pathophysiology, which may serve as a robust tool for early diagnosis and tailored care.

A levitated non-spherical nanoparticle in a vacuum is ideal for studying quantum rotations and is an extremely sensitive torque and force detector. It has been proposed to probe fundamental particle-surface interactions such as the Casimir torque and the rotational quantum vacuum friction, which require it to be driven to rotate near a surface at sub-micrometer separations. Here, we optically levitate a silica nanodumbbell in a vacuum at about 430 nm away from a sapphire surface and drive it to rotate at GHz frequencies. The relative linear speed between the tip of the nanodumbbell and the surface reaches 1.4 km/s at a sub-micrometer separation. The rotating nanodumbbell near the surface demonstrates a torque sensitivity of $(5.0 \pm 1.1) \times 10^{-26} {\rm NmHz}^{-1/2}$ at room temperature. Moreover, we levitate a nanodumbbell near a gold nanograting and use it to probe the near-field intensity distribution beyond the optical diffraction limit. Our numerical simulation shows it is promising to detect the Casimir torque between a nanodumbbell and a nanograting., 4 figures

The transport properties of matter have been widely investigated. In particular, shear viscosity over a wide parameter space is crucial for various applications, such as designing inertial confinement fusion (ICF) targets and determining the Rayleigh-Taylor instability. In this work, an extended random-walk shielding-potential viscosity model (RWSP-VM) [Phys. Rev. E 106, 014142] based on the statistics of random-walk ions and the Debye shielding effect is proposed to elevate the temperature limit of RWSP-VM in evaluating the shear viscosity of metals. In the extended model, we reconsider the collision diameter that is introduced by hard-sphere concept, hence, it is applicable in both warm and hot temperature regions (10^1-10^7 eV) rather than the warm temperature region (10^1-10^2 eV) in which RWSP-VM is applicable. The results of Be, Al, Fe, and U show that the extended model provides a systematic way to calculate the shear viscosity of arbitrary metals at the densities from about 0.1 to 10 times the normal density (the density at room temperature and 1 standard atmosphere). This work will help to develop viscosity model in wide region when combined with our previous low temperature viscosity model [AIP Adv. 11, 015043]., Comment: 6 pages, 5 figures

Paramagnetic ions and radicals play essential roles in biology and medicine, but detecting these species requires a highly sensitive and ambient-operable sensor. Optically addressable spin color centers in 3D semiconductors have been used for detecting paramagnetic spins as they are sensitive to the spin magnetic noise. However, the distance between spin color centers and target spins is limited due to the difficulty of creating high-quality spin defects near the surface of 3D materials. Here, we show that spin qubits in hexagonal boron nitride (hBN), a layered van der Waals (vdW) material, can serve as a promising sensor for nanoscale detection of paramagnetic spins in liquids. We first create shallow spin defects in close proximity to the hBN surface, which sustain high-contrast optically detected magnetic resonance (ODMR) in liquids. Then we demonstrate sensing spin noise of paramagnetic ions in water based on spin relaxation measurements. Finally, we show that paramagnetic ions can reduce the contrast of spin-dependent fluorescence, enabling efficient detection by continuous wave ODMR. Our results demonstrate the potential of ultrathin hBN quantum sensors for chemical and biological applications., Comment: 4 figures

Van der Waals layered materials are a focus of materials research as they support strong quantum effects and can easily form heterostructures. Electron spins in van der Waals materials played crucial roles in many recent breakthroughs, including topological insulators, two-dimensional (2D) magnets, and spin liquids. However, nuclear spins in van der Waals materials remain an unexplored quantum resource. Here we report the first demonstration of optical polarization and coherent control of nuclear spins in a van der Waals material at room temperature. We use negatively-charged boron vacancy ($V_B^-$) spin defects in hexagonal boron nitride to polarize nearby nitrogen nuclear spins. Remarkably, we observe the Rabi frequency of nuclear spins at the excited-state level anti-crossing of $V_B^-$ defects to be 350 times larger than that of an isolated nucleus, and demonstrate fast coherent control of nuclear spins. We also detect strong electron-mediated nuclear-nuclear spin coupling that is 5 orders of magnitude larger than the direct nuclear spin dipolar coupling, enabling multi-qubit operations. Nitrogen nuclear spins in a triangle lattice will be suitable for large-scale quantum simulation. Our work opens a new frontier with nuclear spins in van der Waals materials for quantum information science and technology.

Vision multi-layer perceptrons (MLPs) have shown promising performance in computer vision tasks, and become the main competitor of CNNs and vision Transformers. They use token-mixing layers to capture cross-token interactions, as opposed to the multi-head self-attention mechanism used by Transformers. However, the heavily parameterized token-mixing layers naturally lack mechanisms to capture local information and multi-granular non-local relations, thus their discriminative power is restrained. To tackle this issue, we propose a new positional spacial gating unit (PoSGU). It exploits the attention formulations used in the classical relative positional encoding (RPE), to efficiently encode the cross-token relations for token mixing. It can successfully reduce the current quadratic parameter complexity $O(N^2)$ of vision MLPs to $O(N)$ and $O(1)$. We experiment with two RPE mechanisms, and further propose a group-wise extension to improve their expressive power with the accomplishment of multi-granular contexts. These then serve as the key building blocks of a new type of vision MLP, referred to as PosMLP. We evaluate the effectiveness of the proposed approach by conducting thorough experiments, demonstrating an improved or comparable performance with reduced parameter complexity. For instance, for a model trained on ImageNet1K, we achieve a performance improvement from 72.14\% to 74.02\% and a learnable parameter reduction from $19.4M$ to $18.2M$. Code could be found at https://github.com/Zhicaiwww/PosMLP.

Additional file 2: The top 10 up/downregulated Pathways.

Additional file 3: The details of glycolysis related miRNAs.

Force-based algorithms for $\mathit{\text{ab initio}}$ atomic structure relaxation, such as conjugate gradient methods, usually get stuck in the line minimization processes along search directions, where expensive $\mathit{\text{ab initio}}$ calculations are triggered frequently to test trial positions before locating the next iterate. We present a force-based gradient descent method, WANBB, that circumvents the deficiency. At each iteration, WANBB enters the line minimization process with a trial stepsize capturing the local curvature of the energy surface. The exit is controlled by an unrestrictive criterion that tends to accept early trials. These two ingredients streamline the line minimization process in WANBB. The numerical simulations on nearly 80 systems with good universality demonstrate the considerable compression of WANBB on the cost for the unaccepted trials compared with conjugate gradient methods. We also observe across the board significant and universal speedups as well as the superior robustness of WANBB over several widely used methods. The latter point is theoretically established. The implementation of WANBB is pretty simple, in that no a priori physical knowledge is required and only two parameters are present without tuning., Comment: 8 pages, 9 figures

Learning objectives of recommender models remain largely unexplored. Most methods routinely adopt either pointwise or pairwise loss to train the model parameters, while rarely pay attention to softmax loss due to the high computational cost. Sampled softmax loss emerges as an efficient substitute for softmax loss. Its special case, InfoNCE loss, has been widely used in self-supervised learning and exhibited remarkable performance for contrastive learning. Nonetheless, limited studies use sampled softmax loss as the learning objective to train the recommender. Worse still, none of them explore its properties and answer "Does sampled softmax loss suit for item recommendation?" and "What are the conceptual advantages of sampled softmax loss, as compared with the prevalent losses?", to the best of our knowledge. In this work, we aim to better understand sampled softmax loss for item recommendation. Specifically, we first theoretically reveal three model-agnostic advantages: (1) mitigating popularity bias, which is beneficial to long-tail recommendation; (2) mining hard negative samples, which offers informative gradients to optimize model parameters; and (3) maximizing the ranking metric, which facilitates top-K performance. Moreover, we probe the model-specific characteristics on the top of various recommenders. Experimental results suggest that sampled softmax loss is more friendly to history and graph-based recommenders (e.g., SVD++ and LightGCN), but performs poorly for ID-based models (e.g., MF). We ascribe this to its shortcoming in learning representation magnitude, making the combination with the models that are also incapable of adjusting representation magnitude learn poor representations. In contrast, the history- and graph-based models, which naturally adjust representation magnitude according to node degree, are able to compensate for the shortcoming of sampled softmax loss., Comment: 10 Pages, 1 figure, 5 tables

The dynamics of three interacting objects has been investigated extensively in Newtonian gravitational physics (often termed the three-body problem), and is important for many quantum systems, including nuclei, Efimov states, and frustrated spin systems. However, the dynamics of three macroscopic objects interacting through quantum vacuum fluctuations (virtual photons) is still an unexplored frontier. Here, we report the first observation of Casimir interactions between three isolated macroscopic objects. We propose and demonstrate a three terminal switchable architecture exploiting opto-mechanical Casimir interactions that can lay the foundations of a Casimir transistor. Beyond the paradigm of Casimir forces between two objects in different geometries, our Casimir transistor represents an important development for control of three-body virtual photon interactions and will have potential applications in sensing and information processing with the Casimir effect., Comment: 7 pages, 4 figures

Optically active spin defects in van der Waals materials are promising platforms for modern quantum technologies. Here we investigate the coherent dynamics of strongly interacting ensembles of negatively charged boron-vacancy ($\mathrm{V}_{\mathrm{B}}^-$) centers in hexagonal boron nitride (hBN) with varying defect density. By employing advanced dynamical decoupling sequences to selectively isolate different dephasing sources, we observe more than 5-fold improvement in the measured coherence times across all hBN samples. Crucially, we identify that the many-body interaction within the $\mathrm{V}_{\mathrm{B}}^-$ ensemble plays a substantial role in the coherent dynamics, which is then used to directly estimate the concentration of $\mathrm{V}_{\mathrm{B}}^-$. We find that at high ion implantation dosage, only a small portion of the created boron vacancy defects are in the desired negatively charged state. Finally, we investigate the spin response of $\mathrm{V}_{\mathrm{B}}^-$ to the local charged defects induced electric field signals, and estimate its ground state transverse electric field susceptibility. Our results provide new insights on the spin and charge properties of $\mathrm{V}_{\mathrm{B}}^-$, which are important for future use of defects in hBN as quantum sensors and simulators., Comment: 8+8+4 pages, 4+5+1 figures

Clouds lead to missing or distorted land-related information in impacted areas in optical remote sensing images. Cloud masking, which labels cloud-contaminated pixels, forms the basis for subsequen...

Building extraction from very high-resolution (VHR) remotely sensed imagery has been an area of increased interest. One of the main purposes of building extraction is to generate polygonal represen...

The multiple scattering theory (MST) is one of the most widely used methods in electronic structure calculations. It features a perfect separation between the atomic configurations and site potentials, and hence provides an efficient way to simulate defected and disordered systems. This work studies the MST methods from a numerical point of view and shows the convergence with respect to the truncation of the angular momentum summations, which is a fundamental approximation parameter for all MST methods. We provide both rigorous analysis and numerical experiments to illustrate the efficiency of the MST methods within the angular momentum representations., 33 pages, 7 figures

The wear degree of an elevator’s traction sheave cannot be identified easily, quickly, or accurately using traditional measurement methods. In this study, a new dynamic wear identification method for an elevator’s traction sheave is proposed based on multiple acoustic emission (AE) information fusion. According to the significant differences between the AE signals of running traction sheaves with different wear degrees, AE signals measured by four sensors were collected and analyzed to establish feature databases. The membership functions of each AE signal were optimized based on minimum fuzzy entropy and particle swarm optimization and combined with the fuzziness of AE signals between adjacent wear degrees. Finally, the Dempster-Shafer decision criterion was used to accurately determine the wear degree of the traction sheave. Field experiments were conducted on four randomly selected elevators to verify the accuracy of the proposed identification model. The results showed that the minimum reliability value of the identification result was 0.9945, maximum uncertainty was 0.0001, and identification accuracy was 100%. The proposed identification method for the wear degree of an elevator’s traction sheave could efficiently provide early warnings and improve the safety factor of an elevator.

Optically levitated nonspherical particles in vacuum are excellent candidates for torque sensing, rotational quantum mechanics, high-frequency gravitational wave detection, and multiple other applications. Many potential applications, such as detecting the Casimir torque near a birefringent surface, require simultaneous cooling of both the center-of-mass motion and the torsional vibration (or rotation) of a nonspherical nanoparticle. Here we report the first 5D cooling of a levitated nanoparticle. We cool the 3 center-of-mass motion modes and 2 torsional vibration modes of a levitated nanodumbbell in a linearly-polarized laser simultaneously. The only uncooled rigid-body degree of freedom is the rotation of the nanodumbbell around its long axis. This free rotation mode does not couple to the optical tweezers directly. Surprisingly, we observe that it strongly affects the torsional vibrations of the nanodumbbell. This work deepens our understanding of the nonlinear dynamics and rotation coupling of a levitated nanoparticle and paves the way towards full quantum control of its motion., Comment: 5 pages, 4 figures

Optical liquids are ideal materials for designing apochromatic lens due to their lower refractive index and higher Abbe numbers than those of the ordinary optical glasses. Based on the Buchdahl dispersion formula, the dispersion coefficient diagram of liquids and glasses is established. The liquid-glass combination lens(LGCL) with small secondary spectrum is obtained by calculating the combination structure with low dispersion liquid and glasses. The initial optical structure of the liquid-glass apochromatic lens(LGAL) can be obtained by replacing two glass lenses in an initial optical system with the LGCL. Using the multi-configuration optimization of ZEMAX, the liquid-glass achromatic zoom lens (LGAZL) can be designed by optimizing the LGAL. The LGAZL has an objective field of view ϕ63 mm–ϕ57 mm, an image field of view 8 mm, a working distance 240 mm and the zoom range of focal length 75–85 mm. The chromatic aberration and the secondary spectrum of the LGAZL are all less than 3 μm in the whole zoom range.

The present work shows implementation of SLAM for mapping and navigation in indoor environment under robot operating system ROS, using differential drive robot provided by laser scan. Mapping process is done by using ROS packages based on extended kalman EKF filter algorithm, whereas localization is done by using packages based on adaptive Monte Carlo localization AMCL, navigation is performed by ROS built functions. Paper also will give concrete intuition about using EKF to accomplish SLAM, and shows how the results diverge in case of not using SALM algorithm.

Fatigue life and fatigue stress range of the friction plate which is made of 30CrMnSiA were studied under laboratory environment. By using Scanning Electron Microscopy (SEM) to observe the fracture striation, the width of the fatigue striation can be obtained. Fatigue life and fatigue stress range can be studied with the combination of Paris law and fatigue striation width. The method is simple and mature, and the relative error of estimation is within expected values.

Precise machine vision detection for a large object at a finite working distance (WD) requires that the lens has a high resolution for a large field of view (FOV). In this case, the effect of a secondary spectrum on image quality is not negligible. According to the detection requirements, a high resolution apochromatic objective is designed and analyzed. The initial optical structure (IOS) is combined with three segments. Next, the secondary spectrum of the IOS is corrected by replacing glasses using the dispersion vector analysis method based on the Buchdahl dispersion equation. Other aberrations are optimized by the commercial optical design software ZEMAX by properly choosing the optimization function operands. The optimized optical structure (OOS) has an f-number (F/#) of 3.08, a FOV of φ60 mm, a WD of 240 mm, and a modulated transfer function (MTF) of all fields of more than 0.1 at 320 cycles/mm. The design requirements for a nonfluorite material apochromatic objective lens with a large field and high definition for machine vision detection have been achieved.

It is well known that the irradiation-induced defects strongly influence the mechanical properties of zirconium (Zr) or its alloys in nuclear reactors. However, how the point defect changes the mechanical properties has been rarely studied. Here, we systematically investigated the effect of vacancies on the mechanical properties of alpha-Zr based on density functional theory (DFT). Both uniformly distributed vacancies and vacancy clusters were considered. Our results reveal that the existence of vacancy will reduce the bulk modulus, while enhance the shear and Young's moduli. Based on these moduli, the ductility and hardness were further calculated. With the introduction of vacancy, the ductility decreases, but the hardness increases. However, when the vacancy concentration is larger than a critical value, a rise in the ductility and a reduction in the hardness occur, which indicates the degeneration of the material. Moreover, it was found that the vacancies lead to a more isotropic distribution of Young's modulus in 3D space. To further investigate how the clustering of vacancies influences the mechanical properties, the most stable configurations of di- and trivacancy clusters have been predicted, which correspond to the most compact distribution of vacancies. Compared with the uniform distribution of vacancies, clustering of vacancies will strengthen the above changes of elastic moduli, ductility and hardness. Our results indicate that the increase of the vacancy concentration may be the basic cause for the changes of the mechanical properties under irradiation, while the formation of vacancy clusters intensifies these changes.

Nb 2 O 5 nanowires with controllable carbon coating thickness were prepared by plasma enhanced chemical vapour deposition. These hybrid nanowires were found to be efficient field emitters where the turn-on and threshold fields decreased with increasing carbon coating thickness. Notably, high current density was obtained from these hybrid nanowires (a maximum of ∼59 mA/cm 2 at 11 V/μm) which was an order of magnitude higher than pristine Nb 2 O 5 nanowires. The emission sites were distributed uniformly and current stability tests showed a stable emission current density with

The template-directed assembly of two planar molecules (copper phthalocyanine (CuPc) and pentacene) on SiC nanomesh has been studied by scanning tunneling microscopy and photoelectron spectroscopy, respectively. Both molecules are trapped as single molecules in the cells of SiC nanomesh at low coverage. At high coverage, CuPc forms a highly ordered single-molecular array with identical symmetry and periodicity as the substrate, whereas pentacene forms a quasi-amorphous layer due to the random mixture of three different adsorption configurations. This difference in adsorption behavior is attributed to differences in molecular geometries. The measured changes of work functions reveal weak charge transfer between the molecules and substrate. Both molecules are preferentially adsorbed on the SiC nanomesh rather than on graphene. The CuPc single-molecular array possesses good long-range order, large area coverage, and a molecular density of over 3.0 x 10(13) molecules/cm(2).

The secondary electron emission (SEE) yield of heterostructures of zinc oxide (ZnO) nanoneedles coaxially coated with aluminum nitride (AlN) or gallium nitride (GaN) has been studied using ion and X-ray beams. This paper describes experiments performed with ions (2 MeV protons and 3.6 MeV/nucleon carbon beams) and photons (synchrotron radiation at ≈1 keV). The SEE yield of the heterostructures is enhanced significantly by the intrinsic nanostructure of the ZnO nanoneedle templates as compared to the AlN and GaN thin films on silicon (Si) substrates [T.J. Vink, R.G.F.A. Verbeek, V. Elsbergen, P.K. Bachmann, Appl. Phys. Lett. 83 (2003) 2285]. One of the mechanisms responsible for SEE yield enhancement can be attributed to the larger area of the nanostructured surface.

Humid environment plays a vital role in affecting the performance stability of the organic metal halide perovskite solar cells. Therefore, in situ monitoring the micro-structural evolution of perovskite film in real time will help to reveal the micro-mechanism for the device performance decay induced by humidity. A device providing a controllable humid environment has been set up at X-ray diffraction beamline of Shanghai Synchrotron Radiation Facility, which is used to monitor in situ the perovskite film micro-structural evolution in real time in a humid environment by using grazing incidence X-ray diffraction(GIXRD). After a perovskite film is exposed to the environment with a relative humidity of 60%±2%, a new component emerges near the perovskite(110) diffraction peak in the early stage of the exposure, which is observed for the first time. This new component is attributed to the perovskite intermediate phase structure transformed from the gradual degradation of the perovskite crystalline. Meanwhile, UV-Vis absorption measurements show that humidity causes the absorption of the film to decrease slightly with the blue shift of the absorption edge at ~770 nm, which indicates a reduced amount of perovskite crystalline or a decrease of perovskite crystallinity. Scan electron microscope further demonstrates that the film after the humid exposure presents a worse morphology with a lower coverage, bigger pores, and larger voids between crystalline than the pristine film. The current-voltage(J-V) measurements of the solar cells fabricated on the perovskite films before and after the humid exposure show that both the filling factor and the power conversion efficiencydecrease by over 30% due to the humidity. The present work demonstrates that the close relationship between the device performance and the perovskite film microstructure as well as their morphologies can be studied very well by in-situ synchrotron based characterization technique. The present study could lay a good foundation for the understanding of the degradation mechanism for the organic metal halide perovskites.

A second parallel CCD (CMOS) imaging system for an telescope objective with the fixed D/f' is proposed in detail. As a direct imaging system that the CCD target surface coincides with the imaging surface of the telescope objective, it shows the outstanding performance of more than doubled resolution compared with the ordinary telescope objective under the same D/f'. Based on the discussions about the second parallel optical path telescope system, three design examples are compared and analyzed. The relation between the optical properties of image field and the optical elements of the second parallel path is clarified, which provides an operable method for readers. This practice has proved the outstanding performance of the new telescope objective photoelectronic imaging system which indicates potential applications in broad scientific and industrial prospects.

In this paper, we propose a decomposition approach for eigenvalue problems with spatial symmetries, including the formulation, discretization as well as implementation. This approach can handle eigenvalue problems with either Abelian or non-Abelian symmetries, and is friendly for grid-based discretizations such as finite difference, finite element or finite volume methods. With the formulation, we divide the original eigenvalue problem into a set of subproblems and require only a smaller number of eigenpairs for each subproblem. We implement the decomposition approach with finite elements and parallelize our code in two levels. We show that the decomposition approach can improve the efficiency and scalability of iterative diagonalization. In particular, we apply the approach to solving Kohn--Sham equations of symmetric molecules consisting of hundreds of atoms., Comment: revised presentation in Section 1, results unchanged; Section 2.3 (an illustrative example) added; Section 3.2 divided into two sections for a more clear presentation; Figure 3 added in Section 6.1; Figure 5 added in Appendix A; modified references

Considering constructional algorithms for solving Traveling Salesman Problem (TSP), the solution process of Nearest Neighbor (NN) is the simplest one, but its performance is the worst. This paper proposes an improved NN algorithm for solving TSP in Euclidean Plane. Firstly, the algorithm searches four corner-nodes from all nodes, and gets a simple tour which only includes four corner-nodes, obtains four segments and their start nodes and end nodes, respectively. Then, each segment starts from current corner-node, and the algorithm selects a node as next target node from its multi-orientation nearest neighbor nodes, considering their distance and orientation comprehensively, and searching process repeatedly until each segment arrives at their end nodes. Furthermore, the algorithm inserts those rest nodes into a certain segment. At last, the algorithm connects four segments from stem to stern to form the final tour. Experimental results indicate that the proposed algorithm greatly improves the result of NN algorithm.

We study the initial state radiation process $e^+ e^-\to{J/\psi}+X+\gamma$ for $J/\psi$ production at B factory, and find the cross section is 61% larger than it's Born one for color octet part and is about half as it's Born one for color singlet part. Furthermore, the color singlet and color octet signal are very clearly separated in it's $E_\gamma$ spectra due to kinematics difference. We suggest to measure this $E_\gamma$ spectra at B factory to determine the color octet effect.

The secondary electron emission (SEE) yield of heterostructures of ZnO nanoneedles coaxially coated with AlN or GaN has been studied for the first time using electron, ion, and X‐ray beams. The SEE yield of the heterostructures is enhanced significantly by the intrinsic nanostructure of the ZnO nanoneedle templates as compared to the AlN and GaN thin films on Si substrates. These findings open up a way to develop new universal highly efficient radiation detectors based on the SEE principle by incorporating these one‐dimensional (1D) nanostructures as a material of choice.