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The detection of heterogeneous mental disorders based on brain readouts remains challenging due to the complexity of symptoms and the absence of reliable biomarkers. This paper introduces CAM (Cortical Anomaly Detection through Masked Image Modeling), a novel self-supervised framework designed for the unsupervised detection of complex brain disorders using cortical surface features. We employ this framework for the detection of individuals on the psychotic spectrum and demonstrate its capabilities compared to state-of-the-art methods, achieving an AUC of 0.696 for Schizoaffective and 0.769 for Schizophreniform, without the need for any labels. Furthermore, the analysis of atypical cortical regions, including Pars Triangularis and several frontal areas often implicated in schizophrenia, provides further confidence in our approach. Altogether, we demonstrate a scalable approach for anomaly detection of complex brain disorders based on cortical abnormalities. The code will be made available at https://github.com/chadHGY/CAM., Comment: 5 pages, LaTeX; typos corrected, introduction refined

We consider the quasi Hermitian limit of a non-Hermitian extended Su Schrieffer Heeger model, in which the hopping amplitudes obey a specific relation so that the system may be mapped to a corresponding Hermitian one and its energy spectrum is completely real. Analogous to the Hermitian case, one may use the modified winding number to determine the total number of edge states on the boundaries to achieve a modified bulk-boundary correspondence. Due to the skin effect in nonHermitian systems, the spectral winding numbers must be used to classify such systems further. It dictates how the edge states would be distributed over the left and right boundaries. We then naively extend the criteria to the cases that the quasi Hermitian condition is violated. For all the cases that we consider, no inconsistency has been found., Comment: 21 pages, 10 figures

The discovery of superconductivity in CaC6 with a critical temperature (Tc) of 11.5 K reignites much interest in exploring high-temperature superconductivity in graphite intercalation compounds (GICs). Here we identify a GIC NaC4, discovered by ab initio evolutionary structure search, as a superconductor with a computed Tc of 41.2 K at 5 GPa. This value is eight times higher than that of the synthesized GIC NaC2 and possesses the highest Tc among available GICs. The remarkable superconductivity of GIC NaC4 mainly arises from the coupling of {\pi} electrons in graphene with the low-frequency vibrations involving both Na and C atoms. These findings suggest that Na-GICs may hold great promise as high-Tc superconductors., Comment: 4 figures

The ability to accurately detect onset of dementia is important in the treatment of the disease. Clinically, the diagnosis of Alzheimer Disease (AD) and Mild Cognitive Impairment (MCI) patients are based on an integrated assessment of psychological tests and brain imaging such as positron emission tomography (PET) and anatomical magnetic resonance imaging (MRI). In this work using two different datasets, we propose a behavior score-embedded encoder network (BSEN) that integrates regularly adminstrated psychological tests information into the encoding procedure of representing subject's restingstate fMRI data for automatic classification tasks. BSEN is based on a 3D convolutional autoencoder structure with contrastive loss jointly optimized using behavior scores from MiniMental State Examination (MMSE) and Clinical Dementia Rating (CDR). Our proposed classification framework of using BSEN achieved an overall recognition accuracy of 59.44% (3-class classification: AD, MCI and Healthy Control), and we further extracted the most discriminative regions between healthy control (HC) and AD patients., Comment: 4 pages, 1 figure

Helium (He) is the most inert noble gas at ambient conditions. It adopts a hexagonal close packed structure (P63/mmc) and remains in the insulating phase up to 32 TPa. In contrast, lithium (Li) is one of the most reactive metals at zero pressure, while its cubic high-pressure phase (Fd-3m) is a weak metallic electride above 475 GPa. Strikingly, a stable compound of Li5He2 (R-3m) was formed by mixing Fd-3m Li with P63/mmc He above 700 GPa. The presence of helium promotes the lattice transformation from Fd-3m Li to Pm-3m Li, and tuns the three-dimensional distributed interstitial electrons into the mixture of zero- and two-dimensional anionic electrons. This significantly increases the degree of metallization at the Fermi level, consequently, the coupling of conductive anionic electrons with the Li-dominated vibrations is the key factor to the formation of superconducting electride Li5He2 with a transition temperature up to 26 K, dynamically stable to pressures down to 210 GPa., Comment: 5 pages, 3 figures

Electrocardiogram(ECG) is commonly used to detect cardiac irregularities such as atrial fibrillation, bradycardia, and other irregular complexes. While previous studies have achieved great accomplishment classifying these irregularities with standard 12-lead ECGs, there existed limited evidence demonstrating the utility of reduced-lead ECGs in capturing a wide-range of diagnostic information. In addition, classification model's generalizability across multiple recording sources also remained uncovered. As part of the PhysioNet Computing in Cardiology Challenge 2021, our team HaoWan AIeC, proposed Mixed-Domain Self-Attention Resnet (MDARsn) to identify cardiac abnormalities from reduced-lead ECG. Our classifiers received scores of 0.602, 0.593, 0.597, 0.591, and 0.589 (ranked 54th, 37th, 38th, 38th, and 39th) for the 12-lead, 6-lead, 4-lead, 3-lead, and 2-lead versions of the hidden validation set with the evaluation metric defined by the challenge.

Limited energy resources and sensor nodes adaptability with the surrounding environment play a significant role in the sustainable Wireless Sensor Networks. This paper proposes a novel, dynamic, self-organizing opportunistic clustering using Hesitant Fuzzy Linguistic Term Analysis-based Multi-Criteria Decision Modeling methodology in order to overcome the CH decision making problems and network lifetime bottlenecks. The asynchronous sleep/awake cycle strategy could be exploited to make an opportunistic connection between sensor nodes using opportunistic connection random graph. Every node in the network observe the node gain degree, energy welfare, relative thermal entropy, link connectivity, expected optimal hop, link quality factor etc. to form the criteria for Hesitant Fuzzy Linguistic Term Set. It makes the node to evaluate its current state and make the decision about the required action (CH, CM or relay). The simulation results reveal that our proposed scheme leads to an improvement in network lifetime, packet delivery ratio and overall energy consumption against existing benchmarks., Comment: 10 pages, 5 figures, International Conference on Networks and Communications (NETWORKS 2021)

Natural convection in porous media is a fundamental process for the long-term storage of CO2 in deep saline aquifers. Typically, details of mass transfer in porous media are inferred from the numerical solution of the volume-averaged Darcy-Oberbeck-Boussinesq (DOB) equations, even though these equations do not account for the microscopic properties of a porous medium. According to the DOB equations, natural convection in a porous medium is uniquely determined by the Rayleigh number. However, in contrast with experiments, DOB simulations yield a linear scaling of the Sherwood number with the Rayleigh number (Ra) for high values of Ra (Ra>>1,300). Here, we perform Direct Numerical Simulations (DNS), fully resolving the flow field within the pores. We show that the boundary layer thickness is determined by the pore size instead of the Rayleigh number, as previously assumed. The mega- and proto- plume sizes increase with the pore size. Our DNS results exhibit a nonlinear scaling of the Sherwood number at high porosity, and for the same Rayleigh number, higher Sherwood numbers are predicted by DNS at lower porosities. It can be concluded that the scaling of the Sherwood number depends on the porosity and the pore-scale parameters, which is consistent with experimental studies.

We study the pair production of charged scalar particles from the five-dimensional near extremal Reissner- Nordstr\"om-Anti de Sitter (RN-AdS5) black hole. The pair production rate and the absorption cross section ratio in the full spacetime are obtained and are shown to have proportional relation with their counterparts in the near horizon region. In addition, the holographic descriptions of the pair production both in the IR CFT in the near horizon region and the UV CFT at the asymptotic spatial boundary of the RN-AdS5 black hole are analyzed in the AdS2/CFT1and AdS5/CFT4correspondences, respectively. This work gives a complete description of scalar pair production in the near extremal RN-AdS5black hole., Comment: 23pages, no figures

Langevin dynamics simulations are performed to investigate ejection dynamics of spherically confined flexible polymers through a pore. By varying the chain length $N$ and the initial volume fraction $\phi_0$ of the monomers, two scaling behaviors for the ejection velocity $v$ on the monomer number $m$ in the cavity are obtained: $v \sim m^{1.25}\phi_0^{1.25}/N^{1.6}$ for large $m$ and $v \sim m^{-1.4}$ as $m$ is small. A robust scaling theory is developed by dividing the process into the confined and the non-confined stages, and the dynamical equation is derived via the study of energy dissipation. After trimming the prior stage related to the escape of the head monomer across the pore, the evolution of $m$ is shown to be well described by the scaling theory. The ejection time exhibits two proper scaling behaviors: $N^{2/(3\nu)+y_1}\phi_0^{-2/(3\nu)}$ and $N^{2+y_2}$ under the large and small $\phi_0$- or $N$-conditions, respectively, where $y_1=1/3$, $y_2=1-\nu$, and $\nu$ is the Flory exponent., Comment: 5 pages, 5 figures, accepted for publication in PRL

This paper proposes a deep cerebellar model articulation controller (DCMAC) for adaptive noise cancellation (ANC). We expand upon the conventional CMAC by stacking sin-gle-layer CMAC models into multiple layers to form a DCMAC model and derive a modified backpropagation training algorithm to learn the DCMAC parameters. Com-pared with conventional CMAC, the DCMAC can characterize nonlinear transformations more effectively because of its deep structure. Experimental results confirm that the pro-posed DCMAC model outperforms the CMAC in terms of residual noise in an ANC task, showing that DCMAC provides enhanced modeling capability based on channel characteristics.

In recent years, various doping methods for epitaxial graphene have been demonstrated through atom substitution and adsorption. Here we observe by angle-resolved photoemission spectroscopy (ARPES) a coupling-induced Dirac cone renormalization when depositing small amounts of Ti onto epitaxial graphene on SiC. We obtain a remarkably high doping efficiency and a readily tunable carrier velocity simply by changing the amount of deposited Ti. First-principles theoretical calculations show that a strong lateral (non-vertical) orbital coupling leads to an efficient doping of graphene by hybridizing the 2pz orbital of graphene and the 3d orbitals of the Ti adsorbate, which attached on graphene without creating any trap/scattering states. This Ti-induced hybridization is adsorbate-specific and has major consequences for efficient doping as well as applications towards adsorbate-induced modification of carrier transport in graphene., Comment: 24 pages, 4 figures

The electronic properties of hydrogenated graphenes are investigated with the first-principles calculations. Geometric structures, energy bands, charge distributions, and density of states (DOS) strongly depend on the different configurations and concentrations of hydrogen adatoms. Among three types of optimized periodical configurations, only in the zigzag systems the band gaps can be remarkably modulated by H-concentrations. There exist middle-gap semiconductors, narrow-gap semiconductors, and gapless systems. The band structures exhibit the rich features, including the destruction or recovery of the Dirac-cone structure, newly formed critical points, weakly dispersive bands, and (C,H)-related partially flat bands. The orbital-projected DOS are evidenced by the low-energy prominent peaks, delta-function-like peaks, discontinuous shoulders, and logarithmically divergent peaks. The DOS and spatial charge distributions clearly indicate that the critical bondings in C-C and C-H is responsible for the diversified properties.

A single-walled carbon nanotube presents a seamless cylindrical graphene surface and is thus an ideal adsorption substrate for investigating the physics of atoms and molecules in two dimensions and approaching the one-dimensional limit. When a suspended nanotube is made into a transistor, frequency shifts of its mechanical resonances allow precise measurement of the adsorbed mass down to the single-atom level. Here we show that its electrical characteristics are also modified by the adsorbed atoms and molecules, partly as a result of a small charge transfer between them and the carbon surface. We quantify this charge transfer, finding it similar for many different species, and use the associated sensitivity of the conductance to carry out studies of phase transitions, critical scaling, dynamical fluctuations, and dissipative metastable states in a system of interacting atoms confined to a cylindrical geometry., Comment: 12 pages main text including 8 figures; 8 pages of supplementary material appended

We reexamine a recent result within a nonrelativistic constituent quark model (NRCQM) which maintains that the uuds\bar s component in the proton has its uuds subsystem in P state, with its \bar s in S state (configuration I). When the result are corrected, contrary to the previous result, we find that all the empirical signs of the form factors data can be described by the lowest-lying uuds\bar s configuration with \bar s in P state that has its uuds subsystem in $S$ state (configuration II). Further, it is also found that the removal of the center-of-mass (CM) motion of the clusters will enhance the contributions of the transition current considerably. We also show that a reasonable description of the existing form factors data can be obtained with a very small probability P_{s\bar s}=0.025% for the uuds\bar s component. We further see that the agreement of our prediction with the data for G_A^s at low-q^2 region can be markedly improved by a small admixture of configuration I. It is also found that by not removing CM motion, P_{s\bar s} would be overestimated by about a factor of four in the case when transition dominates over direct currents. Then, we also study the consequence of a recent estimate reached from analyzing the existing data on quark distributions that P_{s\bar s} lies between 2.4-2.9% which would lead to a large size for the five-quark (5q) system, as well as a small bump in both G^s_E+\eta G^s_M and G^s_E in the region of q^2 =< 0.1 GeV^2., Comment: Prepared for The Fifth Asia-Pacific Conference on Few-Body Problems in Physics 2011 in Seoul, South Korea, 22-26 August 2011

We reexamine, within the nonrelativistic constituent quark model (NRCQM), a recent claim that the current data on the strangeness form factors indicates that the uuds\bar{s} component in the proton is such that the uuds subsystem has the mixed spatial symmetry [31]_X and flavor spin symmetry [4]_{FS}[22]_F[22]_S, with \bar{s} in S state (configuration I). We find this claim to be invalid if corrected expressions for the contributions of the transition current to G_A^s and G_E^s are used. We show that, instead, it is the lowest-lying uuds\bar{s} configuration with uuds subsystem of completely symmetric spatial symmetry [4]_X and flavor spin symmetry [4]_{FS}[22]_F[22]_S, with \bar{s} in P state (configuration II), which could account for the empirical signs of all form factors G_E^s, G_M^s, and G_A^s. Further, we find that removing the center-of-mass motion of the clusters will considerably enhance the contributions of the transition current. We also demonstrate that it is possible to give a reasonable description of the existing form factors data with a tiny probability P_{s\bar{s}}=0.025% for the uuds\bar{s} component. We further see that with a small admixture of configuration I, the agreement of our prediction with data for G_A^s at low-q^2 region can be markedly improved. We find that without removing CM motion, P_{s\bar{s}} would be overestimated by about a factor of four in the case when transition current dominates. We also explore the consequence of a recent estimate reached from analyzing existing data on \bar{d} -\bar{u}, s +\bar{s}, and \bar{u} + \bar{d} - s -\bar{s}, that P_{s\bar{s}} lies between 2.4-2.9%. It would lead to a large size for the five-quark system and a small bump in both G_E^s+\eta G_M^s and G_E^s in the region of q^2<=0.1 GeV^2 within the considered model., Comment: 6 pages, 2 figures