Miracle-dz/UniFAR-FTUs huggingface dataset:
Polar nanoregions and dielectric properties in high-strain lead-free 0.93(Bi1/2Na1/2)TiO3-0.07BaTiO3 piezoelectric single crystals

A structural coexistence of rhombohedral (R) and tetragonal (T) phases has been revealed in the (001)c-cut lead-free 0.93(Bi1/2Na1/2)TiO3–0.07BaTiO3 (BNB7T) piezoelectric crystals, which grown by the self-flux method, in the lower temperatures by high-resolution synchrotron X-ray diffraction, reciprocal space mapping, and transmission electron microscopy. The dielectric permittivity exhibits a thermal hysteresis in the region of 120–260 °C, implying a first-order-like phase transition from R+T to T. The real part (e′) of dielectric permittivity begins to deviates from the Curie-Weiss equation, e′ = C/(T − To), from the Burns temperature TB = 460 °C, below which the polar nanoregions (or nanoclusters) develop and attenuate dielectric responses. The polar nanoregions of 5–10 nm were revealed by high-resolution transmission electron microscope. The normal piezoelectric coefficient d33 exhibits a rapid increase at E = 15–20 kV/cm and reaches a maximum of d33 ∼450 pC/N. The high piezoelectric response and E-fi.
A Novel Kernel Matrix Isomap Algorithm Based on Partial Least Squares

In this paper, to alleviate the influence of the noise the inaccurate measurement in the complicated environment, based on the robust ability in multivariate linear regression of PLS, and in combination with nonlinear data dimension reduction of manifold learning, a novel kernel matrix Isomap algorithm is proposed. The contribution rate is used to find and delete the “short circuit” edge. The matrix constructed by double centered transformation and kernel transformation trick is mapped to a high dimensional feature space, finally the relative position is obtained by PLS. Compared with traditional Isomap and MDS, simulation results indicate that the algorithm has good topology stability, generalization property, robustness and lower computational complexity
The System ESO 296-IG11

We present photometric and spectroscopic observations of the system ESO 296-IG11, which is composed of two galaxies, as well as observations of a small galaxy 1. ′3 distant. Colors through the entire system show little variation and reflect the presence of about the same young stellar composition. The quite blue colors of the observed regions in both galaxies of the system indicate star formation activity, and the distribution of the regions through the bodies of the galaxies suggests that a quite generalized starburst has taken place. The spectra of these regions are characteristic of H II regions of comparatively high excitation; their oxygen and nitrogen abundances are low, and their N(N)/N(O) ratios are comparable to those of the Magellanic Clouds and late spiral galaxies. The low abundances of the regions would be consistent with the ages derived for the bursts of star formation in their interiors. The high equivalent widths of the Hα + [N II] emission lines of the integrated spectra of both galaxies indicate enhanced star formation rates compared with isolated galaxies and are compatible with those observed in mergers of two disk galaxies. The velocities indicate that the two galaxies are a physical pair and that they are linked with the small nearby galaxy. The derived information suggests that ESO 296-IG11 is composed of two advanced late-type galaxies with similar general properties, which, together with the small nearby galaxy, constitute a triple system.
A hierarchical Bayesian model for improving short‐term forecasting of hospital demand by including meteorological information

The effect of weather on health has been widely researched, and the ability to forecast meteorological events can offer valuable insights into the effect on public health services. In addition, better predictions of hospital demand that are more sensitive to fluctuations in weather can allow hospital administrators to optimize resource allocation and service delivery. Using historical hospital admission data and several seasonal and meteorological variables for a site near the hospital, the paper develops a novel Bayesian model for short‐term prediction of the numbers of admissions categorized by several factors such as age group and sex. The model proposed is extended by incorporating the inherent uncertainty in the meteorological forecasts into the predictions for the number of admissions. The methods are illustrated with admissions data obtained from two moderately large hospital trusts in Cardiff and Southampton, in the UK, each admitting about 30000–50000 non‐elective patients every year. The Bayesian model, computed by using Markov chain Monte Carlo methods, is shown to produce more accurate predictions of the number of hospital admissions than those obtained by using a 6‐week moving average method which is similar to that widely used by hospital managers. The gains are shown to be substantial during periods of rapid temperature changes, typically during the onset of cold and highly variable winter weather.
Air-stable inverted flexible polymer solar cells using zinc oxide nanoparticles as an electron selective layer

The performance and stability of unencapsulated inverted bulk-heterojunction solar cells with zinc oxide (ZnO) made by different processes as the electron selective contact are compared to conventional bulk-heterojunction solar cells. The low temperature processed inverted devices using ZnO nanoparticles on indium tin oxide plastic substrates showed high power conversion efficiency of ∼3.3%. This inverted device structure possessed much better stability under ambient conditions retaining over 80% of its original conversion efficiency after 40days while the conventional one showed negligible photovoltaic activity after 4days. This is due to the improved stability at the poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate)/Ag interface.
An improved meshless collocation method for elastostatic and elastodynamic problems

Meshless methods for solving differential equations have become a promising alternative to the finite element and boundary element methods. In this paper, an improved meshless collocation method is presented for use with either moving least square (MLS) or compactly supported radial basis functions (RBFs). A new technique referred to as an indirect derivative method is developed and compared with the direct derivative technique used for evaluation of second-order derivatives and higher-order derivatives of the MLS and RBF shape functions at the field point. As the derivatives are obtained from a local approximation (MLS or compact support RBFs), the new method is computationally economical and efficient. Neither the connectivity of mesh in the domain/boundary nor integrations with fundamental/particular solutions is required in this approach. The accuracy of the two techniques to determine the second-order derivative of shape function is assessed. The applications of meshless method to two-dimensional elastostatic and elastodynamic problems have been presented and comparisons have been made with benchmark analytical solutions. Copyright © 2007 John Wiley & Sons, Ltd.
Effect of (2 × 1) Surface Reconstruction on Elasticity of a Silicon Nano-Plate

A semi-continuum approach is developed to describe the effect of (2 × 1) surface reconstruction on the elastic modulus of the silicon nano-plate. Young's moduli of a (001) silicon nano-plate along the high-symmetry [100] direction are obtained with and without considering (2 × 1) surface reconstruction. The approach predicts that the nano-plate with unreconstructed (001) surface is elastically softer than the bulk while it exhibits the opposite behaviour with (2 × 1) reconstructed surface. On the (001) surface, the (2 × 1) reconstructed surface dominates the plate as the thickness of the plate scaling decreases to several tens of nanometre. Whether the nano-plate is softer or stiffer depends on bond loss, bond saturation and direction of bond alignment, which have major impacts on the mechanics of the nano-plate.
Adjoint groups, regular unipotent elements and discrete series characters

It is shown that if G is a finite Chevalley group or twisted type over a field of characteristic p and U is a maximal p-subgroup of G then any nonlinear irreducible character of U vanishes on regular elements. For groups of adjoint type the linear content of the restriction to U of a discrete series character J of G is calculated and it is deduced that J takes the value 0 or (_1)s on regular elements of U (s = rank G). Introduction. This work is concemed primarily with the complex representation theory of finite algebraic groups, although the methods of proof utilise results from algebraic group theory over algebraically closed fields. Two main results are proved: the first is that under appropriate conditions, all nonlinear irreducible characters of the finite unipotent group U vanish on regular unipotent elements (for the definition see next section). This generalizes the result proved in [7] for the unitriangular group. The second result is that if G is one of the finite groups under consideration (e.g. a finite adjoint Chevalley group or twisted type) and J is an irreducible discrete series character of G, then the restriction of J to U (a maximal unipotent subgroup) has linear content which is zero or consists precisely of the sum of all the regular linear characters of U, each occurring with multiplicity one. The notion of a regular linear character of U was first introduced by Gel'fand and Graev [5] and was translated by the words "general aspect". These two results hold in particular for the classical linear groups and twisted types and enable one to deduce that the value of an irreducible discrete series character J of such a group on a regular unipotent element is 0 or ? 1. Also if G is a linear group over GF(q) then the degree of J is 0 or ? 1 mod p, where q = pa. The point of view adopted is to realise G as the group of fixed points of an endomorphism a of the semisimple adjoint group G. The first result (concerning the vanishing of nonlinear characters on regular unipotent elements) is idependent of which group in the isogeny class of G is chosen, since the finite unipotent subgroups are the same in each case. However the second result (concerning the value of J) depends essentially on G being adjoint, as it is necessary to examine the Received by the editors October 8, 1974. AMS(MOS)subject classifications (1970). Primary 20G40, 20C15; Secondary 22E45. 249 Copyiight () 1975, American Mathematical Society This content downloaded from 157.55. 39.104 on Sun, 19 Jun 2016 05:48:06 UTC All use subject to http://about.jstor. org/terms
Tsukamoto Fuzzy Inference System on Internet of Things-Based for Room Temperature and Humidity Control

The idea of the Internet of Things (IoT) is utilized to increase the advantages of internet connectivity. As long as the electrical device is still connected to the internet, IoT can be utilized to operate it. This study applies the concept of IoT as a fan control and monitoring of the humidity and room temperature through a mobile-based application, so that the room can be controlled remotely using a smartphone before use. It is necessary to always keep the room comfortable to use, so that users can increase productivity and always avoid potential disease attacks when the temperature is unstable. In addition, the IoT concept also makes it easier to turn off the fan if at any time you forget to turn it off. This fan is integrated with the ESP32 microcontroller which has been equipped with a Wireless Fidelity (WiFi) module to access data changes in the Firebase Realtime Database. Room temperature and humidity are measured with a DHT22 sensor and processed using Tsukamoto’s Fuzzy Inference System to produce the appropriate fan speed in the Duty Cycle unit. Tools and applications can work as predicted based on the findings of the research conducted. However, the impact of the fan on a closed room cannot cool the room temperature but the room temperature moves up with a change of 0.3 °C to 0.5 °C within 40–75 minutes. Therefore, in the next study it is recommended to use cooling devices such as Exhaust fans or Air Conditioners.
A boundary-volume integral equation method for the analysis of wave scattering

A method for the analysis of wave scattering in 3-D elastic full space is developed by means of the coupled boundary-volume integral equation, which takes into account the effects of both the boundary of inclusions and the uctuation of the wave field. The wavenumber domain formulation is used to construct the Krylov subspace by means of FFT. In order to achieve the wavenumber domain formulation, the boundary-volume integral equation is transformed into the volume integral equation. The formulation is also focused on this transform and its numerical implementation. Several numerical results clarify the accuracy and effectiveness of the present method for scattering analysis.
Review of Neurofilaments as Biomarkers in Sepsis-Associated Encephalopathy

Abstract Sepsis is a common and fatal disease, especially in critically ill patients. Sepsis-associated encephalopathy (SAE) is a diffuse brain dysfunction with acute altered consciousness, permanent cognitive impairment, and even coma, accompanied by sepsis, without direct central nervous system infection. When managing SAE, early identification and quantification of axonal damage facilitate faster and more accurate diagnosis and prognosis. Although no specific markers for SAE have been identified, several biomarkers have been proposed. Neurofilament light chain (NFL) is a highly expressed cytoskeletal component of neurofilament (NF) proteins that can be found in blood and cerebrospinal fluid (CSF) after exposure to axonal injury. NFs can be used as diagnostic and prognostic biomarkers for sepsis-related brain injury. Phosphorylation of NFs contributes to the maturation and stabilization of cytoskeletal structures, especially axons, and facilitates axonal transport, including mitochondrial transport and energy transport. The stability of NF proteins can be assessed by monitoring the expression of NF genes. Furthermore, phosphorylation levels of NFs can be monitored to determine mitochondrial axonal transport associated with cellular energy metabolism at distal axons to assess progression during SAE treatment. This paper provides new insights into the biological characteristics, detection techniques, and scientific achievements of NFs, and discusses the underlying mechanisms and future research directions of NFs in SAE.
Analysis of the Magnetization-Induced Field Error in a Superconducting Bending Magnet for a Compact, Rapid-Cycling Heavy-Ion Synchrotron

An ongoing design study of a 90-degree superconducting bending magnet (SCBM) is being conducted for a compact, rapid-cycling heavy-ion synchrotron at the National Institutes for Quantum Science and Technology (QST). The SCBM is designed to generate a 3.5 T dipole field and a 1.5 T $\cdot$ m$^{-1}$ quadrupole field for bending and horizontally defocusing heavy-ion beams. Since a heavy-ion beam is injected into the synchrotron at the field of 0.3 T, and accelerated to 3.5 T in 5 s, and then it is extracted at the field range from 1.1 T to 3.5 T, field errors derived from the magnetization at such a ramp rate will cause instability of the beam during the acceleration. In this paper, the field errors derived from both the DC and the AC effects are analyzed with numerical models in two dimensions (2D). The DC effects from the screening current in the superconducting coil and iron hysteresis behavior are estimated by the nested ellipse model and the finite element method (FEM) coupled with an inverse Jiles-Atherton model. The AC effects from the eddy current generated in the thermal shield, the beam pipe and the thermal path are estimated by a transient FEM analysis and analytical method. The change of the field error due to the magnetization is estimated to be about 1 unit at the time of beam injection.
GNN-Based Hierarchical Annotation for Analog Circuits

Analog designs consist of multiple hierarchical functional blocks. Each block can be built using one of several design topologies, where the choice of topology is based on circuit performance requirements. A major challenge in automating analog design is in the identification of these functional blocks, which enables the creation of hierarchical netlist representations. This can facilitate a variety of design automation tasks, such as circuit layout optimization, because the layout is dictated by constraints at each level, such as symmetry requirements, that depend on the topology of the hierarchical block. Traditional graph-based methods find it hard to automatically identify the large number of structural variants of each block. To overcome this limitation, this article leverages recent advances in graph neural networks (GNNs). A variety of GNN strategies is used to identify netlist elements for circuit functional blocks at higher levels of the design hierarchy, where numerous design variants are possible. At lower levels of hierarchy, where the degrees of freedom in circuit topology is limited, structures are identified using graph-based algorithms. The proposed hierarchical recognition scheme enables the identification of layout constraints, such as symmetry and matching, which enable high-quality hierarchical layouts. This method is scalable across a wide range of analog designs. An experimental evaluation shows a high degree of accuracy over a wide range of analog designs, identifying functional blocks, such as low-noise amplifiers, operational transconductance amplifiers, mixers, oscillators, and band-pass filters, in larger circuits.
Graphene/ZnO nanowire/graphene vertical structure based fast-response ultraviolet photodetector

time, and recovery speed of our UV detectors are 8 � 10 2 , 0.7s, and 0.5s, respectively, which are significantly improved compared to the conventional ZnO NWs photodetectors. The improved performance is attributed to the existence of Schottky barriers between ZnO NW and graphene electrodes. The graphene/ZnO NW/graphene vertical sandwiched structures may be promising candidates for integrated optoelectronic sensor devices. V C 2012 American Institute of Physics. [http://dx.doi. org/10.1063/1.4724208] ZnO, as a wide direct band gap (3.37eV) compound semiconductor with large exciton binding energy (60meV), has been widely investigated for its potential applications in optoelectronic devices, gas and chemical sensors. 1,2 Due to large surface-to-volume ratio, ZnO nanowires (NWs) exhibit highly susceptible photoelectric properties by means of electron-hole generation or recombination during ultraviolet (UV) illumination. Therefore, ZnO NWs have great potential in high sensitivity and fast-response UV sensors, 3 environmental monitors, and optical communications. 4 Recently, Hu et al. 5 reported ZnO NW based UV sensors using Schottky contact formed between ZnO and Pt electrode and the device performance such as the sensitive and UV response, is much higher than that of the traditional ZnO NW photoconductivity based UV sensors. The UV detectors based on Schottky barriers formed between ZnO NW and other metal electrodes, such as gold electrodes, have also been studied. 6,7 Nevertheless, metal electrodes are poor in transparency and can dramatically influence the absorption efficiency of the UV sensors. Graphene, a monolayer sp 2 carbon atoms with unique physical properties, such as high mobility and conductivity, 8 high optical transparency 9 and mechanical flexibility, 10 etc., has attracted great research interest recently. The high conductive and optical transparent properties make graphene an ideal candidate for the application in transparent electrode. The Schottky barrier is also expected to be existed at the interface between ZnO nanowire and graphene, and it has been utilized for light-emitting diodes 11 and transparent nanogenerators. 12 In this letter, we have fabricated a vertical sandwich structure of graphene/ZnO NW/graphene. We demonstrate the high performance of our ZnO NW based vertical UV photodetector due to the existence of Schottky barriers between graphene electrodes and ZnO NW. The current on-off ratio of the UV detector is up to 8 � 10 2 at a illumination power density of 50lw/lm 2 , the photocurrent
Risk of Infective Endocarditis Associated with Transcatheter Aortic Valve Implantation versus Surgical Aortic Valve Replacement: A Propensity Score-Based Analysis

Background: Infective endocarditis (IE) is a feared complication after surgical aortic valve replacement (SAVR)/transcatheter aortic valve implantation (TAVI). It is not certain which procedure carries a higher risk. Our aim was to assess the risk of IE after SAVR/TAVI. Methods: We conducted an observational study of a prospective cohort, including patients with TAVI/SAVR, from March 2015 to December 2020. IE was defined according to the modified Duke’s criteria. IE occurring during the first 12 months of the procedure was considered early IE, and an episode occurring after 12 months was considered late IE. The propensity score was designed to include variables previously associated with TAVI/SAVR and IE. An inverse probability of treatment weight was generated. Results: In total, 355 SAVR and 278 TAVI were included. Median follow-up, 38 vs. 41 months, p = 0.550. IE occurred in 5 SAVR (1.41%, 95% CI 0.2–2.6) vs. 13 TAVI (4.65%, 95% CI 2.2–7.2), p = 0.016. TAVI patients had more frequent early IE (3.2% vs. 0.3%, p = 0.006). In the PS analyses, IE risk did not differ: OR 0.65, 95% CI 0.32–1.32. Factors associated with TAVI IE included younger age (74y vs. 83y, p = 0.030), complicated diabetes mellitus (38.5% vs. 6.8%, p = 0.002), COPD (46.2% vs. 16.3%, p = 0.015), advanced heart failure (100% vs. 52.9%, p < 0.001), and peripheral arteriopathy (61.5% vs. 26.7%, p = 0.011). Conclusions: Early IE was higher with TAVI, but in the PS analyses, the risk attributable to each procedure was similar. Studies are needed to identify and optimize the risk factors of IE prior to TAVI.
Attack Detection Availing Feature Discretion using Random Forest Classifier

The widespread use of the Internet has an adverse effect of being vulnerable to cyber attacks. Defensive mechanisms like firewalls and IDSs have evolved with a lot of research contributions happening in these areas. Machine learning techniques have been successfully used in these defense mechanisms especially IDSs. Although they are effective to some extent in identifying new patterns and variants of existing malicious patterns, many attacks are still left as undetected. The objective is to develop an algorithm for detecting malicious domains based on passive traffic measurements. In this paper, an anomaly-based intrusion detection system based on an ensemble based machine learning classifier called Random Forest with gradient boosting is deployed. NSL-KDD cup dataset is used for analysis and out of 41 features, 32 features were identified as significant using feature discretion. Our observations confirm the conjecture that both the feature selection and stochastic based genetic operators improves the accuracy and the effectiveness. The training time is shown to be reduced tremendously by 98.59% and accuracy improved to 98.75%.