Miracle-dz/UniFAR-FTUs huggingface dataset:
Toward a regional quantum description of the positronic systems: Primary considerations

This article presents the foundations of a regional quantum description of the positronic systems; molecules containing positron(s), the antielectron. It is demonstrated that by introducing a novel scalar function, called l-field, it is possible to construct a positronic local zero-flux equation. This equation is the basis of the topological analysis of the quantum structure as well as delineating the boundaries of the positronic subsystems, which are 3D regions with well-defined regional kinetic energies. Furthermore, the positronic subsystem hypervirial theorem is proposed, which yields the regional quantum theorems for the positronic subsystems. The regional virial, force, and continuity theorems are all derivable from the positronic subsystem hypervirial theorem. The primary computational considerations on LiH,e þ illustrate that the positronic zero-flux equation results to reasonable subsystems; that is, to 3D regions similar to those derived previously in purely electronic systems. The general approach proposed in this study is extendable to other exotic species and pave the way toward a unified regional description of these systems. V C 2010 Wiley Periodicals, Inc. Int J Quantum Chem 000:000-000, 2010
A Two-stage Algorithm Based on Prediction and Search for Maxk-Truss Decomposition

The cohesive subgraph K-truss is often used to detect communities in large-scale social networks. The truss decomposition algorithm calculates the number of triangles formed by each edge, then peels off the edges with the number of triangles less than k-2 iteratively. The incremental maxk-truss algorithm must detect k-truss one by one making it inefficient. We propose a two-stage maxk-ktruss decomposition algorithm PSKT. The innovation points of PSKT are as follows: 1) The k-core structure is used to predict the maxk value, and the structure helps us avoid unnecessary mass calculations. 2) The characteristic that the k-truss of graph G must be included in the (k-l)-core of graph G is utilized to ensure that the proposed algorithm can safely prune in the graph. 3) A suitable triangle counting algorithm and the dynamic stream compression method are used to improve the algorithm efficiency. Comprehensive experiments demonstrate that PSKT is 15.26 times faster than the incremental algorithm FMT-dec and 3 times faster than the state-of-the-art maxk-truss algorithm FMT-max.
Shadowing, rare events, and rubber bands. A variational Verlet algorithm for molecular dynamics

We present a variational implementation of the Verlet algorithm for molecular dynamics which is both conceptually and computationally attractive. Given an approximate path, this variational Verlet algorithm computes an actual trajectory close to the path. Instead of initial conditions, we specify end‐point conditions, which makes it possible to compute trajectories with fixed end points as well as trajectories that are exactly periodic (nonlinear modes of vibration). With a simple sign change, the method yields approximate reaction pathways. We present several applications which illustrate how this alternative approach to dynamics can yield unusual trajectories that are difficult to attain by conventional means. In our first model system, a simple double well, we examine the seemingly paradoxical shadowing lemma of classical mechanics which claims that, in spite of the cumulative numerical errors which cause rapid deviation from the correct path, a calculated trajectory can still be close to some true tra.
New methods of one-point measurement of pulse wave velocity

Conventional on-line methods of measuring pulse wave velocity (PWV) have mainly been based on "two-point" measurements. This work presents two methods by which "one-point" measurements can be made. The principle of the first method is to measure blood pressure and velocity at a point, and use the water-hammer equation for forward traveling waves. The principle of the second method is to derive PWV from a coefficient of elasticity of the artery. We applied the methods to the common carotid artery in 13 normal humans. The regression line of the PWV (m/s) obtained by the former method on the PWV (m/s) obtained by the latter method was y = 1.03x - 0.90 (R/sup 2/=0.83). Although regional PWV in the human carotid artery has not been reported so far, the correlation between the PWV's obtained by the present methods was so high that we are convinced of the validity of these methods.
Search for Supersymmetry in Trilepton Final States with the DØ Experiment

A search for supersymmetry in the trilepton final state is performed using the full dataset of the DO experiment. The analyzed data amounts to an integrated luminosity of ∫ℒ = 9.7 fb⁻¹ of pp collisions, produced at √s = 1.96 TeV at the Fermilab Tevatron collider. The studied process is the coproduction of charginos and neutralinos, decaying into a final state of three leptons and missing transverse energy. To increase efficiency, only two identified leptons (e, µ) and one additional isolated track are required per event. The QCD multijet background is estimated from data, while other backgrounds are modeled via Monte Carlo. After a series of background-reduction cuts, a multivariate analysis is performed using boosted decision trees (BDT). In the distribution of the BDT output, no excess of data over background is seen. Limits on the cross section are set for the mSUGRA (CMSSM) model, as well as for a scenario with non-universal gaugino masses.
A Two-dimensional Sail In Turbulent Flow

The two-dimensional, incompressible flow at Reynolds number based on chord length of 1.3. 106 around an inextensible, massless sail (flexible membrane airfoil) with varying excess length is examined solving the Reynolds-Averaged NavierStokes (RANS) equations on computational grids deforming according to the sail movement. The grid deformation is computed using the same numerical procedure solving the basic equations of displacements for an isotropic, linearly elastic continuum. Results are presented for fully turbulent conditions employing closure models of different degree of complexity in comparison with experimental and analytical results obtained from literature. The sail is modelled as a chain with frictionless hinges. Good agreement can be found for low angle of attack and small excess length. However, for higher angle of attack, approaching onset of separation and beyond, the predictive accuracy varies significantly with the representation of turbulence in conjunction with strong unsteady phenomena.
Statistical Process Control Methods for Monitoring In-House Reference Standards

For certain types of medicine the biological strength or bioactivity of a drug is the main characteristic for release of products to the market. A pharmaceutical company may decide to use their own in-house reference standard to test the drug instead of using the expensive international reference standard. The company is then legally obliged to verify that the in-house reference standard remains stable over time with respect to the international one. This is a special problem within statistical process control (SPC) since the monitoring period is relatively short and bioassays are typically heterogenous. The objective of this article is to apply methods from SPC and dose-finding studies to different study designs and assess how well these methods perform in detecting a decline in bioactivity. The included methods are the exponentially weighted moving average (EWMA), Shewhart chart, and analysis of variance (ANOVA)-type contrasts (linear, Helmert, and reverse-Helmert). An optimal α-spending function was selected first to avoid inflating the familywise error rate. The normal α-spending function seemed to perform generally the best. Then from the results, the linear, reverse-Helmert, and the EWMA (λ ⩽ 0.6) resulted in high power when a change occurred at earlier time points, while Helmert and the EWMA (λ > 0.6) performed better in later declines. Linear contrasts and the Shewhart chart performed better irrespective of the decline profile. Having more bioassay runs at the beginning of the stability study increased the probability of detecting a decline. If there is no prior information on the expected deterioration profile, linear contrasts or Shewhart chart should be preferred. Otherwise, reverse-Helmert or Helmert contrasts should be chosen for either early or late deterioration, respectively.
Influence of Dieback Disease on Soil Chemistry and Bacterial Diversity in the Rhizosphere of Mango Plants

Influence of dieback disease on the soil chemistry and the morphological, biochemical, and molecular characteristics of bacteria isolated from the rhizosphere of mango plants was studied. The soil samples collected from the rhizosphere of the healthy and dieback-affected mango plants were analyzed for their physicochemical parameters and biochemical characteristics of bacterial isolates. The dieback disease resulted in a significant decrease in pH, water holding capacity, organic matter, total nitrogen content, available phosphorus content, and available potassium content. The number of bacterial isolates showing oxidase production and lactose and sucrose fermentation was increased while the number of those showing urease and hydrogen sulphide production was decreased in the rhizosphere of diseased plants. The genus Bacillus showed maximum prevalence (97%) among the identified genera of rhizobacteria. Eight bacterial species were found to be absent and eight new species appeared in the rhizosphere of diseased plants. The study would be a significant contribution to the literature regarding the dieback mango disease and its relationship with soil composition and its microflora.
Proposal for predicting the facial brightening effect of cosmeceuticals using deep learning

The face of a subject who had been using cosmeceuticals for four years and eight months was photographed in ultraviolet light and RGB color. These images, including those taken before the use of the cosmetics, were subjected to deep learning using a neural network model referred to as pix2pix. It was demonstrated that it is possible to predict the effect of the cosmeceutical on the skin and generate images for new subjects using a trained neural network.
Wave Packets and Turbulent Jet Noise

Turbulent jet noise is a controversial fluid mechanical puzzle that has amused and bewildered researchers for more than half a century. Whereas numerical simulations are now capable of simultaneously predicting turbulence and its radiated sound, the theoretical framework that would guide noise-control efforts is incomplete. Wave packets are intermittent, advecting disturbances that are correlated over distances far exceeding the integral scales of turbulence. Their signatures are readily distinguished in the vortical, turbulent region; the irrotational, evanescent near field; and the propagating far field. We review evidence of the existence, energetics, dynamics, and acoustic efficiency of wave packets. We highlight how extensive data available from simulations and modern measurement techniques can be used to distill acoustically relevant turbulent motions. The evidence supports theories that seek to represent wave packets as instability waves, or more general modal solutions of the governing equations, and confirms the acoustic importance of these structures in the aft-angle radiation of high subsonic and supersonic jets. The resulting unified view of wave packets provides insights that can help guide control strategies.
Fast vector quantization by mean value predictive algorithm

Vector Quantization (VQ), is an efficient technique for signal compression. In traditional VQ, the major computation is on searching the nearest codeword of the codebook for every input vector. This paper presents an efficient search method to speed up the encoding process. The search algorithm is based on partial distance Elimination (PDE) and binary search is used to determine first search point. We sort the codebook by the mean value in pre-processing before all the practical compression. The first search point is the closest mean value between the input vector and the codewords in the codebook. Then, find the best match codeword by PDE to reduce the search time. The proposed algorithm demonstrates outstanding performance in terms of the time saving and arithmetic operations. Compared to full search algorithms, it saves more than 95% search time.
Fabrication of a chirped artificial compound eye for endoscopic imaging fiber bundle by dose-modulated laser lithography and subsequent thermal reflow

Abstract. A chirped artificial compound eye on a curved surface was fabricated using an optical resin and then mounted on the end of an endoscopic imaging fiber bundle. The focal length of each lenslet on the curved surface was variable to realize a flat focal plane, which matched the planar end surface of the fiber bundle. The variation of the focal length was obtained by using a photoresist mold formed by dose-modulated laser lithography and subsequent thermal reflow. The imaging performance of the fiber bundle was characterized by coupling with a coaxial light microscope, and the result demonstrated a larger field of view and better imaging quality than that of an artificial compound eye with a uniform focal length. Accordingly, this technology has potential application in stereoscopic endoscopy.
Mixed Residual Convolutions with Vision Transformer in Hyperspectral Image Classification

In recent years, deep learning methods represented by convolutional neural networks (CNN) have gradually become a research focus in the field of hyperspectral image classification (HSI). Although the proposed CNN-based methods have the advantages of spatial feature extraction, they are difficult to handle the spectral feature. We propose a mixed residual convolutions with Vision Transformer model (MRViT), which uses ViT Transformer (ViT) to overcome this limitation. First, using principal component analysis (PCA) and a channel shift strategy to construct a module to process HSI data. Then, a mixed residual convolution is constructed to extract spectral-spatial features. Finally, the important feature information is enhanced by the ViT model. In this paper, four datasets are used for experimental analysis, which confirms that the performance of MRViT model is superior to other HSI classification models. The research content of this paper enriches related research in HSI classification, and also provides certain reference value for subsequent research.
Entropy testing for nonlinear serial dependence in time series

We propose tests for nonlinear serial dependence in time series under the null hypothesis of general linear dependence, in contrast to the more widely studied null hypothesis of independence. The approach is based on combining an entropy dependence metric, which possesses many desirable properties and is used as a test statistic, with a suitable extension of surrogate data methods, a class of Monte Carlo distribution-free tests for nonlinearity, and a smoothed sieve bootstrap scheme. We show how, in the same way as the autocorrelation function is used for linear models, our tests can in principle be employed to detect the lags at which a significant nonlinear relationship is present. We prove the asymptotic validity of the proposed procedures and the corresponding inferences. The small-sample performance of the tests in terms of power and size is assessed through a simulation study. Applications to real datasets of different kinds are also presented.
Resource Allocation for D2D Underlaying Cellular Networks with Incomplete CSI

Device-to-device (D2D) communications support direct communications of users in proximity. It is a potential technology to improve the spectral efficiency and network capacity. Most researches on D2D resource allocation assume full Channel State Information (CSI). Considering the high overhead of obtaining full CSI, we investigate the resource allocation problem of D2D communications with incomplete CSI. Based on the Modulation and Coding Scheme (MCS), we first derive the closed-form expression of the rate selection probability with incomplete CSI by characterizing the unknown small-scale channel fading factor as Nakagami-m distribution. We then propose a bio-inspired power allocation and matching-based channel assignment strategy. Simulation results demonstrate that our algorithm outperforms the compared algorithms by achieving higher network capacities.
DOA-TDOA Hybrid Location Based on Weighted Least Squares with Observation Station Position Errors

Observation station position errors can significantly reduce the performance of the positioning algorithm. For DOA-TDOA hybrid positioning, this paper proposed a closed-form algorithm to jointly estimate the source and stations with station position errors. The method has two stages. At each stage, the pseudo-linear equation is first established, then the error equation is obtained, and finally the least squares solution of the error equation is obtained. Then, the algorithm is extended to multiple disjoint sources to get higher localization accuracy. The theoretical analysis shows that the accuracy of the source and stations can reach the Cramér-Rao lower bound (CRLB). Finally, the above theoretical analysis is proved by simulations.
pH Effect on the Structure, Rheology, and Electrospinning of Maize Zein

As a simple and convenient technology to fabricate micron-to-nanoscale fibers with controllable structure, electrostatic spinning has produced fiber films with many natural advantages, including a large specific surface area and high porosity. Maize zein, as a major storage protein in corn, showed high hydrophobicity and has been successfully applied as a promising carrier for encapsulation and controlled release in the pharmaceutical and food areas. Proteins exhibit different physical and chemical properties at different pH values, and it is worth investigating whether this change in physical and chemical properties affects the properties of electrospun fiber films. We studied the pH effects on zein solution rheology, fiber morphology, and film properties. Rotational rheometers were used to test the rheology of the solutions and establish a correlation between solution concentration and fiber morphology. The critical concentrations calculated by the cross-equation fitting model were 17.6%, 20.1%, 20.1%, 17.1%, and 19.5% (w/v) for pH 4, 5, 6, 7, and 8, respectively. The secondary structure of zein changed with the variation in solution pH. Furthermore, we analyzed the physical properties of the zein films. The contact angles of the fiber membranes prepared with different pH spinning solutions were all above 100, while zein films formed by solvent evaporation showed hydrophilic properties. The results indicated that the rheological properties of zein solutions and the surface properties of the film were affected by the pH value. This study showed that zein solutions can be stabilized to form electrospun fibers at a variety of pH levels and offered new opportunities to further enhance the encapsulation activity of zein films for bioactive materials.
The Survival Outcomes, Prognostic Factors and Adverse Events following Systemic Chemotherapy Treatment in Bone Sarcomas: A Retrospective Observational Study from the Experience of the Cancer Referral Center in Northern Thailand

Simple Summary Overall survival for osteosarcoma and Ewing’s sarcoma has been improved since the introduction of multi-agent chemotherapy. However, there has been variability in the chemotherapy regimens for both bone sarcomas. The present study describes chemotherapy regimens being prescribed in a tertiary cancer center in Thailand and identifies prognostic factors for survival outcomes. Chemotherapy regimens for osteosarcoma vary, with the two-drug regimens (i.e., Cisplatin plus Doxorubicin and Ifosfamide plus Doxorubicin) being commonly used. The regimen for Ewing’s sarcoma was rather well established, with Cyclophosphamide plus Vincristine plus Doxorubicin alternating with Ifosfamide plus Etoposide being the most commonly used one. Response to neoadjuvant therapy and female gender may be predictive of favorable outcomes in resectable osteosarcoma. Abstract This study aimed to assess survival outcomes, prognostic factors, and adverse events following chemotherapy treatment for osteosarcoma and Ewing’s sarcoma. This retrospective observational study was conducted to collect the data of the patients with osteosarcoma or Ewing’s sarcoma who received chemotherapy treatment between 2008 and 2019. The flexible parametric survival model was performed to explore the adjusted survival probability and the prognostic factors. A total of 102 patients (79 with osteosarcoma and 23 with Ewing’s sarcoma) were included. The estimated 5-year disease-free survival (DFS) and 5-year overall survival (OS) probabilities in patients with resectable disease were 60.9% and 63.3% for osteosarcoma, and 54.4% and 88.3% for Ewing’s sarcoma, respectively, whereas the 5-year DFS and 5-year OS for those with unresectable/metastatic disease remained below 25%. Two prognostic factors for osteosarcoma included a response to neoadjuvant chemotherapy and female gender. Ewing’s sarcoma patients aged 25 years and older were significantly associated with poorer survival outcomes. Of 181 chemotherapy treatment cycles, common self-reported adverse symptoms included tumor pain (n = 32, 17.7%), fever (n = 21, 11.6%), and fatigue (n = 16, 8.8%), while common grade III adverse events included febrile neutropenia (n = 13, 7.3%) and neutropenia (n = 9, 5.1%). There was no chemotherapy-related mortality (grade V) or anaphylaxis events.
Aerodynamic emulation analysis of bionic bat micro flapping-wing aircraft

In this paper, we simulate and analyze a bionic bat micro flapping-wing aircraft aerodynamic by using the finite element analysis method of ANSYS. It is concluded that when the pitch angle is 0°, the lift of the micro flapping-wing aircraft is the smallest. According to the fitting curve based on the simulation data, when the wind speed is 5.8m/s, the maximum lift is 0.000932N. In addition, the flapping-wing aircraft can obtain positive lift with a downward position, and negative lift with an upward position. Under the same wind speed, the lift change rate caused by the same angle of attack change gradient will also change significantly.
Effective Surface Impedance for a Superconductor-Semiconductor Superlattice at Mid-Infrared Frequency

The effective surface impedance for a superconductor-semiconductor superlattice at mid-infrared frequency is calculated based on the transfer matrix method together with the enhanced two-fluid model for the high-temperature superconductor. We first investigate the effective surface resistance and surface reactance in the case of normal incidence. We find that there is a critical thickness for superconductor film such that a minimum loss is attained. We next study the effective surface impedance under the oblique incidence. The calculated effective surface impedance indicates that the angle-dependent feature is only seen for the single period. However, it does not rely on the number of periods when the period is greater than two and, in the meantime, the surface resistance is nearly unchanged as a function of the angle of incidence.