Miracle-dz/UniFAR-FTUs huggingface dataset:
Convolutional Neural Network Based on Crossbar Arrays of (Co-Fe-B)x(LiNbO3)100−x Nanocomposite Memristors

Convolutional neural networks (CNNs) have been widely used in image recognition and processing tasks. Memristor-based CNNs accumulate the advantages of emerging memristive devices, such as nanometer critical dimensions, low power consumption, and functional similarity to biological synapses. Most studies on memristor-based CNNs use either software models of memristors for simulation analysis or full hardware CNN realization. Here, we propose a hybrid CNN, consisting of a hardware fixed pre-trained and explainable feature extractor and a trainable software classifier. The hardware part was realized on passive crossbar arrays of memristors based on nanocomposite (Co-Fe-B)x(LiNbO3)100−x structures. The constructed 2-kernel CNN was able to classify the binarized Fashion-MNIST dataset with ~ 84% accuracy. The performance of the hybrid CNN is comparable to the other reported memristor-based systems, while the number of trainable parameters for the hybrid CNN is substantially lower. Moreover, the hybrid CNN is robust to the variations in the memristive characteristics: dispersion of 20% leads to only a 3% accuracy decrease. The obtained results pave the way for the efficient and reliable realization of neural networks based on partially unreliable analog elements.
Real-Time Non-Contact Millimeter Wave Radar-Based Vital Sign Detection

In this paper, the extraction of the life activity spectrum based on the millimeter (mm) wave radar is designed to realize the detection of target objects and the threshold trigger module. The maximum likelihood estimation method is selected to complete the design of the average early warning probability trigger function. The threshold trigger module is designed for the echo signal of static objects in the echo signal. It will interfere with the extraction of Doppler frequency shift results. The moving target detection method is selected, and the filter is designed. The static clutter interference is filtered without affecting the phase difference between the detection sequences, and the highlight target signal is improved. The frequency and displacement of thoracic movement are used as the detection data. Through the Fourier transform calculation of the sequence, the spectrum value is extracted within the estimated range of the heartbeat and respiration spectrum, and the heartbeat and respiration signals are picked up. The proposed design uses Modelsim and Quartus for CO-simulation to complete the simulation verification of the function, extract the number of logical units occupied by computing resources, and verify the algorithm with the vital signs experiment. The heartbeat and respiration were detected using the sports bracelet; the relative errors of heartbeat detection were 0–6.3%, the respiration detection was 0–9.5%, and the relative errors of heartbeat detection were overwhelmingly less than 5%.
Integrating Cyber Deception Into Attribute-Based Access Control (ABAC) for Insider Threat Detection

Insider threat is an ever-present challenge to corporate security. The availability of knowledge and privileges to insiders makes it extremely difficult to prevent, detect or deter malicious insider activities. In the literature, several studies have proposed deception-based approaches to mitigate insider threats through different layers of corporate systems. However, the integration of access control and cyber deception methods has not been adequately discussed. In this paper, we integrate Attribute-based Access Control (ABAC) with honey-based deception techniques to effectively track insiders, particularly in the context of a dynamic work environment. To the best of our knowledge, this is the first study to design, implement and evaluate this integration. Our evaluation results show that the proposed framework reliably identifies sensitive attributes in the system and generates indistinguishable honey values to protect them with an average similarity score of 0.90 to the truth.
A Deep Recurrent Neural Network With FISTA Optimization for CT Metal Artifact Reduction

Metal Artifact Reduction (MAR) is one of the most challenging problems in Computed Tomography (CT) imaging. In CT imaging, metal implants in patients' bodies cause artifacts due to several factors, such as beam hardening effects, statistical property changes of the X-ray beams, and the shapes of metal implants. Although some promising results have been achieved by previously proposed model-based iterative reconstruction (IR) techniques, there is still much room for improvement. One of the problems is that the image prior models used in the IR techniques are too simple to capture the truly complex nature of the CT images. Recent advances in neural network deep learning (DL) can help address this problem and potentially improve MAR results significantly. In this work, we describe a novel DL-based technique for CT MAR. In this technique, we introduce a novel deep neural network based on an IR formulation and a convex optimization technique known as the FISTA (Fast Iterative Shrinkage-Thresholding Algorithm). The neural network, called the RNN-MAR, is an RNN (Recurrent Neural Network) composed of a set of proposed RFUs (Recurrent FISTA Units). While the structure of the RFU has some connections to the GRU (Gated Recurrent Unit), it is specifically designed for CT MAR. The RNN-MAR conducts dual-domain learning (image and sinogram) but can do this using only one objective function. Furthermore, unlike previous CT MAR techniques, the RNN-MAR does not use a binary metal trace. Instead, we used a novel real-valued sinogram domain confidence map, leading to smoother edges. Results from extensive experiments indicate that our RNN-MAR outperforms state-of-the-art DL MAR techniques in terms of the Root Mean Squared Error (RMSE), Peak Signal-to-Noise Ratio (PSNR), and Structure Similarity (SSIM) as well as in terms of visual appearance.
Strain-induced perpendicular magnetic anisotropy in La$_2$CoMnO$_{6-\epsilon}$ thin films and its dependence with film thickness

Ferromagnetic insulating La$_2$CoMnO$_{6-\epsilon}$ (LCMO) epitaxial thin films grown on top of SrTiO$_3$ (001) substrates presents a strong magnetic anisotropy favoring the out of plane orientation of the magnetization with a strong anisotropy field ($\sim 70$ kOe for film thickness of about 15 nm) and with a coercive field of about 10 kOe. The anisotropy can be tuned by modifying the oxygen content of the film which indirectly has two effects on the unit cell: i) change of the orientation of the LCMO crystallographic axis over the substrate (from c in-plane to c out-of-plane) and ii) shrinkage of the out of plane cell parameter, which implies increasing tensile strain of the films. In contrast, LCMO films grown on (LaAlO$_3$)$_{0.3}$(Sr$_2$AlTaO$_6$)$_{0.7}$ and LaAlO$_3$ substrates (with a larger out-of-plane lattice parameter and compressive stress) display in-plane magnetic anisotropy. Thus, we link the strong magnetic anisotropy observed in La$_2$CoMnO$_{6-\epsilon}$ to the relation between in-plane and out-of-plane parameters and so to the film stress.
In Vitro and In Vivo Characterization of 89Zirconium-Labeled Lintuzumab Molecule

Objective: Positron emission tomography (PET) imaging is a powerful non-invasive method to determine the in vivo behavior of biomolecules. Determining biodistribution and pharmacokinetic (PK) properties of targeted therapeutics can enable a better understanding of in vivo drug mechanisms such as tumor uptake, off target accumulation and clearance. Zirconium-89 (89Zr) is a readily available tetravalent PET-enabling radiometal that has been used to evaluate the biodistribution and PK of monoclonal antibodies. In the current study, we performed in vitro and in vivo characterization of 89Zr-lintuzumab, a radiolabeled anti-CD33 antibody, as a model to evaluate the in vivo binding properties in preclinical models of AML. Methods: Lintuzumab was conjugated to p-SCN-Bn-deferoxamine (DFO) and labeled with 89Zr using a 5:1 µCi:µg specific activity at 37 °C for 1h. The biological activity of 89Zr-lintuzumab was evaluated in a panel of CD33 positive cells using flow cytometry. Fox Chase SCID mice were injected with 2 × 106 OCI-AML3 cells into the right flank. After 12 days, a cohort of mice (n = 4) were injected with 89Zr-lintuzumab via tail vein. PET/CT scans of mice were acquired on days 1, 2, 3 and 7 post 89Zr-lintuzumab injection. To demonstrate 89Zr-lintuzumab specific binding to CD33 expressing tumors in vivo, a blocking study was performed. This cohort of mice (n = 4) was injected with native lintuzumab and 24 h later 89Zr-lintuzumab was administered. This group was imaged 3 and 7 days after injection of 89Zr-lintuzumab. A full ex vivo biodistribution study on both cohorts was performed on day 7. The results from the PET image and ex vivo biodistribution studies were compared. Results: Lintuzumab was successfully radiolabeled with 89Zr resulting in a 99% radiochemical yield. The 89Zr-lintuzumab radioconjugate specifically binds CD33 positive cells in a similar manner to native lintuzumab as observed by flow cytometry. PET imaging revealed high accumulation of 89Zr-lintuzumab in OCI-AML3 tumors within 24h post-injection of the radioconjugate. The 89Zr-lintuzumab high tumor uptake remains for up to 7 days. Tumor analysis of the PET data using volume of interest (VOI) showed significant blocking of 89Zr-lintuzumab in the group pre-treated with native lintuzumab (pre-blocked group), thus indicating specific targeting of CD33 on OCI-AML3 cells in vivo. The tumor uptake findings from the PET imaging study are in agreement with those from the ex vivo biodistribution results. Conclusions: PET imaging of 89Zr-lintuzumab shows high specific uptake in CD33 positive human OCI-AML3 tumors. The results from the image study agree with the observations from the ex vivo biodistribution study. Our findings collectively suggest that PET imaging using 89Zr-lintuzumab could be a powerful drug development tool to evaluate binding properties of anti-CD33 monoclonal antibodies in preclinical cancer models.
Machine learning applications in Cyber-Physical Production Systems: a survey

Cyber-Physical Production Systems (CPPS) play a vital role in realizing the vision of Industry 4.0. In the last decade, various machine learning methods have been implemented in manufacturing systems to improve their intelligence. However, few review papers on machine learning applications in CPPS have been published. In this context, this paper presents a survey of machine learning applications in Cyber-Physical Production Systems. Both bibliometric analysis and qualitative analysis have been conducted based on the related literatures published in the last decade. We identified the major research issues with respect to machine learning applications in CPPS, i.e. anomaly detection, predictive maintenance, fault management, efficiency, quality assurance, and scheduling. The review results show that although machine learning has been extensively applied in manufacturing, its applications in CPPS have not been widely studied. Based on the detailed discussions of the research issues and challenges, this paper indicates the current limitations of CPPS and demonstrates the great advantages and potential for applying machine learning in CPPS in future research.
Clinical and Economic Burden Associated with Prolonged Air Leaks Among Patients Undergoing Thoracic Resection: A Retrospective Database Analysis

Purpose Prophylactic use of lung sealants among patients undergoing thoracic resection has been reported for the management of intraoperative air leaks and is associated with a lower incidence of prolonged air leak (PAL) and a shorter length of stay (LOS). This study estimated the incremental economic and clinical burden of PAL among patients with lung sealants used during thoracic resection in the United States. Patients and Methods This retrospective analysis examined hospital data (Premier Healthcare Database) for adults (age ≥18 years) with inpatient thoracic resection between October 2015 - March 2021 (first admission=index) and lung sealant used during their procedure. Follow-up extended through 90 days post-discharge. Patients were grouped by presence/absence of PAL (ie, diagnosis of post-procedural air leak or post-procedural pneumothorax with associated LOS exceeding 5 days). Outcomes included intensive care unit (ICU) days, total index hospital costs, all-cause 30-, 60-, and 90-day readmission, discharge status, and in-hospital mortality. Generalized linear models quantified associations between PAL and outcomes, accounting for hospital-level clustering, and patient, procedure, and hospital/provider characteristics. Results Among the 9727 patients included for study (51.0% female, 83.9% white, mean age 66 years), 12.5% had PAL, which was associated with significant incremental increases in ICU days (0.93 days, p<0.001) and total hospital cost ($11,119, p<0.001). PAL also decreased the likelihood of discharge to home (from 91.3% to 88.1%, p<0.001) and increased the risk of readmission within 30, 60, and 90 days by up to 34.0% (from 9.3% to 12.6%;11.7% to 15.4%;13.6% to 17.2%, respectively), all p<0.01. Absolute risk of mortality was low, but two times higher in patients with PAL versus those without PAL (2.4% vs 1.1%, p=0.001). Conclusion This analysis demonstrates that despite the prophylactic use of lung sealants, PAL continues to put a burden on the healthcare system, highlighting an unmet need for improved sealant technology.
Achromatizing a Liquid-Crystal Spectropolarimeter: Retardance vs. Stokes-Based Calibration of HiVIS

Astronomical spectropolarimeters can be subject to many sources of systematic error that limit the precision and accuracy of the instrument. We present a calibration method for observing high-resolution polarized spectra using chromatic liquid-crystal variable retarders (LCVRs). These LCVRs allow for polarimetric modulation of the incident light without any moving optics at frequencies ≥10 Hz. We demonstrate a calibration method using pure Stokes input states that enables an achromatization of the system. This Stokes-based deprojection method reproduces input polarization even though highly chromatic instrument effects exist. This process is first demonstrated in a laboratory spectropolarimeter where we characterize the LCVRs and show example deprojections. The process is then implemented on the newly upgraded HiVIS spectropolarimeter on the 3.67 m Advanced Electro-Optical System (AEOS) telescope. The HiVIS spectropolarimeter has also been expanded to include broadband full-Stokes spectropolarimetry using achromatic wave plates in addition to the tunable full-Stokes polarimetric mode using LCVRs. These two new polarimetric modes in combination with a new polarimetric calibration unit provide a much more sensitive polarimetric package with greatly reduced systematic error.
Bell-type inequality and quantum nonlocality in four-qubit systems

We present a Bell-type inequality for four-qubit systems. Using the inequality we investigate quantum nonlocality of a generic family of states |Gabcd〉 [Phys. Rev. A 65, 052112 (2002)] and several canonical four-qubit entangled states. It has been demonstrated that the inequality is maximally violated by so called “four-qubit maximal entangled state |Gm〉” and it is also violated by the fourqubit W state and a special family of states |Gab00〉. Moreover, a useful entanglement-nonlocality relationship for the family of states |Gab00〉 is obtained.
Quantum behavior near a spacelike boundary in the c = 1 matrix model

Certain time-dependent configurations in the c = 1 matrix model correspond to string theory backgrounds which have spacelike boundaries and appear geodesically incomplete. We investigate quantum mechanical properties of a class of such configurations in the matrix model, in terms of fermionic eigenvalues. We describe Hamiltonian evolution of the eigenvalue density using several different time variables, some of which are infinite and some of which are finite in extent. We derive unitary transformations relating these different descriptions, and use those to calculate fermion correlators in the time-dependent background. Using the chiral formalism, we write the time-dependent configurations as a state in the original matrix model Hilbert space.
PLANET–PLANET SCATTERING IN PLANETESIMAL DISKS. II. PREDICTIONS FOR OUTER EXTRASOLAR PLANETARY SYSTEMS

We develop an idealized dynamical model to predict the typical properties of outer extrasolar planetary systems, at radii comparable to the Jupiter-to-Neptune region of the solar system. The model is based upon the hypothesis that dynamical evolution in outer planetary systems is controlled by a combination of planet–planet scattering and planetary interactions with an exterior disk of small bodies (“planetesimals”). Our results are based on 5000 long duration N-body simulations that follow the evolution of three planets from a few to 10 AU, together with a planetesimal disk containing 50 M⊕ from 10 to 20 AU. For large planet masses (M ≳ MSat), the model recovers the observed eccentricity distribution of extrasolar planets. For lower-mass planets, the range of outcomes in models with disks is far greater than that which is seen in isolated planet–planet scattering. Common outcomes include strong scattering among massive planets, sudden jumps in eccentricity due to resonance crossings driven by divergent migration, and re-circularization of scattered low-mass planets in the outer disk. We present the distributions of the eccentricity and inclination that result, and discuss how they vary with planet mass and initial system architecture. In agreement with other studies, we find that the currently observed eccentricity distribution (derived primarily from planets at a ≲ 3 AU) is consistent with isolated planet–planet scattering. We explain the observed mass dependence—which is in the opposite sense from that predicted by the simplest scattering models—as a consequence of strong correlations between planet masses in the same system. At somewhat larger radii, initial planetary mass correlations and disk effects can yield similar modest changes to the eccentricity distribution. Nonetheless, strong damping of eccentricity for low-mass planets at large radii appears to be a secure signature of the dynamical influence of disks. Radial velocity measurements capable of detecting planets with K ≈ 5 m s−1 and periods in excess of 10 years will provide constraints on this regime. Finally, we present an analysis of the predicted separation of planets in two-planet systems, and of the population of planets in mean-motion resonances (MMRs). We show that, if there are systems with ∼ Jupiter-mass planets that avoid close encounters, the planetesimal disk acts as a damping mechanism and populates MMRs at a very high rate (50%–80%). In many cases, resonant chains (in particular the 4:2:1 Laplace resonance) are set up among all three planets. We expect such resonant chains to be common among massive planets in outer planetary systems.
Potential and Alternative Bioactive Compounds from Brown Agaricus bisporus Mushroom Extracts for Xerosis Treatment

This study aimed to investigate the ability of brown Agaricus bisporus extracts to enhance xerosis treatment via their biological activities, including their antioxidant, anti-aging, and anti-inflammation. Brown A. bisporus ethanol extract (EE) and brown A. bisporus water extract (WE) contained ergothioneine and gallic acid as their major compounds, as detected by HPLC, respectively. The WE exhibited the highest total polysaccharide content (734.04 ± 0.03 mg glucose/g extract) and total phenolic content (190.90 ± 0.07 mg gallic acid/g extract). The WE exhibited an inhibitory effect of 83.34 ± 18.66% on a collagenase enzyme, whereas the EE inhibited the elastase enzymes by 81.26 ± 4.37%. In addition, the EE also demonstrated strong activities against DPPH, with an IC50 0.30 ± 0.04 mg/mL, ABTS with a TEAC value of 8.06 ± 0.08 µM Trolox/g extract, and a FRAP assay with a FRAP value of 390.50 ± 0.32 mM FeSO4/g. In addition, all extracts were non-cytotoxic and could decrease the secretion of IL-6 and TNF-α in HaCaT cells. Therefore, brown A. bisporus extracts might be a potential natural raw material that can be further used in cosmeceutical products for xerosis treatment due to their good efficacy.
Service Quality and Customer Loyalty: Evidence from Jordanian Banks

The purpose of this study is to investigate the role of service quality in enhancing customer loyalty in Jordanian banks. Several measurements of service quality are used in this study, such as (tangibility, reliability, responsiveness, empathy and assurance). The study developed a questionnaire which was distributed to retailing customers in Jordanian banks. To achieve the purposes of the study and to analyze the results, the study estimates simple - and multiple-linear regression models using SPSS 26. The results of the study show that there is a significant positive effect of service quality with its different measurements individually and collectively on customer loyalty in Jordanian banks. To enhance service quality, the study recommends that effective recruitment policy and training programs of banking staff be adopted by banks’ managements. This study provides some managerial implications and proposes further research directions on banking service quality
Generalizing Entanglement via Informational Invariance for Arbitrary Statistical Theories

Fil: Holik, Federico Hernan. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - la Plata. Instituto de Fisica la Plata. Universidad Nacional de la Plata. Facultad de Ciencias Exactas. Instituto de Fisica la Plata; Argentina
Holmium Complex with Phospholipids as 1H NMR Relaxational Sensor of Temperature and Viscosity

The sensitivity of Ho–phospholipid complexes to changes in the membrane viscosity of liposomes was checked. An increase in viscosity was observed for DPPC and DMPC near the phase-transition temperature. Ho–phospholipid complexes could be used as sensors of local membrane viscosity in NMR and MRI technologies.
Probing the neutron star spin evolution in the young SMC Be/X-ray binary SXP 1062

The newly discovered Be/X-ray binary in the Small Magellanic Cloud, SXP 1062, provides the first example of a robust association with a supernova remnant (SNR). The short age estimated for the SNR qualifies SXP 1062 as the youngest known source in its class, tau ~ 1e4 yr. As such, it allows to test current models of magneto-rotational evolution of neutron stars ina still unexplored regime. Here we discuss possible evolutionary scenarios for SXP 1062 in the attempt to reconcile its long spin period, P=1062 s, and short age. Although several options can be considered, like an anomalously long initial period or the presence of a fossil disc, our results indicate that SXP 1062 may host a neutron star born with a large initial magnetic field, typically in excess of ~ 1e14 G, which then decayed to ~ 1e13 G.
Characters of Finite Coxeter Groups and Iwahori-Hecke Algebras

1 CARTAN MATRICES AND FINITE COXETER GROUPS 2 PARABOLIC SUBGROUPS 3 CONJUGACY CLASSES AND SPECIAL ELEMENTS 4 THE BRAID MONOID AND GOOD ELEMENTS 5 IRREDUCIBLE CHARACTERS OF FINITE COXETER GROUPS 6 PARABOLIC SUBGROUPS AND INDUCED CHARACTERS 7 REPRESENTATION THEORY OF SYMMETRIC ALGEBRAS 8 IWAHORI-HECKE ALGEBRAS 9 CHARACTERS OF IWAHORI-HECKE ALGEBRAS 10 CHARACTER VALUES IN CLASSICAL TYPES 11 COMPUTING CHARACTER VALUES AND GENERIC DEGREES APPENDIX: TABLES FOR THE EXCEPTIONAL TYPES REFERENCES
3D van der Waals sigma-model and topological excitations with logarithmic energy

The 3D vector van der Waals (or conformal) nonlinear sigma-model is proposed. It is shown that it has the "hedgehog"-like topological excitations with logarithmic energy. Their "neutral" configurations have nontrivial topological structures described by Hopf invariant. A possible influence of these excitations on the properties of the model are discussed.