Miracle-dz/UniFAR-FTUs huggingface dataset:
Supervised classi#cation with structured class de#nitions

Almost all work on supervised classi#cation assumes that the class labels are a simple nominal variable. Often, however, there are relationships between the classes arising from an underlying structure. In particular, in prognostic situations, class memberships are often de#ned in terms of variables to be measured in the future. In such cases new forms of classi#cation rules can be constructed, based on predicting these future variables instead of directly predicting the class memberships. We call such methods indirect methods. The circumstances in which one might expect indirect methods to outperform direct methods are described. Two simulation studies are outlined, the #rst showing that indirect methods can perform well in cases which are essentially impossible for conventional direct approaches, and the second illustrating some of the theoretical arguments. Two real examples, one on smoking and the other on retail banking, demonstrate that indirect methods can outperform conventional direct methods in real applications. c 2001 Elsevier Science B.V. All rights reserved.
Different Measurement System of Lightning

Lightning phenomena is the electrical discharging phenomena. The electromagnetic radiations due to lightning, having various frequencies with different wavelengths are produced. The measurement of lightning by different method like the photography method, current measurement method, electric and magnetic field measurements method and thunder measurement methods can be used. The lightning phenomena produced the waveforms of electric and magnetic field which are the basic parameters to understand the phenomena of lightning discharges. The pair of circular flat metallic plates, separated from each other by insulating material, and are used to capture the signature and measure the electromagnetic radiations produced due to lightning. The waveforms were recorded in the hilly and mountainous country, of Nepal. These types of waveforms are observed and recorded.
ANOVA Procedures for Multiple Linear Regression Model with Non-normal Error Distribution: A Quantile Function Distribution Approach

This paper is an attempt to observe the extent of effect on the power of analysis of variance test to violations of assumptions i.e. normality assumption of the error of multiple linear regression model. The error of the model is considered as g-and-k distribution because of the fact that it has shown a considerable ability to fit to data and facility to use in simulation studies. The strength of ANOVA is evaluated by observing the power function of F-test for different combination of g (skewness) and k (kurtosis) parameter. From the simulation results it is observed that the performance of ANOVA is seen to be immensely affected in presence of excess kurtosis and for small samples (say, n<100). Skewness parameter has not much effect on the power of the test under non-normal situation. The effect of sample size on the existing test for multiple regression models is also observed here in this paper under various non normal situations.
A Box-Cox Approach to QT Interval Correction for Heart Rate

QT interval on an electrocardiogram (ECG) trace is a widely used surrogate parameter in drug development to detect the potential of drugs to cause life threatening cardiac arrhythmias. It changes inversely with the magnitude of heart rate (Heart rate=60/RR, RR stands for RR interval on an ECG reading) and is often corrected to a heart rate independent value known as the corrected QT interval (QTc). Various parametric QT correction formulae have been proposed by specifying the QT and heart rate relationships explicitly by a fixed number of parameters. This paper proposes to use the Box-Cox transformation to fit the QTRR relationship, and develops a new method for correcting the QT interval for heart rate. The six commonly used parametric models are the special cases of Box-Cox transformed model. We discuss the model parameter estimation and assess the performance of QT correction formulae derived from four types of Box-Cox transformations using four off-drug ECG datasets and one on-drug ECG dataset, as well as a simulated dataset. The results show that all four derived QT correction formulae from Box-Cox transformation generate a heart rate independent QTc and that the QT correction formula derived from transformation of both QT and RR generates QTc with smaller variations. The Box-Cox transformation represents a very flexible family for modelling QT-RR relationships including the six commonly used parameter models, thus providing a potentially better QT correction method than the existing parametric models.
Do deep convolutional neural networks really need to be deep when applied for remote scene classification?

Abstract. Deep convolutional neural networks (CNNs) have been widely used to obtain high-level representation in various computer vision tasks. However, for remote scene classification, there are not sufficient images to train a very deep CNN from scratch. From two viewpoints of generalization power, we propose two promising kinds of deep CNNs for remote scenes and try to find whether deep CNNs need to be deep for remote scene classification. First, we transfer successful pretrained deep CNNs to remote scenes based on the theory that depth of CNNs brings the generalization power by learning available hypothesis for finite data samples. Second, according to the opposite viewpoint that generalization power of deep CNNs comes from massive memorization and shallow CNNs with enough neural nodes have perfect finite sample expressivity, we design a lightweight deep CNN (LDCNN) for remote scene classification. With five well-known pretrained deep CNNs, experimental results on two independent remote-sensing datasets demonstrate that transferred deep CNNs can achieve state-of-the-art results in an unsupervised setting. However, because of its shallow architecture, LDCNN cannot obtain satisfactory performance, regardless of whether in an unsupervised, semisupervised, or supervised setting. CNNs really need depth to obtain general features for remote scenes. This paper also provides baseline for applying deep CNNs to other remote sensing tasks.
Optical Forces on Multipoles Induced by the Belinfante Spin Momentum

The Belinfante spin momentum (BSM) is a fundamental yet enigmatic quantity of electromagnetic fields. It vanishes from the global momentum of the field, but can be detected locally, manifesting itself as an optical force on small particles. Hitherto, however, the BSM force is a concept well established only within the dipole approximation, and there is no explicit experimental evidence for its action on multipoles. Here, a theoretical model for multipolar BSM forces, exerted on generic Mie particles supporting multipoles of arbitrary order, is developed. This multipolar mechanical action is observed experimentally from a structured light field, which suppresses the effect of spin–orbit coupling. It can also selectively enhance the multipolar BSM forces, while restraining the dipolar component on a probe particle (Au sphere). These results constitute a distinct chapter in the physics of high‐order interactions in light–matter systems and can facilitate additional progress in optomechanics, optical manipulation, and Mie‐tronics.
Low-Complexity Joint Activity Detection and Channel Estimation With Partially Orthogonal Pilot for Asynchronous Massive Access

In the asynchronous massive machine-type communications (mMTCs) supported by massive MIMO-based grant-free random access, where all active devices asynchronously transmit the pilot sequences to the BS, it necessitates the joint activity detection and channel estimation (JADCE) with imperfect synchronization. In this article, in order to achieve a good balance between the number of pilots and the correlation property of pilots in the presence of time delay, we propose a partially orthogonal pilot sequence (POPS) consisting of multiple modulated chirp symbols. The robustness of the proposed pilots to time asynchrony allows the BS to detect the device activity before the time delay estimation. In sequel, taking advantage of the energy convergence feature of the pilots in the FFT domain after demodulation, we propose a selective interference elimination aided orthogonal matching pursuit (SIE-OMP) algorithm to solve the formulated JADCE problem with a reduced-size set of candidate pilots. The complexity analysis and numerical results validate that, compared with the testbench schemes, the proposed scheme can achieve a better JADCE performance with a lower computational complexity.
Plasma Small Extracellular Vesicle Cardiac miRNA Expression in Patients with Ischemic Heart Failure, Randomized to Percutaneous Intramyocardial Treatment of Adipose Derived Stem Cells or Placebo: Subanalysis of the SCIENCE Study

Small extracellular vesicles (EVs) and their cargo are an important component of cell-to-cell communication in cardiac disease. Allogeneic adipose derived stem cells (ADSCs) are thought to be a potential approach for cardiac regenerative therapy in ischemic heart disease. The SCIENCE study investigated the effect of ADSCs administered via intramyocardial injection on cardiac function in patients with ischemic heart disease. The aim of this substudy, based on samples from 15 patients, was to explore small EV miRNA dynamics after treatment with ADSCs compared to a placebo. Small EVs were isolated at several timepoints after the percutaneous intramyocardial application of ADSCs. No significant effect of ADSC treatment on small EV concentration was detected. After 12 months, the expression of miR-126 decreased significantly in ADSC patients, but not in the placebo-treated group. However, all cardiac miRNAs correlated with plasma cardiac biomarkers. In line with the overall negative results of the SCIENCE study, with the exception of one miR, we did not detect any significant regulation of small EV miRNAs in this patient collective.
Effects of LPS from Rhodobacter sphaeroides, a Purple Non-Sulfur Bacterium (PNSB), on the Gene Expression of Rice Root

The effects of lipopolysaccharide (LPS) from Rhodobacter sphaeroides, a purple non-sulfur bacterium (PNSB), on the gene expression of the root of rice (Oryza sativa) were investigated by next generation sequencing (NGS) RNA-seq analysis. The rice seeds were germinated on agar plates containing 10 pg/mL of LPS from Rhodobacter sphaeroides NBRC 12203 (type culture). Three days after germination, RNA samples were extracted from the roots and analyzed by RNA-seq. The effects of dead (killed) PNSB cells of R. sphaeroides NBRC 12203T at the concentration of 101 cfu/mL (ca. 50 pg cell dry weight/mL) were also examined. Clean reads of NGS were mapped to rice genome (number of transcript ID: 44785), and differentially expressed genes were analyzed by DEGs. As a result of DEG analysis, 300 and 128 genes, and 86 and 8 genes were significantly up- and down-regulated by LPS and dead cells of PNSB, respectively. The plot of logFC (fold change) values of the up-regulated genes of LPS and PNSB dead cells showed a significant positive relationship (r2 = 0.6333, p < 0.0001), indicating that most of the effects of dead cell were attributed to those of LPS. Many genes related to tolerance against biotic (fungal and bacterial pathogens) and abiotic (cold, drought, and high salinity) stresses were up-regulated, and the most strikingly up-regulated genes were those involved in the jasmonate signaling pathway, and the genes of chalcone synthase isozymes, indicating that PNSB induced defense response against biotic and abiotic stresses via the jasmonate signaling pathway, despite the non-pathogenicity of PNSB.
Dominated Choices in a Strategically Simple College Admissions Environment

Although many centralized school assignment systems use the strategically simple deferred-acceptance mechanism, applicants often make dominated choices. Using administrative data from Hungary, we show that 11% of college applicants forgo the free opportunity to receive a tuition waiver. Between 12.3% and 18.7% of these dominated choices are consequential, costing 6,600 dollars on average. Our results suggest that dominated choices are more common when their expected utility cost is lower. Since tuition waivers are highly demanded, dominated choices increase the total number applicants assigned to college.
Prevalence and Factors Affecting Appropriate Inhaler Use in Elderly Patients with Chronic Obstructive Pulmonary Disease: A Prospective Study

Background: Chronic obstructive pulmonary disease (COPD) mainly affects individuals aged 60 and older. The proper use of inhalers is crucial for managing COPD. This study aimed to evaluate the prevalence and factors affecting the appropriate use of inhalers among elderly patients with COPD. Methods: We enrolled 91 elderly patients with COPD admitted to the Department of Respiratory, University Medical Center HCMC between October 2020 and May 2021. Patients who were capable of using the inhaler would have their inhaler usage recorded through video footage. Two respiratory experts carefully analyzed 133 video-recorded demonstrations for evaluation purposes. Results: 18.7% of the patients demonstrated the correct inhaler technique. Pressurized metered dose inhaler (pMDI) and Turbuhaler had the lowest documented correct usage rates (11.9% and 10.0%, respectively). Two critical steps, namely “holding breath for about five seconds or as long as comfortable” and “breathing out gently,” were commonly performed incorrectly when using pMDI, Respimat, Breezhaler, or Turbuhaler. Multivariable logistic regression analysis showed that lower mMRC scores (AOR = 5.3, CI 1.1–25.5, p = 0.037) and receiving inhaler instruction within the past three months (AOR = 5.2, CI 1.3–20.1, p = 0.017) were associated with increased odds of using the inhaler correctly. Conclusions: Our study found that less than 20% of elderly patients with COPD use inhalers correctly. Common errors include inadequate breath-holding and gentle exhalation. mMRC scores and recent inhaler instruction were predictors of proper use. These findings can aid clinicians in improving inhaler management for elderly patients with COPD.
Impact of Industry 6.0 on MSME Entrepreneur's Performance and Entrepreneur's Emotional Intelligence in the Service Industry in India

Objective: The main aim of this paper is to categorize the different contributions to the transformation in robotics in the form of Digital twin, automation, and MSME entrepreneurs' emotional intelligence and their performance in the service industry. Theoretical framework: The first case is, Industry 6.0 would achieve Entrepreneurs' performance (EP) through complete autonomy through implementing full robotics. The second case is Emotional Intelligence (EI) made industry 6.0 to achieve positive performance for the whole period. Method: Based on the extensive literature review (between 2012 and 2022) and study through Scopus journals, concept studies, and case studies of Industry 6.0 predecessors and Original Equipment Manufacturers (OEMs) in the market, this paper highlights the present scenario of autonomous robots. Results and conclusion: The first point summarizes the outcome of the categorical literature review and highlights the novelty of the findings. The second point highlights the type of robots used to make this happen for Industry 6.0. Implications of the research: Only some service industries started utilizing autonomous robots and collaborative robots to fulfill every day operations performed by them with human mind management for attaining the complete autonomy of automation and robotics in each service industry in India. However, many things could be improved to implement this. Originality/value: Automation and Robotics system implementation and Industry 6.0 in the service industry were not evaluated before and it added value in the service industry to alleviate their concerns to have Business sustainability, environmental friendly and competitive in the market.
Nano sensing based on transparency effect in planar metamaterial

Abstract A planar metamaterial, consisting of double-slot cavities in a unit cell, has been investigated in detail. The results indicate that the interaction between two bright modes also leads to the transparency effect. Meanwhile, the transparency window can be adjusted by changing the length of slot cavity and the distance between two slot cavities. Finally, it is demonstrated that the planar metamaterial design may serve as a highly efficient sensor in near-infrared. The sensitivity is as high as 520 nm/RIU, and the FOM is up to 24.83. The planar metamaterial has the advantages of simple and compact structure, easy fabrication, which will greatly benefit the optical switch, nano plasmonic sensor in highly integrated optical circuits.
A theoretical model for the cantilever motion in contact-resonance atomic force microscopy and its application to phase calibration in piezoresponse force and electrochemical strain microscopy

Contact-resonance scanning probe techniques are frequently used for characterizing the mechanical sample properties via atomic force acoustic/ultrasonic microscopy as well as for detecting sample displacement via piezoresponse force microscopy (PFM) and via electrochemical strain microscopy (ESM). For a better understanding of the measurement principle and for a quantification of the signals, a theoretical description of the cantilever motion is necessary. Here, we present a comprehensive model from which the cantilever motion can be calculated numerically. Compared to previous models, our model takes into account a sample tilt and a position-dependent electrostatic load acting on the cantilever. We demonstrate a phase calibration technique for PFM and ESM measurements, which allows us to determine the absolute excitation phase of the signal with an uncertainty of only 2° for an amplification factor of 100.
Growth analysis and yield evaluation under tillage and weed management practices in maize-wheat cropping system

Integrated weed management strategies combine tillage systems and weed control strategies. Conservation agriculture (CA) and sustainable intensification cropping systems are potential sources of improved growth and overall productivity. This study evaluated tillage and weed management strategies effects on crop growth parameters and biological yields in maize-wheat cropping system in North Western Himalayan region. Different tillage (five) and weed management practices (three) were evaluated from 2018 to 2020 on growth indices and yield with fifteen treatments. Conservation agriculture (CA) based production system (ZT, zero tillage; crop rotation and intensification; residue management i.e. ZTR-ZTR) had higher crop dry matter accumulation (DMA), relative growth rate (RGR), crop growth rate (RGR) and biological yield of maize (28698 kg/ha) and wheat crops (18750 kg/ha). The zero tillage in maize and wheat (ZT-ZT) resulted in lowest maize (24677 kg/ha) and wheat biological yield (14009 kg/ha. Among weed management treatments, application of recommended herbicides in maize and wheat crop (H-H) resulted in higher crop DMA and biological yield of maize (27652 kg/ha) and wheat crop (19540 kg/ha). Therefore, for North Western Himalayan conditions, ZTR+H-ZTR+H (Conservation tillage combined with herbicide application in maize and wheat) is superior to other combinations for growth and yield.
Non-multiple medium-sized congenital melanocytic nevi: to excise or to follow up?

Introduction Congenital melanocytic nevi (CMN) are benign lesions composed of clonal proliferations of melanocytes. Although medium-sized CMN are common and generally remain benign throughout a person’s lifetime, they may be precursors of melanoma. There is a limited number of studies focused on the risk of melanoma in solitary, medium-sized, congenital melanocytic nevus; therefore, the incidence of malignant transformation and guidelines for treatment are not well established. Aim Prompted by the limited data, we conducted this study to gather more information about medium-sized CMN, to optimize clinical care. We share our analysis of surgically removed medium-sized CMN. Material and methods A total of 10 patients with non-multiple, medium-sized, congenital melanocytic nevus were included in this study. Lesions were removed using surgical procedures. Results In most of the cases the reason for excision of the medium-sized CMN was evolution of the lesion or aesthetic considerations reported by the patients. In 2 cases, due to the large size of the lesions, serial excisions were performed, while other CMN were removed surgically using simple excision technique. Eight of 10 medium-sized CMN were histologically described as benign, and 2 cases of malignant transformations were reported. Conclusions According to our clinical experience and knowledge, we recommend managing patients on an individual basis, taking into consideration multiple clinical attributes. In our opinion, long-lasting observation is the management of choice, and if there is need of surgery, we recommend total simple or staged excision depending on nevus size.
High Efficiency Spectral Analysis and BLAS-3 Randomized QRCP with Low-Rank Approximations

The purpose of this work is to improve stability and performance of selected matrix decompositions in numerical linear algebra. Chapter 1 examines the Locally Optimal Block Preconditioned Conjugate Gradient (LOBPCG) algorithm used to compute eigenvector-eigenvalue pairs for large sparse symmetric matrices or symmetric matrix pencils. Modifications are developed and analyzed to improve both performance and reliability. Numerical experiments demonstrate the final algorithm often operates several times faster than competing versions and succeeds in processing difficult matrices for which other versions fail.Chapters 2 extends the work on symmetric eigenvalue problems by developing an algorithm specialized to resolve eigenpairs in the interior of the spectrum of a symmetric matrix. An new Spectral Target Residual Descent (STRD) algorithm is proposed based on LOBPCG. This algorithm is demonstrated to reduce the number of iterations required to achieve convergence by roughly half. The component subroutines of STRD also have generalized versions to process interior eigenvalues of symmetric matrix pencils.Chapter 3 explores a variation on the QR decomposition with Column Pivoting using randomized-sampling to process pivoting decisions. Randomized QRCP eliminates the leading order of communication by processing column pivots on a much smaller sample matrix. This produces blocks of column pivots that are processed with BLAS-3 operations on the original matrix. Sample update formulations are explored that allow full matrices to be factorized without re-compressing the matrix after each block iteration. Related low-rank factorizations are also developed and compared in numerical experiments. These experiments show approximation quality for structured matrices to be comparable, and often better than, approximations based on QRCP. Furthermore, performance is shown to be nearly as good as QR without pivoting, which is often an order of magnitude faster than QRCP.
Stability Analysis and Design of Uncertain Discrete‐time Switched Systems with Actuator Saturation Using Antiwindup and Multiple Lyapunov Functions Approach

The stability analysis and anti‐windup design problem is investigated for a class of discrete‐time switched systems with saturating actuators by using the multiple Lyapunov functions approach. Firstly, we suppose that a set of linear dynamic output controllers have been designed to stabilize the switched system without input saturation. Then, we design anti‐windup compensation gains and a switching law in order to enlarge the domain of attraction of the closed‐loop system. Finally, the anti‐windup compensation gains and the estimation of domain of attraction are presented by solving a convex optimization problem with linear matrix inequality (LMI) constraints. A numerical example is given to demonstrate the effectiveness of the proposed design method.