Miracle-dz/UniFAR-FTUs huggingface dataset:
Iterative scheme for a coupled system of fractional‐order differential equations with three‐point boundary conditions

We investigate sufficient conditions for existence of multiple solutions to a coupled system of fractional‐order differential equations with three‐point boundary conditions. By coupling the method of upper and lower solutions together with the method of monotone iterative technique, we develop conditions for iterative solutions. Based on these conditions, we study maximal and minimal solutions to the problem under consideration. We also study error estimates and provide an example. Copyright © 2016 John Wiley & Sons, Ltd.
Antimicrobial Drug Resistance in Poultry Production: Current Status and Innovative Strategies for Bacterial Control

The world population’s significant increase has promoted a higher consumption of poultry products, which must meet the specified demand while maintaining their quality and safety. It is well known that conventional antimicrobials (antibiotics) have been used in livestock production, including poultry, as a preventive measure against or for the treatment of infectious bacterial diseases. Unfortunately, the use and misuse of these compounds has led to the development and dissemination of antimicrobial drug resistance, which is currently a serious public health concern. Multidrug-resistant bacteria are on the rise, being responsible for serious infections in humans and animals; hence, the goal of this review is to discuss the consequences of antimicrobial drug resistance in poultry production, focusing on the current status of this agroeconomic sector. Novel bacterial control strategies under investigation for application in this industry are also described. These innovative approaches include antimicrobial peptides, bacteriophages, probiotics and nanoparticles. Challenges related to the application of these methods are also discussed.
Technology acceptance of augmented reality to attitude and self-efficacy in learning English

This study examined the effects of the technology acceptance of augmented reality on attitude and self-efficacy in learning English and modelled the direct and indirect effects. It employed non-experimental, analytic survey research with structural equation modelling. Two hundred and fifty-seven participants completed the survey questionnaire. Data analysis used SmartPLS to examine the outer loading, validity and reliability, R square, path coefficients, specific indirect effects, total effects, and model fit. Structural equation modelling (SEM) showed that perceived usefulness has no significant effect on attitude and self-efficacy, while perceived ease of use has a significant effect on attitude but no significant effect on self-efficacy. Perceived enjoyment has a positive correlation with attitude and self-efficacy. This study provides empirical facts that support and contradict previous relevant studies on the technology acceptance on attitude and self-efficacy in using augmented reality technology for language learning. The results of the study also contribute ideas on how technology can be anchored not only from technological but also from cognitive and affective perspectives as well.
Torsional Pneumatic Actuator Based on Pre-Twisted Pneumatic Tubes for Soft Robotic Manipulators

The human forearm produces torsional motions that are essential in daily activities such as opening doors or containers. It has a large range of motion (ROM), can produce large torques, can move bidirectionally, and can stiffen at will. Implementing such motions in a rigid robotic manipulator is easy due to the inherently rotational motions of electric motors, but pneumatic actuators do not inherently produce rotational motions. Indeed, most torsional pneumatic actuators are capable of unidirectional or bidirectional motions but do not have the antagonistic actuation capabilities necessary to have variable stiffness. Furthermore, their actuation characteristics are very different from those of the human forearm. This article proposes a torsional pneumatic actuator based on pretwisted pneumatic tubes that uses a hybrid hard-soft structure. These pneumatic tubes can be installed at an offset from the rotation axis such that antagonistic tubes can be installed on a single actuator. The actuator is capable of bidirectional torsional motions, can change its torsional stiffness, and has an actuation performance comparable to that of the human forearm. It was implemented in a soft robotic manipulator with seven degrees of freedom with a wide ROM and is capable of rotating objects while manipulating them.
Fate of multiparticle entanglement when one particle becomes classical

We study the change of multiparticle entanglement if one particle becomes classical, in the sense that this particle is destructed by a measurement, but the gained information is encoded into a new register. We present an estimation of this change for different entanglement measures and ways of encoding. We first simplify the numerical calculation to analyze the change of entanglement under classicalization in special cases. Second, we provide general upper and lower bounds on the entanglement change. Third, we show that the entanglement change caused by classicalization of one qubit only can still be arbitrarily large. Finally, we discuss cases where no entanglement is left under classicalization for any possible measurement. Our results shed light on the storage of quantum resources and help to develop a novel direction in the field of quantum resource theories.
Increasing airway obstruction through life following bronchopulmonary dysplasia: a meta-analysis

Background Few studies exist investigating lung function trajectories of those born preterm; however growing evidence suggests some individuals experience increasing airway obstruction throughout life. Here we use the studies identified in a recent systematic review to provide the first meta-analysis investigating the impact of preterm birth on airway obstruction measured by the forced expiratory volume in 1 s (FEV1) to forced vital capacity (FVC) ratio. Methods Cohorts were included for analysis if they reported FEV1/FVC in survivors of preterm birth (<37 weeks’ gestation) and control populations born at term. Meta-analysis was performed using a random effect model, expressed as standardised mean difference (SMD). Meta-regression was conducted using age and birth year as moderators. Results 55 cohorts were eligible, 35 of which defined groups with bronchopulmonary dysplasia (BPD). Compared to control populations born at term, lower values of FEV1/FVC were seen in all individuals born preterm (SMD −0.56), with greater differences seen in those with BPD (SMD −0.87) than those without BPD (SMD −0.45). Meta-regression identified age as a significant predictor of FEV1/FVC in those with BPD with the FEV1/FVC ratio moving −0.04 sds away from the term control population for every year of increased age. Conclusions Survivors of preterm birth have significantly increased airway obstruction compared to those born at term with larger differences in those with BPD. Increased age is associated with a decline in FEV1/FVC values suggesting increased airway obstruction over the life course. This meta-analysis describes increased airway obstruction in survivors of preterm birth, with those diagnosed with bronchopulmonary dysplasia as infants having worse obstruction that also increases with age https://bit.ly/40Z9BKp
Machine Learning Applications for Reliability Engineering: A Review

The treatment of big data as well as the rapid improvement in the speed of data processing are facilitated by the parallelization of computations, cloud computing as well as the increasing number of artificial intelligence techniques. These developments lead to the multiplication of applications and modeling techniques. Reliability engineering includes several research areas such as reliability, availability, maintainability, and safety (RAMS); prognostics and health management (PHM); and asset management (AM), aiming at the realization of the life cycle value. The expansion of artificial intelligence (AI) modeling techniques combined with the various research topics increases the difficulty of practitioners in identifying the appropriate methodologies and techniques applicable. The objective of this publication is to provide an overview of the different machine learning (ML) techniques from the perspective of traditional modeling techniques. Furthermore, it presents a methodology for data science application and how machine learning can be applied in each step. Then, it will demonstrate how ML techniques can be complementary to traditional approaches, and cases from the literature will be presented.
Study for Performance of MobileNetV1 and MobileNetV2 Based on Breast Cancer

Artificial intelligence is constantly evolving and can provide effective help in all aspects of people's lives. The experiment is mainly to study the use of artificial intelligence in the field of medicine. The purpose of this experiment was to compare which of MobileNetV1 and MobileNetV2 models was better at detecting histopathological images of the breast downloaded at Kaggle. When the doctor looks at the pathological image, there may be errors that lead to errors in judgment, and the observation speed is slow. Rational use of artificial intelligence can effectively reduce the error of doctor diagnosis in breast cancer judgment and speed up doctor diagnosis. The dataset was downloaded from Kaggle and then normalized. The basic principle of the experiment is to let the neural network model learn the downloaded data set. Then find the pattern and be able to judge on your own whether breast tissue is cancer. In the dataset, benign tumor pictures and malignant tumor pictures have been classified, of which 198738 are benign tumor pictures and 78, 786 are malignant tumor pictures. After calling MobileNetV1 and MobileNetV2, the dataset is trained separately, the training accuracy and validation accuracy rate are obtained, and the image is drawn. It can be observed that MobileNetV1 has better validation accuracy and overfit during MobileNetV2 training. From the experimental results, it can be seen that in the case of processing this dataset, MobileNetV1 is much better than MobileNetV2.
Antioxidant and Immune Stimulating Effects of Allium cepa Skin in the RAW 264.7 Cells and in the C57BL/6 Mouse Immunosuppressed by Cyclophosphamide

Allium cepa L. (onion) has been reported to have various pharmacological effects, such as preventing heart disease, and improving antimicrobial activity and immunological effects. The Republic of Korea produced 1,195,563 tons of onions (2022). The flesh of onion is used as food while the onion skin (OS) is thrown away as an agro-food by-product and is considered to induce environmental pollution. Thus, we hypothesize that increasing usage of OS as functional food material could help protect from the environment pollution. The antioxidant effects and immune-enhancing effects of OS were evaluated as functional activities of OS. In this study, OS showed high 1,1-diphenyl-2-picrylhydrazyl (DPPH) and 2,2-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) radical scavenging activities and xanthine oxidase (XO) inhibitory activity. The antioxidant activities increased in a dose-dependent manner. The IC50 values of DPPH, ABTS radical scavenging activity, and XO inhibitory activity were 954.9 μg/mL, 28.0 μg/mL, and 10.7 μg/mL, respectively. Superoxide dismutase and catalase activities of OS in RAW 264.7 cells were higher than those of the media control. There was no cytotoxicity of OS found in RAW 264.7 cells. Nitric oxide and cytokines (IL-1β, IL-6, IFN-γ, and TNF-α) concentrations in RAW 264.7 cells significantly increased in a dose dependent manner. Immune-stimulating effects of OS were evaluated in immunosuppressed mice induced by cyclophosphamide. White blood cell count and the B cell proliferation of splenocytes were higher in OS100 (OS extract 100 mg/kg body weight) and OS200 (OS extract 200 mg/kg body weight) groups than in the negative control (NC) group. Serum IgG and cytokine (IL-1β and IFN-γ) levels were also higher in OS100 and OS200 groups than in the NC group. OS treatment increased NK cell activity compared with the NC group. The results suggested that OS can improve antioxidant and immune stimulating effects. The use of OS as functional supplement can reduce the agro-food by-product and it may contribute to carbon neutrality.
Une propriété arithmétique dans l'analyse du comportement d'un système hydraulique comprenant une chambre d'équilibre avec étranglement

An analytic study based on asymptotic expansions exhibits a difference in the behaviour of a standard hydraulic scheme including a surge tank, depending upon the ratio v=(l 1 |c 1 )/(l 2 |c 2 ), where l 1 , l 2 are the lengths of the tunnel and penstock respectively and c 1 , c 2 the corresponding velocities ; if v=p|q is an irreductible fraction and if p is odd, transients are damped out, while if p is even, there is an oscillatory mode Etude basee sur un developpement asymptotique mettant en evidence une difference de comportement d'un systeme hydraulique standard comprenant une chambre d'equilibre, dependant des longueurs de la galerie et de la conduite forcee et des celerites correspondantes
A SUBOPTIMAL MULTIPLE FADING EXTENDED KALMAN FILTER

A new concept of "strong tracking filters" is proposed, a general structure of a class of strong tracking filters is presented, and an orthogonality principle is also proposed for designing such strong tracking filters. Based on the orthogonality principle, a strong tracking filter-a suboptimal multiple fading extended Kalman filter (SMFEKF) is proposed, which improves the suboptimal fading extended Kalman filter (SFEKF) proposed in [1]. Finally, the effictiveness of the SMFEKF is illustrated by computer simulation.
Eavesdropping Strategies for Remote State Estimation Under Communication Constraints

This paper studies the confidentiality issue of wireless sensor networks under communication constraints from the perspective of an eavesdropper. The considered communication constraints include both medium access constraint and bandwidth limitation. Specifically, the former results in only one sink node gaining access to the shared network at each time step, while the latter requires data to be quantized by a probabilistic quantizer before being transmitted. The task of the eavesdropper is to develop eavesdropping strategies for the constrained network to infer the state of the system as accurately as possible. Since the data is generally unreadable to unauthorized third parties in terms of secure transmission, an eavesdropper with limited power must decide which sink nodes’ data needs to be decrypted. By analyzing the impact of different decryption strategies on the eavesdropping performance, a deciphering scheduling is proposed, which minimizes the expected estimation error without exceeding the energy budget. Besides, a recursive reset algorithm is put forward based on the properties of the probabilistic quantizer, which reflects that an eavesdropper can infer whether its own estimate is accurate enough from the decoded data. Moreover, a sufficient condition is established in which the eavesdropping performance is improved under the proposed algorithm. A numerical example is provided to demonstrate the validity of the developed approaches.
An investigation on energy spectral information of computed tomography for machine learning in lesion classification

Recent advancement of spectral computed tomography (SpCT) technologies by either multi-energy spectral data acquisition with energy-integration detector or single-energy spectral data acquisition with photon counting detector has enabled the reconstruction of virtual monochromatic images (VMIs) at any energy values within and outside the energy spectral ranges of current CTs’ X-ray tubes, resulting in the possibility of not only visualizing the tissue contrast variation characteristics along the X-ray energy dimension, but also quantifying the variation characteristics by machine learning (ML) for prediction of lesion malignancy or computer-aided diagnosis (CADx). This study explored the energy spectral information of SpCT, i.e., the contrast variation characteristics along the X-ray energy dimension, for ML-CADx of lesion type of colorectal polyps. Particularly, the tissue contrast variation patterns, called energy spectral features, along the Xray energy dimension in the VMIs is investigated. A figure of merit (FOM) for the task of ML-CADx is proposed, which ranks the series of VMIs along the X-ray energy dimension by inputting each VMI into a single channel deep learning (DL) pipeline and generating a corresponding a score of AUC (area under the curve of receiver operating characteristics). Then the FOM selects different numbers of the most highly ranked VMIs as the inputs to a multi-channel DL pipeline to generate the corresponding of AUC scores until all VMIs are selected. It is hypothesized that the AUC scores from the multi-channel DL pipeline will increase to reach the highest score and then drop along the ranking order, because all VMIs have the same anatomic structure and, therefore, the strong data redundancy. The FOM reaches the highest AUC score by minimizing the redundancy. We tested the hypothesis by comparing the proposed FOM-rank ML-CADx with the widely used Karhunen-Loève (KL) transform-based ranking method where the principal components are ordered automatically by the KL transform. The lesion data include the CT images of colorectal polyps and the pathological reports after they were resected. The proposed FOM-rank method outperformed the KL-based ranking method with an optimal gain of 4.7%, showing its effectiveness in prediction of lesion malignancy.
Time-space Spectral Method for the 1-D nonlinear Maxwell Equations

A time-space spectral method is given for the 1-D nonlinear Maxwell equations. And the spectral method of time multi interval is considered, that is, the interval decomposition is used in time spectral approximation. By computing some numerical examples for 1-D nonlinear Maxwell’s equations, the effectiveness of the proposed method is verified.
High Temperature Performance Evaluation of High Viscosity Asphalt at Different Aging Degrees Based on Multiple Stress Creep Recovery Test

In order to investigate the effect of high temperature on the performance of three high viscous asphalt in company with various aging degrees (ADs), multiple stress creep recovery (MSCR) test was employed. CRR and irrecoverable compliance were also carried out to measure the high temperature resistance of high viscous asphalt to external loading in the presence of various aging conditions (ACs) as well as to examine the sensitivity of high viscous asphalt towards the stress. The findings of the study demonstrated that after short- and long-term aging, the high-viscosity asphalt turned harder. Also, type I high-viscosity asphalt was observed to have the greatest deformation resistance acted upon by various stress fields and ACs. Furthermore, in company with various ACs, while the average creep recovery rate (CRR) of Type I and Type II high-viscosity asphalt was found to be higher than that of the SBS modified asphalt, the average irrecoverable compliance was observed to be smaller. This indicated the significant effect of high-viscosity modifiers on the improvement of the elastic recovery performance of asphalt and its resistance to high temperature flow deformation. Contrary to the order of their CRRs, the magnitude of stress sensitivity of the three high-viscosity asphalt at various ADs was observed to be type II < type I < SBS modified asphalt, indicating a good negative correlation between stress sensitivity and average CRR. Furthermore, the obtained results revealed that, in the presence of various ACs, the high temperature viscoelastic qualities of high viscosity modified asphalt is considered by the MSCR test. Also, to comprehensively evaluate the high temperature performance of high viscosity modified asphalt at various Ads, the use of such indexes as the average CRR, average irrecoverable compliance and stress sensitivity coefficient were essential.
Electronic solar compass for high precision orientation on any planet

A compact, fully automatic electronic solar compass has been developed at the ENEA Frascati Laboratories. The compass is inspired to ``camera obscura'' sundials like those inside churches. Sun ephemerides are calculated using an approximate but effective analytical solution of Kepler's laws, where the Earth (or other planets) orbit main parameters are introduced. The instrument is light, cheap and it has an accuracy better than 1 arcmin. Some examples of application of the device as well as the possibility to use it on Mars are presented.
The Hα Luminosity Function of Galaxies at z ∼ 4.5

We present the Hα luminosity function (LF) derived from a large sample of Lyman break galaxies at z ∼ 4.5 over the GOODS-South and North fields. This study makes use of the new, full-depth Spitzer/IRAC [3.6] and [4.5] imaging from the GOODS Re-ionization Era wide-Area Treasury from the Spitzer program. The Hα flux is derived from the offset between the continuum flux estimated from the best-fit spectral energy distribution, and the observed photometry in IRAC [3.6]. From these measurements, we build the Hα LF and study its evolution providing the best constraints of this property at high redshift, where spectroscopy of Hα is not yet available. Schechter parameterizations of the Hα LF show a decreasing evolution of Φ∗ with redshift, increasing evolution in L ∗, and no significant evolution in the faint-end slope at high z. We find that star formation rates (SFRs) derived from Hα are higher than those derived from the rest-frame UV for low SFR galaxies but the opposite happens for the highest SFRs. This can be explained by lower mass galaxies (also lower SFR) having, on average, rising star formation histories (SFHs), while at the highest masses the SFHs may be declining. The SFR function is steeper, and because of the excess SFR(Hα) compared to SFR(UV) at low SFRs, the SFR density estimated from Hα is higher than the previous estimates based on UV luminosities.