Miracle-dz/UniFAR-FTUs huggingface dataset:
Frequency Response Data Based Disturbance Observer Design: With Application to a Nonminimum Phase Motion Stage

Disturbance observer based control system, which utilizes estimated disturbance to compensate the influence of real disturbance, is widely applied in industrial systems. In this article, a frequency response data based auto-tuning method is proposed to design a bandwidth-optimized disturbance observer. The identification of a nominal plant model and the design of a low-pass filter are accomplished simultaneously in the discrete domain. This significantly reduces the design effort required in existing parametric model-based and experience-based methods. A convex optimization problem is formulated by converting all the original constraints into convex form to save calculation time. Finally, the efficacy of the proposed method is verified by comparing the experimental results of existing methods with those of the proposed method in a nonminimum phase motion stage.
Application layer DDoS attack detection using Cuckoo Search algorithm-trained Radial Basis Function

In an application-layer distributed denial of service (App-DDoS) attack, zombie computers bring down the victim server with valid requests. Intrusion detection systems (IDS) cannot identify these requests since they have legal forms of standard TCP connections. Researchers have suggested several techniques for detecting App-DDoS traffic. There is, however, no clear distinction between legitimate and attack traffic. In this paper, we go a step further and propose a Machine Learning (ML) solution by combining the Radial Basis Function (RBF) neural network with the cuckoo search algorithm to detect App-DDoS traffic. We begin by collecting training data and cleaning them, then applying data normalizing and finding an optimal subset of features using the Genetic Algorithm (GA). Next, an RBF neural network is trained by the optimal subset of features and the optimizer algorithm of cuckoo search. Finally, we compare our proposed technique to the well-known k-nearest neighbor (k-NN), Bootstrap Aggregation (Bagging), Support Vector Machine (SVM), Multi-layer Perceptron) MLP, and (Recurrent Neural Network) RNN methods. Our technique outperforms previous standard and well-known ML techniques as it has the lowest error rate according to error metrics. Moreover, according to standard performance metrics, the results of the experiments demonstrate that our proposed technique detects App-DDoS traffic more accurately than previous techniques.
Cost-Effectiveness of Structural Health Monitoring in Fuselage Maintenance of the Civil Aviation Industry †

Although structural health monitoring (SHM) technologies using sensors have dramatically been developed recently, their capability should be evaluated from the perspective of the maintenance industry. As a first step toward utilizing sensors, the objective of the paper is to investigate the possibility of using sensors for inspecting the entire fuselage during C-check. First, we reviewed various sensors for their detection range, detectable damage size, and installed weight, which revealed that the piezoelectric wafer active sensor (PWAS) is the most promising sensor for aircraft SHM. Second, we performed a case study of inspecting the fuselage of Boeing-737NG using PWAS. To maintain the same detecting capability of manual inspection in C-check, we estimated the total number of sensors required. It turned out that utilizing sensors can reduce the maintenance downtime and thus, maintenance cost. However, even with a very conservative estimate, the lifetime cost was significantly increased due to the weight of sensor systems. The cost due to the weight increase was an order of magnitude higher than the cost saved by using SHM. We found that a large number of sensors were required to detect damage at unknown locations, which was the main cause of the weight increase. We concluded that to make SHM cost-effective, it would be necessary either to improve the current sensor technologies so that a less number of sensors are used or to modify the aircraft design concept for SHM.
Determination of Organochlorine Pesticide Residues and Trace Metal Concentration in Well and Stream Waters from Agricultural Farm Settlement in Ile-Oluji, Ondo State

Pollutants is constantly introduced into the aquatic environment primarily due to amplified industrial activity, technical development, growing human population and mistreatment of natural resources, agriculture and domestic wastes run-off. Among these pollutants, Organochlorine Pesticides and some trace metals such as Lead (Pb)Mercury(Hg)and Cadmium (Cd) are found as one of the most hazardous because of their toxicity to organisms This study investigate the levels of organochlorine pesticide (OCP) residues and Trace Metal concentration in Well and Stream waters from Agricultural Farm Settlement in Ile-Oluji Ondo State. Ten (10) samples each of 1 Liter Well and Stream waters were collected randomly for trace metal analysis and another Ten (10) samples each of 2.5 Liter Well and Stream waters were collected for Organochlorine Pesticide analysis within the Farm Settlement and its vicinity. Quantitative determination of the OCPs was determined using Gas Chromatography-Mass Spectrometer after liquid-liquid extraction with (v/v) ethyl acetate/dichloromethane mixture and the Trace Metal was determined using Atomic Absorption Spectrophotometer. The results show that organochlorine pesticide residues were not detected in all the well water samples except for AKN where Heptachlor was detected in the concentration of 0.11 mg/L while all samples from the stream were contaminated with the Organochrorine pesticides at appreciably higher concentration than WHO standards. The results also shows that all the trace metals analyzed for are present except for some well samples where Lead concentration is below the detection limit. The mean concentration of some of the sampling sites were below the permissible limit for WHO while some are higher than the permissible limit.
Intratumoural administration of an NKT cell agonist with CpG promotes NKT cell infiltration associated with an enhanced antitumour response and abscopal effect

ABSTRACT Intratumoural administration of unmethylated cytosine-phosphate-guanine motifs (CpG) to stimulate toll-like receptor (TLR)-9 has been shown to induce tumour regression in preclinical studies and some efficacy in the clinic. Because activated natural killer T (NKT) cells can cooperate with pattern-recognition via TLRs to improve adaptive immune responses, we assessed the impact of combining a repeated dosing regimen of intratumoural CpG with a single intratumoural dose of the NKT cell agonist α-galactosylceramide (α-GalCer). The combination was superior to CpG alone at inducing regression of established tumours in several murine tumour models, primarily mediated by CD8+ T cells. An antitumour effect on distant untreated tumours (abscopal effect) was reliant on sustained activity of NKT cells and was associated with infiltration of KLRG1+ NKT cells in tumours and draining lymph nodes at both injected and untreated distant sites. Cytometric analysis pointed to increased exposure to type I interferon (IFN) affecting many immune cell types in the tumour and lymphoid organs. Accordingly, antitumour activity was lost in animals in which dendritic cells (DCs) were incapable of signaling through the type I IFN receptor. Studies in conditional ablation models showed that conventional type 1 DCs and plasmacytoid DCs were required for the response. In tumour models where the combined treatment was less effective, the addition of tumour-antigen derived peptide, preferably conjugated to α-GalCer, significantly enhanced the antitumour response. The combination of TLR ligation, NKT cell agonism, and peptide delivery could therefore be adapted to induce responses to both known and unknown antigens.
Do CSR Ads with Public Health Messages Pertaining to COVID-19 Actually Help Consumers, Advertisers, and Society? Insights from the United States and Germany

Abstract Since the onset of the COVID-19 pandemic, many corporations have employed a new form of corporate social responsibility (CSR) advertising that incorporates COVID-19-related health behavior recommendations. This type of CSR advertising seeks to increase both business-oriented responses and health-oriented responses. As such, these ads are thought to benefit three audiences from inclusion of such messages: (1) society at large when individuals comply with the health messages; (2) individual consumers through increased sense of well-being and safety; and (3) the company through positive effects on the brand. Given the impact on all three audiences, we developed a comprehensive model that incorporates both the health belief model (HBM) and traditional advertising variables. We tested the model in the United States and Germany, surveying a total of 2,302 subjects. The model was largely confirmed in both countries. Importantly, COVID-19-related CSR ads increased the individual consumer’s sense of well-being, which then had a positive effect on brand outcomes but a detrimental effect on message compliance. This effect was stronger in Germany than in the United States. Thus, our findings are indicative of some undesirable effects on society of CSR ads that include COVID-19-related health behavior recommendations.
Internal resonances of nanorods in presence of surface energy effect: Nonlinear torsional vibration

In this paper, effects of the surface energy on the nonlinear torsional vibrations and internal resonances of nanorods are investigated. To this end, the second-order term with respect to angle of rotation is considered for the displacement field. In addition, the geometrically nonlinear strain–displacement relations are obtained based on the von-Kármán theory. Then, Hamilton’s principle is implemented to derive the governing equation of motion for torsional vibration of nanorod. In the governing equation of motion, the surface energy parameters are included by the surface elasticity theory. The multiple-scale method is employed to solve the governing equation of motion for fixed-free and fixed-fixed end conditions. The nanorod considered is made of aluminum and silicon because of different values of their surface parameters. The effect of surface energy parameters on the torsional frequencies of nanorods is investigated for different values of length, radius, frequency number, and amplitude of the nonlinear vibrations. In addition the cases of occurring, the internal resonances are reported. The results obtained in this research may be useful for better design of nanoelectromechanical devices such as nanobearings and rotary servomotors.
Introduction to Technologies Acceptance and Sustainability Modelling

Elaboration and introduction of a new technology is a complex and expensive task, therefore it is necessary to assess the set of factors influencing the future of technology. The most important parameters of assessment are acceptance and sustainability of technology. Different models exist, but mostly they are static and do not offer possibilities for interactive and real time assessment and do not allow forecasting the sustainability of technology. In the framework of FP7-ICT-2009-5 CHOREOS project No. 257178 a new two step methodology, Integrated Acceptance and Sustainability Assessment Model (IASAM), of socio-technical assessment has been elaborated.
Multi-objective optimization of milling process: exploring trade-off among energy consumption, time consumption and surface roughness

ABSTRACT Despite the continuous acceleration of global industrial informatization process, the manufacturing industry is still facing many problems, such as the lack of data in the machining process, the low utilization rate of energy and so on. This paper proposes an integrated framework based on Internet of things (IoT) and machine learning to realize the monitoring and collection of original real-time data, data association and achieve the trade-off optimization among energy consumption, processing time and surface roughness for the milling process in manufacturing system. This framework is composed of four functional modules, i.e. IoT-based processing data acquisition, milling experiment design, performance index prediction based on machine learning and performance index multi-objective optimization. The optimization results exhibit obvious advantages in energy consumption saving, processing time reduction and surface roughness improvement for the milling process.
Modeling and Optimization of Time-of-Use Electricity Pricing Systems

Time-of-use (TOU) pricing is an important strategy for electricity providers to manage supply and make the grid more efficient; as well as for consumers seeking to manage their costs. In this paper, we discuss a general stochastic modeling framework for consumer’s power demand based on which TOU contract characteristics can be selected to minimize the mean electricity price paid by the customer. We exploit the characteristics of power demand observed in real grids to model it during homogeneous peak periods as a constant level with fluctuations described by a scaled fractional Brownian motion. We analyze the exceedance process over pre-specified thresholds and use this information to formulate an optimization problem to determine the key features of the TOU contract. Due to the analytical intractability of certain expressions with the exception of short-range dependence fluctuations, the solution of the posited optimization problem requires using techniques such as Monte Carlo simulation and numerical search. The methodology for two pricing schemes is illustrated using real data.
Maintenance assistée par ordinateur

1 Introduction 2 Types de maintenance 2.1 Maintenance corrective 2.2 Maintenance preventive 2.21 Maintenance preventive systematique 2.22 Maintenance preventive conditionnelle 2.23 Planification de la maintenance preventive 3 Gestion informatisee de la maintenance 3,1 Introduction 3.2 Fonction Maintenance 3.21 Gestion des equipements 3.22 Gestion des travaux 3.3 Fonctions Magasin et Achats 3.31 Gestion des magasins 3.32 Gestion des achats 3.4 Gestion des grands arrets 3.41 Contexte economique 3.42 Elaboration du reseau et analyse des temps 3.43 Allocation des ressources 4 Nouvelles possibilites de l'informatique 4.1 Systemes graphiques 4.2 Systemes experts 4.21 Principales proprietes d'un systeme expert 4.22 Application a la maintenance 5 Mise en œuvre et bilan d'un systeme informatique 5.1 Mise en œuvre 5.11 Etablissement d'un schema directeur 5.12 Realisation d'un systeme informatique 5.13 Installation d'un systeme informatique 5.2 Bilan 5.21 Amelioration de l'efficacite du personnel 5.22 Diminution de la valeur du stock 5.23 Augmentation de la disponibilite des equipements 5.24 Autres avantages Documentation
Targeting IL12/23 in ulcerative colitis: update on the role of ustekinumab

As our comprehension of the pathogenic mechanisms of inflammatory bowel disease (IBD) increases, the therapeutic armamentarium for its treatment can expand, and novel target therapies join the treatment pipeline. Interleukin (IL)-12 and IL23 are two key cytokines responsible for promoting and perpetuating bowel inflammation in IBD. Ustekinumab is a monoclonal antibody directed against the shared p40 subunit of both cytokines, and it was recently approved for the treatment of ulcerative colitis (UC). In the pivotal phase III UNIFI trial, ustekinumab showed a superiority over placebo in both clinical and endoscopic outcomes; furthermore, it was characterized by a favorable safety profile, with a similar rate of adverse events as compared with placebo. Recent evidence from real-life experiences have started accumulating, generally confirming the effectiveness and safety figures emerged from the registration studies. However, most of these observational studies enrolled multirefractory patients; moreover, comparative data with other target therapies are lacking, leaving physicians without clear indications about the appropriate positioning of ustekinumab in the therapeutic pipeline for UC. This review examines the basis of targeting IL12-23 in UC therapy and summarizes the data from both clinical trials and real-life studies, to highlight the main evidence already available and the research gaps that need to be filled for the optimal usage of ustekinumab in UC.
Design of multiple near‐orthogonal spectrally‐compliant waveforms via alternating successive convex approximations and projections

: The authors consider the design of multiple near-orthogonal transmit waveforms for a high-frequency surface wave radar (HFSWR) system operating in a congested spectral environment where the radar must adhere to strict regulations on the interference it can cause to on-going communication links. The HFSWR application necessitates multiple waveforms to increase the overall unambiguous radar range. Ideally, the waveforms would be constant amplitude, have low autocorrelation sidelobes, and low pulse-to-pulse cross-correlations, all while meeting the imposed spectral constraints; however, it is impossible to know a priori that such waveforms exist. They propose an algorithm based on alternating successive convex approximations and projections to design waveforms with low pulse-to-pulse cross-correlation which meet strict spectral and autocorrelation sidelobe constraints while minimising the amplitude modulation. In the simulation, the proposed algorithm is found to converge rapidly and when compared to similar methods from the recent literature, the proposed algorithm is found to generate waveforms with significantly lower peak-to-average power ratios and better pulse compression properties.
Efficiency Analysis of Mediterranean Container Ports

The purpose of this paper is to evaluate the technical efficiency (productivity) of Mediterranean container ports by employing the data envelopment analysis (DEA) approach. In recent years, maritime transportation volume has been increasing with the trend of trade globalization. This tendency has positive effects on container cargo flows. Accordingly, container terminals have incessant expansions to meet this growing demand. However, before making an investment in the terminal area or handling equipment, efficiency evaluation is required to reveal optimal throughput with the present resources. As the Mediterranean Basin is an important region for container transportation, there should be studies on the efficiency of container terminals in this region. In this study, relative efficiency analysis is conducted for Mediterranean container ports which are on the list of world busiest container ports based on the year 2016 data. The findings show that subjected container terminals can increase their output by 1,47 times without expanding their inputs. Efficiency is slightly increasing from eastern through the western part of this region.
Multi-Mode Wideband Filtering Antenna for 5G Millimeter-Wave Communication

The interconnection loss between the radio frequency (RF) front-end and the antenna become prominent for system integration in the millimeter-wave (mm-wave) band, and joint design is required at the device level. Because of the higher propagation loss in the mm-wave band, the cost for communication coverage will increase sharply. This is the main impetus for the development of filtering antenna with low cost and low interconnection loss. In this paper, through the aperture sharing and mode hybridization, three adjacent modes are sequentially excited to achieve broadband characteristics. The simulation impedance bandwidth of the antenna is 24.1~28.4 GHz with a relative bandwidth of 16.4% and the peak realized gain is 5.7dBi. Radiation null can be realized at the edge of the passband with an increased coupling path between the slot and U-shaped ring, hence producing a more than 20dB out-of-band suppression.
Estimating Muscle Activity from the Deformation of a Sequential 3D Point Cloud

Estimation of muscle activity is very important as it can be a cue to assess a person’s movements and intentions. If muscle activity states can be obtained through non-contact measurement, through visual measurement systems, for example, muscle activity will provide data support and help for various study fields. In the present paper, we propose a method to predict human muscle activity from skin surface strain. This requires us to obtain a 3D reconstruction model with a high relative accuracy. The problem is that reconstruction errors due to noise on raw data generated in a visual measurement system are inevitable. In particular, the independent noise between each frame on the time series makes it difficult to accurately track the motion. In order to obtain more precise information about the human skin surface, we propose a method that introduces a temporal constraint in the non-rigid registration process. We can achieve more accurate tracking of shape and motion by constraining the point cloud motion over the time series. Using surface strain as input, we build a multilayer perceptron artificial neural network for inferring muscle activity. In the present paper, we investigate simple lower limb movements to train the network. As a result, we successfully achieve the estimation of muscle activity via surface strain.
Design of a miniaturized RF front-end module with antenna array for 5G millimeter-wave communication

The RF front-end module integrated with the antenna array is one of the key components in the system of 5G millimeter-wave communication, while helps to effectively reduces the insertion loss and circuit size. However, most of them are designed or assembled together which reduces the maintainability of the systems. This work presents a design of miniaturized RF front-end module integrated with antenna array as the core parts, which aims to provide the flexibility of maintenance for coming 5G millimeter-wave communication. The proposed design is introduced in detail, along with some simulated results. By comparing the integrated design and the independent design, it shows that the proposed design reduces the size of the circuit by 81% at the operating frequency.
Nanomedicine Penetration to Tumor: Challenges, and Advanced Strategies to Tackle This Issue

Simple Summary Scientists have been working on the development of nanomedicine-based tumor therapy, rather than conventional treatment, to treat cancer for several years. Unfortunately, biological barriers hinder the delivery of nanomedicine to tumors. There are different strategies applied by researchers to improve the nanomedicine penetration to tumors, such as the modification of nanoparticle features and controlling the cancer micro-environment. However, complicated cancer micro-environments and delivery problems prevent these approaches from achieving optimal results. Changes in the extra-cellular matrix or blood vessels modify tumor microenvironments in a way that provides improved nanomedicine penetration and distribution but not to an optimal level. Herein, we reviewed the challenges of nanomedicine penetration to tumors along with possible approaches to deal with this concern. Abstract Nanomedicine has been under investigation for several years to improve the efficiency of chemotherapeutics, having minimal pharmacological effects clinically. Ineffective tumor penetration is mediated by tumor environments, including limited vascular system, rising cancer cells, higher interstitial pressure, and extra-cellular matrix, among other things. Thus far, numerous methods to increase nanomedicine access to tumors have been described, including the manipulation of tumor micro-environments and the improvement of nanomedicine characteristics; however, such outdated approaches still have shortcomings. Multi-functional convertible nanocarriers have recently been developed as an innovative nanomedicine generation with excellent tumor infiltration abilities, such as tumor-penetrating peptide-mediated transcellular transport. The developments and limitations of nanomedicines, as well as expectations for better outcomes of tumor penetration, are discussed in this review.