Miracle-dz/UniFAR-FTUs huggingface dataset:
Exponential Stability of Leakage Delay and Semi-Markovian Jump for Neutral-Type Neural Network

In this paper, a suitable Lyapunov-Krasovskii functional together with the inequality analysis technique for neutral-type system, and sufficient exponential stability conditions are proposed in the form of linear matrix inequalities (LMIs). Firstly, the system model of leakage delay and semi-Markovian process for neutral-type neural network is established, where the sojourn-time follows Weibull distribution, which is time-varying instead of being constant in the transition rate. Secondly, through combinations of stability analysis method, Lyapunov-Krasovskii functional and inequality analysis technique, some sufficient conditions have been achieved to undertake the exponential stabilization of given neural network system. Moreover, time delays of the system contain leakage and mixed delays, which are more general and appropriate. Finally, in order to show the many advantages of our model, the obtained results will be compared with previous works based on methods different from semi-Markovian jump or leakage delay.
Design and Implementation of Dual Feed Circularly Polarized Dielectric Resonator Antenna for High Gain Applications

This paper portrays the basic plan of a dielectric resonator radio wire utilizing tube shape to increase the gain of the antenna. The dielectric resonator receiving wire comprises of more dielectric constant materials, top notch parameters and having a grounded insulated substrate of lesser permittivity. Proposed receiving wire is of 43x43 mm material of FR-4 epoxy with dielectric (Ɛr= 4.4) and the thickness of substrate has been considered as 0.508mm round and hollow DRA is set on the ground(copper) plane on the rear of substrate two square shape strips are placed for getting the gain. For this proposed work 8.2-8.7 GHz, which is the frequency range that acts as an application for x-band and gain is increasedupto2.5dB.
Review of Architectures Based on Partial Power Processing for DC-DC Applications

This paper presents a review of advanced architectures based on the partial power processing concept, whose main objective is to achieve a reduction of the power processed by the converter. If the power processed by the converter is decreased, the power losses generated by the power converter are reduced, obtaining lower sized converters and higher system efficiencies. Through the review 3 different partial power processing strategies are distinguished: Differential Power Converters, Partial Power Converters and Mixed strategies. Each strategy is subdivided into smaller groups that entail different architectures with their own advantages and disadvantages. Also, due to the lack of agreement that exists in the sources around the naming of the different architectures, this paper seeks to stablish a nomenclature that avoids confusion when indexing this type of architectures. Regarding Partial Power Converters an extensive application oriented description is also developed. Finally, the main conclusions obtained through the review are presented.
A Process Mining Tool for Supporting IoT Security

The development of the Internet has been characterized by a growing interest for the Internet-of-Things (IoT). In particular, connected devices are integrated to other Internet resources (such as cloud resources) to elaboratevalue-added services. However, they pose important challenges with respect to security management due to their heterogeneity, their distribution, and their limited resources. In this demonstration, we present a process mining toool for supporting IoT security. This tool is capable to automate the detection of misbehaviours and attacks in large and heterogeneous IoT infrastructures, based on process mining techniques combined with normalization and clustering data pre-processing. We detail the different building blocks of this tool provided into a docker container, and illustrate its operations with different scenarios.
An Extended Kron Method for Power System Applications

Due to the greater detailing in distribution systems modeling, it is necessary the seek for reliable reduction methods that improve the simulation time, while maintaining the precision of the power flow solution. This work considers the efficient idea regarding Kron reduction and establishes a mathematically exact reduction method to explicitly eliminate buses without loads and generation connection in a three-phase four-wire multi-grounded distribution feeder. Hence, the method is incorporated into the robust Four-conductor Current Injection Method (FCIM) and the results obtained for Kersting’s NEV Test Feeder and IEEE 123 buses are quite encouraging, presenting both an excellent accuracy in the same order of the FCIM’s tolerance and a significant improvement in its computational time. The proposed method is flexible to guarantee exactness and considerable time savings to utility companies when performing analyses that need power flow solutions, e.g., planning studies in modern DS.
Contrasting demographic histories of European and North American sea lamprey (Petromyzon marinus) populations inferred from mitochondrial DNA sequence variation

Populations of anadromous sea lamprey (Petromyzon marinus) have been found to be largely genetically homogeneous across western Europe, and across the eastern seaboard of North America. However, comparatively little is known of the relationship between the European and North American populations. We quantified the extent of population structuring present over a transatlantic scale using mitochondrial DNA sequences. We found clear segregation of the populations on either side of the Atlantic, and considerable genetic homogeneity within Europe over a spatial scale of over 2000 km. The North American populations contained larger genetic diversity than those from Europe, and coalescent analyses showed a corresponding greater overall effective population size. Employing calibration points based on a dated phylogeny of the Petromyzontiformes, our analyses indicated that the North American population has been increasing in effective size since establishment ~500 000 years ago, while the total European population has only undergone population expansion only within the last 125 000 years. This evidence is consistent with a colonisation of Europe from an older North American population, and with the European population persisting through the last glaciation within regional refugia.
Description of a new Myxobolus species, M. colossomatis n. sp. from the teleost Colossoma macropomum of the Amazon River basin

Summary Myxobolus colossomatis n. sp. (Myxosporea) is described from a pond-cultured Amazon River fish (Colossoma macropomum). The parasite cysts developed in the connective tissue of the fins, gills, heart, liver and serous membranes around the intestine.
Effects of Extracts of Dried Leaves of Erythrophleum suaveolens as Anesthetics on Clariid Catfish

ABSTRACT The effects of crude extract, pure extract, aqueous fraction of pure extract and lipid fraction of pure extract of air-dried leaves of Erythrophleum suaveolens as anesthetic on African sharptooth, Clarias gariepinus, and the African vundu catfish, Heterobranchus longifilis, fingerlings were studied. They were exposed to various doses of the extracts in tanks. The time for each fish to reach anesthesia were recorded. The two clariids were anesthetized in up to 3.5 g/L crude extract and recovered in the fresh water. Soaking the leaves for 24 hours or 48 hours produced no significant difference (P> 0.05) in the time to reach anesthesia for the African vundu catfish. These fingerlings reached anesthesia in significantly shorter time (P<0.05) (24.5 minutes at 2.4 g/L concentration) in the pure unseparated extract than in the crude extract (70.5 minutes at 2.4 g/L concentration). All fingerlings exposed to 4 g/L extracts did not recover. Those exposed to less than 3.5 g/L of plant material were anesthe.
A Comprehensive Review of Polyphonic Sound Event Detection

One of the most amazing functions of the human auditory system is the ability to detect all kinds of sound events in the environment. With the technologies and hardware advances, polyphonic Sound Event Detection (SED) can be developed to mimic the ability of the human auditory system. However, the development of a SED system is no trivial task, and several different factors often hinder accuracy. Although there are several overview papers available, most of them only provide a theoretical overview of algorithms used with little discussion. Thus, to the best of the authors’ knowledge, there is no comprehensive review that covers this particular domain. Therefore, this paper aims to provide an in-depth discussion of different methodologies proposed by various authors that include the features used, detection algorithms, and their corresponding accuracy and limitations. Additional information on possible trends is also discussed that can be useful for future development works.
The Service Metrics and Performance Analysis of Internet Time Service

An increasing number of Industry Internet of Things (IIoT) applications put forward the requirements for strict time synchronization and accurate time service from providers. In order to indicate the time service performance of the Internet Time Service Providers (TSPs) on user sides, we build an Internet time service monitoring system which can obtain the real-time data of time service through the Internet. The monitoring system records the time service’s performance from three major categories: NTP pool projects, National Metrology Institutes and Commercial Organizations. After that, we propose three service metrics, in terms of Availability, Stability and Accuracy, to evaluate the performance of time service provided by TSPs. On the other hand, a novel anomaly detection algorithm is proposed to gather the statistics of abnormal data and then remove the abnormal data. Experimental results show that 56 TSPs’ availability are more than 95%. It indicates that a longer transmission path results in a lower availability. The further analyzed results also denote that the link hops have no correlations of Availability, Stability and Accuracy. Moreover, the relationship between Stability and Accuracy is positively correlated.
Analysis of Partial Discharge Measurements in High Voltage XLPE Cable

This paper deals with the study of partial discharge characteristics of 11kV XLPE insulated power cables. Two most common types of issues are considered along with the healthy insulation to study the PD (Partial discharge) characteristics, these are acknowledged as the main cause of insulation deterioration during installation and operation. In this study, a cable under measurement is subjected to mechanical embrasure and insulation chipping. The condition of rough insulation screen is also considered for measurement and analysis of PD characteristics. The method of measurement followed is as per the specified method in the applicable IEC standard. The experimental results are presented under the rated and at higher operating voltages of the cable. The analysis has been carried out and it verifies that these defects are the major contributor to the local discharge phenomena and the measured discharge quantity is on the higher side. The resultsare presented for PD patterns of the induced defects present dissimilarity, which can be utilized as samples for further PD pattern recognition.
A Theoretical and Experimental Investigation on the Measurement of the Electromagnetic Field Level Radiated by 5G Base Stations

This paper presents some theoretical considerations and experimental results regarding the problem of maximum power extrapolation for the assessment of the exposure to electromagnetic fields radiated by 5G base stations. In particular the results of an extensive experimental campaign using an extrapolation procedure recently proposed for 5G signal is discussed and experimentally checked on a SU-MIMO signal. The results confirm the effectiveness of the extrapolation technique. Starting from an analysis (that represents a further novel contribution of this paper) on the impact of Spatial Division Multiple Access techniques used in 5G on the measurement of EMF level, some indications of possible extension of the technique to the highly complex MU-MIMO case are also given.
HTTU-Net: Hybrid Two Track U-Net for Automatic Brain Tumor Segmentation

Brain cancer is one of the most dominant causes of cancer death; the best way to diagnose and treat brain tumors is to screen early. Magnetic Resonance Imaging (MRI) is commonly used for brain tumor diagnosis; however, it is a challenging problem to achieve higher accuracy and performance, which is a vital problem in most of the previously presented automated medical diagnosis. In this paper, we propose a Hybrid Two-Track U-Net(HTTU-Net) architecture for brain tumor segmentation. This architecture leverages the use of Leaky Relu activation and batch normalization. It includes two tracks; each one has a different number of layers and utilizes a different kernel size. Then, we merge these two tracks to generate the final segmentation. We use the focal loss, and generalized Dice (GDL), loss functions to address the problem of class imbalance. The proposed segmentation method was evaluated on the BraTS’2018 datasets and obtained a mean Dice similarity coefficient of 0.865 for the whole tumor region, 0.808 for the core region and 0.745 for the enhancement region and a median Dice similarity coefficient of 0.883, 0.895, and 0.815 for the whole tumor, core and enhancing region, respectively. The proposed HTTU-Net architecture is sufficient for the segmentation of brain tumors and achieves highly accurate results. Other quantitative and qualitative evaluations are discussed, along with the paper. It confirms that our results are very comparable expert human-level performance and could help experts to decrease the time of diagnostic.
Interferon‐γ regulation of TNFα‐induced matrix metalloproteinase 3 expression and migration of human glioma T98G cells

Induction of proinflammatory cytokines in response to malignant cells is an integral component of immune response to control tumor development. However, recent evidences have suggested that tumor cells may evade the immune system and exploit inflammatory responses to enhance its own growth. An exemplary example is the highly invasive and tumor necrosis factor (TNF)α‐resistant glioblastoma, whose growth is associated with TNFα expression. We thus examined whether the tumor takes advantage of TNFα overexpression to enhance its invasiveness. To delineate the contribution of inflammation in tumor migration, we demonstrated that the role of proinflammatory cytokines on matrix metalloproteinases‐3 (MMP‐3) expression, and its consequent effects on the invasiveness of a human glioma cell‐line, T98G. By using Matrigel Invasion Chamber, T98G cell migration was significantly enhanced in response to TNFα. In contrast, interferon‐γ (IFNγ) reduced both basal and TNFα‐enhanced cell invasion. To investigate the mechanisms involved, we demonstrated that TNFα upregulated mRNA and protein expression of MMP‐3 in T98G cells, whereas IFNγ downregulated the MMP‐3 expression. The role of MMP‐3 in glioma invasiveness was further confirmed by transfecting MMP‐3 siRNA in T98G to abrogate the TNFα‐enhanced cell invasion. To delineate the mechanisms further, we showed that IFNγ exerts an inhibitory effect on the binding of TNFα‐activated Ets‐1 and NFκB to their respective enhancer elements found in MMP‐3 promoter. In summary, our results indicated that TNFα enhances the invasiveness of T98G glioma cells through MMP‐3 induction, and such enhancement of cell migration can be inhibited by IFNγ. © 2007 Wiley‐Liss, Inc.
Trunk Model Establishment and Parameter Estimation for a Single Tree Using Multistation Terrestrial Laser Scanning

Parameter estimation and effective tree trunk model establishment are significant to tree biomass measurements and three-dimensional (3D) reconstruction. In this study, we proposed a trunk model establishment and parameter estimation method for a single tree through multistation terrestrial laser scanning (TLS). This approach obtains a more accurate and dense point cloud and yields several improvements. First, to correct the tree position, the angle between the trunk centreline and the vertical line was extracted to normalize the tree point clouds. Subsequently, some tree model parameters were accurately calculated. The tree height was extracted based on individual differences rather than directly adopting the Digital Elevation Model (DEM) model; The B-Spline curve fitting was added to the diameters at breast height (DBH) measure, which better determined the shape of the DBH compared with circle fitting; The CBH was measured by multi-view voxel projection instead of Single-view fixed threshold segmentation, which confirmed the position of the CBH more accurately. To highlight the effectiveness and pertinence of the proposed method, we analysed three plots that the proposed method can achieve more accurate results, where the mean relative error (MRE) of the tree height, DBH and CBH were 1.89%, 1.74% and 2.91% satisfying the accuracy standard specified by the technical indicators (±5%). The experimental results validate the trunk model accuracy and the effectiveness of the parameter measurements (close to the field measurements). The proposed method is significantly different from the accuracy of the previous method. The proposed method has the best accuracy in Multistation Terrestrial Laser Scanning. Hence the proposed method has outstanding performance in the high-precision extraction of trunk parameters and the construction of trunk models which will perform forest inventory and construction of virtual forest more accurately.
Using Human Gaze to Improve Robustness Against Irrelevant Objects in Robot Manipulation Tasks

Deep imitation learning enables the learning of complex visuomotor skills from raw pixel inputs. However, this approach suffers from the problem of overfitting to the training images. The neural network can easily be distracted by task-irrelevant objects. In this letter, we use the human gaze measured by a head-mounted eye tracking device to discard task-irrelevant visual distractions. We propose a mixture density network-based behavior cloning method that learns to imitate the human gaze. The model predicts gaze positions from raw pixel images and crops images around the predicted gazes. Only these cropped images are used to compute the output action. This cropping procedure can remove visual distractions because the gaze is rarely fixated on task-irrelevant objects. This robustness against irrelevant objects can improve the manipulation performance of robots in scenarios where task-irrelevant objects are present. We evaluated our model on four manipulation tasks designed to test the robustness of the model to irrelevant objects. The results indicate that the proposed model can predict the locations of task-relevant objects from gaze positions, is robust to task-irrelevant objects, and exhibits impressive manipulation performance especially in multi-object handling.
Seed banking of Polish endangered plants – the FlorNatur Project

Abstract Among the 2750 species of the Polish vascular flora, about 500 species are threatened with extinction and 430 of them are strictly protected by national law. The FlorNatur project for the ex situ conservation of the most endangered species was started in 2009. The aim of the project is to collect seeds of 61 species from 161 sites in eastern Poland and store them in the Seed Bank of the Polish Academy of Sciences Botanical Garden - Center for Biological Diversity Conservation in Warsaw- Powsin. A complementary program is being carried out by the Forestry Gene Bank at Kostrzyca in western Poland. Their task is to collect 58 species from 129 natural sites in the western part of Poland. To date, seeds of 31 species from 56 populations have been collected, tested and stored in liquid nitrogen.
Fruit Ripeness Based on RGB, HSV, HSL, L*a*b* Color Feature Using SVM

In this study, we have created a fruit ripeness dataset for 8 categories, namely Ripe Mango, Ripe Tomato, Ripe Orange, Ripe Apple, Unripe Mango, Unripe Tomato, Unripe Orange, and Unripe Apple. Based on the fruit ripeness dataset, we build a classification model of fruit ripeness using the SVM algorithm. Color feature extraction implemented in this study is RGB, HSV, HSL, and L * a * b *. To determine fruit ripeness, we done by predict image input to the model generated. Based on the experiment result, we have found that the best SVM model in determining fruit ripeness is the 6th degree polynomial kernel and by extracting HSV color features. We evaluated the model generated based on the value of accuracy, precision, recall, and F-Measure. The best performance of our system for accuracy, precision, recall, and F-Measures are 0.76, 0.80, 0.76, and 0.78, respectively.
Approximation-Based Event-Triggered Control Against Unknown Injection Data in Full States and Actuator of Uncertain Lower-Triangular Nonlinear Systems

This paper addresses an approximation-based adaptive event-triggered control problem against unknown injection data in full state measurements and an actuator of systems with unknown strict-feedback nonlinearities. It is assumed that full state variables measured for state-feedback control are corrupted by unknown injection data that denote cyber attacks or fault signals, and all system nonlinearities are unknown. Owing to the corrupted state feedback information, error surfaces using exactly measured state variables become unknown during the recursive control design procedure for strict-feedback nonlinear systems. Thus, they cannot be used to implement the adaptive event-triggered controller. To address this problem, an approximation-based adaptive recursive event-triggered control design using the corrupted state variables is established to ensure that error surfaces using exactly measured state variables converge to an adjustable neighborhood of the origin in the Lyapunov sense. The adaptive controller and its event-triggering law using corrupted states are designed under uncertain injection data where the adaptive injection data compensators using the neural networks are constructed to deal with the unknown injection data effects. The stability of the closed-loop systems and the exclusion of Zeno behavior are analyzed.
Integration of Wind Power Generation into a Double- sided Competitive Electricity Market For Profit and Social Welfare Maximization

Due to the increase in climatic conditions, the world is moving towards renewable energies. Wind power generation (WPG) is fueled by the wind which is almost free, except the operation and maintenance (O/M) costs, it's a clean, variable and uncertain fuel source, which creates the difficult implications of its integration into the power system. With the continuing demand for an alternative rather than conventional power sources, it is vital to integrate WPG into power systems as it is economically viable for the production cost and the electricity prices in the market. This paper presents interior point method (IPM) to solve the optimal power flow (OPF) problem and the integration of WPG with the variation of wind speed to study its effect on locational marginal prices (LMPs), generation costs, total profit and the social welfare in a doublesided competitive electricity market. All generation companies (GENCO) and distribution companies (DISCO) compete to achieve maximum profit and benefit with their bids to the independent system operator (ISO), simulation is carried out using power system analysis toolbox in MATLAB applied on IEEE 6-bus and IEEE 14-bus systems.