Miracle-dz/UniFAR-FTUs huggingface dataset:
A new algorithm for encryption/decryption based on artificial immunity theory

For the realistic demand of data security communications, the paper proposes a new algorithm for encryption/decryption based on the theory of artificial immunization. It is a new method based on the negative selection algorithm and extracts the encryption factor from the plaintext. Encryption factor as a key group is expanded by the way of the m-sequence and generates pseudo-random key sequence that can be used to encrypt data. Pseudo-random key sequence generated in this way has good characteristics of self-correlation and the encrypted data has a better anti-attack performance. Therefore, there will be a good prospect of application.
Very low-voltage class AB CMOS precision voltage and current rectifiers

Simple class-AB CMOS voltage and current precision rectifier circuits that operate from a single supply close to a transistor's threshold voltage are introduced. The current rectifier has output voltage swings comparable to the supply voltage and the voltage rectifier has wide input and output swings. Simulations of both rectifiers operating at 20 MHz are shown. Experimental results of a test chip are presented that verify the proposed circuits. A full wave precision rectifier based on the proposed rectifier cells is discussed.
Design and Evaluation of a Wearable Skin Stretch Device for Haptic Guidance

We present a wearable skin stretch device for the forearm. It is composed of four cylindrical end effectors, evenly distributed around the user's forearm. They can generate independent skin stretch stimuli at the palmar, dorsal, ulnar, and radial sides of the arm. When the four end effectors rotate in the same direction, the wearable device provides cutaneous stimuli about a desired pronation/supination of the forearm. On the other hand, when two opposite end effectors rotate in different directions, the cutaneous device provides cutaneous stimuli about a desired translation of the forearm. To evaluate the effectiveness of our device in providing navigation information, we carried out two experiments of haptic navigation. In the first one, subjects were asked to translate and rotate the forearm toward a target position and orientation, respectively. In the second experiment, subjects were asked to control a 6-DoF robotic manipulator to grasp and lift a target object. Haptic feedback provided by our wearable device improved the performance of both experiments with respect to providing no haptic feedback. Moreover, it showed similar performance with respect to sensory substitution via visual feedback, without overloading the visual channel.
An Improved Busy-Tone Solution for Collision Avoidance in Wireless Ad Hoc Networks

In a single-channel wireless ad hoc network, the collisions caused by hidden terminals can severely reduce the network capacity. In this paper, a new busy-tone based scheme is proposed, which can completely avoid collisions (including DATA packet and RTS packet collisions) caused by hidden terminals. This is achieved by adding dual busy-tone channels, and setting a larger carrier sense range of the transmitter busy-tone channel than those of the information and receiver busy-tone channels. The proposed scheme also resolves the exposed terminal problem incurred by the increased carrier sense range of the transmitter busy-tone channel. The simulation results demonstrate that the proposed scheme has an improved performance in terms of throughput in the hidden terminal scenario as compared with the traditional busy-tone solution, and also achieves a high channel utilization in the exposed terminal scenario.
Impact of the inclusion of hydrotalcite on the morphological and electrical characteristics of an epoxy-based CNT nanocomposite

The experimental results concerning the correlation between morphological and electrical characteristics of a MWCNT/epoxy based composites are presented. The impact of a nanoclay filler is investigated on the DC conductivity of a matrix loaded with different concentrations of MWCNT in order to evaluate the improvements on the dispersion of CNT inside the epoxy matrix. The dispersion is deemed to be very influencing on the electrical conductivity of the nanocomposite. A detailed morphological and structural characterization allows to interpret the electrical behaviour of the nanocomposites.
Two Bounce Geometric Model for SIR Evaluation in AD-HOC Networks Using Directional Antennas

In this work we present a two-bounce geometrically-based stochastic channel model suitable for ad-hoc networks equipped with directional antennas. It extends existing geometric models with the addition of an interferer. We consider the use of directional antennas both at the receiver and transmitter of the communication link, adding information regarding both the angle of departure from the transmitter and the angle of arrival at the receiver. The performance of a system using directional antennas is evaluated in terms of signal to interference ratio (SIR) improvement in typical indoor and outdoor scenarios in both LOS and NLOS cases. We present results showing that such a system may achieve an average 24 dB SIR improvement with standard deviation less than 2.5 dB
Use of colour parameters for roasted coffee assessment

Fast and non-destructive indicators were evaluated as tools to measure the technological quality of Arabica and Robusta coffee. Accordingly, considering the roasting intensity in highly valuable commercial samples, volume, mass, apparent density, moisture, total ash, ash insoluble in hydrochloric acid, and ether extract were characterized. The chromatic parameters L*, C*, Ho were measured using illuminants D65 and C. It was found that in roasted coffee beans, the parameters L*, C*, Ho, and coordinate b* had an antagonist interaction due to an increase in the roasting intensity, whereas after milling, only L* and Ho decreased progressively. Considering that the parameters L* and Ho followed similar patterns using both illuminants, D65 and C, it can be concluded that they are appropriate to evaluate coffee colour changes during roasting, enabling a relationship with coffee quality.
To Survive Out-of-Hospital Cardiac Arrest: A Search for Meaning and Coherence

The primary responsibility of prehospital emergency personnel at out-of-hospital cardiac arrests (OHCA) is to provide lifesaving care. Ethical considerations, decisions, and actions should be based in the patient's beliefs about health and well-being. In this article, we describe patients' experiences of surviving OHCA. By using a phenomenological approach, we focus on how OHCA influences patients' well-being over time. Nine survivors were interviewed. Out-of-hospital cardiac arrest is described as a sudden and elusive threat, an awakening in perplexity, and the memory gap as a loss of coherence. Survival means a search for coherence with distressing and joyful understanding, as well as existential insecurity exposed by feelings of vulnerability. Well-being is found through a sense of coherence and meaning in life. The study findings show survivors' emotional needs and a potential for prehospital emergency personnel to support them as they try to make sense of what has happened to them.
Observer-based integrated robust fault estimation and accommodation design for discrete-time systems

In this article, a challenging issue on observer-based integrated robust fault estimation and accommodation for a class of discrete-time uncertain nonlinear systems is studied. First, a multiobjective augmented fault estimation observer (AFEO) containing an α-exponential stability performance index and an H ∞ performance index is proposed not only to guarantee the convergence speed of fault estimation but also to restrict the influence of uncertainties with respect to the fault estimation error as much as possible. Then, by introducing a slack matrix, new results are obtained to reduce the conservatism generated by the conventional multiobjective design method. Furthermore, a robust fault tolerant controller based on the dynamic output feedback is designed to guarantee the stability of the closed-loop system in the presence of faults. Moreover, the AFEO and the dynamic output feedback fault tolerant controller (DOFFTC) are designed separately and their performances are considered respectively. Finally, the simulation results of a practical system are presented to illustrate the effectiveness of the proposed design techniques.
Use of Bronchoalveolar Lavage to Detect Lung Injury

This unit describes how bronchoalveolar lavage can be used in laboratory animals to sample the epithelial lining fluid of the lung for information on the degree of pulmonary inflammation induced by exposure to an airborne toxicant. The technique allows quantitative assessment of inflammatory responses and is valuable for providing dose‐response information in exposed animals. Lavage fluid samples may also be used for proteomic analyses, and the protein expression profiles may be used to address specific mechanistic questions.
Effect of the miller-capacitance during switching transients of IGBT and MOSFET

The feedback from the drain to the gate of MOSFET resp. from the collector to the gate of an IGBT during switching transients is described by the miller-capacitance. This is an appropriate approach for MOSFET, where a positive dvDG/dt leads to a positive current through the miller-capacitance. The aim of this paper is to explain, why during turn-off of a bipolar device like an IGBT, this is not always the case. A positive dvCG/dt may lead to a negative current through the miller-capacitance. For a better understanding of the switching behaviour of the IGBT, it is helpful to take the time derivative of the electrical field peak as a measure for the current through the miller-capacitance.
Predicting Student Academic Performance in Blended Learning Using Artificial Neural Networks

Along with the spreading of online education, the importance of active support of students involved in online learning processes has grown. The application of artificial intelligence in education allows instructors to analyze data extracted from university servers, identify patterns of student behavior and develop interventions for struggling students. This study used student data stored in a Moodle server and predicted student success in course, based on four learning activities communication via emails, collaborative content creation with wiki, content interaction measured by files viewed and self-evaluation through online quizzes. Next, a model based on the Multi-Layer Perceptron Neural Network was trained to predict student performance on a blended learning course environment. The model predicted the performance of students with correct classification rate, CCR, of 98.3%.
Optimal Contracting with Subjective Evaluation: The Effects of Timing, Malfeasance and Guile

We introduce a general Principal-Agent model with subjective evaluation and malfeasance characterized by two-sided asymmetric information on performance that allows for an arbitrary information structure. Two generic contract forms are studied. An authority contract has the Principal reveal his information before the Agent responds with her information. Under such a contract, the Agent's compensation varies only with the Principal's information, while her information is used to punish untruthful behavior by the Principal. Conversely, a sales contract has the Agent reveal her information first. In this case, the Agent's performance incentives are affected by the information revealed by both parties. Because the Agent's information affects her compensation, the information revelation constraints are more complex under a sales contract, and provide a way to integrate Williamson's (1975) notion of guile into agency theory. We find that designing sales contracts for expert agents, such as physicians and financial advisors, are significantly more complex than designing optimal authority contracts.
Image Recommendation Algorithm Using Feature-Based Collaborative Filtering

As the multimedia contents market continues its rapid expansion, the amount of image contents used in mobile phone services, digital libraries, and catalog service is increasing remarkably. In spite of this rapid growth, users experience high levels of frustration when searching for the desired image. Even though new images are profitable to the service providers, traditional collaborative filtering methods cannot recommend them. To solve this problem, in this paper, we propose feature-based collaborative filtering (FBCF) method to reflect the user's most recent preference by representing his purchase sequence in the visual feature space. The proposed approach represents the images that have been purchased in the past as the feature clusters in the multi-dimensional feature space and then selects neighbors by using an inter-cluster distance function between their feature clusters. Various experiments using real image data demonstrate that the proposed approach provides a higher quality recommendation and better performance than do typical collaborative filtering and content-based filtering techniques.
Epidemiology of Nontuberculous Mycobacteria in French Polynesia

ABSTRACT As few data are available in the Pacific countries and territories of the Oceania region regarding nontuberculous mycobacteria, we retrospectively identified 87 such isolates from French Polynesia from 2008 to 2013 by hybridization using DNA-strip, matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) and partial rpoB gene sequencing. Partial rpoB gene sequencing classified 42/87 (48.3%) isolates in the Mycobacterium fortuitum complex, 28 (32.2%) in the Mycobacterium abscessus complex, 8 (9.2%) in the Mycobacterium mucogenicum complex, and 5 (5.7%) in the Mycobacterium avium complex. Two isolates were identified as Mycobacterium acapulcensis and Mycobacterium cosmeticum by partial 16S rRNA gene sequencing. One isolate, unidentified by MALDI-TOF MS and yielding less than 92% and 96% sequence similarity with rpoB and hsp65 reference sequences, respectively, was regarded as a potentially new species. Samples from three patients exhibiting ≥2 Mycobacterium porcinum isolates and from one patient with emphysema and a lung abscess exhibiting 2 Mycobacterium senegalense isolates fulfilled the American Thoracic Society microbiological criteria for nontuberculous mycobacterial lung infection. Remote geographic areas, such as French Polynesia, are potential sources for the discovery of new mycobacterial species.
Example-based brushes for coherent stylized renderings

Painterly stylization is the cornerstone of non-photorealistic rendering. Inspired by the versatility of paint as a physical medium, existing methods target intuitive interfaces that mimic physical brushes, providing artists the ability to intuitively place paint strokes in a digital scene. Other work focuses on physical simulation of the interaction between paint and paper or realistic rendering of wet and dry paint. In our work, we leverage the versatility of example-based methods that can generate paint strokes of arbitrary shape and style based on a collection of images acquired from physical media. Such ideas have gained popularity since they do not require cumbersome physical simulation and achieve high fidelity without the need of a specific model or rule set. However, existing methods are limited to the generation of static 2D paintings and cannot be applied in the context of 3D painting and animation where paint strokes change shape and length as the camera viewport moves. Our method targets this shortcoming by generating temporally-coherent example-based paint strokes that accommodate to such length and shape changes. We demonstrate the robustness of our method with a 2D painting application that provides immediate feedback to the user and show how our brush model can be applied to the screen-space rendering of 3D paintings on a variety of examples.
Targeting of exon VI-skipping human RGR-opsin to the plasma membrane of pigment epithelium and co-localization with terminal complement complex C5b-9

Purpose Rare mutations in the human RGR gene lead to autosomal recessive retinitis pigmentosa or dominantly inherited peripapillary choroidal atrophy. Here, we analyze a common exon-skipping isoform of the human retinal G protein-coupled receptor opsin (RGR-d) to determine differences in subcellular targeting between RGR-d and normal RGR and possible association with abnormal traits in the human eye. Methods The terminal complement complex (C5b-9), vitronectin, CD46, syntaxin-4, and RGR-d were analyzed in human eye tissue from young and old donors or in cultured fetal RPE cells by means of immunofluorescent labeling and high-resolution confocal microscopy or immunohistochemical staining. Results We observed that RGR-d is targeted to the basolateral plasma membrane of the RPE. RGR-d, but not normal RGR, is expressed in cultured human fetal RPE cells in which the protein also trafficks to the plasma membrane. In young donors, the amount of RGR-d protein in the basolateral plasma membrane was much higher than that in the RPE cells of older subjects. In older donor eyes, the level of immunoreactive RGR-d within RPE cells was often low or undetectable, and immunostaining of RGR-d was consistently strongest in extracellular deposits in Bruch’s membrane. Double immunofluorescent labeling in the basal deposits revealed significant aggregate and small punctate co-localization of RGR-d with C5b-9 and vitronectin. Conclusions RGR-d may escape endoplasmic reticulum-associated degradation and in contrast to full-length RGR, traffick to the basolateral plasma membrane, particularly in younger subjects. RGR-d in the plasma membrane indicates that the protein is properly folded, as misfolded membrane proteins cannot otherwise sort to the plasma membrane. The close association of extracellular RGR-d with both vitronectin and C5b-9 suggests a potential role of RGR-d-containing deposits in complement activation.
Antiprotozoal Activity of 1-Phenethyl-4-Aminopiperidine Derivatives

ABSTRACT A series of 44 4-aminopiperidine derivatives was screened in vitro against four protozoan parasites (Trypanosoma brucei rhodesiense, Trypanosoma cruzi, Leishmania donovani, and Plasmodium falciparum). This screening identified 29 molecules selectively active against bloodstream-form T. b. rhodesiense trypomastigotes, with 50% inhibitory concentrations (IC50) ranging from 0.12 to 10 μM, and 33 compounds active against the chloroquine- and pyrimethamine-resistant K1 strain of P. falciparum (IC50 range, 0.17 to 5 μM). In addition, seven compounds displayed activity against intracellular T. cruzi amastigotes in the same range as the reference drug benznidazole (IC50, 1.97 μM) but were also cytotoxic to L-6 cells, showing little selectivity for T. cruzi. None of the molecules tested showed interesting antileishmanial activity against axenic amastigotes of L. donovani. To our knowledge, this is the first report of the antitrypanosomal activity of molecules bearing the 4-aminopiperidine skeleton.
Artificial Intelligence Model to Predict Surface Roughness of Ti-15-3 Alloy in EDM Process

Conventionally the selection of parameters depends intensely on the operator’s experience or conservative technological data provided by the EDM equipment manufacturers that assign inconsistent machining performance. The parameter settings given by the manufacturers are only relevant with common steel grades. A single parameter change influences the process in a complex way. Hence, the present research proposes artificial neural network (ANN) models for the prediction of surface roughness on first commenced Ti-15-3 alloy in electrical discharge machining (EDM) process. The proposed models use peak current, pulse on time, pulse off time and servo voltage as input parameters. Multilayer perceptron (MLP) with three hidden layer feedforward networks are applied. An assessment is carried out with the models of distinct hidden layer. Training of the models is performed with data from an extensive series of experiments utilizing copper electrode as positive polarity. The predictions based on the above developed models have been verified with another set of experiments and are found to be in good agreement with the experimental results. Beside this they can be exercised as precious tools for the process planning for EDM.
Concurrent Verbal and Emotion Laterality Effects Exhibited by Normally Achieving and Learning Disabled Children

This study assessed both left- and right-hemisphere functions simultaneously when two-syllable words differing only in the initial stop consonant and spoken in different emotional tones were paired dichotically. Seventy-two right-handed normally achieving children, 12 boys and 12 girls at each of grades 1, 3, and 5, were instructed to detect either the presence of a specific word or of a specific emotion. In addition, 30 right-handed learning disabled (LD) children (age-matched to the normal controls) were assessed to determine whether LD children distribute verbal and nonverbal functions to different hemispheres. Results indicated that although both control and LD children demonstrated an overall REA for word stimuli and an LEA for emotional stimuli, and that emotional stimuli were easier to process than word stimuli, LD children were less accurate in processing both types of stimuli than their control counterparts. ‘Complementary specialization,’ as assessed through distribution of laterality effects, was found to be greater for control children than for LD children. However, the lack of consistency in complementary specialization found among the three developmental grade levels may be indicative that independent brain mechanisms underlying verbal and emotional processing have yet to be fully established in children. Further, in contrast to adult findings, a larger LEA was obtained for the emotion ‘happy’ than for the emotion ‘sad. ’ It was concluded that whereas independent hemisphere processing for words and emotions is somewhat prevalent for control children, LD children might not be as strongly lateralized for opposite hemisphere processing of these functions.
Fault Detection and Classification in Medium Voltage DC Shipboard Power Systems With Wavelets and Artificial Neural Networks

This paper proposes a fault detection and classification method for medium voltage DC (MVDC) shipboard power systems (SPSs) by integrating wavelet transform (WT) multiresolution analysis (MRA) technique with artificial neural networks (ANNs). The MVDC system under consideration for future all-electric ships presents a range of new challenges, in particular the fault detection and classification issues addressed in this paper. The WT-MRA and Parseval's theorem are employed in this paper to extract the features of different faults. The energy variation of the fault signals at different resolution levels are chosen as the feature vectors. As a result of analysis and comparisons, the Daubechies 10 (db10) wavelet and scale 9 are the chosen wavelet function and decomposition level. Then, ANN is adopted to automatically classify the fault types according to the extracted features. Different fault types, such as short circuit faults on both dc bus and ac side, as well as ground fault, are analyzed and tested to verify the effectiveness of the proposed method. These faults are simulated in real time with a digital simulator and the data are then initially analyzed with MATLAB. The case study is a notional MVDC SPS model, and promising classification accuracy can be obtained according to simulation results. Finally, the proposed fault detection algorithm is implemented and tested on a real-time platform, which enables it for future practical use.