Miracle-dz/UniFAR-FTUs huggingface dataset:
Dual‐mode bandpass filters using triangular ring resonators with coupling stubs

A novel dual‐mode bandpass filter using a microstrip triangular ring resonator with coupling stubs has been designed and tested. The basic configuration of this novel dual‐mode filter is a triangular ring resonator. Quasi‐L‐shaped I/O arms used as coupling stubs for enhanced coupling are nonorthogonally and symmetrically separated on each corner of the triangular resonator, and a perturbation element is introduced within the resonator at a symmetrical location. The effects of the lengths of the coupling stubs and the width of the perturbation element are studied. New filters having narrower or wider bandwidth and transmission zeros are presented. The proposed filter responses are in good agreement with the simulations and experiments. © 2004 Wiley Periodicals, Inc. Microwave Opt Technol Lett 43: 512–515, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.20519
Folded dielectric elastomer actuators

Polymer-based linear actuators with contractile ability are currently demanded for several types of applications. Within the class of dielectric elastomer actuators, two basic configurations are available today for such a purpose: the multi-layer stack and the helical structure. The first consists of several layers of elementary planar actuators stacked in series mechanically and parallel electrically. The second configuration relies on a couple of helical compliant electrodes alternated with a couple of helical dielectrics. The fabrication of both these configurations presents some specific drawbacks today, arising from the peculiarity of each structure. Accordingly, the availability of simpler solutions may boost the short-term use of contractile actuators in practical applications. For this purpose, a new configuration is here described. It consists of a monolithic structure made of an electroded sheet, which is folded up and compacted. The resulting device is functionally equivalent to a multi-layer stack with interdigitated electrodes. However, with respect to a stack the new configuration is advantageously not discontinuous and can be manufactured in one single phase, avoiding layer-by-layer multi-step procedures. The development and preliminary testing of prototype samples of this new actuator made of a silicone elastomer are presented here.
ESTIMATING THE POTENTIAL IMPACT OF CLIMATE CHANGE ON STREAMFLOW IN THE OLDMAN RIVER BASIN, ALBERTA: AN ANALOGUE APPROACH

Historical records of temperature and precipitation at three stations in the Upper Oldman drainage basis in southwestern Alberta were searched for values which match those forecast for the basin by three General Circulation models, the Goddard Institute of Space Science (GISS), the Geophysical Fluid Dynamics Laboratory (GFDL) and Oregon State University (OSU). An increase of 1 °C in mean annual temperature over a five year period combined with normal precipitation reduced streamflow by 15% annually. A 1% increase in precipitation combined with normal temperature increased streamflow by 1%.
Implantable Biomedical Devices

Almost a decade after the invention of the first semiconductor transistor in 1948, it took around a decade for the revolutionary technology to evolve from producing single devices to the integration of a few transistors as the first integrated circuit in 1958. Since then, integrated circuits have been in continuous progress for more than half a century as predicted by the well-known Moore’s law. While integrated circuits still continue their progress with the same exponential pace, it is almost a decade that a new branch of science and technology has emerged, known as integrated microsystems. This can be taken as the natural technological evolution from individual circuit chips and non-circuit modules, e.g., microelectromechanical systems (MEMS) devices, and subsequently to complete systems in small physical dimensions and with light weight. Integrated microsystems have opened windows of hope to providing efficient solutions to some of the problems that have not been resolvable by any other means so far.
Matched, Dual Mode Square Waveguide Corner

A design method for matching a square waveguide right angle corner for both E & H-plane (TE/sub 10/ and TE/sub 01/ modes) operation is presented. Results show VSWR <1.05 for 1.0 GHz bandwidth at X-Band with mode-to-mode isolation >30 dB.
A Survey on Caching in Mobile Edge Computing

Boosted by the visions of 5G technology, along with the proliferation of IoT devices, we are lucky to bear witness of a tremendous shift within the Internet, mobile computing, and ubiquitous applications pervading people’s daily life. To catch up with the speed of this evolution, new architectures, which enable us to decentralize and focus more on the edge of the network, have to show up. To effectively address the record-breaking growth of data traffic, we also have to come up with new caching mechanisms in coping with users’ demanding QoE along with other aspects, such as data privacy and energy efficiency. In this paper, we intend to begin with reviews on edge caching. First, we make a detailed overview of mobile edge caching. Then, we move on to the QoS and QoE part, discussing the related literature concerning these topics. We then start to address factors concerning edge caching and QoE. Four cutting-edge applications utilizing these technologies with challenges posed by current network architectures are made clear. Our paper closes with some future research directions.
Mechanical Design Optimization for Multi-Finger Haptic Devices Applied to Virtual Grasping Manipulation

This paper describes the design of a modular multi-finger haptic device for virtual object manipulation. Mechanical structures are based on one module per finger and can be scaled up to three fingers. Mechanical configurations for two and three fingers are based on the use of one and two redundant axes, respectively. As demonstrated, redundant axes significantly increase workspace and prevent link collisions, which is their main asset with respect to other multi-finger haptic devices. The location of redundant axes and link dimensions have been optimized in order to guarantee a proper workspace, manipulability, force capability, and inertia for the device. The mechanical haptic device design and a thimble adaptable to different finger sizes have also been developed for virtual object manipulation.
A Machine Learning Approach to Predictive Modelling of Student Performance

Background - Many factors affect student performance such as the individual’s background, habits, absenteeism and social activities. Using these factors, corrective actions can be determined to improve their performance. This study looks into the effects of these factors in predicting student performance from a data mining approach. This study presents a data mining approach in identify significant factors and predict student performance, based on two datasets collected from two secondary schools in Portugal. Methods – In this study, two datasets are augmented to increase the sample size by merging them. Following that, data pre-processing is performed and the features are normalized with linear scaling to avoid bias on heavy weighted attributes. The selected features are then assigned into four groups comprising of student background, lifestyle, history of grades and all features. Next, Boruta feature selection is performed to remove irrelevant features. Finally, the classification models of Support Vector Machine (SVM) , Naïve Bayes (NB) , and Multilayer Perceptron (MLP) origins are designed and their performances evaluated. Results - The models were trained and evaluated on an integrated dataset comprising 1044 student records with 33 features, after feature selection. The classification was performed with SVM, NB and MLP with 60-40 and 50-50 train-test splits and 10-fold cross validation. GridSearchCV was applied to perform hyperparameter tuning. The performance metrics were accuracy, precision, recall and F1-Score. SVM obtained the highest accuracy with scores of 77%, 80%, 91% and 90% on background, lifestyle, history of grades and all features respectively in 50-50 train-test splits for binary levels classification . SVM also obtained highest accuracy for five levels classification with 39%, 38%, 73% and 71% for the four categories respectively. The results show that the history of grades form significant influence on the student performance.
Bit error rate investigation of spin-transfer-switched magnetic tunnel junctions

A method is developed to enable a fast bit error rate (BER) characterization of spin-transfer-torque magnetic random access memory magnetic tunnel junction (MTJ) cells without integrating with complementary metal-oxide semiconductor circuit. By utilizing the reflected signal from the devices under test, the measurement setup allows a fast measurement of bit error rates at >106, writing events per second. It is further shown that this method provides a time domain capability to examine the MTJ resistance states during a switching event, which can assist write error analysis in great detail. BER of a set of spin-transfer-torque MTJ cells has been evaluated by using this method, and bit error free operation (down to 10−8) for optimized in-plane MTJ cells has been demonstrated.
Piezoelectric AlN-actuated micro-tuning forks for sensing applications

In this work, we present a detailed study of the first vibration modes of a micro-tuning fork electrically actuated by means of a differential electrode lying on a piezoelectric AlN layer. The actuation through a differential electrode allows the optimal excitation of the modes of interest, including in-plane modes. Lateral and perpendicular displacements have been measured for a complete characterization of the resonator. Promising results have been obtained, including high values of the quality factor, which reach values above 4300 in air for the anti-phase in-plane modes.
Efficiency analysis of a sliding-mode controlled quadratic boost converter

A quadratic boost converter with high DC gain to step up the voltage of a standard photovoltaic panel up to 400 V is analysed. First of all, a comparative analysis among boost, quadratic boost and cubic boost reveals that the quadratic boost exhibits the best trade-off between duty ratio range and converter efficiency. A hysteretic comparator is employed as a modulator to ensure the converter operation with high values of the duty ratio without risk of modulation saturation. A two- loop sliding-mode control is used to regulate the output voltage. An internal loop controls cycle by cycle the input current whose reference is established by an outer loop that processes the output voltage error by means of a proportional-integral compensating network. The measured results in a 100 W prototype operating in continuous conduction mode of average values, ripples, frequency and efficiency for different equilibrium points are in good agreement with the theoretical predictions.
High Resolution Forward-Looking Collision Avoidance Automotive Radar Using Stepped-Frequency Pulsed-Doppler(SFPD) Technique

A forward-looking automotive radar typically utilizes the frequency modulated continuous wave(FMCW) or pulsed-Doppler waveform for the Information acquisition of the target range and velocity. In order to obtain the high resolution target information, however, a narrow pulse width and wide bandwidth are inherently required, thus resulting in high peak power and high speed digital converter processing. In this paper, a stepped-frequency pulsed-Doppler(SFPD) waveform algorithm is proposed for high resolution forward looking automotive radar application. The performance of the proposed SFPD waveform technique is analyzed and compared with the conventional FMCW and PD method. Since this technique can be used for the high resolution target imaging with arbitrary range and Doppler resolution, it is expected to be useful In automotive radar target classification for the precision collision avoidance applications in the future.
The advances of integrated geospatial application in workforce management and field service optimization

Historically, workforce management and field services meant dispatchers and field technicians working with trucks, phones and paper. Today there are opportunities to exploit advancements in mobile technologies that distribute data to the field for greater efficiency and customer responsiveness. The business drivers that are forcing the technology issues are reduced drive time, automated dispatch, optimized scheduling and improved availability of information. This paper analyzes the technology revolution in geo-spatial applications and mobile computing platforms.
Aspect Mining Based on Object-Oriented Systems’ Dynamic Behavior Models

Aspect mining is a reverse engineering process that aims at finding crosscutting concerns in existing systems. This paper describes an aspect mining approach making use of the results of reverse engineering, statechart diagram, to aid in the understanding of an object-oriented software system’s behaviors. An aspect based on the recovered statechart diagram is defined as a set of states and an event. These states will transit to the same state after they send the event. Finally, systematic experiment is conducted in the paper in order to verify the correctness and validity of this approach.
Estimation of local pulse wave velocity using arterial diameter waveforms: Experimental validation in sheep

Increased arterial stiffness is associated with an increased risk of cardiovascular events. Estimation of arterial stiffness using local pulse wave velocity (PWV) promises to be very useful for noninvasive diagnosis of arteriosclerosis. In this work we estimated in an instrumented sheep, the local aortic pulse wave velocity using two sonomicrometry diameter sensors (separated 7.5 cm) according to the transit time method (PWVTT) with a sampling rate of 4 KHz. We simultaneously measured aortic pressure in order to determine from pressure-diameter loops (PWVPDLoop), the "true" local aortic pulse wave velocity. A pneumatic cuff occluder was implanted in the aorta in order to compare both methods under a wide range of pressure levels. Mean pressure values ranged from 47 to 101 mmHg and mean proximal diameter values from 12.5. to 15.2 mm. There were no significant differences between PWVTT and PWVPDLoop values (451±43 vs. 447±48 cm/s, p = ns, paired t-test). Both methods correlated significantly (R = 0.81, p<0.05). The mean difference between both methods was only −4±29 cm/s, whereas the range of the limits of agreement (mean ± 2 standard deviation) was −61 to +53 cm/s, showing no trend. In conclusion, the diameter waveforms transit time method was found to allow an accurate and precise estimation of the local aortic PWV.
A novel cryo-electron microscopy support film based on 2D crystal of HFBI protein

Cryo-electron microscopy (cryo-EM) has become the most powerful tool to resolve the high-resolution structures of biomacromolecules in solution. However, the air-water interface induced preferred orientation, dissociation or denaturation of biomacromolecules during cryo-vitrification is still a major limitation factor for many specimens. To solve this bottleneck, we developed a new type of cryo-EM support film using the 2D crystal of hydrophobin I (HFBI) protein. The HFBI-film utilizes its hydrophilic side to adsorb protein particles via electrostatic interactions and keep air-water interface away, allowing thin-enough ice and high-quality data collection. The particle orientation distribution can be optimized by changing the buffer pH. We, for the first time, solved the cryo-EM structure of catalase (2.28-Å) that exhibited strong preferred orientation using conventional cryo-vitrification protocol. We further proved the HFBI-film is suitable to solve the high-resolution structures of small proteins including aldolase (150 kDa, 3.34-Å) and hemoglobin (64 kDa, 3.6-Å). Our work implied that the HFBI-film will have a wide application in the future to increase the successful rate and efficiency of cryo-EM.
Surface Roughness Measurement By 2-D Digital Correlation Of Speckle Images

An optical roughness measuring instrument has been developed for applications in the field of mechanical engineering. It is based upon the angular-speckle-correlation (ASC) method. Two-dimensional processing of the digitized speckle patterns is performed by means of a fast correlation algorithm. Alignment errors, which inevitably occur in practice and may impair the measurement, can be compensated by evaluating the position of the maximum value of the 2D-cross-correlation function of the speckle patterns. Experiments have been carried out using differently machined rough surface samples.
A NOVEL METHOD FOR TRANSFORMED DATA LEAK DETECTION AND PREVENTION IN DISTRIBUTED HETEROGENEOUS DATA SHARING NETWORKS

: In the recent years Data Leakage Detection as a main problem in distributed network, which has heterogeneous users. The increasing ability to trail and collect large amounts of data with the use of technology has lead to an interest in the development of data protection algorithms, which helps to preserve user sensitive data’s in the distributed environment. There are several Data Leakage Detection and Data Leakage Prevention techniques have initiated for securing and protecting data’s. A recently proposed technique addresses the issue of data leakage in transferred data’s by sampling and matching techniques. However, the method can only perform detection part within the application level. There is several other ways to leak the transferred data within the host rather than the application. The proposed method designed and developed a Host Data Scrutinizer framework for distribution data security, which have developed in an email server for reconstruction secure email transfers. This includes different types of algorithms to detect and prevent data leaks either partially or fully. This is more effective than the currently available method in terms of the level of information loss. The proposed approach performs prediction and probability finding in order to identify and protect data from leakers. The experimental result shows the effective results on the distributed data in email security.
BIOMARKERS AS MEDIATORS USED IN ALZHEIMER'S DISEASE

Over the last decade, biomarkers have significantly improved our understanding of the pathophysiology of Alzheimer disease (AD) and provided valuable tools to examine different disease mechanisms and their progression over time. While several markers of amyloid, tau, neuronal, synaptic, and axonal injury, inflammation, and immune dysregulation in AD have been identified, there is a relative paucity of biomarkers which reflect other disease mechanisms such as oxidative stress, mitochondrial injury, vascular or endothelial injury, and calcium-mediated excitotoxicity. Importantly, there is an urgent need to standardize methods for biomarker assessments across different centers, and to identify dynamic biomarkers which can monitor disease progression over time and/or response to potential disease-modifying treatments. The updated research framework for AD, proposed by the National Institute of AgingAlzheimer’s Association (NIAAA) Work Group, emphasizes the importance of incorporating biomarkers in AD research and defines AD as a biological construct consisting of amyloid, tau, and neurodegeneration which spans pre-symptomatic and symptomatic stages. As results of clinical trials of AD therapeutics have been disappointing, it has become increasingly clear that the success of future AD trials will require the incorporation of biomarkers in participant selection, prognostication, monitoring disease progression, and assessing response to treatments. We here review the current state of fluid AD biomarkers, and discuss the advantages and limitations of the updated NIA-AA research framework. Importantly, the integration of biomarker data with clinical, cognitive, and imaging domains through a systems biology approach will be essential to adequately capture the molecular, genetic, and pathological heterogeneity of AD and its spatiotemporal evolution over time.
NovelGridworlds: A Benchmark Environment for Detecting and Adapting to Novelties in Open Worlds

As researchers are developing methods for detecting and accommo-dating novelties that will make AI agents more robust to unknown sudden changes in the “open worlds”, there is an increasing need for benchmark environments that allow for the systematic evaluations of the proposed AI techniques. We present “NovelGridworlds”, an OpenAI Gym environment framework for developing and evaluating AI agents that can detect and adapt to unknown sudden novelties in their environments. Based on a rich taxonomy of nov-elties illustrated in 4 different tasks with 12 novelties in each, we propose evaluation metrics for evaluating both planning systems and learning systems that can handle novelty and illustrate the metrics with results from simulations of both types of AI agents.
The Erika Oil Spill: Laboratory Studies Conducted To Assist Responders

ABSTRACT Immediately following the Erika oil spill, responders raised many questions concerning the identification of the fuel oil, its behavior in the water column, and physical properties, potential toxicity, environmental impacts, and the feasibility of various countermeasures to treat the spill. Several laboratories in France conducted simultaneous complementary investigations. The Laboratoire d'Analyse de Surveillance et d'Expertise de la Marine (LASEM) performed oil analyses of various samples collected at sea and on the shore for identification as well as for confirming the oil drifting predictions. The CEntre de Documentation de Recherche et d'Experimentations sur les pollutions accidentelles des eaux (CEDRE) studied oil behavior and its physical properties under realistic conditions in its flume test canal to predict the evolution of the product spilled at sea. Simultaneously, the Institut Francais du Petrole (IFP) and the Laboratoire de Physico-Toxico Chimie des systemes naturels (LPTC) carried .
Molecular Diversity Study in Tropical Maize inbred lines Using Microsatellites Markers

Background: Maize Tropical (Zea mays L., 2n=20) used in India has high complexity because of the diverse lines of this area. In the study, study, the genetic diversity and population structure decay of 352 selected tropical inbred lines collected from the breeding plan of India. Characterized using the maize lines with 70 Microsatellites. Results: With respect to molecular diversity, six sub grouped were identified. Markers were amplified and shown high polymorphism. With increase K value, the tropical group showed vertical structure with division into further groups All these SSR markers were select to detect high polymorphism. Primers ware showed in various bands showing different
Backpropagating through Fréchet Inception Distance

The Fréchet Inception Distance (FID) has been used to evaluate hundreds of generative models. We introduce FastFID, which can efﬁciently train generative models with FID as a loss function. Using FID as an additional loss for Generative Adversarial Networks improves their FID.