Miracle-dz/UniFAR-FTUs huggingface dataset:
Dielectrophoretic manipulation of drops for high-speed microfluidic sorting devices

We demonstrate a high-throughput drop sorter for microfluidic devices that uses dielectrophoretic forces. Microelectrodes underneath a polydimethylsiloxane channel produce forces of more than 10nN on a water drop in an inert oil, resulting in sorting rates greater than 1.6kHz. We investigate the dependence of such forces on drop size and flow. Alternate designs with electrodes on either side of a symmetric channel Y junction provide refined control over droplet selection.
Realizing homology classses by symplectic submanifolds

In this note we prove that a positive multiple of each even-dimensional integral homology class of a compact symplectic manifold $(M^{2n}, \omega)$ can be represented as the difference of the fundamental classes of two symplectic submanifolds in $(M^{2n}, \omega)$. We also prove the realizability of some integral homology classes by symplectic submanifolds in $(M^{2n}, \omega)$
Geometric Discretization of Lagrangian Mechanics and Field Theories

This thesis presents a unified framework for geometric discretization of highly oscillatory mechanics and classical field theories, based on Lagrangian variational principles and discrete differential forms. For highly oscillatory problems in mechanics, we present a variational approach to two families of geometric numerical integrators: implicit-explicit (IMEX) and trigonometric methods. Next, we show how discrete differential forms in spacetime can be used to derive a structure-preserving discretization of Maxwell's equations, with applications to computational electromagnetics. Finally, we sketch out some future directions in discrete gauge theory, providing foundations based on fiber bundles and Lie groupoids, as well as discussing applications to discrete Riemannian geometry and numerical general relativity.
Some inequalities for the queue GI/G/1

One of the central problems in the theory of queues has been the study of the singleserver queue with various assumptions about the probabilistic nature of the input and service processes. In particular, the queue GI1//1 (in the notation of Kendall (1953)) has been studied by Lindley (1952), and a complete formal solution, under mild analytic conditions, for the equilibrium waiting-time distribution, has been obtained by Smith (1953). This solution is not, however, easy to evaluate except for very special distributions of interarrival and service times. The present paper is concerned with the mean and variance of the waiting time, which are quantities of some practical importance. Inequalities are derived for these moments, both in equilibrium and non-equilibrium conditions. Thus we consider a queueing system in which customers C0, C1, . arrive and are attended to by a single server in the order of their arrival. The customer Cn waits in the queue for a time Wn, and is then served in a further time 8nWe denote by tn the time elapsing between the arrivals of successive customers Cn, Cn+? , and write n-i UnSntn Un E Ur. (1) r=O
An X-ray study of the open clusters NGC 2451 A and B

We have conducted a detailed study of the object NGC 2451, which actually consists of two dierent open clusters A and B along the same line of sight at 206 pc and 370 pc distance, respectively. Although belonging to the nearest clusters, they have not been much investigated until present due to strong contamination by field stars. ROSAT X-ray observations and optical UB VRphotometry are used to identify cluster members by means of X-ray emission and colour-magnitude diagrams. The identified stars concentrate nicely around the expected main sequences in the colour-magnitude diagram at the distances derived from astrometric investigations. Altogether, 39 stars are identified as member candidates of the nearer cluster A, 49 stars as member candidates of the more distant cluster B, and 22 faint stars are probably members of either of the two clusters, but due to large errors it is not clear to which one they belong. Further 40 stars identified with X-ray sources are probably non-members. For the first time, the range of known probable cluster members of NGC 2451 A and B has been extended downwards the main sequence to stars of spectral class M. Isochrone fitting yields an age of 50 to 80 Myrs for NGC 2451 A and 50 Myrs for NGC 2451 B, consistent with the X-ray luminosity distribution functions, which are comparable to other clusters in the same age range. Except from the occurence of four flares, the stars of both clusters do not show strong long-term X-ray variability exceeding a factor 5 over a time span of 1 to 3 years.
Laser operation of a heterojunction bipolar light-emitting transistor

Data are presented demonstrating the laser operation (quasicontinuous, ∼200K) of an InGaP–GaAs–InGaAs heterojunction bipolar light-emitting transistor with AlGaAs confining layers and an InGaAs recombination quantum well incorporated in the p-type base region. Besides the usual spectral narrowing and mode development occurring at laser threshold, the transistor current gain β=ΔIc∕ΔIb in common emitter operation decreases sharply at laser threshold (6.5→2.5,β>1).
User-generated digital flashcards yield better learning than premade flashcards.

Digital ﬂ ashcard users typically must choose between creating their own ﬂ ashcard content or using freely available ﬂ ashcard sets. The latter is more convenient and saves time, but is it more effective for learning? We conducted six experiments, each involving the use of user-generated or premade ﬂ ashcards to learn material drawn from educational text passages, followed by a 48-hr delayed criterial test. Different approaches to generating content and variations in the quality of premade content were also examined. Across experiments, user-generated ﬂ ashcards improved memory relative to premade ﬂ ashcards (an estimated advantage of d = 0.45, 95% CI [0.25, 0.66]), and in most cases, enhanced performance on application questions (an estimated advantage of d = 0.29, 95% CI [0.12, 0.45]). These results suggest that generating one ’ s own ﬂ ashcards enables productive learning processes that enhance memory and comprehension. Accordingly, digital ﬂ ashcard users may bene ﬁ t from eschewing premade versions in favor of making their own.
Morphology and Raman spectral parameters of Bohemian microdiamonds: implications to elastic geothermobarometry

In this work, we combine the morphology and internal structure of northwestern Bohemian microdiamonds with their Raman spectral parameters to describe and understand their relationship. We evaluate our data according to the theory of elasticity and discuss implications for elastic geothermobarometry of diamond inclusions in garnet. We conclude that microdiamonds enclosed in kyanite, garnet and zircon differ in morphology and internal structure depending on the type of the host rock and host phase. Single crystal diamond octahedra in kyanite in the acidic gneiss show predominantly Raman shift towards higher wavenumbers (upshift), while single and polycrystalline diamonds enclosed in garnet and zircon in the intermediate garnet–clinopyroxene rock yield more variable Raman shift including a shift towards lower wavenumbers (downshift). This is consistent with closed boundaries between diamond and kyanite observed using FIB-TEM, while interfaces between diamond and garnet or zircon are commonly open. Moreover, higher variability in the Raman shift in diamond hosted by garnet or zircon may be caused by complex internal structure and the presence of other phases. At the same time, a diamond in kyanite features relatively high full-width-at-half-maximum ( FWHM ) due to the anisotropy of thermal contraction, which is reflected by the plastic deformation of diamond mediated by dislocation glide at T ≥ 1000 °C. The entrapment pressure ( P trap ) for diamonds in garnet was calculated using elastic geobarometry to test its compatibility with the existing peak pressure estimated by conventional thermobarometry. The “downshifted” diamonds exhibit entrapment pressures of 4.8 ± 0.14 and 4.99 ± 0.14 GPa at an entrapment temperature of 1100 °C, using unstrained reference diamond from the literature and own measurements, respectively. This is consistent with the earlier estimates and the elastic theory and does not require any elastic resetting suggested to account for the reported upshift in garnet. Our data suggest that the upshift in diamond hosted by garnet is related to the proximity of other diamond grains. We conclude that the use of diamond inclusions in elastic barometry should be backed by careful evaluation of its internal structure and associated phases and restricted to isometric monocrystalline diamond grains not occurring in clusters as required by the method.
Alternative therapy for respiratory muscle training using breath stacking

Objective: To evaluate the effectiveness of the breath-stacking technique as a method of ventilatory muscle training. Methods: Thirty-eight healthy youngsters were included in the study. The maximum respiratory pressures were evaluated in cmH2O by a digital manovacuometer. The breath-stacking system (face mask attached to a T-tube with a unidirectional inspiratory valve) was used as an overload method in a 4-week 12-session ventilatory muscle training program. Results: Both maximal inspiratory and expiratory pressures increased significantly after ventilatory muscle training for all. Positive peak pressure also increased significantly at the end of the program. Conclusion: Breath-stacking generates sufficient overload to ventilatory muscles to consistently increase maximal respiratory pressures when used in a ventilatory muscle training protocol. The technique was well tolerated, although it needs to be tested in clinical situations involving muscle weakness and other organic dysfunctions.
Anti-Interference Recognition for Aerial Infrared Object Based on Convolutional Feature Inference Network

The infrared decoy countermeasure technology develops along with the infrared imaging guidance technology. The release of infrared decoys can block the object and destroy the integrity of the object features. The traditional statistical approach based on feature fusion matching for pattern recognition is not effective in handling this problem. To improve the characterization ability of the invariant detail features in the infrared object domain and improve the classification accuracy of the probability identification model, this article proposes an inference recognition model that combines the convolutional features and the Bayesian network. The proposed model exploits the convolutional neural network to extract the detailed feature information of the object in the infrared image. Then, it uses the 2DPCANet screening mechanism to reduce the dimensionality and select more obvious detailed information in the candidate region. Based on the combination of human prior knowledge and posterior data, an infrared object recognition probability model is established through the application of the Bayesian network. The performance of the proposed algorithm is tested on the complex air combat simulation image dataset. The experimental results indicate that the recognition rate of the proposed anti-interference recognition algorithm reaches 94.17%.
Enhanced Classification of Dog Activities with Quaternion-Based Fusion Approach on High-Dimensional Raw Data from Wearable Sensors

The employment of machine learning algorithms to the data provided by wearable movement sensors is one of the most common methods to detect pets’ behaviors and monitor their well-being. However, defining features that lead to highly accurate behavior classification is quite challenging. To address this problem, in this study we aim to classify six main dog activities (standing, walking, running, sitting, lying down, and resting) using high-dimensional sensor raw data. Data were received from the accelerometer and gyroscope sensors that are designed to be attached to the dog’s smart costume. Once data are received, the module computes a quaternion value for each data point that provides handful features for classification. Next, to perform the classification, we used several supervised machine learning algorithms, such as the Gaussian naïve Bayes (GNB), Decision Tree (DT), K-nearest neighbor (KNN), and support vector machine (SVM). In order to evaluate the performance, we finally compared the proposed approach’s F-score accuracies with the accuracy of classic approach performance, where sensors’ data are collected without computing the quaternion value and directly utilized by the model. Overall, 18 dogs equipped with harnesses participated in the experiment. The results of the experiment show a significantly enhanced classification with the proposed approach. Among all the classifiers, the GNB classification model achieved the highest accuracy for dog behavior. The behaviors are classified with F-score accuracies of 0.94, 0.86, 0.94, 0.89, 0.95, and 1, respectively. Moreover, it has been observed that the GNB classifier achieved 93% accuracy on average with the dataset consisting of quaternion values. In contrast, it was only 88% when the model used the dataset from sensors’ data.
Diagnostics Using Non-Invasive Technologies in Dermatological Oncology

Simple Summary Skin tumors are appearing with increasing frequency worldwide. To face this health problem, new technologies and devices have been developed in recent years, allowing the acquisition of information about healthy and neoplastic skin, unavailable until a few years ago. Dermatologists need, therefore, continuous training and updating to ensure adequate patient diagnosis and treatment. This article aims to review the currently available technologies for the screening, diagnosis, mapping and monitoring in dermatological oncology highlighting their applications, limitations and possible future perspectives. Abstract The growing incidence of skin cancer, with its associated mortality and morbidity, has in recent years led to the developing of new non-invasive technologies, which allow an earlier and more accurate diagnosis. Some of these, such as digital photography, 2D and 3D total-body photography and dermoscopy are now widely used and others, such as reflectance confocal microscopy and optical coherence tomography, are limited to a few academic and referral skin cancer centers because of their cost or the long training period required. Health care professionals involved in the treatment of patients with skin cancer need to know the implications and benefits of new non-invasive technologies for dermatological oncology. In this article we review the characteristics and usability of the main diagnostic imaging methods available today.
Self-aware cycle curriculum learning for multiple-choice reading comprehension

Multiple-choice reading comprehension task has recently attracted significant interest. The task provides several options for each question and requires the machine to select one of them as the correct answer. Current approaches normally leverage a pre-training and then fine-tuning procedure that treats data equally, ignoring the difficulty of training examples. To solve this issue, curriculum learning (CL) has shown its effectiveness in improving the performance of models. However, previous methods have two problems with curriculum learning. First, most methods are rule-based, not flexible enough, and usually suitable for specific tasks, such as machine translation. Second, these methods arrange data from easy to hard or from hard to easy and overlook the fact that human beings usually learn from easy to difficult, and from difficult to easy when they make comprehension reading tasks. In this article, we propose a novel Self-Aware Cycle Curriculum Learning (SACCL) approach which can evaluate data difficulty from the model’s perspective and train the model with cycle training strategy. The experiments show that the proposed approach achieves better performance on the C3 dataset than the baseline, which verifies the effectiveness of SACCL.
Proportional Fair Trajectory Design and Resource Allocation for UAV-Assisted SWIPT System

In this study, we investigate the proportional fair trajectory design and resource allocation for an unmanned-aerial-vehicle (UAV)-assisted simultaneous wireless information and power transfer (SWIPT) system, where multiple ground nodes (GNs) receive information and harvest energy from the signal transmitted by the UAV using a power-splitting (PS) policy. With this system, we aim to maximize the sum of the logarithmic average spectral efficiency (SE) of the GNs while guaranteeing the average harvested energy requirement to improve the average SE and user fairness simultaneously. To deal with the nonconvexity of the optimization problem, we adopt the quadratic transform and first-order Taylor expansion, proposing an iterative algorithm to find the optimal trajectory and transmit the power of the UAV and the PS ratio of the GNs. Through simulations, we confirm that the proposed scheme achieves a higher average SE compared with the conventional baseline schemes and ensures a level of user fairness similar to that of the state-of-the-art baseline scheme.
Integrated Safety and Security Enhancement of Connected Automated Vehicles Using DHR Architecture

Safety and security are interrelated and both essential for connected automated vehicles (CAVs). They are usually investigated independently, followed in standards ISO 26262 and ISO/SAE 21434 respectively. However, more functional safety and security features of in-vehicle components making existing safety mechanisms weaken security mechanisms and vice versa. This results in a dilemma that the safety-critical and security-critical in-vehicle components can not be protected. In this paper, we propose a dynamic heterogeneous redundancy (DHR) architecture to enhance safety and security of CAVs simultaneously. We first investigate the current status of integrated safety and security analysis and explore the relationship between safety and security. Then, we propose a new taxonomy of in-vehicle components based on safety and security features. Finally, a dynamic heterogeneous redundancy (DHR) architecture is proposed to guarantee integrated functional safety and cyber security of connected vehicles for the first time. A case study on an automated bus shows that DHR architecture can not only detect unknown failures and ensure functional safety, but also detect unknown attacks to protect cyber security. Furthermore, we provide an in-depth analysis of quantification for CAVs performance using DHR architecture, and identify challenges and future research directions. Overall, the integrated safety and security enhancement is an emerging research.
Efficient two-stage vector quantization speech coder using wavelet coefficients of excitation signals

An improved backward prediction coder featuring two-stage vector quantization (VQ) of shape codevectors is presented. Efficient two-stage VQ is achieved using the wavelet coefficients of excitation signals; i.e., wavelet coefficients are calculated by applying a discrete wavelet transform to excitation signals, and the results are divided into an approximation group and a detail group. The data lengths of both approximation and detail coefficients are half that of conventional two-stage VQ systems. Simulation results show that the proposed coder achieves a better weighted signal-to-noise ratio (WSNR) than conventional coders and, in terms of reconstructed speech quality, ranks between the FS-1016 Code Excited Linear Prediction (CELP) coder and the Vector Sum Excited Linear Predictive Coding (VSELP) coder.
Parallel correlation measurements in the scrape-off layer of the Joint European Torus

In the scrape-off layer of the Joint European Torus [P.-H. Rebut, R. J. Bickerton, and B. E. Keen, Nucl. Fusion 25, 1011 (1985)], Langmuir probes were used to measure the correlation of ion saturation current fluctuations parallel to the magnetic-field B. It was possible to realize three different probe tip separations (connection lengths) ∥B under almost identical plasma conditions and magnetic configuration. Among these, a probe tip separation of 66 m ∥B represents the largest value ever realized for this type of experiment. It was found that the correlation is reduced from ⩾80% at 0.75 m probe tip separation ∥B in the divertor to ≈40% at 23 m, but remains at ≈40% even for the 66 m separation. An upper limit for the ratio between the average wave numbers parallel and perpendicular to the magnetic field |k∥/k⊥|<0.0022 is found, but the results are in good agreement with a parallel wave number k∥=0.
Real-Time Prediction of Car Driver's Emotions using Facial Expression with a Convolutional Neural Network-based Intelligent System

When driving, the most crucial factor to consider is your own safety. Driver’s must be kept under observation for any potential harmful act, whether intentional or inadvertent, in order to ensure a safe navigation for a driver. As a result, a real-time emotion detection system for a driver has been developed to detect, exploit, and evaluate the driver's emotional state. This paper discusses how to recognize emotions using facial expressions for application in active security systems for drivers. We discuss our research and development of a Convolutional Neural Network-based intelligent system for face image-based expression classification in this paper.
Direct measurements of neutrino mass

The most compelling evidence of the existence for neutrino masses are the up-down asymmetry of the atmospheric muon neutrino flux and, more recently, the measurement of the solar electron neutrino flux. These experiments, which are interpreted on the basis of the flavor oscillation hypothesis, indicate the there is some spectrum of 3 or more masses. A combination of the experimental flavor oscillation data allows a range of splitting value among the mass eigenstates that makes very attractive the investigation in the sub eV neutrino mass range, down to 0.1 eV/c2. The direct measurements via the β-decay, which are the more straightforward way for determining individual mass eigenstates, must reach such a neutrino mass sensitivity. In these frame a calorimetric experiment with 187-Re, could play a starring role. In fact, a 1 eV energy resolution experiment could be possible with a large array of small microcalorimeters. Together with the project of 1 eV resolution beta electrostatic spectrometer for tritium.
A Comprehensive Review of Bradykinin-Induced Angioedema Versus Histamine-Induced Angioedema in the Emergency Department

Angioedema (AE) is a condition that is frequently encountered in the emergency department (ED). It is a rare condition with localized, asymmetrical swelling of the skin and/or mucosa that is frequently nonpruritic and primarily affects locations with loose connective tissue. Physicians must have a thorough understanding of this condition since it can cause fatal airway compromise, which might be the presenting symptom. Histamine-mediated AE is the most common type of AE seen in EDs. However, ED physicians must be on the lookout for the less common bradykinin-mediated types of AE as these do not respond to the same therapy as histamine-mediated AE. Hospitals may lack specialized drugs or protocols, and many ED staff may be unable to identify or treat bradykinin-mediated AE. It is crucial to understand the pathophysiology of the various kinds of AE in order to optimize treatment. The goal of this review paper is to provide an overview of the pathophysiology, clinical manifestations, and treatment options for bradykinin and histamine-induced AE in the ED.
Front aggregation and labyrinthine pattern in the drying process of two-dimensional wet granular systems

The aggregation process of granules driven by the motion of water-air fronts in the drying process of two-dimensional wet granular systems is experimentally studied. The fronts and aggregated granules interact with each other during this drying, and a labyrinthine pattern is formed as a result. A qualitative framework of the pattern formation is given, and topological and metrical properties of the pattern are also discussed.