Miracle-dz/UniFAR-FTUs huggingface dataset:
Discretized Simulation of Vortex Sheet Evolution with Buoyancy and Surface Tension Effects

The discrete vortex method previously used by Rosenhead and others to compute the roll-up of a vortex sheet in a single fluid is extended to the situation in which the vortex sheet is a horizontal interface separating a lighter inviscid fluid above from a heavier fluid below. The stabilizing effects of gravity and surface tension are included in a discretized circulation equation used to calculate the circulations of individual vortices during the course of the computation. Calculations show the evolution of the interface under stable, unstable, and marginally unstable conditions as given by linear Kelvin-Helmholtz instability theory. Under stable conditions, finite amplitude disturbances oscillate with a period slightly larger than predicted by classical theory for infinitesimal perturbations. For unstable conditions, the finite amplitude growth rate is much smaller than the corresponding linearized growth rate for infinitesimal disturbances. Under marginally unstable conditions, small irregularities along the interface cause numerical difficulties before the maximum disturbance amplitude and extent of roll-up has been computed.
Iterating the Arimoto-Blahut algorithm for faster convergence

The Arimoto-Blahut algorithm determines the capacity of a discrete memoryless channel through an iterative process in which the input probability distribution is adapted at each iteration. While it converges towards the capacity-achieving distribution for any discrete memoryless channel, the convergence can be slow when the channel has a large input alphabet. This is unfortunate when only a small number of the input letters are assigned non-zero probabilities in the capacity-achieving distribution. If we knew which input letters will end up with a probability of zero, we could eliminate these letters and operate the algorithm on a subset of the input alphabet. The algorithm would converge towards the same solution faster. We present an algorithm which makes use of this fact to speed up the convergence of the Arimoto-Blahut algorithm in such situations.
Light element abundances in the young open clusters NGC 3293, NGC 4755 and NGC 6231: Tracers of stellar evolution

The abundances of He (LTE), C, N, and O (NLTE) were derived for 21 B stars in three young open clusters. Almost all the stars show subsolar CNO abundances. However, the mean oxygen abundance for each programme cluster appears to be in marginal agreement with the most recent revisions of the solar value. After consideration of the CN abundances in this sample, there is no clear evidence of internal mixing. Only three stars among the non-supergiants seem to show a nitrogen enhancement. Two of them have a fairly low projected equatorial velocity (admittedly, they may be rapid rotators seen pole-on); the third one is a denite fast rotator. In the lower gravity stars (three stars in this sample with log g< 3:0) some kind of mixing has apparently occurred. The supergiants do not dier signicantly from the other programme stars in their respective helium contents. The mean helium abundance for each cluster is close to the standard value, (He/H) 11:0.
Physiological and Transcriptomic Analyses Revealed That Humic Acids Improve Low-Temperature Stress Tolerance in Zucchini (Cucurbita pepo L.) Seedlings

Zucchini (Cucurbita pepo L.) is one of the main vegetable crops grown under protected cultivation in northern China. Low-temperature (LT) stress severely inhibits the growth of zucchini seedlings, resulting in reductions in yield and quality. Here, using three kinds of different humic acids, including coal-based humic acid (CHA), fulvic acid (FA), and biochemical humic acid (BHA), we investigated the effects of humic acids against LT stress (5 °C) in zucchini seedlings. Treatment with all three kinds of humic acids improves LT stress tolerance by decreasing oxidative damage through increases in antioxidative enzyme activities and the contents of soluble sugar and proline in zucchini seedlings, especially after BHA application. Comparative transcriptomic analysis revealed that a total of 17 differentially expressed genes (DEGs) were commonly induced in the leaves of FA-, CHA-, and BHA-treated zucchini seedlings under LT stress, including calmodulin, ethylene-responsive transcription factors (TFs), peroxidases, and 10 TFs, including two NAC and seven WRKY genes. Altogether, these results indicated that supplementation with humic acids reprograms plant metabolism and modulates the expression of genes involved in ROS scavenging, phytohormone metabolism, or signaling pathways, finally improving LT stress tolerance in zucchini seedlings.
Observation of radio‐frequency discharges at various driving frequencies

Radio‐frequency discharges at various driving frequencies f in the range of 1.9–28 MHz are observed, especially from the viewpoint of the sheath structure. The results reveal that for f≥10 MHz, the sheath thickness Zs measured by an emissive probe varies directly as f−1, while for f≤10 MHz, Zs∝f−1/2. The electron density estimated from the ion saturation current of a needle probe is almost proportional to f2 in the former case. High‐energy electrons accelerated by the expanding rf sheath can contribute to sustaining rf plasmas in the high‐frequency region, whereas in the low‐frequency region, secondary electrons emitted from an electrode can contribute to it in a similar manner to dc and ac discharges.
Image restoration by minimizing objective functions with nonsmooth data-fidelity terms

We present a theoretical study of the recovery of images x from noisy data y by minimizing a regularized cost-function F(x,y)=/spl Psi/(x,y)+/spl alpha//spl Phi/(x), where /spl Psi/ is a data-fidelity term, /spl Phi/ is a smooth regularisation term and /spl alpha/>0 is a parameter. Generally /spl Psi/ is a smooth function; only a few papers make an exception. Non-smooth data-fidelity terms are avoided in image processing. In spite of this, we consider both smooth and non-smooth data-fidelity terms. Our ambition is to catch essential features exhibited by the local minimizers of F in relation with the smoothness of /spl Psi/. Cost-functions with non-smooth data-fidelity exhibit a strong mathematical property which can be used in various ways. We then construct a cost-function allowing aberrant data to be detected and selectively smoothed. The obtained results advocate the use of non-smooth data-fidelity terms.
Cooling of solar wind electrons inside 0.3 AU

Mean temperature gradients of solar wind electrons between 0.3 and 1 AU are determined from Helios observations. Electrons are found to cool more slowly than adiabatically, with flattest temperature profiles in high-speed streams. These in situ observations are used to estimate the radial gradients of Te inside 0.3 AU under the constraint of matching coronal temperatures. Electrons in high-speed streams are inferred to cool more strongly closer to the Sun than within the Helios orbital range. For low-speed wind, no significant breaks in the temperature profiles have been found, while for intermediate-speed structures the results are somewhat ambiguous. These results are discussed in the context of solar wind generation and modeling.
Auditing the Image Quality of Mammograms

A quantitative approach to assessing the image quality of mammograms at screening centres has been developed. In this study an expert radiologist made a subjective judgement of the overall film blackening for each mammogram taken on a sequential series of 100 women attending screening over a period of three days on a single screening system. To relate these subjective judgements to quantitative measurements each mammogram was digitised and the distribution of film densities analysed. Average film densities in the main breast area were found to vary from 1.2 to 2.4, with an average of 1.8 for oblique views and 1.7 for CC views. The densities measured on quality control films of 40 mm thick PMMA exposed at 28 kV and 30 kV, and processed at the same time as the clinical films, were 1.52 and 1.67 respectively. Mammograms were judged satisfactory when film densities in the main breast region were in the range 0.8 to 2.8 with average densities of about 1.6 to 2.0. The method described allows the ideal film blackening to be quantitatively assessed.
Data Utilization in the Education Field by Local and Central Governments in Japan

In Japan, certain local governments have been actively utilizing administrative and other source data to build databases that can be used for children’s education policy. The central government is tackling initiatives in the area of education. However, such initiatives remain to be progressed, compared with initiatives of those local government cases. This paper provides a case study of database construction and its utilization for educational purposes in local and central governments in Japan through 2022. The results show that, while various efforts are currently being made by local and central governments to construct databases and develop methods for their use, linking of data, development of subjective data, and securing and training of human resources are issues to be addressed in the future.
Subject-Invariant Deep Neural Networks Based on Baseline Correction for EEG Motor Imagery BCI

Electroencephalography (EEG)-based brain–computer interface (BCI) systems have been extensively used in various applications, such as communication, control, and rehabilitation. However, individual anatomical and physiological differences cause subject-specific variability of EEG signals for the same task, and BCI systems thus require a calibration procedure that adjusts system parameters to each subject. To overcome this problem, we propose a subject-invariant deep neural network (DNN) using baseline-EEG signals that can be recorded from subjects resting in comfortable states. We first modeled the deep features of EEG signals as a decomposition of subject-invariant and subject-variant features corrupted by anatomical/physiological characteristics. Subject-variant features were then removed from the deep features by learning the network with a baseline correction module (BCM) using the underlying individual information in baseline-EEG signals. The subject-invariant loss forces the BCM to assemble subject-invariant features that have the same class, irrespective of the subject. Using 1-min baseline-EEG signals of the new subject, our algorithm can eliminate subject-variant components from test data without the calibration process. The experimental results show that our subject-invariant DNN framework significantly increases decoding accuracies of the conventional DNN methods for BCI systems. Furthermore, feature visualizations illustrate that the proposed BCM extracts subject-invariant features that are close to each other in the same class.
Integrated Data Mapping Engine (DaME) for Financial Services

Enterprise organizations have vast datasets that need comprehensive analysis on a frequent basis, in order to manage data and take business decisions based on it. However, we observe that there can be a lack of industry standards for definitions of key terms. Additionally, there is a lack of governance for maintaining business processes. This typically leads to disconnected siloed datasets generated from disintegrated systems. To address these challenges, we developed a novel, integrated methodology DaME (Data Mapping Engine) that performs data mapping using ensemble of NLP techniques.The results from the industrial application and evaluation of DaME on a financial services dataset are encouraging that it can help reduce manual effort by automating data mapping and reusing the learning. The accuracy from our dataset in the application is much higher at 69% compared to the existing state-of-the-art with an accuracy of 34%. It has also helped improve the productivity of the industry practitioners, by saving them 14,000 hours of time spent manually mapping vast data stores over a period of ten months.
Why Petals? Naïve, but Not Experienced Bees, Preferentially Visit Flowers with Larger Visual Signals

Simple Summary Why do plants have showy flowers? Clearly, many plant species must attract pollinators and have floral adaptations for this. However, some flowers attract insects without showy petals. This suggests that a key function of showy visual signals is to attract naïve, first-time pollinator visitors. This is similar to how a restaurant with a large sign and showy visual signals may be especially important in gaining first-time visits when competing with other establishments or plants. Customers or pollinators will know if the first visit is rewarding and use this to decide whether to revisit. First, they must visit. Most flowers and restaurants would benefit from more visitors. Restaurants usually have empty tables, and many flowers are pollen limited in their reproduction. Here, we manipulated the ray petals of inflorescences of two garden flowers to test the hypothesis that the role of showy visual signals is to attract naïve visitors. On their first inflorescence visit to both species, naïve honey bees and bumble bees were more likely to visit intact inflorescences, than those with ray petals removed. However, by the tenth consecutive inflorescence, bees showed no preference. A positive correlation was observed between the visitation of inflorescences with no petals and the inflorescence number on both study plants, for both bees. These results strongly suggest that a key function of showy petals is to attract naïve, first-time visitors. Abstract Flower evolution includes a range of questions concerning the function of showy morphological features such as petals. Despite extensive research on the role of petals in attracting pollinators, there has been little experimental testing of their importance in attracting naïve versus experienced flower-visitors. In an exploratory field study, we manipulated the ray petals of inflorescences of two garden flowers, Rudbeckia hirta and Helenium autumnale, to test the hypothesis that these showy structures primarily function to attract first-time, naïve, visitors. On their first inflorescence visit to both species, naïve honey bees and bumble bees were more likely to visit intact inflorescences, than those with ray petals removed. However, by the tenth consecutive inflorescence on the same visit to the flower patch, test insects showed no preference. A positive correlation was observed between the visitation of inflorescences with zero petals and inflorescence number on both study plants, for both bees. These results suggest that a key function of showy petals is to attract naïve, first-time visitors. Similar to how a restaurant attracts diners with a large sign, showy signals may be vital to enticing first-time visitors when competing with other establishments or plants for customers or pollinators. We hope the findings of this exploratory study will stimulate further work in this area.
Quadratic time-frequency analysis and sequential recognition for specific emitter identification

Specific emitter identification (SEI) is a state-of-the-art in electronic warfare. The conventional methods for SEI hardly satisfy the modern electronic reconnaissance. In this study, first the authors study the quadratic time-frequency distributions and its slice features and noise analysis. Based on the time-frequency features, two sequential recognition methods based on probabilistic support vector machine (SVM) and iterative least-square estimation are studied, respectively. The proposed methods are able to reject the interference pulses and update the classifier or feature parameters, which accomplish the online recognition and online learning of specific radar emitter. Experiments on actual intercepted radar signals with the same type verify the correctness and validity of the proposed methods.
Face Detection Based on Gabor Wavelet Transform and Statistical Cluster Model

A gray-image face detection algorithm was proposed, in which feature vectors were Gabor wavelet coefficients at 4 scales and 6 orientations. Firstly, feature vectors of training samples and negative samples were separately clustered. Secondly, these clusters were reduced by discriminate analysis. Finally, distribution model of feature vectors was built and average probability was calculated to determine if the testing image was similar to face samples. The experimental results show the algorithm is effective.
Effects of coil shapes on wireless power transfer via magnetic resonance coupling

The wireless system with four coil resonators is a popular configuration for mid-range wireless power transfer (WPT) via magnetic resonance coupling. The design parameters of four coils have strong impact on efficiency, bandwidth, and transfer distance of the WPT system. In this work, a comprehensive study on effects of coil shapes is conducted. In particular, helix coils, planar spiral coils, and square helix coils are studied. It is shown that the helix coils offer the best performance (e.g. the highest efficiency, the widest bandwidth, and the longest transfer distance) under optimal load whereas the planar spiral coils exhibit the worst performance among these three types of coils. Nevertheless, the performance of the WPT system with helix coils degrades more rapidly than these with other two types of coils when the distance between the transmitting and receiving coils increases.
The Definition and Significance of an Effective Radius for Ice Clouds

Abstract Single scattering shortwave properties of ice clouds are frequently derived in terms of the “effective” radius (re) of the ice crystal population. Substantial discrepancies between definitions exist, making interpretation and comparison of various radiative parameterization schemes and satellite retrieval techniques difficult. Each definition of effective radius can be related to more physically based parameters, such as the crystal dimension of median mass. For vertically inhomogeneous clouds, the relative importance of different cloud heights in determining the retrieved re is examined, and a definition of re for vertically inhomogeneous clouds composed of hexagonal columns is proposed. This definition shows reasonable agreement with the re values that would be retrieved using visible and near-infrared channels for some microphysical data acquired in tropical ice clouds near Kwajalein, Marshall Islands, in the mid-1970s. Because only the upper parts of a thick ice cloud are detected by satellit.
Frontogenesis in the presence of small stability to slantwise convection

Abstract It is often observed that, despite the existence of near neutrality to slantwise convection, rainbands and snowbands can persist for long periods with narrow intense updrafts producing large quantities of precipitation in many cases. This is probably due to the presence of active frontogenesis which, as shown here, maintains such structures. In order to investigate this process, we use two-dimensional semigeostrophic theory to solve the deformation-forced frontogenesis problem for a circumstance in which the stability to moist slantwise convection is small but positive. In this case, numerical simulation is necessary to determine the evolution of the front. Several previous studies have described the role of diabatic forcing in modifying the cross-frontal circulation by use of the Sawyer-Eliassen equation. In particular, analytic solutions of that equation for the case of small moist symmetric stability show that a narrow updraft should occur ahead of the maximum geostrophic frontogenesis. Numeri.
Integrated wearable and mobile ultrasound and photoplethysmography device via transparent ultrasound transducer

Fusion sensors, including photoplethysmograms, cameras, microphones, ultrasound sensors, and accelerometers, are commonly used in mobile and wearable healthcare electronics to measure bio-signals. However, small size is in high demand, but integrating multiple sensors into small mobile or wearable devices is challenging. This study presents two new opto-ultrasound sensors: (1) a wearable device with both photoplethysmography (PPG) and ultrasound (US) capabilities, and (2) a PPG sensor built-in mobile smartphone with an integrated US sensor using a transparent ultrasound transducer (TUT). The TUT has a center frequency of 6 MHz, a 50% bandwidth, and is 82% transparent in the visible and near-infrared ranges. To demonstrate its potential, we developed a wearable device combining photoplethysmography and ultrasound capabilities and fused the TUT to the smartphone. We used this setup to measure heart rates optically and acoustically in human subjects and to calculate oxygen saturation optically through the TUT. This proof-of-concept represents a unique fusion of sensors for small mobile and wearable devices that aim to improve digital healthcare. The results of this research can serve as a basis for innovative development of sensor-based high-tech industrial applications such as healthcare, automobiles, robots, and drones.
Expert Consensus on Morphofunctional Assessment in Disease-Related Malnutrition. Grade Review and Delphi Study

Disease-related malnutrition (DRM) affects approximately a third of hospitalized patients and is associated with an increased risk of morbimortality. However, DRM is often underdiagnosed and undertreated. Our aim is to evaluate the prognostic value of morphofunctional tools and tests for nutritional assessment in clinical practice. A systematic literature review was conducted to identify studies relating to the morphofunctional assessment of nutritional status and mortality or complications. Evidence was evaluated using the GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) method. Twelve GRADE recommendations were made and divided into seven topics: food intake and nutrient assimilation, anthropometry, biochemical analysis, hand grip strength, phase angle, muscle imaging, and functional status and quality of life. From these recommendations, 37 statements were developed and scored in a two-survey Delphi method by 183 experts. A consensus was reached on accepting 26/37 statements. Surveys had high internal consistency and high inter-rater reliability. In conclusion, evidence-based recommendations were made on the prognostic value of morphofunctional assessment tools and tests to assess malnutrition, most of which were found to be feasible in routine clinical practice, according to expert opinions.
A Scalable, Geospatial Segmentation Method for Visiting Trend Analysis

Recently location data has been used for intelligent decision making in various purposes, such as marketing, tourism dynamics analysis and sales. Location intelligence allows users to store, visualize, and analyze user behavior from geospatial data in real time. Such algorithms often rely on identifying users visiting the relevant point of interest (PoI). Visitor statistics of such PoI’s Parking lot has been used to calculate user trends and store dynamics. However, the tagging of such parking lots is often manual and remains a painstaking task. We outline a Floating Car Data based technique that utilizes an unsupervised clustering technique to detect parking lot polygons for a given PoI. We also utilize a novel application of image processing as a noise reduction strategy for the clustering output. Moreover, we take advantage of OpenStreetMaps for end-to-end detection of parking lots polygons. Our approach improves the baseline performance significantly.
Urban Digital Twins for Intelligent Road Inspection

Urban digital twin (UDT) technologies offer new opportunities for intelligent road inspection (IRI). This paper first reviews the state-of-the-art algorithms used in the two key components of UDT-based IRI systems: (1) multi-temporal, multi-dimension, multi-score, and heterogeneous road data acquisition, and (2) road distress detection. This paper then summarizes the UDTIRI competition, organized in conjunction with IEEE Bigdata 2022. More details on our competition are available at sites.google. com/view/udtiri-workshop/bigdata-2022.