Miracle-dz/UniFAR-FTUs huggingface dataset:
Image Data Field-Based Method for Stippling

Computer-based generative art is in the ascendant and widely applied in media contexts such as web design, game resource, and digital entertainment. The process of creating non-photorealistic rendering images can be enjoyable if some useful and efficient methods are involved. This paper presents an automatic and fast method for digital stippling, which produces stipple renderings from photographs. To achieve this, we employ a novel mechanism based on the data field of an original image. Our inspiration is originated from physical fields. The used data field for an image can keep the balance between spatial and grayscale information in the local neighborhood by potential function, as well as the balance between the local information and the global trend. There involve three major steps in the proposed approach, including the generation of image data field, the reduction of potential centers, and the artistic renderings. The second step contains two types of reduction strategies, potential center elimination for stipple placement, and potential center cutting for mosaic construction. A number of experiments, both visual comparisons and quantitative comparisons, are performed. The results show the feasibility and the efficiency of the proposed method and suggest that the proposed method can generate appealing stipple or mosaic images. This would inspire graphic designers who may be interested in the stippled image automatically that is similar to images created by the artist.
Cognitive Relapse in Multiple Sclerosis: New Findings and Directions for Future Research

Multiple sclerosis (MS) is a chronic inflammatory, demyelinating disease of the central nervous system, often presenting with brain atrophy and cognitive impairment (CI). In the relapsing–remitting phenotype, cognitive performance is increasingly recognized to decline acutely during MS relapse, with varying degrees of recovery afterwards. Therefore, CI in MS may result from incomplete recovery from episodes of so-called “cognitive relapse”, gradual neurodegeneration, or both. Among a variety of validated measures of cognitive performance, the Symbol Digit Modalities Test (SDMT) represents the most sensitive measure of cognitive decline and is easily translated to clinical practice. In fact, cognitive relapse identified using the SDMT has been reported in clinically relapsing cohorts as well as in individuals with no other neurological signs, suggesting that routine cognitive assessment may be necessary to fully appreciate the extent of a patient’s disease activity. The aim of this narrative review is as follows: (1) to provide the historical context for neuropsychological assessment in MS, (2) to provide a summation of key studies describing the cognitive relapse phenomenon, and (3) to discuss current gaps in our knowledge and highlight avenues for future research.
Accurate EEG-Based Emotion Recognition on Combined Features Using Deep Convolutional Neural Networks

In order to improve the accuracy of emotional recognition by end-to-end automatic learning of emotional features in spatial and temporal dimensions of electroencephalogram (EEG), an EEG emotional feature learning and classification method using deep convolution neural network (CNN) was proposed based on temporal features, frequential features, and their combinations of EEG signals in DEAP dataset. The shallow machine learning models including bagging tree (BT), support vector machine (SVM), linear discriminant analysis (LDA), and Bayesian linear discriminant analysis (BLDA) models and deep CNN models were used to make emotional binary classification experiments on DEAP datasets in valence and arousal dimensions. The experimental results showed that the deep CNN models which require no feature engineering achieved the best recognition performance on temporal and frequency combined features in both valence and arousal dimensions, which is 3.58% higher than the performance of the best traditional BT classifier in valence dimension and 3.29% higher than that of BT classifier in arousal dimension.
An Efficient RAN Slicing Strategy for a Heterogeneous Network With eMBB and V2X Services

Emerging 5G wireless technology will support services and use cases with vastly heterogeneous requirements. Network slicing, which allows composing multiple dedicated logical networks with specific functionality running on top of a common infrastructure, is introduced as a solution to cope with this heterogeneity. At the radio access network (RAN), the use of network slicing involves the assignment of radio resources to each slice in accordance with its expected requirements and functionalities. Therefore, RAN slicing will provide the required design flexibility and will be necessary for any network slicing solution. This paper investigates the RAN slicing problem for providing two generic services of 5G, namely enhanced mobile broadband (eMBB) and vehicle-to-everything (V2X). In this respect, we propose an efficient RAN slicing scheme based on an off-line reinforcement learning followed by a low-complexity heuristic algorithm, which allocates radio resources to different slices with the target of maximizing the resource utilization while ensuring the availability of resources to fulfill the requirements of the traffic of each RAN slice. A simulation-based analysis is presented to assess the performance of the proposed solution. The simulation results have shown that the proposed algorithm improves the network performance in terms of resource utilization, the latency of V2X services, achievable data rate, and outage probability.
Stability analysis and experimental evaluation of a matrix converter drive system

The interest in using the matrix converter (MC) technology for motor drive applications is steadily increasing due to its advantages: high quality of the input currents, regeneration capability and high power density but a few unsolved issues delays its industrial use. This paper deals with one of them: the stability of a MC drive caused by using the voltage across the input filter capacitor in the control scheme. First, a small-signal model of the matrix converter is carried out for two load types: a passive RL-load and an induction motor, which is helping to assess the stability of the whole system. Based on this model, the factors that influence the stability are analyzed and design guidelines to improve the system stability are given and verified by simulations. Experimental results are carried out on an 8.5 kVA MC prototype, which show some disagreements with the theory but reasons for these are identified.
Language Dynamics in Supreme Court Oral Arguments

References 1. Danescu-Niculescu-Mizil, C. , Lee, L. , Pang, B. , & Kleinberg, J. (2012, April). Echoes of power: Language effects and power differences in social interaction. In Proceedings of the 21st international conference on World Wide Web (pp. 699-708). ACM. 2. Sagi, E. , & Diermeier, D. (2017). Language Use and Coalition Formation in Multiparty Negotiations. Cognitive science, 41(1), 259-271. (esagi@stfrancis.edu)
Ground-Based SAR Moving Target Refocusing Based on Relative Speed for Monitoring Mine Slopes

Ground-based synthetic aperture radar (GBSAR) has the advantage of retrieving submillimeter deformation of the mine slope by using the differential interferometry technique, which is important for safe production in mining applications. However, the moving vehicle’s defocus/displaced signal will mask the SAR image of the mining area which affects the accuracy of interference phase extraction and deformation inversion. In order to remove its influence, the moving target can first be refocused and then removed. To our knowledge, there is no GBSAR moving target refocusing method currently. Hence, the refocusing method is necessary. To solve the above problem, this paper proposes a single-channel FMCW-GBSAR moving target refocusing method based on relative speed. Firstly, the FMCW-GBSAR moving target signal model is analyzed, and then the relative speed based signal model is deduced. Based on the model and GBSAR’s feature of incomplete synthetic aperture, the Range Doppler (RD) algorithm is adopted and improved to achieve refocusing using relative speed parameters. The algorithm is controlled by relative speed and squint angle; thus, the refocused target image can be obtained via searching 2D parameters. The proposed method is verified by the synthetic data, which are generated by combining NCUT FMCW GBSAR real data and simulated moving target echo.
A Graph-based Recommendation Method for the Academic Community

We propose an innovative approach for academic recommendation, which integrates the topic component into the graph-based recommendation. Specifically, based on the topic component extracted from the text data on academic corpus, we propose a User Behavior Graph (UBG) and the User Academic Network (UAN). UBG is a bridge to fuse topic information and UAN. A personalized PageRank (PPR) algorithm is used on UBG for recommendation. Experimental results show that our method for academic recommendation outperforms the content-based recommendation.
Modelling Thermal Performance of Unloaded Spiral Strand and Locked Coil Cables Subject to Pool Fires

Abstract Structural cables are used to design critical bridge structures. These are not typically redundant; a loss or compromise of a few cables can lead to the progressive collapse. Previous experimental research has shown that the degradation of material properties and thermal expansion of structural cables is more onerous than the standard carbon prestressing steel. Despite its importance for design no well-validated methodology exists to aid in the thermal performance of structural cables in the event of a fire, particularly for spiral and locked-coil cables which inherently are complex due to their cross-sectional geometry. A state-of-the-art methodology for modelling structural cables' thermal response is presented. The methodology will enable the development of an understanding of the temperature distribution and thermal deformation in a cable cross-section and allow estimation of post-fire resilience. Validation is performed against experiments of locked-coil and spiral cables, subjected to realistic pool fires. The cables range from 22 to 100 mm in diameter and are constructed of galvanized or stainless steel. The cables are modelled undergoing non-linear thermal analysis in LS-DYNA. 2D models are found to provide conservative estimates for critical values such as peak temperature with 90% accuracy, while 3D models provide slightly more conservative estimates.
Efficient synthesis and replication of diverse sequence libraries composed of biostable nucleic acid analogues

Functional nucleic acids can be evolved in vitro using cycles of selection and amplification, starting from diverse-sequence libraries, which are typically restricted to natural or partially-modified polymer chemistries. Here, we describe the efficient DNA-templated synthesis and reverse transcription of libraries entirely composed of serum nuclease resistant alternative nucleic acid chemistries validated in nucleic acid therapeutics; locked nucleic acid (LNA), 2′-O-methyl-RNA (2′OMe-RNA), or mixtures of the two. We evaluate yield and diversity of synthesised libraries and measure the aggregate error rate of a selection cycle. We find that in addition to pure 2′-O-methyl-RNA and LNA, several 2′OMe-RNA/LNA blends seem suitable and promising for discovery of biostable functional nucleic acids for biomedical applications.
Magnetic correlation functions in the slow and fast solar wind in the Eulerian reference frame

Simultaneous multiple point measurements of the magnetic field from seven spacecraft are employed to estimate the Eulerian correlation function and decorrelation time scales in the near Earth solar wind for two different solar wind speed ranges. We find that the Eulerian decorrelation time scale differs significantly in the slow solar wind (<450 km/s), where quasi‐two‐dimensional turbulence dominates, and in the fast solar (>600 km/s) wind, where slab‐type turbulence dominates. In slow solar wind, the decorrelation time is 215 ± 43 min, and in fast solar wind, the decorrelation time scale is 114 ± 23 min, which indicates that decorrelation times vary with the nature of the turbulence. The values reported here are comparable to estimates of decorrelation times based on a number of different models, but do not clearly support or refute any specific solar wind turbulence model. These results may be useful in magnetohydrodynamic modeling of the solar wind and can contribute to our understanding of solar and galactic cosmic ray diffusion in the heliosphere.
Pilot design for channel estimation in Doubly Selective Channel

We consider pilot sequence designs for channel estimation in doubly-selective channels (DSC) which are modeled using the basis expansion model (BEM) approach. We propose to use pilot sequences (instead of impulse pilots) to reduce the peak-to-average power ratio (PAPR) of the transmitted signal. Specifically, by analysing the mean square error (MSE) metric of the BEM channel coefficients, we propose the use of Huffman sequences to reduce the PAPR during channel estimation. Furthermore, we show that a systematic re-arrangement of the pilot sequence within the transmission frame can significantly improve the channel estimation performance of the system, as compared to the conventional periodic pilot placement.
Effect of Sugar, Pectin, and Processing Temperature on the Qualities of Pineapple Jam

ABSTRACT The present study aimed to investigate the effects of sugar, pectin, and processing temperature on the qualities of jam developed from pineapple (smooth cayenne). The physico-chemical, and proximate composition of pineapple fruit pulp and jam were studied and the results were reported. The jam quality depended highly on the concentration of sugars, pectin, and the processing temperature. Processing of pineapple fruit pulp into jam resulted in a substantial increase in physicochemical properties such as TSS and TA and showed some loss in the nutritional, vitamin C, and mineral composition of the products compared to fresh fruits. The processing methods showed significant effects on the phytochemical contents of the produced jam. Jam formulated with (45%) sugar, and (5%) pectin and processed at (90°C) temperature are proven as best products in terms of their nutritional composition, color, phytochemicals, and vitamin C. In conclusion, these results indicate that converting fresh pineapple into jam has an enormous potential to reduce the post-harvest loss of fresh pineapple fruits, and value-added product jam provides health-promoting compounds to human health.
Differential Activity of the Extracellular Phenoloxidases in Different Strains of the Phytopathogenic Fungus, Microdochium nivale

To cause plant diseases, phytopathogenic fungi use numerous extracellular enzymes, among which, the phenoloxidases (POs) seem underestimated for the pathogens of non-woody plants. Our study aimed to (1) compare extracellular PO activities (lignin peroxidase, Mn peroxidase, laccase, and tyrosinase) in differentially virulent strains (inhabiting winter rye in a single field) of the phytopathogenic species, Microdochium nivale; (2) check whether these activities are responsive to host plant metabolites; and (3) search for correlations between the activities, lignin-decomposing capacity, and virulence. All strains displayed all four enzymatic activities, but their levels and dynamics depended on the particular strain. The activities displayed the hallmarks of co-regulation and responsiveness to the host plant extract. No relationships between the virulence of strains and levels of their extracellular PO activities or lignin-degrading capacity were revealed. We consider that different strains may rely on different POs for plant colonization, and that different POs contribute to the “uniqueness” of the enzymatic cocktails that are delivered into host plant tissues by different virulent strains of M. nivale. Our study supports the hypothesis of the differential behavior of closely related M. nivale strains, and discusses an important role of POs in the interactions of phytopathogens with herbaceous plants.
D-Shaped Fiber Bragg Grating Ultrasonic Hydrophone With Enhanced Sensitivity and Bandwidth

In this paper, we demonstrate a miniature flexible FBG-based underwater ultrasonic sensor with enhanced pressure sensitivity and bandwidth using a side-polished configuration of ∼54 μm depth and ∼15 mm length. The opto-mechanical responses of the sensor to acoustic-induced strain in axial and radial receiving modes are investigated and characterize the gain sensitivity dependent on the wavelength/Bragg length ratio. Then, ultrasonic testing in a water tank exhibited a maximum radial acoustic pressure-induced wavelength shift of 91.29 nm/MPa and a noise equivalent acoustic signal level of ∼49.6 mPa/Hz1/2 in the range of 40–120 kHz, as well as a good gain flatness of less than 9.4 dB. This is significantly superior to FBG-based hydrophones previously ever reported to our knowledge. The proposed technique greatly simplifies the miniaturized integration of all-optical ultrasonic detectors and could, therefore, be further improved for ultra-high sensitive hydrophones in optoacoustic imaging.
Genetic Algorithms for Product Design: How Well do They Really Work?

Recently, Balakrishnan and Jacob (1996) have proposed the use of Genetic Algorithms (GA) to solve the problem of identifying an optimal single new product using conjoint data. Here we extend and evaluate the GA approach with regard to the more general problem of product line design. We consider profit contribution as a firm's economic criterion to evaluate product design decisions and illustrate how the genetic operators work to find the product line with maximum profit contribution. In a Monte Carlo simulation, we assess the performance of the GA methodology in comparison to Green and Krieger's (1985) greedy heuristic.
Neurophysiological Correlates in Patients with Syringomyelia and Chiari Malformation: The Cortico-Diaphragmatic Involvement

Purpose. Brainstem syndromes have frequently been reported in Chiari syndrome and in syringobulbia; previous studies have shown that determining the central motor conduction time (CMCT) along the circuit of the phrenic nerve makes the assessment of the voluntary control of the respiratory pathway possible. In our study, we evaluated the transcranial magnetic stimulation (TMS) of the phrenic nerve in patients affected by Chiari syndrome and/or syringomyelia (Syr) with the aim of identifying subclinical neurophysiological alterations. Methods. One hundred patients (75 females; average age: 51 ± 13.08 SD; range: 18–76) affected by Chiari syndrome and/or Syr without dyspnea were selected. The magnetic stimulation of the second motor neuron correlating with the phrenic nerve was performed using cervical magnetic stimulation (C5-MEP); the cortical MEP after magnetic stimulation (Cz-MEP) was recorded by magnetic stimulation of the motor cortex (areas corresponding to the diaphragm). The CMCT was calculated. The differences between the patients and controls were calculated (Student’s t test). Results. In 13% of the patients, the Cz-MEP were absent bilaterally, and the CMCT was not evaluable. In all these cases, bulbar/cervical Syr was present at MRI; in 10 of them, this was associated with CM1. A bilateral response was obtained in all the other patients (87%), and the CMCTs were normal. All the patients with alterations/absence of Cz-MEP presented bulbar/cervical Syr at MRI. The C5-MEP latency was prolonged or absent in 48%; of these, 84% presented bulbar/cervical Syr associated with CM1 at MRI. The C5-MEP latency values were significantly higher in the group of patients. Conclusions. Neurophysiological alterations of the diaphragmatic pathway were recorded in a group of Chiari syndrome and, particularly, in bulbar/cervical Syr. Future studies with larger cohorts of patients are needed to further assess the specific role of the TMS of the phrenic nerve in CM/Syr patients.
Underwater Formation System Design and Implement for Small Spherical Robots

Aiming at the difficulty of communication and positioning of the existing underwater robot system, this article combines the vision system with a closed leader–follower formation structure to realize the underwater formation of three underwater robots. On account of the long-standing tracking requirements during vision-based formation process, an antiloss and redetecting strategy is fused in the proposed detecting and tracking algorithm and the binocular vision system can achieve real-time positioning underwater and calculate the 3-D coordinate so as to complete the follower's follow-up to the leader. An artificial submarine detection experiment and an antiloss redetection experiment are applied to demonstrate the robustness of the algorithm. And the underwater formation experiment is implemented so that the effectiveness of the proposed vision-based formation strategy is proved, which also provides a new solution for expanded formation system and multilevel cooperation.
Toward the understanding of the constituents of organizational culture: The embedded topic modeling analysis of publicly available employee‐generated reviews of two major U.S.‐based retailers

Organizational culture is considered an important factor affecting several operations‐oriented functions in an organization. However, the research surrounding organizational culture and what constitutes organizational culture remains understudied in the operations management (OM) discipline. This study utilizes 24,965 employee‐generated (EG) text reviews of two major U.S.‐based retailers and applies an advanced embedded topic modeling technique to identify prevalent cultural elements that retail operational workers in these organizations deemed most important. Overall, the analysis yielded 19 distinct cultural elements across the two retailers with unique elements belonging to each organization. The study provides a novel way to study organizational culture in the OM discipline and describes the workings of different text analytics methods in detail. In addition to making a methodological contribution to the field, this study provides actionable insights to practitioners and lists several avenues of future research for OM scholars interested in utilizing text analytics to study organizational culture and other operations‐oriented research problems using text data.