Miracle-dz/UniFAR-FTUs huggingface dataset:
New Opportunities for Multistatic Remote Sensing Of Water Surface Using Receivers with Different Antenna Patterns

This work is devoted to the development of the original approach of multi-static remote sensing laid down in previous works. The basis of the new approach is the analysis of the shape of the Doppler spectrum of the signal reflected in the forward direction from the sea surface. The Doppler spectrum contains more information about the reflecting surface than the radar cross section, since the radar cross section is an integral characteristic of the Doppler spectrum. The advantage of the Doppler spectrum is also its greater versatility when comparing the measurements of various instruments comparing to the radar cross section. An important feature of the proposed approach is the possibility of obtaining explicit dependencies for the surface waves parameters on the characteristics of the Doppler spectrum of reflected radiation obtained using receivers with different antenna patterns. In this paper, special cases of the potential implementation of the developing approach are considered.
A Weighted Genomic Relationship Matrix Based on Fixation Index (FST) Prioritized SNPs for Genomic Selection

A dramatic increase in the density of marker panels has been expected to increase the accuracy of genomic selection (GS), unfortunately, little to no improvement has been observed. By including all variants in the association model, the dimensionality of the problem should be dramatically increased, and it could undoubtedly reduce the statistical power. Using all Single nucleotide polymorphisms (SNPs) to compute the genomic relationship matrix (G) does not necessarily increase accuracy as the additive relationships can be accurately estimated using a much smaller number of markers. Due to these limitations, variant prioritization has become a necessity to improve accuracy. The fixation index (FST) as a measure of population differentiation has been used to identify genome segments and variants under selection pressure. Using prioritized variants has increased the accuracy of GS. Additionally, FST can be used to weight the relative contribution of prioritized SNPs in computing G. In this study, relative weights based on FST scores were developed and incorporated into the calculation of G and their impact on the estimation of variance components and accuracy was assessed. The results showed that prioritizing SNPs based on their FST scores resulted in an increase in the genetic similarity between training and validation animals and improved the accuracy of GS by more than 5%.
Selective Harmonic Elimination for Cascaded Three Phase Multilevel Inverter

Frequent power failures, non-availability of electrical energy from conventional energy sources at the load center or insufficient generation of electrical energy are the major reasons of utilization of non-conventional resources to harness electrical energy. From these sources, usually direct current form of electrical energy is obtained which needs to be regulated for conversion into alternating form of voltages through inverter. Thus, the design of inverters which are widely used as standby power supply at domestic levels, ac drives control, distribution of power generation, play a vital role. The ease of utilization of inverter depends on the magnitude of ac output voltage and frequency which could be directly controlled by switching the controlled semi-conductor devices. However, this leads to injection of harmonics in the output waveform. The dominant order of harmonics needs to be eliminated which otherwise, causes power losses in the form of heat, damaging the inverter. Eliminating these harmonics is a big challenge. Therefore, selective harmonic elimination PWM (SHE-PWM) is one among many techniques which could be used for multi-level Cascaded H-bridge inverter. The optimized switching angles have been generated through Newton-Raphson by solving non-linear equations. This paper tries to bring comparative study of presence of harmonics for different types of load.
Electrical and viscoelastic measurement of cancer cells in epithelial-mesenchymal transition process on a microfluidic device

Microfluidic devices and electrical techniques based on electrical impedance and viscoelastic changes can be used in the measurement of cancer cells in the epithelial-mesenchymal transition (EMT) process. Electrical impedance and transmission time were investigated when a single CRC cell passed the measurable tiny channel which was designed with width smaller than the average diameter of a single cell. The experimental data showed that the electrical impedance characteristics and viscoelasticity of the cells were changed after PMA induction. This property is expected to become a new biomarker for studying EMT.
Towards an integrative understanding of soil biodiversity

Soil is one of the most biodiverse terrestrial habitats. Yet, we lack an integrative conceptual framework for understanding the patterns and mechanisms driving soil biodiversity. One of the underlying reasons for our poor understanding of soil biodiversity patterns relates to whether key biodiversity theories (historically developed for aboveground and aquatic organisms) are applicable to patterns of soil biodiversity. Here, we present a systematic literature review to investigate whether and how key biodiversity theories (species–energy relationship, theory of island biogeography, metacommunity theory, niche theory and neutral theory) can explain observed patterns of soil biodiversity. We then discuss two spatial compartments nested within soil at which biodiversity theories can be applied to acknowledge the scale‐dependent nature of soil biodiversity.
In-Season Prediction of Crop Types In The us Great Plains Using Sequence Based Stochastic Models and Deep Learning

In this study, a convolutional neural network (CNN) is developed that predicts crop type in the US great plains using optical and active microwave remote sensing, historical crop type data and economic commodity crop price information. It includes a Markov chain model that predicts the prior probability of crop types from historical crop type sequences for each pixel. This prior and the remotely sensed imagery is fed through a CNN to produce the final crop type. The CNN is trained using imagery and crop type from the previous year. The field-scale accuracy of this method is found to be $\tilde 85\% $ using imagery from just the first 90 growing days.
Potential Landslide Early Identification Along Nu River with Time Series Interferometry

The bank of Nu River is controlled by several faults, and the geological environment is fragile. It is also affected by the natural factors of atmospheric precipitation. So there are a large number of potential landslide hidden points along Nu River. In this research we proposed an improved Time series InSAR (TSInSAR) technology for landslide investigation and identification from Anmuda to Kaxi along Nu River, China. The technique can identify high coherent scatterers and accurately obtain the surface deformation information. From the deformation rate map and Google earth optical image we identify five potential landslide hidden points along Nu River. We discover the continued acceleration phenomenon of hidden points that had been identified so that timely warnings of landslides with major potential safety hazards. This work is also helpful for the local government to carry out geological survey and disaster monitoring
FAT10: Function and relationship with cancer.

Posttranslational protein modifications are known to be extensively involved in the cancer process, and a growing number of studies have revealed that the ubiquitin-like modifier FAT10 is directly involved in cancer development. FAT10 was found to be highly upregulated in various cancer types, such as glioma, hepatocellular carcinoma, breast cancer and gastrointestinal cancer. Protein FAT10ylation and interactions with FAT10 lead to the functional change of proteins, including proteasomal degradation, subcellular delocalization and stabilization, eventually having significant effects on cancer cell proliferation, invasion, metastasis and even tumorigenesis. In this review, we summarize the current knowledge on FAT10 and discuss its biological functions in the cancer process, as well as potential therapy strategies based on the FAT10 pathway.
Attribute Profiles For Satellite Image Time Series

Morphological attribute profiles have been one of the most effective image features for spatial-spectral classification of remote sensing images during the last decade. The motivation of this paper is to extend attribute profiles to satellite image time series, i.e. taking into account the temporal information. We introduce different approaches and report their performances for land cover mapping. Experiments are conducted on a Sentinel-2 dataset considering well-established supervised classification methods that are Random Forest and Support Vector Machines.
A Voltage Controlled Sensorless Speed Control of PMBLDC Motor Drive for an Electric Two Wheeler

The global warming has led to a widespread acceptance for electric vehicles. They are environment friendly in comparison to conventional and hybrid vehicles. This paper focuses on the speed control strategy of a three phase permanent magnet brushless DC (PMBLDC) motor employed in an electric two wheeler. The speed control of the motor is done using output voltage control of bidirectional boost-buck converter. The presented system is modeled, simulated and analysed using MATLAB/SIMULINK for different speed and load condition.
Spatio-Temporal Assessment of Fire Severity and Vegetation Recovery Utilising Sentinel-2 Imagery in New South Wales, Australia

Fire severity and vegetation indices are widely used to understand fire disturbance and vegetation recovery in heterogenous landscapes. Multispectral sensors are used to understand fire severity and post-fire vegetation dynamics. We utilised four fire severity (dNBR, RBR, RdNBR and MIRBI) and four vegetation indices (Chlorophyll Index of Red-Edge, dNDVI, EVI and NDRE) derived from Sentinel-2 images to understand the spatio-temporal variability of fire severity and vegetation recovery. The Masonite Road fire burned 2321.32 hectares of mixed Eucalyptus and wetland forests in the southwestern Telligerry State Conservation Area of New South Wales, Australia, in January 2018. Spectral and spatial analysis of different fire severity and vegetation indices revealed the blaze affected the landscape with moderate to high level of severity. Fire severity indices showed similar patterns in spatio-temporal analysis for a year, but Chlorophyll Index of Red-Edge and EVI did not show any pattern of fire impacts on vegetation. Among the analysed indices, two combinations of fire severity and vegetation indices (dNBR or RBR or RdNBR with NDVI and MIRBI withNDRE) were significantly correlated and can be effective in assessing fire severity, burned area and vegetation recovery.
Researching the Effectiveness of the Balanced Scorecard by Using the Process Perspective (2): The BSC Process Model and Descriptive Analysis of a Survey of BSC Users in India

The first part of a research proposal for researching the effectiveness of the Balanced Scorecard (BSC) based on using the process perspective was developed in an earlier article (http://ssrn.com/abstract=2368919). It had described how applying a ‘process’ perspective, instead of a ‘variance’ perspective, could lead to a better understanding of the underlying mechanisms that give rise to the variable consequences on the adoption of the BSC. It had developed the proposals for some research hypotheses to be tested. This article develops the BSC Process Model based on these ‘process perspectives’, describes how to operationalize the constructs in the Model and the design of a Questionnaire to test these Hypotheses. It then describes the result of a survey of users of BSC in India and draws some conclusions based on the findings (the ‘how’s and ‘why’s of variable consequences). The factors identified include poor motivation for using the BSC, lack of belief in Consultants, lack of understanding of causality amongst measures used, lack of use of incentive schemes based on BSC and the neglect of national culture. A third article will describe how by applying the PLS-SEM approach some of the relevant processes and factors involved in ‘how to’ improve the effectiveness of the BSC can be uncovered.
Subtle, pervasive genetic correlation between the sexes in the evolution of dimorphic hummingbird tail ornaments *

Male hummingbirds have repeatedly evolved sexually dimorphic tails that they use as ornaments during courtship. We examine how male ornament evolution is reflected in female morphology. Lande's two‐step model of the evolution of dimorphism predicts that γ (the genetic correlation between the sexes) causes trait elaboration to first evolve quickly in both sexes, then dimorphism evolves more slowly. On the hummingbird phylogeny, tail length does not fit this two‐step model; although hummingbirds repeatedly evolved ornamental, elongated tails, dimorphism evolves on the same phylogenetic branch as elongation, implying that γ quickly evolves to be low over phylogenetic timescales. Male “bee” hummingbirds have evolved diverse rectrix shapes that they use to produce sound. Female morphologies exhibit subtle, pervasive correlations with male morphology. No female‐adaptive hypotheses explain these correlations, since females do not also make sounds with their tail. Subtle shape similarity has arisen through the genetic correlation with males, and is subject to intralocus sexual conflict. Intralocus sexual conflict may produce increased phenotypic variation of female ornaments. Other evolutionary constraints on tail morphology include a developmental correlation between neighboring tail‐feathers, biasing tail elaboration to occur most often at the ends of the feather tract (rectrix 5 or 1) and not the middle.
Estimating Soil Moisture Using the Optical Trapezoid Model (OPTRAM) in a Semi-Arid Area of SONGNEN Plain, China Based On Landsat-8 Data

The OPtical TRApezoid Model (OPTRAM) has recently been introduced for calculation of soil moisture using only optical remote sensing data. Based on shortwave infrared transformed reflectance (STR)-Normalized Difference Vegetation Index (NDVI) trapezoidal space, the surface soil moisture can be estimated. In this study, Landsat 8 satellite observations were acquired and used for the analysis. Th soil moisture during growing season in a semi- arid agricultural region in Songnen Plain, China was estimated based on the OPTRAM. The results may help to retrieval soil moisture and monitor its seasonal dynamics, which are of great significance for water resources planning management, sustainable land use and agricultural production.
Design and Implementation of Cache Coherence Protocol for High-Speed Multiprocessor System

To maintain data consistency between the cache memories in centralized and distributed shared-memory multiprocessor system, particular protocols are used known as cache coherence protocols. The performance of a multi-core computer system is strongly influenced by the type of cache coherence protocol used. In this paper, the snoopy bus cache coherence protocols using 3-state, 4-state and 5-state are designed and implemented using the write-invalidate approach in a shared memory dual processor system. The simulation results show that the MOESI protocol reduces the load misses by 48%, memory latency by 35%, power consumption by 18%, increases the gate count by 34% and improves the execution time by 22%. Thus, the overall performance of the MOESI is better than the MESI and MSI cache coherence protocols in a shared memory dual processor system.
SIR based Diplexer for 5G mm-Wave

In this paper, the stepped impedance resonators are used to design a diplexer for the upcoming fifth generation (5G) millimeter-Wave wireless technology. The proposed diplexer design has two output ports, one port for 28 GHz band and the other port for 39 GHz band. The simulated reflection coefficient (S11) is -19.979dB at 28 GHz and -19.618dB at 39 GHz. The transmission coefficient is -0.67dB at 24.25GHz for the low-band section of diplexer and -0.419dB at 37GHz for the high-band section. The rejection level is -25.076 dB at 37GHz for low-band section and -24.344dB at 24GHz for high band section. The total circuit size is 17 x 6 x 0.14 mm3. The design is simulated using CST microwave studio and fabrication is in progress.
Cholinergic denervation in patients with idiopathic rapid eye movement sleep behaviour disorder

Cholinergic dysfunction appears to play a role in the cognitive impairment observed in Parkinson’s disease and dementia with Lewy bodies. The occurrence of cholinergic dysfunction in the early stages of these conditions, however, has not been investigated. The objective of this study was to investigate cholinergic function in patients with idiopathic rapid eye movement sleep behaviour disorder (iRBD), a disorder recognized to be an early stage of both Parkinson’s disease and dementia with Lewy bodies.
A Systematic Review of Detecting Sleep Apnea Using Deep Learning

Sleep apnea is a sleep related disorder that significantly affects the population. Polysomnography, the gold standard, is expensive, inaccessible, uncomfortable and an expert technician is needed to score. Numerous researchers have proposed and implemented automatic scoring processes to address these issues, based on fewer sensors and automatic classification algorithms. Deep learning is gaining higher interest due to database availability, newly developed techniques, the possibility of producing machine created features and higher computing power that allows the algorithms to achieve better performance than the shallow classifiers. Therefore, the sleep apnea research has currently gained significant interest in deep learning. The goal of this work is to analyze the published research in the last decade, providing an answer to the research questions such as how to implement the different deep networks, what kind of pre-processing or feature extraction is needed, and the advantages and disadvantages of different kinds of networks. The employed signals, sensors, databases and implementation challenges were also considered. A systematic search was conducted on five indexing services from 2008–2018. A total of 255 papers were found and 21 were selected by considering the inclusion and exclusion criteria, using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) approach.
Predicting Human Intent for Cooperative Physical Human-Robot Interaction Tasks

In this paper, a robot assistive Impedance and Admittance control methodology is proposed for a cooperative physical human-robot interaction (pHRI) task. In a pHRI task in which the human is the leader, the robot is a passive follower as the human intention of desired motion and force to be applied are unknown. It is generally difficult to predict the intention of the human leader. Recurrent Neural Networks (RNN) with Long Short-Term Memory (LSTM) units are employed to forecast the position,velocity and force anticipated to be applied by the human. The estimated parameters are integrated into the impedance and admittance controllers via a target impedance model which aids the robot in becoming a proactive partner of the human by sharing the physical load. The same methodology is also applied to the Minimum Jerk model which allows the robot to follow the Minimum Jerk trajectory without knowing the trajectory parameters in advance.
Vision Models for Wide Color Gamut Imaging in Cinema

Gamut mapping is the problem of transforming the colors of image or video content so as to fully exploit the color palette of the display device where the content will be shown, while preserving the artistic intent of the original content’s creator. In particular, in the cinema industry, the rapid advancement in display technologies has created a pressing need to develop automatic and fast gamut mapping algorithms. In this article, we propose a novel framework that is based on vision science models, performs both gamut reduction and gamut extension, is of low computational complexity, produces results that are free from artifacts and outperforms state-of-the-art methods according to psychophysical tests. Our experiments also highlight the limitations of existing objective metrics for the gamut mapping problem.
In-Fiber Graphene-hBN Polarizer With Enhanced Performance and Bandwidth

Graphene and hBN as two-dimensional materials with excellent optical properties can be combined with other materials. In this paper, graphene and hBN is sequentially deposited on the surface of the silicon-core fiber to serve as transverse magnetic (TM) or transverse electric (TE) mode polarizer alternatively depending on the input wavelength and the diameter of the silicon-core. The Gr/hBN stack structure on the surface silicon-core microfiber is used not only for enlarging the wavelength bandwidth, such as from 350 nm (TM) and 670 nm (TE) for double Gr/hBN stack to 300 nm (TM) and 550 nm (TE) for single Gr/hBN stack, but also enhancing the light-graphene interaction to multiply the polarization extinction ratio, as compared with that of monolayer graphene. Small radius silicon core could provide large light-graphene interaction for flat extinction ratio with different thickness of the hBN.
Impact of Atmospheric Correction on the Ship Detection Using Airborne Hyperspectral Image

In this study, the effect of hyperspectral atmospheric correction on accuracy of the ship detection was investigated. We applied two atmospheric correction algorithms on airborne hyperspectral data and then detected ship features from reflectance corrected by each algorithms with an unsupervised target detection method. Both ATREM and FLAASH algorithms produce comparable atmospheric correction results but the algorithm which applied with further correction options optimized for coastal monitoring purpose reveals better detection results for ship detection. Compared to the result from ATREM, the result from FLAASH-corrected reflectance shows a distinct contrast between the ship and surrounding background seawater. Mean values of spectral angles between target and endmember spectra were 0.2388 (ATREM) and 0.2169 (FLAASH). This implies a further optimization of the atmospheric correction can improve the performance of target detection using airborne hyperspectral data, especially for maritime search purpose.
Update of inflammasome activation in microglia/macrophage in aging and aging‐related disease

Aging and aging‐related CNS diseases are associated with inflammatory status. As an efficient amplifier of immune responses, inflammasome is activated and played detrimental role in aging and aging‐related CNS diseases. Macrophage and microglia display robust inflammasome activation in infectious and sterile inflammation. This review discussed the impact of inflammasome activation in microglia/macrophage on senescence “inflammaging” and aging‐related CNS diseases. The preventive or therapeutic effects of targeting inflammasome on retarding aging process or tackling aging‐related diseases are also discussed.
Sparse Reconstruction for Synthetic Aperture Radar VIA Generalized Sparse Covariance Fitting

Conventional synthetic aperture radar (SAR) reconstructs the illuminated scene via fast Fourier transform (FFT), which results in high sidelobe level, and poor cross-range resolution due to the finite synthetic aperture length. In this paper, we formulate a sparse reconstruction method for SAR imaging based on the covariance fitting criterion, which assumes that only a few strong scatters exist in the whole scene. The method is able to fully control over the sparsity level and reconstruct the scenario in an adaptive manner. Experimental results with real SAR data show the better performance of our method compared with the conventional methods in terms of resolution improvement and sidelobe suppression.