Miracle-dz/UniFAR-FTUs huggingface dataset:
Large-scale subpixel mapping of landcover from MODIS imagery using the improved spatial attraction model

Abstract. Mapping plastic-mulched landcover (PML) is an important agricultural monitoring task. Because of its daily revisiting, imagery from moderate-resolution imaging spectroradiometer (MODIS) has been widely used to detect PML over a large area. However, the coarse spatial resolution and small field size make subpixel PML a problem for accurate PML mapping from MODIS. This study applies the improved spatial attraction model (ISAM), which estimates the spatial attraction of the central subpixel of a moving window by all subpixels in the window, to map large-scale subpixel PML from MODIS imagery. The linear spectral mixing model is used to obtain fractions of PML and three other landcover classes in each MODIS pixel as the inputs to ISAM for obtaining the hard subpixel PML maps at spatial resolution of 31.25 m. The accuracy evaluation, with validated landcover classification derived from Landsat-8 imagery as the ground truth, shows that overall accuracy, Kappa coefficients, producer accuracy, and user accuracy are 83.51%, 0.69, 90.97%, and 81.51%, respectively, indicating large-scale PML mapping at spatial resolution comparable to Landsat-8 can be derived from MODIS images with acceptable accuracy by ISAM. This study provides a practical and economic way for mapping PML for a large area at ∼30-m spatial resolution.
Analysis of Prevalence and Trends in the Biopsy-Proven Native Kidney Diseases in Iranian Population: A 12-year Survey from a Referral Center

Background & Objective: The prevalence of glomerular diseases, as the leading cause of chronic kidney disease, is increasing. Renal biopsy is still the gold standard for diagnosis of the most kidney disorders. Data on prevalence of the biopsy-proven kidney diseases in Iran is limited and none of the previously reported studies used electron microscopic (EM) evaluation for the diagnosis. This study was conducted to analyze the prevalence of biopsy-proven kidney diseases in a referral center in Iran. Methods: The reports of kidney biopsy samples from 2006 to 2018 referred to a pathology center, affiliated with Tehran University of Medical Sciences were reviewed. The prevalence of different disorders was assessed based on the clinical presentation in 3 age categories, including childhood, adulthood, and elderly. Results: Among 3455 samples, 2975 were analyzed after excluding transplant-related specimens, suboptimal specimens, and those with uncertain diagnoses. Nephrotic syndrome (NS) (39%) was the most common cause of biopsy followed by subnephrotic proteinuria (18%), hematuria in association with proteinuria (15%), renal failure (9%), isolated hematuria (6%), lupus (4%) and the other non-specific manifestations such as hypertetion or malaise (each one less than 2%). The most common diagnoses included membranous nephropathy (MGN) (17.9%), focal segmental glomerulosclerosis (FSGS) (15.9%), lupus nephritis (LN) (13.7%), minimal histopathological findings (unsampled FSGS versus Minimal Change Disease, 12.1%), Immunoglobulin-A (IgA) nephropathy (6.5%) and Alport syndrome (6.1%). MGN was the most frequent disease before 2013, but FSGS became more frequent after that. Conclusion: NS and proteinuria were the most indications for kidney biopsy. Although MGN was the most common disease, the prevalence of FSGS has been increasing in recent years and making it the most common disease after 2013. LN and IgA nephropathy are the most common causes of secondary and primary GN presenting with proteinuria and hematuria, respectively.
The simplicity, complexity, and benefits of multi-aperture imaging in the thermal infrared

We describe how the use of multiple-camera imaging systems provides an interesting alternative imaging modality to conventional single-aperture imaging, but with a different challenge: to computationally integrate diverse images while demonstrating an overall system benefit. We report the use of super-resolution with arrays of nominally identical longwave infrared cameras to yield high-resolution imaging with reduced track length, while various architectures enable foveal imaging, 4π and 3D imaging through the exploitation of integral imaging techniques. Strikingly, multi-camera spectral imaging using a camera array can uniquely demonstrate video-rate imaging, high performance and low cost.
Close stellar encounters with the Sun from the first Gaia Data Release

Abstract I present preliminary results of searching for close stellar encounters with the Sun using the first Gaia data release. Gl 710 is found to be a much closer encounter than found in pre-TGAS studies. More detailed results will be reported in an upcoming publication (Bailer-Jones 2017, in preparation).
RNA-binding proteins as a common ground for neurodegeneration and inflammation in amyotrophic lateral sclerosis and multiple sclerosis

The neurodegenerative and inflammatory illnesses of amyotrophic lateral sclerosis and multiple sclerosis were once thought to be completely distinct entities that did not share any remarkable features, but new research is beginning to reveal more information about their similarities and differences. Here, we review some of the pathophysiological features of both diseases and their experimental models: RNA-binding proteins, energy balance, protein transportation, and protein degradation at the molecular level. We make a thorough analysis on TDP-43 and hnRNP A1 dysfunction, as a possible common ground in both pathologies, establishing a potential link between neurodegeneration and pathological immunity. Furthermore, we highlight the putative variations that diverge from a common ground in an atemporal course that proposes three phases for all relevant molecular events.
Mastitis Tuberkulosis Primer

Objectives : Tuberculous (TB) mastitis is an uncommon presentation of TB even in countries where the incidence of pulmonary and extrapulmonary TB is high. It accounts for < 0.1% of all breast pathologies and <2% of all cases of tuberkulosis. Case presentation : A 25-year-old female presented a palpable lump in the upper-outer quadrant left breast, measuring about 3 cm and accompanied by retraction of the adjacent skin. Conclusion : Tuberculous mastitis is a rare and results from direct infection via the breast ducts opening to the nipple or from breast skin abrasions. Breast sonography and fine needle aspiration biopsy have been used for diagnostic of tuberculous mastitis.
Diagnostic and Predictive Values of IL-6 in a Group of Iraqi Patients with Rheumatoid Arthritis

Background: Researchers have found that interleukin 6 (IL-6) plays a crucial regulatory function in the onset and progression of a wide range of inflammatory disorders. One of the more prevalent inflammatory illnesses affecting people today is rheumatoid arthritis. Aim of the study: The purpose of this study was to compare the IL-6 levels of rheumatoid arthritis (RA) patients to those of healthy controls and to examine the relationship between IL-6 and RA-related demographic and clinical factors. Materials and Method A total of 80 participants: 40 rheumatoid arthritis (RA) sufferers and 40 healthy controls, all of whom ranged in age from 23 to 61. The serum concentrations of (IL-6) were analyzed using an enzyme-linked immunosorbent assay (ELISA). Results: Increased IL-6 blood levels were associated with rheumatoid arthritis, suggesting that this biomarker may be useful for diagnosing the disease at an early stage. There was no statistically significant correlation between disease severity and the DAS28 score and IL-6 levels in the serum. Conclusion: The cytokine interleukin 6 (IL-6) has been proposed as a biomarker and possible player in the etiology of rheumatoid arthritis.
Is there a deductive argument for semantic externalism? Reply to Yli-Vakkuri

Juhani Yli-Vakkuri (2017) has recently argued that the Twin Earth thought experiments offered in favour of semantic externalism can be replaced by a straightforward deductive argument from premises widely accepted by both internalists and externalists alike. The deductive argument Yli-Vakkuri offers, however, depends on premises which are such that, on standard formulations of internalism, they cannot be satisfied by a single belief simultaneously; it does not therefore, constitute a proof of externalism. The aim of this paper is to explain why.
Rôle de la rotation différentielle sur le spectre basse fréquence des étoiles en rotation rapide

Les etoiles massives sont les principaux contributeurs a l’enrichissement du milieu interstellaire. Ce sont generalement des rotateurs rapides, dotes d’une enveloppe radiative dans laquelle l’interaction de la stratification et la rotation genere une rotation differentielle. Celle-ci peut alimenter divers phenomenes de transport et l’evolution rapide de l’etoile. Nombre de ces etoiles sont par ailleurs des pulsateurs classiques. Cette these s’interesse en premier lieu a l’interaction entre la rotation differentielle et les pulsations a basse frequence dans l’etoile : celles-ci sont des modes gravito-inertiels dont la force de rappel est une combinaison de la force de Coriolis et de la poussee d’Archimede. Ils sondent les couches profondes de l’etoile, et sont etudies suivant deux methodes : dans la limite non-dissipative par la methode des caracteristiques, et dans le cas dissipatif par la resolution du probleme complet par une methode spectrale. Nous mettons en evidence differentes singularites (attracteurs, latitudes critiques, resonances de corotation, piegeage en coin) et des modes reguliers. Certains modes sont excites par des instabilites baroclines, qui, si des effets non-lineaires provoquent leur saturation, permettent l’existence d’un mecanisme d’excitation nouveau du a la rotation differentielle. Dans un second temps, nous avons associe le code de structure ESTER au code de calcul d’oscillations TOP. Ces deux codes calculent les quantites dans une etoile en deux dimensions et les modes associes en tenant compte des effets de la rotation de facon complete. Nous utilisons visibilites et taux d’amortissement des modes pour selectionner dans le spectre synthetique les meilleurs candidats a l’identification des modes observes. Nous presentons une application au rotateur rapide Rasalhague (αOph), pour lequel de nombreuses observations sont disponibles. Nous n’avons pas obtenu une identification des modes univoque, mais le probleme est maintenant mieux cerne et diverses pistes de progres ont ete identifiees.
Optical microcavities for quantum communication with single atoms

This thesis describes optical Fabry–Perot microcavities based on CO2 laser-machined mirror substrates with a finesse of up to 190000 that are ideal to couple single photons and single atoms. The observed frequency splitting of polarization eigenmodes is explained by the geometry of the mirrors and can thereby be controlled. A full, realistic quantum-repeater scheme at telecom wavelength using crossed microcavities is proposed and analyzed.
Carcass Characteristics and Meat quality assessments in Broiler Chickens subject to different Pre-Slaughter Restraining Methods

This research aimed to determine how the pre-slaughter restraint method affected broiler chickens' bleeding efficiency, carcass characteristics, and physicochemical qualities. Before slaughter, 30 male Ross broiler chickens were randomly allocated to either shackling or cone restraint. The individual blood loss of each bird was determined by comparing their body weight before and after 90 seconds of exsanguination. On the pectoralis major muscle, meat quality measures including pH, water-holding capacity, colour, tenderness, and total bacterial counts were determined. At the same time, the incidences of haemorrhage on the breast and thigh of each carcass were analysed morphologically. It was found that shackling produced less blood loss than cone restraint. Except for the final pH, shackling significantly affected the quality of the end product, as muscle lightness, shear force, drip loss, cooking loss, lipid-protein oxidation, and bacterial counts increased (p<0.05). A lower reflective density of myosin heavy chain was found in the muscle of broiler chickens subjected to shackle restraint compared to cone restraint. However, actin was not different between the pre-slaughter restraining techniques. In addition, broiler birds held by the shackle exhibited larger (p<0.05) haemorrhages than those restrained by the cone. The results indicated that the method of restraint might affect bleed-out and carcass and meat quality in broiler chickens; consequently, it should be examined in future research.
Unsupervised Domain Adaptation Damage Identification Approach of High Arch Dams after Earthquakes

In actual concrete arch dam engineering scenarios, the dynamic data obtained by the health monitoring system of an arch dam are incomplete. The data acquired typically depend on the state of the dam structure, that is, whether it is intact or incomplete. Besides, the future environmental loads of the structure are unpredictable. Thus, environmental noise is also uncertain. In practical engineering, the use of a damage identification model constructed based on incomplete information is problematic in scenarios with variable loads. Consequently, detecting the water level in actual arch dam projects after an earthquake and determining the impact of environmental uncertainty are necessary. Accordingly, this paper proposes a denoising contractive sparse deep autoencoder (DCS-DAE) model based on domain adaptation. The core idea of the proposed method is to constrain the data probability distribution of feature spaces in the source and target domains using maximum mean discrepancy. This fusion enables the DCS-DAE model to be capable of feature extraction. Moreover, it resolves the problem in which the objective function cannot be applied to other similar scenarios because of the lack of consistency constraints of feature spaces in the source and target domains. Four working conditions are designed to reproduce the uncertainty of structural modeling and the variability of water levels. The conditions are based on the postseismic water level detection requisites of dams in practical engineering. The results show that the proposed anomaly detection model enhances the generalization performance of the DCS-DAE in terms of feature design. Hence, the constructed model can “infer other things from one fact. ” The results of this study are meaningful for the real-time cross-domain monitoring of structures under variable load conditions, providing a driving force to apply similar methods to practical arch dam projects.
Relationship Between the Number of Labeled Samples and Classification Accuracy Based on Sparse Representation

Sparse decomposition algorithm can be implemented to classify high dimensional data without dimension reduction. Empirical examinations have shown that the classification accuracy of the hyperspectral data can be significantly improved based on sparse representation framework. However, the classification accuracy of hyperspectral data is reduced greatly if the quantity of samples is too small. This paper represents an attempt to fill the gap represented by the absence of the lower bound of labeled sample quantity of sparse representations in supervised classification task, in order to focus future analyses towards the most relevant aspects of image classification accuracy and data labeling cost. Based on the boundary conditions of the unique solution of sparse representation, the relationship between the classification accuracy of hyperspectral data and the quantity of labeled samples is analyzed theoretically in this paper. The correlation curves of the sample quantity and the classification accuracy is figured with the Kennedy Space Center (KSC) hyperspectral data.
The ETX Objective Function for RPL

The ETX metric of a wireless link is the expected number of transmissions required to successfully transmit and acknowledge a packet on the link. The Routing Protocol for Low Power and Lossy Networks (RPL) allows the use of objective functions to construct routes that optimize or constrain a routing metric on the paths. This specification describes ETXOF, an objective function that minimizes ETX. The RPL path computation using ETXOF results in minimum-ETX paths from the nodes to the DAG roots, i.e., paths that minimize the number of packet transmissions for packet delivery from nodes in the network to the DAG root.
Analisis Pengambilan Keputusan Ekonomi Rumah Tangga Petani Kelapa di Kecamatan Pulau Burung, Kabupaten Indragiri Hilir

Usahatani kelapa merupakan matapencaharian utama rumahtangga di Kecamatan Pulau Burung. Permasalahan yang dihadapi rumahtangga petani kelapa adalah harga kelapa yang relatif murah, intrusi air laut, tanaman tua dan rusak dan pasar yang bersifat monopsoni. Mengacu pada permasalahan tersebut, maka studi ini dilakukan dengan tujuan untuk menganalisis faktor-faktor yang mempengaruhi keputusan ekonomi rumahtangga dari aspek produksi, curahan waktu kerja, pendapatan dan pengeluaran. Pendekatan ekonometrika persamaan simultan dengan metode Two Stage Least Squares digunakan untuk menjawab tujuan penelitian tersebut. Hasil analisis menunjukkan bahwa: Pertama, jumlah produksi tidak responsif dipengaruhi oleh jumlah tanaman kelapa produktif. Kedua, alokasi waktu kerja pada USAhatani kelapa dipengaruhi secara positif dan responsif oleh angkatan kerja rumahtangga. Penggunaan tenaga kerja upahan dipengaruhi secara positif dan responsif oleh pendapatan USAhatani kelapa. Alokasi waktu kerja non USAhatani kelapa dipengaruhi secara positif dan responsif oleh pendapatan non USAhatani kelapa. Ketiga, pendapatan non USAhatani kelapa dipengaruhi secara positif dan responsif oleh alokasi waktu kerja non USAhatani kelapa. Keempat, pengeluaran rumahtangga petani kelapa dipengaruhi secara positif dan responsif oleh pendapatan total rumahtangga, sebaliknya negatif dan responsif oleh tabungan rumahtangga. Investasi pendidikan dipengaruhi oleh pendapatan total rumahtangga dan konsumsi pangan. Kelima, dalam rangka meningkatkan produksi kelapa diperlukan intervensi pemerintah untuk meremajakan tanaman kelapa yang tua dan rusak, memperbaiki tanggul untuk mencegah intrusi air laut dan pemberantasan hama dan penyakit. Selain itu diperlukan upaya yang dapat mendorong rumahtangga petani kelapa untuk mengalokasikan waktu kerja yang lebih banyak pada USAhatani kelapa miliknya.
LATCHESS21: dataset of damaged chessboard lattice points (chessboard features) used to train LAPS detector (grayscale/21x21px)

Large dataset of damaged __chessboard lattice points__ (chessboard features), generated\r\nautomatically by modifying perfect 2D standard 8x8 chessboard grid, then\r\nevaluated on real photographs during detection process. \r\n\r\n__10%__ - perfect cases\r\n__10%__ - warped (random direction)\r\n__50%__ - evaluated during detection (real)\r\n__20%__ - mostly mistaken (objects)\r\n__10%__ - very hard (destroyed)\r\n\r\nIt contains the following subsets:\r\n\r\n- __ok__: correct chessboard lattice points\r\n- __no__: similar structures but not correct (convergent)\r\n\r\n_This dataset was used to train LAPS detector described in our article. _
Bayesian Learning of Random Graphs & Correlation Structure of Multivariate Data, with Distance between Graphs

We present a method for the simultaneous Bayesian learning of the correlation matrix and graphical model of a multivariate dataset, using Metropolis-within-Gibbs inference. Here, the data comprises measurement of a vector-valued observable, that we model using a high-dimensional Gaussian Process (GP), such that, likelihood of GP parameters given the data, is Matrix-Normal, defined by a mean matrix and between-rows and between-columns covariance matrices. We marginalise over the between-row matrices, to achieve a closed-form likelihood of the between-columns correlation matrix, given the data. This correlation matrix is updated in the first block of an iteration, given the data, and the (generalised Binomial) graph is updated in the second block, at the partial correlation matrix that is computed given the updated correlation. We also learn the 95$\%$ Highest Probability Density credible regions of the correlation matrix as well as the graphical model of the data. The difference in the acknowledgement of measurement errors in learning the graphical model, is demonstrated on a small simulated dataset, while the large human disease-symptom network--with $> 8,000$ nodes--is learnt using real data. Data on the vino-chemical attributes of Portugese red and white wine samples are employed to learn the correlation structure and graphical model of each dataset, to then compute the distance between the learnt graphical models.
Adaptive Coda‐Wave Imaging With Voronoi Tessellation

Reconstructions of Green's functions by ambient noise interferometry enable the imaging of the Earth's subsurface. Coda waves from reconstructed Green's functions can be utilized to perform time‐dependent imaging of processes that vary substantially at daily to monthly time scales in the crust. Time‐lapse Coda‐Wave Imaging (CWI) can detect tiny changes in seismic velocity with high temporal resolution. While previous studies on CWI have mainly focused on the descriptions of coda waves' propagation, little attention has been paid to choosing effective inversion algorithms that are suitable for CWI. Here we address this issue by developing a pragmatic inversion approach based on Voronoi tessellation with mesh cells adapted to coda‐wave sensitivity kernels. Using seismic stations in Central California, we present both synthetic and real data imaging to demonstrate that this approach stabilizes the inversion, is computationally efficient, and provides spatially adaptive resolution. We further propose a heuristic approach for a quantitative assessment of spatial resolution based on multi‐scale checkerboard tests.
Regulatory Mechanisms Underlying Arsenic Uptake, Transport, and Detoxification in Rice

Arsenic (As) is a metalloid environmental pollutant ubiquitous in nature that causes chronic and irreversible poisoning to humans through its bioaccumulation in the trophic chain. Rice, the staple food crop for 350 million people worldwide, accumulates As more easily compared to other cereal crops due to its growth characteristics. Therefore, an in-depth understanding of the molecular regulatory mechanisms underlying As uptake, transport, and detoxification in rice is of great significance to solving the issue of As bioaccumulation in rice, improving its quality and safety and protecting human health. This review summarizes recent studies on the molecular mechanisms of As toxicity, uptake, transport, redistribution, regulation, and detoxification in rice. It aims to provide novel insights and approaches for preventing and controlling As bioaccumulation in rice plants, especially reducing As accumulation in rice grains.