Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Volume Scattering Model for Three-Component Decomposition of Polarimetric SAR Data

A modified volume scattering model for Freeman-Durden three-component decomposition is proposed in this study. Due to the inconsistency between uniform oriented dipole mode and the actual volume scattering mechanism for terrain types, the power of surface scattering and double-bounce scattering are occasionally negative. We established the volume scattering model using dipoles with two dominant orientations and proved it can decrease the probability of negative power occurrence in mathematics. The new volume scattering model is better to mimic the building with sloped roofs. We carried out three-component decomposition with proposed volume scattering model and other three models respectively using the L-band AIRSAR polarimetric SAR data. The results show that the pixels with negative powers are significantly decreased by our model and thus the effectiveness of the new model are demonstrated. In particular, the proposed volume scattering model work well in the forest and oriented building areas.
Association Between Plasma Concentration of Klotho Protein, Osteocalcin, Leptin, Adiponectin, and Bone Mineral Density in Patients with Chronic Kidney Disease

Abstract Patients with early-stage chronic kidney disease (CKD) are susceptible to changes in metabolic processes. Partial loss of kidney function leads to homoeostatic disturbances in bone and fatty tissue. The aim of this study was to investigate the association between plasma concentrations of Klotho protein, FGF23, leptin, adiponectin, osteocalcin, and bone mineral density (BMD) in patients with CKD in the pre-dialysis period. The study involved 52 patients with CKD and 23 patients with no kidney disease. In both groups, BMD, body mass index and serum or plasma concentrations of lipids, glucose, creatinine, calcium, phosphorus, parathormone, leptin, adiponectin, osteocalcin, Klotho, and FGF23 were measured. The group with CKD had statistically significant higher concentrations of leptin (p<0.001), parathormone (p<0.001), and osteocalcin (p<0.001) in comparison with the control group. Patients with CKD also had statistically significant lower BMD in the femoral neck in comparison with the control group. Osteocalcin correlated negatively with BMD. The results of our study suggest that elevated osteocalcin is the most sensitive marker of decreased bone mass in patients with CKD. Osteocalcin correlated negatively with BMD and GFR. The loss of bone mass in CKD patients was greatest in the femoral neck.
Building a Hyperspectral Library and its Incorporation into Sparse Unmixing for Mineral Identification

The objective of the SOLSA project (EU-H2020) is to develop an analytical expert system for on-line-on-mine-real-time mineralogical and geochemical analyses on sonic drill cores. As one aspect of the system, this paper presents the building of the hyperspectral library and its incorporation into sparse unmixing techniques for mineral identification. Twenty seven spectra representing 14 minerals have been collected for the library. Three sparse unmixing techniques have been investigated and evaluated using simulated data generated from our hyperspectral library, and real hyperspectral data acquired from a serpentinized harzburgite sample. Among the three techniques, the collaborative sparse unmixing by variable splitting and augmented Lagrangian (CLSUnSAL) method provided the best accurate results on the simulated data. In addition, the results of the CLSUnSAL method show high correlation with that of the QEMSCAN® analysis on the harzburgite hyperspectral data.
Study on the Effectiveness of Organizational Citizenship Behavior and Engagement on Information Security Policy

With regard to the organizational strengthening of information security, in addition to establishing protective mechanisms from the technical perspective and formulating standards and conduct audits from a management perspective, enabling organizational information security policies and making employees actively or passively comply with information security policies have become important discussion topics in recent years. This study combines organizational citizenship behavior and group engagement models, and uses organizational citizenship behavior to explain extra-role behavior. Group engagement models to strengthen in-role behavior can enable employees to be more involved with work and comply with standards. Furthermore, we examine the causes of organizational citizenship behavior and engagement. This study conducted questionnaire surveys in Taiwanese organizations that have obtained ISO 27001 accreditation. This will contribute to theoretical expansion and provide a theoretical basis for promoting and encouraging information security policies. Organizational identification will be used to improve organizational citizenship behavior and engagement.
Viral Loads Within 6 Weeks After Diagnosis of HIV Infection in Early and Later Stages: Observational Study Using National Surveillance Data

Background Early (including acute) HIV infection is associated with viral loads higher than those in later stages. Objective This study aimed to examine the association between acute infection and viral loads near the time of diagnosis using data reported to the US National HIV Surveillance System. Methods We analyzed data on infections diagnosed in 2012-2016 and reported through December 2017. Diagnosis and staging were based on the 2014 US surveillance case definition for HIV infection. We divided early HIV-1 infection (stage 0) into two subcategories. Subcategory 0α: a negative or indeterminate HIV-1 antibody test was ≤60 days after the first confirmed positive HIV-1 test or a negative or indeterminate antibody test or qualitative HIV-1 nucleic acid test (NAT) was ≤180 days before the first positive test, the latter being a NAT or detectable viral load. Subcategory 0β: a negative or indeterminate antibody or qualitative NAT was ≤180 days before the first positive test, the latter being an HIV antibody or antigen/antibody test. We compared median earliest viral loads for each stage and subcategory in each of the first 6 weeks after diagnosis using only the earliest viral load for each individual. Results Of 203,392 infections, 56.69% (115,297/203,392) were reported with a quantified earliest viral load within 6 weeks after diagnosis and criteria sufficient to determine the stage at diagnosis. Among 5081 infections at stage 0, the median earliest viral load fell from 694,000 copies/mL in week 1 to 125,022 in week 2 and 43,473 by week 6. Among 30,910 infections in stage 1, the median earliest viral load ranged 15,412-17,495. Among 42,784 infections in stage 2, the median viral load declined from 44,973 in week 1 to 38,497 in week 6. Among 36,522 infections in stage 3 (AIDS), the median viral load dropped from 205,862 in week 1 to 119,000 in week 6. The median earliest viral load in stage 0 subcategory 0α fell from 1,344,590 copies/mL in week 1 to 362,467 in week 2 and 47,320 in week 6, while that in subcategory 0β was 70,114 copies/mL in week 1 and then 32,033 to 44,067 in weeks 2-6. The median viral load in subcategory 0α was higher than that in subcategory 0β in each of the first 6 weeks after diagnosis (P<.001). Conclusions In the 1st week after diagnosis, viral loads in early infections are generally several times higher than those in later stages at diagnosis. By the 3rd week, however, most are lower than those in stage 3. High viral loads in early infection are much more common in subcategory 0α than in subcategory 0β, consistent with 0α comprising mostly acute infections and 0β comprising mostly postacute early infections. These findings may inform the prioritization of interventions for prevention.
Hyperspectral Compressive Sensing on Low Energy Consumption Board

Hyperspectral imaging instruments allow remote Earth exploration by measuring hundreds of spectral bands (at different wavelength channels) for the same area of the Earth surface. The acquired data cube comprises several GBs per flight, which have attracted attention to onboard compression techniques. Typically these compression techniques are expensive from the computational point of view. This paper presents a compressive sensing method implementation on a low power consumption Graphic Processing Unit. The experiments are conducted on a Jetson TX1 board, which is well suited to perform vector operations such as dot products. These experiments have been performed to demonstrate the applicability, in terms of accuracy and time consuming, of these methods for onboard processing. The results show that by using this low power consumption GPU it is possible to obtain real-time performance with a very limited power requirements.
Word Embeddings for Morphologically Rich Languages

Word-embedding models commonly treat words as unique symbols, for which a lower-dimensional embedding can be looked up. These representations generalize poorly with morphologically rich languages, as vectors for all possible inﬂections cannot be stored, and words with the same stem do not share a similar representation. We study alternative representations for words, including one subword-model and two character-based models. Our methods outperform classical word embed-dings for a morphologically rich language, Finnish, on tasks requiring sophisticated understanding of grammar and context. Our embeddings are easier to implement than previously proposed methods, and can be used to form word-representations for any common language processing tasks.
The Roles of Endo-Lysosomes in Unconventional Protein Secretion

Protein secretion in general depends on signal sequence (also named leader sequence), a hydrophobic segment located at or close to the NH2-terminus of a secretory or membrane protein. This sequence guides the entry of nascent polypeptides into the lumen or membranes of the endoplasmic reticulum (ER) for folding, assembly, and export. However, evidence accumulated in recent years has suggested the existence of a collection of unconventional protein secretion (UPS) mechanisms that are independent of the canonical vesicular trafficking route between the ER and the plasma membrane (PM). These UPS mechanisms export soluble proteins bearing no signal sequence. The list of UPS cargos is rapidly expanding, along with the implicated biological functions, but molecular mechanisms accountable for the secretion of leaderless proteins are still poorly defined. This review summarizes our current understanding of UPS mechanisms with an emphasis on the emerging role of endo-lysosomes in this process.
Local Similarity Regularized Sparse Representation for Hyperspectral Image Super-Resolution

Recently, performance of hyperspectral image super-resolution (SR) has been significantly improved via sparse representation. However, most of these existing methods fail to consider the local geometrical structure of the sparse coefficients. To take this crucial issue into account, this paper proposes an effective method, which exploits the location related constraint about the sparse coefficients and incorporates their local similarity into the sparse coding process. Thus, the proposed method can preserve the properties of the aforementioned local geometrical structures. Based on the experimental results, the proposed method is demonstrated to be more effective than previous efforts in the task of hyperspectral image SR.
Snow Depth Estimation with Gnss-R Dual-Receiver Observation

Snow is an important part of freshwater resources. Accurately measuring the snow depth is of great significance for studying the hydrological cycle and preventing flood hazards. In addition to the traditional ground -based direct measurement, snow depth can also be estimated by the spaceborne or airborne remote sensing. Compared with the traditional method, the latter has advantages in resource optimization and data processing. GNSS Reflectometry (GNSS-R) as an emerging technology can be used to estimate snow depth. In this paper, we present a new method to estimate snow depth. The method combines the carrier phase observations of GPS dual-frequency (L1 and L2) obtained by the dual-receiver system. This phase combination is geometry free and is not affected by ionospheric delays. A theoretical model is established to describe the relationship between the snow depth and the spectral peak frequency of the combined phase. In the actual snow depth estimation process, the carrier phase observation data recorded by GNSS receivers are processed to obtain the spectral peak frequency which is then used to calculate the snow depth based on the developed model.
Computer-Aided Design for Quantum Computation

Quantum computation is currently moving from an academic idea to a practical reality. The recent past has seen tremendous progress in the physical implementation of corresponding quantum computers - also involving big players such as IBM, Google, Intel, Rigetti, Microsoft, and Alibaba. These devices promise substantial speedups over conventional computers for applications like quantum chemistry, optimization, machine learning, cryptography, quantum simulation, and systems of linear equations. The Computer-Aided Design and Verification (jointly referred as CAD) community needs to be ready for this revolutionizing new technology. While research on automatic design methods for quantum computers is currently underway, there is still far too little coordination between the CAD community and the quantum computation community. Consequently, many CAD approaches proposed in the past have either addressed the wrong problems or failed to reach the end users. In this summary paper, we provide a glimpse into both sides. To this end, we review and discuss selected accomplishments from the CAD domain as well as open challenges within the quantum domain. These examples showcase the recent state-of-the-art but also outline the remaining work left to be done in both communities.
Investment Efficiency Research Theme Changes and Development Trends on the basis of CiteSpace

In order to systematically understand the field of enterprise investment efficiency, this paper analyzes the trend of the development of investment efficiency in the enterprise over time, establishes a cross-sectional research direction and a vertical timeline system, and combines the economic background and research status to make scientific predictions on future development trends. This paper selects “CNKI” and “web of science” as the literature search engine in 2003-2018, and uses the tool (CiteSpace) to cluster and analyze the data, showing the relationship between knowledge structure, main research institutions and evolution law of enterprise investment efficiency. The research results show that the research path of domestic and foreign investment efficiency is different. The domestic undergoes the process from the micro-features of enterprises to the combination of macro-economy. Foreign countries are cutting from macroeconomics and industry factors, gradually combining the micro-features of enterprises, and changing with time. There is a clear trend in research direction. The future development direction of enterprise investment efficiency mainly focuses on the combination of micro-characteristics with economic environment and policies, the commitment of social responsibility, and the influence of market participants' behaviors and emotions on corporate investment efficiency. This research combs the development of research on investment efficiency in domestic and foreign enterprises, and provides a directional reference for the future development of this field. Keywords—Enterprise investment efficiency; Research theme; Research method; Future development
Imaging Comparison Between the Real Aperture and Synthetic Aperture Microwave Radiometers: a Case Study for Geo Sounder

The dream of launching a microwave radiometer into geostationary orbit (GEO) for atmosphere sounding has lasted for over four decades. Several concepts have been proposed, but none of them has come into reality by now. All these concepts can be divided into two different ways, using real aperture microwave radiometer (RA-MWR) and using synthetic aperture microwave radiometer (SA-MWR). This paper is dedicated to make a preliminary comparison between the imaging performances of the RA-MWR and SA-MWR in GEO applications. In the comparison, a similar concept with the Geostationary Observatory for Microwave Atmospheric Sounding (GOMAS) with a Cassegrain antenna proposed by ESA is taken as the RA-MWR example, while the concept of Geostationary Interferometric Microwave Sounder (GIMS) with a circular antenna array pursued in China is taken as the example of SA-MWR. The numerical simulation results indicate that, with the benefits of using a predesigned Earch model, or even using a simple disc target, SA-MWR can greatly reduce the imaging error especially in the areas near to the Earth contour, and thus achieve a higher imaging accuracy than RA-MWR.
Early Results from NOAA-20 (JPSS-1) VIIRS On-ORBIT Calibration and Characterization

Since launch in November 2018, the VIIRS on-board the NOAA-20 (or JPSS-1) satellite has completed its initial intensive on-orbit check-outs and several key calibration and validation activities scheduled to help evaluate sensor at launch performance. This paper provides a brief overview of NOAA-20 VIIRS on-orbit operation and calibration activities, presents early results derived from its on-board calibrators and lunar observations, and discusses potential improvements and future effort to assure sensor data product quality.
Pyrgg: Python Random Graph Generator

Pyrgg is an easy-to-use synthetic random graph generator written in Python which supports various graph file formats including DIMACS . gr files. Pyrgg has the ability to generate graphs of different sizes and is designed to provide input files for broad range of graph-based research applications, including but not limited to testing, benchmarking and performance-analysis of graph processing frameworks. (Zhong and He 2012; Chakrabarti, Zhan, and Faloutsos 2004) Pyrgg target audiences are computer scientists who study graph algorithms and graph processing frameworks.
Evaluation of Different Regularization Methods for the Extreme Learning Machine Applied to Hyperspectral Images

During recent years, many regularization techniques have been proposed to deal with ill-posed problems related to hyperspectral image classification, in which the limited number of training samples contrasts with the very high spectral dimensionality. However, the intrinsic structure of a hyperspectral image often depends on the specific scene and spectrometer, although regularizers like Ridge, LASSO, etc, have been widely used in practical applications. Instead of imposing these regularizers to the probabilistic output of a classifier, this work evaluates the use of extreme learning machines (ELM) with output weights of a single-hidden layer feed-forward neural network (SLFN) regularized with Ridge and LASSO priors, respectively. Experimental results with several real hyperspectral images are conducted to compare the performance and adaptation of these two regularizers with the the original ELM in classification scenarios.
High-Performance Field Emitters of Multiwalled Carbon Nanotubes Grown by Varying Oxygen Gas Pressure Using Arc Discharge

High-current field emission from carbon nanotube (CNT) emitters usually force them to be exposed to high electrostatic forces and Joule heating. Vacuum packaging of field emission devices is also often performed at high temperature. Under these circumstances, CNT emitters may be easily damaged and thus require highly crystalline and thermally stable CNTs. In this study, CNT paste was prepared using highly crystalline CNTs grown arc discharge. This study optimized oxygen gas pressure for the arc discharge growth of CNTs in terms of their crystallinity and thermal stability. Compared with the CNTs grown by catalytic chemical vapor deposition, the arc-produced CNTs showed better lifetime performance, probably due to their higher crystallinity.
Advanced tube formation assay using human endothelial colony forming cells for in vitro evaluation of angiogenesis

The tube formation assay is a widely used in vitro experiment model to evaluate angiogenic properties by measuring the formation of tubular structures from vascular endothelial cells (ECs). in vitro experimental results are crucial when considered the advisability of moving forward to in vivo studies. Thus, the additional attentions to the in vitro assay is necessary to improve the quality of the pre-clinical data, leading to better decision-making for successful drug discovery. In this study, we improved the tube formation assay system in three aspects. First, we used human endothelial colony forming cells (ECFCs), which are endothelial precursors that have a robust proliferative capacity and more defined angiogenic characteristics compared to mature ECs. Second, we utilized a real-time cell recorder to track the progression of tube formation for 48 hours. Third, to minimize analysis error due to the limited observation area, we used image-stitching software to increase the microscope field of view to a 2×2 stitched area from the 4× object lens. Our advanced tube formation assay system successfully demonstrated the time-dependent dynamic progression of tube formation in the presence and absence of VEGF and FGF-2. Vatalanib, VEGF inhibitor, was tested by our assay system. Of note, IC50 values of vatalanib was different at each observation time point. Collectively, these results indicate that our advanced tube formation assay system replicates the dynamic progression of tube formation in response to angiogenic modulators. Therefore, this new system provides a sensitive and versatile assay model for evaluating pro- or anti-angiogenic drugs.
Prolonged Cold-Air Outbreaks Over the Chukchi Sea: Synthesis of Multisensor Satellite Measurements and Reanalysis Dataset

In present study Cold-Air Outbreaks (CAOs) associated with storm winds and extreme air-sea exchange conditions are diagnosed over the Chukchi Sea during autumn-winter periods (Sept-Dec) 2014–2016 using multisensor satellite measurements and high-resolution reanalysis dataset. Analysis of the fields of geophysical parameters from satellite and model data showed that in the autumn-winter period cold-air outbreaks are systematically (on average 2 cases/month) observed over the Chukchi Sea with the near sea surface wind speed $\mathrm{W}\geq 20\ \mathrm{m}/\mathrm{s}$. At the end of November - early December 2014 and 2015 anomalously prolonged (7–13 days) CAOs were identified, accompanied by severe/storm winds and waves, rapid formation and drift of sea ice. In both cases, the cold advection from the polar ice cap was caused by a system of extratropical cyclones over the Bering Sea and the Gulf of Alaska, which strengthens the Aleutian Low, and the Arctic anticyclone. Unlike typical CAOs over the Northwestern Pacific Ocean, covering the lower troposphere layer up to 3–5 km, intense cold advection over the Chukchi Sea was noted mainly in the boundary layer of the atmosphere below 1 km.