Miracle-dz/UniFAR-FTUs huggingface dataset:
Uncover Fully Ignored Vital Bathymetric Data Mysteriously Hidden in Digital Elevation Model Combining with Remote Sensing Imagery (Part 1: Methodology and Theoretical Interpretation)

This is an interdisciplinary research to uncover a miss-observed and very important phenomenon in remote sensing. The high valuable bathymetric data hidden in digital elevation models have completely been ignored by scientists and researchers including main organizations in the world for a long time. The contents have been classified into two parts to demonstrate them. In the part 1, the focus is on introducing a special technique of discovering bathymetric data of lakes and rivers by means of remote sensing Image processing and the fact of water depths found in seeking for a resolution to water pollution for a large scale inland lake. The further performance is in analysing causes starting from radar interferometry. The more attentions are paid to how the microwave emitted and received by antennas of synthetic aperture radar installed in satellites during its propagation and scattering back interacts with molecules of chemical compounds in water body using spectral analysis in spectroscopy such as Raman scattering, nuclear magnetic resonance combining with knowledge of quantum mechanics and physical chemistry. The causes of losing those data have been found from phase shifting interferometry during phase detection and terrain mapping. The outcomes of this research have proved a fact that the capacity of microwave detecting depths of water relies on molecular structure, communication and strength of external electromagnetic fields and bathymetric data could also exist near sea coast. Researchnot only offered difference between optical imaging and radar imaging but also established correlation of effectively using individual data.
Clinical and Basic Cardiology

Background: Increased oxidative stress is a hallmark of end-stage renal disease (ESRD). Glutathione S transferases (GST) are involved in the detoxification of xenobiotics and protection from oxidative damage. We hypothesized that genetic polymorphisms in antioxidant enzymes GSTM1 and GSTT1 are more frequent in ESRD and modulate the degree of oxidative stress in these patients. Objectives: The present study was designed to evaluate oxidized LDA (ox-LDL), high-sensitivity C-reactive protein (hs-CRP), and homocysteine (hcy) levels in children with end-stage renal disease (ESRD) treated with maintenance haemodialysis (MHD) or under conservative treatment, to compare these levels with those assayed in control subjects, and to evaluate these levels with different GSTM1 and GSTT1 genotypes. Methods: This case-control study was conducted in 78 children. They were divided into 3 groups: group I (44 on HD), group II (14 on conservative treatment), and group III (20 normal healthy children) served as controls. All enrolled cases and controls were subjected to genotyping for GSTM1 and GSTT1 by polymerase chain reaction (PCR) and determination of ox-LDL, hs-CRP, and hcy levels. Results: Oxidized LDL levels were significantly higher in both the MHD and conservative treatment groups than in controls and levels were higher in the MHD group than in the conservative treatment group (199.48 ± 78.63 µ/l, 182.07 ± 128.77 µ/l, and 88.25 ± 23.02 µ/l, respectively). hs-CRP levels were significantly higher in the MHD group compared to the control group (4.03 ± 4.59 mg/dl and 1.14 ± 0.75 mg/dl). Homocysteine showed significantly higher levels in the MHD group when compared to both conservative treatment and control groups (73.43 ± 35.08, 20.35 ± 32.81 µmol/ml, and 5.9 ± 2.8 µmol/ml, respectively). Dialyzed and conservative-treatment patients had significantly higher frequencies of the GSTM1 and GSTT1 null genotypes when compared to the control group. Conclusion: Patients with GSTM1 or GSTT1 null genotypes are more vulnerable to oxidative stress compared with those who possess normal gene expression in chronic kidney disease. J Clin Basic Cardiol 2013; 16 (online): 1–5.
Nano-Sized Elements in Electrochemical Biosensors

The emerging nanotechnology has opened novel opportunities to explore analytical applications of the fabricated nano-sized materials. Recent advances in nano-biotechnology have made it possible to realize a variety of enzyme electrodes suitable for sensing application. In coating miniaturized electrodes with biocatalysts, undoubtedly the most of the potential deposition processes suffer from the difficulty in depositing process and reproducible coatings of the active enzyme on the miniature transducer element. The promising prospects can concern to the obtaining of thin protein layers by using, i.e. electrochemical deposition, electrophoretic deposition as well as monolayer methods (Langmuir-Blodgett procedure, Layer-by-Layer—LbL). Many aspects dealing with deposition of enzyme by techniques employing electric field are considered, including surface charge of enzyme, and its migration under applied electric filed. The using of nanoscale materials (i.e. nanoparticles, nanowires, nanorods) for electrochemical biosensing has seen also explosive increase in recent years following the discovery of nanotubes. These structures offer a promise in the development of biosensing, facilitating the great improvement of the selectivity and sensitivity of the current methods. Finally, the perspectives in the further exploration of nanoscaled sensors are discussed.
1 ESG and Crowdfunding Platforms

This paper jumpstarts a conversation between fintech and environmental, social, and governance (ESG) goals. Using data on the population of 508 platforms established in the 38 OECD countries between 2007 and 2020, we document that platforms with higher levels of ESG selection criteria are more likely to survive over time. The importance of ESG criteria is more pronounced for platforms operating in countries with lower power distance. Decomposing ESG, governance is the most significant factor, while environmental criteria have emerged in recent years.
Robust detection of deeply subwavelength pits in simulated optical data-storage disks using photonic jets

We report a means to detect deeply subwavelength pits in optical data-storage media by employing the recently observed giant backscattering perturbation phenomenon of the photonic jet. We conducted microwave experiments with dimensionally scaled-up pits and lands in a simulated optical data-storage device. These measurements were backed up by three-dimensional finite-difference time-domain computational solutions of Maxwell's equations. Results indicate that pits having a lateral area of 0.025 square wavelengths, i.e., much smaller than current BluRay™ device features, can be robustly detected with a contrast ratio approximately 28dB greater than that provided by a lens system.
ELEVATED SERUM PROLACTIN LEVELS AS A MARKER OF INFLAMMATION IN PSORIASIS VULGARIS – AWAKENED ISSUE

Background and aims Psoriasis vulgaris is well-known as a chronic, recurrent, immune-mediated inflammatory disease with a conceded genetic predisposition. Neither the etiology of the psoriasis, nor specific laboratory markers for its disease activity have been clearly elucidated. Prolactin (PRL) acts as a cytokine with immunomodulatory functions, therefore it plays a role in skin biology. However, the results of PRL as a marker remains unclear. The aim of this study was to confirm whether serum PRL levels reflect the activity of the disease or systemic complications, like inflammatory joint disease.
Time-dependent Electron Acceleration in Pulsar Wind Termination Shocks: Application to the 2011 April Crab Nebula Gamma-Ray Flare

The γ-ray flares from the Crab Nebula observed by AGILE and Fermi-LAT between 2007 and 2013 reached GeV photon energies and lasted several days. The strongest emission, observed during the 2011 April “superflare”, exceeded the quiescent level by more than an order of magnitude. These observations challenge the standard models for particle acceleration in pulsar wind nebulae, because the radiating electrons have energies exceeding the classical radiation-reaction limit for synchrotron emission. Particle-in-cell simulations have suggested that the classical synchrotron limit can be exceeded if the electrons also experience electrostatic acceleration due to shock-driven magnetic reconnection. In this paper, we revisit the problem using an analytic approach based on solving a fully time-dependent electron transport equation describing the electrostatic acceleration, synchrotron losses, and escape experienced by electrons in a magnetically confined plasma “blob” as it encounters and passes through the pulsar wind termination shock. We show that our model can reproduce the γ-ray spectra observed during the rising and decaying phases of each of the two sub-flare components of the 2011 April superflare. We integrate the spectrum for photon energies MeV to obtain the light curve for the event, which also agrees with the observations. We find that strong electrostatic acceleration occurs on both sides of the termination shock, driven by magnetic reconnection. We also find that the dominant mode of particle escape changes from diffusive escape to advective escape as the blob passes through the shock.
Karar Ağaçları ile Otistik Spektrum Bozukluğu Tanısı Koyma

Çalışmamız; sosyal etkileşim, tekrarlayan davranışlar, kısıtlı ilgi alanları ve iletişim sorunu olarak ortaya çıkan ve ömür boyu devam eden bir gelişim bozukluğu olan Otizmin erken tanısı üzerine gerçekleştirilmiştir. Karar ağacı algoritmaları ile Otistik Spektrum Bozukluğu tanısı koymada ilişkili özellikle on davranış tespiti sorusu ile %95,73 başarıyla doğru tanı koymada etkili olduğu gözlemlenmiştir. Ayrıca çalışmada, etnik yapının hastalığa etkisi incelenmiş ve sonuçlarda yüksek oranda bir fark tespit edilmemiştir.
Of Open and Closed Wheels Aerodynamic Of Racing Cars in Wind Tunnels With Movable Ground At Different Car Speeds

The paper proposes the CFD study of a GT2 and a F1 racing car in a wind tunnel with movable ground and wheels. After a sensitivity analysis on the modelling of turbulence and the grid generation parameters, simulations are performed at different air speed to determine the pressure and shear contributions to the lift and drag coefficients. For the GT2 car, the drag and lift coefficients are around CD=0.4 and CL=-0.5 (down force). The down force is mostly the result of the under body diffuser and the rear wing. The rear wing contributes more than 85% of the lift force and 7-8% of the drag force. When reference is made to the low speed drag and lift coefficients, increasing the speed from 25 to 100 m/s produces an increase of CD of more than 3 % and a reduction of CL of more than 2 %. For the F1 car, the drag and lift coefficients are strongly variable in between race track and race track, mostly adjusted by the front and rear wing incidence. For the particular set-up, CD is around 0.8 and CL is around -1.2 (down force). The down force is mostly the result of the large front and rear wings immediately visible and the under body diffusers and vortex generators hidden below the car. These results suggest modifying the constant CD and CL values used in lap time simulation tools introducing the tabulated values to interpolate vs. the speed of the car.
Numerical Simulations of the Urban Microclimate

As global urbanization is accelerating and the majority of the world’s population continues to reside in cities, sustainable urban development is becoming increasingly crucial. Evaluation of the urban microclimate is a vital aspect of planning sustainable cities, as it can significantly impact on the health and comfort of urban residents. Computational Fluid Dynamics is a cost-effective and flexible tool to predict microclimate conditions, although often not utilized in the urban planning process until the final stages of a project due to complex pre-processing. The current practice of urban planning also often involves simulating different physical phenomena in separate tools, making it difficult to understand the interaction. This thesis presents the potential of the numerical immersed boundary framework IBOFLow as a tool for urban planners to evaluate the urban microclimate at the early stages of the design processes. The complex and time-consuming pre-processing of urban regions is eliminated using automatically generated Cartesian octree grid meshes where the complex geometries are represented by the immersed boundary methodology. The framework is validated for wind using wind tunnel experiments and compared to a commercially used software to show the importance of including the complex local terrain to generate realistic results. Finally, initial results of the heat simulations are covered to visualize the idea of IBOFlow as a means to simulate the urban microclimate at large, including all necessary physics.
Directions for Big Data Graph Analytics

In the era of big data, interest in analysis and extraction of information from large data graphs is increasing rapidly. This paper examines the field of graph analytics from somewhat of a query processing point of view. Whether it be determination of shortest paths or finding patterns in a data graph matching a query graph, the issue is to find interesting characteristics or information content from graphs. Many of the associated problems can be abstracted to problems on paths or problems on patterns. Unfortunately, seemingly simple problems, such as finding patterns in a data graph matching a query graph are surprisingly difficult. In addition, the iterative nature of algorithms in this field makes the simple MapReduce style of parallel and distributed processing less effective. Still, the need to provide answers even for very large graphs is driving the research. Progress, trends and directions for future research are presented. Keywords-big data; graph analytics; graph databases, Semantic Web, social networks, graph paths, graph patterns;
AN INVESTIGATION ON FLUX DENSITY OF THREE PHASE DISTRUBUTED AIR-GAP 3-5 LEGGED SHUNT REACTOR

Nowadays, transmission and distribution lines provide to transport energy from production area to usage area. However, the reactive power balance on the long transmission lines do not provide, the quality of the power transmission and the efficiency of power line is low. To achieve this situation, reactive power compensation is needed and we provide that to use shunt reactors. The design state of shunt reactor is important to achieve this mission. It’s important to define the parameters of shunt reactor such as yoke heights and air-gap length to set inductance value of reactor. In this study, the important parameters of reactor is calculated and use this parameters to design a reactor. Modeled reactor isanalyzed with Finite Element Method (FEM). Shunt reactor core’s air-gap is distributed for examine the effect of fringing by leakage flux lines and inductance values. Shunt reactor’s main values which are used by Turkish Electricity Transmission Company (TEIAS) is selected. 3 and 5-legged core design reactors simulation results are discussed considering the TEIAS specifications.
Input Illuminant shadings ShadingNet Reflectance chromaticity Reflectance chromaticityInput RGB image Illuminant shadings Separated images

We present a method to separate a single image captured under two illuminants, with different spectra, into the two images corresponding to the appearance of the scene under each individual illuminant. We do this by training a deep neural network to predict the per-pixel reflectance chromaticity of the scene, which we use in a physics-based image separation framework to produce the desired two output images. We design our reflectance chromaticity network and loss functions by incorporating intuitions from the physics of image formation. We show that this leads to significantly better performance than other single image techniques and even approaches the quality of the prior work that require additional images.
P o S ( D I S 2 0 1 7 ) 2 6 4 ATLAS Searches for V H , HH , VV , V + γ and γγ Resonances

The discovery of a Higgs boson at the Large Hadron Collider motivates searches for physics beyond the Standard Model in channels involving coupling to the Higgs boson. A search for massive resonances decaying into couples of bosons is described. The considered final states are: HH, V H, VV , V γ and γγ with V indicating either the W or the Z boson. Final states with different number of leptons or photons and where, in many cases, at least one Higgs decays into a b-quark pair are studied using different jet reconstruction techniques which allow to optimize the signal acceptance for low or high Higgs boson transverse momentum. The most recent diboson resonance searches using LHC Run 2 data are described.
Binding of the 5 0-untranslated region of coronavirus RNA to zinc finger CCHC-type and RNA-binding motif 1 enhances viral replication and transcription

Coronaviruses RNA synthesis occurs in the cytoplasm and is regulated by host cell proteins. In a screen based on a yeast three-hybrid system using the 50-untranslated region (50-UTR) of SARS coronavirus (SARS-CoV) RNA as bait against a human cDNA library derived from HeLa cells, we found a positive candidate cellular protein, zinc finger CCHC-type and RNA-binding motif 1 (MADP1), to be able to interact with this region of the SARS-CoV genome. This interaction was subsequently confirmed in coronavirus infectious bronchitis virus (IBV). The specificity of the interaction between MADP1 and the 50-UTR of IBV was investigated and confirmed by using an RNA pull-down assay. The RNA-binding domain was mapped to the N-terminal region of MADP1 and the protein binding sequence to stem–loop I of IBV 50-UTR. MADP1 was found to be translocated to the cytoplasm and partially co-localized with the viral replicase/transcriptase complexes (RTCs) in IBVinfected cells, deviating from its usual nuclear localization in a normal cell using indirect immunofluorescence. Using small interfering RNA (siRNA) against MADP1, defective viral RNA synthesis was observed in the knockdown cells, therefore indicating the importance of the protein in coronaviral RNA synthesis.
Elucidation of Time Symmetry Predicted by the Special Theory of Relativity Koshun Suto

In the thought experiment in this paper, we considered inertial frames M and A moving at a constant velocity relative to each other. A light signal emitted from inertial frame M, when time of a clock in inertial frame M was 1(s), arrived at inertial frame A when time of a clock in inertial frame A was 2(s). Conversely, the light signal emitted from inertial frame A, when time of a clock in inertial frame A was 1(s), arrived at inertial frame M when time of a clock in inertial frame M was 2(s). These results show that symmetry exists between the two inertial frames. However, the logic of explaining the arrival time of the light signal differs between observers M and A. Einstein regarded all inertial frames as equivalent, but it is not the case that all inertial frames are equivalent.
Development of an immunotherapeutic adenovirus targeting hormone-independent prostate cancer

Background: To develop a targeting therapy for hormone-independent prostate cancer, we constructed and characterized conditionally replicating oncolytic adenovirus (Ad) equipped with mRFP (monomeric red fluorescence protein)/ttk (modified herpes simplex virus thymidine kinase). This construct was then further modified to express both mRFP/ttk and a soluble form of cytokine FLT3L (fms-related tyrosine kinase 3 ligand) simultaneously. Methods: To construct the recombinant oncolytic adenovirus, E1a and E4 genes, which are necessary for adenovirus replication, were controlled by the prostate-specific enhancer sequence (PSES) targeting prostate cancer cells expressing prostate-specific antigen (PSA) and prostate-specific membrane antigen (PSMA). Simultaneously, it expressed the mRFP/ttk fusion protein in order to be able to elicit the cytotoxic effect. Results: The Ad5/35PSES.mRFP/ttk chimeric recombinant adenovirus was generated successfully. When replication of Ad5/35PSES.mRFP/ttk was evaluated in prostate cancer cell lines under fluorescence microscopy, red fluorescence intensity increased more in LNCaP cells, suggesting that the mRFP/ttk fusion protein was folded functionally. In addition, the replication assay including wild-type adenovirus as a positive control showed that PSES-positive cells (LNCaP and CWR22rv) permitted virus replication but not PSES-negative cells (DU145 and PC3). Next, we evaluated the killing activity of this recombinant adenovirus. The Ad5/35PSES. mRFP/ttk killed LNCaP and CWR22rv more effectively. Unlike PSES-positive cells, DU145 and PC3 were resistant to killing by this recombinant adenovirus. Finally, in order to potentiate therapeutic efficacy, we developed a recombinant adenovirus expressing multiexogenous genes, mRFP/ttk and sFLT3L. Conclusion: In the present study, a replication-competent adenovirus was successfully designed to replicate conditionally in PSA-positive and PSMA-positive prostate cancer cells. This recombinant adenovirus is equipped with the fusion protein of suicidal and red-fluorescence fusion protein together with sFLT3L. This construct would be expected to have potent antitumor effects and deserves more extensive investigation.
Augmented Bayesian Networks for Representing Information Equivalences and Extensions to the PC Learning Algorithm

Data containing deterministic relations entail conditional independencies that cannot be represented by a faithful graph, due to violations of the intersection condition. Such data can not be handled by current constraint-based learning algorithms. More generally, these violations are characterized by information equivalence of two sets of variables with respect to a target variable. We argue that deterministically related variables contain valuable information and should not be eliminated from the data. This paper proposes augmented Bayesian networks that explicitly model such information equivalences. For attaining minimality, only the set which has the simplest relation with the target variable is connected to it. Under the assumption that complexity does not increase along a causal path, this selection criterion results in consistent models. Under weak transitivity, faithfulness of the graph is reestablished by using the generalized definition of the d-separation criterion, called Deq-separation, and by limiting the conditional independencies that are graphically described with the simplicity condition. Based on this, an extension to the PC learning algorithm is developed that allows the construction of minimal augmented Bayesian networks from observational data. Correct models are learned from data generated by a set of structural equations.
Malthus and Climate Change: Betting on a Stable Population FORTHCOMING: Journal of Environmental Economics and Management

A standard assumption in integrated assessment models of climate change is that population and productivity are growing, but at a decreasing rate. We explore the signi cance of the assumption of population and productivity growth for greenhouse gas abatement. After all, there has been no long run slow down in the growth of productivity over the past few centuries, and the rate of population growth has actually been increasing for the past 19 centuries. Even if either of these growth rates were expected to slow, by how much is subject to great uncertainty. We show computationally that such continued growth greatly increases the severity of climate change. Indeed we nd that climate change is a problem in large part \caused" by exogenous population and productivity growth. Rapid reductions in growth make climate change a small problem; smaller reductions in growth imply climate change is a very serious problem indeed. Analogously, reductions in the growth rate of population can be e ective in controlling climate change.