Miracle-dz/UniFAR-FTUs huggingface dataset:
X-RAY REFLECTED SPECTRA FROM ACCRETION DISK MODELS. I. CONSTANT DENSITY ATMOSPHERES

We present new models for illuminated accretion disks, their structure, and reprocessed emission. We consider the effects of incident X-rays on the surface of an accretion disk by simultaneously solving the equations of radiative transfer, energy balance, and ionization equilibrium over a large range of column densities. We assume plane-parallel geometry and azimuthal symmetry, such that each calculation corresponds to a ring at a given distance from the central object. Our models include recent and complete atomic data for K-shell processes of the iron and oxygen isonuclear sequences. We examine the effect on the spectrum of fluorescent Kα line emission and absorption in the emitted spectrum. We also explore the dependence of the spectrum on the strength of the incident X-rays and other input parameters, and discuss the importance of Comptonization on the emitted spectrum.
First measurement of σ8 using supernova magnitudes only

A method was recently proposed which allows the conversion of the weak-lensing effects in the supernova Hubble diagram from noise into signal. Such signal is sensitive to the growth of structure in the universe, and in particular can be used as a measurement of $\sigma_8$ which is independent from more traditional methods such as those based on the CMB, cosmic shear or cluster abundance. We extend here that analysis to allow for intrinsic non-Gaussianities in the supernova PDF, and discuss how this can be best modelled using the Bayes Factor. Although it was shown that a precise measurement of $\sigma_8$ requires ~$10^5$ supernovae, current data already allows an important proof of principle. In particular we make use of the 732 supernovae with z < 1 of the recent JLA catalog and show that a simple treatment of intrinsic non-Gaussianities with a couple of nuisance parameters is enough for our method to yield the values $\sigma_8 = 0.84^{+0.28}_{-0.65}$ or $\sigma_8 < 1.45$ at a $2\sigma$ confidence level. This result is consistent with mock simulations and it is also in agreement with independent measurements and presents the first ever measurement of $\sigma_8$ using supernova magnitudes alone.
X-ray outbursts from a new transient in NGC 55

We report the outbursts from a newly discovered X-ray transient in the Magellanic-type, SB(s) m galaxy NGC 55. The transient source, XMMU J001446.81-391123.48, was undetectable in the 2001 XMM-Newton and 2004 Chandra observations, but detected in a 2010 XMM-Newton observation at a significance level of 9 sigma in the 0.3-8 keV energy band. The XMM-Newton spectrum is consistent with a power law with photon index Gamma = 3.17(-0.20)(+0.22), but is better fitted with a kT(in) = 0.70 +/- 0.06 keV disc blackbody. The luminosity was similar to 10(38) erg s(-1), and the source displayed strong short-term X-ray variability. These results, combined with the hardness ratios of its emission, strongly suggest an X-ray binary nature for the source. The follow-up studies with Swift XRT (X-ray Telescope) observations revealed that the source exhibited recurrent outbursts with period about a month. The XRT spectra can be described by a power law (Gamma similar to 2.5-2.9) or a disc blackbody (kT(in) similar to 0.8-1.0 keV), and the luminosity was in a range of 10(38)-10(39) erg s(-1), with no evidence showing any significant changes of the spectral parameters in the observations. Based on the X-ray spectral and temporal properties, we conclude that XMMU J001446.81-391123.48 is a new transient X-ray binary in NGC 55, which possibly contains a black hole primary.
CAUSE RELATED MARKETING AND GREEN PRODUCTS PURCHASE DECISION

Purpose: Current environmental problems has forced marketing managers, academics and research companies to look for factors that might encourage consumers to buy green products. Therefore, the purpose of this research was to empirically investigate the impact of cause–related marketing on green products purchase decision specifically in Pakistan’s context. It examines the level of influence CRM has on green products purchase decision. Design/Methodology/Approach: The current study is primarily based on quantitative research design that used structured questionnaires to collect the data from 4 cities of Pakistan. Data was collected through cross sectional method. Findings: The results revealed that cause-related marketing has a positive and significant relationship with green product purchase decision in Pakistan. People of Pakistan have positive inclination towards green products which are associated with any social or environmental cause. Implications/Originality/Value: On the basis of this research it can be concluded that cause-related marketing technique creates brand’s reputation, brand attitude and make people socially responsibility by involving community.
Detection of COVID‐19 and its pulmonary stage using Bayesian hyperparameter optimization and deep feature selection methods

Since the first case of COVID‐19 was reported in December 2019, many studies have been carried out on artificial intelligence for the rapid diagnosis of the disease to support health services. Therefore, in this study, we present a powerful approach to detect COVID‐19 and COVID‐19 findings from computed tomography images using pre‐trained models using two different datasets. COVID‐19, influenza A (H1N1) pneumonia, bacterial pneumonia and healthy lung image classes were used in the first dataset. Consolidation, crazy‐paving pattern, ground‐glass opacity, ground‐glass opacity and consolidation, ground‐glass opacity and nodule classes were used in the second dataset. The study consists of four steps. In the first two steps, distinctive features were extracted from the final layers of the pre‐trained ShuffleNet, GoogLeNet and MobileNetV2 models trained with the datasets. In the next steps, the most relevant features were selected from the models using the Sine–Cosine optimization algorithm. Then, the hyperparameters of the Support Vector Machines were optimized with the Bayesian optimization algorithm and used to reclassify the feature subset that achieved the highest accuracy in the third step. The overall accuracy obtained for the first and second datasets is 99.46% and 99.82%, respectively. Finally, the performance of the results visualized with Occlusion Sensitivity Maps was compared with Gradient‐weighted class activation mapping. The approach proposed in this paper outperformed other methods in detecting COVID‐19 from multiclass viral pneumonia. Moreover, detecting the stages of COVID‐19 in the lungs was an innovative and successful approach.
Smoothed Particle Hydrodynamics (SPH) method for modelling 2-dimensional free surface hydrodynamics

The main goal of the current research is to implement Smoothed Particle Hydrodynamics (SPH) for the prediction of wave-induced motions and loads within the framework of 3D modelling. In this paper, the focus is twofold. First, implementation of possible additional terms to the standard Incompressible SPH (ISPH) method with reference to generating/propagating regular waves in 2D domain, using a piston wave maker. Improvements to the prediction of pressure and velocity fields are then carried out with kernel renormalization technique and shifting technique without increasing the computational cost. The arc method is employed to improve the accuracy of free surface recognition, i.e. “noise-free” free surface. In addition, the Weakly Compressible (WCSPH) is also applied to the problem of 2D regular wave generation. Comparisons of predicted free surfaces, their kinematic and dynamic characteristics between ISPH, WCSPH and analytical solutions for a range of frequencies are carried out. The second focus of the paper is the 2D radiation problem due to forced sinusoidal oscillation of a rectangular section floating on calm water. The predicted hydrodynamic actions and coefficients in sway by WCSPH are then compared against available experimental measurements
Analysis of malondialdehyde and ferric reducing ability of plasma in type 2 diabetes mellitus patients in Lucknow city, India

Background: The incidence and prevalence of type 2 diabetes mellitus (T2DM) is increasing due to obesity and sedentary lifestyles. Increased oxidative stress leads to oxidative damage of biomolecules and decreased antioxidant capacity.Aim: The study was designed to determine the malondialdehyde (MDA) and ferric reducing ability of plasma (FRAP) in T2DM patients at IIMS&R Hospital, Lucknow.Method: The oxidative stress was analyzed in T2DM patients as MDA. The total antioxidant capacity was estimated through the FRAP in T2DM patients and control subjects.Results: The level of MDA was observed to be higher (4.84 ± 1.09) in T2DM patients compared to controls (2.20 ± 0.85). The FRAP was lower among T2DM patients (509.46 ± 126.36) compared to controls (895.62 ± 179.92). The difference between FRAP in T2DM patients and controls was statistically significant (p=0.0001). Conclusion: MDA was found to be higher in T2DM, and the FRAP level was lower in T2DM patients compared to controls, signifying increased oxidative stress and decreased antioxidant level in T2DM patients.
The XMM deep survey in the CDF-S. IX. An X-ray outflow in a luminous obscured quasar at z~1.6

In active galactic nuclei (AGN)-galaxy co-evolution models, AGN winds and outflows are often invoked to explain why super-massive black holes and galaxies stop growing efficiently at a certain phase of their lives. They are commonly referred to as the leading actors of feedback processes. Evidence of ultra-fast (v>0.05c) outflows in the innermost regions of AGN has been collected in the past decade by sensitive X-ray observations for sizable samples of AGN, mostly at low redshift. Here we present ultra-deep XMM-Newton and Chandra spectral data of an obscured (Nh~2x10^{23} cm^-2), intrinsically luminous (L2-10keV~4x10^{44} erg/s) quasar (named PID352) at z~1.6 (derived from the X-ray spectral analysis) in the Chandra Deep Field-South. The source is characterized by an iron emission and absorption line complex at observed energies of E~2-3 keV. While the emission line is interpreted as being due to neutral iron (consistent with the presence of cold absorption), the absorption feature is due to highly ionized iron transitions (FeXXV, FeXXVI) with an outflowing velocity of 0.14^{+0.02}_{-0.06}c, as derived from photoionization models. The mass outflow rate - ~2 Msun/yr - is similar to the source accretion rate, and the derived mechanical energy rate is ~9.5x10^{44} erg/s, corresponding to 9% of the source bolometric luminosity. PID352 represents one of the few cases where indications of X-ray outflowing gas have been observed at high redshift thus far. This wind is powerful enough to provide feedback on the host galaxy.
Reionization constraints using principal component analysis

Using a semi-analytical model developed by Choudhury & Ferrara we study the observational constraints on reionization via a principal component analysis (PCA). Assuming that reionization at z > 6 is primarily driven by stellar sources, we decompose the unknown function N ion (z), representing the number of photons in the intergalactic medium per baryon in collapsed objects, into its principal components and constrain the latter using the photoionization rate, Γ PI , obtained from Lyα forest Gunn-Peterson optical depth, the 7 yr Wilkinson Microwave Anisotropy Probe (WMAP7) electron scattering optical depth τ el and the redshift distribution of Lyman-limit systems dN LL /dz at z ~ 3.5. The main findings of our analysis are as follows. (i) It is sufficient to model N ion (z) over the redshift range 2 6 are relatively loose. (iii) The weak constraints on N ion (z) at z > 6 do not allow to disentangle different feedback models with present data. There is a clear indication that N ion (z) must increase at z > 6, thus ruling out reionization by a single stellar population with non-evolving initial mass function, and/or star-forming efficiency, and/or photon escape fraction. The data allow for non-monotonic N ion (z) which may contain sharp features around z~7. (iv) The PCA implies that reionization must be 99 per cent completed between 5.8 6 constraints will be significantly improved.
Deep Coupled GAN-Based Score-Level Fusion for Multi-Finger Contact to Contactless Fingerprint Matching

Interoperability between contact to contactless images in fingerprint matching is a key factor in the success of contactless fingerprinting devices, which have recently witnessed an increasing demand for biometric authentication. However, due to the presence of perspective distortion and the absence of elastic deformation in contactless fingerphotos, direct matching between contactless fingerprint probe images and legacy contact-based gallery images produces a low accuracy. In this paper, to improve interoperability, we propose a coupled deep learning framework that consists of two Conditional Generative Adversarial Networks. Generative modeling is employed to find a projection that maximizes the pairwise correlation between these two domains in a common latent embedding subspace. Extensive experiments on three challenging datasets demonstrate significant performance improvements over the state-of-the-art methods and two top-performing commercial off-the-shelf SDKs, i.e., Verifinger 12.0 and Innovatrics. We also achieve a high-performance gain by combining multiple fingers of the same subject using a score fusion model.
Design and Fabrication of Liquid Pressure Sensor Using FBG Sensor Through Seesaw Hinge Mechanism

Pressure sensors are used in various industrial applications assisting in preventing unintended disasters. This paper presents the design and fabrication of a novel Seesaw device incorporating a diaphragm and Fiber Bragg Grating (FBG) sensor to measure the pressure of liquids. The designed sensor has been tested in a static water column. The proposed design enables the user to easily make and modify the diaphragm based on the required pressure range without interfering with the FBG sensor. The developed pressure sensor produces improved accuracy and sensitivity to applied liquid pressure in both low and high-pressure ranges without requiring sophisticated sensor construction. A finite element analysis has been performed on the diaphragm and on the entire structure at 10 bar pressure. The deformation of the diaphragm is comparable to theoretical deformation levels. A copper diaphragm with a thickness of 0.25 mm is used in the experiments. All experiments are performed in the elastic region of the diaphragm. The sensor's sensitivity as 19.244 nm/MPa with the linearity of $99.64 \%$ is obtained based on the experiments. Also, the proposed sensor's performance is compared with recently reported pressure sensors.
Anisotropic deformation of 4H-SiC wafers: insights from nanoindentation tests

In this work, the anisotropic deformation and anisotropic mechanical properties of 4H silicon carbide (4H-SiC) single crystal wafers are proposed by using nanoindentation. The C face of a 4H-SiC wafer has higher hardness and lower fracture toughness than those of the Si face. Because the deformation of 4H-SiC is assisted by the nucleation and slip of basal plane dislocations (BPDs), especially the slip of Si-core partial dislocations (PDs) of the BPDs, the nucleation and slip of the Si-core PDs in the Si face of 4H-SiC is easier than those in the C face, which releases the nanoindentation-induced stress and results in the decrease of the hardness and increase of the fracture toughness of the Si face of 4H-SiC wafers. Due to the hexagonal lattice of 4H-SiC, the hardness along $? > <11ˉ00> of 4H-SiC is higher than that along $? > <112ˉ0> , but the fracture toughness along the $? > <11ˉ00> is lower than that along the $? > <112ˉ0> , as a result of the enhanced glide of dislocations along the most closely-packed direction. The insights gained in this work are expected to shed light on the optimization of the mechanical processing of 4H-SiC wafers.
A Complexity Theory for Public Policy

Introduction Part I: Concepts 1. Complexity Theory and Public Policy 1.1 Public Policy: Simple or Complex? 1.2 A Definition of Public Policy from a Complexity Theory Perspective 1.3 What is Complexity? 1.4 Complex, Complicated, and Simple 1.5 Complex Systems or Complex Adaptive Systems? 1.6 Chapter Summary 2. Systems and Systemness 2.1 What is a "System"? 2.2 Open and Closed Systems 2.3 Systems and Networks 2.4 System Stability and Dynamics: Structures and Procesees 2.5 Systemness and System Integration 2.6 Who Defines a Systems 2.7 Chapter Summary 3. Emergence 3.1 Emergence, Micro-Macro Relations, and Agents and Structures 3.2 A History of the Concepts of Holism and Emergence 3.3 Emergence and Complexity Theory: An Overview 3.4 Emergence and Macro Structures 3.5 Mechanisms of Emergence 3.6 Irreducibility 3.7 Downward Causation 3.8 Structuration 3.9 Chapter Summary and Implication for Policy 4. Self Organization 4.1 A Brief History of Self-Organizational Thinking 4.2 Issues in Self-Organization 4.3 What is Self? 4.4 Self-Organizations Agents 4.5 Self-Organization in Nature 4.6 Autopoiesis and Self-Referentiality 4.7 Applications of Self Organization in Management, Planning and Policy 4.8 Chapter Summary and Implications for Public Policy 5. System Dynamics 5.1 System Dynamics and Complexity Theory 5.2 Self-Organized Criticality 5.3 Self-Referentiality 5.4 Co-evolution 5.5 System Dynamics and Public Policy 5.6 The Five Propositions Revisited Part II: Epistemology and Methodology 6. Epistemology of Complexity - Uncertainty and Contextuality 6.1 Determinism, Certainty and Predictability 6.2 Uncertainty in the Knowledge of Complex Systems 6.3 Objectivity, Generalizability, and Contextuality 6.4 Chapter Summary and Implication for Public Policy 7. Espistemology - Phenomenology, Hermeneutics and Post-Structuralism 7.1 Phenomenology 7.2 Hermeneutics 7.3 Postmodernism/Post Structuralism 7.4 Complexity Theory: Pluralism, Phenomenology and Post Structuralism 7.5 Chapter Summary and Implications for Public Policy 8. Methods in Complexity Research - Overview and Macro Methods 8.1 Quantitative and Qualitative Methods 8.2 Methods for Complexity Research: A Taxonomy 8.3 Macro Methods of Investigating Structures 8.4 Methods of Detecting Structural Change 8.5 Chapter Summary 9. Methods of Complexity Research - Micro-Macro Methods 9.1 Social Network Analyses 9.2 Agent Based Simulations 9.3 Qualitative Case Studies 9.4 Chapter Summary 10. Methods of Complexity Research - Micro Methods 10.1 The Problem of Artificiality in ABS and Experiments 10.2 Methods of Cognitive Mapping 10.3 Q Methodology 10.4 Concept Mapping 10.5 Repertory Grids 10.6 Chapter Summary 11. Closing Thoughts 11.1 What Kind of Theory is Complexity Theory? 11.2 Policies as Systems 11.3 Emergence: Policies and Outcomes 11.4 Systems Dynamics 11.5 Urban Dynamics and Sprawl: An Illustration of Complexity Thinking 11.6 In Closing
Point Process Theory and Applications: Marked Point and Piecewise Deterministic Processes

* Preface Part I: Theory * Introduction * Simple and Marked Point Processes * Construction of SPPs and MPPs * Compensators and Mrtingales * Likelihood Processes * Independence * Piecewise Deterministic Markov Processes (PDMPs) Part II: Applications * Survival Analysis * Branching, Ruin, Soccer * A Model from Finance * Examples of Queueing Models Part III: Appendices * Appendix A: Differentiation of Cadlag Functions * Appendix B: Filtrations, Processes, Martingales * Bibliographical Notes * References * Notation Index * Index
Imperfect detection and wildlife density estimation using aerial surveys with infrared and visible sensors

Aerial vehicles equipped with infrared thermal sensors facilitate quick density estimates of wildlife, but detection error can arise from the thermal sensor and viewer of the infrared video. We reviewed published research to determine how commonly these sources of error have been assessed in studies using infrared video from aerial platforms to sample wildlife. The number of annual articles pertaining to aerial sampling using infrared thermography has increased drastically since 2018, but past studies inconsistently assessed sources of imperfect detection. We illustrate the importance of accounting for some of these types of error in a case study on white‐tailed deer Odocoileus virginianus in Indiana, USA, using a simple double‐observer approach. In our case study, we found evidence of false negatives associated with the viewer of infrared video. Additionally, we found that concordance between the detections of two viewers increased when using a red‐green‐blue camera paired with the infrared thermal sensor, when altitude decreased and when more stringent criteria were used to classify thermal signatures as deer. We encourage future managers and ecologists recording infrared video from aerial platforms to use double‐observer methods to account for viewer‐induced false negatives when video is manually viewed by humans. We also recommend combining infrared video with red‐green‐blue video to reduce false positives, applying stringent verification standards to detections in infrared and red‐green‐blue video and collecting data at lower altitudes over snow when needed.
Application of Topsis Method in Decision Support System Selection of Undergraduate Scholarship Recipients

The procurement of scholarship programs is one of the efforts made by the government, companies, or foundations to help individuals for the ongoing education that is being pursued, one of which is in the world of education such as STMIK Pelita Nusantara, where the campus is under the auspices of the Democrat Cemerlang Foundation, a foundation that participate in the provision of scholarship programs, both underprivileged scholarships and merit scholarships. In granting scholarships, many things must be considered so that the right decisions are made, namely the best students who meet the requirements and criteria that have been set and are not subjective. so far pthe campus is experiencing difficulties because there are many students who graduate each year while there are many conditions that must be considered, so faster, more precise and accurate steps are needed to help the campus determine students who are eligible to receive the scholarship.In this study, the TOPSIS method will be applied to select undergraduate scholarship recipients. The method was chosen because TOPSIS is a method whose basic concept is that the best alternative is the alternative that has the closest distance from the positive ideal solution and has the farthest distance from the negative ideal solution from the point of view ofgeometrically using Eucledian distance to determine the relative proximity of an alternative to the optimal solution. The results obtained in this study are that the TOPSIS method using 5 criteria can be applied in the selection of undergraduate scholarship recipients, where 2 out of 5 alternatives have the highest score of 0.657659 as well as scholarship recipients.