Miracle-dz/UniFAR-FTUs huggingface dataset:
Bayesian modelling of spatial compositional data

Compositional data are vectors of proportions, specifying fractions of a whole. Aitchison (1986) defines logistic normal distributions for compositional data by applying a logistic transformation and assuming the transformed data to be multi- normal distributed. In this paper we generalize this idea to spatially varying logistic data and thereby define logistic Gaussian fields. We consider the model in a Bayesian framework and discuss appropriate prior distributions. We consider both complete observations and observations of subcompositions or individual proportions, and discuss the resulting posterior distributions. In general, the posterior cannot be analytically handled, but the Gaussian base of the model allows us to define efficient Markov chain Monte Carlo algorithms. We use the model to analyse a data set of sediments in an Arctic lake. These data have previously been considered, but then without taking the spatial aspect into account.
Highly Sensitive and Selective Formaldehyde Gas Sensors Based on Polyvinylpyrrolidone/Nitrogen-Doped Double-Walled Carbon Nanotubes

A highly sensitive and selective formaldehyde sensor was successfully fabricated using hybrid materials of nitrogen-doped double-walled carbon nanotubes (N-DWCNTs) and polyvinylpyrrolidone (PVP). Double-walled carbon nanotubes (DWCNTs) and N-DWCNTs were produced by high-vacuum chemical vapor deposition using ethanol and benzylamine, respectively. Purified DWCNTs and N-DWCNTs were dropped separately onto the sensing substrate. PVP was then dropped onto pre-dropped DWCNT and N-DWCNTs (hereafter referred to as PVP/DWCNTs and PVP/N-DWCNTs, respectively). As-fabricated sensors were used to find 1,2-dichloroethane, dichloromethane, formaldehyde and toluene vapors in parts per million (ppm) at room temperature for detection measurement. The sensor response of N-DWCNTs, PVP/DWCNTs and PVP/N-DWCNTs sensors show a high response to formaldehyde but a low response to 1,2-dichloroethane, dichloromethane and toluene. Remarkably, PVP/N-DWCNTs sensors respond sensitively and selectively towards formaldehyde vapor, which is 15 times higher than when using DWCNTs sensors. This improvement could be attributed to the synergistic effect of the polymer swelling and nitrogen-sites in the N-DWCNTs. The limit of detection (LOD) of PVP/N-DWCNTs was 15 ppm, which is 34-fold higher than when using DWCNTs with a LOD of 506 ppm. This study demonstrated the high sensitivity and selectivity for formaldehyde-sensing applications of high-performance PVP/N-DWCNTs hybrid materials.
Some developments in the use of empirical orthogonal functions for mapping meteorological fields

Abstract Some current uses of empirical orthogonal functions (EOF) are briefly summarized, together with some relations with spectral and principal component analyses. Considered as a mean square estimation technique of unknown values within a random process or field, the optimization of error variance leads to a Fredholm integral equation. Its kernel is the autocorrelation function, which in many practical cases is only known as discrete values of interstation correlation coefficients computed from a sample of independent realizations. The numerical solution in one or two dimensions of this integral equation is approximated in a new and more general framework that requires, in practice, the a priori choice of a set of generating functions. Developments are provided for piecewise constant, facetlike linear, and thin plate type spline functions. The first part of the paper ends with a review of the mapping, archiving and stochastic simulating possibilities of the EOF method. A second part includes a case s.
Mid-Term Outcome of Ventricular Arrhythmias Catheter Ablation in Patients with Chronic Coronary Total Occlusion Compared to Ischemic and Non-Ischemic Patients

Chronic coronary total occlusions (CTO) are considered an emerging predictor of ventricular arrhythmias (VAs), but currently there are few data on arrhythmic outcomes in patients affected by CTO undergoing radiofrequency catheter ablation of VAs. This study sought to evaluate the impact of unrevascularized CTO on the recurrence of VAs after catheter ablation. This was a single-center retrospective study enrolling 120 patients between 2015 and 2020. All patients were admitted for ventricular tachycardia (VT) or high premature ventricular contractions burden (>25% detected by Holter ECG), without evidence of acute coronary syndrome; they underwent coronary angiography, electrophysiology (EP) study, and three-dimensional electroanatomic mapping (3D-EAM) followed by VAs ablation. Twenty-eight patients (23%) of 120 patients showed CTO at coronary angiography. At baseline, the CTO group presented with higher prevalence of hypertension, chronic renal disease, systolic ventricular dysfunction, secondary prevention ICD implantation, and higher rate of LAVA by 3D-EAM compared with the non-CTO group. At a median follow-up of 15 months (range 1–96 months) after catheter ablation, the only independent predictor of VAs recurrence was the presence of moderate to severe left ventricular (LV) dysfunction. Therefore, the presence of CTO does not predict VAs recurrence after catheter ablation, which is instead predicted by LV dysfunction.
Bifurcation Analysis of a Predator-Prey System Involving Group Defence

A class of ODEs of generalized Gause type modeling predator-prey interaction is considered. The prey are assumed to exhibit a phenomenon called group defence, that is, predation is decreased or even eliminated due to the ability of the prey to defend or disguise themselves as their numbers increase.Using the carrying capacity of the environment as the bifurcation parameter, it is shown that the model undergoes a sequence of bifurcations that includes a homoclinic bifurcation as well as a Hopf bifurcation. Conditions (that hold even in the case of no group defence) that ensure a subcritical Hopf bifurcation and also the spontaneous appearance of a semistable periodic orbit that splits into a pair (one stable and one unstable) of periodic orbits are given.Ecological ramifications are considered. Unlike the classical model, sufficient enrichment of the environment combined with group defence leads to extinction of the predator (deterministically) for almost all initial conditions, providing strong support fo.
Wavelength tunable optical pulse generation at various repetition rates from a semiconductor fiber ring laser

We report a simple technique to generate wavelength tunable picosecond pulses at various repetition rates. We inject the control signal of data 1100 at 40 Gbps into a semiconductor fiber ring laser, adjust a tunable filter and pulse round-trip time to implement an optical pulse source capable of continuous wavelength tuning at various repetition-rates.
Deep Reinforcement Learning With Reward Design for Quantum Control

Deep reinforcement learning (DRL) has been recognized as a powerful tool in quantum physics, where DRL's reward design is nontrivial but crucial for quantum control tasks. To address the problem of over-reliance on human empirical knowledge to design DRL's rewards, we propose a DRL with a novel reward paradigm designed by the learning process information (DRL-LPI), where the learning process information (LPI) comprises the state information and the experiences. In DRL-LPI, the state information after being classified by a fidelity threshold, and the experiences are first stored simultaneously in the respective sequences, and this process is repeated until a similar-segment ends. Then, the stored state information is converted to the real value and used to design the reward value by applying a self-amplitude function. Next, the designed reward values are integrated with the stored experiences to compose transitions for DRL's training. Through comparisons to five representative reward schemes, the proposed DRL-LPI is evaluated on two typical quantum control tasks, i.e., the spin-(1/2) quantum state control and many-coupled qubits state control, and the experimental results show the superior learning efficiency and control performance of the proposed approach. More results show that DRL-LPI exhibits the ability to learn the control strategy with few control actions compared to stochastic gradient descent (SGD) and genetic algorithm (GA).
Structurally Modified MXenes-Based Catalysts for Application in Hydrogen Evolution Reaction: A Review

Green hydrogen production via electrocatalytic water splitting paves the way for renewable, clean, and sustainable hydrogen (H2) generation. H2 gas is produced from the cathodic hydrogen evolution reaction (HER), where the reaction is catalyzed primarily from Pt-based catalysts under both acidic and alkaline environments. Lowering the loading of Pt and the search for alternative active catalysts for HER is still an ongoing challenge. Two-dimensional MXenes are effective supports to stabilize and homogenously distribute HER-active electrocatalysts to boost the HER performance. Factors involved in the effectiveness of MXenes for their role in HER include transition metal types and termination groups. Recently, tailoring the conditions during the synthesis of MXenes has made it possible to tune the morphology of MXenes from multilayers to few layers (delaminated), formation of porous MXenes, and those with unique crumpled and rolled structures. Changing the morphology of MXenes alters the surface area, exposed active sites and accessibility of electrolyte materials/ions to these active sites. This review provides insight into the effects of varying morphology of MXenes towards the electrocatalytic HER activity of the MXene itself and MXene composites/hybrids with HER-active catalysts. Synthesis methods to obtain the different MXene morphologies are also summarized.
The 3‐D BEM implementation of a numerical Green's function for fracture mechanics applications

The use of Green's functions has been considered a powerful technique in the solution of fracture mechanics problems by the boundary element method (BEM). Closed-form expressions for Green's function components, however, have only been available for few simple 2-D crack geometry applications and require complex variable theory. The present authors have recently introduced an alternative numerical procedure to compute the Green's function components that produced BEM results for 2-D general geometry multiple crack problems, including static and dynamic applications. This technique is not restricted to 2-D problems and the computational aspects of the 3-D implementation of the numerical Green's function approach are now discussed, including examples. Copyright © 2000 John Wiley & Sons, Ltd.
Does Earnings Management Practice Increase Stock Return?

This research aims to get empirical evidence the effect of earnings management in increasing stock return received by investor. Earnings management is an activity to manipulated financial statement. Earnings management can be used to improve company performance when the company has a bad performance or it can be used to maintain company performance. There are 2 earnings management, accrual and real activity manipulation. This research used both to see which one can increase stock return. This research used multiple regression analysis to test the hypothesis and the samples are manufacturing companies listed on Indonesia Stock Exchange from 2017-2019. 86 companies are selected as samples using purposive sampling. The results showed that earnings management is a negative signal for investors. When a negative signal given to investors, it will cause a decrease in stock return received by investor. This research provides an overview of earnings management practice can make investor suffer losses, so that capital market supervisors can increase the monitoring of this manipulation practices.
Inverse Method in Estimating the Base Heat Flux for Irregular Fins

An inverse problem is examined in the present study by an iterative regularization method, i.e., the conjugate gradient method, and commercial package CFD-ACE+ in estimating the unknown base heat flux of an irregular shape fin based on one sensor measurements with time. Results obtained in this inverse problem will be justified based on the numerical experiments, where three different fin base heat fluxes distributions are to be determined. Results show that the inverse solutions can always be obtained accurately with exact measurements. Moreover, the drawbacks of the previous study for this identical inverse problem, such as 1) estimations depend strongly on the number of future time steps, but the optimum number for future time steps is unknown in any real estimations and 2) at least two measure positions are needed to obtain reliable inverse solutions, can both be avoided by applying the present algorithm. Finally, it is concluded that accurate base heat fluxes of a fin can be estimated in the present .
Bayesian Variable Selection in Linear Regression

Abstract This article is concerned with the selection of subsets of predictor variables in a linear regression model for the prediction of a dependent variable. It is based on a Bayesian approach, intended to be as objective as possible. A probability distribution is first assigned to the dependent variable through the specification of a family of prior distributions for the unknown parameters in the regression model. The method is not fully Bayesian, however, because the ultimate choice of prior distribution from this family is affected by the data. It is assumed that the predictors represent distinct observables; the corresponding regression coefficients are assigned independent prior distributions. For each regression coefficient subject to deletion from the model, the prior distribution is a mixture of a point mass at 0 and a diffuse uniform distribution elsewhere, that is, a “spike and slab” distribution. The random error component is assigned a normal distribution with mean 0 and standard deviation .
Measurement of the acoustic nonlinearity parameter in liquid media using focused ultrasound

The principle and the experimental results for a finite amplitude method to measure the acoustic nonlinearity parameter B/A of liquid media using focused ultrasound are presented. The present method takes both absorption and diffraction into account. A liquidlike sample is inserted in the focal region of the acoustic field formed by a spherically focusing Gaussian source. The response of the amplitudes and phases of the fundamental and second harmonic components of the transmitted wave is observed at the post focal region to obtain the experimental value of a quantity named RF, which incorporates the nonlinearity parameter of the sample. The measurement of linear acoustic properties is also carried out using the same focusing source. The value of B/A is determined through comparison between experimental and theoretical values of RF. The experimental results for 4.5‐ml volume samples at the fundamental frequency of 1.9 MHz validate the present method. This suggests the possiblity of obtaining the B/A imagi.
Assessing Impacts of Land Subsidence in Victoria County, Texas, Using Geospatial Analysis

Land subsidence is an ongoing problem negatively affecting Victoria County along the Gulf Coast. Groundwater withdrawal and hydrocarbon extraction in the County are some of the known factors behind this geological hazard. In this study, we have used geospatial analysis and a conceptual model to evaluate land subsidence. A significant decline in the groundwater level in this area was noted from 2006 to 2016. The decline in the water level correlates with the major drought events along the Gulf Coast reported in earlier studies. These results are further corroborated by the emerging hotspot analysis performed on the groundwater data. This analysis divides the study area into intensifying, sporadic, and persistent hotspots in the northwest region and intensifying, persistent coldspots in the southeast region of Victoria County. Hydrocarbon production data show high oil and gas extraction from 2017 to 2021. There are a higher number of hydrocarbon production wells in the central and southern regions of the County than elsewhere. The conceptual models relate these events and suggest the existence of subsidence in the County, through which the water and hydrocarbon reservoirs in the study area may lose their reservoir characteristics due to sediment compaction.
Mediating Learning in the Zones of Development: Role of Teacher and Kindergartner Talk-Turns During Read-Aloud Discussions

ABSTRACT We explored how teacher and child talk-turns were related to children’s subsequent comprehension responses during read-alouds. Data included three kindergarten teachers’ interactive read-alouds (736 talk-turns across six video-recorded and transcribed sessions). Talk-turns were coded using a priori and emergent codes. Statistical discourse analysis, which analyzes how previous talk-turns in a conversation are related to later talk-turns in the conversation, was used to identify how specific teacher an d child talk-turns within a read-aloud were related to a child’s later comprehension expressions during that same read-aloud. Findings show how specific talk-turns in which teachers mediate children’s behavior by (a) promoting particular child actions related to the read-aloud content or (b) restricting or expanding ways that children can participate, predict children’s subsequent comprehension responses during the read-aloud. Further, findings show how children’s talk-turns that mediate other children’s action related to the read-aloud content predict those children’s subsequent comprehension responses. These findings suggest new and more fine-grained ways that teachers and children can support children’s listening comprehension and vocabulary responses during read-aloud discussions.
Electric-field-induced reversible magnetic single-domain evolution in a magnetoelectric thin film

We report experimental results on a Ni-nanobar/lead zirconate titanate-film magnetoelectric device demonstrating control of a metastable magnetic single domain with an electric field due to the converse magnetoelectric effect (i.e., coupling of piezoelectric effect, mechanical coupling, and magnetostriction). The reversible single-domain evolution from an initial single-domain state to a transitional S-shape domain state with an electric field was experimentally observed with magnetic force microscopy. Upon removal of the electric field, the single domain reverts to its original domain configuration. These results confirm change of a single domain in the nanoscale magnetoelectric/multiferroic device is achievable and subsequent control of local magnetic field is possible.
Properties of Bio-Silver Nanoparticles Mediated by Tuber and Leaf Extracts of Manihot esculenta

Bio-silver nanoparticle using plant extract has been the subject of many studies nowadays. Researchers use various plant extracts, especially the popular plant from their places. This study aims to synthesize AgNPs using leaf and tuber extracts of M. esculenta Crantz and to characterize their properties to be compared one to another. The characterization includes surface plasmon resonance wavelength using UV-VIS spectroscopy, the chemical bonds related to the extract on the surface of the particles using FTIR spectroscopy, shape and size of the particles using TEM, and antibacterial properties using the disc diffusion method. Each tuber and leaf extract AgNPs were formed a few minutes after mixing silver nitrate with each extract indicated by the change of the color from transparent to yellowish-brown. The color of the sample was quantified by the wavelength of surface plasmon resonance which was found to be 425 nm for tuber extract AgNPs and 430 nm for leaf extract AgNPs. The results of FTIR spectroscopy indicate the presence of the extract at the surface of nanoparticles for both samples. The particles are mostly spherical, but the diameters of the leaf extract AgNPs are relatively smaller than those of the tuber extract AgNPs. The results of antibacterial assays of both samples show that both AgNPs inhibit the growth of S. aureus as effectively as they inhibit the growth of E. coli.
The homology between the private and the public fields in higher education

Abstract External privatisation of public education has emerged in Finland in the admission to higher education. A field analysis of thematic interviews (N = 22) with powerful actors in the private educational market and middle-class young people applying for places at universities in the highly competitive disciplines of medicine and law was conducted. The research task was to examine the discourses that construct the limits of the public and private fields, and the kind of homology that emerges. Four discourses were identified: support, business, social responsibility, and personal responsibility. The private field distinguished itself from the public fields through the discourse of business and attached itself to it through the discourse of support. The dominance of the symbolic power of transformed economic capital in the private field mobilised in the public field was misrecognised during the admission process as ‘motivation’. The homology between the two fields was strong yet hidden.
A Comparative Study on Machine Learning Algorithms for Congestion Control in VANET

In Vehicular Ad-hoc Networks, vehicles periodically exchange awareness messages for enhanced safety and traffic management. Massively broadcasted messages in a dense environment causes the channel to be congested and further degrades the reliability for safety. As a result, congestion control mechanisms must ensure that the channel load is below a particular threshold. This paper predicts the local density of vehicles and the channel busy ratio using machine learning algorithms such as regression, K-NN, naive Bayes, decision trees, and random forest algorithms without considering beacons. Then, applies a prediction and adaption-based congestion control algorithm to best prediction results. The results of the simulations justify that the P&A-A can adapt the frequency and power of beacons to maintain the load of the network channel under the threshold value (40%).
Molecular Fingerprinting and Microbiological Characterisation of Selected Vitis vinifera L. Varieties

The aim of the study was to analyse selected aspects of the natural variability of selected varieties of Vitis vinifera. Grapevine is one of the most popular and desirable crops in the world due to the great tradition of wine production, but grape extracts also have a wide range of pharmaceutical effects on the human body. It is important to identify different varieties for the conservation of genetic resources, but also for commercial and cultivation purposes. The variability of conserved DNA-derived polymorphism profiles, as well as microbial characteristics, were analysed in this study. Six different varieties of Vitis vinifera L. were used in the study: Cabernet Savignon, Chardonney, Welschriesling, Weisser Riesling, Gewurztramines and Gruner Veltliner. Genetic polymorphism was analysed by CDDP markers for WRKY genes. Polymorphic amplicon profiles were generated by all primer combinations used in the study. Gruner Veltliner and Welschriesling were the most similar, with a similarity value at 0.778. Microbiological quality of grape and antimicrobial activity against Gram-positive and Gram-negative bacteria and yeasts were analysed further. The plate diluting method for microbial quality and the disc diffusion method for antimicrobial activity were evaluated. The number of total count of bacteria ranged between 3.12 in Cabernet Sauvignon to 3.62 log cfu/g in Grűner Veltliner. The best antimicrobial activity showed Gewurztramines against Salmonella enterica, Yersinia enterocolitica, Pseudomonas aeroginosa, Staphylococcus aureus, Listeria monocytogenes, Candida albicans, Candida krusei, and Candida tropicalis. The best antimicrobial activity was found against Enterococcus faecalis in variety Weisser Riesling.