Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of electrolytes on the thermal stability of α–chymotrypsinogen A at acid pH

ABSTRACT This study investigates the effect of electrolytes on the thermodynamic stability of the protein α-chymotrypsinogen A at acid pH. Protein thermal stability in water, buffers and aqueous solutions of (NH4)2SO4, NH4NO3, NaCl, KCl at pH 2.00, 3.00 and 3.50 was followed by ultraviolet-visible spectroscopy (UV-VIS) and differential scanning calorimetry (DSC). Thermodynamic parameters of denaturation of the protein in water and in the aqueous mixed solvents were obtained from thermal denaturation curves. The results suggest that the unfolding process is reversible process and is well represented by a two state model. All the electrolytes used in this study increase the conformational stability of the protein. The stabilising effect of the electrolytes used in this study increases with electrolyte concentration and is in accordance with the effect of anions and cations described for positively charged proteins, being ammonium sulphate the salt that exerts the largest stabilising effect on α-chymotrypsinogen A.
Local People’s Perception of Ecotourism: the Case of Salda Lake

The present research was carried out in the sample of Salda Lake in Turkey in order to determine the perception of local residents about cultural, economic and environmental effects of ecotourism and to identify the effect of these variables on their support for tourism development in the region. In the research, it was concluded that cultural, economic and environmental effects of ecotourism act as an antecedent of the support by local people residing around Salda Lake on tourism development in the region. In addition, the local people’s length of residence in the region creates a moderating effect in the relationship between cultural, economic and environmental effects of tourism and the residents’ support for tourism development. The research findings provide suggestions to tourism planners, destination management organizations (DMO) and academicians studying in the context of tourism literature.
Green Synthesis of Copper Nanoparticles Using Tea Leaves Extract to Remove Ciprofloxacin (CIP) from Aqueous Media

In the present investigation, the synthesis of copper nanoparticles from green tea was attempted and investigated for its capacity to adsorb drugs (Ciprofloxacin). The copper nanoparticles (Cu-NPs) were characterized by different techniques of analysis such as scanning electron microscopy (SEM) images, atomic force microscope (AFM), blumenauer-emmer-teller (BET), fourier transform infrared (FTIR) spectroscopy, and zeta potentials techniques. Cu-NPs lie in the mesoporous material category with a diameter in the range of 2-50 nm. The aqueous solution was investigated for the removal of ciprofloxacin (CIP) with green tea-synthesized Cu-NPs. The results showed that ciprofloxacin efficiency depends on initial pH (2.5-10), CIP (2mg/L-15mg / L) dose, temperature (20 ° C-50 ° C); time (0-180 min) and Cu-NP dose (0.1g /L-1g /L). Spherical nanoparticles with an average size of 47nm and a surface area of 1.6562m2/g were synthesized. The batch experiment showed that 92% of CIP 0.01 mg/L were removed at a maximum adsorbent dose of 0.75 g/L, pH 4, 180 min, and an initial 1:1 rate (w / w) of CIP: Cu-NPs. Kinetic adsorption models and ciprofloxacin removal mechanisms were examined. The kinetic analysis showed that adsorption is a physical adsorption system with activation energy of 0.8409 kJ.mol-1. A pseudo-first-order model is preferred for the kinetic removal after the physically diffusing process due to the low activation energy of 13.221kJ.mol-1. On the other hand, Langmuir, Freundlich, Temkin, and Dubinin isotherm models were also studied; the equilibrium data were best fitted with Langmuir and Dubinin isotherm models with maximum adsorption capacity of 5.5279, and 1.1069 mg/g, respectively. The thermodynamic values of ∆G0 were -0.0166, -0.0691, -4.1084, and -0.7014 kJ/mol at 20, 30, 40, and 50 ° C, respectively. The values of ΔH0 and ΔS0 were 18.8603 kJ/mol and 0.0652kJ/mol.k, respectively. These values showed spontaneous and endothermic sorption. The presence of the CIP concentration in aqueous media was identified by UV-analysis.
Methods For Addressing Public Health Concerns At Municipal Solid Waste Landfills

Municipal solid waste (MSW) landfills are the dominant waste disposal method in the U.S., receiving roughly 56 percent of the MSW generated in the country. Although regulatory programs have been implemented to minimize potential community health risks from MSW landfills, these facilities are often the subject of public health-related complaints. This paper describes available methods for addressing public health concerns at MSW landfills, including epidemiological studies, risk assessments, environmental monitoring, biomonitoring, and public health assessments. Advantages and disadvantages of the methods are discussed, including scientific reliability, and their ability to address landfill-specific health concerns. Case studies and literature results of epidemiological analyses, risk assessments and public health assessments conducted at MSW landfills are also presented.
GENERAL PROJECT'S SETUP FOR FINITE ELEMENT SIMULATION OF BONY ORGANS DEMOSTRATED FOR THE CASE OF A HUMAN MANDIBLE

Due to high complexity of biological tissue, the re quirements of biomechanical finite element simulati on differ from those inherent to projects in conventio nal computational mechanics. Especially, pre- and p ost-processing are of increased impact. For the sake of a valuable application of the simulation results in t he clinical setting, a highly multidisciplinary method of operatio n is recommended. The purpose of this paper is a sh ort description of a general project’s structure of a bio mechanical finite element project. The focus is on examination of bone as an organ where the case of a partially e dentulous human mandible was taken as simulation example.
An on-line self-learning power system stabilizer using a neural network method

Based on the extensive theoretical analysis of a self-learning algorithm, a novel on-line neural network self-learning algorithm is proposed. This algorithm aims to learn the inverse dynamics of a controlled system. Samples can be easily obtained by the measurements. A reference model or a given orbit is used to generate ideal system responses. A scheme for on-line real-time implementation of such a controller is given. The proposed algorithm has been used to design a self-learning power system stabilizer. Simulation results show that the proposed self-learning neural network based PSS is very effective in damping out the lower frequency oscillations.
Closed-Loop Cognitive-Driven Gain Control of Competing Sounds Using Auditory Attention Decoding

Recent advances have shown that it is possible to identify the target speaker which a listener is attending to using single-trial EEG-based auditory attention decoding (AAD). Most AAD methods have been investigated for an open-loop scenario, where AAD is performed in an offline fashion without presenting online feedback to the listener. In this work, we aim at developing a closed-loop AAD system that allows to enhance a target speaker, suppress an interfering speaker and switch attention between both speakers. To this end, we propose a cognitive-driven adaptive gain controller (AGC) based on real-time AAD. Using the EEG responses of the listener and the speech signals of both speakers, the real-time AAD generates probabilistic attention measures, based on which the attended and the unattended speaker are identified. The AGC then amplifies the identified attended speaker and attenuates the identified unattended speaker, which are presented to the listener via loudspeakers. We investigate the performance of the proposed system in terms of the decoding performance and the signal-to-interference ratio (SIR) improvement. The experimental results show that, although there is a significant delay to detect attention switches, the proposed system is able to improve the SIR between the attended and the unattended speaker. In addition, no significant difference in decoding performance is observed between closed-loop AAD and open-loop AAD. The subjective evaluation results show that the proposed closed-loop cognitive-driven system demands a similar level of cognitive effort to follow the attended speaker, to ignore the unattended speaker and to switch attention between both speakers compared to using open-loop AAD. Closed-loop AAD in an online fashion is feasible and enables the listener to interact with the AGC.
Performance analysis of broadband adaptive digital beamforming

The bandwidth performance of a broadband adaptive array is investigated. It is shown that, in a linear array with K antennas each followed by a tapped delay-line with L taps using the multifrequency point constraints in the method of minimum variance distortionless response (MVDR), one may get the plateau of wideband (relative bandwidth /spl ges/ 20%) frequency response in signal direction and adaptive nulling of the wideband interference. The authors present a bandwidth controllable signal and interference model for simulation and discuss the frequency point choice of for distortionless response. Curves of array gain and interference attenuation versus interference-to-noise ratio are given, which show the adaptive rejection of interference. It is proved that any full rank transform between tap samples and weights cannot improve the bandwidth performance in MVDR. <<ETX>>
Octree Representation Improves Data Fidelity of Cardiac CT Images and Convolutional Neural Network Semantic Segmentation of Left Atrial and Ventricular Chambers.

Purpose To assess whether octree representation and octree-based convolutional neural networks (CNNs) improve segmentation accuracy of three-dimensional images. Materials and Methods Cardiac CT angiographic examinations from 100 patients (mean age, 67 years ± 17 [standard deviation]; 60 men) performed between June 2012 and June 2018 with semantic segmentations of the left ventricular (LV) and left atrial (LA) blood pools at the end-diastolic and end-systolic cardiac phases were retrospectively evaluated. Image quality (root mean square error [RMSE]) and segmentation fidelity (global Dice and border Dice coefficients) metrics of the octree representation were compared with spatial downsampling for a range of memory footprints. Fivefold cross-validation was used to train an octree-based CNN and CNNs with spatial downsampling at four levels of image compression or spatial downsampling. The semantic segmentation performance of octree-based CNN (OctNet) was compared with the performance of U-Nets with spatial downsampling. Results Octrees provided high image and segmentation fidelity (median RMSE, 1.34 HU; LV Dice coefficient, 0.970; LV border Dice coefficient, 0.843) with a reduced memory footprint (87.5% reduction). Spatial downsampling to the same memory footprint had lower data fidelity (median RMSE, 12.96 HU; LV Dice coefficient, 0.852; LV border Dice coefficient, 0.310). OctNet segmentation improved the border segmentation Dice coefficient (LV, 0.612; LA, 0.636) compared with the highest performance among U-Nets with spatial downsampling (Dice coefficients: LV, 0.579; LA, 0.592). Conclusion Octree-based representations can reduce the memory footprint and improve segmentation border accuracy.Keywords CT, Cardiac, Segmentation, Supervised Learning, Convolutional Neural Network (CNN), Deep Learning Algorithms, Machine Learning Algorithms© RSNA, 2021.
25 to 300 degrees C ultra-low-power voltage reference compatible with standard SOICMOS process

A new patented voltage reference is presented. The very simple architecture, which can be implemented in standard silicon-on-insulator CMOS processes, gives very low power consumption (from 1 pA at 25degreesC up to 50 nA at 300degreesC) and good voltage stability (about 200 ppm/degreesC) over the whole temperature range.
Dual-polarised patch antenna with low cross-polarisation and high isolation for WiMAX applications

A coax-feed dual-polarised patch antenna with low cross-polarisation and high port isolation is presented. The proposed antenna contains two pairs of narrow slots along the diagonals and two pairs of T-shaped slots along the centrelines, which change the path of the current and keep the cross-polarisation under -38-dB. By introducing two short pins, the isolation between the two ports remains more than 40-dB in the whole bandwidth. Moreover, the proposed antenna achieving a 10-dB return loss bandwidth of 2.15-2.72-GHz has a compact structure, thus making it easy to be extended to form an array, which can be used as the base station antenna for WiMAX applications.
LA CRISIS EN LAS POLÍTICAS DE EMPLEO. LA MODÉLICA DINAMARCA Y LA SITUACIÓN EN ESPAÑA

A través de las siguientes páginas nos adentraremos en la diferencia abismal de dos sistemas de protección del empleo, España y Dinamarca, producto de una concepción y evolución distinta del Estado del bienestar surgido tras la Gran Depresión de los años 30 y la II Guerra Mundial. Las políticas de empleo danesas gozan de una gran estabilidad y eficacia desde la década de 1990. España, por el contrario, tiene una amalgama de políticas desordenada y caótica que pone su acento en los incentivos a la contratación. Mirarse en el espejo danés, de vez en cuando, es una buena idea.
Delamination detection in composite laminates using dispersion change based on mode conversion of Lamb waves

A new ultrasonic propagation system has been constructed using macrofiber composite (MFC) actuators and fiber Bragg grating (FBG) sensors. The MFCs and FBGs can be integrated into composite laminates because of their small size and high fracture strain. The developed system can send and receive broadband Lamb waves. In this research, this system was used to detect delamination damage in composite laminates. First, the multiple modes of Lamb waves in a carbon-fiber-reinforced plastic (CFRP) quasi-isotropic laminate were identified by transmitting and receiving the symmetric and antisymmetric modes separately. Then, the mode conversions at both tips of a delamination were investigated through an experiment and a two-dimensional finite element analysis (FEA). A new delamination detection method was proposed on the basis of the mode conversions, and experiments were carried out on laminates with an artificial delamination. When antisymmetric modes were excited, the frequency dispersion of the received A1 mode changed, depending on the delamination length owing to the mode conversion between the A1 mode and the S0 mode. This phenomenon was confirmed through the FEA and these results prove that this new method is effective in detecting a delamination in CFRP laminates.
Dynamic Maximum Speed Limits

Application of dynamic maximum speed limits may lead to positive effects for the environment, safety, and traffic flows. However, the efficacy of this dynamic traffic management measure depends largely on the behavior of drivers (i.e., compliance). In this paper, it is conjectured that compliance does not depend solely on attitudes of drivers but also depends on drivers’ perceptions of the dynamic maximum speed limit signs and mental workload. It is assumed that characteristics of the dynamic maximum speed limit signs influence the perceptions of drivers as well as their mental workload. It is, however, not yet clear to what extent characteristics of the signs influence perception, mental workload, and compliance of drivers. Therefore, two driving simulator experiments were performed to investigate the influence of four factors on drivers’ perception, mental workload, and compliance. The factors studied were the signs’ content, implementation, location, and frequency. From the results, it followed that different effects of these factors could be observed. For example, it was observed that the frequency with which dynamic maximum speed limit signs were provided to the drivers had a significant influence on perception and compliance, although a significant effect on mental workload could not be established. The paper concludes with a discussion of results and recommendations for future research.
Common Source & Provenance at Virtual Product House

In this paper we address the IT related issues which arise in the multi-fidelity, multi-disciplinary workflow of the Virtual Product House (VPH) start project. Different stakeholders are involved providing functionality as a service to simulate the end2end process from virtual design to virtual certification, including virtual manufacturing and virtual testing. Here, we present our two-fold approach for a collaborative design, implementation and operation of a common workflow among multiple stakeholders: A common simulation environment and the data tracing. A third aspect was added to support long-term reconstruction of data. We believe, that the approach presented in this paper can be used as blueprint for similar workflow settings.
A learning agenda for the advocacy evaluation field's future

This volume set out to document, illustrate, and critique the progress and innovation that has occurred during the advocacy evaluation field's first phase of development. This final chapter identifies how the context in which advocacy evaluation plays out is shifting. It describes how these shifts impact how advocates, advocacy funders, and advocacy evaluators think about what works, and what has value. Given this context, and lifting up the ideas of other chapter authors, the chapter concludes with a learning agenda for the field's next phase of development—four questions to help guide future field innovation and collective learning.
Comparing calibrated statistical and machine learning methods for wildland fire occurrence prediction: a case study of human-caused fires in Lac La Biche, Alberta, Canada

Wildland fire occurrence prediction (FOP) modelling supports fire management decisions, such as suppression resource pre-positioning and the routeing of detection patrols. Common empirical modelling methods for FOP include both model-based (statistical modelling) and algorithmic-based (machine learning) approaches. However, it was recently shown that many machine learning models in FOP literature are not suitable for fire management operations because of overprediction if not properly calibrated to output true probabilities. We present methods for properly calibrating statistical and machine learning models for fine-scale, spatially explicit daily FOP followed by a case-study comparison of human-caused FOP modelling in the Lac La Biche region of Alberta, Canada, using data from 1996 to 2016. Calibrated bagged classification trees, random forests, neural networks, logistic regression models and logistic generalised additive models (GAMs) are compared in order to assess the pros and cons of these approaches when properly calibrated. Results suggest that logistic GAMs can have similar performance to machine learning models for FOP. Hence, we advocate that the pros and cons of different modelling approaches should be discussed with fire management practitioners when determining which models to use operationally because statistical methods are commonly viewed as more interpretable than machine learning methods.
Performance Improvement of Visual-MIMO System Using Image Brightness Information

First Author:Kookmin University, Department of Electronics Engineering, jhbaek@kookmin.ac. kr, 학생회원° Corresponding Author:Kookmin University, School of Electronics Engineering, kdk@kookmin.ac. kr, 종신회원* Incheon National University, Department of Electronics Engineering, kbyun@incheon.ac. kr, 정회원**Kookmin University, School of Electronics Engineering, ypark@kookmin.ac. kr, 종신회원논문번호：KICS2014-11-457, Received November 10, 2014; Revised December 18, 2014; Accepted December 18, 2014
Smart water in urban distribution networks: limited financial capacity and Big Data analytics

Big Data opportunities arise from high rate data streams acquired through smart sensors and smart meters, which, even for small water utilities, may produce a huge amount of data to be stored. This data enables the application of new data analytics to infer reliable predictive functionalities, with implications ranging from reducing No Revenue Water (NRW) to optimizing the water-energy nexus, meeting ever more pressing budgetary constraints. This paper presents the approach proposed in the EU-FP7-ICT project ICeWater, combining time series clustering, for the identification of typical daily urban water demand patterns, and Support Vector Regression for performing a short term forecast. Promising results obtained on the Water Distribution Network (WDN) in Milan are presented. The approach has been designed to also be applied on smart metering data related to individual customers, addressing Big Data analytics issues.
Adaptive Dynamic Control of Nonlinear Systems With Actuator Amplitude and Rate Saturation Constraints

A direct adaptive nonlinear tracking control framework for multivariable nonlinear uncertain systems with actuator amplitude and rate saturation constraints is developed. To guarantee asymptotic stability of the closed-loop tracking error dynamics in the face of amplitude and rate saturation constraints, the control signal to a given reference (governor or supervisor) system is modified to effectively robustify the error dynamics to the saturation constraints. An illustrative numerical example is provided to demonstrate the efficacy of the proposed approach.Copyright © 2007 by ASME
Waist circumference and mortality or cardiovascular events in a general Korean population

Background Obesity is associated with cardiovascular diseases and is a risk factor for all-cause mortality. Until now, the associations between abdominal obesity and mortality or cardiovascular disease (CVD) incidence have not been conclusive. We aimed to evaluate the associations between waist circumference (WC) and mortality or CVD incidence in a general Korean population. Methods We analyzed a total of 204,068 adults older than 40 years of age who had undergone a national health examination at least once from 2009 to 2018 in the Korean National Health Insurance Service Cohort. WC was divided into five categories (< 80, 80–84.9, 85–89.9, 90–94.9, ≥ 95 cm). Hazard ratios for death and CVD incidence were calculated using Cox proportional hazards models. Results In men, WC and overall mortality showed a reverse J-shaped association. In women, the association between WC and overall mortality was not significant. For both men and women, WC was not associated with the risk of cardiovascular mortality. Contrary to the mortality trend, CVD incidence was positively associated with WC in both men and women, and the risk of the CVD incidence was the lowest in subjects with a WC < 80 cm. Conclusions WC exhibited a significant J-shaped association with overall mortality in men, where subjects who had central obesity showed a lower rate of mortality than those in the lowest or highest WC group. The risk of incident CVD showed a positive association with central obesity, where the lowest risk was observed for subjects in the lowest WC group in a general Korean population.
Lens loading approach for improving ultra-wideband performance of spiral antennas

A hemispherical dielectric lens is utilised to reduce the amplitude distortion in ultra-wideband spiral antenna communication links. It is shown that a small lens action achieves a nearly constant-aperture frequency response needed to flatten the system's transfer function when the receiving antenna has a nearly constant gain. A system fidelity factor improvement of over 26% is achieved. In addition, the lens is used to reduce the negative impact of electrical effects of shallow-cavity backing on gain and efficiency while preserving high-quality radiation patterns. Detailed computational and experimental analysis demonstrate a lens-loaded spiral antenna with voltage standing wave ratio (VSWR) <1.6, axial ratio <2 dB over multi-octave bandwidth, significant gain and efficiency improvements and fidelity factor of over 90%.