bluuebunny/crossref_metadata_2025_split huggingface dataset:
Relativistic angular redshift fluctuations embedded in large scale varying gravitational potentials
Authors: Lima-Hernández Adal , Hernández-Monteagudo Carlos , Chaves-Montero Jonás 
Published: September 2022

AbstractWe compute the linear order, general relativistic corrections to angular redshift fluctuations (ARF), a new cosmological observable built upon density-weighted two-dimensional (2D) maps of galaxy redshifts. We start with an existing approach for galaxy/source counts developed in the Newtonian gauge, and generalize it to ARF, modifying for this purpose a standard Boltzmann code. Our calculations allow us identifying the velocity terms as the leading corrections on large scales, emphasizing the sensitivity of ARF to peculiar, cosmological velocity fields. Just like for standard 2D clustering, the impact of gravitational lensing on ARF is dominant on small angular scales and for wide redshift shells, while the signatures associated to gravitational potentials are extremely small and hardly detectable. The ARF also present interesting correlation properties to anisotropies of the Cosmic Microwave Background (CMB): they are highly correlated to CMB lensing potential fluctuations, while also exhibiting a significant (S/N∼ 4–5)anti-correlation with the Integrated Sachs-Wolfe effect (ISW). This negative ARF×ISW signal is quite complementary to the standard 2D clustering×ISW correlation, since the former appears mostly at higher redshift (z∼ 2) than the latter (z≲ 1), and the combination of the two observables significantly increases theχ2statistics testing the null (no ISW) hypothesis. We conclude that ARF constitute a novel, alternative, and potentially powerful tool to constrain the nature of Dark Energy component that gives rise to the ISW.
The Variable Earth’s Rotation in the 4th–7th Centuries: New ΔT Constraints from Byzantine Eclipse Records
Authors: Hayakawa Hisashi , Murata Koji , Sôma Mitsuru 
Published: September 2022

AbstractAs one of the greatest astronomical spectacles, total solar eclipses have long been a subject of scientific interest and have been recorded by numerous civilizations over the millennia. These records are an essential reference for constraining and reconstructing Earth’s variable rotation (ΔT) prior to the 17th century. However, ΔTreconstructions for the 4th–7th centuries have significant uncertainties, mainly owing to a data scarcity. Here, we analyze Byzantine historical sources with reports of total solar eclipses along the Eastern Mediterranean coasts and add probable ΔTconstraints on their basis. We examined five cases of total solar eclipses in 346, 418, 484, 601, and 693 CE, identified times and locations of the observations, and compared them with the existing ΔTspline curve to derive new ΔTconstraints. Our results probably tighten ΔTvariability in 346 CE, show a larger ΔTrange in 418 CE, and give smaller ΔTranges in 484, 601, and 693 CE. Our study tightens the existing ΔTvariations and occasionally support some ΔTconstraints that slightly depart from the ΔTspline curve in the latest reconstructions. Our results are consistent with contemporary ΔTconstraints from other studies and offer an improved understanding of Earth’s variable rotation.
Digitization, Measurement, and Analysis of a 1905 Barnard Atlas Photographic Plate
Authors: Glusman Rowen , Boegen Lauren , Cerny William , Chapman Ali , Escapa Isaiah , Kron Richard G. , Martinez Michael N. , Muratore Amanda , Scott Audrey P. 
Published: September 2022

Abstract
In the second paper in this series, we improve on our previous demonstration of the ability of a commercially available graphic arts scanner and cost-effective analysis tools to produce scientifically useful scans of astronomical photographic plates. We describe a method using freely available tools to extract magnitude measurements from the star images on sky-survey plates, such as are stored in observatory archives around the world. We detail the use of this method on one plate in particular, Plate 8 in E. E. Barnard’s A
Photographic Atlas of Selected Regions of the Milky Way, examine the effects of our scanning method on our magnitude measurements, discuss the difficulties encountered when measuring the magnitudes of stars in crowded fields, and present a case study of red supergiant stars appearing within the field. Our work results in a catalog of more than 66,000 measurements of stellar positions and magnitudes in the central 6.°8 × 6.°8 field of view.
PTB–INRIM comparison of novel digital impedance bridges with graphene impedance quantum standards
Authors: Marzano Martina , Pimsut Yaowaret , Kruskopf Mattias , Yin Yefei , Kraus Marco , D’Elia Vincenzo , Callegaro Luca , Ortolano Massimo , Bauer Stephan , Behr Ralf 
Published: September 2022

Abstract
This paper describes an onsite comparison of two different digital impedance bridges when performing measurements on a quantum Hall resistance standard with the purpose of realizing the SI unit of capacitance, the farad. In the EMPIR Joint Research Project 18SIB07 GIQS, graphene impedance quantum standards, the Physikalisch-Technische Bundesanstalt (PTB), Germany, developed a Josephson impedance bridge, and the Istituto Nazionale di Ricerca Metrologica (INRIM) and the Politecnico di Torino (POLITO), Italy, developed an electronic digital impedance bridge. The former is based on Josephson waveform generators and the latter on an electronic waveform synthesizer. The INRIM–POLITO impedance bridge was moved to PTB and the two bridges were compared by measuring both temperature-controlled standards and a graphene AC quantized Hall resistance (QHR) standard. The uncertainties for the calibration of 10 nF capacitance standards at 1233 Hz are within 1 × 10−8 for the PTB’s bridge and around 1 × 10−7 for the INRIM–POLITO’s bridge. The comparison mutually validates the two bridges within the combined uncertainty. The result confirms that digital impedance bridges allow the realization of the SI farad from the QHR with uncertainties comparable with the best calibration capabilities of the BIPM and the major National Metrology Institutes.
Study of the electrothermal and MHD instabilities in exploding cylindrical foil liner
Authors: Zhang Daoyuan , Wu Jian , Zhou Xinmiao , Wang Zhenyu , Chen Ziwei , Jiang Zhiyuan , Shi Huantong , Li Xingwen , Wang Guanqiong , Zhou Lin 
Published: September 2022

Abstract
An experimental and numerical study of the plasma instabilities in an electrical exploding cylindrical Al liner is reported. The Al liner 3 mm in diameter and 10 μm in thickness is exploded at the Qin-1 facility (450 ns, 400 kA). Various diagnostics, such as multi-frame laser shadowgraphy, an x-ray framing camera, and an x-ray backlighting system are developed. The different imaging systems are sensitive to plasma of different areal densities based on the comparison between the experiments and simulation, which reveal the dynamics of the exploding liner in more detail. The laser shadow images show the low-density plasma (∼1–2 × 10−4 g cm−2) at the edge of the liner, and both the amplitude and wavelength of the plasma instabilities increase over time, which are considered to be magnetohydrodynamic (MHD) instabilities rather than electrothermal instabilities. During the ablation of the liner, quasi-periodic azimuthally correlated striations are directly observed in extreme ultraviolet (EUV) self-emission images. Meanwhile, the vertical filaments, which are electrothermal instabilities for plasma under the condition of ∂η/∂T < 0, are also observed in EUV self-emission images. The x-ray backlighting images of the exploding liner are obtained by placing an X-pinch load on the current-return path to serve as an x-ray point source (∼1 ns, ∼10 μm). The x-ray backlighting results show the behavior of the high-density plasma (∼1.89 × 10−3 g cm−2), which includes the transition from electrothermal to MHD instabilities. Finally, we realized a 2D MHD simulation of the exploding liner under experimental conditions, which shows good agreement with the results of the experimental perturbation.
Analysis of Sleep apnea Considering Electrocardiogram Data Using Deep learning Algorithms
Authors: Rajabrundha A , Lakshmisangeetha A , Balajiganesh A 
Published: September 2022

Abstract
Sleep is a vital component of every human being. Adequate restful and restorative sleep reenergizes the body, enhances overall health and psychological well-being. Sleep hygiene, chaotic lifestyles, disorder breathing, stress, and anxiety contribute to poor sleep quality. Obstructive sleep apnea (OSA) sleep respiratory disorder causes temporary lapses of breathing results in gasping, choking, snoring sounds during sleep. The individual does not consciously wake up, but the brain has to start breathing again which disrupts the sleep quality. Polysomnography (PSG) sleep study is employed to diagnose sleep disorders by using either in-home or laboratory-based comprehensive tests. The untreated OSA leads to deterioration in health, performance consequences with severity including daytime sleepiness, motor vehicle accidents, workplace errors, cardiovascular morbidity, and mortality. The pre-processed, interpolated and segmented ECG signal is considered for the examination of OSA. This paper focuses on three types of deep learning classifiers-based prediction models for detection of apnea from the ECG signal. The accuracy value of Long Short Term Memory model (LSTM) is 85 percent and classifier’s ability to distinguish between normal and apnea events is 0.88.The Gated Recurrent Unit (GRU) classifier and Convolution Neural Network (CNN) model have an f1- score value of 0.80. The proposed LSTM model provides the optimal performance in comparison to other deep learning models used for classification with respect to area under the curve (AUC) and accuracy metrics.
Design and Development of a Caretaker Alert System Using Eye Blink Detection
Authors: Shashikala S , Vinodhini D , Jeeva J B 
Published: September 2022

Abstract
The patient who are bedridden due of weakening of muscles of hands, feet or had lost voice, finds difficult to communicate their needs. These conditions occur when there is an issue in the passage of messages between the brain and the muscles. Some of them are affected with quadriplegia cannot move their limbs and some could move only their eyes. Therefore, the aim of this study is to provide an interactive system which would assist them to communicate with caretakers. Communication was done using pre- defined messages and an alert buzzer to grab attention, for corresponding delay in eye blinks. Once the eye blinks, the eye sensor senses it and compares the duration with the defined delays. If the condition is true then corresponding defined message appears on the display, if the condition is false, then it checks for next condition and so on. The user needs to be trained to communicate through this device. The time delays set for each message can be adjusted as per user’s need. More messages can be displayed by changing the time of closure of the eye. The system is employed to control, manage and communicate with the other people through eye blink action.
MEMS Biosensor Design and Simulation for Diagnostic Purposes
Authors: Malavika J , Parameshwari R , Kalyani D , Lakshmi Prabha P 
Published: September 2022

Abstract
A Biosensor is a device detects a chemical substance that combines a biological component. Micro cantilevers are used as sensors, transducers, probes, needles, transport mechanisms, resonators, latches, switches, and relays. The main concept in bio sensing application is antigen-antibody binding. When the magnitude of the force exerted is small, the sensitivity of the micro cantilever becomes high, so that the device can sense the presence of antigen even if the magnitude of the surface stress over the cantilever is very small. With the help of COMSOL Multi-Physics, micro-cantilever is designed as MEMS biosensors that diagnose various diseases accurately and rapidly when compared to other techniques. This biosensor is capable to detect HBV and N1H1 by immobilizing particular antibodies on the surface of the cantilever. The Moment the patient samples are sensed by sensors sensing element contains antigen; biochemical interactions found on the sensing part. Biochemical interactions occur between the antigens of HBV, H1N1, and the antibodies attached to the sensing element’s surface; as a result, the diseases are detected. In the current paper dual cantilever is designed for diagnosing two diseases in single step at the same time accurately. Here the cantilever can sense even a minute deformation 1.6x10-06 mm, hence it can be applied in designing MEMS based biosensor for diagnostic purpose. The dual-beam cantilever is simulated by choosing a suitable polymer to fabricate biosensor to detect swine flu and jaundice with the help of COMSOL Multi physics.
Medication adherence manager and its clinical application.
Authors: Fathillah M S , Chellappan K 
Published: September 2022

Abstract
Adherence to prescribed medication affects global clinical practice especially on chronic disease management resulting in adverse medical and economic burden. Reliable standard and practice in measuring adherence among patient is yet to be established clinically although aspects from user behavioural, clinical needs and technology-assisted devices design have been studied. Lack of real-time monitoring and inefficient method of medication consumption validation has been identified as the challenges in monitoring patient medication consumption’s pattern. The aim of this study is to design and deploy an IoT driven medication adherence manager. The proposed IoT architecture enabled by real time monitoring through a multi-sensor alert option in medicinal compartment to ensure adherence integrity. The reliability of the proposed device further enhanced with the mobile application and cloud storage and usage analytic support application. The medication adherence manager expected to digitize the medication consumption process thus improving the patient health and well-being at the same time reduce pharmaceutical wastage due to nonadherence.
Adaptable medical device with 3D printing facilities
Authors: Shivaraja T R , Kamal N , Zaidi W A W , Chellappan K 
Published: September 2022

Abstract
3D printing technology has breakthrough many long pending medical challenges. In this study the researchers are addressing epilepsy, a disability that limits mobility freedom, that can appear at any age but usually start in childhood or people over 60 years old. Diagnosing epilepsy quickly can be challenging due to the fact other conditions such as migraines, panic attacks and fainting possess similar symptoms. Regularly, it cannot be confirmed until seizure is detected. Electroencephalogram (EEG) is the most common test used to diagnose epilepsy. Epileptiform brain activity presence is used as a change seen on an EEG recording among epilepsy patients. The availability of EEG device for epilepsy diagnosis is currently limited to clinical settings which restricts the treatment process. The objective of this study is to offer an option for personalized home-based EEG device for epilepsy diagnosis and monitoring. A customized 3D printed EEG headset with 8 channel dry electrodes device is assembled and configured. The customization is managed by offering three different printable headset sizes with material selection options. The device is supported with an OpenBCI application connected through Bluetooth for recording and further processing options. The proposed device has potential to address number of limitations including the recent pandemic’s challenge where hospitalization option is restricted. The outcome of the research is expected to bring a new breakthrough in brain activity related research and clinical diagnosis in patient monitoring. The customization option of this device is also expected to offer a new trend in managing treatment compliance and adherence in clinical practice.
Designing a Mask for Obstructive Breathing Disorder
Authors: Swedha V , Divakaran Sindu , Premkumar J , Sudhakar T 
Published: September 2022

Abstract
Constant Positive Airway Pressure (CPAP) is a method of painless mechanical ventilation to keep the aviation routes open in subjects unfit to do as such independently. It is utilized to treat different scopes of ongoing ailments emerging from obstructive aviation routes infections. Along these lines, this work means to address the plan and development of a veil and test CPAP gadget as verification of idea to be utilized by subjects experiencing different obstructive breathing illnesses. To plan a veil and the test CPAP gadget with tangible instrumentation for giving information to a miniature controlled framework, electro-pneumatic circuits and sign molding sheets of sensors have been fitted to accomplish streamlined CPAP work with low energy utilization. Every one of the boundaries are checked by the microcontroller once the microcontroller identifies any hardships in breathing circumstances it will turn on the steady framework for the subject. In this proposed work breathing pattern, rest design, temperature mugginess controls observing will be put away in mists. By utilizing the proposed work, steady framework subjects can be ready to inhale steadily.
Detection of Liver Dysfunction using Microfluidics Analysis
Authors: Lakshmi Prabha P , Kalyani D , Parameshwari R , Malavika J 
Published: September 2022

Abstract
The body fluids are an important clinical diagnostic marker, considered by the physicians for diagnosis, monitoring and treating various diseases. Bilirubin, orange-yellow coloured pigment, an end-product of heme metabolism is a biomarker for liver dysfunction primarily jaundice. Similarly, blood pressure is one amongst the main parameters raised in most of the abnormalities including liver dysfunction. Hence, screening of blood pressure and concentration of bilirubin in the blood stream helps to detect the pathological conditions. In COMSOL Multiphysics, fluid flow simulation task is taken into account to analyze the flow of blood, blood pressure, bilirubin and also their range of concentration. In the present work, liver dysfunction can be detected in early stage with the help of physiological behavior of hepatic artery by measuring the flow rate, blood pressure and bilirubin levels in the arteries with the aid of COMSOL Multiphysics simulation software. Also, the impact of obstruction due to the presence of blocks of various sizes in the arteries on the flow rate, bilirubin as well as blood pressure is explored.
Analysis of MRI as a screening tool for the diagnosis of schizophrenia
Authors: Thilakavathi B , Sudha S , Vidya K , Subathra Y 
Published: September 2022

Abstract
Schizophrenia (SCZ) is a clinical disorder that affects 0.01% of the world population. It affects people in late teen hood or early maturity resulting in lifelong social and mental disturbance. At present, there is no cure, but this can be diagnosed and treated. Classification of SCZ imposes great challenges even for the most experienced neurologists. A non-intrusive technique like MRI is taken for diagnosing various diseases which are used as a base for our tool. Many researchers used large datasets of SCZ and normal for analyzing SCZ using various parameters like Grey matter, white matter, voxel-based morphometry, etc., This work proposes a simpler but effective approach to classify the same. This paper determined statistical and complexity features from 32 SCZ and 18 normal MRI images. Totally 9 features are determined out of these, novel features Hausdorff dimension and Euclidean distance played an important role in classification. Hausdorff dimension is selected as the most significant feature by student’s t-test with p<0.001. The back propagation neural network receives substantial information from the t-test as input. Our promising approach, with a minimal dataset, classified the subjects with 100% sensitivity, 88.9% specificity, and 94.4% accuracy.
Automatic classification of histology images into normal/cancer class with pre-trained CNN
Authors: Achuthan Geetha , Kadry Seifedine , Suresh Manic K. , Meqdad Maytham N. 
Published: September 2022

Abstract
Deep-Learning-Scheme (DLS) based medical data assessment has been widely employed in recent years due to its improved accuracy. Our goal is to study the performance of the pre-trained DLS on RGB-scale breast-histology images. The implemented idea holds these phases; (i) Data collection, pre-processing and resizing, (ii) Training the DLS with chosen test-pictures, (iii) Testing and validating the performance of the DLS with 5-fold cross-validation. This investigation considered the breast-histology pictures for the study and binary classification is employed to achieve Normal/Cancer class grouping of images. The proposed work compared the classification performance of AlexNet, VGG16 and VGG19.The experimental outcome of this study authenticates that the AlexNet with the Random-Forest (RF) classifier helps to get a higher classification accuracy (>87%) compared to VGG16 and VGG19.
Detection of Pneumonia in Chest X-Ray with Bat-Algorithm Selected Deep and Handcrafted Features
Authors: Suresh Manic K. , Kadry Seifedine , Biju Roshima , Balaji Gangadharam 
Published: September 2022

Abstract
Pneumonia is one infectious disease caused by viruses/bacteria, and early screening is necessary for the detection and treatment. Furthermore, pneumonia causes severe problems in children and elderly. The proposed work aims to develop a disease screening scheme for efficiently classifying the chest radiograph (X-ray) pictures into the Normal/Pneumonia group. The proposed process has the below phases; (i) Image collecting and resizing, (ii) Deep-feature extraction, (iii) Handcrafted feature extraction, (iv) Bat-Algorithm based feature selection and (v) Classification. In this work, the VGG16 scheme is considered to extract the deep-features and the necessary handcrafted features are mined using the Weighted Local Binary Pattern (WLBP). The necessary feature is then selected using the bat-algorithm supported feature selection. The experimental result of this study proves the accuracy of KNN is healthier (>98%) than other methods.
Extraction and assessment of COVID19 infection in lung CT images using VGG-UNet
Authors: Tanavade Satish Suresh , Kadry Seifedine , Suresh Manic K. , Balaji Gangadharam 
Published: September 2022

Abstract
The infectious disease in humans is gradually rising for various reasons, and COVID19 is one of the recently discovered diseases caused by SARS-CoV-2. From early 2020, the infection due to COVID19 has gradually increased, and still, its infection exists. COVID19 will cause severe infection in the respiratory tract, and early detection and treatment are essential. The harshness of the infection needs to be examined before implementing the treatment. This research aims to build up and implement a suitable procedure to extract and assess the infected section in lung CT slices. This work extracts the infected section using the pre-trained VGG-UNet scheme. The separated section is validated against the ground-truth (GT) image, and the necessary presentation standards are calculated. The performance of the VGG-UNet is then compared and verified with the UNet and UNet+ schemes. The investigational product of this study authenticate that the effect reached with the proposed study confirms that the VGG-UNet provides better Jaccard, Dice and accuracy compared to UNet and UNet+.