bluuebunny/crossref_metadata_2025_split huggingface dataset:
Specialized covid-19 detection techniques with machine learning
Authors: Chatterjee Parag , Biswas Mainak , Das Arnab Kumar 
Published: March 2021

Abstract
COVID-19 has been declared as a pandemic in over 200 countries of the world.COVID-19 is an infectious disease that is primarily caused by severe acute respiratory syndrome coronavirus 2((SARS-CoV-2). According to the latest figures by the world health organization, the number of confirmed cases for the COVID-19 pandemic worldwide is more than 20 million worldwide and the number of fatalities reported is over 700,000. It has been found from several studies that medical imaging coupled with machine learning methods holds great promise in the detection and follow-up of the COVID-19 disease due to the enhanced accuracy in results of the experiments performed by the researchers. Machine Learning (ML)-based solutions can be used to simultaneously analyze multiple input computed tomography (CT) images of chest and lungs. A large number of papers have been published that show the application of machine learning methods in successful detection of the COVID-19 disease. Such applications demonstrate the suitability of feature prediction, identification of involved risks and therefore managing and intercepting the outbreak of such diseases. This paper describes some of the techniques in machine learning that can be used detection of COVID-19 disease.
EFFECTIVE HEALTH SCREENING TO PREVENT INFECTION AND CONTROL THE SPREADING OF COVID-19
Authors: Bag S , Sikdar S , Ganguly K , Banerjee S , Lahiri P 
Published: March 2021

Abstract
Health screening or examinations are of paramount importance from medical perspective as prevention is better than cure. In current pandemic situation, effective health screening is essential to detect COVID-19 in its early stage even when there have been no symptoms or signs of such disease. To prevent the transmission of such contagious infection, source control measures should be implemented for everyone in the facility, regardless of symptoms. Recent literatures stated that infected people having no symptoms also likely to perform a crucial role in the spread of corona virus in the society. To restrict the transmitting of such disease in community, it is imperative to identify the CORONA positive patient at each and every entry point of the market places, railway stations, airport premises, hospital buildings etc. and isolate them in an efficient manner. Rapid qualitative detection of such disease is made through body temperature measurement with IR thermal gun and RT-PCR test. Detection of COVID- 19 positive patient early means getting immediate treatment, restrict & control the transmission of such disease within the facility and limit the exposures for other patients and healthcare personnel.
Biomechanical Comparison of A Novel Dynamic Cervical Implant With Conventional Implant: A Finite Element Study
Authors: Samanta S , Paul T , Mondal D , Biswas Dr. J K 
Published: March 2021

Abstract
Ball-socket pair is generally used for designing implants for total disk replacement (TDR) surgery on cervical spine. Although, there is exists an issue of wear which reduces implant’s life as well as success rate. To overcome this issue, without compromising stability, a new design of dynamic cervical implant (DCI) is introduced. In this present study, biomechanical performances of a conventional Prodisc-C and the proposed DCI were compared using finite element (FE) analysis. CT scan data was used to develop three-dimensional model of cervical spine (C4–C7), and the implants were inserted at C5-C6 segment. The FE model with Prodisc-C showed an increase in range of motion (ROM) at the implanted segment and decrease in adjacent segment, while the proposed DCI design showed convenient results in term of ROM compared to intact spine model, and lower risk of stress shielding at the adjacent bone.
Atomic chain of carbon atoms: Smallest negative differential resistance device
Authors: Bhowmick Rinki , Chattopadhyaya Mausumi , Chakraborty Jit , Maity Swarnendu , Basu Arnab , Koley Sayantanu , Roy Anusweta , Sen Sabyasachi 
Published: March 2021

Abstract
In the present work, we report giant negative differential resistance action in probably the simplest molecular nanoelectronic device comprising of carbon chain placed between two ferromagnetic electrodes named as graphitic carbon nitride (g-C4N3). The negative differential resistance action is spin polarized and only evident at spin down channel. Spin polarized quantum transport studies using Keldysh non-equilibrium Green's function based density functional theory reports very high negative differential resistance over the bias range of ±0.1 V to ±0.3 V. This symmetric negative differential resistancec feature has been explained by an analysis of transmission spectrum across the Fermi energy level and Molecular Projected Self-Consistent Hamiltonian states (MPSH) of the system. Role of in-phase and out of phase electron waves in ensuring negative differential resistance feature has been justified through transmission pathways of the system. The simplicity of the molecular system added with robust spin polarized negative differential action added with experimental relevance certainly establishes the uniqueness of the device in respect of modern spintronic research.
Design and Development of IoT based Smart Security System in Covid19 Situation
Authors: Das Sudip , Dhar Abhishek , Pal Biswamoy , Biswas Papun , Gayen Pritam Kumar , Majumder Subhojyoti 
Published: March 2021

Abstract
In COVID19 pandemic situation social distancing and proper thermal screening is very much essential for restrict the spreading of virus. In security purpose human beings directly contacts with several known and unknown persons that is tremendously thoughtful matter. That problem will be overcome by a prototype device which can detect the temperature of the body and the collected data will be uploaded to the server as well as to the predefined consumer mobile number thorough IoT system. This system very much fruitful for office, factory, school even multi stored building security system. Instantly all related data regarding body temperature, image capturing, coming from area, area details scenario during any pandemic situation will be detect to the consumer mobile or computer. Using this it can keep a record to the number of visitors along with their temperature of the body. And in this current situation using this we can avoid human touch and the chances of getting affected will be less and a huge number of people can save their life. Solar powered IoT based smart security system will be automatically notified to the consumer when visitor come to meet in their premises. It will also give an alert if the visitor coming from containment zone or highly affected area.
Design and Development of Fire Fighting System Using Hot Redundant PLC in COVID Situation
Authors: Das Sudip , Dhar Abhishek , Das Abakash , Gayen Pritam Kumar , Pal Biswamoy , Biswas Papun 
Published: March 2021

Abstract
A firefighting system is the most foremost part of any industry and buildings as its aim to protect property, human and industrial equipment. In any pandemic situation like COVID19 it is utmost requirement to increase reliability of all important instruments which are directly involve to human life. In case of fire fighter fight against fire, this required time and skilled man power. Under these pandemic situation chances of infection spreading in firefighters and social distancing will not maintain during this situation. Only one way to resolve this problem is by implementation of fully automated reliable system. In this system we are trying to automate the total system by using hot redundant PLC which is fail safe. It consists of mainly three basic parts - fire storage tank, fire pumps and automated distribution system. Fire storage tank contains the water that used against fire. Fire pumps helps to fill the tank and automated distribution system will be activated during fire and instantly distribute water. There are three pumps one is main electrical pump, second one is diesel backup pump and last one is jockey pump.In redundant configuration there are two PLC acting simultaneously and the entire network component and power supply also has back up so that it will never fail. If one of the PLC fails during operation then second PLC automatically take care of the system within few millisecond. Similarly if power supply failure then UPS supply is also there for uninterrupted power supply.
Second-order Nonlinear Differential Equations: Oscillation Tests and Applications
Authors: Ghosh Tanusri , Santra Shyam S. , Bhattacharjee Rupak , Majumder Debasish 
Published: March 2021

AbstractThe 2nd order Differential Equations (DEs) are applied to analyze various phenomena in physics and it is extended to engineering. Specifically 2nd order linear DEs are having a big role in this field. We already observed this working rule in moving systems like a vertical spring attached with a mass. Another example is an electric circuit with a resistor, an inductor, and a capacitor in series connection. These models are applicable to approximate more complex situations like bond structure between atoms or molecules. They are generally patterned as vibrating springs which is explained by the same DEs. Qualitative theory analysis of DEs is an active area of investigation in theory and application point of view. For instance, oscillatory behavior of 2nd order DEs have many applications in the research related to distributed networks where in high-speed computations lossless transmission lines evolve. These lossless transmission lines are employed to connect switching circuits. Recently the study the functional DEs of neutral type is an active area of research. Many researchers are working in the field of oscillation theory and studying only sufficient conditions. Merely few are considering the necessary and sufficient conditions. We have attempted to set up the necessary and sufficient conditions for oscillation of solutions of 2nd order nonlinear neutral DEs. Mathematics Subject Classification (2010): 34K.
Evaluating student performance based on bloom’s taxonomy levels
Authors: Prasad G. N. R. 
Published: March 2021

Abstract
Knowing the performance of the student in online classes is very difficult. Staff are taking online classes and conducting objective type examinations. It is very difficult to know at which level student is performing better and which is not. Blooms taxonomy is a technique developed by Dr. Benjamin Bloom in the year of 1956. Understudy appraisal is a critical bit of educating and is done through the procedure of examinations and readiness of test question papers has reliably involved scheme. Bloom's taxonomy is a lot of three progressive models used to group instructive learning goals into dimensions of multifaceted nature and explicitness. The cognitive domain list has been the primary focus of most traditional education and is frequently used to structure curriculum learning objectives, assessments and activities. Bloom's taxonomy is a device that can help human services educators expand the profundity of their students' learning.[3] The test with the taxonomy is creating assessments that measure every one of the six levels. There are 19 sorts of psychological procedures that can be grouped into six noteworthy classifications: recall, comprehend, apply, break down, assess, and make. There are four noteworthy classifications of learning: verifiable, applied, procedural, and meta cognitive. Instances of computer based appraisals of critical thinking are given dependent on the assessment of the subjective outcomes of youngsters' cooperation in an after-school computer club. In this paper, an objective question paper have been given using six levels of Bloom's taxonomy and asked students to write the test using online and evaluates the results of student performance[1].
Conventional Education & Online Education in Engineering: A Case Study
Authors: Bhattacharyya Sucharita , Thander Anup Kumar 
Published: March 2021

Abstract
Online education is gaining ground since last few decades all over the world including India. But so far it is utilised mainly in various alternative courses or knowledge-enhancing courses beyond regular curriculum which learners could opt as per their convenience and interest using internet access, particularly if the situations in Indian universities are considered. But under COVID-19 pandemic situation, the utility and use of online education is suddenly multiplied and extended and is made inclusive within regular university semester courses also. Undergraduate engineering is one of the very prominent areas to mention. Accordingly, in the present study, the authors tried to show that in the last even semester, how the online education served the basic subjective needs of engineering students so far as their learning is concerned. For that purpose, a students' feedback data based on the online teaching provided is analysed in detail, which are taken from one of the standard engineering colleges of West Bengal. Corresponding results are analysed for end semester examination conducted online and is compared finally with relevant data obtained from evaluation of conventional education for some interesting discussion.
Non-rigid medical image registration using multi-scale residual deep fully convolutional networks
Authors: Yang T.J. , Tang Q. , Li L. , Bai X.H. 
Published: March 2021

Abstract
Medical image registration technology is important in medical image processing, which can establish correspondence between complex medical images and ensure the comparability of image data. Since the deep convolutional neural network model is prone to degradation and the convolution kernel has limited detection range during training, a Multi-scale residual full convolutional network (MS-ResFCN) model is proposed for unsupervised non-rigid medical image registration tasks. The model introduces a residual structure in the Fully Convolutional Network (FCN) model to ensure effective and stable training. At the same time, a hierarchical multi-scale convolution kernel is constructed within a single convolutional layer of the residual structure, which enhances the nonlinear mapping ability of the network. The local texture information and the contextual information of the image are synchronously extracted and fused to enrich the diversity of features. The experiment results on LPBA40 data sets show that the MS-ResFCN model can effectively eliminate the degradation phenomenon of the deep network during the training process and extract multi-scale features, which achieves better feature representation ability and registration accuracy.
Therapeutic angiogenesis using zinc oxide nanoflowers for the treatment of hind limb ischemia in a rat model
Authors: Barui Ayan Kumar , Nethi Susheel Kumar , Basuthakur Papia , Jhelum Priya , Bollu Vishnu Sravan , Reddy Bommana Raghunath , Chakravarty Sumana , Patra Chitta Ranjan 
Published: March 2021

Abstract
Critical limb ischemia (CLI) is a severe type of peripheral artery disease (PAD) which occurs due to an inadequate supply of blood to the limb extremities. Patients with CLI often suffer from extreme cramping pain, impaired wound healing, immobility, cardiovascular complications, amputation of the affected limb and even death. The conventional therapy for treating CLI includes surgical revascularization as well as restoration of angiogenesis using growth factor therapy. However, surgical revascularization is only suitable for a small percentage of CLI patients and is associated with a high perioperative mortality rate. The use of growth factors is also limited in terms of their poor therapeutic angiogenic potential, as observed in earlier clinical studies which could be attributed to their poor bio-availability and non-specificity issues. Therefore, to overcome the aforesaid disadvantages of conventional strategies there is an urgent need for the advancement of new alternative therapeutic biomaterials to treat CLI. In the past few decades, various research groups, including ours, have been involved in developing different pro-angiogenic nanomaterials. Among these, zinc oxide nanoflowers (ZONFs), established in our laboratory, are considered one of the more potent nanoparticles for inducing therapeutic angiogenesis. In our earlier studies we showed that ZONFs promote angiogenesis by inducing the formation of reactive oxygen species and nitric oxide (NO) as well as activating Akt/MAPK/eNOS cell signaling pathways in endothelial cells. Recently, we have also reported the therapeutic potential of ZONFs to treat cerebral ischemia through their neuritogenic and neuroprotective properties, exploiting angio-neural cross-talk. Considering the excellent pro-angiogenic properties of ZONFs and the importance of revascularization for the treatment of CLI, in the present study we comprehensively explore the therapeutic potential of ZONFs in a rat hind limb ischemia model (established by ligating the hind limb femoral artery), an animal model that mimics CLI in humans. The behavioral studies, laser Doppler perfusion imaging, histopathology and immunofluorescence as well as estimation of serum NO level showed that the administration of ZONFs could ameliorate ischemia in rats at a faster rate by promoting therapeutic angiogenesis to the ischemic sites. Altogether, the present study offers an alternative nanomedicine approach employing ZONFs for the treatment of PADs.
The 2019/2020 mega-fires exposed Australian ecosystems to an unprecedented extent of high-severity fire
Authors: Collins Luke , Bradstock Ross A , Clarke Hamish , Clarke Michael F , Nolan Rachael H , Penman Trent D 
Published: March 2021

Abstract
Extreme fire seasons characterised by very large ‘mega-fires’ have demonstrably increased area burnt across forested regions globally. However, the effect of extreme fire seasons on fire severity, a measure of fire impacts on ecosystems, remains unclear. Very large wildfires burnt an unprecedented area of temperate forest, woodland and shrubland across south-eastern Australia in 2019/2020, providing an opportunity to examine the impact of extreme fires on fire severity patterns. We developed an atlas of wildfire severity across south-eastern Australia between 1988 and 2020 to test (a) whether the 2019/2020 fire season was more severe than previous fire seasons, and (b) if the proportion of high-severity fire within the burn extent (HSp) increases with wildfire size and annual area burnt. We demonstrate that the 2019/2020 wildfires in south-eastern Australia were generally greater in extent but not proportionally more severe than previous fires, owing to constant scaling between HSp and annual fire extent across the dominant dry-forest communities. However, HSp did increase with increasing annual fire extent across wet-forests and the less-common rainforest and woodland communities. The absolute area of high-severity fire in 2019/2020 (∼1.8 M ha) was larger than previously seen, accounting for ∼44% of the area burnt by high-severity fire over the past 33 years. Our results demonstrate that extreme fire seasons are a rare but defining feature of fire regimes across forested regions, owing to the disproportionate influence of mega-fires on area burnt.
Quantum particle across Grushin singularity
*
Authors: Gallone Matteo , Michelangeli Alessandro 
Published: March 2021

Abstract
A class of models is considered for a quantum particle constrained on degenerate Riemannian manifolds known as Grushin cylinders, and moving freely subject only to the underlying geometry: the corresponding spectral and scattering analysis is developed in detail in view of the phenomenon of transmission across the singularity that separates the two half-cylinders. Whereas the classical counterpart always consists of a particle falling in finite time along the geodesics onto the metric’s singularity locus, the quantum models may display geometric confinement, or on the opposite partial transmission and reflection. All the local realisations of the free (Laplace–Beltrami) quantum Hamiltonian are examined as non-equivalent protocols of transmission/reflection and the structure of their spectrum is characterised, including when applicable their ground state and positivity. Besides, the stationary scattering analysis is developed and transmission and reflection coefficients are calculated. This allows to comprehend the distinguished status of the so-called ‘bridging’ transmission protocol previously identified in the literature, which we recover and study within our systematic analysis.
Microscopic experimental analysis on weatherability of roof insulation materials under multi field coupling environment
Authors: Ding Yang , Dong Jing-Liang , Yang Tong-Lin , Wang Zhong-Ping , Zhou Shuang-Xi , Wei Yong-Qi , She An-Ming 
Published: March 2021

Abstract
The weatherability of insulation materials directly affects its thermal insulation performance, so it is necessary to carry out the weatherability experiments for insulation materials. In this paper, three kinds of insulation materials, that is, polyurethane (PUR), foam concrete (FC) and vacuum insulation panel (VIP) are chosen to analyze their thermal conductivity under different kinds of weatherability experiments. For the different kinds of weatherability experiments, the experiments of damp-heat, freeze-thaw, high-low temperature and wet-dry are designed to analyze the thermal conductivity of the insulation materials and the microstructure of insulation materials. The experimental results show that thermal conductivity of FC has a downward trend under the damp-heat experiment, and the thermal conductivity of FC has increased in other experiments. The thermal conductivity of PUR increases in all weatherability experiments, but the thermal conductivity of VIP does not change in all weatherability experiments.
A 3D printed phantom to assess MRI geometric distortion
Authors: Ramachandran Prabhakar , Noble Christopher , Langton Christian , Perrett Ben , Cox Joshua , Chapman Mike , McGill George 
Published: March 2021

Abstract
Geometric distortions in magnetic resonance can introduce significant uncertainties into applications such as radiotherapy treatment planning and need to be assessed as part of a comprehensive quality assurance program. We report the design, fabrication, and imaging of a custom 3D printed unibody MR distortion phantom along with quantitative image analysis. Methods: The internal cavity of the phantom is an orthogonal three-dimensional planar lattice, composed of 3 mm diameter rods spaced equidistantly at a 20 mm centre-centre offset repeating along the X, Y, and Z axes. The phantom featured an overall length of 308.5 mm, a width of 246 mm, and a height of 264 mm with lines on the external surface for phantom positioning matched to external lasers. The MR phantom was 3D printed in Nylon-12 using an advancement on traditional selective laser sintering (SLS) (HP Jet Fusion 3D—4200 machine). The phantom was scanned on a Toshiba Aquilion CT scanner to check the integrity of the 3D print and correct for any resultant issues. The phantom was then filled with NiSO4 solution and scanned on a 3T PET-MR Siemens scanner for selected T1 and T2 sequences, from which distortion vectors were generated and analysed using in-house software written in Python. Results: All deviations of the node positions from the print design were less than 1 mm, with an average displacement of 0.228 mm. The majority of the deviations were smaller than the 0.692 mm pixel size for this dataset. Conclusion: A customised 3D printed MRI-phantom was successfully printed and tested for assessing geometric distortion on MRI scanners. 3D printed phantoms can be considered for clinics wishing to assess geometric distortions under specific conditions, but require resources for design, fabrication, commissioning, and verification.