bluuebunny/crossref_metadata_2025_split huggingface dataset:
Isolated Discitis in Melioidosis: An Unknown Presentation and a Microbiological Challenge
Authors: Varma Anoop , Mathew Jacob Eapen , Gopalakrishnan Chittur Viswanathan , Wilson Arun 
Published: May 2021

Abstract

Burkholderia pseudomallei causes Whitmore’s disease or melioidosis which is endemic in many South Asian countries including India. This gram-negative bacterium is frequently found in the moist soil and agricultural workers get infected most commonly. Most of the infections are asymptomatic and have a wide spectrum of manifestations as in tuberculosis. Melioidosis of the spine manifests as spondylodiscitis with paravertebral and prevertebral abscess and presentation as discitis alone is not reported. We report the first case of melioidosis causing isolated discitis without any obvious bony involvement. It also highlights the need for preoperative suspicion of these rare manifestations even in seemingly innocuous disc disease presenting as back pain and radiculopathy.
Polycythemia Vera Presenting as Hemorrhagic Stroke
Authors: Balagopal Krishnan , Mathew Aju , Koshy Ansa Grace , Jacob Jerin Peter 
Published: May 2021

Abstract
Patients with polycythemia vera are at high risk for vaso-occlusive events including cerebral ischemia and hemorrhage. Cerebral ischemic events are due to increased blood viscosity and platelet activation within the central nervous system arterial vessels. We present a case of a 65-year-old woman who presented to the emergency department with seizures followed by left-sided weakness. Hematologic investigations revealed a hyperviscous state, and magnetic resonance imaging (MRI) was consistent with bilateral hemorrhagic infarction. Genetic studies were positive for polycythemia vera mutation. Symptoms improved with phlebotomy and antiplatelet agents. Through this case, we aim to highlight polycythemia vera as a cause of hemorrhagic stroke and the importance of blood counts in the routine evaluation of the same.
Ion temperature and rotation fluctuation measurements with ultra-fast charge exchange recombination spectroscopy (UF-CHERS) in the DIII-D tokamak
Authors: Truong D. D. , McKee G. R. , Yan Z. , Jaehnig K. , Winz G. R. , Fonck R. J. , Geiger B. 
Published: May 2021

An upgraded detector and several optimizations have significantly improved the Ultra-Fast Charge Exchange Recombination Spectroscopy (UF-CHERS) diagnostic sensitivity to ion temperature and parallel velocity fluctuations at turbulence relevant spatio-temporal scales. Normalized broadband ion temperature and parallel velocity fluctuations down to x̃x∼1% (x = Ti, v∥) and up to ∼450 kHz have been measured in a variety of plasmas. The multi-field nature of the CHERS technique also allows measurements of the cross-phase angles of the fluctuating fields. UF-CHERS is optimized to observe emissions from the electron exchange reaction between intrinsic C6+ and hydrogenic neutral beam injected particles near 529 nm. UF-CHERS consists of two chords separated by ∼1 cm radially, less than the turbulence correlation length in DIII-D plasmas, which enables correlated measurements to suppress incoherent electronic and photon noise. The optical components of the spectrometer include a volume-phase-holographic grating with &gt;90% transmission between 528 and 530 nm and f/2 200-mm lenses, selected to maximize the optical efficiency and photon flux. Diffracted light from each chord is collected in eight spectral bins, each with a bandwidth of ∼0.25 nm, and detected and amplified by chilled avalanche photodiodes and custom high-gain, wide bandwidth low-noise preamplifiers to achieve the optimal signal-to-noise ratio. The resulting signals are digitized at 1 MHz, 103–104× faster than the conventional CHERS diagnostics. Spatial coverage is achieved by repositioning a motorized fiber tray between plasmas. UF-CHERS measurements will advance the understanding of turbulent ion transport and contribute to the validation of transport models and simulations.
Tau forms oligomeric complexes on microtubules that are distinct from tau aggregates
Authors: Gyparaki Melina Theoni , Arab Arian , Sorokina Elena M. , Santiago-Ruiz Adriana N. , Bohrer Christopher H. , Xiao Jie , Lakadamyali Melike 
Published: May 2021

Significance
Tau is a neuronal protein whose aggregation is a hallmark of several neurodegenerative diseases collectively known as tauopathies. Due to a lack of suitable tools, discriminating small, pathological tau aggregates from physiological tau within cells has been difficult. Using super-resolution microscopy, we show that tau forms dimers and trimers on microtubules ex vivo. These dimeric/trimeric tau complexes are distinct from tau aggregates formed in a cell model of frontotemporal dementia with parkinsonism linked to chromosome 17. Machine learning–based classification further shows that hyperphosphorylation of specific tau residues is associated with the formation of distinct tau aggregates. Our approach opens the door to detecting pathological tau oligomers in disease and to screening for drugs that can disrupt these pathological oligomers.
One-step electrodeposition of CuSCN/CuI nanocomposite and its hole transport-ability in inverted planar perovskite solar cells
Authors: Ramachandran Kaliappan , Jeganathan Chellamuthu , Subbian Karuppuchamy 
Published: May 2021

Abstract
The synthesis of CuSCN/CuI nanocomposite by single-step electrodeposition is developed. The surface morphology and film thickness are controlled by changing the electrochemical potential and deposition time. The mixed-phase formation of CuSCN/CuI is confirmed through x-ray diffraction and Raman spectral analysis. Nanopetal (NP) like morphology of CuSCN/CuI is observed in FESEM micrographs. Interestingly, the NPs density and thickness are increased with increasing the deposition potential and time. The device fabricated using CuSCN/CuI nanocomposite as a hole transport layer (HTL) which is grown for 2 min delivers the best photovoltaic performance. The maximum power conversion efficiency of 18.82% is observed for CuSCN/CuI NP with a density of 1153 μm−2 and thickness of 142 nm. The charge transfer ability of the CuSCN/CuI NP HTL is analyzed by electrochemical impedance spectroscopy. Based on the observation, moderate charge transport resistance and optimum film thickness are required for achieving maximum photovoltaic performance in perovskite solar cells (PVSCs). Thus, the developed CuSCN/CuI NP HTL is a potential candidate for PVSCs.
Contributions from populations and coherences in non-equilibrium entropy production
Authors: Varizi Adalberto D , Cipolla Mariana A , Perarnau-Llobet Martí , Drumond Raphael C , Landi Gabriel T 
Published: May 2021

Abstract
The entropy produced when a quantum system is driven away from equilibrium can be decomposed in two parts, one related with populations and the other with quantum coherences. The latter is usually based on the so-called relative entropy of coherence, a widely used quantifier in quantum resource theories. In this paper we argue that, despite satisfying fluctuation theorems and having a clear resource-theoretic interpretation, this splitting has shortcomings. First, it predicts that at low temperatures the entropy production will always be dominated by the classical term, irrespective of the quantum nature of the process. Second, for infinitesimal quenches, the radius of convergence diverges exponentially as the temperature decreases, rendering the functions non-analytic. Motivated by this, we provide here a complementary approach, where the entropy production is split in a way such that the contributions from populations and coherences are written in terms of a thermal state of a specially dephased Hamiltonian. The physical interpretation of our proposal is discussed in detail. We also contrast the two approaches by studying work protocols in a transverse field Ising chain, and a macrospin of varying dimension.
Renewable Energy: Potential, Status, Targets and Challenges in Rajasthan
Authors: Bhukya Muralidhar Nayak , Kumar Manish , Kant Akshat , Punit  
Published: May 2021

Abstract
India has a population of 1.3 billion people and one of largest growing economies in the world. Therefore, there is a strong demand of energy. Till date, the main source of energy is coal which is non renewable and harmful to the environment. Therefore, it is important and necessary to find an alternative source of energy. This indirectly drives us to focus on Renewable Energy Source, which has several advantages. The Ministry of National Renewable Energy (MNRE) has launched many schemes to encourage the domestic and commercial sector to use renewable energy sources. In India the state of Rajasthan is occupying 5th position in the production of electric power generation from Renewable Energy Sources like Solar, Wind and Biomass etc. Therefore this paper discusses the potential and opportunities of electric power generation through renewable energy in the state of Rajasthan.
Fault Detection using Real Time Tracking of Electronic Appliances in Homes & Corporate Offices using Change Detection Algorithm
Authors: Nampelli V R , Yalagi Dr Pratibha 
Published: May 2021

Abstract
In recent years, there is a remarkable rise in the use of electronic appliances in many homes and corporate offices. Such appliances include Air Conditioners, Smart Lights, Refrigerators, and CCTV Cameras, etc. To keep such appliances in a proper working condition, functional working of appliances needs to be checked. Changing the place of appliance, improper settings, cleaning of rooms, etc. lead appliances to failure. In proposed system sensors are used to track the functional working of appliances in real time or when there is a need arises to check working of the appliances before and after the maintenance is done. This sensor data is collected in database server. At database server, preprocessing of data is done to get accurate results. Then preprocessed sensor data are compared with the manufacturer’s data (sensor data when the appliance is in ideal working conditions). For comparison of sensor data with the manufacturer’s data, a Change Detection algorithm is used in the proposed system. The results of the Change Detection algorithm are shown in the form of graphs on the user interface at the server. This is accessed and analyzed using a mobile application in smartphones and a web browser in a desktop PC with, authorized login credentials provided to owners and technicians of appliances. This helps technician or the owner of appliance to identify the basic cause of appliance failure and do necessary repair whenever needed.
Video Content-Based Advertisement Recommendation System using Classification Technique of Machine Learning
Authors: Konapure R C , Lobo L M R J 
Published: May 2021

Abstract
Content-based advertising is a method by which we advertise on a video media based on a relevant topic assigned to the video. In digital advertising, the advertisements shown to a user is based on the user’s behaviour on the internet. Streaming platforms are then used to target audience based on parameters like user’s geo-location, interests, watch history, age, etc. In most cases, the advertisements shown are not relevant; an undesired impact is created. Content-based advertising helps to convey the message with increased efficiency and simultaneously optimizes its conversion rate. In this proposed system we take the video metadata as input and apply the NLP techniques for text classification which categories the video and assigns a relevant advertisement to it. The second module takes the video as an input. Thereafter the video is converted into N individual frames to tackle the video classification as an image classification problem. In this proposed system we train a Convolutional Neural Network to identify the topic of the video on an image dataset and compare its performance with a pre-trained model. We create the image dataset by downloading images from the internet. We also create a video advertisement’s dataset by web scrapping. This proposed system makes sure that the user is shown the advertisement in reference to the video. This increases probability of the user visiting the client’s website.
Implementation of Predictive Modelling Techniques for determining Exhaust Engine Emissions
Authors: Khurana Shivansh , Saxena Shubham , Jain Sanyam , Dixit Ankur 
Published: May 2021

AbstractThe world is going through the biggest change in modern world, the climate change. And this is majorly due to our utmost reliance over fossil fuels. Researchers, industrialists and scientists around the globe are trying to figure out the alternate energy sources or at least the ones with the least poisonous emissions. To design an automobile machinery with such parameters that they would cause possibly the least pollution, a huge sum of money is spent on majorly executing experimentations repeatedly. The paper has shown the objective of testing of such emissions and with the help of known machine learning algorithms, predicting those harmful emissions. In other words, using statistical modelling to predict the engine emissions which is traditionally measured by an exhaust gas analyser. In this research, data of real-time engine emissions produced by burning of Bio-Diesel fuel is recorded and fed into machine learning algorithms for their training. Three machine learning emission models were built up to illustrate their emission ranges. Out of the three, results showed that Decision Tree based engine emission model showed the best results.
Effect of machining parameters on average surface roughness Ra while turning hybrid Mg-MMC-An experimental approach
Authors: Hira Jaspreet , Manna Alakesh , Gera Pushpinder , Sharma Rohit , Kumar Vikas 
Published: May 2021

Abstract
Hybrid metal matrix composite (MMC) reinforced with silicon carbide (SiCp), alumina (Al2O3p) and graphite (Grp) are being preferred for industrial applications due to their lightweight, and lower densities of these combined materials and high strength at the molecular level. These developed hybrid composite materials have been utilized in the wide range of applications in automotive and aerospace industries. The manufacturing industries that are utilizing the hybrid Mg-MMC also go through the machining turning operations for application products. Therefore, it is very important for machining the hybrid Mg-MMC for the desired dimensional accuracy. The present experimental research was therefore aimed at investigating the average surface roughness height Ra while turning the hybrid Mg-MMC using the CCMT 09 T3 08 WF 1525 tungsten carbide insert. The machining parameters includes the cutting speed was 40 m/min, 80 m/min and 120 m/min, the feed rate was 0.08 mm/rev, 0.2 mm/rev, 0.4 mm/rev and the depth of cut was 0.2 mm, 0.5 mm and 0.75 mm. The average surface roughness height Ra was measured using surfcom 130A (profilometer). Experimental investigation found that the average surface roughness height Ra was lower at a high cutting speed and at a lower feed rate. In addition, the built-up edges were formed at a lower feed rate with all cutting speed values.
ENERGY HARVESTING USING PIEZOELECTRIC PLATES IN LEAF SPRING
Authors: Mann Sanjana , Garg Isha , Singh Arushi , Verma Preetika , Kumar Ravinder 
Published: May 2021

Abstract
This paper is designed to lay emphasis on a regenerative form of power generation. A conventional leaf spring is taken and its plates are replaced with piezoelectric plates in order to convert vibrational energy obtained from unevenness and bumps on the road into electrical energy to feed the battery. The plates are replaced alternatively to ensure that the overall structural integrity of the model is not affected negatively. The model is created in SolidWorks and static evaluation is carried out in ANSYS. The stress acting on each piezoelectric leaf is obtained. The stress so obtained is used to calculate input AC voltage for each plate and this voltage is used to estimate DC voltage and DC current using NI MULTISUM software. The procedure is repeated with varying the basic parameters like the thickness of plates and the number of plates to find the optimal case in which maximum voltage generation is observed. Further, the time required to charge the on-board lead battery and the auxiliary battery is calculated. The project aims to find out the optimal case for an Indian road scenario, which will be able to feed the on-board battery of an E-rickshaw to enhance its average running time.
Studying joint spectral intensity of spontaneous four-wave mixing in optical nanofibers
Authors: Shmakova Alevtina L , Shukhin Anatoly A , Kalachev Alexey A 
Published: May 2021

Abstract
Joint spectral intensity of the biphoton field generated via spontaneous four-wave mixing in an optical nanofiber was studied both experimentally and theoretically. The measured two-photon frequency distribution agrees well with the theoretically expected one that is calculated taking into account the spatially inhomogeneous profile of the taper. It is shown that measuring joint spectral intensity of the biphoton field makes it possible to determine the nanofiber radius with high accuracy.
A decade of the U.S. energy mix transitioning away from coal: historical reconstruction of the reductions in the public health burden of energy
Authors: Buonocore Jonathan J , Salimifard Parichehr , Michanowicz Drew R , Allen Joseph G 
Published: May 2021

Abstract
In the last decade, the transition away from coal and to fossil gas and biomass in the U.S. has had a major influence on greenhouse gas emissions, especially from electricity generation. However, the effect of this transition on the public health burden of air pollution is not well understood. We use three reduced complexity models (RCMs) and emissions inventory data to reconstruct the changes in health impacts due to PM2.5 exposure from stationary fuel combustion sources in the U.S., from 2008 to 2017. In 2008, the health impacts of air pollution from stationary sources was largely driven by coal combustion. By 2017, the contribution of coal has dropped precipitously, and the health burden of stationary air pollution sources is shared among a mixture of source types and fuels—largely gas and biomass in buildings and industry, and the remaining coal-fired electricity generation. Nationwide, in 2017, health impacts of biomass and wood combustion are higher than combustion of coal and gas individually. Industrial boilers had the highest emissions and health impacts, followed by residential buildings, electricity, and then commercial buildings. All three RCMs indicate that biomass and wood are the leading sources of stationary source air pollution health impacts in 24 states, and that the total health impacts of gas surpass that of coal in 19 states and the District of Columbia. We develop a projection method using state-level energy consumption data for 2018 and show that these trends likely continued. The RCMs had high agreement for 2008 emissions, when sulfur dioxide emissions from coal-fired power plants were the predominant air pollution source. However there was substantial disagreement between the three RCMs on the 2017 health burden, likely due to pollutants less well-characterized by the RCMs having a higher proportionate share of total impacts.
The effect of some environmental variables on the abundance and distribution of aquatic macrophytes in Al-Hawizeh marsh, Iraq
Authors: Al-Thahaibawi B M H , Al-Abbawy D A H , Al-Mayaly I K A , Younis K H 
Published: May 2021

Abstract
Aquatic macrophyte communities and environmental factors were studied at four Al-Hawizeh marsh sites from December 2017 until November 2018. Quantitative data from thirty species of aquatic plants were collected to investigate density, vegetation cover, biomass and their relationship to the environmental factors. For emerging plants, relative abundance reached the highest values (36%) than submerged and wet species, while free-floating plants produced the lowest value (17%).Physical and chemical properties have been studied including water temperature ranging from 11.3 ° C in January to 31.4 ° C in August, dissolved oxygen (DO)ranging from 1.88 mg/L in September to 10.5 mg / L in April, pH varied from 7.2 in June to 8.4 in December, electrical conductivity (EC μ.S/cm) differs from 2257 μ.S/cm in November to 6859 μ.S/cm in April. The results identified the highest percentages of vegetation cover reported during the summer, the lowest percentages revealed during the winter for all plant groups. The highest annual vegetation cover rates for submergent species achieved 52.54% by C.demersum, for free-floating plants 66.67% of S. polyrrhiza, for emergent plants 85.5% of P. australis, 41.62% of P. paspaloide for wet plants. Total mean biomass of plant groups showed the highest value of 844.02 (gm dry weight/m2) reported by emerging plants, the lowest value of 47.25 (gm dry weight / m2) by the wet plants. Thus, biomass values were correlated with the vegetation cover values for all plants.
Effect of adding silver nanoparticles with drinking water on some lymphatic organs and microflora in the intestinal for broiler chickens (ROSS 308)
Authors: Ibrahim Al-Saeedi Mohammed Khalil , Dakhil Hashem Hadi , Abbas Al-Khafaji Fadhil Rasool 
Published: May 2021

Abstract
This study was conducted in the farm of domestic birds belonging to the Department of Animal Production, College of Agriculture, Al-Qasim Green University for the period from 21/3/2019 to 24/4/2019, Laboratory work was then conducted, where 225 chicks from broiler chicks and raised in 1x1.5 m cages, the chicks were randomly divided into five treatments and for each treatment contains three replicates, each replicate included 15 chicks. Nano-silver was used by adding it with drinking water in concentrations of (0, 20, 30, 40, 50 ppm.L-1 drinking water) for the treatments (T1, T2, T3, T4, T5), respectively. Chicks were bred in the field for 35 days. The study showed the following results: A significant superiority (P <0.05) for the T5 treatment was obtained in the weight of bursa of Fabricius compared to other treatments. It was also found that there was a significant superiority (P <0.05) for the treatments (T1, T5) in the index of the bursa of Fabricius compared to the rest of the treatments. It was also observed a significant superiority (P <0.05) for the treatments (T4, T5) in the number of beneficial bacteria (Lactobacilli) in the Jejunum compared to the rest of the treatments. The excelling of the T5 treatment continued in the number of beneficial bacteria in the ileum compared to other studied treatments. As for the harmful bacteria (E.coli), the T1 treatment was significantly (T <0.01) excelled in Jejunum and ileum over other treatments at the age of 14 days from birds’ age and at the age of 35 days from birds’ age. The treatments (T5, T2) was significantly (P <0.01) excelled in the number of beneficial bacteria in the Jejunum. As for the harmful bacteria, the T1 treatment maintained on their superiority (P <0.01) compared to the rest of the experiment.