bluuebunny/crossref_metadata_2025 huggingface dataset:
An Examination of how E-Cigarette/Cigarette use during Adolescence is Associated with Future use during the Third Trimester of Pregnancy
Authors: Beck Dana C. , Boyd Carol J. , Evans-Polce Rebecca , McCabe Sean Esteban , Veliz Phil T.
Published: August 2021

Background: Adolescent e-cigarette use has increased, as has e-cigarette use during pregnancy, yet little is known about how these types of tobacco/nicotine (cigarettes/e-cigarettes) use during adolescence are associated with tobacco/nicotine use during the third trimester of pregnancy among young adults. Methods: National longitudinal data (2013–2018) from the Population Assessment of Tobacco and Health (PATH) study were used. Young adults ages 18–20 who indicated past-year pregnancy made up the analytic sample ( N = 246). Logistic regression was used to evaluate the association between history of past 30-day use of cigarettes/e-cigarettes during adolescence (i.e., 14–17) and later use during the third trimester of pregnancy among young women (i.e., 18–20). Results: Within the sample of young women who indicated a pregnancy during the past year, 18.9% indicated smoking cigarettes and 4.2% indicated using e-cigarettes during their last trimester. Cigarette smoking in adolescence (wave 1 or 2) was associated with cigarette use during the last trimester (aOR = 4.76, 95% CI = 1.36, 16.6); however, e-cigarette use during adolescence was not associated with either cigarette or e-cigarette use during the third trimester of pregnancy. Conclusions: Tobacco/nicotine prevention in early adolescence has implications for preventing tobacco/nicotine-related harms during pregnancy among young adults. Intervention programs and clinicians informed about various types of tobacco/nicotine are needed to address tobacco/nicotine cessation among adolescents to prevent consequences of tobacco/nicotine use during pregnancy.
State-dependent inhibition of BK channels by the opioid agonist loperamide
Authors: Vouga Alexandre G. , Rockman Michael E. , Yan Jiusheng , Jacobson Marlene A. , Rothberg Brad S.
Published: August 2021

Large-conductance Ca2+-activated K+ (BK) channels control a range of physiological functions, and their dysfunction is linked to human disease. We have found that the widely used drug loperamide (LOP) can inhibit activity of BK channels composed of either α-subunits (BKα channels) or α-subunits plus the auxiliary γ1-subunit (BKα/γ1 channels), and here we analyze the molecular mechanism of LOP action. LOP applied at the cytosolic side of the membrane rapidly and reversibly inhibited BK current, an effect that appeared as a decay in voltage-activated BK currents. The apparent affinity for LOP decreased with hyperpolarization in a manner consistent with LOP behaving as an inhibitor of open, activated channels. Increasing LOP concentration reduced the half-maximal activation voltage, consistent with relative stabilization of the LOP-inhibited open state. Single-channel recordings revealed that LOP did not reduce unitary BK channel current, but instead decreased BK channel open probability and mean open times. LOP elicited use-dependent inhibition, in which trains of brief depolarizing steps lead to accumulated reduction of BK current, whereas single brief depolarizing steps do not. The principal effects of LOP on BK channel gating are described by a mechanism in which LOP acts as a state-dependent pore blocker. Our results suggest that therapeutic doses of LOP may act in part by inhibiting K+ efflux through intestinal BK channels.
Computational study of non-conductive selectivity filter conformations and C-type inactivation in a voltage-dependent potassium channel
Authors: Li Jing , Shen Rong , Rohaim Ahmed , Mendoza Uriarte Ramon , Fajer Mikolai , Perozo Eduardo , Roux Benoît
Published: August 2021

C-type inactivation is a time-dependent process of great physiological significance that is observed in a large class of K+ channels. Experimental and computational studies of the pH-activated KcsA channel show that the functional C-type inactivated state, for this channel, is associated with a structural constriction of the selectivity filter at the level of the central glycine residue in the signature sequence, TTV(G)YGD. The structural constriction is allosterically promoted by the wide opening of the intracellular activation gate. However, whether this is a universal mechanism for C-type inactivation has not been established with certainty because similar constricted structures have not been observed for other K+ channels. Seeking to ascertain the general plausibility of the constricted filter conformation, molecular dynamics simulations of a homology model of the pore domain of the voltage-gated potassium channel Shaker were performed. Simulations performed with an open intracellular gate spontaneously resulted in a stable constricted-like filter conformation, providing a plausible nonconductive state responsible for C-type inactivation in the Shaker channel. While there are broad similarities with the constricted structure of KcsA, the hypothetical constricted-like conformation of Shaker also displays some subtle differences. Interestingly, those are recapitulated by the Shaker-like E71V KcsA mutant, suggesting that the residue at this position along the pore helix plays a pivotal role in determining the C-type inactivation behavior. Free energy landscape calculations show that the conductive-to-constricted transition in Shaker is allosterically controlled by the degree of opening of the intracellular activation gate, as observed with the KcsA channel. The behavior of the classic inactivating W434F Shaker mutant is also characterized from a 10-μs MD simulation, revealing that the selectivity filter spontaneously adopts a nonconductive conformation that is constricted at the level of the second glycine in the signature sequence, TTVGY(G)D.
Control and enhancement of multiband high harmonic generation by synthesized laser fields
Authors: Bruner Barry D , Narovlansky-Uzan Ayelet J , Arusi-Parpar Talya , Orenstein Gal , Shonfeld Assaf , Dudovich Nirit
Published: August 2021

High harmonic generation (HHG) spectroscopy has emerged as an invaluable tool for studying electronic dynamics and structure in crystals. The primary challenges are imposed by the multiple degrees of freedom of the underlying dynamics as well as the low efficiency of the HHG process. Here we show that when the HHG process is driven by a synthesized bichromatic field, its efficiency can be significantly enhanced, increasing the photon flux by 1–2 orders of magnitude. The bichromatic field enhances the signal on a microscopic level by manipulating the tunnel ionization and subsequent electron dynamics driven by the synthesized laser waveform. We examine the scaling of the HHG yield on the field parameters, and observe a pronounced dependence on the HHG energy. Importantly, our study reveals that the different spectral regimes are dictated by different generation mechanisms as well as multiple bands in which the dynamics evolve. Our work demonstrates that shaped laser fields serve as a powerful approach to control multiband electron currents in solids, probe their origin, and enhance the efficiency of the HHG process.
Review of porosity uncertainty estimation methods in computed tomography dataset
Authors: Jaques Victory A J , Plessis Anton Du , Zemek Marek , Šalplachta Jakub , Stubianová Zuzana , Zikmund Tomáš , Kaiser Jozef
Published: August 2021

X-ray computed tomography is a common tool for non-destructive testing and analysis. One major application of this imaging technique is 3D porosity identification and quantification, which involves image segmentation of the analysed dataset. This segmentation step, which is most commonly performed using a global thresholding algorithm, has a major impact on the results of the analysis. Therefore, a thorough description of the workflow and a general uncertainty estimation should be provided alongside the results of porosity analysis to ensure a certain level of confidence and reproducibility. A review of current literature in the field shows that a sufficient workflow description and an uncertainty estimation of the result are often missing. This work provides recommendations on how to report the processing steps for porosity evaluation in computed tomography data using global thresholding, and reviews the methods for the estimation of the general uncertainty in porosity measurements.
Spatially discrete Boussinesq equation: integrability, Darboux transformation, exact solutions and continuum limit
Authors: Zhao Hai-qiong , Zhou Tong
Published: August 2021

The intimate connection between discrete and continuous integrable systems may yield deep insight into some inherent discreteness of physical phenomena. In this paper, a spatially discrete Boussinesq equation is investigated. The integrability of the spatially discrete model is confirmed by showing the existence of Lax pair and infinite number of conservation laws. The Darboux transformation is expressed in terms of Casorati type determinant. Further, by combining the Darboux transformation with different solutions of eigenfunction, we provide a comprehensive approach to construct various types of exact solutions to the spatially discrete Boussinesq equation, such as multi-soliton solutions, periodic solutions, rational solutions and more generally their interaction solutions. Lastly, we prove that the theory of spatially discrete Boussinesq equation including the Lax pair, the conservation laws, the Darboux transformation and the exact solutions converges to the corresponding theory of the Boussinesq equation in the continuum limit.
Optical system research of multi-object fiber spectroscopic survey telescope
Authors: Bai Hua , Su Ding-Qiang , Liang Ming , Shectman Stephen A. , Yuan Xiang-Yan , Cui Xiang-Qun
Published: August 2021

In the first part of this paper, four different Cassegrain optical systems with their correctors are designed and studied for multi-object fiber slit spectroscopic survey. The aperture in 6.5 m and field of view 3° are taken for these optical systems. Assuming observation wavelength range is 0.365–0.95 μm, the maximum zenith distance for observing is 60°, the maximum diameter of these lenses is 1.66 m, the altitude of the telescope site is 2500 m, two correctors are composed of 4-piece lenses and the other two are 5-piece lenses. The results obtained are: f-ratio about 3.7, the image quality for all four systems with EE80D ≤ 0.60″, the linear diameter of the focal surface is about 1.2 m and 11 000 fibers can be set on it. Considering the limit of size of fused silica and optical glass, the maximum diameter for lens is about 1.7 m. Such a 6.5 m telescope is about the largest one if using the above correctors. Considering the multi-object spectroscopic survey is greatly important, we also studied some telescope optical systems having their aperture near or larger than 10 m used for the multi-object fiber spectroscopic survey. Such ideas are introduced in the last section of this paper.
Masses for free-floating planets and dwarf planets
Authors: Gould Andrew , Zang Wei-Cheng , Mao Shude , Dong Su-Bo
Published: August 2021

The mass and distance functions of free-floating planets (FFPs) would give major insights into the formation and evolution of planetary systems, including any systematic differences between those in the disk and bulge. We show that the only way to measure the mass and distance of individual FFPs over a broad range of distances is to observe them simultaneously from two observatories separated by

D
~
O
(
0.01

au
)

(to measure their microlens parallax π
E) and to focus on the finite-source point-lens (FSPL) events (which yield the Einstein radius θ
E). By combining the existing KMTNet 3-telescope observatory with a 0.3 m 4 deg2 telescope at L2, of order 130 such measurements could be made over four years, down to about M ∼ 6 M
⊕ for bulge FFPs and M ∼ 0.7 M
⊕ for disk FFPs. The same experiment would return masses and distances for many bound planetary systems. A more ambitious experiment, with two 0.5 m satellites (one at L2 and the other nearer Earth) and similar camera layout but in the infrared, could measure masses and distances of sub-Moon mass objects, and thereby probe (and distinguish between) genuine sub-Moon FFPs and sub-Moon “dwarf planets” in exo-Kuiper Belts and exo-Oort Clouds.
Effects of resistivity on standing shocks in low angular momentum flows around black holes
Authors: Singh Chandra B. , Okuda Toru , Aktar Ramiz
Published: August 2021

We study two-dimensional low angular momentum flow around a black hole using the resistive magnetohydrodynamic module of PLUTO code. Simulations have been performed for the flows with parameters of specific angular momentum, specific energy and magnetic field which may be expected for the flow around Sgr A*. For flows with lower resistivity η = 10−6 and 0.01, the luminosity and shock location on the equator vary quasi-periodically. The power density spectra of luminosity variation show peak frequencies which correspond to the periods of 5 × 105, 1.4 × 105 and 5 × 104 s. These quasi-periodic oscillations (QPOs) occur due to interaction between the outer oscillating standing shock and the inner weak shocks occurring at the innermost hot blob. While for cases with higher resistivity η = 0.1 and 1.0, the high resistivity considerably suppresses the magnetic activity such as MHD turbulence and the flows tend to be steady and symmetric with respect to the equator. The steady standing shock is formed more outward compared with the hydrodynamical flow. The low angular momentum flow model with the above flow parameters and with low resistivity has a possibility to explain long-term flares of Sgr A* with frequencies ∼ one per day and ∼ 5 – 10 days in the latest observations by Chandra, Swift and XMM-Newton monitoring of Sgr A*.
Optical monitoring and intra-day variabilities of BL Lac Objects OJ 287
Authors: Yuan Yu-Hai , Fan Jun-Hui , Wu Hong , Hao Jing-Meng , Huang Wei-Rong , Liu Xiao-Lan , Huang Hong-Ren
Published: August 2021

Using the 1.26 m National Astronomical Observatory-Guangzhou University Infrared/Optical Telescope (NGT), we monitor one BL Lac object, OJ 287. For this source, we obtain 15 094 gri observations (4900 at g band, 5184 at r band and 5010 at i band) in 155 nights from 2014 December 13 to 2019 March 15. Based on the upper observations, we obtain the following results. (1) The total variation amplitude is ∼2.3 mag. (2) There are intra-day variabilities (IDVs). The IDV timescales (Δ T) are in the range from 7.69 min (Δ m = 0.06 ± 0.02 mag) to 371.09 min (Δ m = 0.26 ± 0.04 mag). (3) There are strong correlations between Δ T and Δ m, Δ m = (2.91 ± 0.66) × 10−4ΔT + (0.08 ± 0.009), with r = 0.52, p = 5.33 × 10−5. (4) There are intra-day periods in this source, with the period P ≈ 94 min on 2017 December 10. When we supplement the observations from the literature, we can obtain that the long-term period is about 12.02 ± 0.41 yr. (5) The spectral properties of OJ 287 show the bluer-when-brighter behavior, whatever state the source is at.
Lunar cratering asymmetries with high lunar orbital obliquity and inclination of the Moon
Authors: Li Hua-Cheng , Zhang Nan , Yue Zong-Yu , Zhang Yi-Zhuo
Published: August 2021

Accurate estimation of cratering asymmetry on the Moon is crucial for understanding Moon evolution history. Early studies of cratering asymmetry have omitted the contributions of high lunar obliquity and inclination. Here, we include lunar obliquity and inclination as new controlling variables to derive the cratering rate spatial variation as a function of longitude and latitude. With examining the influence of lunar obliquity and inclination on the asteroids population encountered by the Moon, we then have derived general formulas of the cratering rate spatial variation based on the crater scaling law. Our formulas with addition of lunar obliquity and inclination can reproduce the lunar cratering rate asymmetry at the current Earth-Moon distance and predict the apex/ant-apex ratio and the pole/equator ratio of this lunar cratering rate to be 1.36 and 0.87, respectively. The apex/ant-apex ratio is decreasing as the obliquity and inclination increasing. Combining with the evolution of lunar obliquity and inclination, our model shows that the apex/ant-apex ratio does not monotonically decrease with Earth-Moon distance and hence the influences of obliquity and inclination are not negligible on evolution of apex/ant-apex ratio. This model is generalizable to other planets and moons, especially for different spin-orbit resonances.
Revisiting pulsar velocities using Gaia Data Release 2
Authors: Yang Meng , Dai Shi , Li Di , Tsai Chao-Wei , Zhu Wei-Wei , Zhang Jie
Published: August 2021

Precise measurements of neutron star (NS) velocities provide critical clues in regard to the supernova physics and evolution of binary systems. Based on Gaia Data Release 2 (DR2), we selected a sample of 24 young (< 3 Myr) pulsars with precise parallax measurements and measured the velocity of their local standard of rest (LSR) and the velocity dispersion among their respective local stellar groups. The median velocity difference between thus calculated LSRs and the Galactic rotation model is ∼ 7.6 km s−1, small compared to the typical velocity dispersion of ∼ 27.5 km s−1. For pulsars off the Galactic plane, such differences grow significantly to as large as ∼40 km s−1. More importantly, the velocity dispersion of stars in the local group of low-velocity pulsars can be comparable to their transverse velocities, suggesting that the intrinsic velocities of NS progenitors should be taken into account when we consider their natal kicks and binary evolution. We also examined the double NS system J0737–3039A/B, and measured its transverse velocity to be

26

−
13

+
18

km s−1 assuming nearby Gaia sources are representative of their birth environment. This work demonstrated the feasibility and importance of using Gaia data to study the velocity of individual systems and velocity distribution of NSs.
Stellar activity cycles as revealed by long-term beat-like patterns from light curves of Kepler
Authors: Han Heng-Geng , Cui Kai-Ming , Liu Ji-Feng , Yang Hui-Qin , Fang Xuan , Zhao Rui-Ning
Published: August 2021

Stellar activity cycles have been found on many stars through different methods. Although in debate, an empirical relation has been found where a period of stellar activity cycle P
cyc is positively correlated with rotation period P
rot along some segregated branches. In this work, we built a systematic process to search for the Kepler objects that are analogous to the long-term solar brightness variations and investigate their possible origins. After a rigorous selection, we obtained 43 objects that all exhibit clear long-term beat-like patterns and their variability (amplitude of rotational modulation) periods and rotation periods were derived. Due to the 4-year duration of the Kepler mission, our targets are located in the region where the cycle periods are longer than ∼1 yr and shorter than ∼2.5 yr. However, all of our targets exhibit clear and notable quasi-periodic variations in variability, yet we cannot confirm any linear trends that were predicted by previous research independently. This may suggest that in the Kepler realm of the P
cyc–P
rot diagram, these relations would mix with each other or the beat-like patterns may not be related to the stellar cycle unless other evidence is provided.
Three pulsars discovered by FAST in the globular cluster NGC 6517 with a pulsar candidate sifting code based on dispersion measure to signal-to-noise ratio plots
Authors: Pan Zhichen , Ma Xiao-Yun , Qian Lei , Wang Lin , Yan Zhen , Luo Jin-Tao , Ransom Scott M. , Lorimer Duncan R. , Jiang Peng
Published: August 2021

We report the discovery of three new pulsars in the globular cluster (GC) NGC 6517, namely NGC 6517 E, F and G, made with the Five-hundred-meter Aperture Spherical radio Telescope (FAST). The spin periods of NGC 6517 E, F and G are 7.60 ms, 24.89 ms and 51.59 ms, respectively. Their dispersion measures are 183.29, 183.713 and 185.3 pc cm−3, respectively, all slightly larger than those of the previously known pulsars in this cluster. The spin period derivatives are at the level of 1 × 10 – 18 s s−1, which suggests these are recycled pulsars. In addition to the discovery of these three new pulsars, we updated the timing solutions of the known isolated pulsars, NGC 6517 A, C and D. The solutions are consistent with those from Lynch et al. but with smaller timing residuals. From the timing solution, NGC 6517 A, B (position from Lynch et al.), C, E and F are very close to each other on the sky and only a few arcseconds from the optical core of NGC 6517.With currently published and unpublished discoveries, nine pulsars have been discovered in NGC 651, ranking it 6th for GCs with the most known pulsars. The discoveries take advantage of the high sensitivity of FAST and a new algorithm used to check and filter possible candidate signals.
Statistical investigation on the formation of sunspot light bridges
Authors: Li Fu-Yu , Chen Yu-Hao , Song Yong-Liang , Hou Zhen-Yong , Tian Hui
Published: August 2021

Light bridges (LBs) are bright lanes that divide one sunspot umbra into two or more parts. Though frequently observed in sunspots, their formation mechanisms have rarely been studied and thus are not well understood. Here we present results from the first statistical investigation on the formation of LBs. Using observations with the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory, we identified 144 LBs within 71 active regions (ARs) over the whole year of 2014. The formation processes of these LBs can be categorized into three groups: penumbral intrusion (type-A), sunspot merging (type-B) and umbral-dot emergence (type-C). The numbers of events in these three categories are 74, 57 and 13, respectively. The duration of the LB formation process is mostly less than 40 hours, with an average of ∼20 hours. Most LBs have a maximum length of less than 20″. For type-A LBs, we found a positive correlation between the LB length and the duration of the LB formation process, suggesting a similar speed of penumbral intrusion in different sunspots.
CALLISTO facilities in Peru: spectrometer commissioning and observations of type III solar radio bursts
Authors: Rengifo Javier Alonso , Loaiza-Tacuri Verónica , Bazo José , Guevara Day Walter Robert
Published: August 2021

The Astrophysics Directorate of CONIDA has installed two radio spectrometer stations belonging to the e-CALLISTO network in Lima, Peru. Given their strategic location near the Equator, it is possible to observe the Sun evenly throughout the whole year. The receiver located at Pucusana, nearby the capital city of Lima, took data from October 2014 until August 2016 in the metric and decimetric bands looking for radio bursts. During this period, this e-CALLISTO detector was unique in its time-zone coverage. To asses the suitability of the sites and the performance of the antennas, we analyzed the radio ambient background and measured their radiation pattern and beamwidth. To demonstrate the capabilities of the facilities for studying solar dynamics in these radio frequencies, we have selected and analyzed type III Solar Radio Bursts. The study of this kind of burst helps to understand the electron beams traversing the solar corona and the solar atmospheric density. We have characterized the most common radio bursts with the following mean values: a negative drift rate of –25.8 ± 3.7 MHz s−1, a duration of 2.6 ± 0.3 s and 35 MHz bandwidth in the frequency range of 114 to 174 MHz. In addition, for some events, it was possible to calculate a global frequency drift which on average was 0.4 ± 0.1 MHz s−1.
Analysis of alcohol abuse using improved artificial intelligence methods
Authors: Kumari D , Swetapadma A
Published: August 2021

In this work, artificial intelligence (AI) based method has been proposed for analysis of alcohol abuse (AA) to evaluate drug risk and find an optimal method for analysis of AA. To detect alcohol abuse, twelve input features are selected. As the number of positive classes and negative classes are imbalanced, input features are processed using synthetic minority oversampling technique (SMOTE). The selected input features are given to the AI based method to predict whether an individual uses alcohol or not. Three AI methods (logistic regression, Naïve Bayes and gradient boost) have been used from which the most suitable method is chosen as optimal method for analysis of AA. Methods used for validation of the proposed AI based method are leave one out cross validation and test sample estimate. Among the three methods used, gradient boost method performs better than other method. Gradient Boost based AI method has 97.55% accuracy to predict alcohol user. Significant achievement of the proposed work is that the accuracy (nearly 97%) to detect alcohol abuse is much more than previously (nearly 70%) suggested methods. This is due to the efficient design of AI method implemented in this work. All the feature processing work and AI algorithm design work has been done using python software.
Construction and characterization of a solar refrigeration system based on nano-graphene
Authors: Subramanian K R V , Raghu Vamshi Krishna B. V. , Nageswara Rao T
Published: August 2021

In this present work, we designed and fabricated a solar refrigeration system with increase in its performance compared to present refrigeration system by using different components (solar cell and Peltier module). The construction of the Peltier module was done using nano-graphene composite and its thermoelectric property was utilized for making the hot and cold junctions. A graphene composite material monolith was synthesized using solid state fabrication techniques and this constituted the junction of the Peltier module. A maximum coefficient of performance (COP) of 8.86 was achieved. ZT factor of graphene composite thermoelectric material can be further increased through modification in processing techniques and defect engineering. This will in turn increase the refrigeration COP further.
Twitter bot detection using supervised machine learning
Authors: Ramalingaiah A , Hussaini S , Chaudhari S
Published: August 2021

In the world of Internet and social media, there are about 3.8 billion active social media users and 4.5 billion people accessing the internet daily. Every year there is a 9% growth in the number of users and half of the internet traffic consists of mostly bots. Bots are mainly categorized into two categories: good and bad bots; good bots consist of web crawlers and chat bots whereas bad bots consist of malicious bots which make up 20% of the traffic, the reason they are not good is that they are used for nefarious purposes, they can mimic human behavior, they can impersonate legal traffic, attack IoT devices and exploit their performance. Among all these concerns, the primary concern is for social media users as they represent a large group of active users on the internet, they are more vulnerable to breach of data, change in opinion based on data. Detection of such bots is crucial to prevent further mishaps. We use supervised Machine learning techniques in this paper such as Decision tree, K nearest neighbors, Logistic regression, and Naïve Bayes to calculate their accuracies and compare it with our classifier which uses Bag of bots’ word model to detect Twitter bots from a given training data set.
Latest trend in building construction: three-dimensional printing
Authors: Babbar Atul , Rai Aryan , Sharma Ankit
Published: August 2021

Today world is looking towards additive manufacturing as a solution for sustainability in the construction business, one of which is three-dimensional printing that involves creating a three-dimensional (3-D) object by printing layer by layer developed digitally. Nowadays, 3-D printers have evolved so much that they can create a whole house from a pin. This technology is not only cost and time effective but also speeds up the construction rate with reduced power, material consumption, and hence reduced waste in building construction. The scope, elements, and classification of 3D printing has been discussed to highlight the work done by past researchers. This paper reviews the elements, merits, and demerits of using 3D printing in construction and evaluates it as a promising technique for sustainable development.
Simulation studies of three types of inverted pendulums via FOPID and PID controller
Authors: Kumar S , Ajmeri M
Published: August 2021

The inverted pendulum systems are very important problem in control literature and frequently studied. A simple and effective controller design is preferred for controlling a complex system. In this work, mathematical model of three types of inverted pendulums are derived depending upon their dynamics. Further, a fractional order PID (FOPID) controller is designed and applied for controlling and stabilizing the three types of inverted pendulums. The proposed fractional order controller is based on the fractional calculus and it is a robust controller. The responses of the pendulum system with FOPID are compared with the responses with conventional PID controllers. The overall performance of the FOPID controller is better than the conventional PID and the results are robust to the outer fast and large disturbances also.
Mechanical and Tribological behaviour of velocity oxygen fuel thermal spray coating: A Review
Authors: Jha Shivani , Mishra R.S.
Published: August 2021

For over decades thermal spraying has been present and optimized over the time and now it has become an effective method to thick coating deposition. Thermal spray coating especially high velocity oxygen fuel (HVOF) have served various industrial sector such as aerospace, defence and thermal electricity generation. To overcome disadvantages of traditional coating there was a need of smart coating process which could integrate new functionalities and coherent responses. The aim of this paper is to present a detailed review of current technological changes in HVOF thermal spray coatings. This paper gives insight view of different type of coatings on substrates, their mechanical and tribological properties. HVOF coating categorised according to various application sector has also been discussed in this paper.
Influenza prediction from social media texts using machine learning
Authors: Singh Sandeep , Kaur Harjot
Published: August 2021

The monitor and prediction of influenza through conventional modes seem obsolete in the Internet era. The flu prediction using machine learning methods is more resourceful for both economically as well as logistically, than traditional methods. The machine learning methods exploit freely available data on social media platforms. The main objective of this paper is to harness the power of publicly available data through machine learning methods. This work involves the scraping of textual data from six social media platforms and training of five machine learning predictors. The paper also proposes a three-layered prediction method based on support-vector-regression for predicting trends of influenza spread. The results obtained from proposed model are validated and analysed against other four machine learning methods. The results reveal that proposed model has better predictive accuracy in terms of least prediction errors among the five methods. Thus, it can provide effective means to control and to prevent the flu outbreak.
Analysis of the quasi-stability of kinematic parameters for manipulators system during the docking process using the Digital Twin approach
Authors: Jędrzejowski M , Błachowicz T , Krafczyk W , Pyka W , Tokarczyk O , Chudy M , Bzymek A. , Sokół Z , Ehrmann A
Published: August 2021

This study analyzes the acceleration of the arms of a dual system of manipulators that aim to achieve the minimum distance by mimicking the process of approaching spacecraft that are trying to connect. The research was performed simultaneously on a real model and its digital equivalent, in accordance with the Digital Twin (DT) approach. The obtained acceleration values show, for some set sampling times, read out positions and velocities, separate distributed regions of achievable values. The Digital Twin, Digital Shadow (DS) and Digital Model (DM) approaches have recently shown great progress in development, both in academic studies and at industrial level. Along a very wide range of applications, we propose some important issues related to satellite technologies.
A deep learning approach for Indian sign language gestures classification with different backgrounds
Authors: Dhiman R. , Joshi G. , Rama Krishna C.
Published: August 2021

The sign language recognition system recently has drawn the attention of various researchers as there is no universal sign language, moreover, it consists of many patterns and postures. Many methods for extracting features and classifying sign language have been proposed in the literature, most of them are based on machine learning techniques. In this article, a deep learning method has been adopted by designing a Convolution Neural Network (CNN) model to extract the sign language features where for classification softmax layer is used. All alphabets in simple as well as complex backgrounds have been considered, where data is collected from 100 subjects in different lighting conditions. The effect of various optimization techniques (Adam, Sgdm, RMSProp), activation functions (ReLU and Leaky ReLU) for generalization ability is also observed. The proposed approach has succeeded in attaining the testing accuracy of 99.10%, 92.69%, and 95.95% on the Indian sign language dataset with simple, complex backgrounds and on a mixed background scenarios, respectively. The model is also tested on NUS dataset-I, NUS dataset-II, their combination, and achieved the accuracy of 100%, 95.95%, and 97.22% respectively.
Design and Development of an Indian Harmonium with Automatic Bellow Mechanism
Authors: Guin B , Ghar K , Modak N
Published: August 2021

Harmonium is a reed instrument widely used in Indian classical music, utilizing a hand-driven bellow to pump air into the soundbox. The pumped air is released through the metallic reeds producing musical notes. The hand-driven bellow action can be challenging and tiresome for beginners as well as professionals during long practice sessions. This problem can be resolved by automating the bellow. The design process is twofold – 1stis the synthesis of a motor-driven linkage capable of generating the rocker motion of the bellow, and 2ndis to obtain the required specification of the motor that can drive the mechanism. A 4-bar crank-rocker linkage has been synthesized using a modified Freudenstein equation, which allows the bellow to compress and expand in one complete rotation of the motor shaft. The novelty of this work is that the nonlinear dynamics of the harmonium bellow has been modeled using a spring-mass equivalence technique. This helps in accurately predicting the operating force for the bellow, the force transmission through the linkage, and estimating the required motor torque. The final design is simple and ergonomic. Based on the design, a working prototype has been developed at the Machine Elements Laboratory of Jadavpur University.
Gar-Bot: Garbage Collecting and Segregating Robot
Authors: Gupta Shreya , Kruthik H M , Hegde Chaya , Agrawal Shreya , Bhanu Prashanth S B
Published: August 2021

This paper presents the design and development of the first prototype of an automated garbage collection robot (Gar-Bot). It operates efficiently in an indoor environment. Main functionality of the robot is to detect and classify the garbage into 3 types, and collect them in different bins. To efficiently use the space in the bin, plastics are crushed after collection. Gar-Bot uses convolutional neural networks implemented on NVIDIA’s Jetson Nano Developer Kit for garbage detection and classification. The IoT platform is used to notify the user with the status of the bin. The robot is equipped with a robotic manipulator, rotating bin for collecting garbage, Kinect V1, Processor and controller, and a base with wheels to facilitate navigation. The robot successfully detected and classified the garbage into various classes at an inference time of 5 seconds per frame, with an accuracy of 90 percent.
A study on influence of eco-friendly technologies in hospitality industry
Authors: Xess Anjali , Bhargave Harshita , Kumar Praveen
Published: August 2021

The Hospitality sector contributes initiatives taken towards the eco-friendly environment and faces lots of challenges towards customer satisfaction and repeat business. With a new modernization of market segments, technology awareness, customers are getting advancement in the field of technology. They are conscious about their health and environment, which is why the hospitality industry needs to pay attention to the customer’s and employee’s health and environment. Promoting eco-friendly technologies by the hospitality industry is useful in both the ways for the customers and sustainability for the environment by adopting the three Rs i.e. reduce, reuse, and recycle. The guests are also getting sensitive about environmental issues. The hospitality industry, therefore, strives to involve them in sustaining the mission of three Rs, which is good for the environment, customer, employee health and the hotel. This research paper aims to discover customer’s behavior, attitude, and level of satisfaction derived from the green technological approach of the hospitality industry and also to understand the level of satisfaction of the employee towards the Eco-Friendly technologies in the hospitality industry in terms of the employee engaging with eco-friendly hotels for the longer period.
Intellectual Tool to Compute Embodied Energy and Carbon Dioxide Emission for Building Construction Materials
Authors: Mukherjee Abhilash , Sumit  , Deepmala  , Dhiman Vishal Kumar , Srivastava Prateek , Kumar Ajay
Published: August 2021

Every material has its capacity to consume energy called embodied energy (EE) and to emit CO2 during the manufacturing process. The estimation procedure of EE and CO2 emission is predominantly based on the existing case examples from various nations across the globe. There is an impressive aperture in instances from developing nations concerning an appraisal of embodied energy and emission of CO2 for used building construction materials. The available tools are also not much user friendly and hence not everyone is capable to use it easily. From this point of view, this research aims to develop an intellectual tool to find out embodied energy and CO2 emission for building materials. This research presents a model for estimation of EE and emission of CO2 (E4-Model) for various building materials used in construction. This research focuses on construction of building in the Indian Construction Section. For the assessment of EE and CO2 emission, the concept of Convolutional Neural Network (CNN) is used and all the values are by weight of material. From the experimental analysis, it is observed that the estimation accuracy of the system is more than 99.62% for small as well as large buildings. The research concluded that the use of CNN is far better than the artificial neural networks in terms of system response time and complexity to estimate the EE and CO2 emission rates. In the research proposed E4-Model is applied and developed using the concept of deep learning and curve-fitting toolboxes within MATLAB Software. The actual emission for all the tested projects were found to be lesser than the estimated emission. The tool developed using CNN proved to work with high accuracy.
Experimental Analysis of Various Materials on Custom-Fit Ankle Foot Orthosis
Authors: Pandey Richa , Singh Rahul
Published: August 2021

Traditional Ankle Foot Orthoses (AFOs) is designed to work for different range of patients. They could not perform comfortable orthotic function arising due to individual differences. This problem can be solved by custom fit AFO’s but the current method involves a lot of manual labor. Rapid Prototyping and reverse engineering can be used on 3-D parts or models designed in CAD software to solve the problem. Through the help of 3-D scanning, customized AFO’s is designed to an individual foot’s anatomy. The scanned data was used to design an AFO structure. The designed structure was virtually tested for different materials and an analysis of the same was done.
Cardiovascular Disease Detection using Artificial Immune System and other Machine Learning Models
Authors: Gupta Ishan , Shangle Ruchir , Latiyan Vishwas , Soni Umang
Published: August 2021

Researchers and medical institutions face problems in detecting and diagnosing cardiovascular diseases in the early stages. Therefore, having a tool for detecting cardiovascular diseases in early stages will be helpful for the medical institutions to combat the disease. In this paper, we have presented a solution for detection of cardiovascular diseases by using clonal selection algorithm. Clonal selection is an Artificial Immune system (AIS) based algorithm which is often used for pattern recognition problems. Here, we propose modified clonal selection algorithm (CLONALG) which effectively detects cardiovascular diseases. With the proposed algorithm, we have achieved an average accuracy of 78%. Further, we compared the accuracy of CLONALG algorithm with different models of Machine Learning, viz. Random Forest Classifier (RFC), Decision Tree Classifier (DTR), Support Vector Machines (SVM), Logistic Regression (LR) and Artificial Neural Networks (MLP-ANN) for cardiovascular disease detection.
Factors influencing environmental perception: A Systematic Review
Authors: Shynu R.V , Santhosh Kumar K.G , Sambath R.D
Published: August 2021

This paper is a systematic meta-analysis based on selected empirical studies to evaluate human-environmental perception. The research concentrates on Eye-tracking technology, electroencephalograph (EEG), electrocardiograph (ECG), and electrodermal activity (EDA). This study investigates the realm of human cognition and its engagement towards the environment. Nevertheless, the studies focus on the factors that enhance human perception towards the surrounding environment by exploring virtual reality. Methods of the review follow systematic meta-analysis guidelines. Meta-analysis is conducted from selected empirical articles, aligned with research questions, published in journals between 2005 and 2020 in the English language. ProQuest, MDPI, PubMed, and Google scholar are the Electronic databases used to extract research works till September 2020 for data analysis. The study analyses the scope for further research using multivariable investigation in the domain of human visual perception. Future explorations could focus on factors such as Semi Immersive technology, the Elderly category, and Color-based influence. Result also suggest the necessity of exploring EEG and Eye-tracking technology in the domain of environmental perception. This work would be a reference for the psycho-physiological researchers on human-environment studies.
Parametric Study of Laser Welding on Polyamide using Design of Experiments
Authors: Girish Kumar R , Narasimha Murthy H N , Anand B , Jabiulla Syed
Published: August 2021

Laser welding was primarily employed for metals but recent developments in laser technology have enabled its applications in the polymers field. Laser transmission welding or joining of two polymers and metal-polymer has become feasible. The study was mainly aimed to investigate the influence of laser power, speed of welding, and number of passes based on Taguchi orthogonal array on responses by using continuous mode high power diode fiber laser on polyamide. The weld quality was assessed by measuring the strength of weld and width of the weld seam. Initial study on diode fiber laser welding machine and the parameters associated with it was essential to design the experimental layout. Polyamide, which is widely used in the automotive industry was selected as the material and the influence of various parameters on the laser welds were studied using design of experiments. The experimental studies were performed based on orthogonal array method. The responses of the weld were measured using an optical metallurgical microscope. The ideal parameters for maximum joint strength and minimum weld width are investigated using Taguchi method. The multi-objective optimization has been done by applying grey relational analysis to identify the levels of factors that result in the maximum strength and minimum weld seam width.
Experience with advanced welding techniques (RMD & P-GMAW) with seamless metal cored wire for Oil & Gas pipeline industries
Authors: Das Subhash , Vora Jaykumar , Patel Vivek , Bogum Surender
Published: August 2021

Regulated Metal Deposition (RMD™) process is a variant of Gas metal arc welding process (GMAW), which was developed with the aim to effectively control the metal transfer in the short-circuiting mode. The process is fundamentally a modified short-circuit GMAW process wherein a uniform droplet deposition, making it easier for the welder to control the puddle and hence achieve an enhanced quality of welded joints. In the present study, RMD technique has been established for API grade pipe (API 5L PSL2 X70 grade) particularly for depositing the root pass on 24” OD and 10.3 mm thick pipe. In addition to this, the RMD technique is tried for the first time with seamless metal cored wires (Megafill 240 M) in order to enhance the deposition rates in Indian Oil & Gas pipeline industry. The joint fill up is further attempted with pulsed GMAW technique using metal cored wires and further analysed. The weldments were tested by mechanical characterization. Mechanical characterization such as tensile properties, impact properties, bend test as well as all weld tensile properties of the weld joint were evaluated and found to be acceptable. A techno-commercial evaluation of the technique was carried out vis-à-vis conventional welding techniques such as SMAW process for root passes and Fill & Cap. It was found the proposed technique was cost effective as well as reliable. One of the inherent benefits of the RMD and Pulse GMAW technique is the reduction in the overall heat input of the welded joint imparting superior mechanical properties. The use of metal cored wires also established the proposed technique as a potential technique for heavy thick weldments by enhancing the overall productivity.
Out Domain Data Augmentation on Punjabi Children Speech Recognition using Tacotron
Authors: Hasija Taniya , Kadyan Virender , Guleria Kalpna
Published: August 2021

The performance of Automatic Speech Recognition (ASR) is directly proportional to the quality of the corpus used and the training data quantity. Data scarcity and more children’s speech variability degrades the performance of ASR systems. As Punjabi is a tonal language and low resource language, less data is available for Punjabi children’s speech. It leads to poor ASR performance for Punjabi children speech recognition. To overcome limited data conditions, in this paper, two corpora of different domains are evaluated for testing the feasibility of ASR performance. We have implemented Tacotron as an artificial speech synthesis system for Punjabi Language. The speech audios synthesized by Tacotron are merged with available speech corpus and tested on Punjabi children ASR using Mel Frequency Cepstral Coefficients (MFCC) + pitch feature extraction, and Deep Neural Network (DNN) acoustic modeling. It is noticed that the merged data corpus has shown reduced Word Error Rate (WER) of the ASR system with a Relative Improvement (RI) of 9-12%.