bluuebunny/crossref_metadata_2025 huggingface dataset:
In vitro antioxidant and antibacterial activities of phenolic and alkaloid extracts of Laurus nobilis
Authors: Khodja Yazid Khaled , Bachir-bey Mostapha , Ladjouzi Rachid , Katia Djenadi , Khettal Bachra
Published: May 2021

Laurus nobilis one of medicinal and aromatic plant endemic to the Mediter-ranean region. It is highly appreciated for the condiment benefits of its leaves. Due to its richness in bioactive compounds, the leaves are also used in traditional therapy to treat several infectious diseases. Phenolic com-pounds and alkaloids are particularly important because they are used in many pharmaceutical, food supplement, and cosmetic fields. The presence of phenolic compounds and alkaloids in L. nobilis leaves attracted our atten-tion due to their various functions such as antioxidant capacity and antibac-terial properties. The main objective of this study was to determine antioxi-dant and antibacterial activities of phenolic and alkaloid extracts of L. nobilis. The quantification of antioxidant substances allowed obtaining phenolic compounds content of 86.46 EAG mg/g and a total alkaloids yield of 700 μg/g. The results of antioxidant activity show that, although the alkaloid concen-trations are low, their antioxidant power is higher than phenolic compounds. The results of antibacterial activity of L. nobilis extracts revealed that the highest inhibition was recorded for alkaloid extract against staphylococcal strains responsible for food poisoning. However, L. nobilis phenolic com-pounds showed better activity against phytopathogenic strains associated particularly with potato rot.
Key Factors Fuelling India's Second COVID Surge
Authors: Chakravorty Indranil
Published: May 2021

Having declared in autumn of 2020, that India had defeated Coronavirus, the steep rise of cases in April-May 2021, caught the authorities unawares. The health care infrastructure was rapidly overwhelmed at every level and equally in the national capital, large and small cities and the vast rural populace. The human catastrophe that was unfolding in front of the digitally connected world was heart-breaking.
The natural ingredients of a battered economy (-23.9% GDP), a large populace (1.34 billion), poor public health, a chronic epidemic of diseases such as tuberculosis, diabetes, hypertension or kidney disease, chronic underfunding of healthcare infrastructure (1.8% of GDP), deficiency of healthcare workforce (estimated deficit of 600,000 doctors and 2 million nurses) and disjointed, disordered leadership combined with an incoherent, incohesive healthcare policy led to the disaster.
After relative stabilisation from the first few weeks of the impact of colossal lack of hospital beds, oxygen, supported ventilation, life-saving drugs, safe and dignified disposal of the dead, and any form of coordinated disaster response, there is now the new epidemic of the black fungus. This editorial explores the emergence of this new health challenge for India and issues a call to rally.
The Geometry of Cold, Metal-enriched Gas around Galaxies at z ∼ 1.2
Authors: Lundgren Britt F. , Creech Samantha , Brammer Gabriel , Kirse Nathan , Peek Matthew , Wake David , York Donald G. , Chisholm John , Erb Dawn K. , Kulkarni Varsha P. , Straka Lorrie , Tremonti Christy , van Dokkum Pieter
Published: May 2021

We present the first results from a Hubble Space Telescope Wide Field Camera 3/Infrared program, which obtained direct imaging and grism observations of galaxies near quasar sightlines with a high frequency of uncorrelated foreground Mg ii absorption. These highly efficient observations targeted 54 Mg ii absorbers along the line of sight to nine quasars at z
(qso ∼ 2. We find that 89% of the absorbers in the range of 0.64 < z < 1.6 can be spectroscopically matched to at least one galaxy with an impact parameter of less than 200 kpc and ∣Δz∣/(1 + z) < 0.006. We have estimated the star formation rates and measured structural parameters for all detected galaxies with impact parameters in the range of 7–200 kpc and star formation rates greater than 1.3 M
⊙ yr−1. We find that galaxies associated with Mg ii absorption have significantly higher mean star formation rates and marginally higher mean star formation rate surface densities compared to galaxies with no detected Mg ii. Nearly half of the Mg ii absorbers match more than one galaxy, and the mean equivalent width of the Mg ii absorption is found to be greater for groups, compared to isolated galaxies. Additionally, we observe a significant redshift evolution in the physical extent of Mg ii-absorbing gas around galaxies and evidence of an enhancement of Mg ii within 50° of the minor axis, characteristic of outflows, which persists to 80 kpc around the galaxies, in agreement with recent predictions from simulations.
Optical Analysis and Modeling of HD96670, a New Black Hole X-Ray Binary Candidate
Authors: Gomez Sebastian , Grindlay Jonathan E.
Published: May 2021

We report on optical observations and modeling of HD96670, a single-line spectroscopic binary in the Carina OB2 association. We collected 10 epochs of optical spectroscopy, and optical photometry on 17 nonconsecutive nights on the source. We construct a radial velocity curve from the spectra, and update the orbital period of the binary to be P = 5.28388 ± 0.00046 days. The spectra show oxygen and helium absorption, consistent with an O-type primary. We see no evidence for spectral lines from the secondary star in the binary. We model the optical light curve and radial velocity curve simultaneously using the Wilson–Devinney code and find a best-fit mass of

for the primary, and

for the secondary. An object of this mass is consistent with either a B-type star, or a black hole. Given that we see no absorption lines from the secondary, in combination with an observed hard power-law X-ray spectrum with Γ = 2.6 detected past 10 keV that may have been produced by wind accretion onto the secondary, we conclude that the secondary is most likely a black hole. We see asymmetrical helium lines with a shape consistent with the presence of a third star. If the secondary is indeed a black hole, this system would add to the small sample of only four possible black hole high mass X-ray binaries in the galaxy.
Magnetofrictional Modeling of an Erupting Pseudostreamer
Authors: Karna Nishu , Savcheva Antonia , Gibson Sarah , Tassev Svetlin , Reeves Katharine K. , DeLuca Edward E. , Dalmasse Kévin
Published: May 2021

In this study, we present the magnetic configuration of an erupting pseudostreamer observed on 2015 April 19, on the southwest limb of the Sun, with a prominence cavity embedded inside. The eruption resulted in a partial halo coronal mass ejection. The prominence eruption begins with a slow rise and then evolves to a fast-rise phase. We analyze this erupting pseudostreamer using the flux-rope insertion method and magnetofrictional relaxation to establish a sequence of plausible out-of-equilibrium magnetic configurations. This approach allows the direct incorporation of observations of structures seen in the corona (filament and cavity) to appropriately model the pseudostreamer based on SDO/HMI line-of-sight photospheric magnetograms. We also perform a topological analysis in order to determine the location of quasiseparatrix layers (QSLs) in the models, producing Q-maps to examine how the QSL locations progress in the higher iterations. We found that the axial flux in our best-fit unstable model was a factor of 20 times higher than we found in our marginally stable case. We computed the average magnetic field strength of the prominence and found that the unstable model exhibits twice the average field strength of the stable model. The eruption height from our modeling matches very well with the prominence eruption height measured from the AIA observation. The Q-maps derived from the model reproduce structures observed in LASCO/C2. Thus, the modeling and topological analysis results are fully consistent with the observed morphological features, implying that we have captured the large magnetic structure of the erupting filament in our magnetofrictional simulation.
Star Formation Histories from Spectral Energy Distributions and Color–magnitude Diagrams Agree: Evidence for Synchronized Star Formation in Local Volume Dwarf Galaxies over the Past 3 Gyr
Authors: Olsen Charlotte , Gawiser Eric , Iyer Kartheik , McQuinn Kristen B. W. , Johnson Benjamin D. , Telford Grace , Wright Anna C. , Broussard Adam , Kurczynski Peter
Published: May 2021

Star formation histories (SFHs) reveal physical processes that influence how galaxies form their stellar mass. We compare the SFHs of a sample of 36 nearby (D ⪅ 4 Mpc) dwarf galaxies from the ACS Nearby Galaxy Survey Treasury (ANGST), inferred from the color–magnitude diagrams (CMDs) of individually resolved stars in these galaxies, with those reconstructed by broadband spectral energy distribution (SED) fitting using the dense basis SED-fitting code. When comparing individual SFHs, we introduce metrics for evaluating SFH reconstruction techniques. For both the SED and CMD methods, the median normalized SFH of galaxies in the sample shows a period of quiescence at lookback times of 3–6 Gyr followed by rejuvenated star formation over the past 3 Gyr that remains active until the present day. To determine if these represent special epochs of star formation in the D <4 Mpc portion of the Local Volume, we break this ANGST dwarf galaxy sample into subsets based on specific star formation rate and spatial location. Modulo offsets between the methods of about 1 Gyr, all subsets show significant decreases and increases in their median normalized SFHs at the same epochs, and the majority of the individual galaxy SFHs are consistent with these trends. These results motivate further study of potential synchronized star formation quiescence and rejuvenation in the Local Volume as well as development of a hybrid method of SFH reconstruction that combines CMDs and SEDs, which have complementary systematics.
Searching for Local Counterparts of High-redshift Poststarburst Galaxies in Integral Field Unit Spectroscopic Surveys of Nearby Galaxies
Authors: Wu 吳柏 Po-Feng 鋒
Published: May 2021

Searching in the MaNGA IFU survey, I identify nine galaxies that have strong Balmer absorption lines and weak nebular emission lines measured from the spectra integrated over the entire IFU. The spectral features measured from the bulk of the stellar light make these galaxies local analogs of high-redshift spectroscopically selected poststarburst galaxies and thus proxies to understand the mechanisms producing poststarburst galaxies at high redshifts. I present the distributions of absorption line indices and emission line strengths, as well as the stellar kinematics of these local poststarburst galaxies. Almost all local poststarburst galaxies have central compact emission line regions at the central <1 kpc, mostly powered by weak star formation activities. The age-sensitive absorption line indices EW(Hδ) and D
n
4000 indicate that the stellar populations at the outskirts are older. Toy stellar population synthesis models suggest that the galaxies as a whole are experiencing a rapid decline of star formation with residual star formation activities at the centers. These features indicate that most poststarburst galaxies are the aftermath of highly dissipative processes that drive gas into centers, invoke centrally concentrated star formation, and then quench the galaxies. Meanwhile, when measurable, poststarburst galaxies have the directions of maximum stellar velocity gradients aligned with photometric major axes, which suggest against major mergers being the principal driving mechanism, while gas-rich minor mergers are plausible. While directly obtaining the same quality of spatially resolved spectra of high-redshift poststarburst galaxies is very difficult, finding proper local counterparts provides an alternative to understand quenching processes in the distant universe.
Evidence for an MHD Disk Wind via Optical Forbidden Line Spectroastrometry*
Authors: Whelan E. T. , Pascucci I. , Gorti U. , Edwards S. , Alexander R. D. , Sterzik M. F. , Melo C.
Published: May 2021

Spectroastrometry is used to investigate the low-velocity component (LVC) of the optical forbidden emission from the T Tauri stars RU Lupi and AS 205 N. Both stars also have high-velocity forbidden emission, which is tracing a jet. For AS 205 N, analysis reveals a complicated outflow system. For RU Lupi, the [O i] λ6300 and [S ii]λλ6716,6731 LV narrow component (NC) is offset along the same position angle (PA) as the high-velocity component but with a different velocity gradient than the jet, in that displacement from the stellar position along the rotation axis is decreasing with increasing velocity. From the LVC, NC, PA, and velocity gradient, it is inferred that the NC is tracing a wide-angled magnetohydrodynamic (MHD) disk wind. A photoevaporative wind is ruled out. This is supported by a comparison with a previous spectroastrometric study of the CO fundamental line. The decrease in offset with increasing velocity is interpreted as tracing an increase in the height of the wind with increasing disk radius. This is one of the first measurements of the spatial extent of the forbidden emission line LVC NC (∼40 au, 8 au for RU Lupi in the [S ii] λ6731 and [O i] λ6300 lines) and the first direct confirmation that the LVC narrow component can trace an MHD disk wind.
A New Fast Monte Carlo Code for Solving Radiative Transfer Equations Based on the Neumann Solution
Authors: Xiao-lin Yang , Jian-cheng Wang , Chu-yuan Yang , Zun-li Yuan
Published: May 2021

In this paper, we propose a new Monte Carlo radiative transport (MCRT) scheme, which is based completely on the Neumann series solution of the Fredholm integral equation. This scheme indicates that the essence of MCRT is the calculation of infinite terms of multiple integrals in the Neumann solution simultaneously. Under this perspective, we redescribe the MCRT procedure systematically, in which the main work amounts to choosing an associated probability distribution function for a set of random variables and the corresponding unbiased estimation functions. We select a relatively optimal estimation procedure that has a lower variance from an infinite number of possible choices, such as term-by-term estimation. In this scheme, MCRT can be regarded as a pure problem of integral evaluation, rather than as the tracing of random-walking photons. Keeping this in mind, one can avert some subtle intuitive mistakes. In addition, the δ functions in these integrals can be eliminated in advance by integrating them out directly. This fact, together with the optimal chosen random variables, can remarkably improve the Monte Carlo (MC) computational efficiency and accuracy, especially in systems with axial or spherical symmetry. An MCRT code, Lemon (Linear integral Equations’ Monte carlo solver based On the Neumann solution; the code is available on the GitHub codebase at https://github.com/yangxiaolinyn/Lemon, and version 2.0 is archived on Zenodo at https://doi.org/10.5281/zenodo.4686355), has been developed completely based on this scheme. Finally, we intend to verify the validation of Lemon; a suite of test problems mainly restricted to a flat spacetime has been reproduced, and the corresponding results are illustrated in detail.
The GBT Diffuse Ionized Gas Survey (GDIGS): Survey Overview and First Data Release
Authors: Anderson L. D. , Luisi Matteo , Liu Bin , Wenger Trey V. , Balser Dana. S. , Bania T. M. , Haffner L. M. , Linville Dylan J. , Mascoop J. L.
Published: May 2021

The Green Bank Telescope (GBT) Diffuse Ionized Gas Survey (GDIGS) traces ionized gas in the Galactic midplane by measuring 4–8 GHz radio recombination line (RRL) emission. The nominal survey zone is 32.°3 > ℓ > − 5°, ∣b∣ < 0.°5, but coverage extends above and below the plane in select fields and additionally includes the areas around W47 (ℓ ≃ 37.°5) and W49 (ℓ ≃ 43°). GDIGS simultaneously observes 22 Hnα (15 usable), 25 Hnβ (18 usable), and 8 Hnγ RRLs (all usable), as well as multiple molecular line transitions (including those of

, H2CO, and CH3OH). Here, we describe the GDIGS survey parameters and characterize the RRL data, focusing primarily on the Hnα data. We produce sensitive data cubes by averaging the usable RRLs, after first smoothing to a common spectral resolution of 0.5 km s−1 and a spatial resolution of 2.′65 for Hnα, 2.′62 for Hnβ, and 2.′09 for Hnγ. The average spectral noise per spaxel in the Hnα data cubes is ∼10 mK (∼5 mJy beam−1). This sensitivity allows GDIGS to detect RRLs from plasma throughout the inner Galaxy. The GDIGS Hnα data are sensitive to emission measures EM ≳ 1100 cm−6 pc, which corresponds to a mean electron density 〈n

e
〉 ≳ 30 cm−3 for a 1 pc path length or 〈n

e
〉 ≳ 1 cm−3 for a 1 kpc path length.
Massive Delayed Hemorrhagic Choroidal Detachment and Giant Retinal Tear Detachment Following Scleral-Fixated Akreos IOL
Authors: Ng Caleb C. , Peng Michelle Y. , McDonald H. Richard
Published: May 2021

A 78-year-old woman underwent 25-gauge pars plana vitrectomy and scleral fixation for a dislocated intraocular lens in the left eye under general anesthesia. She developed massive hemorrhagic choroidal detachment 1 day later. A giant retinal tear detachment and proliferative vitreoretinopathy was noted at postoperative Week 7 and repaired with choroidal drainage, 240° peripheral retinectomy, perfluorocarbon liquid, endolaser, and silicone oil. Hypotony associated with the 25-gauge sclerotomies used for suture fixation was the suspected etiology for this complication. Use of 27-gauge instrumentation or application of fibrin glue to superior sclerotomies may help reduce the incidence of postoperative hypotony.

[
Ophthalmic Surg Lasers Imaging Retina.
2021;52:288–292.]
Zgodbe in prostor
Authors: Šrimpf Vendramin Katarina
Published: May 2021

In her book Zgodbe in prostor ('Stories and Space'), Katarina Šrimpf Vendramin explores and presents the oral tradition of the Upper Sotla Valley along the Slovenian–Croatian border. The first part of the book offers a historical overview of collecting and publishing narrative heritage, and the second part presents contemporary field material and text, texture, and context analysis. The volume highlights the role and importance of literary folklore in the social and cultural life of the region studied. Etiological narratives, historical stories, and tales about mythological creatures are used to present the concepts of the liminal space and time (the chronotope) and the correlation between oral tradition and the formation of collective identities and collective memory. In a border region, narrative tradition is especially important for creating identities—on the one hand, through narratives about the “other” (i.e., that which is different) and, on the other hand, through stories that evoke a feeling of local belonging and establishing a local identity in both the narrator and the audience.
Un estudio de artrópodos epigeos en entornos costeros con influencia urbana cerca de El Altet, sureste de España
Authors: Giraldo-Mendoza Alfredo E.
Published: May 2021

Se realizó un estudio preliminar para caracterizar ensambles de artrópodos epígeos en entornos costeros con influencia urbana cerca de la ciudad de El Altet (Alicante, España), que incluyen duna fija, tomillar, duna móvil y vegetación ruderal. Para ello, se realizó una serie de métricas de diversidad y análisis multivariado con base en un relevamiento realizado desde noviembre de 2004 a marzo de 2005. El hábitat de vegetación ruderal (RV) tuvo mayor abundancia y baja diversidad de artrópodos epigeicos, así como predominio de taxones sinantrópicos, principalmente Dermaptera (Forficulidae) e Isopoda (Armadillidae, Porcellionidae). En contraste, el hábitat de dunas móviles (YD) tuvo abundancia intermedia y baja diversidad, con predominio de coleópteros psamófilos, particularmente Tenebrionidae. Mientras que los hábitats de tomillar y duna fija (HD + GD) tuvieron baja abundancia y alta diversidad, siendo Chrysomelidae y Tenebrionidae nativos sus taxones más representativos.
REFLEXÕES SOBRE ATIVIDADE DE LÍNGUA PORTUGUESA ESCRITA PARA ALUNOS SURDOS
Authors: Steyer Daiana , De Azevedo Fronza Cátia
Published: May 2021

O objetivo deste trabalho é refletir sobre atividade de leitura e escrita da língua portuguesa como segunda língua nos primeiros anos do ensino fundamental em uma escola para surdos localizada na região metropolitana de Porto Alegre. Para a realização desta investigação, foram utilizados dados da pesquisa Língua portuguesa e Libras nos anos iniciais do Ensino Fundamental de 9 anos: rumo ao letramento de surdos[1] coordenada pela Profa. Dra. Cátia Fronza na Unisinos. Para o presente trabalho, foi selecionado um momento em que a língua portuguesa escrita foi trabalhada, durante o ano de 2015, em uma turma de 4° e 5° anos do Ensino Fundamental. Os dados foram coletados pela equipe de pesquisa, por meio de fotos e vídeos. Considerando a comparação entre a fundamentação teórica e a atividade analisada, constata-se que o contexto educacional está organizado de forma que as interações são realizadas pela oralidade, o que faz com que o surdo fique em desvantagem nas articulações entre os saberes na sala de aula. [1] Projeto de pesquisa com o apoio do CNPq Edital 43/2013, processo n. 407692/2013-4.
Intelligent Vision-Based Systems for Public Safety and Protection via Machine Learning Techniques
Authors: B. Rajitha
Published: May 2021

Abnormal behavior detection from on-line/off-line videos is an emerging field in the area of computer vision. This plays a vital role in video surveillance-based applications to provide safety for humans at public places such as traffic signals, shopping malls, railway stations, etc. Surveillance cameras are meant to act as digital eyes (i.e., watching over activities at public places) and provide security. There are a number of cameras deployed at various public places to provide video surveillance, but in reality, they are used only after some incident has happened. Moreover, a human watch is needed in order to detect the person/cause of the incident. This makes surveillance cameras passive. Thus, there is a huge demand to develop an intelligent video surveillance system that can detect the abnormality/incident dynamically and accordingly raise an alarm to the nearest police stations or hospitals as per requirement. If AI-supported CCTV systems are deployed at commercial and traffic areas, then we can easily detect the incidents/crimes, and they can be traced in minimal time.
Impact of Syntactical and Statistical Pattern Recognition on Prognostic Reasoning
Authors: P. Rithesh Pakkala , Rai Prakhyath , Bellipady Shamantha Rai
Published: May 2021

This chapter provides insight on pattern recognition by illustrating various approaches and frameworks which aid in the prognostic reasoning facilitated by feature selection and feature extraction. The chapter focuses on analyzing syntactical and statistical approaches of pattern recognition. Typically, a large set of features have an impact on the performance of the predictive model. Hence, there is a need to eliminate redundant and noisy pieces of data before developing any predictive model. The selection of features is independent of any machine learning algorithms. The content-rich information obtained after the elimination of noisy patterns such as stop words and missing values is then used for further prediction. The refinement and extraction of relevant features yields in performance enhancements of future prediction and analysis.
Promoting a Collegial, Collaborative, and Innovative Teaching and Learning Environment
Authors: Carter Alanna , Fogle Shayne , Seoudi Shereen , Ascenuik Catrina
Published: May 2021

Ryerson University is home to the Real Institute's ESL Foundation Program and was required to adapt programming and curricula for virtual teaching and learning in response to COVID-19. Despite difficulties at the outset, through the collaboration and creativity of a group of curriculum specialists and instructors, best practices regarding course management, assessment design, and program development for the teaching and learning of EAP and ESL curricula across time and space were discovered. The adaptation of curricula and programming for the virtual classroom was made possible due to the collaboration, innovation, and perseverance of instructors, administrative staff, and, of course, students.
Meeting the Needs of Students With Disabilities in Online Learning Environments
Authors: Rutherford Emily N.
Published: May 2021

Online learning environments provide opportunities for students to learn in a flexible manner, regardless of their personal circumstances. These opportunities open the door for many students to have more control over their learning. For students with disabilities, however, the implications are much different. Access to course content and material online can be a major barrier to success for students with disabilities. Making online courses accessible, measuring accessibility, and creating accessible materials and curriculum resources can be daunting tasks for educators, especially those with little to no formal training in special education. This chapter will provide tips developed through the lived experiences of those who work with students who have disabilities to assist educators in successfully meeting the needs of all students in their courses. Consequently, the aim of this chapter is to provide an overview of how to meet the needs of students with disabilities in online learning environments.
Developing and Supporting Mathematics Teacher Educators Through Virtual Collaborations
Authors: Gupta Dittika , Montgomery Mark S. , Eddy Colleen M. , Kalinec-Craig Crystal Anne , Morton Karisma , Hulme Keely , Mahdi Fardowsa
Published: May 2021

This chapter focuses on a group of mathematics teacher educators across the state of Texas that utilized collaboration before and during a global pandemic in order to examine and apply equity issues in their own instruction and delivery of their mathematics methods courses. The authors will highlight and share how the use of collaboration that initiated with the focus on rethinking equity practices in methods courses morphed into a supportive environment that helped the group of mathematics teacher educators through a difficult transition in education due to COVID-19. The goal of the chapter is to urge educators to use collaboration as an impetus for professional development and establishing communities of practice.
An Energy-Efficient Model for Opportunistic Data Collection in IoV-Enabled SC Waste Management
Authors: Ijemaru Gerald K. , Ngharamike Ericmoore T. , Oleka Emmanuel U. , Nwajana Augustine O.
Published: May 2021

Recent advancements in technological research have seen the use of mobile data collectors (MDCs) or data MULEs for wireless sensor network (WSN) applications. In the context of smart city (SC) waste management scenarios, vehicular networks or the internet of Vehicles (IoV) can be exploited as MDCs or data MULEs for data collection and transmission purposes from the sparsely distributed smart sensors that are attached to the smart bins to an access point or sink node and further deployed for waste management operations. A major challenge with the traditional methods of data collection using static sink nodes is the high energy consumption of the sensor-nodes. The use of MDCs has been well studied and shown to be energy efficient. To the best of the authors' knowledge, this scheme has not been exploited for waste management operations in a SC. Compared to the centralized schemes, the data MULE scheme presents several advantages for data collection in WSN applications. This chapter proposes an energy-efficient model for opportunistic data collection in IoV-enabled SC waste management operations.
Development Electronic Design Automation for RF/Microwave Antenna Using MATLAB GUI
Authors: You Kok Yeow
Published: May 2021

This chapter presents the development of a user-friendly MATLAB-based electronic design automation (EDA) tool for RF/microwave antenna design. The development steps of EDA using MATLAB ‘guide' and MATLAB ‘appdesigner' design environments have been explained in detail. In this chapter, seven EDAs of different antennas are developed and described. The EDA is capable of predicting the dimensions of the antenna by inputting the desired operating specifications of the antenna, such as operating frequency. The rigorous analytical formulations that are implemented in this EDA are briefly described. The developed EDAs have simple and standalone guide user interface (GUI) display and fast program running time compared to iterative solution or numerical-based EDAs. The developed EDAs can be packaged and accessed either as standalone desktop app or web app. The accuracy of the EDA output results is validated by comparing to measurement and simulation results obtained from a commercial simulator.
Digital Terrestrial Television Broadcasting in 5G
Authors: K. Chandrakala , Kumari J. Jaya , T. K. Sreeja
Published: May 2021

Digital multimedia broadcasting is a technology for transmitting multimedia signals to devices like mobile phones, PC, laptops, etc. This allows everyone to watch TV on mobile devices. With the fifth-generation network, one can download a movie in a few seconds. Mobile TV offers round-the-clock participation in communication and broadcasting around the globe. This has become possible by watching a live TV program on handheld devices, as it facilitates real-time updates. Digital terrestrial television broadcasting aimed at transmitting two types of information: global and local content. The global content aims at broadcasting over the entire network, and the local content is location specific. Broadcasting the local content using multiple transmitters at different frequencies in multifrequency network requires additional spectrum. Global content can be transmitted through single frequency network. Therefore, if both global and local information are transmitted in a single frequency network (SFN), the system will become highly spectrally efficient and cost-effective.
Investigating the Effects of Temperature, Paste Height, and Time on Solder Paste to Its Printing Performance
Authors: Okafor Patrick Uche , Eke James , Arinze Ndidi Stella , Onah Osondu Ignatius
Published: May 2021

Due to pressure to meet consumer requirements, miniaturization, reliability, and increased functionality have become more important. To achieve good assembly of electronic devices, there must be smooth deposition of tiny and consistent paste deposits on the board which must be up to an acceptable height and volume based on desirable process parameters in the output. The printing performance of the solder paste is dependent on conditions such as paste deformation behavior, good paste roll, complete aperture filling, and paste release onto the substrate pads. Eighteen tests were performed using two types of lead-free solder paste. Three temperatures were investigated under three different time intervals. Results analysis showed that variability of the paste distribution was lowest and more uniform for paste stored at 25˚C for 48 hours. From the analysis, it is obvious that temperature has tremendous effects on the printing performance of solder paste. This study recommends 25˚C as a good temperature for solder paste printing.
Comparative Study of Transmission Line Junction vs. Asynchronously Coupled Junction Diplexers
Authors: Ogbodo Eugene A.
Published: May 2021

A conventional diplexer with a T-junction transmission line is designed in this work and compared with a new approach of designing a diplexer using the asynchronously coupled resonant junction (ACJ). The use of ACJ is to explore its features associated with enhancing the output response of the diplexer as well as its ease in control and implementation of the external couplings at the common port of an all-resonator-base diplexer. The measured and simulated responses of the diplexers were compared, and they agreed with each other.
CLOUDSME
Authors: Otuka Richard
Published: May 2021

Presently, SMEs are finding it difficult to adopt cloud services for their businesses due to various service providers offering similar services. In addition, little work has been carried out in regards to the cloud services adoption process by SMEs. In this chapter, the authors propose CLOUDSME, a novel framework that aids in the adoption process of SaaS cloud services. Accordingly, they implement a decision support system, which includes an ontology of cloud services knowledge within the proposed framework. Analytical hierarchical process (AHP) is used to determine the weight of each cloud service attribute, and a benchmark is set to determine the acceptability of each cloud service based on its ability to meet the acceptable benchmark for each criteria. It can also help in a healthy competition to improve the quality of service among cloud service providers. The CLOUDSME semantic model will guide SME owners in answering user requirements towards decision making in the cloud service adoption process.
Unseen to Seen by Digital Steganography
Authors: Bandyopadhyay Samir Kumar , Goyal Vishal , Dutta Shawni , Pramanik Sabyasachi , Sherazi Hafiz Husnain Raza
Published: May 2021

In this digital era, most of the daily works of users are captured in digital forms like image, audio, video, or even text. These may contain sensitive, confidential, or private information as well. To keep these, there are different techniques exercised over the years like chest, coffer, repository, treasury, etc. Sometimes such ways of hiding information attract unintended users. Therefore, steganography has been applied to digital objects in a new form called digital steganography. This chapter enforces identifying methods in digital steganography. The basic model of any type of digital steganography is composed of three types of objects: cover object, text to be hidden, and stego object. Depending on the type of cover object, different types of digital steganography methods have been defined. Only data hiding in text is discussed.
Advances in Text Steganography Theory and Research
Authors: R. Gurunath , Samanta Debabrata
Published: May 2021

There is an immense advancement in science and technology, and computing systems with the highest degree of security are the present hot topic; however, the domination of hackers and espionage in terms of disclosing the sensitive information are steadily increasing. This chapter presents a theoretical view and critical examination of the few text steganography methods in the contemporary world. It tells the direction in which research has developed over the past few years. Cryptography, the encipherment to a certain extent, protects the data by making it unreadable but not safe. Improvisation of the same can be done using another layer of protection that is steganography in which the secret embedded inside the cover text will not be revealed.
IoT Security Using Steganography
Authors: Majumder Ray Atrayee , Sarkar Anindita , Obaid Ahmed J. , Pandiaraj Saravanan
Published: May 2021

Internet of things (IoT) is one of those emerging technologies, which are going to rule the world in the next few decades. Due to the advancement of low-cost computing systems and mobile technologies, these physical things are now capable of sharing and collecting data with minimal human interference. However, these devices are exposed to various security threats regarding privacy and data confidentiality as they are openly accessible to all in the network. Moreover, many IoT devices have low processing power and weak security level which could be the main targets for hackers. Lightweight cryptographic schemes are used to meet the security needs in IoT environment. Steganography is used as another security tool for IoT devices. This chapter is an attempt to analyze the various steganography techniques used to strengthen the security needs of IoT devices as per their applications. IoT security schemes using different steganography models and algorithms are outlined here with their relative advantages and disadvantages.
Applications of Machine Learning in Steganography for Data Protection and Privacy
Authors: Bartere Mahip M. , Bohra Sneha , Adakane Prashant , Santhosh Kumar B.
Published: May 2021

Data security is one of the most important aspects in today's scenario. Whenever we send our data from source to destination, data protection is one of the prime components. With the help of data hiding and data extraction techniques, we are able to provide the solution of different types of problems whenever we transfer our data. Steganography is a process where we can hide our data and maintain the quality of the image. At the same time, we think about data alteration. With the help of stegtanalysis method, we reverse engineer and extract the original data. In this chapter, data hiding and data extraction techniques are explained in the combination of machine learning architecture. The combination of steganography and steganalysis along with machine learning is used to identify protected data using different techniques.
Sectoral Trade Globalization
Authors: Crespo Nuno , Palan Nicole , Simoes Nadia
Published: May 2021

This chapter aims to shed light on the trends of sectoral trade globalization. This component of trade globalization is often neglected. An accurate evaluation of sectoral trade requires the analysis of the interdependencies of countries and the consideration of distance as a central dimension of trade globalization. As such, sectoral trade globalization is one aspect of a more complex and multi-dimensional phenomenon. Data show that sectoral trade globalization has increased significantly over the last 50 years irrespective of the characteristics of individual sectors. One relevant insight is that the level of trade globalization is on average still different for high-tech sectors compared to low-tech and medium-low-tech sectors even though the former could increase their bilateral trade relationships over time. Even though protectionist tendencies as well as the COVID-19 pandemic have led to a vivid discussion about the return to more local or regional production schemes, digitalization processes could still have the potential to further integrate countries' trade networks.
Globalization, International Trade, and CO2 Convergence
Authors: Yıldız Furkan
Published: May 2021

The goal of this study is to investigate the potential effects of international trade on per-capita CO2 emissions among trade partners. To achieve this purpose, the Group of Seven (G7) countries and each of their developing trade-partner countries with the highest trade volume have been selected as the sample. The stochastic convergence methodology has been employed using Augmented Dickey Fuller (ADF), Phillips-Perron (PP), and Enders-Lee Fourier unit root tests in order to test for convergence or divergence. Various results have been obtained from the unit root tests. These results suggest international trade to have no general or common effects on per capita CO2 emissions.
Exchange Rate Regime Preferences and Budget Deficits in Open Economies
Authors: Kiziltan Mustafa
Published: May 2021

This study investigates the impacts of exchange rate regime (ERR) choice, economic, institutional, and demographic factors on the budget deficit. The recent literature states that fiscal discipline is affected by the ERR preferences in open economies. In this study, the effect of de facto ERR preferences on fiscal discipline were analyzed between 1995 and 2016 for 76 countries classified into income groups. The estimates by Feasible Generalized Least Squares and Panel Corrected Standard Errors estimators show that flexible ERRs provide much more fiscal discipline. The findings highlight the importance of institutional quality, demographic factors, and inflation to ensure fiscal discipline. A country with a high level of trade openness is more vulnerable to exchange rate shocks, which leads to uncertainty in the fiscal policy. The results confirm that ERR preferences affect countries' fiscal disciplines differently, depending on the countries' characteristics.
A Roadmap to India Liberalizing With Major Economic Groups
Authors: Mathur Somesh , Angural Sachin Kumar
Published: May 2021

This chapter aims to look at various existing international economic cooperation groups and analyze the impact of India liberalizing with each of them using the GTAP model. This chapter aims to discuss each of these economic groups composition and identify the key sectors they are specialized in. Further, they analyze the product aggregations in which India and these groups would benefit if we liberalize with them. This chapter looks at different linear and nonlinear methods while performing the simulations and compares them. The chapter looks at the different scenarios with (1) India reducing tariff by 10%, (2) both Indian and the economic group reducing tariff by 10%, (3) both reducing the tariffs to 0%. The chapter then further looks at the impact of each cooperation liberalizing with India in terms of terms of trade (ToT), trade balance, and import and export quantities. Thus, this chapter attempts to get some insights into what product aggregates would be beneficial for India and the economic groups and therefore build a roadmap for the same.
Flexible Crowd-Driven Decision Making in Times of Crisis
Authors: Benali Mohammed , Ghomari Abdessamed Réda , Zemmouchi-Ghomari Leila , Lazar Mohammed
Published: May 2021

In times of crisis, making efficient decisions needs an accurate awareness of the event context and strongly depends on the effective use and coordination of resources, people, and information, where information is owned by either response organizations or non-crisis expert public. In this age of advanced collaborative technologies, citizens' participation to the crisis management process has shifted from the passive one-way contribution of social networking data to more active participation by performing specific tasks related to crisis-data processing. This chapter presents a comprehensive approach for integrating the crowdsourcing process to the collaborative decisional process in crisis situations. Application of the proposal with a real-world case study of the desert locust plague provides evidence of the enabling role that the crowdsourcing paradigm plays in supporting decision makers within desert locust control organizations operating throughout vast, remote, and geographically problematic areas.
A Study of the Readiness of Indian Banks to Absorb COVID-19`s Impact Through New Emerging Technologies and Strategies for Competitive Advantage
Authors: Bhasin Narinder Kumar , Gulati Kamal
Published: May 2021

Digital disruptions and e-collaboration between banks, corporates, and fintech companies are increasing to meet the new challenges posed by COVID-19 across the globe. The Indian economy and the financial ecosystem is undergoing a transformation with the number of reforms introduced by the Government of India and Reserve Bank of India in the last few years. Emerging trends in the Indian economy with new business models being adopted by the banks and financial institutions leading the country to the international standards of the payment system. This chapter focus on the pre-COVID reforms and their impact on banking and finance sector post-COVID 19 in the Indian Economy. The author explains the readiness of Indian banks to meet the challenges and the new emerging technology-based business model being adopted by banks and financial institutions in re-strategizing their operations and have a competitive advantage in the market.
Opportunities and Challenges of M-Learning During the COVID-19 Pandemic
Authors: Hossain Syed Far Abid , Shan Xu , Nurunnabi Mohammad , Tushar Hasanuzzaman , Mohsin A. K. M. , Ahsan Faiza Tanaz
Published: May 2021

The purpose of this study is to explore the opportunities and challenges of m-learning (mobile learning) during COVID-19 pandemic. The study identified how students accepted the m-learning tools due to the pandemic with noticeable challenges and threats, revealing in particular an increased tendency to use smart technologies and apps to collaborate online learning with mobile devices. The study is an enhanced version which utilized mixed methodology research including a survey questionnaire and a focus group interview from university teachers and students. Results from statistical analysis and focus group interview revealed that university students have numerous opportunities besides some noticeable challenges. The study also highlights the education sustainability during COVID-19 pandemic due to m-learning technology.
Ensemble-Based Feature Selection With Long Short-Term Memory for Classification of Network Intrusion
Authors: D. Preethi , Khare Neelu
Published: May 2021

This chapter presents an ensemble-based feature selection with long short-term memory (LSTM) model. A deep recurrent learning model is proposed for classifying network intrusion. This model uses ensemble-based feature selection (EFS) for selecting the appropriate features from the dataset and long short-term memory for the classification of network intrusions. The EFS combines five feature selection techniques, namely information gain, gain ratio, chi-square, correlation-based feature selection, and symmetric uncertainty-based feature selection. The experiments were conducted using the standard benchmark NSL-KDD dataset and implemented using tensor flow and python. The proposed model is evaluated using the classification performance metrics and also compared with all the 41 features without any feature selection as well as with each individual feature selection technique and classified using LSTM. The performance study showed that the proposed model performs better, with 99.8% accuracy, with a higher detection and lower false alarm rates.
Security and Privacy Challenges in Big Data
Authors: Singh Dharmpal , Nath Ira , Singh Pawan Kumar
Published: May 2021

Big data refers to enormous amount of information which may be in planned and unplanned form. The huge capacity of data creates impracticable situation to handle with conventional database and traditional software skills. Thousands of servers are needed for its processing purpose. Big data gathers and examines huge capacity of data from various resources to determine exceptional novel awareness and recognizing the technical and commercial circumstances. However, big data discloses the endeavor to several data safety threats. Various challenges are there to maintain the privacy and security in big data. Protection of confidential and susceptible data from attackers is a vital issue. Therefore, the goal of this chapter is to discuss how to maintain security in big data to keep your organization robust, operational, flexible, and high performance, preserving its digital transformation and obtaining the complete benefit of big data, which is safe and secure.
Overview of Big Data-Intensive Storage and its Technologies for Cloud and Fog Computing
Authors: Segall Richard S. , Cook Jeffrey S , Niu Gao
Published: May 2021

Computing systems are becoming increasingly data-intensive because of the explosion of data and the needs for processing the data, and subsequently storage management is critical to application performance in such data-intensive computing systems. However, if existing resource management frameworks in these systems lack the support for storage management, this would cause unpredictable performance degradation when applications are under input/output (I/O) contention. Storage management of data-intensive systems is a challenge. Big Data plays a most major role in storage systems for data-intensive computing. This article deals with these difficulties along with discussion of High Performance Computing (HPC) systems, background for storage systems for data-intensive applications, storage patterns and storage mechanisms for Big Data, the Top 10 Cloud Storage Systems for data-intensive computing in today's world, and the interface between Big Data Intensive Storage and Cloud/Fog Computing. Big Data storage and its server statistics and usage distributions for the Top 500 Supercomputers in the world are also presented graphically and discussed as data-intensive storage components that can be interfaced with Fog-to-cloud interactions and enabling protocols.