bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modern Perspectives in the Study of Electronic Systems
Authors: Basu Saurabh , Chattopadhyay Sourav 
Published: December 2022

Modern Perspectives in the Study of Electronic Systems focuses on recent developments in selected critical areas of condensed matter physics. The book blends theoretical developments and experimental discoveries of materials, helping the reader understand different phenomena. It studies the Quantum Hall Effect (integer and fractional) and superconductivity from phenomenological and microscopic perspectives. Magnetism and magnetic phenomena in solids via approximate solutions of the Hamiltonian model are also addressed. The book also discusses the topological aspects of materials that have fundamentally changed the study of condensed matter physics in the recent times.
This timely and practical book:Introduces topology that has governed the study of two-dimensional Dirac materials and led to the discovery of three-dimensional materialsIncludes illustrations and plots for better visualization and understanding of the book contentUses a hands-on approach to teach subjects that have influenced teaching and research worldwide
Modern Perspectives in the Study of Electronic Systems is an excellent tutorial for senior undergraduate students, graduate students, and early-career researchers. It will be helpful for teachers in teaching courses on specialized topics in condensed matter physics.
A de novo protein catalyzes the synthesis of semiconductor quantum dots
Authors: Spangler Leah C. , Yao Yueyu , Cheng Guangming , Yao Nan , Chari Sarangan L. , Scholes Gregory D. , Hecht Michael H. 
Published: December 2022

De novo proteins constructed from novel amino acid sequences are distinct from proteins that evolved in nature. Construct K (ConK) is a binary-patterned de novo designed protein that rescues
Escherichia coli
from otherwise toxic concentrations of copper. ConK was recently found to bind the cofactor PLP (pyridoxal phosphate, the active form of vitamin B
6
). Here, we show that ConK catalyzes the desulfurization of cysteine to H
2
S, which can be used to synthesize CdS nanocrystals in solution. The CdS nanocrystals are approximately 3 nm, as measured by transmission electron microscope, with optical properties similar to those seen in chemically synthesized quantum dots. The CdS nanocrystals synthesized using ConK have slower growth rates and a different growth mechanism than those synthesized using natural biomineralization pathways. The slower growth rate yields CdS nanocrystals with two desirable properties not observed during biomineralization using natural proteins. First, CdS nanocrystals are predominantly of the zinc blende crystal phase; this is in stark contrast to natural biomineralization routes that produce a mixture of zinc blende and wurtzite phase CdS. Second, in contrast to the growth and eventual precipitation observed in natural biomineralization systems, the CdS nanocrystals produced by ConK stabilize at a final size. Future optimization of CdS nanocrystal growth using ConK—or other de novo proteins—may help to overcome the limits on nanocrystal quality typically observed from natural biomineralization by enabling the synthesis of more stable, high-quality quantum dots at room temperature.
A novel broad spectrum venom metalloproteinase autoinhibitor in the rattlesnakeCrotalus atroxevolved via a shift in paralog function
Authors: Ukken Fiona P. , Dowell Noah L. , Hajra Mamta , Carroll Sean B. 
Published: December 2022

The complexity of snake venom composition reflects adaptation to the diversity of prey and may be driven at times by a coevolutionary arms race between snakes and venom-resistant prey. However, many snakes are also resistant to their own venom due to serum-borne inhibitors of venom toxins, which raises the question of how snake autoinhibitors maintain their efficacy as venom proteins evolve. To investigate this potential three-way arms race among venom, prey, and autoinhibitors, we have identified and traced the evolutionary origin of serum inhibitors of snake venom metalloproteinases (SVMPs) in the Western Diamondback rattlesnakeCrotalus atroxwhich possesses the largest known battery of SVMP genes among crotalids examined. We found thatC. atroxexpresses five members of a Fetuin A-related metalloproteinase inhibitor family but that one family member, FETUA-3, is the major SVMP inhibitor that binds to approximately 20 differentC. atroxSVMPs and inhibits activities of all three SVMP classes. We show that thefetua-3gene arose deep within crotalid evolution before the origin of New World species but, surprisingly,fetua-3belongs to a different paralog group than previously identified SVMP inhibitors in Asian and South American crotalids. Conversely, theC. atroxFETUA-2 ortholog of previously characterized crotalid SVMP inhibitors shows limited activity againstC. atroxSVMPs. These results reveal that there has been a functional evolutionary shift in the major SVMP inhibitor in theC. atroxlineage as the SVMP family expanded and diversified in theCrotaluslineage. This broad-spectrum inhibitor may be of potential therapeutic interest.
Voltage-dependent extended shortwave infrared (e-SWIR) photodetection-band tuning utilizing the Moss–Burstein effect
Authors: Xiang Boyang , Gu Guiru , Ramaswamyd Nagarajan , Drew Christopher , Lu Xuejun 
Published: December 2022

Abstract
Extended shortwave infrared (e-SWIR) photodetectors and imaging focal plane arrays covering the wavelength beyond the conventional In0.53Ga0.47As cutoff wavelength of 1.65 micrometers (µm) can find numerous applications in infrared sensing and imaging. This paper reports voltage-tunable e-SWIR photodetectors based on the conventional gallium antimonide (GaSb) n–i–p and p–i–n homojunctions on GaSb substrates, which offer bias-dependent photodetection band tuning with a simple structure and high material crystal quality due to the perfect lattice matching on the substrates. Detection bands between the cutoff wavelengths of 1.7 µm and 1.9 µm can be tuned with a low reverse bias voltage of <0.1 volts (V). The mechanism of the voltage-dependent band-tuning was analyzed and attributed to the Moss–Burstein effect, which changes the electron and hole filling factors under different reverse bias voltages. This analysis agreed with the experimental data. The Moss–Burstein effect-induced voltage-dependent band-tuning mechanism can provide useful guidance for the designs of e-SWIR photodetectors.
BPCN: bilateral progressive compensation network for lung infection image segmentation
Authors: Wang Xiaoyan , Yang Baoqi , Pan Xiang , Liu Fuchang , Zhang Sanyuan 
Published: December 2022

Abstract
Lung infection image segmentation is a key technology for autonomous understanding of the potential illness. However, current approaches usually lose the low-level details, which leads to a considerable accuracy decrease for lung infection areas with varied shapes and sizes. In this paper, we propose bilateral progressive compensation network (BPCN), a bilateral progressive compensation network to improve the accuracy of lung lesion segmentation through complementary learning of spatial and semantic features. The proposed BPCN are mainly composed of two deep branches. One branch is the multi-scale progressive fusion for main region features. The other branch is a flow-field based adaptive body-edge aggregation operations to explicitly learn detail features of lung infection areas which is supplement to region features. In addition, we propose a bilateral spatial-channel down-sampling to generate a hierarchical complementary feature which avoids losing discriminative features caused by pooling operations. Experimental results show that our proposed network outperforms state-of-the-art segmentation methods in lung infection segmentation on two public image datasets with or without a pseudo-label training strategy.
Visualization, registration and tracking techniques for augmented reality guided surgery: a review
Authors: Ma Longfei , Huang Tianqi , Wang Jie , Liao Hongen 
Published: December 2022

Abstract
Augmented reality (AR) surgical navigation has developed rapidly in recent years. This paper reviews and analyzes the visualization, registration, and tracking techniques used in AR surgical navigation systems, as well as the application of these AR systems in different surgical fields. The types of AR visualization are divided into two categories of in situ visualization and non in situ visualization. The rendering contents of AR visualization are various. The registration methods include manual registration, point-based registration, surface registration, marker-based registration, and calibration-based registration. The tracking methods consist of self-localization, tracking with integrated cameras, external tracking, and hybrid tracking. Moreover, we describe the applications of AR in surgical fields. However, most AR applications were evaluated through model experiments and animal experiments, and there are relatively few clinical experiments, indicating that the current AR navigation methods are still in the early stage of development. Finally, we summarize the contributions and challenges of AR in the surgical fields, as well as the future development trend. Despite the fact that AR-guided surgery has not yet reached clinical maturity, we believe that if the current development trend continues, it will soon reveal its clinical utility.
A hydrogen atom in strong elliptically polarized laser fields within discrete variable representation
Authors: Shadmehri Sara , Melezhik Vladimir S 
Published: December 2022

Abstract
The nondirect product discrete variable representation (npDVR) is developed for the time-dependent Schrödinger equation with nonseparable angular variables and is applied to a hydrogen atom in elliptically polarized strong laser fields. The 2D npDVR is constructed on spherical harmonics orthogonalized on the 2D angular grids of the Popov and Lebedev 2D cubatures for the unit sphere. With this approach we have investigated the dynamics of a hydrogen atom initially in its ground state in elliptically polarized laser fields with the intensity up to

I
=

10

14

W cm−2 and a wavelength of λ = 800 nm. For these parameters of the laser field and the entire range of ellipticity variation, we have calculated the total excitation and ionization yields of the atom. The performed analysis of the method convergence shows that the achieved accuracy of our calculations significantly exceeds the accuracy of recent works of other authors relevant to the problem, due to the high efficiency of the 2D npDVR in approximating the angular part of the 3D time-dependent Schrödinger equation. We also propose a new simple procedure for infinite summation of the transition probabilities to the bound states of the hydrogen atom when calculating the total excitation yield and prove its accuracy by comparison with conventional methods. The obtained results show the potential prospects of the 2D npDVR for investigating atomic dynamics in stronger laser fields.
Quantum effects on the black hole shadow and deflection angle in the presence of plasma*
Authors: Atamurotov Farruh , Jamil Mubasher , Jusufi Kimet 
Published: December 2022

Abstract
In this study, the optical properties of a renormalization group improved (RGI) Schwarzschild black hole (BH) are investigated in a plasma medium. Beginning with the equations of motion in a plasma medium, we aim to present the modifications in the shadow radius of the RGI BH. To this end, we compute the deflection angle of light in the weak gravity regime for uniform and non-uniform plasma media. Importantly, owing to the plasma media, we discover that the equations of motion for light obtained from the radiating and infalling/rest gas have to be modified. This, in turn, changes and modifies the expression for the intensity observed far away from the BH. Finally, we obtain the shadow images for the RGI BH for different plasma models. Although quantum effects change the background geometry, such effects are minimal, and practically detecting these effects using the current technology based on supermassive BH shadows is impossible. The parameter Ω encodes the quantum effects, and in principle, one expects such quantum effects to play significant roles only for very small BHs. However, the effects of plasma media can play an important role in the optical appearance of BHs, as they affect and modify the equations of motion.
Sustainable Infrastructure with Smart Technology for Energy and Environmental Management
Authors: Karthiga Shenbagam N 
Published: December 2022

Abstract
Editorial Material, Karthiga Shenbagam N
Life on this planet has been undergoing severe challenges owing to the rampant anomalies in the natural climate and ecosystem getting modified by human interventions at multitudes of scales. It is inevitable to admit that we have compromised in maintaining global sustainability during the process of ever-satiating quench for better life comforts. There is a much wanted look-back, get corrections and move forward to ensure the real implementations of sustainability principles in every walk of our life. The concept of sustainable infrastructure envisions inclusive growth for design, development and delivery of the services and products. It is imperative to adopt environmental stewardship for conscious and responsible consumption of natural resources to build sustainable enterprises. Technology has a crucial role in enabling to achieve the audacious goals by promoting institutionalization and large-scale influence in the lifestyle. There are many promising technological inventions happening in the field of infrastructure development to integrate the smartness in functionality and ease in adoption that corroborate with conservative measures on energy and environment.
At the current scenario, there are more suitable ways of building construction which is no longer a personal choice of matter and there are more suitable sectors newly introduced that improves the infrastructure. A sustainable construction takes into account the natural resources, their environmental impact and the risks that reduce people’s safety. In building construction eco-friendly materials known as low carbon concrete are those that reduces the amount of carbon di oxide produced during the production, placing and maintenance actions.
SISTEEM 2022 aims to gather scholars, researchers from all over the world and provide a platform to review the contributions and accomplishments in the field of Civil Engineering in the last few years and draw an agenda for the future course of action keeping the national and global needs in the forefront. This conference will also provide an ideal environment to develop new collaborations and meet experts on the fundamentals, applications, and products of the mentioned fields.
List of committees are available in this Pdf.
Effects of air pollution due to vehicular emission in coimbatore and reduction strategies: A review
Authors: Sadheesh S , Jeyanthi J , Mohan Lakshmi R , Reshmi N , Sashwath Y G 
Published: December 2022

Abstract
Air pollution is a Worldwide challenge that is a reason for premature death. It affects both developing nations and developed nations. In particular, the air is so much polluted so that cities are fighting to fulfill air quality range and protect humans from harmful substances. One of the greatest global challenges of 2050 is the reduction of greenhouse gas emissions. Besides greenhouse gas emissions, air pollution is the major problems in many urban areas this situation is due to the sudden increase in the count of vehicles. According to the studies, Nitric oxide and particulate matter contribute more to air pollution.
Due to urban transportation improvements vehicle traffic volume is on the rise over the past few years. Air pollution is majorly contributed by vehicular congestion and traffic. This paper analyzes traffic data at Coimbatore. From the review, comparing various locations, two-wheelers are the highest in count among all of the rest of the vehicles. Air pollution is a crisis that causes damage to the human who are living in areas where air pollutants are high in level. The type and amount of air pollutant decides the risk of illness. This indicates that carbon monoxide and particulate matter emitted from a vehicle of two passengers is higher than a single passenger vehicle. Although the centralization of poisons close by avenue are not always connected to transportation sector, this marker can be used as an indication of increase in residents. It also acts as an indication of how much surrounding areas are being polluted by metropolitan toxic wastes. This paper examines the vehicular emissions in Coimbatore, India. The study looks at reviewing data from various sources to formulate solutions for improving air quality in the city.
Water Quality Modelling of River Periyar Using Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System
Authors: Shine Anugeetha , Madhu G. 
Published: December 2022

Abstract
Water is requisite on earth for life to survive. The study area of the present work is the river Periyar, the longest river in Kerala, India. The overall objective of the present work is to compare the accuracy and performance of the artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) in the training and prediction of dissolved oxygen (DO) concentration and biochemical oxygen demand (BOD) in the river. The models were used to examine secondary data from the past for four water quality metrics generated at five monitoring stations located along the river Periyar to predict DO concentrations and BOD. The performance of the models was examined using root mean square error (RMSE) and coefficient of correlation (R) values. This study revealed that ANN is superior to ANFIS in most scenarios. In most situations, ANFIS appears to get the superiority in training, however, ANN seemed to have the dominant position in testing and validation. The inputs having the highest relevance in the case of DO prediction were identified to be nitrate and phosphate concentrations, whereas total solids and COD were seen to be the most impactful in the case of BOD forecasting employing sensitivity analysis.
Investigation on Durability of Study Fiber Reinforced Concrete
Authors: Ramakrishnan S , Dinesh A , Gnanaprabhakaran M , Aswin D , Gowthambalaji K 
Published: December 2022

Abstract
The significance of concrete durability cannot be undervalued. Durability of concrete is simply defined as its capability to resist enduring action and chemical attack, while maintaining the engineering properties for desired life time. The durability of concrete is dynamic with looks to a structure’s life span. In this investigation, study on durability of fiber reinforced concrete made with steel and glass fiber has compared for M30 grade of the concrete. The fractions of fiber are 0.5%, 1%, 1.5% and 2% by the volume of concrete. Durability of concrete as relatively measured by conducting laboratory tests such as acid attack test and rapid chloride permeability test. In acid attack test concrete specimens were immersed in acid for 28 days and 56 days. The compressive strength, loss of mass are compared for acid immersed specimen with water curing specimens. Rapid chloride permeability test was conducted at 28 days and 56 days for eight mix proportion. It can be concluded that which type of fiber reinforced concrete is suitable for durability. Also concluded that the optimal usage of fiber in concrete in context of durability.
Machine learning based Air Pollution Monitoring and predicting cause for pollution
Authors: Karthikeyan S , Leeban Moses M , Perarasi T , Raju  
Published: December 2022

Abstract
Over the past few decades, due to human activities, industrialization, and urbanization, air pollution has become a life-threatening factor in many countries around the world. Air pollution has a direct impact on human health through the exposure of pollutants and particulates, which has increased the interest in air pollution and its impacts among the scientific community. The main causes associated with air pollution are the burning of fossil fuels, agriculture, exhaust from factories and industries, residential heating, and natural disasters. The Environmental Protection Agency (EPA) tracks the pollution level by calculating the amount of ground-level ozone (O3), Sulphur dioxide (SO2), particulates matter (PM10 and PM2.5), carbon monoxide (CO), carbon dioxide (CO2), and nitrogen dioxide (NO2) present in the air molecule. These substances are in compositions of a common index, called the Air Quality Index (AQI), indicating how clean or polluted the air is currently or forecasted to become in areas. This work deliberates the implementation of cloud based IoT system for air quality monitoring in which the sensors are used to calculate CO, PM2.5 and PM10, O3, SO2 and NOx pollution level with environmental condition like temperature and humidity. The obtained information can be updated in cloud platform using Lora nodes and Lora Gateway. The information fetched from the cloud is transmitted to the Machine learning models which contains the detailed dataset for the pollutants and these models accurately predict the day-wise pollutant concentrations and display them using an application. This work presents the detailed analysis for predicting the cause of pollution by using Support Vector Machine (SVM), Random forest algorithm and K-nearest neighbours (KNN) algorithm.
Factors influencing financial risk management in construction projects
Authors: Srinivasan N P , Dinesh A , Munshi Surajit , Karthick A 
Published: December 2022

Abstract
The infrastructural and economic development of a country merely depends on the construction industry and its growth. There are many risk factors involved with the construction industry during planning, execution and commissioning of the projects. Dealing with the risk factors in construction industry have been known as a crucial management process in order to achieve the overall objectives of the industry in terms of cost, time, safety, quality and environmental sustainability. This report is related with the financial aspects which directly take part in the industry for which studies have been conducted with various engineers, contractors and labors in and around north-western districts of Tamilnadu. The perspectives at different levels of management have been concluded with the standard questionnaire format that has been investigated and their results are analyzed based on the current scenario. With the help of these surveys and data analysis by Relative Importance Index (RII), the most related factors among the identified factors were found to be labour risk, material risk, credit risk, planning risk, execution and environmental related factors. The suggestions and recommendations have been expressed to overcome those risk moderations.