bluuebunny/crossref_metadata_2025 huggingface dataset:
Analyzing Different Optimizers for the Recognition of Gurmukhi Handwritten Text by Employing CNN
Authors: Sharma Sandhya , Gupta Sheifali
Published: April 2022

Automatic recognition of handwritten data is an important application area in various fields. Recognition of handwritten text, which is cursive in nature, is a cumbersome task. Moreover, handwritten text by different writers makes the recognition even more difficult due to the different writing styles of the individuals. In this paper, a CNN model employing different optimizers is proposed for the recognition of Gurmukhi handwritten dataset. For the purpose of classification and recognition, five different classes of Gurmukhi handwritten text have been created where each class has 1,000 handwritten samples. Results are obtained using four different optimizers: Adagrad, Adam, Adamax, and RMS prop. Maximum validation accuracy of 99.20% is achieved using Adam optimizer.
Comics: An Alternative Medium for Education and Social Progress
Authors: Das Amit Kumar , Singh Arjun Kumar
Published: April 2022

The emergence of alternative media doesn't mean that it is there to compete with the mainstream press. This is not at all about quantity, but about quality and participation, about active citizenship, awareness, different perspectives, and most importantly, about the democratization of media. To get space in newspapers the marginalized community used the medium of comics to raise their voice. These alternative media will go hand in hand with the mainstream media to remind them of the issues involved and the silent masses, and so we need to take comics seriously. This paper will examine the role of comic to break the boundaries of literacy and language and use of comic art for increasing literacy and awareness and to raise the social issue in rural India.
Schmitt Trigger Designs Using Domino Logic Style
Authors: Singh Nikhil , Shekhar Siddharth , Angeline Anita , Bhaaskaran V. S Kanchana
Published: April 2022

The advancements in the VLSI regime at lower technology node necessitate robust circuit design. Schmitt trigger design using domino logic style exhibit better hysteresis, higher noise margin, and reduced power consumption while compared to static CMOS Schmitt trigger design. This paper proposes three different Schmitt trigger designs based on domino logic style which produces a stable output with increased robustness against noise. The evaluation of dynamic logic-based Schmitt trigger using only NMOS transistors makes high speed operation feasible with reduced power consumption and increased hysteresis. The design, simulation, and analysis of the circuits are performed using Cadence Virtuoso using GPDK 180 nm technology library.
Price of Workplace Incivility: Impact on Turnover Intention
Authors: Sao Ruchi , Chandak Shravan , Bhadade Pritam
Published: April 2022

Workplace incivility can be best explained with the help of the incivility continuum which ranges from negative behavior to physical aggression. This research paper finds the various factors affecting the workplace incivility of employees of sales department employed with banking and financial sector. In the study, impact of incivility from colleagues and manager has been found to be significant on turnover intention, which was tested by ordinal regression. Sample size in the study is 340.
An Assessment of Machine Learning and Deep Learning Techniques with Applications
Authors: Sharma Shikha , Mittal Ruchi , Goyal Nitin
Published: April 2022

Nowadays, sheer amount of data is being generated by plethora of sources, like science, business, medicine, sports, geography, environment, etc. This produced data may be formless, bigger sized, and in the raw format and has no importance at all, until analyzed. Conventional techniques of data analysis may be inappropriate due to vast data diverse nature, high dimensionality of data, and much of the data is never explored. So, in order to get relevant data, some techniques need to be incorporated on the existing data, which would be effective for the real-world applications. Artificial intelligence, machine learning, and deep learning are the extensively used technologies with the utmost buzz. Machine learning is a subfield of AI that designs the intelligent model based on past and current trends. The only concentration of this ground is pre-programmed learning techniques without any human interference/intervention. In addition to this, deep learning processes the data and creates pattern for decision use after imitating the working of human brain. So, the objective of this paper is to explore the research application areas and the widely used approaches/techniques in the domain of machine learning and deep learning.
Building Inclusive Societies Through Emotional Intelligence-Based Education Systems: Indian Perspective to Achieve Sustainable Development Goals
Authors: N Harshitha , Warrier Uma
Published: April 2022

Social inequality and quality education are significant challenges faced by tribes in India. The study's key objective is to develop an Emotional Intelligence (EI) based conceptual framework for tribal education to achieve quality education and build inclusive societies. The developed framework integrates the Mixed Model of EI and the path-goal leadership theory. The purpose of the study was to do a literature review towards identifying the link between teachers' Emotional Intelligence Competencies (EIC) and growth mindset for effective teaching and superior performance. The article proposes four prime propositions that constitute prerequisites for further hypothesis formulation and validation studies. By adopting teaching practices embedded with growth mindset and EIC, the study has far-reaching implications in achieving sustainable development goals (SDG), such as SDG 4 – Quality Education and SDG 10 – Reduced Inequalities.
Enhancement of Learning Outcomes Through Blogging
Authors: K Pradeepa , N Hema
Published: April 2022

In the current digital era, it is a significant paradigm shift in academics to write blogs in order to expand the audience, contemporary and reader-friendly style. It can be used in academics to share knowledge and also helps to change the academic discourse to achieve real student-centered learning. In recent years, many social software and networks have been introduced to describe a new phenomenon in the virtual world. There are 17 sustainable goals where “Education” is the 4th goal and is the foremost thing where every student should take over in this contemporary world to ameliorate their education. Blog writing is also one of the ways where it will be discrete from classroom learning. It is also known to be as informal education. This blog writing focuses on the perception of weblogs by students and teachers as a successful medium by applying SIT (Social Interactionist Theory).
Emotional Intelligence and Job Performance: A Review Based Study
Authors: Sharma Geetanjali , Chand Pawan Kumar
Published: April 2022

The 21st century is witness to a rapidly changing workplace because of technological advancements, competition posed by competitors, globalization, and the expansion in the service sector. This necessitates employees to be much more involved in work not just physically but also emotionally and mentally as employees with emotional intelligence competencies have been found to give an outstanding performance at work and contribute more to an organization’s profits (1,2). Hence, after a careful examination of literature, the present study with a literature-based approach brings to the forefront the crucial role played by emotional intelligence in job performance leading to the success of an organization. This study will be valuable for researchers, academicians, industrialists, and other stakeholders in understanding how emotional intelligence has an impact on job performance, and how it could assist an organization in employing a workforce with the necessary emotional intelligence, thereby contributing to an organization’s long-term success.
Implementing a Hybrid Recommendation System to Personalize Customer Experience in E-Commerce Domain
Authors: Bohra Sneha , Bartere Mahip
Published: April 2022

With the rapid use of the internet, a huge amount of data is generated over the network with every passing second. On the other hand, the user demands information that is relevant to his personal search. The processing of such huge data is a challenging task. To serve the user with his specific required information, there is a need for an information retrieval mechanism that can process this large data. A recommendation system is such required technology that retrieves information in order to improve users’ access and thereby recommending items that are relevant to his explicitly mentioned behavior and preferences. The recommendation algorithm analyzes the huge dataset and focuses to recommend accurate content to the user. There are several recommendation systems in use today, some popular among them are Netflix, YouTube, Tinder, and Amazon. In this article, discussion is done on various types of recommendation systems, issues of recommendation systems, and use cases of widely used recommendation engines and their potential benefits. The work introduced in this paper is an integration approach of domain-specific and item-based recommendation system. The performance of the proposed algorithm is measured on evaluation metrics precision and recall. Experimental results prove that the approach introduced in this paper performed well as compared to existing methods.
Gender Equality: An Exploratory Study of Practices Adopted by Star Hotels
Authors: Shende Kiran Murlidhar , Gumaste Rasika , Joshi Sarika
Published: April 2022

Gender equality can be understood as equal access to opportunities and resources regardless of the gender. An awareness of the gender inequality has prompted the hotel industry to review their policies and practices. This research studies gender equality practices adopted by the human resource department of the star category hotels to overcome the above challenges and give equal opportunities as well as support towards the work equilibrium. The results indicate that the practices adopted by the hotels are inclined towards gender equality, especially women centric. It was observed that women employees have taken up positions at all levels in hotels owing to the changing trends in the policies and practices. The results suggest that certain departments like housekeeping and front offices are dominated by women employees, whereas the food production department has male employees. The research is confined to and emphasizes on gender equality with respect to the hotel industry.
Machine Learning Techniques for Precision Agriculture Using Wireless Sensor Networks
Authors: Goel Swati , Guleria Kalpna , Panda Surya Narayan
Published: April 2022

In India, approximately 70% of the total population is dependent on agriculture for their livelihood. Hence, it is essential to pay attention to agriculture to increase crop quality and quantity, thus increasing the overall cultivation yield. The traditional methods used require a lot of farmer’s effort and hard work, which results in delayed crop cultivation. Moreover, it’s challenging to predict the environmental conditions and detect the particular area where there are weeds, insects, etc., which requires immediate treatments, thus affecting overall crop production. So, there is a need to make it automated, and this can be done by adopting advanced techniques of precision agriculture (PA) or intelligent agriculture. Precision agriculture is one of the fields in which wireless sensor networks (WSNs) are widely adopted, which consists of a large number of sensors placed in the field to monitor and measure the various environmental parameters, such as humidity, temperature, soil moisture, soil PH value, precipitation, water level, etc., for enhancing the productivity, profitability, quantity, and quality of crops. The machine learning techniques can be applied to precision agriculture to increase crop growth, manage the process of crop cultivation, and create a perfect environment for the crops to increase productivity with less human effort. This paper provides an insight into various machine learning techniques used for precision agriculture using wireless sensor networks.
Complaint Intentions on Packages of Food Products
Authors: Turaga Nagendra Kumar , Turaga Mohana , P. Venkateswar Rao , B Balaji
Published: April 2022

Packaging plays a significant role in today's rapidly changing market climate and customer demand. The objective of the study set out the base for identifying the relation between the reasons for food package complaints and complaint intentions apropos food products. A systematic samples approach was used in the survey of 272 people. A self-administered questionnaire was prepared for collecting the responses. Findings of the study showed that there is cogent influence of types of injuries than other reasons for complaining.
Sick Building Syndrome (SBS) in Ill-Lit and Ill-Ventilated Buildings
Authors: Boity Antony Kumar , Kaur Jasmeet , Varshney Chirag
Published: April 2022

The quality of the indoor and outdoor has a significant impact on the quality of air that we breathe in our habitable spaces like homes and offices. The buildings especially that are ill-lit or ill-ventilated cause various illnesses, i.e. asthma, allergy, reduced efficiency, lack of energy, known as Sick Building Syndrome (SBS). The SBS, combined with other environmental issues, has a direct or indirect impact on the health of the workers, workplace comfort level, and productivity. However, not much effort is put into buildings to keep the cost of the buildings in check. The fact is both low-cost and high-cost buildings are equally prone to SBS if not dealt with at the design stage from the beginning. This paper aims to address this recurring problem of SBS in ill-lit and ill-ventilated buildings by exploring various systems taken from results from a structured questionnaire given to the users.
An Empirical Study of Waste Heat Reutilization in Thermal Power Plant Using Advanced Fuzzy – PID Technology
Authors: Mishra Rabindra Kumar , Venkatesan S , Kanta Nalini
Published: April 2022

Many industrial heating operations create waste energy, particularly boiler exhaust gas, aiming to minimize global warming. The waste heat from the exhaust gas can be utilized to warm the entering gas. This is one of the most basic waste heat recovery technologies. As a result, the object of this study is how to recover heat waste from boiler exhaust gas using a shell and tube heat exchanger and improve the boiler's efficiency. The goal of this article is to improve the performance of control circuits used in heat exchangers to get the optimum solution; the fuzzy ID controller will replace the PID with the fuzzy controller. This article examines traditional intelligent controllers with the goal of controlling the yield fluid temperature of a shell. Experimental plant data is used to do mathematical modeling of the process to satisfy the control target. A traditional PID control may be utilized to regulate output fluid. By fine tuning the practical problem, you may get improved settling time, rising time, and overshoot. A power station is a multivariable controlled facility, independent of cutting-edge technology and techniques for unit performance, operation, flexibility, and availability; economic optimization and software that position state-of-the-art approaches are among the demands imposed on control & instrumentation engineers. As a result, fuzzy methods are being investigated to achieve resilience, tractability, and cheap cost by using tolerance for imprecision, ambiguity, and partial truth.
Comparison and Analysis of Different Thermography Techniques in the Biomedical Applications
Authors: Rajagopal Sivakumar , Arpan Waarish , Thomas Stefy , Gomare Gajanan , Soangra Rahul
Published: April 2022

Thermography is a technique that involves using a thermal camera to make a thermogram image that depicts the quantity of infrared energy emitted, transmitted, and reflected by an object. Body surface temperature monitoring, which varies when blood flow increases or decreases due to clinical irregularities, has been frequently utilised to diagnose medical problems such as breast cancer, diabetes neuropathy, and peripheral vascular disorders using thermography. Thermography has become a significant tool, particularly for fever screening during infectious disease epidemics such as Ebola and COVID-19, due to its non-invasive and non-contact nature. Thermography is a sensory instrument that can be particularly valuable in protecting human health when paired with thermal physiology data. In this review, we analyze and compare several thermography processes and aspects to come up with the optimal methodology for use in the medical field.
Automatic Hurricane Damage Detection in Satellite Images Using Deep Learning
Authors: Kaur Swapandeep , Gupta Sheifali , Singh Swati
Published: April 2022

Hurricanes or tropical cyclones are very destructive and powerful storms accompanied by strong winds of 119 km/hours or greater. They are also accompanied by rain, thunder, and lightning. This causes huge damage to human lives as well as property. Satellite images are being used for damage detection, but manual methods are prone to errors. Deep learning techniques are gaining popularity for automatic damage detection. With this motivation, a comparative analysis of two Convolutional Neural Networks that is 8-layer model and 16-layer model has been done to classify Hurricane Harvey satellite images into undamaged and damaged categories. It was found that the 16-layer model achieved the best results with an accuracy of 94% and recall of 93%.
In–Service Nursing Education in India: Challenges and Intervention
Authors: Raju P Deepa Mariya , Kumari Vinay
Published: April 2022

The health care profession is a major stakeholder of evidence-based practices and dynamic changes. It is a mandate for the health care professionals to be up to date with their skills and practices. In India, nowadays it is mandatory for each nurse to attend in-service training. It is a requirement from the organization and on the professional end. Multiple barriers dither the nurses to take part in continuing nursing education programs like lack of motivation, employee attrition and shortage, unreachable training programs, time limitation, and family responsibility. The researcher will adopt a blended in-service education model to overcome these difficulties and to measure the satisfaction, facilitators, and barriers using a quasi-experimental one-group pre-test/post-test design in hospitals in Delhi’s national capital region.
Worrywarts of Employees in the Information Technology Sector of India
Authors: Chaturvedi Neha , Chand Pawan Kumar
Published: April 2022

The health of employees in the organization has been a researchable topic for a long time, and there is strong evidence that the workplace environment can have a significant impact on employee health. As a result, employee worrywart has become a major concern of IT organizations. The present study focuses on worrywarts of employees in Information Technology sector of India. India's IT companies, which have been backbone of the economy, are going to lose business due to worrywarts of employees. The study concludes the reason behind the worrywarts in employees of IT sector. The study has been followed the review of literature approach and looked at employee worrywarts in the IT industry during the past two decades. The effort has been posited to recognize the significant worrywarts of workplace. The previous researchers work shows that workload, digital change, a lack of analytics and coding skills, employment risk, health difficulties of employee have been identified as the significant worrywarts as the conclusion of study. The findings of the study are identified by alarming worrywarts in employee’s life. The study findings shall be helpful for employers, investors, employee, researchers and the other stakeholders of service sector of India to recognize the hassles in the employee productivity and organizational resilience.
A Systematic Review on Effect of Whole Blood Donation on Iron Profile in Blood Donors
Authors: Narwal Neha , Mahajan Pooja , Garg Sachin
Published: April 2022

Regular whole blood donations sometimes may result in iron (Fe) inadequacy in the blood donors, which can lead to increased deferral rate among the donors. Blood collection centers must keep a track record of Fe status of regular whole blood donors, as well the impact it has on donor health. The blood centers must also counsel the donors regarding measures to improve the low Fe stores. Serum ferritin levels have been a better indicator of low Fe stores in the body as compared to hemoglobin. There is presently no international agreement on an acceptable approach for Fe monitoring. There are several ways to check the Fe levels in blood of whole blood donors. Hemoglobin- or ferritin-levels and Fe supplementation could be accessed to check the impact of regular blood donations. However, employing an Fe assessment method may provide new confrontations in management and accessibility of blood donors. We present an overview of parameters monitored for Fe stores in regular whole blood donors.
A Review Analysis Techniques of Flower Classification Based on Machine Learning Algorithms
Authors: Kaur Rupinder , Jain Dr. Anubha , Saini Pushpanjali , Kumar Sarvesh
Published: April 2022

A system design for the recognition of flower species will be very beneficial to only in agriculture but also in industries of pharmaceutical science, study, and practice botany, trade, and farming. For the flower classification system, it will require extra species testing as there are varieties of species in flowers and thus it become exceptionally difficult to characterize them when it comes for the basic identification of flower among same species. Therefore, this subject has already become crucial for research purposes. So, for better detection, various techniques have been implemented through machine learning, which the latest trends become for such problems solving. Machine learning is well known for the strongest for its large part of classification and recognition performance in the computer. Classification is the most vital approaches of AI. Major brief of machine learning is information evaluation. Numerous algorithms present for system classification like decision trees (DT), Neural Network, Navie Bayes, SVM, Back Propagation, multi-class classification, Artificial Neural, K-nearest neighbor, multi-layer perception, etc. The paper summarizes the foremost aspects of machine learning and its drawbacks.
Appraising the Prototypes of Smart Cities Policies Taking on the Impact of Pandemic
Authors: Chugh Damanpreet , Kumar Ambuj
Published: April 2022

With many sections of the city affected due to pandemic, there is a dire need to assess the vulnerability of pandemic hit areas in a city. Mainly, marketplaces, slum areas, residential areas, transportations mean, educational institutions, and religious areas, which comes under high density people intensive areas, are vulnerable to any future pandemic. New policies, capacity building, and technologies among people have paved a safer way in eradication and/or curbing the pandemic. There are set prototypes that have proven their worth when implemented within the city. Global smart cities like London, Spain, Montreal, and Indian cities like Bengaluru, Pune have developed solutions to safely handle the pandemic and kept their citizens served and informed. The paper focuses on the study about policies implemented during pandemic in various cities in India and in western world for curbing the spread of the disease.
Synthesis of Heterocyclic Compounds Via 1,3-Diketones
Authors: Sharma Kirti , Sharma Sumesh Chandra , Kapoor Mohit
Published: April 2022

Heterocyclic compounds acquire a unique place in medicinal chemistry as many of the pharmaceuticals, agrochemical industries use heterocyclic moieties in different kinds of drugs. Moreover, many of these compounds are naturally occurring and are known for their antibacterial properties from ancient times. These compounds like thiazole, pyrazole, imidazole, coumarin etc. are synthesized via 1,3-dicarbonyls as an intermediate. Essentially β-dicarbonyls are considered as promising scaffolds for the synthesis of heterocyclic compounds. Especially, due to keto-enol tautomerism, β-diketones show very distinct chemical properties. They could be made by combining an adequate methyl ketone with an acceptable ethyl ester in a Claisen reaction, which allows for a large range of potential combinations. In this review, we will discuss various synthetic approaches for the preparation of five and six membered heterocyclic compounds via 1,3-dicarbonyls.
Modeling Creep on Account of Residual Stress of Thermally Graded Rotating Disc
Authors: Gupta Kunjan , Bose Tania , Rattan Minto , Chamoli Neeraj
Published: April 2022

Rotating discs are an essential structural component in machinery, electronic components, and space structures. Different temperature distributions cause creep deformation in the disc by facilitating the stress distribution. In present framework, Hoffman’s yield criterion is used to describe the yielding of disc material in order to count for residual stress. Disc is subjected to linear and parabolic thermal gradations. Creep rates are evaluated for linear and non-linear reinforcements of the disc. It is seen from the study that residual stress has a crucial role to play in stress and strain rate distribution and finally in the design of the rotating disc.
Are Anti-Inflammatory Drugs Effective In Patients With COVID-19 Cytokine Storm: A Review
Authors: Gupta Navita , Punamiya Zeenal Suresh , Salve Pradnya , Sakpal Neha , Desai Kaushik , Tomar Geetanjali
Published: April 2022

SARS-CoV-2 - Severe acute respiratory syndrome - Coronavirus-2 is one of the most infectious diseases, leading to a pandemic. COVID-19 has extensive involvement in the lower respiratory tract causing acute respiratory syndrome disease (ARDS). No exact treatment is available, so strategies for developing treatment include repurposing of drugs. Pathogenesis of COVID-19 is associated with a cytokine storm in lung alveoli, leading to extensive inflammation and hemorrhage in lung tissue(1). Excessive pro-inflammatory cytokine production contributes to the progression of ARDS, additional tissue damage, multi-organ failure, and death. As there is a correlation between cytokine storm and COVID-19, early management of cytokine storm can improve survival rate and reduce mortality. The authors of this article presented similarities in the pathophysiology of COVID-19 and other inflammatory diseases like rheumatoid arthritis, an overview of the common cytokines associated with both the diseases, and their inhibitory molecules that can be repurposed for the treatment of COVID-19.
Impact of Aesthetics in Innovative Product Development on Consumer Perception and Acceptance
Authors: Pandey Reena
Published: April 2022

“Beauty is how you feel inside, and it reflects in your eyes. It is not something physical.” Sophia Loren Design aesthetics is an important element in any of the product which a man uses in day to day life. This is also one of the major factors which compel a consumer to buy the product. In this growing competition focus is on innovative product development and new approaches to draw customer’s attention towards their products. Aesthetics is one of the integral parts of design principles that define a design’s pleasing qualities. Aesthetics are one of the most important for customer acceptance in almost all the fast moving goods categories. This study aims to investigate the impact of aesthetics in innovative product development and consumers’ perception and acceptability as importance of aesthetics is not being explored by researchers. This paper inspects the importance of aesthetics while working on innovative product development, design process, sustainability, and consumer perception on aesthetics while buying a new product.
Influence of Career Development Learning on Employability with the Mediating Effect of Learning Outcome
Authors: Bano Yasmeen , Vasantha S.
Published: April 2022

Employability is a very real challenge as many students do not possess skill required by industry. It is strongly recommended by several researchers that college management should establish a good contact with the local industries to develop the students’ career development learning because academia and industry collaboration can help in students’ career development learning and make them more employable. The key purpose of the present study is to establish the mediating effect of learning outcome between career development learning and employability. The data collection has been done by collecting the response from 230 management students by utilizing the purposive sampling method. The data has been collected through the questionnaire survey method. And for testing the hypothesis, several statistical approaches were applied. The result of this study revealed that learning outcome partially mediated the employability because career development learning also has direct positive effect on employability. The study has concluded that career development learning improves the students’ employability and make them more successful in their career. The study also concluded that learning outcome also plays an important role in developing the students’ employability.
Effect of E-Learning on the Academic Achievement of Students
Authors: N Keerthi , Garg Shaifali , N S Vijayalakshmi , Tongkachok Korakod
Published: April 2022

E-learning has become one of the most debated concepts in today's global education industry. While some speak in favour of e-learning, others criticize e-learning and state that it cannot cultivate better results compared to traditional learning. In today’s COVID situation, e-learning has become necessary for universities around the world, this research has once again focused on this topic to identify whether e-learning can positively influence the performance of students or not. While identifying the same, three factors are selected that are technical competency, e-learning standards, and e-learning infrastructure. After collecting data and information from existing empirical research works, it was found that e-learning can cultivate positive results in terms of student’s performance in different universities and classes. However, it was found that for that positive performance, technical competency must be high and the standard of materials shared through e-learning must be effective enough. In terms of infrastructure, contradictory results are found as one research work stated that it is not vital for improved performance, while the other stated that it is important for better academic performance. Overall, this research identified that e-learning can increase academic performance with the right tools and techniques implemented with it.
Flipped Classroom and Its Impact on Diverse Variables: An Appraisal
Authors: Varghese Ancy , Sood Parul
Published: April 2022

A country like India remains far from claiming universal literacy. According to the estimate based on Census 2011 data, literacy rate in India varies from lowest in Bihar (63.8%) to highest in Kerala (93.9%). In Jharkhand, where the author is working currently, it was only 67.6% in 2011. The New Education Policy 2020 of India aims at appropriate integration of technology into all levels of education, including preparation and development of the teacher to improve teaching, and learning and evaluation processes there by enriching access of education to all citizens, especially disadvantaged groups. In this respect, flipped classroom methodology appears to be a relevant strategy to transmit the learning concepts to the learner. This study examines the effectiveness of this approach on different variables like quality of students’ learning, student engagement and retention of knowledge, students‘ performance, interaction between educators and students, its effectiveness, students’ satisfaction and attendance, experience of students, students’ perception, achievement, attitude towards society and environment, relationship among different components like teacher, taught and peer leader, and self-direction. The majority of studies advocate positive effects, whereas some stand by negative ones. A redesigned model, such as the flipped-mastery model, which can alleviate the shortcomings, can be adopted for a better effect.
The Influence of Cr-Additives on the Polarization Resistance of Praseodymium-Doped Ceria Cathodes for Solid Oxide Fuel Cells
Authors: Staerz Anna , Seo Han Gil , Klotz Dino , Kim Dennis S. , LeBeau James M. , Tuller Harry L.
Published: April 2022

While Cr poisoning of the oxygen reduction reaction (ORR) at SOFC cathodes is widely agreed to involve deactivation of oxygen exchange sites, the degradation mechanism remains ambiguous. Here, we selected an alternative cathode material Pr0.1Ce0.9O2−

δ
,

free of Sr segregation, to systematically investigate the effect of Cr-induced degradation in ORR. We expand on our previous studies in which the acidity/basicity of binary additives was found to be a strong indicator of the rate of oxygen surface exchange, by electrochemically investigating the ORR activity of the PCO cathode by impedance spectroscopy. Serial infiltration with acidic Cr-based oxides was found to degrade ORR activity as reflected in a 20-fold increase in area specific resistance (ASR) without corresponding changes in activation energy, with the opposite trend obtained with Ca-based oxides. Detected changes in total capacitance, attributed to changes in surface capacitance, also suggest depressed/enhanced PCO surface redox behavior with Cr/Ca-based infiltrants. Taken together, these results point to a more universal source of ORR poisoning/activation, based on acidity/basicity, rather than physical blocking of active sites. With this improved understanding, one can expect progress to be made in the coming years in optimizing means for protecting catalytic surfaces from degradation and/or improving their performance.
A Low-Cost Metal-Free Graphite Felt Electrode for Coal-Assisted Water Electrolysis for Hydrogen Production
Authors: Chen Shuai , Zhou Wei , Ding Yani , Zhao Guangbo , Gao Jihui
Published: April 2022

Cheap, active and stable electrodes are vital for coal-assisted water electrolysis for hydrogen production (CAWE). Conventional CAWE uses relatively costly metal-based anodes such as Pt, SnO2/Ti, and IrO2-RuO2/Ti. Previous work confirms that metal-free carbon anodes, however, demonstrate excellent performance in biomass-assisted water electrolysis. Inspired by this, this work examines the feasibility and effectiveness of low-cost graphite felt (GF) anodes in CAWE. The results show that GF is a promising candidate for CAWE. Compared to Pt, SnO2/Ti, Pt/Ti, IrO2-RuO2/Ti, and IrO2-Ta2O5/Ti, GF has higher reactivity for the CAWE. The current density is higher than 5 mA cm−2 when the cell voltage is 1 V for coal electrolysis at Pt∥GF. When the current density is 1 mA cm−2, 5 mA cm−2, 10 mA cm−2, and 50 mA cm−2, the cell voltage of water electrolysis at Pt∥IrO2-RuO2/Ti is 1.84 times, 1.64 times, 1.50 times and 1.13 times that of coal electrolysis at Pt∥GF, respectively. Compared with precious metal-based electrodes, GF electrodes used for CAWE can greatly reduce the cost. Therefore, this study provides important guidance for the industrial development of CAWE.
An Assessment of Aluminum Electrodeposition from Aluminum Chloride/4-ethylpyridine Ionic Liquid at Ambient Temperature
Authors: Chen Jou-An , Chen Po-Yu , Sun I-Wen
Published: April 2022

The electrodeposition of aluminum from the ionic liquids (ILs) obtained from complexation of aluminum chloride with a neutral ligand, 4-ethylpyridine (AlCl3/4-EP), was assessed using voltammetry, chronoamperometry, and constant potential electrolysis. It is found that reduction current of the AlCl3/4-EP with a molar ratio of 1.3/1 is higher than that with a molar ratio of 1.1/1, suggesting that the reduction of [AlCl2(4-EP)]+ is thermodynamically easier than [AlCl2(4-EP)2]+. While the Al(III)/Al redox is chemically reversible, the reaction is not diffusion limited but kinetically limited resulted from the slow bond-breaking of the bulky 4-EP ligands in the [AlCl2(4-EP)]+ complex cations as well as the adsorption of un-complexed 4-EP molecules on the electrode surface. The kinetic limitation was also observed in the chronoamperometric study of nucleation process. Electrodeposition of Al was conducted on copper foils at 310 K and characterized with scanning electron microscope (SEM) and X-ray diffraction (XRD). The SEM images reveal that the morphologies of the aluminum deposits are dependent on the composition of the IL and the deposition potential whereas the XRD analysis confirms that all the deposits have same crystal texture.
Highly Efficient Photocatalytic Degradation of Methyl Orange by SnO2/Carbon/PANI Composite
Authors: Li Lili , Li Wei , Jiang Ke , Suo Yanhua , Shu Jing , Nie Chunhong
Published: April 2022

Polyaniline (PANI) modified carbon-containing SnO2 composites (SnO2/Carbon/PANI) have been successfully synthesized via a simple liquid phase synthesis method. The compositions, structures and properties of as-synthesized samples were characterized by XRD, FT-IR, BET, XPS, SEM and TEM. Meanwhile, the degradation mechanism of the photocatalysts was put forward. The photocatalytic tests showed that the SnO2/Carbon/PANI composites have excellent photocatalytic activity for methyl orange (MO) degradation under visible light irradiation and the MO can be degraded to 98% within 10 min. The photocatalytic activity is still excellent after three cycles and as-synthesized samples have emerged as powerful foundation for further industrial application.
Effect of oral hormonal contraceptive pill use on the hemodynamic response to the cold pressor test
Authors: Jacob Dain W. , Voshage Aaron M. , Harper Jennifer L. , Limberg Jacqueline K.
Published: April 2022

Acute increases in sympathetic nervous system activity often elicit peripheral vasoconstriction and increases in blood pressure (BP). Given sympathetic support of BP is modulated by ovarian sex hormones (e.g., estradiol), we sought to examine the effect of menstrual cycle and oral hormonal contraceptive pill (OC) phase on the hemodynamic response to acute increases in sympathetic nervous system activity via the cold pressor test. We show OC participants exhibit paradoxical vasodilation during acute sympathetic activation compared with participants with natural menstrual cycles; notably, group differences were unaffected by menstrual/pill phase.
Research on Solving Path of Negative Effect of “Information Cocoon Room” in Emergency
Authors: Liu Wei , Zhou Wei
Published: April 2022

The “information cocoon” can hinder the normal dissemination and flow of emergency information during emergencies. It is important to explore the factors of this effect and to resolve the negative effects of the information cocoon, so as to help the public to “break out of the cocoon” and help the government to better promote emergency information management. Based on information ecology theory and the S‐O‐R model, this study designed questionnaires using a Likert five‐level scale and selected 388 publics from several smart city pilot areas in Changsha, Zhuzhou, Shaoshan, and Yueyang cities in Hunan Province. Field research was conducted based on four factors, information ontology, information technology, government regulation, and social network, and empirical analysis was conducted through structural equations. The study shows that information ontology, information technology, government regulation, and social networks have significant effects on the information cocoon effect by influencing the reinforcement of public information preferences. Among them, government regulation (P = 0.34) has the most significant effect on the reinforcement of public information preferences, followed by information ontology (P = 0.32) and social networks (P = 0.31), and information technology (P = 0.29) has the weakest effect. Combining the results of empirical analysis, we propose a four‐dimensional path of “information‐technology‐regulation‐value” to break the cocoon. By optimizing information ontology, using technology for good governance, promoting algorithmic fairness, and enhancing social stickiness, we help the public break through the shackles and negative effects of the information cocoon and promote the harmonious, stable, and healthy development of the emergency information field.
Palovarotene Can Attenuate Heterotopic Ossification Induced by Tendon Stem Cells by Downregulating the Synergistic Effects of Smad and NF-κB Signaling Pathway following Stimulation of the Inflammatory Microenvironment
Authors: Huang Junchao , Lin Jialiang , Li Congbin , Tang Bo , Xiao Haijun
Published: April 2022

Heterotopic ossification (HO) is defined as the formation of bone tissues outside the bones, such as in the muscles. Currently, the mechanism of HO is still unclear. Tendon stem cells (TSCs) play important roles in the occurrence and development of HO. The inflammatory microenvironment dominated by macrophages also plays an important role in the course of HO. The commonly used clinical treatment methods, such as nonsteroidal anti-inflammatory drugs and radiotherapy, have relatively large side effects, and more efficient treatment methods are needed in clinical practice. Under physiological conditions, retinoic acid receptor (RAR) signal transduction pathway inhibits osteogenic progenitor cell aggregation and chondrocyte differentiation. We focus on palovarotene, a retinoic acid γ-receptor activator, showing an inhibitory effect on HO mice, but the specific mechanism is still unclear. This study was aimed at exploring the specific molecular mechanism of palovarotene by blocking osteogenic differentiation and HO formation of TSCs in vitro and in vivo in an inflammatory microenvironment. We constructed a coculture model of TCSs and polarized macrophages, as well as overexpression and knockdown models of the Smad signaling pathway of TCSs. In addition, a rat model of HO, which was constructed by Achilles tendon resection, was also established. These models explored the role of inflammatory microenvironment and Smad signaling pathways in the osteogenic differentiation of TSCs which lead to HO, as well as the reversal role played by palovarotene in this process. Our results suggest that, under the stimulation of inflammatory microenvironment and trauma, the injured site was in an inflammatory state, and macrophages were highly concentrated in the injured site. The expression of osteogenic and inflammation-related proteins, as well as Smad proteins, was upregulated. Osteogenic differentiation was performed in TCSs. We also found that TCSs activated Smad and NF-κB signaling pathways, which initiated the formation of HO. Palovarotene inhibited the aggregation of osteogenic progenitor cells and macrophages and attenuated HO by blocking Smad and NF-κB signaling pathways. Therefore, palovarotene may be a novel HO inhibitor, while other drugs or antibodies targeting Smad and NF-κB signaling pathways may also prevent or treat HO. The expressions of Smad5, Id1, P65, and other proteins may predict HO formation.
[Retracted] Bhavana, an Ayurvedic Pharmaceutical Method and a Versatile Drug Delivery Platform to Prepare Potentiated Micro‐Nano‐Sized Drugs: Core Concept and Its Current Relevance
Authors: Sharma Rohit , Bedarkar Prashant , Timalsina Deepak , Chaudhary Anand , Prajapati Pradeep Kumar
Published: April 2022

Scholars of ancient Ayurveda (Indian system of medicine) were extremely reasonable and had strong scientific rationality in fundamental concepts, which are also applied to drug manufacture and therapy. Bhavana is a unique traditional method of transformation of raw material/substances into the drug by levigation or wet grinding of powdered drugs with juice/decoction/solution of plant, animal, or mineral origin. This method adds the unique capability of affecting the physicochemical and biological properties of a drug, making the drug quicker, augmented, and persistent action with minimal dose. Despite the fact that Bhavana has a wide range of applications in Ayurvedic pharmaceutics, there is only a limited amount of knowledge of its fundamental notions. A comprehensive review was performed on the core concepts of Bhavana, alongside its possible pharmacotherapeutic effects and relevance in drug development, by probing Ayurvedic claims in light of published pharmaceutical, analytical, and pharmacological reports. Various processes, such as thermo‐ and photochemistry, physicochemical reactions, and mechanic chemical changes, appear to occur during Bhavana.
Session-Based Recommendation with GNN and Time-Aware Memory Network
Authors: Wen Yan , Kang Shitao , Zeng Qingtian , Duan Hua , Chen Xin , Li Wenkai
Published: April 2022

The goal of the session-based recommendation system (SBRS) is to predict the user’s next behavior based on anonymous sessions. Since long-term historical information of users is not available, deep learning technology has become the mainstream technology in session-based recommendation systems instead of traditional content-based recommendation methods. However, most SBRS methods only consider the session itself, ignoring the collaborative information from other sessions. Even if some SBRS models consider collaborations between sessions, they mostly use the click order to calculate the similarity only and ignore the time the user spends on different items, which might imply the user’s varying interest on these items. In this paper, we propose a session-based recommendation model with GNN and time-aware memory networks (SR-GTM), which learns the user’s interest representation by combining the information from the session itself and the collaborative information from relevant neighbor sessions. Specifically, SR-GTM mainly includes inner feature extraction module (IFEM) and outer feature extraction module (OFEM). IFEM uses GNN to learn the session features based on its item sequence, and OFEM uses a memory network with dwell time information encoded to extract collaborative information. Finally, SR-GTM aggregates IFEM and OFEM by the gating mechanism and then decodes the output by a softmax layer to obtain the recommendation score for each candidate item. Experiments on three public datasets Yoochoose1/64, Yoochoose1/4, and RetailRocket show that SR-GTM achieves optimal performance compared with other state-of-the-art methods. More specifically, SR-GTM has improvements of 0.77%, 0.38%, and 3.63% over the best baseline method in P@20 and has improvements of 2.91%, 2.52%, and 2.49% in MRR@20, respectively.