bluuebunny/crossref_metadata_2025_split huggingface dataset:
Energy Harvesting System Design and Optimization Using High Bandwidth Rectenna for CUBESAT used in Asteroid Detection
Authors: Marriwala Nikhil , B Debarpita 
Published: June 2022

Abstract
The aim of this paper is to structure a compact size rectenna for cubeSat applications for asteroid detection. The scale of the antenna is to kept as small as possible 18 X 10 mm. The antenna designed here is probably going to own its applications in satellite communication system. The antenna designed in this project is structured in such a way that it is covering a good wide range of frequency from X-band to K-band.The aim of this paper is to design a cubesat rectenna which will not only make cubesat cost effective but also lighter weight with RF to DC power conversion which will reduce use of solar panels, solar cells or solar array. At first antenna is designed in HFSS keeping its size in mind and simulated than rectifier is designed in MATLAB Simulink and antenna is interfaced with it for conversion process. Rectenna design converts 2.85963102361 watt power to 14.62 watt power for 9 GHz and 3.19124391714 watts to 16.48 watts using a voltage multiplier circuit. Also, two way transmissions by antenna is shown uplink frequency of 18.6 GHz-18.8GHz and downlink frequency of 8.45GHz-8.5GHz.The antenna shown RF output power of 2.85963102361 Watts and in terms of dBW it is 4.5631dBW at 9 GHz and of 3.19124391714 watts and in terms of dBW it is 5.0396dBW at 19 GHz.Return loss for satellite must be less than − 10dB and in this designed this objective is also achieved. DC power in the range of 5–20 Watt is required for desired cubesat mission and as mentioned it generates power of 14.62 watts and 16.48 watts.The main aim of this rectenna is to create a cubesat system suitable for planet defense from asteroid. In this work various parameters like Return loss, Gain, Radiation pattern, rectifier design and dc power generated are also discussed.
Graph Convolution Network for Social Recommendation
Authors: Zhang Yuanyuan , Shi Xinchen , Zhang Yonglong , Zhu Junwu 
Published: June 2022

Abstract
In recent years, due to the characteristics of graph convolutional networks (GCN) that can effectively integrate node information and topological structure, they have shown strong capabilities in graph data representation learning. Since the data in the social recommender systems exists in a graph structure, these characteristics of GNN greatly promote the development of social recommendation. However, the construction of GCN-based social recommender systems faces the following challenges: (1) Users exist in both user-item interaction graphs and social relationship graph, and items exist in both user-item interaction graphs and item collaborative similarity graphs; (2) There is high-order connectivity of the user-user social relationship and the item-item collaborative similar relationship; (3) The embeddings of users and items come from different two graphs have different semantic contributions. In order to solve the above three challenges simultaneously, this paper proposes G raph C onvolution Network for S ocial R ecommendation (GCSR), which models the user-item interaction network, social network and item collaborative similar network into a unified network. Specifically, we provide a principled method to explicitly capture the high-order connectivity of user-items to improve embedding. In addition, the gating mechanism is used for feature fusion to model heterogeneous strengths. A large number of experiments on two real datasets prove the effectiveness of the proposed framework GCSR.
HPTLC Fingerprinting Reveals Leaf and Roots Phytochemical Variability in Developmental stages of Withania somnifera
Authors: Lingfa Lali , Gugulothu Baloji , Jagtap Sandhya , Ankanagari Srinivas 
Published: June 2022

Abstract
Background
Withania somnifera has been the foundation of numerous contemporary medicines today for treatment of various diseases. However, phytochemical variability profile is lacking in the root and leaf organs.
Aim
This study was aimed to elucidate the phytochemical profile in seedling, vegetative and reproductive stages of leaf and roots in W. somnifera using High performance thin layer chromatography (HPTLC) fingerprinting.
Methods
The HPTLC with dual wavelength UV (254/366 nm) was used for the analysis of phytochemical variation in leaf and root methanolic extracts of W. somnifera.
Results
HPTLC chromatograms in 366 nm, 254 nm, and normal day light, seedling, vegetative and reproductive stages leaf and root exhibited bands variability. At 450 nm leaf HPTLC fingerprints in seedling stage showed five peaks with Rf values in the range of 0.42 to 0.90, vegetative stage with nine peaks of Rf values in range of 0.10 to 0.89, and reproductive stage with six peaks of Rf values in range of 0.30 to 0.92. In root showed six peaks with Rf values in range of 0.00 to 0.82 in seedling stage, ten peaks with Rf values in range of 0.00 to 0.96 in vegetative stage, seven peaks with Rf values in range of 0.01 to 0.91 in reproductive stage. In roots, higher peak areas were found at the reproductive stage (3.33%) compared to vegetative stage (1.65%).
Conclusion
The comparative HPTLC fingerprints of leaves and roots in W. somnifera presented phytochemical variability in leaf and root that varied with developmental stages.
Performance Analysis of NOMA Integrated Hybrid Satellite Terrestrial Communication System using ML
Authors: Prasad Priyanka , MK Arti , Jain Aarti 
Published: June 2022

Abstract
The Non Orthogonal Multiple Access (NOMA) is a promising technology for future communication system due to its ability to offer services to multiple users with better connectivity and low latency. The NOMA based Cooperative Relay System (NOMA-CRS) is used to improve the spectral efficiency as compared to conventional Cooperative Relay System (CRS). In this paper, the performance of NOMA over hybrid satellite terrestrial communication system is analyzed over two different fading channels- Shadowed Rician fading channel and Nakagami-m fading channel in two phases of downlink transmission and also derived the expression for end to end Bit Error Rate of proposed model assisted with cooperative relays. The results have shown significant performance with variations in the derived parameters and validated in extensive simulations.
Ranking of Empirical Evapotranspiration Models in Different Climate Zones of Pakistan
Authors: Hamed Mohammed Magdy , Khan Najeebullah , Shahid Shamsuddin , Muhammad Mohd Khairul Idlan 
Published: June 2022

Abstract
Accurate estimation of evapotranspiration (ET) is vital for water resources development, planning and management, particularly in the present global warming context. A large number of empirical ET models have been developed for estimating ET. The main limitations of this method are that it requires several meteorological variables and an extensive data span to comprehend the ET pattern accurately, which is not available in most developing countries. The efficiency of 30 empirical ET models has been evaluated in this study to rank them for Pakistan to facilitate the selection of suitable models according to the availability of data. Princeton Global Meteorological Forcing daily climate data with a 0.25°×0.25° resolution for 1948–2016 was utilized. The ET estimated using Penman-Monteith (PM) was considered as the reference. Multi-criteria group decision-making (MCGDM) was used for the ranking of the models for Pakistan. The results showed the temperature-based Hamon as the best model for most Pakistan, followed by Hargreaves-Samani and Penman models. Hamon also showed the best performance in terms of different statistical metrics used in the study with a mean bias (PBias) of -50.2%, mean error (ME) of -1.62 mm and correlation coefficient (R2) of 0.65. Ivan showed the best performance among the humidity-based models, Irmak-RS and Ritch among the radiation-based models and Penman among the mass transfer-based models. Northern Pakistan was the most heterogeneous region in the relative performance of different ET models.
Gestational bisphenol A exposure impacts hepatic lipid metabolism in male offspring rats by regulating mTOR/CRTC2/SREBP1
Authors: Yang Qiaoqiao , Mao Yaping , Wang Juan , Yu Haiyang , Zhang Xuan , Pei Xiucong , Duan Zhiwen , Xiao Chunling , Ma Mingyue 
Published: June 2022

Abstract
Lipid metabolism is an important biochemical process in the body. Recent studies have found that environmental endocrine disruptors play an important role in the regulation of lipid metabolism. Bisphenol A (BPA), a common environmental endocrine disruptor, has adverse effects on lipid metabolism, but the mechanism is still unclear. This study aimed to investigate the effects of gestational BPA exposure on hepatic lipid metabolism and its possible mechanism in male offspring. The pregnant Sprague-Dawley rats were exposed to BPA (0, 0.05, 0.5, 5 mg/kg/day) from day 5 to day 19 of gestation to investigate the level of triglyceride (TG) and the expression of liver lipid metabolism-related genes in male offspring rats. The results showed that compared with the control group, the TG level in serum and liver in BPA-exposed groups was increased. And the expressions of liver fatty acid oxidation related genes, such as peroxisome proliferators-activated receptor α (PPARα) and carnitine palmitoyl transferase 1α (CPT1α), were down-regulated. However, the expressions of fatty acid synthesis related genes, such as sterol regulatory element binding proteins 1 (SREBP-1), acetyl-CoA carboxylase 1 (ACC1), fatty acid synthase (FAS) and stearoyl-CoA desaturase 1 (SCD-1), were up-regulated. The increased protein levels of mTOR and p-CRTC2 suggested that CREB-regulated transcription coactivator 2 (CRTC2) might be an important mediator in the mTOR/SREBP-1 pathway. In conclusion, these results demonstrated that mTOR/CRTC2/SREBP-1 could be affected by gestational BPA exposure, which may involve in the lipid metabolic disorders in later life.
A Quasi Variational-Hemivariational Inequality for Incompressible Navier-Stokes System with Bingham Fluid
Authors: Dudek Sylwia , Migorski Stanislaw 
Published: June 2022

Abstract
In this paper we examine a class of elliptic quasi-variational inequalities which involve a constraint set and a set-valued map. First, we establish existence of solution and the compactness of the solution set. The approach is based on results for an elliptic variational inequality and the Kakutani-Ky Fan fixed point theorem. Next, we prove an existence and compactness result for a quasi variational-hemivariational inequality. The latter involves a locally Lipschitz functional and a convex potential. Finally, we present an application to the stationary incompressible Navier-Stokes equation with mixed boundary conditions which model a generalized Newtonian fluid of Bingham type.2020 Mathematics Subject Classification. 35J87, 49J40, 76A05.
Development and Analysis of Human Hair Fiber and Chicken Feathers Reinforced Composite
Authors: Worku Tesfaye , Nachippian Sukumar 
Published: June 2022

Abstract
In the current year, composites have been concerned with considerable importance as a potential operational material. Many works have been carried out to enhance the mechanical properties of composites. Chicken feather, human hair and hairs of other birds and animals are commonly described as a waste product. Currently, available disposal methods such as burying and burning of these waste by-products are contributing to environmental pollution. In this research work composite was developed using human hair & chicken feather fiber and analysis the mechanical and physical property of the developed composite sample. Four different composition ratio composite samples were fabricated and then physical and mechanical properties were tested according to standards. Both flexural and compressional strength increase for the first two composite samples, then after it shows a gradual decrease when we have increased the fiber content and decreased resin and sample show that the amount of water absorption in percentage increases when the fiber content increases, and the matrix material (polyester resin) decrease. This research study indicates that using human hair and chicken feather fibers as reinforcement in a polymer matrix could successfully develop a composite material in terms of high strength and rigidity for lightweight house ceiling board material.
Give the nose some credit: rationale for a need to include scent training in medical education
Authors: Liao En-Dien , Majdinasab Elleana Joy , Le Christopher Q , Ramesh Malvika , Satheeshkumar Anu , Ganapathy Vadivel 
Published: June 2022

Abstract
Medical education largely overlooks the sense of smell in clinical training notwithstanding clear evidence that several diseases carry with them pathognomonic scents that can serve as diagnostic clues. We report here an observational cross-sectional study in which we assessed students’ attitudes toward the utility of scent in the process of medical diagnosis as well as their competence and confidence in being able to apply recognition of odor to specific diseases in the clinical setting. We found that nearly 90% of medical students felt that formal incorporation of scent in their medical training would make them more competent physicians. However, approximately 80% of them did not feel confident using scent as a diagnostic aid. Currently, there is a lack of emphasis on the usefulness of the sense of smell in modern medical education, and in the study reported here, we consider the rationale for possible inclusion of olfactory exposure in clinical training.
Exploring B2B Chatbots adoption experiences: Lessons for successful implementation in Businesses
Authors: kaushal vaishali , Yadav Rajan 
Published: June 2022

Abstract
Artificial Intelligence empowered Chatbots are altering the nature of service interfaces which has further resulted in raised expectations from Chatbots to understand customer’s social interactions and respond them within the turnaround time. To close this research gap, we conduct an exploratory study in two phases-Industry’s perspective and B2B customer’s perspective and analyse results with the help of NVIVO 12 plus and Leximancer. The findings reveal perceived risk with respect to Chatbots is high, complex pricing structure along with non-availability of testing options makes the pre purchase more complex. Moreover, interactive speed, Customization especially with respect to language issues, Integration with other platforms is some of the major themes which influence Customer Experience. Advancements in AI, natural Language processing (NLP) and more testing at all phases will bring efficiency, automation first strategies. Our findings suggest Chatbots must provide a more personalized, scalable and omni channel engagement and focus on delivering more enhanced customer experience. Chatbots must offer a grievance management dashboard where the customer can see live queries, resolved queries, present queries status etc to get transparency. Chatbots streamline the lead qualification process, greatly improve, and speed up the data collection therefore, enhancing customer experience.
Towards Uncertainty in Decision: A Survey on Recent Advances and Challenges in Bayesian Reinforcement Learning
Authors: Wang Zicheng , Meng Hua , Zhou Zhengchun , Feng Yanghe , Gao Yang , Yu Chao 
Published: June 2022

Abstract
Reinforcement learning is a research paradigm that is commonly utilized to tackle problems involving sequential decision-making. Agents learn optimum policy from samples generated by interacting with uncertain environments. Bayesian reinforcement learning presents the uncertainty measure of probability significance based on sequential decision-making, which plays a proper auxiliary function in the optimization of agent control policies, attracting a lot of study attention. This paper provides an overview of contemporary Bayesian and reinforcement learning methods in this setting. We begin by outlining the many types of reinforcement learning and Bayesian approaches, as well as their characteristics. Then we review the most sophisticated Bayesian reinforcement learning approaches from the perspective of uncertainty measurement and control, as well as summarize and discuss various challenges and related research in its expansion to complicated control tasks. Applying the Bayesian technique with reinforcement learning in diverse disciplines are then discussed. Finally, we highlight the current challenges of Bayesian reinforcement learning and future research topics that might help promote Bayesian reinforcement learning.
Etiology analysis for full-term newborns with severe hyperbilirubinemia in eastern Guangdong
Authors: Xu Jia-Xin , Lin Fen , Wu Yong-Hao , Ma Yu-Bin , Yang Li-Ye 
Published: June 2022

Abstract
Objective
To explore the etiological characteristics of severe hyperbilirubinemia in full-term newborns of eastern Guangdong.
Methods
Full-term newborns with severe hyperbilirubinemia in one hospital from January 2012 to December 2021 were retrospectively analyzed. The etiology was determined according to the laboratory results and clinical manifestations.
Results
Among 1602 full-term newborns with hyperbilirubinemia in Chaozhou area, 32.20% (580/1602) was severe hyperbilirubinemia, including 213 newborns with TSB levels reaching the recommended exchange transfusion levels and 52 cases diagnosed with prolonged jaundice. Among the causes of severe hyperbilirubinemia, neonatal hemolysis accounted for 15.17%, infection accounted for 10.17%, G6PD deficiency accounted for 9.13%, and the coexistence of multiple etiologies accounted for 6.55%, unknown etiology accounted for 50.00%. ABO hemolysis and G6PD deficiency were the most common causes in the 20 cases with bilirubin encephalopathy. 94 severe hyperbilirubinemia newborns were tested for UGT1A1*6 variant (rs4148323, c.211G > A, p.Arg71Gly,), 9 cases were 211 G to A homozygous variant, 37 cases were 211 G to A heterozygous variant, and 48 cases were wild genotypes.
Conclusion
The main cause for severe hyperbilirubinemia and bilirubin encephalopathy were the hemolytic disease of the newborn, G6PD deficiency and infection. UGT1A1 gene variant was also a high risk factor for neonatal hyperbilirubinemia. Targeted prevention and treatment according to the etiology may reduce the occurrence of bilirubin encephalopathy and kernicterus.
Evaluation of WhatsApp as a Platform for Teledermatology in Botswana: Retrospective Review and Survey
Authors: Koh Erika , Maranga Abena , Yane Tshepo , Ndlovu Kagiso , Jereni Bwanali , Nwako-Mohamadi Maitseo Kuno , Kovarik Carrie , Forrestel Amy , Williams Victoria L 
Published: June 2022

Background
In emerging market countries in sub-Saharan Africa, access to specialty services such as dermatology is limited. Teledermatology is an innovative solution to address this issue; however, many initiatives have been tried without sustained success. Recently, WhatsApp has been used as a store-and-forward telemedicine communication platform for consultation and education in Botswana.

Objective
This study aims to describe the utilization of WhatsApp for teledermatology and the satisfaction levels of participating providers.

Methods
A 2-part pilot study was conducted. First, a retrospective review was performed of WhatsApp communications received by participating dermatologists in Gaborone, Botswana, from January 2016 to December 2019. Sender information, patient demographics and history, response time, diagnoses made, and follow-up recommendations were collected. Second, a 12-question cross-sectional survey was distributed to health care providers who utilized WhatsApp for teledermatology during this period. Descriptive statistics were then performed.

Results
There were 811 communication threads over the study period. The majority (503/811, 62%) of communications were consultations from providers inquiring about a specific patient, followed by multidisciplinary care coordination communications (90/811, 11%). Our in-depth analysis focused on the former. In 323 (64%) provider consultations, dermatologists responded within 1 hour. A diagnosis was made in 274 (55%) consultations. Dermatologists gave treatment recommendations remotely in 281 (56%) consultations and recommended an in-person dermatology visit in 163 (32%). Of the 150 health care providers surveyed, 23 (15%) responded. All respondents (100%) felt that there was a need for teledermatology and improved teledermatology education in Botswana. Moreover, 17 (74%) respondents strongly felt that the guidance received via WhatsApp was high quality, and 22 (96%) were satisfied with WhatsApp as a platform for teledermatology.

Conclusions
This retrospective review and survey demonstrated that WhatsApp is a quick, well-received, and sustainable method of communication between dermatologists and providers across Botswana. The app may offer a solution to the challenges providers face in accessing specialty referral systems, point-of-care education, and medical decision-making support for complex dermatologic cases in Botswana. The information gained from this pilot study can serve as the basis for future telemedicine studies to improve the implementation of teledermatology in Botswana and other resource-limited countries.
The Association Between Dissemination and Characteristics of Pro-/Anti-COVID-19 Vaccine Messages on Twitter: Application of the Elaboration Likelihood Model
Authors: Saini Vipin , Liang Li-Lin , Yang Yu-Chen , Le Huong Mai , Wu Chun-Ying 
Published: June 2022

Background
Messages on one’s stance toward vaccination on microblogging sites may affect the reader’s decision on whether to receive a vaccine. Understanding the dissemination of provaccine and antivaccine messages relating to COVID-19 on social media is crucial; however, studies on this topic have remained limited.

Objective
This study applies the elaboration likelihood model (ELM) to explore the characteristics of vaccine stance messages that may appeal to Twitter users. First, we examined the associations between the characteristics of vaccine stance tweets and the likelihood and number of retweets. Second, we identified the relative importance of the central and peripheral routes in decision-making on sharing a message.

Methods
English-language tweets from the United States that contained provaccine and antivaccine hashtags (N=150,338) were analyzed between April 26 and August 26, 2021. Logistic and generalized negative binomial regressions were conducted to predict retweet outcomes. The content-related central-route predictors were measured using the numbers of hashtags and mentions, emotional valence, emotional intensity, and concreteness. The content-unrelated peripheral-route predictors were measured using the numbers of likes and followers and whether the source was a verified user.

Results
Content-related characteristics played a prominent role in shaping decisions regarding whether to retweet antivaccine messages. Particularly, positive valence (incidence rate ratio [IRR]=1.32, P=.03) and concreteness (odds ratio [OR]=1.17, P=.01) were associated with higher numbers and likelihood of retweets of antivaccine messages, respectively; emotional intensity (subjectivity) was associated with fewer retweets of antivaccine messages (OR=0.78, P=.03; IRR=0.80, P=.04). However, these factors had either no or only small effects on the sharing of provaccine tweets. Retweets of provaccine messages were primarily determined by content-unrelated characteristics, such as the numbers of likes (OR=2.55, IRR=2.24, P<.001) and followers (OR=1.31, IRR=1.28, P<.001).

Conclusions
The dissemination of antivaccine messages is associated with both content-related and content-unrelated characteristics. By contrast, the dissemination of provaccine messages is primarily driven by content-unrelated characteristics. These findings signify the importance of leveraging the peripheral route to promote the dissemination of provaccine messages. Because antivaccine tweets with positive emotions, objective content, and concrete words are more likely to be disseminated, policymakers should pay attention to antivaccine messages with such characteristics.