bluuebunny/crossref_metadata_2025_split huggingface dataset:
A System Dynamic Model of Water-Land-Food-Energy-Ecosystem-Environment-Economic-Social Nexus for Western Lake Erie Basin-USA
Authors: El-Gafy Inas , Apul Defne 
Published: June 2021

Abstract
The concept of water-food-energy nexus has been widely studied in the past decade. In this paper we expand on this concept to Water-Food-Land-Energy-Ecosystem-Environment Nexus with economic and social aspects based on the life cycle assessment thinking. Set of Environment Footprint Assessment (EFA), Life Cycle Assessment (LCA), and Socio-Economic Assessment (SEA) indicators are proposed to apply this approach. Decision Support System for Water-Land-Food-Energy-Ecosystem-Environment-Economic-Social nexus (SD-WLF4ES-Nexus) applying system dynamic model approach for simulating this tackle is utilized. SD-WLF4ES-Nexus is applied to predict the WLF4ES nexus of one of the main crop, corn crop, in twenty counties located in Western Lake Erie Basin (WLEB) in USA for the period 2016-2030. The prediction is based on scenarios for population, planted and harvested land, and yield, crop production use by segments, and crop production costs and returns. A matrix for WLF4ES nexus of corn crop in WLEB is developed. This matrix can help in developing polices and strategies for managing the nexus in the basin.
Analysis of Multiuser Detectors and Performance improvement in DS-CDMA system using Multistage Multiuser Detection Techniques
Authors: Jaladanki Ravindrababu , Ede Krishnarao , Yasoda Raja Rao 
Published: June 2021

Abstract
Among the various interferences, the Multiple Access Interference (MAI) is a significant issue in Direct Sequence Code Division Multiple Access (DS-CDMA) system due to its users. When the number of users is increasing the MAI is likewise increments, subsequently the system performance progressively diminishes particularly in fading environment. In this paper, the system performance is improved by the proposed multistage multiuser detection technique called Multistage Multiuser Differencing Partial Parallel Interference Cancellation (DPPIC). This is the combination of Partial Parallel Interference Cancellation (PPIC) and Differencing Parallel Interference Cancellation (DPIC). Multistage Multiuser Parallel Interference Cancellation (PIC) and Multistage Multiuser PPIC techniques that exist gave improved system performance meaning as the number of stages increases the MAI decreases but at the cost of increased computational complexity. The computational complexity was reduced by utilizing Multistage Difference PIC (DPIC) technique but with no improvement in the performance. To improve the system performance as well as reduce the computational complexity Multistage Multiuser Partial Differencing Parallel Interference Cancellation (PDPIC) method can be used. The simulation results show that the proposed DPPIC technique performs better than PIC, PPIC and PDPIC in terms of Bit Error Rate (BER) versus normalized signal amplitude ( i.e., E b / N 0 ), but computational complexity slightly more than PDPIC in fading environment.
Multi-Model Coupling Water Demand Prediction Optimization Method for Megacities Based on Time Series Decomposition
Authors: Liu Xin , Sang Xuefeng , Chang Jiaxuan , Zheng Yang 
Published: June 2021

Abstract
The fluctuation of water supply is affected by the living habits and population mobility, so the daily water supply is significantly non-stationarity, which presents a great challenge to the water demand prediction based on data-driven model. To solve this problem, the Hodrick-Prescott (HP) and wavelet transform (WT) time series decomposition methods, and ensemble learning (EL) were introduced, coupling model bidirectional long short term memory (BLSTM), seasonal autoregressive integrated moving average (SARIMA) and Gaussian radial basis function neural network (GRBFNN) were developed, and interval prediction was carried out based on student's t-test (T-test). This research method was applied to the daily water demand prediction in Shenzhen and cross-validation was performed. It is found that the decomposed subseries has obvious law, and WT is superior to HP decomposition method. However, the maximum decomposition level (MDL) of WT should not be set too high, otherwise the trend characteristics of subseries will be weakened. The results show that the potential characteristics and quantitative relationships of historical data can be learned accurately based on WT and coupling model. Although the corona virus disease 2019 (COVID-19) outbreak in 2020 caused a variation in water supply law, this variation is still within the interval prediction. The WT and coupling model satisfactorily predicted water demand and provided the lowest mean square error (0.17%), mean relative error (0.1) and mean absolute error (3.32%) and the highest Nash-Sutcliffe efficiency (97.21%) and correlation coefficient (0.99) in testing set.
Morphophysiology and Cryopreservation of Seeds of Dendrobium Nobile Lindl. (Orchidaceae) at Different Stages of Development
Authors: Kolomeitseva Galina L , Nikishina Tatiana V , Babosha Alexander V , Ryabchenko Andrey S , Vysotskaya Olga N 
Published: June 2021

Abstract
We studied the seed maturation of Dendrobium nobile Lindl to establish the optimal stage for green pod culture and long-term storage in liquid nitrogen. It was found that the immature seeds can germinate in vitro starting from 3 months after pollination (MAP) but only develop up to the stage of embryo swelling or protocorm without rhizoids. The maximum staining of embryos with vital dyes FDA and TTC occurs at 4 and 5 MAP that corresponds to the release of suspensor beyond the embryo sac. Embryo staining does not correlate with germination capacity and seed viability in cryogenic storage. The immature seeds acquire resistance to freezing and drying in airflow at the age of 6 MAP. The time of technical maturity for green pod culture and cryopreservation may be reduced from 12 MAP to 6–7 MAP.
An Ensemble Intrusion Detection Model For Internet of Things Network
Authors: Choudhary Sarika , Kesswani Nishtha , Majhi Sudhan 
Published: June 2021

Abstract
The advancements of technology are playing a significant role in protecting the data from intruders. In this paper, a robust network intrusion detection system (IDS) is proposed for Internet of Things (IoT) using deep learning approaches. The type of intrusions we adopted in this work are distributed denial of service (DDoS) and replay attack. Our proposed work is divided into three sections, namely, node deployment, threat detection modelling, and prevention modelling. For detection, ensemble algorithm has been used, i.e., deep neural network (DNN) and support vector machine (SVM). SVM is used to identify the suspected route and DNN is used to identify the suspected node out of suspected routes. The chosen route ensures that it is prevented from attackers by incorporating the throughput and packet delivery ratio (PDR). The simulation results are obtained on the basis of accuracy, recall, precision, and F-measure to determine the effectiveness of the proposed approach. The precision, recall, F- measure, and accuracy of correctly identified intruders are 98.12%, 98.04%, 94.88%, and 98.68%, respectively, which is an improvement over the previous studies. The efficacy of the designed model for IoT is compared with the existing approaches.
An Ultrathin Graphite Based Absorber for Wearable Applications
Authors: Avinash  , Gupta Nisha 
Published: June 2021

Abstract
In this paper, a low-cost, flexible, ultrathin absorber comprising a simple square patch-shaped frequency selective surface (FSS) is proposed for wearable applications. The FSS based absorbing structure contains periodic graphite patch pattern placed on a thin paper substrate, and backed with a copper foil-based ground plane. The dimension and periodicity of the unit cell are 0.31λo and 0.36λo respectively, while the thickness of the absorber is approximately λo/85, where λo is the wavelength of free space at 10 GHz. The characteristics of the FSS absorber is optimized in terms of unit cell periodicity, and dielectric substrate height using a full-wave high frequency structure simulator software (HFSS). The effects of the parameters are also examined using equivalent circuit approach. The proposed absorber shows insensitivity towards the angle of incidence as well as angle of polarization. Finally, a prototype model is fabricated, measured, and validated with simulation results. A good agreement is depicted between simulated and experimental models. The proposed absorber finds application in the field of wearable electronics, medical, and automotive applications for effective mitigation of the EMI.
Assessment of the Marine Ecotoxic State in the Moroccan Coastal Area Anza-Taghazout following the Installation of Two Wastewater Treatment Plants: A Multibiomarker Study using Mytilus Galloprovincialis
Authors: MOURABIT YOUSSEF EL , Agnaou Mustapha , Alla Aicha Ait , Moukrim Abdellatif 
Published: June 2021

Abstract
The aim of the present study is the first to evaluate the ecotoxic state of the marine environment in Anza-Taghazout coasts (Morocco) after installation of two Wastewater Treatment Plants using a natural population of marine bivalves M. galloprovincialis. These coasts are exposed to many discharges generating, thus, different sources of pollutants. These pollutants can modulate the physiological responses of marine bivalves to environmental stress. In this context, a multi-biomarker approach consisting of a battery of biomarkers evaluation was used to assess the response of these species to stress. In the whole soft tissues of M. galloprovincialis, four biomarkers were evaluated: Acetylcholinesterase (AChE), Glutathione S-transferase (GST), Catalase (Cat) and malondialdehyde activity (MDA). In parallel, physico-chemical parameters were measured in the marine water of Anza-Taghazout within three selected sites: S1 considered as ‘hotspot’ located at Anza city; S2 located near of Aourir city and the third site, S3 ‘reference’ located in Imouran beach. Our results showed that activities of both Gluthation-S-Transferase and Catalase were higher in M. galloprovincialis collected from site S1, but high values of Malondialdehyde and Acetylcholinesterase activities were observed successively at S3 and S2. Application of Integrated Biomarker Response index (IBR) was suitable for classifying the stress response in the M. galloprovincialis but did not allow to evaluate the level of the xenobiotic exposure in the studied sites. The statistical results did not show any significant differences between the three studied sites and therefore S1 has recently become clean due to the installation of two wastewater treatment plants.
Base on the Public Scientific Quality Improvement Research on Risk Early Warning of Online Shopping
Authors: Li Xiaoyan , Cao Lixia , Wang Tonghui , Feng Xiangchu 
Published: June 2021

Abstract
In order to improve the scientific quality of the public, the Chinese Association for Science and Technology has put forward a call to combine popular science education with leisure and entertainment. In view of the fact that online shopping involves a wide range of areas, and the people pay more attention to it, the paper completed the innovation of online shopping risk warning science knowledge, the design of popular science mechanism and the dissemination of popular science knowledge. The paper used complex network’s knowledge discovery methods and decision theory to design online shopping risk warning science knowledge; Using the complex network public opinion dissemination trust analysis realize the dissemination of popular science knowledge and promote the improvement of the public's quality of popular science. The spread of risk early warning science knowledge in the network shows that the risk early warning mechanism designed can achieve the purpose of improving public science knowledge when the reward and punishment measures are appropriate.
Medicinal Plants in Semi-Natural Grasslands: Impact of Management
Authors: Kose Marika , Melts Indrek , Ohwaki Atsushi , Uchida Kei , Heinsoo Katrin 
Published: June 2021

Abstract
Background: Semi-natural grasslands as valuable ecosystems are significant for their high biodiversity, cultural importance and landscape values. Quantitative information about medicinal plants in semi-natural grasslands facilitates the evaluation of ecosystem services of these plant communities. Methods: Different literature sources and floristic inventory databases were used to assess the ratio and frequency of medicinal plant species in several Estonian grassland types and the impact of management on these values assessed both in Estonian and Japanese case studies. Lists of medicinal plant species according to different definition scenarios is included as Supplementary Material. Principal Component Analysis was applied for environmental preferences of medicinal plant species compared to other vascular plant species in the semi-natural grasslands.Results: The ratio of medicinal plant species in local total plant species list was the largest in alvars, followed by floodplain and wooded meadows. The average number of medicinal plant species per study plot in wooded meadows and alvars was about twice that found in naturally growing broadleaved forest (according to the most detailed MP species list 7.2, 7.8 and 4.3, respectively). Fertilization of Estonian wooded meadows had no significant impact on medicinal plant species ratio, but decreased the proportion of medicinal plant biomass in total yield. Estonian coastal meadows had a short list of medicinal plant species and the impact of management quality depended therefore on adopted definition scenario. In Japanese Miscanthus sinensis grassland case mowing or burning+mowing combination should be preferred to favor medicinal plant species number. Principal Component Analysis revealed that MP species are more drought-tolerant, common and anthropophyte than the rest of studied grassland species.Conclusions: Alternative usage of herbaceous plant species from semi-natural grasslands is a promising option to achieve sustainable development goals and increase public awareness. Further close cooperation of ecologists, economists and pharmacists is required to guarantee fair and sustainable trade of this ecosystem service in the future.
Automatic Detection of Modulation Scheme Using Convolutional Neural Networks
Authors: Babu Blessy , Sreeniva Hari V 
Published: June 2021

Abstract
This paper summarizes the intelligent detection of modulation scheme in an incoming signal, build on convolutional neural network (CNN). It describes the creation of training dataset, realization of CNN, testing and validation. The raw modulated signals are converted into 2D and put on to the network for training. The resulting prototype is adopted for detection. The results signify that the intended approach gives better prediction for the identification of modulated signal without need for any selective feature extraction. The system performance on noise is also evaluated and modelled.
In vitro mature embryo culture protocol of einkorn (Triticum monococcum ssp. monococum) and bread (Triticumaestivum) wheat under boron stress
Authors: Ağıl Ferdi , Örgeç Mehmet , Karakaş Fatma Pehlivan , Kumar Sandeep Verma , Zencirci Nusret 
Published: June 2021

Abstract
Mature embryos of einkorn (Triticum monococcum ssp. monococcum) and bread (Triticum aestivum) wheat were used for callus induction on media containing four (0, 1, 2 and 4 mg L− 1) different doses of 2,4-D and dicamba supplemented with under five (0, 6.2, 12.4, 24.8, and 37.2 mg L− 1) different boron stresses. The obtained callus was transferred to culture media with three (0, 0.5, and 2 mg L− 1) different BAP doses with five boron stresses for regeneration. The heaviest callus weight in einkorn wheat was in culture media with 1 mg L− 1 dicamba and 6.2 mg L− 1 (3.71 ± 0.13 g). Bread wheat had the heaviest callus weight on culture media with 4 mg L− 1 dicamba and 12.4 mg L− 1 (3.46 ± 0.40 g). Callus diameters were observed as the highest in culture media with 1 mg L− 1 and 12.4 mg L− 1 (1.10 ± 0.31) for einkorn and 4 mg L− 1 dicamba with 6.2 mg L− 1 boron (1.22 ± 0.27 cm) for bread wheat. Regeneration capacity was highest in control group with 6.2 mg L− 1 for both wheat genotypes (einkorn, 71.33% ± 11.78 and bread, 65.33% ± 10.80). The highest plantlet numbers were in only 2 mg L− 1 BAP (2.92 ± 0.88) for einkorn wheat and 0.5 mg L− 1 BAP supplemented with 6.2 mg L− 1 boron (3.71 ± 1.12) for bread wheat. This indirect regeneration protocol using mature embryos of einkorn and bread wheat under boron stresses may be useful for wheat breeding studies.
The Method and Results of a Treatment Targeting SARS-CoV-2-Activated Inflammasomes
Authors: Kanwar Badar , Khattak Asif , Lee Chul Joong , Balentine Jenny , Kast R. E. , Oh Sang-Suk , Sergi Consolato , Lee Jong Hoon 
Published: June 2021

Abstract
Background
Clinicians in critical care medicine considered dapsone administration to treat SARS-CoV-2 inflammasome. Dapsone is useful in the molecular regulation of Nod-like receptor family pyrin domain-containing 3 (NLRP3).
Objective
To study the targeting of NLRP3 itself or up-/downstream factors of the NLRP3 inflammasome by dapsone must be responsible for its observed preventive effects, functioning as a competitor.
Methods
This is case series with or without intervention; a cross-sectional study. We set out to use objective criteria of improvement, such as A. a reduction in the FIO2 requirement and B. a decrease in the progression of hypoxia. We treated the patients with standard COVID-19 ARDS treatment with dapsone 100 mg to target NLRP3 inflammasomes.
Results
The 22 cases were treated with standard COVID-19 therapy with dapsone (trial group), and the 22 cases were the control group. The comparison was made assuming that only decreased FIO2 was influential in the trial and control groups, which applied to only the ARDS onset stage. The chi-square statistic is 5.1836. The p-value is .02280. Fisher’s exact test statistic value is 0.0433. (The result is significant at p < .05) Furthermore, the ARDS-onset mortality rates were 0% (with dapsone) and 40% (without dapsone).
Conclusion
There was a significant difference in dapsone treatment results in the ARDS-onset group. We confirmed that dapsone clinically treated the onset of ARDS by targeting SARS-CoV-2-activated inflammasomes. Like chemically reacting substances, inflammasome and dapsone are competing, proving that it is only effective in treating early ARDS.
Risk Factors for Surgical Site Infection in Head and Neck Cancer
Authors: gan chengwen , wang yannan , tang yan , wang kai , sun bingcan , wang mengxue , Zhu Feiya 
Published: June 2021

Abstract
Purpose
Surgical site infection (SSI) frequently occurs in patients with head and neck cancer (HNC) after tumor resection and can lead to death in severe cases. Moreover, there is no definitive conclusion about the risk factors of SSI. Therefore, it is of great clinical significance to study the factors affecting the SSI.
Methods
The HNC patients included in this study were all from the Department of Oral and Maxillofacial Surgery of the Second Xiangya Hospital of Central South University (CSU), and these patients received surgical treatment in the department from January 2018 to December 2019. Univariate and multivariate regression analysis was applied to determine the risk factors of SSI. To identify the key risk factors of SSI, the caret package was used to construct three different machine learning models to investigate important features involving 26 SSI-related risk factors.
Results
Participants were 632 HNC patients who underwent surgery in our department from January 2018 to December 2019. During the postoperative period, 82 patients suffered from SSI and surgical site infection rate (SSIR) was about 12.97%. Diabetes mellitus, tumor site (floor of mouth) and flap failure were consistently ranked the top three in the 26 SSI-related risk factors. In addition, SSI can increase postoperative hospital stays and flap failure rate.
Conclusion
Diabetes mellitus, tumor site (floor of mouth), flap failure, preoperative radiotherapy, neck dissection (bilateral) are risk factors for SSI of HNC.
Promoter Variations Strongly Enhance the Transcription Level of the BoLMI1 Gene, Causing Lobed Leaves in Ornamental Kale (Brassica Oleracea L. Var. Acephala)
Authors: Zhang Bin , Chen Wendi , Li Xing , Ren Wenjing , Chen Li , Han Fengqing , Fang Zhiyuan , Yang Limei , Zhuang Mu , Lv Honghao , Wang Yong , Zhang Yangyong 
Published: June 2021

Abstract
Background: Leaf shape is an important agronomic trait in ornamental kale (Brassica oleracea L. var. acephala). Although some leaf shape-related genes have been reported in ornamental kale, the detailed mechanism underlying leaf shape formation is still unclear. Here, we report a lobed-leaf trait in ornamental kale, aiming to analyze its inheritance and identify the strong candidate gene.Results: Genetic analysis of F2 and BC1 populations demonstrate that the lobed-leaf trait in ornamental kale is controlled by a single dominant gene, termed BoLl-1. By performing whole-genome resequencing and linkage analyses, the BoLl-1 gene was finely mapped to a 127-kb interval on chromosome C09 flanked by SNP markers SL4 and SL6, with genetic distances of 0.6 cM and 0.6 cM, respectively. Based on annotations of the genes within this interval, Bo9g181710, an orthologous gene of LATE MERISTEM IDENTITY 1 (LMI1) in Arabidopsis, was predicted as the candidate for BoLl-1, and was renamed BoLMI1. The expression level of BoLMI1 in lobed-leaf parent 18Q2513 was significantly higher compared with unlobed-leaf parent 18Q2515. Sequence analysis of the parental alleles revealed no sequence variations in the coding sequence of BoLMI1, whereas a 1737-bp deletion, a 92-bp insertion and an SNP were identified within the BoLMI1 promoter region of parent 18Q2513. Verification analyses with BoLMI1-specific markers corresponding to the promoter variations revealed that the variations were present only in the lobed-leaf ornamental kale inbred lines.Conclusions: This study demonstrated that promoter variations strongly enhance the transcription level of BoLMI1 and cause the leaf shape change from unlobed to lobed, providing new insight into the molecular mechanism underlying leaf shape formation in ornamental kale.
Optimized Lifetime of Wireless Sensor Networks Through Metaheuristic Firefly Based Cluster Head Selection Algorithm
Authors: Chintam Anusha , T.v Madhusudhana Rao , G Rajendra Kumar 
Published: June 2021

Abstract
A wireless sensor network is a type of wireless ad-hoc networks, which is a collection of individual sensor nodes that are battery-operated devices and connected through ad-hoc and self-configuring connectivity. Therefore, the energy-saving of sensor node is a challenging design issue. Hence, the lifetime of a node is decreased. To enhance the network lifetime and optimal energy consumption, clustering is one of the best methods in WSN. While message transmission there is more distance between the cluster head and base station then more energy drained by the cluster head compare to the remaining sensor nodes in a particular cluster and if the energy consumption is more then automatically the network lifetime decreased. Therefore, this paper proposed an optimal metaheuristic firefly based cluster head selection protocol (FCH) by finding fitness value for selecting the best cluster head. This best-elected cluster head drains less energy as well as increase the network lifetime. In addition to the proposed FCH compared with two basic sensor networks algorithms low energy adaptive clustering hierarchy (LEACH) and Data transmission (DT). The FCH algorithm achieved better results than compared algorithms in terms of dead nodes, remaining energy, and alive nodes of the network.