bluuebunny/crossref_metadata_2025_split huggingface dataset:
Survey of Deep-learning Techniques in Big-Data analytics
Authors: Goswami Shubhashish , Kumar Abhimanyu 
Published: July 2021

Abstract
The present elaboration of Big-data research studies relying upon Deep-learning methods had revitalized the decision-making mechanism in the business sectors and the enterprise domains. The firms' operational parameters also have the dependency of the Big-data analytics phase, their way of managing the data, and to evolve the outcomes of Big-data implementation by using the Deep-learning algorithms. The present enhancements in the Deep-learning approaches in Big-data applications facilitate the decision-making process such as the information-processing to the employees, analytical potentials augmentation, and in the transition to having more innovative work. In this DL-approach, the robust-patterns of the data-predictions resulted from the unstructured information by conceptualizing the Decision-making methods. Hence this paper elaborates the above statements stating the impact of the Deep-learning process utilizing the Big-data to operate in the enterprise and Business sectors. Also this study provides a comprehensive survey of all the Deep-learning techniques illustrating the efficiency of Big-Data processing on having the impacts of operational parameters, concentrating the data-dimensionality factors and the Big-data complications rectifying by utilizing the DL-algorithms, usage of Machine-learning or deep-learning process for the decision-making mechanism in the Enterprise sectors and business sectors, the predictions of the Big-data analytics resulting to the decision parameters within the organisations, and in the management of larger scale of datasets in Big-data analytics processing by utilizing the Deep-learning implementations. The comparative analysis of the reviewed studies has also been described by comparing existing approaches of Deep-learning methodologies in employing Big-data analytics.
Reliable Disease Prediction System Based on Association Rule Mining and Pyramid Data Structure
Authors: Jeyasheela Y. , Jinny S. Vinila 
Published: July 2021

Abstract

Data mining rules the world of data, as it is the base for analysing and relating the data with each other. Now-a-days, association rule mining concepts are applicable to almost all domains and the healthcare domain is in strong need of that. Taking this into account, this work attempts to propose a reliable disease prediction system with the help of association rule mining and pyramid data structure. This work processes a symptom dataset which is comprised of twelve health attributes. The health attributes with respect to four different diseases are clustered independently and are organised with the help of pyramid data structure. The process of clustering is carried out by Generalized Hierarchical Fuzzy C Means (GHFCM) and the strong association rules are built for predicting the disease. Finally, the effectiveness of disease prediction is evaluated with respect to the standard performance measures such as accuracy, precision, recall, F-measure and time consumption analysis. The performance of the proposed approach is observed to be satisfactory, which when compared to the existing techniques.
Common Mycorrhizal Networks Asymmetrically Contribute to Increased N and P Acquisition by Millet/Chickpea Mixture
Authors: Li Chunjie , Li Haigang , Hoffland Ellis , Zhang Fusuo , Zhang Junling , Kuyper Thomas W. 
Published: July 2021

Abstract
Aim Cereal/legume intercropping is known to increase yield, partly because of increased nitrogen (N) and phosphorus (P) acquisition. The aim of this paper was to investigate the role of common mycorrhizal networks (CMNs) in overyielding by the crop species mixture and to find out if the effect of a CMN depends on which of the two species was colonized by AM fungi.Methods Microcosms with two compartments were used, separated by a 30-μm nylon mesh. Both compartments contained either chickpea or millet, in monoculture or mixed. One or none of the two compartments was inoculated with the AMF species Funneliformis mosseae. The plant in the inoculated compartment was referred to as the AMF donor, and the plant in the neighboring, non-inoculated compartment as the AMF receiver. Results Inoculation in one compartment resulted in mycorrhiza formation in the other compartment, providing evidence for the formation of CMNs. Inoculation of chickpea in the mixture increased N and P acquisition and biomass of both chickpea (AMF donor) and millet (AMF receiver), whereas inoculation of millet increased biomass of chickpea (AMF receiver) only, but did not increase N or P acquisition by any of the two species. Chickpea as AMF donor had higher numbers of phosphate-solubilizing bacteria in its rhizosphere compared to chickpea as receiver. The shoot N:P ratio of chickpea as AMF donor was lower than as receiver. Conclusion Our study demonstrated asymmetry in nutrient gains by a mixture of cereal and a legume, dependent on which plant species was the AMF donor or receiver. This suggests that initiating mycorrhizal networks by legumes in intercropping could be an important factor contributing to the magnitude of the intercropping effect.
Patterns of Fungal Diversity in Needles, Rootlets and Soil of Endemic Pinus Peuce
Authors: Lazarević Jelena , Topalović Ana , Menkis Audrius 
Published: July 2021

Abstract
Pinus peuce Griseb is five-needle pine native in high-altitude montane habitats of the Balkans. The aim was to assess the diversity and composition of fungal communities associated with the soil, rootlets and living needles of P. peuce at three high-altitude forest sites with different edaphic conditions and stand characteristics in southeastern Montenegro. In total, 90 needle, 90 rootlet and 90 soil samples were sampled. DNA amplification using ITS2 rDNA as a marker and high-throughput sequencing resulted in 17,620 high-quality reads, representing 825 fungal taxa. There were 52.5% Basidiomycota, 43.9% Ascomycota and 3.6% Mucoromycotina. There were 118 unique fungal taxa in the rootlets, 230 in the soil and 113 in the needles, with 8 taxa were shared. The most common fungi in rootlets were Rhizopogon mohelensis (11.0%), Suillus sibiricus (8.4%), R. fallax (6.9%), in the soil – Phlebiopsis gigantea (5.1%), Tylospora asterophora (2.9%), Sollicocossima terricola (2.7%), and in the needles – Dothideomycetes sp. 3360_7 (17.6%), Dothideomycetes sp. 3360_10 (10.7%), Leotiomycetes sp. 3360_16 (6.5%). The results showed that the functional tissues and the rhizosphere soil of P. peuce were inhabited by a high diversity of fungi, which were largely specific to each particular substrate, while. the site conditions had only limited effect on associated fungal communities. Associated fungal communities were largely determined by the host tree species, substrate properties and functional capabilities of associated fungi.
Accuracy of Doppler Assessment of the Uterine Arteries in Healthy Girls for the Diagnosis of Pubertal Onset
Authors: Cheuiche Amanda , Silveira Letícia Guimarães da , Escott Gustavo Monteiro , Lucena Iara Regina Siqueira , Puñales Márcia , Costenaro Fabíola , Kopacek Cristiane , de Paula Leila Cristina Pedroso , Silveiro Sandra Pinho 
Published: July 2021

Abstract
Purpose: To evaluate the accuracy of the uterine artery pulsatility index (PI) for the diagnosis of pubertal onset in girls. Methods: Cross-sectional study of girls with normal pubertal development. Puberty was diagnosed by the presence of Tanner breast development score ≥2. All girls underwent pelvic ultrasound and Doppler imaging of the uterine arteries. We evaluated the uterine artery PI and uterine, endometrial, and ovarian measurements. We used ROC curves with cutoffs determined by Youden index for data analysis. Results: We included 169 girls aged 5-16 years who underwent 202 pelvic ultrasound examinations. Prepubertal girls had a significantly higher mean PI (mean, 6.70; SD, 2.15) than girls in initial puberty (mean, 4.14; SD, 1.55) and in late puberty (mean, 2.81; SD, 1.05) (P<0.001 for all comparisons), which reflects a progressive increase in blood flow to the uterus with the progression of puberty. ROC curve analysis showed that the PI was able to identify the onset of puberty with a mean area under the curve of 0.838 (SD, 0.04) (P<0.001), and the PI cutoff point of 5.05 had a sensitivity of 77%, specificity of 85%, positive predictive value (PPV) of 92%, and accuracy of 79%. The combination of PI <5.05 plus uterine volume >3.75 cm³ had a sensitivity of 73%, specificity of 95%, PPV of 97%, and accuracy of 79% to detect initial puberty. Conclusions: The significant reduction in the PI during pubertal development combined with increasing uterine volume can be a valuable, highly specific, noninvasive tool to confirm the onset of puberty.
Productive and Reproductive Aspects in Dairy Cows Raised with and Without Access to Pasture in Southern Brazil
Authors: Gonçalves Rodrigo Schallenberger , Guagnini Fábio de Souza , Storck Daniel , Brose Mariana de Matos , Contreras Laura Victoria Quishpe , Gonzalez Félix Hilário Diaz , Dalto André Gustavo Cabrera 
Published: July 2021

Abstract
Since productive performance in dairy cows is directly linked to the manner in which cows are raised, the breeding system can have a direct influence on the parameters of a farm. Unlike the main European and North American countries, in southern Brazil the use of confinement systems with access to pasture is widespread. Grazing cows are believed to be less stressed from the metabolic point of view. This study was conducted on nine commercial dairy farms located in the Serra Gaúcha, Rio Grande do Sul, Brazil, from September 2016 to November 2017. A total of 393 Holstein dairy cows were included immediately after birth. The dairy farms had an average of 45 lactating cows and were milked twice a day with an average milk production in 305 days of 9,500 kg / cow for the confinement system with access to pasture and 10,700 kg / cow for the confined system. The confinement system with access to pasture (CAP) was composed of five properties and was characterized by access to rotating pasture, while the confinement system without access to pasture (CNP) was composed of four properties. The study diagnosed uterine diseases, metabolic diseases and their correlations, and assessed the conception rate in the first service of the herds. Animals with access to pasture had generally lower production rates than animals reared in confinement, which suggests that the model with access to pasture used in the extreme south of the country can result in deleterious effects on animal production.
Open Quantum Dynamics Theory on the Basis of Periodical System-Bath Model for Discrete Wigner Function
Authors: Iwamoto Yuki , Tanimura Yoshitaka 
Published: July 2021

Abstract
Discretizing distribution function in a phase space for an efficient quantum dynamics simulation is non-trivial challenge, in particular for a case that a system is further coupled to environmental degrees of freedom. Such open quantum dynamics is described by a reduced equation of motion (REOM) most notably by a quantum Fokker-Planck equation (QFPE) for a Wigner distribution function (WDF). To develop a discretization scheme that is stable for numerical simulations from the REOM approach, we find that a two-dimensional (2D) periodically invariant system-bath (PISB) model with two heat baths is an ideal platform not only for a periodical system but also for a system confined by a potential. We then derive the numerically ''exact'' hierarchical equations of motion (HEOM) for a discrete WDF in terms of periodically invariant operators in both coordinate and momentum spaces. The obtained equations can treat non-Markovian heat-bath in a non-perturbative manner at finite temperatures regardless of the mesh size. The stability of the present scheme is demonstrated in a high-temperature Markovian case by numerically integrating the discrete QFPE with by a coarse mesh for a 2D free rotor and harmonic potential systems for an initial condition that involves singularity.
Exceptional hydrogen evolution in acid enabled by a multi-function-site complex oxide via atomic-scale hydrogen spillover
Authors: Dai Jie , Zhu Yinlong , Chen Yu , Wen Xue , Long Mingce , Wu Xinhao , Hu Zhiwei , Guan Daqin , Wang Xixi , Lin Qian , Sun Yifei , Weng Shih-Chang , Wang Huanting , Zhou Wei , Shao Zongping 
Published: July 2021

Abstract
Improving the catalytic efficiency of platinum (Pt) for hydrogen evolution reaction (HER) is crucial for water splitting technologies, and hydrogen spillover has emerged as a new frontier in designing the binary-component Pt/support HER electrocatalysts. However, such binary catalysts always suffer from long reaction pathway, undesirable interfacial barrier, and complicated synthesis processes. Here we report a single-phase complex oxide La2Sr2PtO7+δ as a high-performance HER electrocatalysts in acidic media via a unique atomic-scale hydrogen spillover effect between multifunctional catalytic sites. With insights from theoretical calculations, a possible synergistic mechanism involving the hydrogen spillover channel from OLa site→La-Pt bridge site→Pt site is proposed; namely, the OLa site enriches proton, the La-Pt bridge site with thermo-neutral H* adsorption facilitates the hydrogen spillover and H2 generation, and Pt site favors the final H2 desorption. Benefiting from such unusual phenomenon, the resulting La2Sr2PtO7+δ exhibits an exceptional HER electrode activity with low overpotential of 13 mV at 10 mA cm− 2 and small Tafel slope of 22 mV dec− 1, and significantly enhanced intrinsic activity and durability than commercial Pt black catalyst.
Interferon-α Auto-Antibodies in Convalescent Plasma Therapy for COVID-19
Authors: Raadsen Matthijs , Gharbharan Arvind , Jordans Carlijn.C.E. , Mykytyn Anna Z. , Lamers Mart M. , Doel Petra B. van den , Endeman Henrik , Akker Johannes P.C. van den , GeurtsvanKessel Corine H. , Koopmans Marion P.G. , Rokx Casper , Goeijenbier Marco , Gorp Eric C.M. van , Rijnders Bart J.A. , Haagmans Bart L. 
Published: July 2021

Abstract
Purpose: ﻿To study the effect of Interferon-α auto-antibodies (IFN-α Abs) on clinical and virological outcomes in critically ill COVID-19 patients and the risk of IFN-α Abs transfer during convalescent plasma treatment.Methods: Sera from cases of COVID-19 and other respiratory illness were tested for IFN-αAbs by ELISA and bioassay. IFN-α Abslevels were compared between critically, severely and moderately ill groups in both acute and convalescent stages. Longitudinal analyses were performed to determine whether IFN-α Abs levels change after convalescent plasma transfusion.Results: Critically ill COVID-19 caseshad significantly higher IFN-α Abs detection rate and levels compared tonon-COVID-19 controls.Neutralizing IFN-α Abs levels were found in 1 out of 118plasma donors.Plasma from 2 positive donors was administered to 5 patients, with no subsequent elevation of IFN-α Abs levels in the recipients. Neutralizing levels of IFN-α Abswere associated with delayed viral clearance from the respiratory tract.Conclusions: IFN-α Abs can be detected by ELISA in critical, severe, moderate and mild COVID-19 cases in both the acute and convalescent stages of disease. The presence of neutralizing IFN-α Abs in critically ill COVID-19 is associated with delayed viral clearance. Levels of IFN-α Abs inCOVID-19 convalescent plasma donorsare likely too low to be clinically relevant to the recipients.
Multi-criteria Optimization Scheduling of Surgical Units: a Case Study at AOU-Policlinico Umberto I
Authors: Croella Anna Livia , Tronci Edoardo Maria , Petitti Federico , Nastasi Alberto , Palagi Laura , Romano Ferdinando 
Published: July 2021

Abstract
Nowadays, Operating Rooms (ORs) scheduling and planning represent one of the most challenging aspects in healthcare systems management. In particular, one of the main concern is doubtless the under-use of the surgery rooms, that one can tackle by modelling different management decision aspects. The number of ORs available in the operating theatre and their daily opening time, the ideal OR Utilization Rate (UR) that the hospital aims to fulfil, the possibility to transfer patients between different surgical units (SUs) are just some of them. Taking into account these management and economic factors, we develop a multi-criteria integer linear optimization model for the advance scheduling of patients for the Azienda Ospedaliera - Universitaria Policlinico Umberto I of Rome, among the largest public hospitals in Europe for by total area occupied. The problem is formulated according to an open scheduling strategy that, for each surgical case placed on a waiting list, determines the date, time, and operating room resources needed. Extensive tests were carried out on real data collected during twelve weeks in two SUs, each of them consisting of two ORs. The aim of the study is to evaluate the impact of different policies of opening times on the hospital Key Performance Indicators (KPIs) of interest. The results show a relevant improvement of the ORs usage of the case study.
Blockchain-based BATMAN protocol using Mobile ad-hoc Network (MANET) with an Ensemble Algorithm
Authors: Singh Upendra , Sharma Sumit Kumar , Shukla Mukul , Jha Preeti 
Published: July 2021

Abstract

A MANET is a decentralized type of wireless network of mobile devices, it can also be defined as an autonomous system of nodes. All the nodes in the network are connected by wireless links and are mobile. They can come together and form a network without any support from any existing network infrastructure. MANET is a new field of study based on blockchain in a wireless ad-hoc environment. However, the main challenge for blockchain applications in ad-hoc networks is how to adapt to the extreme computational complexity of block validation while preserving the characteristics of blockchain and include nodes in the validation process. This article proposes a blockchain-based mobile network (MANET) with an ensemble algorithm. The proposed scheme provides a distributed environment for MANETS routing using a blockchain based on the Byzantine Fault Tolerance (BFT) protocol. Taking advantage of the better approach of mobile ad-hoc networking (BATMAN) to incorporate the concept of blockchain into the MANET as a representative protocol. The proposed method named Extended-BATMAN (E-BATMAN) incorporates the concept of blockchain into BATMAN protocol using MANET. As a secure, distributed and reliable platform, Blockchain solves most BFT security issues, with each node performing repeated security operations individually. The experimental analysis of the proposed ensemble algorithm is based on four parameters such as packet delivery rate, average end-to-end latency, network throughput, and energy. All of these parameters show better results with the proposed ensemble protocol than with existing state-of-the-art protocols.
Genetic Analysis of Gorlin Syndrome Using a Multiplex PCR Gene Panel, and Its Potential Clinical Utility for Liquid Biopsy
Authors: Nakamura Yuriko , Onodera Shoko , Hashimoto Kazuhiko , Takano Masayuki , Katakura Akira , Nomura Takeshi , Azuma Toshifumi 
Published: July 2021

Abstract
Background: Gorlin syndrome is an autosomal dominant, rare disease caused by mutations in PTCH1, PTCH2, and SUFU with various symptoms in multiple organs making early diagnosis challenging. In this study, we generated a Gorlin syndrome gene panel that could help to overcome the difficulties in diagnosing Gorlin syndrome using a single test. Results: This gene panel is time- and cost-efficient and highly reliable with a high-quality score of 30, on-target ratio, and coverage depth, and could detect more mutations than whole-exome sequencing of the same patient. Although the current in silico prediction tools have a limited genetic database of gene mutations in rare hereditary diseases, five prediction tools were used to identify pathological mutations. Pathogenic gene mutations were detected not only in PTCH1 but also in PTCH2 in five out of 12 patients with Gorlin syndrome diagnosed based on clinical symptoms. Conclusions: Using this gene panel, we showed the same gene mutation in the patients and their asymptomatic relatives; hence, it has enabled a highly reliable genetic diagnosis of Gorlin syndrome at a low cost requiring only blood sample.
Emerging SARS-CoV-2 variants expand species tropism to rodents
Authors: Shuai Huiping , Chan Jasper , Yuen Terrence Tsz-Tai , Yoon Chaemin , Hu Jingchu , Wen Lei , Hu Bingjie , Yang Dong , Wang Yixin , Hou Yuxin , Huang Xiner , Chai Yue , Chan Chris , Poon Vincent , Zhang Rui-Qi , Chan Wan-Mui , Ip Jonathan Daniel , Chu Allen Wing Ho , Hu Ye-fan , Cai Jian-Piao , Chan Kwok-Hung , Zhou Jie , Srid Siddharth , Zhang Bao-Zhong , Yuan Shuofeng , Zhang Jinxia , Huang Jiandong , To Kelvin , Yuen Kwok-Yung , Chu Hin 
Published: July 2021

Abstract
Mice are not susceptible to wildtype SARS-CoV-2 infection. Emerging SARS-CoV-2 variants including B.1.1.7, B.1.351, P.1, and P.3 contain mutations in spike, which have been suggested to associate with an increased recognition of mouse ACE2, raising the postulation that they may have evolved to expand species tropism to rodents. Here, we investigated the capacity of B.1.1.7 and other emerging SARS-CoV-2 variants in infecting mouse (Mus musculus) and rats (Rattus norvegicus) under in vitro and in vivo settings. Our results show that B.1.1.7 and P.3, but not B.1 or wildtype SARS-CoV-2, can utilize mouse and rat ACE2 for virus entry in vitro. High infectious virus titers, abundant viral antigen expression, and pathological changes are detected in the nasal turbinate and lung of B.1.1.7-inocluated mice and rats. Together, these results reveal that the current predominant circulating SARS-CoV-2 variant, B.1.1.7, has gained the capability to expand species tropism to rodents.
Hyperbolic graphene framework with optimum efficiency for conductive composites
Authors: Liu Xiaoting , Pang Kai , Liu Yingjun , Gao Chao , Xu Zhen 
Published: July 2021

Abstract
Constructing conductive filler networks with high efficiency is essential to fabricating functional polymer composites. Although two-dimensional (2D) sheets have prevailed in nanocomposites, their efficiency in enhancing conductive functions seems to reach the limit, as if merely addressing the dispersion homogeneity. Here, we exploit the unrecognized geometrical curvature of 2D sheets to break the efficiency limit of filler systems. The hyperbolic curvature meditates the incompatibility between 2D topology and 3D filler space and holds the efficient conductive path through face-to-face contact. The hyperbolic graphene framework exhibits the record efficiency in enhancing electrically and thermally conductive functions of nanocomposites. At volume loading of only 1.6%, the thermal and electrical conductivities reach 31.6 W/(mK) and 13,911 S/m, respectively. Nanocomposites with hyperbolic graphene framework exhibit great potentials in thermal management, sensing and electromagnetic shielding. Our work presents a geometrically optimal filler system to break the efficiency limit of multifunctional nanocomposites and broadens the structural design space of 2D sheets by curvature modulation to meet more applications.