bluuebunny/crossref_metadata_2025_split huggingface dataset:
D-App for providing geriatric aid and to collect and handle periodic health survey data
Authors: Joseph Chinnu , Joseph Chinchu , Atul Krishna P , Mathew Amal George , Rawther Fabeela Ali 
Published: March 2021

Abstract
The system aims to build a health survey platform designed to collect basic health information about residents of particular area. Block chain is used to store the collected information making sure only authenticated persons can have access to crucial information. This system also provides information about government health policies or schemes that the members of a family are eligible for and can have easy access to these facilities. This system can also be used as a platform to host health survey in case of an unexpected outbreak of a disease. Machine learning algorithms may be used predict health issues like the possible occurrence of epidemics etc. The system efficiently reduces the paperwork and inefficiency of traditional door to door health surveys by enabling each family to directly feed in their information.
Object Identification Model using Deep Reinforcement Machine Learning Concept for Image
Authors: Tiwari Saurabh , Veenadhari S , Gupta Sanjeev K 
Published: March 2021

Abstract
This paper presents a model which gives the detailed process of object identification. We need to identify class and location of object in image for completing process of objet identification. Proposed model works on the principal of reinforcement learning which takes action on the basis of rewards and experiences. Normally methods in literature uses sliding window which moves in same direction but proposed algorithm provides a variable mask which moves 360 degree for identifying object using action history vector proposed with RL also not only this work focuses on localization like other work but also used class information with Softmax classification able to classify multiple object in single image with efficient time which is novel. Proposed mask acts as agent and focuses on proposed candidate reason this saves time and works in efficient manner for identification. Agent depends on transformation action and by applying top down reasoning it gives location of object. Classification is done using Softmax classification as we are having features of image by CNN. Reinforcement learning concept used for training of agent and Pascal voc dataset used for testing. Analysis of only 10 to 25 regions is sufficient with proposed work to identify first instance of object. Experiment and performance evaluation shows the efficiency of proposed work.
Enhancing the efficiency of continuous integration environment in DevOps
Authors: Benjamin Jetty , Mathew Juby 
Published: March 2021

Abstract
Faster release of features to the production environment is the need of the hour of every IT organizations. This faster and continuous software delivery is made possible through DevOps. DevOps is a set of practices that bridges the gap between development team and operations team. The different aspects of DevOps came from agile methodology. Continuous integration is the paramount of DevOps life cycle. In a continuous integration development practice, the development code and the applications code are continuously integrated several times a day. Developers follow the practice of committing changes frequently into the version control system such as git. A change in the version control system triggers the continuous integration system such as Jenkins. This exploratory study presents the ways that support the developers during the build break in continuous integration environment and thereby improve the efficiency of continuous integration process. Our findings contribute that the selected list of plugins in the Jenkins support the developers during the build break, thus developers can come up with faster recovery of build failures which in turn increase the efficiency of continuous integration environment.
A comparative study on machine learning algorithms for employee attrition prediction
Authors: Usha P M , Balaji N V 
Published: March 2021

Abstract
The fourth industrial revolution introduces a wide range of technologies for an effective functioning of organizations with optimal usage of all resources including human resource. Machine learning is one of the driving technologies implemented in fourth Industrial Revolution. Machine learning can be utilised for developing models that can predict the retention or attrition of employees. The study is using machine learning algorithms like classification and clustering for preparing the prediction models. A comparison of these algorithms is done based on its performance. The performance is measured using parameters like accuracy, precision, recall, F Measure and time taken to build the model. The study is also finding the correlation between variables used in the work to the decision of staying back in the organization. The study is using the open-source tool Weka and also python for doing the same.
Study of Piezoelectric transducers used for Energy Harvesting Applications
Authors: Samal Nilimamayee , Jeba Shiney O , Patra Abhinandan 
Published: March 2021

Abstract
To manage the soaring power demand, various types of Energy Harvesting Systems (EHS) are being developed. The energy harvesting from unutilized natural renewable sources using piezoelectric transducers is one of them. Day-by-day different analytical models are being reported with different piezoelectric transducers to improve the energy efficiency and output power of the energy harvesting systems. The latest Energy Harvesting Systems (EHS) technology includes the material with outstanding piezoelectric properties, compact fabrication style and distinctive design. They are capable of generating electric power of microwatt to milliwatt range from the unutilized energy sources such as environmental, industrial, vehicular sources and human motion etc. In this study, the reported research works on piezoelectric energy harvesting system (2007-2020) have been reviewed and discussed. The review basically focuses on the constitutional/compositional development of the piezoelectric transducers used in energy harvesting processes.
Lucky and Proper Lucky Labeling of Quadrilateral Snake Graphs
Authors: Sateesh Kumar T. V. , Meenakshi S. 
Published: March 2021

AbstractThe labeling is said to be lucky labeling of the graph if the vertices of the graph are labeled by natural number with satisfying the condition that sum of labels over the adjacent of the vertices in the graph are not equal and if vertices are isolated vertex then the sum of the vertex is zero. The least natural number which labelled the graph is the lucky number. The Lucky Number of graphGis denoted byη(G). The labeling defined as proper labeling if the vertices of the graph are labeled by natural number with fulfilling the condition that label of adjacent vertices is not the same. The labeling is defined as proper lucky labeling if labeling is proper and also lucky. The proper lucky number of graphGis denoted byηp(G). Here we obtain a lucky number and proper lucky number for family of quadrilateral snake graph such as quadrilateral snake graph, double quadrilateral snake graph, alternate quadrilateral snake graph and double alternate quadrilateral snake graph.
Time-reversal symmetry breaking in a square lattice
Authors: Jimenez Kevin , Reslen Jose 
Published: March 2021

Abstract
The bulk conductivity of a two-dimensional system is studied assuming that time-reversal symmetry is broken by internal mechanisms. The study is carried out by direct diagonalization in order to explore the nonlinear-response provoked by the inclusion of an electric field in the system’s Hamiltonian. The system displays a quantized conductivity that depends on the intensity of the field and under specific conditions the conductivity limit at zero electric field displays a nonvanishing value.
Isotropic quantitative differential phase contrast microscopy using radially asymmetric color-encoded pupil
Authors: Lin Yu-Hsiang , Li An-Cin , Vyas Sunil , Huang Yi-You , Yeh J Andrew , Luo Yuan 
Published: March 2021

Abstract
Differential phase contrast (DPC) microscopy provides isotropic phase images by applying asymmetric illumination patterns on the sample. The movement of specimens during series image acquisition may lead to motion blur artifacts, which are difficult to prevent. Here, we propose a new method based on pupil engineering and color multiplexing to obtain an isotropic phase transfer function and to reduce the required frames simultaneously. Radially asymmetric color pupils are implemented in a DPC microscope using a programmable thin-film transistor as a digital pupil, which gives flexibility and dynamic control for projecting illumination patterns on samples. With our approach, an isotropic quantitative phase map can be obtained using only pairwise color images for phase reconstruction. A radially asymmetric color pupil is synthesized by encoding the red, green, and blue colors. To recover accurate phase values, a color-leakage correction algorithm is applied to calibrate each color channel. Compared to a half-circle illumination pupil, our method can significantly enhance the image acquisition speed. The phase recovery accuracy is more than 97%. To show the imaging performance of our proposed method, quantitative phase imaging of living 3T3 mouse fibroblast cells is performed. Our quantitative phase measurement method may find important applications in biomedical research.
Optimized loss function in deep learning profilometry for improved prediction performance
Authors: Van Der Jeught Sam , Muyshondt Pieter G G , Lobato Ivan 
Published: March 2021

Abstract
Single-shot structured light profilometry (SLP) aims at reconstructing the 3D height map of an object from a single deformed fringe pattern and has long been the ultimate goal in fringe projection profilometry. Recently, deep learning was introduced into SLP setups to replace the task-specific algorithm of fringe demodulation with a dedicated neural network. Research on deep learning-based profilometry has made considerable progress in a short amount of time due to the rapid development of general neural network strategies and to the transferrable nature of deep learning techniques to a wide array of application fields. The selection of the employed loss function has received very little to no attention in the recently reported deep learning-based SLP setups. In this paper, we demonstrate the significant impact of loss function selection on height map prediction accuracy, we evaluate the performance of a range of commonly used loss functions and we propose a new mixed gradient loss function that yields a higher 3D surface reconstruction accuracy than any previously used loss functions.
How Do Pathologists in Academic Institutions Across the United States and Canada Evaluate Sentinel Lymph Nodes in Breast Cancer? A Practice Survey
Authors: Asirvatham Jaya Ruth , Jorns Julie M 
Published: March 2021

Abstract

Objectives
There are little data on how changes in the clinical management of axillary lymph nodes in breast cancer have influenced pathologist evaluation of sentinel lymph nodes.

Methods
A 14-question survey was sent to Canadian and US breast pathologists at academic institutions (AIs).

Results
Pathologists from 23 AIs responded. Intraoperative evaluation (IOE) is performed for selected cases in 9 AIs, for almost all in 10, and not performed in 4. Thirteen use frozen sections (FSs) alone. During IOE, perinodal fat is completely trimmed in 8, not trimmed in 9, and variable in 2. For FS, in 12 the entire node is submitted at 2-mm intervals. Preferred plane of sectioning is parallel to the long axis in 8 and perpendicular in 12. In 11, a single H&E slide is obtained, whereas 12 opt for multiple levels. In 11, cytokeratin is obtained if necessary, and immunostains are routine in 10. Thirteen consider tumor cells in pericapsular lymphatics as lymphovascular invasion (LVI), and 10 consider it isolated tumor cells (ITCs).

Conclusions
There is dichotomy in practice with near-equal support for routine vs case-by-case multilevel/immunostain evaluation, perpendicular vs parallel sectioning, complete vs incomplete fat removal, and tumor in pericapsular lymphatics as LVI vs ITCs.
Identifying Influential Nodes in Complex Networks Based on Neighborhood Entropy Centrality
Authors: Qiu Liqing , Zhang Jianyi , Tian Xiangbo , Zhang Shuang 
Published: March 2021

AbstractIdentifying influential nodes is a fundamental and open issue in analysis of the complex networks. The measurement of the spreading capabilities of nodes is an attractive challenge in this field. Node centrality is one of the most popular methods used to identify the influential nodes, which includes the degree centrality (DC), betweenness centrality (BC) and closeness centrality (CC). The DC is an efficient method but not effective. The BC and CC are effective but not efficient. They have high computational complexity. To balance the effectiveness and efficiency, this paper proposes the neighborhood entropy centrality to rank the influential nodes. The proposed method uses the notion of entropy to improve the DC. For evaluating the performance, the susceptible-infected-recovered model is used to simulate the information spreading process of messages on nine real-world networks. The experimental results reveal the accuracy and efficiency of the proposed method.
Is hybrid coronary revascularization really beneficial in the long term?
Authors: Wang Chuan , Li Ping , Zhang Fan , Li Jingxing , Kong Qingyu 
Published: March 2021

Abstract

OBJECTIVES
This analysis aimed to compare both short- and long-term outcomes of hybrid coronary revascularization (HCR) with different techniques and coronary artery bypass grafting (CABG).

METHODS
Twenty-three studies were included, covering 10 468 different patients, among whom 2403 patients underwent HCR with either simultaneous or staged method and 8065 patients underwent CABG.

RESULTS
Compared with CABG, HCR had a statistically significant lower risk of stroke [odds ratio (OR) = 0.55, P = 0.049], major adverse cardiac and cerebrovascular events (OR = 0.69, P = 0.024) and blood transfusion (BT) (OR = 0.39, P &lt; 0.001), whereas no significant differences were detected in mortality, myocardial infarction and repeat revascularization. A network meta-analysis showed that simultaneous HCR had significantly better outcomes in stroke (OR = 0.24, P = 0.01) and major adverse cardiac and cerebrovascular events (OR = 0.29, P &lt; 0.001), and staged HCR had a significantly better outcome in BT (OR = 0.31, P &lt; 0.001). According to the frequentist statistic results, simultaneous HCR had the highest probability of being the best treatment in terms of mortality (84%), stroke (97%), myocardial infarction (88%) and major adverse cardiac and cerebrovascular events (99%), whereas staged HCR had the highest probability of being the best in postoperative repeat revascularization (59%) and BT (83%). However, long-term results showed no significant difference between the HCR and CABG techniques.

CONCLUSIONS
HCR appears to be a feasible option for multivessel coronary artery disease patients. Compared to traditional CABG, HCR had lower risk of adverse events in the short term, but in the long term, survival rate and freedom from major adverse cardiac and cerebrovascular events rate were similar between groups.
Attack by Design: Australia’s Offshore Detention System and the Literature of Atrocity
Authors: Mann Itamar 
Published: March 2021

Abstract
A great work of literature does more for international criminal justice than providing evidence. By couching the evidence in conceptual categories, literature can offer insights on how law should be interpreted. This review essay seeks to demonstrate this argument about legal interpretation through a reading of Behrouz Boochani’s much-acclaimed No Friend but the Mountains. In doing so, it seeks to offer a reflection on the significance of literary evidence authored by those subjected to atrocity. Boochani is far from being the first author whose work has enormous value both as literature and as testimony (an overlap that has been widely studied in the humanities and social sciences). Yet the relationship between the two is still seldom appreciated by lawyers and seldom appreciated for its value to legal theory. The essay aims to contribute to the latter discussion, specifically as it pertains to contemporary abuses against asylum seekers.
MANual vs. automatIC local activation time annotation for guiding Premature Ventricular Complex ablation procedures (MANIaC-PVC study)
Authors: Jáuregui Beatriz , Fernández-Armenta Juan , Acosta Juan , Penela Diego , Terés Cheryl , Ordóñez Augusto , Soto-Iglesias David , Silva Etelvino , Chauca Alfredo , Carreño José M , Scherer Claudia , Pedrote Alonso , Berruezo Antonio 
Published: March 2021

Abstract

Aims
To assess potential benefits of a local activation time (LAT) automatic acquisition protocol using wavefront annotation plus an ECG pattern matching algorithm [automatic (AUT)-arm] during premature ventricular complex (PVC) ablation procedures.

Methods and results
Prospective, randomized, controlled, and international multicentre study (NCT03340922). One hundred consecutive patients with indication for PVC ablation were enrolled and randomized to AUT (n = 50) or manual (MAN, n = 50) annotation protocols using the CARTO3 navigation system. The primary endpoint was mapping success. Clinical success was defined as a PVC-burden reduction of ≥80% in the 24-h Holter within 6 months after the procedure. Mean age was 56 ± 14 years, 54% men. The mean baseline PVC burden was 25 ± 13%, and mean left ventricular ejection fraction (LVEF) 55 ± 11%. Baseline characteristics were similar between the groups. The most frequent PVC-site of origin were right ventricular outflow tract (41%), LV (25%), and left ventricular outflow tract (17%), without differences between groups. Radiofrequency (RF) time and number of RF applications were similar for both groups. Mapping and procedure times were significantly shorter in the AUT-arm (25.5 ± 14.3 vs. 32.8 ± 12.6 min, P = 0.009; and 54.8 ± 24.8 vs. 67.4 ± 25.2, P = 0.014, respectively), while more mapping points were acquired [136 (94–222) AUT vs. 79 (52–111) MAN; P &lt; 0.001]. Mapping and clinical success were similar in both groups. There were no procedure-related complications.

Conclusion
The use of a complete automatic protocol for LAT annotation during PVC ablation procedures allows to achieve similar clinical endpoints with higher procedural efficiency when compared with conventional, manual annotation carried out by expert operators.
RecombinationLactococcus lactisexpressingHelicobacter pylorineutrophil-activating protein A attenuates food allergy symptoms in mice
Authors: Zhang Ke , Mirza Wajid Ameen , Ni Peng , Yu Mingyang , Wang Chen , Wang Bin , Chang Shuailei , Yue Limin , Zhang Rongguang , Duan Guangcai 
Published: March 2021

ABSTRACTBackgroundFood allergy has been a significant public health issue with growing severity, prevalence and limited treatments. The neutrophil-activating protein A subunit (NapA) of Helicobacter pylori has been shown to have therapeutic potential in allergic diseases.MethodsThe NapA expression efficiency of recombinant Lactococcus lactis(L.lactis) were determined. The effects of recombinant bacterium on food allergy in Balb/c mice were also investigated.ResultsNapA were delivered and expressed efficiently via L. lactis. The engineered bacterium ameliorated food allergy symptoms (acute diarrhea and intestinal inflammation) and decreased serum histamine levels. In addition, the secretion of OVA-specific IgG2a, IFN-γ was promoted and the level of IL-4, OVA-specific IgE was restrained.ConclusionsThe recombinant strain may attenuate food allergy in mice through immune regulatory effect, which may be a promising approach for preventing or treating food allergy.
The “sailing-ship effect” as a technological principle
Authors: De Liso Nicola , Arima Serena , Filatrella Giovanni 
Published: March 2021

Abstract
The “sailing-ship effect” is the process whereby improvements to an incumbent technology (e.g. sail) are intentionally sought as a new competing technology (steam) emerges. Despite the fact that the effect has been referred to by quite a few scholars in different technological battles, the effect itself seems to have been taken for granted rather than organically defined and investigated. In this paper, within the context of evolutionary “appreciative theorizing” à la Nelson and Winter, through in-depth study of technological battles between old and new technologies, we transform what was an unfinished concept into a structured, fully-fledged, tool of analysis.
Population structure and gene flow of Geoffroy’s cat (Leopardus geoffroyi) in the Uruguayan Savanna ecoregion
Authors: Bou Nadia , Soutullo Álvaro , Hernández Daniel , Mannise Natalia , González Susana , Bartesaghi Lucía , Pereira Javier , Merino Mariano , Espinosa Caroline , Trigo Tatiane C , Cosse Mariana 
Published: March 2021

AbstractFelids are among the species most threatened by habitat fragmentation resulting from land-use change. In the Uruguayan Savanna ecoregion, about 30% of natural habitats have been lost, large felids have been eradicated from most of the region, and the impact of anthropogenic threats over the smaller species that remain is unknown. To develop management strategies, it is important to enhance knowledge about species population structure and landscape connectivity, particularly when land-use change will continue and intensify in the next years. In this study, we evaluate the population structure and gene flow of Geoffroy’s cat in the Uruguayan Savanna ecoregion. We generated a matrix of 11 microsatellite loci for 70 individuals. Based on Bayesian approaches we found that within the Uruguayan Savanna, Geoffroy’s cat shows high levels of genetic variability and no population structure. However, we observed genetic differences between individuals from the Uruguayan Savanna and those from the contiguous ecoregion, the Argentinian Humid Pampa. Four first-generation migrants from Humid Pampa were identified in the Uruguayan Savanna, suggesting a stronger gene flow in the west-east direction. We detected a past bottleneck followed by a subsequent recovery in Geoffroy’s cat populations in both ecoregions. These results lay the groundwork to understand the population dynamics and conservation status of Geoffroy’s cat in the Uruguayan Savanna ecoregion, and provide baseline data to establish population monitoring.