bluuebunny/crossref_metadata_2025 huggingface dataset:
Rapid serum tube technology overcomes problems associated with use of anticoagulants
Authors: Zhao Kong-Nan , de Jersey John , Lavin Martin F , Masci Paul P , Grant Michael , Johnson Lambro A , Dimeski Goce
Published: October 2019

Introduction: Failure to obtain complete blood clotting in serum is a common laboratory problem. Our aim was to determine whether snake prothrombin activators are effective in clotting blood and producing quality serum for analyte measurement in anticoagulated patients. Materials and methods: Whole blood clotting was studied in a total of 64 blood samples (41 controls, 20 Warfarin patients, 3 anticoagulated patients using snake venom prothrombin activator (OsPA)) with plain tubes. Coagulation was analysed using a visual assay, Hyland-Clotek and thromboelastography. Healthy control blood was spiked with a range of anticoagulants to determine the effectiveness of OsPa-induced clotting. A paired analysis of a Dabigatran patient and a control investigated the effectiveness of the OsPA clotting tubes. Biochemical analytes (N = 31) were determined for 7 samples on chemistry and immunoassay analysers and compared with commercial tubes. Results: Snake venom prothrombin activators efficiently coagulated blood and plasma spiked with heparin and commonly used anticoagulants. Clotting was observed in the presence of anticoagulants whereas no clotting was observed in BDRST tubes containing 3 U/mL of heparin. Snake venom prothrombin activator enhanced heparinised blood clotting by shortening substantially the clotting time and improving significantly the strength of the clot. Comparison of 31 analytes from the blood of five healthy and two anticoagulated participants gave very good agreement between the analyte concentrations determined. Conclusions: Our results showed that the snake venom prothrombin activators OsPA and PtPA efficiently coagulated recalcified and fresh bloods with or without added anticoagulants. These procoagulants produced high quality serum for accurate analyte measurement.
Time-dependent variation of ionized calcium in serum samples
Authors: Perović Antonija , Njire Bratičević Marina
Published: October 2019

Introduction: The aim of this study was to compare ionized calcium (iCa) concentrations in arterial heparinized blood and venous serum and to investigate time-dependent variation of iCa in serum samples centrifuged and analysed at different times. Materials and methods: Ionized calcium was measured (N = 25) in arterial blood within 20 min after puncture, and in serum within 10 min after centrifugation conducted 30 min after sampling. Effect of time between sampling and centrifugation was examined in three tubes (N = 30) centrifuged 15, 30 and 60 min after sampling, and analysed within 10 min. Effect of time between centrifugation and analysis was investigated in three tubes (N = 31) centrifuged 30 min after sampling and analysed: 0-10, 30-40 and 90-100 min after centrifugation. Ionized calcium was measured on the Siemens RapidLab 348EX analysers. Statistical significance was tested using Wilcoxon test and ANOVA analysis. Clinical significance was judged against reference change values (RCV). Results: No statistically significant difference was found between iCa in arterial blood and serum (P = 0.274). A statistically significant decrease was found: in tubes centrifuged 60 and 15 min after sampling versus 30 min (P = 0.005, P = 0.003); and in tubes analysed 30-40 and 90-100 min after centrifugation versus 0-10 min (P = 0.021, P = 0.027). Clinically significant changes were observed: 60 versus 30 min (centrifugation) and 90-100 versus 0-10 and 30-40 min (analysis). Conclusions: Timely analysed arterial blood and serum samples can be used interchangeably. To avoid clinically significant variations, serum tubes should be centrifuged within 30 min after sampling, and analysis should be performed within 30 min after centrifugation.
Making REDD+ Transparent: Opportunities for Mobile Technology
Authors: Bumpus Adam , Huynh Thu-Ba , Pascoe Sophie
Published: October 2019

Transparency in climate finance mechanisms, such as Reducing Emissions from Deforestation and Forest Degradation (REDD+), relies on the transfer of information within a complex global web of state and nonstate actors. Such information is required under internationally agreed REDD+ safeguards, including measurement, reporting and verification (MRV) processes and free, prior, and informed consent (FPIC), and works to establish substantive and normative transparency. However, the sources of, access to, and outcomes from these information flows are still contentious. To address these problems, REDD+ project proponents are increasingly looking to information and communication technologies, such as mobile devices, to improve information gathering, processing, and access. In this article we develop a model and provide tentative examples of how normative and substantive transparency are connected through input and output legitimacy within broader governance contexts. We highlight that even though mobile devices are being used to bring forest communities into the REDD+ process, substantive transparency for emissions reductions through MRV tends to be prioritized over normative dimensions associated with FPIC. We conclude by highlighting the need to further understand the role of decentralized information flows in multilevel carbon governance and opportunities for how mobile technologies may be used to address transparency challenges in the governance of REDD+.
International Transfer Pricing and Tax Avoidance: Evidence from Linked Trade-Tax Statistics in the United Kingdom
Authors: Liu Li , Schmidt-Eisenlohr Tim , Guo Dongxian
Published: October 2019

This paper employs unique data on export transactions and corporate tax returns of UK multinational firms and finds that firms manipulate their transfer prices to shift profits to lower-taxed destinations. It shows that the 2009 tax reform in the United Kingdom, which changed the taxation of corporate profits from a worldwide to a territorial system, led to a substantial increase in transfer mispricing. It also provides evidence for a trade creation effect of transfer mispricing and estimates substantial transfer mispricing in non-tax-haven countries with low- to medium-level corporate tax rates, and in R&D intensive firms.
A New Take on Asceticism: Asceticism as Training and Secession Suspended between Individuality and Collectivity
Authors: Petersen Anders Klostergaard
Published: October 2019

Inspired by Peter Sloterdijk’s Du mußt dein Leben ändern. Über Anthropotechnik (2009), I present a novel take on asceticism as deliberate training. Understanding humans as training animals, I discuss how, with the emergence of kosmos or Axial Age religions, humans came to acknowledge this element and made it a pivotal part of their lives. After presenting three important complements to Sloterdijk’s argument, I present a new take on asceticism by relating it to the two main currents in classical scholarship, those of Durkheim and of Weber. Underlying the two perspectives is the transition in asceticism, highlighted by Sloterdijk in his understanding of the phenomenon as basically constituting training programs, from a ritually determined to an ideologically defined form encompassing one’s entire life. Finally, I argue with Durkheim and Sloterdijk that asceticism should not be reduced to a religious phenomenon only, nor to one exclusively characteristic of religions. It is a basic feature of human life enacted on a continuum suspended between the two poles of individuality and collectivity.
Age-related changes and vocal convergence in titi monkey duet pulses
Authors: Clink Dena J. , Lau Allison R. , Bales Karen L.
Published: October 2019

Duets in pair-bonding primates serve as a primary mode of communication between pairs, and duets may provide cues to conspecifics regarding the calling individual or pair. Here, we test the hypothesis that pulse elements in coppery titi monkey duets vary with condition and identity of the caller. We predicted that pulse elements would vary with age, sex, or pair-bond length. We estimated pulse rate and duration for 378 pulse elements from the duets of 74 captive titi monkeys (Plecturocebus cupreus). We found inter-individual variation in both features, and evidence for vocal convergence among pair mates in pulse rate. Age was the best predictor of pulse rate, and pulse rate decreased with age. Age and pair-bond length reliably predicted pulse duration. Our results suggest that variation in titi monkey duets reflects differences in caller condition and pair identity, and contribute to growing evidence for vocal plasticity in nonhuman primates.
Morphological notes on Pinnaxodes gigas Green, 1992 (Brachyura, Pinnotheridae) emphasizing on length-weight relationship under multi-model approach
Authors: Aragón-Noriega E. Alberto , Alcántara-Razo Edgar , Padilla-Serrato Jesús G. , Rodríguez-Domínguez Guillermo , Castillo-Vargasmachuca Sergio G.
Published: October 2019

This study describes biometric characteristics of the pea crab Pinnaxodes gigas, a symbiont of the geoduck clam Panopea globosa in the eastern-central Gulf of California. Differences were observed in the coefficient of allometry when length-weight relationships (LWR) were analysed under a multi-model approach. The winner model for LWR in females was that exhibiting two phases (”two-segments” and “broken-stick”), while in males the models cubic and quadratic, presenting a continuous change in coefficient of allometry along all sizes, were chosen as the best. The relationships of carapace width, length and height were also tested for females with the two-segment model and the breakpoint was found at 20 mm carapace width for these three relationships. It is concluded that the breakpoint must be related to the size-at-maturity reached by females, and that these changes in dimensions correspond to an adaptation in the female’s shape for carrying the egg clutch.
Dutch-Portuguese Diplomatic Encounters, 1640-1703: Exchanges, Sovereignty and “World Peace”
Authors: Antunes Cátia
Published: October 2019

This article traces the multiplex relationships established between Portuguese ambassadors, consuls and extraordinary envoys in the Dutch Republic between 1640 and 1703 with the Portuguese kingdom, the king, the Portuguese “Nation” in Amsterdam and the Dutch States General. In negotiating multiple contracts and treaties regarding “world peace,” these men determined the course of history not so much because they were bound by the service of a state or a king but rather because they served a multiplicity of interests that often damaged national interest in favor of specific interest groups. The article focuses particularly on the Dutch-Portuguese clashes in Western Africa and Brazil and how their settlements impacted the Dutch-Portuguese power sharing in Asia, ultimately challenging premises of sovereignty at a global scale.
Making the History of Computing. The History of Computing in the History of Technology and the History of Mathematics
Authors: De Mol Liesbeth , Bullynck Maarten
Published: October 2019

A history of writing the history of computing is presented in its relationship to the history of mathematics. As with many historiographies, the initial history of computing was very much an internalistic history. In the late 1970s, the field became more serious and started looking at the histories of mathematics and technology for (methodological) inspiration. Whereas the history of mathematics was initially quite influential, it is the history of technology (in its U.S. form) that has become the dominant framework for doing history of computing since the 1990s.
Violence and the Unconditional
Authors: Caputo John D.
Published: October 2019

I distinguish between the deep culture and the manifest culture, the relationship between the two constituting a circle, which constitutes the circulation of a radical theology of culture. The deep culture surfaces in the manifest, and the manifest draws upon the depths; neither one without the other. My hypothesis is that religion is an expression of the deep culture and for that reason, religion is not accidentally violent; religion is violent in virtue of something essential to religion. Religion is playing with the fire of the concealed depths, of the unconditional, of the impossible, of the undeconstructible. Religion is the best way to save the world, but it also the best way to burn it down. It is both of these things and in virtue of the same property. This is not to say that religion is structurally violent, always and necessarily violent. It is structurally ambiguous, dangerous, on the verge of violence, whipsawing between radical violence and radical non-violence, between martyrdom and murder. Religious beliefs are not the cause of the violence but often a façade for deeper, visceral nationalism or ethnic hatred, The reaction of Christian right to the contemporary world is naive and simplistic but not superficial; it reflects a visceral fear of the postmodern world. Religion is a matter of being claimed by something unconditional, which means it should have the good sense not to lay claim to it. We should never trust anything that has not passes through that apophasis. Before any claims we make, we are laid claim to in advance by the unconditional, the undeconstructible, which Schelling calls the prius, the “un-pre-thinkable” (das Unvordenkliche). The unconditional in the optimal sense is love, which is an expenditure made without the expectation of a return, like loving one’s enemies, which is impossible, the impossible. But love does not get a pass. What would we not do for love? In that question is concentrated all the ambiguity of love, all the courage of the martyr, but no less the violence of the suicide bomber.
The “Light of Light Beyond Light”
Authors: Raschke Carl
Published: October 2019

Despite Jürgen Habermas’ famous suggestion that the violence of history might be mitigated by “the liquidation of unconditional claims,” the issue of whether monotheistic religions and the metaphysical rationality they engender are indeed the hidden source of such violence remains an open one. This essay explores how Derrida with his project “deconstruction” sought to deal in a manner unique to philosophy with the question of the relationship between violence, the unconditional, and the ontological. It proposes that Derrida’s “Jew-Greek” dilemma, which encapsulates the problem of the “violence” of metaphysics, is resolved through Levinas’ project of disrupting Husserlian phenomenology with an alterity that is not simply a heteron that disintermediates the logic of predication, but one that challenges what is normally meant by philosophy itself.
Description of a new fossil Statira Lepeletier et Audinet-Serville, 1828 (Coleoptera: Tenebrionidae: Lagriinae) from Baltic amber of the Sambian Peninsula
Authors: TELNOV DMITRY , BUKEJS ANDRIS , MERKL OTTÓ
Published: October 2019

Statira baltica sp. nov. is described from Eocene Baltic amber found in the Baltic Sea coast, Yantarny settlement, Kaliningrad Region, Russia. This is the second described fossil member of the genus Statira Lepeletier et Audinet-Serville, 1828 and the tribe Lagriini Latreille, 1825, and the first from outside the New World.
Give Attention to Overlapping Network Detection in Networks for Multimedia
Authors: Selvan Mercy Paul , Gupta Akansha , Mukherjee Anisha
Published: October 2019

Finding overlapping agencies from multimedia social networks is an thrilling and important trouble in records mining and recommender systems but, existing overlapping network discovery often generates overlapping community structures with superfluous small groups. Network detection
in a multimedia and social network is a conducive difficulty in the network gadget and it helps to understand and learn the overall network shape in element. Those are essentially the dividing wall of network nodes into a few subgroups in which nodes within these subgroups are densely linked,
but the connections are sparser in between the subgroups. Social network analysis is widely widespread domain which draws the attention of many information mining experts. Some wide variety of actual community common characteristics which it shares are facebook, Twitter show off the idea of
network shape inside the community. Social network is represented as a community graph. Detecting the groups entails locating the densely linked nodes.
Data Storage in the Fog Computing for Smart Environment Monitoring System (SEMS)
Authors: Jalasri M. , Nalini S. , Magesh Kumar N. , Elumalai J.
Published: October 2019

Environment monitoring system for smart cities uses diverse kind of sensors which is used to accumulate the information for managing the resources efficiently. Environment monitoring system provides services such as automation of home, weather monitoring, air quality management and
prediction of pollution. This paper presents the customized design on environment monitoring the basic parameters are temperature, humidity and CO2. These sensed data need to be stored and processed. In previous system, sensed data are stored using cloud computing. In proposed system,
Fog computing is used to store the sensed data from smart environment monitoring system (SEMS) and transfer the data to the mobile app from the fog device which is more efficient than cloud computing.
Big Data Deployment for an Efficient Resource Prerequisite Job
Authors: Prince Mary S. , Usha Nandini D. , Ankayarkanni B. , Sathyabama Krishna R.
Published: October 2019

Integration of cloud and big data very difficult and challenging task and to find the number of resources to complete their job is very difficult and challenging. So, virtualization is implemented it involves 3 phases map reduce, shuffle phase and reduce phase. Many researchers have
been done already they have applied Heterogeneousmap reduce application and they use least-work-left policy technique to distributed server system. In this paper we have discussed about virtualization is used for hadoop jobs for effective data processing and to find the processing time of
job and balance partition algorithm is used. The main objective is to implement virtualization in our local machines.
An Automatic Approach to Extracting Geographic Information from Internet
Authors: Viji Amutha Mary A. , Kumar Konduru Sandeep , Sai Kesa Pavan Sri
Published: October 2019

An automatic approach to extract Geographic information especially represented by Points of Interest (POIs), is critical for identifying locations and provides the basis for various location-based services. Currently, geospatial data of POI are available through some open map services
(e.g., Google Maps, OpenStreetMap, etc.). However, the data supporting these services are either collected through the expensive commercial purchasing and company investment or gathered by the volunteered contribution of high uncertainty. With the rapid geospatial data growing on the Web,
we propose an automatic approach of extracting geographic information for building up POI resources based on the results obtained by the web search engines to mitigate the negative effect from the traditional means. According to the approach, we firstly put the types of POIs extracted from
Google Maps and the street names obtained from OpenStreetMap into the Google search engine, and then retrieve the potential addresses of POIs through parsing the search results. Secondly, the Google search engine is employed again with the retrieved addresses of POIs to extract the potential
place names. Finally, the Google search engine is employed for a third time with learning both the place names and the corresponding addresses to verify whether the place names are correct. The contributed output of the work is a place-name dataset. We respectively select 20 blocks in Chicago
and Houston in U.S. to execute our approach for verifying the research contribution. In the experiments, we choose Google Map that is of high data quality as the reference and compare the results with those from OpenStreet Map and Wikimapia. The final results indicate that the proposed approach
could effectively produce the place-name datasets on a par with Google Maps and outperform OpenStreet Map and Wikimapia.
Retrieval of Encrypted Data Using Trapdoor Method in Cloud Computing
Authors: Gnanesh K. E. , Dheeraj Bhavan Narayana T. , Kamalesh M. D.
Published: October 2019

Cloud computing is a well-known innovation which licenses putting away and getting to information over Internet as opposed to putting away it on nearby machines’ hard drive. Cloud clients can empower to store their information on cloud with no nervousness about its exactness and
dependability. Anyway putting away information on cloud forces certain security challenges. Redistributing information in cloud result may lose physical authority over their information. Putting away and recovering such a lot of information devours part of time as information in the cloud
should be constantly put away in encoded arrangement while putting away and should be decoded while looking. There are various recommendations for executing questions over encoded information. This actualizes the customer to scramble information before re-appropriating it to the cloud in a
database conspire. To stay away from this monstrous utilization of time, information looking rate can be expanded by straightforwardly seeking over scrambled information in the cloud. There are numerous techniques utilized for looking through the encoded information over cloud. In catchphrase
based hunt plans overlook the semantic portrayal data of clients recovery, and can’t totally meet with clients seek goal. In this paper, propose ECSED, a novel semantic inquiry plot dependent on the idea chain of importance and the semantic connection between ideas in the scrambled datasets.
ECSED utilizes two cloud servers. One cloud server is utilized to store the reCloud datasets and restore the positioned outcomes to information clients. The other cloud server is utilized to figure the comparability scores between the archives and the question and send the scores to the principal
server. To additionally enhance the hunt proficiency, framework uses a tree-based file structure to sort out all the archive list vectors. At that point utilize the multi watchword positioned hunt over scrambled cloud information as our essential casing to propose two secure plans.
Implementation of Disease Prediction and Drug Recommendation
Authors: Likhithaa G. , Renuka T. , Christy A.
Published: October 2019

Medication errors are one of the major problems mostly seen in the hospitals. Manual prescription of medicine is difficult now days, so electronic prescription came into form. It is the alternative to the current method of manually prescription in hospitals. This paper introduces a
simple and easy classification technique that can be used to prescribe drugs according to the symptom parameters and if higher rate of symptoms exist then a better hospital for the treatment is suggested for the patient. It has many benefits for those who prescribe and dispense the medicines,
and also for maintenance of medical records. The complexity of the usage of medications has increased enormously. Due to the higher demand it can lead to a greater risk of errors. Hence the usage of E-prescribing has been developed out of it with less error rate. It provides better and more
reliable information about the patient’s medication. It saves staff time and improves the availability of patient information when needed. It also reduces the time spent by rewriting the charts of prescription etc.
Cuckoo Search Based Approach Towards Maximum Power Point Tracking for Solar Photovoltaic System Under Partial Shading
Authors: Nasikkar Paresh S. , Bhos Chandrakant D.
Published: October 2019

Extracting the maximum power from as solar PV system is a critical task when high changes in light intensity or Partial Shading Condition (PSC) are experienced. The latter case is more difficult as it creates multiple maxima points on P–V curve. In this way, it is obligatory
to thoroughly pick a precise Maximum Power Point Tracking (MPPT) method which recognizes adequately the Global Maximum Power Point (GMPP) and tracks it under partial shading. This paper first describes the modeling of PV module and PV characteristics under uniform irradiance as well as effect
of PSC on PV characteristics. In the latter sections, a review of conventional and intelligent MPPT methods is done. To tackle the problem of MPPT under PSC, two metaheurisric algorithms namely Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) are described briefly. A new optimization
method called Cuckoo Search (CS) is implemented in MATLAB SIMULINK tool and tested under three different PSC patterns. A comparative analysis of different MPPT strategies is made after analyzing the results.
Efficient Noise Removal Based Relevant Vector Machine to Detect Lung Disease
Authors: Dhanalakshmi P. , Satyavathy G.
Published: October 2019

The quality of images is decreased by noises. There exist several chances for the noises to occur while capturing and transmission the image. Noise removal becomes a thrust area of research in image processing. The outcome of the noise removal shows the quality of digital image processing
techniques. Noises in image lead to the semantic gap problem in medical image processing. Semantic gap problem becomes a serious issue in the classification of the medical image. With the aim to overcome this issue, this research work proposes an efficient noise removal method based on relevant
vector machine. Instead of using unsuited linear filters to detect noises, this research work uses the nonlinear filters which suit well to detect noises in multiple scale layers. The proposed method is applied to ADL dataset for the detection of lung cancer. The results clearly show that
the proposed noise removal based relevant vector machine performs better in terms of accuracy.
Electric Load Forecasting with Deep Machine Learning
Authors: Eldin Mustafa Abdelaziz Ala Adin Baha , Thang Ka Fei , Lukose Jacqueline
Published: October 2019

The most commonly used form of energy in houses, factories, buildings and agriculture is the electrical energy, however, in recent years, there has been an increase in electrical energy demand due to technology advancements and rise in population, therefore an appropriated forecasting
system must be developed to predict these demands as accurately as possible. For this purpose, five models were selected, they are Bidirectional-Long Short Term Memory (Bi-LSTM), Feed Forward Neural Network (FFNN), Long Short Term Memory (LSTM), Nonlinear Auto Regressive network with eXogenous
inputs (NARX) and Multiple Linear Regression (MLR). This paper will demonstrate the development of these selected models using MATLAB and an android mobile application, which is used to visualize and interact with the data. The performance of the selected models was evaluated by performing
the Mean Absolute Percent Error (MAPE), the selected historical data used to perform the MAPE was obtained from Toronto, Canada and Tasmania, Australia, where the year 2006 until 2016 was used as training data and the year 2017 was used to test the MAPE of the historical data with the models’
data. It is observed that the NARX model had the least MAPE for both the regions resulting in 1.9% for Toronto, Canada and 2.9% for Tasmania, Australia. Google cloud is used as the IoT (Internet of Things) platform for NARX data model, the 2017 datasets is converted to JavaScript Object Notation
(JSON) file using JavaScript programming language, for data visualization and analysis for the android mobile application.
Loan Default Prediction Model Using Sample, Explore, Modify, Model, and Assess (SEMMA)
Authors: Tariq Hafiz Ilyas , Sohail Asim , Aslam Uzair , Batcha Nowshath Kadhar
Published: October 2019

The purpose of this study is to provide a comprehensive research and to develop a model to predict the loan defaults. This kind of models becomes inevitable as the issue of bad loans are very much critical in the financial sector especially in micro financing banks of various underdeveloped
and developed countries. To cope up with this problem a comprehensive literature review was done to study the significant factors that leads to this issue. Moreover, these reviewed studies were critically focused towards applying data mining techniques for the prediction and classification
of the loan defaults. This study used methodologies named KDD, CRISP-DM and SEMMA. While in the experimentation phase, three different data mining techniques were applied for the proposed model and their performances were evaluated on various parameters. Based on these parameters, the best
method was selected, explained and suggested because of its significant characteristics regarding the prediction of the loan defaults in the financial sector.
Decision Support Credit Scoring Model to Improve Loan Default Prediction in Financial Institutions
Authors: Eria Kamya , Subramanian Preethi
Published: October 2019

Credit scoring plays a vital role in assessing the creditworthiness of loan applicants thus speeding up the approval process. Credit score models however rely on the accuracy of classification models for their performance. This accuracy performance depends not only on the choice of
data mining process; it is heavily influenced by the quality of data as well. Although no techniques can be favored over the other, it has been evidenced that logistic regression has been widely employed as an industrial technique for its comprehensive simplicity. This study proposes a SEMMA-based
credit scoring model developed with an improved Logistic Regression (LR) model. Improvements are by exclusion of irrelevant features and adjusting the partition ratios. The model has been compared with the predominant models and proved to contain outstanding results with minimal credit decision
errors.
Forecasting of Stock Price Using Autoregressive Integrated Moving Average Model
Authors: Jiang Loh Chi , Subramanian Preethi
Published: October 2019

Finance sector is highly volatile where the stock prices fluctuate rapidly and it is usually challenging to forecast. The unstable conditions and rapid changes can drastically modify the monetary value of an organization or an individual. Hence, the prediction of stock prices continues
to remain as one of the sizzling and vital topics in the applications of data mining in the finance sector. This forecasting is significant as it has the potential to reduce the losses that happen mainly due to erroneous intuitions and blind investment. Moreover, the prediction of stock prices
endure to increase in complexity with accumulation of more and more historical data. This paper focuses on American Stock Market (New York Stock Exchange and NASDAQ Stock Exchange). Taking into account the complexity of the prediction, this research proposes Autoregressive Integrated Moving
Average (ARIMA) model for estimating the value of future stock prices. ARIMA demonstrated better results for prediction as it can handle the time series data very well which is suitable for forecasting the future stock index.
Cuckoo Search Based Forest Cover Classification
Authors: Shanthasheela A. , Shanmugavadivu P.
Published: October 2019

Cuckoo Search optimization is one of the nature-inspired algorithms being widely experimented and explored to offer optimal and feasible solutions for science and engineering problems. It is inspired by the brood parasitism of cuckoo species laying their eggs in the other host birds’
nests. This research work is designed on the principle of the Cuckoo Search algorithm for the classification of forest cover in the satellite images. The proposed method titled, Cuckoo Search Based Classification (CSBC) is confirmed to have efficiently classified the forest cover with accuracy
of 95 percent and above. The results of this classification method are used to measure the land cover change, deforest cover change and to prepare forest maps.
Support Vector Machine for Effective Robust Visual Tracking
Authors: Ankayarkanni B. , Albert Mayan J. , Aruna J.
Published: October 2019

Protest following is the route toward confining the moving object from the video courses of action. Following is essentially a planning issue being referred to following. There exist innumerable after strategies with revealing accomplishment. Nevertheless, the testing issue in visual
after is to deal with the appearance changes of target question in perspective of its flexible limit. Difficulties in consequent things can appear due to non-inflexible development, quick advancement, broad assortment of stance and scale, obstacle and buoys etc. One of the standard reason
behind such frustrations is that, the unsuccessful picture portrayal designs of various figuring. In this paper, we show a visual after methodology using Support Vector Machine (SVM) close by various piece computation. The Expectation Maximization estimation relies upon the check and score
regard and empower portrayal using SVM. In protest following, select which question is taken after picking by customer. By then that challenge parts are evacuated. In perspective of the cutting edge and establishment stamp is set. By then this stamp and segments are given to the SVM getting
ready. We moreover consolidate an update intend to speak to address appearance change. Our tracker can manage hindrance and performs against existing visual after figuring in dealing with various conditions. Unique and quantitative evaluations over various testing show the engaged implementation
of our following figuring. The spine is question following and strange state affirmation is proposed for single dissent following, in which the target characterization is viably seen in the midst of following.
Mobile Cancer Prophecy System to Assist Patients: Big Data Analysis and Design
Authors: Suganya E. , Sountharrajan S. , Shandilya Shishir K. , Karthiga M.
Published: October 2019

The growth of cancer in India is growing hastily in recent years. Efficient monitoring and medication procedures are needed in high demand. Recent research states diagnose of cancer during its early break through will prevent mortality. The evolution of smart mobile devices paves its
mutual focus in healthcare sectors. In this paper, an Intellectual model of disease diagnosis using the advantage of smart mobile devices has been proposed. This mobile based cancer diagnosis model uses a cloud environment for disease prediction and analysis. The Principal Component Analysis
(PCA) technique is utilized to confiscate the superfluous features and choose the most appropriate features. Using the optimized features, cancer disease classification is accomplished using Support Vector Machines with sigmoid kernel function. SVM classifies the patients as normal and abnormal
and the evaluated results are conveyed to the patients as well as the respective medical practitioners. The accuracy achieved through proposed model is satisfiable in comparison with other existing methods. Proposed Model incorporates with big data technologies to address the current issues
of cancer system.
Effects of Moisture in a Two-Layer Model of the Midlatitude Jet Stream
Authors: Bembenek Eric , Straub David N. , Merlis Timothy M.
Published: October 2019

The effects of moisture on the energetics of a statistically stationary, baroclinically unstable jet representing the midlatitude atmosphere are examined using a two-layer, β-plane shallow-water model. Flow is driven by a relaxation of the interface between the two layers to a baroclinically unstable profile. Moisture is input to the lower layer by evaporation. When supersaturation occurs, precipitation is triggered and the related latent heat release drives a mass transfer between the two layers. A comparison between dry and moist reference atmospheres shows that precipitation reduces eddy kinetic energy. This is related to the meridional distribution of precipitation, which occurs on the poleward side of the jet (where the interface field is raised). This latitudinal structure of precipitation is related to a correlation between poleward flow and ascent, which is analyzed using a shallow-water analog to the ω equation. The precipitation effect on the energy budget is predominately due to zonal- and time-averaged terms. Because of this, dry simulations in which the thermal forcing is modified to mimic the effect of zonally averaged precipitation are carried out and compared with their precipitating counterparts. These simulations show a similar reduction of baroclinic eddy kinetic energy; however, the barotropic eddy kinetic energy response shows a larger difference.
Responses of the Hadley Circulation to Regional Sea Surface Temperature Changes
Authors: Zhou Chen , Lu Jian , Hu Yongyun , Zelinka Mark D.
Published: October 2019

Idealized experiments performed with the Community Atmospheric Model 5.3 indicate that the width and strength of the Hadley circulation (HC) are sensitive to the location of sea surface temperature (SST) increases. The HC edge shifts poleward in response to SST increases over the subtropical regions near and on the equatorward flank of the HC edge, and shifts equatorward in response to warming over the tropical area except for the western Pacific Ocean and Indian Ocean. The HC is strengthened in response to SST increases over the intertropical convergence zone (ITCZ) and is weakened in response to SST increases over the subsidence branch of the HC in the subtropics. Tropical SST increases off the ITCZ tend to weaken the HC in the corresponding hemisphere and strengthen the HC in the opposite hemisphere. These results could be used to explain the simulated HC changes induced by recent SST variations, and it is estimated that more than half of the SST-induced HC widening in 1980–2014 is caused by changes in the spatial pattern of SST.
ACC Subduction by Mesoscales
Authors: Canuto V. M. , Cheng Y.
Published: October 2019

The mesoscale contribution to subduction in the Southern Ocean was studied by Sallée and Rintoul in 2011 (SR11) using the following mesoscale model. The adiabatic (A) regime was modeled with the Gent–McWilliams streamfunction, the diabatic (D) regime was modeled with tapering functions, the D–A interface was taken to be at the mixed layer depth, and the mesoscale diffusivity either was a constant or was given by a 2D model. Since the resulting subductions were an order of magnitude smaller than the data of ±200 m yr−1 as reported by Mazloff et al. in 2010, SR11 showed that if, instead of the above model-dependent mesoscale diffusivities, they employed the ones reported in 2008 by Sallée et al. from surface drifter observations, the subductions compared significantly better to the data. On those grounds, SR11 suggested a 10-fold increase of the diffusivity. In this work, we suggest that, since the mesoscale diffusivity is but one component of a much large mesoscale parameterization, one should first assess the latter’s overall performance followed by an assessment of the predicted Antarctic Circumpolar Current (ACC) subduction. We employ the mesoscale model formulated by Canuto et al. in 2018 and 2019 that includes recent theoretical and observational advances and that was assessed against a variety of data, including the output of 17 other OGCMs. The ACC diffusivities compare well to drifter data from Sallée et al., and the ACC subduction rates are in agreement with the data.
Assessing Drivers’ Trust of Automated Vehicle Driving Styles With a Two-Part Mixed Model of Intervention Tendency and Magnitude
Authors: Lee John D. , Liu Shu-Yuan , Domeyer Joshua , DinparastDjadid Azadeh
Published: October 2019

Objective

This study examines how driving styles of fully automated vehicles affect drivers’ trust using a statistical technique—the two-part mixed model—that considers the frequency and magnitude of drivers’ interventions.

Background

Adoption of fully automated vehicles depends on how people accept and trust them, and the vehicle’s driving style might have an important influence.

Method

A driving simulator experiment exposed participants to a fully automated vehicle with three driving styles (aggressive, moderate, and conservative) across four intersection types (with and without a stop sign and with and without crossing path traffic). Drivers indicated their dissatisfaction with the automation by depressing the brake or accelerator pedals. A two-part mixed model examined how automation style, intersection type, and the distance between the automation’s driving style and the person’s driving style affected the frequency and magnitude of their pedal depression.

Results

The conservative automated driving style increased the frequency and magnitude of accelerator pedal inputs; conversely, the aggressive style increased the frequency and magnitude of brake pedal inputs. The two-part mixed model showed a similar pattern for the factors influencing driver response, but the distance between driving styles affected how often the brake pedal was pressed, but it had little effect on how much it was pressed.

Conclusion

Eliciting brake and accelerator pedal responses provides a temporally precise indicator of drivers’ trust of automated driving styles, and the two-part model considers both the discrete and continuous characteristics of this indicator.

Application

We offer a measure and method for assessing driving styles.
Insights Into Veterans’ Perspectives on a Peer Support Program for Glycemic Management
Authors: Lott Briana D. , Dicks Tanisha N. , Keddem Shimrit , Ganetsky Valerie S. , Shea Judy A. , Long Judith A.
Published: October 2019

Purpose

The purpose of this study was to explore the mentor-mentee relationship in veterans with type 2 diabetes and gain insight into successful pairings.

Methods

Qualitative semistructured interviews were conducted as part of a peer mentoring randomized controlled trial to understand participants’ experiences, their relationship with their partner, and how the intervention affected self-care behaviors. Purposive sampling was done to ensure adequate representation of mentees who made large strides in reaching their glycemic targets, those who made marginal improvements toward their glycemic goals, and those who got worse. All interviews were audio-recorded, transcribed, and analyzed for salient themes.

Results

The intervention was well received, with most participants describing it as valuable. Participants perceived the intervention to have a number of benefits, including accessible support, enhanced self-confidence, increased accountability, better self-efficacy, improved glycemic management, and a fulfilled sense of altruism. Participants did encounter barriers, including logistical, interpersonal, and individual obstacles. The more successful mentees tended to be more effusive in their description of their mentors, endorsed a stronger sense of connection to their mentor, described a more structured interaction with their mentor, and tended to be more complimentary of the intervention.

Conclusions

Large peer support programs are appealing and well received. These programs can be optimized by selecting naturally inclined mentors, providing additional training to introduce more structure into mentorship interactions, and targeting mentees who are not struggling with overwhelming comorbidities.
Patch and glue repair for extensive left ventricular laceration
Authors: Gennari Marco , Giambuzzi Ilaria , Polvani Gianluca
Published: October 2019

Laceration of the left ventricular wall is a rare but potentially life-threatening complication of electrophysiological studies. We describe emergency surgery on a 64-year-old man who suffered cardiac tamponade after an electrophysiological study, which revealed an extensive laceration in the inferior left ventricular wall, requiring repair by a patch and glue technique, with a good clinical outcome.
The impact of school music education: The experiences of four Catalan citizens
Authors: Pérez-Moreno Jessica , Carrillo Carmen
Published: October 2019

This study examines the impact made by music education on a sample of Catalan citizens who studied this subject during their compulsory schooling. A biographical narrative methodology was used to investigate a broad spectrum of the participants’ school musical experiences and to analyze the impact that music education has had on different aspects of their lives. Their perceptions and experiences, collected and expressed through life stories, show a correlation between the theoretical approach to learning music adopted by teachers and its little impact on the participants’ lives. Their stories also bring to light the difficulties involved in identifying and distinguishing the existing impact between both in-school and extracurricular music education but identify emotional impact as the most relevant one overall. Based on the evidence provided, this article aims to contribute to the debate on the role of music education on the school curriculum.
A case report of Sjögren’s syndrome associated with protein-losing gastroenteropathy successfully treated with methylprednisolone
Authors: Li Xiaoming , Lin Fan , Wu Ziyu , Chen Yan , Zhu Pengli
Published: October 2019

Protein-losing gastroenteropathy (PLGE) is a rare manifestation of primary Sjögren’s syndrome that is most commonly reported in Japan. Herein, the case of a 71-year-old Chinese male patient, diagnosed with PLGE and Sjögren’s syndrome, is reported. The patient presented with peripheral oedema, and PLGE was diagnosed based on the result of technetium-99m (99mTc)-labelled albumin scintigraphy. In addition to a positive Schirmer’s test, the patient had atrophy of the salivary gland with lymphocyte infiltration, impaired parotid-gland secretory and excretory function, and an increased level of anti-SSA antibodies, fulfilling the criteria for Sjögren’s syndrome. He was successfully treated with methylprednisolone. Follow-up 99mTc-labelled albumin scintigraphy results correlated well with clinical improvement and increased serum albumin levels. The present case study highlights the necessity of considering a diagnosis of protein loss enteropathy associated with primary Sjögren’s syndrome when patients have unexplained hypoproteinaemia.
Endoscopic therapy for gastro-oesophageal varices of Caroli’s syndrome: a case report
Authors: Wang Song , Xiao Mei , Hua Liqun , Jia Yong , Chen Si , Zhang Kaiguang
Published: October 2019

Caroli’s disease (CD) is a very rare congenital disorder that is characterized by non-obstructive, segmental and cystic dilatation of intrahepatic ducts. Most patients with CD are asymptomatic, but some patients may suffer from hepatic fibrosis, liver cirrhosis or/and portal hypertension. In complex CD, cystic dilatations of the intrahepatic bile ducts can be present with congenital hepatic fibrosis, liver cirrhosis, portal hypertension, oesophageal varices and autosomal recessive polycystic kidney disease; a condition known as Caroli’s syndrome. This report describes the case of a 28-year-old woman that had gastro-oesophageal varices that were caused by hepatic fibrosis and portal hypertension as part of Caroli’s syndrome. The patient underwent successful treatment with endoscopic injection sclerotherapy with lauromacrogol and endoscopic variceal obturation using tissue adhesive. There were no immediate complications and the patient remained free of complications at 1-year follow-up. There are no current reports in the published literature describing Caroli’s syndrome induced by gastro-oesophageal varices that were treated by a combination of endoscopic injection sclerotherapy and endoscopic variceal obturation. Endoscopic therapy was an effective technique for the treatment of gastro-oesophageal varices in a patient with Caroli’s syndrome awaiting a liver transplant.