bluuebunny/crossref_metadata_2025 huggingface dataset:
Google Assistant Controlled Home Automation
Authors: Bhanuabhiram K. , Tharun Kumar L. , Srinivasan N.
Published: October 2019

World’s interest for power had become 85% somewhere in the range of 2010 and 2017 this expansion is more than the present all out utilization of power in India, USA, Japan, Australia consolidated. We can’t diminish the power development rate however we can decrease the measure
of power squandered every year by killing our home machines when not being used. This venture shows a plan and model of Home Automation framework that will utilize ESP8266 Wi-Fi module as a system supplier in associating with different machines. The proposed framework has two principle segments.
The primary fundamental part is Arduino, which controls and oversees contribution of Wi-Fi module. The other principle segment is Wi-Fi module through Wi-Fi module a web server can be added to the module which will help in controlling of gadgets over Internet. One server can oversee numerous
equipment interface modules as long as it exists on Wi-Fi arrange inclusion. It bolsters a wide scope of home mechanization gadgets like power the board segments, and security parts. We need to make this automation framework incorporated and misleadingly astute. The framework is executed utilizing
common family apparatuses Natural language voice directions are given to the Google Assistant and with the assistance of IFTTT (If This Then That) application and the Blynk application the directions are decoded and after that sent to the microcontroller, the microcontroller thusly controls
the transfers associated with it as required, turning the gadget associated with the separate hand-off On or OFF according to the clients demand to the Google Assistant. The microcontroller utilized is Node MCU (ESP8266) and the correspondence between the microcontroller and the application
is built up by means of Wi-Fi.
Smart Car Sharing
Authors: Murugan S. , Madhu Varma K. , Sai Prudhvi M. Y. N.
Published: October 2019

With the tremendous increment in number of vehicles on street, individuals around the nation particularly in metro urban areas have begun confronting issue now because of increment in rush hour gridlock which added a hour or so to their day by day voyaging time. Out of couple of, one
of the techniques to decrease this hopelessness of explorers is to make them share vehicles. In Existing System, With in the city or Particular Destination just The Car Services is Available. The objective of this work is to design a “car pooling,” which is a use of vehicle sharing
(additionally called lift-sharing or ride-sharing) in which drivers (alone-riders) who are heading out to work alone can request individual travelers through our application. For the individuals who utilize open transport framework to go to work day by day can utilize this application to discover
drivers who are heading out to a similar goal and willing to share ride. Get-together individuals into normal excursions prompts individual and social productivity. At an individual dimension, it lessens the complete voyaging cost and the driving worry also. In spite of the fact that it is
less agreeable than utilizing the individual vehicle and individuals generally require more opportunity for playing out the movement, the wide acknowledgment of the mutual use portability demonstrates its feasibility, with down to earth advancements not so much investigated. By utilizing this
strategy the Users can Travel Anywhere with Low expense. This won’t just dispose of the additional voyage time of travelers yet will likewise help condition by diminishing contamination and traffic on streets. This person to person communication application is additionally called toll
sharing and time sharing as you will be you are imparting both to individual voyagers.
Implementation of Smart Attendance Monitoring Using Open-CV and Python
Authors: Anto Praveena M. D. , Eriki Mohana Krishna , Enjam Dharma Teja
Published: October 2019

Uniqueness or individuality of a person is his face. In this paper, face of an individual is used for the purpose of attendance taking automatically. Maintaining attendance of a student is very important task in all the institutes to check the performance of students. Every institute
has its own way for taking attendance. Some of the institutes use paper or file based approach, and some are using methods of automatic attendance taking using biometrics methods which is very time consuming process. There are many methods available for this purpose. Facial recognition may
be a unambiguously distinctive or corroboratory an individual by comparison and analysing the patterns supported person’s facial contours. Facial recognition is mostly used for security purposes at so many places. This process can be divided into two phases, processing before recognition
where face detection takes place, and afterwards face recognition takes place through feature extraction and matching steps. This system uses the face recognition for taking automatic attendance of students in the classroom without student’s intervention. This attendance is recorded
by using a camera that captures images of students and detect the faces after which it compares and faces are detected with the database and mark the attendance for the students. Attendance sheet will be generated and message will be sent to the parents.
Intelligent Security System for Banking Using Internet of Things
Authors: Mohan Kumar U. , Siva SaiManikanta P. , AntoPraveena M. D.
Published: October 2019

This project proposes a technique for planning a security system for banking with email alerts and sensors. In the presence scenario there are so many banking techniques arrived but none of those are secure the properties without vulnerability. So our project main motto is to protect
and also provide security without vulnerability. We use IOT to provide high end security for banking system. Our aim is not only identify the authenticate user but also protecting the customers property from theft. We use tilt sensor, pressure sensor, smoke sensor and pir sensor, this sensors
is used to identify the unauthorized person activity and prevent him steeling the property and capture the victim image by using web cam and transfer it to user. This technique remove all the vulnerabilities and make sure that the credentials are safe and it will capture the unauthorised person
who tries to axis the security system.
Machine Learning Techniques for Rainfall Prediction Using Neural Network
Authors: Refonaa J. , Lakshmi M. , Dhamodaran S. , Teja Surya , Pradeep T. N. M.
Published: October 2019

Rainfall prediction accuracy in meteorological department is still a major research area. Accuracy in prediction of rainfall may help in knowing heavy rainfall prior and preventing disasters. This mainly associated with economy and human life. There is necessary for efficient prediction
system to identify drought and flood prior, so that people and government can get prepared for any disaster. Our country economy are mainly depends on agriculture, there is a great importance for rainfall prediction in India. Dynamics in atmosphere is the major cause for failure of existing
statistical techniques for rainfall prediction. Taking these in consideration, we propose, Neural network based rain fall prediction for better showing better performance. We exploit machine learning, in which neural network model is used from Keras package available in Python. The objective
of the work is to make this model more reliable for non-technical persons.
Automatic User Domain Classification Based on Support Vector Machine (SVM)
Authors: Selvan Mercy Paul , Viji Amutha Mary A. , Jancy S.
Published: October 2019

Finding domain of a research paper and a researcher is a crucial task and would be highly appreciable in order to provide personalized search results to the user. An automatic user domain classification technique based on SVM has been proposed in this paper in order to determine the
domain of a user based on her publications. In this technique, for a given user, his specific area of domain is determined by classifying the keywords from his publication works. It consists of two phases: keyword extraction and domain classification. In keyword extraction phase, the list
of publications corresponding to a user mail id is retrieved by using publish or perish tool. From each of the published papers, the keywords are extracted. In domain classification, SVM classifier is applied to determine the domain of the user. This is performed by training standard keywords
from each domain into the SVM classifier. If a user belongs to more than one domain, then the primary domain with more publications will be considered.
Integrated Wireless Monitoring System Using LoRa and Node-Red for University Building
Authors: Selvaperumal Sathish Kumar , Al-Gumaei Waleed , Abdulla Raed , Thiruchelvam Vinesh
Published: October 2019

This paper aims to design and develop a network infrastructure for a smart campus using the Internet of Things which can be used to control different devices and to update the management with real-time data. In this proposed system, NodeMCU ESP8266 is interfaced with thermal and motion
sensor for human, humidity and temperature sensor for the room and relay to control the lights and the air-conditioned. MQTT broker is used to acquire the data and control to and from NodeMCU ESP8266, Raspberry pi and LoRa, to be interfaced wirelessly with the Node-Red. Thus, the system is
controlled and monitored wirelessly with the help of the developed integrated Graphical User Interface along with the Mobile application. The performance of the developed proposed system is analyzed and evaluated by testing the motion detection in the classroom, the LoRa range with the RSSI,
the average time taken by the system to respond, the average time taken for the Graphical User Interface to response and update its data. Finally, the average time taken by the system and the Graphical User Interface to respond to the lights and air-conditioned control systems is less than
1 s, and for the security and parking systems is less than 2 s.
Autonomous Anomaly Detection System for Crime Monitoring
Authors: Shuaau Muhammed , Thang Ka Fei
Published: October 2019

Autonomous anomaly detection has attracted significant amount of attention in the past decade due to increased security concerns all around the world. The volume of data reported by surveillance cameras has outrun human capacity and there exists a greater need for anomaly detection
systems for crime monitoring. This project proposes a solution to this problem in a reception area context by using trajectory analysis. Trajectory extraction is proposed by using Gaussian Mixture Models and Kalman Filter for data association. Then trajectory analysis is performed on extracted
trajectories to detect four different anomalies which are entering staff area, running, loitering and squatting down. The proposed anomaly detection method is tested on datasets recorded at Asia Pacific University’s reception area. The proposed algorithms were able to achieve a detection
accuracy of 89% and a false positive rate of 4.52%. The results presented show the effectiveness of the proposed method.
Hybrid Particle Swarm Optimization-Extreme Learning Machine Algorithm for Customer Churn Prediction
Authors: Li Koh Guan , Marikannan Booma Poolan
Published: October 2019

Customer churn which also commonly referred to as customer attrition, occurs when a customer ceases or stops doing business with a particular company or service. Predicting customer churn had become one of the major aim of businesses is various sectors, namely the telecommunication
sector as the markets are very saturated. Apart from that, the cost to retain existing customers is much lesser as compared to the cost to acquire or attract new customers through marketing. This paper proposes a new hybrid algorithm which incorporate the algorithms of Particle Swarm Optimization
(PSO) as well as Extreme Learning Machine (ELM) to build a telecommunication churn prediction model which can accurately predict churners and non-churners. This model will be named as Particle Swarm Extreme Learning Machine (PSELM) model. PSO algorithm is able to effectively scale the selected
features so that ELM algorithm can classify data based on these features more easily and provide accurate classification.
Optimization of Series Compensation in Transmission Networks Using Artificial Neural Networks
Authors: Faiz Aunowar Mohammad , Lukose Jacqueline
Published: October 2019

To respond to the ever-increasing power demand of load centers, power is transmitted at extrahigh voltages. However, an increase in power transfer level should be supported by an enhanced level of security. Flexible AC Transmission System (FACTS) devices present an economical and efficient
alternative to consider for achieving higher power transfer level with enhanced security instead of introducing new transmission facilities, to maintain a large stability margin of power in transmission line. This project aims to optimize the level of series compensation in transmission networks
using Artificial Neural Network (ANN). Series compensation enables higher level of power to be transferred by reducing (reactive) losses. Among the series FACTS controllers, Thyristor Controlled Series Compensator (TCSC) has been chosen to be optimized on an SMIB system. Lead-Lag (LL) based
TCSC remain the controller of choice due to the favorable performance to cost ratio. Nevertheless, modeling the highly non-linear power system with a linear controller, limits the system’s performance during adversities. ANN being non-linear per se and possessing high generalization
capabilities, offers more versatility in modeling the power system. Indeed, an ANN based TCSC was designed and the performance during contingencies was compared to that of the LL based TCSC. As expected, the ANN based TCSC demonstrated a damping capability twice as fast and offering the SMIB
system with a higher robustness as well as better resistance to fault condition. To increase the accuracy and reliability of the proposed controller, the investigation can be performed on a multi-machine system with different loading conditions as well as determining the optimal location of
the TCSC module.
Push-n-Pop Genes Xchange (PPX)—A New Crossover Operator in Genetic Algorithm
Authors: Lagarteja Joe G.
Published: October 2019

Crossover operator plays a crucial role in of Genetic Algorithm (GA). It is one of the key elements in GA which is responsible for producing offsprings usually called “solutions” by way of recombining information from two parents providing experimental mechanism of the algorithm.
Crossover operator is a critical factor that affects performance of GA due to its impact on time being used in the crossover process. This paper introduces a new crossover operator named Push-n-Pop Genes Xchange Operator (PPX). Evaluation of its performance in terms of processing time is also
presented in this paper. The results of PPX’s performance with all other six existing GA’s crossover operators (Half-uniform, Surrogate, Segmented, Shuffle, Two-point, and Uniform) show that PPX is in comparable using different population sizes 30, 50, and 100. Results also
show that the new crossover operator performed better with a maximum improvement of 13.1% when population size was gradually increased from 30 to 100.
Proposition of Machine Learning Driven Personalized Marketing Approach for E-Commerce
Authors: Tan Kok Sheng , Subramanian Preethi
Published: October 2019

The ubiquity of digital devices and Internet has formed a constantly connected online environment which led to the extensive adoption of e-commerce. However, the active participation of growing number of stakeholders intensifies the highly competitive landscape of the dynamic e-commerce
market and the scarcity of trust in e-commerce business impede the generation of consistent sales growth. The obstruction necessitates the implementation of innovative marketing strategies to enhance the relationships with customers to develop customer loyalty. Therefore, a machine learning
driven personalized marketing approach is proposed to facilitate the implementation of personalized marketing in which there are 2 significant sequential elements namely, the development of personalized marketing contents and delivery of the contents to prospective customers. Cluster analysis
is employed to perform customer segmentation to discover customer segments due to the capability of the analysis to identify similarities in customer preferences in which the discovered customer segments are used to construct personalized marketing contents. In addition, artificial neural
network is employed to predict prospective customers due to the capability of artificial neural network to comprehend complex relationships between customer demographics and buying behaviour in which the prediction facilitates the delivery of the constructed personalized marketing contents
to potential repeat customer to optimize the marketing initiative. The combination of cluster analysis and artificial neural network empowers the construction of an efficacious marketing pipeline which enhances the competency of e-commerce businesses.
A Comprehensive View of Scheduling Algorithms for MapReduce Framework in Hadoop
Authors: Pandian Asha , Varadharajulu Bharathi , John Albert Mayan , Jacob Prem , Pravin
Published: October 2019

We reside in information world which makes great difficulty in quantifying the aggregate volume of information put away electronically, and exist in the unit of Zettabytes or Exabyte, hence termed as Big Data. They can be unstructured, organized or semi organized, processing of these
data cannot able to be done with normal data management techniques. Hadoop framework is utilized to process huge datasets in a proficient and economical way. MapReduce system is utilized to gather information according to the solicitation. To handle expansive volume of information legitimate
planning is obliged to accomplish more noteworthy execution. Scheduling jobs in parallel across the nodes is an important concern in MapReduce clusters. Also to improve the performance with the large volume of data proper scheduling method should be adopted. The objective of the work is to
study about the different scheduling techniques used in Hadoop environment and to achieve effective fairness without starvation.
A Study of the Cryptographic Technologies on Big Data Privacy and Security in E-Commerce
Authors: Mafas Raheem , Jayabalan Manoj
Published: October 2019

In this era, big data is the most common buzzword across different industries due to its capabilities of collecting, processing, storing and analysing data. The advancement of the E-Commerce paved the way for merchants and customers to meet online to satisfy their requirements by exchanging
goods and services at a reasonable cost. The challenges and opportunities for big data on the emphasis of data privacy and security is a widely discussed topic among businesses especially E-Commerce merchants. There are several reviews available on emphasizing big data opportunities and challenges
with regard to privacy and security. However, a comprehensive review on E-Commerce highlighting thematically on the tools and technologies is not given enough consideration. Therefore, the purpose of this study is to review the state-of-the-art technologies towards privacy and security in
the E-Commerce platforms. The identified cryptographic technologies were also discussed with the rational standpoint to understand the viability to apply in the E-Commerce operations. The study concludes with an enlightening path from which the E-Commerce merchants can be vigilant on data
privacy and security in future.
Dental Radiograph Segmentation and Classification—A Comparative Study of Hu’s Moments and Histogram of Oriented Gradients
Authors: Janardanan Rameswari Poornima , Logeswaran Rajasvaran
Published: October 2019

This paper proposes a method to compare two feature descriptors to classify dental X-rays, using Hu’s Moments (HM) and the Histogram of Oriented Gradients (HOG). The dental radiographs are preprocessed, and the shape features of teeth are derived using HM and HOG. Support Vector
Machine (SVM) is then used for tooth classification and recognition. Comparison of the results of using the two approaches as feature descriptors revealed that regardless of its orientation, size and position, moment invariant functions are very useful for object classification. The classification
of images into molar and premolar has been done on manually cropped images. This method was validated on periapical radiographs. Results obtained show that using both HM and HOG to classify and recognize teeth shape description accuracy as better than, or at least comparable, to the state-of-the-art
approaches. This work aids to improve the computer-assisted diagnosis and decision in dentistry. The forensic odonatological applications of this approach are wide and of immense benefits in both forensic and biometric identification.
Implicit Order 3/2 Strong Method for Numerical Solutions of Stratonovich Stochastic Differential Equations
Authors: Alhojilan Yazid
Published: October 2019

Due to that the explicit methods in solving stochastic differential equations give instability and inaccurate results, the aim of this paper is to derive an effective implicit method gives higher-order approximate solutions for a stiff stochastic differential equations by using Runge-Kutta
method. It relies on the Stratonovich-Taylor expansion and uses the notion of perturbation and coupling to carry out the method. The validity of this new approximation method is shown by implementing in MATLAB and, showing the convergence of the method graphically.
Interventions to Mitigate Fatigue Induced by Physical Work: A Systematic Review of Research Quality and Levels of Evidence for Intervention Efficacy
Authors: Lu Lin , Megahed Fadel M. , Cavuoto Lora A.
Published: October 2019

Objective

We present a literature review on workplace physical fatigue interventions, focusing on evaluating the methodological quality and strength of evidence.

Background

Physical fatigue is a recognized workplace problem, with negative effects on performance and health-related complaints. Although many studies have focused on the mechanisms and consequences of fatigue, few have considered the effectiveness of interventions to mitigate fatigue.

Method

A systematic review of the workplace safety literature for controlled trials of physical fatigue interventions was conducted. Data on intervention type, subject characteristics, targeted tasks and body locations, outcome measures, and study design were extracted. The methodological quality for each study was evaluated using the PEDro scale, and the level of evidence was based on quality, amount, and consistency.

Results

Forty-five controlled trials were reviewed, examining 18 interventions. We categorized those interventions into individual-focused ( N = 28 studies, nine interventions), workplace-focused ( N = 12 studies, five interventions), and multiple interventions ( N = 5 studies, four interventions). We identified moderate evidence for interventions related to assistive devices and task variation. There was moderate evidence supporting no fatigue attenuation for the garment change category of interventions. The interventions in the remaining categories had limited to minimal evidence of efficacy. The heterogeneity of the included trials precludes the determination of effect size.

Conclusion

This review showed a lack of high levels of evidence for the effectiveness of most physical fatigue interventions.

Application

Due to a lack of high levels of evidence for any category of reviewed physical fatigue interventions, further high-quality studies are needed to establish the efficacy of others.
Failure behavior of woven fiberglass composites under combined compressive and environmental loading
Authors: Paradiso Ariana , Mendoza Isabella , Bellafato Amanda , Lamberson Leslie
Published: October 2019

The purpose of this study is to quantitatively characterize the compressive and damage behavior of a woven fiberglass composite under combined environmental loading. Cuboidal samples of a commercially available woven fiberglass epoxy resin composite, garolite G10, are examined under uniaxial compressive loading perpendicular to the plies at quasi-static (10−3 s−1) and dynamic (103 s−1) strain rates using a standard load frame and Kolsky (split-Hopkinson) bar. In order to simulate environmental conditions, a subset of samples were soaked in either distilled or ASTM standard seawater prior to loading. Two time periods of environmental conditioning were investigated: short term at two weeks and long term at four months. Results demonstrate that, on average, the dynamic compressive strength of the fiberglass increased 35% from the quasi-static. Moreover, environmentally treated samples generally experienced a decrease strain to failure, and composites exposed to water for only short periods exhibited signs of the absorbed water sustaining additional load under quasi-static rates. Ultra-high-speed photography combined with digital image correlation, a full-field surface kinematic measurement technique, is used to map 2D strains on the sample during loading. In all cases, a clear shear failure mechanism from local instabilities appears, and a Mohr–Coulomb failure criterion is used to extract a mesoscale cohesive shear stress and coefficient of internal friction.
Characterization of applied tensile stress to carbon epoxy composites by measuring the variation of transverse thermal conductivity using transmission thermography
Authors: Bayat M , Safizadeh MS
Published: October 2019

Using the method of step heating thermography, this study seeks to detect and characterize the existence of stress in a beam sample of carbon epoxy composite with the stacking sequence of [08] aided by empirical and simulation approaches. The applied stress in the longitudinal direction of sample, while considering the Poisson’s ratio, changes the lateral dimensions of sample. Furthermore, it is shown that the thermal conductivity along the sample thickness varies as a result of stress existence. Accordingly, to obtain a relation between transverse thermal conductivity and longitudinal tensile stress, one should calculate and eliminate the effect of lateral deformation caused by stress. To this end, by combining the experimental and simulation results of composite sample under the action of different tensile loads, an equation describing the variation of thermal conductivity along the sample thickness with respect to applied stress is developed. Using the relation of transverse thermal conductivity variation in terms of applied stress, the finite element modeling is again carried out by rectifying the values of thermal conductivity. Simulation results are compared with experimental ones, indicating very good agreement between the two approaches.
How Do Authoritarian Leadership and Abusive Supervision Jointly Thwart Follower Proactivity? A Social Control Perspective
Authors: Li Rui , Chen Zhijun , Zhang Huihua , Luo Jinlian
Published: October 2019

A number of studies have examined how employees regulate their behaviors in keeping with their leaders’ formal control (e.g., authoritarian leadership) or informal control (e.g., abusive supervision). Yet, these two lines of investigation are largely unintegrated. Drawing on a social control perspective, we integrate these two forms of controlling behaviors into one coherent model and link them to employee proactive behaviors. We propose that authoritarian leadership and abusive supervision substitute effects from each other in thwarting followers’ proactivity by increasing their perceived powerlessness. We then test our hypotheses with three field samples of Chinese supervisor-subordinate dyads, using different exemplary behaviors to operationalize proactivity (i.e., taking charge, personal initiative, and proactive performance). The findings across the three studies show that authoritarian leadership and abusive supervision weaken each other’s effects in terms of inhibiting subordinate proactive behaviors. Moreover, in our third study, perceived powerlessness mediates this interaction effect. These results, however, do not generalize to employee affiliative behaviors, operationalized as altruism, cooperation, and conscientious behaviors. The implications of our findings for theory and practice are discussed.
Scientific and Regulatory Policy Committee Points to Consider*: Approaches to the Conduct and Interpretation of Vaccine Safety Studies for Clinical and Anatomic Pathologists
Authors: Sellers Rani S. , Nelson Keith , Bennet Bindu , Wolf Jayanthi , Tripathi Niraj , Chamanza Ronnie , Perron Lepage Marie-France , Adkins Karissa , Laurent Sebastien , Troth Sean P.
Published: October 2019

The design and execution of toxicology studies supporting vaccine development have some unique considerations relative to those supporting traditional small molecules and biologics. A working group of the Society of Toxicologic Pathology Scientific and Regulatory Policy Committee conducted a review of the scientific, technical, and regulatory considerations for veterinary pathologists and toxicologists related to the design and evaluation of regulatory toxicology studies supporting vaccine clinical trials. Much of the information in this document focuses on the development of prophylactic vaccines for infectious agents. Many of these considerations also apply to therapeutic vaccine development (such as vaccines directed against cancer epitopes); important differences will be identified in various sections as appropriate. The topics addressed in this Points to Consider article include regulatory guidelines for nonclinical vaccine studies, study design (including species selection), technical considerations in dosing and injection site collection, study end point evaluation, and data interpretation. The intent of this publication is to share learnings related to nonclinical studies to support vaccine development to help others as they move into this therapeutic area.

[Box: see text]
Susceptibility Variations in Air Pollution Health Effects: Incorporating Neuroendocrine Activation
Authors: Kodavanti Urmila P.
Published: October 2019

Diverse host factors/phenotypes may exacerbate or diminish biological responses induced by air pollutant exposure. We lack an understanding of biological indicators of environmental exposures that culminate in a physiological response versus those that lead to adversity. Variations in response phenotype might arise centrally and/or at the local tissue level. In addition to genetic differences, the current evidence supports the roles of preexisting cardiopulmonary diseases, diabetes, diet, adverse prenatal environments, neurobehavioral disorders, childhood infections, microbiome, sex, and psychosocial stressors in modifying the susceptibility to air pollutant exposures. Animal models of human diseases, obesity, nutritional inadequacies, and neurobehavioral conditions have been compared with healthy controls to understand the causes of variations in susceptibility. Although psychosocial stressors have been associated with increased susceptibility to air pollutant effects, the contribution of neuroendocrine stress pathways in mediating these effects is just emerging. The new findings of neuroendocrine activation leading to systemic metabolic and immunological effects of air pollutants, and the potential contribution to allostatic load, emphasize the consideration of these mechanisms into susceptibility. Variations in susceptibility to air pollution health effects are likely to underlie host genetic and physiological conditions in concert with disrupted neuroendocrine circuitry that alters physiological stability under the influence of stressors.
Adult tetralogy repair: factors affecting early outcome in the current era
Authors: Ramanan Sowmya , Sasikumar Navaneetha , Manohar Krishna , Ramani Salla Sweta , Kumar RaghavanNair Suresh , Agarwal Ravi , Subramanyam Raghavan , Cherian Kotturathu Mammen
Published: October 2019

Background

The benefits of surgical correction of adult tetralogy of Fallot are well known. The current recommendation is for total correction regardless of age. This study analyzed perioperative factors affecting early outcome after corrective surgery in adulthood in the current era.

Methods

This was a retrospective chart review of 40 consecutive patients over 18 years of age who underwent total correction of tetralogy of Fallot from September 2006 to June 2013. Patients with pulmonary atresia and absent pulmonary valve were excluded. The mean age at surgery was 26.60 ± 8.69 years (range 18–49 years).

Results

The mean intensive care unit stay was 3.30 ± 2.29 days (range 0.75–12 days) and hospital stay was 9.97 ± 3.39 days (range 7–22 days). Mortality was 5% (2/40). Multiple parameters indicating immediate postoperative outcomes and their relationships to selected pre-, intra-, and postoperative factors were analyzed. Multivariate analysis showed that postoperative right ventricular dysfunction had a significant influence on mortality ( p < 0.001) and hospital stay ( p = 0.01). Performing zero-balance ultrafiltration decreased the need for renal replacement therapy ( p = 0.034), duration of ventilation ( p = 0.009), incidence of low cardiac output ( p = 0.006), intensive care unit stay ( p = 0.01), and hospital stay ( p = 0.009).

Conclusions

Total correction of tetralogy of Fallot is a safe option for presentations as late as adulthood. The protective effect of zero-balance ultrafiltration on postoperative morbidity needs to be reassessed in larger studies.
Assessment of Anterior Chamber by Ultrasound Biomicroscopy and Anterior Segment Optical Coherence Tomography in Patients with Inflammatory Glaucoma
Authors: Qian Yiyong , Liu Lin , Shi Yuehui , Wang Minli , Li Min , Zou Jun
Published: October 2019

Objective

To investigate the clinical indications of ultrasound biomicroscopy (UBM) and anterior segment optical coherence tomography (AS-OCT) in eyes with inflammatory glaucoma.

Methods

Sixteen patients (16 eyes) with inflammatory glaucoma were analysed retrospectively. All of the subjects underwent UBM and AS-OCT scans, measuring the following parameters: central corneal thickness (CCT), central anterior chamber depth (ACD), angle-opening distance (AOD500), and trabecular-iris angle (TIA500) in four quadrants.

Results

Both the UBM and AS-OCT generated detailed, high-resolution images of the anterior segments of the eyes with inflammatory glaucoma. Moreover, the UBM and AS-OCT exhibited statistically similar measurement results for all of the indices. A Bland–Altman analysis showed a high level of agreement between the two imaging techniques. Additionally, the UBM was able to visualize the ciliary body and pars plana, while the cells and the flare in the anterior chamber appeared more pronounced in the UBM images.

Conclusions

Both the UBM and AS-OCT are useful tools for anterior segment imaging and taking measurements needed for evaluating inflammatory glaucoma. The AS-OCT has the advantages of being noninvasive and fast, whereas the UBM is presently unparalleled in the visualization of the ciliary body and pars plana.
Metabonomics window into plateau hypoxia
Authors: Chang Yue , Zhang Wen , Chen Kai , Wang Zhenguo , Xia Shihai , Li Hai
Published: October 2019

Oxygen deficiency in the plateau environment weakens aerobic metabolism and reduces the energy supply, leading to high-altitude diseases including decreased circulatory function, decreased nutrient and energy supply to tissues and organs, and decreased waste discharge. The involvement of many metabolic pathways is reflected in dramatic changes in levels of endogenous small molecule metabolites. Metabolomics represents a promising technique for mechanistic studies and drug screening, and metabonomics, or quantitative metabolomics, has been increasingly applied to the study of hypoxic diseases and their pathogenesis, as well as to pharmacodynamics at high altitudes. In this article, we review the recent literature on the pathogenesis of altitude hypoxia and the clinical and preclinical metabonomics of drug interventions. Endogenous metabolites and metabolic pathways change significantly under high-altitude hypoxia. Some drug interventions have also been shown to regulate pathway metabolism, and the problems of applying metabonomics to hypoxic diseases at high altitude and the prospects for its future application are summarized.
Visualising urban gentrification and displacement in Greater London
Authors: Zhang Yuerong , Chapple Karen , Cao Mengqiu , Dennett Adam , Smith Duncan
Published: October 2019

Gentrification has long been a contentious issue which has prompted debate among scholars due to variations in its location, timing, context and types of measurements used. Therefore, it is worth seeking a simple and effective approach to measure the processes of gentrification, which enables comparative studies to be conducted across different cities around the world. Using six sets of thematic data from 2001 and 2011 at the neighbourhood level, this study proposes five types of gentrification and displacement by using Chapple and Zuk’s theoretical framework. London was selected as a case study. The results show that gentrification was sweeping in many ways during the 2000s in London, particularly in Inner East London. Some areas in North West London are identified as vulnerable neighbourhoods at risk of displacement and gentrification. Furthermore, it was found that most of the neighbourhoods experiencing ongoing displacement are concentrated in Outer London and Inner South London. The typology provides a useful starting point for planners and policymakers to gain deeper insights into the progress of gentrification in London. Additionally, this work can serve as an example to illustrate the potential for using similar types of open source code and census data to estimate the degree of gentrification in other cities.
Salvation or Commodification? The Role of Money and Markets in Global Ecological Preservation
Authors: Davis Ann E.
Published: October 2019

Rather than view the market as a tool for addressing climate change, through carbon tax or carbon permits, we argue that redefining “property” is more effective. Instead of right to exclude and absolute individual ownershp, we recommend ecological communities which prioritize human relationships and ecological stewardship. Global federations of ecological regions will manage nutrient flows on the local and global level, with democratic participation informed by ecological science. New values of caring for the earth will support and sustain new forms of solidarity.

JEL Classification: B5, Q5
How Nurses Understand Spirituality and Spiritual Care: A Critical Synthesis
Authors: Cooper Katherine Louise , Chang Esther , Luck Lauretta , Dixon Kathleen
Published: October 2019

Aims: To discover how nurses understand spirituality and spiritual care and what affects nurses’ understanding of these terms. Method: A literature search was conducted in CINAHL Plus, MEDLINE, and Google Scholar for research articles dated between 2010 and 2018 that were published in English. Using the Critical Appraisal Skills Program checklist for systematic reviews, nine articles met the inclusion criteria for this review. Most of these articles reported quantitative studies. Results: Although nurses recognize the importance of spirituality and spiritual care in nursing and have ascribed a diversity of meanings, there remains some confusion about what these terms mean. Several influences have been identified as shaping nurses understanding of spirituality and spiritual care, including education, nurses’ own spirituality or religious beliefs, age, years of clinical experience, and place of employment. Conclusions: This review identifies the need for further studies using qualitative approaches to investigate how nurses’ construct their understanding of spirituality and spiritual care and the dominant discourses nurses draw from to inform their understanding using qualitative approaches. Relevance to Clinical Practice: The insights gained by this review may be of value to nurse educators, managers, and policy makers in nursing education and the development of policies and practice guidelines.
Experimental study on the longitudinal resistance of WJ-8 fasteners subjected to torque and vertical loading in continuously welded rails
Authors: Zeng Zhiping , Tian Chunyu , Tu Qinming , Shuaibu Abdulmumin Ahmed , Wang Weidong
Published: October 2019

The key functions of the fastener system are to hold the rail against the sleepers and to restrain the rail from all forms of movements that could lead to loss of geometry and stability of the track. Thus, fastener resistance is an important parameter in the continuously welded rail technology. This study investigates the characteristics of the longitudinal resistance of WJ-8 fasteners subjected to varying torques and vertical loadings. The vertical loading was applied to the rail section through a reaction frame, while the torque was applied using a digital torque wrench. Two types of fasteners, conventional-resistance and small-resistance fasteners, were tested in this study. The study shows that: (1) The growth rate of the longitudinal resistance of the fastener is independent of the vertical loading until the fastener slips. (2) The slip resistance of fasteners increases as the torque and vertical loading are increased. (3) The relationship between the longitudinal resistance and the displacement of fasteners at varying torques and vertical loadings fits a power index function. (4) The relationship between the longitudinal resistance and the displacement of the fastener exhibits hysteresis. The study serves as a reference for verifying and improving future calculation methods for the longitudinal resistance of fasteners in continuously welded rails.
Mapping the relationship between the structural deformation of a simply supported beam bridge and rail deformation in high-speed railways
Authors: Jiang Lizhong , Zheng Lan , Feng Yulin , Lai Zhipeng , Zhou Wangbao
Published: October 2019

By considering the effect of the constraints of the rails on the subgrade section on both sides of a bridge, analytical expressions are derived to study the mapping relationship between the rail deformation and changes in the condition of the supporting beam(s), based on the principle of minimum potential energy. Rail deformations in a slab track–bridge system induced by the subsidence of piers and beam faults are investigated in detail. Results are compared with the finite element calculations to assess the main factors that influence rail deformation. The results show that the rail deformation curves under different working conditions (single or multiple pier subsidence and beam faults) determined using the analytical model fit well with those from the finite element models. With increasing subsidence of piers, the rail deformed more significantly in the subsidence zone. Moreover, both the maximum downward and upward deformations of the rail changed linearly with the subsidence of piers. Use of fasteners or a mortar layer with greater vertical stiffness caused the rail to become more irregular.
Field measurement of the dynamic responses of a suspended monorail train–bridge system
Authors: He Qinglie , Cai Chengbiao , Zhu Shengyang , Zhang Jiawei , Wang Kaiyun , Zhai Wanming
Published: October 2019

This work presents an integrated and large-scale field measurement of the dynamic responses of a suspended monorail train–bridge system, which is rarely reported. This experimental train uses a high-capacity lithium battery for the operation. The maximum running speed of the train is up to 60 km/h. The experimental line was constructed on a full-scale steel bridge composed of a straight section, curved sections with different horizontal radiuses and a slope section of 60‰. First, the train–bridge dynamic responses under different conditions are extracted based on the field test. Then, the car-body accelerations under different train speeds and bridge sections are analysed in detail, and the running stability of the vehicle is assessed by adopting the Sperling index. By comparing the dynamic responses of the train–straight bridge interaction and the train–curved bridge interaction, some significant discrepancies and interesting phenomena could be found. Subsequently, based on the test data, the vertical rotation angles of the beam end and the dynamic amplification factors of the bridge displacements under different vehicle speeds and bridge sections are obtained, and then the vibration levels of the bridge under different conditions are evaluated. Finally, by analysing the frequency spectra of the dynamic responses, the dominant frequencies of the acceleration signals of this monorail vehicle and bridge subsystems are revealed; in addition, the sensitive wavelengths that influence the running stability of the vehicle are found. These measurement results may provide valuable guidance for the design of the suspended monorail system and numerical model validation.
Analysis of the crashworthiness design and collision dynamics of a subway train
Authors: Xie Suchao , Du Xuanjin , Zhou Hui , Wang Da , Feng Zhejun
Published: October 2019

In this study, the crashworthiness of a subway train was assessed by establishing a finite element model for the first three carriages of the train and the track using the Hypermesh software. By utilising the *MAT_HONEYCOMB material model, a honeycomb in an anti-climbing energy-absorbing device was simulated. Moreover, the process of a subway train – travelling at a speed of 25 km/h – colliding with another identical train in a stationary and non-braking state was simulated by employing the finite element analysis software Hypermesh and LS-DYNA. The process of simulation analysis was divided into two parts: (1) analysis of the anti-climbing energy-absorbing devices under static compression for the investigation of energy absorption and (2) collision analysis of the whole train. The contributions of the proposed energy-absorbing structure – at the end of driver’s cab, the coupler and draft gears on each section – to the overall energy absorption in a train collision were calculated. Furthermore, based on the EN15227 standard, the crashworthiness of the train with respect to the survival space for occupants, train acceleration and uplift of wheels relative to the track was evaluated. The coupler of the first carriage fails in a collision at 25 km/h, and the coupler and draft gear are the main energy-absorbing devices. *MAT_HONEYCOMB was used to define the honeycomb materials in anti-climbing energy-absorbing devices and could simulate the mechanical performance thereof. The crashworthiness of the train meets the relevant standard requirements.
Combining Internal and External R&D: The Effects on Innovation Performance in Family and Nonfamily Firms
Authors: Muñoz-Bullón Fernando , Sanchez-Bueno Maria J. , De Massis Alfredo
Published: October 2019

We examine the effect of combining internal and external R&D loci on innovation performance in family firms (FF) and nonfamily firms (non-FFs). Our longitudinal analysis of 27,438 firm-year observations of Spanish manufacturing firms from 1990 to 2016 shows that FFs can better exploit the benefits of simultaneously engaging in internal and external R&D activities, leading to a positive effect on innovation performance. Moreover, the relationship between combined internal and external R&D and innovation performance in FFs is contingent upon firm economic performance. By pointing to the importance of taking into account the combination of internal and external R&D loci to foster innovation in FFs, we challenge current family business innovation research.