bluuebunny/crossref_metadata_2025 huggingface dataset:
Smart Road Surface Monitoring with Privacy Preserved Scheme for Vehicle Crowd Sensing
Authors: Aishwarya R. , Yogitha R. , Kiruthiga V.
Published: October 2019

In the Modern years many varieties of solutions has been framed for transport infrastructure such as street view application, traffic scrutiny, shortest road path navigation and route discovery. The current requirements and most significant of transport infrastructure has been lead
towards the monitoring of road surface condition. Many varieties of solutions have been generated with sensor technology in existing system. Because of this, most of the systems using sensors are getting trouble in existing method for analyzing the condition of road surface and also no awareness
or warning for the people who travel for the first time. So that initially visual observe of every surface of the road for the particular areas has been analyzed for a superior solution. Observation can be done by taking site survey, street view applications and also getting suggestion from
the highway engineers. Later every detail about the surface of the observed road will be updated with the help of crowd sensing and Global Positioning System (GPS) Vehicle based sensing technology frequently which provides the user-friendly transport services to the customer. In our work the
intermediate server called Fog Node is proposed to update the genuine data about the surface of the road condition to the cloud server by applying the Light Weight Signcryption method. The best road condition path for the sensor based cars is to be notified when the car is nearer to the Road
Side Unit (RSU) with the help of Global System for Mobile communication (GSM) and also the details will be provided for the client on demand. The implementation can be proved with our proposed method to reach the best path recover, less storage, power consumption and finding proper route discovery.
Also, it will dispense on demand data for the road based customers through mobile application with privacy preserved technology.
Development of Intrusion Detection System for Security Threats in Internet of Things Using Artificial Neural Network
Authors: Ramadevi R. , Krishnamoorthy N. R. , Marshiana D. , Kumaran Sujatha , Aarthi N.
Published: October 2019

Internet of things (IoT) is a revolutionary technology which changes our life and work. Many industry sectors such as manufacturing, transportation, utilities, health care, consumer electronics and automobiles are invested and adopted towards IoT technology. The major inconvenience
with IoT is its safety, as it is prone to attack by hackers. Detection Systems are used to detect these intrusions to protect the information and communication systems. Hence it is essential to design an intrusion detection system for security threats of IoT networks. This paper focuses, on
the development of Artificial Neural Network (ANN) based Intrusion Detection System for threat analysis in IoT network. KDD-99 data set with Denial of Service (DoS) type attack is used to train and test three different ANN models. In this research, a Feed Forward Back Propagation (FFBP) network
is used to detect the DoS attack. The process of optimization of a FFBP network involves comparison of classification accuracy during both training and testing in terms of true positive and false positive rates. For the data set considered the optimised network has achieved 100% efficiency
during both training and testing.
Gridlock Surveillance and Management System
Authors: Ishwarya M. V. , Deepa D. , Hemalatha S. , Venkata Sai Nynesh A. , Prudhvi Tej A.
Published: October 2019

In today’s world, the traffic problems are high because of more use of vehicles in the cities. So because of this, it is impossible to give away for an emergency vehicle like, (Ambulances, police vehicles, fire engine etc.). So with this project, we are going to reduce this problem,
for this, we have created a system that will monitor the traffic and also gives a way to emergency vehicles. We calculate the current traffic rate with normal traffic rate and if there is any unusual traffic and also if there is an emergency vehicle is passing through that way we change the
signal lights into green to give away for the emergency vehicles. And if there is any heavy traffic for a long time and it does not control then our system will send a message to the driver that u have to take another route. By this way we can reduce the traffic problems and emergency vehicles
will reach their destination in time.
Customer to Customer Parking Reservation System
Authors: Shaik Saif Ali , Revanth Oleti B. , Vigneshwari S.
Published: October 2019

The Online Vehicle Parking Reservation System (OVPRS) is a framework that empowers clients/drivers to save a parking spot. It additionally permits the clients/drivers to see the stopping status at individuals’ park. The venture went for taking care of such issues by planning an
electronic framework that will empower the clients/drivers to reserve a spot of an accessible parking spot at individuals’ park. The necessities for the created framework were gathered utilizing perception and meeting the client and staff part from individuals’ park. The information
from meetings was examined utilizing Microsoft Excel in order to think of the utilitarian, non-useful and framework necessities. These prerequisites were later used to plan the framework by making information stream outlines and substance relationship graphs. The planned framework was actualized
utilizing diverse advancement instruments which incorporate HTML for making interfaces, CSS for styling marry pages, JavaScript, and jQuery for dynamism in the site pages and as an info approval tool. XAMPP was utilized to assemble the database and PHP utilized as a server-side scripting dialect
to associate the UIs to the database. The framework was tried by the specialists for blunders.
Wireless Local Area Network Integration with Telephone Line
Authors: Refonaa J. , Shabu S. L. Jany , Christy  , Bogireddy Gurucharan , Ashokkumar K.
Published: October 2019

The cell phones or mobile phone are required to be in the range of cell phones tower to work properly but due to the increment of the density of buildings in cities, most of the signals are absorbed by the buildings which make the cell phone services unstable. In this article, we have
proposed an idea which combines fixed-line telephones and cellphones technology together to provide the stability of land-line phones and mobility of cell phones. Utilizing the integration of mobile phones and land-line phones user would be able to get a stable voice call service.
Low Power 4×4 Bit Multiplier Design Using DADDA, WALLACE Algorithm and Gate Diffusion Input Technology Kotha Vinil Kumar Reddy, Kondamuri Venkata Bala Manikanta Abhinav,
Authors: Rajasekar B. , Ashokkumar K.
Published: October 2019

We designed two different multipliers in order to reduce the power consumption, propagation delay and also area occupied by the multiplier. Previously there is a multiplier using DADDA algorithm that consumes high power and propagation delay also more in order to overcome that problems
we designed multiplier using WALLACE algorithm. This multiplier can overcome those drawbacks. For more efficient multiplier we used GDI (Gate Diffusion Input) technology used along with the WALLACE algorithm. This model has been designed using Tanner EDA tool.
In N Go Smart Parking System Integrated with Car Plate Recognition
Authors: Abdul Halim Sithiq Hairul Aysa Binti , Rahman Nor Azlina Abd , Limnardy Jimmy
Published: October 2019

The smart parking industry around the world continues to evolve due to the advancement of the technology and inadequate parking availability especially in city areas that congested with traffic makes the parking issues become more crucial. Most of the countries around the world trying
to improve their parking system to increase the efficiency and effectiveness of the parking mechanism. In N Go is a proposed parking system that integrated with Car Plate Recognition Technology to enhance the parking process to become more efficient. Car Plate Recognition is the key technology
of the proposed system that can supported by Mobile Application for ease of information access on parking area, issuing receipts, parking history, parking feedback, manage payment and manage personal account. In N Go system is easy to use by performing 4 easy steps to park, which the first
step is to register an account, followed by register car plate number, register a payment and finally maintain registered payment balance. The payment methods used for this system can be either using Credit or Debit card. The benefits of the system is to improve the traditional parking system
that still using either receipt or card that is inefficient and this system also can prevent long queues for the payment. Others system functionality are to blast the announcements and penalties to the users. This paper is also highlighting on the conceptual model of the In N Go system.
Significance-Based Feature Extraction for Customer Churn Prediction Data in the Telecom Sector
Authors: Eria Kamya , Marikannan Booma Poolan
Published: October 2019

The telecom industry is saturated with many service providers competing for highly rational customers. The current big data and highly technological era calls for real-time churn analysis and decision making which has also been highlighted in previous studies. However, telecom data
is highly dimensional in nature thus when this is coupled with this big data era increases the computational and processing costs. Therefore, this complexity and dimensionality of telecom data coupled with the current need for near or real-time churn analysis demands feature selection-based
models that efficiently consider the most relevant variables in explaining customer churn behaviors. This study proposes a feature extraction-based churn prediction model that concentrates on the most relevant features with significant discriminatory power for churn. The data has been reduced
on the basis of missing values and irrelevant variables. Irrelevant variables were first identified by use of Random Forest and Logistic Regression models. The findings of the study provide churn analysts with insights about the prediction errors to consider and minimize in their future churn
analyses. It also contributes to reducing computational costs incurred by churn analysts working with big data in their churn prediction and analysis.
Mammogram Mass Segmentation Using Fractals
Authors: Sivakumar V. , Shanmugavadivu P.
Published: October 2019

A new fractal-based technique for the segmentation of masses from digital mammograms is shown in this paper. This proposed fractal-based approach aims to detect and segment the masses from mammograms after successful suppression of pectoral muscle. This paper identifies and suppresses
the pectoral muscle efficiently from the input mammogram and further segments the masses precisely with the help of fractal dimensions and fractal hurst based thresholding oriented computation. This approach is proved to be efficient in getting accurate segmentation results that guarantees
the virtue of the projected technique.
A Study on the Application of Machine Learning Algorithms Using R
Authors: Vigneshwari S. , Bharathi B. , Sasikala T. , Mukkamala Srinivas
Published: October 2019

Machine learning is preferred to human interpretations during the analysis of vast scientific datasets, since the data processing time is reduced with and increased accuracy of results. Gene classification is very important in scientific analysis of bio assay datasets especially for
effective disease identification and drug discovery. The important task in gene classification process is the construction of decision tree. Real time datasets are used for this analysis and the results are in terms of 35 known siRNA gene expression factors of 64752 substances. Three types
of machine learning algorithms are used for analyzing the bio assay dataset which are CTree algorithm, Rpart algorithm and K-Means clustering algorithm. The performance analysis shows better accuracy, precision and F-measure rates of Rpart algorithm. From the result analysis, it is
inferred that the performance tree based decision making algorithms like Rpart and CTree is far better than K-Means clustering algorithm in the diagnosis of biological activities in the protein coded genes. It is also proved that the tree based algorithms are less sensitive and less specific
which leads to a development of high impact decision trees even for complex datasets like AID_651811. The analysis is done in R programming tool and the mutation factors are predicted and classified.
Prediction of Children Diabetes by Autoregressive Integrated Moving Averages Model Using Big Data and Not Only SQL
Authors: Bazila Banu A. , Priyadarshini R. K. , Thirumalaikolundusubramanian Ponniah
Published: October 2019

Enormous efforts have been made by the health care organizations to assess the frequency and occurrence of diabetes among children. The epidemiology of diabetes is estimated with different methods. However, to effectively manage and estimate the diabetes, monitoring systems like glucose
meters and Continuous Glucose Monitoring Systems (CGM) can be used. CGM is a way to determine glucose levels right through the day and night. The data obtained from such systems can be utilized effectively to manage as well to predict the diabetes. As the glucose level of the patient is monitored
throughout the day, it results in an enormous amount of data. It is difficult to analyze large datasets using SQL, therefore NoSQL is used for handling big data based prediction. One such NoSQL tool known as ArangoDB is used to process the dataset with Arango Query Language (AQL). Investigations
relevant to selection of attributes required for the model are discussed. In this paper, ARIMA model has been implemented to predict the diabetes among children. The model is evaluated in terms of moving average of glucose value of a particular person on a specific day. The results show that
ARIMA model is appropriate for predicting Time-Series data especially like data obtained by CGM systems.
Autonomous Shopping Trolley Using Color Navigation
Authors: Abdullah Mahmood , Selvaperumal Sathish Kumar , Bahrin Syed Mohd , Seeralan Arun
Published: October 2019

The projected development of “Autonomous Shopping Trolley using Color Navigation” aims to provide customers with a new, efficient and effective means of shopping, which is based on the criteria of self-navigation and self-mobility. Line following methodology is a proven
and most commonly adopted technology today with the use being spread over several applications throughout the industries. To attain the autonomous steering for the purposes of aiding people in free and easy movement.
A Comparative Study on Credit Card Default Risk Predictive Model
Authors: Leong Ooi Jien , Jayabalan Manoj
Published: October 2019

The risk analysis of credit card defaulters is a critical procedure in the banking sector to classify the card applicants. Banks perform credit score check to make decisions on applications and to set credit limit accordingly. With the increase in the amount of data and advances in
data analytics, the approval process can now be automated for quicker processing of applications. This study aims to provide solutions to improve the risk management strategy among financial institutions using predictive analytics. A real-world dataset obtained from a bank in Taiwan were used
to perform the analysis in this project. Four data mining algorithms including Decision Tree, Logistic Regression, Random Forest and Neural Network were constructed with the cleaned dataset. Results revealed that Neural Network is the best performing model with an 82% predictive accuracy of
credit card defaulters.
Smart Meter Data Analysis Using Big Data Tools
Authors: Sulaiman S. M. , Aruna Jeyanthy P. , Devaraj D.
Published: October 2019

In recent years, the problem of electrical load forecasting gained attention due to the arrival of new measurement technologies that produce electrical energy consumption data at very short intervals of time. Such short term measurements become voluminous in very short time. The availability
of big electrical consumption data allows machine learning techniques to be employed to analyze consumption behavior of every consumer on a greater detail. Predicting the consumption of a residential customer is crucial at this point of time because tailor-made consumer-specific tariffs will
play a vital role in load balancing process of Utilities. This paper analyzes the electrical consumption of a single residential customer measured using a smart meter that is capable of measuring electrical consumption at circuit level. The issues and challenges in collecting the data and
pre-processing required for making them suitable for data analytics are discussed in detail. A comparison of the performance of different machine learning algorithms implemented using Python’s Scikit-learn module gives an insight on the consumption pattern.
Reliability score evaluation of continuous assessment tests: A longitudinal study
Authors: López de Vergara Jorge E , Olmos Ricardo
Published: October 2019

In this paper, a longitudinal study is presented about the score reliability in continuous assessment tests of the subject Network Architecture II, which is taught in the Telecommunication Technologies and Services Engineering degree, offered at Universidad Autónoma de Madrid, Spain. It is important to evaluate if scores in tests are reliable, because it shows if the phenomenon under study is measured with precision and low error, which are necessary conditions for a fair assessment. Thus, an analysis is provided about the scores obtained in the 28 continuous assessment tests taken across seven years. Correlation, corrected correlation and Cronbach’s α are used as psychometric indicators. Results show that, in general, there is a high correlation in the students’ scores among the different assessment tests every year, which let us confirm that they have been correctly set out. Additionally, the results are compared among different years, showing that they are similar in the different cohorts. However, variations have also been observed over the years, with tests with poor correlation. Finally, based on the analysed data, a novel method is proposed to early detect problems in the tests’ evaluation before the course ends, by correlating their scores in pairs. A low correlation between two tests in the same year, empirically below 0.2, would imply issues in the evaluation.
Personalizing the Customization Experience: A Matching Theory of Mass Customization Interfaces and Cultural Information Processing
Authors: de Bellis Emanuel , Hildebrand Christian , Ito Kenichi , Herrmann Andreas , Schmitt Bernd
Published: October 2019

Mass customization interfaces typically guide consumers through the configuration process in a sequential manner, focusing on one product attribute after the other. What if this standardized customization experience were personalized for consumers on the basis of how they process information? A series of large-scale field and experimental studies, conducted with Western and Eastern consumers, shows that matching the interface to consumers’ culture-specific processing style enhances the effectiveness of mass customization. Specifically, presenting the same information isolated (by attribute) to Western consumers but contextualized (by alternative) to Eastern consumers increases satisfaction with and likelihood of purchasing the configured product, along with the amount of money spent on the product. These positive consumer responses emerge because of an increase in “interface fluency”—consumers’ subjective experience of ease when using the interface. The authors advise firms to personalize the customization experience by employing processing-congruent interfaces across consumer markets.
Altered Visual and Proprioceptive Spatial Perception in Individuals with Parkinson’s Disease
Authors: José Luvizutto Gustavo , Souza Silva Brito Thanielle , de Moura Neto Eduardo , Aparecida Pascucci Sande de Souza Luciane
Published: October 2019

Difficulties in the integration of visual, vestibular, and somatosensory information in individuals with Parkinson’s disease (PD) may alter perception of verticality. Accordingly, in this cross-sectional study, we analyzed PD patients’ ( n = 13) subjective visual vertical (SVV) and subjective haptic vertical (SHV) perceptions and compared them to those of healthy controls ( n = 14). We compared SVV and SHV findings among participants with PD, healthy controls, and cutoff points of normality based on prior research literature, using the parametric nonpaired t test (at p < .05) and Cohen’s d (at d > 0.8) to determine clinical relevance. We analyzed SVV with the bucket test and SHV with the rod rotations task in clockwise and counterclockwise directions. We calculated Pearson correlations to analyze the association between verticality tests and the most clinically affected body side. We calculated both the percentage of A-effect (expression of body tilt underestimation to the midline) and E-effect (expression of body tilt overestimation in the upright position). Individuals with PD showed greater variability in right SHV supination compared to the healthy control participants ( p = .002). There was greater clinical relevance in right (as opposed to left) SVV ( d = 0.83), right (as opposed to left) SHV pronation ( d = 0.91), and left (as opposed to right) SHV pronation ( d = 0.88). We observed a higher proportion of E-effect in individuals with PD. A significantly higher proportion of patients with PD, compared to patients in past literature, had right SHV pronation ( p = .001), left SHV pronation ( p = .023), right SHV supination ( p = .001), left SHV supination ( p = .046), and left SHV pronation ( p = .046). Thus, subjective visual and proprioceptive perception of verticality is altered in patients with PD, compared to individuals without PD.
Politics of neutrality: Urban knowledge practices and everyday formalisation in Karachi’s waterscape
Authors: Farooqui Usmaan
Published: October 2019

Formalisation in cities is commonly associated with top-down processes like slum demolition, land titling and economic regulation. By contrast, this article explores processes of everyday formalisation by considering how locally grounded understandings of formality and informality are reproduced. It thus theorises everyday formalisation as a process distinct from state-led formalisation in terms of both the scale (local) and mechanisms (everyday) through which formal/informal dichotomisation occurs. To explore the effects of such everyday formalisation, this article draws on a case study of water access in a low-income settlement of Karachi, Pakistan. Turning attention to everyday practices of water access in the settlement, this article highlights how residents and water board officials understand and enact distinctions between formality and informality through daily knowledge practices and meanings of neutrality. By focusing on everyday formalisation, this article makes two wider contributions to urban theory. First, it demonstrates that urban informality gives rise to diverse lived experiences, not all of which may be characterised as examples of subaltern agency. Secondly, it demonstrates that urban learning and local knowledge generation can be conceptualised not only as tools for urban ‘navigation’, but as distinctive practices that reproduce urban space according to hegemonic categories like formal and informal.
Qualitative Assessment of Washington State Medicaid Health Plan Readiness to Implement Systems-Based Approaches to Colorectal Cancer Screening
Authors: Witwer Elizabeth , Baldwin Laura-Mae , Cole Allison
Published: October 2019

Implementation of population-based colorectal cancer screening programs by Medicaid health plans could address colorectal cancer screening disparities. Our objective is to identify facilitators and barriers to implementation of a population-based colorectal cancer screening program by Washington State Medicaid health plans. We conducted semi-structured interviews with leadership from 2 statewide and 3 national Medicaid plans. We organized the interview questions around the Consolidated Framework for Implementation Research (CFIR). We analyzed interview transcripts, guided by directed content analysis, and identified facilitators and barriers to Medicaid health plan implementation of population-based colorectal cancer screening programs. Robust health plan (inner setting) quality improvement infrastructures were facilitators. Lack of statewide Medicaid policy incentives (external setting) to increase colorectal cancer screening were barriers to potential implementation. Efforts to address identified barriers through local and national policies and statewide data sharing efforts may support Medicaid health plan implementation of population-based colorectal cancer screening programs.
Current and future test reference years at a 5 km resolution
Authors: Liu C , Chung W , Cecinati F , Natarajan S , Coley D
Published: October 2019

Frequently, the computer modelling of the natural and human-made environment requires localised weather files. Traditionally, the weather files are based on the observed weather at a small number of locations (14 for the UK). Unfortunately, both the climate and the weather are known to be highly variable across the landscape, so the small number of locations has the potential to cause large errors. With respect to buildings, this results in incorrect estimates of the annual energy use (sometimes by a factor of 2), or of overheating risk. Here we use a validated weather generator running on a 5 × 5 km grid to create probabilistic test reference years (pTRYs) for the UK at 11,326 locations. We then investigate the spatial variability of these pTRYs and of annual energy estimates and temperatures in buildings generated by them, both now and in 2080. Further pTRYs targeted at understanding the impact of minimum and maximum temperatures are proposed and produced at the same locations. Finally, we place these pTRYs, which represent the first set of reference weather files at this spatial resolution in the world and that include the urban heat island effect, into a publicly accessible database so researchers and industry can access them.

Practical applications: Insufficiently localised weather data for building simulations have limited the accuracy of previous estimations of energy use and overheating risk in buildings. This work produces localised probabilistic test reference years (pTRYs) across the whole UK for now and future climates. In addition, a new pTRY method has been proposed in order to overcome an unexpected shortcoming of traditional pTRYs in representing typical maximum and minimum temperatures. These current and future weather data will be of interest to various disciplines including those interested in low carbon design, renewable energy and climate resilience.
The Diverging Effects of Need Fulfillment Obtained from Within and Outside of a Romantic Relationship
Authors: Machia Laura V. , Proulx Morgan L.
Published: October 2019

People have diverse psychological needs that they seek to have fulfilled to maximize their well-being. Romantic relationships are the primary source individuals use for need fulfillment, but fulfillment can come from other sources as well—friends, family, strangers, vocation, and recreation. Whereas having a bevy of available sources puts individuals at an advantage in terms of ensuring their needs are met, which source they utilize may ironically decrease the quality of their valued romantic relationship. Across three studies (total N = 5,169) with diverse methodologies (i.e., nationally representative, cross-sectional, longitudinal), we found that when people achieve psychological need fulfillment from sources other than their romantic partner, they view their relationship less positively (Study 1), perceive greater quality of alternatives to their romantic relationship, and think more about ending the relationship (Studies 2 and 3). Demonstrating robustness, these associations hold independent of the amount of fulfillment provided by the romantic partner.
Vasodilator effects of sulforaphane in cerebral circulation: A critical role of endogenously produced hydrogen sulfide and arteriolar smooth muscle KATP and BK channels in the brain
Authors: Parfenova Helena , Liu Jianxiong , Hoover Daniel T , Fedinec Alex L
Published: October 2019

We investigated the effects of sulforaphane (SFN), an isothiocyanate from cruciferous vegetables, in the regulation of cerebral blood flow using cranial windows in newborn pigs. SFN administered topically (10 µM–1 mM) or systemically (0.4 mg/kg ip) caused immediate and sustained dilation of pial arterioles concomitantly with elevated H2S in periarachnoid cortical cerebrospinal fluid. H2S is a potent vasodilator of cerebral arterioles. SFN is not a H2S donor but it acts via stimulating H2S generation in the brain catalyzed by cystathionine γ-lyase (CSE) and cystathionine β-synthase (CBS). CSE/CBS inhibitors propargylglycine, β-cyano-L-alanine, and aminooxyacetic acid blocked brain H2S generation and cerebral vasodilation caused by SFN. The SFN-elicited vasodilation requires activation of potassium channels in cerebral arterioles. The inhibitors of KATP and BK channels glibenclamide, paxilline, and iberiotoxin blocked the vasodilator effects of topical and systemic SFN, supporting the concept that H2S is the mediator of the vasodilator properties of SFN in cerebral circulation. Overall, we provide first evidence that SFN is a brain permeable compound that increases cerebral blood flow via a non-genomic mechanism that is mediated via activation of CSE/CBS-catalyzed H2S formation in neurovascular cells followed by H2S-induced activation of KATP and BK channels in arteriolar smooth muscle.
Delayed recanalization in acute ischemic stroke patients: Late is better than never?
Authors: Pang Jinwei , Zhang John H , Jiang Yong
Published: October 2019

Successful recanalization of the occluded vessel as early as possible has been widely accepted as the key principle of acute ischemic stroke (AIS) treatment. Unfortunately, for many years, the vast majority of AIS patients were prevented from receiving effective recanalization therapy because of a narrow therapeutic window. Recently, a series of inspiring clinical trials have indicated that more patients may benefit from delayed recanalization during an expanded therapeutic window, even up to 24 h after symptom onset. However, could potentially salvageable brain tissue (penumbra) in patients who do not receive medication within 24 h still possible to be saved?
Perceived Subtle Gender Bias Index: Development and Validation for Use in Academia
Authors: Tran Nellie , Hayes Rashelle B. , Ho Ivy K. , Crawford Sybil L. , Chen Julie , Ockene Judith K. , Bond Meg , Rayman Paula , Dean Brita , Smith Sable , Thorndyke Luanne , Frankin Patricia , Plummer Deborah , Pbert Lori
Published: October 2019

In this article, we present the development and validation of the Perceived Subtle Gender Bias Index. Given the inherent difficulty in identifying and measuring the perceptions of subtle gender biases, this index provides researchers and interventionists with a tool that does not require participants to identify/label an event as a gender bias incident. We used a mixed method and constructivist approach that prioritized and privileged the voices and experiences of women in science, technology, engineering, and mathematics (STEM). The current article describes two studies: (1) index development and (2) index refinement and validation, using a national survey of women academics ( N = 882). Findings support a four-subscale structure, including perceived gender inequity, collegiality, mentorship, and institutional support. Methods and analyses support face, convergent, discriminant, and predictive validity for the use of the index among academic faculty women. Additional online materials for this article are available on PWQ’s website at http://journals.sagepub.com/doi/suppl/10.1177/0361684319877199
Damage sequence of honeycomb sandwich panels under bending loading: Experimental and numerical investigation
Authors: Medina SA , Meza JM , Kawashita Luiz F
Published: October 2019

This work presents a numerical modelling study on the bending response and failure mechanisms of aramid skin/aluminium honeycomb core sandwich panels under quasi-static bending loads. These composite sandwich panels are widely used in aerospace and automotive industries, in spite of the limitations for their use in complex structures, such as the extensive experimental testing needed at the component and full-size structural levels, which are expensive and time-consuming. The aim of this study was to capture the initiation of different failure mechanisms and their multiple interactions, which are known to strongly influence the observed microscopic behaviour of the material. Furthermore, a series of detailed Finite Element models were built and analysed in an attempt to replicate the complex damage mechanisms observed experimentally. The results show good correlation between numerical models and experimental results, both in terms of the global load–displacement behaviour and the observed damage mechanisms, including skin in-plane shear and compression damage, intralaminar fracture, delamination within the skin and core crushing. No debonding between the core and the skins was evidenced. It is proposed that this modelling approach can become a feasible alternative to component-level experimental testing when designing complex sandwich structures.
Combination of fluoride and endosulfan induced teratogenicity and developmental toxicity in Swiss albino mice exposed during organogenesis
Authors: Sharma Anju , John PJ , Bhatnagar Pradeep
Published: October 2019

The present investigation was conducted to evaluate the teratogenic and developmental toxicity of fluoride and endosulfan alone and in combination in pregnant Swiss albino mice exposed during the organogenetic period (5–14 days) of gestation. Fluoride (25.1 mg/kg body weight in water) and endosulfan (1.8 mg/kg bw by oral intubation) when administered alone and in combination (fluoride 25.1 mg/kg bw + endosulfan 1.8 mg/kg bw) to pregnant mice caused significant teratogenic effects in developing fetuses. There was no maternal mortality but significant decreases in maternal weight gain and numbers of live fetuses and significant increases in numbers of fetal resorption were recorded in the treated groups. The fetal body weight and litter size also decreased significantly in all treated groups. No external malformations were observed in any of the fetuses. The percent of visceral and skeletal anomalies increased in the fetuses of all treated groups. The fetal malformations observed were internal hydrocephaly, microphthalmia, anophthalmia, pulmonary edema, subcutaneous edema, reduced ossification of skull bones, widened cranial sutures, rib anomalies (short, wavy, partially ossified, or absent ribs), and reduced ossification of phalanges. The occurrence of visceral and skeletal malformations was more severe in the combination group, suggesting additive interaction of fluoride and endosulfan in inducing developmental toxicity in Swiss albino mice.
Transgender Intimate Partner Violence and Help-Seeking Patterns
Authors: Kurdyla Victoria , Messinger Adam M. , Ramirez Milka
Published: October 2019

Intimate partner violence (IPV) against transgender individuals is highly prevalent and impactful, and thus research is needed to examine the extent to which survivors are able to reach needed assistance and safety. To our knowledge, no U.S.-based quantitative studies have explored transgender utilization patterns and perceptions regarding a broad range of help-giving resources (HGRs). The present article fills this gap in the literature by exploring help-seeking attitudes and behaviors of a convenience sample of 92 transgender adults and 325 cisgender sexual minority adults in the United States. Results from an online questionnaire indicate that, among the subsample experiencing IPV ( n = 187), help-seeking rates were significantly higher among transgender survivors (84.1%) than cisgender sexual minority survivors (67.1%). In addition, transgender survivors most commonly sought help from friends (76.7%), followed by mental health care providers (39.5%) and family (30.2%), whereas formal HGRs such as police, IPV telephone hotlines, and survivor shelters had low utilization rates. Among all transgender participants, IPV survivors were significantly less likely than nonsurvivors to perceive family, medical doctors, and survivor hotlines as helpful HGRs for other survivors in general. Finally, transgender survivors were significantly less likely than nonsurvivors to self-report a willingness to disclose any future IPV to family. Although replication with larger, probability samples is needed, these findings suggest that friends often represent the primary line of defense for transgender survivors seeking help, and thus bystander intervention trainings and education should be adapted to address not just cisgender but also transgender IPV. Furthermore, because most formal HGR types appear to be underutilized and perceived more negatively by transgender survivors, renewed efforts are needed to tailor services, service advertising, and provider trainings to the needs of transgender communities. Directions for future research are reviewed.
Field measurement and model prediction of rail corrugation
Authors: Chen GX , Zhang S , Wu BW , Zhao XN , Wen ZF , Ouyang H , Zhu MH
Published: October 2019

In a field test, three corrugation profiles of rails and their corresponding vibrations were measured, and the wavelengths and frequencies of rail corrugations were obtained. In the model prediction, finite-element models of the self-excited vibrations corresponding to three different wheelset–track systems were established. The corrugation frequencies of these models were predicted, and a comparison between the measured and the predicted corrugation frequencies showed that they are in good agreement. It can be concluded that the self-excited vibration of a wheelset–track system can cause rail corrugation. A benchmark condition for the validation of rail corrugation models is proposed.
An integrated methodology for the prognosis of ballast degradation in railway turnouts
Authors: Asadzadeh Seyed Mohammad , Galeazzi Roberto
Published: October 2019

This study proposes an integrated methodology for modelling and predicting ballast degradation in turnouts by exploiting loaded track geometry data. The rate of increase in track irregularities with respect to the cumulative loading of the track is the index of ballast degradation to be predicted. The methodology combines the fractal analysis method with probabilistic modeling and Bayesian inference to design a prognostic tool that forecasts the expected ballast degradation rate over a period of three months. The foundation of the proposed method is a universal degradation model for the ballast in turnouts, which fuses technological, operational, and environmental information to prognose the rate of ballast deterioration. The methodology has been verified on 15 different turnouts of the Danish railway infrastructure.
Implementation and dissemination of an African American popular opinion model to improve lupus awareness: an academic–community partnership
Authors: Phillip C R , Mancera-Cuevas K , Leatherwood C , Chmiel J S , Erickson D L , Freeman E , Granville G , Dollear M , Walker K , McNeil R , Correia C , Canessa P , Ramsey-Goldman R , Feldman C H
Published: October 2019

Objective

Lupus is a chronic, autoimmune disease that disproportionately affects African Americans. We adapted the Centers for Disease Control and Prevention’s Popular Opinion Leader model to implement an intervention tailored for African American individuals that leverages an academic-community partnership and community-based social networks to disseminate culturally appropriate lupus education.

Methods

Academic rheumatologists, social scientists, and researchers in Boston, MA and Chicago, IL partnered with local lupus support groups, community organizations, and churches in neighborhoods with higher proportions of African Americans to develop curriculum and recruit community leaders with and without lupus (Popular Opinion Leaders; POLs). POLs attended four training sessions focused on lupus education, strategies to educate others, and a review of research methods. POLs disseminated information through their social networks and recorded their impact, which was mapped using a geographic information system framework.

Results

We trained 18 POLs in greater Boston and 19 in greater Chicago: 97% were African American, 97% were female; and the mean age was 57 years. Fifty-nine percent of Boston POLs and 68% of Chicago POLs had lupus. POLs at both sites engaged members of their social networks and communities in conversations about lupus, health disparities, and the importance of care. Boston POLs documented 97 encounters with 547 community members reached. Chicago POLs documented 124 encounters with 4083 community members reached.

Conclusions

An adapted, community-based POL model can be used to disseminate lupus education and increase awareness in African American communities. Further research is needed to determine the degree to which this may begin to reduce disparities in access to care and outcomes.
Relationship of Postoperative Achilles Tendon Elongation With Plantarflexion Strength Following Surgical Repair
Authors: Hürmeydan Önder Murat , Demirel Mehmet , Valiyev Natig , Sahinkaya Turker , Kılıçoğlu Önder İsmet
Published: October 2019

Background:

Little data exist regarding the adverse effects of Achilles tendon (AT) elongation after rupture repair on plantarflexion strength. This study aimed to investigate the effect of AT elongation measured using AT resting angle (ATRA) on the plantarflexion strength in patients with surgically treated acute AT rupture.

Methods:

A retrospective chart review was performed on 40 patients (15 female and 25 female) who underwent open operative repair due to an acute AT rupture. At the final follow-up, AT elongation was assessed using ATRA. Plantarflexion strength (peak torques and angle-specific torques) was measured using an isokinetic dynamometer. All variables were obtained from the operated and unoperated contralateral ankles of the patients.

Results:

The mean ATRA was greater in the operated ankles (mean, 57 degrees; range, 39-71 degrees) compared with the unoperated ones (mean, 52 degrees; range, 36-66 degrees; P = .009). Except the plantarflexion torque at 20 degrees of plantarflexion ( P = .246), all the other angle-specific torques were lower in the operated ankles ( P < .05). Peak flexion torque at 30 degrees/s was lower in the operated ankle ( P = .002). A negative correlation was found between operated/unoperated (O/N) ATRA and O/N plantarflexion torque ratios at 0 degrees ( r = −0.404; P = .01), 10 degrees ( r = −0.399; P= .011), and 20 degrees ( r = −0.387; P = .014).

Conclusion:

Postoperative AT elongation measured using ATRA may have a deleterious effect on the plantarflexion strength in patients with surgically treated acute AT rupture.

Level of Evidence:

Level IV, case series.
Treatment Discontinuation or Interruption in Pulmonary Arterial Hypertension
Authors: Narechania Shraddha , Torbic Heather , Tonelli Adriano R.
Published: October 2019

Pulmonary arterial hypertension (PAH) is a progressive disease, which can be potentially fatal. The management of a complex disease like PAH requires a multidisciplinary approach from a team consisting of physicians, nurses, social workers, and pharmacists. Adherence to PAH-specific therapy is one of the key factors in the management of this disease. Poor adherence to treatment is a common problem in PAH as it is in many chronic diseases. Management of medication interruptions is a challenge in patients with PAH that can lead to negative consequences. However, for most PAH-specific drugs, there are no clear guidelines on how to manage temporary or abrupt medication discontinuations. In this review, we summarized the available literature and provide suggestions on how to manage interruptions of PAH-specific therapies.
The core features and outcomes of a specialised camp programme for children with life-limiting conditions and their families: A qualitative multi-perspective approach
Authors: Mulligan Shane , Guerin Suzanne , McKiernan Aidan , Brown Anna , Hartnett Michelle , Gray Dee , Kiernan Gemma
Published: October 2019

Previous research has reported that the families of children with enduring and life-limiting health conditions are at risk of negative psychosocial effects. Adjunct to medical interventions, specialist camp programmes have been developed to promote familial adjustment. However, limited research has been carried out in this area. The aim of this study was to describe the core features and outcomes of a specialised camp programme for children with life-limiting conditions (LLC) and their family. Semi-structured interviews were conducted with four professionals, three volunteers involved in facilitating the programme and two mothers representing families that attended the programme. Multiple perspectives were sought to gain a detailed understanding of the programme and outcomes. Data were analysed through an inductive thematic approach. There was considerable overlap among participant groups on the core features and outcomes of the programme. Thematically, core features are described in terms of familial togetherness, peer interaction, safety and positive experiences. Noted outcomes include lasting memories, continued peer relations for parents and siblings and enhancement of relationships between family members and professionals. Findings suggest that specialised camp programmes may provide families of children with LLC with positive experiences that support adjustment, although further research is required.
Investigation on sticking for drill rod based on finite element analysis and fuzzy proportion–integration–differentiation
Authors: Li Dongmin , Zhang Yanqiang , Li Jia , Xia Shangfei
Published: October 2019

In order to investigate the essence of sticking for drill rod served in underground coal mine, a comprehensive solution combing finite element analysis with fuzzy proportion–integration–differentiation on the drilling rig is proposed. First, the structure and working mechanism of the drilling rig are studied; then, the static and modal analyses on the drill rod with finite element analysis are performed according to the actual working conditions of the drilling rig. Furthermore, a load-sensing hydraulic power system of the drilling rig is built, and the co-simulation with AMESim and Simulink is performed on the response, overshoot, and vibration, when the hydraulic power is controlled with the conventional control method, proportion–integration–differentiation control method, and fuzzy proportion–integration–differentiation method, respectively. The simulation results show that the strength, stiffness, and vibration frequency of the drilling rig model meet the working requirements, and no resonance occurs; furthermore, the load-sensing hydraulic power system with fuzzy proportion–integration–differentiation method is preferable than the other two control methods.