bluuebunny/crossref_metadata_2025_split huggingface dataset:
Length of stay in long-term care facilities: a comparison of residents in six European countries. Results of the PACE cross-sectional study
Authors: Collingridge Moore Danni , Payne Sheila , Keegan Thomas , Van den Block Lieve , Deliens Luc , Gambassi Giovanni , Heikkila Rauha , Kijowska Viola , Pasman H Roeline , Pivodic Lara , Froggatt Katherine 
Published: March 2020

ObjectivesThis paper aims to investigate resident, facility and country characteristics associated with length of stay in long-term care facilities (LTCFs) across six European countries.SettingData from a cross-sectional study of deceased residents, conducted in LTCFs in Belgium, England, Finland, Italy, the Netherlands and Poland.ParticipantsAll residents aged 65 years and older at admission who died in a 3-month period residing in a proportional random sample of LTCFs were included.Primary and secondary outcome measuresThe primary outcome was length of stay in days, calculated from date of admission and date of death. Resident, facility and country characteristics were included in a proportional hazards model.ResultsThe proportion of deaths within 1 year of admission was 42% (range 32%–63%). Older age at admission (HR 1.04, 95% CI 1.03 to 1.06), being married/in a civil partnership at time of death (HR 1.47, 95% CI 1.13 to 1.89), having cancer at time of death (HR 1.60, 95% CI 1.22 to 2.10) and admission from a hospital (HR 1.84, 95% CI 1.43 to 2.37) or another LTCF (HR 1.81, 95% CI 1.37 to 2.40) were associated with shorter lengths of stay across all countries. Being female (HR 0.72, 95% CI 0.57 to 0.90) was associated with longer lengths of stay.ConclusionsLength of stay varied significantly between countries. Factors prior to LTCF admission, in particular the availability of resources that allow an older adult to remain living in the community, appear to influence length of stay. Further research is needed to explore the availability of long-term care in the community prior to admission and its influence on the trajectories of LTCF residents in Europe.
Quality of life in long-term survivors of advanced melanoma treated with checkpoint inhibitors
Authors: Mamoor Maha , Postow Michael A , Lavery Jessica A , Baxi Shrujal S , Khan Niloufer , Mao Jun J , Rogak Lauren J , Sidlow Robert , Thom Bridgette , Wolchok Jedd A , Korenstein Deborah 
Published: March 2020

BackgroundImmune checkpoint inhibitors (CIs) have revolutionized treatment of advanced melanoma, leading to an emerging population of long-term survivors. Survivors’ quality of life (QOL) and symptom burden are poorly understood. We set out to evaluate symptom burden and QOL in patients with advanced melanoma alive more than 1 year after initiating CI therapy.MethodsCross-sectional surveys, accompanied by chart review of patients with advanced melanoma treated with CIs at Memorial Sloan Kettering Cancer Center, completed therapy, and were alive >1 year after treatment initiation. Surveys were administered between February and August 2018. Surveys included: European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-Core 30, EuroQOL, items from Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events and Fatigue Severity Scale.ResultsWe included 90 patients. The most common CI regimens were ipilimumab plus nivolumab (53%) and pembrolizumab (41%); most patients (71%) were not treated in clinical trials. Median time from CI therapy initiation was 40 months and from last dose was 28 months. Fatigue was reported by 28%, with higher fatigue scores in women than men; 12% reported difficulty sleeping. Aching joints (17%) and muscles (12%) were fairly common. Level of functioning was generally high. Overall QOL was excellent though 40% reported ‘some or moderate’ problems with anxiety/depression and 31% with pain/discomfort.ConclusionsAfter CI therapy, long-surviving advanced melanoma patients commonly report fatigue but otherwise have moderate symptom burden and good QOL. Ensuring appropriate symptom management will optimize clinical outcomes for these patients.
Thermal and thermoelectric conductivity of Einstein-DBI system
Authors: Pal Shesansu Sekhar 
Published: March 2020

AbstractWe calculate the thermoelectric and thermal conductivity of Einstein-DBI system without the translational symmetry. We show that strictly, the longitudinal component of the thermal conductivity in the vanishing dissipation limit, $$k^2\rightarrow 0$$k2→0, is determined only by the metric components evaluated at the horizon of the black hole in the same limit. The temperature dependence of the transport quantities are obtained for $$AdS_4$$AdS4 and $$AdS_2\times R^2$$AdS2×R2 solutions. The Lorentz ratio and Hall–Lorentz ratio are found to be independent of temperature for $$AdS_4$$AdS4 solution in the low temperature limit, whereas the above mentioned quantities are independent of temperature for $$AdS_2\times R^2$$AdS2×R2 solution.
Stratigraphic palynology of the Middle–Late Triassic successions of the Central North Sea
Authors: Burgess Roger , Jolley David , Hartley Adrian 
Published: March 2020

Historically, the continental Triassic successions of the Central North Sea have proven difficult to correlate, in part due to the poor palynomorph recovery associated with these sedimentary rocks. The existing framework for correlation is lithostratigraphic and, whilst this has proven effective in United Kingdom Continental Shelf (UKCS) Quad 30 where the mudstone members are well defined, elsewhere in the basin it is more problematic with confident identification of stratigraphic units becoming more difficult. Samples from 32 wells within UKCS Quads 22, 29 and 30, and Norwegian Quads 7, 15 and 16 underwent palynological analysis in which a processing method was utilized that was designed to concentrate palynomorph recovery from Triassic strata.
The results of this analysis allowed the proposal of a new zonal scheme consisting of eight biozones. These biozones can then be used to correlate the Triassic successions of the Central North Sea (CNS), helping to provide both clarity and age constraint on previously disputed stratigraphic units, particularly the J-members of the Skagerrak Formation. Within the correlation framework outlined here, the Julius Mudstone Member is shown to be a productive horizon for palynomorph recovery, representing a widespread swamp environment. Here, its lateral extent is defined which is an important consideration when correlating the Triassic stratigraphy of the CNS given that this member can compartmentalize potential reservoirs contained within these successions. The stratigraphic palynology outlined here also allows clarity on the J-member equivalence of some of the informal units previously described within Triassic successions of the CNS, including the Marnock Shale and Heron Shale.
One Size Does Not Fit All: Marked Heterogeneity in Incidence of and Survival from Gastric Cancer among Asian American Subgroups
Authors: Huang Robert J. , Sharp Nora , Talamoa Ruth O. , Ji Hanlee P. , Hwang Joo Ha , Palaniappan Latha P. 
Published: March 2020

AbstractBackground:Asian Americans are at higher risk for noncardia gastric cancers (NCGC) relative to non-Hispanic Whites (NHW). Asian Americans are genetically, linguistically, and culturally heterogeneous, yet have mostly been treated as a single population in prior studies. This aggregation may obscure important subgroup-specific cancer patterns.Methods:We utilized data from 13 regional United States cancer registries from 1990 to 2014 to determine secular trends in incidence and survivorship from NCGC. Data were analyzed for NHWs and the six largest Asian American subgroups: Chinese, Japanese, Filipino, Korean, Vietnamese, and South Asian (Indian/Pakistani).Results:There exists substantial heterogeneity in NCGC incidence between Asian subgroups, with Koreans (48.6 per 100,000 person-years) having seven-fold higher age-adjusted incidence than South Asians (7.4 per 100,000 person-years). Asians had generally earlier stages of diagnosis and higher rates of surgical resection compared with NHWs. All Asian subgroups also demonstrated higher 5-year observed survival compared with NHWs, with Koreans (41.3%) and South Asians (42.8%) having survival double that of NHWs (20.1%, P &lt; 0.001). In multivariable regression, differences in stage of diagnosis and rates of resection partially explained the difference in survivorship between Asian subgroups.Conclusions:We find substantial differences in incidence, staging, histology, treatment, and survivorship from NCGC between Asian subgroups, data which challenge our traditional perceptions about gastric cancer in Asians. Both biological heterogeneity and cultural/environmental differences may underlie these findings.Impact:These data are relevant to the national discourse regarding the appropriate role of gastric cancer screening, and identifies high-risk racial/ethnic subgroups who many benefit from customized risk attenuation programs.
A Simple Equation to Estimate Urinary Flow Rate Using Urine Creatinine
Authors: Webster Luke , Larive Brett , Gassman Jennifer , Bullen Alexander , Weisbord Steven D. , Palevsky Paul M. , Fried Linda F. , Raphael Kalani , Isakova Tamara , Ix Joachim H. 
Published: March 2020

<b><i>Background:</i></b> Accurate assessment of urine flow remains challenging in both inpatient and outpatient settings. We hypothesized we could derive an equation that would accurately estimate urine flow rate (eV) through derivation from other existing equations commonly used in nephrology clinical practice. <b><i>Methods:</i></b> The eV equation was derived using the Cockcroft-Gault and the measured creatinine clearance (CrCl = U<sub>Cr</sub>V/P<sub>Cr</sub>) equations. Within the African American Study of Kidney Disease and Hypertension (AASK; <i>n</i> = 570) and COMBINE (<i>n</i> = 133) clinical trials, we identified participants with concordant estimated and measured creatinine excretion rates to define a subset with highly accurate 24-h urine collections, to assure a reliable gold standard. We then compared eV to measured 24-h urine flow rates in these trials. <b><i>Results:</i></b> In AASK, we found a high correlation between eV and measured urine flow rate (V; <i>r</i> = 0.91, <i>p</i> &#x3c; 0.001); however, Bland-Altman plots showed that eV was 9.5 mL/h lower than V, on average. Thus, we added a correction factor to the eV equation and externally validated the new equation in COMBINE. eV and V were again highly correlated (<i>r</i> = 0.91, <i>p</i> &#x3c; 0.001), and bias was improved (mean difference 5.3 mL/h). Overall, 80% of individuals had eV that was within 20% of V. <b><i>Conclusions:</i></b> A simple equation using urine creatinine, demographics, and body weight can accurately predict urine flow rate and may have clinical utility in situations where it is difficult to accurately measure the urine flow rate.
Towards machine learning-based self-tuning of Hadoop-Spark system
Authors: Armanur Rahman Md. , Hossen Abid , Hossen J. , C Venkataseshaiah , Bhuvaneswari Thangavel , Sultana Aziza 
Published: March 2020

Apache Spark is an open source distributed platform which uses the concept of distributed memory for processing big data. Spark has more than 180 predominant configuration parameter. Configuration settings directly control the efficiency of Apache spark while processing big data, to get the best outcome yet a challenging task as it has many configuration parameters. Currently, these predominant parameters are tuned manually by trial and error. To overcome this manual tuning problem in this paper proposed and developed a self-tuning approach using machine learning. This approach can tune the parameter value when it’s required. The approach was implemented on Dell server and experiment was done on five different sizes of the dataset and parameter. A comparison is provided to highlight the experimented result of the proposed approach with default Spark configuration system. The results demonstrate that the execution is speeded-up by about 33% (on an average) compared to the default configuration.
A novel three tier internet of things health monitoring system
Authors: N, Deepika , Anand M. , Jerald F. 
Published: March 2020

<p>Internet of things is a technology where day to day devices, processing, and communication become smarter, intelligent and informative respectively. Health monitoring system is one the most important applications enabled by IOT. IOT health monitoring system comprises of sensors, network and a remote server (cloud). It provides multi-dimensional health monitoring and also suggests treatments. In this paper we have proposed a novel three tier health monitoring system , which stores and process the huge amount of sensor data outside the device using a technology called cloud computing. When the observed clinical sensor value exceeds the threshold clinical value, the system sends alert message to the doctor and caretakers. The history of data and observed data is stored in the cloud for a longer time and it can be viewed by logging into the website.</p>
A weighted least squares consideration for IR-UWB radar based device-free object positioning estimation for indoor environment
Authors: Jerome Daim Terence , Ali Lee Razak Mohd 
Published: March 2020

<p>Impulse Radio Ultra-Wideband (IR-UWB) radar is a type of radar functioning based on UWB transmission technology that uses an exceedingly wide bandwidth low power impulse signal to continuously transmitting and receiving the impulse signal for object detection within a range. To date, most of the proposed Ultra-Wideband (UWB) transmission technology based object positioning estimation systems for indoor environment depends on objects to be attached with an active UWB devices. In certain circumstances, it is ideal to track objects in passive manner without the requirement of any attached tracking devices or device-free object positioning estimation. IR-UWB radar has shown promising utilization in realizing device-free object positioning estimation for indoor environment. With this motivation, in this paper a work on weighted least squares consideration for IR-UWB radar based device-free object positioning estimation for indoor environment is presented.</p>
K-means algorithm with level set for brain tumor segmentation
Authors: Abdelaziz Samah , Lu Songfeng 
Published: March 2020

<p>Brain is a complicated structure consisting of millions of millions cells so that, it’s difficult to identify any diseases without using any computerized technology. Magnetic resonance imaging (mri) is one of the main assessments of brain tumors. One of the most important steps on medical image processing is segmentation. Segmenting brain mri images, which provide accurate information for the diagnosis and therapy decisions of brain tumors. We proposed to segment brain tumor mri images into three parts (wm (white matter), gm (gray matter), and background). The first algorithm is for applying median filtering on brain mri image for removing the noise from the image for achieving accurate results. The second algorithm is for applying k-means algorithm for accuracy in time consuming and for clustering into regions and the third algorithm indicate the detecting the boundary of the image with the use of level set. By comparison, our proposed method, its efficiency to segment perfectly more than other previous used algorithms especially on time consuming.</p>
Pre-scheduled load shutdown in microgrid utilizing computerized surveillance system
Authors: Kanimozhi G , G Kanimozhi , E Umamaheswari , Mani Devi , U Anitha.R 
Published: March 2020

The successful inclusion of microgrids for enhancement of the existing power system is laden with many challenges. Increase in demand and insufficient power generation results in power shutdown in several areas which comprises non-critical loads. The preface of Distributed Generation (DG) in power system has varied implications on the existing system. The concept proposed in this paper helps in time scheduling and load scheduling of a power system based on priority setting and time setting. The load management may also be done using IoT which enables load shedding from remote areas.
An exploratory study of users’ experiences with e-participation: a case study of Malaysia
Authors: Basri Nasrah Hassan , Adnan Wan Adilah Wan , Baharin Hanif 
Published: March 2020

The need to encourage citizens’ adoption of e-participation services has prompted an expanding enthusiasm for the evaluation of e-participation websites. The achievement of e-participation websites depends intensely on how well it is perceived by the users. E-participation is a relatively new approach, so it is important to evaluate it deliberately, in order to comprehend it better, obtain more knowledge about it and distinguish the preferences and advantages it offers, and not to overlook its disadvantages so that we can improve it. Concerning evaluation, many researchers have concentrated on infrastructure and technical issues without giving more attention to user experience as one of the core elements impacting the success or failure of e-participation websites. This paper evaluated e-participation module that located in Malaysia e-government website by utilizing think-aloud method. Think-aloud was being utilized to gauge the perceptions of citizens in their use of e-participation.
An efficient Mppt approach of PV systems: incremental conduction pathway
Authors: Azad Murari Lal , Sadhu Pradip Kumar , Arvind P , Gupta Anagh , Bandyopadhyay Tuhin , Das Soumya , Samanta Sabyasachi 
Published: March 2020

<p class="Abstract">Distributed Generation source have wide application due to their phenomenal advantages. These sources include Photovoltaic (PV) cells producing DC voltage at their output that connects the network through a power electronic interface. PV characteristics, on the other hand, illustrate the fact that maximum power can be extracted at the optimal operating point depending upon the solar radiation and ambient temperature. In order to keep the PV module at its optimal operating point, a DC-DC converter is often used between a PV module and inverter. Consequently, Maximum power point trackers (MPPT) grab the foremost position in the efficiency analysis of the global PV system. Among the several MPPT algorithms, Incremental Conduction technique isemphasised upon as it is extremely simple in implementation within electronic programmable circuits. This paper incorporates the MPPT model using a PV module that always works in its optimal operating point. Design and experimental results of a small prototype of MPPT is presented here based on the Simulink model to verify the advantages of proposed integrated system.</p>
A predictive model for prediction of heart surgery procedure
Authors: Mohd Yusof Aufzalina , Md. Ghani Nor Azura , Mohd Ghani Khairul Asri , Mohd Ghani Khairul Izan 
Published: March 2020

Coronary heart disease (CHD) is a disease in which plague in the form of waxy substance builds up inside the coronary arteries. Coronary artery bypass grafting (CABG) is used as treatment on CHD patients but the role of CABG has been challenged by percutaneous coronary intervention (PCI) when it was introduced in 1977. Drug eluting stents (DES) was introduced with the development of PCI. The purpose of this study was to find the potential risk factors that associated with the procedures (CABG and DES) and to model procedure (CABG vs DES) on coronary heart disease male patients aged 45 years old and below. The study sample was among male patients aged 45 years old and below who has undergone CABG or DES procedure at either IJN or HUKM from January 2007 until December 2010. Logistic regression was used to model treatment selection on coronary heart disease with 87.3% of the classification rate. Patient who i) smoke, ii) obese, or ii) had dyslipidemia was significantly associated with DES, and the other factors were prone to have CABG as their treatment.
Video application to accommodate students’ learning style for moral education in teacher education institutes
Authors: Bin Husin Mohd Razimi , Bin Ahmad Hishamuddin , Bin Hamzah Mahizer 
Published: March 2020

The purpose of this study is to explore the favored video applications in video use, compatible techniques and technology to accommodate the learning styles of moral education students in Teacher Education Institutes. This study is also to explore the contents of lesson suit to technology preferred by students in learning Moral Education. This is a case study in where data were collected through interviews. Six semester four students were chosen through purposive sampling from two Teacher Education Institutes in Malaysia. The constructs and internal validity were verified by experts while the external validity was verified through support from existing studies and theories. Data of the study were analyzed by using the Nvivo software to identify the features of favored video, compatible techniques and contents of lesson suit to technology that enhance the quality of teaching and learning of Moral Education to students. The Physiological Stimulus of Dunn and Dunn Learning Styles Model was used as guidance in the interviews because this model was the most suitable to be applied to students with Physiological Stimulus. The results of the analysis showed that short videos with suitable musics and short duration are the favored video for moral education students in teacher education institutes that enabled students to memorize the content knowledge. This research could be the learning guidelines on the use of videos and consequences activities of the shown videos that accommodate the learning styles of moral education students in Teacher Education Institutes which could be used by instructors in their professional practice in the lecture room.
Sentiment classification of social media reviews using an ensemble classifier
Authors: Sangam Savita , Shinde Subhash 
Published: March 2020

<p>These days it has become a common practice for business organizations and individuals to make use of social media for sharing the opinions about the products or the services. Consumers are also ready to share their views on certain products or commodities. Thus huge amount of unstructured social media data gets generated day by day. Gradually heap of text data will be formed in many areas like automated business, education, health care, and show business and so on. Opinion mining also referred as sentiment analysis or sentiment classification, deals with mining of the review text and classifying the opinions or the sentiments of that text as positive or negative. In this paper we propose an ensemble classifier model consisting of Support Vector Machine and Artificial Neural Network. It combines the knowledge from two feature sets for sentiment classification. The proposed model shows the acceptable performance in terms of accuracy when compared with the baseline model.</p>