1,590 research outputs found
SOCIAL NETWORK PRIVACY DISPOSITIONS: AN OBJECTIVE MEASUREMENT SCALE AND A CAUSAL MODEL
The Information Systems literature has substantially advanced understanding of privacy in both offline contexts and online environments. Despite the rich understanding, existing studies predominately focused on elucidating privacy issues specific to individuals. The increasingly popular usage of mobile apps with social media integration has fundamentally challenged current understanding and conceptualization of information privacy. In particular, mobile apps allow information collection beyond individuals’ personal scope (i.e., his/her personal information) and extend the scope of acquisition into individuals’ online social networks (i.e., his/her list of friends on Facebook). To fill this gap in the literature, drawing on the Communication Privacy Management Theory, this proposal focuses on three unique dimensions of social network privacy dispositions, namely permeability, ownership, and linkage. Second, we propose to operationalize these three dimensions of social network privacy dispositions using a second-order reflective construct, and we plan to develop an objective measurement scale for it. Lastly, we plan to validate the construct using a nomological network
On the Numerical Evaluation of Loop Integrals With Mellin-Barnes Representations
An improved method is presented for the numerical evaluation of multi-loop
integrals in dimensional regularization. The technique is based on
Mellin-Barnes representations, which have been used earlier to develop
algorithms for the extraction of ultraviolet and infrared divergencies. The
coefficients of these singularities and the non-singular part can be integrated
numerically. However, the numerical integration often does not converge for
diagrams with massive propagators and physical branch cuts. In this work,
several steps are proposed which substantially improve the behavior of the
numerical integrals. The efficacy of the method is demonstrated by calculating
several two-loop examples, some of which have not been known before.Comment: 13 pp. LaTe
The All-Data-Based Evolutionary Hypothesis of Ciliated Protists with a Revised Classification of the Phylum Ciliophora (Eukaryota, Alveolata)
This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ The file attached is the published version of the article
Demographics and Medication Use of Patients with Late-Onset Alzheimer's Disease in Hong Kong
BACKGROUND: Alzheimer's disease (AD) is the most common cause of dementia in the elderly population. However, epidemiological studies on the demographics of AD in Hong Kong population are lacking. OBJECTIVE: We investigated the demographics, comorbidities, mortality rates, and medication use of patients with AD in Hong Kong to understand how the disease has been managed locally. METHODS: This was a collaborative study of The Hong Kong University of Science and Technology and the Hospital Authority Data Collaboration Lab. We analyzed the demographic data, clinical records, diagnoses, and medication records of patients with AD under the care of the Hospital Authority between January 1, 2007 and December 31, 2017. RESULTS: We identified 23,467 patients diagnosed with AD. The median age at diagnosis was 84 years old, and 71% of patients were female. The most common comorbidity was hypertension (52.6%). 39.9% of patients received medications for dementia; of those, 68.4% had taken those medications for > 1 year. Compared to nonusers, long-term AD medication users had a significantly younger age of AD onset and were taking more lipid-regulating medication, diabetes medication, or antidepressants. Surprisingly, the use of antipsychotics in patients with AD was quite common; 50.7% of patients had received any type of antipsychotic during disease progression. CONCLUSION: This study provides detailed information on the demographics and medication use of patients with AD in Hong Kong. The data from this AD cohort will aid our future research aiming to identify potential AD risk factors and associations between AD and other diseases
Impact of diastolic dysfunction severity on global left ventricular volumetric filling - assessment by automated segmentation of routine cine cardiovascular magnetic resonance
<p>Abstract</p> <p>Objectives</p> <p>To examine relationships between severity of echocardiography (echo) -evidenced diastolic dysfunction (DD) and volumetric filling by automated processing of routine cine cardiovascular magnetic resonance (CMR).</p> <p>Background</p> <p>Cine-CMR provides high-resolution assessment of left ventricular (LV) chamber volumes. Automated segmentation (LV-METRIC) yields LV filling curves by segmenting all short-axis images across all temporal phases. This study used cine-CMR to assess filling changes that occur with progressive DD.</p> <p>Methods</p> <p>115 post-MI patients underwent CMR and echo within 1 day. LV-METRIC yielded multiple diastolic indices - E:A ratio, peak filling rate (PFR), time to peak filling rate (TPFR), and diastolic volume recovery (DVR<sub>80 </sub>- proportion of diastole required to recover 80% stroke volume). Echo was the reference for DD.</p> <p>Results</p> <p>LV-METRIC successfully generated LV filling curves in all patients. CMR indices were reproducible (≤ 1% inter-reader differences) and required minimal processing time (175 ± 34 images/exam, 2:09 ± 0:51 minutes). CMR E:A ratio decreased with grade 1 and increased with grades 2-3 DD. Diastolic filling intervals, measured by DVR<sub>80 </sub>or TPFR, prolonged with grade 1 and shortened with grade 3 DD, paralleling echo deceleration time (p < 0.001). PFR by CMR increased with DD grade, similar to E/e' (p < 0.001). Prolonged DVR<sub>80 </sub>identified 71% of patients with echo-evidenced grade 1 but no patients with grade 3 DD, and stroke-volume adjusted PFR identified 67% with grade 3 but none with grade 1 DD (matched specificity = 83%). The combination of DVR<sub>80 </sub>and PFR identified 53% of patients with grade 2 DD. Prolonged DVR<sub>80 </sub>was associated with grade 1 (OR 2.79, CI 1.65-4.05, p = 0.001) with a similar trend for grade 2 (OR 1.35, CI 0.98-1.74, p = 0.06), whereas high PFR was associated with grade 3 (OR 1.14, CI 1.02-1.25, p = 0.02) DD.</p> <p>Conclusions</p> <p>Automated cine-CMR segmentation can discern LV filling changes that occur with increasing severity of echo-evidenced DD. Impaired relaxation is associated with prolonged filling intervals whereas restrictive filling is characterized by increased filling rates.</p
The gray matter volume of the amygdala is correlated with the perception of melodic intervals: a voxel-based morphometry study
Music is not simply a series of organized pitches, rhythms, and timbres, it is capable of evoking emotions. In the present study, voxel-based morphometry (VBM) was employed to explore the neural basis that may link music to emotion. To do this, we identified the neuroanatomical correlates of the ability to extract pitch interval size in a music segment (i.e., interval perception) in a large population of healthy young adults (N = 264). Behaviorally, we found that interval perception was correlated with daily emotional experiences, indicating the intrinsic link between music and emotion. Neurally, and as expected, we found that interval perception was positively correlated with the gray matter volume (GMV) of the bilateral temporal cortex. More important, a larger GMV of the bilateral amygdala was associated with better interval perception, suggesting that the amygdala, which is the neural substrate of emotional processing, is also involved in music processing. In sum, our study provides one of first neuroanatomical evidence on the association between the amygdala and music, which contributes to our understanding of exactly how music evokes emotional responses
Bayesian lasso binary quantile regression
In this paper, a Bayesian hierarchical model for variable selection and estimation in the context of binary quantile regression is proposed. Existing approaches to variable selection in a binary classification context are sensitive to outliers, heteroskedasticity or other anomalies of the latent response. The method proposed in this study overcomes these problems in an attractive and straightforward way. A Laplace likelihood and Laplace priors for the regression parameters are proposed and estimated with Bayesian Markov Chain Monte Carlo. The resulting model is equivalent to the frequentist lasso procedure. A conceptional result is that by doing so, the binary regression model is moved from a Gaussian to a full Laplacian framework without sacrificing much computational efficiency. In addition, an efficient Gibbs sampler to estimate the model parameters is proposed that is superior to the Metropolis algorithm that is used in previous studies on Bayesian binary quantile regression. Both the simulation studies and the real data analysis indicate that the proposed method performs well in comparison to the other methods. Moreover, as the base model is binary quantile regression, a much more detailed insight in the effects of the covariates is provided by the approach. An implementation of the lasso procedure for binary quantile regression models is available in the R-package bayesQR
Transparency in health economic modeling : options, issues and potential solutions
Economic models are increasingly being used by health economists to assess the value of health technologies and inform healthcare decision making. However, most published economic models represent a kind of black box, with known inputs and outputs but undisclosed internal calculations and assumptions. This lack of transparency makes the evaluation of the model results challenging, complicates comparisons between models, and limits the reproducibility of the models. Here, we aim to provide an overview of the possible steps that could be undertaken to make economic models more transparent and encourage model developers to share more detailed calculations and assumptions with their peers. Scenarios with different levels of transparency (i.e., how much information is disclosed) and reach of transparency (i.e., who has access to the disclosed information) are discussed, and five key concerns (copyrights, model misuse, confidential data, software, and time/resources) pertaining to model transparency are presented, along with possible solutions. While a shift toward open-source models is underway in health economics, as has happened before in other research fields, the challenges ahead should not be underestimated. Importantly, there is a pressing need to find an acceptable trade-off between the added value of model transparency and the time and resources needed to achieve such transparency. To this end, it will be crucial to set incentives at different stakeholder levels. Despite the many challenges, the many benefits of publicly sharing economic models make increased transparency a goal worth pursuing
In vivo whole-cell recording with high success rate in anaesthetized and awake mammalian brains
Theory of Multidimensional Solitons
We review a number of topics germane to higher-dimensional solitons in
Bose-Einstein condensates. For dark solitons, we discuss dark band and planar
solitons; ring dark solitons and spherical shell solitons; solitary waves in
restricted geometries; vortex rings and rarefaction pulses; and multi-component
Bose-Einstein condensates. For bright solitons, we discuss instability,
stability, and metastability; bright soliton engineering, including pulsed atom
lasers; solitons in a thermal bath; soliton-soliton interactions; and bright
ring solitons and quantum vortices. A thorough reference list is included.Comment: review paper, to appear as Chapter 5a in "Emergent Nonlinear
Phenomena in Bose-Einstein Condensates: Theory and Experiment," edited by P.
G. Kevrekidis, D. J. Frantzeskakis, and R. Carretero-Gonzalez
(Springer-Verlag
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