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A universal health insurance program such as the National Health Insurance in Taiwan offers a wide coverage and increased access to healthcare services. Despite its ongoing efforts to enhance healthcare accessibility, differences in health for people living in urban and resource-deprived areas remain substantial. To investigate the longitudinal impact of the healthcare system and other potential structural drivers such as education and economic development on geographical disparities in health, we designed a panel study with longitudinal open secondary data, covering all 368 townships in Taiwan between 2013 and 2017. Our findings indicated higher mortality rates in the mountainous and rural areas near the east and south regions of the island in both years. Multivariate analyses showed an increase in the density of primary care physicians (PCP) was associated with lower all-cause mortality (β = − 0.72, p < 0.0001) and cardiovascular disease mortality (β = − 0.41, p < 0.0001). Effect of PCP is evident, but merely focusing on access to healthcare is still not enough. Additional measures are warranted to address the health disparities existing between urban and underprivileged areas. [ABSTRACT FROM AUTHOR]

The science objectives of the LISA mission have been defined under the implicit assumption of a 4-years continuous data stream. Based on the performance of LISA Pathfinder, it is now expected that LISA will have a duty cycle of ≈ 0.75 , which would reduce the effective span of usable data to 3 years. This paper reports the results of a study by the LISA Science Group, which was charged with assessing the additional science return of increasing the mission lifetime. We explore various observational scenarios to assess the impact of mission duration on the main science objectives of the mission. We find that the science investigations most affected by mission duration concern the search for seed black holes at cosmic dawn, as well as the study of stellar-origin black holes and of their formation channels via multi-band and multi-messenger observations. We conclude that an extension to 6 years of mission operations is recommended. [ABSTRACT FROM AUTHOR]

User-item interactions in social media provide a rich dataset for wide applications such as viral marketing and recommender systems. Post retweeting behaviors and venue check-in events by users are the most representative. While existing studies predict items' rise and fall, i.e., tweet popularity and venue closure detection, using hand-crafted features, this paper aims at exploring feature representation learning to improve prediction performance. We target at two essential time-series classification tasks on social media, including Shutdown Risk Prediction (SRP) of venues and Tweet Popularity Prediction (TPP) of posts. We study how feature representation learning of items can benefit both SRP and TPP tasks. The main idea is to learn item embedding vectors as features in item-item graphs constructed from time series of check-in events and retweeting behaviors. The learned features are used together with manually-defined features to enlarge the representation capability. In the TPP task, we also propose a pattern-aware self-exciting point process (PSEISMIC) model to generate time-series features. Experiments conducted on Instagram, Foursquare, and Twitter datasets exhibit promising performance of jointly utilizing learned and extracted features in both tasks. PSEISMIC can also further boost TPP accuracy. The major contribution of this work is three-fold. First, we propose to jointly deal with SRP and TPP under the same framework of feature extraction and learning. Second, we show that feature presentation learning of items can benefit these two prediction tasks with time series data. Third, by incorporating time series patterns, the proposed PSEISMIC further improves the performance of popularity prediction. [ABSTRACT FROM AUTHOR]

Background and Objective: Systematic reviews and meta-analyses of direct oral anticoagulants (DOACs) for patients with chronic kidney disease (CKD) or dialysis patients are lacking. We aimed to compare the efficacy and safety of DOACs and warfarin in patients with CKD requiring anticoagulation therapy. Methods: We performed a systematic review and meta-analysis of six randomized controlled trials and 19 observational studies, with the inclusion criteria being a comparative study between DOACs and warfarin in patients with CKD or dialysis patients from database inception until August 2020. The efficacy outcomes were stroke, systemic embolism (SE), or venous thromboembolism (VTE), and the safety outcome was major bleeding. Results: Compared with warfarin, DOACs significantly reduced the risk of stroke/SE/VTE by 22% (hazard ratio [HR] = 0.78, 95% confidence interval [CI] 0.64–0.95) and major bleeding by 17% (HR = 0.83, 95% CI 0.71–0.97). On comparing factor Xa inhibitors and dabigatran with warfarin separately, factor Xa inhibitors significantly reduced the risk of stroke/SE/VTE (HR = 0.78, 95% CI 0.62–0.98) and major bleeding (HR = 0.76, 95% CI 0.64–0.91) overall in patients. Comparing each DOACs with warfarin separately, apixaban was associated with a significantly better risk reduction of stroke/SE/VTE (25% risk reduction) and major bleeding (35% risk reduction) than warfarin. Compared with warfarin, DOACs significantly reduced the risk of stroke, SE, or VTE by 19% (HR = 0.81, 95% CI 0.68–0.97) in patients with CKD stage 3 and significantly lowered the risk of major bleeding by 31% (HR = 0.69, 95% CI 0.56–0.85) in patients with CKD stages 4–5. Conclusions: In pooled, analyzed randomized controlled trials and observational studies, DOACs were associated with better efficacy in early CKD, as well as similar efficacy and safety outcomes to warfarin in patients with CKD stages 4–5 or dialysis patients. The results of patients with CKD stages 4–5 and dialysis patients were from observational studies. Well-designed randomized controlled trials focused on DOAC use in patients with CKD and dialysis patients are needed. PROSPERO register number: CRD42020150599, 6 February, 2020. [ABSTRACT FROM AUTHOR]

Cephalic arch stenosis (CAS) is a common cause of AV dialysis access failure and is notoriously difficult to treat with conventional venoplasty. Although stent graft (SG) placement has improved patency rate, they are prone to stent failure caused by edge stenosis. We investigate the effect of SG diameter relative to cephalic vein on patency rate among hemodialysis patients with dysfunctional arteriovenous access caused by CAS. We identified 22 patients with recalcitrant cephalic arch stenosis or post-venoplasty vessel rupture and received SG placement. Patients were divided into two groups based on the stent-to-vessel diameter (S/V) ratio: undersized group, < 1; and apposed group, 1–1.2. Outcomes were assessed through follow-up angiography. S/V ratio was significant smaller in the undersized patient group (p < 0.001). Placement of undersized SG demonstrated higher primary stent (p = 0.001) and access patency rates (p = 0.021) and a reduced number of post-treatment reinterventions per access year (p = 0.021). A decreased number of lateral edge stenosis was noted in undersized SG (p = 0.005). Increased S/V ratio was significantly associated with lateral edge stenosis (OR = 5.19; p = 0.027). Undersized SG is associated with higher primary stent and access patency rate, and decreased number of post-SG interventions, and are suggested in the treatment of cephalic arch stenosis. [ABSTRACT FROM AUTHOR]

Modern retail chains, such as Starbucks and McDonald's, seek for geographical locations that have higher possibility to bring the maximum profit to establish and open their new stores. For a retail store, the common indicator of profit is its popularity which can be measured by the number of people who had ever consumed there. If one can know the potential popularity of locations along the time or within a certain time period (e.g., Christmas holiday or some memorial days) in advance, it would facilitate the determination of locations that are more profitable for the geographical placement of new retail stores. In this paper, given a targeted retail chain as well as some candidate locations, we propose to predict the popularity values of these locations over time to support their decisions on placing new stores. We devise a semi-supervised learning model, Affinity-based Popularity Inference, to tackle the Temporal Location Popularity Prediction problem. The basic idea is that locations that share similar properties of geo-spatial venue characteristics and human mobility tend to have closer popularity values. Experiments conducted on Foursquare check-in data in New York City exhibit promising results on predicting the temporal popularity of retail chains Starbucks, McDonald's, and Dunkin' Donuts, comparing to interpolation, regression, and state-of-the-art supervised learning methods. [ABSTRACT FROM AUTHOR]

Location-based services allow users to perform check-in actions, which record the geo-spatial activities and provide a plentiful source to do more accurate and useful geographical recommendation. In this paper, we present a novel PreferredTime-aware Route Planning (PTRP) problem, which aims to recommend routes whose locations are not only representative but also need to satisfy users’ preference. The central idea is that the goodness of visiting locations along a route is significantly affected by the visiting time and user preference, and each location has its own proper visiting time due to its category and population. We develop a four-stage preference-based time-aware route planning framework. First, since there is usually either noise time on existing locations or no visiting information on new locations, we devise an inference method, LocTimeInf, to predict the location visiting time on routes. Second, considering the geographical, social, and temporal information of users, we propose the GST-Clus method to group users with similar location visiting preferences. Third, we find the representative and popular time-aware location-transition behaviors by proposing Time-aware Transit Pattern Mining (TTPM) algorithm. Finally, based on the mined time-aware transit patterns, we develop a Preferred Route Search (PR-Search) algorithm to construct the final time-aware routes. Experiments on Gowalla and Foursquare check-in data exhibit the promising effectiveness and efficiency of the proposed methods, comparing to a series of competitors. [ABSTRACT FROM AUTHOR]

The present study explores how culture-based meanings and values toward skin color, which are associated with women's body image ideals and gender-role expectations, profoundly influence women's leisure behaviors. Using in-depth interviews with East Asian, Asian American, and Euro-American women ( n = 43), results revealed how leisure behaviors are tied to cultural perceptions of skin color. People from different cultural backgrounds construct meanings and values pertaining to skin color, including beauty-related standards, social class, gender roles, and lifestyles. Culture-based values, such as the preference for tanned skin among Euro-Americans and for lighter skin among East Asians, affect a wide range of daily behaviors. These behaviors include conscious as well as subtle daily decision-making regarding sun-seeking, sun-avoidance, and sun-protection behaviors; indoor versus outdoor leisure participation; and appearance modifications. The study's results add knowledge to how perceptions and attitudes toward skin color and appearance manifest in women's daily behavior in general and leisure behavior in particular. In addition, the current study shows how individual behaviors reflect cultural meanings and values toward body image, specifically skin color, by emphasizing the links between cultural values and women's day-to-day lives. [ABSTRACT FROM AUTHOR]

Gravitational-wave detections provide a novel way to determine the Hubble constant1-3, which is the current rate of expansion of the Universe. This ‘standard siren’ method, with the absolute distance calibration provided by the general theory of relativity, was used to measure the Hubble constant using the gravitational-wave detection of the binary neutron-star merger, GW170817, by the Laser Interferometer Gravitational-Wave Observatory (LIGO) and Virgo4, combined with optical identification of the host galaxy5,6 NGC 4993. This independent measurement is of particular interest given the discrepancy between the value of the Hubble constant determined using type Ia supernovae via the local distance ladder (73.24 ± 1.74 kilometres per second per megaparsec) and the value determined from cosmic microwave background observations (67.4 ± 0.5 kilometres per second per megaparsec): these values differ7,8 by about 3σ. Local distance ladder observations may achieve a precision of one per cent within five years, but at present there are no indications that further observations will substantially reduce the existing discrepancies9. Here we show that additional gravitational-wave detections by LIGO and Virgo can be expected to constrain the Hubble constant to a precision of approximately two per cent within five years and approximately one per cent within a decade. This is because observing gravitational waves from the merger of two neutron stars, together with the identification of a host galaxy, enables a direct measurement of the Hubble constant independent of the systematics associated with other available methods. In addition to clarifying the discrepancy between existing low-redshift (local ladder) and high-redshift (cosmic microwave background) measurements, a precision measurement of the Hubble constant is of crucial value in elucidating the nature of dark energy10,11. Gravitational-wave observations of binary neutron-star mergers will enable precision measurements of the Hubble constant within five years. [ABSTRACT FROM AUTHOR]

In this study, we investigated wave transformation and wave set-up between a submerged permeable breakwater and a seawall. Modified time-dependent mild-slope equations, which involve parameters of the porous medium, were used to calculate the wave height transformation and the mean water level change around a submerged breakwater. The numerical solution is verified with experimental data. The simulated results show that modulations of the wave profile and wave set-up are clearly observed between the submerged breakwater and the seawall. In contrast to cases without a seawall, the node or pseudo-node of wave height evolution can be found between the submerged breakwater and the seawall. Higher wave set-up occurs if the nodal or pseudo-nodal point appears near the submerged breakwater. We also examined the influence of the porosity and friction factor of the submerged permeable breakwater on wave transformation and set-up. [ABSTRACT FROM AUTHOR]

This review aims at providing an extensive discussion of modern constraints relevant for dense and hot strongly interacting matter. It includes theoretical first-principle results from lattice and perturbative QCD, as well as chiral effective field theory results. From the experimental side, it includes heavy-ion collision and low-energy nuclear physics results, as well as observations from neutron stars and their mergers. The validity of different constraints, concerning specific conditions and ranges of applicability, is also provided. [ABSTRACT FROM AUTHOR]

The Laser Interferometer Space Antenna (LISA) has two scientific objectives of cosmological focus: to probe the expansion rate of the universe, and to understand stochastic gravitational-wave backgrounds and their implications for early universe and particle physics, from the MeV to the Planck scale. However, the range of potential cosmological applications of gravitational-wave observations extends well beyond these two objectives. This publication presents a summary of the state of the art in LISA cosmology, theory and methods, and identifies new opportunities to use gravitational-wave observations by LISA to probe the universe. [ABSTRACT FROM AUTHOR]