Showing papers by "University of Jyväskylä published in 2020"
University of California, Berkeley1, Stellenbosch University2, University of Jyväskylä3, University of Cambridge4, Google5, University of Toronto6, University of Birmingham7, Temple University8, Amazon.com9, University of British Columbia10, University of Georgia11, University of Oxford12, Los Alamos National Laboratory13, University of California, Irvine14
TL;DR: In this paper, the authors review how a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring and analysing scientific data, and their evolution into a flexible interoperability layer between increasingly specialized computational libraries is discussed.
Abstract: Array programming provides a powerful, compact and expressive syntax for accessing, manipulating and operating on data in vectors, matrices and higher-dimensional arrays. NumPy is the primary array programming library for the Python language. It has an essential role in research analysis pipelines in fields as diverse as physics, chemistry, astronomy, geoscience, biology, psychology, materials science, engineering, finance and economics. For example, in astronomy, NumPy was an important part of the software stack used in the discovery of gravitational waves1 and in the first imaging of a black hole2. Here we review how a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring and analysing scientific data. NumPy is the foundation upon which the scientific Python ecosystem is constructed. It is so pervasive that several projects, targeting audiences with specialized needs, have developed their own NumPy-like interfaces and array objects. Owing to its central position in the ecosystem, NumPy increasingly acts as an interoperability layer between such array computation libraries and, together with its application programming interface (API), provides a flexible framework to support the next decade of scientific and industrial analysis. NumPy is the primary array programming library for Python; here its fundamental concepts are reviewed and its evolution into a flexible interoperability layer between increasingly specialized computational libraries is discussed.
7,624 citations
University of Jyväskylä1, University of California, Los Angeles2, California Polytechnic State University3, Los Alamos National Laboratory4, National Research University – Higher School of Economics5, University of California, Berkeley6, University of Birmingham7, Australian Nuclear Science and Technology Organisation8, University of Washington9, University of Massachusetts Amherst10, University of West Bohemia11, Brigham Young University12, University of Texas at Austin13, Universidade Federal de Minas Gerais14, Google15
TL;DR: SciPy as discussed by the authors is an open-source scientific computing library for the Python programming language, which has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year.
Abstract: SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.
6,244 citations
University of California, Berkeley1, Stellenbosch University2, University of Jyväskylä3, University of Cambridge4, Google5, University of Toronto6, University of Birmingham7, Temple University8, University of British Columbia9, Amazon.com10, University of Georgia11, University of Oxford12, Los Alamos National Laboratory13, University of California, Irvine14
TL;DR: How a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring and analysing scientific data is reviewed.
Abstract: Array programming provides a powerful, compact, expressive syntax for accessing, manipulating, and operating on data in vectors, matrices, and higher-dimensional arrays. NumPy is the primary array programming library for the Python language. It plays an essential role in research analysis pipelines in fields as diverse as physics, chemistry, astronomy, geoscience, biology, psychology, material science, engineering, finance, and economics. For example, in astronomy, NumPy was an important part of the software stack used in the discovery of gravitational waves and the first imaging of a black hole. Here we show how a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring, and analyzing scientific data. NumPy is the foundation upon which the entire scientific Python universe is constructed. It is so pervasive that several projects, targeting audiences with specialized needs, have developed their own NumPy-like interfaces and array objects. Because of its central position in the ecosystem, NumPy increasingly plays the role of an interoperability layer between these new array computation libraries.
4,342 citations
University of Jyväskylä1, University of California, Los Angeles2, California Polytechnic State University3, Los Alamos National Laboratory4, National Research University – Higher School of Economics5, University of California, Berkeley6, University of Birmingham7, Australian Nuclear Science and Technology Organisation8, University of Washington9, University of Massachusetts Amherst10, University of West Bohemia11, Brigham Young University12, University of Texas at Austin13, Universidade Federal de Minas Gerais14, Google15
TL;DR: An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.
617 citations
467 citations
Oslo University Hospital1, Cardiff University2, University of Helsinki3, Leiden University Medical Center4, Royal Melbourne Hospital5, Leipzig University6, University of Bonn7, University of Melbourne8, Aarhus University9, Aarhus University Hospital10, Aalborg University11, University of Barcelona12, Imperial College London13, Central Manchester University Hospitals NHS Foundation Trust14, University of Manchester15, Newcastle University16, University of Vermont17, University Medical Center Groningen18, European Institute of Oncology19, Vita-Salute San Raffaele University20, Karolinska Institutet21, Tel Aviv University22, Sheba Medical Center23, University Hospital of Basel24, Hospital Italiano de Buenos Aires25, University of Cologne26, Dresden University of Technology27, Ludwig Maximilian University of Munich28, University Hospital Bonn29, University Hospital Heidelberg30, German Cancer Research Center31, University of Düsseldorf32, Ruhr University Bochum33, Helsinki University Central Hospital34, Stanford University35, Mayo Clinic36, Lunenfeld-Tanenbaum Research Institute37, University of Hawaii38, Fred Hutchinson Cancer Research Center39, Cedars-Sinai Medical Center40, Copenhagen University Hospital41, Leiden University42, Karolinska University Hospital43, University of Jyväskylä44, University of Oslo45
TL;DR: Management guidelines for Lynch syndrome may require revision in light of these different gene and gender-specific risks and the good prognosis for the most commonly associated cancers.
334 citations
Stockholm University1, Stanford University2, Texas A&M University3, University of Exeter4, United States Geological Survey5, University of California, Los Angeles6, University of Jyväskylä7, University of Alberta8, University of Toronto9, Umeå University10, University of New Hampshire11, University of Guelph12, University of Colorado Boulder13, Université de Montréal14, Lehigh University15, Northeast Normal University16
TL;DR: This study compiles over 7,000 field observations to present a data-driven map of northern peatlands and their carbon and nitrogen stocks, and uses machine-learning techniques with extensive peat core data to create observation-based maps ofNorthern peatland C and N stocks and to assess their response to warming and permafrost thaw.
Abstract: Northern peatlands have accumulated large stocks of organic carbon (C) and nitrogen (N), but their spatial distribution and vulnerability to climate warming remain uncertain. Here, we used machine-learning techniques with extensive peat core data (n > 7,000) to create observation-based maps of northern peatland C and N stocks, and to assess their response to warming and permafrost thaw. We estimate that northern peatlands cover 3.7 ± 0.5 million km2 and store 415 ± 150 Pg C and 10 ± 7 Pg N. Nearly half of the peatland area and peat C stocks are permafrost affected. Using modeled global warming stabilization scenarios (from 1.5 to 6 °C warming), we project that the current sink of atmospheric C (0.10 ± 0.02 Pg C⋅y-1) in northern peatlands will shift to a C source as 0.8 to 1.9 million km2 of permafrost-affected peatlands thaw. The projected thaw would cause peatland greenhouse gas emissions equal to ∼1% of anthropogenic radiative forcing in this century. The main forcing is from methane emissions (0.7 to 3 Pg cumulative CH4-C) with smaller carbon dioxide forcing (1 to 2 Pg CO2-C) and minor nitrous oxide losses. We project that initial CO2-C losses reverse after ∼200 y, as warming strengthens peatland C-sinks. We project substantial, but highly uncertain, additional losses of peat into fluvial systems of 10 to 30 Pg C and 0.4 to 0.9 Pg N. The combined gaseous and fluvial peatland C loss estimated here adds 30 to 50% onto previous estimates of permafrost-thaw C losses, with southern permafrost regions being the most vulnerable.
294 citations
University of Basel1, European University Cyprus2, Kore University of Enna3, University of Nicosia4, Cyprus University of Technology5, The Cyprus Institute of Neurology and Genetics6, The Chinese University of Hong Kong7, Universidad de La Sabana8, University College Cork9, University College Dublin10, Babeș-Bolyai University11, International Sleep Products Association12, University of Lisbon13, University of Grenoble14, University of Cádiz15, European University of Madrid16, University of Zaragoza17, University of Jyväskylä18, Ljubljana University Medical Centre19, Université du Québec à Trois-Rivières20, Duke University21, University of Cyprus22
TL;DR: In this paper, the authors conducted a study to determine mental health outcomes during pandemic induced lockdowns and examined known predictors of mental health outcome, including country, sociodemographic factors, lockdown characteristics, social factors, and psychological factors.
Abstract: BACKGROUND: The COVID-19 pandemic triggered vast governmental lockdowns. The impact of these lockdowns on mental health is inadequately understood. On the one hand such drastic changes in daily routines could be detrimental to mental health. On the other hand, it might not be experienced negatively, especially because the entire population was affected. METHODS: The aim of this study was to determine mental health outcomes during pandemic induced lockdowns and to examine known predictors of mental health outcomes. We therefore surveyed n = 9,565 people from 78 countries and 18 languages. Outcomes assessed were stress, depression, affect, and wellbeing. Predictors included country, sociodemographic factors, lockdown characteristics, social factors, and psychological factors. RESULTS: Results indicated that on average about 10% of the sample was languishing from low levels of mental health and about 50% had only moderate mental health. Importantly, three consistent predictors of mental health emerged: social support, education level, and psychologically flexible (vs. rigid) responding. Poorer outcomes were most strongly predicted by a worsening of finances and not having access to basic supplies. CONCLUSIONS: These results suggest that on whole, respondents were moderately mentally healthy at the time of a population-wide lockdown. The highest level of mental health difficulties were found in approximately 10% of the population. Findings suggest that public health initiatives should target people without social support and those whose finances worsen as a result of the lockdown. Interventions that promote psychological flexibility may mitigate the impact of the pandemic.
278 citations
TL;DR: Although it is well known that insects are sensitive to temperature, how they will be affected by ongoing global warming remains uncertain because these responses are multifaceted and ecologically... as discussed by the authors.
Abstract: Although it is well known that insects are sensitive to temperature, how they will be affected by ongoing global warming remains uncertain because these responses are multifaceted and ecologically ...
192 citations
TL;DR: The Deep Underground Neutrino Experiment (DUNE) as discussed by the authors is an international world-class experiment dedicated to addressing these questions as it searches for leptonic charge-parity symmetry violation, stands ready to capture supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model.
Abstract: The preponderance of matter over antimatter in the early universe, the dynamics of the supernovae that produced the heavy elements necessary for life, and whether protons eventually decay—these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our universe, its current state, and its eventual fate. The Deep Underground Neutrino Experiment (DUNE) is an international world-class experiment dedicated to addressing these questions as it searches for leptonic charge-parity symmetry violation, stands ready to capture supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model. The DUNE far detector technical design report (TDR) describes the DUNE physics program and the technical designs of the single- and dual-phase DUNE liquid argon TPC far detector modules. This TDR is intended to justify the technical choices for the far detector that flow down from the high-level physics goals through requirements at all levels of the Project. Volume I contains an executive summary that introduces the DUNE science program, the far detector and the strategy for its modular designs, and the organization and management of the Project. The remainder of Volume I provides more detail on the science program that drives the choice of detector technologies and on the technologies themselves. It also introduces the designs for the DUNE near detector and the DUNE computing model, for which DUNE is planning design reports. Volume II of this TDR describes DUNE's physics program in detail. Volume III describes the technical coordination required for the far detector design, construction, installation, and integration, and its organizational structure. Volume IV describes the single-phase far detector technology. A planned Volume V will describe the dual-phase technology.
187 citations
Newcastle University1, University of Leeds2, Royal Melbourne Hospital3, University of Jyväskylä4, Public Health England5, St Mary's Hospital6, University of Manchester7, Queen Mary University of London8, Karolinska Institutet9, Queen's University Belfast10, University of Cape Town11, University of Helsinki12, Imperial College London13
TL;DR: The case for prevention of colorectal cancer with aspirin in Lynch syndrome is supported by the results and the intention-to-treat and per-protocol analyses showed no effect.
TL;DR: The two-to-three-month home-isolation has had mixed effects on adult health behaviors in China, and the participants were found to have focused more on their eating quality and patterns, which had a positive influence on their QoL.
Abstract: Background: The coronavirus disease 2019 (COVID-19) pandemic has created challenges that have caused profound changes in health behaviors. This study aimed to explore how COVID-19 is affecting the health-related quality of life (QoL) among Chinese adults. Methods: The data of health-related behaviors and QoL were collected via online surveys from 2289 adults (mean age = 27.8 ± 12 years) who had been isolated at home for an average of 77 days. Results: More than 50% of the respondents reported that their time engaged in daily physical activity (PA) decreased, while sedentary behavior (SB) time increased compared with that before the lockdown. Only 20% of the respondents reported engaging in moderate-to-vigorous PA, 23% of adults reported changed their diets to be healthier, and 30% reported consuming more vegetables, fruits, and milk products than before home-isolation. During home-isolation, 75.2% of the adults rated their sleep quality as very good, and 65% reported that they were satisfied with their QoL. Sleep quality mediated the relationship between PA and QoL. Conclusion: The two-to-three-month home-isolation has had mixed effects on adult health behaviors in China. The participants were found to have focused more on their eating quality and patterns, which had a positive influence on their QoL. However, people should be encouraged to exercise at home with limited space to maintain a generally healthy lifestyle during a prolonged quarantine.
TL;DR: This study employed the stressor–strain–outcome (SSO) framework to explain social media discontinuance behaviors from an overload perspective and indicated that the three types of overload are interconnected through system feature overload.
Abstract: While users’ discontinuance of use has posed a challenge for social media in recent years, there is a paucity of knowledge on the relationships between different dimensions of overload and how overload adversely affects users’ social media discontinuance behaviors. To address this knowledge gap, this study employed the stressor–strain–outcome (SSO) framework to explain social media discontinuance behaviors from an overload perspective. It also conceptualized social media overload as a multidimensional construct consisting of system feature overload, information overload, and social overload. The proposed research model was empirically validated via 412 valid questionnaire responses collected from Facebook users. Our results indicated that the three types of overload are interconnected through system feature overload. System feature overload, information overload, and social overload engender user exhaustion, which in turn leads to users’ discontinued usage of social media. This study extends current technostress research by demonstrating the value of the SSO perspective in explaining users’ social media discontinuance.
TL;DR: In this paper, the invariant yields are measured over a wide transverse momentum range from hundreds of MeV/$c$ up to 20 GeV/c$ and the results in Pb-Pb collisions are presented as a function of the collision centrality.
Abstract: Mid-rapidity production of $\pi^{\pm}$, $\rm{K}^{\pm}$ and ($\bar{\rm{p}}$)p measured by the ALICE experiment at the LHC, in Pb-Pb and inelastic pp collisions at $\sqrt{s_{\rm{NN}}}$ = 5.02 TeV, is presented. The invariant yields are measured over a wide transverse momentum ($p_{\rm{T}}$) range from hundreds of MeV/$c$ up to 20 GeV/$c$. The results in Pb-Pb collisions are presented as a function of the collision centrality, in the range 0$-$90%. The comparison of the $p_{\rm{T}}$-integrated particle ratios, i.e. proton-to-pion (p/$\pi$) and kaon-to-pion (K/$\pi$) ratios, with similar measurements in Pb-Pb collisions at $\sqrt{s_{\rm{NN}}}$ = 2.76 TeV show no significant energy dependence. Blast-wave fits of the $p_{\rm{T}}$ spectra indicate that in the most central collisions radial flow is slightly larger at 5.02 TeV with respect to 2.76 TeV. Particle ratios (p/$\pi$, K/$\pi$) as a function of $p_{\rm{T}}$ show pronounced maxima at $p_{\rm{T}}$ $\approx$ 3 GeV/$c$ in central Pb-Pb collisions. At high $p_{\rm{T}}$, particle ratios at 5.02 TeV are similar to those measured in pp collisions at the same energy and in Pb-Pb collisions at $\sqrt{s_{\rm{NN}}}$ = 2.76 TeV. Using the pp reference spectra measured at the same collision energy of 5.02 TeV, the nuclear modification factors for the different particle species are derived. Within uncertainties, the nuclear modification factor is particle species independent for high $p_{\rm{T}}$ and compatible with measurements at $\sqrt{s_{\rm{NN}}}$ = 2.76 TeV. The results are compared to state-of-the-art model calculations, which are found to describe the observed trends satisfactorily.
TL;DR: In this paper, the authors show that TBG flat-band superconductivity relies on such quantum geometric properties of the band as its quantum metric and Berry curvature, which can be used to reveal the yet unknown pairing symmetry.
Abstract: Superconductivity in twisted bilayer graphene (TBG) has inspired fervent research to explain the origin of the phenomenon and to find whether moir\'e materials featuring flat bands offer a route to room-temperature superconductivity. Here, the authors show that TBG flat-band superconductivity relies on such quantum geometric properties of the band as its quantum metric and Berry curvature. The authors predict qualitative differences between different pairing potentials, which can be used to reveal the yet unknown pairing symmetry.
TL;DR: The Dune experiment as discussed by the authors is an international world-class experiment dedicated to addressing these questions as it searches for leptonic charge-parity symmetry violation, stands ready to capture supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model.
Abstract: The preponderance of matter over antimatter in the early universe, the dynamics of the supernovae that produced the heavy elements necessary for life, and whether protons eventually decay—these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our universe, its current state, and its eventual fate. DUNE is an international world-class experiment dedicated to addressing these questions as it searches for leptonic charge-parity symmetry violation, stands ready to capture supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model. Central to achieving DUNE's physics program is a far detector that combines the many tens-of-kiloton fiducial mass necessary for rare event searches with sub-centimeter spatial resolution in its ability to image those events, allowing identification of the physics signatures among the numerous backgrounds. In the single-phase liquid argon time-projection chamber (LArTPC) technology, ionization charges drift horizontally in the liquid argon under the influence of an electric field towards a vertical anode, where they are read out with fine granularity. A photon detection system supplements the TPC, directly enhancing physics capabilities for all three DUNE physics drivers and opening up prospects for further physics explorations. The DUNE far detector technical design report (TDR) describes the DUNE physics program and the technical designs of the single- and dual-phase DUNE liquid argon TPC far detector modules. Volume IV presents an overview of the basic operating principles of a single-phase LArTPC, followed by a description of the DUNE implementation. Each of the subsystems is described in detail, connecting the high-level design requirements and decisions to the overriding physics goals of DUNE.
TL;DR: Findings suggest targeting change in coping planning and action planning may be most effective in promoting participation in COVID‐19 preventive behaviours, and provide insight into potentially modifiable constructs that interventions can target.
Abstract: OBJECTIVES: Rates of novel coronavirus disease 2019 (COVID-19) infections have rapidly increased worldwide and reached pandemic proportions. A suite of preventive behaviours have been recommended to minimize risk of COVID-19 infection in the general population. The present study utilized an integrated social cognition model to explain COVID-19 preventive behaviours in a sample from the Iranian general population. DESIGN: The study adopted a three-wave prospective correlational design. METHODS: Members of the general public (N = 1,718, Mage = 33.34, SD = 15.77, male = 796, female = 922) agreed to participate in the study. Participants completed self-report measures of demographic characteristics, intention, attitude, subjective norm, perceived behavioural control, and action self-efficacy at an initial data collection occasion. One week later, participants completed self-report measures of maintenance self-efficacy, action planning and coping planning, and, a further week later, measures of COVID-19 preventive behaviours. Hypothesized relationships among social cognition constructs and COVID-19 preventive behaviours according to the proposed integrated model were estimated using structural equation modelling. RESULTS: The proposed model fitted the data well according to multiple goodness-of-fit criteria. All proposed relationships among model constructs were statistically significant. The social cognition constructs with the largest effects on COVID-19 preventive behaviours were coping planning (β = .575, p < .001) and action planning (β = .267, p < .001). CONCLUSIONS: Current findings may inform the development of behavioural interventions in health care contexts by identifying intervention targets. In particular, findings suggest targeting change in coping planning and action planning may be most effective in promoting participation in COVID-19 preventive behaviours. Statement of contribution What is already known on this subject? Curbing COVID-19 infections globally is vital to reduce severe cases and deaths in at-risk groups. Preventive behaviours like handwashing and social distancing can stem contagion of the coronavirus. Identifying modifiable correlates of COVID-19 preventive behaviours is needed to inform intervention. What does this study add? An integrated model identified predictors of COVID-19 preventive behaviours in Iranian residents. Prominent predictors were intentions, planning, self-efficacy, and perceived behavioural control. Findings provide insight into potentially modifiable constructs that interventions can target. Research should examine if targeting these factors lead to changes in COVID-19 behaviours over time.
TL;DR: Investigation of the levels of selected antibiotics in four wastewater treatment plants and the receiving water bodies found a medium to high risk of antibiotic resistance developing within the study areas, indicating risk mitigation and prevention strategies are a matter of priority in the affected areas.
TL;DR: In this paper, the authors surveyed teachers' attitudes towards children with special educational needs (SEN) and found that positive teacher attitudes are essential for success when children with SEN are placed into mainstream classrooms.
Abstract: Positive teacher attitudes are essential for success when children with special educational needs (SEN) are placed into mainstream classrooms. The present study surveyed teachers’ attitudes towards...
TL;DR: In this article, the authors show global uniqueness in the fractional Calderon problem with a single measurement and with data on arbitrary disjoint subsets of the exterior, and give a constructive procedure for determining an unknown potential from a single exterior measurement, based on constructive versions of the unique continuation result.
TL;DR: Using a relativized diquark model Hamiltonian, the masses of ground-state tetraquarks in the following systems were calculated in this paper, where they were compared to the experimental data for fully-heavy three-quark systems.
Abstract: Using a relativized diquark model Hamiltonian, we calculate the masses of $$J^{PC}=0^{++}$$
ground-state tetraquarks in the following systems: $$b s {\bar{b}} {\bar{s}}$$
, $$bb {\bar{n}} {\bar{n}}$$
(
$$n=u, d$$
), $$bb {\bar{s}} {\bar{s}}$$
, $$cc{\bar{c}} {\bar{c}}$$
, $$b b {\bar{b}} {\bar{b}}$$
, $$b c{\bar{b}} {\bar{c}}$$
and $$b b {\bar{c}} {\bar{c}}$$
. We also compute extensive spectra for the fully-heavy quark flavour combinations. Finally, as a test of the diquark model approach, we compute the masses of fully-heavy baryons in the diquark model. Our results may be compared soon to the forthcoming experimental data for fully-heavy three-quark systems.
Neuroscience Research Australia1, University of New South Wales2, Johns Hopkins University3, Peking University4, The George Institute for Global Health5, Icahn School of Medicine at Mount Sinai6, University of Oulu7, Fukuoka University8, University of Pittsburgh9, Leiden University10, University of Sheffield11, Maastricht University12, University of Cambridge13, University of California, Irvine14, University of Florida15, University of Alberta16, University of Amsterdam17, Trinity College, Dublin18, University of Calgary19, Newcastle University20, University of Bristol21, University of Jyväskylä22, University of Eastern Finland23, University of Waterloo24, Radboud University Nijmegen25, National University of Singapore26, Dalhousie University27, University of Gothenburg28, Katholieke Universiteit Leuven29, University of Adelaide30, University of Bordeaux31, Australian National University32, University of Warwick33
TL;DR: The findings support clinical freedom in the selection of antihypertensive regimens to achieve blood pressure goals and found no relationship by class with incident cognitive decline or dementia among those aged >65 years.
Abstract: Objective High blood pressure is one of the main modifiable risk factors for dementia. However, there is conflicting evidence regarding the best antihypertensive class for optimizing cognition. Our objective was to determine whether any particular antihypertensive class was associated with a reduced risk of cognitive decline or dementia using comprehensive meta-analysis including reanalysis of original participant data. Methods To identify suitable studies, MEDLINE, Embase, and PsycINFO and preexisting study consortia were searched from inception to December 2017. Authors of prospective longitudinal human studies or trials of antihypertensives were contacted for data sharing and collaboration. Outcome measures were incident dementia or incident cognitive decline (classified using the reliable change index method). Data were separated into mid and late-life (>65 years) and each antihypertensive class was compared to no treatment and to treatment with other antihypertensives. Meta-analysis was used to synthesize data. Results Over 50,000 participants from 27 studies were included. Among those aged >65 years, with the exception of diuretics, we found no relationship by class with incident cognitive decline or dementia. Diuretic use was suggestive of benefit in some analyses but results were not consistent across follow-up time, comparator group, and outcome. Limited data precluded meaningful analyses in those ≤65 years of age. Conclusion Our findings, drawn from the current evidence base, support clinical freedom in the selection of antihypertensive regimens to achieve blood pressure goals. Clinical trials registration The review was registered with the international prospective register of systematic reviews (PROSPERO), registration number CRD42016045454.
TL;DR: In this article, the effects of personalization and hedonic motivation on customer experience and its loyalty outcomes in omnichannel retail context were examined and the results provided both theoretical and managerial insights for improved CX and customer loyalty.
TL;DR: Findings highlight the importance of subjective norm, moral obligation, and PBC as determinants of social distancing intention and intention and habit as behavioral determinants.
Abstract: BACKGROUND: Social distancing is a key behavior to minimize COVID-19 infections. Identification of potentially modifiable determinants of social distancing behavior may provide essential evidence to inform social distancing behavioral interventions. PURPOSE: The current study applied an integrated social cognition model to identify the determinants of social distancing behavior, and the processes involved, in the context of the COVID-19 pandemic. METHODS: In a prospective correlational survey study, samples of Australian (N = 365) and U.S. (N = 440) residents completed online self-report measures of social cognition constructs (attitude, subjective norm, moral norm, anticipated regret, and perceived behavioral control [PBC]), intention, action planning, habit, and past behavior with respect to social distancing behavior at an initial occasion. Follow-up measures of habit and social distancing behavior were taken 1 week later. RESULTS: Structural equation models indicated that subjective norm, moral norm, and PBC were consistent predictors of intention in both samples. Intention, action planning, and habit at follow-up were consistent predictors of social distancing behavior in both samples. Action planning did not have consistent effects mediating or moderating the intention-behavior relationship. Inclusion of past behavior in the model attenuated effects among constructs, although the effects of the determinants of intention and behavior remained. CONCLUSIONS: Current findings highlight the importance of subjective norm, moral obligation, and PBC as determinants of social distancing intention and intention and habit as behavioral determinants. Future research on long-range predictors of social distancing behavior and reciprocal effects in the integrated model is warranted.
Abstract: Although parental burnout can have detrimental consequences to families, the investigation of the syndrome is still in its infancy. The present study investigated what are the key family background variables that contribute to parental burnout among Finnish parents. Moreover, we investigated how self-oriented and socially prescribed perfectionism uniquely and interactively relate to parental burnout over and above the impacts of background variables. Questionnaire-based data was collected from 1725 parents (91% mothers) and analyzed using structural equation modeling (SEM). The results showed that when several family- and child-related background variables were taken into account, parent’s age, unemployment, perceived poor financial situation of the family, and having a child with special needs, showed unique associations with burning out as a parent. Even more crucial risk factor for burning out was, however, socially prescribed perfectionism: the higher the level of socially prescribed perfectionism the parents reported, the higher the level of their parental burnout. The relationship between socially prescribed perfectionism and parental burnout was further strengthened when parents reported also a high level of self-oriented perfectionism. Finally, the relationship between gender and parental burnout was mediated via perfectionism: mothers reported more socially prescribed and self-oriented perfectionism than fathers and, consequently, were also more burned out as parents. The results suggest that in Finland specific attention should be given to families with poor financial resources and unemployment. Moreover, high social expectations experienced by the mothers could be balanced, for example, by teaching them skills of self-acceptance and compassion.
TL;DR: The Calderon problem for the fractional Schrodinger equation has been shown to enjoy logarithmic stability under suitable a priori bounds for potentials in scale-invariant L p or negative order Sobolev spaces.
Abstract: The Calderon problem for the fractional Schrodinger equation was introduced in the work Ghosh et al. (to appear) which gave a global uniqueness result also in the partial data case. This article improves this result in two ways. First, we prove a quantitative uniqueness result showing that this inverse problem enjoys logarithmic stability under suitable a priori bounds. Second, we show that the results are valid for potentials in scale-invariant L p or negative order Sobolev spaces. A key point is a quantitative approximation property for solutions of fractional equations, obtained by combining a careful propagation of smallness analysis for the Caffarelli–Silvestre extension and a duality argument.
TL;DR: The sensitivity of the Deep Underground Neutrino Experiment (DUNE) to neutrino oscillation is determined, based on a full simulation, reconstruction, and event selection of the far detector and full simulation and parameterized analysis of the near detector as mentioned in this paper.
Abstract: The sensitivity of the Deep Underground Neutrino Experiment (DUNE) to neutrino oscillation is determined, based on a full simulation, reconstruction, and event selection of the far detector and a full simulation and parameterized analysis of the near detector. Detailed uncertainties due to the flux prediction, neutrino interaction model, and detector effects are included. DUNE will resolve the neutrino mass ordering to a precision of 5σ, for all δCP values, after 2 years of running with the nominal detector design and beam configuration. It has the potential to observe charge-parity violation in the neutrino sector to a precision of 3σ (5σ) after an exposure of 5 (10) years, for 50% of all δCP values. It will also make precise measurements of other parameters governing long-baseline neutrino oscillation, and after an exposure of 15 years will achieve a similar sensitivity to sin 22 θ13 to current reactor experiments.
TL;DR: In this paper, the authors show global uniqueness in an inverse problem for the fractional Schrodinger equation, where an unknown potential in a bounded domain is uniquely determined by exterior measurements of solutions.
Abstract: We show global uniqueness in an inverse problem for the fractional Schrodinger equation: an unknown potential in a bounded domain is uniquely determined by exterior measurements of solutions. We also show global uniqueness in the partial data problem where measurements are taken in arbitrary open, possibly disjoint, subsets of the exterior. The results apply in any dimension ≥1 and are based on a strong approximation property of the fractional equation that extends earlier work. This special feature of the nonlocal equation renders the analysis of related inverse problems radically different from the traditional Calderon problem.
TL;DR: The global repositioning of lipid-related risk, with non-optimal cholesterol shifting from a distinct feature of high-income countries in northwestern Europe, north America and Australasia to one that affects countries in east and southeast Asia and Oceania should motivate the use of population-based policies and personal interventions to improve nutrition and enhance access to treatment throughout the world.
Abstract: High blood cholesterol is typically considered a feature of wealthy western countries1,2. However, dietary and behavioural determinants of blood cholesterol are changing rapidly throughout the world3 and countries are using lipid-lowering medications at varying rates. These changes can have distinct effects on the levels of high-density lipoprotein (HDL) cholesterol and non-HDL cholesterol, which have different effects on human health4,5. However, the trends of HDL and non-HDL cholesterol levels over time have not been previously reported in a global analysis. Here we pooled 1,127 population-based studies that measured blood lipids in 102.6 million individuals aged 18 years and older to estimate trends from 1980 to 2018 in mean total, non-HDL and HDL cholesterol levels for 200 countries. Globally, there was little change in total or non-HDL cholesterol from 1980 to 2018. This was a net effect of increases in low- and middle-income countries, especially in east and southeast Asia, and decreases in high-income western countries, especially those in northwestern Europe, and in central and eastern Europe. As a result, countries with the highest level of non-HDL cholesterol—which is a marker of cardiovascular risk—changed from those in western Europe such as Belgium, Finland, Greenland, Iceland, Norway, Sweden, Switzerland and Malta in 1980 to those in Asia and the Pacific, such as Tokelau, Malaysia, The Philippines and Thailand. In 2017, high non-HDL cholesterol was responsible for an estimated 3.9 million (95% credible interval 3.7 million–4.2 million) worldwide deaths, half of which occurred in east, southeast and south Asia. The global repositioning of lipid-related risk, with non-optimal cholesterol shifting from a distinct feature of high-income countries in northwestern Europe, north America and Australasia to one that affects countries in east and southeast Asia and Oceania should motivate the use of population-based policies and personal interventions to improve nutrition and enhance access to treatment throughout the world.