Showing papers by "University of Massachusetts Boston published in 2020"

Universal interferometric signatures of a black hole’s photon ring

Abstract: The Event Horizon Telescope image of the supermassive black hole in the galaxy M87 is dominated by a bright, unresolved ring. General relativity predicts that embedded within this image lies a thin “photon ring,” which is composed of an infinite sequence of self-similar subrings that are indexed by the number of photon orbits around the black hole. The subrings approach the edge of the black hole “shadow,” becoming exponentially narrower but weaker with increasing orbit number, with seemingly negligible contributions from high-order subrings. Here, we show that these subrings produce strong and universal signatures on long interferometric baselines. These signatures offer the possibility of precise measurements of black hole mass and spin, as well as tests of general relativity, using only a sparse interferometric array.

Gene Content Evolution in the Arthropods

Abstract: Arthropods comprise the largest and most diverse phylum on Earth and play vital roles in nearly every ecosystem. Their diversity stems in part from variations on a conserved body plan, resulting from and recorded in adaptive changes in the genome. Dissection of the genomic record of sequence change enables broad questions regarding genome evolution to be addressed, even across hyper-diverse taxa within arthropods. Using 76 whole genome sequences representing 21 orders spanning more than 500 million years of arthropod evolution, we document changes in gene and protein domain content and provide temporal and phylogenetic context for interpreting these innovations. We identify many novel gene families that arose early in the evolution of arthropods and during the diversification of insects into modern orders. We reveal unexpected variation in patterns of DNA methylation across arthropods and examples of gene family and protein domain evolution coincident with the appearance of notable phenotypic and physiological adaptations such as flight, metamorphosis, sociality, and chemoperception. These analyses demonstrate how large-scale comparative genomics can provide broad new insights into the genotype to phenotype map and generate testable hypotheses about the evolution of animal diversity.

Addressing the Consequences of School Closure Due to COVID-19 on Children's Physical and Mental Well-Being.

Abstract: Prolonged school closures are one of the most disruptive forces in the COVID-19 era. School closures have upended life for children and families, and educators have been forced to determine how to provide distance learning. Schools are also an essential source of nonacademic supports in the way of health and mental health services, food assistance, obesity prevention, and intervention in cases of homelessness and maltreatment. This article focuses on the physical and emotional toll resulting from school closures and the withdrawal of nonacademic supports that students rely on. The COVID-19 pandemic is shining a spotlight on how important schools are for meeting children's nonacademic needs. We argue that when students return to school there will be a more acute and wider-spread need for school-based nonacademic services and supports. Further, we expect that COVID-19 will serve as a focusing event opening a window of opportunity for programmatic and policy change that improves nonacademic services and supports in the future.

Quantifying sources of variability in infancy research using the infant-directed-speech preference

Abstract: Psychological scientists have become increasingly concerned with issues related to methodology and replicability, and infancy researchers in particular face specific challenges related to replicability: For example, high-powered studies are difficult to conduct, testing conditions vary across labs, and different labs have access to different infant populations. Addressing these concerns, we report on a large-scale, multisite study aimed at (a) assessing the overall replicability of a single theoretically important phenomenon and (b) examining methodological, cultural, and developmental moderators. We focus on infants’ preference for infant-directed speech (IDS) over adult-directed speech (ADS). Stimuli of mothers speaking to their infants and to an adult in North American English were created using seminaturalistic laboratory-based audio recordings. Infants’ relative preference for IDS and ADS was assessed across 67 laboratories in North America, Europe, Australia, and Asia using the three common methods for measuring infants’ discrimination (head-turn preference, central fixation, and eye tracking). The overall meta-analytic effect size (Cohen’s d) was 0.35, 95% confidence interval = [0.29, 0.42], which was reliably above zero but smaller than the meta-analytic mean computed from previous literature (0.67). The IDS preference was significantly stronger in older children, in those children for whom the stimuli matched their native language and dialect, and in data from labs using the head-turn preference procedure. Together, these findings replicate the IDS preference but suggest that its magnitude is modulated by development, native-language experience, and testing procedure.

Electrically injected GeSn lasers on Si operating up to 100 K

Abstract: Monolithic lasers on Si have long been anticipated as an enabler of full photonic integration, and significant progress in GeSn material development shows promise for such laser devices. While there are many reports focused on optically pumped lasers, in this work, we demonstrate electrically injected GeSn lasers on Si. We grew a GeSn/SiGeSn heterostructure diode on a Si substrate in a ridge waveguide laser device and tested it under pulsed conditions, giving consideration to the structure design to enhance the carrier and optical confinement. The peak linewidth of 0.13 nm (0.06 meV) and injection current curves indicated lasing, which was observed up to 100 K with emission peaks at 2300 nm. We recorded a threshold of 598A/cm2 at 10 K. The peak power and external quantum efficiency were 2.7 mW/facet and 0.3%, respectively. The results indicate advances for group-IV-based lasers, which could serve as a promising route for laser integration on Si.

Bereavement in the Time of Coronavirus: Unprecedented Challenges Demand Novel Interventions.

Abstract: COVID-19 fatalities exemplify "bad deaths" and are distinguished by physical discomfort, difficulty breathing, social isolation, psychological distress, and care that may be discordant with the patient's preferences. Each of these death attributes is a well-documented correlate of bereaved survivors' symptoms of depression, anxiety, and anger. Yet the grief experienced by survivors of COVID-related deaths is compounded by the erosion of coping resources like social support, contemporaneous stressors including social isolation, financial precarity, uncertainty about the future, lack of routine, and the loss of face-to-face mourning rituals that provide a sense of community and uplift. National efforts to enhance advance care planning may help dying patients to receive care that is concordant with the preferences of them and their families. Virtual funeral services, pairing bereaved elders with a telephone companion, remote counseling, and encouraging "continuing bonds" may help older adults adapt to loss in the time of pandemic.

A Randomized Trial of a Multifactorial Strategy to Prevent Serious Fall Injuries

Abstract: Background Injuries from falls are major contributors to complications and death in older adults. Despite evidence from efficacy trials that many falls can be prevented, rates of falls res...

Frequency and Types of Patient-Reported Errors in Electronic Health Record Ambulatory Care Notes.

Abstract: Importance As health information transparency increases, patients more often seek their health data. More than 44 million patients in the US can now readily access their ambulatory visit notes online, and the practice is increasing abroad. Few studies have assessed documentation errors that patients identify in their notes and how these may inform patient engagement and safety strategies. Objective To assess the frequency and types of errors identified by patients who read open ambulatory visit notes. Design, Setting, and Participants In this survey study, a total of 136 815 patients at 3 US health care organizations with open notes, including 79 academic and community ambulatory care practices, received invitations to an online survey from June 5 to October 20, 2017. Patients who had at least 1 ambulatory note and had logged onto the portal at least once in the past 12 months were included. Data analysis was performed from July 3, 2018, to April 27, 2020. Exposures Access to ambulatory care open notes through patient portals for up to 7 years (2010-2017). Main Outcomes and Measures Proportion of patients reporting a mistake and how serious they perceived the mistake to be, factors associated with finding errors characterized by patients as serious, and categories of patient-reported errors. Results Of 136 815 patients who received survey invitations, 29 656 (21.7%) responded and 22 889 patients (mean [SD] age, 55.16 [15.96] years; 14 447 [63.1%] female; 18 301 [80.0%] white) read 1 or more notes in the past 12 months and completed error questions. Of these patients, 4830 (21.1%) reported a perceived mistake and 2043 (42.3%) reported that the mistake was serious (somewhat serious: 1563 [32.4%]; very serious: 480 [9.9%]). In multivariable analysis, female patients (relative risk [RR], 1.79; 95% CI, 1.72-1.85), more educated patients (RR, 1.38; 95% CI, 1.29-1.48), sicker patients (RR, 1.89; 95% CI, 1.84-1.94), those aged 45 to 64 years (RR, 2.23; 95% CI, 2.06-2.42), those 65 years or older (RR, 2.00; 95% CI, 1.73-2.32), and those who read more than 1 note (2-3 notes: RR, 1.82; 95% CI, 1.34-2.47; ≥4 notes: RR, 3.09; 95% CI, 2.02-4.73) were more likely to report a mistake that they found to be serious compared with their reference groups. After categorization of patient-reported very serious mistakes, those specifically mentioning the worddiagnosisor describing a specific error in current or past diagnoses were most common (98 of 356 [27.5%]), followed by inaccurate medical history (85 of 356 [23.9%]), medications or allergies (50 of 356 [14.0%]), and tests, procedures, or results (30 of 356 [8.4%]). A total of 23 (6.5%) reflected notes reportedly written on the wrong patient. Of 433 very serious errors, 255 (58.9%) included at least 1 perceived error potentially associated with the diagnostic process (eg, history, physical examination, tests, referrals, and communication). Conclusions and Relevance In this study, patients who read ambulatory notes online perceived mistakes, a substantial proportion of which they found to be serious. Older and sicker patients were twice as likely to report a serious error compared with younger and healthier patients, indicating important safety and quality implications. Sharing notes with patients may help engage them to improve record accuracy and health care safety together with practitioners.

Electronic-photonic arithmetic logic unit for high-speed computing

Abstract: The past two decades have witnessed the stagnation of the clock speed of microprocessors followed by the recent faltering of Moore’s law as nanofabrication technology approaches its unavoidable physical limit. Vigorous efforts from various research areas have been made to develop power-efficient and ultrafast computing machines in this post-Moore’s law era. With its unique capacity to integrate complex electro-optic circuits on a single chip, integrated photonics has revolutionized the interconnects and has shown its striking potential in optical computing. Here, we propose an electronic-photonic computing architecture for a wavelength division multiplexing-based electronic-photonic arithmetic logic unit, which disentangles the exponential relationship between power and clock rate, leading to an enhancement in computation speed and power efficiency as compared to the state-of-the-art transistors-based circuits. We experimentally demonstrate its practicality by implementing a 4-bit arithmetic logic unit consisting of 8 high-speed microdisk modulators and operating at 20 GHz. This approach paves the way to future power-saving and high-speed electronic-photonic computing circuits. Integrated photonics allows integration of complex optical circuits on a single chip. Here, the authors propose a wavelength division multiplexing based electronic-photonic arithmetic logic unit for computing at high speeds and with improved power consumption to help with the physical limits of Moore’s law.

Multicriteria Decision Framework for Cybersecurity Risk Assessment and Management

Abstract: Risk assessors and managers face many difficult challenges related to novel cyber systems. Among these challenges are the constantly changing nature of cyber systems caused by technical advances, their distribution across the physical, information, and sociocognitive domains, and the complex network structures often including thousands of nodes. Here, we review probabilistic and risk-based decision-making techniques applied to cyber systems and conclude that existing approaches typically do not address all components of the risk assessment triplet (threat, vulnerability, consequence) and lack the ability to integrate across multiple domains of cyber systems to provide guidance for enhancing cybersecurity. We present a decision-analysis-based approach that quantifies threat, vulnerability, and consequences through a set of criteria designed to assess the overall utility of cybersecurity management alternatives. The proposed framework bridges the gap between risk assessment and risk management, allowing an analyst to ensure a structured and transparent process of selecting risk management alternatives. The use of this technique is illustrated for a hypothetical, but realistic, case study exemplifying the process of evaluating and ranking five cybersecurity enhancement strategies. The approach presented does not necessarily eliminate biases and subjectivity necessary for selecting countermeasures, but provides justifiable methods for selecting risk management actions consistent with stakeholder and decisionmaker values and technical data.

Transforming knowledge systems for life on Earth: visions of future systems and how to get there

Abstract: Formalised knowledge systems, including universities and research institutes, are important for contemporary societies. They are, however, also arguably failing humanity when their impact is measured against the level of progress being made in stimulating the societal changes needed to address challenges like climate change. In this research we used a novel futures-oriented and participatory approach that asked what future envisioned knowledge systems might need to look like and how we might get there. Findings suggest that envisioned future systems will need to be much more collaborative, open, diverse, egalitarian, and able to work with values and systemic issues. They will also need to go beyond producing knowledge about our world to generating wisdom about how to act within it. To get to envisioned systems we will need to rapidly scale methodological innovations, connect innovators, and creatively accelerate learning about working with intractable challenges. We will also need to create new funding schemes, a global knowledge commons, and challenge deeply held assumptions. To genuinely be a creative force in supporting longevity of human and non-human life on our planet, the shift in knowledge systems will probably need to be at the scale of the enlightenment and speed of the scientific and technological revolution accompanying the second World War. This will require bold and strategic action from governments, scientists, civic society and sustained transformational intent.

Older Adults and the Economic Impact of the COVID-19 Pandemic.

Abstract: The COVID-19 pandemic has impacted communities throughout the United States and worldwide. While the implications of the concomitant economic downturn for older adults are just beginning to be recognized, past experience suggests that the consequences could be devastating for many. Analyses indicate that more than one out of five Americans aged 65 years or older live in counties where high infection rates and high economic insecurity risks occur simultaneously. These findings highlight the overlap between current infection patterns and subsequent challenges to economic security that are impacting older people. Strategies and supports for getting people back to work must take into account the large segment of older people who rely on earnings well into later life. Social Security serves as the foundation of economic security for older adults across the income continuum, but it is frequently insufficient in and of itself, let alone during a crisis. Recognizing the importance of cost of living in shaping economic security highlights the need for the federal and state governments and municipalities to take older people into account in the economic recovery effort.

Time–information uncertainty relations in thermodynamics

Abstract: Physical systems powering motion and creating structure in a fixed amount of time dissipate energy and produce entropy. Whether living, synthetic or engineered, systems performing these dynamic functions must balance dissipation and speed. Here, we show that rates of energy and entropy exchange are subject to a speed limit—a time–information uncertainty relation—imposed by the rates of change in the information content of the system. This uncertainty relation bounds the time that elapses before the change in a thermodynamic quantity has the same magnitude as its s.d. From this general bound, we establish a family of speed limits for heat, dissipated/chemical work and entropy depending on the experimental constraints on the system and its environment. In all of these inequalities, the timescale of transient dynamical fluctuations is universally bounded by the Fisher information. Moreover, they all have a mathematical form that mirrors the Mandelstam–Tamm version of the time–energy uncertainty relation in quantum mechanics. These bounds on the speed of arbitrary observables apply to transient systems away from thermodynamic equilibrium, independent of the physical constraints on the stochastic dynamics or their function. A time–information uncertainty relation in thermodynamics has been derived, analogous to the time–energy uncertainty relation in quantum mechanics, imposing limits on the speed of energy and entropy exchange between a system and external reservoirs.

COVID-19 Interconnectedness: Health Inequity, the Climate Crisis, and Collective Trauma.

Abstract: The COVID-19 pandemic brings to the forefront the complex interconnected dilemmas of globalization, health equity, economic security, environmental justice, and collective trauma, severely impacting the marginalized and people of color in the United States This lack of access to and the quality of healthcare, affordable housing, and lack of financial resources also continue to have a more significant impact on documented and undocumented immigrants This paper aims at examining these critical issues and developing a framework for family therapists to address these challenges by focusing on four interrelated dimensions: cultural values, social determinants of health, collective trauma, and the ethical and moral responsibility of family therapists Given the fact that family therapists may unwittingly function as the best ally of an economic and political system that perpetuates institutionalized racism and class discrimination, we need to utilize a set of principles, values, and practices that are not just palliative or after the fact but bring forth into the psychotherapeutic and policy work a politics of care Therefore, a strong call to promote and advocate for the broader continuum of health and critical thinking preparing professionals to meet the challenges of health equity, as well as economic and environmental justice, is needed The issues discussed in this paper are specific to the United States despite their relevance to family therapy as a field We are mindful not to generalize the United States' reality to the rest of the world, recognizing that issues discussed in this paper could potentially contribute to international discourse

Parallel selection on thermal physiology facilitates repeated adaptation of city lizards to urban heat islands.

Abstract: Only recently have we begun to understand the ecological and evolutionary effects of urbanization on species, with studies revealing drastic impacts on community composition, gene flow, behaviour, morphology and physiology. However, our understanding of how adaptive evolution allows species to persist, and even thrive, in urban landscapes is still nascent. Here, we examine phenotypic, genomic and regulatory impacts of urbanization on a widespread lizard, the Puerto Rican crested anole (Anolis cristatellus). We find that urban lizards endure higher environmental temperatures and display greater heat tolerance than their forest counterparts. A single non-synonymous polymorphism within a protein synthesis gene (RARS) is associated with heat tolerance plasticity within urban heat islands and displays parallel signatures of selection in cities. Additionally, we identify groups of differentially expressed genes between habitats showing elevated genetic divergence in multiple urban-forest comparisons. These genes display evidence of adaptive regulatory evolution within cities and disproportionately cluster within regulatory modules associated with heat tolerance. This study provides evidence of temperature-mediated selection in urban heat islands with repeatable impacts on physiological evolution at multiple levels of biological hierarchy.

The Views and Experiences of Clinicians Sharing Medical Record Notes With Patients.

Abstract: Importance The 21st Century Cures Act of 2016 requires that patients be given electronic access to all the information in their electronic medical records. The regulations for implementation of this law give patients far easier access to information about their care, including the notes their clinicians write. Objective To assess clinicians’ views and experiences with sharing clinical notes (open notes) with patients. Design, Setting, and Participants Web-based survey study of physicians, advanced practice nurses, registered nurses, physician assistants, and therapists at 3 health systems in Boston, Massachusetts; Seattle, Washington; and rural Pennsylvania where notes have been shared across all outpatient specialties for at least 4 years. Participants were clinicians in hospital-based offices and community practices who had written at least 1 note opened by a patient in the year prior to the survey, which was administered from May 21, 2018, to August 31, 2018. Main Outcomes and Measures Clinicians’ experiences with and perceptions of sharing clinical notes with patients. Results Invitations were sent to 6064 clinicians; 1628 (27%) responded. Respondents were more likely than nonrespondents to be female (65% vs 55%) and to be younger (mean [SD] age, 42.1 [12.6] vs 44.9 [12.7] years). The majority of respondents were physicians (951 [58%]), female (1023 [65%]), licensed to practice in 2000 or later (940 [61%]), and spent fewer than 40 hours per week in direct patient care (1083 [71%]). Most viewed open notes positively, agreeing they are a good idea (1182 participants [74%]); of 1314 clinicians who were aware that patients were reading their notes, 965 (74%) agreed that open notes were useful for engaging patients. In all, 798 clinicians (61%) would recommend the practice to colleagues. A total of 292 physicians (37%) reported spending more time on documentation, and many reported specific changes in the way they write their notes, the most frequent of which related to use of language that could be perceived as critical of the patient (422 respondents [58%]). Most physicians (1234 [78%]) favored being able to determine readily that their notes had been read by their patients. Conclusions and Relevance In this survey of clinicians in a wide range of specialties who had several years of experience offering their patients ready access to their notes, more than two-thirds supported this new practice. Even among subgroups of clinicians who were less enthusiastic, most endorsed the idea of sharing notes and believed the practice could be helpful for engaging patients more actively in their care.

Deep learning-based cross-classifications reveal conserved spatial behaviors within tumor histological images

Abstract: Histopathological images are a rich but incompletely explored data type for studying cancer. Manual inspection is time consuming, making it challenging to use for image data mining. Here we show that convolutional neural networks (CNNs) can be systematically applied across cancer types, enabling comparisons to reveal shared spatial behaviors. We develop CNN architectures to analyze 27,815 hematoxylin and eosin scanned images from The Cancer Genome Atlas for tumor/normal, cancer subtype, and mutation classification. Our CNNs are able to classify TCGA pathologist-annotated tumor/normal status of whole slide images (WSIs) in 19 cancer types with consistently high AUCs (0.995 ± 0.008), as well as subtypes with lower but significant accuracy (AUC 0.87 ± 0.1). Remarkably, tumor/normal CNNs trained on one tissue are effective in others (AUC 0.88 ± 0.11), with classifier relationships also recapitulating known adenocarcinoma, carcinoma, and developmental biology. Moreover, classifier comparisons reveal intra-slide spatial similarities, with an average tile-level correlation of 0.45 ± 0.16 between classifier pairs. Breast cancers, bladder cancers, and uterine cancers have spatial patterns that are particularly easy to detect, suggesting these cancers can be canonical types for image analysis. Patterns for TP53 mutations can also be detected, with WSI self- and cross-tissue AUCs ranging from 0.65-0.80. Finally, we comparatively evaluate CNNs on 170 breast and colon cancer images with pathologist-annotated nuclei, finding that both cellular and intercellular regions contribute to CNN accuracy. These results demonstrate the power of CNNs not only for histopathological classification, but also for cross-comparisons to reveal conserved spatial behaviors across tumors.

Fluctuations in Extractable Work Bound the Charging Power of Quantum Batteries

Abstract: We study the connection between the charging power of quantum batteries and the fluctuations of the extractable work. We prove that in order to have a nonzero rate of change of the extractable work, the state ${\ensuremath{\rho}}_{\mathcal{W}}$ of the battery cannot be an eigenstate of a ``free energy operator,'' defined by $\mathcal{F}\ensuremath{\equiv}{H}_{\mathcal{W}}+{\ensuremath{\beta}}^{\ensuremath{-}1}\mathrm{log}({\ensuremath{\rho}}_{\mathcal{W}})$, where ${H}_{\mathcal{W}}$ is the Hamiltonian of the battery and $\ensuremath{\beta}$ is the inverse temperature of a reference thermal bath with respect to which the extractable work is calculated. We do so by proving that fluctuations in the free energy operator upper bound the charging power of a quantum battery. Our findings also suggest that quantum coherence in the battery enhances the charging process, which we illustrate on a toy model of a heat engine.

A consensus-based transparency checklist

Abstract: We present a consensus-based checklist to improve and document the transparency of research reports in social and behavioural research. An accompanying online application allows users to complete the form and generate a report that they can submit with their manuscript or post to a public repository.

Caregiver Influences on Eating Behaviors in Young Children: A Scientific Statement From the American Heart Association.

Abstract: A substantial body of research suggests that efforts to prevent pediatric obesity may benefit from targeting not just what a child eats, but how they eat. Specifically, child obesity prevention should include a component that addresses reasons why children have differing abilities to start and stop eating in response to internal cues of hunger and satiety, a construct known as eating self‐regulation. This review summarizes current knowledge regarding how caregivers can be an important influence on children's eating self‐regulation during early childhood. First, we discuss the evidence supporting an association between caregiver feeding and child eating self‐regulation. Second, we discuss what implications the current evidence has for actions caregivers may be able to take to support children's eating self‐regulation. Finally, we consider the broader social, economic, and cultural context around the feeding environment relationship and how this intersects with the implementation of any actions. As far as we are aware, this is the first American Heart Association (AHA) scientific statement to focus on a psychobehavioral approach to reducing obesity risk in young children. It is anticipated that the timely information provided in this review can be used not only by caregivers within the immediate and extended family but also by a broad range of community‐based care providers.

Deep learning-based cross-classifications reveal conserved spatial behaviors within tumor histological images

Abstract: Histopathological images are a rich but incompletely explored data type for studying cancer. Manual inspection is time consuming, making it challenging to use for image data mining. Here we show that convolutional neural networks (CNNs) can be systematically applied across cancer types, enabling comparisons to reveal shared spatial behaviors. We develop CNN architectures to analyze 27,815 hematoxylin and eosin slides from The Cancer Genome Atlas for tumor/normal, cancer subtype, and mutation classification. Our CNNs are able to classify tumor/normal status of whole slide images (WSIs) in 19 cancer types with consistently high AUCs (0.995±0.008), as well as subtypes with lower but significant accuracy (AUC 0.87±0.1). Remarkably, tumor/normal CNNs trained on one tissue are effective in others (AUC 0.88±0.11), with classifier relationships also recapitulating known adenocarcinoma, carcinoma, and developmental biology. Moreover, classifier comparisons reveal intra-slide spatial similarities, with average tile-level correlation of 0.45±0.16 between classifier pairs. Breast cancers, bladder cancers, and uterine cancers have spatial patterns that are particularly easy to detect, suggesting these cancers can be canonical types for image analysis. Patterns for TP53 mutations can also be detected, with WSI self- and cross-tissue AUCs ranging from 0.65-0.80. Finally, we comparatively evaluate CNNs on 170 breast and colon cancer images with pathologist-annotated nuclei, finding that both cellular and intercellular regions contribute to CNN accuracy. These results demonstrate the power of CNNs not only for histopathological classification, but also for cross-comparisons to reveal conserved spatial biology.

Multi-Source Causal Feature Selection

Abstract: Causal feature selection has attracted much attention in recent years, as the causal features selected imply the causal mechanism related to the class attribute, leading to more reliable prediction models built using them. Currently there is a need of developing multi-source feature selection methods, since in many applications data for studying the same problem has been collected from various sources, such as multiple gene expression datasets obtained from different experiments for studying the causes of the same disease. However, the state-of-the-art causal feature selection methods generally tackle a single dataset, and a direct application of the methods to multiple datasets will result in unreliable results as the datasets may have different distributions. To address the challenges, by utilizing the concept of causal invariance in causal inference, we first formulate the problem of causal feature selection with multiple datasets as a search problem for an invariant set across the datasets, then give the upper and lower bounds of the invariant set, and finally we propose a new M ulti-source C ausal F eature S election algorithm, MCFS. Using synthetic and real world datasets and 16 feature selection methods, the extensive experiments have validated the effectiveness of MCFS.

Protecting and Improving the Lives of Older Adults in the COVID-19 Era.

Abstract: The COVID-19 pandemic has impacted the lives of people throughout the world, either directly, due to exposure to the virus, or indirectly, due to measures taken to mitigate the virus' effects Older adults have been particularly hard hit, dying in disproportionately higher numbers, especially in long-term care facilities Local, regional, and national government actions taken to mitigate the spread of COVID-19 have thus served, in part, to shield older adults from the virus, though not without adverse side effects, including increased social isolation, enhanced economic risk, revealed ageism, delayed medical treatment, and challenges getting basic needs met This special issue of the Journal of Aging & Social Policy explores the myriad ways in which the COVID-19 pandemic has affected older adults and their families, caregivers, and communities It proposes policies and strategies for protecting and improving the lives of older people during the pandemic It draws lessons for aging policy and practice more generally, given underlying challenges brought to the fore by government, provider, community, and individual responses to the pandemic

Probing the universality of topological defect formation in a quantum annealer: Kibble-Zurek mechanism and beyond

Abstract: The authors show that the prediction of the universal Kibble-Zurek mechanism for an open quantum system reproduces the mean number of topological defects generated in a quantum annealer, providing a benchmark for the latter.