Boston University

About: Boston University is a education organization based out in Boston, Massachusetts, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 48688 authors who have published 119622 publications receiving 6276020 citations. The organization is also known as: BU & Boston U.

Discovering similar multidimensional trajectories

Abstract: We investigate techniques for analysis and retrieval of object trajectories in two or three dimensional space. Such data usually contain a large amount of noise, that has made previously used metrics fail. Therefore, we formalize non-metric similarity functions based on the longest common subsequence (LCSS), which are very robust to noise and furthermore provide an intuitive notion of similarity between trajectories by giving more weight to similar portions of the sequences. Stretching of sequences in time is allowed, as well as global translation of the sequences in space. Efficient approximate algorithms that compute these similarity measures are also provided. We compare these new methods to the widely used Euclidean and time warping distance functions (for real and synthetic data) and show the superiority of our approach, especially in the strong presence of noise. We prove a weaker version of the triangle inequality and employ it in an indexing structure to answer nearest neighbor queries. Finally, we present experimental results that validate the accuracy and efficiency of our approach.

Deep CORAL: Correlation Alignment for Deep Domain Adaptation

Abstract: Deep neural networks are able to learn powerful representations from large quantities of labeled input data, however they cannot always generalize well across changes in input distributions. Domain adaptation algorithms have been proposed to compensate for the degradation in performance due to domain shift. In this paper, we address the case when the target domain is unlabeled, requiring unsupervised adaptation. CORAL is a "frustratingly easy" unsupervised domain adaptation method that aligns the second-order statistics of the source and target distributions with a linear transformation. Here, we extend CORAL to learn a nonlinear transformation that aligns correlations of layer activations in deep neural networks (Deep CORAL). Experiments on standard benchmark datasets show state-of-the-art performance.

The Mental Health Consequences of COVID-19 and Physical Distancing: The Need for Prevention and Early Intervention.

Abstract: Since the first case of novel coronavirus disease 2019 (COVID-19) was diagnosed in December 2019, it has swept across the world and galvanized global action. This has brought unprecedented efforts to institute the practice of physical distancing (called in most cases “social distancing”) in countries all over the world, resulting in changes in national behavioral patterns and shutdowns of usual day-to-day functioning. While these steps may be critical to mitigate the spread of this disease, they will undoubtedly have consequences for mental health and well-being in both the short and long term. These consequences are of sufficient importance that immediate efforts focused on prevention and direct intervention are needed to address the impact of the outbreak on individual and population level mental health. The sparse literature on the mental health consequences of epidemics relates more to the sequelae of the disease itself (eg, mothers of children with congenital Zika syndrome) than to social distancing. However, largescale disasters, whether traumatic (eg, the World Trade Center attacks or mass shootings), natural (eg, hurricanes), or environmental (eg, Deepwater Horizon oil spill), are almost always accompanied by increases in depression, posttraumatic stress disorder (PTSD), substance use disorder, a broad range of other mental and behavioral disorders, domestic violence, and child abuse.1 For example, 5% of the population affected by Hurricane Ike in 2008 met the criteria for major depressive disorder in the month after the hurricane; 1 out of 10 adults in New York City showed signs of the disorder in the month following the 9/11 attacks.2,3 And almost 25% of New Yorkers reported increased alcohol use after the attacks.4 Communities affected by the Deepwater Horizon oil spill showed signs of clinically significant depression and anxiety.5 The SARS epidemic was also associated with increases in PTSD, stress, and psychological distress in patients and clinicians.6 For such events, the impact on mental health can occur in the immediate aftermath and then persist over long time periods. In the context of the COVID-19 pandemic, it appears likely that there will be substantial increases in anxiety and depression, substance use, loneliness, and domestic violence; and with schools closed, there is a very real possibility of an epidemic of child abuse. This concern is so significant that the UK has issued psychological first aid guidance from Mental Health UK.7 While the literature is not clear about the science of population level prevention, it leads us to conclude that 3 steps, taken now, can help us proactively prepare for the inevitable increase in mental health conditions and associated sequelae that are the consequences of this pandemic. First, it is necessary to plan for the inevitability of loneliness and its sequelae as populations physically and socially isolate and to develop ways to intervene. The use of digital technologies can bridge social distance, even while physical distancing measures are in place.8 Normal structures where people congregate, whether places of worship, or gyms, and yoga studios, can conduct online activities on a schedule similar to what was in place prior to social distancing. Some workplaces are creating virtual workspace where people can work and connect over video connections, so they are not virtually alone. Employers should ensure that each employee receives daily outreach during the work week, through a supervisor or buddy system, just to maintain social contact. Many observers note that outreach that involves voice and/or video is superior to email and text messaging. Extra efforts should be made to ensure connections with people who are typically marginalized and isolated, including the elderly, undocumented immigrants, homeless persons and those with mental illness. Social media can also be used to encourage groups to connect and direct individuals to trusted resources for mental health support. These platforms can also enhance check-in functions to provide regular contact with individuals as well as to allow people to share with others information about their well-being and resource needs. Even with all of these measures, there will still be segments of the population that are lonely and isolated. This suggests the need for remote approaches for outreach and screening for loneliness and associated mental health conditions so that social support can be provided. Particularly relevant here is the developing and implementing routines, particularly for children who are out of school, ensuring that they have access to regular programmed work. Online substitutes for daily routines, as mentioned above, can be extremely helpful, but not all children have access to technologies that enable remote connectivity. Needed are approaches for ensuring structure, continuity of learning, and socialization to mitigate the effect of shortand long-term sheltering in place. Second, it is critical that we have in place mechanisms for surveillance, reporting, and intervention, particularly, when it comes to domestic violence and child abuse. Individuals at risk for abuse may have limited opportunities to report or seek help when shelter-in-place requirements demand prolonged cohabitation at home and limit travel outside of the home. Systems will need to balance the need for social distancing with the availability of safe places to VIEWPOINT

The Immunological Genome Project: networks of gene expression in immune cells

Abstract: nology is an ideal field for the application of systems approaches, with its detailed descriptions of cell types (over 200 immune cell types are defined in the scope of the Immunological Genome Project (ImmGen)), wealth of reagents and easy access to cells. Thanks to the broad and robust approaches allowed by gene-expression microarrays and related techniques, the transcriptome is probably the only ‘-ome’ that can be reliably tackled in its entirety. Generating a complete perspective of gene expression in the immune system