Indexing the Earth Mover's Distance Using Normal Distributions

Querying uncertain data sets (represented as probability distributions) presents many challenges due to the large amount of data involved and the difficulties comparing uncertainty between distributions. The Earth Mover's Distance (EMD) has increasingly been employed to compare uncertain data due to its ability to effectively capture the differences between two distributions. Computing the EMD entails finding a solution to the transportation problem, which is computationally intensive. In this paper, we propose a new lower bound to the EMD and an index structure to significantly improve the performance of EMD based K-nearest neighbor (K-NN) queries on uncertain databases. We propose a new lower bound to the EMD that approximates the EMD on a projection vector. Each distribution is projected onto a vector and approximated by a normal distribution, as well as an accompanying error term. We then represent each normal as a point in a Hough transformed space. We then use the concept of stochastic dominance to implement an efficient index structure in the transformed space. We show that our method significantly decreases K-NN query time on uncertain databases. The index structure also scales well with database cardinality. It is well suited for heterogeneous data sets, helping to keep EMD based queries tractable as uncertain data sets become larger and more complex.Comment: VLDB201

A Latent Parameter Node-Centric Model for Spatial Networks

Spatial networks, in which nodes and edges are embedded in space, play a vital role in the study of complex systems. For example, many social networks attach geo-location information to each user, allowing the study of not only topological interactions between users, but spatial interactions as well. The defining property of spatial networks is that edge distances are associated with a cost, which may subtly influence the topology of the network. However, the cost function over distance is rarely known, thus developing a model of connections in spatial networks is a difficult task. In this paper, we introduce a novel model for capturing the interaction between spatial effects and network structure. Our approach represents a unique combination of ideas from latent variable statistical models and spatial network modeling. In contrast to previous work, we view the ability to form long/short-distance connections to be dependent on the individual nodes involved. For example, a node's specific surroundings (e.g. network structure and node density) may make it more likely to form a long distance link than other nodes with the same degree. To capture this information, we attach a latent variable to each node which represents a node's spatial reach. These variables are inferred from the network structure using a Markov Chain Monte Carlo algorithm. We experimentally evaluate our proposed model on 4 different types of real-world spatial networks (e.g. transportation, biological, infrastructure, and social). We apply our model to the task of link prediction and achieve up to a 35% improvement over previous approaches in terms of the area under the ROC curve. Additionally, we show that our model is particularly helpful for predicting links between nodes with low degrees. In these cases, we see much larger improvements over previous models

The Relationship Between Disperal Ability and Geographic Range Size

There are a variety of proposed evolutionary and ecological explanations for why some species have more extensive geographical ranges than others. One of the most common explanations is variation in species’ dispersal ability. However, the purported relationship between dispersal distance and range size has been subjected to few theoretical investigations, and empirical tests reach conflicting conclusions. We attempt to reconcile the equivocal results of previous studies by reviewing and synthesizing quantitative dispersal data, examining the relationship between average dispersal ability and range size for different spatial scales, regions and taxonomic groups. We use extensive data from marine taxa whose average dispersal varies by seven orders of magnitude. Our results suggest dispersal is not a general determinant of range size, but can play an important role in some circumstances. We also review the mechanistic theories proposed to explain a positive relationship between range size and dispersal and explore their underlying rationales and supporting or refuting evidence. Despite numerous studies assuming a priori that dispersal influences range size, this is the first comprehensive conceptual evaluation of these ideas. Overall, our results indicate that although dispersal can be an important process moderating species’ distributions, increased attention should be paid to other processes responsible for range size variation

Dynamics of an Acute Coral Disease Outbreak Associated with the Macroalgae \u3cem\u3eDictyota\u3c/em\u3e SPP. in Dry Tortugas National Park, Florida, USA

Reports of coral disease outbreaks have increased in recent decades, but often few details are known about these outbreaks, such as environmental triggers, associated biological variables, or even the precise temporal span of the outbreak. Here we document an acute outbreak of a rapid tissue loss disease on the highest live coral cover (15%–30%) reefs within Dry Tortugas National Park, Florida, USA. This disease exhibited similar signs to white plague disease with the notable exception that a white film often was observed on the recently denuded skeleton. The temporal span of the disease was short (\u3c2 mo). Partial mortality was recorded but there was no detectable impact to overall coral cover. A significant increase and then decrease in the cover of macroalgae, primarily of the genus Dictyota, occurred simultaneously with the increase and drop in disease lesion density (number of lesions per living tissue area), respectively. No other anomalous biological or physical factors (e.g., unusual temperature, turbidity, passage of storms) corresponded with the outbreak, although it is likely that some environmental anomaly that was undetectable with the methods employed favored both disease and Dictyota expansion. This is the first study to associate a rapid increase in a macroalgal population with a coral disease outbreak. We highlight the need for increased study of the initiation of such outbreaks in the caribbean

Improving mental health and psychosocial wellbeing in humanitarian settings: Reflections on research funded through R2HC

From Springer Nature via Jisc Publications RouterMajor knowledge gaps remain concerning the most effective ways to address mental health and psychosocial needs of populations affected by humanitarian crises. The Research for Health in Humanitarian Crisis (R2HC) program aims to strengthen humanitarian health practice and policy through research. As a significant portion of R2HC’s research has focused on mental health and psychosocial support interventions, the program has been interested in strengthening a community of practice in this field. Following a meeting between grantees, we set out to provide an overview of the R2HC portfolio, and draw lessons learned. In this paper, we discuss the mental health and psychosocial support-focused research projects funded by R2HC; review the implications of initial findings from this research portfolio; and highlight four remaining knowledge gaps in this field. Between 2014 and 2019, R2HC funded 18 academic-practitioner partnerships focused on mental health and psychosocial support, comprising 38% of the overall portfolio (18 of 48 projects) at a value of approximately 7.2 million GBP. All projects have focused on evaluating the impact of interventions. In line with consensus-based recommendations to consider a wide range of mental health and psychosocial needs in humanitarian settings, research projects have evaluated diverse interventions. Findings so far have both challenged and confirmed widely-held assumptions about the effectiveness of mental health and psychosocial interventions in humanitarian settings. They point to the importance of building effective, sustained, and diverse partnerships between scholars, humanitarian practitioners, and funders, to ensure long-term program improvements and appropriate evidence-informed decision making. Further research needs to fill knowledge gaps regarding how to: scale-up interventions that have been found to be effective (e.g., questions related to integration across sectors, adaptation of interventions across different contexts, and optimal care systems); address neglected mental health conditions and populations (e.g., elderly, people with disabilities, sexual minorities, people with severe, pre-existing mental disorders); build on available local resources and supports (e.g., how to build on traditional, religious healing and community-wide social support practices); and ensure equity, quality, fidelity, and sustainability for interventions in real-world contexts (e.g., answering questions about how interventions from controlled studies can be transferred to more representative humanitarian contexts).All studies described here were funded by Elrha’s Research for Health in Humanitarian Crises (R2HC) Programme, which aims to improve health outcomes by strengthening the evidence base for public health interventions in humanitarian crises.14pubpu

Improving mental health and psychosocial wellbeing in humanitarian settings: reflections on research funded through R2HC

Major knowledge gaps remain concerning the most effective ways to address mental health and psychosocial needs of populations affected by humanitarian crises. The Research for Health in Humanitarian Crisis (R2HC) program aims to strengthen humanitarian health practice and policy through research. As a significant portion of R2HC’s research has focused on mental health and psychosocial support interventions, the program has been interested in strengthening a community of practice in this field. Following a meeting between grantees, we set out to provide an overview of the R2HC portfolio, and draw lessons learned. In this paper, we discuss the mental health and psychosocial support-focused research projects funded by R2HC; review the implications of initial findings from this research portfolio; and highlight four remaining knowledge gaps in this field. Between 2014 and 2019, R2HC funded 18 academic-practitioner partnerships focused on mental health and psychosocial support, comprising 38% of the overall portfolio (18 of 48 projects) at a value of approximately 7.2 million GBP. All projects have focused on evaluating the impact of interventions. In line with consensus-based recommendations to consider a wide range of mental health and psychosocial needs in humanitarian settings, research projects have evaluated diverse interventions. Findings so far have both challenged and confirmed widely-held assumptions about the effectiveness of mental health and psychosocial interventions in humanitarian settings. They point to the importance of building effective, sustained, and diverse partnerships between scholars, humanitarian practitioners, and funders, to ensure long-term program improvements and appropriate evidence-informed decision making. Further research needs to fill knowledge gaps regarding how to: scale-up interventions that have been found to be effective (e.g., questions related to integration across sectors, adaptation of interventions across different contexts, and optimal care systems); address neglected mental health conditions and populations (e.g., elderly, people with disabilities, sexual minorities, people with severe, pre-existing mental disorders); build on available local resources and supports (e.g., how to build on traditional, religious healing and community-wide social support practices); and ensure equity, quality, fidelity, and sustainability for interventions in real-world contexts (e.g., answering questions about how interventions from controlled studies can be transferred to more representative humanitarian contexts)