Perinatal Depression

2014 ◽  
Author(s):  
Jennifer N. Felder ◽  
Abigail Lindemann ◽  
Sona Dimidjian
Keyword(s):  
Risk Factors ◽  
Perinatal Depression ◽  
Perinatal Period ◽  
Future Research ◽  
Childbearing Age ◽  
Research Directions ◽  
Wide Range ◽  
Assessment And Treatment ◽  
Future Research Directions ◽  
Assessment Strategies

Depression is a common problem among pregnant andpostpartum women, with rates comparable to or greater than those among women of childbearing age who are not pregnant or postpartum. Perinatal depression is associated with a wide range of unique assessment and treatment complexities, risk factors, and consequences for women and offspring. In this chapter, we review current research on the prevalence of perinatal depression, etiology, risk factors, and consequences, and we discuss assessment strategies and interventions. Limitations to current research and future research directions are noted. We conclude with guidelines for practitioners for assessing and treating depression during the perinatal period.

Synthesis

2020 ◽  
pp. 421-428
Author(s):  
Lauren Brookman-Frazee ◽  
Amy Drahota ◽  
Colby Chlebowski ◽  
Yael Koenig ◽  
Katherine Nguyen Williams ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Autism Spectrum ◽  
Future Research ◽  
Research Directions ◽  
Course Assessment ◽  
Academic Partnerships ◽  
Assessment And Treatment ◽  
Important Field ◽  
Future Research Directions ◽  
Psychiatric Conditions

Recent research and clinical attention devoted to co-occurring psychiatric conditions within autism spectrum disorder (ASD) has led to significant advances in the understanding of and ability to assess and treat co-occurring problems effectively. This chapter summarizes those advances while also highlighting the substantial gaps that remain in the understanding of co-occurring problems in people with ASD. The chapter provides recommendations for future research directions in the areas of etiology, developmental course, assessment, and treatment. It also offers suggestions for improving the representativeness of research participants and strengthening community–academic partnerships in this important field of study.

scholarly journals A matrix-less method to approximate the spectrum and the spectral function of Toeplitz matrices with real eigenvalues

2021 ◽  
Author(s):  
Sven-Erik Ekström ◽  
Paris Vassalos
Keyword(s):  
Distribution Function ◽  
Asymptotic Distribution ◽  
Numerical Experiments ◽  
Toeplitz Matrices ◽  
Future Research ◽  
Research Directions ◽  
Numerical Examples ◽  
Working Hypothesis ◽  
Wide Range ◽  
Future Research Directions

AbstractIt is known that the generating function f of a sequence of Toeplitz matrices {Tn(f)}n may not describe the asymptotic distribution of the eigenvalues of Tn(f) if f is not real. In this paper, we assume as a working hypothesis that, if the eigenvalues of Tn(f) are real for all n, then they admit an asymptotic expansion of the same type as considered in previous works, where the first function, called the eigenvalue symbol $\mathfrak {f}$ f , appearing in this expansion is real and describes the asymptotic distribution of the eigenvalues of Tn(f). This eigenvalue symbol $\mathfrak {f}$ f is in general not known in closed form. After validating this working hypothesis through a number of numerical experiments, we propose a matrix-less algorithm in order to approximate the eigenvalue distribution function $\mathfrak {f}$ f . The proposed algorithm, which opposed to previous versions, does not need any information about neither f nor $\mathfrak {f}$ f is tested on a wide range of numerical examples; in some cases, we are even able to find the analytical expression of $\mathfrak {f}$ f . Future research directions are outlined at the end of the paper.

scholarly journals CubeSat Communications: Recent Advances and Future Challenges

2020 ◽  
Author(s):  
Nasir Saeed ◽  
Ahmed Elzanaty ◽  
Heba Almorad ◽  
Hayssam Dahrouj ◽  
Tareq Y. Al-Naffouri ◽  
...  
Keyword(s):  
Channel Modeling ◽  
Future Research ◽  
New Paradigm ◽  
Earth Remote Sensing ◽  
Research Directions ◽  
Space Industry ◽  
Recent Advances ◽  
Wide Range ◽  
Future Challenges ◽  
Future Research Directions

<pre><pre>Given the increasing number of space-related applications, research in the emerging space industry is becoming more and more attractive. One compelling area of current space research is the design of miniaturized satellites, known as CubeSats, which are enticing because of their numerous applications and low design-and-deployment cost. </pre><pre>The new paradigm of connected space through CubeSats makes possible a wide range of applications, such as Earth remote sensing, space exploration, and rural connectivity.</pre><pre>CubeSats further provide a complementary connectivity solution to the pervasive Internet of Things (IoT) networks, leading to a globally connected cyber-physical system.</pre><pre>This paper presents a holistic overview of various aspects of CubeSat missions and provides a thorough review of the topic from both academic and industrial perspectives.</pre><pre>We further present recent advances in the area of CubeSat communications, with an emphasis on constellation-and-coverage issues, channel modeling, modulation and coding, and networking.</pre><pre>Finally, we identify several future research directions for CubeSat communications, including Internet of space things, low-power long-range networks, and machine learning for CubeSat resource allocation.</pre></pre>

scholarly journals A Systematic Survey on Deep Generative Models for Graph Generation

2020 ◽  
Author(s):  
Xiaojie Guo ◽  
Liang Zhao
Keyword(s):  
Generative Models ◽  
Future Research ◽  
Specific Domain ◽  
Research Directions ◽  
Wide Range ◽  
Data Representations ◽  
Future Research Directions ◽  
Definition Of ◽  
Rich History ◽  
Graph Generation

Graphs are important data representations for describing objects and their relationships, which appear in a wide diversity of real-world scenarios. As one of a critical problem in this area, graph generation considers learning the distributions of given graphs and generating more novel graphs. Owing to its wide range of applications, generative models for graphs have a rich history, which, however, are traditionally hand-crafted and only capable of modeling a few statistical properties of graphs. Recent advances in deep generative models for graph generation is an important step towards improving the fidelity of generated graphs and paves the way for new kinds of applications. This article provides an extensive overview of the literature in the field of deep generative models for graph generation. Firstly, the formal definition of deep generative models for the graph generation as well as preliminary knowledge is provided. Secondly, two taxonomies of deep generative models for unconditional, and conditional graph generation respectively are proposed; the existing works of each are compared and analyzed. After that, an overview of the evaluation metrics in this specific domain is provided. Finally, the applications that deep graph generation enables are summarized and five promising future research directions are highlighted.

Information Technology Outsourcing Risk Factors and Provider Selection

2017 ◽  
pp. 214-228
Author(s):  
Salim Lahmiri
Keyword(s):  
Risk Factors ◽  
Information Technology ◽  
Future Research ◽  
Business Managers ◽  
Research Directions ◽  
Utility Of Information ◽  
Future Research Directions ◽  
Information Technology Outsourcing

Information technology outsourcing has become a major issue in business and received a large attention from both business managers and scholars. Indeed, it helps a business company to reduce it costs and to maintain its competitiveness. The purpose of this chapter is to introduce the utility of information technology outsourcing for the enterprise and to review some recent works in outsourcing risk factors identification and provider selection. Finally, drawbacks of information technology outsourcing will be presented along with future research directions.

Modern Downsizing

2021 ◽  
pp. 1970-1983
Author(s):  
Grzegorz Wojtkowiak
Keyword(s):  
Financial Analysis ◽  
Management Tool ◽  
Future Research ◽  
Research Directions ◽  
Good Practices ◽  
Strategic Option ◽  
Wide Range ◽  
Future Research Directions ◽  
Points Of View

The aim of the chapter is to present the concept of downsizing from different points of view: as a strategic option, as a management tool and as a phenomenon. It describes the evolution of the term, its definitions, and different directions of development. A scale and possible outcomes are described on the basis of financial analysis; however it also discusses the role of non-financial aspects. The chapter points out reasons, aims and a wide range of tools that may be used during implementation of downsizing. One of the conclusions of the chapter is to present future research directions aiming at increasing knowledge of managers and providing them with detailed good practices.

Aspects of battle damage repair of helicopter structures

2010 ◽  
Vol 114 (1155) ◽  
pp. 321-332 ◽  
Author(s):  
J. Wang ◽  
A. Baker
Keyword(s):  
Composite Structures ◽  
Future Research ◽  
Research Directions ◽  
Strength Assessment ◽  
Damage Prediction ◽  
Damage Repair ◽  
Repair Materials ◽  
Wide Range ◽  
Future Research Directions ◽  
Non Destructive

Abstract This paper summarises recent research conducted at the Defence Science and Technology Organisation in the area of aircraft battle damage repair, covering aspects such as ballistic testing, ballistic damage prediction, non-destructive damage inspection, structure residual-strength assessment, repair materials and techniques, repair design approaches, repair implementation and demonstration. The research has been focused on military helicopter composite structures. This paper provides an overview of a wide range of research conducted and detailed information in selected areas. Considerations for future research directions are also briefly discussed.

scholarly journals Virtual Knowledge Graphs: An Overview of Systems and Use Cases

2019 ◽  
Vol 1 (3) ◽  
pp. 201-223 ◽  
Author(s):  
Guohui Xiao ◽  
Linfang Ding ◽  
Benjamin Cogrel ◽  
Diego Calvanese
Keyword(s):  
Data Integration ◽  
Domain Knowledge ◽  
Data Access ◽  
Use Cases ◽  
Future Research ◽  
Knowledge Graph ◽  
Research Directions ◽  
Wide Range ◽  
Future Research Directions ◽  
Knowledge Graphs

In this paper, we present the virtual knowledge graph (VKG) paradigm for data integration and access, also known in the literature as Ontology-based Data Access. Instead of structuring the integration layer as a collection of relational tables, the VKG paradigm replaces the rigid structure of tables with the flexibility of graphs that are kept virtual and embed domain knowledge. We explain the main notions of this paradigm, its tooling ecosystem and significant use cases in a wide range of applications. Finally, we discuss future research directions.

scholarly journals Understanding Suicide Risk Within the Research Domain Criteria (RDoC) Framework: Insights, Challenges, and Future Research Considerations

2017 ◽  
Vol 5 (3) ◽  
pp. 568-592 ◽  
Author(s):  
Catherine R. Glenn ◽  
Christine B. Cha ◽  
Evan M. Kleiman ◽  
Matthew K. Nock
Keyword(s):  
Risk Factors ◽  
Suicidal Behavior ◽  
Suicide Risk ◽  
Future Research ◽  
Research Domain Criteria ◽  
Research Directions ◽  
Future Research Directions ◽  
Research Domain ◽  
Over Time ◽  
Broad Overview

Suicide is a leading cause of death worldwide. Prior research has focused primarily on sociodemographic and psychiatric risk factors with little improvement in the prediction or prevention of suicidal behavior over time. The Research Domain Criteria (RDoC) may be an especially useful framework for advancing research in this area. This article provides a brief and broad overview of research on suicidal behavior relating to each of the RDoC domains—highlighting the RDoC construct(s) where research has focused, the construct(s) where research is lacking, and suggestions for future research directions. We also discuss major challenges for suicide research within the RDoC framework, including the intersection of RDoC domains, interaction of domains with the environment, incorporation of developmental stage, integration of distal and proximal processes, and inclusion of suicide-specific constructs. We conclude by underscoring important considerations for future research aimed at using the RDoC framework to study suicidal behavior and other forms of psychopathology.

scholarly journals Person Search Challenges and Solutions: A Survey

2021 ◽  
Author(s):  
Xiangtan Lin ◽  
Pengzhen Ren ◽  
Yun Xiao ◽  
Xiaojun Chang ◽  
Alex Hauptmann
Keyword(s):  
Free Form ◽  
Future Research ◽  
Search Query ◽  
Research Directions ◽  
Wide Range ◽  
Person Features ◽  
Real World Applications ◽  
Person Search ◽  
Future Research Directions ◽  
Open Issues

Person search has drawn increasing attention due to its real-world applications and research significance. Person search aims to find a probe person in a gallery of scene images with a wide range of applications, such as criminals search, multicamera tracking, missing person search, etc. Early person search works focused on image-based person search, which uses person image as the search query. Text-based person search is another major person search category that uses free-form natural language as the search query. Person search is challenging, and corresponding solutions are diverse and complex. Therefore, systematic surveys on this topic are essential. This paper surveyed the recent works on image-based and text-based person search from the perspective of challenges and solutions. Specifically, we provide a brief analysis of highly influential person search methods considering the three significant challenges: the discriminative person features, the query-person gap, and the detection-identification inconsistency. We summarise and compare evaluation results. Finally, we discuss open issues and some promising future research directions.

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