7,192 research outputs found
Beam scanning by liquid-crystal biasing in a modified SIW structure
A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium
Resilience and food security in a food systems context
This open access book compiles a series of chapters written by internationally recognized experts known for their in-depth but critical views on questions of resilience and food security. The book assesses rigorously and critically the contribution of the concept of resilience in advancing our understanding and ability to design and implement development interventions in relation to food security and humanitarian crises. For this, the book departs from the narrow beaten tracks of agriculture and trade, which have influenced the mainstream debate on food security for nearly 60 years, and adopts instead a wider, more holistic perspective, framed around food systems. The foundation for this new approach is the recognition that in the current post-globalization era, the food and nutritional security of the world’s population no longer depends just on the performance of agriculture and policies on trade, but rather on the capacity of the entire (food) system to produce, process, transport and distribute safe, affordable and nutritious food for all, in ways that remain environmentally sustainable. In that context, adopting a food system perspective provides a more appropriate frame as it incites to broaden the conventional thinking and to acknowledge the systemic nature of the different processes and actors involved. This book is written for a large audience, from academics to policymakers, students to practitioners
High-throughput Tools and Techniques to Investigate Environmental Effects on Aging Behaviors in Caenorhabditis elegans
Aging is modulated by genetic and environmental cues; however, it is difficult to study how these perturbations modulate the aging process in a robust, high-throughput manner. Methods to gather large-scale behavioral data for aging studies are labor-intensive, lack individual-level resolution, or lack precise spatiotemporal environmental control. In addition, tools to analyze large-scale behavioral data sets are difficult to scale, unable to be broadly applied across complex environments, or fail to detect subtle behavioral changes.
In this thesis I develop tools to enable robust, microfluidic culture and behavioral analysis of C. elegans to examine how environmental cues, such as dietary restriction, influence longevity and behavior with age. In Aim 1, I engineer a robust pipeline for the long-term longitudinal culture and behavioral monitoring of C. elegans in aging studies with precise spatiotemporal environmental control. In Aim 2, I develop a flexible deep learning based pipeline for detecting and extracting postural information from large-scale behavioral datasets across heterogeneous environments. In Aim 3, I characterize how the full behavioral repertoire of individuals change with age, along with examining how these age-related behavioral changes are modulated by different dietary restriction regimes. The completion of this thesis provides 1) a new toolset to robustly explore how genetic or environmental effects influence longevity and healthspan, 2) a flexible pipeline for analyzing large-scale behavioral data in C. elegans, and 3) insight into how environmental perturbations influence health through age-related changes in behavior.Ph.D
Intelligent computing : the latest advances, challenges and future
Computing is a critical driving force in the development of human civilization. In recent years, we have witnessed the emergence of intelligent computing, a new computing paradigm that is reshaping traditional computing and promoting digital revolution in the era of big data, artificial intelligence and internet-of-things with new computing theories, architectures, methods, systems, and applications. Intelligent computing has greatly broadened the scope of computing, extending it from traditional computing on data to increasingly diverse computing paradigms such as perceptual intelligence, cognitive intelligence, autonomous intelligence, and human computer fusion intelligence. Intelligence and computing have undergone paths of different evolution and development for a long time but have become increasingly intertwined in recent years: intelligent computing is not only intelligence-oriented but also intelligence-driven. Such cross-fertilization has prompted the emergence and rapid advancement of intelligent computing
Modelling, Monitoring, Control and Optimization for Complex Industrial Processes
This reprint includes 22 research papers and an editorial, collected from the Special Issue "Modelling, Monitoring, Control and Optimization for Complex Industrial Processes", highlighting recent research advances and emerging research directions in complex industrial processes. This reprint aims to promote the research field and benefit the readers from both academic communities and industrial sectors
The Meta-Evaluation Problem in Explainable AI: Identifying Reliable Estimators with MetaQuantus
Explainable AI (XAI) is a rapidly evolving field that aims to improve
transparency and trustworthiness of AI systems to humans. One of the unsolved
challenges in XAI is estimating the performance of these explanation methods
for neural networks, which has resulted in numerous competing metrics with
little to no indication of which one is to be preferred. In this paper, to
identify the most reliable evaluation method in a given explainability context,
we propose MetaQuantus -- a simple yet powerful framework that meta-evaluates
two complementary performance characteristics of an evaluation method: its
resilience to noise and reactivity to randomness. We demonstrate the
effectiveness of our framework through a series of experiments, targeting
various open questions in XAI, such as the selection of explanation methods and
optimisation of hyperparameters of a given metric. We release our work under an
open-source license to serve as a development tool for XAI researchers and
Machine Learning (ML) practitioners to verify and benchmark newly constructed
metrics (i.e., ``estimators'' of explanation quality). With this work, we
provide clear and theoretically-grounded guidance for building reliable
evaluation methods, thus facilitating standardisation and reproducibility in
the field of XAI.Comment: 30 pages, 12 figures, 3 table
Late-bound code generation
Each time a function or method is invoked during the execution of a program, a stream of instructions is issued to some underlying hardware platform. But exactly what underlying hardware, and which instructions, is usually left implicit. However in certain situations it becomes important to control these decisions. For example, particular problems can only be solved in real-time when scheduled on specialised accelerators, such as graphics coprocessors or computing clusters.
We introduce a novel operator for hygienically reifying the behaviour of a runtime function instance as a syntactic fragment, in a language which may in general differ from the source function definition. Translation and optimisation are performed by recursively invoked, dynamically dispatched code generators. Side-effecting operations are permitted, and their ordering is preserved.
We compare our operator with other techniques for pragmatic control, observing that: the use of our operator supports lifting arbitrary mutable objects, and neither requires rewriting sections of the source program in a multi-level language, nor interferes with the interface to individual software components. Due to its lack of interference at the abstraction level at which software is composed, we believe that our approach poses a significantly lower barrier to practical adoption than current methods.
The practical efficacy of our operator is demonstrated by using it to offload the user interface rendering of a smartphone application to an FPGA coprocessor, including both statically and procedurally defined user interface components. The generated pipeline is an application-specific, statically scheduled processor-per-primitive rendering pipeline, suitable for place-and-route style optimisation.
To demonstrate the compatibility of our operator with existing languages, we show how it may be defined within the Python programming language. We introduce a transformation for weakening mutable to immutable named bindings, termed let-weakening, to solve the problem of propagating information pertaining to named variables between modular code generating units.Open Acces
Evaluation of mHealth apps for women of reproductive age: generating evidence to inform best practice
Background
Preconception and antenatal care are crucial to improving outcomes. Women of childbearing age use various strategies to receive information including mHealth. It is unknown what works in terms of apps that promote positive behaviour changes; how women access such information; what information women want; and what are the best mHealth apps available in Australia.
Aim
To generate evidence to inform the development and utilisation of preconception and pregnancy-specific mHealth behaviour change interventions.
Methods
Five studies were conducted. Firstly, a systematic review was undertaken to compare the effectiveness of mHealh apps verse standard care in promoting positive behaviour changes preconception. Secondly, a survey of women of reproductive age was done to explore the knowledge, attitudes, beliefs, and preferences for information about preconception and pregnancy care. Thirdly, a qualitative study was conducted to explore how women access pregnancy information. Fourthly, a study was undertaken to identify and review pregnancy mHealth apps available in Australia. Finally, we retrospectively mapped a high-quality app to examine the important components.
Findings
The systematic review showed no clear benefit in using mHealth apps compared to usual care in promoting positive behaviour changes for women before they are pregnant. The survey showed that women both prior to and during pregnancy access many sources for reproductive health information. The most popular freely available apps for pregnancy in Australia are generally of low quality and are not underpinned by behaviour change theory. The analysis of the development of the UK app Baby Buddy showed that using a behavioural change framework to guide design of mHealth apps is beneficial.
Conclusion
Given that women prefer to receive information from healthcare professionals and access mHealth often, new health strategies must be co-designed with women and clinicians to meet current and future needs
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