Fostering energy awareness in residential homes using mobile devices

There is considerable global effort being made towards identifying ways of reducing energy consumption to cope with growing demands. Although there is potential for energy saving in many sectors, our focus is on reducing energy consumption in residential homes. We have developed a system which combines home automation and energy usage monitoring technologies. The system offers a range of tools designed for mobile devices to assist users with monitoring their energy usage and provides mechanisms for setting up and controlling home appliances to conserve energy. In this paper we describe our system and a user study we have conducted to evaluate its effectiveness. The findings of the study show the potential benefits of this type of mobile technology

USEM: A ubiquitous smart energy management system for residential homes

With the ever-increasing worldwide demand for energy, and the limited available energy resources, there is a growing need to reduce our energy consumption whenever possible. Therefore, over the past few decades a range of technologies have been proposed to assist consumers with reducing their energy use. Most of these have focused on decreasing energy consumption in the industry, transport, and services sectors. In more recent years, however, growing attention has been given to energy use in the residential sector, which accounts for nearly 30% of total energy consumption in the developed countries. Here we present one such system, which aims to assist residential users with monitoring their energy usage and provides mechanisms for setting up and controlling their home appliances to conserve energy. We also describe a user study we have conducted to evaluate the effectiveness of this system in supporting its users with a range of tools and visualizations developed for ubiquitous devices such as mobile phones and tablets. The findings of this study have shown the potential benefits of our system, and have identified areas of improvement that need to be addressed in the future

Assisting Inhabitants of Residential Homes with Management of Their Energy Consumption

Although there are already a range of energy monitoring and automation systems available in the market that target residential homes, mostly with the aim of reducing their total energy consumption, very few of these systems are directly concerned with how those energy savings are actually made. As such, these systems do not provide tools that would allow users to make intelligent decisions about their energy usage strategies, and encourage them to change their energy use behaviour. In this paper we describe a system designed to facilitate planning and control of energy usage activities in residential homes. We also report on a user study of this system which demonstrates its potential for making energy savings possible

Glia Cell Morphology Analysis Using the Fiji GliaMorph Toolkit

Glial cells are the support cells of the nervous system. Glial cells typically have elaborate morphologies that facilitate close contacts with neighboring neurons, synapses, and the vasculature. In the retina, Müller glia (MG) are the principal glial cell type that supports neuronal function by providing a myriad of supportive functions via intricate cell morphologies and precise contacts. Thus, complex glial morphology is critical for glial function, but remains challenging to resolve at a sub-cellular level or reproducibly quantify in complex tissues. To address this issue, we developed GliaMorph as a Fiji-based macro toolkit that allows 3D glial cell morphology analysis in the developing and mature retina. As GliaMorph is implemented in a modular fashion, here we present guides to (a) setup of GliaMorph, (b) data understanding in 3D, including z-axis intensity decay and signal-to-noise ratio, (c) pre-processing data to enhance image quality, (d) performing and examining image segmentation, and (e) 3D quantification of MG features, including apicobasal texture analysis. To allow easier application, GliaMorph tools are supported with graphical user interfaces where appropriate, and example data are publicly available to facilitate adoption. Further, GliaMorph can be modified to meet users’ morphological analysis needs for other glial or neuronal shapes. Finally, this article provides users with an in-depth understanding of data requirements and the workflow of GliaMorph. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Download and installation of GliaMorph components including example data Basic Protocol 2: Understanding data properties and quality 3D—essential for subsequent analysis and capturing data property issues early Basic Protocol 3: Pre-processing AiryScan microscopy data for analysis Alternate Protocol: Pre-processing confocal microscopy data for analysis Basic Protocol 4: Segmentation of glial cells Basic Protocol 5: 3D quantification of glial cell morpholog

3D Quantification and Description of the Developing Zebrafish Cranial Vasculature

Background: Zebrafish are an excellent model to study cardiovascular development and disease. Transgenic reporter lines and state-of-the-art microscopy allow 3D visualization of the vasculature in vivo. Previous studies relied on subjective visual interpretation of vascular topology without objective quantification. Thus, there is the need to develop analysis approaches that model and quantify the zebrafish vasculature to understand the effect of development, genetic manipulation or drug treatment. Aim: To establish an image analysis pipeline to extract quantitative 3D parameters describing the shape and topology of the zebrafish vasculature, and examine how these are impacted during development, disease, and by chemicals. Methods: Experiments were performed in zebrafish embryos, conforming with UK Home Office regulations. Image acquisition of transgenic zebrafish was performed using a Z.1 Zeiss light-sheet fluorescence microscope. Pre-processing, enhancement, registration, segmentation, and quantification methods were developed and optimised using open-source software, Fiji (Fiji 1.51p; National Institutes of Health, Bethesda, USA). Results: Motion correction was successfully applied using Scale Invariant Feature Transform (SIFT), and vascular enhancement based on vessel tubularity (Sato filter) exceeded general filter outcomes. Following evaluation and optimisation of a variety of segmentation methods, intensity-based segmentation (Otsu thresholding) was found to deliver the most reliable segmentation, allowing 3D vascular volume measurement. Following successful segmentation of the cerebral vasculature, a workflow to quantify left-right intra-sample symmetry was developed, finding no difference from 2-to-5dpf. Next, the first vascular inter-sample registration using a manual landmark-based approach was developed and it was found that conjugate direction search allowed automatic inter-sample registration. This enabled extraction of age-specific regions of similarity and variability between different individual embryos from 2-to-5dpf. A workflow was developed to quantify vascular network length, branching points, diameter, and complexity, showing reductions in zebrafish without blood flow. Also, I discovered and characterised a previously undescribed endothelial cell membrane behaviour termed kugeln. Conclusion: A workflow that successfully extracts the zebrafish vasculature and enables detailed quantification of a wide variety of vascular parameters was developed

Meeting in the Middle: Towards Successful Multidisciplinary Bioimage Analysis Collaboration

With an increase in subject knowledge expertise required to solve specific biological questions, experts from different fields need to collaborate to address increasingly complex issues. To successfully collaborate, everyone involved in the collaboration must take steps to "meet in the middle". We thus present a guide on truly cross-disciplinary work using bioimage analysis as a showcase, where it is required that the expertise of biologists, microscopists, data analysts, clinicians, engineers, and physicists meet. We discuss considerations and best practices from the perspective of both users and technology developers, while offering suggestions for working together productively and how this can be supported by institutes and funders. Although this guide uses bioimage analysis as an example, the guiding principles of these perspectives are widely applicable to other cross-disciplinary work

The ifo Education Survey 2014-2021

The ifo Education Survey is a representative opinion survey of the German voting-age population on education topics that has been conducted annually since 2014. It covers public preferences on a wide range of education policy issues ranging from early childhood education, schools, and apprenticeships to university education and life-long learning. The dataset comprises several survey experiments that facilitate investigating the causal effects of information provision, framing, and question design on answering behavior. This paper gives an overview of the survey content and methodology, describes the data, and explains how researchers can access the dataset of over 4000 participants per wave

GliaMorph: A modular image analysis toolkit to quantify Müller glial cell morphology

Cell morphology is critical for all cell functions. This is particularly true for glial cells as they rely on complex shape to contact and support neurons. However, methods to quantify complex glial cell shape accurately and reproducibly are lacking. To address this, we developed the image analysis pipeline "GliaMorph". GliaMorph is a modular analysis toolkit developed to perform (i) image pre-processing, (ii) semi-automatic region-of-interest (ROI) selection, (iii) apicobasal texture analysis, (iv) glia segmentation, and (v) cell feature quantification. Müller Glia (MG) have a stereotypic shape linked to their maturation and physiological status. We here characterized MG on three levels, including (a) global image-level, (b) apicobasal texture, and (c) regional apicobasal vertical-to-horizontal alignment. Using GliaMorph we quantified MG development on a global and single-cell level, showing increased feature elaboration and subcellular morphological rearrangement in the zebrafish retina. As proof-of-principle, we analysed expression changes in a mouse glaucoma model, identifying subcellular protein localization changes in MG. Together, GliaMorph enables an in-depth understanding of MG morphology in the developing and diseased retina

The NCOR-HDAC3 co-repressive complex modulates the leukemogenic potential of the transcription factor ERG

The ERG (ETS-related gene) transcription factor is linked to various types of cancer, including leukemia. However, the specific ERG domains and co-factors contributing to leukemogenesis are poorly understood. Drug targeting a transcription factor such as ERG is challenging. Our study reveals the critical role of a conserved amino acid, proline, at position 199, located at the 3' end of the PNT (pointed) domain, in ERG's ability to induce leukemia. P199 is necessary for ERG to promote self-renewal, prevent myeloid differentiation in hematopoietic progenitor cells, and initiate leukemia in mouse models. Here we show that P199 facilitates ERG's interaction with the NCoR-HDAC3 co-repressor complex. Inhibiting HDAC3 reduces the growth of ERG-dependent leukemic and prostate cancer cells, indicating that the interaction between ERG and the NCoR-HDAC3 co-repressor complex is crucial for its oncogenic activity. Thus, targeting this interaction may offer a potential therapeutic intervention