Smart environment
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Smart hydrogels are special type of hydrogels that undergo solution-gelation transition in response to alterations in the environment. Solution-gel transformation is brought about through either physical or chemical cross-linking that occur between the hydrogel chains. Various stimulating factors have been identified to be responsible for the change in the physical state of the intelligent hydrogel. The most important triggering factors are the temperature, pH, ions, electrical signalling, magnetic field, glucose, light and others. Each of these stimulating factors can trigger the swelling of the hydrogel through unique mechanism. Many of these triggering factors are characteristics of the biological systems which make the smart polymers quite beneficial for different biomedical applications. Numerous natural and synthetic polymers have been distinguished to act as smart materials. These polymers impressed the scientists to use them in many biomedical and industrial applications such as drug delivery systems, gene therapy applications, tissue engineering and many other applications.
"Smart city", "sustainable city", "ubiquitous city", "smart sustainable city", "eco-city", "regenerative city" are fuzzy concepts; they are established to mitigate the negative impact on urban growth while achieving economic, social, and environmental sustainability. This study presents the result of the literature network analysis exploring the state of the art in the concepts of smart and regenerative urban growth under urban metabolism framework. Heat-maps of impact citations, cutting-edge research on the topic, tip-top ideas, concepts, and theories are highlighted and revealed through VOSviewer bibliometrics based on a selection of 1686 documents acquired from Web of Science, for a timespan between 2010 and 2019. This study discloses that urban growth is a complex phenomenon that covers social, economic, and environmental aspects, and the overlaps between them, leading to a diverse range of concepts on urban development. In regards to our concepts of interest, smart, and regenerative urban growth, we see that there is an absence of conceptual contiguity since both concepts have been approached on an individual basis. This fact unveils the need to adopt a more holistic and interdisciplinary approach to urban planning and design, integrating these concepts to improve the quality of life and public health in urban areas.
- MeSH
- kvalita života * MeSH
- obnova měst * MeSH
- plánování měst * MeSH
- trvale udržitelný rozvoj MeSH
- velkoměsta MeSH
- veřejné zdravotnictví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- přehledy MeSH
- Geografické názvy
- velkoměsta MeSH
In order to study the relationship between human physical activity and the design of the built environment, it is important to measure the location of human movement accurately. In this study, we compared an inexpensive GPS receiver (Holux RCV-3000) and a frequently used Garmin Forerunner 35 smart watch, with a device that has been validated and recommended for physical activity research (Qstarz BT-Q1000XT). These instruments were placed on six geodetic points, which represented a range of different environments (e.g., residential, open space, park). The coordinates recorded by each device were compared with the known coordinates of the geodetic points. There were no differences in accuracy among the three devices when averaged across the six sites. However, the Garmin was more accurate in the city center and the Holux was more accurate in the park and housing estate areas compared to the other devices. We consider the location accuracy of the Holux and the Garmin to be comparable to that of the Qstarz. Therefore, we consider these devices to be suitable instruments for locating physical activity. Researchers must also consider other differences among these devices (such as battery life) when determining if they are suitable for their research studies.
- MeSH
- cvičení * MeSH
- lidé MeSH
- vytvořené prostředí * MeSH
- zdroje elektrické energie MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
Development in the area of sensor technologies and subsequently applications within the Internet of Things allows the implementation of systems for continuous monitoring of human's vital parameters and daily activities. This development is welcomed since the population aged 65 and over is constantly increasing. Moreover, the number of seniors living alone is also increasing. The monitoring systems can contribute to the safety and security of elderly people and allow them to stay at home where they are used to live as long as possible. Application of various sensor types raises questions on the most suitable sensor data representation, not losing useful information, and also on the design of detection and evaluation algorithms. In the paper, we briefly present several existing approaches and explain why we decided to use the basic ideas coming from the area of behaviour informatics.
- MeSH
- algoritmy * MeSH
- bydlení MeSH
- elektrokardiografie * MeSH
- lidé MeSH
- monitorování fyziologických funkcí * MeSH
- senioři MeSH
- srdeční arytmie MeSH
- Check Tag
- lidé MeSH
- senioři MeSH
- Publikační typ
- časopisecké články MeSH
During the last decade we have been witnessing fast development in the area of sensor technologies and communications that have enabled applications within the Internet of Things (IoT). Subsequently implementations of systems for continuous monitoring of human ́s vital parameters and daily activities started to appear. Since the ageing population is constantly increasing, the development of such applications is necessary. The growing number of sensor types and their producers introduces a problem concerning data formats and data representation. Sensor data representation is an important issue since we do not want to lose any useful information. Additional issue is the design of detection and evaluation algorithms. In the article we present briefly the considered types of sensors, proposed systems architecture, and experimental setup installed in a real apartment.
The plasma membrane, as a highly complex cell organelle, serves as a crucial platform for a multitude of cellular processes. Its collective biophysical properties are largely determined by the structural diversity of the different lipid species it accommodates. Therefore, a detailed investigation of biophysical properties of the plasma membrane is of utmost importance for a comprehensive understanding of biological processes occurring therein. During the past two decades, several environment-sensitive probes have been developed and become popular tools to investigate membrane properties. Although these probes are assumed to report on membrane order in similar ways, their individual mechanisms remain to be elucidated. In this study, using model membrane systems, we characterized the probes Pro12A, NR12S and NR12A in depth and examined their sensitivity to parameters with potential biological implications, such as the degree of lipid saturation, double bond position and configuration (cis versus trans), phospholipid headgroup and cholesterol content. Applying spectral imaging together with atomistic molecular dynamics simulations and time-dependent fluorescent shift analyses, we unravelled individual sensitivities of these probes to different biophysical properties, their distinct localizations and specific relaxation processes in membranes. Overall, Pro12A, NR12S and NR12A serve together as a toolbox with a wide range of applications allowing to select the most appropriate probe for each specific research question.
It is important for older and disabled people who live alone to be able to cope with the daily challenges of living at home. In order to support independent living, the Smart Home Care (SHC) concept offers the possibility of providing comfortable control of operational and technical functions using a mobile robot for operating and assisting activities to support independent living for elderly and disabled people. This article presents a unique proposal for the implementation of interoperability between a mobile robot and KNX technology in a home environment within SHC automation to determine the presence of people and occupancy of occupied spaces in SHC using measured operational and technical variables (to determine the quality of the indoor environment), such as temperature, relative humidity, light intensity, and CO2 concentration, and to locate occupancy in SHC spaces using magnetic contacts monitoring the opening/closing of windows and doors by indirectly monitoring occupancy without the use of cameras. In this article, a novel method using nonlinear autoregressive Neural Networks (NN) with exogenous inputs and nonlinear autoregressive is used to predict the CO2 concentration waveform to transmit the information from KNX technology to mobile robots for monitoring and determining the occupancy of people in SHC with better than 98% accuracy.
- MeSH
- lidé MeSH
- oxid uhličitý MeSH
- robotika * metody MeSH
- samostatný způsob života MeSH
- senioři MeSH
- služby domácí péče * MeSH
- technologie MeSH
- Check Tag
- lidé MeSH
- senioři MeSH
- Publikační typ
- časopisecké články MeSH
COVID-19 has depleted healthcare systems around the world. Extreme conditions must be defined as soon as possible so that services and treatment can be deployed and intensified. Many biomarkers are being investigated in order to track the patient's condition. Unfortunately, this may interfere with the symptoms of other diseases, making it more difficult for a specialist to diagnose or predict the severity level of the case. This research develops a Smart Healthcare System for Severity Prediction and Critical Tasks Management (SHSSP-CTM) for COVID-19 patients. On the one hand, a machine learning (ML) model is projected to predict the severity of COVID-19 disease. On the other hand, a multi-agent system is proposed to prioritize patients according to the seriousness of the COVID-19 condition and then provide complete network management from the edge to the cloud. Clinical data, including Internet of Medical Things (IoMT) sensors and Electronic Health Record (EHR) data of 78 patients from one hospital in the Wasit Governorate, Iraq, were used in this study. Different data sources are fused to generate new feature pattern. Also, data mining techniques such as normalization and feature selection are applied. Two models, specifically logistic regression (LR) and random forest (RF), are used as baseline severity predictive models. A multi-agent algorithm (MAA), consisting of a personal agent (PA) and fog node agent (FNA), is used to control the prioritization process of COVID-19 patients. The highest prediction result is achieved based on data fusion and selected features, where all examined classifiers observe a significant increase in accuracy. Furthermore, compared with state-of-the-art methods, the RF model showed a high and balanced prediction performance with 86% accuracy, 85.7% F-score, 87.2% precision, and 86% recall. In addition, as compared to the cloud, the MAA showed very significant performance where the resource usage was 66% in the proposed model and 34% in the traditional cloud, the delay was 19% in the proposed model and 81% in the cloud, and the consumed energy was 31% in proposed model and 69% in the cloud. The findings of this study will allow for the early detection of three severity cases, lowering mortality rates.
- MeSH
- algoritmy MeSH
- COVID-19 * MeSH
- internet věcí * MeSH
- lidé MeSH
- poskytování zdravotní péče MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
The coronavirus disease 2019 (COVID-19) pandemic has magnified the insufficient readiness of humans in dealing with such an unexpected occurrence. During the pandemic, sustainable development goals have been hindered severely. Various observations and lessons have been highlighted to emphasise local impacts on a single region or single sector, whilst the holistic and coupling impacts are rarely investigated. This study overviews the structural changes and spatial heterogeneities of changes in healthcare, energy and environment, and offers perspectives for the in-depth understanding of the COVID-19 impacts on the three sectors, in particular the cross-sections of them. Practical observations are summarised through the broad overview. A novel concept of the healthcare-energy-environment nexus under climate change constraints is proposed and discussed, to illustrate the relationships amongst the three sectors and further analyse the dynamics of the attention to healthcare, energy and environment in view of decision-makers. The society is still on the way to understanding the impacts of the whole episode of COVID-19 on healthcare, energy, environment and beyond. The raised nexus thinking could contribute to understanding the complicated COVID-19 impacts and guiding sustainable future planning.
Tento návrh jednoduché metody vizualizace daktyloskopických stop na základě elektrochemické depozice polyfenazinových barviv (polyneutrální červeně a polytoluidinové modři) z neutrálního prostředí, kdy je minimalizováno poškození genetické informace, by mohl usnadnit snímání otisků prstů z nábojnic ve forenzní praxi. Parametry elektrochemických metod cyklické voltametrie a chronoamperometrie (základní elektrolyt, aplikovaný potenciál, doba depozice nebo potenciálový rozsah a počet cyklů) byly postupně optimalizovány, dokud nebyl otisk dostatečně viditelný. Morfologie a struktura modifikovaných povrchů daktyloskopických stop a polyfenazinových filmů byly studovány pomocí skenovací elektronové mikroskopie. Je předpokládán další rozvoj metody a především aplikace metody na vystřelené nábojnice.
A simple fingerprint visualization method based on the electrochemical deposition of polytoluidine blue (PTB) and polyneutral red (PNR) from a neutral environment with the possibility of minimal damage to the genetic information could facilitate fingerprinting from cartridge cases in forensic practice. The parameters of both visualization methods (supporting electrolyte, applied potential, deposition time or potential range, and number of cycles) were optimized until the imprint was sufficiently visible. The morphology and structure of modified fingerprint surfaces and polyphenazine films were studied using scanning electron microscopy. It is assumed that the method will be applied in the future to fired cartridges, which are crucial in forensics.
