Existing research indicates that mineralization of Carlin-type gold deposit is related to geological structures, but current studies mostly focus on the qualitative association, and lack quantitative analysis of the relationship between mineralization and structural features, which limits the potential for predictive mineral exploration. In this study, the Nibao Carlin-type gold deposit was selected as the research area to conduct three-dimensional geological modeling, spatial analysis, and three-dimensional prospectivity modeling. Spatial analysis revealed that the majority of gold ore bodies are situated near the main fault, with gold mineralization primarily occurring within a spatial range of approximately -80 meters to 20 meters from the main fault plane. This spatial distribution predominantly aligns in a SW-NE direction. Spatial characteristic extraction of fault slope indicators suggests that the slope angles are conducive to the migration and accumulation of ore-forming hydrothermal fluids, with ore body metal content rapidly increasing within an angle range of approximately 20° to 60°. The shape analysis of the mainfault indicates that the principal spaces of mineralization enrichment are within -10m to 20m of the fault plane undulations, where gold resources are concentrated in a relatively flat area. However, the degree of mineralization is more pronounced in the protruding sections than in the depressed areas. The areas with significant dip changes in faults display higher variations in orebody attitudes, with mineralization noticeably weaker in areas where the fault steepness changes markedly. Ore-bearing units exhibit significantly higher grades within the -17° to 3° interval of fault steepness transition. This interval also sees a rapid accumulation of gold resources. The Nibao gold mine's mineralization is derived from deep, ore-bearing hydrothermal fluids ascending along major fractures, precipitating, and accumulating in favorable ore-hosting spaces (faults, anticline cores) and lithological combinations (sedimentary tuffs, tuffs). Three deep potential gold targets were identified, highlighting the deep western edge of the F1 fault and the deep southeast-trending lower plate as prospective areas for future exploration. This study underscores the effectiveness of 3D prospective modeling as an indispensable tool for elucidating the spatial distribution of fault-controlled Carlin-type gold deposits and their tectonic determinants.

The present grievous situation of the tuberculosis disease can be improved by efficient case management and timely follow-up evaluations. With the advent of digital technology this can be achieved by quick summarization of the patient-centric data. The aim of our study was to assess the effectiveness of the ODK Scan paper-to-digital system during testing period of three months. A sequential, explanatory mixed-method research approach was employed to elucidate technology use. Training, smartphones, application and 3G enabled SIMs were provided to the four field workers. At the beginning, baseline measures of the data management aspects were recorded and compared with endline measures to see the impact of ODK Scan. Additionally, at the end, users’ feedback was collected regarding app usability, user interface design and workflow changes. 122 patients’ records were retrieved from the server and analysed for quality. It was found that ODK Scan recognized 99.2% of multiple choice bubble responses and 79.4% of numerical digit responses correctly. However, the overall quality of the digital data was decreased in comparison to manually entered data. Using ODK Scan, a significant time reduction is observed in data aggregation and data transfer activities, however, data verification and form filling activities took more time. Interviews revealed that field workers saw value in using ODK Scan, however, they were more concerned about the time consuming aspects of the use of ODK Scan. Therefore, it is concluded that minimal disturbance in the existing workflow, continuous feedback and value additions are the important considerations for the implementing organization to ensure technology adoption and workflow improvements.

The Inefficient water use, varying and low productivity in Kenya public irrigation schemes is a major concern. It is therefore necessary to periodically monitor and evaluate the performance of public irrigation schemes. The performance of public irrigation in western Kenya was assessed by combining benchmarking methodology and principal component analysis. The aim was to quantify and rank the performance of pumped public irrigation schemes in Kenya. Eleven benchmarking indicators were computed for the period from 2012 to 2016 and compared to global benchmark values. The indicators used fall under agricultural productivity, water supply and financial performance categories. The computed agricultural productivity was 36%–51% in Ahero, 23%–42% in West Kano and 26%–50% Bunyala irrigation scheme. Water supply performance in Ahero, West Kano and Bunyala irrigation schemes varied from 24% to 58%, 3% to 49% and 19% to 43% respectively. Financial performance varied from 46% to 54% in Ahero, 25% to 32% in West Kano and 54%–56% in Bunyala irrigation scheme. An average overall performance efficiency of 46%, 39% and 31% was obtained in Ahero, Bunyala and West Kano irrigation schemes respectively. The performance of the irrigation schemes is very poor and measures on improving performance are needed.

The necessity for precise and current data concerning the dynamics of land cover change in Indonesia is crucial for efforts to reduce natural vegetation cover due to agricultural expansion. The functionality of monitoring systems that incorporate Terra-MODIS is currently compromised by the limited availability of data for the immediate future. This study seeks to assess the potential of VIIRS satellite imagery in developing an early warning system for monitoring vegetation cover change in Indonesia. The Normalized Differential Open Area Index (NDOAI) computed from the 8-day’ VIIRS data was employed to detect changes in vegetation cover based on pixel-by-pixel subtraction in the NDOAI data time series. Evaluating the pixel-level accuracy of change detection is complicated due to the fact that we evaluate a change map at a coarser resolution than the Landsat-based reference map. The results revealed that increasing the threshold percentage is associated with improved accuracy. In change detection, there is often a trade-off between accuracy and sensitivity. A threshold that is too low may result in false positives, while a threshold that is too high may lead to missed changes. This study demonstrates that when a threshold value of less than 20% is applied, Landsat can identify vegetation cover changes at an earlier stage. Conversely, when a threshold value greater than 20% is employed, VIIRS will detect the change 4.5 days earlier than Landsat. Additionally, VIIRS is capable of detecting changes 25.4 days and 54.8 days faster than Landsat, respectively, when using thresholds of 40% and 75%.

Sensor fusion algorithms and models have been widely used in recent times. Although research evidence has informed the use of sensor fusion models in diverse applications, there is room for improvement, especially in home-based health monitoring applications which require less supervision and technical knowledge of users. The present work compares data mining-based fusion software packages such as RapidMiner Studio, Anaconda, Weka, and Orange, and proposes a data fusion framework suitable for in-home applications. 574 privacy-friendly (binary) images and 1,722 datasets gleaned from thermal and Radar sensing solutions respectively, were fused using the software packages on instances of homogeneous and heterogeneous data aggregation. Experimental results indicated that the proposed fusion framework achieved an average Classification Accuracy of 84.7% and 95.7% on homogeneous and heterogeneous datasets respectively, with the help of data mining and machine learning models such as Naïve Bayes, Decision Tree, Neural Network, Random Forest, Stochastic Gradient Descent, Support Vector Machine, K-Nearest Neighbours and CN2 induction. Further evaluation of the sensor data fusion framework based on cross validation of features indicated average values of 94.4% for Classification Accuracy, 95.7% Precision and 96.4% for Recall.

The proposed research methodology aims to design a generally implementable framework for providing a house owner/member with the immediate notification of an on-going theft (unauthorized access to their premises). For this purpose, a rigorous analysis of existing systems was undertaken to identify research gaps. The problems found with existing systems were that they can only identify the intruder after the theft, or cannot distinguish between human and non-human objects. Wireless Sensors Networks (WSNs) combined with the use of Internet of Things (IoT), Cognitive Internet of Things, Internet of Medical Things, and Cloud Computing are expanding smart home concepts and solutions, and their applications. The primary objective of the present research work was to design and develop IoT and cloud computing based smart home solutions. In addition, we also propose a novel smart home anti-theft system that can detect an intruder, even if they have partially/fully hidden their face using clothing, leather, fiber, or plastic materials. The proposed system can also detect an intruder in the dark using a CCTV camera without night vision facility. The fundamental idea was to design a cost-effective and efficient system for an individual to be able to detect any kind of theft in real-time and provide instant notification of the theft to the house owner. The system also promises to implement home security with large video data handling in real-time.

This paper describes a system that is used to gather data from Smart Home sensors measuring energy consumption, analyze and predict future consumption by using machine learning algorithm for prediction. It focuses on the architecture of the system as well as the need for such system to exist in practice – why the consumption should be measured at all and how that measurement can be put to good use for achieving energy efficiency.

Global coverage and scale up of interventions to reduce newborn mortality remains low, though progress has been achieved in improving newborn survival in many low-income settings. An important factor in the success of newborn health interventions, and moving to scale, is appropriate design of community-based programs and strategies for local implementation. We report the results of formative research undertaken to inform the design of a newborn health intervention in Cambodia. Information was gathered on newborn care practices over a period of three months using multiple qualitative methods of data collection in the primary health facility and home setting. Analysis of the data indicated important gaps, both at home and facility level, between recommended newborn care practices and those typical in the study area. The results of this formative research have informed strategies for behavior change and improving referral of sick infants in the subsequent implementation study. Collection and dissemination of data on newborn care practices from settings such as these can contribute to efforts to advance survival, growth and development of newborns for intervention research, and for future newborn health programming.

The ability to monitor Sprained Ankle Rehabilitation Exercises (SPAREs) in home environments can help therapists to ascertain if exercises have been performed as prescribed. Whilst wearable devices have been shown to provide advantages such as high accuracy and precision during monitoring activities, disadvantages such as limited battery life, users' inability to remember to charge and wear the devices are often the challenges for their usage. Also, video cameras, which are notable for high frame rates and granularity, are not privacy-friendly. This paper, therefore, proposes the use and fusion of unobtrusive and privacy-friendly sensing solutions for data collection and processing during SPAREs in home environments. Two Infrared Thermopile Array (ITA-32) thermal sensors and two Frequency Modulated Continuous Wave (FMCW) Radar sensors were used to simultaneously monitor 15 healthy participants during SPAREs which involved twisting their ankle in 4-fundamental movement patterns namely (i) extension, (ii) flexion, (iii) eversion and (iv) inversion. Experimental results indicated the ability to identify thermal blobs of participants performing the 4 fundamental movement patterns of the human ankle. Cluster-based analysis of data gleaned from the ITA-32 sensors and the FMCW Radar sensors indicated average classification accuracy of 96.9% with K-Nearest Neighbours, Neural Network, AdaBoost, Decision Tree, Stochastic Gradient Descent and Support Vector Machine, amongst others.

This paper is aimed at studying the temporal evolution of the surface displacements occurred over the past few years in the ocean-reclaimed platforms of the Shanghai megacity (China), which are mainly ascribable to consolidation processes of large dredger fills and alluvial deposits. With respect to previous analyses carried out over the same area, this work provides a joint multi-platform differential interferometry synthetic aperture radar (DInSAR) analysis, based on the application of the advanced Small BAseline Subset (SBAS) algorithm. This led us to retrieve long-term deformation time-series that are helpful for a better understanding of the on-going deformation phenomena. To this aim, we have exploited two sequences of SAR data collected by the ASAR/ENVISAT and by the COSMO-SkyMed (CSK) sensors, respectively, spanning the whole time period from 2007 to 2016. Unfortunately, the large time gap (of about three years) existing between the available ASAR/ENVISAT and CSK datasets gave rise to additional difficulties for their combination. Nevertheless, this problem has been faced by benefiting from the knowledge of a time-dependent model describing the temporal evolution of the expected deformations affecting the Shanghai ocean-reclaimed platforms.

Recently, the Internet of Things (IoT) has attracted wide attention from many fields, especially healthcare, because of its large capacities of information perception and collection. In this paper, we present an IoT-based home telehealth system for providing smart healthcare management for individuals, especially older people. Each client node of the system is mainly composed of an electronic water meter that records the user's daily water usage and an unobtrusive sleep sensor that monitors the user's physiological parameters during sleep such as heart rate (HR), respiratory rate (RR), body movement (BM), and states on the bed or outside the bed. The sleep sensor senses the biosignals and states by a sensor matrix composed of 12 piezoelectric sensors. The collected data can be transmitted to a remote centralized cloud service by a wireless home gateway for analyzing the living pattern and rhythm of users. Furthermore, the periodic feedback of results can be provided to users themselves as well as their family and health advisers. In the present study, data collections from a total of 18 older subjects were made for one year to evaluate the effectiveness of the proposed system. By analyzing living pattern and rhythm, preliminary results indicate the effectiveness of the telehealth system and suggest the potential of the system regarding improvement of quality of life (QoL) of older people and promotion of their health.

One of the tools for optimal crop production is regular monitoring and assessment of crops. During the growing season of fruit trees, the bloom period has increased photosynthetic rates that correlate with the fruiting process. This paper presents the development of an image processing algorithm to detect peach blossoms on trees. Images of an experimental peach orchard were acquired from the Parma Research and Extension Center of the University of Idaho using an off-the-shelf unmanned aerial system (UAS), equipped with a multispectral camera (Near-infrared, Green, Blue). The orchard has different stone fruit varieties and different plant training system. Individual tree images (high-resolution) and arrays of trees images (low-resolution) were acquired to evaluate the detection capability. The image processing algorithm was based on different vegetation indices. Initial results showed that the image processing algorithm could detect peach blossoms and demonstrate good potential as a monitoring tool for orchard management.

Dolichandrone spathacea is a rare and endangered semi-mangrove plant species with an extremely small population, naturally distributed only in Zhanjiang City and the east coast of Hainan Island, China. Regrettably, the present situation of the D. spathacea population in China has not yet been carefully investigated. In this study, we aim to evaluate the current resource status and population dynamic characteristics of D. spathacea on Hainan Island, China, in order to propose sustainable conservation and management strategies for future ecological restoration of its natural population. Our results show that D. spathacea on Hainan Island can be divided into four populations. All the D. spathacea populations present a state of overall dispersion, local concentration, and occasionally sporadic existence, and they exist in geographical isolation. The young, middle, and old D. spathacea plants account for 20.42%, 66.20%, and 13.38%, respectively, indicating that the overall age class of the D. spathacea population on Hainan Island belongs to a declining type. Furthermore, instead of temporal structure, we chose diameter at breast height (DBH) to establish a static life table, draw a population survival curve, and quantify the future development trend through population dynamic analysis and time-series prediction. These results directly point out that the D. spathacea population on Hainan Island is sensitive to external disturbances and possesses two main increases in mortality rate—namely, in its juvenile and mature stages—due to weak vitality, competition, and anthropogenic interferences, which are the most important reasons for its endangered status. Depending on the current conditions of the D. spathacea population, we should conserve and expand mature trees in situ, preserve their germplasm resources, rehabilitate their habitats to promote provenance restoration, and conduct artificial cultivation and spreading planting in order to realize the sustainable conservation and management of D. spathacea.

This paper investigates an Energy Neutral System using Micro Energy Harvesters for a Health Monitoring Wireless Sensor Node (HM-WSN). We have implemented HM-WSN consisting of a solar cell energy harvester, a Power Management Unit (PMU) and the ucontroller, sensor and transmitter acting as load. A battery extender and a switching logic circuit for sensor node is designed to evaluate the efficiency of the proposed system. The HM-WSN senses body temperature with improvement in lifetime of coincell. The HM-WSN is built using commercially available off the shelf (COTS components and consumes 47.2uW for data being updated every 134s. It can be operated for approximately 1.32 years only on a coincell. Furthermore, the HM-WSN can be operated with solar energy at 200lux, achieving 96.36 years with a combination of a coincell with an additional capacitor of 2.2mF. It attains 4.07 years to 16.87 years lifetime with the load capacitor varying from 1mF to 1.5mF at 350lux lighting condition. With the same ambient condition and a 2mF load capacitor, HM-WSN attains complete energy autonomy.

This paper details the comprehensive activities conducted in a laboratory setting to assess the Structural Health Monitoring (SHM) of prefabricated building envelopes. Aimed at enhancing the structural evaluation of buildings, the focus of this research lies in employing nondestructive sensors for SHM with the objective to advance in the understanding and assessment of facade conditions. The paper outlines the methodologies employed, starting with a modal analysis to define the structural vibration's modal frequency. Subsequently, tests were defined and executed to validate building envelope compliance in case of stress typical of high-rise building. Throughout these tests, continuous monitoring of the façade was conducted using both conventional (accelerometers, extensimeter washers) and non-conventional sensors (Fiber Optic Sensing) The gathered data underwent thorough processing and analysis to provide an overall perspective on the structure's behavior during the stress test. The investigation aimed to identify whether specific physical phenomena correlate with distinct signals and to evaluate if continuous façade monitoring over the building's lifespan aids in preventing potential structural damage. Moreover, two modal analyses were conducted to compare final data and frequencies with earlier data, enabling the detection of any structural alterations. The results from compliance testing and structural analysis yielded noteworthy insights contributing to the evolving field of structural health monitoring, offering valuable findings that advance our ability to proactively manage and maintain the integrity of building structures.

Abstract: Toxicity of emerging organic pollutants to photosystems of aquatic plants are still not well clarified. This study aimed to develop a novel ecotoxicological experimental protocol based on nanoscale electrochemical mapping of photosynthetic oxygen evolution of aquatic plants by SECM (scanning electrochemical microscopy). The protocol was also checked by confocal laser scanning microscopy (CLSM), the traditional Clark oxygen electrode method and chlorophyll fluorescence technique. The typical persistent organic pollutant 2,4-dichlorophenol (2,4-DCP) in water environment and the common aquatic Microsorium pteropus (M. pteropus) were chosen as the model organic pollutant and tested plant, respectively. It was found that the SECM method could well discriminated the responses of stoma micromorphology and spatial pattens of photosynthetic oxygen evolution on single stoma. The shape of stoma blurred with increasing 2,4-DCP concentration, which was in good agreement with the CLSM images. The dose-response curves and IC50 values obtained from the SECM data were verified by the data measured by the traditional Clark oxygen electrode method and chlorophyll fluorescence test. The IC50 value of single stoma oxygen emission of 24 h exposed plant leave, which was derived from the SECM current data (32535 μg L-1), was close to those calculated from the maximum photosynthetic efficiency (Fv/Fm) measured by chlorophyll fluorescence test (33963 μg L-1), and the Clark oxygen electrode method photosynthetic oxygen evolution rate (32375 μg L-1). The 72 h and 96 h 2,4-DCP exposure data further confirmed the reliability of the nanoscale stoma oxygen emission mapping methodology for ecotoxicological assessment. In this protocol, the procedures for how to collect effective electrochemical data and how to extract useful information from the single stoma oxygen emission pattern were well established. This study showed that SECM is a feasible and reliable ecotoxicological tool for evaluation of toxicity of organic pollutants to higher plants with unique nanoscale visualization advantage over the conventional methods.

This review delves into the growing field of flexible and stretchable strain sensors utilized in human gait analysis, focusing on determining knee bending angle and muscle activities when a human subject walks. Recent advancements have enabled these sensors to accurately capture biomechanical parameters while accommodating the body's natural movements. We examine the principles underlying these sensors' design and fabrication techniques, emphasizing their flexibility, stretchability, and biocompatibility for seamless integration into wearable systems. Through critical evaluation of existing methodologies, we assess the reliability and validity of these sensors in quantifying gait parameters. Furthermore, we discuss this technology's clinical and research implications, highlighting its potential in personalized rehabilitation and sports performance optimization. We provide an overview of flexible strain sensors and their application for analyzing human walking gait, especially for observing walking gait in rehabilitation programs. First, we present the basic working principles of various flexible strain sensors. Second, by the application of flexible strain sensors as walking gait monitoring. Finally, current challenges and future opportunities in this research area are discussed. By synthesizing current knowledge and outlining future directions, this review aims to provide insights for researchers and practitioners seeking to leverage flexible and stretchable strain sensors for comprehensive human gait analysis.

: Tunnel instability and lining integrity are intimately tied to the creep properties of the surrounding rock. The acquisition of rock mass creep parameters is critical in ascertaining the appropriate timing for lining construction. Nevertheless, creep tests on rock specimens conducted in a controlled setting cannot be straightforwardly extrapolated to rock mass creep analysis. This study performs laboratory-based creep tests on mudstone samples and establishes the corresponding creep constitutive model. Integration of a Mohr-Coulomb element with the Burgers model in series serves to characterise the yield creep behaviour of the rock mass. Additionally, the research outlines a series of 100 orthogonal experiments utilising randomised creep parameters, and formulates a GA-BP neural network inversion model. Employing long-term deformation measurements from the crown and sidewalls of the project site, this study deduces the creep parameters of the mudstone in the investigated tunnel section and examines the prolonged deformation traits of the surrounding rock. Drawing on the deformation traits of the surrounding rock and the forces impacting the primary support and lining structures, this paper evaluates the earliest and latest viable lining casting periods and pinpoints an optimal timing interval for lining implementation. The methodologies employed herein can serve as a benchmark for analogous endeavors internationally.

Floods are a common natural disaster whose severity in terms of duration, water resource volume, peak and accumulated rainfall-based damage are likely to differ significantly for different geographical regions. In this paper, we first propose a novel hourly flood index (SWRI24−hr−S), derived from normalising the existing 24-hourly water resources index (WRI24−hr−S) in literature, to monitor flash flood risks on an hourly scale. The proposed SWRI24−hr−S is adopted to identify a flood situation and derive its characteristics, such as the duration (D), volume (V) and peak (Q). The comprehensive result analysis establishes the practical utility of SWRI24−hr−S in identifying flood situations at seven study sites in Fiji between 2014 and 2018 and deriving their characteristics (i.e., D, V, and Q). Secondly, this study develops a vine copula-probabilistic risk analysis system that models the joint distribution of flood characteristics (i.e., D, V, and Q) to extract their joint exceedance probability for the seven study sites in Fiji, enabling probabilistic flood risk assessment. The vine copula approach, particularly suited to Fiji’s study sites, introduces a novel probabilistic framework for flood risk assessment. The results show moderate differences in the spatial patterns of joint exceedance probability of flood characteristics in different combination scenarios generated by the proposed vine copula approach. In the worst-case scenario, the probability of any flood event occurring where the flood volume, peak and duration are likely to exceed the 95th-quantile value (representing an extreme flood event) is found to be less than 5% for all study sites. The proposed hourly flood index and the vine copula approach can be feasible and cost-effective tools for flood risk monitoring and assessment. The methodologies proposed in this study can be applied to other data-scarce regions where only rainfall data is available, offering crucial information for flood risk monitoring, assessment, and the development of effective mitigation strategies.

In recent decades, as eutrophication in inland and coastal waters (ICWs) has increased due to anthropogenic activities and global warming, so has the need for timely monitoring. Compared with traditional sampling and laboratory analysis methods, satellite remote sensing technology can provide macro-scale, low-cost, and near real-time water quality monitoring services. The Geostationary Ocean Color Imager (GOCI), integrated onboard the Communication Ocean and Meteorological Satellite (COMS) from the Republic of Korea, was the first geostationary ocean color observation satellite and was operational from April 1, 2011 to March 31, 2021. Over ten years, GOCI has observed oceans, coastal waters, and inland waters within its 2,500 km×2,500 km target area centered on the Korean Peninsula. The most attractive feature of GOCI, compared with other commonly used watercolor sensors, was its high temporal resolution (1h, eight times daily from 0 UTC to 7 UTC), providing the opportunity to monitor the quality of ICWs, where optical properties can change rapidly throughout the day. This systematic review aims to comprehensively review GOCI features and applications in ICWs, analyzing progress in atmospheric correction algorithms and water quality monitoring. Analyzing 123 articles from the Web of Science and China National Knowledge Infrastructure (CNKI) through a bibliometric quantitative approach, we examined GOCI’s strength and performance with different processing methods. These articles reveal that GOCI played an essential role in monitoring the ecological health of ICWs in its observation area in East Asia. GOCI has led the way to a new era of geostationary ocean satellites, providing new technical means for monitoring water quality in oceans, coastal zones, and inland lakes. We also discuss the challenges encountered by geostationary satellites in monitoring water quality and provide suggestions for improvements.

Air pollution has created a lot of problems in the developed and developing countries. To avoid or reduce these problems, constant monitoring of the air should be ensured. The conventional techniques is costly because it requires a lot of money and time consuming. Biomonitoring has been the alternative method. Moss, lichens and plants are biomonitors available to entrap air pollutants. The aim of this paper is to discuss one of the ways of monitoring air pollution – Moss bag technique. To do this, types, choice, preparation, handling of bags after preparation of moss were discussed. From the literatures consulted, it was discovered that there were differences in the techniques used by the researchers. In all, the use of mosses with emphasis on the employment of moss bag have proved to be a powerful tool in airborne particulate and toxic elements. To conclude, developing countries should focus more on this technique because it will reduce cost of air monitoring.

To make wind power more competitive, it is necessary to reduce turbine downtime and reduce costs associated with wind turbine Operation and Maintenance (O&M). Incorporating machine learning in developing condition-based predictive maintenance methodologies for wind turbines can enhance their efficiency and reliability. This paper presents a monitoring method that utilizes Base Density for the Support Vector Machine (BDSVM) and the evolutionary Fourier spectra of vibrations. This method allows smart monitoring of the function evolution of the turbine. A complex optimal function (FO) for 5-degree order has been developed that will be the boundary function of the BDSVM to timely determine the magnitude, frequency, and place of the failure occurring in wind turbine drive.

Solid waste management is a global issue that affects every individual living in the world directly or indirectly. Failing to manage the waste properly will cause harm on public health, our natural environment, and even our happiness and prosperity. When asked about the reason behind the failure of third time plastic ban in Bhutan, one of the Bhutanese said it’s because of the lack of cooperation from public to support the move of government. Clean Bhutan, a non-governmental organization (NGO) that aims Zero Waste Bhutan by 2030, has collected around 5,900 metric tons of waste from December 2014 to February 2018. This project will create some awareness regarding the management of waste at individual level when people come in contact with the family of the researcher. It also talks abot how waste management and biodiversity conservation can go side by side.

Agro-meteorology is the relationship between agriculture and weather. All farm activities are affected by weather. Therefore it is always necessary to monitor the weather as a forecast. The aim of the research was to monitor the weather and rainwater samples obtained at Federal College of Agriculture, Akure, Ondo State, Nigeria. For the eight months periods, results were obtained. The mean results for the physicochemical parameters were: TDS (12.25 mg/L), temp (28.13 ^oC), pH (6.63), EC (24.25µS/cm), Free CO₂ (24.38mg/L), nitrate (0.16mg/L), phosphate (0.17mg/L), sulphate (0.18mg/L). The rainwater was colorless and had no odor. The mean meteorological data: The prevailing wind directions were from SE, mostly in May, June, July and November and NE. The dry and wet temperatures were 22-29 ^oC and 20-26 ^oC respectively. The maximum value was observed in the month of July. The correlation matrix showed that there were many strong correlations in the physicochemical properties. The months of May, June and July had the highest wind speed. In these months there would be a need to use a windbreaker around the crops planted to avoid soil erosion and damaging of plants.

The Food and Drug Administration’s 2011 Process Validation Guidance and International Council for Harmonization Quality Guidelines recommend continued process verification (CPV) as a mandatory requirement for pharmaceutical, biopharmaceutical, and other regulated industries. As a part of product life cycle management, after process characterization in stage 1 and process qualification and validation in stage-2, CPV is performed as stage-3 validation during commercial manufacturing. CPV ensures that the process continues to remain within a validated state. CPV requires the collection and analysis of data related to critical quality attributes, critical material attributes, and critical process parameters on a minimum basis. Data is then used to elucidate process control regarding the capability to meet predefined specifications and stability via statistical process control tools. In statistical process control, control charts and Nelson rules are commonly used throughout the industry to monitor and trend data to ensure that a process remains in control. In the control chart, the mean value is taken as the center line, and 3σ limits are placed on either side of the center line. In CPV, manufactured lots are summarized, trended, and discussed at a cross-functional level at pre-defined intervals (either weekly, bi-weekly, or even monthly) based on the batch run rate. A cross-functional team assesses details regarding 1) violation frequency, 2) statistical strength of the signal, 3) violation magnitude and its impact on process or quality, and 4) any potential root causes for out-of-expectation or out-of-trend signals. The cross-functional team must analyze whether any signal identified by the control chart is reliable and must determine whether corrective action should be taken and justify the decision in the CPV meeting minutes based on statistical strength and reliability of the signal. However, basic control charts are susceptible to false alarms and nuisance alarms. Therefore, it is imperative to understand the assumptions behind control charts and the inherent false alarm rates for different Nelson rules. In this article, the authors have detailed the assumptions behind the usage of control charts, the rate of false alarms for different Nelson rules, the impact of skewness and kurtosis of a data distribution on the false alarm rate, and methods for optimizing control chart design by reducing false alarm rates and nuisance signals.

Monitoring of clients living with HIV encompasses a specific array of activities that routinely check on various aspects of ART following its initiation depending on the availability of resources in that particular state, among other factors as per guidelines from the World Health Organisation. This is a significant practice as it promotes positive health outcomes for patients and efficient utilisation of ART regimens to reduce resistance to the medication – hence it is a measure to guard avoidable costs. It also forms a basis on which decisions are made from. It can be done clinically by assessing for signs e.g., skin rash and symptoms e.g., nausea and vomiting, checking vital organ function and measuring weights across all populations, or can be also be done by assessing specimens for their respective viral loads, white blood cell count, pregnancy status or other infections such as hepatitis B. There have not been any special indications required for one to be eligible for monitoring during ART in developing countries; all qualify for routine monitoring even though some may be more frequent than others in cases of comorbidities such as renal failure where medications can be attributed to exacerbating the condition.

In 2020 the world experienced the threat of the COVID-19 epidemic, as seniors and chronic disease patients typically try to reduce their exercise and social activities to avoid increasing the risk of infection, which could lead to increased loneliness and even many diseases. This research combining golf croquet games with AIoT companion robots constructs a home-based intelligent exercise system thus uses the Technology Acceptance Model (TAM), deduces users’ intention to use this system based on perceived usefulness and perceived ease of use, and adds the needs of love and belonging, esteem, cognitive, aesthetic, and self-actualization in Maslow’s needs theory to conduct system needs analysis. The analysis results show that participants have a high level of acceptance of this system, believing that it is easy to learn and operate, can increase interaction with others, also found that this system can improve self-confirmation, satisfying the third for knowledge, feeling happy, and self-actualization needs are easier to fulfill. In the future, we shall collect and record the seniors in the process of use, so as to find out their health problems as soon as possible, expand their daily life through this exercise, and achieve the goal of happy living and health care.

The study reports about a case of a lung cancer patient with increasing difficulties in falling asleep and frequent periods of wakefulness. Severe dyspnea related to pneumonitis caused as a side effect of immunotherapy worsened the situation. Eventually, fear of falling asleep developed, including panic attacks and anxiety of choking, which was shown to lead to nights of complete wakefulness. The patient did not only sleep poorly; he did not sleep at all at night for several days, as evidenced by the notes he made during the night. Polygraphy showed no evidence of sleep-disordered breathing, but frequent periods of wakefulness and reduced basal saturation around 90% during sleep due to lung changes such as extensive functional failure of the left upper lobe with position-dependent shunts. The authors hypothesized that the symptoms described were causally related to a drop in oxygen saturation in the patient's blood. Therefore, they pursued the goal of finding a measurement technique that is as inexpensive as possible and that the patient can operate without outside assistance and great effort. So the patient started using a low-cost wearable device that allows simultaneous measurements of blood oxygen content, pulse rate and movement intensity. It consists of a finger ring with pulse oximetry sensor and a wristband with the control unit containing a vibration motor. The described device reliably warned of disturbances in oxygen concentration in the blood during the night with its vibration alarm. By use of that device during the whole night at home, the events of reduced oxygen saturation and the anxiety symptoms were reduced. Sleep disturbances with sudden awakenings did not occur when using the device. The patient benefited from the security gained in this way and slept much more peacefully, and he could spend nights without waking up again. In conclusion, wearable oximeters with vibration alarm can be recommended for patients’ home care in lung cancer patients.

The increasing regulatory pressure to monitor and reduce GHG emissions and air pollutants requires cost-effective methods for their surveillance. The most common technique used for scientific investigations on gas concentration monitoring in barns are accurate but expensive and with a complex maintenance. This research study analysed the potential use of a low-cost portable measurement devices for the measurement of ammonia (NH3) and carbon dioxide (CO2) concentrations in an open dairy barn. A comparison between gas concentrations acquired at different heights from the floor by using portable devices and those acquired by a photoacoustic infrared multigas spectroscope (i.e., reference measurement) in the same sampling locations was carried out to determine the precision of the low-cost portable devices. The performance of low-cost portable devices was statistically analysed by the application of the one-way analysis of variance, correlation analysis and regression analysis. The results showed a significant difference between gas concentration values at various heights from the floor for both NH3 and CO2. The correlations between concentrations acquired by the low-cost portable device and the INNOVA were statistically significant (r=0.83; P<0.001) for gas concentrations monitored at 0.4 m from the floor. Compared with the reference measurement device, the low-cost devices were effective in the monitoring of NH3 concentrations at 0.40 m from the floor though it underestimated them in the barn at increasing of the height from the floor, whereas the device was not adequate for CO2 concentrations. In detail, the relative measurement error of the low-cost devices compared to INNOVA was reduced close to the floor during NH3 concentration measurements. Within these limitations, this device could be useful for monitoring NH3 concentration in the barn and to assess variation in NH3 concentrations mainly related to the animal occupied zone. Further efforts are needed in this field of research to identify low-cost device that could simplify emission estimation from open dairy barns.

The practice of telework, remote work, and working from home has grown significantly across the pandemic era (2020+). These practices offer new ways of working but come with a lack of clarity as to the role it plays in supporting the wellbeing of staff. (1) Background: the purpose of this study is to examine the current literature on wellbeing outcomes and effects of telework; (2) Methods: this study adopts a systematic literature review from 2000-2022 using the PRISMA approach and thematic analysis guided by the United Nations Sustainable Development Goals (Wellbeing, Decent Work, Gender Equality, and Inclusive Production); (3) Results: it was evident that there is a lack of clarity on the actual effects of telework on employee wellbeing, but it appeared that it had a generally positive effect on short-term wellbeing of staff, and created more flexible and proactive work design opportunities; (4) Conclusions: there is a need for more targeted research into work designs that support wellbeing and productivity of staff, and consider the environmental sustainability changes from reduced office and onsite work and increased working from home.

Abstract Background: Premature babies have a greater risk for having health issues after being discharged from the hospital whilst the mother ability to provide premature baby care still has many issues as well. Interventions are needed to be given to mothers at home to improve the ability of mothers to care their premature babies. Methods: Search for articles used the bolean operator of “or” and “and” with the keywords used were “preterm or premature”, “intervention or program”, and “mother and home”. Data based used were Sciencedirect, Ebscohost, PubMed, SAGE, Proquest and Scopus with inclusion criteria using full text in English from 2018 to 2021. There were 428 articles obtained, the articles were then screened by reading the main focus of articles with paying attention to the topic and the suitability of article content and we obtained 13 suitable articles. Results: The interventions at home carried out for mothers and premature babies were divided into two namely the follow-up interventions from the hospital and the interventions carried out at the patient's home. Seven articles about research of interventions that were as a combination from hospital intervention with follow-up hospital intervention plus five full interventions at the patient's home. Interventions were provided through home visits (12 articles) and by telephone (1 article). The results of the article analysis resulted in 4 main themes of intervention for mothers and premature babies, they were health education, counceling, support, and care for premature babies. Conclusion: Quality care is essential for the best health, growth and development of premature babies. Interventions need to be carried out by health workers to ensure the readiness and ability of mothers to care for their babies. Maternal readiness and abilities can be improved by providing health education, counseling, support and care for premature babies.

Shared public buildings have become centers of innovation, integrating advanced technologies to meet evolving societal needs. With a heightened emphasis on occupants’ health and well-being, these buildings serve as hubs for technological convergence, facilitating seamless connectivity and intelligent data analysis and management. Within this context, environmental monitoring emerges as a foundational element, pivotal to all aspects of building management. This article provides findings from the nationally funded RE-START project, which focuses on shared public buildings, with special regard to educational and medical facilities. The project explores enhanced indoor air quality monitoring, focusing in particular on CO2 concentration that is directly correlated with occupancy, as a fundamental element for developing health and safety protocols, energy efficiency strategies, integration of smart building technologies, and data-driven energy management. The intersection of environmental monitoring, energy efficiency, security, and IoT technologies in in indoor spaces are relevant. The outcomes of the study reveal the delicate nature of all the involved components, that need to be carefully developed in an integrated manner.

This manuscript presented an autonomous home farm for predicting metrological characteristics that can not only automate the process of growing crops but also, due to a neural network, significantly increase the productivity of the farm. The developed farm monitors and manages the following indicators: illumination, soil PH, air temperature, earth temperature, air humidity, CO2 concentration, and soil moisture. The presented farm can also be considered as a device for testing various weather conditions to determine the optimal temperature characteristics for different crops. This farm as a result is completely autonomous grows tomatoes at home.

Solid tumors universally possess the ability to evade contact inhibition of proliferation (CIP), a mechanism halting cell proliferation when cell-cell contacts occur. Merlin, an ERM-like protein, crucially regulates CIP and is frequently deactivated in various cancers, indicating its signifi-cance as a tumor suppressor in cancer biology. Despite extensive investigations into Merlin's role in cancer, its lack of intrinsic catalytic activity and frequent conformation changes has made it notoriously challenging to study. To address this challenge, we harnessed innovative luciferase technologies to create and validate a split-luciferase biosensor system. This system enables precise quantification of Merlin's conformation and activity both in vitro and within living cells. This biosensor significantly enhances the study of Merlin's molecular functions, serving as a potent tool to explore its contributions to CIP and tumorigenesis.

The study assessed the trapping efficacy of locally-modified 1) Gravid Aedes Trap(GAT) lined with insecticide-treated net (ITN) as a killing agent, 2) Autocidal Gravid Ovitrap(AGO) with sticky board in the semi-field system (SFS) and field setting. Fully-balanced Latin square experiments were conducted to compare GAT lined with ITN vs AGO, both with either yeast or grass infusion. Biogents-Sentinel (BGS) with BG-Lure and no CO2 was used as standard trap for Aedes mosquitoes. In the SFS, GAT outperformed AGO in collecting both nulliparous (65% vs 49%,OR=2.22,[95%CI:1.89-2.60],p

Acute and chronic graft versus host disease (a/cGVHD) are major complications of allogeneic stem cell transplantation and a frequent cause of non relapse-mortality. The treatment of a/cGVHD consists of steroid administration at full dose. In the case of aGVHD, around 60 % of patients with grade III/IV fails to respond (steroid-resistant, SR), requiring a second line therapy. Extracorporeal photopheresis (ECP) represents a good option for second line treatment, leading to multiorgan response in several patients. Here, we have evaluated the performances of a cytofluorimetric quality control of the first ECP procedure in 29 patients with severe SR aGVHD who underwent ECP. The quality control represents a check control of in vitro cell apoptosis/death induction in collected and irradiated CD3+ cells by ECP. Our analysis shows that in more than 70 % quality controls a relevant apoptotosis/death of CD3+ cells was observed after cell irradiation, as compared to non-irradiated controls. Albeit observed in a small patients’ series, the occurrence of relevant in vitro effect after ECP relates to less procedures and/or to a better survival on ECP. Age, disease, gender, aGVHD grade and time from transplant to the first ECP had not impact on ECP efficacy in this patients’ series.

Persistent land subsidence or uplift can cause serious latent hazards to urban infrastructure. To thoroughly investigate the causes and impacts of land surface deformation, this study examines the case of Wuxi City, focusing on the land fluctuation patterns in the region following the enforcement of the groundwater abstraction prohibition policy in 2005. This research utilizes the PS-InSAR technique to quantify land surface deformations in the Wuxi region from November 2015 to June 2023 and analyzes 100 SAR images to obtain comprehensive spatiotemporal evolution data of the land surface. Furthermore, this study conducts an in-depth analysis of the effects of various factors, including groundwater, precipitation, and soil geology, on the characteristics of land surface deformation. It pioneers the application of the GARCH (Generalized Autoregressive Conditional Heteroskedasticity) model to analyze the time-series displacement in the study area and innovatively introduces the "amplitude factor" index to assess land surface fluctuations. This study investigates the recent land surface deformation patterns and mechanisms in Wuxi City. By integrating the "amplitude factor", it provides a scientific foundation for future urban development and disaster mitigation strategies in Wuxi City, offering valuable insights for related research.

The European Union Water Framework Directive (2000/60/EC; WFD) aims to achieve a good ecological and chemical status of all bodies of surface water by 2027. The development of an integrated guidance on surface water chemical monitoring (e.g. WFD Guidance Document No. 7/19) has been transferred into national German law (Ordinance for the Protection of Surface Waters, OGewV). For the majority of compounds, this act requires a monthly sampling frequency to assess the chemical water quality status of a surface water body. To evaluate the representativeness of the sampling strategy under the OGewV, high-frequency online monitoring data is investigated under different sampling scenarios and compared with current, monthly grab sampling strategy. About 23 million data points were analyzed for this study, three chemical parameters (dissolved oxygen, nitrate-nitrogen, chloride concentration) and discharge data were selected from four catchment of different sizes ranging from 51391 km² to 84 km² (Elbe, Vereinigte Mulde, Neiße and two stations at Lockwitzbach). In this paper we proposed short-term online-monitoring (STOM) as a sampling alternative. STOM considers the placement of online sensors over a limited duration and return interval. In general we: (I) compare the results of conventional grab sampling with STOM, (II) investigate the different performance of STOM and grab sampling using discharge data as proxy for analyzing event-mobilized pollutants and (III) investigate the related uncertainties and costs of both sampling methods. Results show, that STOM outperforms grab sampling for parameters where minimum/maximum concentrations are required by law as the probability to catch a single extreme value is higher with STOM. Furthermore, parameters showing a pronounced diurnal pattern, like dissolved oxygen, are also captured considerably better. The performance of STOM showed no substantial improvements for parameters with small concentration variability, as nitrogen-nitrate The analysis of discharge events as a proxy parameter for event-mobilized pollutants proved that the probability of capturing samples during events is significantly increased by STOM.

Background: Nursing home residents (NHRs) have special needs and may experience reduced functionality, higher sedentary behavior time (SBT) and decreased physical activity (PA). This study aimed to characterize NHRs based on SBT, PA, and functional performance (FP), and to identify associations between these factors. Methods: Cross-sectional study with 65 NHRs aged ≥60, evaluated by accelerometer (SBT, PA) and the following tests: Timed Up and Go (TUG), Short Physical Performance Battery (SPPB), Barthel Index (BI), and Mini-Mental State Examina-tion (MMSE). Health-related variables and anthropometry were assessed. The FP (TUG, SPPB, BI), SBT, PA intensities were used for K-means clustering analysis. Results: The cluster analysis identified: C1 – better FP, shorter SBT, and longer time in PA intensities; C2 - lower FP, longer SBT, and shorter time in PA. In addition, C2 were older, with lower MMSE, lower body mass index, and walking aids use. The SBT showed a negative weak correlation with BI. The moderate PA (MPA) was moderately correlated with the SPPB and strongly correlated with the TUG and BI. Conclusions: MPA is strongly associated with better FP and independence. NHRs have dif-ferent physical and cognitive profiles, which indicates the need for personalized strategies to prevent disability and increase PA.

Parental stresses are normal responses to raising children. They are affected by stresses parents and children accumulate and bring to their interrelations. Background factors like economic difficulties or the relations between the parents may affect parental stresses as well as demographic and environmental factors like noise and access to urban parks. Most studies on parental stress are based on a verified psychological questionnaire. We suggest using frequency domain heart rate variability index (HRV) to measure parental stress enabling, by thus, the measurement of physiological aspects of stress and risk to health. Parental stress is measured as the difference between HRV accumulated at home while staying with the children and without the husband and HRV measured in the neighborhood while staying without the children and the husband. We use the index to compare differences among Muslim and Jewish mothers in exposure to maternal stress at their homes and to expose the factors that predict differences in maternal stress. We found that Muslim mothers suffer from home-related maternal stress while Jewish mother do not. Number of children and ethnically related environmental aspects predict differences in maternal stress between Muslim and Jewish mothers. Muslims' lower access to parks stems from lack of home garden and parks in their neighborhoods in the Arab towns but mainly by restrictions on Muslim women's' freedom of movement to parks. Despite differences in levels of noise at home and in the status of the mother in the household, these factors did not predict differences in parental stress. Instead, the study highlights the crucial role of greenery and freedom of movement to parks in moderating home-related maternal stress.

A Smart Home is characterized by the presence of a huge number of small, low power devices, along with more classical devices. According to the Internet of Things (IoT) paradigm, all of them are expected to be always connected to the Internet in order to provide enhanced services. In this scenario, an attacker can undermine both the network security and the user’s security/privacy. Traditional security measures are not sufficient, because they are too difficult to setup and are either too weak to effectively protect the user or too limiting for the new services effectiveness. The paper suggests to dynamically adapt the security level of the smart home network according to the user perceived risk level what we have called network sentiment analysis. The security level is not fixed, established by a central system (usually by the Internet Service Provider) but can be changed with the users cooperation. The security of the smart home network is improved by a distributed firewalling and Intrusion Detection Systems both to the smart home side as to the Internet Service Provider side. These two parts must cooperate and integrate their actions for reacting dynamically to new and ongoing threats. Moreover, the level of network sentiment detected can be propagate to nearby home networks (e.g. the smart home networks of the apartments inside a building) to increase/decrease their level of security, thus creating a true in-line Intrusion Prevention System (IPS). The paper also presents a test bed for Smart Home to detect and counteract to different attacks against the IoT devices,,Wi-Fi and Ethernet connections .

Home Security Systems are very important features of modern residential and office setups. This system is used to keep home safe from harmful gases, fire and intruders. It must be affordable, reliable and effective. In this paper, a GSM based home security system has been designed and implemented. The system consists of a GSM Module, MQ-2 smoke detector, Ultrasonic sonar sensor, LM35 temperature sensor, Arduino Uno and relay module. The MQ-2 smoke detector is used to detect harmful gases i.e. LPG, CH₄, CO, Alcohol, Smoke or Propane. Any of the harmful gases stated above is detected it will warn the owner by activating the buzzer and displaying a warning message on the LCD display. It will also send a SMS to the owner. Our system can also measure temperate and if the temperature is increased above a certain range it will compensate it by activating Air Conditioner through the relay module. The system will also send a SMS to the owner. It can also detect intruders using Ultrasonic sensor and warn us through buzzer, SMS and displaying message on the LCD. Our system is reliable as it has very fast response and cost effective and it has been developed using our own technologies.

In contrast to physical sustainable measures carried out in homes, such as insulation, the installation of a Home Energy Management System (HEMS) has no direct and immediate energy-saving effect. A HEMS gives insight into resident behaviour regarding energy use. When this is linked to the appropriate feedback, the resident is in a position to change his or her behaviour. This should result in reduced gas and/or electricity consumption. The aim of our study is to contribute towards the effective use of home energy management systems (HEMS) by identifying types of homeowners in relation to the use of HEMS. The research methods used were a literature review and the Q-method. A survey using the Q-method was conducted among 39 owners of single-family homes in various Rotterdam neighbourhoods. In order to find shared views among respondents, a principal component analysis (PCA) was performed. Five different types of homeowner could be distinguished: the optimists, the privacy-conscious, the technicians, the sceptics, and the indifferent. Their opinions vary as regards the added value of a HEMS, what characteristics a HEMS should have, how much confidence they have in the energy-saving effect of such systems, and their views on the privacy and safety of HEMS. The target group classification can be used as input for a way in which local stakeholders, e.g. a municipality, can offer HEMS that is in line with the wishes of the homeowner.

Separase is a key cysteine protease to separate sister chromatids through digestion of cohesion ring that inhibits chromosome segregation as trigger of metaphase–anaphase transition in eukaryotes and highly regulated its activity by binding with securin and cyclinB-CDK1 complex. Those bindings prevent proteolytic activity of separase until the onset of anaphase. Chromosome missegregation and aneuploidy are frequently observed in malignancies. However, there are some difficulties for biochemical examinations due to instability of separase in vitro and a few spatiotemporal resolution approaches monitoring live separase activity throughout mitotic processes. Here we have developed FRET-based molecular sensors including GFP variants with separase cleavable sequences as donor and covalently attached fluorescent dye as acceptor molecules applicable to conventional live cell imaging and flow cytometric analysis because of efficient live cell uptake. We investigated performance of equivalent molecular sensors localized or not localized inside nucleus under cell cycle control using flow cytometry. Synchronized cell cycle progression rendered significant separase activity detections in both molecular sensors. We obtained consistent outcomes with localized molecular sensor introduction and cell cycle control by fluorescent microscopic observations. We thus established live cell separase activity monitoring systems specifically or statistically that could lead to elucidate separase properties in detail.

Spodoptera frugiperda (J.E. Smith) is a global agricultural pest that poses a threat to crop production, characterized by its refractory polyphagous nature that makes it difficult to control and may lead to damage to woody plants. However, research on its adaptability to woody plants remains limited. This study compares the feeding adaptations (survival rate, pupation time, pupation rate, weight, length, and feeding volume), protective enzyme activities, and feeding preferences of S. frugiperda on leaves of six economically significant tree species (Areca catechu, Aquilaria sinensis, Cocos nucifera, Camellia oleifera, Dalbergia odorifera and Hevea brasiliensis) and maize as a control treatment. The results indicate that A. sinensis as the most vulnerable trees in high risk, H. brasiliensis and C. nucifera presented varying degrees of susceptibility, A. catechu, C. oleifera, and D. odorifera were unsuitability for S. frugiperda. In conclusion, this report extensively explores the feeding effects of S. frugiperda on six economically important tree species, and provides insights into the feeding preferences on these plants, thereby informing the potential threat posed by S. frugiperda to economically vital trees.

In order to investigate the size distributions and seasonal variations of carbonaceous aerosols (OC and EC), the carbonaceous species were collected and then analyzed by using a 9-stage Anderson-type aerosol sampler and DRI Model 2001A Thermal/Optical Carbon Analyzer on the typical industrial city Nanjing in Yangtze River Delta, China in the summer, autumn and winter of 2013 and spring of 2014. OC, EC, SOC and POC exhibited obvious seasonal variations, with the highest level in winter (39.1±14.0, 5.7±2.1, 23.6±11.7 and 14.1±5.7 μg•m^-3) and the lowest level in summer (20.6±6.7, 3.3±2.0, 12.2±3.8 and 8.4±4.1 μg•m^-3), and were mainly centralized in PM_1.1 in four seasons. The concentrations of OC in PM_1.1 varied in the order of winter > autumn > spring > summer, while EC ranked in the order of autumn > winter > summer > spring. In the PM_1.1-2.1 and PM_2.1-10, the concentrations of OC and EC decreased in the sequence of winter > spring > autumn > summer. The size spectra of OC, EC and SOC had bimodal distributions in four seasons, except for EC with four peaks in summer. The size spectra of POC varied greatly with seasons, exhibiting bimodal distribution in winter, trimodal distribution in spring and summer, and four peaks in autumn. The OC/EC ratios were 7.0, 6.3, 7.6 and 6.9 in spring, summer, autumn and winter, respectively, which demonstrated the abundance of secondary organic aerosols in Nanjing. The sources of carbonaceous aerosol varied significantly with seasons, and were dominated by vehicle exhaust, coal and biomass burning in PM_2.1, and dominant by dust, coal and biomass burning in PM_2.1-10.

This paper presents a study about the integration of Piezoelectric Energy Harvesting Systems (PE-EHS) in building envelopes for powering Fiber Bragg Grating (FBG) sensors, enabling efficient and low-consumption monitoring with the objective to leverage Structural Health Monitoring (SHM). The research includes preliminary tests conducted in a real environment to validate the PE-EHS when fully integrated into the façade, capturing mechanical vibrations generated mainly by wind loads. Based on these activities, the final configuration of PE-EHS is defined to provide a complete system for façade monitoring. This integrated system includes the Piezoelectric Generator (PEG), Supercapacitor (SC), Power Conditioner Circuit (PCC), Fibre Optic Sensing (FOS) Interrogator, and the IoT Gateway trans-mitting measurement data within an Internet of Things (IoT) monitoring platform. This configuration is tailored to address the challenges related to the structural integrity of building envelopes. Results demonstrate a potential for a stand-alone solution in the façade sector, but, raising issues for certain limitations, requiring further investigation. In particular, the study emphasizes constraints related to the energy production of PE-EHS for façade integration. It highlights the necessity to carefully consider these limitations within the broader context of their applicability, providing insights for the informed deployment of Piezoelectric Energy Harvesting technology in building envelope monitoring.

The non-contact patient monitoring paradigm moves patient care into their homes and enables long-term patient studies. The challenge, however, is to make the system non-intrusive, privacy-preserving, and low-cost. To this end, we describe an open-source edge computing and ambient data capture system, developed using low-cost and readily available hardware. We describe five applications of our ambient data capture system. Namely: (a) Estimating occupancy and human activity phenotyping; (b) Medical equipment alarm classification; (c) Geolocation of humans in a built environment; (d) Ambient light logging; and (e) Ambient temperature and humidity logging. We obtained an accuracy of 94% for estimating occupancy from video. We stress-tested the alarm note classification in the absence and presence of speech and obtained micro averaged F1 scores of 0.98 and 0.93, respectively. The geolocation tracking provided a room-level accuracy of 98.7%. The root mean square error in the temperature sensor validation task was 0.3°C and for the humidity sensor, it was 1% Relative Humidity. The low-cost edge computing system presented here demonstrated the ability to capture and analyze a wide range of activities in a privacy-preserving manner in clinical and home environments and is able to provide key insights into the healthcare practices and patient behaviors.

The fact that Thailand’s energy policy has set a new renewable energy target of 30% of total final energy consumption by 2036. It also has the potential of solar energy and community demands in remote areas. However, most of the renewable energy technology will still be able to achieve renewable energy goals, similar to the case of the national policy that promotes Solar Home System (SHS) in remote areas, lack of good handling. Therefore, achieving the goal of the renewable energy policy should be in position using the right strategy. This article presents the result of a case study in the Akha upland community, northern Thailand, where we used the mixing method and factor analysis to analyze strategies for SHS related criteria. The key scopes and challenge included bottom-up planning concepts and subsidies from expert persons, while contributions to factors have an impact on developing sustainable SHS, include the creating approval of SHS technologies, developing of SHS management, promoting of SHS technologies, and supporting of SHS policies, respectively. Mainly, social factors provide positive effects, which thus influence the sustainable development of process SHS in terms of the creation of approval. Furthermore, there should be managed appropriately for each community, for the positive imagery of solar power.

Diabetic foot ulcers (DFUs) significantly affect the lives of patients and increase the risk of hospital stay and amputation. We suggest a remote-monitoring platform for better DFU care. This system uses digital health metrics (scaled from 0 to 10, where higher scores indicate a greater risk of slow healing) to provide a comprehensive overview through a visual interface. The platform features smart offloading devices that capture behavioral metrics such as offloading adherence, daily steps, and cadence. Coupled with remotely measurable frailty and phenotypic metrics, it offers an in-depth patient profile. Additional demographic data, wound characteristics, and clinical parameters, such as cognitive function, were integrated, contributing to a comprehensive risk factor profile. We evaluated the feasibility of this platform with 124 DFU patients over 12 weeks; 39% experienced unfavorable outcomes such as dropout, adverse events, or non-healing. Digital biomarkers were benchmarked (0-10), categorized into low, medium, and high risk for unfavorable outcomes, and visually represented using color-coded radar plots. The initial results of case reports illustrate the value of this holistic visualization to pinpoint the underlying risk factors for unfavorable outcomes, including a high number of steps, poor adherence, and cognitive impairment. Although future studies are needed to validate the effectiveness of this visualization in personalizing care and improving wound outcomes, early results in identifying risk factors for unfavorable outcomes are promising.

Conventional monitoring relies on "in vivo" (non-destructive) measurements of aboveground organ traits (such as stems, branches, and leaves) to analyze plantation growth trends and assess the effectiveness of management practices like watering and fertilization. This study reveals the necessity of “ex vivo” (destructive) approaches, post-excavation, to ensure fully reliable monitoring of plantation performance, including belowground organ growth and development trends. We showcase the effectiveness of dendrometric analysis, which measures the annual ring width in the secondary xylem (wood) of the taproot and stem. Monitoring above- and belowground organ growth trends allow for the exploration of similarities and differences in how different tree organs respond to internal and external factors. Such monitoring is especially crucial for assessing plantation performance in challenging climates, such as those found in arid and semi-arid lands.

Quite a number of new metered parking systems have been introduced in recent years by the local authorities of various spa towns in Poland in connection with home zone conversion projects. The traffic signs posted in these locations were limited to the beginning and end of the demarcated parking area. Traffic circle (TC) is an example of traffic calming measures (TCM) used in home zones to slow down the traffic (case study – home zone in a small spa village). This article presents the results of a study investigating the speed reductions obtained with a home zone and traffic circle used as traffic calming measures. The indispensable speed surveys were carried out in relation to this study in two periods: in summer when the streets are crowded with tourists and in September with little pedestrian traffic. Two research hypotheses were formulated as part of the speed data analysis to verify the slowing effect of traffic circle and the relevance of traffic circles design parameters and location, road function and the surrounding streetscape. For each hypothesis statistical analyses were carried out using two nonparametric tests: two-sample Kolmogorov–Smirnov test and median test. The third research hypothesis formulated in this study was related to sustainable development factors related to fuel consumption and traffic-related air pollution including carbon dioxide, carbon monoxide, nitrogen oxide and hydrocarbons. This hypothesis was verified by estimating the amount of air pollution in the home zone under analysis in three different situations (scenarios): in summer with the travel speed reduced by pedestrian traffic to ca. 8–10 km/h and in September with a small number of pedestrians and 20–25 km/h resulting speed between traffic circles, reduced at traffic circle, and in a theoretical 30 km/h zone with 25–30 km/h assumed speed between traffic circles, dropping at traffic circle. These analyses confirmed the appropriateness of traffic circle as a home zone traffic calming measure, as long as its design is based on a detailed analysis of the relevant factors, including location, road function and the surrounding streetscape.

IoT system becomes hot topic nowadays for smart home, IoT helps devices to communicate together without human intervention inside home, so it is offering many challenges. A new smart home IoT platform powered using electromagnetic energy harvesting is proposed in this paper. It contains a high gain transmitted antenna array and efficient circular polarized array rectenna system to harvest enough power from any direction to increase life time of the batteries used in IoT system. Optimized energy consumption, the software with adopting the Zigbee protocol of the sensor node and low power microcontroller are used to operate in lower power modes. The proposed system has an 84.6 days lifetime which is approximately 10 times the lifetime for similar system. On the other hand, the proposed power management circuit operated at 0.3 V DC to boost the voltage to ~3.7V from radio frequency energy harvesting and manage battery level to increase the batteries lifetime. A predictive indoor environment monitoring system is designed based on a novel hybrid system to provide a non-static plan, approve energy consumption and avoiding failure of sensor nodes in smart home.

Background: Critical states present scale-free dynamics, optimizing neuronal complexity. We explored electroencephalogram (EEG) criticality in amnesic Mild Cognitive Impairment (aMCI) patients with clinical improvement in working memory, verbal memory, verbal fluency and overall executive functions after the completion of a 6-month prospective memory training. (2) Methods: We compared “before” and “after” stationary resting-state EEG records of right-handed MCI patients (n = 17; 11 females), using the method of critical fluctuations and Haar wavelet analysis. (3) Results: Significant criticality enhancement was present in frontotemporal electrodes [mean dif: 0.10; Z = 7, p = .019] and isolated electrodes T6 [mean dif: 0.204; t (10) = - 2.3, p = .044] and F4 [mean dif: 0.0194; t (10) = - 2.82; p = .018]. (4) Conclusions: EEG criticality agreed with clinical improvement, consisting a possible monitoring biomarker in MCI and Alzheimer’s disease. Further evaluation is needed in patients under cognitive training or even drug-modifying therapies.

Direct and indirect effects after mine operations cease must ideally be subject to perpetual monitoring routines in order to detect possible risks or avoid adverse effects on the surrounding ecosystems at an early stage. In this contribution, mining subsidence lakes created inside the nature reserve Kirchheller Heide and Hilsfeld Forest are subjected to analysis for a long-term monitoring scheme. For this purpose, we employ high-resolution unmanned aerial system (UAS)-based multispectral and thermal mapping tools to provide a fast, non-invasive and multitemporal environmental monitoring method. Specifically, we propose to monitor vegetation evolution through multispectral analysis, biotypes identification using machine learning algorithms, and water surface extent detection, together with their thermal behavior. The aim of this contribution is to present the proposed workflow and first results to establish a baseline for future analyses and subsequent surveys for longterm multi-temporal monitoring

Cognitive impairment affects 34-65% of People with Multiple Sclerosis (PwMS), significantly impacting their quality of life. Clinicians routinely address cognitive deficits with in-clinic neuro-behavioural interventions, but accessibility issues exist. Telerehabilitation is a promising solution that utilises digital tools for home-based cognitive remediation. This narrative review assessed the feasibility and efficacy of cognitive telerehabilitation in PwMS, identifying 13 relevant studies. Regarding the feasibility of cognitive telerehabilitation, evidence shows adherence rates are generally good, although, surprisingly, not all studies reported a measure of compliance with the cognitive training explored. Considering the efficacy of different rehabilitative techniques on cognitive performance of PwMS, findings are generally inconsistent, with only one study reporting consistently positive results. A range of methodological limitations are reported as potential factors contributing to the variability of results. Overcoming some of these issues will be key. Upcoming research is necessary to determine optimal intervention approaches, long-term effects of rehabilitation, and how to best integrate the use of telerehabilitation into routine clinical practice. By exploiting digital tools in the best way and addressing methodological concerns, home-based rehabilitation holds the potential for improving cognitive functions and enhancing the quality of life in PwMS.

Goals: To use visual logistics for interpreting COVID-19 molecular and rapid antigen test (RAgT) performance, determine prevalence boundaries where risk exceeds expectations, and evaluate benefits of recursive testing along home, community, and emergency spatial care paths. Methods: Mathematica/open access software helped graph relationships, compare performance patterns, and perform recursive computations. Results: Tiered sensitivity/specificity comprise: T1) 90%/95%; T2) 95%/97.5%; and T3) 100%/≥99%, respectively. In emergency medicine, median RAgT performance peaks at 13.2% prevalence, then falls below T1, generating risky prevalence boundaries. RAgTs in pediatric ERs/EDs parallel this pattern with asymptomatic worse than symptomatic performance. In communities, RAgTs display large uncertainty with median prevalence boundary of 14.8% for 1/20 missed diagnoses, and at prevalence >33.3-36.9% risk 10% false omissions for symptomatic subjects. Recursive testing improves home RAgT performance. Home molecular tests elevate performance above T1, but lack adequate validation. Conclusions: Widespread RAgT availability encourages self-testing. Asymptomatic RAgT and PCR-based saliva testing present the highest chance of missed diagnoses. Home testing twice, once just before mingling, and molecular-based self-testing help avoid false omissions. Community and ER/ED RAgTs can identify contagiousness in low prevalence (<22%). Real-world trials of performance, cost-effectiveness, and public health impact could identify home molecular diagnostics as the optimal diagnostic portal.

The market of ready-to-eat salads is experiencing a noticeable growth in Europe. Since they are intended to be consumed without additional treatments, these ready-to-eat products are associated with a high microbiological risk. The aim of this work was to evaluate the microbiological quality and safety of ready-to-eat salads sold in widespread supermarket chains in Lazio, Italy, at the packaging date, during shelf-life and during home-refrigeration. The study also aimed to determine the differences between low, medium, and high cost products. Salmonella spp., L. monocytogenes were chosen as safety indicators as specified by European regulations while total aerobic mesophilic bacteria and Escherichia coli were chosen as quality indicators as suggested by national guidelines. Analyses were performed following the ISO standards and in parallel, for the evaluation of total aerobic mesophilic bacteria, with an alternative colorimetric system, the Micro Biological Survey method, in order to propose a simple, affordable and accurate alternative for testing the microbiological quality of products, especially suitable for small and medium enterprises and on-site analyses. The study revealed high, unsatisfactory, total bacterial loads in all analyzed samples at the packaging date and expiring date and a very high prevalence of Salmonella spp. (67%) regardless of the selected varieties and cost-categories; L. monocytogenes was instead not recovered aligning with the results obtained in other studies.

The market of ready-to-eat salads is experiencing a noticeable growth in Europe. The commercial success of these products is linked to the growing demand for fresh, healthy and nutritionally valuable products that can be consumed without preparation time and are perceived as safe and very high-quality products. Since they are intended to be consumed without additional treatments, these ready-to-eat products are associated with a high microbiological risk. The aim of this work was to evaluate the microbiological quality and safety of ready-to-eat salads sold in widespread supermarket chains in Lazio, Italy, at the packaging date, during shelf-life and during home-refrigeration. The study also aimed to determine the differences between low, medium and high cost products. Salmonella spp., L. monocytogenes were chosen as safety indicators as specified by European regulations while total aerobic mesophilic bacteria and Escherichia coli were chosen as quality indicators as suggested by national guidelines. Analyses were performed following the ISO standards and in parallel, for the evaluation of total aerobic mesophilic bacteria, with an alternative colorimetric system, the MBS method, in order to propose a simple, affordable and accurate alternative for testing the microbiological quality of products, especially suitable for small and medium enterprises and on-site analyses.

(1) Background: There is not much research about obesity in nursing homes although knowledge will help us to develop customized treatment plans and prevention strategies, which may help to decrease the burden for all persons involved. The objective of conducting this study was to describe the prevalence of obesity and the association between obesity and care problems in nursing home patients. (2) Methods: This study is a secondary data analysis of data collected in an annually performed cross-sectional study called “Nursing Quality Measurement 2.0”. A standardized and tested questionnaire was used to collect data. (3) Results: 1236 nursing home patients took part and 16.7% of them were obese. The multivariate logistic regression analysis results show that urinary incontinence is significantly associated with the presence of obesity (OR 2.111). The other care problems of pressure injuries, fecal and double incontinence, physical restraints, falls and pain were not associated with obesity. (4) Conclusion: The results indicate that, in the nursing home setting, health care staff should pay special attention to the patients’ nutritional and continence status and help patients maintain a normal, healthy weight. Conducting more studies with larger sample sizes is recommended, as this will allow differentiation among different obesity classes.

Viruses are silent enemies that intrude and take control of the plant cell's machinery for their own multiplication. Infection by viruses and the resulting damage is still a major challenge in the agriculture sector. Plants have the ability to fight back, but the ability of viruses to counteract and mutate at a fast rate helps them to hide from the host response. Therefore, classical approaches for introgressing resistance genes by breeding have obtained limited success in counteracting the virus menace. Genetic modification (GM) based strategies have been successful in engineering artificial resistance in plants. Several different approaches based on pathogen derived resistance, antisense constructs, hairpin RNA, double stranded RNA etc. have been used to enhance plant resistance to the virus. Recently, genome editing (GE) strategies mainly involving the CRISPR/Cas mediated modifications are being used for virus control. In this review, we discuss the developments and advancements in the GM and GE based methods in tackling virus infection in plants.

Levels of trace element pollution in surface soil can be estimated using soil analyses and leaching tests. These methods may reveal different results due to the effect of soil properties, such as grain size and mineral composition, on elemental availability. Therefore, this study advocates an alternative method for monitoring and assessment of trace element pollution in surface soil using terricolous fruticose lichens. Lichens growing at abandoned mine sites and unpolluted areas in southwest Japan and their substrata were analyzed using inductively coupled plasma-mass spectrometry and X-ray fluorescence spectrometry to clarify the relationships between Cu, Zn, As, and Pb concentrations in lichens and soils, including their absorption properties. Concentrations of these elements in the lichens were positively correlated with those in the soils regardless of lichen species, location, habitat, or conditions of soils. The analyzed lichens had neither competitive nor antagonistic properties in their elemental absorption, which made them good biomonitors of trace element pollution in surface soil. The distribution maps of average Cu, Zn, As, and Pb concentrations at each sampling region detected almost all of the Cu, Zn, and As pollution of the soils. Therefore, lichens could be used in practical applications to monitor Cu, Zn, and As pollution in surface soils.

This project involves the development of Fire Suppression System (FSS) leveraging of Home automation system using Graphical System design (LabVIEW) software and Arduino microcontroller for real-time monitoring and control. The system integrates an Infrared (IR) flame sensor, an MQ2 gas sensor to detect and suppress fire hazards efficiently. The LabVIEW interface facilitates real-time monitoring of sensor data, allowing users to visualize and analyze the environmental conditions. Through this system, fires are automatically subdued, enhancing safety without requiring human intervention. This advances fire safety by swiftly containing threats and minimizing potential damage.

This paper proposes the localisation of room occupants in home environments using Unobtrusive Sensing Solutions (USSs). The ability to localise room occupants in home environments can help in the objective monitoring of sedentary behaviour. While wearable sensors can provide tangible information on health and wellness, they have battery life issues and the inability to perform prolonged monitoring. This work uses heterogeneous USSs in the form of an Infrared Thermopile Array (ITA-64) thermal sensor and a Multi-Chirp Frequency Modulated Continuous Wave Mono-pulse (MC-FMCW-M) Radar sensor to monitor room occupants. Digital filters and background subtraction algorithms were used to process the thermal images gleaned from the ITA-64 thermal sensors. The MC-FMCW-M Radar sensor used multi-chirp and Doppler shift principles to estimate the exact location of the targeted room occupants. The estimated distances from the Radar Sensor were compared with ground truth values. Experimental results demonstrated the ability to identify thermal blobs of occupants present in the room at any particular time. Data analyses indicated no significant difference (p = 0.975) and a very strong positive correlation (r = 0.998) between the ground truth distance values and those obtained from the Radar Sensor.

Age-in-place can reduce the progress of dementia syndrome and improve the quality of life of the sufferers and their families. This work proposes an innovative information home support system to be established at the houses of people suffering from dementia. The main innovation of the system are its transparent character that overcomes the need for training of the sufferer, as well as the exploitation of a well-known technique for dementia, namely music therapy. It addresses the need of people suffering from dementia as well as their familiars to be recognized by them and have better interaction and collaboration. The system offers a ubiquitous recognition system, just by using smart devices like smart-phones or smart-wristbands. When a familiar person is detected in the house, then a sound file is reproduced on smart speakers placed in the house, in order to trigger the memory, based on the principles of music therapy. The system reproduced the appropriate time at 100% of the cases and the benefits of music therapy are evident daily. To the best of the authors' knowledge, this is the first system of its kind ever reported in the literature.

Robot-assisted rehabilitation has emerged as a promising approach for enhancing motor function in stroke survivors. However, the feasibility and effectiveness of home-based robotic training in this population are underexplored, especially in low/middle-income countries. This feasibility study aimed to address this gap by examining the feasibility and effectiveness of independent home-based training using PLUTO, a robotic device for hand training. A total of 7 chronic stroke survivors were recruited, with 5 completing the study. The results revealed high engagement and adherence to the home-based training program, with participants averaging 1659.8 minutes of training over 24.8 days. The PLUTO system demonstrated excellent usability and elicited positive user perceptions. Significant improvements were observed in functional outcomes, as evidenced by a noteworthy increase in Fugl-Meyer Assessment scores (mean increase of 6.2 points, exceeding the minimal clinically important difference (MCID) of 5.35 points). Furthermore, participants showed improvements in the ABILHAND measure (mean improvement of 1.24 logits, surpassing the MCID of 0.2 logits) and the Barthel Index (mean increase of 8.8 points). These findings demonstrate the feasibility and effectiveness of home-based robotic rehabilitation for chronic stroke survivors. This has implications for expanding access to rehabilitation services in low- and middle-income countries, enhancing patient engagement and adherence, and improving functional outcomes. Larger controlled studies are warranted to evaluate the effectiveness of home-based robotic rehabilitation programs.

Background: The cumulative number of patients during the COVID-19 pandemic led to a significant shortage of hospital beds. Many patients may not require hospitalization and can be clinically observed in home settings. However, some psychosocial factors are correlated with unsuccessful home isolation (HI), which might negatively affect the transmission control in the community. Therefore, we developed a new psychosocial screening tool (CCPHIET) for assessing HI suitability and examined its validity and reliability.Methods: This cross-sectional descriptive study included COVID-19 patients who were deemed to be medically safe for 14 days of HI. The CCPHIET is comprised of 8 clinical domains pertinent to HI behavioral compliance and risk. We explored its statistical validity and reliability and discussed the potential utility of this tool. Results: A total of 65 COVID-19 patients participated in this study. Most patients (58.5%) were evaluated as good candidates for HI. The CCPHIET has an acceptable content validity (IOC index > 0.5), moderate internal consistency (Cronbach’s alpha = 0.611) and substantial to excellent inter-rater reliability (Intraclass correlation coefficient = 0.944, Cohen’s kappa= 0.627).Conclusions: To compromise between strict and costly absolute institutional quarantine and the potentially unsuccessful absolute HI, the CCPHIET may help to identify good candidates for HI in mild and asymptomatic COVID-19 patients. This psychosocial information would support the physicians in matching each patient to the most suitable setting. Therefore, safe medical care is provided, unnecessary use of medical resources is spared, and local transmission is contained.

In recent years, the management of health systems is a main concern of governments and decision makers. Home health care is one of the newest methods of providing services to patients in developed societies that can respond to the individual lifestyle of modern age and the increase of life expectancy. The home health care routing and scheduling problem is a generalized version of the vehicle routing problem, which is extended to a complex problem by adding special features and constraints of health care problems. In this problem, there are multiple stakeholders such as nurses for which an increase of their satisfaction level is very important. In this study, a mathematical model is developed to expand traditional home health care routing and scheduling models to downgrading cost aspects by adding the objective of minimizing the difference between the actual and potential skills of the nurses. Downgrading can lead to a dissatisfaction of the nurses. In addition, skillful nurses have higher salaries and high-level services increase equipment costs and need more expensive trainings and nursing certificates. Therefore, downgrading can enforce hidden huge costs to the managers of a company. To solve the bi-objective model, an -constraint based approach is suggested and the model applicability and its ability to solve the problem in various sizes are discussed. A sensitivity analysis on the Epsilon parameter is conducted to analyze the effect of this parameter on the problem. Finally, some managerial insights are presented to help the managers in this field, and some directions for future studies are mentioned as well.

Home Security Systems are very important features of modern residential and office setups. This system is used to keep home safe from harmful gases, fire and intruders. It must be affordable, reliable and effective. In this paper, a GSM based home security system has been designed and implemented. The system consists of a GSM Module, MQ-2 smoke detector, Ultrasonic sonar sensor, LM35 temperature sensor, Arduino Uno and relay module. The MQ-2 smoke detector is used to detect harmful gases i.e. LPG, CH4, CO, Alcohol, Smoke or Propane. Any of the harmful gases stated above is detected it will warn the owner by activating the buzzer and displaying a warning message on the LCD display. It will also send a SMS to the owner. Our system can also measure temperate and if the temperature is increased above a certain range it will compensate it by activating Air Conditioner through the relay module. The system will also send a SMS to the owner. It can also detect intruders using Ultrasonic sensor and warn us through buzzer, SMS and displaying message on the LCD. Our system is reliable as it has very fast response and cost effective and it has been developed using our own technologies.

Malawi has developed an excellent, nation-wide system for monitoring people infected with HIV and keeping track of key epidemic markers. Their success lies in two things: the focus on simplicity and the use of data collection not only to track the epidemic and identify problems but also to give regular feedback and support to every clinic in the country. This achievement is the more remarkable given that Malawi is one of the poorest countries in the world, ranking 190 out of 194 countries by GDP, but has one of the most severe epidemics of HIV in the world, ranking 9th out of 168 countries by HIV prevalence. We first discuss the current state and likely future epidemic trends in Malawi: unless we know where we are and where we are going we cannot decide what to do or how to do it to in order to achieve a better outcome. We then discuss the history and development of Malawi’s patient monitoring system, as reported in their Integrated HIV Program Reports,ix which have been published quarterly since the beginning of 2004. We consider the current state of patient monitoring and support as reflected in the most recent report for the third quarter (Q3) of 2016 and comment on some of the questions that this raises. Finally, we consider ways in which the current system could be improved by strengthening Malawi’s analytical capacity and making better use of this unique data set. The focus here is on HIV in adultsv because if ART is initiated early in all adults living with HIV this should include testing all pregnant women for HIV and starting them on treatment immediately. However, PMTCT is especially important and care must be given to reducing MTCT and identifying the long-term child survivors of mother-to-child transmission and this demands a complementary assessment. There is an ongoing debate about the relative merits of treatment and prevention in reducing transmission and it should be made clear that the primary reason for starting people on treatment early is that it is in the best interest of the individual patient to start treatment as soon as possible after becoming infected. Allowing a person’s immune system to deteriorate to any degree is not consistent with the clinician’s commitment to ‘first do no harm’ and even those with the highest CD4⁺ cell count are at a substantially increased risk of death. What matters, therefore, is to get as many people as possible onto ART, ensure that they remain virally suppressed, and consider prevention in this context.

The availability of current land cover and land use (LCLU) information for monitoring the status of land resources has considerable value in ensuring sustainable land use planning. Similarly, the need to provide updated information on the extent of LCLU change in West Africa has become apparent, given the increasing demand for land resources driven by the rapid population growth in the sub-region. SERVIR West Africa, a regional consortium jointly supported by USAID and NASA to foster the use of geospatial and earth observation data and science for decision-making on critical environmental and food security challenges, in collaboration with the Food and Agriculture Organization of the United Nations (FAO), is building technical capacity in the sub-region to develop and implement harmonized regional land cover classification system for LULC change monitoring in West Africa, based on the Land Cover Meta Language (LCML-ISO 19144-2). This article focuses on the process, potential opportunities, outputs of this collaboration, exemplary use cases, and recommendations for the next steps.

The increase in population and the challenges caused by it are always among the concerns of decision-makers and policymakers in large countries. One of the most serious concerns is in the field of energy consumption. Optimizing energy use is one of the most effective ways to manage limited resources and energy. Energy consumption in residential houses constitutes a significant percentage of the total energy consumption worldwide; therefore, current research focusing on mathematical models aims to provide a predictive multi-objective linear mathematical model for residential house consumption. For this purpose, the consumption of water, electricity, and gas for 80 residential houses, including 10 household appliances and equipment on a weekly basis, has been considered. The results showed that the mixed-integer multi-objective predictor model is able to optimize household consumption plans compared to the actual state of household energy consumption. Since the goals of household satisfaction and energy consumption costs in the model conflict with each other, the influence coefficient was calculated to demonstrate the simultaneous achievement of these goals. The optimal value achievable with the default model for the model's purposes is 69%.

Sociality in animal populations is a continuum, and interactions between conspecifics are meaningful for all vertebrates. Ignorance of social structures can lead to misunderstanding their ecology and, consequently, to unsuccessful species management. Here, we combined genetic and spatial data on radio-collated brown bears (Ursus arctos) to investigate kin-related home range overlap and kin-related centroid distance within central and eastern Finland. We found that the extent of overlap of home ranges was positively linked with relatedness among adult females. A similar positive correlation could be detected between home range centroid distance and relatedness among adult females. Moreover, there were significant differences between the two studied regions: female brown bears in central Finland were more closely related to each other, and the sizes of their home ranges were larger than those in eastern Finland. The smaller home ranges and lower degree of relatedness among bears in eastern Finland might be a result of the substantially higher hunting pressure in the area, combined with immigration of new unrelated individuals from Russia.

Fetuses of pregnant women affected by anti-Ro/anti La antibodies are at risk to develop complete atrioventricular heart block (CAVB) and other potentially life-threatening cardiac affections. CAVB can develop in less than 24 hours. Treatment with anti-inflammatory drugs and immuno-globulins (IVIG) can restore normal rhythm if applied in the transition period. Routine weekly echocardiography as often recommended will seldomly detect emergent AVB. Surveillance of these pregnancies is controversial. To obtain an overview of the current practice in Germany we have developed a web-based survey sent by the DEGUM (German Society of Ultrasound in Med-icine) to ultrasound specialists. Home-monitoring by hand-held Doppler is a promising new approach. With the intention to evaluate practicability, we instructed pregnant women at risk to use hand-held Doppler in the vulnerable period between 18-26 weeks at our university center.

Background: After the increasingly common anterior cruciate ligament reconstruction (ACLR) procedure in competitive athletes, rehabilitation is crucial for facilitating a timely return to sports (RTS) and preventing re-injury. This pilot study investigates the biomechanical and psychological outcomes of postoperative rehabilitation in competitive athletes, comparing supervised rehabilita-tion (SVR) and home-based rehabilitation (HBR). Methods: After ACLR, 60 (out of 74 screened) athletes were recruited and equally divided into 2 groups using non-probability convenience sam-pling: 30 HBR and 30 SVR (each group comprising 15 males and 15 females). Rehabilitation out-comes in respective groups were evaluated at 8 months using measures (Tegner-Activity-Scale [TAS], International Knee Documentation Committee subjective knee form [IKDC-SKF], ACL Return to Sport after Injury [ACL-RSI]) and objective parameters (isometric muscle strength, hamstring/quadriceps asymmetry). RTS was evaluated at 9 months; with ACL re-injury rates rec-orded approximately 6 months post-RTS. Results: Both groups exhibited decreased TAS scores (HBR: 8 to 6, SVR: 8 to 7), with the SVR group demonstrating superior post-operative IKDC-SKF scores (81.82 vs. 68.43) and lower ACL-RSI scores (49.46 vs. 55.25). Isometric and isokinetic mus-cle strength, along with asymmetry values, favored the SVR group 8 months post-ACLR (p

Home care centers face both an increase in demand and many variations during the execution of routes, compromising the routes initially planned: robust solutions are not effective enough, it is necessary to move on to resilient approaches. We create a close to reality use case supported by interviews of staff at home health care centers, where caregivers are faced with unexpected events that compromise their initial route. We model, analyze and compare three resilient approaches to deal with these disruptions: a baseline approach without any collaboration, a distributed collaborative approach, and a centralized collaborative approach, where we propose a centralization and sharing of information to improve local decision-making. The latter reduces the number of late arrivals by 11% and the total time of late arrival by 21%, and also halves the number of routes exceeding the end of work time (contrary to the distributed collaborative approach, due to the time wasted reaching colleagues). The use of a device, such as a smartphone application, to centralize and share information thus allows better mutual assistance between caregivers. Moreover, we highlight several possible openings like the coupling of simulation and optimization to propose a more resilient approach.

Family support is offered to Australian parents of young children using a mix of targeted and universal child and family health services. A feature of the universal services is the ability for nurses to work in partnership with families and to offer flexibility depending on need. This model of progressive universalism relies on the voluntary engagement of families, including families with complex needs. In this study, the capacity to engage and retain families, including those at risk for child maltreatment and family violence, was examined. Child and Family Health Nurses (n=129) participated in a pragmatic, multilevel mixed-methods study using the McCurdy and Daro (2001) Integrated Theory of Parent Involvement. A questionnaire was used in the first phase of the study to collect the quantitative data. Focus groups were then held with 27 participants recruited from phase one. Both homogeneous and heterogenous practices identified from the questionnaire were the focus of the discussions. Three phases of practice were identified and described: enrolment, retention and conclusion of the nurse-parent relationship and are presented and discussed in this paper. The retention of families with complex needs relies on flexible, advanced, and multidimensional nursing practices.

Racial and ethnic disparities exist in diabetes prevalence, health services utilization, and out-comes including disabling and life-threatening complications. Home health care may especially benefit older adults with diabetes through individualized education, advocacy, care coordina-tion, and psychosocial support for patients and their caregivers. This study examined factors as-sociated with hospital discharge to home health care and subsequent utilization of home health care among a cohort of Medicare beneficiaries with diabetes, age 50 and older, living in the United States. The cohort (n=786,758) was followed for 14 days after a diabetes-related index hospitalization, using linked Medicare administrative, claims, and assessment data (2014-2016). Multivariate logistic regression models included patient demographics, comorbidities, hospital length of stay, geographic region, neighborhood area deprivation, and rural/urban setting. In ful-ly adjusted models, hospital discharge to home health care was significantly less likely among Hispanic (OR 0.8, 95% CI 0.8-0.8) and American Indian (OR 0.8, CI 0.8-0.8) compared to white patients. Among those discharged to home health care, all racial/ethnic minority patients were less likely to receive services within 14-days. Further work should focus on eliminating systemic racism in home health care referral and systemic barriers to receiving home health care services.

Therapeutic Drug Monitoring (TDM) is potentially a useful tool that can be employed to increase the efficacy and decrease the toxicity of antifungal drugs. The aim of this narrative review is to provide an overview of the current use of TDM in clinical practice, and to present the evidence available regarding its use in proactive clinical settings for preventing and managing treatment failure. This review also presents the existing evidence regarding the association of various clinical outcomes with specific thresholds of drug concentrations in everyday practice. Articles concerning the use of TDM of triazoles in the treatment of fungal infections were retrieved through an electronic search using PubMed. In clinical practice, TDM has an increasingly important role in the management of antifungal drugs as a consequence of the improvement in the knowledge of the pharmacokinetics and pharmacodynamics of these drugs. The currently available evidence shows a direct exposure-response relationship for triazoles, though the PK/PD profile is unpredictable. Current guidelines and treatment consensus statements recommend the proactive TDM of voriconazole, posaconazole, and itraconazole to optimize dosage regimens and improve outcomes for adult and pediatric patients.

Human populations and natural ecosystems are bound to be exposed to ionizing radiation1from the deposition of artificial radionuclides resulting from nuclear accidents, nuclear devices2or radiological dispersive devices ("dirty bombs"). On the other hand, NORM industries such as3phosphate production or uranium mining, contribute to the on site storage of residuals with enhanced4concentrations of natural radionuclides. Therefore, in the context of the European agreements5concerning nuclear energy, namely the EURATOM (European Atomic Energy Community) Treaty,6monitoring is an essential feature of the environmental radiological surveillance. In this work, we7obtain 3D maps from outdoor scenarios, and complete such maps with measured radiation levels8and with its radionuclide signature. In such scenarios, we face challenges such as unknown and9rough terrain, limited number of sampled locations and the need for different sensors and therefore10different tasks. We propose a radiological solution for scouting, monitoring and inspecting an area of11interest, using a fleet of drones and a controlling ground station. First, we scout an area with a LiDAR12onboard a drone to accurately 3D-map the area. Then, we monitor that area with a Geiger-Muller13sensor at a low-vertical distance from the ground to produce a radiological (heat)map that is overlaid14on the 3D map of the scenario. Next, we identify the hotspots of radiation, and inspect them in detail15using a drone by landing on them, to reveal its radionuclide signature using a CZT sensor. We present16the algorithms used to implement such tasks both at the ground station and on the drones. The three17mission phases were validated using actual experiments in three different outdoor scenarios. We18conclude that drones can not only perform the mission efficiently, but in general they are faster and19as reliable as personnel on the ground

The assessment of welfare and disease progression in animal models is critical. Most tools rely on evaluating individual subjects, whereas social behaviors, also sensitive to acute illness, chronic diseases, or mental health, are scarcely monitored because of their complexity, are invasive, and time-consuming. We propose the evaluation of social nesting, a species-typical behavior naturally occurring in standard housing conditions, for such behavioral monitoring. We provide an example of its use to evaluate social deficits and the long-term effects of neonatal sensorial stimulation in male and female adult 3xTg-AD mice for Alzheimer's disease compared to sex- and age-matched NTg counterparts with normal aging. Social nesting was sensitive to genotype (worse in 3xTg-AD mice), sex (worse in males), profile, and treatment (distinct temporal patterns, time to observe the maximum score and incidence of the perfect nest). Since social nesting can be easily included in housing routines, this neuroethological approach can be useful for animal's welfare, monitoring the disease's progress, and evaluating potential risk factors and effects of preventive/therapeutical strategies. Finally, the non-invasive, painless, simple, short time and low-cost features of this home-cage monitoring are advantages that make social nesting feasible to be successfully implemented in most animal department settings.

The purpose of this qualitative study was to describe parent perceptions of the home exercise pro-gram (HEP) for their infant with congenital muscular torticollis (CMT), and how these perceptions evolved over a physical therapy (PT) plan of care. Twelve participants were recruited from a pediatric PT clinic, and nine completed interviews at three time points. Qualitative description and an iterative approach for thematic analysis of 27 interviews yielded three themes that corresponded to the research questions. The participants’ responses were categorized into three main themes: 1) parents’ perceptions of three key exercises within the HEP; 2) internal and external sources of stress; and 3) sources of empowerment and disempowerment. Regarding the HEP, parents articulated common sentiments for three frequently prescribed exercises for the management of CMT: 1) Tummy time was the fast favorite, 2) ipsilateral cervical rotation was perceived as stressful, and 3) contralateral cervical lateral flexion felt uncomfortable. Additionally, participants disclosed internal and external sources of stress (guilt, uncertainty, and the demands of returning to work) and sources of disempowerment (inconsistent messaging from providers, feeling overwhelmed) and empowerment (being able to see the bigger picture and clear communication and education about the diagnosis) with respect to managing their infant’s CMT. These themes provide insight into the evolution of parent perceptions over a PT plan of care for CMT. Participants’ insights suggest a need for consistent messaging regarding the diagnosis and evidence-based management of CMT, addressing parent stress, and modifying how exercises are taught. This study contributes updated research on parents’ experience with physical therapy and the HEP for their infant’s CMT.

In this article, we analyse the ESG determinants of the “Elderly People Treated in Integrated Home Care”-EPIHC in the Italian regions between 2004 and 2022. We used data from the ISTAT-BES database. We used different econometric techniques i.e.: Panel Data with Random Effects, Panel Data with Fixed Effects, Pooled Ordinary Least Squares-OLS and Weighted Least Squares-WLS. The results show that the EPIHC is positively associated with “Nurses, midwives, and Soil sealing by artificial cover" and negatively associated with "Museum heritage density and relevance" and "Trust in law enforcement agencies and firefighters fire". Furthermore, we have applied a k-Means algorithm with the Silhouette Coefficient and we find the presence of two clusters. Finally, we propose a confrontation among eight different machine-learning algorithms and we find that Linear Regression is the best predictive algorithm.

The quadruple burden of diseases, early discharge from hospital and hospital at home have resulted in home-based care services becoming a requirement in South Africa. The home-based care services generate a significant amount of health care risk waste that is mismanaged. However, more attention is given to the health care risk waste generated in hospitals and clinics than to health care risk waste generated by home-based caregivers. Therefore, this study investigates the health care risk waste management practices by home-based caregivers. The study adopted a mixed research approach, qualitative and quantitative methods, using a literature review, interviews, and questionnaires as means of data collection. Results show that there are different types of health care risk waste generated as a result of different activities performed by home-based caregivers, but that the waste was found to be managed in an unsafe manner. The majority of households receiving home-based care did not have basic sanitation facilities such as toilets, running water and waste removal services, aggravating the issue of health care risk waste mismanagement. The study recommends a new policy framework that will lead to safe management practices of generated health care risk waste to be adopted by home-based caregivers.

This research explores the impact of working from home on employees' happiness, collaboration, and promotion prospects using machine learning techniques. The study is guided by three research questions aiming to investigate the correlation between working from home and employees' collaboration and promotion prospects. Moreover, the research aims to find a relationship between the number of households and employees' happiness levels while working from home. The data is collected from ICT engineers working at a technology company in Sweden through a questionnaire-based survey. Probability sampling was selected for data collection to reduce bias and enhance the generalizability of the findings. The data is pre-processed and then analysed in Jupyter Notebook using the Python programming language. Various libraries and models, including Pandas, NumPy, Matplotlib, Seaborn, and Scikit-learn, were employed for data analysis. Both Pearson correlation and p-values in Pearson correlation were used in this study to analyse the relationships between different variables.However, based on the results, this study did not find any significant relationship between working from home and employees' promotion prospects or collaboration issues. Additionally, the results did not provide evidence of a significant relationship between the number of households of employees and their happiness levels while working from home.

Social and behavioral rhythms (SBRs) are related to circadian rhythms well known as central points in the pathophysiology of bipolar disorders. The purpose is to verify in elderly people if having functional SBRs correlated with a positive perception of the quality of life (QoL) and health parameters and if there was an association between dysfunctionality of SBRs and Major Depressive Disorder (MDD). Sample: 141 people aged 65 years (58,9%Female). Each subject was submitted to SBRs Scale (in which higher scores show more dysfunctional SRB); SF-12 for QoL; PHQ-9 for depressive symptoms and underwent blood levels essays including cholesterol and triglyceride. The medical documented lifetime diagnosis including Major Depressive Disorder was taken into account. SBRs Scale score correlated inversely with SF-12 score (r=-0.360, p&lt;0.0001) and positively with PHQ9 (r=0.396, p&lt;0.0001). Lifetime MDD medical diagnosis was associated with a higher score at scale on social rhythms (24.811.9 vs 20.18.0, F=15.848, p&lt;0.0001).The study highlighted, for the first time, that SBRs such as sleep, and nutrition have a role in well-being and that dysregulation of SBRs is related to MDD. Further longitudinal studies with a sufficient number of individuals will have to confirm these data and clarify causal links of the association between QoL and SBRs.

Older adults with diabetes are at elevated risk of complications following hospitalization. Home health care services mitigate the risk of adverse events and facilitate a safe transition home. In the United States, when home health care services are prescribed, federal guidelines require they begin within two days of hospital discharge. This study examined the association between timing of home health care initiation and 30-day rehospitalization outcomes in a cohort of 786,734 Medicare beneficiaries following a diabetes-related index hospitalization. Of these patients, 26.6% were discharged to home health care. To evaluate the association between timing of home health care initiation and 30-day rehospitalizations, multivariate logistic regression models including patient demographics, clinical, geographic variables, and neighborhood socio-economic variables were used. Inverse probability-weighted propensity scores were incorporated into the analysis to account for potential confounding between the timing of home health care initiation and the outcome in the cohort. Compared to patients who received home health care within the recommended first two days, patients who received delayed services (3-7 days after discharge) had higher odds of rehospitalization (OR 1.28, 95% CI 1.25-1.32). Among patients who received late services (8-14 days after discharge), the odds of rehospitalization were four times greater than for patients receiving services within 2 days (OR 4.12, 95% CI 3.97-4.28). Timely initiation of home health care following diabetes-related hospitalizations is one strategy to improve outcomes.

As consequence of COVID-19, millions of households suffered mobility restrictions and changes in their lifestyle during several months. The aim of this study was to evaluate the effects of COVID-19 home confinement in food habits, lifestyle and emotional balance of the Spanish population. This cross-sectional study used data collected via an anonymous online questionnaire during the last month before lockdown finished in Spain in a total of 675 participants. 38.8% of the respondents experienced weight gain while 31.1% lost weight during confinement. The increase in body weight was positively correlated with the age (Rs = 0.14, p &lt;0.05) and BMI (Rs = 0.20, p &lt;0.05). We also identified that 39.7% reported poorer quality sleep, it was positively correlated with BMI (Rs = -0.18, p &lt;0.05) and with age (Rs = -0.21, p &lt;0.05). 44.7% of the participants had not performed physical exercise during confinement with differences by sex (p &lt;0.05), by age (p &lt;0.05), by BMI (p &lt;0.05) and sleep quality (p &lt;0.05). According to emotional-eater questionnaire, 21.8% and 11% were classified as emotional eater and very emotional eater, respectively. We emphasize the importance of adopting a healthy lifestyle, as the COVID-19 pandemic nowadays is ongoing.

Without the use of medicine drones, users are responsible for transporting goods at a high cost. The goal of this patient monitoring system is to identify people's health and, if necessary, administer medicine. The transportation drone is capable of finding healthcare information in a 360-degree rotation within the transportation infrastructure. IoT: Drone doctors are critical for the transportation of small gadgets such as drug treatments, blood leakages, and vaccines in the critical conditions of a heart patient, in the event of failure of traffic location infrastructure, highway roads, or hospitals due to intense climate or site visitor congestion, and for the transportation of small gadgets such as drug treatments, blood leakages, and vaccines. When transmission is difficult, the self-maintaining drone is the format for quickly transporting drug treatments to the appropriate locations. The shipping drone equipped with an Ardupilot can drive in autopilot mode, which guides the drone to its destination. It has a 7-minute flying period and can deliver up to 2 kg of medicine. When the detected heartbeat is 94bpm and the fever range is 101 degrees, a method has been presented in which an IoT Drone Doctor (IDD) System distributes the first AID box to vulnerable patients and heart patients.

In this study, we evaluated the physicochemical and microbial qualities of source and stored household waters in some communities in Southwestern Nigeria using standard methods. Compared parameters include physicochemical constituents; Temperature (T), pH, Total Dissolved Solids (TDS), Total Hardness (TH), Biological Oxygen Demand (BOD), Magnesium ion (Mg²⁺) and Calcium ion (Ca²⁺) and microbiological parameters included Total Coliform Counts (TC), Faecal Coliform Counts (FC), Fungal Counts (Fung C), Heterotrophic Plate Counts (HPC). Comparing Stored and Source samples, the mean values of some physicochemical parameters of most of the stored water samples significantly (P<0.05) exceeded that of Sources and ranged in the following order: T (15.3±0.3^oC - 28.3±0.5^oC), pH (6.4±0.1 - 7.6±0.1), TDS (192.1±11.1 ppm - 473.7±27.9 ppm), TH (10.6±1.7 mg/L - 248.6±18.6 mg/L), BOD (0.5±0.0 mg/L - 3.2±0.3 mg/L), Mg²⁺ (6.5±2.4 mg/L - 29.1±3.2 mg/L) and Ca²⁺ (6.5±2.4 mg/L - 51.6±4.4 mg/L). The mean microbial counts obtained from microbial comparison of different points (Stored and Source) of collection showed that most of the stored water had counts significantly exceeding (P<0.05) those of the source water samples (cfu/100 mL) which ranged as follows: TC (3.1±1.5 - 156.8±42.9), FC (0.0±0.0 - 64.3±14.2) and HPC (47.8±12.1 - 266.1±12.2) across all sampled communities. Also, the predominant isolates recovered from the samples were identified as Escherichia coli, Klebsiella pneumonia, Pseudomonas aeruginosa, Enterobacter aerogenes, Aspergillus spp, Mucor spp, Rhizopus spp and Candida spp. The presence of these pathogenic and potentially pathogenic organisms in the waters and the high counts of the indicator organisms suggest the waters to be a threat to public health.

The background of this work is related to the scheduling of household appliances, taking into account variations in energy costs during the day, due to official Brazilian domestic tariffs: constant and white. The white tariff can reach an average price of around 17\% lower than the constant, but charges twice its value at peak hours. In addition to cost reduction, we propose a methodology to reduce user discomfort due to time shifting of controllable devices, presenting a balanced solution through the analytical analysis of a new method here called tariff space, derived from white tariff posts. To achieve this goal, we explore the geometric properties of the movement of devices through the tariff space (geometric locus of the load), over which we can define a limited region in which the cost of a load under the white tariff will be equal to or less than the constant tariff. As a trial for the efficiency of this new methodology, we collected some benchmarks (such as execution time and memory usage) against a classic multi-objective algorithm (Hierarchical) available in the language portfolio in which the project has been executed (Julia language). As a result, both methodologies achieve similar results, but the one presented in this article shows a significant reduction in processing time and memory usage, which could lead to the future implementation of the solution in a simple, low-cost embedded system like an ARM cortex M.

The home is becoming a key location for healthcare delivery, including the use of technology driven by autonomous systems (AS) to monitor and support healthcare plans. Using the example of a smart mirror, this paper describes the outcomes of focus groups with people with multiple sclerosis (MS; n=6) and people who have had a stroke (n=15) to understand their attitudes towards the use of AS for healthcare in the home. We thematic analysis to analyse the data. The results indicate that the use of such technology depends on the level of adaptability and responsiveness to the users’ specific circumstances, including their relationships with the healthcare system. A smart mirror would need to support manual entry, responsive goal setting, effective aggregation of data sources and integration with other technology, have a range of input methods, be supportive rather than prescriptive in messaging, and give the user full control of their data. Barriers to adoption include a perceived lack of portability and practicality, lack of accessibility and inclusivity, a sense of redundancy, being overwhelmed by multiple technological devices, and a lack of trust in data sharing. These results inform the development and deployment of future health technologies based on the lived experiences of people with health conditions who require ongoing care.

The complexity and interconnection of smart cities provide huge political, technical, and socioeconomic challenges for the designers, integrators, and organisations who are responsible for the administration of these new entities. A growing number of studies are concentrating their attention on the safety, privacy, and potential dangers that exist within smart cities. These studies are drawing attention to the dangers that are associated with information security as well as the challenges that smart city infrastructure faces in the management and processing of personal data. This state of the art review of the literature analyses a number of issues pertaining to smart homes, offers a helpful synthesis of the important information found in the primary research, and creates a model for the interaction between smart cities. An overview of smart home research incorporating machine learning, including everything from definition to current research state. The state of art begins with a smart home definition, followed by descriptions of smart home elements, typical research projects, smart home network research status, smart home appliances, and difficulties. The term "smart home" refers to a subcategory of "everyday computing" that includes "smart technology" in order to improve a person's level of convenience, health, safety, and security while also reducing their When controlled by artificial intelligence, the applications for the smart home provide users with context-aware settings, services, and remote control, which significantly increases the level of user satisfaction.

Home-field advantage (HFA) encompasses all the processes leading to faster litter decomposition in the 'home' environment as compared to that of ‘away’ environments. To determine the occurrence of HFA in a forest and adjacent clear-cut, we set up a reciprocal litter decomposition experiment within the forest and clear-cut for two soil types (Cambisols and Gleysols) in temperate Germany. The forest was dominated by Norway spruce (Picea abies), whereas forest regeneration of European Beech (Fagus sylvatica) after clearcutting was encouraged. Our observation that Norway spruce decomposed faster than European beech in 70-yr-old spruce forest, was therefore most likely related to specialized litter-microbial interaction under existing spruce, and leading to a HFA. The ‘spruce’ microbial biome and soil conditions of original forest were then rapidly changed even after a short-term regeneration following clearcutting, resulting in faster beech decomposition also masking any HFA for spruce, particularly in moisture- and nutrient-deficient Cambisols. Divergence between forest and clear-cut in the Cambisol of their litter δ15N values beyond 9 months, implied litter N decomposition was only initially independent of soil and residual C status. We conclude that clearcutting modifies HFA and helps promote the establishment or regeneration of European beech in this and similar forest mountain upland areas.

The understanding of various health-oriented vital sign data generated from body sensor networks (BSN) and discovery of the association between the generated parameters is an important task that may assist and promote important decision making in healthcare. For example, in a smart home scenario where the occupants’ health status is continuously monitored remotely, it is essential to provide required assistance when an unusual or critical situation is detected in their vital sign data. In this paper, we present an efficient approach to mine the incomplete (partial) periodic patterns obtained from BSN data. In addition, we employ a correlation test on the generated patterns and introduce the productive-associated partial periodic frequent patterns as the set of correlated partial periodical frequent items. The combination of these measures has the advantage of empowering healthcare providers and patients for quality of diagnosis, and also for better treatment and smart care, especially for the elderly people at smart home. We developed an efficient algorithm named PPFP-Growth (Productive Periodic Frequent Pattern growth) to discover all productive associated partial periodic patterns using these measures. PPFP-Growth is efficient, and the productiveness measure removes uncorrelated periodic items. An experimental evaluation on synthetic and real datasets shows the efficiency of the proposed PPFP-Growth algorithm, and can filter a huge number of partial periodic patterns to reveal only the correlated ones.

To identify the effect of frailty on loneliness of older adults receiving home care, considering their socioeconomic and homebound status. This cross-sectional study enrolled 218 individuals aged ≥65 years receiving home-based health services “Help at Home” in the Region of Evrytania, Greece, after an open invitation by Municipality authorities from March to June 2022. Tilburg Frailty Indicator (TFI) was used for the evaluation of frailty, UCLA Loneliness Scale version 3 for loneliness and social isolation was accessed through five questions (living alone, frequency of interaction with children, relatives, friends, and participation in social organizations). The mean age of the participants was 81.48 ± 9.06, 61.9% were female, 54.1% experienced high levels of loneliness (UCLA-3 mean 45.76 ±11.10 [range 20-68]), and 46.3% of the participants identified as socially isolated. Also, 58.3% of the individuals were classified as frail (TFI mean 5.95 ± 3.07, [TFI range 0-13], with 57.3% experiencing physical frailty, 43.6% psychological frailty, and 27.1% social frailty. An analysis of covariance (ANCOVA) placing UCLA-3 as the dependent variable revealed that loneliness and across all domains of TFI were significantly higher in participants with frailty (total frailty [yes] 49.27 vs. [no] 40,87 p &lt;0.001) particularly, (physical frailty [Yes]=48.99 vs. [No]=41.42, p &lt;0.001, psychological: 48.60 vs. 43.57 p &lt;0.001 and social: 53.38 vs. 42.94 p &lt;0.001) compared to non-frail individuals, even after adjusting for potential confounding effects (covariates: gender, age, marital status, family status, living status, educational level, annual income, chronic diseases, homebound status, and social isolation). Our data analysis confirmed that frailty is a significant risk factor for higher levels of loneliness among older adults who received home-based healthcare.

Comprehensively understanding the spatial ecology and habitat preferences of endangered species is essential for population restoration and conservation. We investigated the home range and movement of the endangered Amur soft-shell turtle (Pelodiscus maackii) in the Ussuri River, Heilongjiang Province, Northeastern China. The study involved tracking 19 Amur soft-shell turtles from late June to mid-October, 2022, resulting in complete and partial home range size data for eight subadults and two adults, respectively. The primary analysis focused on eight subadults, and the models that best described daily movement were identified. We also explored the potential factors influencing home range size. Mean movement rate ranged from 39.18 ± 20.04 m to 72.45 ± 29.36 m and was positively correlated with the linear home range and water temperature. The most insightful home range estimate was a 95% kernel density estimate, employing likelihood cross-validation smoothing with constraints set to the river boundaries. The mean home range size was 1.02 ha and was not correlated with body size. Subadults tended to establish well-defined home ranges over time; whereas, defining home ranges for adults proved challenging. This research addresses a gap regarding the ecology of the Amur soft-shell turtle and provides a foundation for future conservation plans.

Wildland-Urban Interfaces (W-UI) are at high risk of wildfires. Defensible spaces and home ignition zones are the two main aspects to protect lives and livelihoods of W-UI in the United States, Canada and Australia. The different part of the world has different rules and regulations for W-UI land management. We have discussed the defensible spaces in fire-prone areas, current ignition zone distances from structures, building materials, architectural design, the fire resistance trees, ground cover, landscaping and some other precautions to save lives and assets in the prominent fire-prone zones for three different countries (United States, Canada and Australia) of the world.

Muscle mass at admission is important to survive stroke, and stroke-induced sarcopenia is a serious problem because of its poor prognosis. Muscle mass measurement and monitoring are essential for appropriate re-habilitation and nutrition management. Several methods are used to assess skeletal muscle mass in stroke, such as computed tomography (CT), ultrasonography, bioelectrical impedance analysis, dual-energy X-ray absorptiometry, biomarkers, and anthropometrics. In stroke, a head CT is used to estimate muscle mass by measuring the temporal muscle. However, it is mostly retrospectively conducted due to radiation exposure. After stroke, limb muscle atrophy and diaphragm dysfunction are observed using ultrasound. However, ultrasound requires an understanding of the methods and skill. A bioelectrical impedance analysis can be used to assess muscle mass in patients after a stroke unless they have dynamic fluid changes. Dual-energy X-ray absorptiometry is used for follow-up after hospital discharge. Urinary titin N-fragment and serum C-terminal agrin fragment reflect muscle atrophy after stroke. Anthropometrics may be useful with limited resources. We summarized the features of each measurement and proved the recent evidence to properly measure and monitor skeletal muscle mass after stroke.

Wetlands are recognized as one of the world’s most valuable natural resources. With the increasing world population, human demands on wetland resources for agricultural expansion and urban development continue to increase. In addition, global climate change has pronounced impacts on wetland ecosystems through alterations in hydrological regimes. To better manage and conserve wetland resources, we need to know the distribution and extent of wetlands and monitor their dynamic changes. Wetland maps and inventories can provide crucial information for wetland conservation, restoration, and management. Geographic Information System (GIS) and remote sensing technologies have proven to be useful for mapping and monitoring wetland resources. Recent advances in geospatial technologies have greatly increased the availability of remotely sensed imagery with better and finer spatial, temporal, and spectral resolution. This chapter presents an introduction to the uses of GIS and remote sensing technologies for wetland mapping and monitoring. A case study is presented to demonstrate the use of high-resolution light detection and ranging (LiDAR) data and aerial photographs for mapping prairie potholes and surface hydrologic flow pathways.