RESUMO

INTRODUCTION: Common side effects after stem cell transplantation (SCT), such as anorexia, nausea, and vomiting, can disrupt the quality of life of patients. Therefore, this study aimed to determine the effect of self-care education with smart phone applications on the severity of nausea and vomiting after SCT in leukemia patients. MATERIALS AND METHODS: In this clinical trial study, using the blocked randomization method 104 leukemia patients undergoing SCT were assigned to two groups, intervention and control. The patients of the Control Group received routine care, and the Intervention Group received self-care education with a smart mobile phone application, in addition to routine care. Two weeks, one month, and three months after the start of the intervention, the severity of nausea and vomiting was evaluated using the visual analog scale (VAS) and the Khavar Oncology scale, both of which were completed by both Control and Intervention Groups. Data were analyzed using chi-square, Fisher's exact, Mann-Whitney, and Friedman tests using the Statistical Package for Social Sciences version 25 software. RESULTS: The severity of nausea and vomiting in leukemia patients undergoing SCT was significantly different in the two groups at all three timepoints (two weeks, one month, and three months) after transplantation (p-value = 0.000). CONCLUSION: The severity of nausea and vomiting after SCT in leukemia patients was improved by self-care education with a smart phone application. Therefore, this method is recommended to reduce the severity of nausea and vomiting in leukemia patients who undergo transplantation.

RESUMO

Given the growth of domotics and home automation, there is a need to use smart devices that integrate energy management systems and enable the automation of the environment. Considering the need to study the relationship between the environmental parameters in which the equipment is located and the energy parameters, an Environmental Awareness smart Plug (EnAPlug) is proposed with the application of machine learning (Tiny ML).This article presents a demonstration of EnAPlug applied to a refrigerator for predictions on internal humidity and activation motor for 5 min-ahead prediction on its operation, i.e., turning on or off. The two models for forecasting humidity presented Root Mean Squared Error (RMSE) results of 0.055 and 0.058 and a Coefficient of determination (r2 score) of 0.97 and 0.99, respectively. For the motor activation prediction, the results obtained were an accuracy of 94.74% and 94.84%, an F1 score of 0.97 for OFF, 0.94 for ON for Forecast 1 and 0.97 for OFF and 0.93 for ON for Forecast 2. Although the prototype does not have commercial purposes, what differs from existing smart plugs is the option to store data locally. The results are promising, as it allows for better energy management with implementation of machine learning.

RESUMO

Jataí is a pollinator of some crops; therefore, its sustainable management guarantees quality in the ecosystem services provided and implementation in precision agriculture. We acquired videos of natural and artificial hives in urban and rural environments with a camera positioned at the hive entrance. In this way, we obtained videos of the entrance of several colonies for multiple bee tracking and removed images from the videos for bee detectors. This data, their respective labels, and metadata make up the dataset. The dataset displays potential for utilization in computer vision tasks such as comparative studies of deep learning models. They can also integrate intelligent monitoring systems for natural and artificial hives.

RESUMO

Digital image datasets for Precision Agriculture (PA) still need to be available. Many problems in this field of science have been studied to find solutions, such as detecting weeds, counting fruits and trees, and detecting diseases and pests, among others. One of the main fields of research in PA is detecting different crop types with aerial images. Crop detection is vital in PA to establish crop inventories, planting areas, and crop yields and to have information available for food markets and public entities that provide technical help to small farmers. This work proposes public access to a digital image dataset for detecting green onion and foliage flower crops located in the rural area of Medellín City - Colombia. This dataset consists of 245 images with their respective labels: green onion (Allium fistulosum), foliage flowers (Solidago Canadensis and Aster divaricatus), and non-crop areas prepared for planting. A total of 4315 instances were obtained, which were divided into subsets for training, validation, and testing. The classes in the images were labeled with the polygon method, which allows training machine learning algorithms for detection using bounding boxes or segmentation in the COCO format.

Assuntos

RESUMO

INTRODUCTION: Up to 25% of children and 5.6% of adults in the USA have atopic dermatitis (AD), with substantial impacts on quality of life. Effective control can be challenging despite therapy efforts. The emergence of information and communication technologies (ICT) in AD management prompted this study to assess its impact on self-management. We conducted a meta-analysis to assess outcomes from peer-reviewed clinical trials evaluating the effectiveness of teledermatology, mobile health (mHealth) apps, and electronic devices for managing AD. METHODS: We searched PubMed, Web of Science, Scopus, and Embase for articles written in English and published until May 2023. RESULTS: Twelve trials with 2424 participants were selected from 811 studies. A meta-analysis of 1038 individuals reported a mean difference (MD) of -1.57 [95% confidence interval (CI): -2.24, -0.91] for the Patient Oriented Eczema Measure (POEM). A meta-analysis of 495 individuals reported a Dermatology Life Quality Index (DLQI) MD of -0.59 [95% CI: -0.95, -0.23]. Despite heterogeneity (I2 = 47% and I2 = 74%), the impact was significant (P ≤ 0.001). SCORing Atopic Dermatitis (SCORAD) showed an insignificant MD of -0.12 (P = 0.91). CONCLUSION: mHealth applications and telemonitoring show significant improvement in patients' quality of life (DLQI) and self-management (POEM) but no significant impact on AD severity (SCORAD).

RESUMO

Smart nanocarrier-based bioactive delivery systems are a current focus in nanomedicine for allowing and boosting diverse disease treatments. In this context, the design of hybrid lipid-polymer particles can provide structure-sensitive features for tailored, triggered, and stimuli-responsive devices. In this work, we introduce hybrid cubosomes that have been surface-modified with a complex of chitosan-N-arginine and alginate, making them pH-responsive. We achieved high-efficiency encapsulation of acemannan, a bioactive polysaccharide from Aloe vera, within the nanochannels of the bioparticle crystalline structure and demonstrated its controlled release under pH conditions mimicking the gastric and intestinal environments. Furthermore, an acemannan-induced phase transition from Im3m cubic symmetry to inverse hexagonal HII phase enhances the bioactive delivery by compressing the lattice spacing of the cubosome water nanochannels, facilitating the expulsion of the encapsulated solution. We also explored the bioparticle interaction with membranes of varying curvatures, revealing thermodynamically driven affinity towards high-curvature lipid membranes and inducing morphological transformations in giant unilamellar vesicles. These findings underscore the potential of these structure-responsive, membrane-active smart bioparticles for applications such as pH-triggered drug delivery platforms for the gastrointestinal tract, and as modulators and promoters of cellular internalization.

Assuntos

RESUMO

BACKGROUND: Navigated augmented reality (AR) through a head-mounted display (HMD) has led to accurate glenoid component placement in reverse shoulder arthroplasty (RSA) in an in-vitro setting. The purpose of this study is to evaluate the deviation between planned, intraoperative, and postoperative inclination, retroversion, entry point, and depth of the glenoid component placement during RSA, assisted by navigated AR through an HMD, in a surgical setting. METHODS: A prospective, multicenter study was conducted. All consecutive patients undergoing RSA in 2 institutions, between August 2021 and January 2023, were considered potentially eligible for inclusion in the study. Inclusion criteria were as follows: age >18 years, surgery assisted by AR through an HMD, and postoperative computed tomography (CT) scans at 6 weeks. All participants agreed to participate in the study and informed consent was provided in all cases. Preoperative CT scans were undertaken for all cases and used for 3-dimensional (3D) planning. Intraoperatively, glenoid preparation and component placement were assisted by a navigated AR system through an HMD in all patients. Intraoperative parameters were recorded by the system. A postoperative CT scan was undertaken at 6 weeks, and 3D reconstruction was performed to obtain postoperative parameters. The deviation between planned, intraoperative, and postoperative inclination, retroversion, entry point, and depth of the glenoid component placement was calculated. Outliers were defined as >5° for inclination and retroversion and >5 mm for entry point. RESULTS: Seventeen patients (9 females, 12 right shoulders) with a mean age of 72.8 ± 9.1 years (range, 47.0-82.0) met inclusion criteria. The mean deviation between intra- and postoperative measurements was 1.5° ± 1.0° (range, 0.0°-3.0°) for inclination, 2.8° ± 1.5° (range, 1.0°-4.5°) for retroversion, 1.8 ± 1.0 mm (range, 0.7-3.0 mm) for entry point, and 1.9 ± 1.9 mm (range, 0.0-4.5 mm) for depth. The mean deviation between planned and postoperative values was 2.5° ± 3.2° (range, 0.0°-11.0°) for inclination, 3.4° ± 4.6° (range, 0.0°-18.0°) for retroversion, 2.0 ± 2.5 mm (range, 0.0°-9.7°) for entry point, and 1.3 ± 1.6 mm (range, 1.3-4.5 mm) for depth. There were no outliers between intra- and postoperative values and there were 3 outliers between planned and postoperative values. The mean time (minutes : seconds) for the tracker unit placement and the scapula registration was 03:02 (range, 01:48 to 04:26) and 08:16 (range, 02:09 to 17:58), respectively. CONCLUSION: The use of a navigated AR system through an HMD in RSA led to low deviations between planned, intraoperative, and postoperative parameters for glenoid component placement.

RESUMO

The present study aimed to investigate the associations between nature-based intervention and peripheral pulse characteristics of patients with PAOD using new smart technology specifically designed for this purpose. A longitudinal panel study performed between 1 January 2022 and 31 December 2022 included 32 patients diagnosed with peripheral arterial occlusive disease (PAOD) who were treated in the vascular surgeons' hospital "Dobb" in Valjevo. These patients were exposed for six months to moderate-intensity physical activity (MPA) in a nature-based environment. They practiced 150 to 300 min of walking 6 km/h and cycling activities (16-20 km/h) weekly as recommended for patients with chronic conditions and those living with disability. Univariate logistic regression analysis was used to identify factors associated with major improvements in peripheral pulse characteristics of patients with PAOD. After six months of MPA, half of the patients (50%, 16/32) achieved minor, and half of them major improvements in peripheral pulse characteristics. The major improvements were associated with current smoking (OR = 9.53; 95%CI = 1.85-49.20), diabetes (OR = 4.84; 95%CI = 1.09-21.58) and cardiac failure, and concurrent pulmonary disease and diabetes (OR = 2.03; 95%CI = 1.01-4.11). Our pilot study showed that patients with PAOD along with other chronic conditions and risk factors benefited more from continuous physical activity in a nature-based environment.

Assuntos

RESUMO

The prediction of domestic electricity consumption is relevant because it helps to plan energy production, among many other benefits. In this work a dataset was collected from one house in an urban city of north-east of Mexico. An ad-hoc acquisition system was implemented to collect the data using a smart meter and the open weather API. The data was collected every minute over a period of 14 months since November 5, 2022, to January 5, 2024. The dataset contains 605,260 samples of 19 variables related with energy consumption and weather data. This dataset is specifically tailored for predicting domestic energy consumption and understanding consumption behaviours, filling a void in the existing literature where such datasets for Mexico are scarce. Moreover, the multivariate nature of the dataset allows researchers to investigate and propose new techniques for forecasting or pattern classification using multivariate data collected in a real scenario.

RESUMO

-The automatic identification of human physical activities, commonly referred to as Human Activity Recognition (HAR), has garnered significant interest and application across various sectors, including entertainment, sports, and notably health. Within the realm of health, a myriad of applications exists, contingent upon the nature of experimentation, the activities under scrutiny, and the methodology employed for data and information acquisition. This diversity opens doors to multifaceted applications, including support for the well-being and safeguarding of elderly individuals afflicted with neurodegenerative diseases, especially in the context of smart homes. Within the existing literature, a multitude of datasets from both indoor and outdoor environments have surfaced, significantly contributing to the activity identification processes. One prominent dataset, the CASAS project developed by Washington State University (WSU) University, encompasses experiments conducted in indoor settings. This dataset facilitates the identification of a range of activities, such as cleaning, cooking, eating, washing hands, and even making phone calls. This article introduces a model founded on the principles of Semi-supervised Ensemble Learning, enabling the harnessing of the potential inherent in distance-based clustering analysis. This technique aids in the identification of distinct clusters, each encapsulating unique activity characteristics. These clusters serve as pivotal inputs for the subsequent classification process, which leverages supervised techniques. The outcomes of this approach exhibit great promise, as evidenced by the quality metrics' analysis, showcasing favorable results compared to the existing state-of-the-art methods. This integrated framework not only contributes to the field of HAR but also holds immense potential for enhancing the capabilities of smart homes and related applications.

RESUMO

The reliability and scalability of Linear Wireless Sensor Networks (LWSNs) are limited by the high packet loss probabilities (PLP) experienced by the packets generated at nodes far from the sink node. This is an important limitation in Smart City applications, where timely data collection is critical for decision making. Unfortunately, previous works have not addressed this problem and have only focused on improving the network's overall performance. In this work, we propose a Distance-Based Queuing (DBQ) scheme that can be incorporated into MAC protocols for LWSNs to improve reliability and scalability without requiring extra local processing or additional signaling at the nodes. The DBQ scheme prioritizes the transmission of relay packets based on their hop distance to the sink node, ensuring that all packets experience the same PLP. To evaluate the effectiveness of our proposal, we developed an analytical model and conducted extensive discrete-event simulations. Our numerical results demonstrate that the DBQ scheme significantly improves the reliability and scalability of the network by achieving the same average PLP and throughput for all nodes, regardless of traffic intensities and network sizes.

RESUMO

Orthopaedic surgeons routinely assess the biomechanical environment of a fracture to create a fixation construct that provides the appropriate amount of stability in efforts to optimize fracture healing. Emerging concepts and technologies including reverse dynamization, "smart plates" that measure construct strain, and FractSim software that models fracture strain represent recent developments in optimizing construct biomechanics to accelerate bone healing and minimize construct failure.

RESUMO

The background of this work is related to the scheduling of household appliances, taking into account variations in energy costs during the day from 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 referred to as 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 (the Julia language). As a result, while both methodologies yield similar results, the approach presented in this article demonstrates 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.

RESUMO

The increasing urbanization in a poorly planned way accentuates the imbalance between the population's needs and the organized development in urban spaces. The present study is based on the development of a situational diagnosis in the scope of a smart city, for the contextualization of potential opportunities for actions and innovation strategies in urban spaces. This article presents a literature overview covering the innovative actions developed in the scope of smart cities in scientific publications. Furthermore, the scope of the study is identifying innovation initiatives in the performance of actions and solutions for urban spaces. A literature review was developed supported by mappings, couplings, and diagrams, through the use of VOSViewer and SciMat software, and 115 articles were selected and analyzed, considering the articles based on the criterion of the coefficient of the number of citations concerning the year of publication. In the literature overview developed, it was found that the research within the scope of smart cities has been deepened over the years, with the evolution of the number of words related to the theme in the period from 2014 to 2021, as the advance in the number of publications from 2018 is noticeable, which highlights the increase in popularity regarding the topic, as well as its current relevance. The study identified thematic axes with an emphasis on technology and innovation, environment, urbanism, energy, governance, mobility, and accessibility. The results contributed by assembling innovative smart city actions and practices in an interrelated way with technology, innovation, and market-oriented constructs aimed to reach urban demands, as well as the development of innovative solutions between public institutions and business organizations to integrate urban spaces.

RESUMO

Nowadays, the higher peak capacity achievable by comprehensive two-dimensional liquid chromatography (LC×LC) for the analysis of vegetal samples is well-recognized. In addition, numerous compounds may be present in very different amounts. Cannabinoids and terpenes represent the main components of Cannabis sativa inflorescence samples, whose quantities are relevant for many application purposes. The analyses of both families are performed by different methods, at least two different separation methodologies, mainly according to their chemical characteristics and concentration levels. In this work, concentration differences and sample complexity issues were addressed using an LC×LC method that incorporates an optimized modulation strategy, namely smart active modulation, for the simultaneous analysis of cannabinoids and terpenes. The system was built by interposing an active flow splitter pump between both dimensions. This set up aimed to exploit the known advantages of LC×LC. In addition, here we proposed to use the splitter pump for online control over the splitting ratio to facilitate the selective dilution of different eluted fractions containing compounds with highly different concentrations. This work represents the first application and demonstration of smart active modulation (SAM) in LC×LC to simultaneously determine analytes with significant differences in concentration levels present in complex samples. The proposed method was tested with eight different strains, from which fingerprints were taken, and numerous cannabinoids and terpenes were identified in these samples. With this strategy, between 49 and 54 peaks were obtained in the LC×LC chromatograms corresponding to different strains. THCA-A was the main component in six strains, while CBDA was the main component in the other two strains. The main terpenes found were myrcene (in five strains), limonene (in two strains), and humulene (in one strain). Additionally, numerous other cannabinoids and terpenes were identified in these samples, providing valuable compositional information for growers, as well as medical and recreational users. The SAM strategy here proposed is simple and it can be extended to other complex matrices.

Assuntos

RESUMO

In recent years, nanocarriers have played an ever-increasing role in clinical and biomedical applications owing to their unique physicochemical properties and surface functionalities. Lately, much effort has been directed towards the development of smart, stimuli-responsive nanocarriers that are capable of releasing their cargos in response to specific stimuli. These intelligent-responsive nanocarriers can be further surface-functionalized so as to achieve active tumor targeting in a sequential manner, which can be simply modulated by the stimuli. By applying this methodological approach, these intelligent-responsive nanocarriers can be directed to different target-specific organs, tissues, or cells and exhibit on-demand controlled drug release that may enhance therapeutic effectiveness and reduce systemic toxicity. Light, an external stimulus, is one of the most promising triggers for use in nanomedicine to stimulate on-demand drug release from nanocarriers. Light-triggered drug release can be achieved through light irradiation at different wavelengths, either in the UV, visible, or even NIR region, depending on the photophysical properties of the photo-responsive molecule embedded in the nanocarrier system, the structural characteristics, and the material composition of the nanocarrier system. In this review, we highlighted the emerging functional role of light in nanocarriers, with an emphasis on light-responsive liposomes and dual-targeted stimuli-responsive liposomes. Moreover, we provided the most up-to-date photo-triggered targeting strategies and mechanisms of light-triggered drug release from liposomes and NIR-responsive nanocarriers. Lastly, we addressed the current challenges, advances, and future perspectives for the deployment of light-responsive liposomes in targeted drug delivery and therapy.

Assuntos

RESUMO

OBJECTIVES: To describe the prevalence of Owlet Smart Sock (OSS) use in infants with supraventricular tachycardia (SVT) and associated demographic and clinical characteristics of users and to analyze the association of OSS use on medical resource use and clinical outcomes from emergency department (ED) encounters for SVT. STUDY DESIGN: This was a single-center, retrospective cohort study of infants with confirmed SVT from 2015 to 2022. OSS users and nonusers were compared across clinical and demographic parameters. Medical resource use (phone calls, office visits, ED visits) and outcomes (need for intensive care, length of stay, echocardiographic function, clinical appearance) were compared between OSS users and nonusers. RESULTS: Of 133 infants with SVT, OSS was used by 31 of 133 (23%), purchased before SVT diagnosis in 5 in 31 (16%) of users. No demographic difference was found between OSS users and nonusers. OSS users had more phone notes than nonusers, (P = .002) and more ED visits (P = .03), but the number of office visits and medication adjustments did not differ. During ED presentation, OSS users had better preserved left ventricular ejection fraction on echocardiogram (P = .04) and lower length of hospital stay by a mean 1.7 days (P = .02). CONCLUSIONS: OSS is used by a portion of infants with SVT. It is associated with more frequent phone calls and ED visits but lower length of stay and better-preserved cardiac function upon presentation.

Assuntos

RESUMO

The risk to human health from mosquito-borne viruses such as dengue, chikungunya and yellow fever is increasing due to increased human expansion, deforestation and climate change. To anticipate and predict the spread and transmission of mosquito-borne viruses, a better understanding of the transmission cycle in mosquito populations is needed. We present a pathogen-agnostic combined sequencing protocol for identifying vectors, viral pathogens and their hosts or reservoirs using portable Oxford Nanopore sequencing. Using mosquitoes collected in São Paulo, Brazil, we extracted RNA for virus identification and DNA for blood meal and mosquito identification. Mosquitoes and blood meals were identified by comparing cytochrome c oxidase I (COI) sequences against a curated Barcode of Life Data System (BOLD). Viruses were identified using the SMART-9N protocol, which allows amplified DNA to be prepared with native barcoding for nanopore sequencing. Kraken 2 was employed to detect viral pathogens and Minimap2 and BOLD identified the contents of the blood meal. Due to the high similarity of some species, mosquito identification was conducted using blast after generation of consensus COI sequences using RACON polishing. This protocol can simultaneously uncover viral diversity, mosquito species and mosquito feeding habits. It also has the potential to increase understanding of mosquito genetic diversity and transmission dynamics of zoonotic mosquito-borne viruses.

Assuntos

RESUMO

PURPOSE: Assistive technologies based on IoT can contribute to improve quality of living of patients with severe motor difficulties by providing partial or total independence. The aim of this work was to analyse the usability and performance of an assistive system based on the IoT when is evaluated by a child patient with spinal muscular atrophy type 1 (SMA-I). MATERIALS AND METHODS: The study involved a child with SMA-I and his caregiver. The materials used include an M5Stack Core2 kit, a mobile app, and a smart switch based on the ESP-01S card. The patient sends requests to the caregiver from the app installed on the M5Stack Core2 to a mobile app, and controls smart switches located in the rooms. The system was tested by the participants for a period of 30 days to later evaluate its usability and performance. RESULTS: The results show that the control function of smart switches is the most used and there is no decrease in interactions over the days for the system in general. In addition, the scores obtained from both usability tests (patient and caregiver) were 87.5% and 90%, respectively. The average performance of the entire system was 93.33%. CONCLUSION: The application of assistive technologies based on the IoT allows obtaining a practical solution that improves the development of daily activities in a patient with SMA-I.

A low-cost device can contribute to improve the quality of living of spinal muscular atrophy patients by favouring partial or total independence.IoT-based assistive technologies allow obtaining practical solutions that improve the development of daily activities.

Assuntos