Challenges and Limitation Analysis of an IoT-Dependent System for Deployment in Smart Healthcare Using Communication Standards Features.

The use of IoT technology is rapidly increasing in healthcare development and smart healthcare system for fitness programs, monitoring, data analysis, etc. To improve the efficiency of monitoring, various studies have been conducted in this field to achieve improved precision. The architecture proposed herein is based on IoT integrated with a cloud system in which power absorption and accuracy are major concerns. We discuss and analyze development in this domain to improve the performance of IoT systems related to health care. Standards of communication for IoT data transmission and reception can help to understand the exact power absorption in different devices to achieve improved performance for healthcare development. We also systematically analyze the use of IoT in healthcare systems using cloud features, as well as the performance and limitations of IoT in this field. Furthermore, we discuss the design of an IoT system for efficient monitoring of various healthcare issues in elderly people and limitations of an existing system in terms of resources, power absorption and security when implemented in different devices as per requirements. Blood pressure and heartbeat monitoring in pregnant women are examples of high-intensity applications of NB-IoT (narrowband IoT), technology that supports widespread communication with a very low data cost and minimum processing complexity and battery lifespan. This article also focuses on analysis of the performance of narrowband IoT in terms of delay and throughput using single- and multinode approaches. We performed analysis using the message queuing telemetry transport protocol (MQTTP), which was found to be efficient compared to the limited application protocol (LAP) in sending information from sensors.

Chatbots and messaging platforms in the classroom: An analysis from the teacher's perspective.

Messaging platforms are applications, generally mediated by an app, desktop program or the web, mainly used for synchronous communication among users. As such, they have been widely adopted officially by higher education establishments, after little or no study of their impact and perception by the teachers. We think that the introduction of these new tools and the opportunities and challenges they have needs to be studied carefully in order to adopt the model, as well as the tool, that is the most adequate for all parties involved. We already studied the perception of these tools by students, in this paper we examine the teachers' experiences and perceptions through a survey that we validated with peers, and what they think these tools should make or serve so that it enhances students learning and helps them achieve their learning objectives. The survey has been distributed among tertiary education teachers, both in universitary and other kind of tertiary establishments, based in Spain (mainly) and Spanish-speaking countries. We have focused on collecting teachers' preferences and opinions on the introduction of messaging platforms in their day-to-day work, as well as other services attached to them, such as chatbots. What we intend with this survey is to understand their needs and to gather information about the various educational use cases where these tools could be valuable. In addition, an analysis of how and when teachers' opinions towards the use of these tools varies across gender, experience, and their discipline of specialization is presented. The key findings of this study highlight the factors that can contribute to the advancement of the adoption of messaging platforms and chatbots in higher education institutions to achieve the desired learning outcomes.

Correlation between diet and gut bacteria in a population of young adults.

Dietary habits strongly influence gut microbiota. The aim of this study was to compare and correlated the abundance of Firmicutes and Bacteroidetes phyla, some representative bacteria of these phyla such as Bacteroides thetaiotaomicron, Prevotella, Faecalibacterium prausnitzii, Clostridium leptum and Bifidobacterium longum as a member of Actinobacteria phylum in young adults with their food intake. Faecal samples used came from lean subjects (BMI = 19.83 ± 0.94 kg/m(2)), overweight (BMI = 27.17 ± 0.51 kg/m(2)) and obese (BMI = 41.33 ± 5.25 kg/m(2)). There were significant differences in total studied gut microbiota between the overweight and lean groups. Members of the Firmicutes phylum, and Bifidobacterium longum, were more abundant in the lean group. The results suggest that diet rich in unsaturated fatty acids and fibre promote an abundant population of beneficial bacteria such as B. longum and Bacteroidetes. However, it has been considered that the results may be biased due to the size of the individuals studied; therefore the results could be only valid for the studied population.

Correction: Specialty detection in the context of telemedicine in a highly imbalanced multi-class distribution.

[This corrects the article DOI: 10.1371/journal.pone.0290581.].

Specialty detection in the context of telemedicine in a highly imbalanced multi-class distribution.

The Covid-19 pandemic has led to an increase in the awareness of and demand for telemedicine services, resulting in a need for automating the process and relying on machine learning (ML) to reduce the operational load. This research proposes a specialty detection classifier based on a machine learning model to automate the process of detecting the correct specialty for each question and routing it to the correct doctor. The study focuses on handling multiclass and highly imbalanced datasets for Arabic medical questions, comparing some oversampling techniques, developing a Deep Neural Network (DNN) model for specialty detection, and exploring the hidden business areas that rely on specialty detection such as customizing and personalizing the consultation flow for different specialties. The proposed module is deployed in both synchronous and asynchronous medical consultations to provide more real-time classification, minimize the doctor effort in addressing the correct specialty, and give the system more flexibility in customizing the medical consultation flow. The evaluation and assessment are based on accuracy, precision, recall, and F1-score. The experimental results suggest that combining multiple techniques, such as SMOTE and reweighing with keyword identification, is necessary to achieve improved performance in detecting rare classes in imbalanced multiclass datasets. By using these techniques, specialty detection models can more accurately detect rare classes in real-world scenarios where imbalanced data is common.

Bifidobacterium longum LBUX23 Isolated from Feces of a Newborn; Potential Probiotic Properties and Genomic Characterization.

Bifidobacterium longum is considered a microorganism with probiotic potential, which has been extensively studied, but these probiotic effects are strain dependent. This work aims to characterize the probiotic potential, based on the biochemical and genomic functionality, of B. longum LBUX23, isolated from neonates' feces. B. longum LBUX23 contains one circular genome of 2,287,838 bp with a G+C content of 60.05%, no plasmids, no CRISPR-Cas operon, possesses 56 tRNAs, 9 rRNAs, 1 tmRNA and 1776 coding sequences (CDSs). It has chromosomally encoded resistance genes to ampicillin and dicloxacillin, non-hemolytic activity, and moderate inhibition of Escherichia coli ATCC 25922 and to some emergent pathogen's clinical strains. B. longum LBUX23 was able to utilize lactose, sucrose, fructooligosaccharides (FOS), and lactulose. The maximum peak of bacterial growth was observed in sucrose and FOS at 6 h; in lactose and lactulose, it was shown at 8 h. B. longum LBUX23 can survive in gastrointestinal conditions (pH 4 to 7). A decrease in survival (96.5 and 93.8%) was observed at pH 3 and 3.5 during 120 min. argC, argH, and dapA genes could be involved in this tolerance. B. longum LBUX23 can also survive under primary and secondary glyco- or tauro-conjugated bile salts, and a mixture of bile salts due to the high extracellular bile salt hydrolase (BSH) activity (67.3 %), in taurocholic acid followed by taurodeoxycholic acid (48.5%), glycocholic acid (47.1%), oxgall (44.3%), and glycodeoxycholic acid (29.7%) probably due to the presence of the cbh and gnlE genes which form an operon (start: 119573 and end: 123812). Low BSH activity was determined intracellularly (<7%), particularly in glycocholic acid; no intracellular activity was shown. B. longum LBUX23 showed antioxidant effects in DPPH radical, mainly in intact cells (27.4%). In the case of hydroxyl radical scavenging capacity, cell debris showed the highest reduction (72.5%). In the cell-free extract, superoxide anion radical scavenging capacity was higher (90.5%). The genome of B. longum LBUX23 contains PNPOx, AhpC, Bcp, trxA, and trxB genes, which could be involved in this activity. Regarding adherence, it showed adherence up to 5% to Caco-2 cells. B. longum LBUX23 showed in vitro potential probiotic properties, mainly in BSH activity and antioxidant capacity, which indicates that it could be a good candidate for antioxidant or anti-cholesterol tests using in vivo models.