Internet of Things Framework in Athletics Physical Teaching System and Health Monitoring

The modern Internet of Things (IoT) paradigm enables creating small devices that can provide sensor, process, and connect, facilitating sensors, embedded devices, and other “things” ready for understanding the environment. Physical education and physical activity can improve both the physical and mental health of practitioners. However, there are many issues or accidents occurred to the athletes during training and tournament. In addition, lack of awareness during a match or game could lead to injuries and dropping the competition or match. This study proposes an IoT-based Wearable Intelligent Health Monitoring system (IoTW-IHMS) for the physical teaching system and athletes’ health monitoring. This study intends to collect and track data on player rates, body temperature, and response time to stimulation while using compact wearable devices and microprocessors as the main device to relay them wirelessly. Multiple sensors tracked the heart rate, current body temperature, and response time of the athlete. The simulation analysis shows that the proposed IoTW-IHMS method enhances the accuracy (93.6%), response time ratio (95.4%), sensitivity ratio (97.5%), performance ratio (91.3%), and prediction ratio (96.8%) compared to other popular methods.

Real-time profilometry by bicolor grating video projection

A novel real-time 2+1 three-dimensional(3D) measuring method based on bicolor grating video projection is proposed. Firstly, only two frames of bicolor gratings, in which the red channels are two sinusoidal fringes with a shifting phase of π/2 and the blue channels are the same background light equivalent to the DC component of the two sinusoidal fringes are encoded and arranged alternatively to synthesize into a repetitive bicolor grating video, While this video is projected onto the measured object, the real-time bicolor deformed pattern video can be recorded by using a color CMOS camera, and the bicolor deformed pattern sequence at different moments can be extracted by computer processing, so that the 2+1 algorithm can be used to accomplish real-time 3D measurement of moving object. Before measuring, we used the same method to design two sinusoidal fringes with a difference of π in their red channels, respectively, to calibrate the sensitivity ratio between the red and blue channels of the CMOS camera, which can effectively eliminate the chromaticity imbalance between R and B channels and reduce the color crosstalk. Experimental results and analysis confirm the feasibility and effectiveness of the proposed method. Because the proposed method needs a repetitive bicolor grating video synthesized with only two-frame bicolor gratings to be projected, the 3D measurement acquisition speed and real-time accuracy will be improved compared with the traditional 2+1 3D measuring method.

A Study of Compressibility, Compactability and Mucoadhesivity of Tableting Materials for Matrix Systems Based on Chitosan

The objective of the present research is to evaluate directly compressible chitosan-based tableting materials for the formulation of mucoadhesive matrix tablets intended for targeted drug release to distal segments of the GIT. The influence of sodium alginate, hypromellose, and silicified microcrystalline cellulose (P90) on compressibility, compactability and lubricant sensitivity ratio was tested. Furthermore, the rheological properties of the hydrated surface layer of the matrix tablets and the mucoadhesion to a mucin substrate were analysed. Compressibility was evaluated using the energy profile of the compression process, compactability by means of the tensile strength of tablets, and lubricant sensitivity ratio was calculated to assess the sensitivity to lubricant. Addition of P90 to chitosan improved compressibility, which is demonstrated by the increase in the energy of plastic deformation and the higher tensile strength of tablets. P90 also significantly reduced the high lubricant sensitivity of chitosan. Presence of retarding components led to a decrease in Emax. All tested matrix tablets revealed a good mucoadhesion without a negative effect of P90 content. The viscosity of a gel layer on the surface of matrix tablets containing hypromellose was higher compared to those with sodium alginate. This was not reflected in the adhesive strength of the tablets. The formulated tableting materials combining chitosan and P90 are a suitable matrix for incorporation of an active ingredient, whose delayed release in the intestine can be achieved by the functionality of the chitosan-sodium alginate complex.

Deep learning for early dental caries detection in bitewing radiographs

The early detection of initial dental caries enables preventive treatment, and bitewing radiography is a good diagnostic tool for posterior initial caries. In medical imaging, the utilization of deep learning with convolutional neural networks (CNNs) to process various types of images has been actively researched, with promising performance. In this study, we developed a CNN model using a U-shaped deep CNN (U-Net) for caries detection on bitewing radiographs and investigated whether this model can improve clinicians’ performance. The research complied with relevant ethical regulations. In total, 304 bitewing radiographs were used to train the CNN model and 50 radiographs for performance evaluation. The diagnostic performance of the CNN model on the total test dataset was as follows: precision, 63.29%; recall, 65.02%; and F1-score, 64.14%, showing quite accurate performance. When three dentists detected caries using the results of the CNN model as reference data, the overall diagnostic performance of all three clinicians significantly improved, as shown by an increased sensitivity ratio (D1, 85.34%; D1′, 92.15%; D2, 85.86%; D2′, 93.72%; D3, 69.11%; D3′, 79.06%; p < 0.05). These increases were especially significant (p < 0.05) in the initial and moderate caries subgroups. The deep learning model may help clinicians to diagnose dental caries more accurately.

Investigation of the characteristics of matrix multi-element avalanche photodetectors operating in the photon counting mode

At present, matrix multi-element avalanche photodetectors operating in the photon counting mode are widely used for detecting optical radiation. However, the char-acteristics of matrix multi-element avalanche photodetectors operating in this mode are currently insufficiently studied. Prototypes of Si-photomultiplier tubes (Si-PMTs) with a p+–p–n+ structure produced by JSC Integral (Republic of Belarus), as well as serially produced silicon photomultipliers Ketek PM 3325 and ON Semi FC 30035 have been used as objects of research. This article presents the research results of characteristics in the photon counting mode of the specified photodetec-tors. The dependences of the specific amplitude sensitivity ratio on the wavelength of optical radiation, the temperature, the supply voltage of the matrix multi-element avalanche photodetector are determined.

Soccer player activity prediction model using an internet of things-assisted wearable system

BACKGROUND: Soccer is one of the world’s most successful sports with several players. Quality player’s activity management is a tough job for administrators to consider in the Internet of Things (IoT) platform. Candidates need to predict the position, intensity, and path of the shot to look back on their results and determine the stronger against low shot and blocker capacities. OBJECTIVE: In this paper, the IoT-assisted wearable device for activity prediction (IoT-WAP) model has been proposed for predicting the activity of soccer players. METHOD: The accelerometer built wearable devices formulates the impacts of multiple target attempts from the prevailing foot activity model that reflect a soccer player’s characteristics. The deep learning technique is developed to predict players’ various actions for identifying multiple targets from the differentiated input data compared to conventional strategies. The Artificial Neural Network determines a football athlete’s total abilities based on football activities like transfer, kick, run, sprint, and dribbling. RESULTS: The experimental results show that the suggested system has been validated from football datasets and enhances the accuracy ratio of 97.63%, a sensitivity ratio of 96.32%, and a specificity ratio of 93.33% to predict soccer players’ various activities.

Challenges and issues in the development of the human healthcare system

The social health care system is a single-stop solution for overseas patients seeking worldwide. Human is linked to globally certified healthcare companies, clinics, dental centers, and allows patients to access the best medical care. The significant challenges in developing the human healthcare system include efficiency, security, and sustainable medical devices linked to the Internet. A healthcare system usually includes different intelligent technologies from various disciplines. This manuscript proposed a Virtual reality-based Integrated delivery model (VRIDS) for the healthcare system to minimize the challenges. This paper uses Exclusive Provider Organizations’ methods, Point-of-Service methods, for developing the human health system. VRIDS provides a Higher quality of care with more efficiency in tracking the body’s movements to view the human’s inner body and allow an immersion sensation. Finally, results from various patients and doctors are highly recommended in these techniques to improve the human healthcare system and a cost-effective system and convenience to patients and doctors. The experimental results have been performed, and the suggested VRIDS model enhances the accuracy ratio of 97.8%, sensitivity ratio of 98.2%, decision-making level 96.5%, network performance ratio of 97.1%, and quality of service of 98.3% compared to other existing methods.

Blue light inactivation of the enveloped RNA virus Phi6

Objective Ultraviolet radiation is known for its antimicrobial properties but unfortunately, it could also harm humans. Currently, disinfection techniques against SARS-CoV-2 are being sought that can be applied on air and surfaces and which do not pose a relevant thread to humans. In this study, the bacteriophage phi6, which like SARS-CoV-2 is an enveloped RNA virus, is irradiated with visible blue light at a wavelength of 455 nm. Results For the first time worldwide, the antiviral properties of blue light around 455 nm can be demonstrated. With a dose of 7200 J/cm2, the concentration of this enveloped RNA virus can be successfully reduced by more than three orders of magnitude. The inactivation mechanism is still unknown, but the sensitivity ratio of phi6 towards blue and violet light hints towards an involvement of photosensitizers of the host cells. Own studies on coronaviruses cannot be executed, but the results support speculations about blue-susceptibility of coronaviruses, which might allow to employ blue light for infection prevention or even therapeutic applications.

Assessing the risk of ketoacidosis due to sodium-glucose cotransporter (SGLT)-2 inhibitors in patients with type 1 diabetes: A meta-analysis and meta-regression

Background Sodium-glucose cotransporter-2 (SGLT2) inhibitors (SGLT2i) showed benefits in type 1 diabetes mellitus (T1DM), but the risk of diabetic ketoacidosis (DKA) limits their use. Ability to predict DKA risk and therapeutic responses would enable appropriate patient selection for SGLT2i. We conducted a meta-analysis and meta-regression of randomized controlled trials (RCTs) evaluating SGLT2i in T1DM to assess moderators of the relative risk (RR) of DKA, of glycemic (HbA1c, fasting plasma glucose, continuous glucose monitoring parameters, insulin dose, and insulin sensitivity indices) and non-glycemic (body mass index (BMI), systolic BP, renal function, albuminuria, and diabetic eye disorders) efficacy, and of other safety outcomes (including hypoglycemia, infections, major adverse cardiovascular events, and death). Methods and findings We searched MEDLINE, Cochrane Library, EMBASE, ClinicalTrials.gov, Cochrane CENTRAL Register of Controlled Trials, and other electronic sources through August 30, 2020, for RCTs comparing SGLT2i with active comparators or placebo in adult patients with T1DM. Reviewers extracted data for relevant outcomes, performed random effects meta-analyses, subgroup analyses, and multivariable meta-regression. The strength of evidence was summarized with the GRADE approach. Among 9,914 records identified, 18 placebo-controlled RCTs (7,396 participants, 50% males, mean age 42 y (range 23 to 55 y), 5 different SGLT2i evaluated), were included. Main outcome measures were effect sizes and moderators of glycemic and non-glycemic efficacy and of safety outcomes. In a multivariable meta-regression model, baseline BMI (β = 0.439 [95% CI: 0.211, 0.666], p < 0.001) and estimated glucose disposal rate (eGDR) (β = −0.766 [−1.276, −0.256], p = 0.001) were associated with the RR of DKA (RR: 2.81; 95% CI:1.97, 4.01; p < 0.001, R2 = 61%). A model including also treatment-related parameters (insulin dose change-to-baseline insulin sensitivity ratio and volume depletion) explained 86% of variance across studies in the risk of DKA (R2 = 86%). The association of DKA with a BMI >27 kg/m2 and with an eGDR <8.3 mg/kg/min was confirmed also in subgroup analyses. Among efficacy outcomes, the novel findings were a reduction in albuminuria (WMD: −9.91, 95% CI: −16.26, −3.55 mg/g, p = 0.002), and in RR of diabetic eye disorders (RR: 0.27[0.11, 0.67], p = 0.005) associated with SGLT2i. A SGLT2i dose-response gradient was consistently observed for main efficacy outcomes, but not for adverse events (AEs). Overall, predictors of DKA and of other AEs differed substantially from those of glycemic and non-glycemic efficacy. A limitation of our analysis was the relatively short (≤52 weeks) duration of included RCTs. The potential relevance for clinical practice needs also to be confirmed by real-world prospective studies. Conclusions In T1DM, the risk of DKA and main therapeutic responses to SGLT2i are modified by baseline BMI and insulin resistance, by total insulin dose reduction-to-baseline insulin sensitivity ratio, and by volume depletion, which may enable the targeted use of these drugs in patients with the greatest benefit and the lowest risk of DKA.

Comparison between Specificity and Sensitivity of Intestinal Giardialamblia Assays in AL-Door District, Salahdin Province, Iraq

The Giardia lamblia is known as a considerable cause of diarrhea in human. Difficulties are confronted in the detection of that parasite in patients’ faces because of intermittent excretion of the parasite.In this study it was determined specificity and sensitivity of floatation methodby zinc sulphate solution and ELISA assay for Giardialamblia detection compared with direct iodine stain methodAmong 82 patients who were attending AL-Door hospital through period of September to December 2018. The prevalence of Giardiasis was 32.9% and 67.1% was negative. As well this study showed that the percentage of G. lamblia infection was 31.7% by direct iodine stain method, 29.3% was by floatation methodand the sensitivity ratio was 92.3%, specificity was 100%,While 32.9% was positive by ELISA assay and the sensitivity ratio was 92.3%, specificity was 94.6%. Also our study found that the prevalence for Giardiasis depending on gender in this study was 67% for male, 33.3% for female. The results of study were showed the prevalence of infection was 23.2% in age group 8-25 years, 7.3% in 26-35 years and 2.4% in age group 36-45 years. The distribution of infection depends on residencewhich was 20.7% for rural and 12.2% for urban