ROLE OF PERMITTIVITY MATCHING IN DESIGNING OF EFFICIENT LIQUID IONIC ANTENNA

The aim of this paper is to provide an understanding of the use of NaCl based ionic solution in biocompatible antenna structures and to explain some of the previously unfamiliar limitations of such antennas especially when they are operated nearby or inside the human body. In this paper, role of matching the permittivity of wearable loop antenna with body tissues is discussed and the performance of the liquid ionic solution loop antenna is compared with the metallic loop antenna  using FEK

Detection of Paracetamol as substrate of the gut microbiome

Gut microbiome, a new organ; represent targets to alter pharmacokinetics of orally administered drugs. Recently, in vitro trials endorsed the idea that orally administered drugs interact and some of their quantity may be taken up by normal microbiome during transit through gut. Such transport mechanisms in microbiome may compete for drug with the host itself. Currently, no data confirms specific transport system for paracetamol uptake by gut microbiome. In vivo trial was conducted in normal healthy male rats (n=36). Paracetamol was administered orally in a single dose of 75mg/kg to isolate microbial mass after transit of 2, 3, 4, 5 and 6 hours post drug administration. Paracetamol absorbance by microbiome was pursued by injecting extracted microbial lysate in RP-HPLC-UV with C18 column under isocratic conditions at 207nm using acetonitrile and water (25:75 v/v) pH 2.50 as mobile phase. Paracetamol absorbance (14.10±0.75μg/mg of microbial mass) and percent dose recovery (13.16±0.55%) seen at transit of 4 hours was significantly higher (P<0.05) compared to other groups. Study confirms the hypothesis of homology between membrane transporters of the gut microbiome and intestinal epithelium. Orally administered drugs can be absorbed by gut microbes competitively during transit in small intestine and it varies at various transit times

Voice disorder detection using machine learning algorithms: An application in speech and language pathology

The healthcare industry is currently seeing a significant rise in the use of mobile devices. These devices not only provide ways for communication and sharing of multimedia information, such as clinical notes and medical records, but also offer new possibilities for people to detect, monitor, and manage their health from anywhere at any time. Digital health technologies have the potential to improve patient care by making it more efficient, effective, and cost-effective. Utilizing digital devices and technologies can have a positive impact on many health conditions. This research focuses on dysphonia, a change in the sound of the voice that affects around one-third of individuals at some point in their lives. Voice disorders are becoming more common, despite being often overlooked. Mobile healthcare systems can provide quick and efficient assistance for detecting voice disorders. To make these systems reliable and accurate, it is important to develop an algorithm that can classify intelligently healthy and pathological voices. To achieve this task, we utilized a combination of several datasets such as Saarbruecken voice dataset (SVD), the Massachusetts Eye and Ear Infirmary database (MEEI), and a few private datasets of various voices (healthy and pathological) Additionally, we applied multiple machine learning algorithms, including decision tree, random forest, and support vector machine, to evaluate and determine the most effective algorithm among them for the detection of voice disorders. The experimental analyses are performed in terms of sensitivity, accuracy, receiver operating characteristic area, specificity, F-score and recall. The results demonstrated that the support vector machine algorithm, depending on the features selected by using appropriate feature selection methods, proved to be the most accurate in detecting voice diseases

A Brief Assessment on Recent Developments in Efficient Electrocatalytic Nitrogen Reduction with 2D Non-Metallic Nanomaterials

In recent years, the synthesis of ammonia (NH3) has been developed by electrocatalytic technology that is a potential way to effectively replace the Haber&ndash;Bosch process, which is an industrial synthesis of NH3. Industrial ammonia has caused a series of problems for the population and environment. In the face of sustainable green synthesis methods, the advantages of electrocatalytic nitrogen reduction for synthesis of NH3 in aqueous media have attracted a great amount of attention from researchers. This review summarizes the recent progress on the highly efficient electrocatalysts based on 2D non-metallic nanomaterial and provides a brief overview of the synthesis principle of electrocatalysis and the performance measurement indicators of electrocatalysts. Moreover, the current development of N2 reduction reaction (NRR) electrocatalyst is discussed and prospected

Outcomes after anti-thymocyte globulin vs Basiliximab induction before deceased donor kidney transplants

Background: Deceased donor kidney transplants represent an important source of renal replacement for the 100 000 patients initiating hemodialysis annually. We compared the association of induction therapy, anti-thymocyte globulin [rabbit] (rATG) or basiliximab, with posttransplant rejection, graft and patient survival.Methods: Using the United Network for Organ Sharing (UNOS) database, we identified patients that received deceased donor kidney transplants. The outcomes analyzed were 6- month rejection, 1-year rejection, patient survival and graft survival. Multivariate logistic regression models were constructed to understand the association of induction therapy and rejection. Cox-proportional hazards models were constructed to ascertain the association of choice of induction therapy with both patient and graft survival.Results: Of 45 339 patients, 33 906 patients received rATG induction therapy and 11 433 patients received basiliximab induction therapy. The rATG group were younger (53.44 years vs 55.28 years, P \u3c 0.001), more frequently female (58.74% male vs 66.08%, P \u3c 0.001) and more frequently Black (34.78% vs 25.66%, p \u3c 0.001) compared with patients in the basiliximab group. Rejection was more likely with basiliximab compared with rATG at 6 months(OR = 1.64, P \u3c 0.001; 7.81% Basiliximab vs 5.23% rATG)and at 12 months (OR = 1.56, P \u3c 0.001; 8.81% Basiliximab vs 6.31% rATG). Basiliximab induction therapy was associated with worse patient survival, (HR = 1.05, P = 0.017). Basiliximab induction therapy was associated with worse graft survival, (HR = 1.03, P = 0.037).Conclusion: The analysis of the national experience demonstrated favorable rejection, patient survival, and graft survival with rATG usage. Further prospective data are necessary to provide treatment recommendations