Models and Methods for Improving Performance of Wireless Computer Networks Based on the Decomposition of Lower Layers of the OSI Reference Model

The paper discusses models and methods for improving the performance of wireless computer networks built based on the decomposition of the lower levels of the OSI reference model. A method to improve the performance of networks is suggested, which functionally combines the physical and network layers, which improves its efficiency in marginal reception areas almost twice. A model of the block diagram of a device for improving data transmission quality in marginal reception areas or those with insufficient noise immunity is developed based on the so-called communication quality status monitoring, as well as a model of the block diagram of a wireless adaptive capacity reallocation router based on dynamic channels capacity reallocation, which allows adequately reallocating IS resources depending on traffic and user priority. Keywords— Bluetooth, FIFO discipline, IEEE 802.11, OSI/ISO reference model, wireless computer networks.

Microbiome Research and Multi-Omics Integration for Personalized Medicine in Asthma

Asthma is a multifactorial inflammatory disorder of the respiratory system characterized by high diversity in clinical manifestations, underlying pathological mechanisms and response to treatment. It is generally established that human microbiota plays an essential role in shaping a healthy immune response, while its perturbation can cause chronic inflammation related to a wide range of diseases, including asthma. Systems biology approaches encompassing microbiome analysis can offer valuable platforms towards a global understanding of asthma complexity and improving patients’ classification, status monitoring and therapeutic choices. In the present review, we summarize recent studies exploring the contribution of microbiota dysbiosis to asthma pathogenesis and heterogeneity in the context of asthma phenotypes–endotypes and administered medication. We subsequently focus on emerging efforts to gain deeper insights into microbiota–host interactions driving asthma complexity by integrating microbiome and host multi-omics data. One of the most prominent achievements of these research efforts is the association of refractory neutrophilic asthma with certain microbial signatures, including predominant pathogenic bacterial taxa (such as Proteobacteria phyla, Gammaproteobacteria class, especially species from Haemophilus and Moraxella genera). Overall, despite existing challenges, large-scale multi-omics endeavors may provide promising biomarkers and therapeutic targets for future development of novel microbe-based personalized strategies for diagnosis, prevention and/or treatment of uncontrollable asthma.

Perubahan IMT pada Penderita Hipertensi Sebelum dan Selama Masa Pandemi Covid-19

Changes in Body Mass Index (BMI) are the main predictors in controlling blood pressure, especially during the COVID-19 pandemic. This article aims to measure changes in BMI before and during COVID-19 for controlling obesity in hypertensive. This is a further analysis data from the Bogor Cohort Study on NCD Risk Factor and the study of the Impact of the COVID-19 Pandemic Period on Health and Mental Health Service Efforts in 2020 conducted 750 hypertension cases during 2011-2018. The dependent variable is the change in BMI which is categorized stable, decreasing, increasing based on the cut off of the mean difference in BMI. The independent variables include demographic characteristics, ownership of Health Insurance, behavior, disease status, monitoring of blood pressure, height and body weight and therapy. Data were analyzed by multinomial logistic regression. The proportion of hypertensive who experienced changes in BMI was stable, decreased and increased, respectively by 24.5 percent, 49 percent and 26.5 percent. Factors associated with changes in BMI decreased in hypertensive patients were obesity with a risk of 1.7 times (95% CI 1.1–2.6) and stress 4.8 times (95% CI 1.4–16). The factor of increased BMI changes were obesity with a protective risk of 0.6 times (95% CI 0.4 -0.9), sitting more than 5.5 hours had a risk of 1.6 (95 % CI 1.1 – 2.6), and smoking ≥200 cigarettes/day has a 4.2 times risk (95% CI 1.4 – 13.0). Suggestions need efforts to maintain a stable BMI by doing physical activity, managing stress and not smoking. Key words: changes in BMI, hypertension, COVID-19 pandemic Abstrak Perubahan Indeks Massa Tubuh (IMT) merupakan prediktor utama dalam pengendalian tekanan darah khususnya di masa pendemi COVID-19. Artikel bertujuan mengukur perubahan IMT sebelum dan pada masa COVID-19 untuk pengendalian obesitas pada penderita hipertensi. Artikel ini merupakan hasil analisis lanjut dari sumber data Studi Kohor Faktor Risiko PTM Bogor dan studi Dampak Masa Pandemi COVID-19 pada Upaya Pelayanan Kesehatan dan Kesehatan Mental tahun 2020 pada 750 kasus hipertensi periode 2011-2018. Variabel dependen adalah perubahan IMT yang dikategorikan menjadi 3 yaitu stabil, turun, naik berdasarkan cut off rerata perbedaan IMT. Variabel independen meliputi karakteristik demografi (umur, jenis kelamin, pekerjaan), kepemilikan Jaminan Kesehatan Nasional (JKN), perilaku (merokok, olahraga, lama duduk), status penyakit (gangguan mental emosional, komorbid), pemantauan (tekanan darah, tinggi badan, berat badan) dan perilaku pengobatan. Data dianalisis dengan regresi logistik multinomial. Proporsi penderita hipertensi yang mengalami perubahan IMT stabil, turun dan naik, masing-masing sebesar 24,5 persen, 49 persen dan 26,5 persen. Faktor-faktor yang berhubungan bermakna dengan perubahan IMT turun pada penderita hipertensi adalah obesitas dengan risiko 1,7 kali (95% CI 1,1– 2,6) dibanding normal dan stress 4,8 kali (95% CI 1,4 – 16,0), sedangkan faktor perubahan IMT naik yang berhubungan bermakna adalah obesitas risiko protektif 0,6 kali (95% CI 0,4 -0,9) dibandingkan tidak obese, lama duduk lebih dari 5,5 jam berisiko 1,6 (95% CI 1,1 – 2,6), serta merokok ≥200 batang/hari berisiko 4,2 kali (95% CI 1,4 – 13,0) dibandingkan bukan perokok. Saran perlu upaya menjaga IMT tetap stabil dengan cara melakukan aktifitas fisik, mengelola stres dan tidak merokok. Kata kunci : perubahan IMT, hipertensi, pandemic COVID-19

Musculoskeletal Rehabilitation Status Monitoring Based on sEMG

The reduction and improper movements in people’s modern life will lead to physical discomfort, pain, and inflammation, which have generally affected the quality of people’s daily life and work efficiency. The pain caused by improper movements are called musculoskeletal pain, which can be relieved or eliminated with treatment. Musculoskeletal disorders are actually one of the most common medical conditions, which affects approximately one quarter of all adults in the world. Although surface electromyography (sEMG) is an acknowledged technology in musculoskeletal rehabilitation study, it is considerably significant to monitor the musculoskeletal rehabilitation status based on sEMG. In order to monitor the musculoskeletal rehabilitation status, we combine fuzzy theory with neural network. This article proposes variable size, sliding window-based, generalized, dynamic, fuzzy neural network (GD-FNN), musculoskeletal rehabilitation status monitoring, that is, the window length of sliding window of sample data changes with the size of sample period. Finally, this study made a simulation on subjects, and the experimental results show that the proposed variable size, sliding window-based GD-FNN, musculoskeletal rehabilitation status monitoring method not only has good monitoring effect but also put on a good performance in root-mean-squared error (RMSE) and mean absolute percentage error (MAPE).