Eulers Totient Function (Number Theoretic Functions), Right Angle Triangle and Their Applications

In this paper, we introduce some new theorem and results(section Ⅱ,Ⅲ and Ⅵ) on Euler’ s Totient Function , Right angle triangle and their applications Keywords: Euler’ s totient function, right angle triangle, Golden ratio, Hardy – Ramanujan number, student’s pencil compass and etc.

Evaluation of Parameter Settings for Training Neural Networks Using Backpropagation Algorithms

Artificial neural networks (ANN) are widely used for classification, and the training algorithm commonly used is the backpropagation (BP) algorithm. The major bottleneck faced in the backpropagation neural network training is in fixing the appropriate values for network parameters. The network parameters are initial weights, biases, activation function, number of hidden layers and the number of neurons per hidden layer, number of training epochs, learning rate, minimum error, and momentum term for the classification task. The objective of this work is to investigate the performance of 12 different BP algorithms with the impact of variations in network parameter values for the neural network training. The algorithms were evaluated with different training and testing samples taken from the three benchmark clinical datasets, namely, Pima Indian Diabetes (PID), Hepatitis, and Wisconsin Breast Cancer (WBC) dataset obtained from the University of California Irvine (UCI) machine learning repository.

SPEECH RECOGNITION APPLICATION AS AN ANIMATED OBJECT MOVEMENT CONTROLLER SYSTEM

Technological developments in the world have no boundaries. One of them is Speech Recognition. At first, words spoken by humans cannot be recognized by computers. To be recognizable, the word is processed using a specific method. Linear Predictive Coding Method (LPC) is a method used in this research to extract the characteristics of speech. The result of the LPC method is the LPC coefficient which is the number of LPC orders plus 1. The LPC coefficient is processed using Fast Fourier Transform (FFT) 512 to simplify the process of speech recognition. The results are then trained using Backpropagation Neural Network (BPNN) to recognize the spoken word. Speech recognition on the program is implemented as an animated object motion controller on the computer. The end result of this research is animated objects move in accordance with the spoken word. The optimal BPNN structure in this research is to use traingda training function, number of nodes 3, learning rate 0.05, epoch 1000, performance goal 0,00001. This structure can produce the smallest MSE value that is 0,000009957. So, this structure can recognize new words with 100% accuracy for trained data, 80% for the same respondents with trained data and reach 67.5% for new respondents.

Lymphopenia, Lymphopenia-Induced Proliferation, and Autoimmunity

Immune homeostasis is a tightly regulated system that is critical for defense against invasion by foreign pathogens and protection from self-reactivity for the survival of an individual. How the defects in this system might result in autoimmunity is discussed in this review. Reduced lymphocyte number, termed lymphopenia, can mediate lymphopenia-induced proliferation (LIP) to maintain peripheral lymphocyte numbers. LIP not only occurs in normal physiological conditions but also correlates with autoimmunity. Of note, lymphopenia is also a typical marker of immune aging, consistent with the fact that not only the autoimmunity increases in the elderly, but also autoimmune diseases (ADs) show characteristics of immune aging. Here, we discuss the types and rates of LIP in normal and autoimmune conditions, as well as the coronavirus disease 2019 in the context of LIP. Importantly, although the causative role of LIP has been demonstrated in the development of type 1 diabetes and rheumatoid arthritis, a two-hit model has suggested that the factors other than lymphopenia are required to mediate the loss of control over homeostasis to result in ADs. Interestingly, these factors may be, if not totally, related to the function/number of regulatory T cells which are key modulators to protect from self-reactivity. In this review, we summarize the important roles of lymphopenia/LIP and the Treg cells in various autoimmune conditions, thereby highlighting them as key therapeutic targets for autoimmunity treatments.

Telerehabilitation During the Covid-19 Pandemic in Outpatient Rehabilitation Settings: A Descriptive Study

Objective COVID-19 has widely affected delivery of health care. In response, telerehabilitation (TR) has emerged as alternative care model. Aims were: (1) describe baseline patient characteristics and available unadjusted outcomes for episodes of care administered during COVID-19 using TR vs. traditional in-person care, (2) describe TR frequency levels by condition and telecommunication modes. Methods A descriptive retrospective observational design was used to report patient variables and outcomes including physical function, number of visits, and patient satisfaction, by TR frequency (few, most, or all visits) and telecommunication modes. Standardized differences were used to compare baseline characteristics between episodes with and without TR. Results Sample consisted of 222,680 patients [59% female; mean age (SD) = 55(18)]. Overall TR rate was 6% decreasing from 10% to 5% between 2nd and 3rd quarters of 2020. Outcome measures were available for 90% to 100% of episodes. Thirty-seven percent of clinicians administered care via TR. Patients treated using TR compared to in-person care were more likely to be younger, and live in large metropolitan areas. From those with TR, 55%, 20%, and 25% had TR during few, most, or all visits, respectively. TR care was administered equally across orthopedic body parts, with lower use for non-orthopedic conditions such as stroke, edema, and vestibular dysfunction. TR was primarily administered using synchronous (video or audio) modes. The rate of patients reported being very satisfied with their treatment results was 3% higher for no TR compared to TR. Conclusions These results provide new knowledge about to whom and how TR is being administered during the pandemic in outpatient rehabilitation practices throughout the USA. The database assessed was found to be suitable for conducting studies on associations between TR and diverse outcome measures, controlling for a comprehensive set of patient characteristics, to advance best TR care models, and promote high quality care. Impact This study provided detailed and robust descriptive information using an existing national patient database containing patient health and demographic characteristics, outcome measures, and TR administration data. Findings support the feasibility to conduct future studies on associations between TR care and patient outcomes, adjusting for a wide range of patient characteristics and clinical setting factors that may be associated with the probability of receiving TR. Finding of limited and decreasing use of TR over the study period calls for studies aimed to better understand facilitators and inhibitors of TR use by rehabilitation therapists during everyday practice to promote its use when clinically appropriate.

Perencanaan Partisipatif Tanggap Darurat Bencana Tsunami Di Pesisir Selatan Watulimo, Trenggalek

The research aims to mapping the tsunami-prone areas in Watulimo District using numerical simulation methods and spatial analysis as well as compiling tsunami response planning by determining shelters and evacuation routes in a participatory manner according to the characteristics of residents local wisdom of Watulimo District using weighting analysis and network analysis with ArcGIS. The most prone area to tsunami is Prigi Village because it has the lowest topography compared to the other two villages. Determination of shelter is carried out by considering the building function, number of floors, building area, building capacity, distance from the coastline, location from the road, and building construction. Public facilities with the number of floors >1 such as flat, trade facilities; religious facilities; educational facilities; government facilities; as well as health facilities in Watulimo District can be used as shelters during tsunami. Based on the analysis, the shelters obtained can accommodate the population in tsunami-prone areas. The evacuation route can be determined by considering the distance, road width, road conditions, road class, and travel time to obtain the fastest route from settlement to the nearest shelter. The evacuation routes that can be used in Watulimo District are the existing roads. However, there is a need for road repairs in damaged/ potholed road conditions, road widening, adding new roads to facilitate the evacuation process of disaster victims to the shelter, and carrying out routine road maintenance on roads that will be used as evacuation routes, so that these roads are always in good condition.

Prevalence of Loneliness and Related Factors Among Older Adults in Taiwan: Evidence From a Nationally Representative Survey

Background Loneliness is a common problem among older populations, and very few studies have examined loneliness among older adults in Taiwan. Aim This study aimed to understand the prevalence of loneliness and factors associated with it among older adults in Taiwan. Methods Data from the Taiwan Longitudinal Study of Aging collected in 2015 were analyzed and involved 4588 participants aged ≥65 years. The outcome variable was a self-reported loneliness question, and independent variables included demographic characteristics, a self-reported health status, physical function, number of comorbidities, cognitive function, and social support. A multivariate logistic regression was used to identify predictors of loneliness. Results The prevalence of loneliness among older adults in Taiwan was 10.5%. The multivariate logistic regression showed that old persons who were male, lived alone, perceived that they had a poor health condition, had no spouse, had no job, and had poor emotional support had higher likelihood of feeling lonely. Conclusions This study investigated loneliness in a nationally representative sample of older adults and revealed that one-tenth of this older population might experience loneliness which requires immediate action. Special attention should be given to the aforesaid factors in older adults to identify problems and provide interventions as early as possible in order to prevent loneliness and thus reduce the resultant negative effects on physical and mental conditions. Appropriate interventions should be developed to prevent or ameliorate feelings of loneliness among older populations using rigorous research designs such as randomized controlled trials.

Morphological Characterization of the Antennal Sensilla of the Afrotropical Sand Fly, Phlebotomus duboscqi (Diptera: Psychodidae)

We investigated by scanning electron microscopy the morphology, distribution, and abundance of antennal sensilla of females Phlebotomus duboscqi sand fly, an important vector of zoonotic cutaneous leishmaniasis at Afrotropical region. Thirteen well-differentiated sensilla were identified, among six types of cuticular sensilla. The probable function of these sensillary types is discussed in relation to their external structure and distribution. Five sensillary types were classified as olfactory sensilla, as they have specific morphological characters of sensilla with this function. Number and distribution of sensilla significantly differed between antennal segments. The results of the present work, besides corroborating in the expansion of the morphological and ultrastructural knowledge of P. duboscqi, can foment future electrophysiological studies for the development of volatile semiochemicals, to be used as attractants in traps for monitoring and selective vector control of this sand fly.

Evaluation of Parameter Settings for Training Neural Networks Using Backpropagation Algorithms

Artificial neural networks (ANN) are widely used for classification, and the training algorithm commonly used is the backpropagation (BP) algorithm. The major bottleneck faced in the backpropagation neural network training is in fixing the appropriate values for network parameters. The network parameters are initial weights, biases, activation function, number of hidden layers and the number of neurons per hidden layer, number of training epochs, learning rate, minimum error, and momentum term for the classification task. The objective of this work is to investigate the performance of 12 different BP algorithms with the impact of variations in network parameter values for the neural network training. The algorithms were evaluated with different training and testing samples taken from the three benchmark clinical datasets, namely, Pima Indian Diabetes (PID), Hepatitis, and Wisconsin Breast Cancer (WBC) dataset obtained from the University of California Irvine (UCI) machine learning repository.

Comparison of Different Techniques to Calculate Properties of Atmospheric Turbulence from Low-Resolution Data

In this work we study different techniques to estimate basic properties of turbulence, that is its characteristic velocity and length scale from low-resolution data. The methods are based on statistics of the signals like the velocity spectra, second-order structure function, number of signal’s zero-crossings and the variance of velocity derivative. First, in depth analysis of estimates from artificial velocity time series is performed. Errors due to finite averaging window, finite cut-off frequencies and different fitting ranges are discussed. Next, real atmospheric measurement data are studied. It is demonstrated that differences between results of the methods can indicate deviations from the Kolmogorov’s theory or the presence of external intermittency, that is the existence of alternating laminar/turbulent flow patches.