Detection and categorization of severe cardiac disorders based solely on pulse interval measurements

Cardiac disorders are common conditions associated with a high mortality rate. Due to their potential for causing serious symptoms, it is desirable to constantly monitor cardiac status using an accessible device such as a smartwatch. While electrocardiograms (ECGs) can make the detailed diagnosis of cardiac disorders, the examination is typically performed only once a year for each individual during health checkups, and it requires expert medical practitioners to make comprehensive judgments. Here we describe a newly developed automated system for alerting individuals about cardiac disorders solely based on pulse interval measurements. For this purpose, we examined two metrics of heart rate variability (HRV) and analyzed 1-day ECG recordings of more than 1,000 subjects in total. We found that a newly introduced metric of local variation was more efficient than conventional HRV metrics for detecting premature contraction, and furthermore, that a suitable combination of the old and new metrics resulted in much superior detectability particularly for atrial fibrillation, which requires more attention. Even with a 1-minute recording of pulse intervals, our new detection system had a diagnostic performance even better than that of the conventional analysis method applied to a 1-day recording.

Analysis of control factors and surface integrity during wire-EDM of Inconel 718 alloy using T-GRA approach

In today’s competitive modern manufacturing sectors, there is a vital need of utter precision and rigorous processing using various manufacturing approaches that directly influences the cost and processing duration of mechanized materials in addition to the consistency of the finished products. Therefore, it’s essential to figure out the required output by adjusting the control factors of any machining techniques which resulted in optimal values of the desired outcome. In this study, machining evaluation and process optimization is carried out on volumetric extraction of material namely material removal rate (MRR), kerf obtained during the machining (KW) and surface roughness (SR) of Inconel 718 superalloy during CNC controlled wire- electrical discharge machining. Four controllable factors- pulse interval, wire speed, pulse duration and peak current are considered to investigate the influence on performance measures. Taguchi's L16 has been used to construct the set of experiments before physical experimental runs and most influencing factors have been evaluated using ANOVA. SEM images and EDXS analysis have been resorted to examine the morphology of Inconel 718. These findings assist in identifying the topography of the machined surface. Further, the optimum integration has been obtained for the best yield and recorded using grey relational analysis integrated with Taguchi’s technique (T-GRA). The unfamiliarity of the work is based on consideration of zinc coated thin wire electrode and Taguchi-Grey combined approach of modelling with four levels of experimental design.

Experimental Investigations On Optimizing Manufacturing Parameters For Electro-Spark Deposition Diamond Wire Saw

The third generation of superhard semiconductor materials, represented by single-crystal SiC, is used widely in microelectronics due to their excellent physical and mechanical properties. However, their high hardness and brittleness become the bottleneck of their development. Diamond wire saw (DWS) has become the mainstream tool for sawing hard and brittle crystal materials. However, the diamond abrasive is consolidated on the core wire through resin or electroplated nickel, and the holding strength is not high. When sawing superhard crystal materials, the efficiency is low. In order to improve the sawing efficiency of superhard crystal materials, it is of great significance to improve the wear resistance of wire saw and the holding strength of abrasive particles. Electro-spark deposition (ESD) can deposit electrode materials on the substrate with low heat input to achieve metallurgical bonding between metal materials. It can effectively improve the gripping strength of the abrasive grains. And the sawing ability of the wire saw to make the consolidated DWS by the ESD process. In this paper, the ESD equipment has been designed according to the characteristics of the ESDDWS process. The discharge gap size and electrode consumption are monitored in real-time by a single-chip microcomputer (SCM). Orthogonal experiments were carried out for the two motion modes. The effects of process parameters, such as (A) Grain size, (B) Abrasive content, (C) Pulse duration time, (D) Compacting pressure, (E) Current, (F) Electrode diameter, (G) Pulse interval time, (H) Reciprocating times, (I) Wire feed speed, on the quality of ESDDWS were analyzed. Through the extremum difference analysis, the optimal parameter combinations of ESDDWS were obtained. The results of the validation experiment are better than the original experimental results.

RESEARCH OF AlO и Al NANOPOWDER FORMATION PROCESSES IN PLASMA UNDER THE INFLUENCE OF DEFOCUSED DUAL LASER PULSES ON ALUMINUM IN THE AIR ATMOSPHERE

Изучено влияние величины и типа расфокусировки сдвоенных лазерных импульсов на целенаправленное формирование компонентного и зарядового состава лазерной плазмы при воздействии сдвоенных лазерных импульсов на мишень из алюминиевого сплава АД1 (спектрометр LSS-1). Показано, что при расфокусировке более +1 мм интенсивность линии ионов Al III увеличивается в несколько раз в сравнении с нулевой расфокусировкой, интенсивность линий ионов Al II, N II также более менее монотонно увеличивается. Одновременно с этим интенсивность полос AlO практически становится равным нулю. При значении величины расфокусировки 1 мм проведены исследование процессов образования смешанных нанопорошков AlO и Al при воздействии последовательных серий сдвоенных лазерных импульсов энергией 53 мДж и меж-импульсным интервалом 10 мкс на алюминиевую мишень, помещенную в закрытую стеклянную прямоугольную кювету. Размер первичных частиц AlOоцененный с помощью электронной микроскопии высокого разрешения, преимущественно составил 30 - 40 нм, а Al - 45 - 60 нм. Частицы собраны в агломераты. The influence of the magnitude and type of defocusing of twin laser pulses on the purposeful formation of the component and charge composition of laser plasma under the influence of twin laser pulses on a target made of aluminum alloy AD1 (LSS-1 spectrometer) has been studied. It is shown that when defocusing is more than 1 mm, the intensity of the ion line Al III increases several times in comparison with zero defocusing, the intensity of the ion lines Al II, N II also increases more or less monotonously. At the same time, the intensity of the bands AlO practically becomes zero. At the 1 mm defocusing value, the processes of formation of mixed nanopowders were studied and, under the influence of successive series of double laser pulses with the energy of 53 mJ and the inter-pulse interval of the iss on an aluminum target placed in a closed rectangular glass cuvette, the size of primary Al Oparticles estimated using high-resolution electron microscopy was mainly 30 - 40 nm, and Al -45 - 60 nm. The particles are collected into agglomerates.

Data Acquisition and Dissemination for the Internet of Nano Things

<p>Electromagnetic-based Wireless NanoSensor Networks (EM-WNSNs) operating in the Terahertz band (0.1 THz – 10 THz) will enable nano-scale applications and stimulate the evolution from the Internet of Things (IoT) to the Internet of Nano Things (IoNT). Data delivery, which is one of the key functionalities of EM-WNSNs, faces three major challenges that will affect network performance: the frequency-selective channel in the THz band due to molecular absorption, the limited ability to support networking functions due to their small size, and the limited bandwidth of the existing infrastructure for transferring sensed data to the Internet. However, to date, limited amount of research on data delivery has been done to address the peculiarities of IoNT from the networking perspective. To fill the gap, in this thesis, data acquisition and dissemination solutions are studied for IoNT to improve the resource utilization efficiency during data delivery. Different from existing literatures that focus on standalone nanonetworks, this thesis investigates solutions for connecting nanodevices to the Internet. In detail, the contributions of this thesis are composed of four components: First, a preliminary study namely the Channel-aware Forwarding (CForward) is conducted on multi-hop forwarding for THz networks; second, the On-demand Probabilistic polling (OP polling) is developed for IoNT with dynamic IoT bandwidth and channel conditions; third, a TTLbased Efficient Forwarding (TEForward) is designed for the polling-based nanonetworks under dynamic channel conditions; fourth, the Enhanced Adaptive Pulse Interval Scheduling (EAPIS) is implemented to collect data from event-based nanonetworks under limited IoT bandwidth.</p>

Data Acquisition and Dissemination for the Internet of Nano Things

<p>Electromagnetic-based Wireless NanoSensor Networks (EM-WNSNs) operating in the Terahertz band (0.1 THz – 10 THz) will enable nano-scale applications and stimulate the evolution from the Internet of Things (IoT) to the Internet of Nano Things (IoNT). Data delivery, which is one of the key functionalities of EM-WNSNs, faces three major challenges that will affect network performance: the frequency-selective channel in the THz band due to molecular absorption, the limited ability to support networking functions due to their small size, and the limited bandwidth of the existing infrastructure for transferring sensed data to the Internet. However, to date, limited amount of research on data delivery has been done to address the peculiarities of IoNT from the networking perspective. To fill the gap, in this thesis, data acquisition and dissemination solutions are studied for IoNT to improve the resource utilization efficiency during data delivery. Different from existing literatures that focus on standalone nanonetworks, this thesis investigates solutions for connecting nanodevices to the Internet. In detail, the contributions of this thesis are composed of four components: First, a preliminary study namely the Channel-aware Forwarding (CForward) is conducted on multi-hop forwarding for THz networks; second, the On-demand Probabilistic polling (OP polling) is developed for IoNT with dynamic IoT bandwidth and channel conditions; third, a TTLbased Efficient Forwarding (TEForward) is designed for the polling-based nanonetworks under dynamic channel conditions; fourth, the Enhanced Adaptive Pulse Interval Scheduling (EAPIS) is implemented to collect data from event-based nanonetworks under limited IoT bandwidth.</p>

The Optimal Performance of the Energy Efficiency of a Pulse Dust Collection System towards Sustainability

A growing number of manufacturers are realizing cost and environmental benefits through the sustainability of innovation and optimization processes. Based on polluting less and creating less, the study is pursuing sustainability on increasing operational efficiency by reducing costs and waste. Pulse dust collection systems are commonly used filtration equipment in industries and have lots of energy consumption due to running all day. This study is focused on the optimal parameters for energy saving and cost reduction, and the model is represented by the pressure drop of the filter and the residual powder. The characteristic values of the cleaning efficiency and the air permeability reduction are used for MATLAB to analyze the optimization state. This study found that the material of filter elements, the type of dust, the conditions of pulse-jet, and the filtering speed are the factors that affect the operational efficiency. In terms of cost, the pulse interval time in 10 s is the best parameter, and the pulse time does not affect the overall cost of the filter. Considering energy saving, 0.1 s of the pulse time is the best parameter. In addition, a lower dust concentration is a way to improve efficiency for increasing the filter life and reducing cost.

Generation and dynamics of soliton and soliton molecules from a VSe2/GO-based fiber laser

Recently, in addition to exploring the application of new saturable absorber devices in fiber lasers, soliton dynamics has also become a focus of current research. In this article, we report an ultrashort pulse fiber laser based on VSe2/GO nanocomposite and verify the formation process of soliton and soliton molecules by the numerical simulation. The prepared VSe2/GO-based device shows excellent saturable absorption characteristics with a modulation depth of 14.3% and a saturation absorption intensity of 0.93 MW/cm2. The conventional soliton is obtained with pulse width of 573 fs, which is currently the narrowest pulse width based on VSe2-related material, and has a signal-to-noise ratio of 60.4 dB. In addition, the soliton molecules are realized based on the VSe2/GO for the first time and have a pulse interval of ∼2.2 ps. We study the soliton dynamics through numerical simulation and reveal that before the formation of the soliton, it undergoes multiple nonlinear stages, such as soliton mode-locking, soliton splitting, and soliton oscillation. Furthermore, the results of numerical simulation are agreed well with the experimental data. These results indicate that the VSe2/GO might be another promising saturable absorber material for ultrafast photonics, and deepen the understanding of soliton dynamics in ultrafast fiber lasers.

Comparison of Gait Speed Reserve, Usual Gait Speed, and Maximum Gait Speed of Adults Aged 50+ in Ireland Using Explainable Machine Learning

Gait speed is a measure of general fitness. Changing from usual (UGS) to maximum (MGS) gait speed requires coordinated action of many body systems. Gait speed reserve (GSR) is defined as MGS–UGS. From a shortlist of 88 features across five categories including sociodemographic, cognitive, and physiological, we aimed to find and compare the sets of predictors that best describe UGS, MGS, and GSR. For this, we leveraged data from 3,925 adults aged 50+ from Wave 3 of The Irish Longitudinal Study on Ageing (TILDA). Features were selected by a histogram gradient boosting regression-based stepwise feature selection pipeline. Each model’s feature importance and input–output relationships were explored using TreeExplainer from the Shapely Additive Explanations explainable machine learning package. The mean Radj2 (SD) from fivefold cross-validation on training data and the Radj2 score on test data were 0.38 (0.04) and 0.41 for UGS, 0.45 (0.04) and 0.46 for MGS, and 0.19 (0.02) and 0.21 for GSR. Each model selected features across all categories. Features common to all models were age, grip strength, chair stands time, mean motor reaction time, and height. Exclusive to UGS and MGS were educational attainment, fear of falling, Montreal cognitive assessment errors, and orthostatic intolerance. Exclusive to MGS and GSR were body mass index (BMI), and number of medications. No features were selected exclusively for UGS and GSR. Features unique to UGS were resting-state pulse interval, Center for Epidemiologic Studies Depression Scale (CESD) depression, sit-to-stand difference in diastolic blood pressure, and left visual acuity. Unique to MGS were standard deviation in sustained attention to response task times, resting-state heart rate, smoking status, total heartbeat power during paced breathing, and visual acuity. Unique to GSR were accuracy proportion in a sound-induced flash illusion test, Mini-mental State Examination errors, and number of cardiovascular conditions. No interactions were present in the GSR model. The four features that overall gave the most impactful interactions in the UGS and MGS models were age, chair stands time, grip strength, and BMI. These findings may help provide new insights into the multisystem predictors of gait speed and gait speed reserve in older adults and support a network physiology approach to their study.

Estimation of Probability Distributions of Geoacoustic Signal Characteristics

The paper presents an estimation of probability distributions of geoacoustic signal characteristics. The studied signals have a pulsed nature. The ones have been recording at the geodynamic test site of the IKIR FEB RAS (Kamchatka Peninsula) for more than 20 years. To estimate the distribution of characteristics, such time intervals were determined in which histograms of the distribution did not change. The following characteristics were chosen for the estimation: maximum amplitude, the position of pulse envelope maximum, duration, filling frequency, and pulse-to-pulse interval. The obtained estimates made it possible to develop an empirical model of the geoacoustic emission signal. The model can help to test new and existing algorithms for the processing and analysis of geoacoustic signals. The paper also shows that the formalization of the selected characteristics makes it possible to search for anomalies, including those associated with seismic events, by the characteristic variations.