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Background: Temperature variability (TV) is associated with increased mortality risk. However, it is still unknown whether intra-day or inter-day TV has different effects. Objectives: We aimed to assess the association of intra-day TV and inter-day TV with all-cause, cardiovascular, and respiratory mortality. Methods: We collected data on total, cardiovascular, and respiratory mortality and meteorology from 758 locations in 47 countries or regions from 1972 to 2020. We defined inter-day TV as the standard deviation (SD) of daily mean temperatures across the lag interval, and intra-day TV as the average SD of minimum and maximum temperatures on each day. In the first stage, inter-day and intra-day TVs were modelled simultaneously in the quasi-Poisson time-series model for each location. In the second stage, a multi-level analysis was used to pool the location-specific estimates. Results: Overall, the mortality risk due to each interquartile range [IQR] increase was higher for intra-day TV than for inter-day TV. The risk increased by 0.59% (95% confidence interval [CI]: 0.53, 0.65) for all-cause mortality, 0.64% (95% CI: 0.56, 0.73) for cardiovascular mortality, and 0.65% (95% CI: 0.49, 0.80) for respiratory mortality per IQR increase in intra-day TV0–7 (0.9 °C). An IQR increase in inter-day TV0–7 (1.6 °C) was associated with 0.22% (95% CI: 0.18, 0.26) increase in all-cause mortality, 0.44% (95% CI: 0.37, 0.50) increase in cardiovascular mortality, and 0.31% (95% CI: 0.21, 0.41) increase in respiratory mortality. The proportion of all-cause deaths attributable to intra-day TV0–7 and inter-day TV0–7 was 1.45% and 0.35%, respectively. The mortality risks varied by lag interval, climate area, season, and climate type. Conclusions: Our results indicated that intra-day TV may explain the main part of the mortality risk related to TV and suggested that comprehensive evaluations should be proposed in more countries to help protect human health.

Human-machine interfaces for hand gesture recognition across multiple sessions and days of doffing and re-donning while maintaining acceptable recognition accuracy are still challenging. In this paper, a flexible wristband, which was integrated with a highly sensitive capacitive pressure sensing array, was used for inter-day hand gesture recognition. The performance of the entire system was further improved by utilizing a triplet network for deep feature embedding. Seven hand gestures were included into the gesture set, and inter-day experiments which lasted for five consecutive days with three sessions on each day were conducted. Five healthy subjects participated in the experiment. Between each session, the wristband was doffed, and re-donned before the next session. The triplet network achieved an average recognition accuracy of 91.98% across all the sessions of all the subjects, and yielded a higher classification result (p < 0.05) over the convolutional neural network trained with softmax-cross-entropy loss (with an average accuracy of 84.65%). Furthermore, we also found that the capacitive array size had an evident influence on the inter-day classification result. The array with the full size (thirty-two channels) achieved a higher average recognition accuracy over all the down-sampled arrays. This work demonstrated the feasibility of improving the hand gesture recognition performance over days of usage by fabricating a wearable, flexible multi-channel capacitive wristband and implementing the triplet network.

Human-machine interfaces for hand gesture recognition across multiple sessions and days of doffing and re-donning while maintaining acceptable recognition accuracy are still challenging. In this paper, a flexible wristband, which was integrated with a highly sensitive capacitive pressure sensing array, was used for inter-day hand gesture recognition. The performance of the entire system was further improved by utilizing a triplet network for deep feature embedding. Seven hand gestures were included into the gesture set, and inter-day experiments which lasted for five consecutive days with three sessions on each day were conducted. Five healthy subjects participated in the experiment. Between each session, the wristband was doffed, and re-donned before the next session. The triplet network achieved an average recognition accuracy of 91.98% across all the sessions of all the subjects, and yielded a higher classification result (p < 0.05) over the convolutional neural network trained with softmax-cross-entropy loss (with an average accuracy of 84.65%). Furthermore, we also found that the capacitive array size had an evident influence on the inter-day classification result. The array with the full size (thirty-two channels) achieved a higher average recognition accuracy over all the down-sampled arrays. This work demonstrated the feasibility of improving the hand gesture recognition performance over days of usage by fabricating a wearable, flexible multi-channel capacitive wristband and implementing the triplet network. [ABSTRACT FROM AUTHOR]

For infants in the first months of life, breast milk is a complete source of nutrition; however, it can also contain elements that are harmful to the infant. It is therefore critical for infant health to characterize breast milk. The aim of this study was to determine the intra- and inter-day variation of elements in breast milk, for which there is currently limited information, as a pilot study for a larger study. Firstly, we developed a simple and robust analytical method for the determination of multiple elements in breast milk. It was accurate (accuracy ranged from 98% to 107%) for measurement of 26 elements in breast milk by quadrupole inductively coupled plasma-mass spectrometry. Intra- and inter-day variation of elements, protein, and fat in breast milk was determined by analyzing breast milk collected from 11 women at 12 sampling points over three days and calculating intraclass correlation coefficients. Intraclass correlation coefficients showed that while some elements were consistent across time points (e.g., Sr, Ca, and Cu), others showed very high variability (e.g., As, Cd, and Ni). Correlation analyses between elements in breast milk showed strong relationships between those including Fe and Mo, Ca and Sr, and Cd and Fe. [ABSTRACT FROM AUTHOR]

Background: Temperature variability (TV) is associated with increased mortality risk. However, it is still unknown whether intra-day or inter-day TV has different effects., Objectives: We aimed to assess the association of intra-day TV and inter-day TV with all-cause, cardiovascular, and respiratory mortality., Methods: We collected data on total, cardiovascular, and respiratory mortality and meteorology from 758 locations in 47 countries or regions from 1972 to 2020. We defined inter-day TV as the standard deviation (SD) of daily mean temperatures across the lag interval, and intra-day TV as the average SD of minimum and maximum temperatures on each day. In the first stage, inter-day and intra-day TVs were modelled simultaneously in the quasi-Poisson time-series model for each location. In the second stage, a multi-level analysis was used to pool the location-specific estimates., Results: Overall, the mortality risk due to each interquartile range [IQR] increase was higher for intra-day TV than for inter-day TV. The risk increased by 0.59% (95% confidence interval [CI]: 0.53, 0.65) for all-cause mortality, 0.64% (95% CI: 0.56, 0.73) for cardiovascular mortality, and 0.65% (95% CI: 0.49, 0.80) for respiratory mortality per IQR increase in intra-day TV 0-7 (0.9 °C). An IQR increase in inter-day TV 0-7 (1.6 °C) was associated with 0.22% (95% CI: 0.18, 0.26) increase in all-cause mortality, 0.44% (95% CI: 0.37, 0.50) increase in cardiovascular mortality, and 0.31% (95% CI: 0.21, 0.41) increase in respiratory mortality. The proportion of all-cause deaths attributable to intra-day TV 0-7 and inter-day TV 0-7 was 1.45% and 0.35%, respectively. The mortality risks varied by lag interval, climate area, season, and climate type., Conclusions: Our results indicated that intra-day TV may explain the main part of the mortality risk related to TV and suggested that comprehensive evaluations should be proposed in more countries to help protect human health., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

For infants in the first months of life, breast milk is a complete source of nutrition; however, it can also contain elements that are harmful to the infant. It is therefore critical for infant health to characterize breast milk. The aim of this study was to determine the intra- and inter-day variation of elements in breast milk, for which there is currently limited information, as a pilot study for a larger study. Firstly, we developed a simple and robust analytical method for the determination of multiple elements in breast milk. It was accurate (accuracy ranged from 98% to 107%) for measurement of 26 elements in breast milk by quadrupole inductively coupled plasma-mass spectrometry. Intra- and inter-day variation of elements, protein, and fat in breast milk was determined by analyzing breast milk collected from 11 women at 12 sampling points over three days and calculating intraclass correlation coefficients. Intraclass correlation coefficients showed that while some elements were consistent across time points (e.g., Sr, Ca, and Cu), others showed very high variability (e.g., As, Cd, and Ni). Correlation analyses between elements in breast milk showed strong relationships between those including Fe and Mo, Ca and Sr, and Cd and Fe.

A precise, sensitive and quick High Performance Liquid Chromatographic (HPLC) method for the determination of rosuvastatin calcium in bulk and tablet dosage forms has been validated. The chromatographic scheme involved: Sil-20A auto sampler, LC-20A pump, SPD-20A UV/visible detector with separation attained by C18 column at 40°C temperature through a mobile phase of acetonitrile and buffer (50:50) at a flow rate of 1.0ml/min. The method is precise (%RSD for intra-day and inter-day extended between 1.06-1.54% and 0.103-1.78%) and linear (r2=0.9997). Limit of detection and quantification (LOD & LOQ) of the adopted method were 0.78 and 1.56μg/ml. The proposed HPLC method was established to be sensitive, precise and swift that can be proficiently adopted in quality control/quality assurance laboratories for predictable investigation of the bulk and oral solid dosage forms of rosuvastatin calcium. [ABSTRACT FROM AUTHOR]

The aim of this study was to determine the intra-participant variabilities (i.e. intra-day and inter-day reliabilities) in leg and vertical stiffness, as well as related kinematic parameters, during treadmill running using the sine-wave method. Twenty-two healthy men ran on a treadmill at 4.44 m/s, and the flight and contact times were measured with a high-speed video camera. Three 30-s running bouts with 2-min inter-bout rests were performed to examine the intra-day reliability, and single 30-s running bouts on three separate days with 24- to 48-h inter-bout intervals were performed to examine the inter-day reliability. The reliability statistics included repeated-measure analyses of variance, average inter-trial correlations, intra-class correlation coefficients (ICCs), Cronbach's α reliability coefficient, and the coefficient of variation. Both leg and vertical stiffness produced high ICCs within 0.972 and 0.982, respectively, and between 0.922 and 0.873 days, respectively. High values were also observed for all of the reliability coefficients. Similar results were found regarding contact time, flight time, step length, and step rate. It was concluded that the measurements of leg and vertical stiffness, as well as related kinematic parameters, obtained using the sine-wave method during treadmill running at 4.44 m/s, were highly reliable, both within and across days. [ABSTRACT FROM PUBLISHER]