No abstract

Wearable devices for continuous non-invasive monitoring of physiological signals are crucial for preventive care and management of chronic conditions. However, these devices are either sensitive to skin conditions or require external stimuli, such as light or electrical excitation, to penetrate the skin for pulse detection. This often results in large motion artifacts and unsuitability for certain skin conditions. Here we demonstrate a simple fingertip-type device which can detect clear pulse signals under a range of conditions, including fingers covered by opaque substances such as a plaster or nail polish, or fingers immersed in water. The structure of the device consists of a pair of magnets and a magnetic sensor. Both experimental and numerical results show that the detected pulsation signals correspond directly to the vibrations induced by blood circulation with negligible influence from modulated magnetic signature of blood. Therefore, this device could be used in conditions which are challenging for existing pulse detectors and might also have its application extended to blood pressure measurement.

<p style='text-indent:20px;'>This paper studies the problem of scheduling <inline-formula><tex-math id="M1">\begin{document}$ n $\end{document}</tex-math></inline-formula> jobs with equal processing times on <inline-formula><tex-math id="M2">\begin{document}$ m $\end{document}</tex-math></inline-formula> uniform machines to optimize two criteria simultaneously. The main contribution is an <inline-formula><tex-math id="M3">\begin{document}$ O(n\log m+n^3) $\end{document}</tex-math></inline-formula>-time algorithm for two general min-max criteria, improving the previous <inline-formula><tex-math id="M4">\begin{document}$ O(n\log m+n^4) $\end{document}</tex-math></inline-formula> time complexity. For a particular min-sum criterion (total weighted completion time or total tardiness) in combination with a general min-max criterion, <inline-formula><tex-math id="M5">\begin{document}$ O(n\log m+n^3) $\end{document}</tex-math></inline-formula>-time algorithms are also obtained, improving the previous <inline-formula><tex-math id="M6">\begin{document}$ O(n\log m+n^3\log n) $\end{document}</tex-math></inline-formula> time complexity. The algorithms can produce all Pareto optimal points together with the corresponding schedules.</p>