Anticipating Daily Intention using On-Wrist Motion Triggered Sensing

Anticipating human intention by observing one's actions has many applications. For instance, picking up a cellphone, then a charger (actions) implies that one wants to charge the cellphone (intention). By anticipating the intention, an intelligent system can guide the user to the closest power outlet. We propose an on-wrist motion triggered sensing system for anticipating daily intentions, where the on-wrist sensors help us to persistently observe one's actions. The core of the system is a novel Recurrent Neural Network (RNN) and Policy Network (PN), where the RNN encodes visual and motion observation to anticipate intention, and the PN parsimoniously triggers the process of visual observation to reduce computation requirement. We jointly trained the whole network using policy gradient and cross-entropy loss. To evaluate, we collect the first daily "intention" dataset consisting of 2379 videos with 34 intentions and 164 unique action sequences. Our method achieves 92.68%, 90.85%, 97.56% accuracy on three users while processing only 29% of the visual observation on average

An Optimal Algorithm for Higher-Order Voronoi Diagrams in the Plane: The Usefulness of Nondeterminism

We present the first optimal randomized algorithm for constructing the order-$k$ Voronoi diagram of $n$ points in two dimensions. The expected running time is $O(n\log n + nk)$, which improves the previous, two-decades-old result of Ramos (SoCG'99) by a $2^{O(\log^*k)}$ factor. To obtain our result, we (i) use a recent decision-tree technique of Chan and Zheng (SODA'22) in combination with Ramos's cutting construction, to reduce the problem to verifying an order-$k$ Voronoi diagram, and (ii) solve the verification problem by a new divide-and-conquer algorithm using planar-graph separators. We also describe a deterministic algorithm for constructing the $k$-level of $n$ lines in two dimensions in $O(n\log n + nk^{1/3})$ time, and constructing the $k$-level of $n$ planes in three dimensions in $O(n\log n + nk^{3/2})$ time. These time bounds (ignoring the $n\log n$ term) match the current best upper bounds on the combinatorial complexity of the $k$-level. Previously, the same time bound in two dimensions was obtained by Chan (1999) but with randomization.Comment: To appear in SODA 2024. 16 pages, 1 figur

Fixed-point theorems in fuzzy real line

AbstractSome sufficient conditions for the existence of fixed points of increasing operators in fuzzy real line RL are given. We also establish some coupled quasi-fixed-point theorems of mixed monotone operators in fuzzy real line RL

Novel biodegradable sandwich-structured nanofibrous drug-eluting membranes for repair of infected wounds: an in vitro and in vivo study

Dave Wei-Chih Chen1,2, Jun-Yi Liao3, Shih-Jung Liu2, Err-Cheng Chan41Department of Orthopedic Surgery, Chang Gung Memorial Hospital, 2Department of Mechanical Engineering, 3Graduate Institute of Medical Mechatronics, 4School of Medical Technology, Chang Gung University, Kwei-San, Tao-Yuan, TaiwanBackground: The purpose of this study was to develop novel sandwich-structured nanofibrous membranes to provide sustained-release delivery of vancomycin, gentamicin, and lidocaine for repair of infected wounds.Methods: To prepare the biodegradable membranes, poly(D, L)-lactide-co-glycolide (PLGA), collagen, and various pharmaceuticals, including vancomycin, gentamicin, and lidocaine, were first dissolved in 1,1,1,3,3,3-hexafluoro-2-propanol. They were electrospun into sandwich-structured membranes with PLGA/collagen as the surface layers and PLGA/drugs as the core. An elution method and a high-pressure liquid chromatography assay were used to characterize in vivo and in vitro drug release from the membranes. In addition, repair of infected wounds in rats was studied. Histological examination of epithelialization and granulation at the wound site was also performed.Results: The biodegradable nanofibrous membranes released large amounts of vancomycin and gentamicin (well above the minimum inhibition concentration) and lidocaine in vivo for more than 3 weeks. A bacterial inhibition test was carried out to determine the relative activity of the antibiotics released. The bioactivity ranged from 40% to 100%. The nanofibrous membranes were functionally active in treating infected wounds, and were very effective as accelerators in early-stage wound healing.Conclusion: Using the electrospinning technique, we will be able to manufacture biodegradable, biomimetic, nanofibrous, extracellular membranes for long-term delivery of various drugs.Keywords: nanofibrous, sandwich-structured, drug-eluting membranes, electrospinning, release characteristics, repair, wound infectio

Dose pre-hospital laryngeal mask airway use has a survival benefit in non-shockable cardiac arrest?

Background. Whether pre-hospital laryngeal mask airway (LMA) use poses a survival benefit and should be approved as routine airway management in non-shockable cardiac arrest is of major concern. The present study examined the effectiveness of LMA, in comparison to other pre-hospital airway management on individuals who have experienced non-shockable cardiac arrest. Methods. Adult patients who experienced non-shockable cardiac arrest with activation of the emergency medical service (EMS) made up our study cohort in Taoyuan, Taiwan. The data were abstracted from EMS records and cardiac arrest registration protocols. Results. Among the 1912 enrolled patients, most received LMA insertion (72.4%), 108 (5.6%) bag-valve-mask (BVM) ventilation, 376 (19.7%) high-flow oxygen non-rebreather facemask, and only 44 (2.3%) received endotracheal tube intubation (ETI). With regard to survival to discharge, no significant differences in prevalence were evident among the groups: 2.8% of oxygen facial mask, 1.1% of BVM, 2.1% of LMA, and 4.5% of the ETI group survived to discharge (p = 0.314). In comparison to oxygen facial mask use, different types of airway management remained unassociated with survival to discharge after adjusting for variables by logistic regression analysis (BVM: 95% confidence interval [CI], 0.079 – 1.639 [p = 0.186]; LMA: 95% CI, 0.220–2.487 [p = 0.627]; ETI: 95% CI, 0.325–17.820 [p = 0.390]). The results of Hosmer-Lemeshow goodness-of-fit test of logistic regression model revealed good calibration. Conclusions. Pre-hospital LMA use was not associated with additional survival to discharge compared with facial oxygen mask, BVM, or ETI following non-shockable cardiac arrest