A 3D-printed microfluidic-enabled hollow microneedle architecture for transdermal drug delivery.

Embedding microfluidic architectures with microneedles enables fluid management capabilities that present new degrees of freedom for transdermal drug delivery. To this end, fabrication schemes that can simultaneously create and integrate complex millimeter/centimeter-long microfluidic structures and micrometer-scale microneedle features are necessary. Accordingly, three-dimensional (3D) printing techniques are suitable candidates because they allow the rapid realization of customizable yet intricate microfluidic and microneedle features. However, previously reported 3D-printing approaches utilized costly instrumentation that lacked the desired versatility to print both features in a single step and the throughput to render components within distinct length-scales. Here, for the first time in literature, we devise a fabrication scheme to create hollow microneedles interfaced with microfluidic structures in a single step. Our method utilizes stereolithography 3D-printing and pushes its boundaries (achieving print resolutions below the full width half maximum laser spot size resolution) to create complex architectures with lower cost and higher print speed and throughput than previously reported methods. To demonstrate a potential application, a microfluidic-enabled microneedle architecture was printed to render hydrodynamic mixing and transdermal drug delivery within a single device. The presented architectures can be adopted in future biomedical devices to facilitate new modes of operations for transdermal drug delivery applications such as combinational therapy for preclinical testing of biologic treatments

Event-based pedestrian detection using dynamic vision sensors

Pedestrian detection has attracted great research attention in video surveillance, traffic statistics, and especially in autonomous driving. To date, almost all pedestrian detection solutions are derived from conventional framed-based image sensors with limited reaction speed and high data redundancy. Dynamic vision sensor (DVS), which is inspired by biological retinas, efficiently captures the visual information with sparse, asynchronous events rather than dense, synchronous frames. It can eliminate redundant data transmission and avoid motion blur or data leakage in high-speed imaging applications. However, it is usually impractical to directly apply the event streams to conventional object detection algorithms. For this issue, we first propose a novel event-to-frame conversion method by integrating the inherent characteristics of events more efficiently. Moreover, we design an improved feature extraction network that can reuse intermediate features to further reduce the computational effort. We evaluate the performance of our proposed method on a custom dataset containing multiple real-world pedestrian scenes. The results indicate that our proposed method raised its pedestrian detection accuracy by about 5.6–10.8%, and its detection speed is nearly 20% faster than previously reported methods. Furthermore, it can achieve a processing speed of about 26 FPS and an AP of 87.43% when implanted on a single CPU so that it fully meets the requirement of real-time detection

Multidimensional context awareness in mobile devices

Ministry of Education, Singapore under its Academic Research Funding Tier

The Dynamics of Disorder-Order Transition in Hard Sphere Colloidal Dispersions

The Physics of Hard Spheres Experiment (PHaSE) seeks a complete understanding of the entropically driven disorder-order transition in hard sphere colloidal dispersions. The light scattering instrument designed for flight collects Bragg and low angle light scattering in the forward direction via a CCD camera and performs conventional static and dynamic light scattering at 10-160 deg. through fiber optic cables. Here we report on the kinetics of nucleation and growth extracted from time-resolved Bragg images and measurements of the elastic modulus of crystalline phases obtained by monitoring resonant responses to sinusoidal forcing through dynamic light scattering. Preliminary analysis of the former indicates a significant difference from measurements on the ground, while the latter confirms nicely laboratory experiments with the same instrument and predictions from computer simulations

Biodegradable double-network GelMA-ACNM hydrogel microneedles for transdermal drug delivery

As a minimally invasive drug delivery platform, microneedles (MNs) overcome many drawbacks of the conventional transdermal drug delivery systems, therefore are favorable in biomedical applications. Microneedles with a combined burst and sustained release profile and maintained therapeutic molecular bioactivity could further broaden its applications as therapeutics. Here, we developed a double-network microneedles (DN MNs) based on gelatin methacrylate and acellular neural matrix (GelMA-ACNM). ACNM could function as an early drug release matrix, whereas the addition of GelMA facilitates sustained drug release. In particular, the double-network microneedles comprising GelMA-ACNM hydrogel has distinctive biological features in maintaining drug activity to meet the needs of application in treating different diseases. In this study, we prepared the double-network microneedles and evaluated its morphology, mechanical properties, drug release properties and biocompatibility, which shows great potential for delivery of therapeutic molecules that needs different release profiles in transdermal treatment

Study on the Construction of 3D Geological Model of Quaternary Loose Sedimentary Strata Based on the Global Stratigraphic Discrete Points

Accurately depicting the spatial structure characteristics of Quaternary loose sedimentary strata is not only of great significance for the research of Quaternary geological evolution, but also for the analysis of spatial variation characteristics of the inner hydrogeological and engineering geological attributes of the strata. In this study, an approach for constructing a 3D geological model of Quaternary loose sedimentary strata is proposed based on global stratigraphical discrete points. The approach obtains the discrete control point set of each stratum by using limited borehole data for interpolation and encryption, and the contact relationships and intersection modes of adjacent strata can be determined via the analysis of stratigraphic sequence; finally, taking these as the professional basis, the construction of the 3D geological model of Quaternary loose sedimentary strata can be carried out. This application can not only accurately describe the three-dimensional spatial distribution characteristics of the Quaternary loose sedimentary strata, it can also be used to perform a layered simulation of the spatial variation characteristics of the inner geological properties of the Quaternary loose sedimentary strata, such as lithology, porosity, and water content, by taking the three-dimensional spatial framework of each stratum as the simulation boundary. Finally, this study takes the citizen center of Xiong’an new area as an example in order to verify the reliability and advancement of the 3D geological modeling scheme

Computation Avlastning och uppgift Schemaläggning bland Multi-Robot Systems

that some goals that are impossible for a single robot to achieve become feasible and attainable. Developing rapidly and exploited widely, cloud further extends the resources a robot can access thereby bringing significant potential benefits to robotic and automation systems. One of the potential benefits is Computation Offloading that moves the computational heavily parts of an application onto a server to reduce the execution time. However, to enable the computation offloading, the question must be answered when, what, where and how to offload? While some offloading mechanisms proposed in the mobile computing area (i.e., smartphones, pads), the question remains not fully answered and many new challenges emerge when it comes to the robotic realm. This paper aims to apply computation offloading technology to a Multi-Robot System and investigate the performance impact it has on the processing time of robot applications. For this purpose, a computation offloading framework is proposed for an elastic computing model with the engagement of a two-tier cloud infrastructure, i.e., a public cloud infrastructure and an ad-hoc local network (fog) formed by a cluster of robots. Two scheduling algorithms: Heterogeneous-Earliest-Finish-Time (HEFT) and Critical-Path-on-a-Processor (CPOP) are implemented to schedule the offloaded tasks to available robots and servers such that the total execution time of the application is minimized. The offloading framework is implemented based on Robot Operating System (ROS) and tested through simulated applications. The results prove the feasibility of proposed offloading framework and indicate potential execution speeding up of robot applications by exploiting offloading technology.I ett Multi-Robot System (MRS) samarbetar flertalet robotar för att utföra uppgifter som en ensam robot inte klarar av. På grund av molnets hastiga utveckling och vida exploatering kan det utöka resurserna en robot kan få tillgång till och innebär därmed potentiella fördelar för robotik- och automatiseringssystem. En av dessa potentiella fördelar är beräkningsavlastning (computation offloading) som innebär att de beräkningstunga delarna av en applikation utförs på en server för att minska exekveringstiden. För att möjliggöra beräkningsavlastning måste man dock först svara på när, vad, vart, och hur man skall avlasta? Trots att vissa avlastnings-mekanismer har föreslagits inom området av mobil beräkning (dvs smartphones, pads), förblir dessa frågor till en stor del obesvarade och många nya utmaningar är troliga att uppstå inom världen av robotik. Denna rapport ämnar applicera beräkningsavlastning på ett Multi-Robotsystem och undersöka dess effekt på prestandan (beräkningstid) för robotapplikationer. Till detta ändamål så föreslås ett avlastnings-ramverk för en elastisk beräkningsmodell med en molnstruktur utgjord av två lager: en allmän infrastruktur och en ad-hoc baserat lokalt nätverk (fog) uppbyggt av ett kluster av robotar. Två schemaläggnings algoritmer: Heterogeneous-Earlist-Finish-Time (HEFT) och Critical-Path-on-a-Processor (CPOP) är implementerade för att schemalägga de avlastade uppgifterna åt tillgängliga robotar och servrar så att applikationens totala exekveringstid är minimerad. Avlastnings-ramverket är implementerat baserat på Robot Operating System (ROS) och testat med hjälp av simulerade applikationer. Resultaten demonstrerar genomförbarheten av det föreslagna avlastnings-ramverket och att utnyttjandet av avlastningsteknik innebär en potentiellt snabbare exekvering för robotapplikationer

Computation Offloading and Task Scheduling among Multi-Robot Systems

In a Multi-Robot System (MRS), robots perform some collaborative behaviors so that some goals that are impossible for a single robot to achieve become feasible and attainable. Developing rapidly and exploited widely, cloud further extends the resources a robot can access thereby bringing significant potential benefits to robotic and automation systems. One of the potential benefits is Computation Offloading that moves the computational heavily parts of an application onto a server to reduce the execution time. However, to enable the computation offloading, the question must be answered when, what, where and how to offload? While some offloading mechanisms proposed in the mobile computing area (i.e., smartphones, pads), the question remains not fully answered and many new challenges emerge when it comes to the robotic realm. This paper aims to apply computation offloading technology to a Multi-Robot System and investigate the performance impact it has on the processing time of robot applications. For this purpose, a computation offloading framework is proposed for an elastic computing model with the engagement of a two-tier cloud infrastructure, i.e., a public cloud infrastructure and an ad-hoc local network (fog) formed by a cluster of robots. Two scheduling algorithms: Heterogeneous-Earliest-Finish-Time (HEFT) and Critical-Path-on-a-Processor (CPOP) are implemented to schedule the offloaded tasks to available robots and servers such that the total execution time of the application is minimized. The offloading framework is implemented based on Robot Operating System (ROS) and tested through simulated applications. The results prove the feasibility of proposed offloading framework and indicate potential execution speeding up of robot applications by exploiting offloading technology.I ett Multi-Robot System (MRS) samarbetar flertalet robotar för att utföra uppgifter som en ensam robot inte klarar av. På grund av molnets hastiga utveckling och vida exploatering kan det utöka resurserna en robot kan få tillgång till och innebär därmed potentiella fördelar för robotik- och automatiseringssystem. En av dessa potentiella fördelar är beräkningsavlastning (computation offloading) som innebär att de beräkningstunga delarna av en applikation utförs på en server för att minska exekveringstiden. För att möjliggöra beräkningsavlastning måste man dock först svara på när, vad, vart, och hur man skall avlasta? Trots att vissa avlastnings-mekanismer har föreslagits inom området av mobil beräkning (dvs smartphones, pads), förblir dessa frågor till en stor del obesvarade och många nya utmaningar är troliga att uppstå inom världen av robotik. Denna rapport ämnar applicera beräkningsavlastning på ett Multi-Robotsystem och undersöka dess effekt på prestandan (beräkningstid) för robotapplikationer. Till detta ändamål så föreslås ett avlastnings-ramverk för en elastisk beräkningsmodell med en molnstruktur utgjord av två lager: en allmän infrastruktur och en ad-hoc baserat lokalt nätverk (fog) uppbyggt av ett kluster av robotar. Två schemaläggnings algoritmer: Heterogeneous-Earlist-Finish-Time (HEFT) och CriticalPath-on-a-Processor (CPOP) är implementerade för att schemalägga de avlastade uppgifterna åt tillgängliga robotar och servrar så att applikationens totala exekveringstid är minimerad. Avlastnings-ramverket är implementerat baserat på Robot Operating System (ROS) och testat med hjälp av simulerade applikationer. Resultaten demonstrerar genomförbarheten av det föreslagna avlastnings-ramverket och att utnyttjandet av avlastningsteknik innebär en potentiellt snabbare exekvering för robotapplikationer