Pulse oximetry has revolutionized the ability to monitor oxygenation in a continuous, accurate, and non-invasive fashion. Despite its ubiquitous use, it is our impression and supported by studies that many providers do not know the basic principles behind its mechanism of function. This knowledge is important because it provides the conceptual basis of appreciating its limitations and recognizing when pulse oximeter readings may be erroneous. In this review, we discuss how pulse oximeters are able to distinguish oxygenated hemoglobin from deoxygenated hemoglobin and how they are able to recognize oxygen saturation only from the arterial compartment of blood. Based on these principles, we discuss the various conditions that can cause spurious readings and the mechanisms underlying them.

SLICED PROGRAMMABLE NETWORKSOpenFlow [4] has been demonstrated as a way for researchers to run networking experiments in their production network. Last year, we demonstrated how an OpenFlow controller running on NOX [3] could move VMs seamlessly around an OpenFlow network [1]. While OpenFlow has potential [2] to open control of the network, only one researcher can innovate on the network at a time. What is required is a way to divide, or slice, network resources so that researchers and network administrators can use them in parallel. Network slicing implies that actions in one slice do not negatively affect other slices, even if they share the same underlying physical hardware. A common network slicing technique is VLANs. With VLANs, the administrator partitions the network by switch port and all traffic is mapped to a VLAN by input port or explicit tag. This coarse-grained type of network slicing complicates more interesting experiments such as IP mobility or wireless handover.Here, we demonstrate FlowVisor, a special purpose OpenFlow controller that allows multiple researchers to run experiments safely and independently on the same production OpenFlow network. To motivate FlowVisor's flexibility, we demonstrate four network slices running in parallel: one slice for the production network and three slices running experimental code (Figure 1). Our demonstration runs on real network hardware deployed on our production network 1 at Stanford and a wide-area test-bed with a mix of wired and wireless technologies.

In the past couple of years we've seen quite a change in the wireless industry: Handsets have become mobile computers running user-contributed applications on (potentially) open operating systems. It seems we are on a path towards a more open ecosystem; one that has been previously closed and proprietary. The biggest winners are the users, who will have more choice among competing, innovative ideas.The same cannot be said for the wireless network infrastructure, which remains closed and (mostly) proprietary, and where innovation is bogged down by a glacial standards process. Yet as users, we are surrounded by abundant wireless capacity and multiple wireless networks (WiFi and cellular), with most of the capacity off-limits to us. It seems industry has little incentive to change, preferring to hold onto control as long as possible, keeping an inefficient and closed system in place.This paper is a "call to arms" to the research community to help move the network forward on a path to greater openness. We envision a world in which users can move freely between any wireless infrastructure, while providing payment to infrastructure owners, encouraging continued investment. We think the best path to get there is to separate the network service from the underlying physical infrastructure, and allow rapid innovation of network services, contributed by researchers, network operators, equipment vendors and third party developers.We propose to build and deploy an open-but backward compatible-wireless network infrastructure that can be easily deployed on college campuses worldwide. Through virtualization, we allow researchers to experiment with new network services directly in their production network.

Opinion Statement Treatment of non-tuberculous mycobacterial lung disease (NTM-LD) is challenging for several reasons including the relative resistance of NTM to currently available drugs and the difficulty in tolerating prolonged treatment with multiple drugs. Yet-to-be-done, large, multicenter, prospective randomized studies to establish the best regimens will also be arduous because multiple NTM species are known to cause human lung disease, differences in virulence and response to treatment between different species and strains within a species will make randomization more difficult, the need to distinguish relapse from a new infection, and the difficulty in adhering to the prescribed treatment due to intolerance, toxicity, and/or drug-drug interactions, often necessitating modification of therapeutic regimens. Furthermore, the out-of-state resident status of many patients seen at the relatively few centers that care for large number of NTM-LD patients pose logistical issues in monitoring response to treatment. Thus, current treatment regimens for NTM-LD is largely based on small case series, retrospective analyses, and guidelines based on expert opinions. It has been nearly 10 years since the publication of a consensus guideline for the treatment of NTM-LD. This review is a summary of the available evidence on the treatment of the major NTM-LD until more definitive studies and guidelines become available.

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Implantable functional electrical stimulation (IFES) has demonstrated its effectiveness as an alternative treatment option for diseases incurable pharmaceutically (e.g., retinal prosthesis, cochlear implant, spinal cord implant for pain relief). However, the development of IFES for gastrointestinal (GI) tract modulation is still limited due to the poorly understood GI neural network (gut–brain axis) and the fundamental difference among activating/monitoring smooth muscles, skeletal muscles and neurons. This inevitably imposes different design specifications for GI implants. This paper thus addresses the design requirements for an implant to treat GI dysmotility and presents a miniaturized wireless implant capable of modulating and recording GI motility. This implant incorporates a custom-made system-on-a-chip (SoC) and a heterogeneous system-in-a-package (SiP) for device miniaturization and integration. An in vivo experiment using both rodent and porcine models is further conducted to validate the effectiveness of the implant.

We present OpenRoads, an open-source platform for innovation in mobile networks. OpenRoads enable researchers to innovate using their own production networks, through providing an wireless extension OpenFlow. Therefore, you can think of OpenRoads as "OpenFlow Wireless".The OpenRoads' architecture consists of three layers: flow, slicing and controller. These layers provide flexible control, virtualization and high-level abstraction. This allows researchers to implement wildly different algorithms and run them concurrently in one network. OpenRoads also incorporates multiple wireless technologies, specifically WiFi and WiMAX. We have deployed OpenRoads, and used it as our production network. Our goal here is for those to deploy OpenRoads and build their own experiments on it.