Alpine Storm

https://digitalcommons.library.umaine.edu/mmb-ps/2545/thumbnail.jp

Phantom midge mandibles in lake sediments as bioindicators of historic fish absence in Minnesota’s shallow lakes

Research Question: Is Chaoborus americanus a useful bioindicator of contemporary and historical fish absence in Minnesota’s shallow lakes? The phantom midge Chaoborus americanus (Diptera: Chaoboridae) is restricted to fishless habitats due to their vulnerability to fish predation (Von Ende, 1979, Schilling et al. 2009). Their chitinous mandibles are preserved in pond sediments, making this species an excellent bioindicator of historical fish absence in water bodies with unknown fish colonization history (Lamontagne and Schindler, 1994; Schilling et al. 2008). Our research is part of a larger project using paleolimnological techniques to understand historical regime shifts (from clear to turbid states) in shallow lakes in the Prairie Pothole Region (PPR) of Minnesota (Hobbs et al. 2016). As part of the larger study, fish and macroinvertebrate communities were sampled and sediment cores were collected from a large set of study lakes in the PPR (Hobbs et al. 2016). We are interested in examining the role that fish colonization/extinction has played in triggering regime shifts in shallow lakes. Our current research objective is to test methods for detecting fish presence/absence developed in Maine (Schilling et al. 2008, 2009) to see if they are applicable to lakes in the PPR.https://idun.augsburg.edu/zyzzogeton/1005/thumbnail.jp

A review of the reproductive habitat preferences and conservation challenges of a rare, transient, and ecologically restricted darner dragonfly: Rhionaeschna mutata

Rhionaeschna mutata is a rare North American dragonfly that is considered a species of concern or threatened throughout its range. It is most widely distributed in the eastern USA, but recent adult records indicate that its range extends further north and west than previously known. Effective conservation planning for rare species requires understanding their habitat requirements, and no comprehensive characterization of this species’ reproductive habitat has previously been conducted. We conducted a review to synthesize information from records throughout this species’ range and identified a narrow set of conditions that describe R. mutata reproductive habitat: small, heavily vegetated, fish-free ponds with a wooded riparian edge and with sphagnum present. While this habitat type may formerly have been widespread across this species’ native range, anthropogenic activities have likely resulted in loss and increased fragmentation of R. mutata reproductive habitat. Our review also revealed that this species is transient or ephemeral, collected at a site one year and absent in subsequent years. Effective conservation planning for ecologically restricted odonates, such as R. mutata, requires consideration of multiple anthropogenic activities that threaten species’ ability to persist

Design and Manual to Construct Rainout-Shelters for Climate Change Experiments in Agroecosystems

Climate change models predict reduced summer precipitations for most European countries, including more frequent and extreme summer droughts. Rainout-shelters which intercept part of the natural precipitation provide an effective tool to investigate effects of different precipitation levels on biodiversity and ecosystem functioning. In this study, we evaluate and describe in detail a fixed-location rainout shelter (2.5×2.5m) with partial interception of natural rainfall. We provide a complete parts list, a construction manual and detailed CAD drawings allowing to rebuild and use these shelters for rainfall manipulation studies. In addition, we describe a rainout-shelter control treatment giving the possibility to quantify and account for potential shelter artifacts. To test the rainout-shelters, we established the following three treatments each in eight winter wheat plots of the agricultural long-term farming system comparison trial DOK in Therwil (Switzerland): (1) A rainout-shelter with 65% interception of rainfall, (2) a rainout-shelter control without interception of rainfall, and (3) an ambient control. The rainout-shelter effectively excluded 64.9% of the ambient rainfall, which is very close to the a priori calculated exclusion of 65.1%. In comparison to the ambient control plots, gravimetric soil moisture decreased under the rainout-shelter by a maximum of 11.1 percentage points. Air temperature under the rainout-shelter differed little from the ambient control (−0.55◦C in 1.2m height and +0.19◦C in 0.1m height), whereas soil temperatures were slightly higher in periods of high ambient temperature (+1.02◦C), but remained basically unaffected in periods of low ambient temperature (+0.14◦C). A maximum edge effect of 0.75m defined a sampling area of 1 × 1m under the rainout-shelter. The rainout-shelters presented here, proved to sustain under heavy weather and they were well-suited to be used in agricultural fields where management operations require the removal of the rainout-shelters for management operations. Overall, the results confirmed the good performance of the presented rainout-shelters regarding rainout-shelter artifacts, predictable rain exclusion, and feasibility for experimental studies in agricultural fields

S4ND: Single-Shot Single-Scale Lung Nodule Detection

The state of the art lung nodule detection studies rely on computationally expensive multi-stage frameworks to detect nodules from CT scans. To address this computational challenge and provide better performance, in this paper we propose S4ND, a new deep learning based method for lung nodule detection. Our approach uses a single feed forward pass of a single network for detection and provides better performance when compared to the current literature. The whole detection pipeline is designed as a single $3D$ Convolutional Neural Network (CNN) with dense connections, trained in an end-to-end manner. S4ND does not require any further post-processing or user guidance to refine detection results. Experimentally, we compared our network with the current state-of-the-art object detection network (SSD) in computer vision as well as the state-of-the-art published method for lung nodule detection (3D DCNN). We used publically available $888$ CT scans from LUNA challenge dataset and showed that the proposed method outperforms the current literature both in terms of efficiency and accuracy by achieving an average FROC-score of $0.897$. We also provide an in-depth analysis of our proposed network to shed light on the unclear paradigms of tiny object detection.Comment: Accepted for publication at MICCAI 2018 (21st International Conference on Medical Image Computing and Computer Assisted Intervention

Accelerating Network Functions using Reconfigurable Hardware. Design and Validation of High Throughput and Low Latency Network Functions at the Access Edge

Providing Internet access to billions of people worldwide is one of the main technical challenges in the current decade. The Internet access edge connects each residential and mobile subscriber to this network and ensures a certain Quality of Service (QoS). However, the implementation of access edge functionality challenges Internet service providers: First, a good QoS must be provided to the subscribers, for example, high throughput and low latency. Second, the quick rollout of new technologies and functionality demands flexible configuration and programming possibilities of the network components; for example, the support of novel, use-case-specific network protocols. The functionality scope of an Internet access edge requires the use of programming concepts, such as Network Functions Virtualization (NFV). The drawback of NFV-based network functions is a significantly lowered resource efficiency due to the execution as software, commonly resulting in a lowered QoS compared to rigid hardware solutions. The usage of programmable hardware accelerators, named NFV offloading, helps to improve the QoS and flexibility of network function implementations. In this thesis, we design network functions on programmable hardware to improve the QoS and flexibility. First, we introduce the host bypassing concept for improved integration of hardware accelerators in computer systems, for example, in 5G radio access networks. This novel concept bypasses the system’s main memory and enables direct connectivity between the accelerator and network interface card. Our evaluations show an improved throughput and significantly lowered latency jitter for the presented approach. Second, we analyze different programmable hardware technologies for hardware-accelerated Internet subscriber handling, including three P4-programmable platforms and FPGAs. Our results demonstrate that all approaches have excellent performance and are suitable for Internet access creation. We present a fully-fledged User Plane Function (UPF) designed upon these concepts and test it in an end-to-end 5G standalone network as part of this contribution. Third, we analyze and demonstrate the usability of Active Queue Management (AQM) algorithms on programmable hardware as an expansion to the access edge. We show the feasibility of the CoDel AQM algorithm and discuss the challenges and constraints to be considered when limited hardware is used. The results show significant improvements in the QoS when the AQM algorithm is deployed on hardware. Last, we focus on network function benchmarking, which is crucial for understanding the behavior of implementations and their optimization, e.g., Internet access creation. For this, we introduce the load generation and measurement framework P4STA, benefiting from flexible software-based load generation and hardware-assisted measuring. Utilizing programmable network switches, we achieve a nanosecond time accuracy while generating test loads up to the available Ethernet link speed

Ecosystem Metabolism in Small Ponds: The Effects of Floating-Leaved Macrophytes

Small ponds constitute a significant number of standing water bodies on earth and may contribute to CO2 uptake or release into the atmosphere. Despite their importance, few studies have examined ecosystem metabolism in ponds, especially in ponds that may be dominated by floating-leaved macrophytes. In this study, we examined ecosystem metabolism by measuring changes in dissolved oxygen levels every 10 min from late May through late October for four shallow ponds (0.5–1.5 m) in east-central Minnesota, USA. Ponds had varying levels of floating-leaved macrophytes from sparse (\u3c1% coverage) to abundant (61% coverage). We found significant dierences in a number of physical/chemical factors including P, N, DOC, water temperature and light penetration. We also found significant dierence in gross primary production (GPP—average ranged from 2.2 to 5.5 mg O2/L/day), respiration (R—average ranged from 6.8 to 3.6 mg O2/L/day) and net ecosystem production (NEP—average ranged from 1.5 to 0.1 mg O2/L/day) among the ponds. On average, all of the ponds were heterotrophic (R \u3e GPP). While it appeared that floating-leaved macrophytes provided a significant impact on ecosystem metabolism, there was not a one-to-one correspondence between the amount of macrophytes and the level of ecosystem metabolism

User Plane Hardware Acceleration in Access Networks: Experiences in Offloading Network Functions in Real 5G Deployments

Fulfilling the ambitious Quality of Service demands of today’s wireless networks, especially low latency, high bandwidths and availability, is a big challenge for researchers, network architects, and operators. Each networking component on the data path between the user equipment and the destination data network, e.g., the Internet, must provide the highest performance to meet these requirements. This work demonstrates how different network elements of the user plane, describing the whole path of user traffic, can be sped up with different hardware acceleration technologies. For that, we demonstrate how to build up a 5G standalone campus network for evaluation, working end-to-end with real user equipment and open-source software components. Further, we analyze the user-plane network functions of 5G networks from the radio access network to the core. Based on our real 5G setup, the practical evaluation of the analysis results shows up how the 5G user-plane hardware can be accelerated best

Network Testing Utilizing Programmable Network Hardware

QoS requirements on modern network hardware, including switches and routers, require the ability to conduct precise measurements of the packet processing and forwarding of network elements. This requires tracing packet processing and detecting the loss of packets with high timing accuracy. Current approaches for network testing rely on special and purpose-built devices, which are costly and inflexible as these devices cannot be reconfigured to include new testing or monitoring functionality. In this article, we demonstrate the power behind novel programmable network switches to enable highly accurate and flexible testing and monitoring of network element functionality before and during deployment. While the cost of such switches is comparable to traditional commodity switches, their processing logic can be programmed to realize specific networking functionality. In the context of P4STA, an open source measurement framework previously presented by us, we show how the programmability of modern network switches helps to perform highly accurate and purpose-independent testing of network elements. In addition, we also highlight its ability to support reconfigurable monitoring tasks within the network after deployment