Radio Dynamic Zones (RDZs) enable diverse spectrum-sharing scenarios, including advancing coexistence between active and passive spectrum users. We consider RDZs where radio astronomy coexists with active transmitters and introduce the Adaptive Spectrum Tuning and Reactive Allocation (ASTRA) framework, used by a Zone Management System to manage spectrum access to transmitters. We develop and deploy the first RDZ testbed at a radio astronomy facility, the Hat Creek Radio Observatory, to demonstrate a practical solution for managing interference from active transmitters to radio telescopes in over-the-air experiments. To comprehensively evaluate our approach, we simulate RDZs of varying sizes and demonstrate that ASTRA maintains interference at the radio telescopes below acceptable thresholds while maximizing spectrum access to transmitters in the zone.

Accurate RF propagation modeling in urban environments is crucial for developing high-fidelity digital spectrum twins and optimizing wireless communication systems. This paper introduces OpenGERT, an open-source automated Geometry Extraction tool for Ray Tracing. OpenGERT automates the collection and processing of terrain and building data from multiple sources, including OpenStreetMap, Microsoft Global ML Building Footprints, and USGS terrain elevation data. Leveraging the Blender Python API, the tool creates detailed urban models necessary for high-fidelity ray-tracing simulations specifically designed for NVIDIA Sionna RT. Moreover, we conduct sensitivity analyses to assess the impact of variations in building height, position, and electromagnetic material properties on the accuracy of ray-tracing models. Specifically, we present pairwise dispersion plots of channel statistics-such as path gain, mean excess delay, delay spread, link outage, and Rician K-factor-in response to perturbations to analyze the covariance of different channel statistics. The analyses also explore how the sensitivities of these statistics change as a function of distance from the transmitters. Additionally, we provide visualizations of the variance of the channel statistics within the scene for selected transmitter locations to offer deeper insights. Our study reports results from the Munich and Etoile scenes, each featuring 10 transmitter locations. For each transmitter location, we apply perturbations across five different types, 50 perturbations for each: material, position, height, height and position combined, and all combined. The findings reveal that, assuming the initial material properties of buildings are roughly accurate, minor perturbations in permittivity and conductivity do not significantly alter the channel statistics. In contrast, variations in building height and position have a considerable impact on all the statistics, even with a noise standard deviation of 1 meter for building heights and 0.4 meters for building positions. These results highlight the importance of precise environmental modeling in achieving reliable propagation predictions, which are essential for the deployment of digital spectrum twins and advanced communication networks. Finally, we share the code for geometry extraction and sensitivity analyses at https://github.com/serhatadik/OpenGERT/ to facilitate further experimentation and development.

While various spectrum sharing approaches aim to remedy the spectrum crunch and improve spectral utilization, they typically support only radios that are certified for and physically locked down to a single frequency band and power configuration. This limits their utility and re-usability as they do not support flexible license changes post-production, but there is generally no alternative dynamic technical license enforcement mechanism suitable for more flexible SDRs (Software-Defined Radios). This limits the utility of SDRs: SDR operators must use unlicensed bands, or obtain special permission from the FCC via a manual process. Further, they are subject to fines if they operate outside these bounds and/or interfere with other spectrum users. In response, we present SpectraCert--a dynamic, PKI-based (Public Key Infrastructure) system that enables safe, multi-faceted spectrum sharing while simultaneously enforcing license-holder rights directly within flexible transmitting radios. Entities receive specific frequency transmission rights from government authorities or other Spectrum-Authorized Entities (SAEs) through a spectracert : a certificate that specifies allowed frequencies and all required transmission conditions, such as allowed times, geographic areas, maximum transmit powers, expirations and more. Child spectracerts are derived from other spectracerts and have increasingly limited transmission rights, and trusted modules (TMs) within radios validate spectracert authenticity to ensure the rights defined by each parental spectracert are legal and not revoked. TMs only allow transmission according to validated spectracerts and control radio configurations. Spectracerts can also be used to verify SAE attestations of spectrum interference or occupancy reports. We implement a prototype of the SpectraCert system that automatically revokes or replaces spectracerts across SAE hierarchies when license updates occur, describe an integration with the OpenZMS spectrum management system, and evaluate how SpectraCert uniquely protects license rights while simultaneously allowing for more diverse, accessible spectrum sharing methods.

Radio Dynamic Zones (RDZs) are being explored by the research community as an approach to safely test and evaluate spectrum sharing mechanisms and technologies. There is general consensus in the research community regarding the conceptual architecture of an RDZ. In this paper, we present our work on the Powder-RDZ, a prototype RDZ developed and built on the Powder platform. We present a practical RDZ architecture and explore a number of end-to-end use-cases. We present the design and implementation of OpenZMS, our prototype RDZ Zone Management System, and evaluate it in the Powder platform.

The University of Colorado, Boulder (CU), has been collaborating with the Hat Creek Radio Observatory (HCRO) and UC Berkeley (UCB) to prototype a National Radio Dynamic Zone (NRDZ) which facilitates spectrum sharing between Radio Astronomy (RA), and active users of the electromagnetic spectrum.

Radio Dynamic Zones (RDZs) are being explored by the research community as an approach to safely test and evaluate spectrum sharing mechanisms and technologies. There is general consensus in the research community regarding the conceptual architecture of an RDZ. In this paper, we present our work on the Powder-RDZ, a prototype RDZ developed and built on the POWDER platform. We present a practical RDZ architecture and explore a number of end-to-end use-cases. We present the design and implementation of OPENZMS, our prototype RDZ Zone Management System, and evaluate it in the POWDER platform.

This demonstration will showcase our efforts to develop a radio access network (RAN) slicing mechanism that is controllable via management software in an Open RAN framework. To our knowledge, our work represents the first effort that combines an open source Open RAN framework with an open source mobility stack, provides a top-to-bottom RAN application via the RAN intelligent control (RIC) provided by that framework and illustrates its functionality in a realistic wireless environment. Our software is publicly available and we provide a profile in the POWDER platform to enable others to replicate and build on our work.

Selective activation of dopamine D1 receptors remains a promising pro-cognitive therapeutic strategy awaiting robust clinical investigation. PF-6142 is a key example from a recently disclosed novel series of non-catechol agonists and partial agonists of the dopamine D1/5 receptors (D1R) that exhibit pharmacokinetic (PK) properties suitable for oral delivery. Given their reported potential for functionally biased signaling compared to known catechol-based selective agonists, and the promising rodent PK profile of PF-6142, we utilized relevantin vivoassays in male rodents and male and female non-human primates (NHP) to evaluate the pharmacology of this new series. Studies in rodents showed that PF-6142 increased locomotor activity and prefrontal cortex acetylcholine release, increased time spent in wakefulness, and desynchronized the EEG, like known D1R agonists. D1R selectivity of PF-6142 was supported by lack of effect in D1R knock-out mice and blocked response in the presence of the D1R antagonist SCH-23390. Further, PF-6142 improved performance in rodent models of NMDA receptor antagonist-induced cognitive dysfunction, such as MK-801-disrupted paired-pulse facilitation, and ketamine-disrupted working memory performance in the radial arm maze. Similarly, PF-6142 reversed ketamine-induced deficits in NHP performing the spatial delayed recognition task. Of importance, PF-6142 did not alter the efficacy of risperidone in assays predictive of antipsychotic-like effect in rodents including pre-pulse inhibition and conditioned avoidance responding. These data support the continued development of non-catechol based D1R agonists for the treatment of cognitive impairment associated with brain disorders including schizophrenia.

Given the highly empirical nature of research in cloud computing, networked systems, and related fields, testbeds play an important role in the research ecosystem. In this paper, we cover one such facility, CloudLab, which supports systems research by providing raw access to programmable hardware, enabling research at large scales, and creating a shared platform for repeatable research. We present our experiences designing CloudLab and operating it for four years, serving nearly 4,000 users who have run over 79,000 experiments on 2,250 servers, switches, and other pieces of datacenter equipment. From this experience, we draw lessons organized around two themes. The first set comes from analysis of data regarding the use of CloudLab: how users interact with it, what they use it for, and the implications for facility design and operation. Our second set of lessons comes from looking at the ways that algorithms used "under the hood," such as resource allocation, have importantand sometimes unexpected-effects on user experience and behavior. These lessons can be of value to the designers and operators of IaaS facilities in general, systems testbeds in particular, and users who have a stake in understanding how these systems are built.

Kernel-resident malware remains a significant threat. An effective way to detect such malware is to examine the kernel memory of many similar (virtual) machines, as one might find in an enterprise network or cloud, in search of anomalies: i.e., the relatively rare infected hosts within a large population of healthy hosts. It is challenging, however, to compare the kernel memories of different hosts against each other. Previous work has relied on knowledge of specific kernels-e.g., the locations of important variables and the layouts of key data structures-to cross the "semantic gap" and allow kernels to be compared. As a result, those previous systems work only with the kernels they were built for, and they make assumptions about the malware being searched for. We present a new approach to detecting kernel-resident malware within a "herd" of similar virtual machines. Our approach uses limited knowledge of the kernels under examination-e.g., the location of the page global directory and the processor's instruction set-to concisely fingerprint each kernel. It uses no kernel-specific semantics to compare the fingerprints and find those that represent anomalous hosts. We implement our method in a tool called Fluorescence and demonstrate its ability to identify Linux and Windows hosts infected with real-world, kernel-resident malware. Fluorescence can examine a herd of 200 virtual machines with Linux guests in about an hour.

Rice in Myanmar is grown in diverse environments, including inland dry zone and salt-affected coastal deltas. This study evaluated management options that could improve productivity and reduce risks of rice crop in stressprone areas of the country. We selected four sites from two regions in the central dry zone (Wundwin) and the Ayeyarwady delta (Labutta, Bogale and Mawlamyinegyun). We used experimental and survey datasets on farmers' practices and rice yields from 2012 to 2014 to run the ORYZA model to simulate the climatic yield potential (YP; yield without stress) and the attainable yield under rainfed conditions (YW; yield limited by water), saline conditions (YS; yield limited by salinity), and under conditions of current farmers' practices (YF; yield in farmers' practices). Simulated yield responses to different management practices showed spatial variability within and among the selected sites. YP ranged from 5.4 to 11.1 t ha(-1), YW ranged from 0.5 to 7.5 t ha(-1 ) and YF ranged from 2.2 to 4.2 t ha(-1). In salt-affected areas, average YS ranged from less than 0.1 t ha(-1) to 5.6 t ha(-1). Yield gains with the choice of an improved variety and adjusted sowing date were estimated at up to 53% above YF. Changing the time of sowing and using improved rice varieties provided the greatest yield gains in salt-affected and drought-prone areas where YF was the least. In areas where YF was greater, the improvement of nitrogen management provided larger benefits than in areas with lower YF. We conclude that an integrated approach using remote-sensing technologies, crop modeling, and a geographic information system is valuable for targeting the best management options to close the yield gap in unfavorable rice environments in Asia.

The sustainability of agroecosystems in Asia is threatened by the impacts of climate change and decreasing rural population. This study sought to identify promising approaches to technology dissemination for smallholder farmers in unfavorable rice environments. We compared farmer-participatory methods for the dissemination of new stress-tolerant rice cultivars in drought-prone areas in the Philippines from 2016 to 2018. The study, involving 10,176 farmers, compared on-farm demonstration-cum-participatory varietal selection, farmer field schools, farmer-to-farmer extension through local farmer technicians, seed systems enhancement, and seed caravans. Responses were recorded from 386 farmers in a random sample to determine which approach best reflected their opinion on dissemination pathways. Socio-demographic characteristics influencing the farmers' preferences for dissemination pathways were also assessed. Overall, technology demonstration was the preferred pathway, followed by farmer field schools and the farmer-to-farmer extension. Women favored farmer-to-farmer extension more than men did. Membership of a farmer association enhanced preference for farmer-to-farmer extension and seed caravans. These results can be used to guide the choice of appropriate pathways for the dissemination of new rice cultivars depending on the socio-demographic characteristics of the target farming communities.

Researchers conduct experiments in a variety of computing environments, including dedicated testbeds and commercial clouds, and they need convenient mechanisms for deploying their software within these disparate platforms. To address this need, we have extended Emulab so that it can instantiate and configure container-based virtual devices using Docker images. Docker is a de facto standard for packaging and deploying software in cloud environments; now, researchers can use Docker to package and deploy software within Emulab-based testbeds as well. We describe how Emulab incorporates Docker and how it extends Docker images to support the interactivity that researchers expect within a testbed. We show that Emulab can use many popular Docker images to create testbed experiments. We expect that Emulab’s support for Docker will make it easier for researchers to move their activities freely, both into the testbed and out into production.

Clouds, HPC clusters, HTC systems, and testbeds all serve different parts of the computing ecosystem: each are designed for different types of workloads and suited to different types of research and commercial users. We propose that an effective way to share resources among these diverse applications is to not shoehorn them all into the same resource management framework, but to partition a common hardware substrate among different frameworks: for example, to have part of a cluster managed by a cloud framework such as OpenStack, part of it managed by an HPC scheduler such as SLURM, etc. In order to efficiently manage such a shared resource, it must be possible to adjust the set of resources controlled by each in an elastic manner. While resource allocation and scheduling within each of these types of environments are well studied, what we consider in this paper is elasticity between them. Our goal is to enable each management framework to separately manage the resources currently within its own domain, scheduling jobs, VMs, etc. according to its own needs and policies. At the same time, the frameworks can coordinate with one another so that when resources must be moved between them, it can be done in the most fair and efficient manner possible. We evaluate our ideas using a prototype that shares resources between a testbed and an HPC cluster, and with simulations using real workload traces. We find that with only minimal information flow it is possible to elastically adjust resource assignments while each framework optimizes for its own internal criteria.

Higher education has the opportunity (and often the mandate) to provide STEM outreach to their communities. Summer camp programs are one mechanism for providing quality CS learning experiences to a wide audience. This BOF will provide a platform for discussing strategies to make summer camps fun and sustainable. What are camp topics have been successful? How is funding obtained and sustained? Nationally, technology camps run the gamut from small, one-week programs to large camps that serve hundreds. The proposer will share his experience developing the University of Utah GREAT camps (www.cs.utah.edu/~dejohnso/GREAT), which have over 700 students attend one-week camps and hopes the BOF will attract others with their own experiences.

In this paper, we describe ITCH, an automatic testing system for projects in the Scratch programming language. While Scratch lacks traditional input/output mechanisms, ITCH overcomes this by exploiting the persistent saved project state to embed ITCH-specific lists that retain project output. In addition, the ITCH system replaces Scratch user input commands with automatically assigned test values. ITCH can gather variable state from running code, redirect output to a file, and capture drawings done by a Scratch project to save in a report format. The ITCH system has been successfully used in a large computer science explorations class where small practice code questions are assigned before extending work to larger, more creative projects without further burdening course graders. Examples of course projects and the ITCH-tested practice questions are given.

Escherichia coli is the leading cause of urinary tract infections (UTIs), one of the most common infections in humans. P fimbria was arguably the first proposed virulence factor for uropathogenic E. coli, based on the capacity of E. coli isolated from UTIs to adhere to exfoliated epithelial cells in higher numbers than fecal strains of E. coli. Overwhelming epidemiologic evidence has been presented for involvement of P fimbriae in colonization. It has been difficult, however, to demonstrate this requirement for uropathogenic strains in animal models of infections or in humans. In this study, a signature-tagged mutagenesis screen identified a P-fimbrial gene (papC) and 18 other genes as being among those required for full fitness of cystitis isolate E. coli F11. A P-fimbrial mutant was outcompeted by the wild-type strain in cochallenge in the murine model of ascending UTI, and this colonization defect could be complemented with the cloned pap operon. To our knowledge, this study is the first to fulfill molecular Koch's postulates in which a pathogenic strain was attenuated by mutation of pap genes and then complemented to restore fitness, confirming P fimbria as a virulence factor in a pathogenic clinical isolate.

Kynurenic acid (KYNA) is a tryptophan metabolite that acts in the brain as an endogenous antagonist at multiple receptors, including glutamate and α7 nicotinic acetylcholine receptors. Increased levels of KYNA have been demonstrated in the brain of patients with a range of neurocognitive disorders, including schizophrenia, and are hypothesized to contribute to cognitive symptoms. Reducing KYNA levels by administering inhibitors of enzymes of the kynurenine pathway, particularly kynurenine aminotransferase II (KAT II), has been proposed as a treatment for such cognitive impairments. Here we report that administration of a systemically available KAT II inhibitor, PF-04859989, restores glutamate release events (“transients”) evoked by pressure ejections of nicotine into the prefrontal cortex of rats exhibiting elevated KYNA levels. Nicotine-evoked glutamatergic transients can be reliably evoked and recorded after repeated pressure ejections of nicotine over 4–5 h. Systemic administration of l-kynurenine (100 mg/kg; i.p.) significantly increased frontal cortical KYNA levels and greatly attenuated the amplitude of nicotine-evoked glutamatergic transients. Systemic administration of PF-04859989 30 min prior to administration of l-kynurenine, but not when administered 30 min after l-kynurenine, restored glutamatergic transients recorded up to 75 min after the administration of the KAT II inhibitor. Furthermore, the KAT II inhibitor significantly reversed l-kynurenine-induced elevations of brain KYNA levels. The KAT II inhibitor did not affect nicotine-evoked glutamatergic transients in rats not pre-treated with l-kynurenine. Because PF-04859989 restores evoked glutamate signaling it therefore is a promising therapeutic compound for benefiting the cognitive symptoms of schizophrenia and other disorders associated with elevated brain KYNA levels.

Crop productivity is largely affected by abiotic factors such as flooding and by biotic factors such as weeds. Although flooding after direct seeding of rice helps suppress weeds, it also can adversely affects germination and growth of rice, resulting in poor crop establishment. Barnyard grasses (Echinochloa spp.) are among the most widespread weeds affecting rice, especially under direct seeding. The present work aimed to establish effective management options to control these weeds. We assessed the effects of variable depths and time of submergence on germination, seedling growth and carbohydrate metabolism of (i) two cultivars of rice known to differ in their tolerance to flooding during germination and (ii) two barnyard grasses (Echinochloa colona and E. crus-galli) that commonly infest rice fields. Flooding barnyard grasses with 100-mm-deep water immediately after seeding was effective in suppressing germination and growth. Echinochloa colona showed greater reductions in emergence, shoot and root growth than E. crus-galli. Delaying flooding for 2 or 4 days was less injurious to both species. Echinochloa colona was also more susceptible to flooding than the flood-sensitive rice cultivar 'IR42'. The activity of alcohol dehydrogenase (ADH) and pyruvate decarboxylase (PDC) in rice seedlings was increased by flooding after sowing but with greater increases in 'Khao Hlan On' compared with 'IR42'. The activity of ADH and PDC was enhanced to a similar extent in both barnyard grasses. Under aerobic conditions, the activity of ADH and PDC in the two barnyard grasses was downregulated, which might contribute to their inherently faster growth compared with rice. Aldehyde dehydrogenase activity was significantly enhanced in flood-tolerant 'Khao Hlan On' and E. crus-galli, but did not increase in flood-sensitive E. colona and 'IR42', implying a greater ability of the flood-tolerant types to detoxify acetaldehyde generated during anaerobic fermentation. Confirmation of this hypothesis is now being sought.