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Ultrafast electron diffraction imposes stringent constraints on the full 6D brightness of the probe electron beam. The desired normalized emittance, often in the few-nanometer regime and below, renders the beam very sensitive to field aberrations and space charge effects. In this proceeding, we report the correction of normal quadrupole, skew quadrupole, and sextupole aberrations in the MEDUSA ultrafast electron micro-diffraction beamline and measurements of the subsequent emittance. This low emittance is enabled by alkali-antimonide photocathodes driven at the photoemission threshold. We demonstrate that the measured emittance is consistent with that of optimized simulations with these cathodes, indicating that low emittance beams from high quality photocathodes can be preserved and used in practical applications., Proceedings of the 13th International Particle Accelerator Conference, IPAC2022, Bangkok, Thailand

Opioid Use Disorder (OUD) is a multi-faceted, complex ailment affecting many individuals and their families across the globe. Currently, there are multiple interventions used in the treatment of OUD, many of which are designed to reduce cravings for opioids. Cravings for opioids are a strong predictor of relapse in the disorder. However, many of the interventions used in clinical practice have inherent risks including a potential for abuse and diversion. Repetitive Transcranial Magnetic Stimulation (rTMS) is an outpatient procedure that may be effective in reducing cravings for opioids, thereby reducing relapse. Methods: This study employed a randomized, single-blind, experimental design with a control group. Ten rTMS or sham treatments were delivered. The intervention group received active rTMS treatment delivered at 10 Hz, 100% resting motor threshold, 2000 pulses delivered in five seconds per train with a 10-second intra-train pause, delivered once daily, five days per week, Monday through Friday for 10 days (10 total treatments). The control group received a sham treatment where the coil was turned 90 degrees counter-clockwise, and the side of the coil rested on the scalp over the area of the skull corresponding to the motor cortex, so the participant felt the coil making contact. Cravings for opioids were measured at various time points throughout the study, including at baseline, after a single treatment, at various increments throughout the delivery of 10 rTMS treatments, and again 30 days after the final treatment. The Desires for Drug Questionnaire (DDQ) was used to measure cravings for opioids. The DDQ contains 13 items to evaluate cravings in three domains: desire and intention, negative reinforcement, and control. Results: Each of the intervention and control groups had 12 participants who were randomly assigned (n = 24). After a single rTMS treatment, the intervention group showed a significant decrease in the desire domain score (p < .001) and negative reinforcement domain score (p = .01), and a significant increase in the control domain score (p = .01). 30 days after the last rTMS treatment, the intervention group had significant reductions in the desire domain score (p = .042) and negative reinforcement domain score (p = .015), compared to immediately after 10 rTMS treatments. Mixed effect regression revealed reduced cravings for opioids for the intervention group evidenced by a decreased desire domain score (p < .001) and negative reinforcement domain score (p < .001), and increased control domain scores (p = 0.17) over time. However, only the desire domain score revealed a statistically significant reduction in opioid cravings compared to the control group (p < 0.001). Discussion: rTMS may be a useful intervention for clinicians to consider in the treatment of adults with OUD. These findings also contribute to the body of knowledge to help identify the most effective rTMS protocol to be used to reduce opioid cravings. There was a significant reduction in the desire domain of opioid cravings over time with rTMS treatment compared to the control group, but this reduction was not as prominent in the negative reinforcement and control domains of opioid cravings. This suggests that rTMS should be used with other treatment options to address the negative reinforcement and control domains of opioid cravings. This study also included female participants in the study design suggesting the effect of rTMS on opioid cravings in females may be similar to that demonstrated in males.

Wireless Internet Service Provider (WISP) networks are an essential part of providing Internet connectivity in remote and rural areas. Typically operating where large commercial Internet service providers deem it financially unviable to do so, WISPs frequently deal with sparse population densities and financial constraints that inhibit reliable network performance. Venture Networks, a research partner, and a WISP that serves the rural Horowhenua Region, has observed that many WISPs fail to become sustainable businesses, and pondered what could be done to improve outcomes for those providing Internet access where limited other options exist. This research proposes to investigate what commercial opportunities may exist for assisting WISP operators to run their networks in an easier, sustainable manner. To encourage the ubiquitous deployment of high-performance WISP networks, it was recognised that first the unique challenges faced by WISP operators on a wide scale must be understood. A Grounded Theory research methodology was adopted, and a study was conducted to develop an objective understanding of issues commonly encountered by WISP network operators. Interviews were conducted with WISP network operators, digital advocacy organisations, and network engineering consultants. Interview participants came primarily from New Zealand and North America. Of the New Zealand participants, nearly every WISP known to operate within the country was interviewed. Results of the Grounded Theory study helped to isolate a potential Minimum Viable Product (MVP) and formed the basis for product development and commercialisation. It was shown that start-up and established WISPs frequently lack the technical knowledge to design and implement high-performance networks. Unsurprisingly, a WISP operator that does not thoroughly understand their network will struggle to operate it without difficulty. Consequently, it was proposed that developing a platform around the shortcomings in the knowledge that WISP operators have would be appropriate. Given the proposed platform would take form as a physical network appliance, it was decided that initially leveraging a disruptive, solution provider business model would be appropriate. The business model chosen enables Venture Networks to work directly with other WISPs, ideally forming long-term relationships through a customer-centric approach. Venture Networks has several engineering resources devoted to continued development of the proposed MVP, and envisions developing an ecosystem of products to assist WISPs in operating higher-performance, higher-reliability networks. Ongoing testing of the platform is being carried out with Venture Networks, and a small number of other WISPs selected during the interview phase of this research. Feedback from the trials is continuously integrated into revised versions on the platform. Development of the platform has been carried out using the Agile product development methodology, which enables feedback-responsive development and quick-to-release iterations of the platform. Upon final release, it is envisioned that the platform designed will not only enable WISPs to design and implement networks in a straightforward manner, but also offer significant cost-savings over alternative solutions available for sale today. For a prospective WISP operator without strong technical competencies, improving Internet connectivity in a remote or rural area would be a daunting challenge. The proposed MVP seeks to make such a task achievable.

Internet Service Providers need to deploy and maintain many wireless sites in isolated or inaccessible terrain to provide Internet connectivity to rural communities. Addressing failures at such sites can be very expensive, both in identifying the fault, and also in the repair or rectification. Data monitoring can be useful, to spot anomalies and predict a fault (and possibly pre-empt it altogether), or to locate and isolate it quickly once it causes an issue for the network. There might be hundreds of variables to be monitored in principle, but only a few of significance for detecting faults. Here, in a case study involving a Wireless Internet Service Provider (WISP) in a rural area, we first illustrate a bottom-up approach to the identification of variables likely to be of use in an automatic anomaly detector. For the purpose of this study, the detector consists of an autoencoder neural network with weights optimized by machine learning (ML). We then show how the cause of an anomaly can be derived from indirect measurements, and use the model to learn relationships between certain variables.

The provision of rural broadband infrastructure is a challenge for network operators across the globe, irrespective of their size. Wireless Internet Service Providers (WISPs) have shown that the small scale deployment of wireless broadband infrastructure is a viable alternative to relying on cellular network providers for remote coverage. However, out of concern for excessive energy consumption WISPs must often resort to using off-grid renewable energy sources such as solar energy for powering network sites, often resulting in undesirable, low-performance backhaul radios being used between sites. To encourage the development of high-performance, sustainable WISP networks, we present ElasticWISP, a backhaul optimisation architecture. ElasticWISP dynamically controls the configuration of backhaul radios based on bandwidth demands and the network-wide energy consumption of these radios. Through simulations driven by real WISP topology and data traffic, we show that ElasticWISP can offer energy savings of approximately 65% when following our design methodology.