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Interacting torsions are examined within a two-dimensional monolayer crystal suspended in an argon complex plasma for 1–10 W discharge powers and pressures of 135–155 mTorr. Two torsions embedded in a lattice are shown to amplify the kinetic energy and range of motion of particles located between the torsions to nearly three times that observed in single torsion systems. It is also shown that multiple torsions can interact via amplified particle energy when separated by up to 14 interparticle distances (Δ). The torsion separation distance also showed a positive linear trend with power and a slightly positive correlation with the pressure. This amplification of energy is possible due to the fact that multiple torsions in a lattice increase the interparticle distance of the lattice by 16% more than single torsion systems, leading to additional freedom of motion in the lattice plane. These combined findings show that multiple torsions heat the lattice differently depending on their separation from the other torsion. The midpoint particles between torsions absorb the majority of energy from the two torsions, and energy addition at the midpoint is nonlinear. The addition of more torsions to the lattice may lead to melting of the plasma crystal. 

As urban populations grow, cities are becoming more complex, driving the deployment of interconnected sensing systems to realize the vision of smart cities. These systems aim to improve safety, mobility, and quality of life through applications that integrate diverse sensors with real-time decision-making. Streetscape applications—focusing on challenges like pedestrian safety and adaptive traffic management—depend on managing distributed, heterogeneous sensor data, aligning information across time and space, and enabling real-time processing. These tasks are inherently complex and often difficult to scale. The Streetscape Application Services Stack (SASS) addresses these challenges with three core services: multimodal data synchronization, spatiotemporal data fusion, and distributed edge computing. By structuring these capabilities as clear, composable abstractions with clear semantics, SASS allows developers to scale streetscape applications efficiently while minimizing the complexity of multimodal integration. We evaluated SASS in two real-world testbed environments: a controlled parking lot and an urban intersection in a major U.S. city. These testbeds allowed us to test SASS under diverse conditions, demonstrating its practical applicability. The Multimodal Data Synchronization service reduced temporal misalignment errors by 88%, achieving synchronization accuracy within 50 milliseconds. Spatiotemporal Data Fusion service improved detection accuracy for pedestrians and vehicles by over 10%, leveraging multicamera integration. The Distributed Edge Computing service increased system throughput by more than an order of magnitude. Together, these results show how SASS provides the abstractions and performance needed to support real-time, scalable urban applications, bridging the gap between sensing infrastructure and actionable streetscape intelligence. 

Abstract BackgroundWe hypothesized that alemtuzumab use is safe in pediatric kidney transplant recipients (KTRs) with equivalent long‐term outcomes compared to other induction agents. MethodsUsing pediatric kidney transplant recipient data in the UNOS database between January 1, 2000, and June 30, 2022, multivariate logistic regression, multivariable Cox regression, and survival analyses were utilized to estimate the likelihoods of 1st‐year and all‐time hospitalizations, acute rejection, CMV infection, delayed graft function (DGF), graft loss, and patient mortality among recipients of three common induction regimens (ATG, alemtuzumab, and basiliximab). ResultsThere were no differences in acute rejection or graft failure among induction or maintenance regimens. Basiliximab was associated with lower odds of DGF in deceased donor recipients (OR 0.77 [0.60–0.99],p = .04). Mortality was increased in patients treated with steroid‐containing maintenance (HR 1.3 [1.005–1.7]p = .045). Alemtuzumab induction correlated with less risk of CMV infection than ATG (OR 0.76 [0.59–0.99],p = .039). Steroid‐containing maintenance conferred lower rate of PTLD compared to steroid‐free maintenance (HR 0.59 [0.4–0.8]p = .001). Alemtuzumab was associated with less risk of hospitalization within 1 year (OR 0.79 [0.67–0.95]p = .012) and 5 years (HR 0.54 [0.46–0.65]p < .001) of transplantation. Steroid maintenance also decreased 5 years hospitalization risk (HR 0.78 [0.69–0.89]p < .001). ConclusionsPediatric KTRs may be safely treated with alemtuzumab induction without increased risk of acute rejection, DGF, graft loss, or patient mortality. The decreased risk of CMV infections and lower hospitalization rates compared to other agents make alemtuzumab an attractive choice for induction in pediatric KTRs, especially in those who cannot tolerate ATG. 

Abstract IntroductionIgA nephropathy (IgAN) can cause end‐stage kidney disease (ESKD). This study assesses the impact of induction and maintenance immunosuppression on IgAN recurrence, graft survival, and mortality in living and deceased donor kidney transplants (LDKT and DDKT). MethodsRetrospective analysis of the UNOS database in adults with ESKD secondary to IgAN who received kidney transplants between January 2000 and June 30, 2022. Patients with thymoglobulin (ATG), alemtuzumab, or basiliximab/daclizumab induction with calcineurin inhibitor (CNI) and mycophenolate mofetil (MMF) with or without prednisone maintenance were analyzed. Multivariate logistic regression was performed to identify factors correlated with IgA recurrence. Multivariable Cox regression analyses were performed for clinically suspected risk factors. Kaplan Meir Analysis was utilized for overall graft survival. ResultsCompared to ATG with steroid maintenance, alemtuzumab with steroid increased the odds of IgAN recurrence in DDKTs (OR 1.90,p <.010, 95% CI [1.169–3.101]). Alemtuzumab with and without steroid increased the odds of recurrence by 52% (p = .036) and 56% (p = .005), respectively, in LDKTs. ATG without steroids was associated with less risk of IgAN recurrence (HR .665,p = .044, 95% CI [.447–.989]), graft failure (HR .758,p = .002, 95% CI [.633–.907]), and death (HR .619,p <.001, 95% CI [.490–.783]) in DDKTs. Recurrence was strongly associated with risks of graft failure in DDKTs and LDKTs and death in LDKTs. ConclusionIn patients with IgAN requiring a kidney transplant, Alemtuzumab induction correlates with increased IgAN recurrence. Relapse significantly affects graft survival and mortality. ATG without steroids is associated with the least graft loss and mortality. 

Time-series data gathered from smart spaces hide user's personal information that may arise privacy concerns. However, these data are needed to enable desired services. In this paper, we propose a privacy preserving framework based on Generative Adversarial Networks (GAN) that supports sensor-based applications while preserving the user identity. Experiments with two datasets show that the proposed model can reduce the inference of the user's identity while inferring the occupancy with a high level of accuracy. 

The effectiveness of social distancing as a disease-slowing measure is dependent on the degree of compliance that individuals demonstrate to such orders. In this ongoing research, we study outdoor pedestrian activity in New York City, specifically using (a) video streams gathered from public traffic cameras (b) dashcam footage from vehicles driving through the city, and (c) mobile phone geo-location data volunteered by local citizens. This project seeks to form a multi-scale map of urban mobility and space occupancy under social distancing policy. The data collected will enable researchers to infer the activities, contexts, origins, and destinations of the people in public spaces. This information can reveal where and, in turn, why stay-at-home orders are and are not being followed. As a work in progress, it is yet too early for detailed findings on this project. However, we report here on several unanticipated factors that have already influenced the course of the project, among them: the death of George Floyd and subsequent protests, data collection challenges, changes in the weather, and the unexpected nature of the progression of COVID-19.