Rationale and design of the RIACT–study: a multi-center placebo controlled double blind study to test the efficacy of RItuximab in Acute Cellular tubulointerstitial rejection with B-cell infiltrates in renal Transplant patients: study protocol for a randomized controlled trial

BACKGROUND: Acute kidney allograft rejection is a major cause for declining graft function and has a negative impact on the long-term graft survival. The majority (90%) of acute rejections are T-cell mediated and, therefore, the anti-rejection therapy targets T-cell-mediated mechanisms of the rejection process. However, there is increasing evidence that intragraft B-cells are also important in the T-cell-mediated rejections. First, a significant proportion of patients with acute T-cell-mediated rejection have B-cells present in the infiltrates. Second, the outcome of these patients is inferior, which has been related to an inferior response to the conventional anti-rejection therapy. Third, treatment of these patients with an anti-CD20 antibody (rituximab) improves the allograft outcome as reported in single case observations and in one small study. Despite the promise of these observations, solid evidence is required before incorporating this treatment option into a general treatment recommendation. METHODS/DESIGN: The RIACT study is designed as a randomized, double-blind, placebo-controlled, parallel group multicenter Phase III study. The study examines whether rituximab, in addition to the standard treatment with steroid-boli, leads to an improved one-year kidney allograft function, compared to the standard treatment alone in patients with acute T-cell mediated tubulointerstitial rejection and significant B-cell infiltrates in their biopsies. A total of 180 patients will be recruited. DISCUSSION: It is important to clarify the relevance of anti-B cell targeting in T-cell mediated rejection and answer the question whether this novel concept should be incorporated in the conventional anti-rejection therapy. TRIAL REGISTRATION: Clinical trials gov. number: NCT0111766

The Ticker, March 26, 2007

The Ticker is the student newspaper of Baruch College. It has been published continuously since 1932, when the Baruch College campus was the School of Business and Civic Administration of the City College of New York

An extensive study on iterative solver resilience : characterization, detection and prediction

Soft errors caused by transient bit flips have the potential to significantly impactan applicalion's behavior. This has motivated the design of an array of techniques to detect, isolate, and correct soft errors using microarchitectural, architectural, compilation­based, or application-level techniques to minimize their impact on the executing application. The first step toward the design of good error detection/correction techniques involves an understanding of an application's vulnerability to soft errors. This work focuses on silent data e orruption's effects on iterative solvers and efforts to mitigate those effects. In this thesis, we first present the first comprehensive characterizalion of !he impact of soft errors on !he convergen ce characteris tics of six iterative methods using application-level fault injection. We analyze the impact of soft errors In terms of the type of error (single-vs multi-bit), the distribution and location of bits affected, the data structure and statement impacted, and varialion with time. We create a public access database with more than 1.5 million fault injection results. We then analyze the performance of soft error detection mechanisms and present the comparalive results. Molivated by our observations, we evaluate a machine-learning based detector that takes as features that are the runtime features observed by the individual detectors to arrive al their conclusions. Our evalualion demonstrates improved results over individual detectors. We then propase amachine learning based method to predict a program's error behavior to make fault injection studies more efficient. We demonstrate this method on asse ssing the performance of soft error detectors. We show that our method maintains 84% accuracy on average with up to 53% less cost. We also show, once a model is trained further fault injection tests would cost 10% of the expected full fault injection runs.“Soft errors” causados por cambios de estado transitorios en bits, tienen el potencial de impactar significativamente el comportamiento de una aplicación. Esto, ha motivado el diseño de una variedad de técnicas para detectar, aislar y corregir soft errors aplicadas a micro-arquitecturas, arquitecturas, tiempo de compilación y a nivel de aplicación para minimizar su impacto en la ejecución de una aplicación. El primer paso para diseñar una buna técnica de detección/corrección de errores, implica el conocimiento de las vulnerabilidades de la aplicación ante posibles soft errors. Este trabajo se centra en los efectos de la corrupción silenciosa de datos en soluciones iterativas, así como en los esfuerzos para mitigar esos efectos. En esta tesis, primeramente, presentamos la primera caracterización extensiva del impacto de soft errors sobre las características convergentes de seis métodos iterativos usando inyección de fallos a nivel de aplicación. Analizamos el impacto de los soft errors en términos del tipo de error (único vs múltiples-bits), de la distribución y posición de los bits afectados, las estructuras de datos, instrucciones afectadas y de las variaciones en el tiempo. Creamos una base de datos pública con más de 1.5 millones de resultados de inyección de fallos. Después, analizamos el desempeño de mecanismos de detección de soft errors actuales y presentamos los resultados de su comparación. Motivados por las observaciones de los resultados presentados, evaluamos un detector de soft errors basado en técnicas de machine learning que toma como entrada las características observadas en el tiempo de ejecución individual de los detectores anteriores al llegar a su conclusión. La evaluación de los resultados obtenidos muestra una mejora por sobre los detectores individualmente. Basados en estos resultados propusimos un método basado en machine learning para predecir el comportamiento de los errores en un programa con el fin de hacer el estudio de inyección de errores mas eficiente. Presentamos este método para evaluar el rendimiento de los detectores de soft errors. Demostramos que nuestro método mantiene una precisión del 84% en promedio con hasta un 53% de mejora en el tiempo de ejecución. También mostramos que una vez que un modelo ha sido entrenado, las pruebas de inyección de errores siguientes costarían 10% del tiempo esperado de ejecución.Postprint (published version

Electromagnetic Interference to Flight Navigation and Communication Systems: New Strategies in the Age of Wireless

Electromagnetic interference (EMI) promises to be an ever-evolving concern for flight electronic systems. This paper introduces EMI and identifies its impact upon civil aviation radio systems. New wireless services, like mobile phones, text messaging, email, web browsing, radio frequency identification (RFID), and mobile audio/video services are now being introduced into passenger airplanes. FCC and FAA rules governing the use of mobile phones and other portable electronic devices (PEDs) on board airplanes are presented along with a perspective of how these rules are now being rewritten to better facilitate in-flight wireless services. This paper provides a comprehensive overview of NASA cooperative research with the FAA, RTCA, airlines and universities to obtain laboratory radiated emission data for numerous PED types, aircraft radio frequency (RF) coupling measurements, estimated aircraft radio interference thresholds, and direct-effects EMI testing. These elements are combined together to provide high-confidence answers regarding the EMI potential of new wireless products being used on passenger airplanes. This paper presents a vision for harmonizing new wireless services with aeronautical radio services by detecting, assessing, controlling and mitigating the effects of EMI

Mira variables in the Milky Way’s nuclear stellar disc: discovery and classification

© 2022 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society. This is the final manuscript version of an article which has been published in final form at https://doi.org/10.1093/mnras/stac2274The properties of the Milky Way's nuclear stellar disc give crucial information on the epoch of bar formation. Mira variables are promising bright candidates to study the nuclear stellar disc, and through their period-age relation dissect its star formation history. We report on a sample of 1782 Mira variable candidates across the central 3x3 deg^2 of the Galaxy using the multi-epoch infrared VISTA Variables in Via Lactea (VVV) survey. We describe the algorithms employed to select candidate variable stars and then model their light curves using periodogram and Gaussian process methods. By combining with WISE, 2MASS and other archival photometry, we model the multi-band light curves to refine the periods and inspect the amplitude variation between different photometric bands. The infrared brightness of the Mira variables means many are too bright and missed by VVV. However, our sample follows a well-defined selection function as expected from artificial star tests. The multi-band photometry is modelled using stellar models with circumstellar dust that characterise the mass loss rates. We demonstrate how > c.90 per cent of our sample is consistent with O-rich chemistry. Comparison to period-luminosity relations demonstrates that the bulk of the short period stars are situated at the Galactic Centre distance. Many of the longer period variables are very dusty, falling significantly under the O-rich Magellanic Cloud and solar neighbourhood period-luminosity relations and exhibit high mass-loss rates of ~2.5x10^{-5} M_{sun}/yr. The period distribution appears consistent with the nuclear stellar disc forming > c. 8 Gyr ago although it is not possible to disentangle the relative contributions of the nuclear stellar disc and the contaminating bulge.Peer reviewe

Flood Risk and Resilience

Flooding is widely recognized as a global threat, due to the extent and magnitude of damage it causes around the world each year. Reducing flood risk and improving flood resilience are two closely related aspects of flood management. This book presents the latest advances in flood risk and resilience management on the following themes: hazard and risk analysis, flood behaviour analysis, assessment frameworks and metrics and intervention strategies. It can help the reader to understand the current challenges in flood management and the development of sustainable flood management interventions to reduce the social, economic and environmental consequences from flooding

The morphology, growth and metabolic state of Fusarium venenatum in cation modified media

Fusarium venenatum is a filamentous ascomycete fungus that is currently used in the production of QuornTM food products. This is an important organism for research as there is scope for increasing our knowledge of the fungus in order to develop and improve production methods. This research involved investigating the morphology and metabolic responses of F. venenatum when grown in media modified in the amounts of iron and calcium, and in recycled growth medium. This type of analysis has not been attempted before in this fungus. Methods were developed for the analysis of the intracellular metabolites and proteins using LC-MS/MS technology, along with software and database searches. Targeted analysis of amino acids by GC-MS was also carried out. The morphology of the fungus was measured using light-microscopy and software. Increases in the length of the hyphae and decreases in branching were observed in iron-limited cultures, and the branching was increased in calcium-limited medium. These results could be significant for QuornTM production as the morphology could affect the texture and quality of the product. In the iron-limited condition there was a downregulation of amino acid synthesis, with a 31% reduction of total amino acids without any reduction in biomass. The metabolome and proteome results revealed that many diverse pathways were affected. For example, respiration was downregulated in the iron-limited cultures but upregulated in excess iron cultures. Knowledge of changes in metabolites such as amino acids and nucleotides could lead to the development of ways to control the flavour of the product. The growth of the fungus in recycled medium showed a significant increase in biomass, although there were changes to the morphology. This is a significant result as the use of recycled media would reduce expensive wastewater treatment, decrease waste, and a higher biomass would increase profitability