Patterns, trends and sex differences in HIV/AIDS reported mortality in Latin American countries: 1996-2007

<p>Abstract</p> <p>Background</p> <p>International cohort studies have shown that antiretroviral treatment (ART) has improved survival of HIV-infected individuals. National population based studies of HIV mortality exist in industrialized settings but few have been presented from developing countries. Our objective was to investigate on a population basis, the regional situation regarding HIV mortality and trends in Latin America (LA) in the context of adoption of public ART policies and gender differences.</p> <p>Methods</p> <p>Cause of death data from vital statistics registries from 1996 to 2007 with "good" or "average" quality of mortality data were examined. Standardized mortality rates and Poisson regression models by country were developed and differences among countries assessed to identify patterns of HIV mortality over time occurring in Latin America.</p> <p>Results</p> <p>Standardized HIV mortality following the adoption of public ART policies was highest in Panama and El Salvador and lowest in Chile. During the study period, three overall patterns were identified in HIV mortality trends- following the adoption of the free ART public policies; a remarkable decrement, a remarkable increment and a slight increment. HIV mortality was consistently higher in males compared to females. Mean age of death attributable to HIV increased in the majority of countries over the study period.</p> <p>Conclusions</p> <p>Vital statistics registries provide valuable information on HIV mortality in LA. While the introduction of national policies for free ART provision has coincided with declines in population-level HIV mortality and increasing age of death in some countries, in others HIV mortality has increased. Barriers to effective ART implementation and uptake in the context of free ART public provision policies should be further investigated.</p

On-chip Built-In Self-Calibration of Thermal Variations for Mixed-Signal In-Memory Computing

Publisher Copyright: © 2024 IEEE.In-memory computing (IMC) accelerators have become a pivotal architecture for enhancing AI algorithm computations, particularly critical for embedding deep neural networks (DNNs) in edge devices. The efficiency of these systems is paramount, yet IMC cores are prone to fluctuations due to process, temperature, and voltage variations, which can detrimentally impact DNN accuracy. This research introduces an innovative Built-In Self-Calibration (BISC) methodology, specifically designed to compensate for temperature-induced variations in mixed-signal IMC cores. The methodology enables real-time, on-chip adjustment of DNN weights during computation within the IMC core without modifying the computation path. The proposed approach, implemented on a silicon prototype, not only maintained DNN computation accuracy under substantial temperature variations but also fully compensated for almost 90% of the offset caused by these variations, without introducing any non-idealities.Peer reviewe