Xilinx (United States)

• Transparent, reproducible workflow to build overhead power grids from public data. • Map electricity end users by integrating Google Places API and OpenStreetMap. • Novel distance–capacity method links end users to substations. • Cascading failures modelled via power flow analysis, beyond topological methods. • Estimate service disruptions via post-disruption electricity-served ratio. Cascading failures in power grids can escalate localized disruptions into extensive service outages. This study presents a transparent, reproducible framework to build power grids from publicly available data, integrating commissioned power plants, substations, transmission lines, and hypothetical transformers, for large-scale power system modelling. To assess how grid disruptions lead to service interruptions for industrial users, we combine Google Places API industrial points of interest with OpenStreetMap industrial zones, and link them to substations based on capacity and proximity. We model initial disruptions under two scenarios: 1) random disruptions, implemented through percolation analysis to assess network robustness under stochastic component removals; and 2) targeted disruptions, generated by Monte Carlo sampling of wind-induced fragility curves derived from the 2024 Typhoon Yagi wind field to produce probabilistic failures. The analysis reveals distinct spatial variation in grid vulnerability and traces the propagation of failures through the network, quantifying downstream service disruptions for industrial users. System-wide simulations further identify critical transmission corridors with higher failure and overload risks. These insights provide a basis for targeted investment, resilience assessment, and future research on multi-hazard and adaptive protection strategies.

Abstract Overgrazing has caused widespread global concern. However, how grazing intensity affects ecosystem carbon dioxide (CO 2 ) fluxes with wetness fluctuations in grasslands at a global scale remains poorly understood. Here we measured ecosystem CO 2 fluxes covering the 7th to 11th years of a continuous grazing experiment in a typical steppe, and conducted a meta-analysis of 585 observations by collecting relevant data in global grasslands. Our experimental results showed that mean gross primary productivity (GPP) and ecosystem respiration (ER) were decreased under heavy grazing (HG) compared with control without grazing (CK), whereas net ecosystem productivity (NEP) was not different between HG and CK in the typical steppe. The NEP was higher under light grazing in the wetter years, but it was not different between LG and CK under drier years in the typical steppe. In contrast, grazing decreased GPP, ER and NEP, respectively, in global grasslands. Both our field experiment and the meta-analysis revealed that the response of NEP to light grazing was linearly correlated with the wetness index, which may be mediated by greater plant relative growth rate in wetter years. Higher wetness and aboveground biomass (AGB) increased the response of NEP to grazing in global grasslands. However, heavy grazing reduced NEP and AGB even under higher wetness indices in global grasslands, resulting from a loss of their resilience in long-term heavy grazing. These findings indicate that light grazing appears to be a promising management to promote plant relative growth rate and CO 2 flux sequestration. Furthermore, major drivers influencing ecosystem CO 2 fluxes in response to grazing were aboveground biomass, grazing intensity and wetness index. Overall, this study provides a global perspective on the response of ecosystem CO 2 fluxes to grazing intensity and improves our knowledge of the factors influencing the response of ecosystem CO 2 fluxes to grazing intensity.

We self-injection locked two free-running DFB lasers to two adjacent resonances of microring resonators (MRRs) to enhance the lasers frequency spacing stability. The frequency spacing stability between the two locked lasers was <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$&lt; $</tex-math></inline-formula>300 MHz while locking to a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\sim$</tex-math></inline-formula>0.5 million Q microring with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\sim$</tex-math></inline-formula>19.6 GHz free spectral range (FSR), improving to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$&lt; $</tex-math></inline-formula>100 MHz level after locking to a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\sim$</tex-math></inline-formula>1.5 million Q microring with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\sim$</tex-math></inline-formula>25.2 GHz FSR. The locked lasers were modulated with dual polarisation 16-QAM signals with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$&lt; $</tex-math></inline-formula>1 GHz guard-band between two channels, and the MRR locked DFB lasers achieved similar performance to commercial external cavity lasers in the coherent communication system.

In order to improve mall evacuation efficiency, Pyrosim software and Anylogic software are used to study the coupled evacuation of mall personnel using escalators and stairs in a fire scenario. The available safe evacuation time of each evacuation exit was explored by analyzing the smoke transport, temperature, CO concentration and visibility of each floor of the mall under different fire source locations when the fire shutter was lowered to 1.8m from the ground. Then, the evacuation model of mall personnel under fire scenario was built by using Anylogic to compare and analyze the evacuation time of mall personnel using escalators coupled with stairs and stairs only, and analyze the evacuation time of personnel using escalators coupled with stairs when the fire shutter at the escalator is down to 1.8m from the ground and when the fire shutter is not down. The study shows that when the fire source is located on the top floor of the mall, the smoke does not affect the evacuation of people on other floors during the simulation time. Under the fire scenario, the escalator-coupled staircase evacuation can shorten the maximum evacuation time by 23.37% compared with the staircase only. The fire shutter descends to 1.8m from the ground and the evacuation efficiency is 6.41% higher than when the fire shutter is not descended. This research contributes to the enhancement of mall safety and has practical implications for future emergency management strategies in public spaces.

Mesozoic is an interdisciplinary journal dedicated to the study of Earth and life evolution during the Mesozoic Era. Its scope within the geosciences is broad, encompassing disciplines such as stratigraphy, palaeontology, palaeogeography, palaeoclimate, palaeoenvironment, geochronology, sedimentology, geochemistry, palaeomagnetism, and tectonic geology. We encourage interdisciplinary collaboration to explore the deep relationships between biotic evolution and Earth’s surface processes.

This paper presents a platform and design approach for enabling radiation-tolerant deep learning acceleration on SRAM-based 20nm Kintex UltraScale™ FPGAs, for terrestrial and high-radiation environments. The presented platform is suitable for deep neural network (DNN) implementations with an emphasis on image classification and includes solutions to mitigate both radiation-induced Single Event Functional Interrupts (SEFIs) and network datapath corruptions. The radiation-tolerant deep learning platform combines Xilinx’s Deep Learning Processing Unit (DPU) IP, Triple Modular Redundancy (TMR) MicroBlaze soft processor IP and Soft Error Mitigation (SEM)-IP to mitigate SEFIs. Furthermore, a technique known as Fault Aware Training (FAT) was applied to effectively mitigate single event effects in the datapath. Test results from a high-energy proton beam (> 60 MeV) experiment using the ResNet-18 Convolutional Neural Network (CNN) for image classification are presented. The Single Event Upset (SEU) rate, system-level SEFI rate and neural network classification/datapath performance are compared between the radiation-tolerant platform and a standard, non-mitigated approach. Results show that datapath classification errors dominate the system response (90%) vs. SEFIs (10%). When compared to standard non-mitigated training techniques, the radiation-tolerant platform using fault aware training methods shows dramatic improvements in overall system response: the overall single event cross-section was reduced by half and 40% reduction in misclassification errors were observed. Also, datapath events with classification accuracy degradation larger than 5% were completely mitigated. The SEFI rate was reduced by 100X with implemented solutions and can be further reduced by optimizing the physical separation between TMR modules.

The human endogenous protein galectin-9 (Gal-9) reactivates latently HIV-infected cells in vitro and ex vivo , which may allow for immune-mediated clearance of these cells. However, Gal-9 also activates several immune cells, which could negatively affect HIV persistence by promoting chronic activation/exhaustion. This potential 'double-edged sword' effect of Gal-9 raises the question of the overall impact of Gal-9 on HIV persistence in vivo . We used the BLT (bone marrow, liver, thymus) humanized mouse model to evaluate the impact of Gal-9 on HIV persistence in vivo during antiretroviral therapy (ART). Two independent cohorts of ART-suppressed HIV-infected BLT mice were treated with either recombinant Gal-9 or phosphate-buffered saline control. Plasma viral loads and levels of tissue-associated HIV DNA and RNA were measured by qPCR. Immunohistochemistry and HIV RNAscope were used to quantify CD4 + T, myeloid, and HIV RNA+ cells in tissues. T cell activation and exhaustion were measured by flow cytometry, and plasma markers of inflammation were measured by multiplex cytokine arrays. Gal-9 did not induce plasma markers of inflammation or T cell markers of activation/exhaustion in vivo . However, the treatment significantly increased levels of tissue-associated HIV DNA and RNA compared to controls ( P = 0.0007 and P = 0.011, respectively, for cohort I and P = 0.002 and P = 0.005, respectively, for cohort II). RNAscope validated the Gal-9 mediated induction of HIV RNA in tissue-associated myeloid cells, but not T cells. Our study highlights the overall adverse effects of Gal-9 on HIV persistence and the potential need to block Gal-9 interactions during ART-suppressed HIV infection.