Exponent (formerly Failure Analysis Associates) is an American engineering and scientific consulting firm. Exponent has a multidisciplinary team of scientists, physicians, engineers, and business consultants which performs research and analysis in more than 90 technical disciplines. The company operates 20 offices in the United States and five offices overseas.
Most extreme natural hazard mitigation projects are analyzed using monetary indices, thereby not fully accounting for social benefits. Rigorous modeling and quantification of nonmonetary social impacts are needed to effectively estimate project benefits. In the case of habitation this requires modeling the infrastructure systems that provide critical products and services. This study proposes and demonstrates a system dynamics-based model to quantify the habitation-related impacts of mitigation projects by simulating the availability of habitable residential units based on the performance of critical internal infrastructure systems (CIIS). The model was applied to the Halls Bayou watershed in Houston, Texas, under various storm scenarios, with and without a planned mitigation project. Simulation results show that, in the case study, wastewater treatment outages primarily drive initial habitation loss, while residential shelter availability governs recovery duration and habitation loss scale. In a 500-year storm scenario, the mitigation project decreased total habitation loss scale by 100,320 residence-days (18%) and shortened recovery duration by 14 days (9%). The model structure helps explain these results. This dynamic modeling approach and model offer a new tool for disaster planning and management by facilitating the incorporation of social impacts into mitigation project analyses.
“Grooving” corrosion, or selective seam weld corrosion, is a common failure mode in tubular steel products joined by electric resistance welding (ERW). This type of corrosion is generally attributed to the formation of “active” MnS inclusions with sulfur-rich zones around the weld seam (producing anodic sites for corrosion to occur) and can be misinterpreted as a welding imperfection. This paper details the features and mechanisms associated with grooving corrosion, along with two case studies.
Driver distraction remains a leading contributor to motor vehicle crashes, necessitating rigorous evaluation of new in-vehicle technologies. This study assessed the visual and cognitive demands associated with an advanced Large Language Model (LLM) conversational agent (Gemini Live) during on-road driving, comparing it against handsfree phone calls, visual turn-by-turn guidance (low load baseline), and the Operation Span (OSPAN) task (high load anchor). Thirty-two licensed drivers completed five secondary tasks while visual and cognitive demands were measured using the Detection Response Task (DRT) for cognitive load, eye-tracking for visual attention, and subjective workload ratings. Results indicated that Gemini Live interactions (both single-turn and multi-turn) and hands-free phone calls shared similar levels of cognitive load, between that of visual turn-by-turn guidance and OSPAN. Exploratory analysis showed that cognitive load remained stable across extended multi-turn conversations. All tasks maintained mean glance durations well below the well-established 2-second safety threshold, confirming low visual demand. Furthermore, drivers consistently dedicated longer glances to the roadway between brief off-road glances toward the device during task completion, particularly during voice-based interactions, rendering longer total-eyes-off-road time findings less consequential. Subjective ratings mirrored objective data, with participants reporting low effort, demands, and perceived distraction for Gemini Live. These findings demonstrate that advanced LLM conversational agents, when implemented via voice interfaces, impose cognitive and visual demands comparable to established, low-risk hands-free benchmarks, supporting their safe deployment in the driving environment.
Background The long-term care (LTC) Data Cooperative is a National Institute on Aging-funded data resource that links skilled nursing facility (SNF) electronic health record (EHR) data with Medicare and Medicaid claims for use in comparative effectiveness and interventional research. Here we characterize the population of residents and SNFs represented in the LTC Data Cooperative and report on the completeness of key data elements.Methods We compared facility and resident characteristics between SNF participants in the LTC Data Cooperative in 2023 and all US SNFs. We examined frequencies and variation in documentation of key EHR data elements including resident census data, vital signs, blood glucose readings, medication administration records, and immunizations.Results The LTC Data Cooperative included 2557 SNFs in 48 states plus D.C. in 2023, or 17% of US SNFs. The LTC Data Cooperative population was generally similar to the national population with small differences including being slightly older (21.3% under age 65 vs. 23.8% in the national population); having fewer females (61.0% vs. 63.2%), fewer Black residents (15.1% vs. 17.5%); and fewer residents with dementia (45.5% vs. 47.2%). Data availability varied across SNFs, however most had relatively consistent documentation of key elements. The number of SNFs with vital sign records available on at least 80% of days ranged from 2248 SNFs for temperature documentation to 2303 SNFs for blood pressure documentation. Approximately 2300 SNFs (90%) had at least some medication administration records available, while 2485 SNFs (97%) had immunization records.Conclusions The LTC Data Cooperative offers novel EHR data capturing clinical measures not available in the Minimum Data Set or claims data on a SNF resident population that is comparable to the national population. Studies using these data can generate evidence to inform and improve clinical care and outcomes for older adults in the SNF setting.
Metallography, etching, and optical microscopy are some of the most common methods used to evaluate the microstructure of metallic materials (such as structural and specialty alloys). However, etching can be problematic for components with multiple metals, such as claddings, and certain multiphase materials, where differential etching rates may obscure critical microstructural features. In instances where etching is not a viable option, grain contrast imaging utilizing a scanning electron microscope provides an alternative for microstructure evaluation without the need for etching.
