A Framework for Sustained Climate Assessment in the United States

The National Climate Assessment’s ability to support decision-making partly relies on engaging stakeholders throughout the assessment process. The guiding vision for the Third National Climate Assessment (NCA3) was for an inclusive, broad-based, and sustained process attentive to both the conduct of assessments and communication of findings. Such a process promotes dialogue between scientific experts, stakeholders, and decision-makers about what is important in a particular region or sector, the potential impacts of climate change, and possible responses. We sought to create actionable research and assessment products widely perceived as credible, salient, and legitimate. The process also sought to build capacity to conduct sustained assessments and use climate change information in decision-making processes. Here we describe how we pursued this stakeholder engagement vision during the planning, development, and release of NCA3. Through repeated opportunities for stakeholder. input, we ensured process transparency and inclusiveness in the framing of assessment and built human capital. We also increased connectivity among stakeholder organizations. By cultivating a network of collaborators who connected the NCA to other networks, the NCA3 engagement process laid the groundwork for a sustained assessment - which is envisaged to transition the traditional quadrennial assessment approach into a more dynamic and adaptive assessment process.

Depression is a common psychiatric disorder with devastating effects on the older Hispanic population. This review synthesizes the research on depression among older Hispanics in the United States to educate and provide direction for further research and practice. A literature search of PubMed, CINAHL, and PsycINFO databases was conducted. Article titles, abstracts, and texts of articles were scanned for those that met the inclusion criteria for this review. Inclusion criteria included the following: research studies published between 2000 and 2012; studies published in the English language; studies about depression that included older Hispanics (50 years old and older) who resided in the United States; and studies about depression, acculturation, and other associated stressors that may contribute to depression in this population. The results of this review indicate that acculturation, associated stressors, health-related factors, and psychosocial factors may have a negative impact on older Hispanics’ mental health. More research is needed to further explore Hispanics’ perceptions and experiences of depression as well as the cultural dimensions of Hispanic depression. The cultural formulation can be a useful framework for assessment, prevention, and treatment of older Hispanics with depression. Knowledge regarding depression and what causes it can lead to better assessment practices, early detection, and culturally sensitive interventions, care and services.

Artificial intelligence (AI) and machine-learning (ML) technologies are increasingly being incorporated into orthopaedic medical devices, offering the potential to enhance surgical planning, intraoperative precision, and personalized care. The incorporation of AI into medical devices introduces unique risks and challenges that traditional regulatory pathways in the United States and European Union (EU) were not designed to address. Although the EU Artificial Intelligence Act is currently being implemented to provide a specific framework for AI medical device assessment, no equivalent directive exists in the United States. In consideration of these evolving regulatory contexts, this study sought to address the following questions related to FDA-approved, AI/ML-enabled orthopaedic devices: (1) How often are FDA-approved, AI/ML-enabled orthopaedic devices also approved under the EU Medical Device Regulation (MDR)? (2) How often are AI/ML-enabled orthopaedic devices approved through the FDA 510(k) pathway using non-AI predicate devices? (3) How often do approved AI/ML-enabled orthopaedic devices have independent, peer-reviewed evidence supporting their use? (4) How often are the details of the training and validation datasets of these devices disclosed in publicly available regulatory documents? A total of 37 AI/ML-enabled orthopaedic device approvals were identified from the FDA's list of 1017 AI/ML-enabled medical devices as of May 2025. Regulatory documents were analyzed to identify training and validation data sets and predicate devices. A predicate device is an existing legally marketed device that the FDA has previously approved; a manufacturer may claim that a new device is "substantially equivalent" to this approved device to obtain clearance through the 510(k) pathway. The availability of devices in the EU was assessed through the publicly available European Database on Medical Devices (EUDAMED) database and manufacturer websites. A systematic review of PubMed and manufacturer websites identified peer-reviewed evidence for each device. Our results showed that 38% (14 of 37) of AI/ML-enabled orthopaedic devices were approved for use in the EU, and devices were more frequently available in the United States first. All AI/ML-enabled orthopaedic devices approved by the FDA received regulatory clearance through the 510(k) pathway; most devices (62% [23 of 37]) were approved based on substantial equivalence to non-AI enabled devices. Independent peer-reviewed evidence was identified for 30% (11 of 37) of devices, with 67% (34 of 51) of published studies reporting manufacturer involvement. Information on training and validation datasets was disclosed in 57% (21 of 37) of 510(k) summaries, with dataset sizes ranging from 21 to 150,000 for training and 20 to 29,991 for validation. AI/ML-enabled orthopaedic devices have entered the market under existing regulatory frameworks in the United States and, at a slower pace, in the EU. Reliance on non-AI comparators and limited postmarket evaluation raises concerns regarding their long-term clinical reliability. As the level of patient risk under the current regulatory pathways remains uncertain, future research should compare AI/ML-enabled device recall rates across jurisdictions to assess whether AI-specific regulatory frameworks improve patient safety and device reliability.

This study examined the current landscape of transition to residency (TTR) courses in the United States. A nonincentivized survey was distributed electronically from October 2023 to March 2024 to contacts at 187 accredited U.S. medical schools (153 allopathic and 34 osteopathic schools). The survey inquired about the presence of a TTR course or plans for implementation. For schools with a course, respondents were asked about course requirements, content, structure, duration, resources used, assessment framework, grading, remediation, professionalism concerns, and faculty support. Of the 187 surveyed medical schools, 132 (70.6%) responded; 115 (87.1%) have a TTR course, with 8 of the 16 medical schools (50.0%) without a TTR course planning to implement one in the next 3 years. Ninety-one courses (79.1%) are required. The median (range) duration of the shared TTR course is 2 (0-10) weeks. The most commonly used external resources are MedEdPORTAL (40 [34.8%]) and the TTR compendium (37 [32.2%]). Sixty-seven schools (58.3%) structure the course using Accreditation Council for Graduate Medical Education core competencies and/or milestones. Grades are predominantly pass/fail (108 [93.9%]); 21 schools (18.3%) incorporate remediation. Topics include responding to common inpatient issues, pages from nurses, and rapid responses and codes. A total of 105 respondents (91.3%) reported at least one student in their course with professionalism concerns. Respondents with knowledge about full-time equivalent faculty support (75 [65.2%]) revealed that the total median full-time equivalent support for all TTR faculty is 0.1 (interquartile range, 0-0.3; range, 0 to > 2). Most medical schools have a TTR course, but aspects of the course vary. Future directions to improve the national TTR experience include the creation of standardized content, validated assessments, and collaborative research examining the impact of TTR courses on interns and the programs to which they match.

We consider why international business research comparing values, attitudes, and behaviors of managers from the United States and Canada shows conflicting results about cultural differences and similarities between these two nations. We argue that one reason behind these inconsistent findings is the presence of intranational subcultural regions in these nations. The second reason is that the variable(s) under scrutiny influence the generalizability of research findings. Employing Lenartowicz and Roth’s (1999) framework for culture assessment, theories of cultural evolution and maintenance, and data from the World Values Survey, we test the distinctiveness of subcultural regions in the United States and Canada, at both the individual level and the regional level of analysis. Results support our hypothesized arguments.

<p>In recent years, several locations in the United States have been experiencing a significant increase in seismicity that has been attributed to oil and gas production. As oil and natural gas production in the United States continues to increase, it is expected that the seismic hazard in these locations will continue to experience a corresponding upsurge. However, many urban structures in these locations are not designed to withstand these increasing levels of seismicity. Accordingly, it is crucial to develop methodologies that can help us quantify the seismic performance of these structures, establish their risk levels, and identify optimal retrofit strategies that will enhance the seismic resilience of these structures. In this context, structural health monitoring (SHM) plays an important role in understanding the seismic performance of structures. SHM can be used, in conjunction with finite element modelling, to provide a realistic representation of the structural performance during a seismic event. In this paper, a framework for seismic risk assessment of reinforced concrete buildings based on SHM is presented. The framework combines nonlinear finite element modeling and SHM data to establish the seismic fragility profile of the structure. The approach is illustrated on a multi- story reinforced concrete structure located on the Oklahoma State University Campus.</p>

The National Assessment of Educational Progress (NAEP) in Reading aims to measure reading comprehension for students in the United States and to monitor progress in our education system. NAEP Reading is developed based on an assessment framework document that is periodically revised to reflect the latest understandings about reading comprehension and its assessment. A key goal of the Visioning Panel (VP) and the Development Panel (DP) charged with updating the NAEP Reading Assessment Framework for 2026 was to lay the foundation for an assessment that made progress toward greater fairness, equity, and validity. In this essay, we discuss how the Framework development process unfolded and its results. We document the unusual ways the National Assessment Governing Board (“the Board”) shaped the development process. We provide evidence that a small group of Board members aimed to preserve the status quo in reading assessment by downplaying reliance on expertise and authoritative sources of research on reading, learning, and assessment and by removing attention to equity in NAEP Reading. We also discuss both successful (i.e., approved by the Board) and unsuccessful (i.e., rejected by the Board) recommendations for changes to the 2026 Framework that initially were proposed by the DP. We end by considering how, despite the efforts of the small group of Board members, we as a literacy field can improve the nature and impact of our large-scale reading assessments, and NAEP in particular.

The spread of nonindigenous (nonnative) species introduced into the United States is a significant and growing national problem and results in lost agricultural productivity, increased health problems, native species extinctions, and expensive prevention and eradication efforts. Thousands of nonindigenous species have either become established or spread, and introduction of aquatic nuisance species (ANS) into freshwater lakes threaten aquatic biodiversity. Expanding global trade is likely to increase the number of species that are spread across the globe, so the need to develop an approach to predict potential ANS invasions is great. Risk assessments currently being used to assess ANS risk rely on qualitative or semiquantitative information and expert opinion; thus, such approaches lack transparency and repeatability. A more quantitative approach is needed to augment the qualitative approaches currently in use. A quantitative approach with the use of the traditional ecological risk assessment (traditional ERA) framework combined with decision analysis tools was developed for assessing ANS risks in which the causative ecological risk agent is an organism rather than a chemical. This paper presents a systematic risk assessment framework that includes structured decision analysis to help organize and analyze pertinent data, state assumptions, address uncertainties in estimating the probability of an undesired ANS introduction, or spread and integrate these outputs with stakeholder values. This paper also describes when and how decision analysis tools can be used in such assessments for ANS. This framework and methodology will enable risk managers to systematically evaluate and compare alternatives and actions supporting ANS risk management and thus credibly prioritize resources.

The discussion in chapter 2 addressed what might be described as a microview of the US energy economy— how we use energy as individuals, how we measure our personal consumption, and how we pay for it. We turn attention now to a more expansive perspective— the use of energy on a national scale, including a discussion of associated economic benefits and costs. We focus specifically on implications for emissions of the greenhouse gas CO2. If we are to take the issue of human- induced climate change seriously— and I do— we will be obliged to adjust our energy system markedly to reduce emissions of this gas, the most important agent for human- induced climate change. And we will need to do it sooner rather than later. This chapter will underscore the magnitude of the challenge we face if we are to successfully chart the course to a more sustainable climate- energy future. We turn later to strategies that might accelerate our progress toward this objective.We elected in this volume to focus on the present and potential future of the energy economy of the United States. It is important to recognize that the fate of the global climate system will depend not just on what happens in the United States but also to an increasing extent on what comes to pass in other large industrial economies. China surpassed the United States as the largest national emitter of CO2 in 2006. The United States and China together were responsible in 2012 for more than 42% of total global emissions. Add Russia, India, Japan, Germany, Canada, United Kingdom, South Korea, and Iran to the mix (the other members of the top 10 emitting countries ordered in terms of their relative contributions), and we can account for more than 60% of the global total. Given the importance of China to the global CO2 economy (more than 26% of the present global total and likely to increase significantly in the near term), I decided that it would be instructive to include here at least some discussion of the situation in China— to elaborate what the energy economies of China and the United States have in common, outlining at the same time the factors and challenges that set them apart.

We are grateful to the editor and reviewers for this opportunity to respond to the five essays reviewing two recent books comparing regulation in the US and Europe: The Politics of Precaution: Regulating Health, Safety, and Environmental Risks in Europe and the United States, and The Reality of Precaution: Comparing Risk Regulation in the United States and Europe. We agree with reviewer Maria Weimer and with David Vogel that both of these books help create a research agenda for comparative studies of regulation, including studies of relative precaution, by developing theoretical explanations and a systematic basis for collecting data to test them. We also agree with reviewer Susan Rose-Ackerman that comparative studies of regulation should examine not only relative precaution, but more broadly the interrelationships among precaution, proportionality, impact assessment, cost-benefit analysis, and other analytic frameworks – and the value choices embedded in them. We addressed those important issues in the concluding chapter of our book, but they certainly deserve additional inquiry. And we thank Fabrizio Cafaggi for his extensive review of our book in an earlier issue of this journal; there he emphasized our book’s contribution to the evolving understanding of transnational regulatory networks. Both books undertake a descriptive comparison of relative precaution in American and European regulation over the past several decades. The two books differ in their findings, and in the evidence on which those findings rest. We thank reviewers Susan RoseAckerman, Adam Burgess, and Jane K. Winn for acknowledging the strong empirical evidence of actual policymaking that is assembled in our book. We disagree, however, with the reviewers who allege that our book has somehow “missed the wood for the trees” or cast “empiricism” against “humanism”, ostensibly because Europe yearns to define its “identity” as precautionary or because European regulation “feels” more precautionary. In our view, it is a mistake to confuse rhetoric with reality, or feelings with actions, and it is an illusion to conflate political aspirations with actual policymaking. That is why we studied actual policies: to test whether they reflect the political rhetoric or not. To characterize the forest and see whether it has moved, one must examine a representative sample of the trees – which is what we have done. To compare regulatory policies, one must actually study the policies and avoid being seduced by aspirational rhetoric and symbolic politics which are not themselves evidence of real regulation. * Jonathan B. Wiener is Perkins Professor of Law at Duke Law School, Professor of Environmental Policy at the Nicholas School of the Environment, and Professor of Public Policy at the Sanford School of Public Policy, at Duke University and a University Fellow of Resources for the Future (RFF). Brendon Swedlow is an Associate Professor in the Department of Political Science, at Northern Illinois University. James K. Hammitt is Professor of Economics and Decision Sciences at the Department of Health Policy and Management, Harvard School of Public Health, and visiting professor at the Toulouse School of Economics (LERNA-INRA). Michael D. Rogers is a former member of the Bureau of European Policy Advisers, at the European Commission. Peter H. Sand is lecturer in International Environmental Law at the University of Munich.

In the first section, the panel summarizes background information relevant to the topic. In the second section, the panel poses questions regarding the diagnosis and treatment of neurocysticercosis (NCC), evaluates applicable clinical trial and observational data, and makes recommendations using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) framework [1]. The following 27 clinical questions were answered: How should neurocysticercosis be diagnosed? What imaging studies should be used to classify disease? What additional tests should be performed prior to initiation of therapy? How should antiparasitic and anti-inflammatory therapy be monitored? What is the role of antiparasitic drugs in viable parenchymal neurocysticercosis? What is the role of anti-inflammatory therapy in management of viable parenchymal neurocysticercosis? What is the role of antiepileptic drugs in viable parenchymal neurocysticercosis? What follow-up is recommended after initial antiparasitic therapy for patients with viable parenchymal neurocysticercosis? What should be the initial approach to the patient with multiple enhancing lesions from neurocysticercosis? What is the role of antiepileptic medications in patients with single enhancing lesions from cysticercosis with seizures? What is the role of antiparasitic drugs in patients with single enhancing lesions? What is the role of anti-inflammatory therapy in single enhancing lesions? How should patients with single enhancing lesions be followed? What should the initial approach be to patients with calcified lesions suggestive of calcified parenchymal neurocysticercosis? What is the role of antiparasitic drugs, antiepileptic drugs, and anti-inflammatory medications in the management of patients with calcified parenchymal neurocysticercosis? Is there a role for surgical therapy in refractory cases? How are extraparenchymal cysts best identified? What is the optimal approach to management of ventricular neurocysticercosis in the lateral and third ventricles? What is the optimal surgical approach to management of ventricular neurocysticercosis in the fourth ventricles? What is the optimal approach to adherent ventricular neurocysticercosis? Does medical therapy as an adjunct to procedures or as primary therapy have an impact on outcome in treating patients with ventricular neurocysticercosis? What is the role of medical therapy in subarachnoid neurocysticercosis in the basilar cisterns or Sylvian fissures? What is the role of neurosurgery in subarachnoid neurocysticercosis? How is spinal neurocysticercosis best treated? What is the optimal management of ocular cysticercosis? Should children be managed differently than adults? Should management be different in pregnant women? BACKGROUND Neurocysticercosis, caused by the larval form of the cestode parasite Taenia solium, is a major cause of seizure and neurologic disease worldwide and is common among immigrant populations in the United States. Highly endemic regions include Latin America, sub-Saharan Africa, and parts of Asia [2, 3]. In endemic areas, it is linked to approximately 29% of cases of seizures [4]. Estimates suggest that there are >2000 cases per year in the United States, with hospital charges of nearly $100 million per year [5, 6]. Humans can be hosts to both the tapeworm form and larval forms of the parasite. Taeniasis (also termed taeniosis) refers to infestation of the human intestines with the tapeworm form. The tapeworm is acquired by ingestion of undercooked pork. The scolex evaginates and attaches to the intestinal wall, and segments termed proglottids form a long ribbon-like chain referred to as the strobili. The gravid proglottids and eggs are passed in stool. Humans can also develop cysticercosis after ingestion of ova. Cysticercosis refers to infection of the tissues with the larval cyst (or metacestode). Normally, pigs host the cysts, which are acquired by ingestion of ova or proglottids from human feces. However, humans can be infected by ingestion of ova and develop cysticercosis. Neurocysticercosis refers to cysticercosis involving the central nervous system, including the brain parenchyma, ventricles, basilar cisterns, sulci, gyri, spine, and retina. The pathogenesis, natural history, clinical manifestations, and management vary with the location of the cysticerci [3]. For example, the main clinical manifestations vary between different forms of disease (Table 1). Parenchymal NCC typically presents with seizures or headache. Ventricular NCC most often presents with obstructive hydrocephalus. Subarachnoid NCC can present with communicating hydrocephalus, meningitis, stroke, or focal neurologic findings. Mixed forms are also common. Due to the complexity of diagnosis and management, the American Society for Tropical Medicine and Hygiene (ASTMH) and the Infectious Diseases Society of America (IDSA) agreed to jointly develop guidelines for the diagnosis and management of NCC.

Natural threats like earthquakes, hurricanes or tsunamis have had serious impacts on communities. In the past, major earthquakes in the United States like Loma Prieta 1989, Northridge 1994, or recent events in Italy like L’Aquila 2009 or Emilia 2012 emphasized the importance of preparedness and awareness to reduce social impacts. In addition to that, earthquake damaged businesses dramatically reduced the gross regional product. Generating scenario earthquakes in a proper way is important to suitably assess the risk in bridge networks and social losses in terms of gross regional product reduction. Seismic hazard is traditionally assessed by means of probabilistic seismic hazard analysis (PSHA). Although PSHA well represents the hazard at a specific location it is not suitable for spatially distributed systems. Scenario earthquakes can overcome this problem; they represent the actual distribution of ground shaking for a spatially distributed system while being hazard consistent. In this work a methodology to generate scenario earthquakes has been proposed using a novel approach with the aim of being the basic step for investigating possible earthquake consequences in seismic areas and contributing to reduce losses.

Bioaccumulation of decabromodiphenylethane (DBDPE) in aquatic and terrestrial biota in the global environment and its toxicological significance assessed by chemical activity.

Climate change is intensifying the frequency, severity, and duration of extreme weather events such as heatwaves and wildfires, disproportionately affecting vulnerable urban populations, particularly the elderly. This thesis presents a dual risk assessment focused on populations aged 65 and older in Bologna, Italy, and California, the United States. By integrating environmental, infrastructural, and demographic data, it identifies susceptibilities and proposes data-driven mitigation strategies using Machine Learning (ML). Using wildfire (2014–2021) and heatwave (2014–2023) data at the census tract level, the study develops risk maps under Representative Concentration Pathways (RCP) scenarios 4.5, 6.0, and 8.5. It applies Random Forest (RF) and Long Short-Term Memory (LSTM) models to identify high-risk urban areas, advocating for transdisciplinary and equitable urban resilience strategies. The methodology builds upon the risk triangle, hazard, exposure, and vulnerability. Hazards include temperature extremes and wildfire intensity. Exposure is assessed through population density in hazard-prone areas. Vulnerability accounts for age, gender, socioeconomic status, health, and built infrastructure. Advanced Geographic Information Systems (GIS) and ML methods enhance the assessment’s scalability and accuracy over traditional approaches. This dissertation documents and evaluates the methodology through a structured three-phase approach: creation, analysis, and application of risk maps. The creation phase uses ML to model spatial and temporal risk dynamics. Case studies in Bologna and California demonstrate the integration of diverse datasets, including meteorological, topographical, and demographic variables. The analysis phase optimizes model performance using GridSearchCV and the Hippopotamus Optimization Algorithm (HOA), validated through confusion matrices, statistical metrics, and ROC curves. In the application phase, risk maps inform urban planning and highlight strategies to protect the elderly. This study develops a data-driven framework for climate risk assessment and mitigation. By merging Nature-Based Solutions (NBS), ML, and urban planning, it promotes healthier, more equitable, and climate-resilient cities.

Physics-based simulations, while central to transmission tower fragility analysis, are often computationally prohibitive for system-level or regional-scale assessments, where the objective is to evaluate the performance of multiple transmission towers with diverse geometries over large geographic regions. The study addresses these challenges by developing a generalized surrogate wind fragility modeling framework. This framework facilitates rapid and comprehensive vulnerability assessment of transmission towers by integrating structural design, fragility analysis, and deep-learning-based surrogate modeling. This integration allows the framework to explicitly account for site-specific environmental conditions and tower-specific design characteristics across diverse geographic regions in the United States, thereby enhancing its generalizability and applicability to a wide range of tower designs and locations. Moreover, contrary to traditional fragility models, the framework considers a more realistic representation of extreme wind events, where multiple hazard variables (i.e., wind speed, direction, and rainfall intensity) influence tower fragility concurrently. The resulting surrogate models provided high prediction accuracies. For unseen towers, the models achieved a mean square error of 0.0202 and an R 2 of 0.899 and demonstrated consistency with conventional physics-based fragility models. Moreover, the inclusion of location-specific design parameters enabled the models to adapt to different regional performance objectives, while considering tower-specific parameters in the design phase facilitated rapid vulnerability assessments for various tower designs within the transmission network. Overall, the proposed framework can potentially reinforce decision-making for grid resilience planning by offering a practical and computationally efficient solution for system-level vulnerability analysis of transmission tower networks. • The framework combines design and fragility processes for model generalizability. • The interaction of three environmental parameters is considered in tower fragility. • The developed surrogate models provide a high prediction accuracy. • Surrogate models can be generalized for various tower configurations and locations. • The framework provides a computationally-efficient solution for network-level analysis.