The reporting of adverse events (AEs) relating to medical devices is a long-standing area of concern, with suboptimal reporting due to a range of factors including a failure to recognize the association of AEs with medical devices, lack of knowledge of how to report AEs, and a general culture of nonreporting. The introduction of artificial intelligence as a medical device (AIaMD) requires a robust safety monitoring environment that recognizes both generic risks of a medical device and some of the increasingly recognized risks of AIaMD (such as algorithmic bias). There is an urgent need to understand the limitations of current AE reporting systems and explore potential mechanisms for how AEs could be detected, attributed, and reported with a view to improving the early detection of safety signals. The systematic review outlined in this protocol aims to yield insights into the frequency and severity of AEs while characterizing the events using existing regulatory guidance. Publicly accessible AE databases will be searched to identify AE reports for AIaMD. Scoping searches have identified 3 regulatory territories for which public access to AE reports is provided: the United States, the United Kingdom, and Australia. AEs will be included for analysis if an artificial intelligence (AI) medical device is involved. Software as a medical device without AI is not within the scope of this review. Data extraction will be conducted using a data extraction tool designed for this review and will be done independently by AUK and a second reviewer. Descriptive analysis will be conducted to identify the types of AEs being reported, and their frequency, for different types of AIaMD. AEs will be analyzed and characterized according to existing regulatory guidance. Scoping searches are being conducted with screening to begin in April 2024. Data extraction and synthesis will commence in May 2024, with planned completion by August 2024. The review will highlight the types of AEs being reported for different types of AI medical devices and where the gaps are. It is anticipated that there will be particularly low rates of reporting for indirect harms associated with AIaMD. To our knowledge, this will be the first systematic review of 3 different regulatory sources reporting AEs associated with AIaMD. The review will focus on real-world evidence, which brings certain limitations, compounded by the opacity of regulatory databases generally. The review will outline the characteristics and frequency of AEs reported for AIaMD and help regulators and policy makers to continue developing robust safety monitoring processes. PRR1-10.2196/48156.

ABSTRACT In the past decade or so, an increasing number of construction organizations have shifted from traditional CAD to BIM, which requires organizations to make corresponding changes and can be seen as a progressive organizational change. However, existing research knows little about the organizational management mechanisms for BIM implementation. From the perspective of organizational change, considering the role of transformational leadership and organizational unlearning, this study constructs a framework to explore the organizational mechanism of BIM implementation. Based on empirical analysis of 124 samples from mainland China, it was found that transformational leadership contributes to the improvement of an organization’s BIM implementation level and the pathway is mainly achieved through organizational unlearning. This study contributes to the construction industry’s organizational change and new technology implementation by inferring and validating the positive roles of transformational leadership and organizational unlearning in promoting BIM implementation. Research findings can also provide helpful guidance for industry participants to implement BIM within organizations successfully.

Common variable immunodeficiency (CVID) is a primary B cell immunodeficiency disorder. Symptoms do not develop immediately after birth, and patients are often diagnosed in childhood and adulthood. These patients often develop autoimmune diseases and malignant tumors. We herein report a 50-year-old woman with severe hypogammaglobulinemia and recurrent respiratory tract infections who was diagnosed with CVID. Target sequencing showed a TNFRSF13B heterozygous frameshift variant. The patient had many comorbidities, probably caused by a CVID-induced immune imbalance. Physicians who treat adult patients are often unaware of CVID. CVID should be recognized as a differential diagnosis in hypogammaglobulinemia and recurrent infections.

ABSTRACT This study aims to investigate the role of civil engineers and architects in driving consumer adoption of smart and green building materials in Bengaluru, India. A mixed-method approach is employed, including quantitative surveys of 350 consumers and qualitative interviews with 30 civil engineers and architects. The data are analyzed using descriptive, Confirmatory Factor Analysis (CFA), Structural Equation Modeling (SEM), and thematic analysis. Income acts as a moderating variable influencing the consumers in adoption. Civil engineers and architects use innovative marketing strategies, public education campaigns, and consumer involvement in decision-making. However, various barriers such as initial costs, limited availability, lack of expertise, and complex regulations prevent widespread adoption. The qualitative analysis highlighted the environmental benefit as the most relevant factor, increasing awareness and providing education as the most powerful strategy. Conversely, the lack of a uniform rating system and certification system is the most critical challenge affecting the adoption of these materials from a consumer behaviour perspective. Therefore, the study recommended incentivising green building materials, promote knowledge via professional development, and expedite regulatory procedures to encourage widespread use. The study uses civil engineers and architects as consumer acceptability influencers to help policymakers create a smart and green building material consumption roadmap.

Autoimmune neuromuscular disorders in patients with eosinophilic granulomatosis with polyangiitis (EGPA) are relatively uncommon. Although two cases of myasthenia gravis (MG) comorbid with EGPA have been reported, both patients developed EGPA several years after starting immunosuppressive treatment for MG. We herein report a 75-year-old man with a rare co-occurrence of EGPA and MG that developed simultaneously and was successfully treated with immunosuppressive therapy. Distinguishing the neurological symptoms of EGPA from complications of other neurological autoimmune diseases, such as MG, is crucial, especially in patients with eosinophilia.

Large language models (LLMs) such as generative pretrained transformers (GPTs) have shown potential for various commercial applications, but their applicability for materials design remains underexplored. In this Letter, AtomGPT is introduced as a model specifically developed for materials design based on transformer architectures, demonstrating capabilities for both atomistic property prediction and structure generation. This study shows that a combination of chemical and structural text descriptions can efficiently predict material properties with accuracy comparable to graph neural network models, including formation energies, electronic bandgaps from two different methods, and superconducting transition temperatures. Furthermore, AtomGPT can generate atomic structures for tasks such as designing new superconductors, with the predictions validated through density functional theory calculations. This work paves the way for leveraging LLMs in forward and inverse materials design, offering an efficient approach to the discovery and optimization of materials.

Synaptic transistors have been proposed to implement neuron activation functions of neural networks (NNs). While promising to enable compact, fast, inexpensive, and energy-efficient dedicated NN circuits, they also have limitations compared to digital NNs (realized as codes for digital processors), including shape choices of the activation function using particular types of transistor implementation, and instabilities due to noise and other factors present in analog circuits. We present a computational study of the effects of these factors on NN performance and find that, while accuracy competitive with traditional NNs can be realized for many applications, there is high sensitivity to the instability in the shape of the activation function, suggesting that, when highly accurate NNs are required, high-precision circuitry should be developed beyond what has been reported for synaptic transistors to date.

We introduce a quantum information analysis of vibrational wave functions to understand complex vibrational spectra of molecules with strong anharmonic couplings and vibrational resonances. For this purpose, we define one- and two-modal entropies to guide the identification of strongly coupled vibrational modes and to characterize correlations within modal basis sets. We evaluate these descriptors for multiconfigurational vibrational wave functions which we calculate with the n-mode vibrational density matrix renormalization group algorithm. Based on the quantum information measures, we present a vibrational entanglement analysis of the vibrational ground and excited states of CO2, which display strong anharmonic effects due to the symmetry-induced and accidental (near-) degeneracies. We investigate the entanglement signature of the Fermi resonance and discuss the maximally entangled state arising from the two degenerate bending modes.

Physical activity is recommended as part of guideline-based care for managing chronic obstructive pulmonary disease (COPD) at all stages of the disease. However, physical activity interventions are less effective in individuals with co-occurring emotional distress (i.e., depression and/or anxiety symptoms). Interventions that dually promote improved physical and mental health in COPD are needed. The first step for intervention development is understanding individuals' experience of these factors. To understand the experience of emotional distress in U.S. Veterans diagnosed with COPD and to explore how emotional distress impacts physical activity engagement. Structured interviews informed by the cognitive and behavioral models of psychopathology were conducted with 29 United States Veterans with COPD (89.66% male, age 67.72 ± 6.55 years, 93.10% White) at the VA Boston Healthcare System. Interviews were audio recorded, transcribed, and underwent thematic analysis. Three major themes encapsulating 17 codes emerged through thematic analysis: (i) the experience of emotional distress in Veterans with COPD; (ii) the complex relationship between emotional distress, physical activity engagement, and COPD; (iii) contextual and personal factors. Veterans' interpretation of their COPD symptoms as unpredictable and uncontrollable and COPD-related physical limitations influenced their experience of emotional distress, while the experience of emotional distress both promoted and deterred physical activity engagement. Veterans were motivated to engage in physical activity despite experiencing emotional distress when they faced a responsibility in daily life. They identified motivational strategies and self-regulation techniques to manage emotional distress and to foster physical activity.

ABSTRACT Against the backdrop of mounting concerns about misinformation's destabilizing impact paired with growing distrust in established news, this study explores how people estimate misinformation salience in their news environment when engaging in comparative risk assessment with other countries. The study derives from two opposite lines of reasoning on risk perceptions: While research indicating the relative scarcity of misinformation might imply an overestimation of its significance within people's own information environments, the literature on third-person perceptions could counteract this perspective, suggesting a tendency toward underestimating the relative personal risk of misinformation exposure. A survey in seven countries (N = 2,979; the USA, the UK, The Netherlands, Germany, France, Poland, India) showed how perceptions of misinformation salience are not characterized by a systematic underestimation of relative personal risks, but rather reflect a general concern regarding news landscapes being undermined by misinformation. These findings highlight the importance of understanding and studying how audiences themselves make sense of misinformation salience, as these perceptions determine how people navigate a news environment that is perceived to be disrupted by the omnipresence of misinformation.