Publications by authors named "Reuter K"

Objectives: Despite broader eligibility under the 2021 US Preventive Services Task Force guidelines, national lung cancer screening (LCS) uptake remains at around 16%. This radiologist-led study sought to identify LCS barriers in primary care settings and develop a theory-based behavior change and implementation strategy to improve screening rates in these settings.

Methods: A multiphase approach was used, including qualitative methods and frameworks (ie, Behavior Change Wheel; Capability, Opportunity, and Motivation of Behavior model; Theoretical Domains Framework; and Expert Recommendations for Implementing Change glossary) to understand and address LCS barriers.

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The activation of H on NaY-encapsulated Mo sulfide clusters is significantly influenced by the presence of Ni at ion exchange positions. Ni was incorporated by partially ion exchanging the NaY zeolite with Ni cations. Mo(CO) vapors were subsequently deposited on the ion exchanged NiNaY zeolites followed by sulfidation in 10 vol % HS/H at 673 K, leading to the formation of dimeric MoS clusters connected to Ni via bridging S atoms.

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RNA modification is a well-recognized way for gene expression regulation in a living cell. Natural enzymatic RNA modifications have been characterized for decades. Recently, additional mechanisms, more related to RNA damage, have emerged, which do not involve targeted enzymatic activity but nonetheless alter the chemical structure of nucleosides.

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The Bayesian error estimation functional (BEEF-vdW) is widely used in surface science and catalysis, because it provides a balanced description of molecular, surface, and solid state systems, along with reliable error estimates. However, the nonlocal van-der-Waals density functional (vdW-DF2) employed in BEEF-vdW can be computationally costly and displays relatively low accuracy for molecular systems. Therefore, this work explores whether atom-pairwise and many-body dispersion treatments represent viable alternatives to using the vdW-DF2 functional with BEEF-vdW.

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tRNA-guanine transglycosylases (TGT) occur in all domains of life. They are unique among RNA-modifying enzymes as they exchange a guanine base in the primary RNA transcript by various 7-substituted 7-deazaguanines leading to the modified nucleosides queuosine and archaeosine. Archaeosine is found in the D-loop of archaeal tRNAs, queuosine in the anticodon of bacterial and eukaryotic tRNAs specific for Asp, Asn, His and Tyr.

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In catalysis research, the amount of microscopy data acquired when imaging dynamic processes is often too much for nonautomated quantitative analysis. Developing machine learned segmentation models is challenged by the requirement of high-quality annotated training data. We thus substitute expert-annotated data with a physics-based sequential synthetic data model.

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Generic statements ('Tigers have stripes') are pervasive and developmentally early-emerging modes of generalization with a distinctive linguistic profile. Previous experimental work suggests that generics display a unique asymmetry between the prevalence levels required to accept them and the prevalence levels typically implied by their use. This asymmetry effect is thought to have serious social consequences: if speakers use socially problematic generics based on prevalence levels that are systematically lower than what is typically inferred by their recipients, then using generics will likely exacerbate social stereotypes and biases.

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Future carbon management strategies require storage in elemental form, achievable through a sequence of CO hydrogenation reactions. Hydrogen is recycled from molecular intermediates by dehydrogenation, and side product acetylene selectively hydrogenated to ethylene. Existing Pd alloy catalysts for gas purification underperform in concentrated feeds, necessitating novel concepts.

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Background: Caregivers of people living with dementia (PLWD) often experience burden based on their care recipients' symptoms of wandering, disorientation, and agitation.

Objective: To examine the utilization and perceived value of technology-based solutions for caregiving among caregivers of PLWD.

Methods: In collaboration with three Texas sites, PLWD and family caregiver dyads were recruited from clinical and community sites to assess the feasibility of a caregiving technology.

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Article Synopsis
  • The study investigates how using small datasets to select an optimal cutoff score for the Patient Health Questionnaire-9 (PHQ-9) can lead to inaccurate results.
  • Researchers evaluated whether data-driven methods for cutoff selection resulted in scores that were significantly different from the true population optimal score and if these methods produced biased accuracy estimates.
  • Findings showed that many small studies frequently failed to identify the correct optimal cutoff score, particularly in smaller samples, leading to an overestimation of test sensitivity.
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The growing number of adolescent and young adult (AYA) cancer survivors and their unmet needs demand innovative communication and care strategies. This study uses social media data to examine how survivors' demographic and clinical characteristics relate to their social media use. Data from 300 AYA cancer survivors on six social media sites (YouTube, Instagram, Facebook, TikTok, Reddit, X/formerly Twitter) were collected between August 2022 and March 2023 and analyzed using descriptive statistics and statistical tests (chi-square, Fisher's exact, Welch, Games-Howell post-hoc, logistic regression).

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Unlabelled: Loads and limits for outpatient psychotherapists after the reform Objectives: The reform of the psychotherapy directive in 2017 challenged psychotherapists by new obligations and processes. We investigated burdens psychotherapists experience due to the reform and differences concerning urban vs. rural region, half vs.

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Climate Change and Materials Criticality challenges are driving urgent responses from global governments. These global responses drive policy to achieve sustainable, resilient, clean solutions with Advanced Materials (AdMats) for industrial supply chains and economic prosperity. The research landscape comprising industry, academe, and government identified a critical path to accelerate the Green Transition far beyond slow conventional research through Digital Technologies that harness Artificial Intelligence, Smart Automation and High Performance Computing through Materials Acceleration Platforms, MAPs.

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We present an efficient first-principles based method geared toward reliably predicting the structures of solid materials across the Periodic Table. To this end, we use a density functional theory baseline with a compact, near-minimal min+s basis set, yielding low computational costs and memory demands. Since the use of such a small basis set leads to systematic errors in chemical bond lengths, we develop a linear pairwise correction, available for elements Z = 1-86 (excluding the lanthanide series), parameterized for use with the Perdew-Burke-Ernzerhof exchange-correlation functional.

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Purpose: Commonly employed in polyp segmentation, single-image UNet architectures lack the temporal insight clinicians gain from video data in diagnosing polyps. To mirror clinical practices more faithfully, our proposed solution, PolypNextLSTM, leverages video-based deep learning, harnessing temporal information for superior segmentation performance with least parameter overhead, making it possibly suitable for edge devices.

Methods: PolypNextLSTM employs a UNet-like structure with ConvNext-Tiny as its backbone, strategically omitting the last two layers to reduce parameter overhead.

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Salient semantics.

Synthese

July 2024

Semantic features are components of concepts. In philosophy, there is a predominant focus on those features that are necessary (and jointly sufficient) for the application of a concept. Consequently, the method of cases has been the paradigm tool among philosophers, including experimental philosophers.

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The density functional tight-binding (DFTB) approach allows electronic structure-based simulations at length and time scales far beyond what is possible with first-principles methods. This is achieved by using minimal basis sets and empirical approximations. Unfortunately, the sparse availability of parameters across the periodic table is a significant barrier to the use of DFTB in many cases.

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Gefapixant is a weakly basic drug which has been formulated as an immediate release tablet for oral administration. A physiologically based biopharmaceutics model (PBBM) was developed based on gefapixant physicochemical properties and clinical pharmacokinetics to aid formulation selection, bioequivalence safe space assessment and dissolution specification settings. In vitro dissolution profiles of different free base and citrate salt formulations were used as an input to the model.

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Grand-canonical (GC) constant-potential methods within an implicit solvent environment provide a general approach to compute the potential-dependent energetics at electrified solid-liquid interfaces with first-principles density-functional theory. Here, we use a mindfully chosen set of 27 isostructural 2D metal halides MX2 to analyze the variation of this energetics when the electronic structure changes from metallic to semiconducting and insulating state. Apart from expectable changes due to the opening up of the electronic bandgap, the calculations also show an increasing sensitivity to the numerical Brillouin zone integration and electronic smearing, which imposes computational burdens in practice.

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The USP Rotating Basket Dissolution Testing Apparatus 1 is listed in the USP as one of the tools to assess dissolution of oral solid dosage forms. Baskets of different mesh sizes can be used to differentiate between dissolution profiles of different formulations. Here, we used Particle Image Velocimetry (PIV) to study the hydrodynamics of the USP Apparatus 1 using baskets with different mesh openings (10-, 20- and 40-mesh) revolving at 100 rpm, when the vessel was filled with 500 mL.

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Article Synopsis
  • Liquid metal catalysts, particularly liquid copper, have become important in efficiently synthesizing high-quality graphene through chemical vapor deposition, but the catalytic processes behind this are not well understood.
  • This study combines experimental observations and computational modeling to analyze how graphene grows on the liquid copper catalyst, particularly focusing on the effect of pressure ratios and temperatures on growth rates and shapes of graphene flakes.
  • Findings suggest that the growth mechanisms differ from those on solid catalysts, with factors like precursor attachment and availability playing key roles in enhancing graphene quality due to the unique properties of the liquid state.
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Through a series of empirical studies involving native speakers of English, German, and Chinese, this paper reveals that the predicate "true" is inherently ambiguous in the empirical domain. Truth statements such as "It is true that Tom is at the party" seem to be ambivalent between two readings. On the first reading, the statement means "Reality is such that Tom is at the party.

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High entropy alloys (HEAs) are a highly promising class of materials for electrocatalysis as their unique active site distributions break the scaling relations that limit the activity of conventional transition metal catalysts. Existing Bayesian optimization (BO)-based virtual screening approaches focus on catalytic activity as the sole objective and correspondingly tend to identify promising materials that are unlikely to be entropically stabilized. Here, we overcome this limitation with a multiobjective BO framework for HEAs that simultaneously targets activity, cost-effectiveness, and entropic stabilization.

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Most membrane proteins are modified by covalent addition of complex sugars through N- and O-glycosylation. Unlike proteins, glycans do not typically adopt specific secondary structures and remain very mobile, shielding potentially large fractions of protein surface. High glycan conformational freedom hinders complete structural elucidation of glycoproteins.

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