bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multiplexing Meta‐Illusion with High Correlation in Both Near‐ and Far‐Field Region
Authors: Huang Hailin , Guan Chunsheng , Zheng Bin , Li Xiaofeng , Cui Xingshuo , Liang Jiangang , Jiang Weixiang , Chen Hongsheng , Cai Tong 
Published: June 2024

AbstractMicrowave illusion, which can generate the scattering field of objects that don't exist to deceive the detecting devices, is an important and advanced technology in modern science. The conventional illusion device is limited by the narrow working band, non‐flat structure, or single functionality, which is inconvenient for electromagnetic integration. The newly multiplexing metasurfaces provide an effective method to achieve microwave illusion due to their excellent ability in wavefront tailoring. Here, a dual‐band microwave illusion enabled by multiplexing metasurface is proposed, and such a device can simulate two independent scattering fields of real objects at two separate frequencies by recording the near‐ and far‐field information. As a proof of concept, a meta‐illusion, realizing the electromagnetic information of the scaled‐down Sydney Opera House and Pyramid, is designed and fabricated. Microwave experiments are performed to demonstrate the predicted effects. The results show high correlation properties in both near‐ and far‐field characterizations, which is 83%, 80%, and 91%, 80% at two operating frequencies, respectively, verifying the high performance of the meta‐illusion. The findings may motivate the realizations of high‐performance meta‐illusions in other frequency domains and meta‐devices with complex functionalities.
Synthesis of New Glycine‐Based Polymers and their Thermoresponsive Behavior in Water
Authors: Mohimont Florent , Rieger Jutta , Stoffelbach François 
Published: June 2024

AbstractIn this work, new glycine‐derived polymers are developed that exhibit thermoresponsive properties in water. Therefore, a series of monomers containing one, two, or three amide functional groups and one terminal cyanomethyl group is synthesized. The resulting homopolymers, obtained by free radical polymerization (FRP) and reversible addition fragmentation chain transfer (RAFT) polymerization, display a sharp and reversible upper critical solution temperature (UCST)‐type phase transition in water. Additionally, it is shown that the cloud point (TCP) can be adjusted over more than 60 °C by the number of glycyl groups present in the monomer structure and by the polymer's molar mass. These novel thermoresponsive polymers based on cyanomethylglycinamide enrich the range of nonionic UCST polymers and are promising to find applications in various fields.
Chromatic bleaching and fractionation effects on optically stimulated luminescent dosimeter reuse
Authors: Scott Hayden , Alvarez Paola E. , Howell Rebecca M. , Riegel Adam , Sun Ryan , Liu Kevin , Kry Stephen F. 
Published: June 2024

AbstractBackgroundOptically stimulated luminescent dosimeters (OSLDs) can be bleached and reused, but questions remain about the effects of repeated bleaching and fractionation schedules on OSLD performance.PurposeThe aim of this study was to investigate how light sources with different wavelengths and different fractionation schemes affect the performance of reused OSLDs.MethodsOSLDs (N = 240) were irradiated on a cobalt‐60 beam in different step sizes until they reached an accumulated dose of 50 Gy. Between irradiations they were bleached using light sources of different wavelengths: the Imaging and Radiation Oncology Core (IROC) bleaching system (our control); monochromatic red, green, yellow, and blue lights; and a polychromatic white light. Sensitivity and linearity‐based correction factors were determined as a function of dose step‐size. The rate of signal removal from different light sources was characterized by sampling these OSLDs at various time points during their bleaching process. Relative doses were calculated according to the American Association of Physicists in Medicine Task Group‐191. Signal repopulation was investigated by irradiating OSLDs (N = 300) to various delivered doses of 2, 10, 20, 30, 40, and 50 Gy in a single fraction, bleached with one of the colors, and read over time. Fractionation effects were evaluated by irradiating OSLDs up to 30 Gy in different size steps. After reading, the OSLDs were bleached following IROC protocol. OSLDs (N = 40) received irradiations in 5, 10, 15, 30 Gy fractions until they had an accumulated dose of 30 Gy; The sensitivity response of these OSLDs was compared with reference OSLDs that had no accumulated dose.ResultsLight sources with polychromatic spectrums (IROC and white) bleached OSLDs faster than did sources with monochromatic spectra. Polychromatic light sources (white light and IROC system) provided the greatest dose stability for OSLDs that had larger amounts of accumulated dose. Signal repopulation was related to the choice of bleaching light source, timing of bleaching, and amount of accumulated dose. Changes to relative dosimetry were more pronounced in OSLDs that received larger fractions. At 5‐Gy fractions and above, all OSLDs had heightened sensitivity, with OSLDs exposed to 30‐Gy fractions being 6.4% more sensitive than reference dosimeters.ConclusionsThe choice of bleaching light plays a role in how fast an OSLD is bleached and how much accumulated dose an OSLD can be exposed to while maintaining stable signal sensitivity. We have expanded upon investigations into signal repopulation to show that bleaching light plays a role in the migration of deep traps to dosimetric traps after bleaching. Our research concludes that the bleaching light source and fractionation need to be considered when reusing OSLD.
Novel radiation quality metrics accounting for proton energy spectra for RBE proton models
Authors: Kalholm Fredrik , Toma‐Dasu Iuliana , Traneus Erik , Bassler Niels 
Published: June 2024

AbstractBackgroundFor proton therapy, a relative biological effectiveness (RBE) of 1.1 is widely applied clinically. However, due to abundant evidence of variable RBE in vitro, and as suggested in studies of patient outcomes, RBE might increase by the end of the proton tracks, as described by several proposed variable RBE models. Typically, the dose averaged linear energy transfer () has been used as a radiation quality metric (RQM) for these models. However, the optimal choice of RQM has not been fully explored.PurposeThis study aims to propose novel RQMs that effectively weight protons of different energies, and assess their predictive power for variable RBE in proton therapy. The overall objective is to identify an RQM that better describes the contribution of individual particles to the RBE of proton beams.MethodsHigh‐throughput experimental set‐ups of in vitro cell survival studies for proton RBE determination are simulated utilizing the SHIELD‐HIT12A Monte Carlo particle transport code. For every data point, the proton energy spectra are simulated, allowing the calculation of novel RQMs by applying different power levels to the spectra of LET or effective () values. A phenomenological linear‐quadratic‐based RBE model is then applied to the in vitro data, using various RQMs as input variables, and the model performance is evaluated by root‐mean‐square‐error (RMSE) for the logarithm of cell surviving fractions of each data point.ResultsIncreasing the power level, that is, putting an even higher weight on higher LET particles when constructing the RQM is generally associated with an increased model performance, with dose averaged (i.e., dose averaged cubed LET, ) resulting in a RMSE value 0.31, compared to 0.45 for a model based on (linearly weighted) , with similar trends also observed for track averaged and ‐based RQMs.ConclusionsThe results indicate that improved proton variable RBE models can be constructed assuming a non‐linear RBE(LET) relationship for individual protons. If similar trends hold also for an in vitro‐environment, variable RBE effects are likely better described by or tracked averaged cubed LET (), or corresponding ‐based RQM, rather than linearly weighted or which is conventionally applied today.
Use of a pressure sensor array for multifunctional patient monitoring in radiotherapy: A feasibility study
Authors: Jeon Hosang , Kim Dong Woon , Joo Ji Hyeon , Park Dahl , Kim Wontaek , Nam Jiho , Kim Dong Hyeon , Ki Yongkan 
Published: June 2024

AbstractBackgroundModern radiotherapeutic techniques, such as intensity‐modulated radiation therapy or stereotactic body radiotherapy, require high‐dose delivery precision. However, the precise localization of tumors during patient respiration remains a challenge. Therefore, it is essential to investigate effective methods for monitoring respiration to minimize potential complications. Despite several systems currently in clinical use, there are drawbacks, including the complexity of the setup, the discomfort to the patient, and the high cost.PurposeThis study investigated the feasibility of using a novel pressure sensor array (PSA) as a tool to monitor respiration during radiotherapy treatments. The PSA was positioned between the treatment couch and the back of the patient lying on it and was intended to overcome some limitations of current methods. The main objectives included assessing the PSA's capability in monitoring respiratory behavior and to investigate prospective applications that extend beyond respiratory monitoring.MethodsA PSA with 31 pressure‐sensing elements was used in 12 volunteers. The participants were instructed to breathe naturally while lying on a couch without any audio or visual guidance. The performance of the PSA was compared to that of a camera‐based respiratory monitoring system (RPM, Varian, USA), which served as a reference. Several metrics, including pressure distribution, weight sensitivity, and correlations between PSA and RPM signals, were analyzed. The PSA's capacity to provide information on potential applications related to patient stability was also investigated.ResultsThe linear relationship between the weight applied to the PSA and its output was demonstrated in this study, confirming its sensitivity to pressure changes. A comparison of PSA and RPM curves revealed a high correlation coefficient of 0.9391 on average, indicating consistent respiratory cycles. The PSA also effectively measured the weight distribution at the volunteer's back in real‐time, which allows for monitoring the patient's movements during the radiotherapy.ConclusionPSA is a promising candidate for effective respiratory monitoring during radiotherapy treatments. Its performance is comparable to the established RPM system, and its additional capabilities suggest its multifaceted utility. This paper shows the potential use of PSA for patient monitoring in radiotherapy and suggests possibilities for further research, including performance comparisons with other existing systems and real‐patient applications with respiratory training.
Presentation of microstructural diffusion components by color schemes in abdominal organs
Authors: Wittsack Hans‐Jörg , Thiel Thomas Andreas , Valentin Birte , Stabinska Julia , Benkert Thomas , Schimmöller Lars , Antoch Gerald , Ljimani Alexandra 
Published: June 2024

AbstractPurposeDevelopment of a color scheme representation to facilitate the interpretation of tri‐exponential DWI data from abdominal organs, where multi‐exponential behavior is more pronounced.MethodsMulti‐exponential analysis of DWI data provides information about the microstructure of the tissue under study. The tri‐exponential signal analysis generates numerous parameter images that are difficult to analyze individually. Summarized color images can simplify at‐a‐glance analysis. A color scheme was developed in which the slow, intermediate, and fast diffusion components were each assigned to a different red, green, and blue color channel. To improve the appearance of the image, histogram equalization, gamma correction, and white balance were used, and the processing parameters were adjusted. Examples of the resulting color maps of the diffusion fractions of healthy and pathological kidney and prostate are shown.ResultsThe color maps obtained by the presented method show the merged information of the slow, intermediate, and fast diffusion components in a single view. A differentiation of the different fractions becomes clearly visible. Fast diffusion regimes, such as in the renal hilus, can be clearly distinguished from slow fractions, such as in dense tumor tissue.ConclusionCombining the diffusion information from tri‐exponential DWI analysis into a single color image allows for simplified interpretation of the diffusion fractions. In the future, such color images may provide additional information about the microstructural nature of the tissue under study.
Recovering high‐quality fiber orientation distributions from a reduced number of diffusion‐weighted images using a model‐driven deep learning architecture
Authors: Bartlett Joseph J. , Davey Catherine E. , Johnston Leigh A. , Duan Jinming 
Published: June 2024

AbstractPurposeThe aim of this study was to develop a model‐based deep learning architecture to accurately reconstruct fiber orientation distributions (FODs) from a reduced number of diffusion‐weighted images (DWIs), facilitating accurate analysis with reduced acquisition times.MethodsOur proposed architecture, Spherical Deconvolution Network (SDNet), performed FOD reconstruction by mapping 30 DWIs to fully sampled FODs, which have been fit to 288 DWIs. SDNet included DWI‐consistency blocks within the network architecture, and a fixel‐classification penalty within the loss function. SDNet was trained on a subset of the Human Connectome Project, and its performance compared with FOD‐Net, and multishell multitissue constrained spherical deconvolution.ResultsSDNet achieved the strongest results with respect to angular correlation coefficient and sum of squared errors. When the impact of the fixel‐classification penalty was increased, we observed an improvement in performance metrics reliant on segmenting the FODs into the correct number of fixels.ConclusionInclusion of DWI‐consistency blocks improved reconstruction performance, and the fixel‐classification penalty term offered increased control over the angular separation of fixels in the reconstructed FODs.
Viscosity‐coupled curing simulation model for L‐shaped composites considering flow and compaction
Authors: Ye Yaoyao , Zhang Fan , Chen Qisen , Xu Qiang , Ke Yinglin 
Published: June 2024

AbstractComputational methods provide effective tools for the prediction of the curing behavior of composites, especially for large‐scale complex composite structures. The flow‐compaction analysis during curing receives insufficient attention in current studies. In this work, an integrated framework considering the heat transfer, the cross‐linking reaction, the flow and compaction, and the stress–strain module is established. A comprehensive resin flow termination criterion is proposed. L‐shaped composites with a stacking layer of [45/90/−45/0]s were fabricated, and the good agreement between the experimentally measured and the numerically predicted contour data validated the current model. Compared with Hubert's model, the prediction accuracy of the thickness and fiber volume content increases by 4.24% and 3.92%, respectively. Correlation analysis between the fiber volume ratio predicted by numerical methods and experimental results (94% for this method, −41% for Hubert's model) demonstrates the well‐capture of nonuniform fiber distribution in curved composites for the current strategy. The overall framework provides an accurate and promising tool for the prediction of the curing behavior of complex composite components.Highlights
An integrated numerical methodology is proposed considering the resin flow and compaction.
The viscosity‐temperature coupled feature of resin is considered in the permeability coefficients.
A comprehensive resin flow termination criterion is proposed for an accurate prediction.
The resin content, thickness, and spring‐in angle of L‐shaped laminates are characterized.
The good correlation between the experimental and numerical results validates this method.
Compared with the model proposed by Hubert, the prediction accuracy improves.
Data blanks by design: Intellectual property and restrictions on genetic diversity assessments of the maize standing crop in the USA Upper Midwest
Authors: McCluskey Cathleen A. , Tracy William F. 
Published: June 2024

Societal Impact StatementAll US commercial maize (Zea mays) is a single race, “Corn Belt Dent,” and its genetic base has been in decline for at least 40 years. Independent genotyping can only be conducted after patent and licensing restrictions have expired, a period of 20 years. These restrictions also impede a molecular based assessment of the standing crop by the United States Department of Agriculture (USDA) as recommended by experts. Data blanks about landscape vulnerability put farmers at risk of crop failure and the public at risk of food insecurity. Understanding maize diversity experts' perspectives and analysis helps describe the contours of these data blanks and inform policy recommendations.Summary

Recommendations by the Maize Crop Germplasm Committee to the United States Department of Agriculture (USDA) for a molecular based vulnerability assessment on the US standing maize (Zea mays) crop have not been acted on because of intellectual property and licensing restrictions. This research explores maize diversity experts' access to data and perceptions and analysis of the standing crop.
The data come from semi‐structured interviews conducted with 44 maize diversity experts in the public and private sectors.
Experts explain that genetic data blanks restrict non‐industry research, describe public sector concerns that standing diversity is narrow(ing), and find historic sources of pedigree data in Plant Variety Protection and patent records are no longer reliable. Some interviewees perceive that industry monitoring of standing diversity is in their best financial interest. Industry participants describe concentration in US maize allows them to control diversity over time, while public researchers discuss efficiency of scale narrowing genetic diversity and global concentration spreading this trend.
Knowledge gaps about genetic diversity in US commercial maize are designed through patents, contracts, non‐disclosure agreements, and confidentiality agreements by patent holders who do not want their inbred lines genotyped by competitors. This restricts research and knowledge flow about genetic information into public networks. The Maize Crop Germplasm Committee is a node for knowledge flow; however, the lack of mechanisms for action suggests it is performative. We recommend all protections used on seed include exemptions for research, breeding, and seed saving; an independent assessment of how industry monitors standing diversity; and a molecular analysis of the standing crop conducted by the USDA.
The strongest protein binder is surprisingly labile
Authors: Fernandez‐Calvo Alba , Reifs Antonio , Saa Laura , Cortajarena Aitziber L. , De Sancho David , Perez‐Jimenez Raul 
Published: June 2024

AbstractBacterial adhesins are cell‐surface proteins that anchor to the cell wall of the host. The first stage of infection involves the specific attachment to fibrinogen (Fg), a protein found in human blood. This attachment allows bacteria to colonize tissues causing diseases such as endocarditis. The study of this family of proteins is hence essential to develop new strategies to fight bacterial infections. In the case of the Gram‐positive bacterium Staphylococcus aureus, there exists a class of adhesins known as microbial surface components recognizing adhesive matrix molecules (MSCRAMMs). Here, we focus on one of them, the clumping factor A (ClfA), which has been found to bind Fg through the dock‐lock‐latch mechanism. Interestingly, it has recently been discovered that MSCRAMM proteins employ a catch‐bond to withstand forces exceeding 2 nN, making this type of interaction as mechanically strong as a covalent bond. However, it is not known whether this strength is an evolved feature characteristic of the bacterial protein or is typical only of the interaction with its partner. Here, we combine single‐molecule force spectroscopy, biophysical binding assays, and molecular simulations to study the intrinsic mechanical strength of ClfA. We find that despite the extremely high forces required to break its interactions with Fg, ClfA is not by itself particularly strong. Integrating the results from both theory and experiments we dissect contributions to the mechanical stability of this protein.
Targeting the protein folding transition state by mutation: Large scale (un)folding rate accelerations without altering native stability
Authors: Campos Luis A. , Muñoz Victor 
Published: June 2024

AbstractProteins are constantly undergoing folding and unfolding transitions, with rates that determine their homeostasis in vivo and modulate their biological function. The ability to optimize these rates without affecting overall native stability is hence highly desirable for protein engineering and design. The great challenge is, however, that mutations generally affect folding and unfolding rates with inversely complementary fractions of the net free energy change they inflict on the native state. Here we address this challenge by targeting the folding transition state (FTS) of chymotrypsin inhibitor 2 (CI2), a very slow and stable two‐state folding protein with an FTS known to be refractory to change by mutation. We first discovered that the CI2's FTS is energetically taxed by the desolvation of several, highly conserved, charges that form a buried salt bridge network in the native structure. Based on these findings, we designed a CI2 variant that bears just four mutations and aims to selectively stabilize the FTS. This variant has >250‐fold faster rates in both directions and hence identical native stability, demonstrating the success of our FTS‐centric design strategy. With an optimized FTS, CI2 also becomes 250‐fold more sensitive to proteolytic degradation by its natural substrate chymotrypsin, and completely loses its activity as inhibitor. These results indicate that CI2 has been selected through evolution to have a very unstable FTS in order to attain the kinetic stability needed to effectively function as protease inhibitor. Moreover, the CI2 case showcases that protein (un)folding rates can critically pivot around a few key residues‐interactions, which can strongly modify the general effects of known structural factors such as domain size and fold topology. From a practical standpoint, our results suggest that future efforts should perhaps focus on identifying such critical residues‐interactions in proteins as best strategy to significantly improve our ability to predict and engineer protein (un)folding rates.