bluuebunny/crossref_metadata_2025_split huggingface dataset:
Rhodium concave nanocubes and nanoplates as deep‐UV resonant SERS platform
Authors: Kumar Govind , Soni Ravi Kant 
Published: July 2022

AbstractWe report on the detection of molecules at the trace level using deep‐UV surface‐enhanced Raman spectroscopy (SERS) on shape‐anisotropic rhodium (Rh) nanoparticles. Rh nanoparticles of three distinct morphologies, triangular nanoplates, rectangular nanoplates, and concave nanocubes, that exhibit strong plasmon resonances in the UV range were exploited for deep‐UV SERS. With an enhancement factor greater than 105, Rh concave nanocubes demonstrate the highest SERS activity, which is well corroborated by electric field distribution maps calculated using finite‐difference time‐domain (FDTD) simulations. The deep‐UV SERS substrate based on Rh concave nanocubes enables the detection of trace levels of explosive molecules such as p‐nitrobenzoic acid and 2,4‐dinitrotoluene with detection limits of 10−10 M and 10−7 M, respectively, and ammonium nitrate with a detection limit of 10−12 M. Deep‐UV SERS detection of explosive molecules on a low‐cost and simple‐to‐fabricate Rh nanoparticles substrate holds tremendous potential for the SERS‐based identification of hazardous materials.
Existence of solutions for critical Fractional FitzHugh–Nagumo type systems
Authors: Torres Ledesma César E. 
Published: July 2022

AbstractIn this paper we study the existence of radially symmetric solutions for a Fractional FitzHugh–Nagumo type systems

where , , denotes the fractional Laplacian operator and is a continuous function which is allowed to have critical growth: polynomial in case and exponential if and . We transform the system into an equation with a nonlocal term. We find a critical point of the corresponding energy functional defined in the space of functions with norm endowed by a scalar product that takes into account such nonlocal term. For that matter, and due to the lack of compactness, we deal with weak convergent minimizing sequences and sequences of Lagrange multipliers of an action minima problem.
Poly (3‐hexylthiophene) (P3HT) Crystalsomes: Tiling 1D Polymer Crystals on a Spherical Surface
Authors: Staub Mark Clyde , Yu Shichen , Li Christopher Yuren 
Published: July 2022

AbstractPolymer crystalsomes are a class of hollow crystalline polymer nanoparticles with shells formed by single crystals with broken translational symmetry. They have shown intriguing mechanical, thermal, and biomedical properties associated with spherical packing. Previously reported crystalsomes are formed by quasi‐2D lamellae which can readily tile on a spherical surface. In this work, the formation of polymer crystalsomes formed by 1D polymer crystals is reported. Poly (3‐hexylthiophene) (P3HT) is chosen as the model polymer because of its 1D growth habit. P3HT crystalsomes are successfully fabricated using a miniemulsion solution crystallization method, as confirmed by scanning electron microscopy and transmission electron microscopy. X‐ray diffraction (XRD) and selected area electron diffraction experiments confirm that P3HT crystallized into a Form I crystal structure. XRD, differential scanning calorimetry and UV–Vis results reveal curvature‐dependent structural, thermal and electro‐optical properties.
The effects of the interactions of STAT4 rs7574865 with HBV mutations on the risk of hepatocellular carcinoma
Authors: Yang Chou , Chen Haitao , Zhou Bin , Yin Jianhua , Cao Guangwen , Hou Jinlin , Jiang Deke 
Published: July 2022

AbstractSignal transducer and activator of transcription 4 (STAT4) is closely related to liver diseases and affects the processes of inflammation and carcinogenesis by regulating immune responses. A single‐nucleotide polymorphism rs7574865 (T > G) in STAT4 has been reported to be associated with the risk of hepatocellular carcinoma (HCC). In addition, hepatitis B virus (HBV) mutations are crucial risk factors for HBV‐induced HCC. However, the effects of the interactions of STAT4 rs7574865 with HBV mutations on the risk of HCC remain unknown. Rs7574865 was genotyped in 846 healthy controls (HCs), 968 chronic hepatitis B (CHB) subjects, 316 liver cirrhosis (LC) subjects and 1021 HCC subjects using Sequenom MassArray. HBV mutations were detected via direct sequencing. Multivariate logistic regression analysis was used to evaluate the effects of the interactions of STAT4 rs7574865 with HBV mutations on the risk of HCC. We found that the rs7574865 TT genotype was significantly associated with HBeAg seroconversion (TT vs. GG, p = 0.012; TT vs. GT, p = 0.033). The rs7574865 GG genotype was significantly associated with increased risks of CHB (p = 0.048), LC (p = 0.005) and HCC (p < 0.001). The interaction term between rs7574865 and HBV C1913A significantly increased the risk of progression from CHB to HCC (p = 0.038), while the interaction term between rs7574865 and HBV T1674C significantly increased the risk of progression from LC to HCC (p = 0.023). STAT4 rs7574865 is significantly associated with the risks of CHB, LC and HCC. The interactions of rs7574865 with HBV C1913A and T1674C mutations significantly increase the risk of HCC, which have the potential to identify HBV‐infected individuals who tend to progress from CHB or LC to HCC.
Effect of subject motion and gantry rotation speed on image quality and dose delivery in CT‐guided radiotherapy
Authors: Hrinivich William T. , Chernavsky Nicole E. , Morcos Marc , Li Taoran , Wu Pengwei , Wong John , Siewerdsen Jeffrey H. 
Published: July 2022

AbstractPurposeTo investigate the effects of subject motion and gantry rotation speed on computed tomography (CT) image quality over a range of image acquisition speeds for fan‐beam (FB) and cone‐beam (CB) CT scanners, and quantify the geometric and dosimetric errors introduced by FB and CB sampling in the context of adaptive radiotherapy.MethodsImages of motion phantoms were acquired using four CT scanners with gantry rotation speeds of 0.5 s/rotation (denoted FB‐0.5), 1.9 s/rotation (FB‐1.9), 16.6 s/rotation (CB‐16.6), and 60.0 s/rotation (CB‐60.0). A phantom presenting various tissue densities undergoing motion with 4‐s period and ranging in amplitude from ±0.5 to ±10.0 mm was used to characterize motion artifacts (streaks), motion blur (edge‐spread function, ESF), and geometric inaccuracy (excursion of insert centroids and distortion of known shape). An anthropomorphic abdomen phantom undergoing ±2.5‐mm motion with 4‐s period was used to simulate an adaptive radiotherapy workflow, and relative geometric and dosimetric errors were compared between scanners.ResultsAt ±2.5‐mm motion, phantom measurements demonstrated mean ± SD ESF widths of 0.6 ± 0.0, 1.3 ± 0.4, 2.0 ± 1.1, and 2.9 ± 2.0 mm and geometric inaccuracy (excursion) of 2.7 ± 0.4, 4.1 ± 1.2, 2.6 ± 0.7, and 2.0 ± 0.5 mm for the FB‐0.5, FB‐1.9, CB‐16.6, and CB‐60.0 scanners, respectively. The results demonstrated nonmonotonic trends with scanner speed for FB and CB geometries. Geometric and dosimetric errors in adaptive radiotherapy plans were largest for the slowest (CB‐60.0) scanner and similar for the three faster systems (CB‐16.6, FB‐1.9, and FB‐0.5).ConclusionsClinically standard CB‐60.0 demonstrates strong image quality degradation in the presence of subject motion, which is mitigated through faster CBCT or FBCT. Although motion blur is minimized for FB‐0.5 and FB‐1.9, such systems suffer from increased geometric distortion compared to CB‐16.6. Each system reflects tradeoffs in image artifacts and geometric inaccuracies that affect treatment delivery/dosimetric error and should be considered in the design of next‐generation CT‐guided radiotherapy systems.
A streak artifact reduction algorithm in sparse‐view CT using a self‐supervised neural representation
Authors: Kim Byeongjoon , Shim Hyunjung , Baek Jongduk 
Published: July 2022

AbstractPurposeSparse‐view computed tomography (CT) has been attracting attention for its reduced radiation dose and scanning time. However, analytical image reconstruction methods suffer from streak artifacts due to insufficient projection views. Recently, various deep learning‐based methods have been developed to solve this ill‐posed inverse problem. Despite their promising results, they are easily overfitted to the training data, showing limited generalizability to unseen systems and patients. In this work, we propose a novel streak artifact reduction algorithm that provides a system‐ and patient‐specific solution.MethodsMotivated by the fact that streak artifacts are deterministic errors, we regenerate the same artifacts from a prior CT image under the same system geometry. This prior image need not be perfect but should contain patient‐specific information and be consistent with full‐view projection data for accurate regeneration of the artifacts. To this end, we use a coordinate‐based neural representation that often causes image blur but can greatly suppress the streak artifacts while having multiview consistency. By employing techniques in neural radiance fields originally proposed for scene representations, the neural representation is optimized to the measured sparse‐view projection data via self‐supervised learning. Then, we subtract the regenerated artifacts from the analytically reconstructed original image to obtain the final corrected image.ResultsTo validate the proposed method, we used simulated data of extended cardiac‐torso phantoms and the 2016 NIH‐AAPM‐Mayo Clinic Low‐Dose CT Grand Challenge and experimental data of physical pediatric and head phantoms. The performance of the proposed method was compared with a total variation‐based iterative reconstruction method, naive application of the neural representation, and a convolutional neural network‐based method. In visual inspection, it was observed that the small anatomical features were best preserved by the proposed method. The proposed method also achieved the best scores in the visual information fidelity, modulation transfer function, and lung nodule segmentation.ConclusionsThe results on both simulated and experimental data suggest that the proposed method can effectively reduce the streak artifacts while preserving small anatomical structures that are easily blurred or replaced with misleading features by the existing methods. Since the proposed method does not require any additional training datasets, it would be useful in clinical practice where the large datasets cannot be collected.
Learning low‐dose CT degradation from unpaired data with flow‐based model
Authors: Liu Xuan , Liang Xiaokun , Deng Lei , Tan Shan , Xie Yaoqin 
Published: July 2022

AbstractBackgroundThere has been growing interest in low‐dose computed tomography (LDCT) for reducing the X‐ray radiation to patients. However, LDCT always suffers from complex noise in reconstructed images. Although deep learning‐based methods have shown their strong performance in LDCT denoising, most of them require a large number of paired training data of normal‐dose CT (NDCT) images and LDCT images, which are hard to acquire in the clinic. Lack of paired training data significantly undermines the practicability of supervised deep learning‐based methods. To alleviate this problem, unsupervised or weakly supervised deep learning‐based methods are required.PurposeWe aimed to propose a method that achieves LDCT denoising without training pairs. Specifically, we first trained a neural network in a weakly supervised manner to simulate LDCT images from NDCT images. Then, simulated training pairs could be used for supervised deep denoising networks.MethodsWe proposed a weakly supervised method to learn the degradation of LDCT from unpaired LDCT and NDCT images. Concretely, LDCT and normal‐dose images were fed into one shared flow‐based model and projected to the latent space. Then, the degradation between low‐dose and normal‐dose images was modeled in the latent space. Finally, the model was trained by minimizing the negative log‐likelihood loss with no requirement of paired training data. After training, an NDCT image can be input to the trained flow‐based model to generate the corresponding LDCT image. The simulated image pairs of NDCT and LDCT can be further used to train supervised denoising neural networks for test.ResultsOur method achieved much better performance on LDCT image simulation compared with the most widely used image‐to‐image translation method, CycleGAN, according to the radial noise power spectrum. The simulated image pairs could be used for any supervised LDCT denoising neural networks. We validated the effectiveness of our generated image pairs on a classic convolutional neural network, REDCNN, and a novel transformer‐based model, TransCT. Our method achieved mean peak signal‐to‐noise ratio (PSNR) of 24.43dB, mean structural similarity (SSIM) of 0.785 on an abdomen CT dataset, mean PSNR of 33.88dB, mean SSIM of 0.797 on a chest CT dataset, which outperformed several traditional CT denoising methods, the same network trained by CycleGAN‐generated data, and a novel transfer learning method. Besides, our method was on par with the supervised networks in terms of visual effects.ConclusionWe proposed a flow‐based method to learn LDCT degradation from only unpaired training data. It achieved impressive performance on LDCT synthesis. Next, we could train neural networks with the generated paired data for LDCT denoising. The denoising results are better than traditional and weakly supervised methods, comparable to supervised deep learning methods.
Choice of computational protocol for carbon‐lithium spin–spin coupling constants 1JCLi
Authors: Karpov Valerii V. , Antonov Alexander S. , Tupikina Elena Yu. 
Published: July 2022

AbstractIn this work, we tested various computational schemes for calculations of 1JCLi constants with a high accuracy. On the example of six organolithium reagents (phenyllithium monomer and dimer, monomer s‐butyllithium, monomers of 1‐ and 2‐lithionaphthalenes, and a methyllithium tetramer), the following aspects are discussed: (i) the role of a model system geometry, (ii) influence of solvent effects, and (iii) the choice of a functional and basis set. Practical recommendations for calculation of 1JCLi with an accuracy ±2 Hz are formulated.
The impact of interprofessional education on students' current and desired competence in diabetes care
Authors: Kangas Sanna , Rintala Tuula‐Maria , Hannula Päivi , Jämsen Esa , Kannisto Ritva , Paavilainen Eija , Jaatinen Pia 
Published: July 2022

AbstractAimTo explore the impact of interprofessional education (IPE) on undergraduate nursing and medical students' knowledge, competence and targeted competence in diabetes care.DesignMixed methods design.MethodsA voluntary IPE course of diabetes management was organized for nursing (n = 15) and medical (n = 15) students, who performed a diabetes knowledge test and self‐evaluation of diabetes competence before and after the course and were compared with non‐participating students. The participating students' focus‐group interviews were analysed using inductive content analysis.ResultsThe IPE course improved nursing students' diabetes knowledge and self‐evaluated competence among nursing and medical students. The baseline differences in self‐evaluated competence between the groups disappeared. The non‐participating students evaluated their competence higher than the participants, though they scored lower or equally in the knowledge test. In conclusion, IPE showed potential in increasing students' self‐evaluated competence, motivation to learn more and nursing students' diabetes knowledge, offering better prospects for future interprofessional diabetes management.
The talus of the pre‐Hispanic population from Punta Azul (El Hierro, Canary Islands): Variability and sexual dimorphism of nonmetric traits
Authors: Cockerill Samuel James , Ordóñez Alejandra C. , Guamán‐Chulunchana Richard G. , Serrano Javier G. , Fregel Rosa , Díaz‐Pérez Clara , González‐Reimers Emilio , Arnay‐de‐la‐Rosa Matilde 
Published: July 2022

AbstractThe aim of this study was assessing the prevalence ofos trigonum, talo‐calcaneal facets, and squatting facet variations among pre‐Hispanic individuals (around 940 ± 30 bp) placed in the collective burial cave of Punta Azul (El Hierro, Canary Islands), and to assess whether prevalence differed among sexes. A total of 149 tali (70 right and 79 left) belonging to adult individuals were found in a comingled context. Sex determination was achieved as follows: genetic sexing of a subsample of 35 tali was assessed using paleogenomic procedures. Anthropometric measurements of the genetically sexed bones were used to calculate an accurate discriminant function that was later applied to the remaining 114 tali. We observed marked differences in theos trigonumpattern among male and female tali, whereas no relevant differences were observed regarding the other two traits. A very high prevalence of squatting facets was observed in both sexes, higher than the reported frequencies for other population groups. The summarized conclusions in this study are the following: (a) the high prevalence of the squatting facets observed in both males and females could indicate the performance of a similar activity that requires a squatting position, such as shellfishing. (b) We observed a predominance of the type C talo‐calcaneal facet configuration among the population that indicates a maximal mobility of the talar joint, well adapted to displacement and/or activities such as goat herding in the steep landscape of El Hierro. (c) The statistically differentos trigonumpattern among sexes may suggest a greater activity associated to jumping and climbing among males, possibly related to goat herding in the steep landscape of the island of El Hierro.
ShadeTreeAdvice methodology: Guiding tree‐species selection using local knowledge
Authors: Rigal Clément , Wagner Sigrun , Nguyen Mai Phuong , Jassogne Laurence , Vaast Philippe 
Published: July 2022

Abstract

Selection of shade tree species for agroforestry systems must take the complexity of these systems into account. Tree species selection should maximize the provision of ecosystem services while minimizing disservices. Selected species must be adapted to local agroecological conditions and cater to farmers' needs, while considering their preferences and constraints.

The ShadeTreeAdvice methodology was developed to support said selection process using farmers' local ecological knowledge. It provides the steps to rapidly identify tree species and evaluate their impacts on a range of locally important ecosystem services. Results are uploaded to a decision support tool to tailor tree species recommendations to individual farmers' needs (www.shadetreeadvice.org). During the 5 year timeframe between 2016 and 2020, eight studies following this methodology were conducted in various coffee and cocoa growing regions across Africa, Asia and Central America.

This article looks back at these studies to synthesize their findings and evaluate the methodology. We identified similarities in the use of tree species across different study areas, notably regarding leguminous and fruit tree species. We showed that the method was efficient to evaluate tree species' impacts on soil and climate regulation, crop production, and economic benefits. It was less efficient for evaluating impacts related to incidence of pests and diseases, often associated with knowledge gaps. The method also successfully allowed investigating the links between LEK and socio‐economic groups or environmental factors.

Furthermore, we suggest a series of improvements in the methodology for future studies. These improvements include (i) broadening the scope of studies beyond tree species provision of ecosystem services to include tree species impact on farming practices; (ii) allowing the comparison of tree performances in agroforestry systems versus in full sun; (iii) providing a clear pathway for validation of the results; (iv) using tree species' functional traits to generalize the results.

Read the free Plain Language Summary for this article on the Journal blog.
Robust colloidal photonic crystal polymer films for anticounterfeiting
Authors: Xiang Xiaoman , Tang Qiyue , Dan Li , Shang Jingyu , Xia Hongbo 
Published: July 2022

AbstractPhotonic crystals (PCs) with brilliant structural colors have attracted considerable attention in the field of display and anti‐counterfeiting. Here, free‐standing PC films with antistretching property and invariant brilliant structural colors during compression and deformation were prepared, by combining SiO2 PCs (nSiO2 = 1.46) into polyether sulfone (PES) matrix which has higher refractive index (nPES = 1.68). The excellent physical and chemical stability of the PC films are ascribed to the inherent robust properties of PES resin. In fact, during the stretching, compressing, friction, and bending process, the film retains its structure and optical integrity due to its stable ordered array with constant lattice spacing and effective refractive index. In addition, the appropriate index difference not only contributes to bright structural color, but also enables the PC films to have high transparency. Thus, the pattern in the film can be switched between invisible and visible state under the transformation of weak and strong light. Thereby, the film has great potential in the application of anti‐counterfeiting.
Epistatic modifiers influence the expression of continual flowering in strawberry
Authors: Cockerton Helen Maria , Nellist Charlotte Florence , Hytönen Timo , Litthauer Suzanne , Hopson Katie , Whitehouse Adam , Sobczyk Maria , Harrison Richard Jonathan 
Published: July 2022

Society Impact StatementUntil the 1970s, the majority of commercial strawberry varieties produced a single bloom of flowers. However, continuously flowering, everbearing strawberries are now routinely cultivated and use is increasing. Indeed, introgression of the everbearing flowering trait can lead to economic benefits for growers through the production of a continual crop from the same plant. Genetically guided improvement has the power to streamline everbearing generation. As such, the genetic markers reported here can help to identify everbearing individuals at an early time point in the breeding process. Furthermore, these markers can help to improve the predictions of progeny segregation ratios.Summary

Previous work within the community led to the identification of a single dominant allele that controls the everbearing trait. However, frequent observations have indicated that crosses do not segregate in a Mendelian fashion, as would be expected for a trait controlled by a single dominant gene. Therefore, it was hypothesised that one or more unidentified epistatic alleles interact with the major gene.
A genome‐wide association study (GWAS) was conducted on 587 June bearers and 207 everbearers to assess the genetic components associated with flowering habit. The segregation ratios of parental strawberry lines with known phenotypes were used to validate the identified alleles.
Three loci including the known major FaPFRU locus and two epistatic modifiers were identified. These modifiers function as enhancers of the everbearing trait in individuals containing a single copy of the FaPFRU everbearing allele and appear to be functionally redundant. Principally, heterozygous individuals required the presence of two modifying alleles in order to allow expression of the everbearing trait.
Inclusion of the epistatic alleles improved the prediction of everbearing segregation ratios; beyond that of a single allele model, however, a large proportion of the variation remained unexplained. Future work should identify the additional repressor and enhancer modifiers not identified here. Discovering the genetic components controlling the everbearing trait can enable genetic informed strawberry improvement.