bluuebunny/crossref_metadata_2025_split huggingface dataset:
Elucidating Microstructural Alterations in Neurodevelopmental Disorders: Application of Advanced Diffusion‐Weighted Imaging in Children With Rasopathies
Authors: Plank Julia R. , Gozdas Elveda , Dai Erpeng , McGhee Chloe A. , Raman Mira M. , Green Tamar 
Published: December 2024

ABSTRACTNeurodevelopmental disorders (NDDs) can severely impact functioning yet effective treatments are limited. Greater insight into the neurobiology underlying NDDs is critical to the development of successful treatments. Using a genetics‐first approach, we investigated the potential of advanced diffusion‐weighted imaging (DWI) techniques to characterize the neural microstructure unique to neurofibromatosis type 1 (NF1) and Noonan syndrome (NS). In this prospective study, children with NF1, NS, and typical developing (TD) were scanned using a multi‐shell DWI sequence optimized for neurite orientation density and dispersion imaging (NODDI) and diffusion kurtosis imaging (DKI). Region‐of‐interest and tract‐based analysis were conducted on subcortical regions and white matter tracts. Analysis of covariance, principal components, and linear discriminant analysis compared between three groups. 88 participants (Mage = 9.36, SDage = 2.61; 44 male) were included: 31 NS, 25 NF1, and 32 TD. Subcortical regions differed between NF1 and NS, particularly in the thalamus where the neurite density index (NDI; estimated difference 0.044 [95% CI: −0.034, 0.053], d = 2.36), orientation dispersion index (ODI; estimate 0.018 [95% CI: 0.010, 0.026], d = 1.39), and mean kurtosis (MK; estimate 0.049 [95% CI: 0.025, 0.072], d = 1.39) were lower in NF1 compared with NS (all p < 0.0001). Reduced NDI was found in NF1 and NS compared with TD in all 39 white matter tracts investigated (p < 0.0001). Reduced MK was found in a majority of the tracts in NF1 and NS relative to TD, while fewer differences in ODI were observed. The middle cerebellar peduncle showed lower NDI (estimate 0.038 [95% CI: 0.021, 0.056], p < 0.0001) and MK (estimate 0.057 [95% CI: 0.026, 0.089], p < 0.0001) in NF1 compared to NS. Multivariate analyses distinguished between groups using NDI, ODI, and MK measures. Principal components analysis confirmed that the clinical groups differ most from TD in white matter tract‐based NDI and MK, whereas ODI values appear similar across the groups. The subcortical regions showed several differences between NF1 and NS, to the extent that a linear discriminant analysis could classify participants with NF1 with an accuracy rate of 97%. Differences in neural microstructure were detected between NF1 and NS, particularly in subcortical regions and the middle cerebellar peduncle, in line with pre‐clinical evidence. Advanced DWI techniques detected subtle alterations not found in prior work using conventional diffusion tensor imaging.
Deep level transient spectroscopy: Tracing interface and bulk trap‐induced degradation in AlGaN/GaN‐heterostructure based devices
Authors: Deng Kexin , Huang Sen , Wang Xinhua , Yao Yixu , Yang Yang , Yu Li , Pei Yaoyao , An Jiayi , Jiang Qimeng , Liu Xinyu , Yang Song , Chen Kevin J. 
Published: December 2024

AbstractThe exceptional physical properties of gallium nitride (GaN) position GaN‐based power devices as leading candidates for next‐generation high‐efficiency smart power conversion systems. However, GaN's multi‐component nature results in a high density of epitaxial defects, whereas the introduction of dielectric layers further contributes to severe interface states and dielectric traps. These factors collectively impair reliability, manifesting as threshold voltage instability and current collapse, which pose significant barriers to the advancement of GaN‐based electronics. Establishing the intrinsic relationship between device reliability and defects is crucial for understanding and addressing reliability degradation issue. Deep level transient spectroscopy (DLTS) offers valuable insights by revealing defect‐induced changes in electrical parameters during the capture and emission processes under varying biases, thereby elucidating the influence of defects from GaN buffer layers, AlGaN barriers, dielectric layer, and even at dielectric/(Al)GaN interfaces. This research aims to provide a foundational understanding of reliability degradation whereas further enabling enhancements in device performance from the perspectives of epitaxial growth and process preparation, ultimately striving to improve the reliability of GaN‐based devices and unlock their full potential for practical applications.
Back cover image
Authors: Li Peng , Li Fangchao , Ma Jiani , Lin Dong , Ma Jiangang , Ding Lizhi , Guo Junjun , Cao Xingzhong , Shi Junwei , Xu Haiyang , Liu Yichun 
Published: December 2024

Prof. Yichun Liu et al. develop F&Al co‐doped ZnO transparent conductive films that withstand temperatures above 500 °C and are ideal for extreme optoelectronic devices.
image
Analyzing Uncertain Time Series Temperature Data for Forecasting and Streaming Using EDA‐LSTM Model
Authors: Raju Gara Jaya , Raju G. Samuel Vara Prasada 
Published: December 2024

ABSTRACTTime series data generated by IoT devices are called uncertain data, and streaming them is difficult since they have uncertain values and flow. The dataset is time series and big data since it is increasing continuously. An enormous amount of data are analyzed to predict the abnormalities in the climate or the environment. At the same time, the monitoring and generating process should be continuous because discontinuity in data generation will not provide accurate conditions. Earlier works focused on the device status detection process and intimate, where the process cannot continue where the faulty device is located. This article carries out the entire process in two phases: (i) Investigate the status of the IoT devices to replace or rectify the issues that occur in the devices and continue the same process at the exact location. (ii) Pre‐process the data using exploratory data analytics and analyze and predict the IoT‐Bigdata using a robust machine learning algorithm, Long‐Short‐Term‐Memory. The proposed machine learning algorithms are implemented in Python with environmental datasets to predict abnormalities. The experimental results help verify the algorithms' efficiency and compare them with similar methods to evaluate the performance. From the comparison, it is identified that the proposed algorithms outperform the others.
Evaluating genetic counseling session duration: A scoping review of patient care time, influencing factors, and impact on patient outcomes
Authors: Glanton Emily , Kocher Megan , Bostrom Molly , Erlandson Brady , Zierhut Heather 
Published: December 2024

AbstractOne key element of evaluating the quality of a genetic counseling session is the measurement of its efficiency, yet limited research exists on how the genetic counseling process relates to time and which elements contribute to improved quality of care. A scoping review was undertaken to document studies that have reported genetic counseling patient care time and provide a landscape of the average patient care time, which factors impact patient care time, and how patient care time relates to experiences and outcomes. Twenty‐five studies met criteria and were included. Patient care time was reported variably among the studies included. On average, genetic counseling patient care time was a mean of 60 min (53 min median) for observational studies and control groups in experimental studies and 44 min (41 min median) for intervention groups in experimental studies. Interventions impacting patient care time included pre‐genetic counseling education and group genetic counseling sessions. The impact of patient care time on patient experiences and outcomes was rarely evaluated, and therefore, efficiency could not often be assessed in the studies. Studies that reported on patient care time and outcomes were able to draw conclusions such as shorter time did not negatively impact patients and some groups of patients may benefit from longer sessions. Most studies did not analyze the relationship between patient care time and patient experiences or outcomes. Future research should aim to identify factors influencing patient care time, assess the content of genetic counseling sessions, and evaluate patient care time in relation to patient experiences and outcomes. Understanding these aspects could lead to improved efficiency and patient‐centered, equitable care in genetic counseling practices.
A Quantitative Analysis of Human and Material Resources for Endoscopy Services in Pacific Island Countries
Authors: Perman Mai Ling , Hair Chris , Malani Joji , Macrae Finlay , Jones Dianne , Natuzzi Eileen , Jagilly Rooney 
Published: December 2024

ABSTRACTAimsThis study aims to evaluate the current state of endoscopy services in Pacific Island Countries (PICs) by quantifying human and material resources, including the number of trained endoscopists and nurses, the types of procedures performed, and the availability and maintenance of endoscopic equipment.Methods and ResultsA mixed methods survey was conducted in 2023, targeting doctors and nurses who participated in the WGO‐FNU‐ANZGITA endoscopy training program as well as non‐participants. Survey invitations were sent through email, WhatsApp, and Facebook Messenger. Data were collected from 16 sites across 12 PICs, achieving an 85% response rate. Survey results indicated a total of 58 endoscopists (2.1/100000 population) and 52 nurses (1.9/100000 population), with a majority having received training through international partnerships. Basic endoscopy services, such as gastroscopy and colonoscopy, were widely available, but advanced procedures were limited to a few sites. Most sites reported using donated equipment, with significant challenges in equipment maintenance and repair. The availability of functional endoscopes averaged four per site. Common issues included outdated equipment, lack of qualified personnel, and insufficient funding for new equipment.ConclusionDespite efforts to enhance endoscopy services in PICs through international collaborations, significant gaps remain, particularly in terms of advanced procedural capacity and equipment maintenance. Recommendations include expanding training programs, improving equipment maintenance infrastructure, securing funding for new equipment, and fostering stronger partnerships to support the sustainability of endoscopy services. Addressing these areas can enhance the quality and availability of endoscopy services, ultimately improving healthcare outcomes for populations in PICs.
Wavelength Decoupling Based on Minimalist Metasurfaces Enabling Bicolor Display and Information Encryption
Authors: Huang Tian , Xie Yingxin , Zhang Zhiyao , Zhao Yu , Hu Dongyu , Yu Shaohua , Zheng Guoxing , Li Gongfa , Li Zile 
Published: December 2024

AbstractMetasurfaces garner widespread attention for their remarkable ability to precisely manipulate light and construct optical multiplexing devices. However, there is still a lack of effective solutions for achieving high‐performance wavelength decoupling in the realm of wavelength multiplexing. In this work, a novel wavelength decoupling method based on minimalist metasurfaces featuring a single‐celled configuration is proposed. These metasurfaces are composed of only two types of nanobricks, each capable of modulating the phase of two different wavelengths simultaneously as desired. The proposed minimalist metasurfaces possess the advantages of flexible design, enabling wavelength decoupling with incidences at both co‐ and cross‐polarization states. Interestingly, by integrating the wavelength decoupling metasurface with liquid crystal devices, information encryption can be achieved. The proposed wavelength decoupling method holds broad application prospects in the fields of optical data storage, image display, information security, and beyond.
Outsourcing Strategy Selection of Original Brand Manufacturers in the Fashion Industry Under the Influence of Brand Spillover
Authors: Jiang Bing , Fang Zhou 
Published: December 2024

ABSTRACTOutsourcing strategy plays an essential role in manufacturing production. Compared to traditional manufacturing industries, brand spillover behavior from contract manufacturers is more prominent in the fashion industry's outsourcing practices. Therefore, we have developed a model for original brand manufacturers (OBM) to choose an outsourcing strategy under the influence of various factors: OBM can outsource production to a competing manufacturer (CM), a non‐competing manufacturer (NCM), or produce internally. If CM is the only contractor for OBM, it will enhance its brand power through brand spillover. If NCM is the only contractor for OBM, there are quality control issues. In summary, we consider three outsourcing strategies for the OBM: outsourcing production to CM, outsourcing to NCM, or establishing internal production, which correspond to strategies C, N, and F, respectively. We find that the brand spillover has a greater impact on OBM than expected. It affects OBM's production planning by influencing market demand, resulting in the profit of strategy C always being lower than strategy N. This forces OBM to face quality control issues. On this basis, we discuss blockchain technology that enables OBM to address quality control issues while dealing with brand spillovers. Interestingly, blockchain technology does not always bring benefits and can only solve problems under specific conditions. In addition, we also prove that the dual‐source strategy, that is, OBM outsources production to CM and NCM simultaneously, is better than the C and N strategies, but whether it is better than the F strategies depends on the investment cost.
A knowledge‐based materials descriptor for compositional dependence of phase transformation in NiTi shape memory alloys
Authors: Li Cheng , Liang Qingkai , Zhou Yumei , Xue Dezhen 
Published: December 2024

AbstractThis study presents ∆τ, a novel descriptor that captures the compositional dependence of phase transformation temperature (Ap) in NiTi‐based shape memory alloys (SMAs). Designed to address the complexity of multicomponent SMAs, ∆τ was integrated into symbolic regression (SR) and kernel ridge regression (KRR) models, yielding substantial improvements in predicting key functional properties: transformation temperature, enthalpy, and thermal hysteresis. Using the KRR model with ∆τ, we explored the NiTiHfZrCu compositional space, identifying six promising alloys with high Ap (>250°C), large enthalpy (>27 J/g), and low thermal hysteresis. Experimental validation confirmed the model's accuracy with the alloys showing high‐temperature transformation behavior and low hysteresis, suitable for high‐performance applications in aerospace and nuclear industries. These findings underscore the power of domain‐informed descriptors like ∆τ in enhancing machine learning‐driven materials design.
Exploring the Fecal Metabolome in Infants With Cow's Milk Allergy: The Distinct Impacts of Cow's Milk Protein Tolerance Acquisition and of Synbiotic Supplementation
Authors: Zhu Pingping , Savova Mariyana V. , Kindt Alida ,   the PRESTO study team, Wopereis Harm , Belzer Clara , Harms Amy C. , Hankemeier Thomas 
Published: December 2024

ABSTRACTScopeCow's milk allergy (CMA) is one of the most prevalent food allergies in early childhood, often treated via elimination diets including standard amino acid‐based formula or amino acid‐based formula supplemented with synbiotics (AAF or AAF‐S). This work aimed to assess the effect of cow's milk (CM) tolerance acquisition and synbiotic (inulin, oligofructose, Bifidobacterium breve M‐16 V) supplementation on the fecal metabolome in infants with IgE‐mediated CMA.Methods and ResultsThe CMA‐allergic infants received AAF or AAF‐S for a year during which fecal samples were collected. The samples were subjected to metabolomics analyses covering gut microbial metabolites including SCFAs, tryptophan metabolites, and bile acids (BAs). Longitudinal data analysis suggested amino acids, BAs, and branched SCFAs alterations in infants who outgrew CMA during the intervention. Synbiotic supplementation significantly modified the fecal metabolome after 6 months of intervention, including altered purine, BA, and unsaturated fatty acid levels, and increased metabolites of infant‐type Bifidobacterium species: indolelactic acid and 4‐hydroxyphenyllactic acid.ConclusionThis study offers no clear conclusion on the impact of CM‐tolerance acquisition on the fecal metabolome. However, our results show that 6 months of synbiotic supplementation successfully altered fecal metabolome and suggest induced bifidobacteria activity, which subsequently declined after 12 months of intervention.
Unsupervised Bayesian generation of synthetic CT from CBCT using patient‐specific score‐based prior
Authors: Peng Junbo , Gao Yuan , Chang Chih‐Wei , Qiu Richard , Wang Tonghe , Kesarwala Aparna , Yang Kailin , Scott Jacob , Yu David , Yang Xiaofeng 
Published: December 2024

AbstractBackgroundCone‐beam computed tomography (CBCT) scans, performed fractionally (e.g., daily or weekly), are widely utilized for patient alignment in the image‐guided radiotherapy (IGRT) process, thereby making it a potential imaging modality for the implementation of adaptive radiotherapy (ART) protocols. Nonetheless, significant artifacts and incorrect Hounsfield unit (HU) values hinder their application in quantitative tasks such as target and organ segmentations and dose calculation. Therefore, acquiring CT‐quality images from the CBCT scans is essential to implement online ART in clinical settings.PurposeThis work aims to develop an unsupervised learning method using the patient‐specific diffusion model for CBCT‐based synthetic CT (sCT) generation to improve the image quality of CBCT.MethodsThe proposed method is in an unsupervised framework that utilizes a patient‐specific score‐based model as the image prior alongside a customized total variation (TV) regularization to enforce coherence across different transverse slices. The score‐based model is unconditionally trained using the same patient's planning CT (pCT) images to characterize the manifold of CT‐quality images and capture the unique anatomical information of the specific patient. The efficacy of the proposed method was assessed on images from anatomical sites including head and neck (H&N) cancer, pancreatic cancer, and lung cancer. The performance of the proposed CBCT correction method was evaluated using quantitative metrics, including mean absolute error (MAE), non‐uniformity (NU), and structural similarity index measure (SSIM). Additionally, the proposed algorithm was benchmarked against other unsupervised learning‐based CBCT correction algorithms.ResultsThe proposed method significantly reduced various kinds of CBCT artifacts in the studies of H&N, pancreatic, and lung cancer patients. In the lung stereotactic body radiation therapy (SBRT) patient study, the MAE, NU, and SSIM were improved from 47 HU, 45 HU, and 0.58 in the original CBCT images to 13 HU, 14 dB, and 0.67 in the generated sCT images. Compared to other unsupervised learning‐based algorithms, the proposed method demonstrated superior performance in artifact reduction.ConclusionsThe proposed unsupervised method can generate sCT from CBCT with reduced artifacts and precise HU values, enabling CBCT‐guided segmentation and replanning for online ART.
Hand Performance Assessed by Functional Dexterity Test Correlates With Clinical Disease Activity but Remains Altered in Rheumatoid Arthritis Patients Achieving Treatment Goals: A Cross‐Sectional Cohort Study
Authors: Shouval Aniela , Levkoviz Amihai , Keret Shiri , Rosner Itzhak , Rokhyan Irina , Tchalabian Boris , Hof Esther , Slobodin Gleb 
Published: December 2024

ABSTRACTObjectivesDirect hand function is not commonly evaluated in patients with rheumatoid arthritis (RA). The Functional Dexterity Test (FDT) assesses a patient's ability to use the hand for daily tasks and is an accepted quantitative assessment tool in occupational medicine. This pilot study aimed to examine the correlations of FDT‐measured hand performance with disease activity status in a cohort of RA patients.MethodsForty‐eight patients with established RA performed the FDT during their regular follow‐up visits. The dominant and non‐dominant hands were assessed separately. FDT results were compared among patients with active RA and Clinical Disease Activity Index (CDAI) > 10, RA patients achieving controlled disease activity state (CDAI ≤ 10), and 20 volunteers with no rheumatic disease.ResultsMean FDT for the dominant hand was 43 s in active RA, 35 s in controlled RA, and 25 s in persons without arthritis. Corresponding FDT results for the non‐dominant hand were 50, 38, and 29 s, respectively. FDT significantly correlated with CDAI in the entire cohort of RA patients and the subgroup with CDAI > 10. Patients with controlled disease, CDAI ≤ 10, still demonstrated significantly reduced hand performance compared with non‐rheumatic controls.ConclusionsFDT is a sensitive tool for assessing rheumatoid hand function. Reduced hand performance by FDT in many RA patients who have already achieved existing treatment goals speaks to the question of the suitability of direct hand performance assessment as an RA outcome measure.
A Water Relaxation Atlas for Age‐ and Region‐Specific Metabolite Concentration Correction at 3 T
Authors: Simegn Gizeaddis Lamesgin , Song Yulu , Murali‐Manohar Saipavitra , Zöllner Helge J. , Davies‐Jenkins Christopher W. , Simicic Dunja , Hupfeld Kathleen E. , Gudmundson Aaron T. , Muska Emlyn , Carter Emily , Hui Steve C. N. , Yedavalli Vivek , Oeltzschner Georg , Dean Douglas C. , Ceritoglu Can , Ratnanather J. Tilak , Porges Eric , Edden Richard 
Published: December 2024

ABSTRACTMetabolite concentration estimates from magnetic resonance spectroscopy (MRS) are typically quantified using water referencing, correcting for relaxation‐time differences between metabolites and water. One common approach is to correct the reference signal for differential relaxation within three tissue compartments (gray matter, white matter, and cerebrospinal fluid) using fixed literature values. However, water relaxation times (T1 and T2) vary between brain locations and with age. MRS studies, even those measuring metabolite levels across the lifespan, often ignore these effects, because of a lack of reference data. The purpose of this study is to develop a water relaxometry atlas and to integrate location‐ and age‐appropriate relaxation values into the MRS analysis workflow. One hundred one volunteers (51 men, 50 women; ~10 male, and 10 female participants per decade from the 20s to 60s) were recruited. T1‐weighted MPRAGE images ((1‐mm)3 isotropic resolution) were acquired. Whole‐brain water T1 and T2 measurements were made with DESPOT ((1.4 mm)3 isotropic resolution) at 3T. T1 and T2 maps were registered to the JHU MNI‐SS/EVE atlas using affine and LDDMM transformation. The atlas's 268 parcels were reduced to 130 by combining homologous parcels. Mean T1 and T2 values were calculated for each parcel in each subject. Linear models of T1 and T2 as functions of age were computed, using age − 30 as the predictor. Reference atlases of “age‐30‐intercept” and age‐slope for T1 and T2 were generated. The atlas‐based workflow was integrated into Osprey, which co‐registers MRS voxels to the atlas and calculates location‐ and age‐appropriate water relaxation parameters for quantification. The water relaxation aging atlas revealed significant regional and tissue differences in water relaxation behavior across adulthood. Using location‐ and subject‐appropriate reference values in the MRS analysis workflow removes a current methodological limitation and is expected to reduce quantification biases associated with water‐referenced tissue correction, especially for studies of aging.