bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pearl millet for good health and nutrition – An overview
Authors: Nibhoria Amarjeet , Kumar Mukesh , Arya Rajesh Kumar , Siroha Anil Kumar 
Published: October 2024

Abstract

Previously food was taken to satiate hunger and survival, but now it is for better health and wellbeing. It is imperative to take a healthy diet that includes energy, carbohydrates, proteins, fiber, and all essential vitamins and nutrients in optimum proportions. Millets have been acknowledged as climate-resilient crops and smart foods. Pearl millet is a C
4
plant grown mostly under scarce input and water supply conditions. Owing to high photosynthetic efficiency, it produces more dry matter and gives better economic returns even under adverse agro-climatic conditions. Globally, pearl millet is grown on 31.0 million ha, mainly in Africa and Asia and is a staple food for 90 million poor people. Among food crops (cereals and pulses), pearl millet is the cheapest energy source (361 kcal/100g), minerals, namely, phosphorus (296–360 mg/100g), iron (8–11 mg/100g), zinc (3.1–6.6 mg/100g), calcium (40–42 mg/100 g), magnesium (97–137 mg/100g) and vitamins, namely, vitamin A, E, riboflavin, thiamine, vitamin K and niacin, etc. Besides, it also has significant amount of fiber, protein, antioxidants like phenolic acids, flavonoids and low fats. Because of its rich nutritional composition, Government of India has designated it as nutri-cereals (Gazette of India, No. 133 dated 13th April, 2018) for production, consumption and trade. Besides rich nutritional value, pearl millet improves our immunity through enormous health benefits like reducing the risk of chronic diseases such as obesity, diabetes, and cardiovascular diseases. It improves the digestibility and bioavailability of food nutrients by reducing anti-nutrients. Being non-acid forming, it is also helpful in gastrointestinal problems and is non-glutinous beneficial for people suffering from celiac diseases. With these properties, it is regarded as a significant grain worldwide, yet it is least exploited. However, because of numerous potential health benefits and contributions to national food security, millet grains are now getting the growing attention of food nutritionists, scientists, technologists and industrialists.
AFRIMETS.EM-S2: comparison on digital multimeter for DC voltage, DC current, DC resistance, AC voltage and AC current parameters
Authors: Khoza Michael , Hlakola Marcus , Sayed Rasha , Abdel Hala M 
Published: October 2024

Main text
During the 13th intra-Africa metrology system (AFRIMETS) technical committee on electricity and magnetism (TCEM) meeting held on 8th to 9th of July 2019 at Giza, Egypt, a supplementary comparison was approved on a digital multimeter. The primary aim of the comparison is to support the calibration measurement capabilities of the national metrology institutes in measuring DC voltage, DC current, DC resistance, AC voltage and AC current parameters. The National Institute of Standards, Egypt (NIS) piloted the comparison and National Metrology Institute of South Africa (NMISA) provided the comparison reference values and eight AFRIMETS national metrology designated institutes participated. The comparison commenced in January 2020 and completed in August 2021. This report describes the behaviour of the comparison standard, participants reported corrections and calculated comparison reference values with associated uncertainties of measurements at 95% confidence level, normalized errors and degrees of equivalence.
To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database https://www.bipm.org/kcdb/.
The final report has been peer-reviewed and approved for publication by the CCEM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).
Towards the solution of coating loss measurements using thermoelastic-dominated substrates
Authors: Silenzi L , Fabrizi F , Granata M , Mereni L , Montani M , Piergiovanni F , Trapananti A , Travasso F , Cagnoli G 
Published: October 2024

Abstract
The characterization of thin film parameters derives from the measurement difference between the coated and bare substrate. This method of comparison is based on the stationarity of the substrate: the characteristics of the substrate do not depend on the presence of the film. However, the thermoelastic loss of a coated substrate depends on the thermo-mechanical parameters of the film as well, which are generally unknown. When thermoelastic loss is dominant, the coating loss measurements are completely altered. In this paper, we propose a model that helps to understand the role of each material property in the thermoelasticity of layered plates, and with this we identified three possible cases in which any coating-substrate combination could be classified. In particular, we analyzed the IBS silica film deposited on silicon. Using the model, we were able to explain the experimental results and also selected a thinner substrate for future coating loss measurements. With this choice, cryogenic loss measurements on bare substrate confirm that thermoelastic loss becomes irrelevant for temperatures below 130 K–180 K, depending on the mode.
An adaptive parameter decoupling algorithm-based image reconstruction model (ADAIR) for rapid golden-angle radial DCE-MRI
Authors: Chen Zhifeng , Yuan Zhenguo , Cheng Junying , Liu Jinhai , Liu Feng , Chen Zhaolin 
Published: October 2024

Abstract

Objective. The acceleration of magnetic resonance imaging (MRI) acquisition is crucial for both clinical and research applications, particularly in dynamic MRI. Existing compressed sensing (CS) methods, despite being effective for fast imaging, face limitations such as the need for incoherent sampling and residual noise, which restrict their practical use for rapid MRI. Approach. To overcome these challenges, we propose a novel image reconstruction framework that integrates the MRI physical model with a flexible, self-adjusting, decoupling data-driven model. We validated this method through experiments using both simulated and in vivo dynamic contrast-enhanced MRI datasets. Main results. The experimental results demonstrate that the proposed framework achieves high spatial and temporal resolution reconstructions. Additionally, when compared to state-of-the-art image reconstruction approaches, our method significantly enhances acceleration capabilities, enabling sparse and rapid imaging with high resolution. Significance. Our proposed framework offers a promising solution for real-time imaging and image-guided radiation therapy applications by providing superior performance in achieving high spatial and temporal resolution reconstructions, thus addressing the limitations of existing CS schemes.
Exploring dual energy CT synthesis in CBCT-based adaptive radiotherapy and proton therapy: application of denoising diffusion probabilistic models
Authors: Viar-Hernandez David , Manuel Molina-Maza Juan , Pan Shaoyan , Salari Elahheh , Chang Chih-Wei , Eidex Zach , Zhou Jun , Antonio Vera-Sanchez Juan , Rodriguez-Vila Borja , Malpica Norberto , Torrado-Carvajal Angel , Yang Xiaofeng 
Published: October 2024

Abstract

Background. Adaptive radiotherapy (ART) requires precise tissue characterization to optimize treatment plans and enhance the efficacy of radiation delivery while minimizing exposure to organs at risk. Traditional imaging techniques such as cone beam computed tomography (CBCT) used in ART settings often lack the resolution and detail necessary for accurate dosimetry, especially in proton therapy. Purpose. This study aims to enhance ART by introducing an innovative approach that synthesizes dual-energy computed tomography (DECT) images from CBCT scans using a novel 3D conditional denoising diffusion probabilistic model (DDPM) multi-decoder. This method seeks to improve dose calculations in ART planning, enhancing tissue characterization. Methods. We utilized a paired CBCT-DECT dataset from 54 head and neck cancer patients to train and validate our DDPM model. The model employs a multi-decoder Swin-UNET architecture that synthesizes high-resolution DECT images by progressively reducing noise and artifacts in CBCT scans through a controlled diffusion process. Results. The proposed method demonstrated superior performance in synthesizing DECT images (High DECT MAE 39.582 ± 0.855 and Low DECT MAE 48.540± 1.833) with significantly enhanced signal-to-noise ratio and reduced artifacts compared to traditional GAN-based methods. It showed marked improvements in tissue characterization and anatomical structure similarity, critical for precise proton and radiation therapy planning. Conclusions.
This research has opened a new avenue in CBCT-CT synthesis for ART/APT by generating DECT images using an enhanced DDPM approach. The demonstrated similarity between the synthesized DECT images and ground truth images suggests that these synthetic volumes can be used for accurate dose calculations, leading to better adaptation in treatment planning.
Optical Möbius strips in isotropic random non-paraxial light
Authors: Grigoriev K S , Makarov V A 
Published: October 2024

Abstract
The statistics of Möbius strips with various topologies, formed by the axes of polarization ellipses as they are traced along a closed circular contour of small size passing through the center of a solitary circular polarization singularity line (C-line), have been investigated both analytically and numerically in a random isotropic electromagnetic field. Found are the analytical expressions for the joint probability density function of the differential characteristics of the random isotropic electromagnetic field, which allow for the determination of the topological properties of diagrams of polarization ellipses and the normal vectors to them, as well as the optical strips that arise in the space around C-lines.
Improved experimental scheme for the generation of pair coherent state in traveling-wave optical fields
Authors: Truong Minh Duc , Tran Quang Dat , Le Phuoc Dinh 
Published: October 2024

Abstract
Pair coherent state (PCS) is a two-mode non-Gaussian state recently generated within spatially confined superconducting cavities. Under typical conditions, it is unsuitable for performing global quantum missions in open space. Several methods have been proposed to generate this state with the capability to propagate unrestrictedly. However, these methods employed an excessive amount of unnecessary physical resources or relied on coherent displacement within the low regime. This paper presents a novel experimental approach to generate this state, specifically designed for facilitating long-distance quantum information processing and communication tasks. The method involves the utilization of two weak cross-Kerr nonlinear media, two balanced beam splitters, and an on/off photodetector. Furthermore, the input comprises three CSs with high amplitudes. These physical resources are potentially accessible within existing technology. The analysis of success probability and fidelity demonstrates that the PCS can be successfully generated with a high coherent parameter amplitude, even in scenarios where the photodetector efficiency is low, provided that the coherent amplitudes are sufficiently high.
Genetic diversity of Spotted scat (Scatophagus argus) based on 16s rRNA gene markers in WPP 573 Western part as management basis
Authors: Fitri D A , Mashar A , Ayu I P 
Published: October 2024

Abstract
Spotted scat (Scatophagus argus) is one of the demersal fish that has important economic value, this fish is used as a consumption fish and ornamental fish. It is also an active migratory fish that allows genetic transfer from different waters. This study aims to analyze the genetic diversity of Spotted scat in WPP 573 West Part based on 16s rRNA gene markers as a sustainable resource management. Amplification results show amplicon with single strand band but there are still smears due to the presence of contaminants. The BLASTn sequencing and validation results showed that all Spotted scat samples belonged to the Scatophagus argus species with a percent identification of 99.51 until 100%. The results showed that the Spotted scat samples had a very close kinship relationship, but the population of spotted scat was classified into the unfavorable category because of the low level of diversity.
Distributional response of the rare and critically endangered Ilex nanchuanensis to climate change in East Asia
Authors: Chen Zhiming , Kang Wenjuan , Li Guang , He Renyuan , Luo Zhuzhu 
Published: October 2024

Abstract
Global climate change, dominated by climate warming, is seriously affecting the balance of global ecosystems, but the risk of species extinction is particularly high in low-altitude mountain areas. To clarify the response of the endemic and critically endangered species Ilex nanchuanensis to climate change, this study used the MaxEnt model to simulate and predict the potential habitat of I. nanchuanensis during the Last Interglacial, Last Glacial Maximum, the current period, and two future periods (the 2050 s and 2070 s). The results showed that the hottest monthly minimum temperature is the most important climatic factor affecting the geographical distribution of I. nanchuanensis. Furthermore, I. nanchuanensis will be at risk of population shrinkage and extinction in the future, with the center of mass moving further northwest as concentrations of greenhouse gases increase, especially in the 2070 s, when its geographical distribution shrinks the most under the RCP6 scenario. Therefore, to actively respond to the impacts of climate change, protected areas should be established around the geographical distribution centers of species, and core, buffer, and experimental areas should be scientifically and rationally delineated for the conservation and cultivation of germplasm resources.
Thermal management of mixed convection in a partially heated triangular cavity with a cylindrical enclosure
Authors: T Ravi Kumar Reddy , Srinivasan D R 
Published: October 2024

Abstract
Numerical Investigations are carried out to study the thermal performance of the magnetohydrodynamics laminar mixed convection in a triangular cavity with a circular enclosure. The present work analysis is carried out on a triangular cavity with circular blockage by varying the Re (200–600), Ri (0.01–1), and Gr (4000–36000), respectively. The working system is a triangular cavity filled with water with a circular block. Non-linear partial differential equations are the governing equations that use the finite element method. The moving upper wall and temperature difference contribute to the convection heat transfer. The upper wall is heated and maintained at high temperatures. The other walls are kept as adiabatic. The obstacle at the center is kept at a low temperature. The physical parameters are non-dimensional numbers like the Reynolds, Richardson, and Hartmann numbers that influence the heat transfer rate. The Richardson and Reynolds numbers impact positively, and the Hartmann numbers tend to decrease heat transfer rates.
Green-synthesized Ag hierarchical assemblies for SERS detection of rhodamine dye
Authors: Sayson Luce Vida A , Taaca Kathrina Lois M , Madera Rozen Grace B , Vasquez Magdaleno R , Regulacio Michelle D 
Published: October 2024

Abstract
This study presents a simple benchtop synthetic protocol for the fabrication of silver (Ag) hierarchical structures in aqueous media using environmentally friendly and inexpensive reagents under mild experimental conditions. Natural organic acids that are known to be present in plants were employed as reducing and morphology-directing reagents. SEM and TEM imaging revealed that the products are three-dimensional hierarchical structures that were formed from self-assembly of smaller nanoparticles. They are generally spherical in shape, measure around 1.5 to 5 μm in size, and possess highly roughened surfaces due to the interstitial gaps between their nanoparticle subunits. Their hierarchical architecture allows for strong absorption of light in a broad range of wavelengths that extends to the near-infrared region. In addition, their surface morphology has an abundance of hot spot regions, which are capable of inducing strong SERS enhancement effects. The green-synthesized Ag nanostructures showed remarkable SERS activity when used as substrates for the detection of rhodamine 6G dye, a highly toxic water contaminant, even at a concentration as low as 10–8 M. Overall, this study does not only provide a greener approach to Ag hierarchical structures, but also demonstrates the immense potential of these nano-assembled architectures in the sensitive detection of organic dye pollutants.
ULTRA-effective labeling of tandem repeats in genomic sequence
Authors: Olson Daniel R , Wheeler Travis J 
Published: October 2024

Abstract

In the age of long read sequencing, genomics researchers now have access to accurate repetitive DNA sequence (including satellites) that, due to the limitations of short read-sequencing, could previously be observed only as unmappable fragments. Tools that annotate repetitive sequence are now more important than ever, so that we can better understand newly uncovered repetitive sequences, and also so that we can mitigate errors in bioinformatic software caused by those repetitive sequences. To that end, we introduce the 1.0 release of our tool for identifying and annotating locally repetitive sequence, ULTRA Locates Tandemly Repetitive Areas (ULTRA). ULTRA is fast enough to use as part of an efficient annotation pipeline, produces state-of-the-art reliable coverage of repetitive regions containing many mutations, and provides interpretable statistics and labels for repetitive regions.

Availability and implementation
ULTRA is released under an open source license, and is available for download at https://github.com/TravisWheelerLab/ULTRA.
MSDAFL: molecular substructure-based dual attention feature learning framework for predicting drug–drug interactions
Authors: Hou Chao , Duan Guihua , Yan Cheng 
Published: October 2024

Abstract

Motivation
Drug–drug interactions (DDIs) can cause unexpected adverse drug reactions, affecting treatment efficacy and patient safety. The need for computational methods to predict DDIs has been growing due to the necessity of identifying potential risks associated with drug combinations in advance. Although several deep learning methods have been recently proposed to predict DDIs, many overlook feature learning based on interactions between the substructures of drug pairs.

Results
In this work, we introduce a molecular Substructure-based Dual Attention Feature Learning framework (MSDAFL), designed to fully utilize the information between substructures of drug pairs to enhance the performance of DDI prediction. We employ a self-attention module to obtain a set number of self-attention vectors, which are associated with various substructural patterns of the drug molecule itself, while also extracting interaction vectors representing inter-substructure interactions between drugs through an interactive attention module. Subsequently, an interaction module based on cosine similarity is used to further capture the interactive characteristics between the self-attention vectors of drug pairs. We also perform normalization after the interaction feature extraction to mitigate overfitting. After applying three-fold cross-validation, the MSDAFL model achieved average precision scores of 0.9707, 0.9991, and 0.9987, and area under the receiver operating characteristic curve scores of 0.9874, 0.9934, and 0.9974 on three datasets, respectively. In addition, the experiment results of five-fold cross-validation and cross-datum study also indicate that MSDAFL performs well in predicting DDIs.

Availability and implementation
Data and source codes are available at https://github.com/27167199/MSDAFL.
RTF: an R package for modelling time course data
Authors: Brombacher Eva , Kreutz Clemens 
Published: October 2024

Abstract

Summary
The retarded transient function (RTF) approach serves as a complementary method to ordinary differential equations (ODEs) for modelling dynamics typically observed in cellular signalling processes. We introduce an R package that implements the RTF approach, originally implemented within the MATLAB-based Data2Dynamics modelling framework. This package facilitates the modelling of time and dose dependencies, and it includes the possibility of model reduction to minimize overfitting. It can be applied to experimental data or trajectories of ODE models to characterize their dynamics. Additionally, it can generate a low-dimensional representation based on the fitted RTF parameters of a set of time-resolved data, aiding in the identification of key targets of experimental perturbations.

Availability and implementation
The R package RTF is available at https://github.com/kreutz-lab/RTF.
The use of 7T MRI in multiple sclerosis: review and consensus statement from the North American Imaging in Multiple Sclerosis Cooperative
Authors: Harrison Daniel M , Sati Pascal , Klawiter Eric C , Narayanan Sridar , Bagnato Francesca , Beck Erin S , Barker Peter , Calvi Alberto , Cagol Alessandro , Donadieu Maxime , Duyn Jeff , Granziera Cristina , Henry Roland G , Huang Susie Y , Hoff Michael N , Mainero Caterina , Ontaneda Daniel , Reich Daniel S , Rudko David A , Smith Seth A , Trattnig Siegfried , Zurawski Jonathan , Bakshi Rohit , Gauthier Susan , Laule Cornelia 
Published: October 2024

Abstract
The use of ultra-high-field 7-Tesla (7T) MRI in multiple sclerosis (MS) research has grown significantly over the past two decades. With recent regulatory approvals of 7T scanners for clinical use in 2017 and 2020, the use of this technology for routine care is poised to continue to increase in the coming years. In this context, the North American Imaging in MS Cooperative (NAIMS) convened a workshop in February 2023 to review the previous and current use of 7T technology for MS research and potential future research and clinical applications. In this workshop, experts were tasked with reviewing the current literature and proposing a series of consensus statements, which were reviewed and approved by the NAIMS. In this review and consensus paper, we provide background on the use of 7T MRI in MS research, highlighting this technology’s promise for identification and quantification of aspects of MS pathology that are more difficult to visualize with lower-field MRI, such as grey matter lesions, paramagnetic rim lesions, leptomeningeal enhancement and the central vein sign. We also review the promise of 7T MRI to study metabolic and functional changes to the brain in MS. The NAIMS provides a series of consensus statements regarding what is currently known about the use of 7T MRI in MS, and additional statements intended to provide guidance as to what work is necessary going forward to accelerate 7T MRI research in MS and translate this technology for use in clinical practice and clinical trials. This includes guidance on technical development, proposals for a universal acquisition protocol and suggestions for research geared towards assessing the utility of 7T MRI to improve MS diagnostics, prognostics and therapeutic efficacy monitoring. The NAIMS expects that this article will provide a roadmap for future use of 7T MRI in MS.