bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bouillon fortification as a strategy to address inequities in micronutrient adequacy of diets in Nigeria
Authors: Adams Katherine P. , Vosti Stephen A. , Becher Emily , Ishaya Faith , Engle‐Stone Reina 
Published: September 2024

AbstractBouillon is a widely consumed condiment in many West African countries, including Nigeria. Although Nigeria has mandatory fortification standards for multiple food vehicles, bouillon fortification could help address remaining gaps in micronutrient intake. Using household food consumption data, we used the nutrient density method to model the additional contribution of bouillon fortified with vitamin A (40–250 µg/g bouillon), folic acid (20–120 µg/g), vitamin B12 (0.2–2 µg/g), iron (0.6–5 mg/g), and zinc (0.6–5 mg/g) for meeting micronutrient requirements of women of reproductive age (WRA) and children aged 6–59 months. Accounting for existing fortification programs, our results showed that, except for iron, the prevalence of inadequacy was substantially higher among WRA and children living in poorer and rural households. Given the ubiquity of bouillon consumption, bouillon fortification has the potential to virtually eliminate vitamin A, folate, and vitamin B12 inadequacy, reduce the prevalence of zinc inadequacy by over 20 percentage points, and improve equity in the micronutrient adequacy of diets across socioeconomic strata and urban and rural residence. Our results also suggested that designing a bouillon fortification program would require careful planning to balance reductions in inadequacy with the risk of high intakes. This evidence provides important input into decisions around bouillon fortification in Nigeria.
The importance of World Health Organization international reference standards in the product life cycle of biosimilars
Authors: Kang Hye‐Na , Wadhwa Meenu , Knezevic Ivana , Burns Chris , Griffiths Elwyn 
Published: September 2024

AbstractTechnological advances in analytics, as well as scientific and regulatory knowledge and experience gained from biosimilar development/approvals over the last decade, enabled the World Health Organization (WHO) in 2022 to revise its guidelines on the evaluation of biosimilars. Among the revisions, there is more reliance on analytical and functional aspects to prove similarity (and likely fewer clinical requirements). WHO international reference standards for biosimilars provide additional confidence to regulators looking for evidence‐ and data‐based regulatory convergence in scientific and technical measures of quality attributes. These standards serve as a benchmark for harmonizing the bioactivity or potency of biosimilars, ensuring their future sustainability. This article discusses the availability and role of WHO international reference standards throughout the product life cycle of biosimilars.
Asymmetric Warming of Day and Night Benefits the Early Growth of Acer mono Seedlings More Than Symmetric Warming
Authors: Yuan Junfeng , Yu Xinlei , Wu Ting , Gao Shitong , Zhang Ting , Yan Qiaoling , Li Rongping , Zhu Jiaojun 
Published: September 2024

AbstractAsymmetric warming refers to the difference between the increase in daytime maximum temperature and the increase in nighttime minimum temperature and has been documented in temperate regions. However, its impacts on seedling growth have been largely ignored. In this study, seedlings of a widely distributed tree species, Acer mono Maxim., were exposed to both symmetric warming (SW) and asymmetric warming scenarios (day warming [DW], night warming [NW] and diurnal asymmetric warming [DAW]). Compared to control, all warming scenarios were found to enhance belowground biomass. DW promoted the seedling growth, while NW reduced the stem biomass. DAW did not impact the total biomass relative to the control. Compared to SW, DAW advanced phenology, increased indole‐3‐acetic acid content and chlorophyll content, which enhanced total biomass and stored more NSC in the root. Future DAW would be not beneficial to the growth of A. mono seedlings by comparing with the control. This research encourages further exploration of tree growth experiments under asymmetric warming conditions, as most studies tend to underestimate the warming effects on plant growth by focusing on SW. Incorporating the responses of seedling physiology and growth to non‐uniform diurnal warming into earth system models is crucial for more accurately predicting carbon and energy balances in a warmer world.
2024 RSS Presidential Address: Reconceptualizing Rurality and Nurturing Rural Sociological Souls☆
Authors: Sherman Jennifer 
Published: September 2024

AbstractThis address focuses on the importance of inclusivity and diversity to the future of the Rural Sociological Society. It begins by sharing the author's experiences within the society as a rural‐focused scholar trained in a Sociology department without strong ties to the RSS, and the challenges she faced in earning recognition in the RSS. It goes on to explore the development of the RSS and the ways in which this history continues to shape who is and isn’t perceived as a rural sociologist. It then argues that the society should strive to be more inclusive in the ways it conceptualizes both rurality and rural sociology. This inclusivity should be extended to those who care about rural places and populations and treat them with respect, regardless of whether they were trained in historic departments of Rural Sociology. The Society should view multidisciplinarity as a benefit, not a detriment to its long‐term health and flourishing. The address ends by calling upon members to engage in the work of nurturing rural sociological souls wherever they are trained and working. It emphasizes the importance of a renewed commitment to diversity and inclusivity in multiple forms.
General boundary conditions for a Boussinesq model with varying bathymetry
Authors: Lannes David , Rigal Mathieu 
Published: September 2024

AbstractThis paper is devoted to the theoretical and numerical investigation of the initial boundary value problem for a system of equations used for the description of waves in coastal areas, namely, the Boussinesq–Abbott system in the presence of topography. We propose a procedure that allows one to handle very general linear or nonlinear boundary conditions. It consists in reducing the problem to a system of conservation laws with nonlocal fluxes and coupled to an ordinary differential equation. This reformulation is used to propose two hybrid finite volumes/finite differences schemes of first and second order, respectively. The possibility to use many kinds of boundary conditions is used to investigate numerically the asymptotic stability of the boundary conditions, which is an issue of practical relevance in coastal oceanography since asymptotically stable boundary conditions would allow one to reconstruct a wave field from the knowledge of the boundary data only, even if the initial data are not known.
The effects of foreign direct investment on human capital accumulation—Evidence from China
Authors: Liu Yan 
Published: September 2024

AbstractThis paper examines the effect of foreign direct investment (FDI) on human capital accumulation in China. The identification strategy exploits variations in FDI inflows across manufacturing sub‐sectors caused by China's FDI liberalisation and initial sectoral composition patterns across cities. Using a panel of city‐level data from 1990 to 2005, the paper shows that FDI liberalisation accelerated human capital accumulation. Cities with higher exposure to FDI liberalisation experienced higher growth in high school and college enrollment. FDI incentivizes individuals' investment in their human capital by paying a higher wage premium for skilled workers, pushing up the skill premium in the local labor market, and raising household income. Compared to export‐oriented FDI and FDI in less‐skilled industries, market‐seeking FDI and skill‐intensive FDI have a much larger effect on college enrollment.
Chromatic symmetric functions and polynomial invariants of trees
Authors: Aliste‐Prieto José , Martin Jeremy L. , Wagner Jennifer D. , Zamora José 
Published: September 2024

AbstractStanley asked whether a tree is determined up to isomorphism by its chromatic symmetric function. We approach Stanley's problem by studying the relationship between the chromatic symmetric function and other invariants. First, we prove Crew's conjecture that the chromatic symmetric function of a tree determines its generalized degree sequence, which enumerates vertex subsets by cardinality and the numbers of internal and external edges. Second, we prove that the restriction of the generalized degree sequence to subtrees contains exactly the same information as the subtree polynomial, which enumerates subtrees by cardinality and number of leaves. Third, we construct arbitrarily large families of trees sharing the same subtree polynomial, proving and generalizing a conjecture of Eisenstat and Gordon.
Burner and Flame Transfer Matrices of Jet-Stabilized Flames: Influence of Jet Velocity and Fuel Properties
Authors: Nedden Philipp zur , Eck Mattias E. G. , Lückoff Finn , Paschereit Christian Oliver , Orchini Alessandro 
Published: September 2024

Abstract
To achieve the decarbonization of electrical power generation, gas turbines need to be upgraded to combust high-hydrogen content fuels reliably. One of the main challenges in this upgrade is the burner design. A promising burner concept for a high-hydrogen fuel mixture are jet burners, which are highly flashback resistant thanks to their high bulk velocity. Due to its nonacoustically compact extension and the presence of hydrogen in the fuel mixture, new challenges arise in assessing the (thermo)acoustic response of this burner design. A burner transfer matrix (BTM) and the flame transfer function (FTF) or transfer matrix (FTM) are typically measured with the multimicrophone method (MMM) to assess the performance of new burner types in relation to thermoacoustic stability. With the switch toward hydrogen, the fuel/air mixture is significantly altered in its properties regarding the speed of sound and density, which are of fundamental importance for acoustic waves propagation and their reconstruction via the MMM, as highlighted in recent work. In this work, we extend this discussion by studying the influence of the gas composition within the burner when measuring BTMs, and its indirect effect on the assessment of FTFs. Experimentally, we achieve this by adapting the preheating temperature during the measurement of the BTM with a nonreactive mixture in order to match the speed of sound of the hydrogen–air mixture required to flow in the burner under reactive conditions. Additionally, we present an analytical model for the jet burner transfer matrix, which is validated against the experimental data. Since the BTM is fundamental for the assessment of the FTM and FTF, the propagation of the error of changing fuel mixtures in the burner is evaluated. The influence of the variation in reactant composition of the BTM on the FTM assessment is noticeable, particularly in the gain of the FTFs. Furthermore, the influence of the total mass flow and, thus, the bulk flow velocity on the FTF is analyzed.
Infants Sucking Pattern Identification Using Machine-Learned Computational Modeling
Authors: Olapojoye Abdullahi , Singh Abhishek , Nishi Eri , Fei Baowei , Nostratinia Aria , Hassanipour Fatemeh 
Published: September 2024

Abstract
Breastfeeding involves a complex coordination of swallowing, breathing, and sucking, with the infant's sucking proficiency being crucial for adequate nutrient intake. However, real-time assessment of milk intake is difficult, and issues with sucking often become apparent after the infant shows signs of nutrient deficiency. Traditional assessments by clinicians rely on the expertise and subjective judgment of healthcare professionals, enabling personalized evaluations. In this research, we introduce a novel approach to identifying sucking patterns by leveraging data collected from infants during breastfeeding sessions. This method utilizes artificial nipple-based sensors to capture the tongue forces exerted by infants, generating valuable clinical data. In the analysis of the collected time-series data, we applied machine-learned computational modeling (MLCM) algorithms to extract pertinent features and identify distinctive sucking patterns. The best-performing model demonstrated an accuracy of 90%, an 80% recall score, a perfect 100% precision score, a 0.90 f1-score, and an area under the curve (AUC) of 0.80. The proposed classification system has the potential to serve as a reliable decision-support tool for clinicians, offering valuable insights into infants' sucking behaviors. By integrating machine learning (ML)-based computational modeling into clinical practice, we aim to enhance the early identification of unhealthy sucking patterns, allowing for timely interventions and pro-active healthcare management.
Optimization of Power Control for Autonomous Hybrid Electric Vehicles With Flexible Power Demand
Authors: Kargar Mohammadali , Song Xingyong 
Published: September 2024

Abstract
Technology advancement for on-road vehicles has gained significant momentum in the past decades, particularly in the field of vehicle automation and powertrain electrification. The optimization of powertrain controls for autonomous vehicles typically involves a separated consideration of the vehicle’s external dynamics and powertrain dynamics, with one key aspect often overlooked. This aspect, known as flexible power demand, recognizes that the powertrain control system does not necessarily have to precisely match the power requested by the vehicle motion controller at all times. Leveraging this feature can lead to control designs achieving improved fuel economy by adding an extra degrees-of-freedom to the powertrain control while maintaining safety and drive comfort. The present research investigates the use of an approximate dynamic programming (ADP) approach to develop a powertrain controller, which takes into account the flexibility in power demand within the ADP framework. The concept of reachable sets is incorporated into the ADP framework to ensure safety, improve ride comfort, and enhance the accuracy of the optimization solution. The formulation is based on an autonomous hybrid electric vehicle, while the methodology can also be applied to other types of vehicles. It is also found that necessary customization of the ADP algorithm is needed for this particular control problem to prevent convergence issues. Finally, a case study is presented to evaluate the effectiveness of flexible power demand, as addressed by the ADP method. The experiment demonstrates a 14.1% improvement in fuel economy compared to a scenario without flexible power demand.
A Fault Diagnosis Method for Electric Vehicle Lithium Power Batteries Based on Dual-Feature Extraction From the Time and Frequency Domains
Authors: Chang Chun , Dai Jiuhe , Pan Yaliang , Lv Lu , Gao Yang , Jiang Jiuchun 
Published: September 2024

Abstract
This study focuses on the safety and reliability issues of lithium-ion batteries, proposing a fault diagnosis strategy that leverages dual-feature extraction from both the time and frequency domains. Additionally, by modifying the traditional autoencoder, the study proposes a feature-guided autoencoder as an unsupervised model for extracting features in the time domain. Initially, wavelet packet decomposition and its energy-denoising treatment are employed to refine fault information within battery voltage signals. Subsequently, the reconstruction error outputted by the Feature-Guided Autoencoder is utilized as the time-domain fault feature, while the cosine similarity of the energy of signals in various frequency bands obtained after wavelet packet decomposition serves as the frequency-domain fault feature. Ultimately, this article selects the Isolation Forest algorithm for two-dimensional outlier detection of time and frequency features. Experimental results demonstrate that the feature-guided autoencoder proposed in this study not only enhances the sensitivity of time-domain fault features compared to traditional autoencoders and their variants but also optimizes issues related to training time and computational load. The effectiveness of the proposed dual-feature fault diagnosis method in both the time and frequency domains is validated through data from two actual vehicles, showing superior early fault detection capability relative to single-feature fault diagnosis methods.
Analysis of ansys fluent for Wall-Modeled Large-Eddy Simulation of Turbulent Channel Flow
Authors: Li Weiyi , Giometto Marco G. 
Published: September 2024

Abstract
This study assesses the accuracy of ansysfluent 19.2, a commonly employed general-purpose finite volume solver, in the context of wall-modeled large-eddy simulation for turbulent channel flow at a moderate Reynolds number, Reτ=2000. The sensitivity of the solution to variations in grid resolution, aspect ratio, grid arrangement (collocated versus staggered), and subgrid-scale (SGS) model is analyzed and contrasted to results from a corresponding direct numerical simulation (DNS) and a mixed pseudospectral and finite differences solver. Results indicate good convergence of first- and second-order statistics from the staggered grid setups as the grid is refined, whereas no clear trend is observed in cases with collocated grid setups. Velocity spectra show a lack of an apparent inertial range trend and rapid decay of energy density at high wavenumbers, with a spurious energy pile-up near the cutoff wavenumber indicating the presence of unphysical oscillations in the velocity fields. Grid refinement strengthens such oscillations in collocated grid setups and reduces them in staggered grid setups. Two-point streamwise velocity autocorrelation maps reveal an underprediction of turbulent structure size. In contrast, cross-stream autocorrelations agree with corresponding curves from direct numerical simulation, showing signatures of alternating high- and low-momentum streaks in the logarithmic layer.
Assessment of Aging Degradation in Rubber Using Quasi-Static Components of Ultrasonic Longitudinal Waves
Authors: Lai Quanqing , Xu Caibin , Wang Gonglin , Deng Mingxi 
Published: September 2024

Abstract
Aging degradation is the main form of failure of rubber in service, leading to a decline in its physical and mechanical properties. This paper presents an efficient method for assessing the aging degradation of rubber using the quasi-static component (QSC) of ultrasonic longitudinal waves induced by acoustic radiation. The experiments quantitatively observe the response of the QSC pulse to different levels of aging degradation. A pulse-echo ultrasonic transducer is employed to simultaneously capture the primary longitudinal wave (PLW) and QSC echoes, enabling the determination of the acoustic nonlinearity parameter of QSC with a single transducer excitation. The results suggest that, in comparison to traditional linear ultrasonic techniques based on attenuation coefficient and wave velocity measurements, the relative acoustic nonlinear parameter of QSC proves to be more sensitive to aging degradation in rubber. Particularly, the amplitude of the QSC pulse undergoes a significant change with increasing aging degradation, even when the PLW tone burst is completely attenuated. These findings confirm the effectiveness of QSC as a method for evaluating aging degradation in highly attenuative materials.
Case Studies and Parametric Analysis of Heliostat Performance With a Tradeoff-Informed Technoeconomic Analysis Metric
Authors: Zolan Alexander , Augustine Chad , Armijo Kenneth 
Published: September 2024

Abstract
The Heliostat Consortium (HelioCon) was launched in 2021 to advance heliostat technology. This work presents a collection of baseline case studies for the technoeconomic analysis (TEA) of candidate heliostat improvements for concentrating solar power (CSP) and concentrated solar thermal (CST) systems that employ central receivers. The case studies we develop include a large-scale CSP plant, a smaller, modular CSP plant, and a small CST plant used for industrial process heat. In this work, we also propose a novel metric for TEA of a plant component technology that recasts relative changes in levelized system costs into component-specific capital cost budgets. This measure, which we refer to as the equivalent breakeven installed cost, is the maximum budget for the technology component that leads to improved levelized costs. Finally, we perform a parametric analysis to show the impact of candidate technologies on the levelized cost of heat and, by extension, equivalent breakeven installed cost.
The Building Decarbonization in High-Density Cities: Challenges and Solutions
Authors: Lv Guoquan , Zhao Zilong , Zhao Kang , Ge Jian 
Published: September 2024

Abstract
Decarbonization of buildings is an imperative and challenging task. Beyond the common challenges associated with building decarbonization, those in high-density urban areas also face technical challenges due to geographical conditions and resource endowments. As decarbonization practices deepen, it has been found that reliance on conventional methods is fraught with difficulties, primarily due to the high proportion of incremental costs involved. This review study explores methods not widely incorporated into existing building energy efficiency standards but which hold the potential for aiding decarbonization. It advocates for a synergistic strategy involving surrounding infrastructure such as power and other building energy systems, innovative low-carbon building materials, and greenery to facilitate this transition.
Optimization of the Distributor Setup in an Axial Turbine at Speed-No-Load Using Machine Learning
Authors: Kranenbarg Jelle , Jonsson Pontus P. , Mulu Berhanu G. , Sundström Joel , Cervantes Michel J. 
Published: September 2024

Abstract
Axial hydraulic turbines are operated more frequently at standby mode operation, also known as Speed-No-Load (SNL), to connect rapidly to the grid when required. This operation is harmful to the turbine and is sometimes characterized by large rotating vortical flow structures extending from the vaneless space to the draft tube, introducing detrimental pressure pulsations. A previous study showed that the flow structures can be mitigated with individual control of the guide vanes. The present study is a continuation that aims to find the best distributor layout for mitigation of the flow structures by introducing machine learning. A reduced CFD model, without runner blades and spiral casing, is developed to generate steady-state input data for a Gaussian process regression model. The surrogate model predicts that the best distributor layout is to open seven guide vanes out of 20 in a row while keeping the remaining ones closed. A cross-validation with a transient simulation on the reduced CFD model shows that the flow structures are mitigated, resulting in a stable and predictable flow field. The pressure pulsations in the vaneless space have been reduced by up to 94%. In addition, there is no risk for cavitation in the distributor domain by not opening all guide vanes, and the forces on the runner hub are less compared to regular SNL operation. The proposed distributor setup can potentially increase the turbine’s life span and make it better suited for grid regulation purposes.