bluuebunny/crossref_metadata_2025_split huggingface dataset:
YJMob100K: City-scale and longitudinal dataset of anonymized human mobility trajectories
Authors: Yabe Takahiro , Tsubouchi Kota , Shimizu Toru , Sekimoto Yoshihide , Sezaki Kaoru , Moro Esteban , Pentland Alex 
Published: April 2024

AbstractModeling and predicting human mobility trajectories in urban areas is an essential task for various applications including transportation modeling, disaster management, and urban planning. The recent availability of large-scale human movement data collected from mobile devices has enabled the development of complex human mobility prediction models. However, human mobility prediction methods are often trained and tested on different datasets, due to the lack of open-source large-scale human mobility datasets amid privacy concerns, posing a challenge towards conducting transparent performance comparisons between methods. To this end, we created an open-source, anonymized, metropolitan scale, and longitudinal (75 days) dataset of 100,000 individuals’ human mobility trajectories, using mobile phone location data provided by Yahoo Japan Corporation (currently renamed to LY Corporation), named . The location pings are spatially and temporally discretized, and the metropolitan area is undisclosed to protect users’ privacy. The 90-day period is composed of 75 days of business-as-usual and 15 days during an emergency, to test human mobility predictability during both normal and anomalous situations.
Effects of human milk odor stimulation on feeding in premature infants: a systematic review and meta-analysis
Authors: Qin Yangyang , Liu Shu , Yang Yanming , Zhong Yuan , Hao Danshi , Han Han 
Published: April 2024

AbstractPrevious studies suggested odor stimulation may influence feeding of premature neonates. Therefore, this systematic review and meta-analysis of randomized controlled trials was conducted to assess the effect of human milk odor stimulation on feeding of premature infants. All randomized controlled trials related to human milk odor stimulation on feeding in premature infants published in PubMed, Cochrane, Library, Medline, Embase, Web of science databases and Chinese biomedical literature databases, China National Knowledge Infrastructure, China Science and Technology Journal Database (VIP) and Wanfang Chinese databases were searched, and The Cochrane Handbook 5.1.0 was used to evaluate the quality and authenticity of the literature. Relevant information of the included studies was extracted and summarized, and the evaluation indexes were analyzed using ReviewManager5.3. The retrieval time was from the establishment of the database to July 28, 2022.12 articles were assessed for eligibility, and six randomized controlled studies were eventually included in the meta-analysis (PRISMA). A total of 6 randomized controlled studies with 763 patients were finally included in the study, and the quality evaluation of literatures were all grade B. Human milk odor stimulation reduced the transition time to oral feeding in premature infants [SMD = − 0.48, 95% CI (− 0.69, − 0.27), Z = 4.54, P < 0.00001] and shortened the duration of parenteral nutrition [MD = − 1.01, 95% CI (− 1.70, − 0.32), Z = 2.88, P = 0.004]. However, it did not change the length of hospitalization for premature infants [MD = − 0.03, 95% CI (− 0.41, 0.35), Z = 0.17, P = 0.86]. The implementation of human milk odor stimulation can reduce the transition time to oral feeding and the duration of parenteral nutrition in premature infants, but further studies are needed to determine whether it can reduce the length of hospital stay in premature infants. More high-quality, large-sample studies are needed to investigate the effect of human milk odor stimulation on the feeding process and other outcomes in premature infants.
Soil pollution indices and health risk assessment of metal(loid)s in the agricultural soil of pistachio orchards
Authors: Taghavi Mahmoud , Bakhshi Khadije , Zarei Ahmad , Hoseinzadeh Edris , Gholizadeh Abdolmajid 
Published: April 2024

AbstractElevated levels of metal(loid)s in soil may pose potential threats to the ecosystem and can be harmful for human health. The concentrations of As, Cd, Pb, Cr and Ni were determined in agricultural soil collected from 45 pistachio orchards around Feizabad city, Khorasan Razavi province, Iran using ICP-OES. Also, soil pollution indices including contamination factor (CF), pollution load index (PLI) and geo-accumulation index (Igeo) were evaluated. In addition, non-carcinogenic and carcinogenic risk indices were estimated. The mean concentrations of metal(loid)s were in the order of Ni = 466.256 > Cr = 120.848 > Pb = 12.009 > As = 5.486 > Cd = 0.394 mg/kg. Concentrations of As, Cd and Pb in the soil samples were within their respective permissible limits set by World Health Organization (WHO). But concentrations of Cr and Ni in 84.4 and 100% of the samples, respectively exceeded the WHO allowable limits. The CF, PLI and Igeo showed that soil of some of the pistachio orchards was contaminated with some metals. The possible sources of the metals in the soil are application of pesticides, chemical fertilizers, manures as well as irrigation water. Hazard quotient (HQ) ad Hazard index (HI) values from soil of all the orchards were found to be well below the respective threshold limit (1), suggesting that there is no immediate non-cancer threat arising from the contamination at all the orchards with metal(loid)s for children and adults. The highest cancer risk values (1.13E-02 for children and 1.25E-03 for adults) were estimated for Ni in the soil. Collectively, this study provides valuable information to improve the soil in the pistachio orchards to reduce metal(loid)s contamination and minimize the associated health risks to the population in the area.
Joint transformer architecture in brain 3D MRI classification: its application in Alzheimer’s disease classification
Authors: Alp Sait , Akan Taymaz , Bhuiyan Md. Shenuarin , Disbrow Elizabeth A. , Conrad Steven A. , Vanchiere John A. , Kevil Christopher G. , Bhuiyan Mohammad A. N. 
Published: April 2024

AbstractAlzheimer’s disease (AD), a neurodegenerative disease that mostly affects the elderly, slowly impairs memory, cognition, and daily tasks. AD has long been one of the most debilitating chronic neurological disorders, affecting mostly people over 65. In this study, we investigated the use of Vision Transformer (ViT) for Magnetic Resonance Image processing in the context of AD diagnosis. ViT was utilized to extract features from MRIs, map them to a feature sequence, perform sequence modeling to maintain interdependencies, and classify features using a time series transformer. The proposed model was evaluated using ADNI T1-weighted MRIs for binary and multiclass classification. Two data collections, Complete 1Yr 1.5T and Complete 3Yr 3T, from the ADNI database were used for training and testing. A random split approach was used, allocating 60% for training and 20% for testing and validation, resulting in sample sizes of (211, 70, 70) and (1378, 458, 458), respectively. The performance of our proposed model was compared to various deep learning models, including CNN with BiL-STM and ViT with Bi-LSTM. The suggested technique diagnoses AD with high accuracy (99.048% for binary and 99.014% for multiclass classification), precision, recall, and F-score. Our proposed method offers researchers an approach to more efficient early clinical diagnosis and interventions.
Modulation instability in nonlinear media with sine-oscillatory nonlocal response function and pure quartic diffraction
Authors: Yang Yuwen , Shen Ming 
Published: April 2024

AbstractModulation instability of one-dimensional plane wave is demonstrated in nonlinear Kerr media with sine-oscillatory nonlocal response function and pure quartic diffraction. The growth rate of modulation instability, which depends on the degree of nonlocality, coefficient of quartic diffraction, type of the nonlinearity and the power of plane wave, is analytically obtained with linear-stability analysis. Different from other nonlocal response functions, the maximum of the growth rate in media with sine-oscillatory nonlocal response function occurs always at a particular wave number. Theoretical results of modulation instability are confirmed numerically with split-step Fourier transform. Modulation instability can be controlled flexibly by adjusting the degree of nonlocality and quartic diffraction.
Multiple factors and features dictate the selective production of ct-siRNA in Arabidopsis
Authors: Feng Li , Yan Wei , Tang Xianli , Wu Huihui , Pan Yajie , Lu Dongdong , Ling-hu Qianyan , Liu Yuelin , Liu Yongqi , Song Xiehai , Ali Muhammad , Fang Liang , Guo Hongwei , Li Bosheng 
Published: April 2024

AbstractCoding transcript-derived siRNAs (ct-siRNAs) produced from specific endogenous loci can suppress the translation of their source genes to balance plant growth and stress response. In this study, we generated Arabidopsis mutants with deficiencies in RNA decay and/or post-transcriptional gene silencing (PTGS) pathways and performed comparative sRNA-seq analysis, revealing that multiple RNA decay and PTGS factors impede the ct-siRNA selective production. Genes that produce ct-siRNAs often show increased or unchanged expression and typically have higher GC content in sequence composition. The growth and development of plants can perturb the dynamic accumulation of ct-siRNAs from different gene loci. Two nitrate reductase genes, NIA1 and NIA2, produce massive amounts of 22-nt ct-siRNAs and are highly expressed in a subtype of mesophyll cells where DCL2 exhibits higher expression relative to DCL4, suggesting a potential role of cell-specific expression of ct-siRNAs. Overall, our findings unveil the multifaceted factors and features involved in the selective production and regulation of ct-siRNAs and enrich our understanding of gene silencing process in plants.
Quantifying maternal investment in mammals using allometry
Authors: Huijsmans Tim E.R.G. , Courtiol Alexandre , Van Soom Ann , Smits Katrien , Rousset François , Wauters Jella , Hildebrandt Thomas B. 
Published: April 2024

AbstractMaternal investment influences the survival and reproduction of both mothers and their progeny and plays a crucial role in understanding individuals’ life-history and population ecology. To reveal the complex mechanisms associated with reproduction and investment, it is necessary to examine variations in maternal investment across species. Comparisons across species call for a standardised method to quantify maternal investment, which remained to be developed. This paper addresses this limitation by introducing the maternal investment metric – MI – for mammalian species, established through the allometric scaling of the litter mass at weaning age by the adult mass and investment duration (i.e. gestation + lactation duration) of a species. Using a database encompassing hundreds of mammalian species, we show that the metric is not highly sensitive to the regression method used to fit the allometric relationship or to the proxy used for adult body mass. The comparison of the maternal investment metric between mammalian subclasses and orders reveals strong differences across taxa. For example, our metric confirms that Eutheria have a higher maternal investment than Metatheria. We discuss how further research could use the maternal investment metric as a valuable tool to understand variation in reproductive strategies.
Spatial modeling connecting childhood atopic dermatitis prevalence with household exposure to pollutants
Authors: Ratley Grace , Zeldin Jordan , Sun Ashleigh A. , Yadav Manoj , Chaudhary Prem Prashant , Myles Ian A. 
Published: April 2024

Abstract
Background
Atopic dermatitis (AD) is a chronic, inflammatory disease characterized by dry, pruritic skin. In the U.S., the prevalence of AD has increased over three-fold since the 1970s. We previously reported a geographic association between isocyanate-containing air pollution and AD as well as mechanistic data demonstrating that isocyanates induce skin dysbiosis and activate the host itch receptor TRPA1. However, non-spatial models are susceptible to spatial confounding and may overlook other meaningful associations.

Methods
We added spatial analysis to our prior model, contrasting pollution data with clinical visits. In addition, we conducted a retrospective case-control survey of childhood exposure to BTEX-related products. Finally, we assessed implicated compounds, in pure form and as part of synthetic fabric, for their effect on the growth and metabolism of skin commensal bacteria.

Results
Spatial analysis implicate benzene, toluene, ethylbenzene, and, most significantly, xylene (BTEX) compounds. Survey odds ratios for AD were significant for xylene-derived polyester bed sheets (OR = 9.5; CI 2.2–40.1) and diisocyanate-containing wallpaper adhesive (OR = 6.5; CI 1.5–27.8). Staphylococcus aureus lives longer on synthetic textiles compared to natural textiles. Meanwhile, synthetic fabric exposure shifts the lipid metabolism of health-associated commensals (Roseomonas mucosa and S. epidermidis) away from therapeutic pathways.

Conclusions
We propose that BTEX chemicals in their raw forms and in synthetic products represent a unifying hypothesis for environmentally induced AD flares through their ability to create dysbiosis in the skin microbiota and directly activate TRPA1. Unequal distribution of these pollutants may also influence racial disparities in AD rates.
Unlocking the Potentials of Biodegradable Plastics with Proper Management and Evaluation at Environmentally Relevant Concentrations
Authors: Yu Yingxue , Flury Markus 
Published: April 2024

AbstractBiodegradable plastics have been proposed as an alternative to conventional plastics for many applications, such as single-use plastic bags, disposable cutleries and tablewares, and agricultural plastic mulch films. However, concerns have arisen about environmental sustainability of biodegradable plastics, especially regarding degradability, generation of biodegradable micro- and nanoplastics, and release of additives. Here, we critically evaluate literature on the degradation and ecotoxicity of biodegradable plastics with the consideration of environmentally relevant concentrations. Our evaluation suggests that, provided with proper disposal and full biodegradation, biodegradable plastics, including biodegradable micro- and nanoplastics, would not accumulate substantially in the environment and would be far from reaching concentrations at which negative impacts on ecosystems can be expected. In addition, we highlight existing regulatory efforts to prevent adverse ecotoxicity of biodegradable plastics. To ensure timely biodegradation under various disposal conditions, we propose to calibrate the actual biodegradability in disposal environments against the intrinsic biodegradability in standards. Further, we recommend to supplement biodegradability certificates on biodegradable plastics with clear disposal instructions, to ensure proper end-of-life management. With proper testing, comprehensive labeling, and effective management, we believe that, for certain applications, biodegradable plastics are a promising substitute for conventional plastics.
Recursive attention collaboration network for single image de‐raining
Authors: Li Zhitong , Li Xiaodong , Gong Zhaozhe , Yu Zhensheng 
Published: April 2024

AbstractSingle‐image rain removal is an important problem in the field of computer vision aimed at recovering clean images from rainy images. In recent years, data‐driven convolutional neural network (CNN)‐based rain removal methods have achieved significant results, but most of them cannot fully focus on the contextual information in rain‐containing images, which leads to the failure of recovering some of the background details of the images that have been corrupted due to the aggregation of rain streaks. With the success of Transformer‐based models in the field of computer vision, global features can be easily acquired to better help recover details in the background of an image. However, Transformer‐based models often require a large number of parameters during the training process, which makes the training process very difficult and makes it difficult to apply them to specific devices for execution in reality. The authors propose a Recursive Attention Collaboration Network, which consists of a recursive Swin‐transformer block (STB) and a CNN‐based feature fusion block. The authors designed the Recursively Integrate Transformer Block (RITB), which consists of several STBs recursively connected, that can effectively reduce the number of parameters of the model. The final part of the module can integrate the local information from the STBs. The authors also design the Feature Enhancement Block, which can better recover the details of the background information corrupted by rain streaks of different density shapes through the features passed from the RITB. Experiments show that the proposed network has an effective rain removal effect on both synthetic and real datasets and has fewer model parameters than other mainstream methods.
An analytical adaptive optimal control approach without solving HJB equation for nonlinear systems with input constraints
Authors: Sereshki Zahra Tavanaei , Talebi Heidar Ali , Abdollahi Farzaneh 
Published: April 2024

AbstractThis paper presents an analytical method to solve the optimal control problem for affine nonlinear systems with unknown drift dynamics. A new non‐quadratic cost function over an infinite horizon is presented that considers input constraints and includes the cost of the feed‐forward component of the control law. The mean value theorem for vector‐valued functions has been used to derive an integral form of this theorem. Based on this theorem, a rigorous proof is provided demonstrating that the cost function can be converted into another form. In the presence of input constraints, this converted form enables extracting the optimal control solution without solving the HJB equation. Additionally, unknown nonlinearity effects in drift dynamics are compensated in the control input. This is accomplished by estimating the unknown drift dynamics via an adaptive neural network (NN) approach. It is proven that the states and weights of NN are uniformly ultimately bounded based on a Lyapunov technique. The necessary and sufficient conditions are provided that ensure the optimality of the infinite horizon optimal control problem with a discount factor. As a result, it is demonstrated that the proposed approach satisfies the optimality criteria. To evaluate the effectiveness of the proposed approach, simulation examples are provided.
Effects of electrothermal ageing on dielectric performance of metallised biaxial orientation polypropylene film capacitors in strong magnetic fields
Authors: Liu Haoliang , Du Boxue , Xiao Meng , Chen Ke , Ma Yanwei 
Published: April 2024

AbstractThe dielectric performance of the pristine and the electrothermal‐aged metallised polypropylene capacitors are investigated under different magnetic fields. The energy storage capacity decreases under the magnetic field. At 12 T, the capacitance value of the pristine capacitors decreases by 8.4%–17% and that of the aged capacitors declines by 15%–20%. The dielectric loss is reduced by 2.6%–6.3%, but the equivalent series resistance shows an 8.3%–23.1% growth. The leakage conductivity increases to 202%–354%, which leads to a weakened voltage holding capacity. In addition to the effects of the magnetic fields, the impacts of ageing have also been investigated. The effects of the magnetic field and ageing on the electrical parameters of the capacitors are discussed separately. The molecular chains of the dielectric are oxidised and decomposed during the ageing process, which reduces the insulating properties of the dielectric. The magnetic field inhibits polarisation by changing the polarisation behaviour through Lorentz force and excites the electrons to enhance charge transmission.
Multi‐port medium‐frequency PET topology for integrating photovoltaic generation with battery storage
Authors: Li Xuejiao , Wang Mingyan , Zhu Bingda , Liu Chuang 
Published: April 2024

AbstractThis paper proposes a multi‐port medium‐frequency power electronic transformer (PET) topology for integrating photovoltaic (PV) generation with battery storage (BS). Firstly, this proposed PET provides multiple ports for renewable energy grid generation, so that it can achieve multi‐energy source management and energy complementary. Secondly, different from the conventional topology for renewable energy grid connected system, the proposed PET topology is safer and more reliable due to the separate connection of PV and BS through the voltage source converter to the primary winding of the PET. Finally, the PET only uses a single medium‐frequency transformer for voltage regulation and electrical isolation, so that it can avoid the use of DC capacitors in the traditional line/high‐frequency transformers, reduce the PET volume and its costs, as well as simplify the control strategy. The PET topology is introduced in detail and the simulation results verify the feasibility of the proposed topology.
Fresh view of the hot brown dwarf HD 984 B through high-resolution spectroscopy
Authors: Costes J. C. , Xuan J. W. , Vigan A. , Wang J. , D’Orazi V. , Mollière P. , Baker A. , Bartos R. , Blake G. A. , Calvin B. , Cetre S. , Delorme J. , Doppmann G. , Echeveri D. , Finnerty L. , Fitzgerald M. P. , Hsu C. , Jovanovic N. , Lopez R. , Mawet D. , Morris E. , Pezzato J. , Phillips C. L. , Ruffio J. , Sappey B. , Schneeberger A. , Schofield T. , Skemer A. J. , Wallace J. K. , Wang J. 
Published: April 2024

Context. High-resolution spectroscopy has the potential to drive a better understanding of the atmospheric composition, physics, and dynamics of young exoplanets and brown dwarfs, bringing clear insights into the formation channel of individual objects.
Aims. Using the Keck Planet Imager and Characterizer (KPIC; R « 35 000), we aim to characterize a young brown dwarf HD 984 B. By measuring its C/O and 12CO/13CO ratios, we expect to gain new knowledge about its origin by confirming the difference in the formation pathways between brown dwarfs and super-Jupiters.
Methods. We analysed the KPIC high-resolution spectrum (2.29–2.49 μm) of HD 984 B using an atmospheric retrieval framework based on nested sampling and petitRADTRANS, using both clear and cloudy models.
Results. Using our best-fit model, we find C/O = 0.50 ± 0.01 (0.01 is the statistical error) for HD 984 B which agrees with that of its host star within 1σ (0.40 ± 0.20). We also retrieve an isotopolog 12CO/13CO ratio of 98-25+20 in its atmosphere, which is similar to that of the Sun. In addition, HD 984 B has a substellar metallicity with [Fe/H] =-0.62-0.02+0.02. Finally, we find that most of the retrieved parameters are independent of our choice of retrieval model.
Conclusions. From our measured C/O and 12CO/13CO, the favored formation mechanism of HD 984 B seems to be via gravitational collapse or disk instability and not core accretion, which is a favored formation mechanism for giant exoplanets with m < 13 MJup and semimajor axis between 10 and 100 au. However, with only a few brown dwarfs with a measured 12CO/13CO ratio, similar analyses using high-resolution spectroscopy will become essential in order to determine planet formation processes more precisely.