bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluating stability of attenuated Sabin and two novel type 2 oral poliovirus vaccines in children
Authors: Wahid Rahnuma , Mercer Laina , Gast Chris , De Leon Tirza , Sáez-Llorens Xavier , Fix Alan , Macadam Andrew , Stephens Laura , Chumakov Konstantin , Smits Saskia L. , Murreddu Marta , Konopka-Anstadt Jennifer L. , Steven Oberste M. , Burns Cara C. , Andino Raul , Bachtiar Novilia Sjafri , Tritama Erman , Bandyopadhyay Ananda S. , Aguirre Gabriela , Rüttimann Ricardo , Konz John O. 
Published: February 2022

AbstractNovel oral poliovirus vaccine type 2 (nOPV2) is being developed to reduce the rare occurrence of disease and outbreaks associated with the genetic instability of the Sabin vaccine strains. Children aged 1 to 5 years were enrolled in two related clinical studies to assess safety, immunogenicity, shedding rates and properties of the shed virus following vaccination with nOPV2 (two candidates) versus traditional Sabin OPV type 2 (mOPV2). The anticipated pattern of reversion and increased virulence was observed for shed Sabin-2 virus, as assessed using a mouse model of poliovirus neurovirulence. In contrast, there were significantly reduced odds of mouse paralysis for shed virus for both nOPV2 candidates when compared to shed Sabin-2 virus. Next-generation sequencing of shed viral genomes was consistent with and further supportive of the observed neurovirulence associated with shed Sabin-2 virus, as well as the reduced reversion to virulence of shed candidate viruses. While shed Sabin-2 showed anticipated A481G reversion in the primary attenuation site in domain V in the 5’ untranslated region to be associated with increased mouse paralysis, the stabilized domain V in the candidate viruses did not show polymorphisms consistent with reversion to neurovirulence. The available data from a key target age group for outbreak response confirm the superior genetic and phenotypic stability of shed nOPV2 strains compared to shed Sabin-2 and suggest that nOPV2 should be associated with less paralytic disease and potentially a lower risk of seeding new outbreaks.
Modelling the emergence dynamics of the western corn rootworm beetle (Diabrotica virgifera virgifera)
Authors: Jaksons Rodelyn , Falkner Katharina , Moltchanova Elena 
Published: February 2022

AbstractThe western corn rootworm is an invasive species to Europe and is a major agricultural pest that causes widespread economic and yield losses to maize producers. The Gompertz curve was originally used to model human population mortality. It is a sigmoidal curve where the beginning and end of a period shows the slowest time for growth, and adequately describes observed dynamics of many phenomena. We propose the use of the Gompertz function in a Bayesian Hierarchical framework to model the emergence dynamics of the western corn rootworm beetle. The proposed model includes the use of climatic variables to assess how weather can influence the observed dynamics. We apply the model to Austrian monitoring data collected in 2004–2015.
Changes in rays’ swimming stability due to the phase difference between left and right pectoral fin movements
Authors: Sumikawa Hiroaki , Naraoka Yoshikazu , Fukue Takashi , Miyoshi Tasuku 
Published: February 2022

AbstractSwimming motions of rays that swim using undulation locomotion are not always symmetrical; there may be a phase difference between the left and right pectoral fins. However, few studies on the swimming of rays have mentioned left and right pectoral fin movements. Moreover, the effects of movements of the left and right pectoral fins on swimming have not been clarified. This paper describes a computational study of phase differences of pectoral fin movements in the swimming of rays with the validity of fluid analysis methods. The movement and shape of the ray were made based on previous biological research and pictures. An overset grid was used to reproduce the ray’s complex motions. The analysis was performed under four phase difference conditions: 0 $$T$$
T
($$T$$
T
is the period), 0.25 $$T$$
T
, 0.5 $$T$$
T
, and 0.75 $$T$$
T
. The results show that a phase difference between the left and right pectoral fin movements affects swimming stability and maneuverability but not propulsive efficiency. We suggest that the phase difference in pectoral fin movements is essential for the swimming of rays, and rays adjust the phase difference between the movement of the left and right pectoral fins to suit their purpose.
A community-based study on lower urinary tract symptoms in Malaysian males aged 40 years and above
Authors: Mohamad Anuar Mohamad Fuad , Solihin Rezali Muhammad , Mohamed Daud Mohamed Ashraf , Ismail Shaiful Bahari 
Published: February 2022

AbstractLower urinary tract symptoms (LUTS) commonly affecting ageing men and is thought to be linked with other comorbidities and unhealthy lifestyles. This study was performed to report the prevalence of LUTS and its association with quality of life (QOL) in urination and other related factors. The study was part of the National Health and Morbidity Survey (NHMS) 2019, a cross-sectional community-based survey in Malaysia. Validated self-administered bilingual International Prostate Symptom Score (IPSS) was used to assess the LUTS. Other comorbidities and unhealthy lifestyles were recorded using face-to-face interview and in-situ measurements such as anthropometry assessment and blood measurement. There were a total of 2251 respondents. 16.3% of the respondents had clinically significant LUTS (IPSS ≥ 8). LUTS was found to be significantly associated with QOL, age and inactive physical activities. Nocturia was the most prevalent and bothersome symptom. LUTS is a common condition and adversely affect QOL. Ageing and physically inactive males are associated with the development of LUTS. It is recommended to increase public awareness of the condition and availability of treatment options for LUTS. Any upcoming survey should have a more in-depth investigation such as clinical profiling of subjects.
Silica nanospheres KCC-1 as a good catalyst for the preparation of 2-amino-4H-chromenes by ultrasonic irradiation
Authors: Oboudatian Hourieh Sadat , Safaei-Ghomi Javad 
Published: February 2022

AbstractFibrous nano-silica sphere (KCC-1) has appeared as a good and efficient catalyst for ultrasonic irradiation conditions in chemical reactions. This catalyst has the unique properties such as a fibrous surface morphology, high surface area and high mechanical stability. The results indicated that the KCC-1 nanocatalyst could be used as high-performance catalysts under high temperature and pressure condition in organic reaction under ultrasonic irradiation. Morphology, structure, and composition of the fibrous nano-silica sphere were described by N2 adsorption–desorption analysis, scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray powder diffraction (XRD), thermogravimetric analysis (TGA) and Fourier-transform infrared spectroscopy (FT-IR). In this work, we used KCC-1@NH2 nanosilica as a basic catalyst for the preparation of chromenes under ultrasonic irradiation conditions for the first time. The recyclability, nontoxicity and high stability of the catalyst, combined with low reaction times and excellent yields, make the present protocol very useful for the synthesis of the title products under ultrasonic conditions. The produced products were confirmed via 1H NMR, 13C NMR, FT-IR analysis.
Two-dimensional finite quantum Hall clusters of electrons with anisotropic features
Authors: Ciftja Orion 
Published: February 2022

AbstractLow-dimensional nano and two-dimensional materials are of great interest to many disciplines and may have a lot of applications in fields such as electronics, optoelectronics, and photonics. One can create quantum Hall phases by applying a strong magnetic field perpendicular to a two-dimensional electron system. One characterizes the nature of the system by looking at magneto-transport data. There have been a few quantum phases seen in past experiments on GaAs/AlGaAs heterostructures that manifest anisotropic magnetoresistance, typically, in high Landau levels. In this work, we model the source of anisotropy as originating from an internal anisotropic interaction between electrons. We use this framework to study the possible anisotropic behavior of finite clusters of electrons at filling factor 1/6 of the lowest Landau level.
An adaptive-neuro fuzzy inference system based-hybrid technique for performing load disaggregation for residential customers
Authors: Abbas Muhammad Zaigham , Sajjad Intisar Ali , Hussain Babar , Liaqat Rehan , Rasool Akhtar , Padmanaban Sanjeevikumar , Khan Baseem 
Published: February 2022

AbstractEffective and efficient use of energy is key to sustainable industrial and economic growth in modern times. Demand-side management (DSM) is a relatively new concept for ensuring efficient energy use at the consumer level. It involves the active participation of consumers in load management through different incentives. To enable the consumers for efficient energy management, it is important to provide them information about the energy consumption patterns of their appliances. Appliance load monitoring (ALM) is a feedback system used for providing feedback to customers about their power consumption of individual appliances. For accessing appliance power consumption, the determination of the operating status of various appliances through feedback systems is necessary. Two major approaches used for ALM are intrusive load monitoring (ILM) and non-intrusive load monitoring (NILM). In this paper, a hybrid adaptive-neuro fuzzy inference system (ANFIS) is used as an application for NILM. ANFIS model being sophisticated was difficult to work with, but ANFIS model helps to achieve better results than other competent approaches. An ANFIS system is developed for extracting appliance features and then a fine tree classifier is used for classifying appliances having more than 1 kW power rating based on the extracted feature. Several case studies have been performed using ANFIS on a publicly available United Kingdom Domestic Appliance Level Electricity (UK-Dale dataset). The simulation results obtained from the ANFIS for NILM are compared with relevant literature to show the performance of the proposed technique. The results prove that the novel application of ANFIS gives better performance for solving the NILM problem as compared to the other existing techniques.
Using energy time–frequency of Hilbert Huang transform to analyze the performance of the variable valve timing engine
Authors: Mohammed Arshed Abdulhamed , Haris Sallehuddin Mohamed 
Published: February 2022

AbstractIn this study, a diagnosis method was successfully implemented to identify different sounds coming from individual mechanical parts within a group of engine moving parts controlled through a variable valve timing system. The novelty of this diagnosis method is in the determination of specific sounds coming from each part within this group when they are in good working condition and without any defects. This will facilitate in early detection of faults occurring on the parts, identified through changes in the sound wave energy. Through this study, this diagnosis method was validated in three ways, namely the consistency of the results with previous studies, the synchronization of sounds from mechanical parts in overlapping cases, and the cross-correlation of engine sound modes that results from analysis using the Hilbert Huang Transform. In this paper, the distribution of sound energy according to its frequencies was utilized to distinguish which of the engine combustion chambers of a Dodge Journey 2.4 was faulty. To conduct that, the noise-based test technique was selected to record the engine sound. The results show that there is a link between the RMS energy of the engine sound and the engine output torque.
Machine learning prediction and tau-based screening identifies potential Alzheimer’s disease genes relevant to immunity
Authors: Binder Jessica , Ursu Oleg , Bologa Cristian , Jiang Shanya , Maphis Nicole , Dadras Somayeh , Chisholm Devon , Weick Jason , Myers Orrin , Kumar Praveen , Yang Jeremy J. , Bhaskar Kiran , Oprea Tudor I. 
Published: February 2022

AbstractWith increased research funding for Alzheimer’s disease (AD) and related disorders across the globe, large amounts of data are being generated. Several studies employed machine learning methods to understand the ever-growing omics data to enhance early diagnosis, map complex disease networks, or uncover potential drug targets. We describe results based on a Target Central Resource Database protein knowledge graph and evidence paths transformed into vectors by metapath matching. We extracted features between specific genes and diseases, then trained and optimized our model using XGBoost, termed MPxgb(AD). To determine our MPxgb(AD) prediction performance, we examined the top twenty predicted genes through an experimental screening pipeline. Our analysis identified potential AD risk genes: FRRS1, CTRAM, SCGB3A1, FAM92B/CIBAR2, and TMEFF2. FRRS1 and FAM92B are considered dark genes, while CTRAM, SCGB3A1, and TMEFF2 are connected to TREM2-TYROBP, IL-1β-TNFα, and MTOR-APP AD-risk nodes, suggesting relevance to the pathogenesis of AD.
Structural and functional analyses explain Pea KAI2 receptor diversity and reveal stereoselective catalysis during signal perception
Authors: Guercio Angelica M. , Torabi Salar , Cornu David , Dalmais Marion , Bendahmane Abdelhafid , Le Signor Christine , Pillot Jean-Paul , Le Bris Philippe , Boyer François-Didier , Rameau Catherine , Gutjahr Caroline , de Saint Germain Alexandre , Shabek Nitzan 
Published: February 2022

AbstractKAI2 proteins are plant α/β hydrolase receptors which perceive smoke-derived butenolide signals and endogenous, yet unidentified KAI2-ligands (KLs). The number of functional KAI2 receptors varies among species and KAI2 gene duplication and sub-functionalization likely plays an adaptative role by altering specificity towards different KLs. Legumes represent one of the largest families of flowering plants and contain many agronomic crops. Prior to their diversification, KAI2 underwent duplication resulting in KAI2A and KAI2B. Here we demonstrate that Pisum sativum KAI2A and KAI2B are active receptors and enzymes with divergent ligand stereoselectivity. KAI2B has a higher affinity for and hydrolyses a broader range of substrates including strigolactone-like stereoisomers. We determine the crystal structures of PsKAI2B in apo and butenolide-bound states. The biochemical, structural, and mass spectra analyses of KAI2s reveal a transient intermediate on the catalytic serine and a stable adduct on the catalytic histidine, confirming its role as a bona fide enzyme. Our work uncovers the stereoselectivity of ligand perception and catalysis by diverged KAI2 receptors and proposes adaptive sensitivity to KAR/KL and strigolactones by KAI2B.
Language Control and Code-Switching in Bilingual Children With Developmental Language Disorder
Authors: Gross Megan C. , Kaushanskaya Margarita 
Published: February 2022

Purpose:
The current study examined language control and code-switching in bilingual children with developmental language disorder (DLD) compared to bilingual peers with typical language development (TLD). In addition, proficiency in each language and cognitive control skills were examined as predictors of children's tendency to engage in cross-speaker and intrasentential code-switching.

Method:
The participants were 62 Spanish/English bilingual children, ages 4;0–6;11 (years;months), including 15 children with DLD and 47 children with TLD. In a scripted confederate dialogue task to measure language control, children took turns describing picture scenes with video partners who were monolingual speakers of English or Spanish. The Dimensional Change Card Sort indexed cognitive control, the Bilingual English Spanish Assessment assisted in identifying DLD, and parent ratings from the Inventory to Assess Language Knowledge indexed proficiency in Spanish and English.

Results:

Children with DLD were more likely to engage in
cross-speaker code-switching
from Spanish to English (i.e., responding in English when addressed in Spanish) than children with TLD, even when controlling for proficiency in each language.
Intrasentential code-switching
(i.e., integrating both languages within an utterance) did not differ between groups. Cognitive control was more associated with cross-speaker than with intrasentential code-switching.

Conclusions:
These findings highlight the need to consider cross-speaker and intrasentential code-switching separately when seeking distinguishing features of code-switching in bilingual children with DLD. The use of increased cross-speaker code-switching by children with DLD especially with Spanish speakers highlights the need for increased support of home language use.
Working Memory Predicts New Word Learning Over and Above Existing Vocabulary and Nonverbal IQ
Authors: Gray Shelley I. , Levy Roy , Alt Mary , Hogan Tiffany P. , Cowan Nelson 
Published: February 2022

Purpose:The purpose of this study was to use an established model of working memory in children to predict an established model of word learning to determine whether working memory explained word learning variance over and above the contributions of expressive vocabulary and nonverbal IQ.Method:One hundred sixty-seven English-speaking second graders (7- to 8-year-olds) with typical development from two states participated. They completed a comprehensive battery of working memory assessments and six word learning tasks that assessed the creation, storage, retrieval, and production of phonological and semantic representations of novel nouns and verbs and the ability to link those representations.Results:A structural equation model with expressive vocabulary, nonverbal IQ, and three working memory factors predicting two word learning factors fit the data well. When working memory factors were entered as predictors after expressive vocabulary and nonverbal IQ, they explained 45% of the variance in the phonological word learning factor and 17% of the variance in the semantic word learning factor. Thus, working memory explained a significant amount of word learning variance over and above expressive vocabulary and nonverbal IQ.Conclusion:Results show that working memory is a significant predictor of dynamic word learning over and above the contributions of expressive vocabulary and nonverbal IQ, suggesting that a comprehensive working memory assessment has the potential to identify sources of word learning difficulties and to tailor word learning interventions to a child's working memory strengths and weaknesses.Supplemental Material:https://doi.org/10.23641/asha.19125911
Optimal control of nonlinear Markov jump systems by control parametrisation technique
Authors: Jin Liqiang , Yin Yanyan , Loxton Ryan , Lin Qun , Liu Fei , Teo Kok Lay 
Published: February 2022

AbstractThis paper considers an optimal control problem of nonlinear Markov jump systems with continuous state inequality constraints. Due to the presence of continuous‐time Markov chain, no existing computation method is available to solve such an optimal control problem. In this paper, a derandomisation technique is introduced to transform the nonlinear Markov jump system into a deterministic system, which simultaneously gives rise to an equivalent deterministic dynamic optimisation problem. The control parametrisation technique is then used to partition the time horizon into a sequence of subintervals such that the control function is approximated by a piecewise constant function consistent with the partition. The heights of the piecewise constant function on the corresponding subintervals are taken as decision variables to be optimised. In this way, the approximate dynamic optimisation problem is an optimal parameter selection problem, which can be viewed as a finite dimensional optimisation problem. To solve it using a gradient‐based optimisation method, the gradient formulas of the cost function and the constraint functions are derived. Finally, a real‐world practical problem involving a bioreactor tank model is solved using the method proposed.
Multi‐scale network for remote sensing segmentation
Authors: Wang Gaihua , Zhai Qianyu , Lin Jinheng 
Published: February 2022

AbstractThe semantic segmentation of remote sensing images is a critical and challenging task. How to easily and reliably segment useful information from vast remote sensing images is a significant issue. Many methods based on convolutional neural networks have been widely explored to obtain more accurate segmentation from remote sensing images. However, due to the uniqueness of remote sensing images, such as the dramatic changes in the scale of the target object, the results are not satisfactory. To solve the problem, a special network is designed: (1) Create a new backbone network. Compared with ResNet50, the proposed method extracts features of varying sizes more effectively. (2) Reduce spatial information loss. Building a hybrid location module to compensate for the position loss caused by the down‐sampling operation. (3) Models with high discriminant ability. In order to improve the discrimination ability of the model, a novel auxiliary loss function is designed to constrain the distance between inter‐class and intra‐class. The proposed algorithm is tested on remote sensing datasets (e.g., NWPU‐45, DLRSD, and WHDLD). The experimental results show that this method obtains the best results and achieves state‐of‐the‐art performance.
Galactic center gamma-ray production by cosmic rays from stellar winds and Sgr A East
Authors: Scherer Andrés , Cuadra Jorge , Bauer Franz E. 
Published: February 2022

Context. The High Energy Stereoscopic System, the Major Atmospheric Gamma-ray Imaging Cherenkov Telescope, and the Very Energetic Radiation Imaging Telescope Array System have observed diffuse gamma-ray emission strongly correlated with the central molecular zone in the Galactic center. The most accepted scenario to generate this emission is via a hadronic interaction between cosmic rays (CRs) and ambient gas, where CRs are accelerated from a central and continuous source of 1 PeV protons.
Aims. We explore the influence of the three-dimensional (3D) shape of the central molecular zone on the indirect observation of the CR energy density via gamma-ray detection.
Methods. We simulated synthetic gamma-ray maps using a CR diffusion model with spherical injection, one isotropic diffusion coefficient, no advection, and mono-energetic particles of 1 PeV. Also, we used two different 3D gas distributions considering the observed gas column density, both with and without an inner cavity.
Results. We find that when using a persistent CR source, a disk-like gas distribution is needed to reproduce the existing CR indirect observations. This is in agreement with the continuous gas distribution implied by some dynamical models and studies based on the comparison of emission and absorption molecular lines. However, it contradicts several models of the central molecular zone, which imply that this structure has a significant inner cavity. This tension can be reconciled by an additional, impulsive CR injection.
Conclusions. If the central molecular zone has a cavity, a composite CR population, coming from the stellar winds of the Wolf-Rayet stars in the central 0.5 pc and the supernova Sgr A East, produces a good match to the observed gamma-ray morphology in the Galactic center.