bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Sentinel Bait Station: an automated, intelligent design pest animal baiting system
Authors: Charlton G. , Falzon G. , Shepley A. , Fleming P. J. S. , Ballard G. , Meek P. D. 
Published: April 2023

Context Ground baiting is a strategic method for reducing vertebrate pest populations. Best practice involves maximising bait availability to the target species, although sustaining this availability is resource intensive because baits need to be replaced each time they are taken. This study focused on improving pest population management through the novel baiting technique outlined in this manuscript, although there is potential use across other species and applications (e.g. disease management). Aims To develop and test an automated, intelligent, and semi-permanent, multi-bait dispenser that detects target species before distributing baits and provides another bait when a target species revisits the site. Methods We designed and field tested the Sentinel Bait Station, which comprises a camera trap with in-built species-recognition capacity, wireless communication and a dispenser with the capacity for five baits. A proof-of-concept prototype was developed and validated via laboratory simulation with images collected by the camera. The prototype was then evaluated in the field under real-world conditions with wild-living canids, using non-toxic baits. Key results Field testing achieved 19 automatically offered baits with seven bait removals by canids. The underlying image recognition algorithm yielded an accuracy of 90%, precision of 83%, sensitivity of 68% and a specificity of 96% throughout field testing. The response time of the system, from the point of motion detection (within 6–10 m and the field-of-view of the camera) to a bait being offered to a target species, was 9.81 ± 2.63 s. Conclusion The Sentinel Bait Station was able to distinguish target species from non-target species. Consequently, baits were successfully deployed to target species and withheld from non-target species. Therefore, this proof-of-concept device is able to successfully provide baits to successive targets from secure on-board storage, thereby overcoming the need for daily bait replacement. Implications The proof-of-concept Sentinel Bait Station design, together with the findings and observations from field trials, confirmed the system can deliver multiple baits and increase the specificity in which baits are presented to the target species using artificial intelligence. With further refinement and operational field trials, this device will provide another tool for practitioners to utilise in pest management programs.
Gravito-electromagnetic fields and superconductors in a regime of weak static gravitational field
Authors: Das D K , Panda S , Das Salila 
Published: April 2023

Abstract
A Deeper interweaving of different scientific areas has always proven to be a powerful tool for improving our understanding of several fascinating physical aspects of the world. For example, researchers worldwide have investigated the intriguing existence of the interaction between gravity and superconductivity in recent decades, owing to its enormous conceptual implications and various potential applications. Different theories using various approaches and techniques have been proposed to predict these interactions. To study the anomalous couplings between the super condensate and local gravitational field, we provide a detailed calculation of the thermodynamic properties and coherence length on behalf of the gravitational wave vector. In addition, this study provides a framework for calculating the gravitational penetration depth compared with the electromagnetic (E.M.) penetration depth. Furthermore, we demonstrate macroscopic quantum interference events by applying the Josephson effect using a superconducting quantum interface device (SQUID) link. Finally, similar to other calculations, we demonstrate how the quantum of the gravity flux is used to manage a sinusoidally oscillating current. This phenomenon will help future researchers study the effects of gravitational perturbation on supercurrents and super-condensates, and the latter could be used as ‘gravitational antennas’ for gravitational wave detection.
Neutron stars in modified teleparallel gravity
Authors: Vilhena S.G. , Duarte S.B. , Dutra M. , Pompeia P.J. 
Published: April 2023

Abstract
We investigate compact objects in modified teleparallel gravity with realistic equations
of state. We propose a modification of Teleparallel Equivalent to General Relativity, then an
appropriate tetrad is applied to the field equations. A specific set of relations showing an
equivalency between our gravitational model and the New General Relativity is found. The
conservation equation implies that our Tolman-Oppenheimer-Volkoff equations are presented with an
effective gravitational coupling constant. Numerical analysis using realistic equations of state
is made, and the behavior of mass, radius, and the relation mass-radius as functions of a free
parameter of our model is also investigated.
The Study of Helium Variations in Star Clusters Using China Space Station Telescope
Authors: Ji Xin , Deng Licai , Chen Yang , Li Chengyuan , Liu Chao 
Published: April 2023

Abstract
The China Space Station Telescope (CSST) is a 2 m space-based optical-UV telescope. Its primary goal is to carry out a high-resolution photometric imaging survey of a 17,500 square degree sky area using the on board Survey Camera. With its wide field of view (1.1 square degrees) and a mosaic imager containing 640 million pixels, studying the different populations of stars within star clusters is highly feasible. The aim of this study is to assess the CSST’s ability to distinguish between stellar populations with varying helium abundance levels, with the help of Modules for Experiments in Stellar Astrophysics. The results of the CSST’s photometry for these different populations are presented by transferring the models into the CSST Survey Camera photometric system. The findings confirm that helium-enriched stellar populations will have unique patterns in the color–magnitude diagrams under the CSST photometric system, compared to normal stellar populations. The CSST, with its filters and wide field of view of the Survey Camera, provides a new avenue for the study of multiple populations in star clusters.
Calibration model averaging in chemical analysis: a case study for the method of standard additions
Authors: Pagliano Enea , Meija Juris 
Published: April 2023

Abstract
In this study we demonstrate that the method of standard additions can provide unreliable results in chemical analysis when the linear calibration model is forced to fit the data. A well designed standard addition experiment can still yield results biased by 10% when the analyst relies only on the linear model. Recently, the Joint Committee for Guides in Metrology (GUM-6) has emphasized the need to address the uncertainty inherent to the choice of measurement models and here we show how model averaging can provide a practical way to account for model uncertainty in the method of standard additions.
Evaluation method of the turbine impeller imbalance based on the headroom analysis
Authors: Ma Sixiang , Chang Feng , Zhang Feng , Yang Meng , Li Jian 
Published: April 2023

Abstract
Impeller imbalance is an unavoidable problem in the process of the operation of wind turbines, and it often has a serious impact on the safety and stability of wind turbines, thus shortening their life cycle. Aiming at the current problems, such as high cost and instability caused by the impeller imbalance in wind turbines, this paper proposes an assessment method for impeller imbalance in wind turbines based on image processing and headroom analysis. Firstly, the deep-learning image-processing technology is used to convert the video monitoring data into numerical data, and then the comprehensive imbalance index of the three blades based on the numerical data is calculated, so as to determine if an impeller imbalance problem exists or not. The proposed method was validated with the operation data of wind turbines in field and good results were achieved.
Effect of Different Droplet Impinging Models on Oil Film Formation of Diesel Engine’s Piston
Authors: Feng Shiquan , Xu Zengtian , Li Changqing , Wu Beibei , Yao Jia 
Published: April 2023

Abstract
After diesel fuel injection, when spray droplets in the air hit the wall, four types of impingement states will be formed: stick, rebound, spread, and splash. There are already many models describing the impingement of droplets on the wall. In order to analyze the impact of the droplet-wall model on the formation of oil film, this paper constructed a three-dimensional model of the diesel combustion in engine’s cylinder. The main part of the model was the simulation of the diesel fuel injection process, and different droplet collision models were used to calculate their influence on oil film formation of engine’s piston.
Research on Photovoltaic Power Prediction Based on BP Neural Network Algorithm
Authors: Zhang Bozhi , Wei Zirui , Li Shunjie , Zhou Lixia 
Published: April 2023

Abstract
The output power of photovoltaic (PV) power plant is influenced by the fluctuation of meteorological conditions, which, coupled with the intermittent nature of the power output, has raised concerns about the stability of power grid. According to the variations in meteorological conditions, PV power prediction technology can predict the PV output power in advance to decrease the influence of PV power generation on the stable operation of the power grid. In this paper, the PV power prediction model is built on Matlab simulation software with a BP neural network algorithm. After that, the power prediction calculation of a PV power station is carried out under the operation conditions of sunny and cloudy days. The results show that, in the periods of prediction, the power curve of the predicted value is close to the power curve of the real value, which demonstrates the great accuracy of the BP prediction model established in this paper.
Study of Site-specific Wind Turbine Residual Life based on Uncertainty Analysis
Authors: Zhang Haochen , Zhang Xingang , Feng Jiangzhe , Ren Huaihui 
Published: April 2023

Abstract
This paper investigated whether wind turbines have a residual life to ensure their continued safe and reliable operation after 20 years of design life. A modeling method for the load simulation of the wind turbine with a lack of design documents was proposed. A method for calculating the residual life of wind turbines based on site-specific load comparison analysis and uncertainty analysis was established. This method was applied to evaluate the residual life of 66 600 kW wind turbines at an old wind farm in northwest China. The equivalent loads of the turbine components were calculated under design conditions and actual operating conditions, and the residual lives of the turbine components were further evaluated by uncertainty analysis. The results showed that all components of these wind turbines had a residual life after operating over their 20-year design lives, and the wind farm could continue operating for at least 4.6 years.
Design of Lead Hybrid Halide Perovskite for Solar Cells
Authors: Ma Zi-Qian , Zhu Xiuli , Wang Chuanhui 
Published: April 2023

Abstract
Hybrid organic-inorganic halide perovskites solar cells have attracted extensive interest because of their outstanding properties, including an optimal band gap, high carrier mobility, and excellent optoelectronic merits. We study the electronic and crystal structural properties of hybrid organic-inorganic halide APbX3 (A = Cs, methylammonium (MA), formamidinium (FA), X = I, Br) perovskites using first-principles calculations based on density functional theory. We find that halide atoms and A-site cations strongly affect their structural and electronic properties. The radius of a halide atom and the size of an organic molecule determine their lattice parameters and bond length. A relatively large halide atom can increase the value of the lattice parameters (a and b). Meanwhile, the electronic properties (band gap & carrier effective mass) of the Pb-based hybrid halide APbX3 can be effectively modified by adopting appropriate A- and X-site atoms or organic sections. We predict that HOIPs may have outstanding potential in solar light harvesting with promoted power conversion efficiency due to a tunable band gap and excellent electronic properties.
Vaccination strategies in structured populations under partial immunity and reinfection
Authors: Rodriguez-Maroto Gabriel , Atienza-Diez Iker , Ares Saúl , Manrubia Susanna 
Published: April 2023

Abstract
Optimal protocols of vaccine administration to minimize the effects of infectious diseases depend on a number of variables that admit different degrees of control. Examples include the characteristics of the disease and how it impacts on different groups of individuals as a function of sex, age or socioeconomic status, its transmission mode, or the demographic structure of the affected population. Here we introduce a compartmental model of infection propagation with vaccination and reinfection and analyze the effect that variations on the rates of these two processes have on the progression of the disease and on the number of fatalities. The population is split into two groups to highlight the overall effects on disease caused by different relationships between vaccine administration and various demographic structures. As a practical example, we study COVID-19 dynamics in various countries using real demographic data. The model can be easily applied to any other disease transmitted through direct interaction between infected and susceptible individuals, and any demographic structure, through a suitable estimation of parameter values. Two main conclusions stand out. First, the higher the fraction of reinfected individuals, the higher the likelihood that the disease becomes quasi-endemic. Second, optimal vaccine roll-out depends on demographic structure and disease fatality, so there is no unique vaccination protocol, valid for all countries, that minimizes the effects of a specific disease. Simulations of the general model can be carried out at this interactive webpage Atienza (2021 S2iyrd model simulator).
Second root of dilute Bose-Fermi mixtures
Authors: Hryhorchak O , Pastukhov V 
Published: April 2023

Abstract
We discuss an equilibrium mean-field properties of mixtures consisting of bosons and spin-polarized fermionic atoms with a point-like interaction in an arbitrary dimension

2
<
d
<
4

. Particularly, besides the standard weak-coupling limit of the system with slightly depleted Bose condensate and almost ideal Fermi gas, we discuss the (meta)stable phase with dimers composed exactly of one boson and one fermion. The peculiarities of the fermion-dimer and the boson-dimer three-body effective interactions and their impact on the thermodynamic stability of the dilute Bose-Fermi mixtures are elucidated.
Beyond Motivations: A Qualitative Pilot Exploration of Women's Experiences Prior to Labiaplasty
Authors: Sharp Gemma , Draganidis Adriana , Hamori Christine , Oates Jayson , Fernando Anne Nileshni 
Published: April 2023

Abstract

Background
The demand for labiaplasty has increased rapidly over the last 10 to 15 years. Women's reasons for pursuing the procedure have been thoroughly documented in the literature, but other preoperative aspects are less well defined. These include women's expected outcomes, concerns about having the surgery, and the impacts of support from others in their personal lives as well as their treating team.

Objectives
The aim of this study was to explore women's preoperative labiaplasty experiences, particularly expectations, concerns, and interpersonal support.

Methods
Semistructured interviews were completed with 15 adult women in the United States and Australia who had undergone a labia minora reduction. The women were asked about their motivations for having a labiaplasty, expected outcomes, concerns regarding surgery, and support received from family members, friends, and the treating surgeon. The interviews were audio recorded, transcribed verbatim, and analyzed thematically.

Results
Two overarching themes with accompanying subthemes emerged from the analyses: (1) “motivations/influences” which included appearance concerns, physical discomfort, negative impacts on self-confidence, and negative experiences with partners and/or peers; and (2) “perceptions approaching labiaplasty procedure” where women reported concerns about recovery duration and impacts on sexual sensation as well as expectations for their postoperative vulvar appearance to be “neat,” “tidy,” and “natural.” In addition, the women stated that they felt well supported by their surgeons prior to the procedure, but some felt too embarrassed to seek support from family members and friends.

Conclusions
These new insights into women's preoperative experiences may assist clinical teams in enhancing their support and education of women seeking labiaplasty.

Level of Evidence: 4
A comprehensive assessment and comparison of tools for HLA class I peptide-binding prediction
Authors: Wang Meng , Kurgan Lukasz , Li Min 
Published: April 2023

Abstract
Human leukocyte antigen class I (HLA-I) molecules bind intracellular peptides produced by protein hydrolysis and present them to the T cells for immune recognition and response. Prediction of peptides that bind HLA-I molecules is very important in immunotherapy. A growing number of computational predictors have been developed in recent years. We survey a comprehensive collection of 27 tools focusing on their input and output data characteristics, key aspects of the underlying predictive models and their availability. Moreover, we evaluate predictive performance for eight representative predictors. We consider a wide spectrum of relevant aspects including allele-specific analysis, influence of negative to positive data ratios and runtime. We also curate high-quality benchmark datasets based on analysis of the consistency of the data labels. Results reveal that each considered method provides accurate results, which can be explained by our analysis that finds that their predictive models capture meaningful binding motifs. Although some methods are overall more accurate than others, we find that none of them is universally superior. We provide a comprehensive comparison of the convenience as well as the accuracy of the methods under specific prediction scenarios, such as for specific alleles, metrics of predictive performance and constraints on runtime. Our systematic and broad analysis provides informative clues to the users to identify the most suitable tools for a given prediction scenario and for the developers to design future methods.
HMMerge: an ensemble method for multiple sequence alignment
Authors: Park Minhyuk , Warnow Tandy 
Published: April 2023

Abstract

Motivation
Despite advances in method development for multiple sequence alignment over the last several decades, the alignment of datasets exhibiting substantial sequence length heterogeneity, especially when the input sequences include very short sequences (either as a result of sequencing technologies or of large deletions during evolution) remains an inadequately solved problem.

Results
We present HMMerge, a method to compute an alignment of datasets exhibiting high sequence length heterogeneity, or to add short sequences into a given ‘backbone’ alignment. HMMerge builds on the technique from its predecessor alignment methods, UPP and WITCH, which build an ensemble of profile HMMs to represent the backbone alignment and add the remaining sequences into the backbone alignment using the ensemble. HMMerge differs from UPP and WITCH by building a new ‘merged’ HMM from the ensemble, and then using that merged HMM to align the query sequences. We show that HMMerge is competitive with WITCH, with an advantage over WITCH when adding very short sequences into backbone alignments.

Availability and implementation
HMMerge is freely available at https://github.com/MinhyukPark/HMMerge.

Supplementary information
Supplementary data are available at Bioinformatics Advances online.
CurSa: scripts to curate metadata and sample genomes from GISAID for analysis and display in nextstrain and microreact
Authors: Delaye Luis 
Published: April 2023

Abstract
The coronavirus SARS-CoV-2 is the most sequenced pathogen ever, with several million genome copies deposited in the GISAID database. This large amount of genomic information poses non-trivial bioinformatic challenges for those interested in studying the evolution of SARS-CoV-2. One common problem when studying the phylogeny of the coronavirus in its geographical context is to count with accurate information of the location of the samples. However, this information is filled by hand by research groups all over the world and sometimes typos and inconsistencies are introduced in the metadata when submitting the sequences to GISAID. Correcting these errors is laborious and time-consuming. Here, we provide a suite of Perl scripts designated to facilitate the curation of this vital information and perform a random sampling of genome sequences if necessary. The scripts provided here can be used to curate geographic information in the metadata and sample the sequences from any country of interest to ease the preparation of files for Nextstrain and Microreact, thus accelerating evolutionary studies of this important pathogen. CurSa scripts are accessible via: https://github.com/luisdelaye/CurSa/.
A novel echocardiographic risk score for light-chain amyloidosis
Authors: Geenty Paul , Sivapathan Shanthosh , Stefani Luke D , Zada Matthew , Boyd Anita , Richards David , Kwok Fiona , Thomas Liza 
Published: April 2023

Abstract

Aims
The prognosis of light-chain (AL) amyloidosis, a plasma cell dyscrasia, is largely determined by the presence of cardiac involvement. Conventional staging is achieved using cardiac biomarkers (high-sensitivity troponin, N-terminal pro-beta natriuretic peptide) and free light-chain difference (Mayo staging). We sought to evaluate the role of echocardiographic parameters as prognostic markers in AL amyloidosis and examine their utility compared with conventional staging.

Methods and results
Seventy-five consecutive patients with AL amyloidosis reviewed at a referral amyloid clinic who underwent comprehensive echocardiographic assessment were retrospectively identified. The evaluated echocardiographic parameters included left ventricular (LV) ejection fraction, mass, diastolic function parameters, global longitudinal strain (GLS), and left atrial (LA) volume. Mortality was assessed through a review of clinical records. During a median follow-up of 51 months, 29/75 (39%) patients died. Patients who died had a larger LA volume (47 ± 12 vs. 35 ± 10 mL/m2, P &lt; 0.001) and a higher E/e′ (18 ± 10 vs. 14 ± 6, P = 0.026). Univariate clinical and echocardiographic predictors of survival included LA volume, E/e′, e′, LVGLS, and Mayo stage (at significance of P &lt; 0.1). Left atrial volume and LVGLS were significant determinants of mortality when examined using clinical cut-offs, although E/e′ was not. A composite echocardiographic risk score comprising LA volume and LVGLS provided similar prognostic performance to Mayo stage [area under the curve (AUC) 0.75, 95% confidence interval (CI) 0.64–0.85 vs. AUC 0.75, 95% CI 0.65–0.858, P = 0.91].

Conclusion
Left atrial volume and LVGLS were independent predictors of mortality in AL amyloidosis. A composite echocardiographic score combining LA volume and LVGLS has similar prognostic power to Mayo stage for all-cause mortality.