bluuebunny/crossref_metadata_2025_split huggingface dataset:
Differences in broiler bone, gut, and tissue mineral parameters, as influenced by broilers grouped based on bodyweight
Authors: Elvis-Chikwem Chinwendu L. , White Gavin A. , Burton Emily , O’Shea Cormac J. 
Published: January 2024

Context Variation in bodyweight is an undesirable feature in broiler production. Compositional differences between high- and low-bodyweight (BW) chicks in bone parameters and tissue mineral concentrations may provide insight into underlying causes of variation in BW. Aims This study aimed to investigate differences in bone measurements, tissue mineral concentrations, and gut parameters of Ross 308 male broiler chicks with identical diet and environmental conditions, but with distinct BW on Day 21 (D21). Methods A 3-week growth study was conducted involving 40 male, day-old chicks from the Ross 308 line. Chicks were reared in a deep-litter house with a controlled environment and the same commercial diet. On D21, BW data collected from chicks were used as a criterion to rank them into high- and low-BW groups (n = 11/group). Retrospective BW measurements were compared between groups. Birds were selected for assessing bone parameters, liver mineral profile, gut pH, gizzard neutral detergent fibre (NDF) and acid detergent fibre (ADF) contents. Key results Retrospective BW measurements among the high- and low-BW groups showed a consistent difference in BW between the two groups in early life. Tibial concentrations of manganese and strontium were significantly (P < 0.05) higher in the low-weight (LW) group relative to the high-weight (HW) group. Concentrations of manganese, cadmium and caesium in the liver tissue showed significant differences, with the LW group having higher concentration of these trace elements. The LW chicks had lower gizzard digesta pH, higher gizzard NDF and a statistical tendency for higher ADF concentrations compared to the HW group. Conclusions and implications In summary, broilers ranked on the basis of D21 BW showed differences in tibial bone, gut, and tissue mineral parameters. The LW group had lower gizzard pH and higher gizzard fibre content than did the HW group, which may be attributed to factors such as behavioural activities relating to more litter consumption among the LW group than the HW group.
Environmental DNA detection of spot-tailed quoll from soil is unlikely to be useful for routine monitoring
Authors: White Lauren C. , Nelson Jenny L. , Cardoso Maria , Pacioni Carlo 
Published: January 2024

Context Accurate monitoring data on species presence and distribution are crucial for effective conservation management. Environmental DNA (eDNA)-based techniques, in which species are detected from trace amounts of DNA found throughout the environment, are promising tools that may complement traditional monitoring methods and improve detection. However, imperfect detection is a feature of all survey methods that should be properly assessed so that the probability of detecting a target species’ DNA at a site where it is present (i.e. the sensitivity of the method) can be determined. The spot-tailed quoll (Dasyurus maculatus), a carnivorous marsupial found in eastern Australia, is a difficult species to detect as it is rare and has large home ranges, often in remote and difficult to access habitat. Aims In this study, we aimed to evaluate the feasibility of using eDNA soil analysis as a viable alternative or complement to traditional monitoring techniques for detecting spot-tailed quoll. Methods We developed a species-specific assay and validated it using synthetic oligos, tissue samples and soil collected from a captive quoll enclosure. We then assessed the assay on natural environment soil samples taken from the Snowy River region from communal quoll defecation sites (latrines) and from broader quoll habitat. We used amplification success data to model the concentration of quoll DNA in soil from different site types and calculate the sensitivity of our assay. Key results Sensitivity was highest at latrine sites, but decreased sharply when sampling just 1 m away. In non-latrine habitat, the positive amplification rate was too low to allow for meaningful statistical analyses, suggesting that a prohibitively large number of samples would need to be analysed for detection probabilities to be adequate for routine monitoring programs. Conclusions Overall, we found that low sensitivity was driven by the low concentration of spot-tailed quoll DNA at many of the surveyed sites. Implications Given that quoll latrines can usually be identified from the accumulation of scats, and scats themselves can be sampled for DNA, we suggest that eDNA analysis of soil is unlikely to offer improvements over current spot-tailed quoll monitoring methods.
VOT for plosives in the indigenous languages of Balochistan
Authors: Syed Nasir Abbas , Bibi Shah 
Published: January 2024

Abstract
Different models of L3 acquisition have different predictions about the cross-linguistic effects of previous
learning. The ‘Cumulative Enhancement Model’ predicts that both L1 and L2 have cumulative facilitative effects on L3, but L2 the
Status Factor (L2SF) claims that L2 has stronger effects on L3 acquisition. Similarly, while the Typological Primacy Model claims
that among the already acquired languages, a typologically similar language transfers more properties to L3, the Linguistic
Proximity Model predicts a transfer of structurally similar properties from the previously learnt languages. On the other hand,
the Scalpel Model, besides considering linguistic similarity, gives importance to factors such as frequency of use and nature of
the input, language dominance, and learning context. The current paper contributes to this debate by presenting data collected
from two groups of Balochi learners of English in Balochistan (Pakistan) who were taught British English (BrE) aspiration contrast
in plosives at the allophonic level after they had acquired Pakistani English (PakE) as adult L2 learners. Thus, Balochi was L1,
PakE L2, and BrE L3 of the learners. After teaching for more than a year, the learners were tested for accuracy in VOTs for BrE
plosives. The results support the L2SF and Scalpel Model.
Contradicting potential climate misinformation during televised debates
Authors: Beck Nielsen Søren 
Published: January 2024

Abstract
Experimental research recommends that climate change debaters actively contradict misinformation. This study
examines discursively how participants do so during prominent televised Danish debates, that is, how they orient towards elements
in other participants’ preceding talk about climate change causes and implications as factually wrong. Three types are considered:
(i) contradictions produced by the interviewer in the next turn; (ii) contradictions produced by a co-participant after being
allocated the turn by the interviewer; and (iii) contradictions produced by a co-participant in a self-selected turn. Analysis
reveals that the contradictions are attuned to and limited by these sequential circumstances. The study overall finds that
sequential context significantly impacts climate change debaters’ possibilities for contradicting misinformation; in particular,
potential misinformation may be ‘smuggled’ into multi-unit turns, which can prove difficult for co-panelists to confront because
of the format’s turn-taking provision.
Liposome encapsulated hemoglobin modified Au@TiO2 for sonodynamic therapy
Authors: He Yulu , Zhang Cong , Wang Qian , Weng Yulong , Ran Xia , Kuang Yanmin , Zhang Kun , Guo Lijun 
Published: January 2024

Abstract
Sonodynamic therapy (SDT) has attracted considerable attention owing to its large penetration depth. However, the low efficiency of traditional sonosensitizers and the hypoxia environment of deep tumors hinder their therapeutic effect in practical application. Herein, the Au@TiO2-hemoglobin loaded liposome (Au@TiO2-Hb-Lip) complex has been constructed to improve the efficiency of SDT against hypoxic tumors. The results indicate that the generated carriers upon ultrasound activation of TiO2 nanoparticles (NPs) can be effectively trapped by Au NPs, and the production of reactive oxygen species is increased by two times compared to that of bare TiO2 NPs. Particularly, the introduction of liposomes as a carrier and hemoglobin as an oxygen supplier not only prevents the aggregation of Au@TiO2 NPs in the blood environment but also improves the adaptability of Au@TiO2-Hb-Lip to hypoxic tumors. These synergic actions of different moieties in Au@TiO2-Hb-Lip sonosensitizer significantly enhance the SDT efficiency.
Longitudinal vibration estimation of a mine hoist using a hybrid signal fusion method combining UKF, ND and improved DE
Authors: Chen Xiao , Zhang Chun , Chang Ju-Cai , Zhao Guang-Ming , Zang Wan-Shun , Zhu Zhen-Cai , Shen Gang 
Published: January 2024

Abstract
The monitoring of cage longitudinal vibration can directly indicate the operational status of mine hoists. However, it is always challenging to collect the sensor signals of moving cages with high dynamic characteristics in real time from complex working environments using traditional monitoring methods. In this study, a more practical hybrid signal fusion approach is proposed to realize estimation of cage longitudinal vibration from a low sampling rate acceleration acquisition signal and a low cost encoder signal for state estimation. A nonlinear differentiator is applied to extract encoder differential signals and expand observation variables. An unscented Kalman observer based on nonlinear mine hoist model is designed to estimate the unknown state. To overcome the influence of the uncertain parameters, an improved differential evolution (DE) algorithm combining parameter adaptive method, reverse learning competition scheme and multiple parallel populations strategy is proposed to find unknown parameters of the observation model and autotune the parameters of the algorithms by using low sampling rate acceleration. Sensor data of the simulated experiment platform were collected and processed by the xPC system to validate the effectiveness of the proposed strategy. The experimental results showed that the improved DE (IDE) algorithm had a faster mean time for parameter tuning and the smallest fitness value compared to the standard DE, the particle swarm optimization algorithm and the genetic algorithm. Moreover, the longitudinal vibration estimation system, after parameter tuning by the IDE optimization algorithm, could achieve the purpose of signal estimation, with a smaller estimation error and a better estimation effect.
A weighted sparse classification method based on period analysis dictionary
Authors: Wang Huaqing , Zhang Hongjie , Wang Baoguo , Han Changkun , Song Liuyang 
Published: January 2024

Abstract
The periodic transient shocks triggered by damages in rolling bearings are frequently overshadowed by disruptive elements such as noise and harmonics. Therefore, the extraction of fault characteristics from these disturbances to identify the health status of the bearing is crucial for fault diagnosis. This study presents a novel approach, the period analysis dictionary weighted sparse representation classification (PAD-WSRC) method, designed specifically for rolling bearings. The proposed approach incorporates Bi-damped wavelet as the dictionary wavelet atom, while accounting for the pulse characteristics induced by faults and leveraging prior knowledge of periodicity. A weighted sparse representation (SR) method was also designed, which calculates the weighted SR coefficients of samples, amplifying the local features of samples while addressing the impact of time-shift bias. In addition, the bearing fault type is identified using a mutual correlation classification criterion based on sparse approximation. Our PAD-WSRC strategy has demonstrated its effectiveness in classifying the health status of bearings across three datasets, achieving recognition accuracies of 99.75%, 99.69% and 99.17%, respectively. Comparisons with several traditional methods further underscore the effectiveness and superiority of our proposed method in classifying rolling bearing faults.
Pulmonary nodule detection in x-ray images by feature augmentation and context aggregation
Authors: Liu Chenglin , Wu Zhi , Wang Binquan , Zhu Ming 
Published: January 2024

Abstract
Recent developments in x-ray image based pulmonary nodule detection have achieved remarkable results. However, existing methods are focused on transferring off-the-shelf coarse-grained classification models and fine-grained detection models rather than developing a dedicated framework optimized for nodule detection. In this paper, we propose PN-DetX, which as we know is the first dedicated pulmonary nodule detection framework. PN-DetX incorporates feature fusion and self-attention into x-ray based pulmonary nodule detection tasks, achieving improved detection performance. Specifically, PN-DetX adopts CSPDarknet backbone to extract features, and utilizes feature augmentation module to fuse features from different levels followed by context aggregation module to aggregate semantic information. To evaluate the efficacy of our method, we collect a LArge-scale Pulmonary NOdule Detection dataset, LAPNOD, comprising 2954 x-ray images along with expert-annotated ground truths. As we know, this is the first large-scale chest x-ray pulmonary nodule detection dataset. Experiments demonstrates that our method outperforms baseline by 3.8% mAP and 5.1% AP
0.5. The generality of our approach is also evaluated on the publicly available dataset NODE21. We aspire for our method to serve as an inspiration for future research in the field of pulmonary nodule detection. The dataset and codes will be made in public.
Improvement of lithium battery corner detection accuracy based on image restoration method
Authors: Cheng Hao , Bi Qilin , Chen Xiaoxin , Zheng Hongxin , Du Yixian , Jiang Zhansi 
Published: January 2024

Abstract
Target detection technology has been widely used in the automatic production of lithium batteries. However, motion blur will lead to the reduction of the angular position detection accuracy of lithium batteries. To solve this problem, an improved fuzzy recovery model for angular position of lithium battery is proposed in this paper. Firstly, the improved lightweight neural network RepVGG was used as the main module of the backbone network, so that the network could improve the performance of network feature extraction while reducing the number of calculation parameters and improving the reasoning speed of fuzzy restoration. Secondly, we optimize the multi-Dconv head transposed attention (MDTA) module and reference it to the generator, which reduces the complexity of the model and strengthens the network’s attention to details and textures, and improves the visual effect of the restored image. Finally, we design a lightweight globally connectable residual network called SAC Block and use it to to improve the discriminator, which enhances the global receptive field of the model and improves the structural similarity between the restored image and the original image. In order to verify the effectiveness of the method, we verify it on the self-built dataset and GoPro dataset. The experiments show that our proposed lightweight model improves the peak signal-to-noise ratio (PSNR) index by 9.2% and 8.6% respectively compared with the original model. The visual effect of the restored image is better than that of other current similar algorithms, and it is confirmed that our model can better improve the accuracy of lithium battery angular position detection.
Analog electromagnetic induced transparency of T-type Si-based metamaterial and its applications
Authors: He Mengyue , Wang Qiaoqiao , Zhang Hao , Xiong Jing , Liu Xiangpeng , Wang Junqiao 
Published: January 2024

Abstract
A T-type silicon-based metamaterial is proposed, which realizes electromagnetically induced transparency (EIT) by using the asymmetry of its structure. This dielectric metamaterial exhibits an ultranarrow EIT transparent window, with a transmittance of 91% and a Q factor of 180. Measuring its sensing performance, a refractive index sensor with a sensitivity of 466 nm RIU−1 is obtained. In addition, by analyzing the dispersion characteristics of the structure, the maximum group delay value is 2.84 ps, and the corresponding group refractive index is 4250. Therefore, dielectric metamaterials with this structure are expected to be used in refractive index sensing and slow light devices.
Comparative study of current carrying capacity between 1G and 2G HTS tape samples at different temperatures and magnetic fields
Authors: Yang Tianhui , Li Wenxin , Xin Ying 
Published: January 2024

Abstract
Two categories of high-temperature superconducting (HTS) tapes, the silver-sheathed BSCCO tape (1G HTS tape) and REBCO coated conductor (2G HTS tape), have been commercialized worldwide and widely used in applications. In this study, the 1G HTS tape produced by Sumitomo and 2G HTS tape produced by Superpower were selected for a systematic comparative study in critical current (I
c) performances under various temperature and magnetic field conditions. The anisotropy and I
c variation patterns of these two types of samples in the temperature range of 25–77 K, magnetic field from 0 to 7 T and field angle from 0 to 90° were compared and analyzed. The results of this study reveal certain comprehensive characteristic features of these two categories of HTS tapes, supplementing some new systematic information to the literature.
Dynamic all-optical memory switching based on atomic optical bistable behavior in a three level Λ-type atomic system
Authors: He Haiqiang , Fan Bixuan , Xie Min 
Published: January 2024

Abstract
We theoretically investigate the atomic optical bistability (AOB) in a three-level Λ-type atomic system confined in a unidirectional optical ring cavity. The role of the intensity or detuning of the control field on AOB is explored, and results show that absorption, dispersion, and nonlinearity can be modified significantly by the control field due to quantum coherence and interference in multilevel atomic systems. Thus, tuning the intensity or detuning of the control field can manipulate the switch-up and switch-down thresholds, as well as the area of the bistable hysteresis loop. According to the controllability of AOB, we design various schemes to realize dynamical all-optical switching between the high and low outputs of two bistable curves for a fixed cavity input. In addition, dynamical all-optical memory switching can be implemented by adding a pulse sequence for the intensity or detuning of the control field. For appropriate parameters, such as the cooperative coefficient, the extinction ratio of the switching can be improved dramatically.
Dark Matter Search in Dwarf Irregular Galaxies with Ten Years of Data from the IceCube Neutrino Observatory
Authors: Lü Yi-Fei , Zhu Ben-Yang , Li Rong-Lan , Guo Xue-Kang , Liu Tian-Ci , Huang Yong-Bo , Liang Yun-Feng 
Published: January 2024

Abstract
Dwarf irregular galaxies (dIrrs), as rotationally supported systems, have more reliable J-factor measurements than dwarf spheroidal galaxies and have received attention as targets for dark matter detection in recent years. In this paper, we use 10 yr of IceCube muon-track data and an unbinned maximum-likelihood-ratio method to search for neutrino signals beyond the background from the directions of seven dIrrs, aiming to detect neutrinos produced by heavy annihilation dark matter. We do not detect any significant signal. Based on such null results, we calculate the upper limits on the velocity-averaged annihilation cross section for 1 TeV–10 PeV dark matter. Our limits, although weaker than the strictest constraints in the literature in this mass range, are also a good complement to the existing results considering the more reliable J-factor measurements of dIrrs.
A Machine Learning Made Catalog of FR-II Radio Galaxies from the FIRST Survey
Authors: Lao Bao-Qiang , Yang Xiao-Long , Jaiswal Sumit , Mohan Prashanth , Sun Xiao-Hui , Qin Sheng-Li , Zhao Ru-Shuang 
Published: January 2024

Abstract
We present an independent catalog (FRIIRGcat) of 45,241 Fanaroff–Riley Type II (FR-II) radio galaxies compiled from the Very Large Array Faint Images of the Radio Sky at Twenty-centimeters (FIRST) survey and employed the deep learning method. Among them, optical and/or infrared counterparts are identified for 41,425 FR-IIs. This catalog spans luminosities 2.63 × 1022 ≤ L
rad ≤ 6.76 × 1029 W Hz−1 and redshifts up to z = 5.01. The spectroscopic classification indicates that there are 1431 low-excitation radio galaxies and 260 high-excitation radio galaxies. Among the spectroscopically identified sources, black hole masses are estimated for 4837 FR-IIs, which are in 107.5 ≲ M
BH ≲ 109.5
M
⊙. Interestingly, this catalog reveals a couple of giant radio galaxies (GRGs), which are already in the existing GRG catalog, confirming the efficiency of this FR-II catalog. Furthermore, 284 new GRGs are unveiled in this new FR-II sample; they have the largest projected sizes ranging from 701 to 1209 kpc and are located at redshifts 0.31 < z < 2.42. Finally, we explore the distribution of the jet position angle and it shows that the faint Images of the FIRST images are significantly affected by the systematic effect (the observing beams). The method presented in this work is expected to be applicable to the radio sky surveys that are currently being conducted because they have finely refined telescope arrays. On the other hand, we are expecting that further new methods will be dedicated to solving this problem.
Real-time estimation of EEG-based engagement in different tasks
Authors: Natalizio Angela , Sieghartsleitner Sebastian , Schreiner Leonhard , Walchshofer Martin , Esposito Antonio , Scharinger Josef , Pretl Harald , Arpaia Pasquale , Parvis Marco , Solé-Casals Jordi , Sebastián-Romagosa Marc , Ortner Rupert , Guger Christoph 
Published: January 2024

Abstract

Objective. Recent trends in brain–computer interface (BCI) research concern the passive monitoring of brain activity, which aim to monitor a wide variety of cognitive states. Engagement is such a cognitive state, which is of interest in contexts such as learning, entertainment or rehabilitation. This study proposes a novel approach for real-time estimation of engagement during different tasks using electroencephalography (EEG). Approach. Twenty-three healthy subjects participated in the BCI experiment. A modified version of the d2 test was used to elicit engagement. Within-subject classification models which discriminate between engaging and resting states were trained based on EEG recorded during a d2 test based paradigm. The EEG was recorded using eight electrodes and the classification model was based on filter-bank common spatial patterns and a linear discriminant analysis. The classification models were evaluated in cross-task applications, namely when playing Tetris at different speeds (i.e. slow, medium, fast) and when watching two videos (i.e. advertisement and landscape video). Additionally, subjects’ perceived engagement was quantified using a questionnaire. Main results. The models achieved a classification accuracy of 90% on average when tested on an independent d2 test paradigm recording. Subjects’ perceived and estimated engagement were found to be greater during the advertisement compared to the landscape video (p = 0.025 and p

<

0.001, respectively); greater during medium and fast compared to slow Tetris speed (p

<

0.001, respectively); not different between medium and fast Tetris speeds. Additionally, a common linear relationship was observed for perceived and estimated engagement (r

rm
= 0.44, p

<

0.001). Finally, theta and alpha band powers were investigated, which respectively increased and decreased during more engaging states. Significance. This study proposes a task-specific EEG engagement estimation model with cross-task capabilities, offering a framework for real-world applications.