bluuebunny/crossref_metadata_2025_split huggingface dataset:
APPSO‐NN: An adaptive‐probability particle swarm optimization neural network for sensorineural hearing loss detection
Authors: Yang Jingyuan , Zhang Yu‐Dong 
Published: June 2023

AbstractAs a hearing disorder, sensorineural hearing loss (SNHL) can be effectively detected by magnetic resonance imaging (MRI). However, the manual detection of MRI scanning is subjective, time‐consuming, and unpredictable. An accurate and automatic computer‐aided diagnosis system is proposed for SNHL detection, providing reliable references for professionals. The system first employs a wavelet entropy layer to extract features of MRI images. Then, a neural network layer is proposed as the classifier consisting of a feedforward neural network (FNN) and an adaptive‐probability PSO (APPSO) algorithm. The authors prove the rotation‐variant property of the basic particle swarm optimization (PSO) by the algebraic property of matrix transformation. The property is unsuitable for optimising parameters of neural networks. Thus, in APPSO, the authors integrate the new update rules based on all‐dimensional variation and adaptive‐probability mechanism into the basic PSO, which can improve its searching ability without losing population diversity. The authors compare APPSO‐NN with FNN trained by five popular evolutionary algorithms. The simulation results show that APPSO performs best in training FNN. The method also compares with six state‐of‐the‐art methods. The simulation results show that the best performance in sensitivity and overall accuracy of hearing loss classification, which proves that the method is effective and promising for SNHL detection.
Difference analysis of dissolved gas in natural ester insulating fluids under typical electrical and thermal faults: An experimental study
Authors: Xing Yadong , Hu Yizhuo , Ma Yaoxiang , Liu Yang , Dong Ming , Xu Yang 
Published: June 2023

AbstractNatural ester insulating oil is widely used in transformers due to its good fire resistance and biodegradability. It is mainly composed of triglycerides, and there are some differences in fatty acid composition and content among natural esters. Therefore, the fault diagnosis methods based on dissolved gas analysis are different. Three kinds of natural ester insulating oils are used to study the dissolved gas in oil under typical electrical and thermal faults of power transformers. Thermal faults from 200°C to 800°C and electrical faults with different discharge energies, which include partial discharge, breakdown discharge, and arc discharge, are simulated. The characteristic gases and their variation trends of natural esters under thermal and electrical faults are obtained through the experimental results. The gas generation characteristics of the three natural ester insulating oils under typical electrical and thermal faults are almost similar, but the relative percentages of characteristic gases have certain differences. Natural ester insulating oil with a higher unsaturation degree tends to produce more H2 and less C2H4. Finally, the fault diagnosis methods are used to determine the fault gas data, and the Duval pentagon is modified and improved according to the gas generation characteristics of natural esters.
Simultaneous and panchromatic observations of the fast radio burst FRB 20180916B
Authors: Trudu M. , Pilia M. , Nicastro L. , Guidorzi C. , Orlandini M. , Zampieri L. , Marthi V. R. , Ambrosino F. , Possenti A. , Burgay M. , Casentini C. , Mereminskiy I. , Savchenko V. , Palazzi E. , Panessa F. , Ridolfi A. , Verrecchia F. , Anedda M. , Bernardi G. , Bachetti M. , Burenin R. , Burtovoi A. , Casella P. , Fiori M. , Frontera F. , Gajjar V. , Gardini A. , Ge M. , Guijarro-Román A. , Ghedina A. , Hermelo I. , Jia S. , Li C. , Liao J. , Li X. , Lu F. , Lutovinov A. , Naletto G. , Ochner P. , Papitto A. , Perri M. , Pittori C. , Safonov B. , Semena A. , Strakhov I. , Tavani M. , Ursi A. , Xiong S. L. , Zhang S. N. , Zheltoukhov S. 
Published: June 2023

Aims.Fast radio bursts are bright radio transients whose origins are not yet understood. The search for a multi-wavelength counterpart of those events can set a tight constraint on the emission mechanism and the progenitor source.Methods.We conducted a multi-wavelength observational campaign on FRB 20180916B between October 2020 and August 2021 over eight activity cycles of the source. Observations were carried out in the radio band by the SRT both at 336 and 1547 MHz and the uGMRT at 400 MHz. Simultaneous observations were conducted by the optical telescopes Asiago (GalileoandCopernico), CMO SAI MSU, CAHA 2.2 m, RTT-150 and TNG, and X/γ-ray detectors on board the AGILE,Insight–HXMT, INTEGRAL, andSwiftsatellites.Results.We present the detection of 14 new radio bursts detected with the SRT at 336 MHz and seven new bursts with the uGMRT from this source. We provide the deepest prompt upper limits in the optical band for FRB 20180916B to date. In fact, the TNG/SiFAP2 observation simultaneous to a burst detection by uGMRT gives an upper limitEoptical/Eradio <  1.3 × 102. Another burst detected by the SRT at 336 MHz was also co-observed byInsight–HXMT. The non-detection in the X-rays yields an upper limit (1 − 30 keV band) ofEX − ray/Eradioin the range of (0.9 − 1.3) × 107, depending on the model that is considered for the X-ray emission.
Beurteilung der Sakroiliitis mittels künstlicher Intelligenz
– Fortschritte und Limitationen
Authors: Adams Lisa , Vahldiek Janis L. , Poddubnyy Denis , Bressem Keno 
Published: June 2023

ZusammenfassungDie Sakroiliitis ist eine entzündliche Erkrankung des
Sakroiliakalgelenks, die durch Faktoren wie Infektionen, Traumata und
Autoimmunerkrankungen ausgelöst werden kann. Sie verursacht Schmerzen
und Steifheit im unteren Rücken, weshalb eine frühzeitige
Diagnose für eine optimale Behandlung entscheidend ist. Die Diagnose ist
anspruchsvoll und erfordert klinische Beurteilung, Labortests und bildgebende
Verfahren wie Röntgen, MRT oder CT. In den letzten Jahren hat sich die
künstliche Intelligenz (KI) als vielversprechendes Instrument
für die Beurteilung von Veränderungen im Rahmen der Sakroiliitis
herausgestellt. KI-Algorithmen analysieren verschiedene bildgebende Verfahren,
um strukturelle Veränderungen und Entzündungen im
Sakroiliakalgelenk zu erkennen, zu quantifizieren und einzuordnen. Die Anwendung
von KI kann die Diagnosegenauigkeit und Effizienz des Radiologen bzw. des
Rheumatologen bei der Beurteilung von Sakroiliitis durch bildgebende Verfahren
verbessern. KI-Algorithmen können strukturelle Veränderungen und
Entzündungen im Sakroiliakalgelenk quantifizieren und Vorhersagemodelle
für den Krankheitsverlauf erstellen. Herausforderungen wie der Bedarf an
qualitativ hochwertigen Daten und die Minimierung von Verzerrungen und Fehlern
in den Daten und Algorithmen müssen jedoch bewältigt werden.
Weitere Studien sind erforderlich, um das volle Potenzial der KI bei der
Beurteilung von Sakroiliitis auszuschöpfen. Der Einsatz von KI kann
jedoch die Ergebnisse für Patienten verbessern, indem er eine
frühzeitige Diagnose und Behandlung ermöglicht.
Benchmark coupled-cluster lattice energy of crystalline benzene and assessment of multi-level approximations in the many-body expansion
Authors: Borca Carlos H. , Glick Zachary L. , Metcalf Derek P. , Burns Lori A. , Sherrill C. David 
Published: June 2023

The many-body expansion (MBE) is promising for the efficient, parallel computation of lattice energies in organic crystals. Very high accuracy should be achievable by employing coupled-cluster singles, doubles, and perturbative triples at the complete basis set limit [CCSD(T)/CBS] for the dimers, trimers, and potentially tetramers resulting from the MBE, but such a brute-force approach seems impractical for crystals of all but the smallest molecules. Here, we investigate hybrid or multi-level approaches that employ CCSD(T)/CBS only for the closest dimers and trimers and utilize much faster methods like Møller–Plesset perturbation theory (MP2) for more distant dimers and trimers. For trimers, MP2 is supplemented with the Axilrod–Teller–Muto (ATM) model of three-body dispersion. MP2(+ATM) is shown to be a very effective replacement for CCSD(T)/CBS for all but the closest dimers and trimers. A limited investigation of tetramers using CCSD(T)/CBS suggests that the four-body contribution is entirely negligible. The large set of CCSD(T)/CBS dimer and trimer data should be valuable in benchmarking approximate methods for molecular crystals and allows us to see that a literature estimate of the core-valence contribution of the closest dimers to the lattice energy using just MP2 was overbinding by 0.5 kJ mol−1, and an estimate of the three-body contribution from the closest trimers using the T0 approximation in local CCSD(T) was underbinding by 0.7 kJ mol−1. Our CCSD(T)/CBS best estimate of the 0 K lattice energy is −54.01 kJ mol−1, compared to an estimated experimental value of −55.3 ± 2.2 kJ mol−1.
The impact of climate change and wildfire on decadal alpine vegetation dynamics
Authors: Verrall Brodie , Norman Patrick , Mackey Brendan , Fisher Scout , Dodd Jack 
Published: June 2023

Context Climate-induced changes of alpine vegetation diversity, cover and composition have been recorded globally, but most insights have been gleaned from field studies over small spatiotemporal scales. Aims We assess dynamics in climate and vegetation of Australia’s highest and most biologically diverse alpine area that surrounds Mount Kosciuszko (~455 km2), as well as recovery following the 2003 wildfires. Methods Climatic changes were analysed using gridded climate data for mean annual temperature (1910–2019) and seasonal precipitation (1900–2019), and changes in snow cover were assessed from snow course records (1954–2021). A vegetation cover time series (1990, 2000, 2010, 2020) was modelled with an optimised random forest classification using recursive feature selection, and the LandTrendr algorithm was used to detect areas burnt during wildfires. Key results Over time, temperatures and summer precipitation increased, whereas snow cover and winter precipitation decreased. Subsequently, vegetation dynamics were dominated by the densification of subalpine woodlands at lower elevations, replacing dry and wet heathlands. There was treeline stasis but upslope advancement of dry and wet shrublines but grassland vegetation types were relatively stable. However, in burnt areas there was suppressed upslope advancement of shrublines, treeline recession and relatively less expansion of subalpine woodlands. Conclusions Alpine vegetation may be impacted by climate change incrementally through relatively gradual changes in climatic conditions, and transformatively through landscape-level disturbance from wildfires. Implications Higher temperatures and altered precipitation regimes increase the frequency and severity of wildfires, which may be amplified by increasing fuel loads and dryness from the proliferation and advance of woody vegetation in alpine areas.
Population dynamics of chital deer (Axis axis) in northern Queensland: effects of drought and culling
Authors: Pople Anthony , Amos Matt , Brennan Michael 
Published: June 2023

Context Chital deer (Axis axis) are long established in the northern Queensland dry tropics, and at high densities are considered pests by cattle graziers. Cost-effective management is difficult for widespread, fluctuating populations of vertebrate pests such as these deer. Historically, control of chital deer has been limited to recreational and some commercial ground-shooting and trapping. Concerns over chital deer impacts were heightened during drought in 2015 and funding became available for aerial culling. Aim This study set out to determine (1) distribution and abundance, (2) seasonal reproductive output, (3) potential and actual rates of increase and their determinants, and (4) efficient management strategies for chital deer in the northern Queensland dry tropics. Methods In 2014, ~13 000 km2 of the main distribution was surveyed by helicopter. Multiple vehicle ground surveys per year monitored chital deer density on two properties during 2013–2022. Seasonal shot samples of deer on both properties assessed reproductive output during 2014–2016. Aerial surveys during 2016–2020 determined chital deer densities on seven properties, prior to aerial culling on four properties. Finally, the maximum rate of increase of chital deer was calculated from life-history data. Key results Regionally, chital deer are patchily distributed and so are best monitored locally where densities can be >50 deer km−2. Vehicle ground surveys recorded an ~80% decline in chital deer populations on two properties over 7–10 months during drought in early 2015, with a similar rate being recorded by aerial survey at a third site. There was little recruitment during the drought, but the decline was seemingly driven by adult mortality. Aerial shooting further reduced populations by 39–88% to <3 deer km−2 on four properties. Where there was no continuing control, culled populations recovered to pre-cull densities or higher after 2.4 years. One unculled property recovered to its pre-drought density after 6 years. Rates of recovery were at or higher than the maximum annual rate of increase for chital deer estimated here as 26–41%. Conclusions Drought has a lasting effect on this chital deer population, because of the resulting large population decline and the modest rate of any recovery in the absence of culling. Culling can reduce populations to low density, but the removal rate needs to be sustained to suppress future growth. Implications Drought provides a strategic opportunity to further reduce chital deer populations for enduring control. Large reductions are feasible given the clumped dispersion of populations within properties and in the region.
What’s the fuzz: The frequency, practice and perceptions of equine facial hair trimming revealed in a survey of horse owners in Australia
Authors: Hazel Susan J. , Holman Carly , Thompson Kirrilly 
Published: June 2023

Abstract
Recently, equine organizations from multiple countries around the world, including Australia, have implemented bans on the trimming of vibrissae (sensory hairs located around the muzzle and eyes) of horses competing in their events. These hairs are likely to have sensory functions that are important to horses, and the ban is based on welfare grounds. The aims of this study were to determine: the proportions of horse owners trimming equine facial hairs (ear and muzzle hair) across different types of equestrian disciplines in Australia, the types of equine facial hairs trimmed, whether horses were restrained for trimming, and attitudes related to the practice. An online survey of Australian horse owners was advertised through organizations involving equine competitive sports. A total of 422 responses were obtained, with respondents mostly female and a wide range of age groups. Respondents involved in showing competitions were more likely to trim muzzle and ear hairs than the other competition types. Respondents in showing competitions more commonly believed that trimming muzzle and ear hairs was a normal practice in their discipline, made it more likely a horse would win, and that horses did not need muzzle or ear hairs for day-to-day living. The results of this study provide valuable insight into the widespread trimming of horse muzzle and ear hairs in some horse disciplines prior to the implementation of the ban in Australia. The information gained may also be useful for the design and implementation of behaviour change interventions for other management and presentation practices used for horses and other animals. Further studies are needed to determine if and how the practice and attitudes to facial hair trimming in horses have changed with the enforcement of the ban.
Lipschitz stability of recovering the conductivity from internal current densities
Authors: Qiu Lingyun , Zheng Siqin 
Published: June 2023

Abstract
In recent years, coupled physics imaging techniques have been developed to produce clearer images than those produced by electrical impedance tomography. This paper focuses on the inverse problem arising in current density impedance imaging and magneto-acousto-electric tomography. We consider the electrostatic equation

∇
⋅
(
σ
∇

w
b

)
=
0

in a bounded domain

Ω
⊂

R

3

with either the Dirichlet or Neumann boundary condition b, where σ is a scalar conductivity function. The inverse problem is formulated as recovering σ from vector fields

J
b

=
σ
∇

w
b

with different boundary conditions b. We provide a local Lipschitz stability, stating that near some known σ
0 and under some regularity assumptions, we can find b
1 and b
2 by constructing complex geometrical optics (CGO) solutions such that

‖
ln

σ

(
1
)

−
ln

σ

(
2
)

‖

C

m
,
α

(

Ω
¯

)

⩽
C

∑

j
=
1

2

‖

J

b
j

(
1
)

−

J

b
j

(
2
)

‖

C

m
,
α

(

Ω
¯

)

. Furthermore, we modify the CGO solutions using the reflection method to make b
1 and b
2 vanish on a portion of a plane, and prove a local Lipschitz stability with partial data.
Control of rotation angles of multilayer graphene on SiC (000
1‾
) by substrate off-direction and angle
Authors: Sakakibara Ryotaro , Bao Jianfeng , Hayashi Naoki , Ito Takahiro , Hibino Hiroki , Norimatsu Wataru 
Published: June 2023

Abstract
Graphene on SiC (000

1
‾

) tends to grow in multiple layers and does not have a single orientation relation with the SiC substrate. It has been considered impossible to control the rotation angle of multilayer graphene on SiC (000

1
‾

). In this study, we grew graphene on off-axis SiC substrates with various off angles from 0° to 8° and investigated their in-plane rotation and electronic structures systematically. As the off angle toward the [11

2
‾

0]SiC direction increased, graphene rotated by 30° with respect to SiC became less dominant and instead, graphene rotated by 30 ± 2.5° appeared. We also found that the uniformity of the graphene rotation angle was relatively high on SiC substrates with a small off angle toward the [1

1
‾

00]SiC direction. Our results suggest that the step-terrace structure defined by the substrate off-direction and angle plays an important role in the controllability of the rotation angle of graphene.
SN-SAE: a new damage diagnosis method for CFRP using Lamb wave
Authors: Li Zhiyong , Wang Zhiyong , Li Yong , Han Shanling 
Published: June 2023

Abstract
The damage diagnosis of carbon fiber reinforced polymer (CFRP) using Lamb wave has been widely developed, but it is still a challenging task to obtain reliable damage diagnosis results by analysis of Lamb wave, the emergence of deep learning models provides an effective solution for this work. However, the internal covariate shift and overfitting exist in traditional deep networks. The SN-SAE (stochastic normalization-stacked autoencoder) deep neural network model is proposed by introducing stochastic normalization (SN) into stacked autoencoder (SAE). The signals of 28 different damage locations in the CFRP plate provided by the open platform were processed by SN-SAE, and the damage diagnosis at different locations was achieved. The validity of SN-SAE was further verified by data obtained through building an experimental platform. The results demonstrated that the SN-SAE model can achieve high test accuracy with only 15% of the data samples as training with limited data sample, which provides a simple and effective solution for damage diagnosis of composite plates.
Fault detection of a reciprocating plunger pump with fault-free data based on an unsupervised feature encoder and minimum covariance determinant
Authors: Lai Yuehua , Li Ran , Zhang Yang , Meng Lingyu , Chen Rongming 
Published: June 2023

Abstract
It is well known that complex mechanical equipment has many differnt the failure modes, and monitoring data for fault conditions are scarce. Therefore, research on fault detection for reciprocating plunger pumps with fault-free data is significant for theory and application. Due to the lack of prior knowledge of faults, it is always a great challenge for researchers to extract fault features from signals. In this paper, an innovative fault detection method for a reciprocating plunger pump is proposed based on an unsupervised feature encoder (UFE) and minimum covariance determination (MCD). Firstly, a criterion based on mutual information maximization for local and global features is proposed for unsupervised feature extraction. In addition, an unsupervised training strategy based on negative sampling is proposed to train the encoder, so that the model can converge quickly and improve the stability of model training. A fault detection algorithm for a reciprocating plunger pump is proposed based on a UFE and MCD. Finally, the effectiveness and superiority of the proposed method are verified with the measured data for a reciprocating plunger pump. The results show that the proposed method can accurately detect the faults in the reciprocating plunger pump with a detection accuracy of more than 98%. Compared with other methods, the proposed fault detection algorithm has better applicability and accuracy for fault detection with fault-free data.
Large-range and high-sensitivity displacement sensing based on a SNAP microresonator by multimode encoding technique
Authors: Dong Yongchao , Zeng Xueliang , Wang Jiebo , Li Yongkang , Cai Nian , Wang Han 
Published: June 2023

Abstract
Probe-type micro-displacement sensors with a large range and high sensitivity have important applications in both aerospace and nano-lithography. However, the state-of-the-art measurement range achieved using conventional methods such as charge coupled device imaging and fiber grating demodulation is limited to only tens of micrometers. In this study, we propose and demonstrate a displacement sensing mechanism with a large range and high sensitivity for measuring linear displacements. The mechanism is based on a multimode encoding technique implemented on a surface nanoscale axial photonics (SNAP) microcavity platform. By tracking the transmittance variations of multiple axial modes and employing encoding techniques, we can determine the rough absolute position as well as the axial mode with the highest sensitivity in each region. Moreover, the selected mode for each region is exploited to accurately measure the micro-displacement with a large range and high accuracy. As a proof-of-principle experiment, the results indicate a large sensing range about 346 μm and a high sensitivity ranging up to 0.013 μm−1. Assuming that the transmittance can be resolved by 0.1%, the resolution of the measurement is about 0.1 μm.