bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bacterial succession in an abandoned circum-neutral opencast coal mine in India
Authors: Banerjee Sohini , Misra Arijit , Sar Abhijit , Pal Srikanta , Chaudhury Shibani , Dam Bomba 
Published: September 2023

Context Abandoned mines provide an ideal opportunity to study the succession of microbial communities, which is crucial for the development and stability of the soil. Aims We examined the diversity and temporal succession of the microbial community in an abandoned coal mine. Methods We investigated soil geochemical parameters and microbial succession using high-throughput 16S rRNA gene amplicon sequences over a 4-year period in a derelict opencast circum-neutral coal mine in Tasra colliery, Jharkhand, India. Results Soil pH (4.46–6.13), organic carbon (0.86–4.53%), available nitrogen (0.001–0.003%) and total cultivable heterotrophic microbial load increased, and concentrations of chloride (24 865–15 067 ppm), sulfate (26 417–417 ppm) and heavy metals reduced over the period of 4 years. The 16S rRNA gene sequences identified Proteobacteria as the dominant phylum across samples except for the fourth year, where Actinobacteria was predominant. Chlorobi, WPS-2 and Spirochaetes were exclusively identified in the first year. Twelve phyla present in the first year were completely absent by the end. In the fourth year, an abundance of nitrogen-fixing members such as Burkholderiales, Rhizobiales, Roseiflexales and Actinomycetales was noted and semi-quantitative PCR suggested that nitrogenases were predominately vanadium dependent (relative to molybdenum). Gradual shifts from purportedly chemolithotrophic to heterotrophic metabolic strategies were also observed. Conclusion This work establishes that soil improvement in abandoned coal mines involves the dynamic interplay of physicochemical parameters and shifts in microbial communities and dominant metabolic guilds. This knowledge can be used to plan and monitor remediation measures in such sites.
Tangut and Horpa languages
Authors: Beaudouin Mathieu 
Published: September 2023

AbstractFieldwork from the past decade has yielded new data from a cluster of languages in Western Sichuan (China), resulting in new observations relevant for the understanding of Tangut grammar. In this paper, I intend to present morphosyntactic evidence pointing to the Tangut language’s membership within the Horpa taxon, located within the larger Gyalrongic group of the Qiangic branch of Sino-Tibetan. Tangut exclusively shares with Horpa languages cognates that are far too peculiar to be the result of mere chance. By successively considering the verbal, nominal, and postpositional domains, the present paper highlights evidence that links Tangut to Horpa, while proposing new paths to the understanding of grammatical categories of Tangut proper, such as orientational/aspectual preverbs.1
Precision feeding for optimizing poultry production
Authors: Kidd M.T. , Tillman P.B. , Tillman N.S. , Chrystal P. 
Published: September 2023

Abstract
Consumable poultry from the broiler chicken sector represents a highly complex production and processing supply chain system, yet poultry products are highly versatile, healthy, and affordable for consumers on a global scale. However, the accessibility of broilers to many in developing countries is insufficient to meet daily protein needs. As such, broiler chicken production markets will increase in the foreseeable future in the Americas due to available corn and soybean meal, and in developing countries where protein consumption falls below consumer needs. Feed represents the highest variable costs in broiler chicken production. Broiler diet balanced protein supply differs among producers geographically which is primarily dependent on soybean meal availability and price. In this review, dietary protein supply in terms of feed grade amino acids is discussed. Moreover, broiler diet formulation matrices on a dynamic versus static template are also discussed. In doing so, efficiency and profitability can be gleaned from optimizing the ingredient and nutrient matrices for the overall business as ingredient nutrient compositions and price vary via equations and models, respectively.
Spinning black holes with axion hair
Authors: Burrage Clare , Fernandes Pedro G S , Brito Richard , Cardoso Vitor 
Published: September 2023

AbstractIn this work we construct and analyze non-perturbative stationary and axially-symmetric black hole solutions in general relativity coupled to an electromagnetic and an axion field. The axion field is coupled to the electromagnetic field, which leads to hairy solutions in the presence of an electric charge and rotation. We investigate the existence and characteristics of these solutions for different values of the spin, charge and coupling constant. Our analysis shows the presence of violations of the Kerr–Newman bound, solutions with large positive and negative values of the gyromagnetic ratio, and the existence of multiple branches of solutions with distinct properties, demonstrating that black hole uniqueness does not hold in this scenario. The code used in this study ispublicly available, providing a valuable tool for further research on this model.
From disformal electrodynamics to exotic spacetime singularities
Authors: Bittencourt Eduardo , Fernandes Ricardo , Goulart Érico , Ottoni José Eloy 
Published: September 2023

Abstract
We study different types of spacetime singularities which emerge in the context of disformal electrodynamics. The latter is characterized by transformations of the background metric which preserve regular (non-null) solutions of Maxwell equations in vacuum. Restricting ourselves to the case of electrostatic fields created by charged point particles along a line, we show that exotic types of singularities arise.
Sparse Bayesian inference with regularized Gaussian distributions
*
Authors: Everink Jasper M , Dong Yiqiu , Andersen Martin S 
Published: September 2023

Abstract
Regularization is a common tool in variational inverse problems to impose assumptions on the parameters of the problem. One such assumption is sparsity, which is commonly promoted using lasso and total variation-like regularization. Although the solutions to many such regularized inverse problems can be considered as points of maximum probability of well-chosen posterior distributions, samples from these distributions are generally not sparse. In this paper, we present a framework for implicitly defining a probability distribution that combines the effects of sparsity imposing regularization with Gaussian distributions. Unlike continuous distributions, these implicit distributions can assign positive probability to sparse vectors. We study these regularized distributions for various regularization functions including total variation regularization and piecewise linear convex functions. We apply the developed theory to uncertainty quantification for Bayesian linear inverse problems and derive a Gibbs sampler for a Bayesian hierarchical model. To illustrate the difference between our sparsity-inducing framework and continuous distributions, we apply our framework to small-scale deblurring and computed tomography examples.
Bursts of polarised single photons from atom-cavity sources
Authors: Ernst Jan Ole , Alvarez Juan Rafael , Barrett Thomas D , Kuhn Axel 
Published: September 2023

Abstract
Photonic qubits play an instrumental role in the development of advanced quantum technologies, including quantum networking, boson sampling and measurement based quantum computing. A promising framework for the deterministic production of indistinguishable single photons is an atomic emitter coupled to a single mode of a high finesse optical cavity. Polarisation control is an important cornerstone, particularly when the polarisation defines the state of a quantum bit. Here, we propose a scheme for producing bursts of polarised single photons by coupling a generalised atomic emitter to an optical cavity, exploiting a particular choice of quantisation axis. In connection with two re-preparation methods, simulations predict ten-photon bursts coincidence count rates on the order of 1 kHz with single

87

R
b

atoms trapped in a state of the art optical cavity. This paves the way for novel n-photon experiments with atom-cavity sources.
Spatiotemporal evolution of electrical conductivity in current-limiting-fuse arc
Authors: Inada Yuki , Fukai Yusuke , Takayasu Naoki , Nakano Yusuke , Zen Shungo , Ohnishi Wataru , Yamano Yasushi , Maeyama Mitsuaki , Kodama Naoto 
Published: September 2023

Abstract
To improve the interruption capacity of a current-limiting fuse, a detailed diagnosis of the spatial electrical conductivity distribution inside the fuse arc under the current limiting phase around current zero is required, because this distribution determines the distribution of transient recovery voltage inside the fuse. However, well-established methodologies applicable to fuse arcs are lacking, so the spatial distribution remains unknown. This study presents a borescope-integrated spectroscopic system that simultaneously obtains single-shot recordings of the axial distributions of the electron density and arc temperature in the fuse arc just before extinction. Combining the electron densities and arc temperatures, we can identify the fuse arc composition and hence calculate the axial electrical conductivity distribution under the first Chapman–Enskog approximation. The electrical conductivity provided by this systematic methodology includes no large uncertainties, thus demonstrating its superiority against previous estimation methods of the electrical conductivity.
Unipolar carrier multiplication high-gain and low-noise AlGaN ultraviolet avalanche photodiode with periodically stacked structure
Authors: Cao Jiying , Wang Jin , You Haifan , Shao Pengfei , Guo Hui , Xue Junjun , Cai Qing , Chen Dunjun 
Published: September 2023

Abstract
Highly sensitive avalanche photodetector (APD) has become a promising candidate for detecting extremely weak target signals. However, the impact ionization multiplication simultaneously triggered by electrons and holes will lead to large excess noise, thus significantly influencing device avalanche performance. Herein, we propose a distinctive AlGaN-based ultraviolet avalanche photodiode with AlN/Al0.2Ga0.8N periodically stacked multiplication region. The higher effective masses and density of states in valence band renders holes limited in the quantum-well region, where thermalization plays a dominant role during carrier transport process. On the contrary, in the atomic-scale AlN/AlGaN stacked structure with a periodic thickness of 10 nm, the electron mutualization motion is conductive to electron obtaining sufficient energy to induce impact ionization. Hence, the mechanism of unipolar carrier induced avalanche multiplication effectively reduces device noise and improving multiplication gain. Meanwhile, the high electric field intensity and tilted energy band in the AlGaN/AlN periodically stacked region significantly contribute to the carrier impact ionization. Consequently, the device achieves a superior avalanche gain of more than 105 at 74 V reverse bias. It is envisioned that the unipolar carrier triggering avalanche events offers a viable route to build high-performance APDs.
On the electronic and spin-valley coupling of vanadium doped MoS2(1−
x
)Se2x
monolayers
Authors: Maity Dipak , Sharma Rahul , Sahoo Krishna Rani , Panda Janmey Jay , Lal Ashique , Puthirath Anand B , Ajayan Pulickel M , Narayanan Tharangattu N 
Published: September 2023

Abstract
Monolayers of MoS2 with tunable bandgap and valley positions are highly demanding for their applications in opto-spintronics. Herein, selenium (Se) and vanadium (V) co-doped MoS2 monolayers (vanadium doped MoS2(1−x)Se2x
(V-MoSSe)) are developed and showed their variations in the electronic and optical properties with dopant content. Vanadium gets substitutionally (in place of Mo) doped within the MoS2 lattice while selenium doped in place of sulfur, as shown by a detailed microstructure and spectroscopy analyses. The bandgap tunability with selenium doping can be achieved while valley shift is occurred due to the doping of vanadium. Chemical vapor deposition assisted grown MoS2 (also selenium doped MoS2 as shown here) is known for its n-type transport behavior while vanadium doping is found to be changing its nature to p-doping. Chirality dependent photoexcitation studies indicate a room temperature valley splitting in V-MoSSe (∼8 meV), where such a valley splitting is verified using density functional theory based calculations.
Efficient channel attention residual learning for the time-series fault diagnosis of wind turbine gearboxes
Authors: Du Wenliao , Guo Zhen , Gong Xiaoyun , Pu Ziqiang , Li Chuan 
Published: September 2023

Abstract
Due to harsh and variable working conditions, the wind turbine gearbox may be damaged during the operation, resulting in an extended downtime with reduced productivity and economic loss. This calls for efficient fault diagnostics for the wind turbine gearboxes. Commonly-used diagnostics based on classical deep learning networks cannot guarantee good performance with time series signals due to the weakness of feature extraction. For this reason, an efficient channel attention residual learning approach is proposed to enhance the feature extraction and fault diagnosis for wind turbine gearboxes, leading to the development of a channel attention residual network (CAResNet). The collected time series signals are directly employed as the input. The efficient channel attention is embedded into the residual network to capture features and improve fault diagnosis capability. Experiments are carried out on a real wind turbine gearbox. The results showed that the average diagnostic accuracy of the CAResNet model was 94.41%. CAResNet has better diagnostic accuracy than other methods proposed in this paper.
Machine learning-enabled thickness estimation of thin coatings on carbon fibre composites using microwaves
Authors: Li Zhen , Meng Zhaozong , Liu Jian , Soutis Constantinos , Gibson Andrew 
Published: September 2023

Abstract
Accurate thickness measurement of thin coatings (typically 50–500 μm) on carbon fibre-reinforced polymer composites is a major challenge in the manufacturing and maintenance processes of modern aircraft. Different from the conventional material-dependent technique for prediction, a machine learning-enabled strategy with an artificial neural network configuration is used with no requirement of prior knowledge of the type of coating or substrate under test. In the test, an open microwave cavity resonator sensor is directly placed on a coated composite, and any variation of the coating material, coating thickness and conductivity of the composite alters the resonance frequency. Principal component analysis is employed in the signal pre-processing for the dimensionality reduction of the raw measurement data. In terms of the root-mean-square error, the maximum value for the calibration approach is approximately 15 μm and that for the machine learning-based approach is 12 μm. The sensor system developed enables real-time on-site assessment of coated composite structures and thus offers a new approach for non-destructive evaluation 4.0 with improved efficiency, accuracy and automation.
GNSS/MEMS IMU vehicle integrated navigation algorithm constrained by displacement vectors in urban environment
Authors: Feng Yihang , Huang Guanwen , Jing Ce , Li Xin , Li Zhenhong 
Published: September 2023

AbstractThe global navigation satellite system (GNSS) and a micro-electro-mechanical system inertial measurement unit (MEMS IMU) can be integrated to form a robust navigation system, providing continuous and accurate location information on dynamic vehicles. However, the performance of a GNSS/MEMS IMU integrated navigation system is easily affected by the accuracy of measurement noise matrix, which is significantly reduced in the urban environment. The adaptive Kalman filter can improve the measurement noise matrix reliability by constructing robust equivalent weight factors; however, GNSS observations are easily misjudged as exception sources that can deteriorate the filter stability. To address these problems, a novel integrated algorithm with a displacement vector constraint is proposed based on the kinematic characteristics of vehicles, which are considered as judgment factors. In this case, the measurement noise can be adjusted accordingly only when the GNSS observations are judged as abnormal. In this study, two types of vehicle navigation experiments were conducted: a low-speed wheeled robot in a campus environment and a dynamic vehicle in an actual urban environment. The experimental results showed that the three-dimensional navigation accuracy was improved by 47% and 55% compared with the conventional algorithm under the two different environments, respectively.
Improving the optoelectronic properties of monolayer MoS2 field effect transistor through dielectric engineering
Authors: Vrinda Narayanan P , Majumder Sudipta , Gokul M A , Taneja Chetna , Kumar G V Pavan , Rahman Atikur 
Published: September 2023

Abstract
The reduced dielectric screening in atomically thin two-dimensional materials makes them very sensitive to the surrounding environment, which can be modulated to tune their optoelectronic properties. In this study, we significantly improved the optoelectronic properties of monolayer MoS2 by varying the surrounding environment using different liquid dielectrics, each with a specific dielectric constant ranging from 1.89 to 18. Liquid mediums offer the possibility of environment tunability on the same device. For a back-gated field effect transistor, the field effect mobility exhibited more than two-order enhancement when exposed to a high dielectric constant medium. Further investigation into the effect of the dielectric environment on the optoelectronic properties demonstrated a variation in photoresponse relaxation time with the dielectric medium. The rise and decay times were observed to increase and decrease, respectively, with an increase in the dielectric constant of the medium. These results can be attributed to the dielectric screening provided by the surrounding medium, which strongly modifies the charged impurity scattering, the band gap, and defect levels of monolayer MoS2. These findings have important implications for the design of biological and chemical sensors, particularly those operating in a liquid environment. By leveraging the tunability of the dielectric medium, we can optimize the performance of such sensors and enhance their detection capabilities.
Bilateral sidewall engineering Si1–x
Ge
x
iTFET for low power display application
*
Authors: Lin Jyi-Tsong , Chu Chun-Ju 
Published: September 2023

Abstract
In this work, we demonstrate the performance enhancement of bottom-gated inductive line-tunneling TFET (iTFET) through the integration of bilateral sidewall engineering with SiGe mole fraction variation, considering the feasibility of the fabrication process. We also employ a metal-semiconductor interface for carrier induction to improve the I
ON, resulting in a lower subthreshold swing average (S.S
avg). Using Sentaurus TCAD simulations, we show that the dominant current mechanism is line tunneling, and the hump effect is mitigated by using SiGe with different mole fractions on the sidewalls. Compared to conventional tunnel field-effect transistors, which require at least three doping processes and annealing, the proposed device requires only one doping process and utilizes the metal-semiconductor interface for carrier induction, significantly reducing the fabrication cost and thermal budget. These measurement based simulations show that the S.S
avg is improved to 21.5 mV dec−1 with an I
ON/I
OFF ratio of 106 at V
D = 0.2 V. This is the first time that a TFT with a subthreshold swing of less than 60 mV dec−1 has been proposed, so it will save much more power in the future and displays with high energy efficiency can be realized and widely used in IoT applications.
Spin–orbit torque on nuclear spins exerted by a spin accumulation via hyperfine interactions
Authors: Cahaya Adam B , Leon Alejandro O , Fauzi Mohammad H 
Published: September 2023

Abstract
Spin-transfer and spin–orbit torques allow controlling magnetic degrees of freedom in various materials and devices. However, while the transfer of angular momenta between electrons has been widely studied, the contribution of nuclear spins has yet to be explored further. This article demonstrates that the hyperfine coupling, which consists of Fermi contact and dipolar interactions, can mediate the application of spin–orbit torques acting on nuclear spins. Our starting point is a sizable nuclear spin in a metal with electronic spin accumulation. Then, via the hyperfine interactions, the nuclear spin modifies the an electronic spin density. The reactions to the equilibrium and nonequilibrium components of the spin density is a torque on the nucleus with field-like and damping-like components, respectively. This nuclear
spin–orbit
torque is a step toward stabilizing and controlling nuclear magnetic momenta, in magnitude and direction, and realizing nuclear spintronics.
Realizing high efficiency and luminance in green, yellow and blue organic light emitting diode by deoxyribonucleic acid
Authors: Song Jiayi , Guan Yunxia , Wang Cheng , Bao Xi , Li Wanjiao , Peng Keao , Xu Shuang , Chen Lijia , Niu Lianbin 
Published: September 2023

Abstract
Although the effect of the electron blocking layer (EBL) material, deoxyribonucleic acid (DNA), on the electroluminescence (EL) performance of organic light-emitting diodes (OLEDs) has been studied, the process of DNA regulation of exciton recombination region within the device is still unclear. Herein, devices with and without EBL were fabricated using different DNA spin-coating speeds, and the photoelectric performance of device were measured. By using DNA compounded with cetyltrimethyl ammonium (CTMA) as the EBL and hole buffer layer, so-called BioLEDs. The DNA-based green Alq3 BioLEDs achieve higher luminance (39 000 cd m−2) and higher current efficiency (8.4 cd A−1), which are increased by 49% and 54%, respectively, compared to the reference OLEDs without the addition of DNA. Similarly, the maximum luminance and efficiency of yellow Rubrene BioLEDs is increased by 64% (from 12 120 to 19 820 cd m−2) and 74% (from 1.36 to 2.36 cd A−1), the luminance and efficiency of blue TCTA BioLEDs is increased by 101% and 245%. Specifically, we found that as the thickness of DNA-CTMA increases, the exciton recombination region moves towards the interface between the emitting layer (EML) and the hole transport layer (HTL). By better confining excitons within the EML, the current efficiency of the BioLEDs is effectively improved. Accordingly, we provide a possible idea for achieve high performance DNA-based BioLEDs by adding DNA-CTMA EBL and hole buffer layers. Meanwhile, as the DNA thickness increases, the exciton recombination region moves towards the EML/HTL interface, thereby enhancing the efficiency of the DNA-based BioLEDs.