bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparative study on deep-learning-based leather surface defect identification
Authors: Chen Zhiqiang , Xu Daxing , Deng Jiehang , Chen Yi , Li Chuan 
Published: September 2023

Abstract
Detecting leather surface defects has become an important subject in industrial inspections and attracted significant attention as a challenging task. Traditional image processing techniques struggle with the detection of leather surface defects with a variety of shapes, sizes, backgrounds, and noise. Deep learning is a promising solution to this problem. This work focuses on the comparative study of 26 classical deep learning models in the field of leather surface defect type recognition. That aims to lay a foundation for the design and development of new schemes for leather defect inspection. Based on tanned leather from an enterprise, eight types of leather surface defects (cavities, pinholes, scratches, rotten surfaces, growth lines, healing wounds, folds, and bacterial wounds) were collected using an ultra-high definition whole leather imaging device. Two challenging datasets with various shapes, sizes, and colours were constructed. Extensive experimental evaluations were conducted. The deep learning model can achieve more than 95% accuracy when the defect imaging is ideal and limited. In case that the shapes, sizes, and colour of the above eight defects keep diverse, Densenet169 performed the best with a recognition accuracy of 72.5%, and ShuffleNet model with the worst performance reached 64.3%. Systematic in-depth experimental evaluation shows that deep learning models are promising in the field of leather surface defect detection, however, challenges remain.
Photovoltaic arrays fault diagnosis based on an improved dilated convolutional neural network with feature-enhancement
Authors: Gong Bin , An Aimin , Shi Yaoke 
Published: September 2023

Abstract
Photovoltaic (PV) arrays are installed outdoors and prone to abnormalities and various faults under harsh natural conditions, reducing power conversion efficiency and the life of the PV modules, and even causing electric shock and fire. Current fault diagnosis methods are unable to accurately identify and locate faults in PV arrays in PV power systems, leading to increased operation and maintenance costs. Therefore, the feature-enhancement improved dilated convolutional neural network (CNN) is proposed for fault diagnosis of PV arrays in this paper. Firstly, aim at the problem of information loss due to data structure and spatial hierarchy within the traditional CNN, and the loss of data after down-sampling, which leads to the inability to reconstruct information, a dilated convolution is introduced to obtain a larger perceptual field while reducing the computational effort. Meanwhile, the adaptive dual domain soft threshold group convolution attention module is proposed to enhance the essential features of faults and reduce the information redundancy given the ambiguity and blindness of the feature data in PV array fault extraction. Finally, the model performance of the proposed model is validated and the operability and effectiveness of the proposed method are verified experimentally. The diagnostic results show that the average diagnostic accuracy of the proposed model is 98.95% compared with other diagnostic models, with better diagnostic accuracy and more stable diagnostic performance.
Nondestructive observation of state of water in concrete using dielectric spectroscopy
Authors: Sudo Seiich , Sato Sachie , Kurihara Norihiko , Asano Megumi , Hayakawa Kenji 
Published: September 2023

Abstract
We present a method of observing the relaxation process reflecting the motion of water molecules masked by the contribution of electrical conduction. By using this method, we can observe the Cole–Cole-type relaxation process reflecting the motion of the bound water molecules in cement-based materials. The relaxation time and strength of this process increase with curing time, and both parameters saturate to a constant value. The curing time dependence of compressive strength can be described by a logarithmic function, and the change in compressive strength correlates strongly with the change in relaxation time. In the analysis using the τ-β
CC diagram, the trajectory of the τ-β
CC diagram shifts to the lower right as the curing progresses, and the feature of the trajectory of the τ-β
CC diagram depends on the difference in the wetting environment. Our results indicate that the state of water retained in the pore structure can be used as a probe to obtain information on the curing progress of concrete.
Exploring photovoltaic effect through simple experiments
Authors: Francisco S , Salgueiro da Silva M A , Cavadas B , Seixas T M 
Published: September 2023

Abstract
This work describes a laboratory practice centred around the demonstration of the photovoltaic effect and its application for renewable energy production. Several experiments are proposed to allow students to investigate how a PV cell works and how irradiance, load resistance, temperature, and light trapping mechanisms can affect its performance. Additionally, students can be introduced to the quantum nature of light and how it relates to the behaviour of semiconductor devices, by exploring how the incident light colour affects power output.
Theoretically assisted and empirical scalings in the problem of determination of internal inductance in tokamaks
Authors: Pustovitov V D 
Published: September 2023

Abstract
The problem of inferring the internal inductance

ℓ
i

from external magnetic measurements in tokamaks is considered. It was practically resolved in JET (Barana O et al 2002 Plasma Phys. Control. Fusion
44 2271), but several questions remain to be addressed before extrapolation of that method on other tokamaks. These naturally arise because of the integral nature of

ℓ
i

determined by unknown distribution of the magnetic field inside the plasma. Without universal solutions, the quality of approximations should be examined along with potential experimental enforcements of the existing procedures. This is the main goal of the study that is fully analytical. Several relevant quantities are calculated for the large-aspect-ratio plasma with elliptical shifted magnetic surfaces. Usually the plasma elongation

K

is mentioned as a key factor in the task. Here it is explicitly shown that not only

K

, but its radial derivative too plays a role. The latter parameter did not appear in the JET scaling and in the accompanying discussions. It is also shown that the

K

-dependent term representing there the first iteration actually brings a systematic error. Therefore, several improvements to that scaling can be proposed. The study is based on the use of virial relations for the toroidal axisymmetric configurations.
A review of UTe2at high magnetic fields
Authors: Lewin Sylvia K , Frank Corey E , Ran Sheng , Paglione Johnpierre , Butch Nicholas P 
Published: September 2023

AbstractUranium ditelluride (UTe2) is recognized as a host material to unconventional spin-triplet superconductivity, but it also exhibits a wealth of additional unusual behavior at high magnetic fields. One of the most prominent signatures of the unconventional superconductivity is a large and anisotropic upper critical field that exceeds the paramagnetic limit. This superconductivity survives to 35 T and is bounded by a discontinuous magnetic transition, which itself is also field-direction-dependent. A different, reentrant superconducting phase emerges only on the high-field side of the magnetic transition, in a range of angles between the crystallographicbandcaxes. This review discusses the current state of knowledge of these high-field phases, the high-field behavior of the heavy fermion normal state, and other phases that are stabilized by applied pressure.
Bayesian inference of supernova neutrino spectra with multiple detectors
Authors: Huang Xu-Run , Sun Chuan-Le , Chen Lie-Wen , Gao Jun 
Published: September 2023

Abstract
We implement the Bayesian inference to retrieve energy spectra of all neutrinos from a galactic core-collapse supernova (CCSN). To achieve high statistics and full sensitivity to all flavours of neutrinos, we adopt a combination of several reaction channels from different large-scale neutrino observatories, namely inverse beta decay on proton and elastic scattering on electron from Hyper-Kamiokande (Hyper-K), charged current absorption on Argon from Deep Underground Neutrino Experiment (DUNE) and coherent elastic scattering on Lead from RES-NOVA. Assuming no neutrino oscillation or specific oscillation models, we obtain mock data for each channel through Poisson processes with the predictions, for a typical source distance of 10 kpc in our Galaxy, and then evaluate the probability distributions for all spectral parameters of theoretical neutrino spectrum model with Bayes' theorem. Although the results for either the electron-neutrinos or electron-antineutrinos reserve relatively large uncertainties (according to the neutrino mass ordering), a precision of a few percent (i.e., ±1% ∼ ±4% at a credible interval of 2σ) is achieved for primary spectral parameters (e.g., mean energy and total emitted energy) of other neutrino species. Moreover, the correlation coefficients between different parameters are computed as well and interesting patterns are found. Especially, the mixing-induced correlations are sensitive to the neutrino mass ordering, which potentially makes it a brand new probe to determine the neutrino mass ordering in the detection of galactic supernova neutrinos. Finally, we discuss limitations and perspectives for further improvement on our results.
The magnificent ACT of flavor-specific neutrino self-interaction
Authors: Das Anirban , Ghosh Subhajit 
Published: September 2023

Abstract
We revisit the cosmology of neutrino self-interaction and use the latest cosmic microwave background data from the Atacama Cosmology Telescope (ACT) and the Planck experiment to constrain the interaction strength. In both flavor-universal and nonuniversal coupling scenarios, we find that the ACT data prefers strong neutrino self-interaction that delays neutrino free streaming until just before the matter-radiation equality. When combined with the Planck 2018 data, the preference for strong interaction decreases due to the Planck polarization data. For the combined dataset, the flavor-specific interaction still provides a better fit to the CMB data than ΛCDM. This trend persists even when neutrino mass is taken into account and extra radiation is added. We also study the prospect of constraining such strong interaction by future terrestrial and space telescopes, and find that the upcoming CMB-S4 experiment will improve the upper limit on neutrino self-interaction by about a factor of three.
Energetic particle marginal stability profile for HL-2M integrated simulation based on neural network module
Authors: Zou Yunpeng , Chan Vincent S. , Chen Wei , Zhu Yiren , Li Zeyu , Xue Miao 
Published: September 2023

Abstract
A critical gradient model is employed to develop a module of energetic particle (EP) marginal stability profiles in OMFIT integrated simulations for studying EP transport. Currently, each iteration of transport evolution is approximately 10 min in the integrated simulation, whereas, the EP marginal stability profile, which serves as an input in the integrated simulation could take much longer; the reason being a combination of the TGLFEP and EPtran codes is employed in our previous investigation. To reduce the simulation time, the critical gradient is predicted by a neural network instead of the TGLFEP code, and the EPtran code is revised with parallel computing, so that the running time of this module can be controlled to within 5 min. The predictions are in good agreement with previous approaches. The integrated simulation of HL-2M with Alfven eigenmodes transported by neutral beam EP profiles indicates that EP transport reduces the total pressure and current as expected, but could also under some conditions raise the safety factor in the core, which is favorable for reversed magnetic shear and high-performance plasmas.
People can understand IPCC visuals and are not influenced by colors
Authors: Battocletti Vittoria , Romano Alessandro , Sotis Chiara 
Published: September 2023

Abstract
We carry out two online experiments with large representative samples of the US population to study key climate visuals included in the Sixth Report of the Intergovernmental Panel on Climate Change (IPCC). In the first study (N = 977), we test whether people can understand such visuals, and we investigate whether color consistency within and across visuals influences respondents’ understanding, their attitudes toward climate change and their policy preferences. Our findings reveal that respondents exhibit a remarkably good understanding of the IPCC visuals. Given that IPCC visuals convey complex multi-layered information, our results suggest that the clarity of the visuals is extremely high. Moreover, we observe that altering color consistency has limited impact on the full sample of respondents, but affects the understanding and the policy preferences of respondents who identify as Republicans. In the second study (n = 1169), we analyze the role played by colors’ semantic discriminability, that is the degree to which observers can infer a unique mapping between the color and a concept (for instance red and warmth have high semantic discriminability). We observe that semantic discriminability does not affect attitudes toward climate change or policy preferences and that increasing semantic discriminability does not improve understanding of the climate visual.
How atmospheric humidity drives the outgoing longwave radiation–surface temperature relationship and inter-model spread
Authors: Feng Jing , Paynter David , Wang Chenggong , Menzel Raymond 
Published: September 2023

Abstract
The Earth’s global radiation budget depends critically on the relationship between outgoing longwave radiation (OLR) and surface temperature (

T

s

). Using the fifth generation of European ReAnalysis dataset, we find that although OLR appears to be linearly dependent on

T

s

over a wide range, there are significant deviations from the linearity in the OLR–

T

s

relationship for regions warmer than 270 K

T

s

, which covers 89% of the surface of Earth. While the AMIP runs of CMIP6 models largely capture the overall OLR–

T

s

relationship, considerable discrepancies are found in clear-sky OLR at given

T

s

ranges. In this study, we investigate physical mechanisms that control the clear-sky OLR–

T

s

relationship seen in reanalysis and CMIP6 models by using accurate radiative transfer calculations. Our study identifies three key mechanisms to explain both the linearity and departure from linearity of the clear-sky OLR–

T

s

relationship. The first is a surface contribution, controlled by the thermal emission of the surface and the infrared opacity of the atmosphere, accounting for 60% of the observed clear-sky OLR–

T

s

linear slope. The second is changes in atmospheric emission induced by a foreign pressure effect on water vapor and other greenhouse gases, which accounts for 30% of the linear slope in a clear-sky condition. The third is changes in atmospheric emission induced by variations in relative humidity (RH), particularly in the mid-troposphere (250 to 750 hPa), which determines the non-linearity in the clear-sky OLR–

T

s

relationship and adds to the remaining 10% of the slope. The inter-model spread in mid-tropospheric RH explains a large fraction of the differences in clear-sky OLR across CMIP6 models at given surface temperatures. Furthermore, the three key mechanisms outlined here apply to the OLR–

T

s

relationship in all-sky conditions: clouds disguise the surface contribution but increase the atmospheric contribution, retaining a similar linear slope to the clear-sky condition while amplifying the non-linear curvature.
Diagnosing observed extratropical stationary wave changes in boreal winter
Authors: Sun Wanying , Wang Lei 
Published: September 2023

Abstract
Stationary waves are time-averaged zonally asymmetric component of the climatological mean atmospheric circulation, primarily due to the unevenly distributed topography and diabatic heating. Stationary waves are subject to influence from long-term external forcing. In this study, the temporal evolution of the winter (January) Northern Hemisphere stationary waves during 1961–2020 is diagnosed with the fifth generation European Centre for Medium-range Weather Forecasts reanalysis data (ERA5), which shows an overall strengthening in amplitude and an eastward shift in phase. A stationary wave model is used to attribute the stationary wave response to changes in the zonal mean basic state (ΔZM) and the zonally asymmetric diabatic heating forcing (

Δ

q
∗

). The pattern of stationary wave changes is well captured by the response to ΔZM alone, whereas the contribution of

Δ

q
∗

to the amplitude increases in height and becomes dominant in the stratosphere.

Δ

q
∗

is also found to be important in driving stationary wave changes in the North Pacific and Western Europe regions. Furthermore, changes in tropospheric stationary waves are probably a result of internal variability, whereas stratospheric changes are more likely to be driven by external forcing.
Continuous phase transition induced by non-Hermiticity in the quantum contact process model
Authors: He Wen-Bin , Jin Jiasen , Iemini Fernando , Lin Hai-Qing 
Published: September 2023

Abstract
Non-Hermitian (NH) quantum system recently have attracted a lots of attentions theoretically and experimentally. However, the results based on the single-particle picture may not apply to understand the property of NH many-body system. How the property of quantum many-body system especially the phase transition will be affected by the non-Hermiticity remains unclear. Here we study NH quantum contact process (QCP) model, whose effective Hamiltonian is derived from Lindbladian master equation. We show that there is a continuous phase transition induced by the non-Hermiticity in QCP. We also determine the critical exponents β of order parameter, γ of susceptibility and study the correlation and entanglement near phase transition point. We observe that the order parameter and susceptibility display infinitely singularity even for finite size system, since non-Hermiticity endow many-body system with different singular behavior from classical phase transition. Moreover our results show that the phase transition have no counterpart in Hermitian case and belongs to completely different universality class.
Gleason’s theorem for composite systems
Authors: Frembs Markus , Döring Andreas 
Published: September 2023

Abstract
Gleason’s theorem (Gleason 1957 J. Math. Mech.
6 885) is an important result in the foundations of quantum mechanics, where it justifies the Born rule as a mathematical consequence of the quantum formalism. Formally, it presents a key insight into the projective geometry of Hilbert spaces, showing that finitely additive measures on the projection lattice

extend to positive linear functionals on the algebra of bounded operators

. Over many years, and by the effort of various authors, the theorem has been broadened in its scope from type I to arbitrary von Neumann algebras (without type

I
2

factors). Here, we prove a generalisation of Gleason’s theorem to composite systems. To this end, we strengthen the original result in two ways: first, we extend its scope to dilations in the sense of Naimark (1943 Dokl. Akad. Sci. SSSR
41 359) and Stinespring (1955 Proc. Am. Math. Soc.
6 211) and second, we require consistency with respect to dynamical correspondences on the respective (local) algebras in the composition (Alfsen and Shultz 1998 Commun. Math. Phys.
194 87). We show that neither of these conditions changes the result in the single system case, yet both are necessary to obtain a generalisation to bipartite systems.
Application of value chain analysis to corn (Zea mays) commodities in Indonesia: Integrative review
Authors: Jayadi Faisal , Latief Rindam 
Published: September 2023

Abstract
Analysis of the value chain begins with raw materials and finishes with a product that is ready for commercialization. The objective of this article review is to determine how chain analysis (value chain) is used to corn commodities in Indonesia. In the analysis of the corn value chain, farmers, middlemen, inter-island traders, the feed industry, and breeders are considered stakeholders. After the feed has undergone the drying process and been converted into feed, the profit margin is the highest at IDR 1,600, while the profit margin for middlemen or breeders purchasing directly from farmers ranges from IDR 350 to IDR 1,000.
Characteristics of sago and pectin edible film with the addition of chitosan and its use in hard candy wrappers
Authors: Layuk Payung , Winanda Elisa , Lintang Meivie , Lukas Amos , Ramlah Sitti , Ola La Onu La 
Published: September 2023

AbstractBiodegradable packaging is currently indispensable to reducing the use of plastics. The edible film is a type of food packaging that is safe, biodegradable, and environmentally friendly. This study aims to determine the characteristics of edible films of sago and pectin with different concentrations of chitosan. Comparison of sago and pectin (2:1) with 0.2%, 0.4%, 0.6%, and 0.8% of chitosan concentrations and 1% w/w and 1% glycerol b/v in each treatment. Observations were made on the solubility of the film, thickness, elongation, tensile strength, and color. Statistical analysis showed that the concentration of chitosan affected the thickness and color of the edible film but not elongation, tensile strength, and solubility. The best treatment was found at a concentration of 1% chitosan resulting in a film thickness of 0.115 mm, yellowish white color with a value of 6, a solubility of 98.80%, elongation of 5.75%, and tensile strength of 24.84 KPa. Edible film as a hard candy wrapper can reduce hygroscopic properties by 7.58% per hour.
Analysis of BPP readiness in realizing the Kostratani program
Authors: Yatim Hertasning , Yatim Herwin , Bakri R , Zahrah A 
Published: September 2023

Abstract
The Strategic Command for Agricultural Development (KOSTRATANI) at BPP is the center of the movement that will determine the success of agricultural development through coordination, synergy, and harmonization of agricultural development activities in the sub-districts. This study aims to analyze the readiness of BPP in realizing the KOSTRATANI program. The research method is quantitative descriptive. Based on the results of the study, the P value <0.05 of each variable with a variable value of <0.05, indicating the validity of the instrument and the reliability test showing that each variable is said to be reliable (reliable) because the respondents’ answers to the questions are consistent or stable. Based on the results of the study, it can be concluded that the readiness of the institution has a ready level, the readiness of human resources has a ready level, information readiness has a ready level, the readiness of information technology infrastructure has a ready level, and the readiness of the external environment has a ready level.