bluuebunny/crossref_metadata_2025 huggingface dataset:
Reducing Glare on Building Facade by Implementing Vertical Greenery Shading – user-sensation vs luminance-measurement
Authors: Kristanto Luciana , Nastiti Nugrahani Ekasiwi Sri , Dinapradipta Asri
Published: May 2024

The user of high-rise office building usually feel discomfort glare because of high luminance from glass facade. This experimental research has an objective to find out how vertical greenery can reduce the sensation of glare. Using here a cubicle that represent one person workstation in 2m x 4m x 3.45m dimension with opening from clear glass, WWR 50%. The base case was the condition without vegetation compared to condition with Vernonia elliptica plant LAI 0.75 and LAI 1.5 which implemented as shading. The result found that vegetation LAI 1.5 can reduce luminance 54.3-56.1% compared to without vegetation. The sensation of glare from Uncomfortable becomes Perceptible (for direct light); from Perceptible-Acceptable becomes Imperceptible-Perceptible (for diffuse light). Vegetation LAI 0.75, for direct light, can reduce luminance 35.3-53.6% compared to condition without vegetation. The glare sensation vote becomes Acceptable. Whilst for diffuse light, although the luminance measurement was increase because of the reflected glare from surroundings, the natural aesthetic and green colour of leaves was relaxing, so that the sensation of glare still at the same vote, between Perceptible-Acceptable compared to without vegetation. This result proof that for biotic shading, besides the quantitative, the qualitative variables play the role.
Advancing Sustainable Herbal Medicine: Synthesizing Nanoparticles from Medicinal Plants
Authors: Grace Pratiwi Rumahorbo Cheryl , Ilyas Syafruddin , Hutahaean Salomo , Fatimah Zuhra Cut
Published: May 2024

The crucial challenge in herbal medicine development lies in ensuring the safety, quality, and effectiveness of herbal materials to comply with the regulatory standards in the herbal medicine industry. This research aims to synthesize nano-based herbal medicine by combining two medicinal plants: Bischofia javanica leaves and Phaleria macrocarpa fruits. Through the High-Energy Milling (HEM) process, both materials are transformed into nanoparticles to enhance the solubility and bioavailability of active compounds. The herbal medicine standards are measured through Scanning Electron Microscopy (SEM), Particle Size Analysis (PSA), and Fourier-transform infrared spectroscopy (FTIR) tests. The SEM analysis results indicate optimal dispersion of nanoparticles, while PSA analysis reveals a reduction in particle size and increased homogeneity after nanonization with HEM. FTIR analysis results show various functional groups in nanoparticles, indicating the potential interaction between the combined components. The effectiveness of nanoparticles in the Rattus norvegicus Oral Squamous Cell Carcinoma (OSCC) model demonstrates an increase in lipid profile comparable to the effectiveness of Vitamin C. These findings highlight the potential of combined herbal treatment with nanoparticles produced by HEM, offering better efficacy and potential safety improvement, particularly in addressing lipid metabolism disorders.
Static Convergence Behaviour of Discrete Kirchhoff-Mindlin Triangular Element on Rectangular Functionally Graded Material Plates
Authors: Putrilan Syamnah Harahap Muthiah , Jauhari Maknun Imam , Atika Putri Cut
Published: May 2024

Rapid infrastructure development is consistent with the increase in innovation in structural elements. One of the main parameters in infrastructure development is materials. An advanced composite material called Functionally Graded Material (FGM) has been widely used. FGM is composed of the combination of two or more materials. FGM increases the bond strength between the layers compared to conventional composite materials, eliminating stress at the interface layers, and reducing cracks. However, further studies are required to understand the behaviour of the FGM plate. Finite element analysis (FEA) was considered to evaluate the convergence behaviour of the FGM plates. The Discrete Kirchhoff-Mindlin Triangular (DKMT) element is employed in the analysis. Studies regarding the FGM plates with the DKMT element were limited to square shapes and skew shapes. Thus, this study aims to study the convergence behaviour of the rectangular FGM plates composed of ceramic and metal. The FEA was carried out in different types of meshing, ratio a/h, ratio a/b, the power-law index, and boundary conditions. The analysis results indicate that the application of the DKMT element in analyzing the FGM plates gives good asymptotic and convergence behaviour. Thus, this method has proved reliable and sustainable.
Crashworthiness Evaluation of Electric Vehicle Battery Packs Using Honeycomb Structures and Explicit Dynamic Analysis
Authors: Agarwal Abhishek , Cavicchioli Batista Rafael , Tashi
Published: May 2024

The battery pack system is crucial to safeguard battery units during any collision. The crashworthiness of battery packs could be improved with the incorporation of honeycomb structures. The objective of the current study is to evaluate the structural characteristics of battery encasing using ANSYS explicit dynamic analysis. The modal analysis is conducted to determine the natural frequency, mode shape, and peak displacement values. The CAD model of the battery pack is developed in Creo parametric design software. The use of a honeycomb structure enabled the reduction of the effect of impact on battery units. At the time of the collision, the honeycomb structure would absorb maximum crash impact and would save the battery unit cells from major damage. The natural frequency of a battery pack with a honeycomb structure has a higher first, 2nd, and 3rdnatural frequency. At the time of impact and without any honeycomb structure, the internal energy of the battery unit is 1021.8mJ while with the honeycomb lattice structure, it is 0.80376mJ. The results have shown that with the incorporation of a honeycomb structure, there is a substantial reduction in the internal energy of the cell with the incorporation of the lattice structure.
Next-Generation Sequencing and Emerging Technologies*
Authors: Kumar Kishore R. , Cowley Mark J. , Davis Ryan L.
Published: May 2024

Genetic sequencing technologies are evolving at a rapid pace with major implications for research and clinical practice. In this review, the authors provide an updated overview of next-generation sequencing (NGS) and emerging methodologies. NGS has tremendously improved sequencing output while being more time and cost-efficient in comparison to Sanger sequencing. The authors describe short-read sequencing approaches, such as sequencing by synthesis, ion semiconductor sequencing, and nanoball sequencing. Third-generation long-read sequencing now promises to overcome many of the limitations of short-read sequencing, such as the ability to reliably resolve repeat sequences and large genomic rearrangements. By combining complementary methods with massively parallel DNA sequencing, a greater insight into the biological context of disease mechanisms is now possible. Emerging methodologies, such as advances in nanopore technology, in situ nucleic acid sequencing, and microscopy-based sequencing, will continue the rapid evolution of this area. These new technologies hold many potential applications for hematological disorders, with the promise of precision and personalized medical care in the future.
miR-92b-3p Protects against Myocardial Ischemia-Reperfusion Injury by Inhibiting MAP3K2 in a Mouse Model
Authors: Zhao Kun , Wang Mei
Published: May 2024

Objective MicroRNAs are well-known RNA regulators modulating biological functions in complex signaling networks. This work aims to explore the impact of microRNA-92b-3p (miR-92b-3p) on myocardial ischemia-reperfusion (I/R) injury.

Materials and Methods The I/R model was established by left anterior descending coronary artery ligation in mice. The hemodynamic parameters were detected through a multichannel physiological recorder. Myocardial injury markers: serum cardiac troponin I, myocardial kinase isoenzyme (creatine kinase-MB), and serum inflammatory factors (tumor necrosis factor-α, interleukin [IL]-1β, and IL-6) were evaluated by enzyme-linked immunosorbent assay. Cardiac tissue oxidative stress-related factors (malondialdehyde, glutathione peroxidase, total antioxidation capability, and superoxide dismutase) were assessed by colorimetry, myocardial pathology was observed by hematoxylin–eosin staining, and cardiomyocyte apoptosis was measured by triphosphate nick end-labeling staining, as well as the expression of miR-92b-3p and mitogen-activated protein kinase kinase kinase 2 (MAP3K2) in cardiac tissues were determined by reverse transcription quantitative polymerase chain reaction or western blot assay. The targeting relationship between miR-92b-3p and MAP3K2 was verified by bioinformatics, RNA immunoprecipitation, and luciferase reporter assays.

Results miR-92b-3p was lowly expressed and MAP3K2 was highly expressed in myocardial I/R injury mice. Upregulation of miR-92b-3p improved hemodynamic indices, decreased serum levels of myocardial injury biomarkers, inhibited serum inflammatory response, alleviated cardiac tissue oxidative stress, relieved myocardial pathology, and reduced cardiomyocyte apoptosis during the myocardial I/R injury in mice. MAP3K2 was a direct target gene of miR-92b-3p.

Conclusion This research suggests that miR-92b-3p protects against myocardial I/R injury by inhibiting MAP3K2, which may provide novel candidates for treatment of myocardial I/R injury.
Research on transformer fault diagnosis based on active learning with imbalanced data of dissolved gas in oil
Authors: Tang Pengfei , Zhang Zhonghao , Tong Jie , Ma Zhenyuan , Long Tianhang , Huang Can , Qi Zihao
Published: May 2024

The power transformer is the core equipment of the power system, a sudden failure of which will seriously endanger the safety of the power system. In recent years, artificial intelligence techniques have been applied to the dissolved gas analysis evaluation of power transformers to improve the accuracy and efficiency of power transformer fault diagnosis. However, most of the artificial intelligence techniques are data-driven algorithms whose performance decreases when the data are limited or significantly imbalanced. In this paper, we propose an active learning framework for power transformer dissolved gas analysis, in which the model can be dynamically trained based on the characteristics of the data and the training process. In addition, this paper also improves the original active learning spatial search strategy and uses the product of sample feature differences instead of the original sum of differences as a measure of sample difference. Compared to passive learning algorithms, the novel approach could significantly reduce the data labeling effort while improving prediction accuracy.
Exploring electron donor and acceptor effects: DFT analysis of ESIPT/GSIPT in 2-(oxazolinyl)-phenols for photophysical and luminophore enhancement
Authors: Panneerselvam Murugesan , Francis Reshma Rensil , Nathiya Singaravel , Solomon Rajadurai Vijay , Jaccob Madhavan , Costa Luciano T.
Published: May 2024

Understanding excited-state intramolecular proton transfer (ESIPT) is essential for designing organic molecules to enhance photophysical and luminophore properties in the development of optoelectronic devices. In this context, an attempt has been made to understand the impact of substituents on the ESIPT process of 2-(oxazolinyl)-phenol. Electron donating (EDG: –NH2, –OCH3, and –CH3) and electron withdrawing (EWG: –Cl, –Br, –COOH, –CF3, –CN, and –NO2) substitutions have been computationally designed and screened through density functional theory (DFT) and time-dependent density-functional theory (TDDFT) calculations. Furthermore, the ground state intramolecular proton transfer and ESIPT mechanisms of these designed luminophores are explored using the transition state theory. The results reveal that molecules with EDG show higher absorption and emission peaks than molecules with EWG and also indicate that the mobility of charge carriers in 2-(oxazolinyl)-phenol derivatives is significantly influenced by substituents. We found that the EWGs decrease the reorganization energy and increase the vertical ionization potential and electron affinity values, as well as the highest occupied molecular orbital-lowest unoccupied molecular orbital gap, compared to the EDG substituted molecules. Significantly, the excited state (S1) of the keto emission (K) form shows notably larger values for the EDG substitutions. The intersystem crossing pathway efficiency weakens with reduced spin–orbit coupling matrix element in the enol form with electron-donating substituents and vice versa in the keto form during S1–T3 transitions. Our research links intramolecular proton transfers and triplet generation, making these substituted molecules appealing for optoelectronic devices. Introducing EDGs, such as –NH2, boosts the ESIPT reaction in 2-(oxazolinyl)-phenol. This study guides designing ESIPT emitters with unique photophysical properties.
Exploration of Stokes hydrodynamic law at molecular length scales
Authors: Acharya Subhajit , Bagchi Biman
Published: May 2024

The celebrated generalized Stokes law predicts that the velocity of a particle pulled through a liquid by an external force, Fex, is directly proportional to the force and inversely proportional to the friction ζ acted by the medium on the particle. We investigate the range of validity of the generalized Stokes law at molecular length scales by employing computer simulations to calculate friction by pulling a tagged particle with a constant force. We thus calculate friction for two model interaction potentials, Lennard-Jones and soft sphere, for several particle sizes, ranging from radius (a) smaller than the solvent particles to three times larger. We next obtain friction from diffusion (D) by using Einstein’s relation between diffusion and friction ζ in an unperturbed liquid. We find a quantitative agreement between the two at a small-to-intermediate pulling force regime for all the sizes studied. The law does break down at a large pulling force beyond a threshold value. Importantly, the range of validity of Stokes’ scheme to obtain friction increases substantially if we turn off the attractive part of the interaction potential. Additionally, we calculate the viscosity (η) of the unperturbed liquid and find a good agreement with the Stokes–Einstein relation ζ = Cηa for the viscosity dependence with a value of C close to 5 π, which is intermediate between the slip and stick boundary condition.
Variational umbrella seeding for calculating nucleation barriers
Authors: Gispen Willem , Espinosa Jorge R. , Sanz Eduardo , Vega Carlos , Dijkstra Marjolein
Published: May 2024

In this work, we introduce variational umbrella seeding, a novel technique for computing nucleation barriers. This new method, a refinement of the original seeding approach, is far less sensitive to the choice of order parameter for measuring the size of a nucleus. Consequently, it surpasses seeding in accuracy and umbrella sampling in computational speed. We test the method extensively and demonstrate excellent accuracy for crystal nucleation of nearly hard spheres and two distinct models of water: mW and TIP4P/ICE. This method can easily be extended to calculate nucleation barriers for homogeneous melting, condensation, and cavitation.
Thermodynamics of the gas-phase dimerization of formic acid: Fully anharmonic finite temperature calculations at the CCSD(T) and many DFT levels
Authors: Vrška Dávid , Pitoňák Michal , Bučko Tomáš
Published: May 2024

A proof-of-concept study is undertaken to demonstrate the utility of the machine learning combined with the thermodynamic perturbation theory (MLPT) to test the accuracy of electronic structure methods in finite-temperature thermodynamic calculations. As a test example, formic acid dimer is chosen, which is one of the systems included in the popular benchmark set S22 [Jurečka et al., Phys. Chem. Chem. Phys. 8, 1985–1993 (2006)]. Starting from the explicit molecular dynamics and thermodynamic integration performed at the PBE + D2 level, the MLPT is used to obtain fully anharmonic dimerization free and internal energies at the reference quality CCSD(T) level and 19 different density functional approximations, including GGA, meta-GGA, non-local, and hybrid functionals with and without dispersion corrections. Our finite-temperature results are shown to be both qualitatively and quantitatively different from those obtained using the conventional benchmarking strategy based on fixed structures. The hybrid functional HSE06 is identified as the best performing approximate method tested, with the errors in free and internal energies of dimerization being 36 and 41 meV, respectively.
Interdependence of cellular and network properties in respiratory rhythm generation
Authors: Phillips Ryan S. , Baertsch Nathan A.
Published: May 2024

How breathing is generated by the preBötzinger complex (preBötC) remains divided between two ideological frameworks, and a persistent sodium current (I
NaP
) lies at the heart of this debate. Although I
NaP
is widely expressed, the pacemaker hypothesis considers it essential because it endows a small subset of neurons with intrinsic bursting or “pacemaker” activity. In contrast, burstlet theory considers I
NaP
dispensable because rhythm emerges from “preinspiratory” spiking activity driven by feed-forward network interactions. Using computational modeling, we find that small changes in spike shape can dissociate I
NaP
from intrinsic bursting. Consistent with many experimental benchmarks, conditional effects on spike shape during simulated changes in oxygenation, development, extracellular potassium, and temperature alter the prevalence of intrinsic bursting and preinspiratory spiking without altering the role of I
NaP
. Our results support a unifying hypothesis where I
NaP
and excitatory network interactions, but not intrinsic bursting or preinspiratory spiking, are critical interdependent features of preBötC rhythmogenesis.
Revisiting the aspectual BUSY
in (South African) English
Authors: Breed Adri
Published: May 2024

This paper investigates the so-called South African English busy progressive (for example,
I’m busy working). Linguistic literature on South African English (SAfE) often states that this construction
is a typical feature of this variety of English. The use and the frequency of this construction is mostly attributed to the
influence of the Afrikaans [BUSYPROG XCOMP VINF] construction, as in Ek is besig om te
werk (‘I am working’). The aim of this paper is twofold: Firstly, it critically evaluates some of the claims that
have been made about the so-called “SAfE busy progressive” and, secondly, it uses a corpus- and usage-based approach that employs
a greater assortment of available corpus data from SAfE and other English varieties, as well as available information on the
Afrikaans and Dutch progressives, to explore the possibility of new insights into the use of busy in English
aspectual constructions.
Een mooi paar mouwen
Authors: de Vaan Michiel
Published: May 2024

This paper investigates the etymology of Dutch mooi ‘beautiful’. It argues that Dutch
mooi and Dutch mouw ‘sleeve’, which are not directly related within Germanic,
may be derived from the same Proto-Indo-European root *muH- ‘to move’.
Sound change, analogy, and urban koineization in the regularization of verbs in late fourteenth-century
English
Authors: Fertig David
Published: May 2024

This paper presents a detailed comparison of certain verb forms in Sir Firumbras, a text
produced in a relatively remote part of southwestern England around 1380, with those found in texts produced in the
London area around the same time. The forms in question reflect a collapse in some dialects of earlier present-tense
distinctions between strong verbs and the largest class of weak verbs. This collapse is commonly assumed to have
affected southern English in general but the evidence presented here suggests that it may initially have been
characteristic only of urban regions with an influx of migrants from other parts of the country.
Weaving data strands together
Authors: Auer Anita , Gordon Moragh S.
Published: May 2024

The important role of historical cities as centers of higher literacy and text production in the
standardization processes of written languages has been recognized some time ago by scholars working on different
languages. The current article, which is couched in the study of urban vernaculars in the field of historical
sociolinguistics, focuses on written language use in Norwich during the period 1422–1760. Within the context of the
city’s socio-economic history, the article investigates two linguistic variables, notably the third person present
tense forms and periphrastic DO, in the manuscript-based Corpus of Middle English Local Documents
(MELD) and An Electronic Text Edition of Depositions 1560–1760 (ETED) and compares them to findings
from other urban centers. Despite the restricted data set, the study shows that the supralocalization processes and
the speed of change differ from one linguistic feature to another in the different urban datasets. The Norwich data
confirms previous findings of other urban datasets that the supralocalization of the morphological feature precedes
that of the syntactic feature.
The dialect of Vriezenveen
Authors: van Bree Cor
Published: May 2024

The village of Vriezenveen (not far from Almelo in Twente, an eastern region of the Netherlands) has a
dialect that differs from its neighboring dialects in a number a features. For instance, instead of lengthened vowels
in open syllables it can have rising diphthongs whereas the other Twente dialects have centered diphthongs or short
vowels more open than the original short ones: ljèvn ‘to live’ [jæ.] opposite to
lèëvn [εǝ] of lèvvn [ε] (Standard Dutch leven [e.] <
[ε]).1 The Vriezenveen dialect also has (or had) diphthongs in
stein ‘stone’ [εi], geitn ‘to pour’, bouk ‘book’ [ɔu] instead
of Twente dialect stèèn [ε.], geetn [e.], book [o.], Standard Dutch
steen [e.], gieten [i], boek [u]. These conservative features
can be explained by the fact that the inhabitants of Vriezenveen had extensive contacts with the Westphalian region
through which they travelled on their commercial tours to Russia (Saint Petersburg). In this German region these
features can still be found. On the other hand, a form like huus ‘house’, with [y.] instead of [u.],
points in a western direction. Nowadays the young inhabitants of Vriezenveen are adapting their dialect to the more
general Twente dialect. This regiolectization clearly manifested itself during interviews organized from 2012 through
2015.
An excursion into the lost history of historical sociolinguistics
Authors: Lauersdorf Mark Richard , Salmons Joseph
Published: May 2024

An origin story has emerged and solidified around the relatively new research area called historical
sociolinguistics – a story based primarily on the field’s relatively brief history as a “named” field (reaching back
only a few decades) and repeated regularly and largely uniformly in summary, overview, encyclopedic, and introductory
presentations of historical sociolinguistics. We argue that the defining characteristics of the modern field are
deeply connected to and clearly rooted in the key traditions of historical and sociolinguistics and allied areas going
back to the nineteenth century. We highlight select instances of sociolinguistic thinking in early historical
linguistic work and historical considerations in early sociolinguistic research, as well as key notions, including
uniformitarianism from historical-comparative linguistics and ego-documents from social history. Better understanding
of the history of historical sociolinguistics, we argue, helps us anchor our future work better in the full relevant
context.
R-matrix calculations for opacities: IV. Convergence, completeness, and comparison of relativistic R-matrix and distorted wave calculations for Fe xvii and Fe xviii
Authors: Zhao L , Nahar S N , Pradhan A K
Published: May 2024

To investigate the completeness of coupled channel (CC) Breit–Pauli R-matrix (BPRM) calculations for opacities we employ the relativistic distorted wave (RDW) method to complement (‘top-up’) and compare the BPRM photoionization cross sections for high-

n
ℓ

levels of both Fe xvii and Fe xviii . Good agreement is found with background photoionization cross sections using these two methods, which also ensures the correct matching of bound level cross sections for completeness. In order to top-up the CC-BPRM calculations, bound–bound transitions involving additional bound levels, and a large number of doubly-excited quasi-bound levels corresponding to BPRM autoionizing resonances described in the paper RMOPII are calculated using the RDW method. Photoionization cross sections in the high energy region are also computed and compared up to about 500 Ry, and contributions from higher core level excitations than BPRM are considered. The effect of configuration interaction is investigated, which plays a significant role in correctly reproducing some background cross sections. Due to the fact that the additional RDW levels correspond to high-

n
ℓ

bound levels that are negligibly populated according to the Mihalas–Hummer–Däppen equation-of-state (paper I), the effect on opacities is expected to be small.
A pipeline corrosion detecting method using percussion and residual neural network
Authors: Yang Dan , Ji Songlin , Wang Tao , Shu XianTao , Lu Guangtao
Published: May 2024

Corrosion of pipeline walls can lead to serious safety accidents such as leaks, fires and even explosions. This paper proposes a corrosion detection method using deep learning based on percussion sound for pipelines. The percussion induced acoustic signals are processed by wavelet threshold noise reduction and double threshold endpoint detection to generate the Mel spectrograms, and then an 18-layer residual network (ResNet18) is used to mine the depth information and classify the degree of pipeline corrosion. We conducted experiments to verify the validity of the approach. Seven working conditions are generated by electrochemical corrosion of a pipe specimen, and percussions are applied at five different positions under the same working conditions to collect the impact acoustic signals. The test results show that the method can quickly, efficiently and accurately detect the degree of pipeline corrosion, classify the degree of pipe corrosion without being affected by the striking position Therefore, the model has great potential for application in detecting the internal corrosion of pipelines based on percussion sounds.
Self-supervised monocular visual odometry based on cross-correlation
Authors: Hu Jiaxin , Tao Bo , Qian Xinbo , Jiang Du , Li Gongfa
Published: May 2024

Visual odometry constitutes a critical component in enabling autonomous navigation. However, the existing methods are limited by the feature extraction and matching accuracy, and cannot show good real-time performance while combining accuracy and robustness. In this paper, we propose a novel monocular visual odometry framework based on cross-correlation. The framework starts with a parameter-sharing Siamese network to build feature extractors that can simultaneously process multiple images as inputs. Moreover, we design cross-correlation modules and define a cross-correlation matrix to describe the strength of correlation between different parts of the input feature maps, reflecting the rotational and translational transformations of the input images. Furthermore, a novel loss function is introduced to impose constraints on the network. Additionally, a fully convolutional network is designed for pose estimation, computing poses alterations from the structure of the cross-correlation matrix. Channel attention and spatial attention mechanisms are introduced to improve the performance. More importantly, our method innovatively uses time intervals as labels, enables self-supervised training, and relies only on a monocular camera. Experimental results on the KITTI visual odometry dataset and the Oxford Robotcar Dataset show that our method produces competitive performance, demonstrating the superiority of the proposed method.
A cascaded GRU-based stereoscopic matching network for precise plank measurement
Authors: Xiong Xiang , Li Yibo , Liu Jiayi , Qin Wenjin , Qian Liu
Published: May 2024

Wooden plank images in industrial measurements often contain numerous textureless areas. Furthermore, due to the thin plate structure, the three-dimensional (3D) disparity of these planks is predominantly confined to a narrow range. Consequently, achieving accurate 3D matching of wooden plank images has consistently presented a challenging task within the industry. In recent years, deep learning has progressively supplanted traditional stereo matching methods due to its inherent advantages, including rapid inference and end-to-end processing. Nonetheless, the acquisition of datasets for stereo matching networks poses an additional challenge, primarily attributable to the difficulty in obtaining accurate disparity data. Thus, this paper presents a novel stereo matching method incorporating three key innovations. Firstly, an enhanced gated recurrent unit network is introduced, accompanied by a redesigned structure to achieve higher matching accuracy. Secondly, an efficient preprocessing module is proposed, aimed at improving the algorithm’s efficiency. Lastly, in response to the challenges posed by datasets acquisition, we innovatively employed image simulation software to obtain a high-quality simulated dataset of wooden planks. To assess the feasibility of our approach, we conducted both simulated and real experiments. The experiments results clearly exhibit the superiority of our method when compared to existing approaches in terms of both stability and accuracy. In the simulation experiment, our method attained a bad1.0 score of 2.1% (compared to the baseline method’s 9.76%); In the real experiment, our method achieved an average error of 0.104 mm (compared to the baseline method’s 0.268 mm). It is worth noting that our study aims to address the challenge of acquiring datasets for deep learning and bridging the gap between simulated and real data, resulting in increased applicability of deep learning in more industrial measurement domains.
Phononic origin of the infrared dielectric properties of RE2O3 (RE = Y, Gd, Ho, Lu) compounds
Authors: Luo Yixiu , Wang Juan , Sun Luchao , Wang Jingyang
Published: May 2024

Understanding the phononic origin of the infrared (IR) dielectric properties of yttria (Y2O3) and other rare-earth sesquioxides (RE2O3) is a fundamental task in the search of appropriate RE2O3 materials that serve particular IR optical applications. We herein investigate the IR dielectric properties of RE2O3 (RE = Y, Gd, Ho, Lu) using density functional theory-based phonon calculations and Lorentz oscillator model. The abundant IR-active optical phonon modes that are available for effective absorption of photons result in high reflectance of RE2O3, among which four IR-active modes originated from large distortions of REO6 octahedra are found to contribute dominantly to the phonon dielectric constants. Particularly, the present calculation method by considering one-phonon absorption process is demonstrated with good reliability in predicting the IR dielectric parameters of RE2O3 at the far-IR as well as the vicinity of mid-IR region, and the potential cutoff frequency/wavelength of its applicability is disclosed as characterized by the maximum frequency of IR-active longitudinal phonon modes. The results deepen the understanding on IR dielectric properties of RE2O3, and aid the computational design of materials with appropriate IR properties.
Mid-infrared Period–Luminosity Relations of Gaia DR3 Long Period Variables
Authors: Chen Xiaohan , Chen Xiaodian , Deng Licai , Wang Shu , Chen Tianlu
Published: May 2024

Long period variable (LPV) stars are very promising distance indicators in the infrared bands. We selected asymptotic giant branch (AGB) stars in the Large and Small Magellanic Cloud (LMC and SMC) from the Gaia Data Release 3 LPV catalog, and classified them into oxygen-rich (O-rich) and carbon-rich (C-rich) AGB stars. Using the Wide-field Infrared Survey Explorer database, we determined the W1- and W2-band period–luminosity relations (PLRs) for each pulsation-mode sequence of AGB stars. The dispersion of the PLRs of O-rich AGB stars in sequences

C
′

and C is relatively small, around 0.14 mag. The PLRs of LMC and SMC are consistent in each sequence. In the W2 band, the PLR of large-amplitude C-rich AGB stars is steeper than that of small-amplitude C-rich AGB stars, due to their more circumstellar dust. By two methods, we find that some PLR sequences of O-rich AGB stars in the LMC are dependent on metallicity. The coefficients of the metallicity effect are β = –0.533 ± 0.213 mag dex1 and β = –0.767 ± 0.158 mag dex1 for sequence C in W1 and W2 bands, respectively. The significance of the metallicity effect in W1 band for the four sequences is 2.2−3.5σ. Both of these imply that distance measurements using O-rich Mira may need to take the metallicity effect into account.
Frustration—no frustration crossover and phase transitions in 2D spin models with zig-zag structures
Authors: Sznajd Jozef
Published: May 2024

Three 2D spin models made of frustrated zig-zag chains with competing interactions which, by exact summation with respect to some degrees of freedom, can be replaced by an effective temperature-dependent interaction, were considered. The first model, exactly solvable Ising chains coupled by only four-spin interactions, does not exhibit any finite temperature phase transition; nevertheless, temperature can trigger a frustration–no frustration crossover accompanied by gigantic specific heat. A similar effect was observed in several two-leg ladder models (Weiguo 2020 arXiv:2006.08921v2; 2020 2006.15087v1). The anisotropic Ising chains coupled by a direct interchain interaction and, competing with it, indirect interaction via spins located between chains, are analyzed using the exact Onsager’s equation and linear perturbation renormalization group (LPRG). Depending on the parameter set, such a model exhibits one antiferromagnetic (AF) or ferromagnetic (FM) phase transition or three phase transitions with a re-entrant disordered phase between AF and FM ones. The LPRG method was also used to study coupled uniaxial XXZ chains which, for example, can be a minimal model to describe the magnetic properties of compounds in which uranium and rare earth atoms form zig-zag chains. As with the Ising model, for a certain set of parameters, the model can undergo three phase transitions. However, both intrachain and interchain plain interactions

s

i
,
j

x

s

k
,
l

x

+

s

i
,
j

y

s

k
,
l

y

can eliminate the re-entrant disordered phase, and then only one transition takes place. Additionally, the XXZ model can undergo temperature-induced metamagnetic transition.
Deep learning improves sub-seasonal marine heatwave forecast
Authors: Sun Di , Jing Zhao , Liu Hailong
Published: May 2024

Marine heatwaves (MHWs) are extreme anomalously warm water events, which are projected to cause increasing numbers of disastrous impacts on ecosystems and economies under global ocean warming. Our ability to forecast MHWs determines what effective measures can be taken to help reduce the vulnerability of marine ecosystems and human communities. In this study, we combine a deep learning model, the convolutional neural network, with a real-time sub-seasonal to seasonal physical forecast model, improving MHW forecast skills by nearly 10% of the global average in leading two weeks by correcting the physical model bias with observational data. This improvement has a nearly consistent influence (∼10%–20%) on a global scale, reflecting the wide-coverage promotion by deep learning. This work reveals the advantages and prospects of the combination of deep learning and physical models in ocean forecasts in the future.
Unraveling the dynamics of atmospheric methane: the impact of anthropogenic and natural emissions
Authors: Fu Bo , Jiang Yongye , Chen Guolong , Lu Mengmeng , Lai Yuqin , Suo Xinhao , Li Bengang
Published: May 2024

The reduction in methane concentration is crucial for achieving the goals of the Paris agreement. However, its annual growth rate is unstable, and understanding the reasons for changes in methane growth is essential for climate policy-making. Currently, there is considerable uncertainty regarding its attribution. Here, we utilize multi-source data and optimal fingerprinting methods to detect the contributions of several key drivers to the methane trend and interannual variability. We find that the methane growth trend is primarily influenced by anthropogenic emissions, while interannual variability is predominantly determined by wetland and biomass burning emissions. This result underscores the central role of anthropogenic emissions in methane dynamics, providing confidence in the effectiveness of human efforts to control methane atmospheric concentrations through emission reductions. It also helps alleviate concerns about the recent surge in atmospheric methane concentration, as it may be a short-term peak caused by increased wetland emissions rather than a long-term change.
Machine learning-based model for the intelligent estimation of critical heat flux in nanofluids
Authors: Alipour Bonab Shahin , Yazdani-Asrami Mohammad
Published: May 2024

The rising demand for advanced energy systems requires enhanced thermal management strategies to maximize resource utilization and productivity. This is quite an important industrial and academic trend as the efficiency of energy systems depends on the cooling systems. This study intends to address the critical need for efficient heat transfer mechanisms in industrial energy systems, particularly those relying on pool boiling conditions, by mainly focusing on Critical Heat Flux (CHF). In fact, CHF keeps a limit in thermal system design, beyond which the efficiency of the system drops. Recent research materials have highlighted nanofluids’ superior heat transfer properties over conventional pure fluids, like water, which makes them a considerable substitution for improving CHF in cooling systems. However, the broad variability in experimental outcomes challenges the development of a unified predictive model. Besides, Machine Learning (ML) based prediction has shown great accuracy for modeling of the designing parameters, including CHF. Utilizing ML algorithms—Cascade Forward Neural Network (CFNN), Extreme Gradient Boosting (XGBoost), Extra Tree, and Light Gradient Boosting Method (LightGBM)— four predictive models have been developed and the benchmark shows CFNN’s superior accuracy with an average goodness of fit of 89.32%, significantly higher than any available model in the literature. Also, the iterative stability analysis demonstrated that this model with a 0.0348 standard deviation and 0.0268 mean absolute deviation is the most stable and robust method that its performance minorly changes with input data. The novelty of the work mainly lies in the prediction of CHF with these advanced algorithm models to enhance the reliability and accuracy of CHF prediction for designing purposes, which are capable of considering many effective parameters into account with much higher accuracy than mathematical fittings. This study not only explains the complex interplay of nanofluid parameters affecting CHF but also offers practical implications for the design of more efficient thermal management systems, thereby contributing to the broader field of energy system enhancement through innovative cooling solutions.
On Rhaly operators on 𝑙²
Authors: Popescu George , Prǎjiturǎ Gabriel
Published: May 2024

We study the class of Rhaly operators and discuss their property onl2l^2. In particular we studied when such operators are bounded, and offered estimates for the norm, when they are compact and they are hyponormal. We also discussed some of their spectral properties.
More on skew braces and their ideals
Authors: Smoktunowicz Agata
Published: May 2024

This paper introduces the notion of a strongly prime ideal, and shows that the largest solvable ideal in a finite brace equals the intersection of all strongly prime ideals in this brace. This is used to generalise some well-known results from ring theory into the context of braces and pre-Lie algebras. Several open questions are also posed.
Estimation of the eigenvalues and the integral of the eigenfunctions of the Newtonian potential operator
Authors: Alsenafi Abdulaziz , Ghandriche Ahcene , Sini Mourad
Published: May 2024

We consider the problem of estimating the eigenvalues and the integral of the corresponding eigenfunctions, associated to the Newtonian potential operator, defined in a bounded domain

Ω
⊂

R

d

\Omega \subset \mathbb {R}^{d}

, where

d
=
2
,
3

d=2,3

, in terms of the maximum radius of

Ω
\Omega

. We first provide these estimations in the particular case of a ball and a disc. Then we extend them to general shapes using a, derived, monotonicity property of the eigenvalues of the Newtonian operator. The derivation of the lower bounds is quite tedious for the 2D-Logarithmic potential operator. Such upper/lower bounds appear naturally while estimating the electric/acoustic fields propagating in

R

d

\mathbb {R}^{d}

in the presence of small scaled and highly heterogeneous particles.
Higher residues and canonical pairing on the twisted de Rham cohomology
Authors: Kim Hoil , Kim Taejung
Published: May 2024

We describe an explicit formula of the canonical pairing on the twisted de Rham cohomology associated with the category of local matrix factorizations and by characterizing its relation to Saito’s higher residue pairings we reprove the conjecture of Shklyarov [Adv. Math. 292 (2016), pp. 181–209].
Early Christianity as Evidence for Socially Superior Religion
Authors: Stowers Stanley
Published: May 2024

The chapter uses the work of the sociologist Rodney Stark on ancient Christianity strategically to raise and consider questions about Christianity’s beginnings, reputed overwhelming success, and moral and social superiority. For Stark, employing rational choice theory, “paganism” was a failed form of religion that Christianity easily defeated. My theory of four subkinds shows that Stark has mischaracterized ancient Mediterranean religion. The Christian social formation is not comparable to the religion of everyday social exchange and civic religion, and it did not compete in a general market of religious goods. One section takes up the debate between the methodological individualism of rational choice theory and the holism of theories that have the economy embedded in social norms and obligations. The results show why Stark’s analysis of ancient Mediterranean religion does not work and sheds light on the nature of the four subkinds.
Explaining the Evidence of Ancient Christian Formation
Authors: Stowers Stanley
Published: May 2024

A good test of a social theory’s power comes from its ability to explain the evidence for a historical claim. The chapter shows that the kinds theory gives better explanation to four illustrative issues: the character of lay (nonexpert insiders) Christianity, supposed ancient Jewish and Christian monotheism, the growth of early Christianity, and the character of ancient Christian almsgiving. Knowledge of nonexpert/lay belief and activity, since they did not write, can only be derived from archeological sources and especially from critical reading of the constant expert complaints about their failures to be good Christians. Monotheism is an invention of the early modern West, did not exist in antiquity, and is not the key to the attractiveness and success of Christianity. The standard over-the-top claims by historians about the growth of ancient Christianity are based on the myth of origins in early Christian writings of miraculous and explosive growth and do not stand up to critical scrutiny. Stark, an expert on Mormonism, made the same mistakes with it as he did with ancient Christian claims about growth.
Chlorophyll fluorescence characteristics and H2O2 contents of Chinese tallow tree are dependent on population origin, nutrients and salinity
Authors: He Mengyue , Ge Lihong , Hui Xue , Li Wenrao , Ding Jianqing , Siemann Evan
Published: May 2024

Plants from invasive populations often have higher growth rates than conspecifics from native populations due to better environmental adaptability. However, the roles of improved chlorophyll fluorescence or antioxidant defenses in helping them to grow better under adverse situations are insufficient, even though this is a key physiological question for elucidating mechanisms of plant invasion. Here, we conducted experiments with eight native (China) and eight introduced (USA) populations of Chinese tallow tree (Triadica sebifera). We tested how salinity, nutrients (overall amount or N:P in two separate experiments) and their interaction affected T. sebifera aboveground biomass, leaf area, chlorophyll fluorescence and antioxidant defenses. Plants from introduced populations were larger than those from native populations, but salinity and nutrient shortage (low nutrients or high N:P) reduced this advantage, possibly reflecting differences in chlorophyll fluorescence based on their higher PSII maximum photochemical efficiency (Fv/Fm) and PSI maximum photo-oxidizable P700 in higher nutrient conditions. Native population plants had lower Fv/Fm with saline. Except in high nutrients/N:P with salinity, introduced population plants had lower electron transfer rate and photochemical quantum yield. There were no differences in antioxidant defenses between introduced and native populations except accumulation of hydrogen peroxide (H2O2), which was lower for introduced populations. Low nutrients and higher N:P or salinity increased total antioxidant capacity and H2O2. Our results indicate that nutrients and salinity induce differences in H2O2 contents and chlorophyll fluorescence characteristics between introduced and native populations of an invasive plant, illuminating adaptive mechanisms using photosynthetic physiological descriptors in order to predict invasions.