bluuebunny/crossref_metadata_2025_split huggingface dataset:
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

Abstract
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

Abstract
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

Abstract
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

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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

Abstract
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

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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

Abstract
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

Abstract
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

Abstract
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.
Early Christianity as Evidence for Socially Superior Religion
Authors: Stowers Stanley 
Published: May 2024

Abstract
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

Abstract
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

Abstract
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.
Comparison of conventional diffusion-weighted imaging and intravoxel incoherent motion in differentiating between chromophobe renal cell carcinoma and renal oncocytoma: a preliminary study
Authors: Zhu Qingqiang , Sun Jun , Ye Jing , Zhu Wenrong , Chen Wenxin 
Published: May 2024

Abstract

Objective
Quantitative comparison of the diagnostic efficacy of conventional diffusion-weighted imaging (DWI) and intravoxel incoherent motion (IVIM) in differentiating between chromophobe renal cell carcinoma (ChRCC) from renal oncocytoma (RO).

Methods
A total of 48 patients with renal tumours who had undergone DWI and IVIM were divided into two groups—ChRCC (n = 28) and RO (n = 20) groups, and the apparent diffusion coefficient (ADC), true diffusivity (D), pseudo-diffusion coefficient (D*), perfusion fraction (f) and their diagnostic efficacy were compared between the two groups.

Results
The D* values were higher in the ChRCCs group compared to the RO groups (0.019 ± 0.003 mm2/s vs 0.008 ± 0.002 mm2/s, P &lt; .05). Moreover, the ADC, D and f values were higher in ROs compared to ChRCCs (0.61 ± 0.08 × 10−3 mm2/s vs 0.51 ± 0.06 × 10−3 mm2/s, 1.02 ± 0.15 × 10−3 mm2/s vs 0.86 ± 0.07 × 10−3 mm2/s, 0.41 ± 0.05 vs 0.28 ± 0.02, P &lt; .05). The areas of the ADC, D, D* and f values under the ROC curves in differentiating ChRCCs from ROs were 0.713, 0.839, 0.856 and 0.906, respectively. The cut-off values of ADC, D, D* and f were 0.54, 0.91, 0.013 and 0.31, respectively. The AUC, sensitivity, specificity and accuracy of the f values were 0.906, 89.3%, 80.0% and 89.6%, respectively. For pairwise comparisons of ROC curves and diagnostic efficacy, IVIM parameters, that is, D, D* and f offered better diagnostic accuracy than ADC in differentiating ChRCCs from ROs (P = .013, .016, and .008) with f having the highest diagnostic accuracy.

Conclusion
IVIM parameters presented better performance than ADC in differentiating ChRCCs from ROs.

Advances in knowledge
(1) D* values of ChRCCs were higher, while ADC, D and f values were lower than those of RO tumours. (2) f values had the highest diagnostic efficacy in differentiating ChRCC from RO. (3) IVIM parameters, that is, D, D* and f offered better diagnostic accuracy than ADC in differentiating ChRCC from RO (P=.013, .016, and .008).
The ketogenic diet does not improve cardiac function and blunts glucose oxidation in ischaemic heart failure
Authors: Ho Kim L , Karwi Qutuba G , Wang Faqi , Wagg Cory , Zhang Liyan , Panidarapu Sai , Chen Brandon , Pherwani Simran , Greenwell Amanda A , Oudit Gavin Y , Ussher John R , Lopaschuk Gary D 
Published: May 2024

Abstract

Aims
Cardiac energy metabolism is perturbed in ischaemic heart failure and is characterized by a shift from mitochondrial oxidative metabolism to glycolysis. Notably, the failing heart relies more on ketones for energy than a healthy heart, an adaptive mechanism that improves the energy-starved status of the failing heart. However, whether this can be implemented therapeutically remains unknown. Therefore, our aim was to determine if increasing ketone delivery to the heart via a ketogenic diet can improve the outcomes of heart failure.

Methods and results
C57BL/6J male mice underwent either a sham surgery or permanent left anterior descending coronary artery ligation surgery to induce heart failure. After 2 weeks, mice were then treated with either a control diet or a ketogenic diet for 3 weeks. Transthoracic echocardiography was then carried out to assess in vivo cardiac function and structure. Finally, isolated working hearts from these mice were perfused with appropriately 3H or 14C labelled glucose (5 mM), palmitate (0.8 mM), and β-hydroxybutyrate (β-OHB) (0.6 mM) to assess mitochondrial oxidative metabolism and glycolysis. Mice with heart failure exhibited a 56% drop in ejection fraction, which was not improved with a ketogenic diet feeding. Interestingly, mice fed a ketogenic diet had marked decreases in cardiac glucose oxidation rates. Despite increasing blood ketone levels, cardiac ketone oxidation rates did not increase, probably due to a decreased expression of key ketone oxidation enzymes. Furthermore, in mice on the ketogenic diet, no increase in overall cardiac energy production was observed, and instead, there was a shift to an increased reliance on fatty acid oxidation as a source of cardiac energy production. This resulted in a decrease in cardiac efficiency in heart failure mice fed a ketogenic diet.

Conclusion
We conclude that the ketogenic diet does not improve heart function in failing hearts, due to ketogenic diet-induced excessive fatty acid oxidation in the ischaemic heart and a decrease in insulin-stimulated glucose oxidation.
Spontaneous and double-strand break repair-associated quasipalindrome and frameshift mutagenesis in budding yeast: role of mismatch repair
Authors: Sugawara Neal , Towne Mason J , Lovett Susan T , Haber James E 
Published: May 2024

Abstract
Although gene conversion (GC) in Saccharomyces cerevisiae is the most error-free way to repair double-strand breaks (DSBs), the mutation rate during homologous recombination is 1,000 times greater than during replication. Many mutations involve dissociating a partially copied strand from its repair template and re-aligning with the same or another template, leading to −1 frameshifts in homonucleotide runs, quasipalindrome (QP)-associated mutations and microhomology-mediated interchromosomal template switches. We studied GC induced by HO endonuclease cleavage at MATα, repaired by an HMR::KI-URA3 donor. We inserted into HMR::KI-URA3 an 18-bp inverted repeat where one arm had a 4-bp insertion. Most GCs yield MAT::KI-ura3::QP + 4 (Ura−) outcomes, but template-switching produces Ura+ colonies, losing the 4-bp insertion. If the QP arm without the insertion is first encountered by repair DNA polymerase and is then (mis)used as a template, the palindrome is perfected. When the QP + 4 arm is encountered first, Ura+ derivatives only occur after second-end capture and second-strand synthesis. QP + 4 mutations are suppressed by mismatch repair (MMR) proteins Msh2, Msh3, and Mlh1, but not Msh6. Deleting Rdh54 significantly reduces QP mutations only when events creating Ura+ occur in the context of a D-loop but not during second-strand synthesis. A similar bias is found with a proofreading-defective DNA polymerase mutation (poI3-01). DSB-induced mutations differed in several genetic requirements from spontaneous events. We also created a + 1 frameshift in the donor, expanding a run of 4 Cs to 5 Cs. Again, Ura+ recombinants markedly increased by disabling MMR, suggesting that MMR acts during GC but favors the unbroken, template strand.