bluuebunny/crossref_metadata_2025_split huggingface dataset:
Shadow removal method of soil surface image based on GAN used for estimation of farmland soil moisture content
Authors: Meng Chao , Yang Wei , Wang Dong , Hao Ziyuan , Li Minzan 
Published: April 2023

Abstract
It is important to obtain soil moisture content (SMC) in farmland, and soil surface images can be used to rapidly estimate SMC. The objective of this study was to propose a shadow removal algorithm to eliminate the effect of shadows in soil surface images, so as to improve the accuracy of SMC estimation. The structure of the proposed soil shadow generative adversarial networks (SS GAN) was a circulating network, which is an unsupervised method and does not require paired shadow image sets for network training. Four loss functions were defined for the network to effectively remove shadows and ensure texture detail and color consistency. This method is compared with traditional methods, supervised and unsupervised deep learning techniques by comparative experiments. Evaluations were made from visual and quantitative comparisons. Visually, the best shadow removal method was proved, it almost has no shadow boundaries or shadow areas visible for samples. The peak signal to noise ratio (PSNR) and structural similarity (SSIM) were used to quantitatively compare shadow removal images with real non-shadow images. The PSNR and SSIM of SS GAN were 28.46 and 0.95 respectively, which are superior to other methods, indicating that the images processed by SS GAN were closer to the real non-shadow images. Field experiments results shown that SS GAN has excellent shadow removal performance in the self-developed vehicle-mounted detection system. In order to verify the improvement effect of shadow removal image on SMC estimation accuracy, further field test was conducted to estimate SMC. Compared with SMC estimation results before and after shadow removal, R
2 increased from 0.69 to 0.76, and root mean square error decreased from 1.39 to 0.94%. The results show that the proposed method can effectively remove the shadow of soil image and improve the accuracy of SMC estimation in farmland.
Perspective on small mass and force measurements
Authors: Arumugam Kumar , Shaw Gordon 
Published: April 2023

Abstract
The measurement of small mass and force is as pertinent now as it was in 1923 when E M Eden and C G Eden published their article titled ‘Two machines for rapidly weighing loads of a few milligrams’ in the inaugural edition of the Measurement Science and Technology journal (formerly known as the Journal of Scientific Instruments). In the century since, measurement techniques have evolved and become more accurate with current uncertainties of nanograms at the milligram level measurements. This article reviews these advancements as well as the applications for small mass and force measurement that have evolved over the last century.
Enhancing some separability criteria in many-body quantum systems
Authors: Tang Liang , Wu Fan 
Published: April 2023

Abstract
Quantum measurements based on mutually unbiased bases, mutually unbiased measurements and general symmetric informationally complete positive operator valued measurements, which are commonly used in quantum information and quantum computation. In this paper, by a broad class of informationally complete symmetric measurements and correlation matrices, some separability criteria are proposed for different quantum systems that are more robust and comprehensive than the corresponding criteria previously introduced L M Lai, T Li, S M Fei, and Z X Wang, (2018 Quantum Inf. Process., 17, 314); J W Shang, A Asadian, and H J Zhu, (2018 Phys. Rev. A
98, 022309). Furthermore, we extend the separability criteria of tripartite quantum systems to many-body systems. The proposed entanglement criteria may further enrich the relationship between quantum entanglement and measurement.
Impact of QCD uncertainties on antiproton spectra from dark-matter annihilation
Authors: Jueid Adil , Kip Jochem , Ruiz de Austri Roberto , Skands Peter 
Published: April 2023

Abstract
Dark-matter particles that annihilate or decay can undergo complex sequences of processes, including strong and electromagnetic radiation, hadronisation, and hadron decays, before particles that are stable on astrophysical time scales are produced. Antiprotons produced in this way may leave footprints in experiments such as AMS–02. Several groups have reported an excess of events in the antiproton flux in the rigidity range of 10–20 GV. However, the theoretical modeling of baryon production is not straightforward and relies in part on phenomenological models in Monte Carlo event generators.
In this work, we assess the impact of QCD uncertainties on the spectra of antiprotons from dark-matter annihilation. As a proof-of-principle, we show that for a two-parameter model that depends only on the thermally-averaged annihilation cross section (〈σv〉) and the dark-matter mass (Mχ
), QCD uncertainties can affect the best-fit mass
by up to ∼ 14% (with large uncertainties for large DM masses), depending on the choice of Mχ
and the annihilation channel (bb̅ or W
+
W
-),
and 〈σv〉 by up to ∼ 10%. For comparison, changes to the underlying diffusion parameters are found to be within 1%–5%, and the results are also quite resilient to the choice of cosmic-ray propagation model. These findings indicate that QCD uncertainties need to be included in future DM analyses. To facilitate full-fledged analyses, we provide the spectra in tabulated form including QCD uncertainties and code snippets to perform mass interpolations and quick DM fits. The code can be found in this GitHub [1] repository.
Hundred watt level and high energy compact hybrid fiber femtosecond laser with good beam quality
Authors: Li Qianglong , Li Feng , Zhao Wei , Wang Yishan , Wen Wenlong , Yang Yang , Zhao Hualong , Cao Xue , Si Jinhai 
Published: April 2023

Abstract
A hundred watt level compact femtosecond laser system comprised of a high gain, low nonlinearity silicate glass fiber amplifier and a highly efficient Yb:YAG single-crystal fiber amplifier is demonstrated. By reducing the harmful thermal lens effect of amplifiers and optical elements, and precisely tuning dispersion of the stretcher, 110 W, 495 fs laser output at 1 MHz repetition rate and 250 μJ, 494 fs laser output at 200 kHz repetition rate are obtained. An optimized beam-quality factor (M
2) of better than 1.3 is obtained by filtering the beam with a small-aperture diaphragm. To our best knowledge, this is the first demonstration of such a hybrid femtosecond laser over 100 W and 100 μJ with good beam quality.
Identifying Host Galaxies of Extragalactic Radio Emission Structures using Machine Learning
Authors: Lou Kangzhi , Lake Sean E. , Tsai Chao-Wei 
Published: April 2023

Abstract
This paper presents an automatic multi-band source cross-identification method based on deep learning to identify the hosts of extragalactic radio emission structures. The aim is to satisfy the increased demand for automatic radio source identification and analysis of large-scale survey data from next-generation radio facilities such as the Square Kilometre Array and the Next Generation Very Large Array. We demonstrate a 97% overall accuracy in distinguishing quasi-stellar objects, galaxies and stars using their optical morphologies plus their corresponding mid-infrared information by training and testing a convolutional neural network on Pan-STARRS imaging and WISE photometry. Compared with an expert-evaluated sample, we show that our approach has 95% accuracy at identifying the hosts of extended radio components. We also find that improving radio core localization, for instance by locating its geodesic center, could further increase the accuracy of locating the hosts of systems with a complex radio structure, such as C-shaped radio galaxies. The framework developed in this work can be used for analyzing data from future large-scale radio surveys.
3D-printed hierarchical arrangements of actuators mimicking biological muscular architectures
Authors: De Pascali Corrado , Palagi Stefano , Mazzolai Barbara 
Published: April 2023

Abstract
Being able to imitate the sophisticated muscular architectures that characterize the animal kingdom in biomimetic machines would allow them to perform articulated movements with the same naturalness. In soft robotics, multiple actuation technologies have been developed to mimic the contraction of a single natural muscle, but a few of them can be implemented in complex architectures capable of diversifying deformations and forces. In this work, we present three different biomimetic muscle architectures, i.e. fusiform, parallel, and bipennate, which are based on hierarchical arrangements of multiple pneumatic actuators. These biomimetic architectures are monolithic structures composed of thirty-six pneumatic actuators each, directly 3D printed through low-cost printers and commercial materials without any assembly phase. The considerable number of actuators involved enabled the adoption and consequent comparison of two regulation strategies: one based on input modulation, commonly adopted in pneumatic systems, and one based on fiber recruitment, mimicking the regulation behavior of natural muscles. The straightforward realization through additive manufacturing processes of muscle architectures regulated by fiber recruitment strategies facilitates the development of articulated muscular systems for biomimetics machines increasingly similar to the natural ones.
Generalized polarization measurement and its connection with information energy
Authors: Canturk B , Gedik Z 
Published: April 2023

Abstract
We generalize the polarization measurement to the projective measurements of mutually unbiased bases (MUBs). Based on this result, we reveal a direct connection between polarization measurement and information energy function. We also express the polarization measurement by means of symmetric informationally complete positive operator-valued measures (SIC-POVMs). We present an argument suggesting that polarization measurement by means of SIC-POVMs requires fewer resources than the projective measurements of MUBs.
Infection risk and management strategies for patients with cirrhosis taking proton pump inhibitors
Authors: Zerr Beth , Vazquez Alejandro , Erstad Brian L 
Published: April 2023

Abstract

Purpose
The purpose of this review is to discuss infectious disease–related adverse effects associated with long-term proton pump inhibitor (PPI) therapy in patients with cirrhosis and to provide recommendations for appropriate use and choice of PPI when such therapy is indicated.

Summary
Long-term PPI therapy in patients with cirrhosis increases the risk of infections, with infections in turn increasing the risk of mortality in this patient population. Expert recommendations include restricting long-term PPI use in cirrhosis to patients with appropriate gastrointestinal indications, using a PPI for the shortest possible duration and at the lowest possible dose, and avoiding PPIs with unfavorable pharmacogenetic properties.

Conclusion
Long-term PPI use in patients with cirrhosis has been associated with increased infections. The risk of adverse effects in observational studies, including decompensation, severe infection (especially spontaneous bacterial peritonitis), and increased mortality, appears to increase as the dose and duration of PPI increase.
Multi-modality attribute learning-based method for drug–protein interaction prediction based on deep neural network
Authors: Dong Weihe , Yang Qiang , Wang Jian , Xu Long , Li Xiaokun , Luo Gongning , Gao Xin 
Published: April 2023

AbstractIdentification of active candidate compounds for target proteins, also called drug–protein interaction (DPI) prediction, is an essential but time-consuming and expensive step, which leads to fostering the development of drug discovery. In recent years, deep network-based learning methods were frequently proposed in DPIs due to their powerful capability of feature representation. However, the performance of existing DPI methods is still limited by insufficiently labeled pharmacological data and neglected intermolecular information. Therefore, overcoming these difficulties to perfect the performance of DPIs is an urgent challenge for researchers. In this article, we designed an innovative ’multi-modality attributes’ learning-based framework for DPIs with molecular transformer and graph convolutional networks, termed, multi-modality attributes (MMA)-DPI. Specifically, intermolecular sub-structural information and chemical semantic representations were extracted through an augmented transformer module from biomedical data. A tri-layer graph convolutional neural network module was applied to associate the neighbor topology information and learn the condensed dimensional features by aggregating a heterogeneous network that contains multiple biological representations of drugs, proteins, diseases and side effects. Then, the learned representations were taken as the input of a fully connected neural network module to further integrate them in molecular and topological space. Finally, the attribute representations were fused with adaptive learning weights to calculate the interaction score for the DPIs tasks. MMA-DPI was evaluated in different experimental conditions and the results demonstrate that the proposed method achieved higher performance than existing state-of-the-art frameworks.
Glycyrrhizin ameliorates impaired glucose metabolism and ovarian dysfunction in a polycystic ovary syndrome mouse model
Authors: Yang Jun-Pu , Ullah Amin , Su Ya-Nan , Otoo Antonia , Adu-Gyamfi Enoch Appiah , Feng Qian , Wang Ying-Xiong , Wang Mei-Jiao , Ding Yu-Bin 
Published: April 2023

Abstract
The aim of this study was to determine the impact of glycyrrhizin, an inhibitor of high mobility group box 1, on glucose metabolic disorders and ovarian dysfunction in mice with polycystic ovary syndrome. We generated a polycystic ovary syndrome mouse model by using dehydroepiandrosterone plus high-fat diet. Glycyrrhizin (100 mg/kg) was intraperitoneally injected into the polycystic ovary syndrome mice and the effects on body weight, glucose tolerance, insulin sensitivity, estrous cycle, hormone profiles, ovarian pathology, glucolipid metabolism, and some molecular mechanisms were investigated. Increased number of cystic follicles, hormonal disorders, impaired glucose tolerance, and decreased insulin sensitivity in the polycystic ovary syndrome mice were reverted by glycyrrhizin. The increased high mobility group box 1 levels in the serum and ovarian tissues of the polycystic ovary syndrome mice were also reduced by glycyrrhizin. Furthermore, increased expressions of toll-like receptor 9, myeloid differentiation factor 88, and nuclear factor kappa B as well as reduced expressions of insulin receptor, phosphorylated protein kinase B, and glucose transporter type 4 were restored by glycyrrhizin in the polycystic ovary syndrome mice. Glycyrrhizin could suppress the polycystic ovary syndrome-induced upregulation of high mobility group box 1, several inflammatory marker genes, and the toll-like receptor 9/myeloid differentiation factor 88/nuclear factor kappa B pathways, while inhibiting the insulin receptor/phosphorylated protein kinase B/glucose transporter type 4 pathways. Hence, glycyrrhizin is a promising therapeutic agent against polycystic ovary syndrome.
Sin as Intellectual Evil: Refusal of Insight in the Contemporary Debate on the Ends of Marriage
Authors: Hogan Margaret Monahan 
Published: April 2023

Abstract
This paper focuses on the possibility of sin as intellectual evil as operative in the contemporaneous culture in the debate over the essential nature of marriage and the accomplishment of the ends of marriage. It presents an account of theology as a science and the application of this understanding and its canons of operation to the issues presented in two recent documents—the Statement of the Wijngaards Institute for Catholic Research and the Affirmation of the Church’s Teaching on the Gift of Sexuality, each of which addresses the encyclical Humanae vitae on the occasion of its 50th anniversary. The paper concludes with an examination of the essential nature of marriage to guide the fulfillment of its ends now described as intrinsic/essential and intrinsic/contingent.
Long-term study into the development of a plenter structure in a forest comprising a mix of European and north American species
Authors: Cameron Andrew , Alexander Ruth 
Published: April 2023

Abstract
Irregular or plenter forestry evolved in Central Europe around a small number of shade-tolerating species; however, increasing interest in developing more climatically resilient, diverse forest structures has seen a greater range of species being studied. A critical question is whether stands comprising a wide geographic mix of species can form irregular structures in the long term. Using data from a unique experimental site established in 1953 at Faskally Forest, North Scotland, temporal changes in structure, density, growth and species diversity were studied in a stand comprising a mix of European and North American species undergoing the latter stages of transformation. A 1-ha permanent sample plot was established in 1997 and data evaluated from five complete inventories carried out at six-yearly intervals (latest in 2021). Metrics describing the irregular structure – defined by negative exponential diameter distributions, q values, Lorenz curves, Gini coefficients and stand density indices – have stabilized over the last three inventories suggesting a relative balance has been achieved between recruitment and harvesting/mortality losses. Whilst shade tolerating species dominate regeneration and recruitment, species diversity has increased since the start of the study. Analyses of transition periods (average time required for all trees to progress from one diameter class into the next) and annual recruitment (average number of trees moving from each diameter class into the next higher class) highlight a growth advantage of shade tolerating species. The range of values defining the irregular stand at Faskally compare well with those from long-term plenter forests in Continental Europe highlighting the potential of forming irregular stand structures comprising geographically diverse species. The study also indicates that the silvicultural characteristics of species are more important than whether they are native or non-native. Stand characteristics reported here could aid managers of irregular/plenter forests by indicating values of such characteristics to guide the transformation of similar mixed-species stands.
Association of Night Shifts and Lifestyle Risks With Incident Dementia
Authors: Ren Jiao-Jiao , Zhang Pei-Dong , Li Zhi-Hao , Zhang Xi-Ru , Zhong Wen-Fang , Chen Pei-Liang , Huang Qing-Mei , Wang Xiao-Meng , Gao Ping-Ming , Mao Chen 
Published: April 2023

AbstractBackgroundLittle is known about the combined relationship between night shifts and lifestyle risks with incident dementia or their potential interactions. To evaluate the association of night shifts and lifestyle risks with incident dementia and further analyze their interactions.MethodsA total of 276 059 participants were included in this study from the UK Biobank cohort. Cox proportional hazards models were used to investigate the combined association of night shifts and lifestyle risks with incident dementia.ResultsParticipants with always night shifts and 3 or 4 unhealthy lifestyle factors had the highest risk of incident all-cause dementia (hazard ratio: 3.15, 95% confidence interval [CI]: 1.74–5.69). An additive interaction was found between night shifts and lifestyle risks for incident all-cause dementia (p &lt; .001), with a relative excess risk due to the interaction of 0.14 (95% CI: 0.11–0.45). The attributable proportions of the combined effect on the incidence of all-cause dementia were 22.6% (95% CI: 20.91%–26.75%) for night shift work, 65.0% (95% CI: 63.12%–69.80%) for unhealthy lifestyle factors, and 12.1% (95% CI: 8.67%–18.04%) for their interaction.ConclusionsBoth night shifts and lifestyle risks were associated with a higher risk of incident dementia. The combined impact was higher than the increase in the risks related to each single factor. Our results indicated that most incident dementia cases might be prevented by a healthy lifestyle, and the benefits would be greater among night shift workers. Further studies are needed to confirm our results and explore the underlying mechanisms.
Habitat openness and predator abundance determine predation risk of warningly colored longhorn beetles (Cerambycidae) in temperate forest
Authors: Goßmann Anika , Ambrožová Lucie , Cizek Lukas , Drag Lukas , Georgiev Kostadin , Neudam Liane , Perlík Michal , Seidel Dominik , Thorn Simon 
Published: April 2023

Abstract
Organisms have evolved different defense mechanisms, such as crypsis and mimicry, to avoid detection and recognition by predators. A prominent example is Batesian mimicry, where palatable species mimic unpalatable or toxic ones, such as Clytini (Coleoptera: Cerambycidae) that mimic wasps. However, scientific evidence for the effectiveness of Batesian mimicry in Cerambycids in natural habitats is scarce. We investigated predation of warningly and nonwarningly colored Cerambycids by birds in a temperate forest using beetle dummies. Dummies mimicking Tetropium castaneum, Leptura aethiops, Clytus arietis, and Leptura quadrifasciata were exposed on standing and laying deadwood and monitored predation events by birds over one season. The 20 surveyed plots differed in their structural complexity and canopy openness due to different postdisturbance logging strategies. A total of 88 predation events on warningly colored beetle dummies and 89 predation events on nonwarningly colored beetle dummies did not reveal the difference in predation risk by birds. However, predation risk increased with canopy openness, bird abundance, and exposure time, which peaked in July. This suggests that environmental factors have a higher importance in determining predation risk of warningly and nonwarningly colored Cerambycidae than the actual coloration of the beetles. Our study showed that canopy openness might be important in determining the predation risk of beetles by birds regardless of beetles’ warning coloration. Different forest management strategies that often modify canopy openness may thus alter predator–prey interactions.