bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mean dimension of Bernstein spaces and universal real flows
Authors: Jin Lei , Qiao Yixiao , Tu Siming 
Published: September 2022

Abstract
We study the action of translation on the spaces of uniformly bounded continuous functions on the real line which are uniformly band-limited in a compact interval. We prove that two intervals themselves will decide if two spaces are topologically conjugate, while the length of an interval tells the mean dimension of a space. We also investigate universal real flows. We construct a sequence of compact invariant subsets of a space consisting of uniformly bounded smooth one-Lipschitz functions on the real line, which have mean dimension equal to one, such that all real flows can be equivariantly embedded in the translation on their product space. Moreover, we show that the countable self-product of any among them does not satisfy such a universal property. This, on the one hand, presents a more reasonable choice of a universal real flow with a view towards mean dimension, and on the other hand, clarifies a seemingly plausible impression; meanwhile, it refines the previously known results in this direction. Our proof goes through an approach of harmonic analysis. Furthermore, both the universal space that we provide and an embedding mapping which we build for any real flow are explicit.
Dynamic study of pendulum systems through smartphone-based laboratory experiments
Authors: Ait Ben Ahmed A , Touache A , ElHakimi A , Chamat A 
Published: September 2022

Abstract
The dynamic study of pendulum systems is considered an indispensable subject for physics and mechanics students in colleges and high schools. In this paper, a detailed methodology is given concerning the use of smartphones in pedagogical practical work for studying the dynamics of pendulum systems. Whereas, three aspects have been discussed through three cases concerning the study of the oscillatory motion, trajectories, and the energy aspect. Besides, some recommendations were provided regarding the process of data acquisition and curve-fitting processing to mitigate measurement errors. Experimental results exhibit a good agreement with theoretical results regarding the period of motion, trajectories, and mechanical energy. This makes the smartphone highlights a real opportunity to be a useful instrument to perform an overall study of the pendulum systems, the thing that was impossible without the intervention of professional equipment.
Generation of 18F-FDG PET standard scan images from short scans using cycle-consistent generative adversarial network
Authors: Ghafari Ali , Sheikhzadeh Peyman , Seyyedi Negisa , Abbasi Mehrshad , Farzenefar Saeed , Yousefirizi Fereshteh , Ay Mohammad Reza , Rahmim Arman 
Published: September 2022

Abstract

Objective. To improve positron emission tomography (PET) image quality, we aim to generate images of quality comparable to standard scan duration images using short scan duration (1/8 and 1/16 standard scan duration) inputs and assess the generated standard scan duration images quantitative and qualitatively. Also, the effect of training dataset properties (i.e. body mass index (BMI)) on the performance of the model(s) will be explored. Approach. Whole-body PET scans of 42 patients (41 18F-FDG and one 68Ga-PSMA) scanned with standard radiotracer dosage were included in this study. One 18F-FDG patient data was set aside and the remaining 40 patients were split into four subsets of 10 patients with different mean patient BMI. Multiple copies of a developed cycle-GAN network were trained on each subset to predict standard scan images using 1/8 and 1/16 short duration scans. Also, the models’ performance was tested on a patient scanned with the 68Ga-PSMA radiotracer. Quantitative performance was tested using peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and normalized root mean squared error (NRMSE) metrics, and two nuclear medicine specialists analyzed images qualitatively. Main results. The developed cycle-GAN model improved the PSNR, SSIM, and NRMSE of the 1/8 and 1/16 short scan duration inputs both 18F-FDG and 68Ga-PSMA radiotracers. Although, quantitatively PSNR, SSIM, and NRMSE of the 1/16 scan duration level were improved more than 1/8 counterparts, however, the later were qualitatively more appealing. SUVmean and SUVmax of the generated images were also indicative of the improvements. The cycle-GAN model was much more capable in terms of image quality improvements and speed than the NLM denoising method. All results proved statistically significant using the paired-sample T-Test statistical test (p-value < 0.05). Significance. Our suggested approach based on cycle-GAN could improve image quality of the 1/8 and 1/16 short scan-duration inputs through noise reduction both quantitively (PSNR, SSIM, NRMSE, SUVmean, and SUVmax) and qualitatively (contrast, noise, and diagnostic capability) to the level comparable to the standard scan-duration counterparts. The cycle-GAN model(s) had a similar performance on the 68Ga-PSMA to the 18F-FDG images and could improve the images qualitatively and quantitatively but requires more extensive study. Overall, images predicted from 1/8 short scan-duration inputs had the upper hand compared with 1/16 short scan-duration inputs.
Iterative tomographic reconstruction with TV prior for low-dose CBCT dental imaging
Authors: Friot--Giroux Louise , Peyrin Françoise , Maxim Voichita 
Published: September 2022

Abstract

Objective. Cone-beam computed tomography is becoming more and more popular in applications such as 3D dental imaging. Iterative methods compared to the standard Feldkamp algorithm have shown improvements in image quality of reconstruction of low-dose acquired data despite their long computing time. An interesting aspect of iterative methods is their ability to include prior information such as sparsity-constraint. While a large panel of optimization algorithms along with their adaptation to tomographic problems are available, they are mainly studied on 2D parallel or fan-beam data. The issues raised by 3D CBCT and moreover by truncated projections are still poorly understood. Approach. We compare different carefully designed optimization schemes in the context of realistic 3D dental imaging. Besides some known algorithms, SIRT-TV and MLEM, we investigate the primal-dual hybrid gradient (PDHG) approach and a newly proposed MLEM-TV optimizer. The last one is alternating EM steps and TV-denoising, combination not yet investigated for CBCT. Experiments are performed on both simulated data from a 3D jaw phantom and data acquired with a dental clinical scanner. Main results. With some adaptations to the specificities of CBCT operators, PDHG and MLEM-TV algorithms provide the best reconstruction quality. These results were obtained by comparing the full-dose image with a low-dose image and an ultra low-dose image. Significance. The convergence speed of the original iterative methods is hampered by the conical geometry and significantly reduced compared to parallel geometries. We promote the pre-conditioned version of PDHG and we propose a pre-conditioned version of the MLEM-TV algorithm. To the best of our knowledge, this is the first time PDHG and convergent MLEM-TV algorithms are evaluated on experimental dental CBCT data, where constraints such as projection truncation and presence of metal have to be jointly overcome.
Polynomial T-depth quantum solvability of noisy binary linear problem: from quantum-sample preparation to main computation
Authors: Song Wooyeong , Lim Youngrong , Jeong Kabgyun , Lee Jinhyoung , Park Jung Jun , Kim M S , Bang Jeongho 
Published: September 2022

Abstract
The noisy binary linear problem (NBLP) is known as a computationally hard problem, and therefore, it offers primitives for post-quantum cryptography. An efficient quantum NBLP algorithm that exhibits a polynomial quantum sample and time complexities has recently been proposed. However, the algorithm requires a large number of samples to be loaded in a highly entangled state and it is unclear whether such a precondition on the quantum speedup can be obtained efficiently. Here, we present a complete analysis of the quantum solvability of the NBLP by considering the entire algorithm process, namely from the preparation of the quantum sample to the main computation. By assuming that the algorithm runs on ‘fault-tolerant’ quantum circuitry, we introduce a reasonable measure of the computational time cost. The measure is defined in terms of the overall number of T gate layers, referred to as T-depth complexity. We show that the cost of solving the NBLP can be polynomial in the problem size, at the expense of an exponentially increasing logical qubits.
Diabatic potential energy surfaces and semiclassical multi-state dynamics for fourteen coupled 3
A′ states of O3
Authors: Varga Zoltan , Shu Yinan , Ning Jiaxin , Truhlar Donald G 
Published: September 2022

Abstract
Dissociation and energy transfer in high-energy collisions of O2 play important roles in simulating thermal energy content and heat flux in flows around hypersonic vehicles. Furthermore, atomic oxygen reactions on the vehicle surface are an important contributor to heat shield erosion. Molecular dynamics modeling is needed to better understand the relevant rate processes. Because it is necessary to model the gas flows in high-temperature shock waves, electronically excited states of O2 and O can be populated, and molecular dynamics simulations should include collisions of electronically excited species and electronically nonadiabatic collisions. This requires potential energy surfaces and state couplings for many energetically accessible electronic states. Here we report a systematic strategy to calculate such surfaces and couplings. We have applied this method to the fourteen lowest-energy potential energy surfaces in the 3
A′ manifold of O3, and we report a neural-network fit to diabatic potential energy matrix (DPEM). We illustrate the use of the resulting DPEM by carrying out semiclassical dynamics calculations of cross sections for excitation of O2 in 3
A′ collisions with O at two collision energies; these dynamics calculations are carried out by the curvature-driven coherent switching with decay of mixing method.
Quantitative corrosion detection of reinforced concrete based on self-magnetic flux leakage and rust spot area
Authors: Chen Lin , Liu Xianlin , Lin Yunfei , Xia Junfeng , Zhao Siyu , Zhang Senhua 
Published: September 2022

Abstract
The internal rebar corrosion of reinforced concrete (RC) structures harm the bearing capacity and durability of structures. Existing methods can measure rebar corrosion but are unsuitable for RC structures. Given this, the self-magnetic flux leakage (SMFL) field of V-shaped rebar corrosion damage was analyzed according to the magnetic dipole model, and the parameter K was proposed to characterize the corrosion degree. Using the naive Bayes algorithm, the SMFL method and the rust spot area analysis method were correlated to propose a rebar corrosion detection method. A corrosion detection experiment was conducted on RC specimens. The results showed that the parameter K was linearly correlated with the maximum cross-sectional rust loss rate η. Using the parameter K to evaluate the rust degree, the accuracy of rebar rust classification was 70%. After introducing the rust spot area ratio S as a supplementary parameter, the accuracy of rebar rust classification increased by 12.5% to 82.5%. This indicates that the proposed method could quantitatively detect the corrosion of the rebars within the concrete.
Age and phenology control photosynthesis and leaf traits in the understory woody species,Rhamnus catharticaandPrunus serotina
Authors: Heskel Mary , Pengra Jean , Kruper Ally , Anderson Michael D , Dosch Jerald J , Goldstein Lianna , Hahn Shannon , Hoffman Sarah 
Published: September 2022

AbstractUnderstory plants are often inadequately represented or neglected within analyses of forest ecosystem productivity. Further, the potential impacts of the biological factors of age class and growth form on carbon cycling physiology, and how it may vary across the growing season and amongst species of different native/non-native status, have not been thoroughly considered. Our study examines photosynthesis and associated physical leaf traits in two understory woody species, Rhamnus cathartica, introduced and invasive in North America, and Prunus serotina, a common subcanopy species native to North America. We estimated leaf-level photosynthesis as measured through light and carbon dioxide response curves, dark-adapted chlorophyll fluorescence and leaf traits (leaf mass per area and stomatal density) for each combination of species and age class at plots in the understory of a temperate deciduous research forest in the US Upper Midwest at two time points during the growing season, late spring (late May) and mid-summer (mid-July). Carbon assimilation rates from light response curves (Asat, A400) and fluorescence capacity estimate Fv/Fm all increased between the two measurement points in both species and age class. Estimates of carbon reaction capacity (Vcmax and Jmax) exhibited a different directional response to seasonal development, declining in seedlings of both species and P. serotina trees (~8–37 % reduction in Vcmax, ~9–34 % reduction in Jmax), though increased in trees of R. cathartica (+24 % in Vcmax, +9 % in Jmax). Divergent responses in photosynthetic parameters amongst these factors may be explained by species differences in leaf mass per area and stomatal density, which together are likely influenced by both growth form, canopy position and ontogeny. Overall, we believe our findings suggest complex, varied influences on photosynthesis that indicate environmental and biological plasticity which may contribute to the historic and continued expansion of R. cathartica in the US Upper Midwest region.
BioGPT: generative pre-trained transformer for biomedical text generation and mining
Authors: Luo Renqian , Sun Liai , Xia Yingce , Qin Tao , Zhang Sheng , Poon Hoifung , Liu Tie-Yan 
Published: September 2022

AbstractPre-trained language models have attracted increasing attention in the biomedical domain, inspired by their great success in the general natural language domain. Among the two main branches of pre-trained language models in the general language domain, i.e. BERT (and its variants) and GPT (and its variants), the first one has been extensively studied in the biomedical domain, such as BioBERT and PubMedBERT. While they have achieved great success on a variety of discriminative downstream biomedical tasks, the lack of generation ability constrains their application scope. In this paper, we propose BioGPT, a domain-specific generative Transformer language model pre-trained on large-scale biomedical literature. We evaluate BioGPT on six biomedical natural language processing tasks and demonstrate that our model outperforms previous models on most tasks. Especially, we get 44.98%, 38.42% and 40.76% F1 score on BC5CDR, KD-DTI and DDI end-to-end relation extraction tasks, respectively, and 78.2% accuracy on PubMedQA, creating a new record. Our case study on text generation further demonstrates the advantage of BioGPT on biomedical literature to generate fluent descriptions for biomedical terms.
LION: an integrated R package for effective prediction of ncRNA–protein interaction
Authors: Han Siyu , Yang Xiao , Sun Hang , Yang Hu , Zhang Qi , Peng Cheng , Fang Wensi , Li Ying 
Published: September 2022

Abstract
Understanding ncRNA–protein interaction is of critical importance to unveil ncRNAs’ functions. Here, we propose an integrated package LION which comprises a new method for predicting ncRNA/lncRNA–protein interaction as well as a comprehensive strategy to meet the requirement of customisable prediction. Experimental results demonstrate that our method outperforms its competitors on multiple benchmark datasets. LION can also improve the performance of some widely used tools and build adaptable models for species- and tissue-specific prediction. We expect that LION will be a powerful and efficient tool for the prediction and analysis of ncRNA/lncRNA–protein interaction. The R Package LION is available on GitHub at https://github.com/HAN-Siyu/LION/.
Reduced hippocampal-cortical connectivity during memory suppression predicts the ability to forget unwanted memories
Authors: Yan Yuchi , Hulbert Justin C , Zhuang Kaixiang , Liu Wei , Wei Dongtao , Qiu Jiang , Anderson Michael C , Yang Wenjing 
Published: September 2022

AbstractThe ability to suppress unwelcome memories is important for productivity and well-being. Successful memory suppression is associated with hippocampal deactivations and a concomitant disruption of this region’s functionality. Much of the previous neuroimaging literature exploring such suppression-related hippocampal modulations has focused on the region’s negative coupling with the prefrontal cortex. Task-based changes in functional connectivity between the hippocampus and other brain regions still need further exploration. In the present study, we utilize psychophysiological interactions and seed connectome-based predictive modeling to investigate the relationship between the hippocampus and the rest of the brain as 134 participants attempted to suppress unwanted memories during the Think/No-Think task. The results show that during retrieval suppression, the right hippocampus exhibited decreased functional connectivity with visual cortical areas (lingual and cuneus gyrus), left nucleus accumbens and the brain-stem that predicted superior forgetting of unwanted memories on later memory tests. Validation tests verified that prediction performance was not an artifact of head motion or prediction method and that the negative features remained consistent across different brain parcellations. These findings suggest that systemic memory suppression involves more than the modulation of hippocampal activity—it alters functional connectivity patterns between the hippocampus and visual cortex, leading to successful forgetting.
Learning whom to cooperate with: neurocomputational mechanisms for choosing cooperative partners
Authors: Jin Tao , Zhang Shen , Lockwood Patricia , Vilares Iris , Wu Haiyan , Liu Chao , Ma Yina 
Published: September 2022

AbstractCooperation is fundamental for survival and a functioning society. With substantial individual variability in cooperativeness, we must learn whom to cooperate with, and often make these decisions on behalf of others. Understanding how people learn about the cooperativeness of others, and the neurocomputational mechanisms supporting this learning, is therefore essential. During functional magnetic resonance imaging scanning, participants completed a novel cooperation-partner-choice task where they learned to choose between cooperative and uncooperative partners through trial-and-error both for themselves and vicariously for another person. Interestingly, when choosing for themselves, participants made faster and more exploitative choices than when choosing for another person. Activity in the ventral striatum preferentially responded to prediction errors (PEs) during self-learning, whereas activity in the perigenual anterior cingulate cortex (ACC) signaled both personal and vicarious PEs. Multivariate pattern analyses showed distinct coding of personal and vicarious choice-making and outcome processing in the temporoparietal junction (TPJ), dorsal ACC, and striatum. Moreover, in right TPJ the activity pattern that differentiated self and other outcomes was associated with individual differences in exploitation tendency. We reveal neurocomputational mechanisms supporting cooperative learning and show that this learning is reflected in trial-by-trial univariate signals and multivariate patterns that can distinguish personal and vicarious choices.
The Perceived Convincingness Model: why and under what conditions processing fluency and emotions are valid indicators of a message’s perceived convincingness
Authors: Hoeken Hans , Fikkers Karin , Eerland Anita , Holleman Bregje , van Berkum Jos , Pander Maat Henk 
Published: September 2022

AbstractPersuasive messages aim to influence people’s behavior. Arguments in these messages typically refer to the positive consequences of the advocated behavior or the negative consequences of failing to do so. It has been claimed that people automatically generate a judgment about the message’s convincingness. We present the Perceived Convincingness Model (PCM) to explain how people generate this judgment based upon the fluency with which they process the message and the intensity of the resulting emotions. When these experiences are elicited by the processing of the message’s arguments, they can be crude, yet relevant indicators of the extent to which the arguments meet the normative criteria of acceptability, relevance, and sufficiency. Thus, under some conditions, trusting one’s feelings may be a rational strategy when deciding to heed an advice or not.
17. EFFECT OF BILE ACID AND PANCREATIC JUICE IN REFLUX ESOPHAGITIS AFTER TOTAL GASTRECTOMY IN RAT MODEL
Authors: Hashimoto Naoki 
Published: September 2022

Abstract
Esophagitis after total gastrectomy has been associated with the reflux of duodenal content into the esophagus.
This study is to determine which fraction of the duodenum content reflux, pancreatic juice or bile acids contributes to the development of reflux esophagitis.
8 week Wistar Rats were used.
1. Reflux of Pancreatic juice and Bile(TG):End-to-end esophago-duodenostomy with total gastrectomy (n = 8)
2. Reflux of Pancreatic Juice (TG + P):End-to-end esophago-duodenostomy with total gastrectomy. Then, a bypass operation of the upper bile duct was made 25 cm below the esophagoduodenostomy anastomosis. Choledocho-jejunostomy was performed. (n = 6)
3. Reflux of Bile (TG + B) (n = 4):Roux-en-Y esophagojejunostomy with total gastrectomy. The bile duct was then divided and reimplanted into the proximal portion of the Roux limb, preceding the esophagojejunostomy to produce biliary reflux.
Three weeks after, all rats were euthanized and the esophagus was evaluated histologically.
1. Macroscopy: In TG rats, the esophageal wall was thickened and covered with whitish nodular patches. The gross appearance of the esophagus from TG + P and TG + B group showed only scattered erosions. The ulcer score in TG + P and TG + B were significantly lowered compared to TG. 2. Microscopy: TG group developed large and long longitudinal ulcers. The inflammatory cell infiltration scores and hyperplasia scores were significantly decreased in the TG + B and TG + P group compared to TG group.
The reflux of pancreatic juice alone and bile acid alone are not significant development of reflux esophagitis. Reflux of combined of bile acid and pancreatic juice to esophagus caused sever reflux esophagitis.