bluuebunny/crossref_metadata_2025 huggingface dataset:
Background identification in cryogenic calorimeters through $$\alpha -\alpha $$ delayed coincidences
Authors: Azzolini O. , Beeman J. W. , Bellini F. , Beretta M. , Biassoni M. , Brofferio C. , Bucci C. , Capelli S. , Cardani L. , Carniti P. , Casali N. , Chiesa D. , Clemenza M. , Cremonesi O. , Cruciani A. , Dafinei I. , D’Addabbo A. , Di Domizio S. , Ferroni F. , Gironi L. , Giuliani A. , Gorla P. , Gotti C. , Keppel G. , Martinez M. , Nagorny S. , Nastasi M. , Nisi S. , Nones C. , Orlandi D. , Pagnanini L. , Pallavicini M. , Pattavina L. , Pavan M. , Pessina G. , Pettinacci V. , Pirro S. , Pozzi S. , Previtali E. , Puiu A. , Rusconi C. , Schäffner K. , Tomei C. , Vignati M. , Zolotarova A.
Published: August 2021

Localization and modeling of radioactive contaminations is a challenge that ultra-low background experiments are constantly facing. These are fundamental steps both to extract scientific results and to further reduce the background of the detectors. Here we present an innovative technique based on the analysis of $$\alpha -\alpha $$

α
-
α

delayed coincidences in $${}^{232}$$

232

Th and $${}^{238}$$

238

U decay chains, developed to investigate the contaminations of the ZnSe crystals in the CUPID-0 experiment. This method allows to disentangle surface and bulk contaminations of the detectors relying on the different probability to tag delayed coincidences as function of the $$\alpha $$
α
decay position.
Theoretical analysis of pT spectra of light-flavor hadrons in p + p collisions at s = 7 TeV under differential and single freeze-out scenarios
Authors: Kumar Pramod , Khandai P. K. , Saraswat Kapil , Singh V.
Published: August 2021

We present the published data of ALICE at mid-rapidity region ([Formula: see text]) to study the [Formula: see text] spectra of light-flavor hadrons in different charged-particle multiplicities ([Formula: see text]) for [Formula: see text] collisions at [Formula: see text] TeV. We parametrize the [Formula: see text] spectra of different hadrons such as pion ([Formula: see text]), kaon ([Formula: see text]), [Formula: see text], [Formula: see text] ([Formula: see text]), [Formula: see text], proton ([Formula: see text]), lambda ([Formula: see text]), cascade ([Formula: see text]) and omega ([Formula: see text]) using Tsallis distribution. We perform this analysis by considering both differential and single freeze-out scenarios. In the differential freeze-out scenario, both the Tsallis parameters [Formula: see text] and [Formula: see text] increase with charged multiplicities for most of the particles. This implies that the multipartonic interactions increase the multiplicities in [Formula: see text] collisions and it brings the system towards thermal equilibrium. Here we observe that both [Formula: see text] and [Formula: see text] have different trends with different masses of particles. The parameters [Formula: see text] and [Formula: see text] are higher for massive particles (except for multistrange baryons) in comparison to lighter ones, which supports the differential freeze-out scenario and suggests that massive particles freeze-out earlier from the system. In the case of single freeze-out scenario, the value of parameter [Formula: see text] has a little variation with multiplicity and the parameter [Formula: see text] increases with multiplicity. This implies that the degree of thermalization remains similar for the events of different multiplicity classes.
Systematic investigation of magnetic, optical and transport properties of RTX (R = Rare earth, T = 3d/4d and X = p-block elements) for thermoelectric applications
Authors: Jamil A. , Muhammad Nawaz , Murtaza G. , Asif Muhammad
Published: August 2021

The half-Heusler compounds have been extensively studied because of their exceptional transport properties. We have explored rare earth (RE)-based half-Heusler bismuthides compounds, [Formula: see text]PdBi ([Formula: see text][Formula: see text]=[Formula: see text]Gd, Dy and Ho) with the cubic crystal structure. Structural, magnetic, optical and transport properties are investigated using PBE-GG approximations by solving exchange-correlation potential. Electronic properties including spin-polarized band structure and density of states verified that semimetals with half-filled [Formula: see text]-orbitals across the Fermi-level are useful for thermoelectric applications. Magnetic properties reveal that values of the total spin magnetic moment are in close agreement with the experimental data. Optical properties with spin–orbit coupling (SOC) have a higher absorption coefficient and comparatively lesser energy loss which shows that studied materials are appropriate for optoelectronic devices. Moreover, transport properties including electrical and thermal conductivities, Seebeck coefficient, specific heat, power factor and figure of merit have been discussed in detail. The consistency of our results with the literature reveals that SOC plays a vital role in the transport properties of the materials.
Analytical simulation of nanoparticle-embedded blood flow control with magnetic field influence through spectra homotopy analysis method
Authors: Ige Ebenezer Olubunmi , Oyelami Funmilayo Helen , Adedipe Emmanuel Segun , Tlili Iskander , Khan M. Ijaz , Khan Sami Ullah , Malik M. Y. , Xia Wei-Feng
Published: August 2021

Nanoparticles-based infusion strategies are presently being employed for a range of clinical interventions either for in vivo or in vitro applications while imposition of magnetic field is also identified as an important technique for fluid manipulation during nanoparticles-based propulsion. The impact of magnetic field to control of the transport of nanoparticles-based blood flow is demonstrated numerically over an elaborate variant of transport mechanisms. Mathematical formulations were undertaken and stability analysis of the mathematical problem was a scrutinized by generation of eigen values using the Lyapunov scheme. The numerical solution based on Chebysehev pseudo-spectra and spectra homotopy analysis method (SHAM) was implemented to handle the combination on nonlinear ordinary differential equations derived from the transport models. We observed that far-field of the stagnation point, nanoparticles specie dispersion increased with higher thermal diffusivity, while the decrease in concentration profile around the vicinity of stagnation point depicts clustering of nanoparticles-embedded blood flow. The observations revealed that higher magnitude of thermophoretic parameters constitute significantly to increase in momentum as well as energy fields during transport of nanoparticles-containing blood flow under magnetic field influence. These findings showed the potentials of magnetic-field for control of suspended particles in transport medium which could be harnessed to manipulate transport of nanoparticles-containing fluids in microfluidic platforms with intricate configurations.
Uncovering the impact of delay phenomenon on random walks in a family of weighted m-triangulation networks
Authors: Guo Junhao , Wu Zikai
Published: August 2021

Uncovering the impact of special phenomena on dynamical processes in more distinct weighted network models is still needed. In this paper, we investigate the impact of delay phenomenon on random walk by introducing delayed random walk into a family of weighted m-triangulation networks. Specifically, we introduce delayed random walk into the networks. Then one and three traps are deployed, respectively, on the networks in two rounds of investigation. In both rounds of investigation, average trapping time (ATT) is applied to measure trapping efficiency and derived analytically by harnessing iteration rule of the networks. The analytical solutions of ATT obtained in both investigations show that ATT increases sub-linearity with the size of the network no matter what value the parameter [Formula: see text] manipulating delayed random walk takes. But [Formula: see text] can quantitatively change both its leading scaling and prefactor. So, introduction of delay phenomenon can control trapping efficiency quantitatively. Besides, parameters [Formula: see text] and [Formula: see text] governing networks’ evolution quantitatively impact both the prefactor and leading scaling of ATT simultaneously. In summary, this work may provide incremental insight into understanding the impact of observed phenomena on special trapping process and general random walks in complex systems.
Solitary wave solutions of (2+1)-dimensional Maccari system
Authors: Akram Ghazala , Sajid Naila
Published: August 2021

In this article, three mathematical techniques have been operationalized to discover novel solitary wave solutions of (2+1)-dimensional Maccari system, which also known as soliton equation. This model equation is usually of applicative relevance in hydrodynamics, nonlinear optics and plasma physics. The [Formula: see text] function, the hyperbolic function and the [Formula: see text]-expansion techniques are used to obtain the novel exact solutions of the (2+1)-dimensional Maccari system (arising in nonlinear optics and in plasma physics). Many novel solutions such as periodic wave solutions by [Formula: see text] function method, singular, combined-singular and periodic solutions by hyperbolic function method, hyperbolic, rational and trigonometric solutions by [Formula: see text]-expansion method are obtained. The exact solutions are shown through 3D graphics which present the movement of the obtained solutions.
Generalizing dendriform algebras: Dyckm-algebras, Rotam-algebras, and Rota–Baxter operators
Authors: Martinez Wilson Arley , Reyes Enrique G. , Ronco Maria
Published: August 2021

We review the notion of a [Formula: see text], an algebraic structure introduced recently by López, Préville-Ratelle and Ronco during their work on the splitting of associativity via [Formula: see text]-Dyck paths, and we also introduce Rota[Formula: see text]-algebras: both structures can be considered as generalizations of dendriform structures. We obtain examples of Dyck[Formula: see text]-algebras in terms of planar rooted binary trees equipped with a particular type of Rota–Baxter operator, and we present examples of Rotam-algebras using left averaging morphisms. As an application, we observe that the structures presented here allow us to introduce quite naturally a “non-associative version” of the Kadomtsev–Petviashvili hierarchy.
Quasi-stationary probability distribution for the SIR epidemic model
Authors: Ouicher Fahima , Kernane Tewfik
Published: August 2021

In this paper, we propose two new approximations to the joint quasi-stationary distribution (QSD) of the number susceptible and infected individuals in the Susceptible-Infected-Recovered (SIR) stochastic epidemic model and we derive the marginal QSD of the infected individuals. These two approximations depend on the basic reproduction number [Formula: see text] and give a positive probability of the QSD to all the transient states. Numerical comparisons are presented to check the accuracy of these approximations.
A federated interpretable scorecard and its application in credit scoring
Authors: Zheng Fanglan , Erihe  , Li Kun , Tian Jiang , Xiang Xiaojia
Published: August 2021

In this paper, we propose a vertical federated learning (VFL) structure for logistic regression with bounded constraint for the traditional scorecard, namely FL-LRBC. Under the premise of data privacy protection, FL-LRBC enables multiple agencies to jointly obtain an optimized scorecard model in a single training session. It leads to the formation of scorecard model with positive coefficients to guarantee its desirable characteristics (e.g., interpretability and robustness), while the time-consuming parameter-tuning process can be avoided. Moreover, model performance in terms of both AUC and the Kolmogorov–Smirnov (KS) statistics is significantly improved by FL-LRBC, due to the feature enrichment in our algorithm architecture. Currently, FL-LRBC has already been applied to credit business in a China nation-wide financial holdings group.
Spatial variation in provenance signal: identifying complex sand sourcing within a Carboniferous basin using multiproxy provenance analysis
Authors: Anders B. , Tyrrell S. , Chew D. , Mark C. , O'Sullivan G. , Murray J. , Graham J.R. , Badenszki E.
Published: August 2021

Multiple factors (e.g. source rock composition, climate, nature/scale of sedimentary system) influence the volume and composition of sediment delivered to basins. Fluctuations in these parameters produce cryptic source signals which can vary within the same sedimentary system. Bespoke multi-proxy provenance approaches, targeted at minerals of variable stability, allow for an assessment of natural biasing (recycling) and intra-basinal spatial variations.

Provenance of fluvial/deltaic sandstones (Mullaghmore Sandstone Formation) in the NW Carboniferous Basin, Ireland, has been constrained using zircon and apatite U–Pb geochronology, trace elements in apatite and Pb-in-K-feldspar analysis. Zircon U–Pb grain populations are consistent with feldspar data, suggesting Proterozoic basement highs offshore Ireland and Scotland were the main contributor with minor supply from Archean–Paleoproterozoic rocks of Greenland/NW Scotland and Caledonian-aged rocks. However, apatite data show a much larger proportion of Caledonian-aged grains of metamorphic origin, suggesting significant sediment was recycled from Neopropterozoic metasedimentary rocks. The spatial variation in provenance indicates that, at onset of clastic input, sediment was being routed to the basin through a complex drainage system, comprising several discrete hinterland catchments, rather than supply from a single, large interconnected sedimentary system. Such complexities can only be identified with the careful application of a bespoke multi-proxy provenance approach.

Supplementary material:
Tables 1-5 and individual Pb-in-K feldspar plots are available at
https://doi.org/10.6084/m9.figshare.c.5536691
Machine Learning Empowered IoT for Intelligent Vehicle Location in Smart Cities
Authors: Wan Liangtian , Zhang Mingyue , Sun Lu , Wang Xianpeng
Published: August 2021

Intelligent Transportation System (ITS)
can boost the development of smart cities, and artificial intelligence and edge computing are key technologies that support the implementation of ITS. Vehicle localization is critical for ITS since the safety driving and location-aware serves highly depend on the accurate location information. In this article, we construct a vehicle localization system architecture composed of multiple
Internet of Things (IoT)
with arbitrary array configuration and a large amount of vehicles in smart cities. In order to deal with the coexisting of circular and non-circular signals transmitted by vehicles, we proposed several vehicle number estimation methods for non-circular signals. Based on the machine learning technique, we extend the vehicle number estimation method into mixed signals in more complex scenario of smart cities. Then the DOA estimation method for non-circular signals based on IoT is proposed, and then the performance of this method is analyzed as well. Simulation outcomes verify the excellent performance of the proposed vehicle number estimation methods and the DOA estimation method in smart cities, and the vehicle positions can be achieved with high estimation accuracy.
Improving Sensor Network Performance with Directional Antennas: A Cross-layer Optimization
Authors: Schandy Javier , Olofsson Simon , Gammarano Nicolás , Steinfeld Leonardo , Voigt Thiemo
Published: August 2021

The use of directional antennas for wireless communications brings several benefits, such as increased communication range and reduced interference. One example of directional antennas are electronically switched directional (ESD) antennas that can easily be integrated into Wireless Sensor Networks (WSNs) due to their small size and low cost. However, current literature questions the benefits of using ESD antennas in WSNs due to the increased likelihood of hidden terminals and increased power consumption. This is mainly because earlier studies have used directionality for transmissions but not for reception.

In this article, we introduce novel cross-layer optimizations to fully utilize the benefits of using directional antennas. We modify the
Medium Access Control (MAC)
, routing, and neighbor discovery mechanisms to support directional communication. We focus on convergecast investigating a large number of different network topologies. Our experimental results, both in simulation and with real nodes, show when the traffic is dense, networks with directional antennas can significantly outperform networks with omnidirectional ones in terms of packet delivery rate, energy consumption, and energy per received packet.
Ancient Invaders: How Paleogenetic Tools Help to Identify and Understand Biological Invasions of the Past
Authors: Knapp Michael , Collins Catherine J. , Matisoo-Smith Elizabeth
Published: August 2021

Past biological invasions have contributed to shaping our present day biodiversity. For many island ecosystems, they are the only source of terrestrial life. At the same time, biological invasions, in particular when caused by human activity, are a major concern for the conservation of native species. It is therefore essential to understand the drivers of biological invasions as well as the role invasions have played in different ecosystems. Molecular tools have provided valuable data to reconstruct biological invasions, their drivers, and their impacts. Recent technological developments have further increased the potential of molecular tools to track past shifts in biodiversity. Here, we provide a perspective on how such molecular tools have influenced our understanding of past biological invasions and discuss how they may further help to shape our understanding and management of biological invasions.
Eales’ Disease: When the Rare Sounds Frequent
Authors: Lopes Beatriz Oliveira , Brízido Margarida Sena , Reis Ana Isabel , Miranda Margarida Maria , Pina Susana Morais
Published: August 2021

Eales’ disease is a peripheral occlusive retinal phlebitis, with an unclear pathogenesis. The classic association with hypersensitivity to Mycobacterium tuberculosis protein infers that immunologic disturbance may be involved. Here, we described three cases of Eales’ disease. All patients are Caucasian men aged 27-58 years and presented with vitreous hemorrhage and/or peripheral venous vasculitis. Tuberculin skin sensitive test (Mantoux screening test) and interferon-gamma release assay (IGRA) were positive in all patients. Therapeutic approach included antituberculosis therapy and systemic steroids, associated or not to immunosuppressive therapy, and retinal scatter photocoagulation in all cases. Antivascular endothelial grow factor (VEGF) intravitreal injections were also required in two cases. Since various retinal diseases can resemble this presentation, Eales’ disease is considered a diagnosis of exclusion. Early diagnosis and appropriate therapeutic approach are both essential to accomplish disease control and reduce ophthalmologic complications.
5-Aminosalicylic Acid Prevents Disease Behavior Progression and Intestinal Resection in Colonic and Ileocolonic Crohn’s Disease Patients: A Retrospective Study
Authors: Wan Jian , Wang Xuan , Zhang Yujie , Xue Xianmin , Li Yani , Liu Zhenzhen , Han Shuang , Chen Min , Nie Yan , Shi Yongquan , Liang Jie , Wu Kaichun
Published: August 2021

Background and Aims. The efficacy of 5-aminosalicylic acid (5-ASA) in the long-term outcome of Crohn’s disease (CD) patients was uncertain. This study aimed to evaluate the efficacy of the 5-ASA in preventing disease behavior progression and intestinal resection in CD patients. Methods. CD patients were prospectively enrolled from January 2008 to September 2019 in Xijing Hospital. Disease behavior progression was defined as the development of stricturing (B2) or penetrating disease (B3) in patients with nonstricturing/nonpenetrating disease (B1) at diagnosis. Cox regression analyses were used to investigate the associations between disease location progression, disease behavior progression, and intestinal resection and multiple covariates. Results. In total, 122 CD patients were followed up for 4.3 years. At the time of diagnosis, disease location was ileal in 19.7% (24/122), colonic in 41.0% (50/122), and ileocolonic in 39.3% (48/122). A total of 87 (71.3%) patients had B1 at diagnosis. The disease behavior progression and intestinal resection rates were 42.5% (37/87) and 29.5% (36/122). The use of 5-ASA reduced the risk of disease behavior progression (HR 0.30, 95% CI 0.14–0.61,

P

 = 0.001) and intestinal resection (HR 0.33, 95% CI 0.17–0.90,

P

 = 0.027) in colonic and ileocolonic CD patients. Patients who presented with ileal disease at diagnosis did not have the same protective effects when taking 5-ASA (

P

 > 0.05). Conclusions. The use of 5-ASA could improve the long-term outcome of CD patients with colon involvement. The result emphasized the importance of early use of 5-ASA in the daily management of colonic involved CD.
Cognitive Dysfunction of Pregnant Women with Gestational Diabetes Mellitus in Perinatal Period
Authors: Sana Siriguleng , Deng Xijin , Guo Lei , Wang Xunhong , Li Enyou
Published: August 2021

Purpose. To explore whether pregnant women with gestational diabetes mellitus (GDM) had cognitive impairment and assess cognitive function in normal pregnant women. Methods. A total of 75 consecutive women diagnosed with GDM (GDM group), 70 normal pregnant women (NP group) without diabetes and matched for age, and 51 female volunteers (CG group) with the similar age level, normal blood glucose, and nonpregnancy were included in the study. For the assessment of cognitive functions, Montreal Cognitive Assessment (MoCA) was performed. Venous blood samples were collected to measure blood glucose, glycated hemoglobin (HbA1c), methylglyoxal (MGO), beta amyloid (Aβ), and tau protein. Results. The score of MoCA of GDM was lowest, and the score of the NP group was lower than volunteers (

P
<
0.05

). The incidence of cognitive dysfunction increased significantly in the GDM group with statistical significance (

P
<
0.05

). The levels of tau and MGO in the GDM group were significantly less than those in the NP and CG groups, and Aβ in the GDM group was significantly more than that in the NP and CG groups (

P
<
0.05

), but the differences between NP and CG groups were not statistically significant (

P
<
0.05

). Conclusion. The pregnant women with GDM showed a significant decline in cognitive function, and the normal pregnant women also showed a decline in cognitive function which is very light.
The Hydroethanolic Stem Bark Extract of Tieghemella heckelii (A.Chev.) Pierre ex Dubard (Sapotaceae) Produced N-Methyl-D-Aspartate (NMDA) Receptor-Dependent Analgesia and Attenuates Acute Inflammatory Pain via Disruption of Oxidative Stress
Authors: Kumatia Emmanuel K. , Appiah-Opong Regina
Published: August 2021

Background. Tieghemella heckelii stem bark is used in African traditional medicine to treat inflammatory pain conditions. However, these biological actions of the plant have not been proven. This study investigates the phytochemical composition and the mechanisms of analgesic and anti-inflammatory actions of the hydroethanolic stem bark extract of T. heckelii (THBE). Methods. Phytochemical composition of THBE was investigated using qualitative and quantitative phytochemical analyses. Anti-inflammatory activity was evaluated using the carrageenan-induced paw oedema assay. Analgesic activity was evaluated using hot plate and acetic acid-induced writhing assays. Mechanism of analgesic action was determined using pharmacological antagonist such as naloxone, atropine, flumazenil, nifedipine, or ketamine. Test agents were administered orally as follows: Tween 80 (5%) (control), diclofenac sodium (DS) 10/tramadol 9 mg/kg (standard), or THBE 10, 100, and 450 mg/kg. Glutathione peroxidase (GPx), superoxide dismutase (SOD), and lipid peroxidation levels were also measured. Results. THBE which contained 58.45% saponins, 229.04 ± 0.049 GAE mg/g phenolic compounds,and 0.482 ± 0.0028 QE mg/g flavonoids produced (

p

 < 0.5) anti-inflammatory effect of 56.22% and analgesia of 330 ± 72% and 50.4% in the hot plate and writhing assays, respectively, at 10 mg/kg and inhibited oxidative stress by GPx and SOD elevation in rats during inflammation. Ketamine significantly blocked the analgesia of THBE, indicating NMDA receptor-dependent analgesic action. Whereas, naloxone, atropine, nifedipine, and flumazenil could not antagonize the analgesic action of THBE. Conclusion. These results show that THBE produced potent anti-inflammatory effect via disruption of oxidative stress and also generated NMDA receptor-dependent analgesia.
SSGD: A Safe and Efficient Method of Gradient Descent
Authors: Duan Jinhuan , Li Xianxian , Gao Shiqi , Zhong Zili , Wang Jinyan
Published: August 2021

With the vigorous development of artificial intelligence technology, various engineering technology applications have been implemented one after another. The gradient descent method plays an important role in solving various optimization problems, due to its simple structure, good stability, and easy implementation. However, in multinode machine learning system, the gradients usually need to be shared, which will cause privacy leakage, because attackers can infer training data with the gradient information. In this paper, to prevent gradient leakage while keeping the accuracy of the model, we propose the super stochastic gradient descent approach to update parameters by concealing the modulus length of gradient vectors and converting it or them into a unit vector. Furthermore, we analyze the security of super stochastic gradient descent approach and demonstrate that our algorithm can defend against the attacks on the gradient. Experiment results show that our approach is obviously superior to prevalent gradient descent approaches in terms of accuracy, robustness, and adaptability to large-scale batches. Interestingly, our algorithm can also resist model poisoning attacks to a certain extent.
Image Fusion Algorithm at Pixel Level Based on Edge Detection
Authors: Chen Jiming , Chen Liping , Shabaz Mohammad
Published: August 2021

In the present scenario, image fusion is utilized at a large level for various applications. But, the techniques and algorithms are cumbersome and time-consuming. So, aiming at the problems of low efficiency, long running time, missing image detail information, and poor image fusion, the image fusion algorithm at pixel level based on edge detection is proposed. The improved ROEWA (Ratio of Exponentially Weighted Averages) operator is used to detect the edge of the image. The variable precision fitting algorithm and edge curvature change are used to extract the feature line of the image edge and edge angle point of the feature to improve the stability of image fusion. According to the information and characteristics of the high-frequency region and low-frequency region, different image fusion rules are set. To cope with the high-frequency area, the local energy weighted fusion approach based on edge information is utilized. The low-frequency region is processed by merging the region energy with the weighting factor, and the fusion results of the high findings demonstrate that the image fusion technique presented in this work increases the resolution by 1.23 and 1.01, respectively, when compared to the two standard approaches. When compared to the two standard approaches, the experimental results show that the proposed algorithm can effectively reduce the lack of image information. The sharpness and information entropy of the fused image are higher than the experimental comparison method, and the running time is shorter and has better robustness.
A General Inequality for CR-Warped Products in Generalized Sasakian Space Form and Its Applications
Authors: Li Yanlin , Ali Akram , Ali Rifaqat
Published: August 2021

In the present paper, by considering the Gauss equation in place of the Codazzi equation, we derive new optimal inequality for the second fundamental form of CR-warped product submanifolds into a generalized Sasakian space form. Moreover, the inequality generalizes some inequalities for various ambient space forms.
SERR-U-Net: Squeeze-and-Excitation Residual and Recurrent Block-Based U-Net for Automatic Vessel Segmentation in Retinal Image
Authors: Wang Jinke , Li Xiang , Lv Peiqing , Shi Changfa
Published: August 2021

Background and Objective. Accurate segmentation of retinal vessels is considered as an important prerequisite for computer-aided diagnosis of ophthalmic diseases, diabetes, glaucoma, and other diseases. Although current learning-based methods have greatly improved the performance of retinal vessel segmentation, the accuracy could not meet the requirements of clinical assistance yet. Methods. A new SERR-U-Net framework for retinal vessel segmentation is proposed, which leverages technologies including Squeeze-and-Excitation (SE), residual module, and recurrent block. First, the convolution layers of encoder and decoder are modified on the basis of U-Net, and the recurrent block is used to increase the network depth. Second, the residual module is utilized to alleviate the vanishing gradient problem. Finally, to derive more specific vascular features, we employed the SE structure to introduce attention mechanism into the U-shaped network. In addition, enhanced super-resolution generative adversarial networks (ESRGANs) are also deployed to remove the noise of retinal image. Results. The effectiveness of this method was tested on two public datasets, DRIVE and STARE. In the experiment of DRIVE dataset, the accuracy and AUC (area under the curve) of our method were 0.9552 and 0.9784, respectively, and for SATRE dataset, 0.9796 and 0.9859 were achieved, respectively, which proved a high accuracy and promising prospect on clinical assistance. Conclusion. An improved U-Net network combining SE, ResNet, and recurrent technologies is developed for automatic vessel segmentation from retinal image. This new model enables an improvement on the accuracy compared to learning-based methods, and its robustness in circumvent challenging cases such as small blood vessels and intersection of vessels is also well demonstrated and validated.
Dynamic Optimal Pricing of Ridesharing Platforms under Network Externalities with Stochastic Demand
Authors: Wang Wenjie , Xie Lei
Published: August 2021

Ridesharing two‐sided platforms link the stochastic demand side and the self‐scheduling capacity supply side where there are network externalities. The main purpose of this paper is to establish the optimal pricing model of ridesharing platforms to dynamically coordinate uncertain supply and stochastic demand with network externalities in order to maximize platforms’ revenue and social welfare. We propose dynamic pricing strategies under two demand scenarios that minimize order loss in the surge demand period and maximize social welfare in the declining demand period. The numerical simulation results show that dynamic pricing strategies could stimulate the supply to reduce delayed orders in the surge demand scenario and adjust the demand to maximize social welfare under declining demand scenario. Additionally, we further find that the direct network externalities positively influence the platforms’ revenue, and the indirect network externalities have a negative effect on social welfare in the declining demand scenario, and a higher wage ratio cannot enhance the platforms’ revenue.
Uncommon Occurrence of an Air Embolism during the Preanhepatic Phase of an Orthotopic Liver Transplant
Authors: Smart Klint J. , Yaghoubian Saman
Published: August 2021

Vascular air embolism (VAE) during liver transplantation usually occurs during the dissection phase of the procedure or during liver reperfusion. If this phenomenon occurs, it can cause significant cardiovascular, pulmonary, and neurological complications. Prompt identification of VAE is essential, and the surgeon should be immediately notified. The mainstay treatment is identification and rectification of the source of the air embolus, hemodynamic support, and prevention of further air entrainment. This case report describes the occurrence of a pulmonary air embolism during the preanhepatic phase of an orthotopic liver transplant.
Dahuang Danshen Decoction Inhibits Pancreatic Fibrosis by Regulating Oxidative Stress and Endoplasmic Reticulum Stress
Authors: Liang Xiaoqiang , Han Mian , Zhang Xuelin , Sun Xun , Yu Kui , Liu Congying , Zhang Jiaqi , Hu Cheng , Zhang Jingzhe
Published: August 2021

Background. In Traditional Chinese Medicine (TCM), Dahuang Danshen decoction (DD) is used to treat pancreatic fibrosis. Pancreatic fibrosis is a typical manifestation of chronic pancreatitis (CP), which affects the digestive system. The therapeutic mechanisms of DD in pancreatic fibrosis are unclear. Aim. This study aimed to investigate the regulatory mechanisms of DD on oxidative stress and endoplasmic reticulum stress in CP. Materials and Methods. Experimental rats were intraperitoneally injected with 500 mg/kg BW of diethyldithiocarbamate (DDC) twice a week for six weeks to induce CP. At the same time, DD was administered orally at daily doses of 1.37 g/kg BW, 2.74 g/kg BW, and 5.48 g/kg BW to evaluate its treatment effects on CP. After all treatments, pancreatic tissues were harvested and subjected to H&E staining. Transmission electron microscopy (TEM) was also performed to show the endoplasmic reticulum structure in the pancreatic tissues. Immunohistochemistry was used to detect the α-SMA expression level in the pancreatic tissues. Metabolomics analysis of the serum and proteomics analysis of the pancreatic tissues were performed to reveal the changes of endogenous metabolites and proteins, respectively. Concentrations of GSH, MDA, SOD, ROS, col-1, and col-3 were determined using corresponding kits. The western blotting method was used to determine the protein levels of Keap-1, HO-1, NQO1, Nrf2, GRP, JNK, and caspase 12. The pancreatic mRNA levels of NQO1, GPX1, HO-1, GST-π, GRP, JNK, and caspase 12 were also determined by quantitative PCR. The interactions between TCM components and Keap-1 were investigated by molecular docking modeling. Results. The pathohistological results demonstrated that DD could ameliorate DDC-induced CP in vivo, indicated by reduction of α-SMA, col-1, col-3, TNF-α, and IL-6. DD increased serum levels of GSH and SOD but reduced pancreatic ROS. DD decreased cytoplasmic Keap-1 and increased Nrf2 nuclear localization. Correspondingly, DD increased the expression levels of Nrf2 downstream antioxidant genes NQO1, GPX1, HO-1, and GST-π. DD also decreased ERS hallmarks caspase 12 cleavage and GRP expression. Eventually, DD inhibited PSC activation by reducing JNK phosphorylation and MMK-3/p38 expression. Molecular docking analysis showed that salvianolic acid B and emodin had a good binding affinity toward Keap-1. Conclusions. These results demonstrated that DD could ameliorate the oxidative and endoplasmic reticulum stress through releasing Nrf2 from Keap-1 binding and inducing the downstream antioxidant enzymes. As a result, DD could thwart pancreatic fibrosis by inhibiting PSCs activation, which was induced by OS and ERS through JNK and MMK3/p38 pathways.
Building Information Modeling Application Maturity Model (BIM‐AMM) from the Viewpoint of Construction Project
Authors: Sun Chengshuang , Xu Hanting , Wan Dongjun , Li Ying
Published: August 2021

BIM maturity models have become a significant method used to show the development stage of building information modeling (BIM) and to assist in measuring BIM capability. However, most of the existing maturity models focus on the evaluation technology, but the effect of BIM is not only related to technology, and most of them are mostly used for a comprehensive evaluation of BIM capability after the event. In this paper, for the purpose of comprehensive preevaluation of BIM application maturity of the project, considering the temporary characteristics of the project, based on Nolan’s growth stage model, from the perspective of technology, social environment, and project participants, a BIM application maturity model (BIM‐AMM) including 10 measurement indicators is proposed. The model integrates the Barrel Principle in accordance with the characteristics of a single project. The conditions of BIM implementation are evaluated in advance, and specific deficiencies of BIM implementation are identified; then, BIM decision‐making is determined for the project. Finally, an actual project is taken as the application demonstration case of BIM‐AMM, and according to the results, the obstacles faced by the project organization in adopting BIM technology and the improvement strategies are put forward. The research results further expand the BIM maturity research to the early stage of the project and provide new ideas for BIM maturity research.
Multimodal MRI Analysis of Brain Metabolism in Maintenance Hemodialysis Patients Based on Cognitive Computing
Authors: Zhang Yan , Ma Hui , Lv Xinguang , Han Qinjun
Published: August 2021

This paper investigates cognitive computation of brain metabolism in maintenance hemodialysis patients with multimodal MRI therapy assessment. This paper constructs a cross-individual emotion recognition method using dynamic sample entropy pattern learning. The cross-individual emotion recognition was carried out on subjects using the EEG emotion dataset SEED. The experimental results show that the proposed dynamic sample entropy-based pattern learning has better performance in cross-individual emotion recognition and exhibits better generalization and generalization ability when compared with the results of existing related studies. The constructed cognitive computing method for cross-individual emotion state recognition achieves optimization and innovation of EEG emotion pattern recognition, which can effectively predict people’s mental emotion state from EEG signals. We also explore the value of diffusion-weighted magnetic resonance imaging and dynamic enhanced magnetic resonance imaging-based volumetric measurements in assessing the efficacy of neoadjuvant therapy in maintenance hemodialysis patients. We analyze and compare the results of different studies to find the best multimodal MRI to assess the efficacy of neoadjuvant therapy in maintenance hemodialysis patients. The use of ADC value growth rates to assess neoadjuvant efficacy provides the best diagnostic efficacy and allows the screening of patients who respond well to neoadjuvant therapy while avoiding the impact of two different b-value combinations commonly used to assess neoadjuvant efficacy.
Evaluation of the Floor Acceleration Amplification Demand of Instrumented Buildings
Authors: Huang Baofeng , Lu Wensheng
Published: August 2021

The floor acceleration amplification (FAA) factor is one of the most critical parameters in computing the equivalent seismic force of nonstructural component (NC). To evaluate the heightwise FAA distribution profile, the recorded acceleration response of the instrumented buildings was analyzed using the California Strong Motion Instrumentation Program (CSMIP) database. The FAA demands for three groups of buildings consisting of reinforced concrete, steel, and masonry buildings were analyzed. In each group, the buildings were classified into four subgroups according to their heights. Parabolic distribution profiles were suggested that could envelop most of the FAA data, as demonstrated by the processed results. An earthquake experience‐based importance factor was suggested in terms of the percentage of the enveloped records. The obtained FAAs at the roof were generally larger than those in other levels. The percentile distributions of the roof acceleration amplification (RAA) were computed. The results showed that the roof FAA was underestimated in ASCE 7‐16. The magnitudes of the FAA and the RAA correlated to the fundamental period of the building, which was considered by classifying the buildings according to the period ranges. The RAA profile against the period was obtained from a regression analysis. The developed FAA profile is expected to be useful in the seismic design of NCs, and it is expected to be adopted in future code provisions.
Rheological Parameters and Transport Characteristics of Fresh Cement Tailings Backfill Slurry in an Underground Iron Mine
Authors: Zhang Chi , Tan Yu-Ye , Zhang Kai , Zhang Chun-Yue , Song Wei-Dong
Published: August 2021

Pipeline transportation is the key component of the mine filling system. In this study, fresh cement tailing backfill (CTB) slurry made by unclassified tailings from the Daye iron mine is taken as the research object, and its rheological parameters and transport characteristics are studied via laboratory test and FLUENT software. It was found that the relationship curve of the dynamic yield stress, viscosity, and solid content (SC) of CTB slurry fits the law of the H‐B model when SC varies between 60% and 68%. However, the relationship curve gradually changes to fit the Bingham mode when SC reaches up to 70%. Numerical simulation results demonstrate that when the SC of CTB slurry exceeds 65%, the static pressure at the pipeline’s outlet begins to distribute symmetrically. At this point, the slurry flow state is relatively stable, and the pipeline resistance loss is positively correlated with SC and flow rate. When SC exceeds 70%, resistance loss begins to increase significantly. The findings of this study can be used to identify the suitable transportation conditions of CTB slurry and provide the theoretical direction for the pipeline transportation design of filling systems in mines.
Study on the Retention of Large Mining Height and Small Coal Pillar under Thick and Hard Roof of Bayangaole Coal
Authors: Zhao Shankun , Zuo Jianping , Liu Lei , Wu Kaijun
Published: August 2021

The coal pillar stress distribution at the 311102 working face in the Bayangaole Mine is analyzed and revealed. In addition, borehole stressmeter, PASSAT monitoring system, and numerical modelling are fully utilized. Based on the patterns of acoustic wave velocity distribution, it is discovered that the impact created by mining activity can expand into the working face around 40 m, where the peak stress concentration is found about 15 m ahead. According to borehole stressmeter readings, mildly impacted, ordinarily impacted, and severely impacted zones are distinguished. The equilibrium theory and corresponding calculation indicated that the coal body in front of the working face has a plastic zone width of 4.96 m. The stress‐displacement analysis based on numerical simulation showed that the relationship between peak vertical stress and pillar width is unimodal and bimodal. Specifically, both 5 and 10 m wide pillars showed a unimodal stress‐width correlation and the peak vertical stresses are all located at the pillar center, whereas 15 m wide pillar has a bimodal stress‐width relationship. In comparison, 10 m wide pillar holds the maximum in‐situ stress. In consideration of site conditions and economic influences, 6 m wide coal strip coal pillar is designed at the working face 311102. As a result, stopping was successfully completed, and remarkable economic benefits were achieved.
Synthesis and Characterizations of Biobased Copolymer Poly(ethylene-co-butylene 2,5-Furandicarboxylate)
Authors: Trung Nam Vu , Nguyen Mai Ngoc , Ngoc Anh Nguyen Thi , Thi Ni Pham , Quang Tung Tran , Thi Thuy Tran
Published: August 2021

Homopolymers and copolymers derived from 2,5-furandicarboxylic acid have been extensively studied for their potential in the development of sustainable plastics. This research definitely spotlighted the synthesis of poly(ethylene-co-butylene 2,5-furandicarboxylate) copolymer via the two-step melting polycondensation with various ethylene glycol/1,4-butanediol molar ratios. The structural characterization of the obtained biobased copolymer was carried out by ATR-FTIR and 1H NMR. The average molecular weight of the obtained copolymer was determined by the intrinsic viscosity measurements. It was found that ethylene glycol was preferentially incorporated into the copolymer structures when the molecular weight of the products was not high enough (>18000). The decomposition of two types of monomer units of the obtained copolymer was proven through the degradation two-step process by TGA measurements.
Frequency-Modulated Continuous Wave Radar Respiratory Pattern Detection Technology Based on Multifeature
Authors: Wang Qisong , Dong Zhening , Liu Dan , Cao Tianao , Zhang Meiyan , Liu Runqiao , Zhong Xiaocong , Sun Jinwei
Published: August 2021

Respiratory diseases including apnea are often accompanied by abnormal respiratory depth, frequency, and rhythm. If different abnormal respiratory patterns can be detected and recorded, with their depth, frequency, and rhythm analyzed, the detection and diagnosis of respiratory diseases can be achieved. High-frequency millimeter-wave radar (76–81 GHz) has low environmental impact, high accuracy, and small volume, which is more suitable for respiratory signal detection and recognition compared with other contact equipment. In this paper, the experimental platform of frequency-modulated continuous wave (FMCW) radar was built at first, realizing the noncontact measurement of vital signs. Secondly, the energy intensity and threshold of respiration signal during each period were calculated by using the rectangular window, and the accurate judgment of apnea was realized via numerical comparison. Thirdly, the features of respiratory and heart rate signals, the number of peaks and valleys, the difference between peaks and valleys, the average and the standard deviation of normalized short-term energy, and the average and the standard deviation and the minimum of instantaneous frequency, were extracted and analyzed. Finally, support vector machine (SVM) and K-nearest neighbor (KNN) were used to classify the extracted features, and the accuracy was 98.25% and 88.75%, respectively. The classification and recognition of respiratory patterns have been successfully realized.
DNA‐Aptamer Raised against Receptor for Advanced Glycation End Products Improves Survival Rate in Septic Mice
Authors: Koga Yoshinori , Sotokawauchi Ami , Higashimoto Yuichiro , Nishino Yuri , Hashizume Naoki , Kakuma Tatsuyuki , Akiba Jun , Tanaka Yoshiaki , Matsui Takanori , Yagi Minoru , Yamagishi Sho-ichi
Published: August 2021

Despite remarkable scientific advances in the understanding of molecular mechanisms for sepsis, therapeutic options are far from satisfactory. High mobility group box 1 (HMGB1), one of the ligands of receptor for advanced glycation end products (RAGE), is a late mediator of lethality in septic mice. We have recently found that the DNA‐aptamer raised against RAGE (RAGE‐aptamer) significantly blocks experimental diabetic nephropathy and melanoma growth and metastasis. We examined the effects of RAGE‐aptamer on sepsis score, survival rate, and inflammatory and oxidative stress responses in serum, peripheral monocytes, kidneys and livers of lipopolysaccharide‐ (LPS‐) injected mice, and on LPS‐exposed THP‐1 cells. RAGE‐aptamer inhibited the binding of HMGB1 to RAGE in vitro. RAGE‐aptamer significantly (P = 0.002) improved sepsis score at 8 hours after LPS injection and survival rate at 24 hours (P < 0.01, 70%) in septic mice compared with LPS+vehicle‐ or LPS+control‐aptamer‐treated mice. RAGE‐aptamer treatment significantly decreased expression of p‐NF‐κB p65, an active form of redox‐sensitive transcriptional factor, NF‐κB and gene or protein expression of TNF‐α, IL‐1β, IL‐6, and HMGB1 in serum, peripheral monocytes, and kidneys of septic mice in association with the reduction of oxidative stress and improvement of metabolic acidosis, renal and liver damage. LPS‐induced oxidative stress, inflammatory reactions, and growth suppression in THP‐1 cells were significantly blocked by RAGE‐aptamer. Our present study suggests that RAGE‐aptamer could attenuate multiple organ damage in LPS‐injected septic mice partly by inhibiting the inflammatory reactions via suppression of HMGB1‐RAGE interaction.