bluuebunny/crossref_metadata_2025 huggingface dataset:
Manifold Markov Chain Monte Carlo Methods for Bayesian Inference in Diffusion Models
Authors: Graham Matthew M. , Thiery Alexandre H. , Beskos Alexandros
Published: April 2022

Bayesian inference for nonlinear diffusions, observed at discrete times, is a challenging task that has prompted the development of a number of algorithms, mainly within the computational statistics community. We propose a new direction, and accompanying methodology—borrowing ideas from statistical physics and computational chemistry—for inferring the posterior distribution of latent diffusion paths and model parameters, given observations of the process. Joint configurations of the underlying process noise and of parameters, mapping onto diffusion paths consistent with observations, form an implicitly defined manifold. Then, by making use of a constrained Hamiltonian Monte Carlo algorithm on the embedded manifold, we are able to perform computationally efficient inference for a class of discretely observed diffusion models. Critically, in contrast with other approaches proposed in the literature, our methodology is highly automated, requiring minimal user intervention and applying alike in a range of settings, including: elliptic or hypo-elliptic systems; observations with or without noise; linear or non-linear observation operators. Exploiting Markovianity, we propose a variant of the method with complexity that scales linearly in the resolution of path discretisation and the number of observation times. Python code reproducing the results is available at http://doi.org/10.5281/zenodo.5796148.
Backcasting world trade growth using data reduction methods
Authors: Charles Amélie , Darné Olivier
Published: April 2022

This paper compares backcasting performance of models based on variable selection to dynamic factor model for backcasting the world trade growth rate with two months ahead. The variable selection models are specified by applying penalised regressions and an automatic general‐to‐specific procedure, using a large data set. A recursive forecast study is carried out to assess the backcasting performance by distinguishing crisis and non‐crisis periods. The results show that, some selection‐based models exhibit a good backcasting performance during both periods. The more accurate backcasts seem to be SCAD, adaptive Elastic‐Net and adaptive SCAD during the global financial crisis (GFC) and COVID‐19 crisis, whereas it seems rather Lasso, Elastic‐Net, adaptive Lasso and DFM during the non‐crisis period. Amongst the predictors for backcasting world trade growth, it appears that the index of global economic conditions proposed by Baumeister et al. (The Review of Economics and Statistics, 2020), the PMI indicator on new export orders in manufacturing sector and the MSCI world index are relevant.
Enhancing the photo-response characteristics of graphene/n-Si based Schottky barrier photodiodes by increasing the number of graphene layers
Authors: Fidan Mehmet , Ünverdi Özhan , Çelebi Cem
Published: April 2022

The impact of the number of graphene layers on the spectral responsivity and response speed of graphene/n-type Si (Gr/n-Si)-based Schottky barrier photodiodes is investigated. Gr/n-Si photodiode devices are fabricated by transferring chemical vapor deposition-grown graphene layers one by one on n-Si substrates, reaching up to three graphene layers. The devices show a clear rectifying Schottky character and have a maximum responsivity at a peak wavelength of 905 nm. Wavelength-resolved and time-dependent photocurrent measurements demonstrated that both spectral responsivity and response speed are enhanced as the number of graphene layers is increased from 1 to 3 on n-Si substrates. For example, the spectral responsivity and the response speed of the fabricated device were found to be improved by about 15% (e.g., from 0.65 to 0.75 AW−1) and 50% (e.g., 14 to 7 μs), respectively, when three graphene layers are used as the hole-collecting cathode electrode. The experimentally obtained results showed that the device parameters, such as spectral responsivity and response speed of Gr/n-Si Schottky barrier photodiodes, can be boosted simply by increasing the number of graphene layers on n-Si substrates.
Under-ice acoustic navigation using real-time model-aided range estimation
Authors: Bhatt EeShan C. , Viquez Oscar , Schmidt Henrik
Published: April 2022

The long baseline (LBL) underwater navigation paradigm relies on the conversion of travel times into pseudoranges to trilaterate position. For real-time autonomous underwater vehicle (AUV) operations, this conversion assumes an isovelocity sound speed. For re-navigation, computationally and/or labor-intensive acoustic modeling may be employed to reduce uncertainty. This work demonstrates a real-time ray-based prediction of the effective sound speed along a path from source to receiver. This method was implemented for an AUV-LBL system in the Beaufort Sea in an ice-covered and a double-ducted propagation environment. Given the lack of Global Navigation Satellite Systems (GNSS) data throughout the vehicle's mission, the pseudorange performance is first evaluated on acoustic transmissions between GNSS-linked beacons. The mean real-time absolute range error between beacons is roughly 11 m at distances up to 3 km. A consistent overestimation in the real-time method provides insights for improved eigenray filtering by the number of bounces. An operationally equivalent pipeline is used to reposition the LBL beacons and re-navigate the AUV, using modeled, historical, and locally observed sound speed profiles. The best re-navigation error is 1.84 ± 2.19 m root mean square. The improved performance suggests that this approach extends the single meter accuracy of the deployed GNSS units into the water column.
Targeting AML at the intersection of epigenetics and signaling
Authors: Narayan Nisha , Huntly Brian J. P.
Published: April 2022

Mutations in multiple cancers may synergize to alter the cellular epigenetic and transcriptional state and corrupt key signaling pathways. In this issue of
Science Signaling
, Pedicona
et al.
illustrate how the two processes intersect to regulate cellular differentiation in acute myeloid leukemia (AML) and show how inhibition of epigenetic regulators promotes sensitivity to kinase inhibitors.
Shining a light on rhodopsin signaling
Authors: Foley John F.
Published: April 2022

Monitoring rhodopsin signaling in real time reveals the role of native lipids in modulating GPCR interactions.
Characterization of a Near-Complete Genome Sequence of a Chaphamaparvovirus from an Australian Boobook Owl (Ninox boobook)
Authors: Sarker Subir , Athukorala Ajani , Phalen David N.
Published: April 2022

This study reports a complete genome sequence of a variant of psittacine chaphamaparvovirus 2 detected in kidney tissue from an Australian boobook (
Ninox boobook
), compiled using next-generation sequencing. The genome was 4,312 bp long, encoding four open reading frames. The detection of this variant in boobook represents a significant host-switching event.
Comparable Effectiveness of Cefuroxime and Piperacillin-Tazobactam as Empirical Therapy for Methicillin-Susceptible Staphylococcus aureus Bacteremia
Authors: Bigseth Robert Strengen , Sandholdt Håkon , Petersen Andreas , Østergaard Christian , Benfield Thomas , Thorlacius-Ussing Louise
Published: April 2022

This multicenter retrospective matched cohort study evaluated the effect of empirical antimicrobial therapy on the clinical outcome of methicillin-susceptible
Staphylococcus aureus
bacteremia (MS-SAB) in >1100 adult patients. To the best of our knowledge, this is the largest study to date evaluating the effect of empirical treatment on the MS-SAB outcome.
SGK1, a Serine/Threonine Kinase, Inhibits Prototype Foamy Virus Replication
Authors: Zhang Junshi , Han Chunhua , Xiong Zhenjie , Qiu Manman , Tuo Xiaopeng , Wang Chenchen , Qiao Wentao , Tan Juan
Published: April 2022

Foamy viruses can integrate into the host chromosome and are nonpathogenic in natural hosts or in experimentally infected animals. Therefore, foamy viruses are considered to be safe and efficient gene transfer vectors.
Small Insertions and Deletions Drive Genomic Plasticity during Adaptive Evolution of Yersinia pestis
Authors: Wu Yarong , Hao Tongyu , Qian Xiuwei , Zhang Xianglilan , Song Yajun , Yang Ruifu , Cui Yujun
Published: April 2022

Yersinia pestis, the causative agent of plague, is a highly pathogenic clone ofYersinia pseudotuberculosis. Previous genome-wide SNP analysis provided few adaptive signatures during its evolution.
Comprehensive clinical, radiological, pathological and biochemical analysis required to differentiate VV1 sporadic Creutzfeldt-Jakob disease from suspected variant CJD
Authors: Holper Sarah , Lewis Victoria , Wesselingh Robb , Gaillard Frank , Collins Steven J , Butzkueven Helmut
Published: April 2022

Background

A diagnosis of variant Creutzfeldt-Jakob disease (vCJD), the zoonotic prion disease related to transmission of bovine spongiform encephalopathy, can carry enormous public health ramifications. Until recently, all vCJD clinical cases were confined to patients displaying methionine homozygosity (MM) at codon 129 of the prion protein gene (PRNP). The recent diagnosis of vCJD in a patient heterozygous (MV) at codon 129 reignited concerns regarding a second wave of vCJD cases, with the possibility of phenotypic divergence from MM vCJD and greater overlap with sporadic CJD (sCJD) molecular subtypes.

Method and results

We present a case of CJD with clinico-epidemiological and radiological characteristics creating initial concerns for vCJD. Thorough case evaluation, including data provided by genetic testing, autopsy and neuropathological histological analyses, provided a definitive diagnosis of the rare VV1 molecular subtype of sCJD.

Conclusion

Distinguishing vCJD from sCJD is of vital public health importance and potentially more problematic with the development of non-MM vCJD cases. The patient described herein demonstrates that in addition to the clinico-epidemiological profile, combined supplementary pathological, biochemical and critical radiological analysis may be necessary for confident discrimination of sCJD, especially rare sub-types, from vCJD.
Prospects of CKM elements $$|V_{cs}|$$ and decay constant $$f_{D_{s}^+}$$ in $$D_s^+\rightarrow \mu ^+\nu _\mu $$ decay at STCF
Authors: Liu Jia-Jun , Shi Xiao-Dong , Li Hui-Jing , Zhou Xiao-Rong , Zheng Bo
Published: April 2022

We report a feasibility study of pure leptonic decay $$D_s^+\rightarrow \mu ^+\nu _\mu $$

D
s
+

→

μ
+

ν
μ

by using a fast simulation software package at STCF. With an expected luminosity of $$1~\mathrm {ab}^{-1}$$

1

ab

-
1

collected at STCF at a center-of-mass energy of 4.009 GeV, the statistical sensitivity of the branching fraction is determined to be 0.3%. Combining this result with the $$c \rightarrow s$$

c
→
s

quark mixing matrix element $$|V_{cs}|$$

|

V

cs

|

determined from the current global Standard Model fit, the statistical sensitivity of $$D_s^+$$

D
s
+

decay constant, $$f_{D_s^+}$$

f

D
s
+

, is estimated to be 0.2%. Alternatively, combining the current results of $$f_{D_s^+}$$

f

D
s
+

calculated by lattice QCD, the statistical sensitivity of $$|V_{cs}|$$

|

V

cs

|

is determined to be 0.2%, which helps probe possible new physics beyond Standard Model. The unprecedented precision to be achieved at STCF will provide a precise calibration of QCD and rigorous test of Standard Model.
Mechanical performance according to fiber lamination pattern for radar mast application
Authors: Park Chang Wook , Kim Yun Hae , Yoon Sung Won
Published: April 2022

As the IMO has strengthened its environmental regulations to increase the energy efficiency of ships, the IMO has also begun to consider operational economics such as reducing energy consumption by reducing the weights of ships and their parts. This study conducts an analysis examining the application of a ship radar mast. The applicability of the laminated composite material was analyzed through tension, shear, compressive, and tension-tension fatigue tests and the FRP fatigue limit for one million cycles by the slope of the [Formula: see text]–[Formula: see text] curve was found to be about 231 MPa. It is expected that this method can be utilized in the design stage by predicting the fatigue life of radar masts for ships through fatigue testing.
Rock-salt-type lithium–titanium oxynitride as anode material for Li-Ion secondary batteries
Authors: Mizuta Yusuke , Shizukawa Kohei , Takahara Rie , Murai Kei-Ichiro , Moriga Toshihiro
Published: April 2022

We synthesized rock-salt-type Li–Ti oxynitride (LiTi[Formula: see text]O[Formula: see text]N[Formula: see text], [Formula: see text], 1.25, 1.5, 1.75, and 2) using solid-phase reaction. The best charge/discharge characteristics were obtained with a Ti/Li ratio of 1.25, and the maximum discharge capacity was 140 mAh/g.
Production of H2S gas sensor by a facile fabrication of Au-decorated ZnO
Authors: Rodiawan  , Wang Sheng-Chang
Published: April 2022

H2S is a gas that can cause poisoning with a composition starting from 2.5 ppm. This study investigated the ability of gas sensors to detect H2S gas at below 1 ppm. The primary material used for the gas sensor was ZnO. To increase sensor response, Au was used as a decorated metal. These materials were dissolved using deionized water with ultrasonication and were deposited by solution deposition method onto the Pt electrode. Powder and film characterizations were made using XRD, SEM, and TEM. The characterization results show high crystallinity of the annealed ZnO. The coating material shows a highly porous interconnected structure that can absorb gas quickly. There are Au spots attached to the ZnO particles, which are spherical and homogeneous. Based on these results, the device sensor can detect H2S gas with a high sensing response even at low gas concentration.
Investigation of the growth of Na+-Doped ZnO nanorods using hydrothermal method and their photoluminescence properties
Authors: Hsu Wei-Ling , Chang Yi-Jheng , Li Jia-En , Yang Cheng-Fu
Published: April 2022

In this study, the hydrothermal method was used to synthesize Na[Formula: see text]-doped ZnO nanowires with different concentrations of Na[Formula: see text] ions under different synthesis temperatures. First, ZnO films with a thickness of about 300 nm were deposited on glass substrates as a seed layer, and C6H[Formula: see text]N4, Na(NO[Formula: see text]H2O, and Zn(NO[Formula: see text]H2O were used as source materials to grow the Na[Formula: see text]-doped ZnO nanowires using different Na[Formula: see text] concentrations and under different synthesis temperatures. After the Na[Formula: see text]-doped ZnO nanowires were synthesized, their XRD patterns were obtained to analyze their crystal phases. FESEM observations were used to observe the synthesized morphologies, and a fluorescence spectrophotometer was used to show the photoluminescence excitation (PLE) and photoluminescence (PL) emission properties of the Na[Formula: see text]-doped ZnO nanowires. We showed that Na[Formula: see text] precursor concentrations and synthesis temperatures had considerable effects on the crystal phase, surface morphologies, and PL emission and PLE properties of the Na[Formula: see text]-doped ZnO nanowires.
Optical soliton solutions of multi-dimensional Boiti–Leon–Manna–Pempinelli equations
Authors: Hussain Amjad , Jabeen Farah , Abbas Naseem
Published: April 2022

In this paper, we consider [Formula: see text] and [Formula: see text]-dimensional Boiti–Leon–Manna–Pempinelli equations. We obtain the soliton solutions by using the new extended direct algebraic method. The resulting solutions carry a variety of new families including the singular solution of type 1 and 2, dark, dark-bright, and dark-singular soliton solution. These solutions contain trigonometric, hyperbolic, and exponential type functions. Moreover, to highlight the important features of the obtained solutions, some three-dimensional and two-dimensional diagrams of these solutions are plotted with the suitable choice of the values of the involving parameters.
Asymptotic properties of generalized D-solutions to the stationary axially symmetric Navier–Stokes equations
Authors: Li Zijin , Pan Xinghong
Published: April 2022

In this paper, we derive asymptotic properties of both the velocity and the vorticity fields to the 3-dimensional axially symmetric Navier–Stokes equations at infinity under the generalized D-solution assumption [Formula: see text] for [Formula: see text]. We do not impose any zero or non-zero constant vector asymptotic assumption to the solution at infinity. Our results generalize those in [H. Choe and B. Jin, Asymptotic properties of axis-symmetric D-solutions of the Navier–Stokes equations, J. Math. Fluid Mech. 11(2) (2009) 208–232; S. Weng, Decay properties of axially symmetric D-solutions to the steady Navier–Stokes equations, J. Math. Fluid Mech. 20(1) (2018) 7–25; B. Carrillo, X. Pan and Q. S. Zhang, Decay and vanishing of some axially symmetric D-solutions of the Navier–Stokes equations, J. Funct. Anal. 279(1) (2020) 108504], where the authors focused on the case [Formula: see text] and the velocity field approaches zero at infinity. Meanwhile, when [Formula: see text] and the velocity field approaches zero at infinity, our results coincide with the results in [H. Choe and B. Jin, Asymptotic properties of axis-symmetric D-solutions of the Navier–Stokes equations, J. Math. Fluid Mech. 11(2) (2009) 208–232; S. Weng, Decay properties of axially symmetric D-solutions to the steady Navier–Stokes equations, J. Math. Fluid Mech. 20(1) (2018) 7–25; B. Carrillo, X. Pan and Q. S. Zhang, Decay and vanishing of some axially symmetric D-solutions of the Navier–Stokes equations, J. Funct. Anal. 279(1) (2020) 108504].
Determining functions by slopes
Authors: Thibault Lionel , Zagrodny Dariusz
Published: April 2022

It is shown that by knowing the slope of a bounded from below lower semicontinuous convex function at each point of a Banach space, we know the function up to an additive constant.
Helmholtz solutions for the fractional Laplacian and other related operators
Authors: Guan Vincent , Murugan Mathav , Wei Juncheng
Published: April 2022

We show that the bounded solutions to the fractional Helmholtz equation, [Formula: see text] for [Formula: see text] in [Formula: see text], are given by the bounded solutions to the classical Helmholtz equation [Formula: see text] in [Formula: see text] for [Formula: see text] when [Formula: see text] is additionally assumed to be vanishing at [Formula: see text]. When [Formula: see text], we show that the bounded fractional Helmholtz solutions are again given by the classical solutions [Formula: see text]. We show that this classification of fractional Helmholtz solutions extends for [Formula: see text] and [Formula: see text] when [Formula: see text]. Finally, we prove that the classical solutions are the unique bounded solutions to the more general equation [Formula: see text] in [Formula: see text], when [Formula: see text] is complete Bernstein and certain regularity conditions are imposed on the associated weight [Formula: see text].
Regularity and symmetry for semilinear elliptic equations in bounded domains
Authors: Dupaigne Louis , Farina Alberto
Published: April 2022

In this paper, we investigate the regularity and symmetry properties of weak solutions to semilinear elliptic equations which are stable or more generally of finite Morse index or even more generally locally stable.
Symmetry and symmetry breaking for Hénon-type problems involving the 1-Laplacian operator
Authors: Pimenta Marcos T. O. , Gonzaga Anderson dos Santos
Published: April 2022

In this work, we study a class of Hénon-type equations which involve the 1-Laplacian operator in the unit ball. Under mild assumptions on the nonlinearity, the existence of radial solutions is proved and, for a parameter in a certain range, the existence of symmetry breaking is proved, through the presence of non-radial solutions. The approach is based on an approximation scheme, where a thorough analysis of the solutions of the associated p-Laplacian problems is necessary.
Exact and optimal controllability for scalar conservation laws with discontinuous flux
Authors: Adimurthi  , Ghoshal Shyam Sundar
Published: April 2022

This paper describes the reachable set and resolves an optimal control problem for the scalar conservation laws with discontinuous flux. We give a necessary and sufficient criteria for the reachable set. A new backward resolution has been described to obtain the reachable set. Regarding the optimal control problem, we first prove the existence of a minimizer and then the backward algorithm allows us to compute it. The same method also applies to compute the initial data control for an exact control problem. Our methodology for the proof relies on the explicit formula for the conservation laws with the discontinuous flux and finer properties of the characteristics curves.
Temporal Vector Visibility Graph: A Tool for Complexity Analysis of Multivariate Time Series
Authors: Shang Binbin , Shang Pengjian
Published: April 2022

The family of visibility algorithms provides a new point of view to describe time series by transforming them into networks. In this paper, we propound a new visibility algorithm named Temporal Vector Visibility graph [Formula: see text], which maps the multivariate time series to a directed network. Computed by the [Formula: see text] and [Formula: see text] degree distributions obtained from the [Formula: see text], these statistics such as the Kullback–Leibler divergence (KLD), the normalized Shannon entropy and the statistical complexity measure, are introduced to assess the complexity of time series. Furthermore, we also apply the Multivariate Multiscale Entropy Plane (MMEP) to evaluate the complexity of multivariate time series. The experimental results of eight different types of time series verify the effectiveness of our method. Subsequently, this method is employed to explore the complexity characteristics of financial time series and classify different stock markets. Our research reveals that this method is capable of investigating the physical structures of financial time series.
Binomial transform of the generalized third-order Jacobsthal sequence
Authors: Soykan Yüksel , Taşdemir Erkan , Göcen Melih
Published: April 2022

In this study, we establish the binomial transform of the generalized third-order Jacobsthal sequence. We also describe the binomial transform of four special cases of third-order Jacobsthal sequence such as the binomial transform of the third-order Jacobsthal, third-order Jacobsthal–Lucas, modified third-order Jacobsthal–Lucas, third-order Jacobsthal–Perrin sequences. Moreover, we examine their features in more detail.
Stability analysis and numerical simulation of dynamic and fractional SEIRD models for spread of nCOVID-19 in Turkey
Authors: Yildiz B. , Haspolat E. , Yilmaz A. , Önes Z.
Published: April 2022

There are various mathematical models that have been designed for forecasting the future behavior of coronavirus spreading, which helps to rapidly control the process while there is no treatment and vaccines. The main aim of this study is to describe COVID-19 dynamics in Turkey by using a Susceptible–Exposed–Infected–Recovered–Deceased (SEIRD) model. For this purpose, a new SEIRD model of nCOVID-19 and its fractional-order version are designed. The basic reproduction number is calculated with the generation operator method. All possible equilibria of the dynamic model are investigated in terms of the basic reproduction number. Further, stability conditions are obtained through the Routh–Hurwitz and Lyapunov stability theories. Finally, some numerical simulations of the dynamic system and its fractional version are given based on the data from the number of nCOVID-19 cases in Turkey. These results provide to implicate the theoretical findings corresponding to the model.
A Taxonomy of Information Attributes for Test Case Prioritisation: Applicability, Machine Learning
Authors: Ramírez Aurora , Feldt Robert , Romero José Raúl
Published: April 2022

Most software companies have extensive test suites and re-run parts of them continuously to ensure that recent changes have no adverse effects. Since test suites are costly to execute, industry needs methods for test case prioritisation (TCP). Recently, TCP methods use machine learning (ML) to exploit the information known about the system under test and its test cases. However, the value added by ML-based TCP methods should be critically assessed with respect to the cost of collecting the information. This article analyses two decades of TCP research and presents a taxonomy of 91 information attributes that have been used. The attributes are classified with respect to their information sources and the characteristics of their extraction process. Based on this taxonomy, TCP methods validated with industrial data and those applying ML are analysed in terms of information availability, attribute combination and definition of data features suitable for ML. Relying on a high number of information attributes, assuming easy access to system under test code and simplified testing environments are identified as factors that might hamper industrial applicability of ML-based TCP. The
TePIA
taxonomy provides a reference framework to unify terminology and evaluate alternatives considering the cost-benefit of the information attributes.
Evaluation of Low-cost Air Quality Sensor Calibration Models
Authors: Aula Kasimir , Lagerspetz Eemil , Nurmi Petteri , Tarkoma Sasu
Published: April 2022

We contribute a novel model evaluation technique that divides available measurements into training and testing sets in a way that adheres to the requirements imposed on professional monitoring stations. We perform extensive and systematic experiments with a wide range of state-of-the-art calibration models to demonstrate that our approach provides accurate insights about the performance of calibration models in real-world deployments, while at the same time highlighting issues with evaluation techniques used in previous works. Among others, our results show that although trained and tested in the same location, calibration errors can exhibit deviation up to 116% depending on the evaluation protocol that is being adopted. We also demonstrate that models trained with continuous data can suffer up to 76% greater error when tested with data coming from diverse environmental conditions. In contrast, when models are trained and tested with our method, the variability of errors is significantly reduced and the robustness of calibration models is significantly improved. The overall performance improvements depend on pollutant concentration, ranging from 10% for low concentrations to 90% for high concentrations that represent conditions that are most dangerous for human health.
Effective Representation of Active Material and Carbon Binder in Porous Electrodes
Authors: Li Weiyu , Tartakovsky Daniel M.
Published: April 2022

Active cathode material and graphite anode material are routinely mixed with conductor and binder to improve the electric conductivity and mechanical stability of electrodes. Despite its benefits, this carbon binder domain (CBD) impedes ionic transport and reduces the active surface area, thus impacting the battery performance. We consider a composite spherical particle, whose active-material core is coated with CBD, and its homogeneous counterpart, for which we derived equivalent electrical conductivity, ionic diffusivity, and reaction parameters in the Butler-Volmer equation. These equivalent characteristics are defined to ensure that the same mass and charge enter the composite and homogenized spheres. They are expressed in terms of the volume fraction of the active material and transport properties of the active material and CBD. In general, the equivalent effective diffusion coefficient and reaction parameters are time-dependent and exhibit two-stage behavior characterized by the reaction delay time. At later times, these characteristics are time-independent and given explicitly by closed-form formulae. The simplicity of these expressions facilitates their use in single- and multi-particle representations of Li-ion and Li-metal batteries.
Imatinib alleviates lung injury and prolongs survival in ventilated rats
Authors: Xin Yi , Cereda Maurizio , Yehya Nadir , Humayun Shiraz , Delvecchio Paolo , Thompson Jill M. , Martin Kevin , Hamedani Hooman , Martorano Paul , Duncan Ian , Kadlecek Stephen , Makvandi Mehran , Brenner Jacob S. , Rizi Rahim R.
Published: April 2022

Imatinib, a tyrosine kinase inhibitor, attenuates pulmonary edema and inflammation in lung injury. However, the physiological effects of this drug and their impact on outcomes are poorly characterized. Using serial computed tomography (CT), we tested the hypothesis that imatinib reduces injury severity and improves survival in ventilated rats. Hydrochloric acid (HCl) was instilled in the trachea (pH 1.5, 2.5 mL/kg) of anesthetized, intubated supine rats. Animals were randomized ( n = 17 each group) to receive intraperitoneal imatinib or vehicle immediately prior to HCl. All rats then received mechanical ventilation. CT was performed hourly for 4 h. Images were quantitatively analyzed to assess the progression of radiological abnormalities. Injury severity was confirmed via hourly blood gases, serum biomarkers, bronchoalveolar lavage (BAL), and histopathology. Serial blood drug levels were measured in a subset of rats. Imatinib reduced mortality while delaying functional and radiological injury progression: out of 17 rats per condition, 2 control vs. 8 imatinib-treated rats survived until the end of the experiment ( P = 0.02). Imatinib attenuated edema after lung injury ( P < 0.05), and survival time in both groups was negatively correlated with increased lung mass ( R2 = 0.70) as well as other physiological and CT parameters. Capillary leak (BAL protein concentration) was significantly lower in the treated group ( P = 0.04). Peak drug concentration was reached after 70 min, and the drug half-life was 150 min. Imatinib decreased both mortality and lung injury severity in mechanically ventilated rats. Pharmacological inhibition of edema could be used during mechanical ventilation to improve the severity and outcome of lung injury.
Moving bronchopulmonary dysplasia research from the bedside to the bench
Authors: Gilfillan Margaret , Bhandari Vineet
Published: April 2022

Although advances in the respiratory management of extremely preterm infants have led to improvements in survival, this progress has not yet extended to a reduction in the incidence of bronchopulmonary dysplasia (BPD). BPD is a complex multifactorial condition that primarily occurs due to disturbances in the regulation of normal pulmonary airspace and vascular development. Preterm birth and exposure to invasive mechanical ventilation also compromises large airway development, leading to significant morbidity and mortality. Although both predisposing and protective genetic and environmental factors have been frequently described in the clinical literature, these findings have had limited impact on the development of effective therapeutic strategies. This gap is likely because the molecular pathways that underlie these observations are yet not fully understood, limiting the ability of researchers to identify novel treatments that can preserve normal lung development and/or enhance cellular repair mechanisms. In this review article, we will outline various well-established clinical observations while identifying key knowledge gaps that need to be filled with carefully designed preclinical experiments. We will address these issues by discussing controversial topics in the pathophysiology, the pathology, and the treatment of BPD, including an evaluation of existing animal models that have been used to answer important questions.
Inducible Clindamycin-Resistant Staphylococcus aureus Strains in Africa: A Systematic Review
Authors: Assefa Muluneh
Published: April 2022

Introduction. Excessive use of clindamycin enhances the acquisition of inducible clindamycin-resistant S. aureus strains, which is a significant health problem in Africa. The main objective of this review study was to determine the prevalence of inducible clindamycin resistance and related genes among S. aureus isolates in Africa. Methods. A qualitative systematic review was conducted on inducible clindamycin resistance among S. aureus isolates in Africa using electronic databases such as Google Scholar and PubMed. Articles published in English before 2021 were selected, and relevant data were extracted, collected, and analyzed. Results. In our search, 22 articles met the eligibility criteria for this review study. Of 3064 total S. aureus isolates, 605 had iMLSB phenotype. The overall prevalence of inducible clindamycin resistance in S. aureus isolates was 19.8% with a range of 2.9% to 44.0%. A high number of iMLSB phenotypes were observed in MRSA isolates (3.6–77.8%) than MSSA (0–58.8%). The overall prevalence of the iMLSB phenotype in MRSA strains was 26.8% (279/1041). The maximum peak prevalence of inducible clindamycin resistance among S. aureus isolates recorded in the continent was 44.0% in Egypt, followed by 35.8% in Libya and 33.3% in Uganda in 2017, 2007, and 2013, respectively. The highest prevalence of iMLSB phenotype in MRSA strains was reported in Egypt, 77.8%, followed by Nigeria, 75.0%, and Libya, 66.2%. Among the recovered drug-resistance genes, ermA, ermC, and msrA genes were commonly detected in Egypt with 67.9%, 70.0%, and 70.0% prevalence, respectively. Conclusion. This review highlights a higher inducible resistance of S. aureus, including MRSA strains to clindamycin in the continent. Regular screening of these strains, wise use of clindamycin, and molecular detection and genotyping of resistant genes are urgent.
Genetic Analysis of Prunus salicina L. by Random Amplified Polymorphic DNA (RAPD) and Intersimple Sequence Repeat (ISSR)
Authors: Li Jun , Gao Guangchun , Li Bin , Li Bai , Lu Qihua
Published: April 2022

Background. Prunus salicina L. is an important fruit tree species of great economic value which is mainly distributed in the northern hemisphere. Methods. 25 samples of Prunus salicina L. were collected from 8 provinces in China, Japan, USA, and New Zealand. The genetic variations of these samples were characterized by the random amplified polymorphic DNA (RAPD) and intersimple sequence repeat (ISSR) technique, respectively, and in combination. Results. Totally, 257 RAPD bands ranging 200∼2300 bp was found, and 81.59% of these bands were polymorphic. ISSR analysis identified 179 bands ranging 300∼2500 bp, and 87.74% of the bands were polymorphic. ISSR results showed that the similarity coefficient index between samples P10 (Maihuangli in Anhui, Chin) and P13 (Longyuanqiuli in Heilongjiang, China) was lowest, while that between samples P10 (Maihuangli in Anhui, Chin) and P15 (Baili in Japan) was highest. Combined analysis of RAPD and ISSR demonstrated that the similarity coefficient index between samples P4 (Qiepili in Ningbo, Zhejiang, China) and P13 (Longyuanqiuli in Heilongjiang, China) was lowest, while that between samples P19 (Laroda in USA) and P20 (Red heart in USA) was highest. Conclusion. RAPD combined with ISSR analysis can be used for genetic characterization of Prunus L. species.
Tweedie Model for Predicting Factors Associated with Distance Traveled to Access Inpatient Services in Kenya
Authors: Mwenda Ngugi , Kosgei Mathew , Kerich Gregory , Nduati Ruth
Published: April 2022

Aim. This study aims to examine which factors influence the distance traveled by patients for inpatient care in Kenya. Methods. We used data from the fourth round of the Kenya Household Health Expenditure and Utilization survey. Our dependent variable was the self-reported distance traveled by patients to access inpatient care at public health facilities. As the clustered data were correlated, we used the generalized estimating equations approach with an exchangeable correlation under a Tweedie distribution. To select the best-fit covariates for predicting distance, we adopted a variable selection technique using the

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I

C

u

and

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2

criteria, wherein the lowest (highest) value for the former (latter) is preferred. Results. Using data for 451 participants from 47 counties, we found that three-fifths were admitted between 1 and 5 days, two-thirds resided in rural areas, and 90% were satisfied with the facilities’ service. Wealth quintiles were evenly distributed across respondents. Most admissions (81%) comprised

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15,

>

65, and 25–54 years. Many households were of medium size (4–6 members) and had low education level (48%), and nine-tenths had no access to insurance. While two-thirds reported employment-based income, the same number reported not having cash to pay for inpatient services; 6 out of 10 paid over 3000 KES. Thus, differences in employment, ability to pay, and household size influence the distance traveled to access government healthcare facilities in Kenya. Interpretation. Low-income individuals more likely have large households and live in rural areas and, thus, are forced to travel farther to access inpatient care. Unlike the unemployed, the employed may have better socioeconomic status and possibly live near inpatient healthcare facilities, thereby explaining their short distances to access these services. Policymakers must support equal access to inpatient services, prioritize rural areas, open job opportunities, and encourage smaller families.
[Retracted] Mechanism of RNA circHIPK3 Involved in Resistance of Lung Cancer Cells to Gefitinib
Authors: Zhao Yi , Zhang Caiming , Tang Haibo , Wu Xiaomin , Qi Qiugan
Published: April 2022

To study the mechanism of circular ribonucleic acid (RNA) circHIPK3 involved in the resistance of lung cancer cells to gefitinib, 110 patients with lung cancer were recruited as the research objects, and the tumor tissue and para‐cancerous tissue of each patient’s surgical specimens were collected and paraffinized to detect the expression of circHIPK3 in different tissues. Gefitinib drug‐resistant cell line of lung cancer was constructed with gefitinib to detect cell apoptosis under different conditions. As a result, the relative expression of circHIPK3 in patients with tumor diameter no less than 3 cm was dramatically inferior to that in patients with tumor diameter less than 3 cm (P < 0.05). The relative expression of circHIPK3 in patients with TNM stage II/III was dramatically inferior to that in patients with tumor, node, and metastasis (TNM) stage I (P < 0.05). Expression of circHIPK3 in patients with lymph node metastasis was dramatically inferior to that in patients without lymph node metastasis (P < 0.05). Of the lung cancer tissues of patients with different TNM stages, only six patients had high expression, and the remaining 104 patients had low expression. Moreover, electrophoresis revealed that circHIPK3 can only be amplified in cDNA, but not in gDNA. Gefitinib‐mediated apoptosis rate of lung cancer drug‐resistant cell lines decreased notably. In summary, the circular RNA circHIPK3 may have a notably low expression in lung cancer tissues, whose low expression had a certain enhancement effect on the drug resistance of lung adenocarcinoma cells to gefitinib.
Prediction of Visual Acuity after anti-VEGF Therapy in Diabetic Macular Edema by Machine Learning
Authors: Zhang Ying , Xu Fabao , Lin Zhenzhe , Wang Jiawei , Huang Chao , Wei Min , Zhai Weibin , Li Jianqiao
Published: April 2022

Purpose. To predict visual acuity (VA) 1 month after anti-vascular endothelial growth factor (VEGF) therapy in patients with diabetic macular edema (DME) by using machine learning. Methods. This retrospective study included 281 eyes with DME receiving intravitreal anti-VEGF treatment from January 1, 2019, to April 1, 2021. Eighteen features from electronic medical records and measurements data from OCT images were extracted. The data obtained from January 1, 2019, to November 1, 2020, were used as the training set; the data obtained from November 1, 2020, to April 1, 2021, were used as the validation set. Six different machine learning algorithms were used to predict VA in patients after anti-VEGF therapy. After the initial detailed investigation, we designed an optimization model for convenient application. The VA predicted by machine learning was compared with the ground truth. Results. The ensemble algorithm (linear regression + random forest regressor) performed best in VA and VA variance predictions. In the validation set, the mean absolute errors (MAEs) of VA predictions were 0.137-0.153 logMAR (within 7-8 letters), and the mean square errors (MSEs) were 0.033-0.045 logMAR (within 2-3 letters) for the 1-month VA predictions, respectively. For the prediction of VA variance at 1 month, the MAEs were 0.164-0.169 logMAR (within 9 letters), and the MSEs were 0.056-0.059 logMAR (within 3 letters), respectively. Conclusions. Our machine learning models could accurately predict VA and VA variance in DME patients receiving anti-VEGF therapy 1 month after, which would be much valuable to guide precise individualized interventions and manage expectations in clinical practice.
Artemisinin Alleviates Intestinal Inflammation and Metabolic Disturbance in Ulcerative Colitis Rats Induced by DSS
Authors: Jia Xuemei , Gao Yunxiao , Liu Liran , Guo Yuxi , Wang Jie , Ma Hongyu , Zhao Runyuan , Li Bolin , Du Yao , Yang Qian
Published: April 2022

Objective. This study is aimed to reveal the possible mechanisms of artemisinin in the treatment of ulcerative colitis (UC) through bioinformatics analysis and experimental verification in UC model rats. Methods. Firstly, we searched two microarray data of the Gene Expression Omnibus (GEO) database to explore the diﬀerentially expressed genes (DEGs) between UC samples and normal samples. Then, we selected DEGs for gene ontology (GO) function enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The acute UC model of rats was established by using 3.5% dextran sulfate sodium (DSS) for 10 days to verify the core pathway. Finally, we evaluated the therapeutic effect of artemisinin at the molecular level and used metabonomics to study the endogenous metabolites in the rat serum. Results. We screened in the GEO database and selected two eligible microarray datasets, GSE36807 and GSE9452. We performed GO function and KEGG pathway enrichment analyses of DEGs and found that these DEGs were mainly enriched in the inflammatory response, immune response, and IL-17 and NF-κB signaling pathways. Finally, we verified the IL-17 signaling pathway and key cytokines, and ELISA and immunohistochemical results showed that artemisinin could downregulate the expression of proinflammatory cytokines such as IL-1β and IL-17 in the IL-17 signaling pathway and upregulate the expression of the anti-inflammatory cytokine PPAR-γ. Metabolomics analysis showed that 33 differential metabolites were identified in the artemisinin group (AG) compared to the model group (MG). Differential metabolites were mainly involved in alanine, aspartate, and glutamate metabolism and synthesis and degradation of ketone bodies. Conclusion. In this study, we found that artemisinin can significantly inhibit the inflammatory response in UC rats and regulate metabolites and related metabolic pathways. This study provides a foundation for further research on the mechanism of artemisinin in the treatment of UC.
Issues of Clinical Identity Verification for Healthcare Applications over Mobile Terminal Platform
Authors: Ahmad Sultan , Abdeljaber Hikmat A. M. , Nazeer Jabeen , Uddin Mohammed Yousuf , Lingamuthu Velmurugan , Kaur Amandeep
Published: April 2022

According to recent research, attacks on USIM cards are on the rise. In a 5G setting, attackers can also employ counterfeit USIM cards to circumvent the identity authentication of specified standard applications and steal user information. Under the assumption that the USIM can be replicated, the identity authentication process of common mobile platform applications is investigated. The identity authentication tree is generated by examining the application behavior of user login, password reset, and sensitive operations. We tested 58 typical applications in 7 categories, including social communication and personal health. We found that 29 of them only needed the SMS verification code received by the USIM card to pass the authentication. In response to this problem, it is recommended to enable two-step verification and use USIM anti-counterfeiting methods to complete the verification.
[Retracted] Level and Drivers of China’s Construction Industry Energy Efficiency under Carbon Dioxide Emissions
Authors: Xie Yani
Published: April 2022

Taking the carbon dioxide emissions of energy utilization in construction industry (CI) as an unwanted output, this study builds an index system for construction industry energy efficiency (CIEE) under carbon dioxide emissions, adopts the super‐SBM to assess the CI energy efficiencies (CIEEs) of 30 Chinese provincial administrative regions (PARs) in 2005–2018, and further examines the influencing factors of the CIEEs with the panel data model. The main results show that, during the study period, only a few PARs (e.g., Beijing, Heilongjiang, Zhejiang, and Tianjin) realized the optimal CIEEs and most PARs failed to optimize their CIEEs. After dividing China into three parts, the CIEEs of oriental, middle, and occidental parts followed a trend like an inverted U in the study period and their CIEEs first increased and then decreased with the elapse of time. There were significant differences in CIEE between the three parts: the oriental part realized the greatest CIEE, the middle part came at the second, and the occidental part ended up at the bottom. Empirical results demonstrate that CIEE is significantly promoted by enterprise scale, property right structure, and environmental regulation, greatly inhibited by economic growth and technical level and not greatly affected by production level or urbanization level.
Online Course Model of Social and Political Education Using Deep Learning
Authors: Zhang Min , Gao Qiong
Published: April 2022

This study aims to improve the social and political literacy of college students. Social and Political Education (SPE) is studied for undergraduates. Firstly, the background of the subject research is introduced. The face recognition module is built based on deep convolutional neural network (DCNN). The sociopolitical situation of the study subjects is analyzed through a questionnaire. Secondly, a model of the learning process is constructed. Finally, the SPE online course learning platform is constructed. Empirical studies are divided into experimental and control groups. The findings show that all model assumptions are valid. There is a significant structural relationship between the influencing factors of the SPE learning process of college students in the study area. The students selected as research objects lack innovation and critical thinking in the learning process and have certain deficiencies in innovative thinking and critical thinking. The questionnaire has good reliability and validity. The predicted data of the designed platform are compared with the predicted data of the control group. Social science competencies by gender are compared. The results showed little difference in the effectiveness of students using other methods for sociopolitical learning. The data of the experimental group before and after the test are quite different, indicating that the designed experimental platform has played a certain positive role. There are significant differences in the posttest data between the experimental group and the control group, indicating that the constructed online course learning model has a positive impact on students’ innovative thinking and critical thinking. Women’s learning motivation and transfer learning ability are stronger than those of men. The constructed model has certain feasibility for the learning of SPE online courses with face recognition module. These contents provide a reference for the reform of social and political courses.