bluuebunny/crossref_metadata_2025 huggingface dataset:
Dietary wheat amylase trypsin inhibitors exacerbate CNS inflammation in experimental multiple sclerosis
Authors: Zevallos Victor F , Yogev Nir , Hauptmann Judith , Nikolaev Alexei , Pickert Geethanjali , Heib Valeska , Fittler Nicola , Steven Sebastian , Luessi Felix , Neerukonda Manjusha , Janoschka Claudia , Tobinski Ann-Marie , Klotz Luisa , Waisman Ari , Schuppan Detlef
Published: August 2023

Objective

Wheat has become a main staple globally. We studied the effect of defined pro-inflammatory dietary proteins, wheat amylase trypsin inhibitors (ATI), activating intestinal myeloid cells via toll-like receptor 4, in experimental autoimmune encephalitis (EAE), a model of multiple sclerosis (MS).

Design

EAE was induced in C57BL/6J mice on standardised dietary regimes with defined content of gluten/ATI. Mice received a gluten and ATI-free diet with defined carbohydrate and protein (casein/zein) content, supplemented with: (a) 25% of gluten and 0.75% ATI; (b) 25% gluten and 0.19% ATI or (c) 1.5% purified ATI. The effect of dietary ATI on clinical EAE severity, on intestinal, mesenteric lymph node, splenic and central nervous system (CNS) subsets of myeloid cells and lymphocytes was analysed. Activation of peripheral blood mononuclear cells from patients with MS and healthy controls was compared.

Results

Dietary ATI dose-dependently caused significantly higher EAE clinical scores compared with mice on other dietary regimes, including on gluten alone. This was mediated by increased numbers and activation of pro-inflammatory intestinal, lymph node, splenic and CNS myeloid cells and of CNS-infiltrating encephalitogenic T-lymphocytes. Expectedly, ATI activated peripheral blood monocytes from both patients with MS and healthy controls.

Conclusions

Dietary wheat ATI activate murine and human myeloid cells. The amount of ATI present in an average human wheat-based diet caused mild intestinal inflammation, which was propagated to extraintestinal sites, leading to exacerbation of CNS inflammation and worsening of clinical symptoms in EAE. These results support the importance of the gut-brain axis in inflammatory CNS disease.
Multi-objective optimized design of two-dimensional multi-phase phononic crystals with materials self-selection
Authors: Nie Yangwen , Wu Jianhua , Fan Hao
Published: August 2023

In this paper, the multi-objective optimization problem (MOOP) of selecting suitable materials from four materials for phononic crystals layouts is investigated based on an optimization method combined nondominated sorting-based genetic algorithm II (NSGA-II) and finite element method (FEM). Driven by different optimization objectives, the changes in the optimized structure compared to the seed structure are the change of the bandgap mechanism from a local resonance mechanism to a Bragg scattering mechanism, the change of the included materials from four to three, and the significant change in the location and extent of the pores and other materials, respectively. The obtained nondominated Pareto solution of MOOP can balance the bandgap and the structural mass, which provides the decision-maker trade-off to select the appropriate optimized solution. Compared with the single-objective optimization problem (SOOP), the MOOP not only obtains a nondominated solution close to the result of SOOP, but also obtains other nondominated solutions of MOOP, which proves the effectiveness of the optimization algorithm in this paper. The design method in this paper can be easily extended to select suitable materials from a wider variety of materials for bandgap optimization design of PnCs, which has very promising applications.
The relationship between the degree of violation of Bell-CHSH inequality and measurement uncertainty in two classes of spin squeezing mechanisms
Authors: Ait Chlih Anas , Habiballah Nabil , Khatib Driss
Published: August 2023

In solid-state systems, spin squeezing states have acquired much interest in quantum information processing since they are not only essential from a basic physics standpoint but also have many applications, notably reducing noise in interferometry. This paper addresses the study of quantum nonlocality as examined by the violation of the Bell and Clauser–Horne–Shimony–Holt (CHSH) inequality in two classes of spin squeezing states and how this relates to the quantum-memory-assisted entropic uncertainty relation (QMA–EUR). The spin squeezing states in the two classes are systematically generated by two twisting nonlinear interactions. These separately describe two spin-[Formula: see text] interaction mechanisms that undergo one-axis twisting (OAT) and two-axis countertwisting (TAC). We investigate each spin squeezing mechanism in a thermal bath ([Formula: see text]) with a transverse magnetic field. Our main results indicate that the degree of violation of the Bell-CHSH inequality and the entropic uncertainty relation (EUR) is typically anticorrelated in both mechanisms. We demonstrate that the spin squeezing states in the OAT mechanism violate the Bell-CHSH inequality and thus exhibit Bell nonlocality only at low temperatures ([Formula: see text]), whereas in the TAC mechanism, increasing the strength of the spin squeezing interaction leads to a violation of the Bell-CHSH inequality even at finite temperatures. We have also shown that there is always an expansion of the EUR and a decrease in the degree of violation of the Bell-CHSH inequality in the high-temperature regime. In addition, the transverse magnetic field exhibits different behavior under the considered temperature regimes in the two classes of spin squeezing states. Other results will also be discussed.
A comment on the solutions of the generalized Faddeev–Volkov model
Authors: Dede Mehmet
Published: August 2023

We consider two recent solutions of the generalized Faddeev–Volkov model, which is an exactly solvable Ising-type lattice spin model. The first solution is obtained by using the noncompact quantum dilogarithm, and the second one is constructed in a recent study via the gauge/YBE correspondence. We show that the weight functions of these models obtained by different techniques are the same upto a constant.
The optimized field amplitude ratio for nonsequential double ionization by counter-rotating two-color circularly polarized fields
Authors: Wang Qian , Xu Jingkun , Cao Chuanpeng , Liang Jintai , Li Min , Liu Kunlong , Huang Cheng , Zhou Yueming
Published: August 2023

With a classical trajectory Monte Carlo model, we systematically study the laser intensity and field amplitude ratio dependence of nonsequential double ionization by counter-rotating two-color circularly polarized fields (800 and 1600[Formula: see text]nm). The results show that the optimized field amplitude ratio changes with the laser intensity, which is attributed to the shift of the most probable amplitude ratio of electron returning with the laser intensity. Moreover, the laser intensity-dependent double ionization probability curve shows a remarkable dip in the transition region between the nonsequential and sequential channels. It can be well explained by the reduction of the probability of electron returning with the increase of the laser intensity.
Unsteady Magnetohydrodynamics (MHD) mixed convection flow over a cone with the effect of chemical reaction and viscous dissipation
Authors: Mustafa Zubair , Javed T. , Hayat T.
Published: August 2023

This paper investigates the Magnetohydrodynamics (MHD) convective flow over a cone with the influence of viscous dissipation, variable viscosity, chemical reaction and variable thermal conductivity effects. Related equations are tackled by the Homotopy analysis method (HAM). The impacts of physical variables on concentration, velocity and temperature are presented through numerical tables and graphs. It is noticed that the heat transfer rate (Nusselt number) increases against Prandtl number. Similarly, the mass transfer rate (Sherwood number) increases against Schmidt number. Also, it is seen that skin friction in tangential and azimuthal direction increases against the buoyancy forces ratio parameter. Current results are validated with previous literature work.
Multiparameter estimation of quantum metrology in a Heisenberg system with Dzyaloshinskii–Moriya interaction
Authors: Ben hammou Rachid , EL Achab Abdelfattah , Habiballah Nabil
Published: August 2023

In this work, we study the quantum Fisher information on the Heisenberg model in presence of the Dzyaloshinskii–Moriya interaction, basing on the multi-parametric estimation strategy in quantum metrology. First, we employ the density matrix vectorization method with a tool of the quantum Fisher information matrix through quantum Cramer–Rao bound. Second, we show that the multi-parameter quantum Cramer–Rao bound for simultaneous and individual estimation of the temperature and Dzyaloshinskii–Moriya interaction strongly relies on the concepts of the quantum Fisher information matrix. We confirm also the simultaneous strategy that provides a high precision than the individual.
Effect of Ni-concentration on the linear and nonlinear optical properties of MoS2 nanostructures
Authors: Zaimia Randa , Kaddour Sondes , Mastour Nouha , Baachaoui Sabrine , Jemai Mohsen , Ridene Said , Raouafi Noureddine
Published: August 2023

Ni-doped molybdenum disulfide (MoS[Formula: see text] powders at 1%, 2%, 3%, 4%, 5% and 7% of Ni are prepared by the hydrothermal method. Sophisticated analytical studies such as X-ray diffraction, Raman, TEM and photoluminescence (PL) were analyzed to predict their structural, morphological and optical properties. Effects of Ni-doping with MoS2 on crystalline structure, morphology as well their optical phenomenon were examined in detail. Ni doping on MoS2 revealed tetragonal crystal structure of the parent compound. A significant decrease in their optical energy gap (from 1.86 to 1.76[Formula: see text]eV) was perceived with Ni doping concentration increment. PL intensity exhibited a considerable improvement with Ni-doped MoS2 samples at room temperature. From a theoretical viewpoint, the compact density matrix method is applied for Ni–MoS2 to calculate their linear and nonlinear absorption coefficients as well as refractive index modulations for undoped and Ni-doped samples at the focal points of their corresponding intra-band and inter-band transitions. Observed findings are well correlated with the practical results which prove that Ni–MoS2 layers are promoters for potential applications in optoelectronic technology.
Welding Defect Classification Based on Lightweight CNN
Authors: Guo Bo , Wang Youtao , Li Xu , Zhou Yeping , Li Jianmin , Rao Lanxiang
Published: August 2023

The welding defect classification method based on deep learning often faces problems such as insufficient training data and complex model structures, which affect its real-time performance. Therefore, a welding defect classification method based on lightweight convolutional neural network (CNN) is proposed. The problems of insufficient and unbalanced welding defect image are solved by using the generative adversarial networks (GANs) data augmentation method. A lightweight CNN model is developed, which reduces the structural parameters under the premise of ensuring classification accuracy. The feature data of each convolution layer are visualized to verify the feasibility of the model and improve the interpretability of the model. By comparing the accuracy and real-time performance with other lightweight models, the excellent performance of the proposed model in welding defect classification is verified. Additionally, our model achieves 98.25% accuracy on the MNIST dataset.
SCADefender: An Autoencoder-Based Defense for CNN-Based Image Classifiers
Authors: Nguyen Duc-Anh , Do Minh Kha , Nhu Ngoc Nguyen , Hung Pham Ngoc
Published: August 2023

Convolutional neural networks (CNNs) have been enormously successful in a variety of image recognition tasks. Robustness is an important metric to evaluate the quality of CNNs. However, recent research shows that CNNs are particularly vulnerable to adversarial attacks. This paper proposes an adversarial defense method to increase the robustness of CNNs, namely, SCADefender. The proposed method trains a reformer on adversarial examples and the training set of a target classifier. The architecture of the reformer is stacked convolutional autoencoder. The adversarial examples are generated by using various adversarial attacks such as untargeted FGSM, untargeted CW [Formula: see text] and untargeted BIS. Given an input image, the trained reformer could remove the adversarial perturbations with a low computational cost. To demonstrate the effectiveness, the proposed method is compared with PuVAE, MagNet, and adversarial training on three well-known datasets including MNIST, Fashion-MNIST, and CIFAR-10. In terms of the average detection rate, the proposed method outperforms other methods. While the proposed method achieves an average detection rate of 97.78% for MNIST, 90.43% for Fashion-MNIST, and 80.64% for CIFAR-10, the comparable methods achieve only 23.69- 86.18% for MNIST, 63.90-79.70% for Fashion-MNIST, and 25.55-77.36% for CIFAR-10.
Full-Reference Image Quality Assessment via Low-Level and High-Level Feature Fusion
Authors: Wu Chao , Liao Xiaofeng , Yue Hong , Xu Xueyong , Wei Xuekai , Wu Dingcheng , Zhou Mingliang
Published: August 2023

We propose a full-reference image quality assessment (FR-IQA) method by incorporating low-level and high-level image features. First, in contrast to the preexisting deep IQA methods, which only use the features extracted by the deep network, we not only use the image gradient to replace the low-level features in the first two stages of the deep network, but also combine them with the middle-stage features of the deep network to construct the new low-level features. The deep features of shallow layers contain some unwanted noise and further result in a decline in IQA performance. Second, we combine the global features extracted by the self-attention-based model with the semantic features extracted by the convolutional neural network to form the high-level features. Instead of directly using the self-attention-based model trained on the classification task, we first train a no-reference (NR) IQA regression model on a larger dataset and then use the global features of this NR-IQA model. The self-attention-based model can capture the internal connections of the image and is more effective in extracting global information due to its larger perceptual field. In the final pooling stage, we combine the average pooling and the standard deviation pooling to obtain the dispersion and concentration of the similarity maps for a more comprehensive description of quality. Experiments show that our FR-IQA method is able to obtain competitive results on three standard IQA datasets.
Construction of Multi-Label Personality Trait Recognition Model in Chinese Text Based on Emotional Features
Authors: Gu Yan , Wang Miao , Zhu Liuqian , Hu Yongjun , Zou Yutong
Published: August 2023

The key to improve the service effect of virtual digital human is the personality trait recognition technology of users. However, the complexity of Chinese and the sparsity of short texts limit the accuracy of personality trait recognition. Therefore, we applied emotional features to the research of personality trait recognition and constructed a deep learning model for Chinese corpus personality trait recognition to improve the accuracy of personality trait recognition. The model ([Formula: see text] extracted semantic features and embedded emotional features through RoBERTa-wwm-ext Chinese pre-training model, BiLSTM neural network, and attention mechanism. Some experiments were carried out using two Chinese datasets with different scenes. The comparative experiments and ablation experiments showed that the overall effect of the personality trait recognition model ([Formula: see text] is the best, and the Macro-F1 value reaches 75.3%, which is significantly better than the existing models. The results showed that emotional features can significantly improve the accuracy of multi-label personality trait classification in both Chinese daily life scenarios and online scenarios. The proposed model can integrate emotional features and Chinese semantic features to improve the accuracy of personality traits recognition. These findings support the development of personality trait recognition and the application of virtual digital human.
DNA Chromatogram Classification Using Entropy-Based Features and Supervised Dimension Reduction Based on Global and Local Pattern Information
Authors: Öz Ersoy , Yiğit Öyküm Esra , Sakarya Ufuk
Published: August 2023

Gene sequence classification can be seen as a challenging task due to the nonstationary, noisy and nonlinear characteristics of sequential data. The primary goal of this research is to develop a general solution approach for supervised DNA chromatogram (DNAC) classification in the absence of sufficient training data. Today, deep learning comes to the fore with its achievements, however this requires a lot of training data. Finding enough training data can be exceedingly challenging, particularly in the medical area and for rare disorders. In this paper, a novel supervised DNAC classification method is proposed, which combines three techniques to classify hepatitis virus DNA trace files as HBV and HCV. The features that are capable of reflecting the complex-structured sequential data are extracted based on both embedding and spectral entropies. After the supervised dimension reduction step, not only global behavior of the entropy features but also local behavior of the entropy features is taken into account for classification purpose. A memory-based learning, which cannot lose any information coming from training data as its nature, is being used as a classifier. Experimental results show that the proposed method achieves good results that although 19% training data is used, a performance of 92% is obtained.
Self-Balancing and Position Control of a Balancer System Using a Pattern-Based Intelligent Optimization Method
Authors: Chaudhary Abhishek , Bhushan Bharat
Published: August 2023

This paper presents a new Data-Driven Teaching Learning-Based Optimization (DDTLBO) method used to improve the self-balancing and position control of a two-degree of freedom ball and balancer (2DOFBB) system. DDTLBO is a modified version of teaching learning-based optimization (TLBO) method, based on the natural pattern followed by “learners” in an academic class to improve their knowledge. In this, an intelligent algorithm is used on MATLAB platform to handle the nonlinearities and un-stability of the ball and balancer system. A ball-balancer is a highly nonlinear, electromechanical, multivariable and underactuated system. A sophisticated automated intelligent control approach is used to handle these complications. In the proposed approach, the pattern followed by inclination angle of balancer plate is traced after observing the control dynamics of 2DOFBB system. Modeling of ball balancer system is accomplished with the help of proportional integral and derivative (PID) controller. Further, an intelligent data-driven computational approach is implemented, which improves the execution of TLBO optimization method. This improved optimization is used to tune the performance of proportional integral derivative controller employed on the ball balancer system. This approach addresses the major challenge of unknown disturbances on the closed loop system of the considered problem. The dominance of proposed intelligent approach is verified over other optimization techniques using benchmark CEC functions. The optimized parameters of PID controllers hence obtained are implemented on 2DOFBB system. Results obtained are validated using real-time response analysis on the MATLAB/Simulation platform, which demonstrates the dominance of DDTLBO-PID controller over traditional controllers.
Research on Robust Digital Watermarking Based on Reversible Information Hiding
Authors: Gao Zhijing , Qiu Weilin , Wenqi Ren , Xiao Yan
Published: August 2023

The development of modern Internet communication technology and the popularization of multimedia technology have brought convenience to the sharing and storage of multimedia information such as images, videos, and audio. However, at the same time, it has brought about the problem of copyright theft of multimedia information, causing serious information security risks. Digital watermarking technology embeds copyright information in multimedia information in an invisible way, which can effectively realize copyright protection and traceability of infringement. Aiming at the problem that the existing learning model-based methods cannot fully extract and fuse the features of carrier images and watermark images, a robust digital watermarking method based on reversible information hiding is proposed. First, a watermark embedding model based on reversible information hiding is established, and the features of the download volume image and the watermark image in different dimensions are fully extracted and fused to generate a dense image with excellent visual quality. Then, a watermark extraction model based on reversible information hiding is established, and a noise layer is added between the embedding and the extraction model, and the attacked dense image is input to the watermark extraction model to extract the watermark. Under the constraint of the loss function, the network model learns to embed watermark information in the area that is more robust to the attack and is not easy to cause visual quality degradation, so as to optimize the comprehensive performance of the method. Experimental results show that the proposed method effectively improves the imperceptibility and robustness.
Analyzing the Effects of White Noise on Software Release Planning Using SDE-Based SRGM
Authors: Aggarwal Anu G. , Anand Sameer , Bibyan Ritu , Verma Vibha
Published: August 2023

The efficiency and performance of a software application largely depend on the testing strategy adopted by the firm. Apart from the tools, techniques, and skills used for testing, the duration also plays an important influence in establishing software reliability. This defines the operational performance of the software. The testing duration decision is dependent on the failure behavior depicted by the software during the process of testing and the cost spent at various phases of development. In this paper, we study the multi-release model whose fault removal process is affected by random irregular fluctuations (white noise) and error generation phenomenon and determine the optimal time of testing for a multi-release-based software. The fault removal process is governed by the phenomenon of testing coverage which is affected by random fluctuations. The model shows encouraging results as it handles the stochastic property of the fault detection process. The optimal testing time is determined with the goal to minimize the expected development cost related to software while achieving the desired reliability levels of software for that release using a Genetic Algorithm. A real-life four-release fault dataset of tandem computers has been used to numerically demonstrate the methodology. It is observed through sensitivity analysis that the presence of white noise directly affects the cost and optimal testing duration. The potential to improve sensitivity, flexibility, early detection, discovering unsuspected patterns, and boost fault diagnosis is enhanced by collecting irregular fluctuations in the fault detection rate. This technology, by going beyond existing methodologies, has distinct advantages for detecting faults and can contribute to more dependable and efficient systems in a variety of domains.
Nonlinear Dynamic Analysis of the U.S. Defense Stock Markets under the Russia–Ukraine Conflict
Authors: Wu Xinpei , Xu Heming , Wu Shuo , Huang Menghao , Wang Jian
Published: August 2023

In this paper, we adopt multifractal detrended fluctuation analysis (MF-DFA) to explore relationships between the Russia–Ukraine conflict and defense stock markets. Specifically, we analyze the behaviors of 20 U.S. defense stock markets confronting with the Russia–Ukraine conflict. By using the stock price charts, combined with multifractal spectra and singularity exponents calculated by MF-DFA, we explore how the conflict affects the defense stock markets in perspectives of closing price, market efficiency and stability. In addition, the obtained results reveal high level of consistency while each type shows distinct features. According to singularity exponents, we observe that all 20 stocks can be divided into three types which we note as [Formula: see text] A, B and C. We infer from the singularity spectra that the [Formula: see text] A stock price will experience plummet after the conflict, instead, stock price of [Formula: see text] A increases based on stock price charts, while stock price of [Formula: see text] B and C rises as predicted. For [Formula: see text] A stocks, their market efficiency and stability show increments where we draw completely opposite conclusion for [Formula: see text] B stocks. Furthermore, we also note that [Formula: see text] C stocks include two defense stocks having a special phenomenon, and their multifractal spectra indicate the increase in stock price which behave like [Formula: see text] B stocks. However, their singularity exponents reduce during the conflict, meaning the slump in their market efficiency, which share the same characteristic as [Formula: see text] A stocks. Hence, we treat [Formula: see text] C stocks as a unique type. To mitigate the influence of stochastic elements in the experimental process, three comparative analyses are undertaken. We humbly believe that the induced implications are aroused by the Russia–Ukraine conflict.
The semitrivial ideal extension
Authors: Troia D.
Published: August 2023

In this paper, we aim to generalize the ideal duplication defined for numerical semigroups to commutative rings with unity. We introduce the semitrivial ideal extension, a construction that, starting with an ideal of a commutative ring [Formula: see text] with unity and a submodule of a module [Formula: see text] over [Formula: see text], under specific assumptions, produces an ideal of the semitrivial extension [Formula: see text]. Using this tool we characterize the homogeneous prime ideals of a semitrivial extension and we completely describe the family of the maximal ideals. Furthermore, as it was done for the numerical duplication, using the semitrivial ideal extension, we characterize the modules [Formula: see text] such that [Formula: see text] is nearly Gorenstein.
On Hirata separability and inner partial group action
Authors: Kuo Jung-Miao , Szeto George
Published: August 2023

In this paper, we generalize in the context of partial group action a result of Sugano by giving some equivalent conditions for partial Galois extensions to be Hirata-separable extensions. As an application, we show that every partial Galois extension with inner partial group action is Hirata-separable.
Robust Walking and Running Gaits for Biped Robots with a QP-Based Whole-Body Controller
Authors: Luo Qiuyue , Ou Yongsheng , Pang Jianxin , Ge Ligang , Fu Chunjiang
Published: August 2023

This paper presents a new control approach for a humanoid biped robot to perform highly dynamic locomotion and keep balance under large external disturbances. The proposed control approach mainly contains two parts: a simplified model-based task planner and an online whole-body controller. The periodic stability is achieved with a foot placement policy presented in this paper. The landing position is predicted and adjusted at every time step to adapt to uncertain disturbances. Then the desired task trajectories are tracked with a quadratic programming (QP) based task space whole-body controller, while satisfying some specific physical constraints. The whole-body controller outputs the optimized joint accelerations, which are then used to produce desired joint torques for the robot’s actuators. The positions of the center of mass (CoM) along sagittal and lateral axes are not controlled in the whole-body controller. Meanwhile, the torques at the ankles are constrained to be small and the robot follows a passive-like behavior, which is energetically efficient and helps the feet of the robot to fit better in the environment. Simulations on several highly dynamic gaits have been conducted, two examples among which are presented in this paper. The first demonstrates a walking gait with an increasing sagittal speed and its capability to resist large external disturbances. In the second example, the robot is able to run stably on uneven terrain without knowing any information about it.
Opportunistic Digital Twin: an Edge Intelligence enabler for Smart City
Authors: Savaglio Claudio , Barbuto Vincenzo , Awan Faraz Malik , Minerva Roberto , Crespi Noel , Fortino Giancarlo
Published: August 2023

Although Digital Twins (DTs) became very popular in industry, nowadays they represent a pre-requisite of many systems across different domains, by taking advantage of the disrupting digital technologies such as Artificial Intelligence (AI), Edge Computing and Internet of Things (IoT). In this paper we present our “opportunistic” interpretation, which advances the traditional DT concept and provides a valid support for enabling next-generation solutions in dynamic, distributed and large scale scenarios as smart cities. Indeed, by collecting simple data from the environment and by opportunistically elaborating them through AI techniques directly at the network edge (also referred to as Edge Intelligence), a digital version of a physical object can be built from the bottom up as well as dynamically manipulated and operated in a data-driven manner, thus enabling prompt responses to external stimuli and effective command actuation. To demonstrate the viability of our Opportunistic Digital Twin (ODT) a real use case focused on a traffic prediction task has been incrementally developed and presented, showing improved inference performance and reduced network latency, bandwidth and power consumption.
Quasi-3D Model for Diagnostics of Experimental Performance Curve of Proton Exchange Membrane Fuel Cell
Authors: Vasilyev O. A. , Atrazhev V. V. , Dmitriev D. V.
Published: August 2023

Fast acting quasi-3D model of proton exchange membrane fuel cell (PEMFC) is developed. The model utilizes multi-scale approach taking advantage of large difference in the spatial scales in the direction along and perpendicular to the gas channels. This allows to decompose the numerical solution of 3D reaction-transport equations on the 2D problem in the plane perpendicular to the gas channels and 1D equations along the channels. The model is formulated in terms of Characteristic Currents (CCs), calibration lumped parameters that characterize the rate of specific processes in the membrane-electrode assembly (MEA). The model calibration through experimental V-I curve using χ
2 optimization criterion determines the values of CCs for a particular MEA and allows to identify the process that limits performance of this MEA. After calibration, the model allows to predict the PEMFC performance with this particular MEA but arbitrary geometry of bipolar plate. The model predictions are in a good agreement with the literature experimental data.
Design of PGM-Free Cathode Catalyst Layers for PEMFC Applications: The Impact of Electronic Conductivity
Authors: Li Yan-Sheng , Menga Davide , Gasteiger Hubert A. , Suthar Bharatkumar
Published: August 2023

The impact of the electronic resistance of platinum-group-metal-free cathode catalyst layers (PGM-free CCLs) for proton-exchange-membrane fuel cells (PEMFCs) was systematically investigated. Here we selected two different PGM-free catalysts (having high and low electronic conductivity) and integrated them into CCLs without and with conductive carbon fiber additives. To investigate the impact of the electronic resistivity (

ρ

e

−

) of PGM-free catalysts and CCLs, their through-plane

ρ

e

−

values were quantified by an in situ electrochemical impedance spectroscopy (EIS) approach based on a one-dimensional transmission line model. The results indicate that the electronic conductivity of PGM-free CCLs can be increased by adding carbon additive, resulting in a significant improvement of the fuel cell performance (by ∼60 mV at 1 A cm−2 in H2/O2 configuration). Ex situ four-point probe measurements of the in-plane

ρ

e

−

values of some of the CCLs were found to differ vastly from the through-plane

ρ

e

−

values. This difference is attributed to the anisotropic morphology of the CCLs, caused by preferential fiber orientation and/or cracks in the CCLs. In the end, we suggest guidelines for the design and evaluation of PGM-free CCLs and for assessing and improving their electronic resistance.
Functional reserve and contractile phenotype of atrial myocardium from patients with atrial remodeling without and with atrial fibrillation
Authors: Deissler Peter M. , Tran Khai Liem , Falk Volkmar , Pieske Burkert , Grubitzsch Herko , Primessnig Uwe , Heinzel Frank R.
Published: August 2023

Mechanical alterations in atrial remodeling without (AR/−AF) and with atrial fibrillation (AR/+AF) have not been studied in detail in human atrial tissue preparations. To our knowledge, this is the first study to compare the mechanical phenotype and inotropic reserve in human atrial myocardial preparations from patients with no atrial remodeling, AR/−AF, and AR/+AF. We identify specific patterns of contractile dysfunction and heterogeneity for both, AR/−AF and AR/+AF, indicating the progression of atrial disease.
The Role of Forest Ecosystems for Carbon Sequestration and Poverty Alleviation in Ethiopia
Authors: Cherinet Abirham , Lemi Tamiru
Published: August 2023

The objective of the review was to examine and document the contributions of forests in Ethiopia to both climate change mitigation and poverty alleviation. A comprehensive analysis was conducted, encompassing several research articles from reputable journals and international report papers. The findings of the review reveal that Chilimo-Gaji forest exhibited the highest levels of above- and belowground biomass carbon sequestration, while the Egdu forest area demonstrated the highest soil organic carbon content. The variations in carbon sequestration capacity among forest areas can be attributed to several factors, including forest density, variation in diameter at breast height (DBH) among trees, tree height classes, altitude, slope, and aspect, which significantly influence carbon concentration. Furthermore, discrepancies in the application of allometric models to estimate forest biomass also contribute to these variations. In addition to their role in climate change mitigation, forests play an invaluable role in poverty alleviation, particularly in developing countries. Ethiopia has implemented various afforestation strategies to enhance the contribution of forest ecosystems to climate change mitigation and poverty alleviation.
Antibacterial, Antibiofilm, Antiswarming, and Antioxidant Activities of Flavonoids Isolated from Allium colchicifolium Leaves
Authors: Majnooni Mohammad Bagher , Ghanadian Syed Mustafa , Mojarrab Mahdi , Bahrami Gholamreza , Mansouri Kamran , Mirzaei Arezoo , Farzaei Mohammad Hossain
Published: August 2023

Allium (A.) species are one of the most widespread plants in the world, which have played a special role in terms of nutrition, treatment, and economy since long ago. This study is the first report on the phytochemical and biological activities of A. colchicifolium. Five flavonoids, including isorhamnetin (compound 1), quercetin (compound 2), morin (compound 3), isorhamnetin-3-O-glucoside (compound 4), and quercetin 3-O-glucoside (compound 5), were isolated and purified for the first time from A. colchicifolium leaves. All isolated flavonoids showed antibacterial and antibiofilm activities. Compound 3 revealed prominent antibacterial activities against Staphylococcus (S.) aureus and Proteus (P.) mirabilis. Also, compounds 3 and 5 showed the highest antibiofilm activities on S. aureus and P. mirabilis, respectively. The docking study results showed that compounds 3, 4, and 5 had the most robust interactions with two critical proteins in biofilm formation, including staphylococcal accessory regulator A (SarA) and mannose-resistant Proteus-like fimbriae H (MrpH). Besides, compounds 2 and 3 revealed significant antioxidant activities in 2, 2-diphenyl-1-picrylhydrazyl (DPPH) and ferric (Fe3+)-reducing antioxidant power (FRAP) tests compared to the other compounds and positive controls. Also, the ADMET (absorption, distribution, metabolism, excretion, and toxicity) prediction assay showed that compounds 1, 2, and 3 have suitable physicochemical and pharmacokinetic properties. The results of this study confirm that the flavonoids isolated from the leaves of A. colchicifolium can be promising candidates for use in the pharmaceutical and food industries.
Impact on the Volume of Pathology Reports Before and During the COVID-19 Pandemic in SEER Cancer Registries
Authors: Chtourou Amina , Sanchez Pamela V. , Golden Todd , Chen Huann-Sheng , Schwartz Stephen M. , Wu Xiao-Cheng , Hernandez Brenda Y. , Harrison Jovanka N. , Penberthy Lynne , Negoita Serban
Published: August 2023

Introduction:

Health care procedures including cancer screening and diagnosis were interrupted due to the COVID-19 pandemic. The extent of this impact on cancer care in the United States is not fully understood. We investigated pathology report volume as a reflection of trends in oncology services pre-pandemic and during the pandemic.

Methods:

Electronic pathology reports were obtained from 11 U.S. central cancer registries from NCI's SEER Program. The reports were sorted by cancer site and document type using a validated algorithm. Joinpoint regression was used to model temporal trends from January 2018 to February 2020, project expected counts from March 2020 to February 2021 and calculate observed-to-expected ratios. Results were stratified by sex, age, cancer site, and report type.

Results:

During the first 3 months of the pandemic, pathology report volume decreased by 25.5% and 17.4% for biopsy and surgery reports, respectively. The 12-month O/E ratio (March 2020–February 2021) was lowest for women (O/E 0.90) and patients 65 years and older (O/E 0.91) and lower for cancers with screening (melanoma skin, O/E 0.86; breast, O/E 0.88; lung O/E 0.89, prostate, O/E 0.90; colorectal, O/E 0.91) when compared with all other cancers combined.

Conclusions:

These findings indicate a decrease in cancer diagnosis, likely due to the COVID-19 pandemic. This decrease in the number of pathology reports may result in a stage shift causing a subsequent longer-term impact on survival patterns.

Impact:

Investigation on the longer-term impact of the pandemic on pathology services is vital to understand if cancer care delivery levels continue to be affected.
Supplementary Figure S13 from LNS8801 inhibits Acute Myeloid Leukemia by Inducing the Production of Reactive Oxygen Species and Activating the Endoplasmic Reticulum Stress Pathway
Authors: Lee Inyoung , Doepner Miriam , Weissenrieder Jillian , Majer Ariana D. , Mercado Sophia , Estell Angela , Natale Christopher A. , Sung Pamela J. , Foskett J. Kevin , Carroll Martin P. , Ridky Todd W.
Published: August 2023

Supplementary Figure S13. IRE1⍺ inhibitor blocks LNS8801-induced caspase cleavage Western blot of U937 cells treated with 250nM LNS8801 and/or 1uM IRE1⍺ inhibitor Kira6 or 5uM PERK inhibitor GSK414 for 24 hours. Western blot quantification was done by normalizing each band to the respective actin band.
FIGURE 6 from LNS8801 inhibits Acute Myeloid Leukemia by Inducing the Production of Reactive Oxygen Species and Activating the Endoplasmic Reticulum Stress Pathway
Authors: Lee Inyoung , Doepner Miriam , Weissenrieder Jillian , Majer Ariana D. , Mercado Sophia , Estell Angela , Natale Christopher A. , Sung Pamela J. , Foskett J. Kevin , Carroll Martin P. , Ridky Todd W.
Published: August 2023

LNS8801 induces apoptosis in AML cells via ER stress response. Western blot analysis of ER stress proteins in response to LNS8801 in U937 (A) and MOLM14 (B) cells. A total of 250 nmol/L LNS8801 (LNS) and 50 nmol/L thapsigargin (Tg) were used for this experiment. Shown Western blots are representative of at least three experiments. XBP1 and CHOP quantification was done by normalizing to actin bands. Annexin V flow cytometry analysis done with 250 nmol/L LNS8801 and/or (C) 1 μmol/L IREα inhibitor Kira6 and 5 μmol/L PERK inhibitor GSK414 for 24 hours. Three replicates were used per condition. P values in C and D were calculated via one-way ANOVA with multiple comparisons (*, P ≤ 0.05; **, P ≤ 0.01; ***, P ≤ 0.001; ****, P ≤ 0.0001).
FIGURE 5 from LNS8801 inhibits Acute Myeloid Leukemia by Inducing the Production of Reactive Oxygen Species and Activating the Endoplasmic Reticulum Stress Pathway
Authors: Lee Inyoung , Doepner Miriam , Weissenrieder Jillian , Majer Ariana D. , Mercado Sophia , Estell Angela , Natale Christopher A. , Sung Pamela J. , Foskett J. Kevin , Carroll Martin P. , Ridky Todd W.
Published: August 2023

ROS induction mediates LNS8801-induced cell death. Representative DCF histogram (A) and summary graph (B) of median fluorescence intensity (MFI) of U937 cells treated with 250 nmol/L LNS8801. Representative DCF histogram (C) and summary graph (D) of MFI of MOLM14 cells treated with 250 nmol/L LNS8801. Three replicates were analyzed per condition. MFI DCF (E) and annexin V+ flow cytometry analysis (F) of U937 cells treated with 4 mmol/L NAC and/or 250 nmol/L LNS8801. MFI DCF (G) and annexin V+ flow cytometry analysis (H) of MOLM14 cells treated with 4 mmol/L NAC and/or 250 nmol/L LNS8801. Cells were pretreated with NAC or vehicle for 1 hour, followed by an 8-hour incubation with LNS8801 or vehicle for MFI DCF measurements. Cells were pretreated with 4 mmol/L NAC or vehicle for 1 hour, followed by 24-hour treatment of 250 nmol/L LNS8801 or vehicle for annexin V+ measurements. Statistical analysis was done via one-way ANOVA with multiple comparisons was used for B, D, and E–H (*, P ≤ 0.05; **, P ≤ 0.01; ***, P ≤ 0.001; ****, P ≤ 0.0001).
FIGURE 3 from LNS8801 inhibits Acute Myeloid Leukemia by Inducing the Production of Reactive Oxygen Species and Activating the Endoplasmic Reticulum Stress Pathway
Authors: Lee Inyoung , Doepner Miriam , Weissenrieder Jillian , Majer Ariana D. , Mercado Sophia , Estell Angela , Natale Christopher A. , Sung Pamela J. , Foskett J. Kevin , Carroll Martin P. , Ridky Todd W.
Published: August 2023

LNS8801 inhibits AML independently of canonical GPER signaling. Concentration–response curves done with LNS8801 and estradiol (E2) in U937 (A) and MOLM14 (B). Cells were incubated for 72 hours. Proliferation assay performed with 125 nmol/L LNS8801 and/or 1 μmol/L G36 in U937 (C) and MOLM14 (D). Five replicates were used per condition. Cells were incubated for 72 hours. E, LNS8801 concentration–response curve in MOLM14 GPER knockdown cells. Representative Western blots show GPER expression in knockdown cells. Full blot is available in Supplementary Fig. S4. One-way ANOVA with multiple comparisons was used to calculate P values for C and D (*, P ≤ 0.05; **, P ≤ 0.01; ***, P ≤ 0.001; ****, P ≤ 0.0001).
Age-Related Prevalence of Open Ductus Arteriosus in Full-Term Newborns
Authors: Mariager Anton Friis , Hammeken Alberte , Malham Mikkel , Raja Anna Axelsson , Sellmer Anna , Skjellerup Signe Levring , Raja Raheel Altaf , Navne Johan , Sillesen Anne-Sophie , Vejlstrup Niels , Bundgaard Henning , Iversen Kasper Karmark , Garne Ester , Jeppesen Dorthe Lisbeth
Published: August 2023

Background: The ductus arteriosus is part of the fetal circulation. Normally, the vessel closes during the cardiac transition. Delayed closure is associated with complications. The aim of this study was to evaluate the age-related prevalence of open ductus arteriosus in full-term neonates. Methods: Echocardiograms were collected in the population study, the Copenhagen Baby Heart Study. The present study included full-term neonates with an echocardiogram performed within 28 days after birth. All echocardiograms were reviewed to assess ductus arteriosus patency. Results: A total of 21,649 neonates were included. In neonates examined at day zero and day seven, an open ductus arteriosus was found in 36% and 0.6%, respectively. Beyond day seven, the prevalence remained stable at 0.6%. Conclusion: More than one-third of full-term neonates had an open ductus arteriosus on the first day of life, declining rapidly within the first week and stabilizing below 1% after day seven.
Analysis of Fractional Cerebral Oxygen Extraction in Preterm Infants during the Kangaroo Care
Authors: Solaz-García Álvaro , Sánchez-Illana Ángel , Lara-Cantón Inmaculada , Montejano-Lozoya Raimunda , Gimeno-Navarro Ana , Pinilla-González Alejandro , Torrejón-Rodríguez Laura , Vento Maximo , Sáenz-González Pilar
Published: August 2023

Introduction: We aimed to investigate the cerebral fractional tissue oxygen extraction (FtOE) during kangaroo care (KC) in premature infants and compare cardiorespiratory stability and hypoxic or bradycardic events between KC and incubator care. Methods: A single-center prospective observational study was carried out at the NICU of a level 3 perinatal center. Preterm infants <32 weeks gestational age were subjected to KC. Patients were subjected to continuous monitoring of regional cerebral oxygen saturation (rScO2), peripheral oxygen saturation (SpO2), and heart rate (HR) during KC, before KC (pre-KC), and after KC (post-KC). The monitoring data were stored and exported to MATLAB for synchronization and signal analysis including the calculation of the FtOE and events analysis (i.e., desaturations and bradycardias counts and anormal values). Furthermore, the event counts and the mean SpO2, HR, rScO2, and FtOE were compared between studied periods employing the Wilcoxon rank-sum test and the Friedman test, respectively. Results: A total of forty-three KC sessions with their corresponding pre-KC and post-KC segments were analyzed. The distributions of the SpO2, HR, rScO2, and FtOE showed different patterns according to the respiratory support, but not differences between the studied periods were detected. Accordingly, no significant differences in monitoring events were evidenced. However, cerebral metabolic demand (FtOE) was significantly lower during KC compared with post-KC (p = 0.019). Conclusion: Premature infants remain clinically stable during KC. Moreover, cerebral oxygenation is significantly higher and cerebral tissular oxygen extraction is significantly lower during KC compared with incubator care in post-KC. No differences in HR and SpO2 were shown. This novel data analysis methodology could be expanded to other clinical situations.