bluuebunny/crossref_metadata_2025 huggingface dataset:
Direction-optimizing Label Propagation Framework for Structure Detection in Graphs: Design, Implementation, and Experimental Analysis
Authors: Liu Xu , Lumsdaine Andrew , Halappanavar Mahantesh , Barker Kevin , Gebremedhin Assefaw
Published: October 2022

Label Propagation is not only a well-known machine learning algorithm for classification but also an effective method for discovering communities and connected components in networks. We propose a new Direction-optimizing Label Propagation Algorithm (DOLPA) framework that enhances the performance of the standard Label Propagation Algorithm (LPA), increases its scalability, and extends its versatility and application scope. As a central feature, the DOLPA framework relies on the use of
frontiers
and alternates between label
push
and label
pull
operations to attain high performance. It is formulated in such a way that the same basic algorithm can be used for finding communities or connected components in graphs by only changing the objective function used. Additionally, DOLPA has parameters for tuning the processing order of vertices in a graph to reduce the number of edges visited and improve the quality of solution obtained. We present the design and implementation of the enhanced algorithm as well as our shared-memory parallelization of it using OpenMP. We also present an extensive experimental evaluation of our implementations using the LFR benchmark and real-world networks drawn from various domains. Compared with an implementation of LPA for community detection available in a widely used network analysis software, we achieve at most five times the F-Score while maintaining similar runtime for graphs with overlapping communities. We also compare DOLPA against an implementation of the Louvain method for community detection using the same LFR-graphs and show that DOLPA achieves about three times the F-Score at just 10% of the runtime. For connected component decomposition, our algorithm achieves orders of magnitude speedups over the basic LP-based algorithm on large-diameter graphs, up to 13.2× speedup over the Shiloach-Vishkin algorithm, and up to 1.6× speedup over Afforest on an Intel Xeon processor using 40 threads.
Local Eyebrow Feature Attention Network for Masked Face Recognition
Authors: Huang Baojin , Wang Zhongyuan , Wang Guangcheng , Han Zhen , Jiang Kui
Published: October 2022

During the COVID-19 coronavirus epidemic, wearing masks has become increasingly popular. Traditional occlusion face recognition algorithms are almost ineffective for such heavy mask occlusion. Therefore, it is urgent to improve the recognition performance of the existing face recognition technology on masked faces. Due to the limited visible feature points of the masked face image relative to the normal face image, we have to exploit the identification potential of eyebrow (referring to eyes and brows) features. This article proposes a local eyebrow feature attention network for masked face recognition, which consists of feature extraction, eyebrow region pooling, and feature fusion. To highlight the eyebrow region, we first use the eyebrow region pooling to separate the local features of eyebrows from the learned overall facial features. We then make full use of the symmetry of left and right eyebrows to emphasize their discriminant ability, due to the inadequate fine information of the low-resolution eyebrows. In particular, in view of the symmetrical similarity between eyebrow pairs and the subordinate relationship between facial components and the whole, we propose a feature fusion model based on graph convolutional network (GCN) to learn the feature association structure of eye features, brow features, and global facial features. We construct the benchmark datasets for masked face recognition to validate our approach, including real-world masked face recognition dataset (RMFRD) and synthetic masked face recognition dataset (SMFRD). Extensive experimental results on both public datasets and our built masked face datasets show that our approach significantly outperforms the state-of-the-arts.
Micro-Electrochemical Aspects of the Effects of Temperature on Pit Initiation at MnS Inclusion in Type 304 Stainless Steel
Authors: Takayama Riku , Nishimoto Masashi , Muto Izumi , Sugawara Yu
Published: October 2022

In 1 M NaCl, the pitting potentials of resulfurized Type 304 stainless steel decreased as the temperature increased from 25 °C to 75 °C. The dissolution potential of MnS in 0.1 M Na2SO4 also decreased with increase in temperature. As the macroscale pitting potentials at all temperatures ranged within the dissolution potential range of MnS, the decrease in MnS dissolution potential was critical in determining the decrease in pitting potentials at high temperatures. However, in 1 M NaCl, the microscale pitting potentials exceeded those of the macroscale pitting: pits were generated at the boundaries of the MnS and steel matrix at 25 and 50 °C, but at 75 °C, pitting occurred in a deeper portion of the MnS inclusion. The formation of an occluded geometry is essential for pitting; however, because the dissolution rate and potential of MnS vary with temperature, the shape and location of the occluded geometry at inclusions as well are expected to vary with temperature. The depassivation pH of Type 304 stainless steel in 1 M NaCl–10 mM Na2S2O3 increased from 2 to approximately 3 at temperatures from 25 °C to 75 °C. The dissolved MnS species appeared to significantly influence the decrease in pitting potential.
Chloride transporters controlling neuronal excitability
Authors: Pressey Jessica C. , de Saint-Rome Miranda , Raveendran Vineeth A. , Woodin Melanie A.
Published: October 2022

Synaptic inhibition plays a crucial role in regulating neuronal excitability, which is the foundation of nervous system function. This inhibition is largely mediated by the neurotransmitters GABA and glycine that activate Cl−-permeable ion channels, which means that the strength of inhibition depends on the Cl− gradient across the membrane. In neurons, the Cl− gradient is primarily mediated by two secondarily active cation-chloride cotransporters (CCCs), NKCC1 and KCC2. CCC-mediated regulation of the neuronal Cl− gradient is critical for healthy brain function, as dysregulation of CCCs has emerged as a key mechanism underlying neurological disorders including epilepsy, neuropathic pain, and autism spectrum disorder. This review begins with an overview of neuronal chloride transporters before explaining the dependent relationship between these CCCs, Cl− regulation, and inhibitory synaptic transmission. We then discuss the evidence for how CCCs can be regulated, including by activity and their protein interactions, which underlie inhibitory synaptic plasticity. For readers who may be interested in conducting experiments on CCCs and neuronal excitability, we have included a section on techniques for estimating and recording intracellular Cl−, including their advantages and limitations. Although the focus of this review is on neurons, we also examine how Cl− is regulated in glial cells, which in turn regulate neuronal excitability through the tight relationship between this nonneuronal cell type and synapses. Finally, we discuss the relatively extensive and growing literature on how CCC-mediated neuronal excitability contributes to neurological disorders.
Pixel-Boundary-Dependent Segmentation Method for Early Detection of Diabetic Retinopathy
Authors: Sandhya S. G. , Suhasini A. , Hu Yu-Chen
Published: October 2022

Early and precise detection of diabetic retinopathy prevents vision impairments through computer-aided clinical procedures. Identifying the symptoms and processing those by using sophisticated clinical procedures reduces hemorrhage kind of risks. The input diabetic retinopathy images are influenced by using computer vision-based processes for segmentation and classification through feature extractions. In this article, a delimiting segmentation using knowledge learning (DS-KL) is introduced for classifying and detecting exudate regions by using varying histograms. The input image is identified for its histogram changes from the feature-dependent segmentation process. Depending on the training knowledge from multiple inputs with different exudate regions, the segmentation is performed. This segmentation identifies infected and noninfected regions across the delimiting pixel boundaries. The knowledge-learning process stores the newly identified exudate region for training and pixel correlation. The recurrent training improves the segmentation accuracy with precise detection and limited errors.
Endoscopic Nipple- or Skin-Sparing Mastectomy and Immediate Breast Reconstruction with Endoscopic Harvesting of the Latissimus Dorsi Flap: A Preliminary Experience of an Innovative Technique
Authors: Feng Yu , Wen Nan , Liang Faqing , Zhou Jiao , Qin Xiangquan , Liu Xinran , Li Juan , Qiu Mengxue , Yang Huanzuo , Du Zhenggui
Published: October 2022

Background. Endoscopic nipple- or skin-sparing mastectomy (E-N/SSM) and endoscopic latissimus dorsi muscle flap (E-LDMF) harvest have been operational difficulties over decades. The aim of this study was to describe the preliminary outcomes of our novel surgical technique, which allows the performance of E-N/SSM and E-LDMF harvest for immediate breast reconstruction (IBR) through a single cosmetic axillary incision for breast cancer patients. Methods. This prospective study included 20 breast cancer patients who underwent E-N/SSM and E-LDMF harvesting through a single axillary incision in our hospital from September 2020 to June 2022. The outcomes were statistically calculated, including patient characteristics, operative data, complication rate, hospital length of stay and costs, and patient-reported outcomes. Results. A total of 20 breast cancer patients underwent our sufficiently mature novel endoscopy technique. The mean LD flap harvest time was 96.5 ± 25.3 min, the mean operation time was 262.6 ± 54.4 min, and the average length of LDMF was 26.9 ± 3.1. During the median follow-up time of 7.5 months, 4 patients developed donor-site seroma. One of them was also complicated by hypopigmentation of the nipple areola, and one of them suffered from breast cellulitis. No bleeding or flap necrosis happened. No tumor recurrence or metastasis was found until the last follow-up. In the BREAST-Q evaluation, although they gave a lower score beginning at 1-month post-operation than preoperatively (

P
>
0.05

, except for physical well-being: chest and physical well-being: back and shoulder,

P
<
0.01

), there was an uptrend at 3 months postoperatively. Because of the hidden and short incision, the mean score of the appearance scale of the SCAR-Q at 3 months post-operation was 74.2 ± 8.8. Conclusions. The novel endoscopy technique, which was first reported to perform lymph node surgery, N/SSM, and LDMF harvesting in an operation for breast cancer patients through a single axillary incision, is associated with a shorter surgery time, lower complication rates, and better patient-reported outcomes.
Study on the Constant Resistance Coupling Support Technology for Rock Column at the Intersection Point of Deep Soft Rock Large Section Roadway: A Case Study in China
Authors: Xu Huichen , Zhang Yong , Yang Jinkun , Li Jiangbing , Sun Xiaoming , Xie Cheng
Published: October 2022

In order to solve the problem on the serious deformation and failure of the rock column at the intersection of large cross sections in Shiyakou coal mine, based on field engineering geomechanics analysis, theoretical analysis, and three-dimensional numerical simulation, combined with the mutual coupling between the constant resistance coupling support cable and surrounding rock, a dual-control constant-resistance coupling control technology with high prestressed constant resistance coupling support cable as the core solution is proposed. The field engineering practice and field monitoring data show that the dual-control constant resistance coupling support control technology has a good control effect on the deformation of the rock column at the large cross section intersection of the deep soft rock roadway and can be effectively used in the engineering practice.
The Effect of Sumac Fruit on Serum Lipids and Body Mass Index in Hemodialysis Patients
Authors: Alahnoori Fereshteh , Toulabi Tahereh , Kordestani-Moghadam Parastou , Jafari Pour Fatemeh , Khatereh Anbari  , Salimikia Iraj
Published: October 2022

Background. Sumac fruit is an antioxidant and reduces serum triglyceride (TG) and cholesterol (CHOL) levels. Therefore, this study aimed to investigate the effect of sumac fruit on serum lipids and body mass index (BMI) of hemodialysis (HD) patients. Materials and Methods. This triple-blind randomized clinical trial study was conducted for 12 weeks on HD patients. Participants were randomly divided into three groups of 2-gram sumac (N = 40), 3-gram sumac (N = 40), and placebo (N = 40) by nonprobability consecutive sampling and stratified block randomization method based on inclusion criteria. Serum lipids and BMI were measured at the beginning of the study and also at the end of the sixth and the twelfth weeks. The physical activity and 24-hour dietary recall questionnaires were used to collect data. Results. No significant difference was found between the level of nutrient and micronutrient intake (

P
>
0.05

), physical activity (

P
=
0.159

), and BMI (

P
=
0.718

) of patients in the three groups before and after the intervention. However, the difference in serum low-density lipoprotein (LDL) levels in each studied group was significant over time (

P
<
0.001

). The difference was not statistically significant between the groups before the intervention, 6 and 12 weeks after the intervention (group effect), and between the study groups over time (time-group interaction). No statistically significant difference was observed between the mean levels of TG (

P
=
0.875

), CHOL level (

P
=
0.969

), LDL level (

P
=
0.998

), high-density lipoprotein (HDL) level (

P
=
0.136

), and BMI (

P
=
0.608

) in the groups over time. Conclusion. Consumption of sumac fruit significantly changed the LDL level over time. Although BMI and serum lipids changed in HD patients, these changes were not significant. Future studies are needed to determine the effective dose of sumac and any dose increase should take toxicity into account and consider a larger sample size and longer intervention and follow-up times.
Flexible Least Squares Algorithm for Switching Models
Authors: Ni Yunxia , Lv Lixing , Ji Yuejiang
Published: October 2022

The self‐organizing model and expectation‐maximization method are two traditional identification methods for switching models. They interactively update the parameters and model identities based on offline algorithms. In this paper, we propose a flexible recursive least squares algorithm which constructs the cost function based on two kinds of errors: the neighboring two‐parameter estimation errors and the output estimation errors. Such an algorithm has several advantages over the two traditional identification algorithms: it (1) can estimate the parameters of all the sub‐models without prior knowledge of the model identities; (2) has less computational efforts; and (3) can update the parameters with newly arrived data. The convergence properties and simulation examples are provided to illustrate the efficiency of the algorithm.
Characteristics of Gut Microbiota in Female Patients with Diabetic Microvascular Complications
Authors: Gao Shan , Zhao Li-hua , Tian Xue , Kong Mo-wei , He Jian-qiu , Ge Xiao-chun , Liu Xiao-yan , Feng Zeng-bin , Gao Yu
Published: October 2022

Objective. To explore the characteristics and analyze the gut microbiota in female patients with diabetic microvascular complications (DMC). Methods. Thirty-seven female patients with type 2 diabetes mellitus (T2DM) were included in the study. These patients were divided into DM group with microvascular complications (T2DM-MC,

n
=
17

) and no microvascular complications group (T2DM-0,

n
=
20

). Patients in the microvascular group presented with the involvement of at least one of the following: kidney, retinal, or peripheral nerves. Using real-time fluorescence quantitative polymerase chain reaction, fecal samples from the two groups were tested for Bacteroides, Prevotella, Bifidobacterium spp, Lactobacillus, Faecalibacterium prausnitzii, Enterococcus spp, Eubacterium rectale, Veillonellaceae, Clostridium leptum, and Roseburia inulinivorans. Levels of fasting and 2 h postprandial blood glucose, glycosylated hemoglobin (HbA1c), lipids, and creatinine were determined to explore the correlation between gut microbiota and blood sugar. Mann–Whitney

U

test was used to analyze the differences between the two groups. Spearman correlation analysis was used to determine the correlation between gut microbiota and blood glucose. Multifactor logistic regression was used to analyze the risk factors for DMC. Results. The HbA1c levels in the T2DM-MC group were higher than those in the T2DM-0 group. The abundances of Bacteroides and Enterococcus spp in the T2DM-MC group were higher than that in the T2DM-0 group. The abundances of Bacteroides and Enterococcus spp in the T2DM-MC group were lower than that in the T2DM-0 group. Spearman’s correlation analysis showed that Bacteroides, Prevotella, Lactobacillus, C. leptum, and R. inulinivorans were related to the levels of HbA1c or blood glucose (

p
<
0.05

). Logistic regression analysis showed that after adjusting for confounding factors such as age, body mass index, family history, HbA1c, hypertension, dyslipidemia, and creatinine, Bacteroides remained an independent risk factor in female patients with DMC. Conclusion. Gut microbiota is related to blood glucose levels. Female patients with DMC experience gut microbiota disorders. The abundances of Bacteroidesare related to DMC, and the abundances of intestinal flora may affect the blood sugar levels of the body.
Correlation between the Neutrophil-to-Lymphocyte Ratio and Multiple Sclerosis: Recent Understanding and Potential Application Perspectives
Authors: Zhou Qingqing , Jia Rui , Dang Jingxia
Published: October 2022

Multiple sclerosis (MS) is a chronic debilitating immune-mediated disease of the central nervous system, which causes demyelination and neuroaxonal damage. Low-grade systemic inflammation has been considered to lead to pathogenesis owing to the amplification of pathogenic immune response activation. However, there is a shortage of reliable systemic inflammatory biomarkers to predict the disease activity and progression of MS. In MS patients, a series of cytokines and chemokines promote the proliferation of neutrophils and lymphocytes and their transfer to the central nervous system. The neutrophil-to-lymphocyte ratio (NLR), which combines the information of the inherent and adaptive parts of the immune system, represents a reliable measure of the inflammatory burden. In this review, we aimed to discuss the inflammatory response in MS, mainly the function of lymphocytes and neutrophils, which can be implemented in the utility of NLR as a diagnostic tool in MS patients. The underlying pathophysiology is highlighted to identify new potential targets for neuroprotection and to develop novel therapeutic strategies.
A Graph Convolution Neural Network-Based Framework for Communication Network K-Terminal Reliability Estimation
Authors: Zhang Zi-xuan , Xu You-wei , Cao Yi-ning , Yang Lin
Published: October 2022

The exact computation of network k-terminal reliability is an NP-hard problem, and many approximation methods have been proposed as alternatives, among which the neural network-based approaches are believed to be the most effective and promising. However, the existing neural network-based methods either ignore the local structures in the network topology or process the local structures as Euclidean data, while the network topology represented by the graph is in fact non-Euclidean. Seeing that the Graph Convolution Neural network (GCN) is a generalization of convolution operators onto non-Euclidean data structure, in an effort to fill in the gap, this paper proposes a GCN-based framework for the estimation of communication network reliability. First, a dataset with sufficient sample size is constructed, by calculating the k-terminal reliability via the exact contraction-deletion method for the generated network samples. Then, an estimation model based on GCN is built, where several graph convolution layers process input information and extract node-level structural features from the network topology, a concatenation layer fuses the structural features into a graph-level representation feature, and a multi-layer perceptron computes the k-terminal reliability as output. To demonstrate the practicality and rationality of our proposed model, comparative experiments are carried out on 12 datasets, the results of which show that our proposed GCN model has an average of 59.60% and 57.52% improvement over existing methods on homogeneous datasets and heterogeneous datasets, respectively.
General Phenotype of NADase Induction by CLI Treatment in Streptococcus pyogenes
Authors: Tatsuno Ichiro , Isaka Masanori , Hasegawa Tadao
Published: October 2022

The administration of high-dose clindamycin (CLI) along with penicillin is recommended for the treatment of streptococcal toxic-shock syndrome (STSS). However, we previously reported that a “subinhibitory dose” of CLI induced the expression of the NAD-glycohydrolase (NADase) exotoxin in an emm1-type Streptococcus pyogenes 1529 strain isolated from an STSS patient. In this study, we examine NADase induction by CLI treatment using an extracellular NADase activity assay instead of the previous two-dimensional gel electrophoresis assay. The examination revealed that CLI administration can induce NADase expression in a dose-dependent manner. We analyzed 23 CLI-susceptible strains (5 emm1 strains, 6 emm3 strains, 3 emm4 strains, 1 emm6 strain, 3 emm12 strains, 1 emm28 strain, and 4 emm89 strains), and 19 of the 23 strains showed similar NADase induction phenotypes to that shown in strain 1529. These results indicate that NADase induction by CLI treatment is not restricted to specific strains and it could be a standard phenotype among CLI-susceptible S. pyogenes strains. We also analyzed four CLI-resistant strains. All four strains showed increased extracellular NADase activities at high concentrations of CLI that did not inhibit bacterial growth. These results indicated that the subinhibitory dose of CLI was not the critical factor for NADase induction.
Evolutionary Design of Machining Fixture Layout for Thin-Walled Structure
Authors: Liu Yang , Guan Shixi , Zhao Hong , Liu Waner , Duan Liancheng , Sha Yedian
Published: October 2022

Fixture layout for machining thin-walled structures plays an important role in fixture performance. This work focuses on the optimization design of machining fixture layout including clamp layout and the layout of support heads. A universal optimization methodology that can automatically generate the optimal machining fixture layout is proposed. The optimization of fixture layout is implemented based on the criteria of minimizing maximum deflection of the thin-walled workpiece while remain relatively small torque caused by the clamping tables. An evolutionary algorithm is employed to solve the fixture layout optimization for the optimal solution. The optimal position of the support heads and the layout of clamping tables obtained from this work vary along with the change of cutting force. To validate the proposed optimization methodology, a fixture layout design for a typical thin-walled structure is optimized as an example. The case study demonstrates the application of the proposed approach in the fixture layout design for thin-walled structures, which is beneficial to design an optimal fixture layout.
Differential Sandwich Theorems for Atangana–Baleanu Fractional Integral Applied to Extended Multiplier Transformation
Authors: Alina Alb Lupaş , Hazarika Bipan
Published: October 2022

In this paper we derive subordination and superordination results regarding the Atangana–Baleanu fractional integral applied to multiplier transformation and we give several differential sandwich-type theorems. Then, we apply the Atangana–Baleanu fractional integral to extended multiplier transformation on the class

A
ζ
∗

of normalized analytic functions and we derive strong differential subordination and strong differential superordination results regarding the extended new operator and we give the corresponding differential sandwich-type theorems from the first part of the paper.
A Clinical Nomogram Based on the Triglyceride-Glucose Index to Predict Contrast-Induced Acute Kidney Injury after Percutaneous Intervention in Patients with Acute Coronary Syndrome with Diabetes Mellitus
Authors: Hu Yue , Wang Xiaotong , Xiao Shengjue , Sun Na , Huan Chunyan , Wu Huimin , Guo Minjia , Xu Tao , Pan Defeng
Published: October 2022

The aim of the study was to investigate the factors influencing contrast-induced acute kidney injury (CI-AKI) after percutaneous intervention (PCI) in patients with acute coronary syndrome (ACS) with diabetes mellitus (DM). A total of 1073 patients with ACS combined with DM who underwent PCI at the Affiliated Hospital of Xuzhou Medical University were included in this study. We divided the patients into the CI-AKI and non-CI-AKI groups according to whether CI-AKI occurred or not. The patients were then randomly assigned to the training and validation sets at a proportion of 7 : 3. Based on the results of the LASSO regression and multivariate analyses, we determined that the subtypes of ACS, age, multivessel coronary artery disease, hyperuricemia, low-density lipoprotein cholesterol, triglyceride-glucose index, and estimated glomerular filtration rate were independent predictors on CI-AKI after PCI in patients with ACS combined with DM. Using the above indicators to develop the nomogram, the AUC-ROC of the training and validation sets were calculated to be 0.811 (95% confidence interval (CI): 0.766-0.844) and 0.773 (95% CI: 0.712-0.829), respectively, indicating high prediction efficiency. After verification by the Bootstrap internal verification, we found that the calibration curves showed good agreement between the nomogram predicted and observed values. And the DCA results showed that the nomogram had a high clinical application. In conclusion, we constructed and validated the nomogram to predict CI-AKI risk after PCI in patients with ACS and DM. The model can provide a scientific reference for predicting the occurrence of CI-AKI and improving the prognosis of patients.
Lipid Profiles Obtained from MALDI Mass Spectrometric Imaging in Liver Cancer Metastasis Model
Authors: Kwon Hee Jung , Oh Joo Yeon , Lee Kwang Seon , Lim Hyun Kyung , Lee Jisun , Yoon Hye-Ran , Jung Joohee
Published: October 2022

Liver cancer metastasis is known to be a poor prognosis and a leading cause of mortality. To overcome low therapeutic efficacy, understanding the physiological properties of liver cancer metastasis is required. However, the metastatic lesion is heterogeneous and complex. We investigate the distribution of lipids using matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) in an experimental metastasis model. We obtained the differentially expressed mass peaks in comparison between normal sites and metastatic lesions. The relationship of mass to charge ratio (m/z) and intensity were measured, m/z-indicated species were analyzed by MALDI-MS/MS analysis, and identification of these mass species was confirmed using the METASPACEannotation platform and Lipid Maps®. MALDI-MSI at m/z 725.6, 734.6, 735.6, 741.6, 742.6, 744.6, 756.6, and 772.6 showed significantly higher intensity, consistent with the metastatic lesions in hematoxylin-stained tissues. Sphingomyelin SM [d18:0/16:1], phosphatidylcholine (PC) [32:0], PC [31:0], PC [31:1], and PE [36:2] were highly expressed in metastatic lesions. Our results could provide information for understanding metastatic lesions. It suggests that the found lipids could be a biomarker for the diagnosis of metastatic lesions.
Color Image Encryption Based on Deep Learning and Block Embedding
Authors: Liu Yi , Cen Gang , Xu Bijun , Wang Xiaogang
Published: October 2022

Because of the advent of the information age, digital multimedia data are mainly transmitted through the Internet. Image is one of the most popular digital multimedia data. Therefore, this paper proposes a block-based key embedding method and a color image encryption scheme based on deep learning with this method. By using a neural network model to predict the initial chaotic sequence, the key data generated by prediction are encrypted to the color image in layers and blocks. This paper proposed the color image encryption scheme time complexity

O

n

2

, which is simple and effective. Simulation results show that the proposed scheme exhibits good statistical properties with information entropy mean close to eight and correlation coefficient close to zero. Good robustness to common image attacks like noise addition and cropping. Excellent encryption performance includes enormous key space and low PSNR.
Coordinated Control of an Islanded Microintegrated Energy System with an Electrolyzer and Micro-Gas Turbine
Authors: Wu Huaren
Published: October 2022

Microintegrated energy systems (MIESs) can be disconnected from power distribution systems during power system faults. This paper develops a control scheme for an islanded MIES. The VSC inverter controls the AC bus voltage and frequency using a modified AC voltage regulator and a modified frequency regulator. The control structures of the power-to-gas and PMSG-based microturbine generator (MTG) systems are improved. Renewable generation always runs at the maximum power point. The surplus renewable energy in the MIES can be converted into natural gas using power-to-gas, and the MIES can make full use of renewable energy. The proposed coordinated control scheme of the electrolyzer and the supercapacitor can achieve a power balance of the islanded MIES and reduce the DC-link voltage fluctuation. A micro-gas turbine can provide electric energy to the load and enhance distribution system resilience. A coordinated control scheme of the MTG and the supercapacitor is developed to improve MIES operation. A feature of this paper is the research on fault ride-through of the islanded MIES. A fault ride-through strategy is proposed, where the AC voltage of the VSC inverter is reduced to limit the short-circuit current during AC system faults. Islanded MIES simulations are conducted in a MATLAB/Simulink environment to test the control scheme. The simulation results verify the effectiveness of the control scheme during normal operation and failure.
Implementation and Evaluation of a Dynamic Neck Brace Rehabilitation Device Prototype
Authors: Ibrahem Mostafa El-Hussien , El-Wakad Mohamed Tarek , El-Mohandes Mostafa Saied , Sami Sherif A.
Published: October 2022

Rehabilitation assistive devices for head/neck pain treatment cannot allow dynamic changes in position and orientation of the head/neck. Moreover, such devices can neither be used simultaneously nor can they assess the patients’ head/neck conditions. This paper aims at designing and implementing a novel dynamic head/neck brace that provides static and dynamic support and/or traction at symmetric and asymmetric positions. This device also provides assessments of the head/neck stiffness for the purpose of fulfilling diagnoses of the head/neck disorders. The device was used and evaluated for its range of motion and its symmetric traction capability using two control modalities. In addition, it was also evaluated in determining the stiffness of the head/neck throughout a simulating mechanical model involved in a set of springs. The device could apply right/left lateral bending to the head/neck ranged −6.97 ± 0.01° to 7.02 ± 0.01° with accuracies of 99.89% and 99.48%, and flexion/extension ranged −8.10 ± 0.02° to 8.12 ± 0.01° with accuracies of 99.57% and 99.42%, respectively, throughout a traction phase of 20 mm. The practical measurements through the symmetric traction tests showed some deviations as compared to that being calculated. Such deviations were greater in flexion/extension rather than the right/left lateral bending. The mean of the obtained error was less than 0.34° for all situations of tests. The accuracies of stiffness measurement of the mechanical model were 99.78% and 99.96%, respectively, throughout performing stair and step tests. The paper presented a novel design of a dynamic head/neck brace that provides support and/or traction to any head/neck positions and capable of evaluating the head/neck stiffness during cervical traction.
Bradykinin and Galectin-3 in Survived and Deceased Patients with COVID-19 Pneumonia: An Increasingly Promising Biochemical Target
Authors: Turnic Tamara Nikolic , Popadic Viseslav , Klasnja Slobodan , Sekulic Ana , Nikolic Novica , Zivkovic Vladimir , Jeremic Nevena , Andjic Marijana , Draginic Nevena , Srejovic Ivan , Jeremic Jovana , Zdravkovic Marija , Jakovljevic Vladimir
Published: October 2022

Introduction. There are still no definite curative or preventive strategies for COVID-19 disease. It is crucial to fully comprehend the pathogenesis of COVID-19 infection so that we can develop expedient pharmacological protocols. While the impact of cytokine storm on COVID-19 severity has been one of the most tested hypotheses, the role of bradykinin and various other oxidative stress markers has been relatively under-researched. Their levels can be determined immediately after a hospital admission so they could be used as early predictors of the further development of the disease. Aim. The study aims at evaluating the possibility of using bradykinin and galectin-3 levels as early predictors that COVID-19 disease will progress into a severe case. Material and methods. The study was conducted as a prospective cross-sectional study. It included 47 consecutive adult patients with confirmed SARS-CoV-2 infection and COVID-19 pneumonia. All study subjects were admitted for a hospital treatment to the tertiary Clinical Hospital Center Bezanijska kosa, Belgrade, Serbia on June 2021. The blood samples were collected at the patients’ admission. The analyses of demographic, radiological, and clinical data were later conducted for both groups (the deceased patients and those who survived). In addition, we analyzed the potential relations between the outcome and the levels of bradykinin and galectin-3 measured immediately after the patients were admitted to the hospital. Results. The patients who passed away were predominantly older men with comorbidities. We recorded higher CT scores in the deceased patients and the significantly higher levels of urea, creatinine, CK, troponine, CRP, and other laboratory markers. They stayed at the ICU unit longer and required mechanical ventilation more frequently than the patients who survived. On the other hand, no differences were recorded in the time periods passing from the onset of the systems to the hospital admissions. Finally, we can highlight several independent predictors of mortality in patients with COVID-19 pneumonia, including the following: (1) patients who are 50 or more years old, (2) with in-hospital stays are longer that 4 days, (3) bradykinin levels surpass 220000 pg/ml, (4) D-dimer, creatinine, and CRP are elevated, and (5) comorbidities were present (such as hypertension and diabetes). Conclusion. The present study strongly supports the bradykinin storm hypothesis. Since elevated bradykinin levels have been found in most COVID-19 cases with fatal outcomes, the future therapeutical strategies for COVID-19 have to be focused on reducing bradykinin serum concentrations.
A Novel Fractional Hausdorff Discrete Grey Model for Forecasting the Renewable Energy Consumption
Authors: Chen Yuzhen , Li Suzhen , Guo Shuangbing
Published: October 2022

Reducing carbon dioxide emissions and using renewable energy to replace fossil fuels have become an essential trend in future energy development. Renewable energy consumption has a significant impact on energy security so accurate prediction of renewable energy consumption can help the energy department formulate relevant policies and adjust the energy structure. Based on this, a novel Fractional Hausdorff Discrete Grey Model, abbreviated FHDGM (1,1), is developed in this study. The paper investigates the model’s characteristics. The fractional‐order r of the FHDGM (1,1) model is optimized using particle swarm optimization. Subsequently, through two empirical analyses, the prediction accuracy of the FHDGM (1,1) model is proven to be higher than that of other models. Finally, the proposed model is applied with a view to forecasting the consumption of renewable energy for the years 2021 to 2023 in three different areas: the Asia Pacific region, Europe, and the world. The study’s findings will offer crucial forecasting data for worldwide energy conservation and emission reduction initiatives.
Deep Echo State Network with Variable Memory Pattern for Solar Irradiance Prediction
Authors: Li Qian , Li Tao , Ouyang Jiangang , Yang Dayong , Guo Zhijun
Published: October 2022

Accurate solar irradiance prediction plays an important role in ensuring the security and stability of renewable energy systems. Solar irradiance modeling is usually a time‐dependent dynamic model. As a new kind of recurrent neural network, echo state network (ESN) shows excellent performance in the field of time series prediction. However, the memory length of classical ESN is fixed and finite, which makes it hard to map sufficient features of solar irradiance with long‐range dependency. Therefore, a novel deep echo state network with variable memory pattern (VMP‐DESN) is proposed in this brief. VMP‐DESN consists of multiple connected reservoirs in series, and there exist different types of memory modes in VMP‐DESN. To remember more input history information in the states, the time delay links are added in each reservoir and between every two reservoirs. The VMP‐DESN is more flexible to deal with different input signals due to its variable memory modes in the reservoir states. Additionally, the effect of different memory patterns on the VMP‐DESN performance is discussed in detail, including the antidisturbance ability, memory capacity, and prediction accuracy. Finally, the effectiveness of VMP‐DESN is evaluated by predicting the real solar irradiance task.
A Novel Prognostic Model for Patients with Primary Gastric Diffuse Large B-Cell Lymphoma
Authors: Lu Guangrong , Lin Zijian , Ruan Yejiao , Huang He , Lin Jiafeng , Pan Jialin
Published: October 2022

Objectives. Primary gastric diffuse large B-cell lymphoma (PG-DLBCL) is a common phenotype of extranodal non-Hodgkin’s lymphoma (NHL). This research aims to identify a model for predicting overall survival (OS) and cancer-specific survival (CSS) in PG-DLBCL. Methods. A total of 1716 patients diagnosed with PG-DLBCL between 1975 and 2017 were obtained from the SEER database and further randomly divided into the training and validating cohorts at a ratio of 7 : 3. Univariate and multivariate cox analyses were conducted to determine significant variables for the construction of nomogram. The performance of the model was then assessed by the concordance index (C-index), the calibration plot, and the area under the receiver operating characteristic (ROC) curve (AUC). Results. Multivariate analysis revealed that age, race, insurance status, Ann Arbor stage, marital status, chemotherapy, and radiation therapy all showed a significant association with OS and CSS. These characteristics were applied to build a nomogram. In the training cohort, the discrimination of nomogram for OS and CSS prediction was excellent (C-index = 0.764, 95% CI, 0.744–0.784 and C-index = 0.756, 95% CI, 0.732–0.780). The AUC of the nomogram for predicting 3- and 5-year OS was 0.779 and 0.784 and CSS was 0.765 and 0.772. Similar results were also observed in the internal validation set. Conclusions. We have successfully established a novel nomogram for predicting OS and CSS in PG-DLBCL patients with good accuracy, which can help physicians to quickly and accurately complete the evaluation of survival probability, risk stratification, and therapeutic strategy at diagnosis.
Inhibition of Wnt Signaling in Colon Cancer Cells via an Oral Drug that Facilitates TNIK Degradation
Authors: Zhou Kun , Cheong Jae Eun , Krishnaji Subrahmanian Tarakkad , Ghalali Aram , Fu Haojie , Sui Lufei , Alix-Panabières Catherine , Cayrefourcq Laure , Bielenberg Diane , Sun Lijun , Zetter Bruce
Published: October 2022

We have synthesized an oxetane derivative of the benzimidazole compound mebendazole (OBD9) with enhanced solubility and strong anticancer activity in multiple types of cancer cells, especially colorectal cancer. In this report, we provide evidence that OBD9 suppresses colorectal cancer growth by interfering with the Wnt signaling pathway, a main driver of cell growth in colorectal cancer. Specifically, we find that OBD9 induces autophagic degradation of TNIK (traf2 and Nck-interacting kinase), which promotes T-cell factor-4 (TCF4)/beta-catenin–mediated gene expression. Thus, OBD9 as a TNIK inhibitor blocks Wnt/beta-catenin signaling at the final step of transcriptional activation. We suggest that OBD9 provides a potential novel autophagy-mediated, Wnt-damping therapeutic strategy for the treatment of colorectal cancer.
Distinct Mechanisms of Mismatch-Repair Deficiency Delineate Two Modes of Response to Anti–PD-1 Immunotherapy in Endometrial Carcinoma
Authors: Chow Ryan D. , Michaels Tai , Bellone Stefania , Hartwich Tobias M.P. , Bonazzoli Elena , Iwasaki Akiko , Song Eric , Santin Alessandro D.
Published: October 2022

Mismatch repair–deficient (MMRd) cancers have varied responses to immune-checkpoint blockade (ICB). We conducted a phase II clinical trial of the PD-1 inhibitor pembrolizumab in 24 patients with MMRd endometrial cancer (NCT02899793). Patients with mutational MMRd tumors (6 patients) had higher response rates and longer survival than those with epigenetic MMRd tumors (18 patients). Mutation burden was higher in tumors with mutational MMRd compared with epigenetic MMRd; however, within each category of MMRd, mutation burden was not correlated with ICB response. Pretreatment JAK1 mutations were not associated with primary resistance to pembrolizumab. Longitudinal single-cell RNA-seq of circulating immune cells revealed contrasting modes of antitumor immunity for mutational versus epigenetic MMRd cancers. Whereas effector CD8+ T cells correlated with regression of mutational MMRd tumors, activated CD16+ NK cells were associated with ICB-responsive epigenetic MMRd tumors. These data highlight the interplay between tumor-intrinsic and tumor-extrinsic factors that influence ICB response.

Significance:

The molecular mechanism of MMRd is associated with response to anti–PD-1 immunotherapy in endometrial carcinoma. Tumors with epigenetic MMRd or mutational MMRd are correlated with NK cell or CD8+ T cell–driven immunity, respectively. Classifying tumors by the mechanism of MMRd may inform clinical decision-making regarding cancer immunotherapy.

This article is highlighted in the In This Issue feature, p. 247
Ketogenic-Diet Shake Containing Uncaria tomentosa-Associated Acute Interstitial Nephritis
Authors: Portalatin Gilda , Shettigar Shruti , Carrion-Rodriguez Astrid , Medikayala Sushma , Herlitz Leal , Sandy Dianne , Gebreselassie Surafel K. , Bobart Shane A.
Published: October 2022

Uncaria tomentosa is a plant that has been used in traditional medicine for its anti-inflammatory, immunomodulatory, and immunostimulant properties. As a result, it can be found in several over-the-counter supplements worldwide. Acute interstitial nephritis (AIN) can be due to an offending medication, infection, or autoimmunity. We present a case of a patient who was on a strict ketogenic diet, utilizing over-the-counter diet shakes containing the herbal supplement Uncaria tomentosa who developed acute kidney injury with a serum creatinine of 3.6 mg/dL up from a baseline of 0.7 mg/dL. Serological evaluation was negative, and kidney biopsy revealed interstitial inflammatory infiltrates including focally prominent eosinophils and multifocal tubulitis. Stopping the keto-diet shake containing Uncaria tomentosa and concomitant corticosteroid therapy resulted in improvement in kidney function to near baseline. To our knowledge, this is the only biopsy-proven case of AIN in the setting of Uncaria tomentosa use.
Refractive Corneal Lenticule Extraction on Previous Photorefractive Keratectomy, with Optical Coherence Tomography Study
Authors: Leccisotti Antonio , Fields Stefania V. , De Bartolo Giuseppe
Published: October 2022

We report the first case of refractive corneal lenticule extraction with the femtosecond laser application CLEAR as retreatment technique after previous laser vision correction. A 42-year-old woman, operated by bilateral photorefractive keratectomy (PRK) 19 years previously, with moderate dry eye, came for post-PRK regression and underwent correction of a residual myopia of −3 −0.5 × 159° D in the left eye by CLEAR. Surgery was uneventful, with a regular laser pattern and a normal dissection of the lenticule. At day 1, uncorrected visual acuity was 20/25; at 3 months, it was 20/20, with a refraction of +0.25 × 115° D. The cornea and interface were regular and transparent; no dry eye symptoms occurred. At 3 months, on optical coherence tomography, the treatment was well centered, the surgical interface was centrally regular, whereas the anterior profile of the stromal surface was slightly corrugated, compensated by a smooth epithelial surface. The present case demonstrates that myopia after PRK can be achieved by CLEAR; an irregular stromal surface may occur, not affecting the visual result in virtue of epithelial remodeling.
Central Serous Chorioretinopathy Development following Cessation of Terbinafine Treatment
Authors: Shmueli Or , Nitzan Itay , Averbukh Edward
Published: October 2022

This report describes a case of central serous chorioretinopathy (CSCR) occurring following cessation of terbinafine treatment. A 51-year-old man presented for a routine ophthalmic examination. He was treated with oral terbinafine for onychomycosis up to 3 months before the presentation. Spectral-domain optical coherence tomography (OCT) showed extrafoveal subretinal fluid in both eyes with small underlying pigment epithelial detachments. There were no additional relevant findings in the patient history or ocular examination. A diagnosis of CSCR was made. After 10 weeks without treatment, OCT demonstrated almost complete resolution of subretinal fluid in both eyes. The exact key ingredients of the perfect storm leading to CSCR in young, healthy individuals are still unknown. Here, we describe, to our knowledge, the first documented case, where the appearance of CSCR was apparently triggered by cessation of antifungal treatment. This unusual case may provoke further research that will bring us closer to understanding the mechanism behind the appearance of CSCR. It may also widen the scope of the routine anamnesis when dealing with patients newly diagnosed with this enigmatic condition.