bluuebunny/crossref_metadata_2025 huggingface dataset:
41 Assessment of the spatial distribution of CD4+ T cells subpopulations in the tumor microenvironment by Brightplex®, a sequential chromogenic multiplex assay
Authors: Collignon Aurelie , Trinh Alex , Olive Marion , Jaume Clémence , Chamourin Maïté , Sfeir Nour , Anselmo Dylan , Ramouz-Charpentier Raana , Culey Georgia , Haond Christophe , Galon Jerome , Fieschi-Meric Jacques
Published: November 2021

Background

Cancer immunotherapy reinvigorates tumor-specific T cell responses of CD8+ cytotoxic T lymphocytes that detect intracellular antigens that are presented by MHC class I molecules expressed by all tumor cell types. Because most tumors do not express MHC class II, the potential antitumor protective role of CD4 T cells, which bind MHC class II molecules on target cells, has been less studied. However, CD4+ T cells are also required for efficacious antitumor immunity; they are core components of adaptive immunity that differentiate into lineages responsible for effector activities. Both TH1 and TH2 cell types mediate antitumor immunity, although TH1 cells may be more potent due to the production of large amounts of IFN-γ, as well as chemokines that enhance the priming and expansion of CD8 cells. TH1 cells help in recruiting natural killer cells and type I macrophages to tumor sites, which can act in concert toward tumor eradication. The ability of TH2 cells to mobilize innate cells, may represent a general pathway for their impact on the host antitumor response. Tumor infiltrating TFH cells play a key role in immune cell recruitment to the tumor and in the formation of intratumoral follicular structures, which correlate with a positive prognosis. On the contrary, cells from the TH17 subset induces inflammatory responses resulting in a tumor-promoting environment. CD4+ Tregs which are critically important for the maintenance of self-tolerance, impede effective immunity against the tumor when they are present in the tumor microenvironment (TME).Therefore, beyond the detection of total CD4+ T cells within the TME, it is of critical importance to determine to which subpopulation each CD4+ T cell belongs to decipher their roles in tumor rejection.

Methods

We have developed a multiplex 7-plex panel of of antibodies against biomarkers to identify main types of CD4+ T cells

Results

On a single FFPE tissue section, main types of CD4+ T cells: TH1, TH2, TFH, TH17 and Tregs are identified by a combination of antibodies against transcription factors and membrane proteins. Following images registration, complex cells phenotypes can be detected and quantified. Furthermore, digital pathology tools allow the evaluation of the spatial distribution of CD4+ T cells within the TME.

Conclusions

This new tool unravels the diversity of CD4+ T cells in TME and could help clinical researchers to design more effective immunotherapies in cancer treatment. Integrated into an Immunogram, this new Brightplex® Panel will also be critical to understand the immune contexture of tumors.
49 Highly multiplexed detection of critical immune checkpoints and immune cell subtypes in cancerous FFPE tissues using CODEX
Authors: Shang Olive , Gordon Judi , Nikulina Nadya , Mistry Sejal , Singh Jasmine , Zong Hailing , Yuan Jessica , Blackmer Trillium , Locke Darren , Braubach Oliver , Kennedy-Darling Julia , Miller Peter
Published: November 2021

Background

There is growing consensus that spatial biology is the key to unlocking the underlying mechanisms of cancer immunotherapy and to predicting patient outcomes. Indeed, a recent example using the Akoya Phenoptics technology revealed a unique phenotypic signature of CD8/Foxp3 positive cells embedded within the tumor microenvironment of patients that responded favorably to PD-1 checkpoint inhibition.1 In this case, the combination of both multiparameter and spatial readouts was required to correlate significantly with outcome. As the number of treatment options expands and knowledge regarding cell types that contribute to treatment mechanisms improves, so too do the number of markers required to analyze responses that enable discovery of new signatures.

Methods

Here, we present data from the analysis of human FFPE cancer tissues using an expanded CODEX antibody catalog targeting a variety of immune, immune checkpoint and transcription factors. CODEX enables the highly multiplexed detection of more than 40 targets within the same tissue sample, with single cell resolution and without degradation of the sample.

Results

Our expanded target list enables detection of key macrophage populations, T and B cell subtypes, granulocytes, dendritic cells, natural killer cells, stromal, tumor and epithelial cells. Additionally, the activation state of these immune and tumor cell types can be measured through detection of key immune checkpoints, including PD-1 and PD-L1. Through the addition of these critical markers, both cells known to contribute to treatment outcome and new biomarker signatures can be identified.

Conclusions

Continued expansion of spatial biology discovery capabilities will be critical to continuing to improve patient outcomes and to develop new treatment options of solid tumors using cancer immunotherapies.

Reference

Berry S, Taube J, et al. Analysis of multispectral imaging with the AstroPath platform informs efficacy of PD-1 blockade. Science. 2021; 372: 6547.
78 Novel RNA-seq platform improve patient outcome in clinical oncology and enable implementation of AI in the clinic
Authors: Nguyen Vy , Pedersen Gitte , Pedersen Morten
Published: November 2021

Background

Only 1 out of 4 cancer treatments prolongs life while expenditure for cancer treatment is greater than $100 billion/year. RNA-sequencing has allowed researchers to gain insight into the transcriptome of human cancers. However, RNA-sequencing remains widely unused in clinical oncology. We address this issue through the development and CLIA validation of OneRNA—an RNA-sequencing platform for cancer diagnostics and the design of new treatments. The development of OneRNA had to overcome the two main hurdles for implementation of RNA sequencing in the clinic: 1) clinical samples are typically embedded in FFPE which results in highly fragmented RNA making sequencing of these samples difficult. 2) how to interpret aberrant gene expression events and translate these results into clinical action. We demonstrate how OneRNA® would enable the design of sophisticated combinatorial clinical studies. An example is combining immune targeting agents such as checkpoint inhibitors with mRNA vaccines. OneRNA also supports the integration of gene expression algorithms because of its ability to interrogate the entire sample transcriptome. OneRNA® has been CLIA certified using FFPE, FF, blood, and saliva samples. Furthermore, the sample preparation method has demonstrated >95% concordance between FF and FFPE and 5–10X the sensitivity compared to Truseq.

Methods

This study aims to demonstrate the clinical utility of OneRNA in detecting aberrant gene expression events and connecting these to already approved drugs that targets these events to offer truly individualized treatment options.

Results

We show that OneRNA has the ability to predict results for not only validated biomarkers used in standard of care such as ER, PR and HER2 in breast cancer, but also provide insight into biomarkers for response to already approved drugs independent of tissue type and with no standard test. Finally, we demonstrate the reproducibility of OneRNA in predicting IHC status in ER, PR and HER2.

Conclusions

These results demonstrate that OneRNA has applications in both cancer research, drug discovery and development, development of companion diagnostic algorithms and implementation of truly individualized treatment.
230 Preclinical efficacy of CLEC-1 antagonist as novel myeloid immune checkpoint therapy for oncology
Authors: Gauttier Vanessa , Drouin Marion , Pengam Sabrina , Saenz Javier , Evrard Bérangère , Neyton Stéphanie , Mary caroline , Teppaz Géraldine , Desselle Ariane , Thépénier Virginie , Wilhelm Emmanuelle , Poirier Nicolas , Chiffoleau Elise
Published: November 2021

Background

C-type lectin receptors (CLRs) are powerful pattern recognition receptors shaping immune cell-mediated tissue damage by positively or negatively regulating myeloid cell functions and hence tumor elimination or evasion. We previously reported that the orphan CLR CLEC-1 expressed by dendritic cells (DCs) tempers T cell’s responses in vivo by limiting antigen cross-presentation by cDC1. Furthermore, we observed that CLEC-1 is highly expressed by myeloid cells purified from human tumor microenvironment, in particular tumor-associated macrophages.

Methods

Macrophages were generated from monocytes of healthy volunteers for phagocytosis assays. MC38 and Hepa 1.6 murine tumor cells were implanted in Clec1a KO or KI mice for immunotherapeutic treatment evaluation.

Results

Using newly developed anti-human CLEC-1 monoclonal antibodies (mAbs), we found that antagonist anti-CLEC-1 mAbs with the capacity to block CLEC-1/CLEC-1Ligand interaction, as opposed to non-antagonist CLEC-1 mAbs, increase the phagocytosis of CLEC-1Ligand-positive human tumor cells by human macrophages, in particular when opsonized by tumor-associated antigen mAbs (Rituximab, Cetuximab, Trastuzumab) or with anti-CD47 mAb (Magrolimab). In-vivo, CLEC-1 knock-out (KO) mice (n=19) display significant prolonged survival in monotherapy as compared to wild-type littermates (n=12) in an orthotopic hepatocellular carcinoma (HCC) model and anti-tumor memory responses was demonstrated by tumor rechallenge in cured mice. CLEC1 KO mice also illustrate significant eradication of MC38 colorectal tumors in combination with chemotherapy promoting CLEC-1Ligand expression by tumor cells (n=16 with Gemcitabine or n=11 with Cyclophosphamide). HCC tumor microenvironment analysis after 2 weeks of tumor implantation shows significantly higher number of CD8+ and memory CD8+ T cells with reduced PD1 expression in CLEC1 KO animals (n=16 versus n=12 for KO vs WT mice respectively). Finally, we recently generated human CLEC-1 knock-in mice expressing the extracellular human CLEC1 domain fused to the intracellular mouse CLEC1 tail and confirmed preclinical efficacy in vivo with anti-human CLEC1 antagonist mAb in monotherapy in the orthotopic HCC model.

Conclusions

These data illustrate that CLEC-1 inhibition represents a novel therapeutic target for immuno-oncology modifying T cell immune responses and tumor cell phagocytosis by macrophages.
279 ILT3 blockade reduces tumor blast cells in acute myeloid leukemia PBMC and inhibits tumor cell growth in a humanized AML tumor model
Authors: Byford Alan , Qu Yujie , Xu Haiyan , Robinson Gain , Singh Latika , Muise Eric , Pinheiro Elaine , Chen Mei , Moy Lily , Alves Stephen , Zhang-Hoover Jie
Published: November 2021

Background

Immunoglobulin-like transcript 3 (ILT3), an immune-inhibitory receptor expressed on myeloid cells, is highly expressed in acute myeloid leukemia (AML) with monocytic differentiation (M4 and M5 subtypes) and clinically is negatively correlated with overall survival. We examined the effects of a highly selective and potent chimeric anti-ILT3 mAb (c52B8) on tumor cell survival/growth and human immune cell modulation in AML PBMC and AML tumor cell lines in pre-clinical in vitro and in vivo models.

Methods

ILT3 mRNA and cell surface expression levels were measured by RNAseq and FACS, respectively. PBMC from AML patients with different levels of ILT3 cell surface expression were treated with c52B8 in vitro.A systemic AML model was generated by IV inoculation of NSG mice with luciferase-transfected MV-4-11 human AML cells, with or without human PBMC engraftment. Tumor bearing mice were treated weekly with c52B8, modified to contain the human Fc of either the IgG1 or IgG4 subclass. MV-4-11 growth in vivo was measured by bioluminescence imaging (BLI).CyTOF was performed to phenotype AML PBMC in in vitro culture and bone marrow samples from the systemic MV-4-11 model after the treatment.THP-1 cells/human T cell co-cultures stimulated with anti-CD3/CD28 antibodies were treated with c52B8. Human T cell activity was assessed by levels of IFNγ production in the culture using MSD ELISA.

Results

In ILT3 high AML patient PBMC, c52B8 treatment in vitro decreased the frequency of tumor blasts, modulated Tregs, and increased monocytic myeloid cells. In the MV-4-11 model, weekly treatment with c52B8 significantly reduced tumor burden in vivo, regardless of the IgG subclass. Importantly, tumor cell growth inhibition by c52B8 occurred in the absence of human PBMC. Additional post-mortem CyTOF analysis of bone marrow cells from MV-4-11/human PBMC inoculated mice confirmed a reduction in MV-4-11 cells, identified by CD3-CD19- human myeloid cells following c52B8 treatment. In THP-1/human T cell co-cultures, c52B8 treatment reversed THP-1 induced T cell suppression, as measured by enhanced IFNγ production.

Conclusions

Anti-ILT3 mAb (c52B8) is efficacious in blocking progression of AML with monocytic differentiation by directly influencing tumor cell growth and enhancing human T cell activity in pre-clinical models. These studies support a potential role for this compound in humans.

Ethics Approval

All animal work was reviewed and approved by Merck IACUC before experiments were conducted.
Bound orbits around modified Hayward black holes
Authors: Gao Bo , Deng Xue-Mei
Published: November 2021

The neutral time-like particle’s bound orbits around modified Hayward black holes have been investigated. We find that both in the marginally bound orbits (MBO) and the innermost stable circular orbits (ISCO), the test particle’s radius and its angular momentum are all more sensitive to one of the parameters [Formula: see text]. Especially, modified Hayward black holes with [Formula: see text] could mimic the same ISCO radius around the Kerr black hole with the spin parameter up to [Formula: see text]. Small [Formula: see text] could mimic the ISCO of small-spinning test particles around Schwarzschild black holes. Meanwhile, rational (periodic) orbits around modified Hayward black holes have also been studied. The epicyclic frequencies of the quasi-circular motion around modified Hayward black holes are calculated and discussed with respect to the observed Quasi-periodic oscillations (QPOs) frequencies. Our results show that rational orbits around modified Hayward black holes have different values of the energy from the ones of Schwarzschild black holes. The epicyclic frequencies in modified Hayward black holes have different frequencies from Schwarzschild and Kerr ones. These might provide hints for distinguishing modified Hayward black holes from Schwarzschild and Kerr ones by using the dynamics of time-like particles around the strong gravitational field.
Zero inertia limit of incompressible Qian–Sheng model
Authors: Luo Yi-Long , Ma Yangjun
Published: November 2021

The Qian–Sheng model is a system describing the hydrodynamics of nematic liquid crystals in the Q-tensor framework. When the inertial effect is included, it is a hyperbolic-type system involving a second-order material derivative coupling with forced incompressible Navier–Stokes equations. If formally letting the inertial constant [Formula: see text] go to zero, the resulting system is the corresponding parabolic model. We provide the result on the rigorous justification of this limit in [Formula: see text] with small initial data, which validates mathematically the parabolic Qian–Sheng model. To achieve this, an initial layer is introduced to not only overcome the disparity of the initial conditions between the hyperbolic and parabolic models, but also make the convergence rate optimal. Moreover, a novel [Formula: see text]-dependent energy norm is carefully designed, which is non-negative only when [Formula: see text] is small enough, and handles the difficulty brought by the second-order material derivative.
Uncertain Response Analysis of Fractionally-Damped Beams Based on Interval Process Model
Authors: Shen C. K. , Mi D. , Li J. W.
Published: November 2021

In the uncertain vibration analysis of fractionally-damped beams whose damping characteristic is described using fractional derivative model, the uncertain excitation is usually modeled as a stochastic process. However, it is often difficult to obtain sufficient samples of the excitation to establish a precise probability distribution function for the stochastic process model in practical engineering problems. Hence, in this paper, a nonrandom vibration analysis method for fractionally-damped beams is proposed to obtain the dynamic displacement response bounds of the beams under the uncertain excitation. Specifically, the uncertain excitation applied to the fractionally-damped beam is treated as a spatial-time interval field, so that the dynamic displacement response of the beam is also a space-time interval field. The middle point function and the radius function of the displacement response of the fractionally-damped beam can be derived based on the modal superposition method and the Laplace transform, through which the bound functions of the dynamic displacement response can be obtained. In addition, several numerical examples are given to demonstrate the effectiveness of the proposed method.
Debris-covered glacier systems and associated glacial lake outburst flood hazards: challenges and prospects
Authors: Racoviteanu A.E. , Nicholson L. , Glasser N.F. , Miles Evan , Harrison S. , Reynolds J.M.
Published: November 2021

Glaciers respond sensitively to climate variability and change, with associated impacts on meltwater production, sea-level rise and geomorphological hazards. There is a strong societal interest in understanding the current response of all types of glacier systems to climate change and how they will continue to evolve in the context of the whole glacierized landscape. In particular, understanding the current and future behaviour of debris-covered glaciers is a ‘hot topic’ in glaciological research because of concerns for water resources and glacier-related hazards. The state of these glaciers is closely related to various hazardous geomorphological processes which are relatively poorly understood. Understanding the implications of debris-covered glacier evolution requires a systems approach. This includes the interplay of various factors such as local geomorphology, ice ablation patterns, debris characteristics and glacier lake growth and development. Such a broader, contextualized understanding is prerequisite to identifying and monitoring the geohazards and hydrologic implications associated with changes in the debris-covered glacier system under future climate scenarios. This paper presents a comprehensive review of current knowledge of the debris-covered glacier landsystem. Specifically, we review state-of-the-art field-based and the remote sensing-based methods for monitoring debris-covered glacier characteristics and lakes and their evolution under future climate change. We advocate a holistic process-based framework for assessing hazards associated with moraine-dammed glacio-terminal lakes that are a projected end-member state for many debris-covered glaciers under a warming climate.
Low-precision Floating-point Arithmetic for High-performance FPGA-based CNN Acceleration
Authors: Wu Chen , Wang Mingyu , Chu Xinyuan , Wang Kun , He Lei
Published: November 2021

Low-precision data representation is important to reduce storage size and memory access for convolutional neural networks (CNNs). Yet, existing methods have two major limitations: (1) requiring re-training to maintain accuracy for
deep
CNNs and (2) needing 16-bit floating-point or 8-bit fixed-point for a good accuracy. In this article, we propose a low-precision (8-bit) floating-point (LPFP) quantization method for FPGA-based acceleration to overcome the above limitations. Without any re-training, LPFP finds an optimal 8-bit data representation with negligible top-1/top-5 accuracy loss (within 0.5%/0.3% in our experiments, respectively, and significantly better than existing methods for
deep
CNNs). Furthermore, we implement one 8-bit LPFP multiplication by one 4-bit multiply-adder and one 3-bit adder, and therefore implement
four
8-bit LPFP multiplications using one DSP48E1 of Xilinx Kintex-7 family or DSP48E2 of Xilinx Ultrascale/Ultrascale+ family, whereas one DSP can implement only
two
8-bit fixed-point multiplications. Experiments on six typical CNNs for inference show that on average, we improve throughput by

over existing FPGA accelerators. Particularly for VGG16 and YOLO, compared to six recent FPGA accelerators, we improve average throughput by 3.5

and 27.5

and average throughput per DSP by 4.1

and 5

, respectively.
Autonomous Airborne Wind Energy Systems: Accomplishments and Challenges
Authors: Fagiano Lorenzo , Quack Manfred , Bauer Florian , Carnel Lode , Oland Espen
Published: November 2021

Airborne wind energy (AWE) is a fascinating technology to convert wind power into electricity with an autonomous tethered aircraft. Deemed a potentially game-changing solution, AWE is attracting the attention of policy makers and stakeholders with the promise of producing large amounts of cost-competitive electricity with wide applicability worldwide. Since the pioneering experimental endeavors in the years 2000–2010, there has been a clear technology convergence trend and steady progress in the field. Today, AWE systems can operate automatically with minimal supervision in all operational phases. A first product is also being commercialized. However, all-around fully autonomous operation still presents important fundamental challenges that are conceptually similar to those of other systems that promise to change our lives, such as fully autonomous passenger cars or service drones. At the same time, autonomous operation is necessary to enable large-scale AWE, thus combining challenging fundamental problems with high potential impact on society and the economy. This article describes the state of the art of this technology from a system perspective and witha critical view on some fundamental aspects, presents the latest automatic control results by prominent industrial players, and finally points out the most important challenges on the road to fully autonomous AWE systems.
Role of the Inflammasome in Liver Disease
Authors: de Carvalho Ribeiro Marcelle , Szabo Gyongyi
Published: November 2021

The involvement of inflammasomes in the proinflammatory response observed in chronic liver diseases, such as alcohol-associated liver disease (ALD) and nonalcoholic fatty liver disease (NAFLD), is widely recognized. Although there are different types of inflammasomes, most studies to date have given attention to NLRP3 (nucleotide-binding oligomerization domain-like receptor family, pyrin domain containing 3) in the pathogenesis of ALD, NAFLD/nonalcoholic steatohepatitis, and fibrosis. Canonical inflammasomes are intracellular multiprotein complexes that are assembled after the sensing of danger signals and activate caspase-1, which matures interleukin (IL)-1β, IL-18, and IL-37 and also induces a form of cell death called pyroptosis. Noncanonical inflammasomes activate caspase-11 to induce pyroptosis. We discuss the different types of inflammasomes involved in liver diseases with a focus on ( a) signals and mechanisms of inflammasome activation, ( b) the role of different types of inflammasomes and their products in the pathogenesis of liver diseases, and ( c) potential therapeutic strategies targeting components of the inflammasomes or cytokines produced upon inflammasome activation.
Factors and Economic Evaluation of Transnational Investment Risks
Authors: Xiong Guanghui , Wang Lei
Published: November 2021

Transnational investment is featured by its large scale and high risks. During transnational investment, the frequent risks often bring a huge loss to the investors. Therefore, the risk factors should be included in the economic evaluation of transnational investment projects. However, the existing evaluation models and systems are rather complex, lacking a unified framework. Besides, there are few practical applications of these models or systems. To solve the problem, this paper explores the factors and economic evaluation of transnational investment risks. Firstly, an economic evaluation system was constructed for transnational investment projects, and the economic evaluation result was depicted in two aspects: economic income factors and investment risk factors. Then, the applicability and economic meanings of common indices were clarified one after another. After that, the economic evaluation flow was designed for risk-based transnational investment projects. Finally, an economic evaluation was performed on actual projects, which verifies the feasibility of the proposed evaluation method.
[Retracted] The Study of Midinfrared Extremely Narrow Dual‐Band Absorber Based on a Novel Metamaterial Structure
Authors: Li Zichun , Li Jinhua , Zhang Ye , Zhai Yingjiao , Chu Xueying , Zhang Yu
Published: November 2021

Due to the problems that the metal pattern layer on the top of the traditional metamaterial structure is easy to be oxidized and easy to fall off, in this paper, a novel semiconductor metamaterial nanostructure composed of a periodic array of GaAs‐SiO2 cubes and a gold (Au) film has been proposed. Using FDTD solutions software to prove this metamaterial structure can achieve ultranarrow dual‐band, nearly perfect absorption with a maximum absorbance of 99% and a full‐width at half‐maximum (FWHM) value that is less than 20 nm in the midinfrared region. The refractive index sensitivity is demonstrated by changing the background index and analyzing the absorption performance. It had been proved that this absorber has high sensitivity (2000/RIU and 1300/RIU). Using semiconductor material instead of the metal material of the top pattern layer can effectively inhibit the performance failure of the metamaterial structure caused by metal oxidation. The proposed narrow, dual‐band metamaterial absorber shows promising prospects in applications such as infrared detection and imaging.
Cooperation Mechanism in Blockchain by Evolutionary Game Theory
Authors: Zhang Jinxin , Wu Meng
Published: November 2021

In the blockchain network, to get rewards in the blockchain, blockchain participants pay for various forms of competition such as computing power, stakes, and other resources. Because of the need to pay a certain cost, individual participants cooperate to maintain the long‐term stability of the blockchain jointly. In the course of such competition, the game between each other has appeared invisibly. To better understand the blockchain design of cooperation mechanisms, in this paper, we constructed a game framework between participants with different willingness, using evolutionary game theory, and complex network games. We analyzed how the behavior of participants potentially develops with cost and payoff. We consider the expected benefits of participants for the normal growth of the blockchain as the major factor. Considering the behavior of malicious betrayers, the blockchain needs to be maintained in the early stage. Numerical simulation supports our analysis.
Equipment Maintenance Support Effectiveness Evaluation Based on Improved Generative Adversarial Network and Radial Basis Function Network
Authors: Li Zhen , Hao Jianping , Gao Cuijuan
Published: November 2021

Due to the lack of maintenance support samples, maintenance support effectiveness evaluation based on the deep neural network often faces the problem of small sample overfitting and low generalization ability. In this paper, a neural network evaluation model based on an improved generative adversarial network (GAN) and radial basis function (RBF) network is proposed to amplify maintenance support samples. It adds category constraint based on category probability vector reordering function to GAN loss function, avoids the simplification of generated sample categories, and enhances the quality of generated samples. It also designs a parameter initialization method based on parameter components equidistant variation for RBF network, which enhances the response of correct feature information and reduces the risk of training overfitting. The comparison results show that the mean square error (MSE) of the improved GAN‐RBF model is 5.921 × 10−4, which is approximately 1/2 of the RBF model, 1/3 of the Elman model, and 1/5 of the BP model, while its complexity remains at a reasonable level. Compared with traditional neural network evaluation methods, the improved GAN‐RBF model has higher evaluation accuracy, better solves the problem of poor generalization ability caused by insufficient training samples, and can be more effectively applied to maintenance support effectiveness evaluation. At the same time, it also provides a good reference for evaluation research in other fields.
Efficacy of the Kombucha Beverage Derived from Green, Black, and Pu’er Teas on Chemical Profile and Antioxidant Activity
Authors: Hsieh Yi , Chiu Ming-Chung , Chou Jui-Yu
Published: November 2021

Kombucha is a symbiotic culture of bacteria and yeast which produces a high-end fruity fitness beverage by fermentation of normal tea for approximately two weeks. In addition to the advantage of being a low-sugar probiotic-rich drink, kombucha also offers the benefits of the tea used for its preparation, especially its high antioxidant content. In this research, kombucha tea was prepared by using three different tea types: green, black, and pu’er tea, and the chemical profiles and antioxidant activity were analyzed during the fermentation process (up to 20 days). The results showed that the tea type has an obvious influence on the factors associated with the antioxidant potential. The fermentation process caused a marked increase in polyphenol content and antioxidant activity initially, but this slowed progressively over time. In contrast, the fermentation of black tea contributed to the degradation of flavonoids but showed no significant effect on the other tea types. Therefore, we conclude that the tea type selected to make kombucha affects the end product as well as the fermentation time.
The Ensemble Machine Learning-Based Classification of Motor Imagery Tasks in Brain-Computer Interface
Authors: Subasi Abdulhamit , Mian Qaisar Saeed
Published: November 2021

The Brain-Computer Interface (BCI) permits persons with impairments to interact with the real world without using the neuromuscular pathways. BCIs are based on artificial intelligence piloted systems. They collect brain activity patterns linked to the mental process and transform them into commands for actuators. The potential application of BCI systems is in the rehabilitation centres. In this context, a novel method is devised for automated identification of the Motor Imagery (MI) tasks. The contribution is an effective hybridization of the Multiscale Principal Component Analysis (MSPCA), Wavelet Packet Decomposition (WPD), statistical features extraction from subbands, and ensemble learning-based classifiers for categorization of the MI tasks. The intended electroencephalogram (EEG) signals are segmented and denoised. The denoising is achieved with a Daubechies algorithm-based wavelet transform (WT) incorporated in the MSPCA. The WT with the 5th level of decomposition is used. Onward, the Wavelet Packet Decomposition (WPD), with the 4th level of decomposition, is used for subbands formation. The statistical features are selected from each subband, namely, mean absolute value, average power, standard deviation, skewness, and kurtosis. Also, ratios of absolute mean values of adjacent subbands are computed and concatenated with other extracted features. Finally, the ensemble machine learning approach is used for the classification of MI tasks. The usefulness is evaluated by using the BCI competition III, MI dataset IVa. Results revealed that the suggested ensemble learning approach yields the highest classification accuracies of 98.69% and 94.83%, respectively, for the cases of subject-dependent and subject-independent problems.
Nonclinical Safety Pharmacology Study of the Herbal Product HAD-B1
Authors: Kim Soo-Dam , Yang Jae-Ho , Kwag Eun-Bin , Park Ji-Hye , Park So-Jung , Yoo Hwa-Seung
Published: November 2021

HAD-B1 is a Korean herbal formula designed to treat solid tumors, and through cell experiments, it has proven to have an anticancer effect. The current study aims to test the safety of HAD-B1. This experiment is under the regulation of ICH. In order to find if HAD-B1 has any effect on the CNS, 0, 500, 1000, and 2000 mg/kg/day of HAD-B1 were orally administered to male and female rats once. To discover any effect on the respiratory system, 0, 500, 1000, and 2000 mg/kg/day of HAD-B1 were orally given to male rats followed by measuring the respiratory rate, tidal volume, and minute respiratory volume. To assess the possibility of a delayed QT period as a result of the drug administration, hERG analysis was conducted at 0, 0.1, 0.3, and 1 μg/ml. To assess any effect on the cardiovascular system, 0, 500, 1000, and 2000 mg/kg/day of HAD-B1 were orally given to male beagle dogs once followed by temperature, blood pressure, ECG, and heart rate analyses. There were no clinically significant changes in both male and female rats on assessing any effects on the CNS. There were no clinically significant changes in male rats’ respiratory assessment. There were no clinically significant changes in hERG analysis results. There were no clinically significant changes in the cardiovascular system of male beagle dogs. Our results demonstrate that HAD-B1 is a safe herbal formula that does not have a clinically significant effect on the CNS, respiratory, and cardiovascular systems.
Preparation and Properties of Core‐Shell Structure/Ni60 Coating
Authors: Xinsheng Wang , Liu Yanpei , Hou Junjian , He Wenbin , Liu Kun , Zhaobin She
Published: November 2021

As the most important element in improving the service life of a mechanical system, surface coating materials are of key importance in the development of high‐end equipment. To improve the comprehensive properties of the surface coating, the common core‐shell structure/Ni60 coating was prepared on the surface of #45 steel by supersonic plasma spraying. The results show that the Ni60 has no layer structure, pores, cracks, and other defects on the surface of the coating. The nanohardness of the NNA(Ni60/Ni (Al) mixture powder), NNM(Ni60/Ni (MoS2) mixture powder), and NNC(Ni60/Ni (C) mixture powder) coatings is 6815 μN, 5750 μN, and 2000 μN. The results show that the wear resistance of the NNA coating is better. In the friction and wear test, the NNA coating mainly shows adhesive wear and abrasive wear, while the NNM and NNC coatings mainly show abrasive wear.
Analysis of Cumulative Damage Characteristics of Long Spiral Belled Pile under Horizontal Cyclic Loading at Sea
Authors: Liang Haian , Zeng Hao , Cao Kaiwei , Liu Chao , Cheng Xinjun
Published: November 2021

In order to study the cumulative damage and failure characteristics of long spiral belled pile under horizontal cyclic loading of offshore wind and waves, a series of indoor experiments on single piles under horizontal cyclic load were carried out. The cycle times as well as load amplitude at the same frequency were considered during the horizontal pseudo‐static cyclic tests. On the basis of the distribution of pile deflection, bending moment, and Earth pressure around the pile, the pile‐soil interaction was comprehensively discussed. The cumulative energy dissipation characteristics were introduced to describe the damage of test piles. Meanwhile, the effects of load amplitude and cycle times on the cumulative damage of long spiral belled piles were discussed. A power function model for energy dissipation coefficient prediction under multi‐stage cyclic load was proposed. The results show that the horizontal peak bearing capacity of long spiral belled pile is increased by 57.2% and 40.4%, respectively, as compared with the straight pile and belled pile under the same conditions. The horizontal displacement mainly occurs at the upper part of the pile. Under the condition of limited cyclic times, the load amplitude has more significant effect on the bearing characteristics of the long spiral belled pile. In contrast to the straight pile and belled pile, the long spiral belled pile has better energy dissipation capacity, and the rank of the energy dissipation capacity of these three piles is long spiral belled pile > belled pile > straight pile. The power function model can well reflect the cumulative damage characteristics of long spiral belled pile under horizontal cyclic loading, and there is a good linear relationship between power function model parameters and load amplitude. The energy dissipation coefficient of long spiral belled pile with diverse cycle times at different mechanical stages of test pile is analysed. Then, the recommended power function model parameters according to different failure stages are proposed. The verification example indicates that the prediction results are close to the measured values with a calculation error of 22%. The prediction model can provide a certain reference for the application of long spiral belled pile in marine structures.
Classification and Evolution Analysis of Key Transportation Technologies Based on Bibliometrics
Authors: Chen Hua , Cai Ming , Huang Ke , Jin Shuxin
Published: November 2021

To study the classification and evolution of key technologies in the transportation field, the data of 36 authoritative SCI journals in the transportation field were collected from the Web of Science core collection database from 2001 to 2020. Based on the bibliometric method, this study used Python to process and visualize data, combined with bibliometric software VOSviewer to assist data visualization. Firstly, a preprocessing data algorithm was designed to deduplicate the collected data, merge synonyms, and extract key technologies. Then the paper records that contained the key technology lexicon were filtered out. Next, the annual number of publications and the distribution of key technologies over time were counted. The least squares method was used to fit the distribution of the annual proportion of the publications, and the slope k1 of the fitted linear regression equation was used to determine the research interest trend of key technologies. The key technologies were divided into “hot technology,” “cold technology,” and “other technologies,” according to the research heat trend. In order to further explore the research hotspots, the least squares method was also used to fit the citations of all technologies to obtain the slope k2. We use the Gaussian mixture model (GMM) algorithm to cluster k1 and k2 of each technology. As a result, the 144 technologies were divided into 13 super-key technologies, 60 key technologies, 59 relative key technologies, and 12 lower-key technologies. Then, the evolution of key technologies was analyzed from two perspectives of weighted evolution and cumulative evolution. And the technology evolution trend in the transportation field in the past 20 years was explored. Finally, the cooccurrence clustering method was adopted to divide key transportation technologies into five categories: vehicle technology and control, optimization algorithms and simulation techniques, artificial intelligence and big data, Internet of Things and computing, and communication technology. The research results can provide references for different people in the transportation field, including but not limited to researchers, journal editors, and funding agencies.
An Intuitionistic Calculus to Complex Abnormal Event Recognition on Data Streams
Authors: Lijun Zhao , Guiqiu Hu , Qingsheng Li , Guanhua Ding
Published: November 2021

Data mining in real-time data streams is associated with multiple types of uncertainty, which often leads the respective categorizers to make erroneous predictions related to the presence or absence of complex events. But recognizing complex abnormal events, even those that occur in extremely rare cases, offers significant support to decision-making systems. Therefore, there is a need for robust recognition mechanisms that will be able to predict or recognize when an abnormal event occurs or will occur on a data stream. Considering this need, this paper presents an Intuitionistic Tumbling Windows event calculus (ITWec) methodology. It is an innovative data analysis system that combines for the first time in the literature a set of multiple systems for Complex Abnormal Event Recognition (CAER). In the proposed system, the probabilities of the existence of a high-level complex abnormal event for each period are initially calculated nonparametrically, based on the probabilities of the low-level events associated with it. Because cumulative results are sought in consecutive, nonoverlapping sections of the data stream, the method uses the clearly defined rules of initialization and termination of the tumbling windows method, where there is an explicit determination of the time interval within which several blocks of a particular stream are investigated window. Finally, the number of maximum probable intervals in which an event is likely to occur based on a certain probability threshold is calculated, based on a parametric representation of intuitively fuzzy sets.
Numerical Simulation of the Stress Field in Repeated Mining of Coal Seams Based on In Situ Stress Measurement
Authors: Yang Donghui , Yang Bohu , Lv Zhaoheng , Li Yongming , Cheng Hongming , Ning Zhangxuan
Published: November 2021

We established an evaluation index of the rock mass stress state for underground coal mines using the strength-stress ratio based on the measured in situ stress and the generalized Hoek–Brown strength criterion. Three in situ stress states, σcm/σ1m < 1.4 (high), 1.4 < σcm/σ1m < 3.6 (medium), and σcm/σ1m > 3.6 (low), were established based on the value of the unconfined compressive strength (σcm) and the maximum principal stress of the rock mass (σ1m). This index classifies the Burtai mine as a medium-high in situ stress field, which is in agreement with the on-site situation, establishing the reliability of the index. The working face was a three-dimensional geological model based on the log sheets. The initial conditions for the model were determined using the combined measurements of the in situ stress regression model. We performed numerical simulations of the roof stress field distribution under repeated mining. Mining the overlying coal seam leads to significant variation in the value and direction of the main roof, σ1, within the range of the front abutment pressure under the pillar and gob. Along the main roof strike direction, σ1 under the pillar is 1.5 times that under the gob, and the σ1 direction under the pillar is deflected by 5°, which is 30° smaller than that under the gob. This provides a reference for optimized underground coal mining.
Influence of Social Network Strength on Entrepreneurial Opportunity Recognition: A Chain Mediation Model of Need Knowledge and Technological Knowledge
Authors: Fan Jing , Su Jiafu
Published: November 2021

Entrepreneurial opportunity recognition is a key focus of entrepreneurship research and has received considerable attention in recent years. Previous research has highlighted that social network strength, need knowledge, and technological knowledge are important factors in entrepreneurial opportunity recognition and that these factors in isolation cannot sufficiently explain how entrepreneurial opportunities are recognized. Nonetheless, little is known about the effect that social network strength may exert on entrepreneurial opportunity recognition through need knowledge and technological knowledge. Building on social network theory, this study develops and examines a chain mediation model that incorporates need knowledge and technological knowledge into the relationship between social network strength and entrepreneurial opportunity recognition. The results of this study demonstrate that the effect of social network strength on entrepreneurial opportunity recognition can be partitioned into the direct and indirect effects. In particular, the effect of social network strength on entrepreneurial opportunity recognition is mediated by need knowledge, not by technological knowledge. Moreover, need knowledge and technological knowledge play a continuous mediating role in the relationship between social network strength and entrepreneurial opportunity recognition. These findings extend the entrepreneurial opportunity recognition literature by casting light on the knowledge conduits linking social network strength to entrepreneurial opportunity recognition.
Hypoxia Enhances Activity and Malignant Behaviors of Colorectal Cancer Cells through the STAT3/MicroRNA-19a/PTEN/PI3K/AKT Axis
Authors: Tang Yingchun , Weng Xiahui , Liu Chang , Li Xing , Chen Chao
Published: November 2021

Hypoxia is a typical microenvironment feature in almost all solid tumors and is frequently associated with growth of cancers including colorectal cancer (CRC). This study focuses on the influence of hypoxic microenvironment on the activity of CRC cells and the molecules involved. CRC cells were cultured under hypoxic conditions for 48 h, after which the proliferation, migration, invasion, and epithelial-mesenchymal transition activities of cells were increased. MicroRNA- (miR-) 19a was significantly upregulated in cells after hypoxia exposure according to a microarray analysis. STAT3 was confirmed as an upstream regulator of miR-19a which bound to the promoter region of miR-19a at the 96 bp/78 bp sites, and miR-19a bound to the PTEN mRNA to activate the PI3K/AKT signaling pathway. Hypoxia exposure induced STAT3 phosphorylation and PTEN knockdown in CRC cells. Silencing of STAT3 reduced the hypoxia-induced activity of CRC cells, whereas the malignant behaviors of cells were restored after miR-19a upregulation but blocked after PTEN overexpression. Similar results were reproduced in vivo where downregulation of STAT3 or overexpression of PTEN suppressed tumor growth and metastasis in nude mice. This study demonstrated that hypoxia augments activity and malignant behaviors of colorectal cancer cells through the STAT3/miR-19a/PTEN/PI3K/AKT axis.
Odd Inverse Power Generalized Weibull Generated Family of Distributions: Properties and Applications
Authors: Al-Moisheer A.S. , Elbatal I. , Almutiry Waleed , Elgarhy Mohammed
Published: November 2021

A novel family of produced distributions, odd inverse power generalized Weibull generated distributions, is introduced. Various mathematics structural properties for the odd inverse power generalized Weibull generated family are computed. Numerical analysis for mean, variance, skewness, and kurtosis is performed. The new family contains many new models, and the densities of the new models can be right skewed and symmetric with “unimodal” and “bimodal” shapes. Also, its hazard rate function can be “constant,” “decreasing,” “increasing,” “increasing-constant,” “upside-down-constant,” and “decreasing-constant.” Different types of entropies are calculated. Some numerical values of various entropies for some selected values of parameters for the odd inverse power generalized Weibull exponential model are computed. The maximum likelihood estimation, least square estimation, and weighted least square estimation approaches are used to estimate the OIPGW-G parameters. Many bivariate and multivariate type models have been also derived. Two real-world data sets are used to demonstrate the new family’s use and versatility.