bluuebunny/crossref_metadata_2025 huggingface dataset:
Effective Technique for Noise Removal and Emotion Recognition in Speech Signals Using Cat Swarm Optimized Spiking Neural Networks
Authors: Revathy C. , Sureshbabu R.
Published: November 2021

Speech processing is one of the required fields in digital signal processing that helps in processing the speech signals. The speech process is utilized in different fields such as emotion recognition, virtual assistants, voice identification, etc. Among the various applications, emotion recognition is one of the critical areas because it is used to recognize people’s exact emotions and eliminate physiological issues. Several researchers utilize signal processing and machine learning techniques together to find the exact human emotions. However, they fail to attain their feelings with less computational complexity and high accuracy. This paper introduces the intelligent computational technique called cat swarm optimized spiking neural network (CSSPNN). Initially, the emotional speech signal is collected from the Toronto emotional speech set (TESS) dataset, which is then processed by applying a wavelet approach to extract the features. The derived features are further examined using the defined classifier CSSPNN, which recognizes human emotions due to the effective training and learning process. Finally, the proficiency of the system is determined using experimental results and discussions. The proposed system recognizes the speech emotions up to 99.3% accuracy compared to recurrent neural networks (RNNs), deep neural networks (DNNs) and deep shallow neural networks (DSNNs).
L-algebras and topology
Authors: Rump Wolfgang
Published: November 2021

L-algebras are based on an equation which is fundamental in the construction of various torsion-free groups, including spherical Artin groups, Riesz groups, certain mapping class groups, para-unitary groups, and structure groups of set-theoretic solutions to the Yang–Baxter equation. A topological study of L-algebras is initiated. A prime spectrum is associated to certain (possibly all) L-algebras, including three classes of L-algebras where the ideals are determined in a more explicite fashion. Known results on orthomodular lattices, Heyting algebras, or quantales are extended and revisited from an L-algebraic perspective.
New compounding lifetime distributions with applications to real data
Authors: Esmaeili Leila , Niaparast Mehrdad
Published: November 2021

Motivation to fit the Danish reinsurance claim and aircraft windshield data sets, we introduce exponentiated half logistic-power series (EHLPS) distributions, which are obtained by compounding exponentiated half-logistic distribution with power series distributions. Some mathematical properties have been studied. Maximum likelihood estimation of unknown parameters for the complete data is discussed via the EM algorithm. Simulation results to assess the performance of the estimation methods are discussed. Finally, two applied examples are given for indicating the flexibility and appropriateness of the distribution.
Data Acquisition System for a Distributed Smartphone Cosmic Ray Observatory
Authors: Swaney Jeff , Shimmin Chase , Whiteson Daniel
Published: November 2021

A scientific instrument comprised of a global network of millions of independent, connected, remote devices presents unique data acquisition challenges. We describe the software design of a mobile application which collects data from smartphone cameras without overburdening the phone’s CPU or battery. The deployed software automatically calibrates to heterogeneous hardware targets to improve the quality and manage the rate of data transfer, and connects to a cloud-based data acquisition system which can manage and refine the operation of the network.
A Jurassic flower bud from China
Authors: Cui Da-Fang , Hou Yemao , Yin Pengfei , Wang Xin
Published: November 2021

Angiosperms may be distinguished from their gymnosperm peers by their flowers, and thus a flower is a good proxy of fossil angiosperms. However, flowers and their parts are usually too frail to be preserved in the fossil record. This makes the origin of angiosperms and their flowers the foci of controversy in botany. Eliminating such botanical controversies can only be achieved by studying related plant fossils. Applying routine scanning electron microscopy, light microscopy and micro-computed tomography (micro-CT) technologies, we document a fossil flower bud,
Florigerminis jurassica
gen. et sp. nov., from the Jurassic of Inner Mongolia, China. This fossil includes not only a leafy branch but also physically connected fruit and flower bud. The developmentally interpolated existence of a blooming flower between the flower bud and mature fruit in
Florigerminis
suggests that angiosperm flowers were present in the Jurassic, in agreement with recent botanical progress.
Florigerminis jurassica
underscores the presence of angiosperms in the Jurassic and demands a rethinking of angiosperm evolution.
Deep Level Analysis of Legitimacy in Bengali News Sentences
Authors: Das Soma , Rai Pooja , Chatterji Sanjay
Published: November 2021

The tremendous increase in the growth of misinformation in news articles has the potential threat for the adverse effects on society. Hence, the detection of misinformation in news data has become an appealing research area. The task of annotating and detecting distorted news article sentences is the immediate need in this research direction. Therefore, an attempt has been made to formulate the legitimacy annotation guideline followed by annotation and detection of the legitimacy in Bengali e-papers. The sentence-level manual annotation of Bengali news has been carried out in two levels, namely “Level-1 Shallow Level Classification” and “Level-2 Deep Level Classification” based on semantic properties of Bengali sentences. The tagging of 1,300 anonymous Bengali e-paper sentences has been done using the formulated guideline-based tags for both levels. The validation of the annotation guideline has been done by applying benchmark supervised machine learning algorithms using the lexical feature, syntactic feature, domain-specific feature, and Level-2 specific feature in both levels. Performance evaluation of these classifiers is done in terms of Accuracy, Precision, Recall, and F-Measure. In both levels, Support Vector Machine outperforms other benchmark classifiers with an accuracy of 72% and 65% in Level-1 and Level-2, respectively.
The Strong Scaling Advantage of FPGAs in HPC for N-body Simulations
Authors: Menzel Johannes , Plessl Christian , Kenter Tobias
Published: November 2021

N-body methods are one of the essential algorithmic building blocks of high-performance and parallel computing. Previous research has shown promising performance for implementing n-body simulations with pairwise force calculations on FPGAs. However, to avoid challenges with accumulation and memory access patterns, the presented designs calculate each pair of forces twice, along with both force sums of the involved particles. Also, they require large problem instances with hundreds of thousands of particles to reach their respective peak performance, limiting the applicability for strong scaling scenarios. This work addresses both issues by presenting a novel FPGA design that uses each calculated force twice and overlaps data transfers and computations in a way that allows to reach peak performance even for small problem instances, outperforming previous single precision results even in double precision, and scaling linearly over multiple interconnected FPGAs. For a comparison across architectures, we provide an equally optimized CPU reference, which for large problems actually achieves higher peak performance per device, however, given the strong scaling advantages of the FPGA design, in parallel setups with few thousand particles per device, the FPGA platform achieves highest performance and power efficiency.
Design and Evaluation of a Tunable PUF Architecture for FPGAs
Authors: Streit Franz-Josef , Krüger Paul , Becher Andreas , Wildermann Stefan , Teich Jürgen
Published: November 2021

FPGA-based Physical Unclonable Functions (PUF) have emerged as a viable alternative to permanent key storage by turning effects of inaccuracies during the manufacturing process of a chip into a unique, FPGA-intrinsic secret. However, many fixed PUF designs may suffer from unsatisfactory statistical properties in terms of uniqueness, uniformity, and robustness. Moreover, a PUF signature may alter over time due to aging or changing operating conditions, rendering a PUF insecure in the worst case. As a remedy, we propose
CHOICE
, a novel class of FPGA-based PUF designs with tunable uniqueness and reliability characteristics. By the use of addressable shift registers available on an FPGA, we show that a wide configuration space for adjusting a device-specific PUF response is obtained without any sacrifice of randomness. In particular, we demonstrate the concept of address-tunable propagation delays, whereby we are able to increase or decrease the probability of obtaining “
1
”s in the PUF response. Experimental evaluations on a group of six 28 nm Xilinx Artix-7 FPGAs show that CHOICE PUFs provide a large range of configurations to allow a fine-tuning to an average uniqueness between 49% and 51%, while simultaneously achieving bit error rates below 1.5%, thus outperforming state-of-the-art PUF designs. Moreover, with only a single FPGA slice per PUF bit, CHOICE is one of the smallest PUF designs currently available for FPGAs. It is well-known that signal propagation delays are affected by temperature, as the operating temperature impacts the internal currents of transistors that ultimately make up the circuit. We therefore comprehensively investigate how temperature variations affect the PUF response and demonstrate how the tunability of CHOICE enables us to determine configurations that show a high robustness to such variations. As a case study, we present a cryptographic key generation scheme based on CHOICE PUF responses as device-intrinsic secret and investigate the design objectives resource costs, performance, and temperature robustness to show the practicability of our approach.
Where Has All the Carbon Gone?
Authors: Denning A. Scott
Published: November 2021

Carbon is among the most abundant substances in the universe; although severely depleted on Earth, it is the primary structural element in biochemistry. Complex interactions between carbon and climate have stabilized the Earth system over geologic time. Since the modern instrumental CO2record began in the 1950s, about half of fossil fuel emissions have been sequestered in the oceans and land ecosystems. Ocean uptake of fossil CO2is governed by chemistry and circulation. Net land uptake is surprising because it implies a persistent worldwide excess of growth over decay. Land carbon sinks include ( a) CO2fertilization, ( b) nitrogen fertilization, ( c) forest regrowth following agricultural abandonment, and ( d) boreal warming. Carbon sinks in both land and oceans are threatened by warming and are likely to weaken or even reverse as emissions fall with the potential for amplification of climate change due to the release of previously stored carbon. Fossil CO2will persist for centuries and perhaps many millennia after emissions cease. ▪ About half the carbon from fossil fuel combustion is removed from the atmosphere by sink processes in the land and oceans, slowing the increase of CO2and global warming. These sinks may weaken or even reverse as climate warms and emissions fall. ▪ The net land sink for CO2requires that plants have been growing faster than they decay for many decades, causing carbon to build up in the biosphere over and above the carbon lost to deforestation, fire, and other disturbances. ▪ CO2uptake by the oceans is slow because only the surface water is in chemical contact with the air. Cold water at depth is physically isolated by its density. Deep water mixes with the surface in about 1,000 years. The deep water does not know we are here yet! ▪ After fossil fuel emissions cease, much of the extra CO2will remain in the atmosphere for many centuries or even millennia. The lifetime of excess CO2depends on total historical emissions; 10% to 40% could last until the year 40,000 AD.
Political Participation Amid Mass Incarceration
Authors: White Ariel R.
Published: November 2021

Contact with the carceral state—ranging from police stops to prison time—is a frequent experience in the United States, particularly in communities marginalized on the basis of race and class. In recent years, political scientists have sought to measure the impacts of these encounters on individuals’ and communities’ political engagement. This review describes the main sources of evidence in this literature and what we learn from them. I present a series of stylized facts about the carceral state and political behavior, highlighting places where we know a great deal (such as the relative underrepresentation of people with criminal convictions among voters) and places where more work is needed (such as nonvoting participation and community spillovers). Then, I discuss policy proposals that seek to mitigate the political impacts of the carceral state, and what is and is not yet known about what they might accomplish.
Review—Pseudocapacitive Energy Storage Materials from Hägg-Phase Compounds to High-Entropy Ceramics
Authors: Zhang Xian-Li , Zhang Wei-Bin , Han Xiong-Wei , Zhang Lun , Bao Xu , Guo Yao-Wen , Chai Shan-Shan , Guo Shao-Bo , Zhou Xia , Ma Xue-Jing
Published: November 2021

Energy storage material that provide both high power and high energy density are needed to meet current needs. Pseudocapacitive materials have become a focus of research in the field of electrochemical energy storage because of their high specific capacitance and good rate performance. To increase the energy and power density, the key lies in selecting suitable electrode material types or optimizing the electrode layer structure to increase the potential window. This review, starting from the pseudocapacitive materials, introduces the energy storage mechanism of pseudocapacitance, describes the general development of pseudocapacitive materials including oxide materials and their derivative, development of Hägg-phase compounds extended by the MXenes in the past decade, and focuses on the development of several Hägg-phase compounds and the advantages of high-entropy ceramics as future pseudocapacitive materials. Due to the “high-entropy effect,” high-entropy ceramics have better physical and chemical properties to become the most candidate pseudocapacitive material. Focusing on the application potential of the high-entropy ceramics in pseudocapacitive research, they will provide a new pseudocapacitive material system.
Parametrisation and Use of a Predictive DFN Model for a High-Energy NCA/Gr-SiOx Battery
Authors: Zülke Alana , Korotkin Ivan , Foster Jamie M. , Nagarathinam Mangayarkarasi , Hoster Harry , Richardson Giles
Published: November 2021

We demonstrate the predictive power of a parametrised Doyle-Fuller-Newman (DFN) model of a commercial cylindrical (21700) lithium-ion cell with NCA/Gr-SiOx chemistry. Model parameters result from the deconstruction of a fresh commercial cell to determine/confirm chemistry and micro-structure, and also from electrochemical experiments with half-cells built from electrode samples. The simulations predict voltage profiles for (i) galvanostatic discharge and (ii) drive-cycles. Predicted voltage responses deviate from measured ones by <1% throughout at least ∼95% of a full galvanostatic discharge, whilst the drive cycle discharge is matched to a ∼1%–3% error throughout. All simulations are performed using the online computational tool DandeLiion, which rapidly solves the DFN model using only modest computational resources. The DFN results are used to quantify the irreversible energy losses occurring in the cell and deduce their location. In addition to demonstrating the predictive power of a properly validated DFN model, this work provides a novel simplified parametrisation workflow that can be used to accurately calibrate an electrochemical model of a cell.
Regional difference in prefrontal oxygenation before and during overground walking in humans: a wearable multichannel NIRS study
Authors: Asahara Ryota , Ishii Kei , Liang Nan , Hatanaka Yukari , Hihara Kei , Matsukawa Kanji
Published: November 2021

Using wireless multichannel near-infrared spectroscopy, regional difference in cortical activity over the prefrontal cortex (PFC) was examined before and during overground walking and in response to changes in speed and cognitive demand. Oxygenated-hemoglobin concentration (Oxy-Hb) as index of cortical activity in ventrolateral PFC (VLPFC), dorsolateral PFC (DLPFC), and frontopolar cortex (FPC) was measured in 14 subjects, whereas heart rate was measured as estimation of exercise intensity in six subjects. The impact of mental imagery on prefrontal Oxy-Hb was also explored. On both sides, Oxy-Hb in VLPFC, DLPFC, and lateral FPC was increased before the onset of normal-speed walking, whereas Oxy-Hb in medial FPC did not respond before walking onset. During the walking, Oxy-Hb further increased in bilateral VLPFC, whereas Oxy-Hb was decreased in DLPFC and lateral and medial FPC. Increasing walking speed did not alter the increase in Oxy-Hb in VLPFC but counteracted the decrease in Oxy-Hb in DLPFC (but not in lateral and medial FPC). Treadmill running evoked a greater Oxy-Hb increase in DLPFC ( n = 5 subjects). Furthermore, increasing cognitive demand during walking, by deprivation of visual feedback, counteracted the decrease in Oxy-Hb in DLPFC and lateral and medial FPC, but it did not affect the increase in Oxy-Hb in VLPFC. Taken together, the profound and localized Oxy-Hb increase is a unique response for the VLPFC. The regional heterogeneity of the prefrontal Oxy-Hb responses to natural overground walking was accentuated by increasing walking speed or cognitive demand, suggesting functional distinction within the PFC.
ROMK channels are inhibited in the aldosterone-sensitive distal nephron of renal tubule Nedd4-2-deficient mice
Authors: Zhang Dan-Dan , Zheng Jun-Ya , Duan Xin-Peng , Lin Dao-Hong , Wang Wen-Hui
Published: November 2021

We demonstrate that renal outer medullary K+ (ROMK) channel activity is inhibited in the late distal convoluted tubule/initial connecting tubule and cortical collecting duct of neural precursor cell-expressed developmentally downregulated protein 4-2 (Nedd4-2)-deficient mice. Also, deletion of Nedd4-2 abolishes the stimulatory effect of dietary K+ intake on ROMK. The lack of high K+-induced stimulation of ROMK is associated with the absence of high K+-induced inhibition of with no lysine kinase 1.
Home Automation and RFID-Based Internet of Things Security: Challenges and Issues
Authors: Fatima Haram , Khan Habib Ullah , Akbar Shahzad
Published: November 2021

Internet of Things (IoT) protection refers to the software field related to securing the Internet of Things and associated linked devices and systems. The IoT is a system of interconnected computers, sensors, actuators, or people on the World Wide Web (WWW). All these different devices have a unique identity in the IoT and must convey data across the network automatically. If computers are not adequately secured, allowing them to connect to the Internet exposes them to a range of serious vulnerabilities. Because the consequences of IoT failures are severe, it is necessary to observe and analyze security issues related to IoT. The prime goal of IoT security is to protect personal safety, while also guaranteeing and ensuring accessibility. In the context of IoT technology, the present study conducts a systematic literature review that analyzes the security problems associated with commercial and educational applications of home automation and details the technical possibilities of IoT with respect to the network layer. In this systematic review, we discuss how current contexts result in the inability of designers of IoT devices to enhance their cyber-security initiatives. Typically, application developers are responsible for training themselves to understand recent security advancements. As a result, active participation on the ridge scale with passive improvement can be achieved. A comparative analysis of the literature was conducted. The main objective of this research is to provide an overview of current IoT security research in home automation, particularly those using authentication methods in different devices, and related technologies in radio frequency identification (RFID) on network layers. IoT security issues are addressed, and various security problems in each layer are analyzed. We describe cross-layer heterogeneous integration as a domain of IoT and demonstrate how it can provide some promising solutions.
Research on Wind Load Calculation Based on Identical Guarantee Rate Method
Authors: Ye Tao , Zhu Ledong , Tan Zhongxu , Li Lanlan
Published: November 2021

Wind load on building surface is one of the main loads for structural design; scholars in this field have put forward some methods to calculate wind load, such as Simiu method and Kasperski method. Based on the basic theory of probability and the systematic analysis of the surrounding environment and turbulence, a random variable model for calculating wind load is established. According to the model, through the analysis of the relationship between guarantee rate and wind load, a numerical calculation method to calculate wind load is proposed based on extreme value analysis and polynomial fitting theory. To verify the performance of the algorithm, wind tunnel experiments were carried out to obtain a large number of first‐hand measured data of high‐rise building (Shanghai World Financial Center). Based on the measured data, the algorithm is simulated, and calculated results are analyzed, including wind pressure distribution on building and probability distribution of fluctuating wind pressure of some measuring points. The validity and accuracy of the proposed model and algorithm are verified by the comparative analysis and theoretical analysis of the calculation results.
CT Image Feature under Intelligent Algorithm in the Evaluation of Continuous Blood Purification in the Treatment and Nursing of Pulmonary Infection-Caused Severe Sepsis
Authors: Liu Liping , Liu Yanyan , Xing Aimin , Chen Siyu , Gu Mingli
Published: November 2021

This study was to explore the CT image features based on intelligent algorithm to evaluate continuous blood purification in the treatment of severe sepsis caused by pulmonary infection and nursing. 50 patients in the hospital were selected as the research objects. Convolutional neural network algorithm was used to segment CT images of severe sepsis caused by pulmonary infection. They were randomly divided into 25 cases of experimental group and 25 cases of control group. The experimental group was given continuous blood purification treatment, combined with comprehensive nursing. The control group was given routine treatment and basic nursing. Fasting plasma glucose (FPG) and fasting insulin (FIN), interleukin-6 (IL-6), tumor necrosis factor (TNF-α), high-sensitivity c-reactive protein (hs-CRP) levels, CD3+, CD4+, CD4+/CD8+ levels, ICU monitoring time, malnutrition inflammation score (MIS), and incidence of adverse events were compared between the two groups before and after treatment. There was no difference in FPG and FIN between the two groups before treatment. After treatment, the FPG and FIN of the experimental group were lower than those of the control group, and there was statistical significance (

P
<
0.05

). There was no difference in IL-6, TNF-α, and hs-CRP between the two groups before treatment. After treatment, IL-6, TNF-α, and hs-CRP in the experimental group were lower than those in the control group. There was no difference in the percentage of CD3+, CD4+, and CD4+/CD8+ between the two groups before treatment. After treatment, the CD3+, CD4+, and CD4+/CD8+ in the experimental group were higher than those in the control group. The ICU monitoring time, MIS, and incidence of adverse events in the experimental group were lower than those in the control group (

P
>
0.05

). Convolutional neural network algorithm can accurately identify and segment CT images of patients with severe sepsis, which has high clinical application value. Continuous blood purification therapy can effectively control blood glucose level, improve immune function, and reduce the content of inflammatory factors in patients with severe sepsis caused by pulmonary infection. Effective nursing measures can improve the therapeutic effect.
Alkali‐Active Sand Slate Powder for Use as Mineral Admixture in Mass Hydraulic Concrete: Technical and Economic Analysis
Authors: Chen Xia , Zhou Xian , Peng Ziling , Li Jiazheng
Published: November 2021

This work has launched a comprehensive investigation on the macro performance and micro structure of mass concrete produced with alkali‐active sand slate powder (ASSP) for use as the mineral admixture and a thorough analysis on its technical and economic effects is also conducted. Results indicated ternary blend with hybrid of 5–8 wt.% silica fume (SF) and 15–20 wt.% ASSP has the optimal compressive and flexural strength. ASSP particle participates in hydration, accelerates hydration of cement clinker within 8.5 hours, and reduces the autogenous strain of pastes by 164 × 10−6 in case of dosage less than 25% by mass. Improvement in the mechanical and deformation properties of concrete produced with the hybrid of SF and ASSP is attributed to better particles gradation, compactness enhancement, and transformation in products of hydration. On the whole, it provides another new approach for use of alkali‐active rock after second processing as mineral admixture in hydraulic concrete in terms of good performance and economic effects.
Deep Learning-Based Three-dimensional Transvaginal Ultrasound in Diagnosis of Intrauterine Adhesion
Authors: Li Ji , Liu Dan , Qing Xiaofeng , Yu Lanlan , Xiang Huizhen
Published: November 2021

This study was aimed to enhance and detect the characteristics of three-dimensional transvaginal ultrasound images based on the partial differential algorithm and HSegNet algorithm under deep learning. Thereby, the effect of quantitative parameter values of optimized three-dimensional ultrasound image was analyzed on the diagnosis and evaluation of intrauterine adhesions. Specifically, 75 patients with suspected intrauterine adhesion in hospital who underwent the hysteroscopic diagnosis were selected as the research subjects. The three-dimensional transvaginal ultrasound image was enhanced and optimized by the partial differential equation algorithm and processed by the deep learning algorithm. Subsequently, three-dimensional transvaginal ultrasound examinations were performed on the study subjects that met the standards. The March classification method was used to classify the patients with intrauterine adhesion. Finally, the results by the three-dimensional transvaginal ultrasound were compared with the diagnosis results in hysteroscope surgery. The results showed that the HSegNet algorithm model realized the automatic labeling of intrauterine adhesion in the transvaginal ultrasound image and the final accuracy coefficient was 97.3%. It suggested that the three-dimensional transvaginal ultrasound diagnosis based on deep learning was efficient and accurate. The accuracy of the three-dimensional transvaginal ultrasound was 97.14%, the sensitivity was 96.6%, and the specificity was 72%. In conclusion, the three-dimensional transvaginal examination can effectively improve the diagnostic efficiency of intrauterine adhesion, providing theoretical support for the subsequent diagnosis and grading of intrauterine adhesion.
A Commitment Scheme with Output Locality-3 Fit for the IoT Device
Authors: Miyaji Hideaki , Wang Yuntao , Kawachi Akinori , Miyaji Atsuko
Published: November 2021

Low output locality is a property of functions, in which every output bit depends on a small number of input bits. In IoT devices with only a fragile CPU, it is important for many IoT devices to cooperate to execute a single function. In such IoT’s collaborative work, a feature of low output locality is very useful. This is why it is desirable to reconstruct cryptographic primitives with low output locality. However, until now, commitment with a constant low output locality has been constructed by using strong randomness extractors from a nonconstant-output-locality collision-resistant hash function. In this paper, we construct a commitment scheme with output locality-3 from a constant-output-locality collision-resistant hash function for the first time. We prove the computational hiding property of our commitment by the decisional

M
,
δ

-bSVP assumption and prove the computational binding property by the

M
,
δ

-bSVP assumption, respectively. Furthermore, we prove that the

M
,
δ

-bSVP assumption can be reduced to the decisional

M
,
δ

-bSVP assumption. We also give a parameter suggestion for our commitment scheme with the 128 bit security.
Proteomic Analysis of Human Serum for Patients at Different Pathological Stages of Hepatic Fibrosis
Authors: Zhao Kang , Huang Jucun , Xia Hongmei , Zhang Jianjun , Liu Liming
Published: November 2021

Background. Hepatic fibrosis is a severe liver disease that has threatened human health for a long time. In order to undergo timely and adequate therapy, it is important for patients to obtain an accurate diagnosis of fibrosis. Laboratory inspection methods have been efficient in distinguishing between advanced hepatic fibrosis stages (F3, F4), but the identification of early stages of fibrosis has not been achieved. The development of proteomics may provide us with a new direction to identify the stages of fibrosis. Methods. We established serum proteomic maps for patients with hepatic fibrosis at different stages and identified differential expression of proteins between fibrosis stages through ultra‐high‐performance liquid chromatography tandem mass spectrometry proteomic analysis. Results. From the proteomic profiles of the serum of patients with different stages of liver fibrosis, a total of 1,338 proteins were identified. Among three early fibrosis stages (control, F1, and F2), 55 differential proteins were identified, but no proteins simultaneously exhibited differential expression between control, F1, and F2. Differential proteins were detected in the comparison between different fibrosis stages. Significant differences were found between advanced fibrosis stages (F2‐vs.‐F3 and F3‐vs.‐F4) through a series of statistical analysis, including hierarchical clustering, Gene Ontology (GO) functional annotation, Kyoto Encyclopedia of Genes and Genomes pathway, and protein‐protein interaction network analysis. The differential proteins identified by GO annotation were associated with biological processes (mainly platelet degranulation and cell adhesion), molecular functions, and cellular components. Conclusions. All potential biomarkers identified between the stages of fibrosis could be key points in determining the fibrosis staging. The differences between early stages may provide a useful reference in addressing the challenge of early fibrosis staging.
A Decision-Making Approach for Ranking Tertiary Institutions’ Service Quality Using Fuzzy MCDM and Extended HiEdQUAL Model
Authors: Oladipupo Olufunke , Amoo Taiwo , Daramola Olawande
Published: November 2021

The attainment of excellence in institutions is maintained through the institutions’ adherence to its core values and efficient service delivery. These factors are very important in facilitating global development of a country and determining the world ranking of an institution. To this effect, this study presents an effective approach for evaluating and ranking quality of services in a higher institution, taking four higher institutions in Nigeria as case studies. Service quality consists of different attributes and many of them are intangible and difficult to measure, which means that using the previously known measurement approach will be insufficient. Therefore, a fuzzy method was proposed to resolve the ambiguity of the concepts and intra-uncertainty, which are associated with human judgments in decision-making. This study adopted a contextualized service quality model for educational domain called HiEdQUAL with some extended criteria in order to evaluate the perception of service quality by respondents from the selected higher institutions: two private universities and two public universities from the south-west region of Nigeria. Four Multi-Criteria Decision-Making (MCDM) methods: TOPSIS, Yager’s min-max, Compensatory AND, and Ordered Weighted Averaging are applied to comparatively evaluate the quality of services in the four higher institutions. The MCDM methods are engaged independently to validate the reliability of the ranking results. The importance weight of each performance criterion is found with Fuzzy Analytical Hierarchy Process (FAHP) algorithm. This study has been able to practically establish Ext-HiEdQUAL as a new service quality model for higher education with six concepts and 33 criteria. The output of the Fuzzy MCDM ranking recommends institution B as the best institution to students based on the Ext-HiEdQUAL measures. Also, findings from the sensitivity analysis showed that Yager’s min-max outperform the other investigated methods in this study by being consistent and exceptionally tolerant in most instances when there is significant deviation in criteria weights.
Cost‐Effectiveness Analysis of Biopharmaceuticals for Treating Rheumatoid Arthritis: Infliximab, Adalimumab, and Etanercept
Authors: Gholami Ahmad , Azizpoor Jassem , Aflaki Elham , Rezaee Mehdi , Keshavarz Khosro
Published: November 2021

Introduction. Rheumatoid arthritis (RA) is a chronic progressive inflammatory disease that causes joint destruction. The condition imposes a significant economic burden on patients and societies. The present study is aimed at evaluating the cost‐effectiveness of Infliximab, Adalimumab, and Etanercept in treating rheumatoid arthritis in Iran. Methods. This is a cost‐effectiveness study of economic evaluation in which the Markov model was used. The study was carried out on 154 patients with rheumatoid arthritis in Fars province taking Infliximab, Adalimumab, and Etanercept. The patients were selected through sampling. In this study, the cost data were collected from a community perspective, and the outcomes were the mean reductions in DAS‐28 and QALY. The cost data collection form and the EQ‐5D questionnaire were also used to collect the required data. The results were presented in the form of an incremental cost‐effectiveness ratio, and the sensitivity analysis was used to measure the robustness of the study results. The TreeAge Pro and Excel softwares were used to analyze the collected data. Results. The results showed that the mean costs and the QALY rates in the Infliximab, Adalimumab, and Etanercept arms were $ 79,518.33 and 12.34, $ 91,695.59 and 13.25, and $ 87,440.92 and 11.79, respectively. The one‐way sensitivity analysis confirmed the robustness of the results. In addition, the results of the probabilistic sensitivity analysis (PSA) indicated that on the cost‐effectiveness acceptability curve, Infliximab was in the acceptance area and below the threshold in 77% of simulations. The scatter plot was in the mentioned area in 81% and 91% of simulations compared with Adalimumab and Etanercept, respectively, implying lower costs and higher effectiveness than the other two alternatives. Therefore, the strategy was more cost‐effective. Conclusion. According to the results of this study, Infliximab was more cost‐effective than the other two medications. Therefore, it is recommended that physicians use this medication as the priority in treating rheumatoid arthritis. It is also suggested that health policymakers consider the present study results in preparing treatment guidelines for RA.
A Deep Learning Framework Based on Multisensor Fusion Information to Identify the Airplane Wake Vortex
Authors: Ai Yi , Wang Yuanji , Pan Weijun , Wu Dingjie
Published: November 2021

Along with the rapid improvement of the aviation industry, flight density also increases with the increase of flight demand, which directly leads to the increasingly prominent influence of wake vortex on flight safety and aviation control. In this paper, we propose a new joint framework—a deep learning framework—based on multisensor fusion information to address the detection and identification of wake vortices in the near‐Earth phase. By setting multiple Doppler lidar in near‐Earth flight areas at different airports, a large number of accurate wind field data are captured for wake vortex detection. Meanwhile, the airport surveillance radar is used to locate the wake vortex. In the deep learning framework, an end‐to‐end CNN‐LSTM model has been employed to identify the airplane wake vortex from the data detected by Doppler lidar and the airport surveillance radar. The variables including the wind field matrix, positioning matrix, and the variance sequence are used as inputs to the CNN channel and LSTM channel. The identification and location information of the wake vortex in the wind field image will be output by the framework. Experiments show that the joint framework based on a multisensor possesses stronger ability to capture local feature and sequence feature than the traditional CNN or LSTM model.
Metformin Increases Sensitivity of Melanoma Cells to Cisplatin by Blocking Exosomal-Mediated miR-34a Secretion
Authors: Ge Lan , Wu Yaguang , Wan Ming , You Yi , Zhai Zhifang , Song Zhiqiang
Published: November 2021

Melanoma, also known as malignant melanoma, is a type of cancer derived from the pigment-containing cells known as melanocytes. Cisplatin (CDDP) is widely used in the treatment of different types of tumors with high response rates, but it generally has low efficiency in melanoma. This study aimed to investigate whether metformin could sensitize the melanoma cell line A375 to cisplatin. Our results for the first time indicated that CDDP increased the miR-34a secretion by exosomes in melanoma A375 cells, which was, at least partially, related to the cisplatin resistance of melanoma cells. Moreover, metformin significantly sensitized A375 cells to cisplatin. Mechanistically, metformin significantly blocked the exosome-mediated miR-34a secretion induced by cisplatin. Our study not only reveals a novel mechanism that exosomal secretion of miR-34a is involved in the cisplatin resistance of melanoma cells but also provides a promising therapeutic strategy by synergistic addition of metformin.
Exploration of the Key Proteins of High-Grade Intraepithelial Neoplasia to Adenocarcinoma Sequence Using In-Depth Quantitative Proteomics Analysis
Authors: Zhang Yin , Li Chun-Yuan , Pan Meng , Li Jing-Ying , Ge Wei , Xu Lai , Xiao Yi
Published: November 2021

Purpose. In this study, we aimed to provide a comprehensive description of typical features and identify key proteins associated with the high-grade intraepithelial neoplasia- (HIN-) adenocarcinoma (AC) sequence. Methods. We conducted tandem mass tag-based quantitative proteomic profiling of normal mucosa, HIN, and AC tissues. Protein clusters representative of the HIN-AC sequence were identified using heatmaps based on Pearson’s correlation analysis. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Reactome analyses were performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) database, ClueGO plugin in Cytoscape, and the Metascape database. The prognostic value of the key proteins and their effects on the tumor microenvironment and consensus molecular subtype were explored based on The Cancer Genome Atlas. Results. We identified 536 proteins categorized into three clusters. Among the biological processes and pathways of the highly expressed proteins in the HIN-AC sequence, proteins were predominantly enriched in response to gut microbiota, cell proliferation, leukocyte migration, and extracellular matrix (ECM) organization events. SERPINH1 and P3H1 were identified as the key proteins that promote the HIN-AC sequence. In the correlation analysis of infiltrating immune cells, both SERPINH1 and P3H1 expression correlated negatively with tumor purity, while correlating positively with abundance of CD8+ T cells, B cells, macrophage/monocytes, dendritic cells, cancer-associated fibroblasts, endothelial cells, neutrophils, and natural killer cells. Furthermore, both SERPINH1 and P3H1 expression positively correlated with common immune checkpoints and mesenchymal molecular subtype. High P3H1 expression was associated with poor disease-free survival and overall survival. Conclusions. ECM-related biological processes and pathways are typical features of the HIN-AC sequence. SERPINH1 and P3H1 might be the key proteins in this sequence and be related to ECM remodeling and immune suppression status in CRC.
Exploring the Mechanisms of Arsenic Trioxide (Pishuang) in Hepatocellular Carcinoma Based on Network Pharmacology
Authors: Wang Xinmiao , Cao Luchang , Wu Jingyuan , Zhu Guanghui , Zhu Xiaoyu , Zhang Xiaoxiao , Han Duoduo , Shui Ning , Ni Baoyi , Li Jie
Published: November 2021

Objective. Arsenic trioxide (Pishuang, Pishi, arsenolite, As2O3, and CAS 1327-53-3), a naturally occurring and toxic mineral as a drug for more than 2000 years in China, has been found to have a valuable function in hepatocellular carcinoma (HCC) in recent years. However, its exact mechanism remains to be elucidated. Therefore, this study was intended to explore the potential anti-HCC mechanism of arsenic trioxide through network pharmacology. Methods. The potential targets of arsenic trioxide were collected from PubChem and TargetNet. HCC targets were obtained from the GeneCards database. Then, a protein-protein interaction (PPI) network of arsenic trioxide and HCC common targets was established using STRING. GO and KEGG pathway enrichment analyses were performed by the Database for Annotation, Visualization, and Integrated Discovery (DAVID). Finally, an arsenic trioxide-target-pathway-HCC network was built by Cytoscape 3.2.1, and network topological analysis was carried out to screen the key candidate targets. Results. A total of 346 corresponding targets of arsenic trioxide and 521 HCC-related targets were collected. After target mapping, a total of 52 common targets were obtained. GO analysis showed that the biological process was mainly involved in the negative regulation of cellular senescence, response to tumor necrosis factor, and cellular response to hypoxia. Molecular functions included NF-kappa B binding, enzyme binding, p53 binding, and transcription factor binding. Cellular components mainly were replication fork, ESC/E(Z) complex, RNA polymerase II transcription factor complex, and organelle membrane. KEGG pathways were mainly enriched in the PI3K-Akt signaling pathway, VEGF signaling pathway, p53 signaling pathway, HIF-1 signaling pathway, TNF signaling pathway, AMPK signaling pathway, NF-kappa B signaling pathway, FoxO signaling pathway, ErbB signaling pathway, and MAPK signaling pathway. In the arsenic trioxide-target-pathway-HCC network, targets such as AKT1, RAF1, RELA, TP53, and PTEN had a higher degree. Conclusions. Our study showed that key targets of arsenic trioxide were mainly involved in multiple biological processes and pathways. It provided a theoretical basis for the screening of drug targets.
Degradation of Lignocelluloses Cocoa Shell (Theobroma cacao L.) by Various Types of Mould Treatments
Authors: Djali Mohamad , Kayaputri Indira Lanti , Kurniati Dian , Sukarminah Een , Mudjenan Inna Muslimah Hanifa , Utama Gemilang Lara
Published: November 2021

Lignocellulose can be degraded by lignocellulolytic microorganisms such as moulds. The purpose of the study was to obtain the right type of moulds in degrading lignocellulose on the cocoa shell powder. The study used a completely randomized design method using four treatments of different types of mould (Trichoderma viride, Neurospora sitophila, Aspergillus niger, and Rhizopus oryzae) towards cocoa shell powder fermentation. Solid fermentation of cocoa shell powder was carried out for 5 days in an incubator with a temperature of 30°C for T. viride, N. sitophila, and R. oryzae, while A. niger of 35°C. The fermented substrate was then dried in a cabinet oven with a temperature of 50°C for 4 days. Tests of lignin, cellulose, and hemicellulose were performed towards the treatments by the Chesson method, while the moisture content test was performed using the AOAC method. Degradation of fermented cocoa shell powder has shown a significant effect on moisture, lignin, cellulose, and hemicellulose contents. Trichoderma viride resulted in the highest lignocellulose degradation compared with the other treatments. The percentage decrease of lignin content is up to 46.69 wt%; while cellulose of 22.59 wt%; and hemicellulose is about 19.41 wt% from the initial lignin weight.
A New Root‐Finding Algorithm for Solving Real‐World Problems and Its Complex Dynamics via Computer Technology
Authors: Naseem Amir , Rehman M. A. , Younis Jihad
Published: November 2021

Nowadays, the use of computers is becoming very important in various fields of mathematics and engineering sciences. Many complex statistics can be sorted out easily with the help of different computer programs in seconds, especially in computational and applied Mathematics. With the help of different computer tools and languages, a variety of iterative algorithms can be operated in computers for solving different nonlinear problems. The most important factor of an iterative algorithm is its efficiency that relies upon the convergence rate and computational cost per iteration. Taking these facts into account, this article aims to design a new iterative algorithm that is derivative‐free and performs better. We construct this algorithm by applying the forward‐ and finite‐difference schemes on Golbabai–Javidi’s method which yields us an efficient and derivative‐free algorithm whose computational cost is low as per iteration. We also study the convergence criterion of the designed algorithm and prove its quartic‐order convergence. To analyze it numerically, we consider nine different types of numerical test examples and solve them for demonstrating its accuracy, validity, and applicability. The considered problems also involve some real‐life applications of civil and chemical engineering. The obtained numerical results of the test examples show that the newly designed algorithm is working better against the other similar algorithms in the literature. For the graphical analysis, we consider some different degrees’ complex polynomials and draw the polynomiographs of the designed quartic‐order algorithm and compare it with the other similar existing methods with the help of a computer program. The graphical results reveal the better convergence speed and the other graphical characteristics of the designed algorithm over the other comparable ones.