bluuebunny/crossref_metadata_2025 huggingface dataset:
English Pronunciation Calibration Model Based on Multimodal Acoustic Sensor
Authors: Zhou Yurui , Zhao Guolong
Published: April 2022

In recent years, with the increasing frequency of international exchanges, people have gradually realized that language is a tool of communication and communication, and language learning should attach importance to oral teaching. However, in traditional classrooms, one of the problems faced by oral teaching is the mismatch of the teacher-student ratio: a teacher has to deal with dozens of students, one-on-one oral teaching and pronunciation guidance is impossible, and it is also affected by the teachers and the environment constraints. Therefore, the research on how to efficiently automate pronunciation training is becoming more and more popular. Many phonemes in English have different facial visual features, especially vowels. Almost all of them can be distinguished by the roundness and tightness of the lips in appearance. In order to give full play to the role of lip features in oral pronunciation error detection, this paper proposes a multimodal feature fusion model based on lip angle features. The model interpolates the lip features constructed based on the opening and closing angles and combines audio and video in time series. Feature alignment and fusion and feature learning and classification are realized through the two-way LSTM SOFTMAX layer, and finally, end-to-end pronunciation error detection is realized through CTC. It is verified on the GRID audio and video corpus after phoneme conversion and the self-built multimodal test set. The experimental results show that the model has a higher false pronunciation recognition rate than the traditional single-modal acoustic error detection model. The increase in error detection rate is more obvious. Verification by the audio and video corpus with white noise was added, and the proposed model has better noise immunity than the traditional acoustic model.
Prediction-Based Resource Deployment and Task Scheduling in Edge-Cloud Collaborative Computing
Authors: Su Mingfeng , Wang Guojun , Choo Kim-Kwang Raymond
Published: April 2022

Edge computing is becoming increasingly commonplace, as consumer devices become more computationally capable and network connectivity improves (e.g., due to 5G). With the rapid development of edge computing and Internet of Things (IoT), the use of edge-cloud collaborative computing to provide service-oriented network application (i.e., task) in edge-cloud IoT has become an important research topic. In this paper, we present an edge-cloud collaborative computing framework and our resource deployment algorithm with task prediction (RDAP). Based on our paradigm, tasks in the cloud service center are predicted using the two-dimensional time series, and task classification aggregation and delay threshold determination are combined to optimize task resource deployment of edge servers. A task scheduling algorithm with Pareto improvement (TSAP) is also proposed. At the edge servers, the Pareto progressive comparison is conducted in two stages to obtain the tangent point or any intersection point of the two objective curves of user’s quality of service and effect of system service to optimize task scheduling. The experimental results show that for varying user task scales and different Zipf distribution

α

parameters, combining RDAP and TSAP (RDAP-TSAP) can improve the average user task hit rate. In addition, the average task completion time of users, the overall system service effect, and the total task delay rate of RDAP-TSAP are better than TSAP and the benchmark algorithms for task scheduling.
Mechanical Property of Biomodified Geogrid and Reinforced Calcareous Sand
Authors: Ou Qiang , Li Yifu , Yang Yang , Luo Zhaogang , Han Shaokang , Zou Tan
Published: April 2022

The strength and deformation properties of maritime geotechnical structures made primarily of calcareous sand are critical for project safety. The geogrid reinforcement is developed as a promising approach to improve the mechanical properties of calcareous sand. This study investigates the mechanical property of biomodified geogrid via a microbially induced calcite precipitation (MICP) process to improve the effectiveness of geogrid for reinforcement of calcareous sand. A series of unconsolidated undrained triaxial experiments were conducted to evaluate the mechanical property and deformation behaviors of biomodified geogrid and reinforced calcareous sand (BGRCS), taking into consideration the impacts of the geogrid layer, times of biotreatment, and confining pressure. Compared to the untreated geogrid, the strength of the BGRCS is distinctly changed due to the increase roughness, and the deviatoric stress-strain curves are evidently hardening. Strength and pseudocohesive force can be further enhanced by raising the geogrid layer of the reinforced specimens, while internal friction angle also increases the amplitude of variation with the times of biotreatment. The geogrid, times of biotreatment, and confining pressure are all intimately related to the strength and the deformation of the reinforced specimens. The interactions of geogrid ribs and calcareous sand particles are analyzed and friction using scanning electron microscope tests that could provide a reference for revealing the mechanical mechanism of BGRCS.
Artificial Intelligence Algorithm-Based Differential Diagnosis of Crohn’s Disease and Ulcerative Colitis by CT Image
Authors: Jiang Fangyun , Fu Xiaoping , Kuang Kai , Fan Dan
Published: April 2022

The aim of this study was to investigate the effect of low-dose CT enterography (CTE) based on modified guided image filtering (GIF) algorithm in the differential diagnosis of ulcerative colitis (UC) and Crohn’s disease (CD). Methods. One hundred and twenty patients with suspected diagnosis of IBD were studied. They were randomly divided into control group (routine CT examination) and observation group (low-dose CTE examination based on improved GIF algorithm), with 60 cases in each group. Comprehensive diagnosis was used as the standard to assess the diagnostic effect. Results. (1) The peak signal-to-noise ratio (PSNR) (26.02 dB) and structural similarity (SSIM) (0.8921) of the algorithm were higher than those of GIF (17.22 dB/0.8491), weighted guided image filtering (WGIF) (23.78 dB/0.8489), and gradient domain guided image filtering (GGIF) (23.77 dB/0.7567) (

P
<
0.05

); (2) the diagnostic sensitivity (91.49%), specificity (92.31%), accuracy (91.67%), positive predictive value (97.73%), and negative predictive value (75%) of the observation group were higher than those of the control group (

P
<
0.05

); the sensitivity and specificity of CTE in the diagnosis of UD and CD were 96.77% and 81.25% and 98.33% and 93.33%, respectively (

P
<
0.05

); there were significant differences in symmetrical intestinal wall thickening and smooth serosal surface between UD and CD (

P
<
0.05

). Conclusion. (1) The improved GIF algorithm has a more effective application value in the denoising processing of low-dose CT images and can better improve the image quality; (2) the accuracy of CTE in the diagnosis of IBD is high, and CTE is of great value in the differential diagnosis of UD and CD.
Investigation of Initial Atmospheric Corrosion of Carbon and Weathering Steels Exposed to Urban Atmospheres in Myanmar
Authors: Thandar Wint , Win Yu Yu Kyi , Khaing Thinzar , Suzuki Yasuo , Sugiura Kunitomo , Nishizaki Itaru
Published: April 2022

This research is aimed at studying the corrosion rates of carbon and weathering steels due to exposure at three urban exposure sites and the characteristics of corrosion products of carbon steel in Yangon, Myanmar. The ISO 9223 standard was used to classify the corrosion aggressiveness of the atmosphere. There is a high level of time of wetness (TOW) class which is

τ

4

in the south and

τ

3

in the central part of Myanmar. At the recent exposure sites in Myanmar, the atmospheric impurities are low, so the corrosion rates of carbon and weathering steels are mainly governed by TOW. The corrosion rates of test sites fall into the ISO C2 category. It appears that corrosion kinetics fit the power model well, since the correlation coefficient is high. Various morphologies of corrosion products including globular, flowery, and sandy lepidocrocite emerged in the early stage of exposure. The longer TOW conditions resulted in the formation of lepidocrocite and goethite. The growth of goethite products on carbon steel was discovered after nine months of exposure.
Successful Treatment of Severe Paravalvular Leak by Repositioning a Self-Expandable Percutaneous Aortic Valve Bioprosthesis (Evolut PRO+) Using the “Double Snare” Technique
Authors: González-Bravo Diego H. , Colón-Hernández Pedro , Quintana-Serrano Melanie , Alegre-Boschetti Sergio , Vázquez-Fuster Juan , Acevedo-Valles José J. , Avilés-Rivera Eric
Published: April 2022

Significant (moderate or severe) paravalvular leak (PVL) after transcatheter aortic valve replacement (TAVR) remains a common phenomenon and has been associated with decrease survival and quality of life. Transcatheter valve embolization and migration (TVEM) is a rare post-TAVR complication that can occur in 1% of cases and has been associated with worse patient outcomes. Valve embolization or migration into the left ventricle can result in significant PVL causing hemodynamic instability, shock, heart failure, and hemolytic anemia. Although this complication most commonly occurs in the acute setting (90%) within 4 hours of TAVR, it can also present late (4 hr-43 days later) in 10% of cases. There are no clear guidelines as to how this condition should be managed; however, several percutaneous bailout techniques exist that can ultimately spare the patient from emergent cardiovascular surgery. We present a rare case of late ventricular transcatheter aortic valve migration 3 days after TAVR causing severe PVL and heart failure symptoms that was successfully treated using the percutaneous “double snare” technique.
A New Method on Construction of Brain Effective Connectivity Based on Functional Magnetic Resonance Imaging
Authors: Zhang Jincan , Yang Wenya , Nan Jiaofen
Published: April 2022

Most of the existing methods about the causal relationship based on functional magnetic resonance imaging (fMRI) data are either the hypothesis-driven methods or based on a linear model, which can result in the deviation for detecting the original brain activity. Therefore, it is necessary to develop a new method for detecting the effective connectivity (EC) of the brain activity by the nonlinear calculation. In this study, we firstly proposed a new technology evaluating effective connectivity of the human brain based on back-propagation neural network with nonlinear model, named EC-BP. Next, we simulated four time series for assessing the feasibility and accuracy of EC-BP compared to Granger causality analysis (GCA). Finally, the proposed EC-BP was applied to the brain fMRI from 60 healthy subjects. The results from the four simulated time series showed that the proposed EC-BP can detect the originally causal relationship, consistent with the actual causality. However, the GCA can not find nonlinear causality. Based on the analysis of the fMRI data from the healthy participants, EC-BP and GCA showed the huge differences in the top 50 connections in descending order of EC. EC-BP showed all ECs related to hippocampus and parahippocampus, whereas GCA showed most ECs related to the paracentral lobule, caudate, putamen, and pallidum, which represents the brain regions with most frequent information passing measured by different methods. The proposed EC-BP method can provide supplementary information to GCA, which will promote more comprehensive detection and evaluation of brain EC.
Trigonella foenum‐graecum Methanolic Extract on Isolated Smooth Muscles and Acetylcholinesterase Enzyme: An In Vitro and Mechanistic In Silico Investigation
Authors: Ghayur Muhammad Nabeel , Abdalla Mohnad , Khalid Asaad , Ahmad Saeed , Gilani Anwarul Hassan
Published: April 2022

Background and Objective. Trigonella foenum‐graecum Linn., also called fenugreek, is a popular medicinal plant cultivated all over the globe. Fenugreek seeds are known for their many medicinal properties. We present our findings on the effect of a 70% aqueous methanolic fenugreek seed extract (Tfg.Cr) on isolated GI smooth muscles (rabbit jejunum and rat ileum) and the effect of extract and its constituent diosgenin on acetylcholinesterase (AChE) enzyme. Results. When tested on the baseline of isolated tissues, Tfg.Cr was devoid of any activity (stimulant or relaxant) till 10 mg/ml. This is an interesting finding, keeping in mind that the fenugreek seeds are used to alleviate constipation and diarrhoea. When Tfg.Cr was tried for any potential AChE inhibitory activity, it did show an inhibitory effect in increasing concentrations (47‐380 μg/ml). This inhibitory effect was comparable to the effect produced by a standard AChE inhibitor physostigmine. One of the known fenugreek constituents, diosgenin, was also tested, and it also showed an AChE inhibitory effect in a concentration‐dependent manner (11‐190 μg/ml). Interaction between diosgenin and AChE was further investigated by molecular docking and molecular dynamics simulations for 100 ns, which showed that diosgenin interacted with the active‐site gorge of AChE through hydrophobic, pi‐pi stacking, and hydrogen bonds with various amino acids of the AChE enzyme. Conclusion. The results show that the fenugreek extract does not possess any GI stimulant or relaxant activity even though it is used traditionally in GI motility disorders. The extract and diosgenin could inhibit the AChE enzyme pointing towards their benefit to enhance the memory.
Effects of Seamless Operating Room Nursing Combined with Multistyle Health Education on the Psychological State, Rehabilitation Quality, and Nursing Satisfaction in Patients with Internal Fixation of Femoral Fracture
Authors: Liu Qingyan , Wang Juan , Han Jie , You Tongyang , Li Lijuan
Published: April 2022

Objective. To explore the effects of seamless operating room nursing combined with multistyle health education on the psychological state, rehabilitation quality, and nursing satisfaction in patients with internal fixation of femoral fracture. Methods. Eighty patients who received internal fixation of femoral fracture in our hospital (November 2020–November 2021) were chosen as the research objects, and their clinical data were retrospectively analyzed. They were divided into experimental group and control group according to the sequence of hospital admission. In perioperative period, the control group received routine nursing measures and the experimental group received seamless operating room nursing combined with multistyle health education. The patients’ psychological state, rehabilitation quality, and nursing satisfaction after intervention were compared between the two groups. Results. Compared with the control group, the experimental group achieved remarkably lower score of Profile of Mood States (POMS) after nursing (

p

 < 0.001). The experimental group had much higher cognitive level scores, Harris hip score (HHS), Functional Independence Measure (FIM) score, and nursing satisfaction score in comparison with the control group (

p

 < 0.05). In perioperative period, the experimental group had much lower total incidence of complications in comparison with the control group (

p

 < 0.05). Conclusion. Seamless operating room nursing combined with multistyle health education, as an effective measure to improve the rehabilitation quality of the patients with internal fixation of femoral fracture, has better effects on improving the patients’ psychological state and reducing complications in perioperative period in comparison with the routine nursing intervention. Further studies are conducive to providing a better solution for the patients with internal fixation of femoral fracture.
New Fixed Point Theorems for Admissible Hybrid Maps
Authors: Noorwali Maha , Yeşilkaya Seher Sultan
Published: April 2022

The aim of this work is to investigate the concept of a new hybrid Suzuki contractive by using the Rus-Reich-Ćirić-type interpolative mappings in

b

-metric spaces. We seek the presence and uniqueness of a fixed point of such new contraction type mappings and prove some related results. We further give an application of Ulam-Hyers-type stability to show the well-posedness of our results.
Higher Education Management Analysis of Smart Transportation Big Data Application under the Background of Internet +
Authors: Jiang Qi , Zhang Le
Published: April 2022

Big data is an unprecedented approach, in line with the development trend of today’ s era of rapid technological development; the ultimate purpose is to analyze and process the corresponding software and data of the huge data collected. This paper is aimed at studying the higher education management of big data application in the context of Internet + and at providing comprehensive optimization and development of Internet + and higher education management services. On the whole, the article first conducts a series of detailed analysis on the concepts of Internet +, big data, and higher education management based on the understanding of the general background, followed by an in-depth study of big data service methods and then the experimental design of higher education management cases based on big data. By comparing the two test scores of the two groups, the experimental results show that the average score of the two groups has changed from a difference of only 1.1 to a difference of 5 points, 58% of the students in the experimental group were satisfied with higher education management.
Numerical Analysis of the Influence of Deep Foundation Pit Construction on Adjacent Subway Stations in Soft Soil Areas
Authors: Yang Tao , Xiong Shengyuan , Liu Shuailei , Liu Yang , Zhao Hao , Li Yanwei
Published: April 2022

Deep foundation pit construction adjacent to a subway station in a soft soil area was numerically simulated with Midas GTS NX calculation software. The influence of the deep foundation pit construction on the deformation and stress of the subway station structure was studied, and the influence of the foundation pit retaining structure on the station was analyzed. The results show that during the foundation pit excavation process, the subway station slab rose as a whole and was greatly affected by the deformation of the common ground connecting wall, with the most unfavorable position changing as the excavation area changed. The excavation of foundation pits in different zones had a considerable influence on the east‐to‐west displacement of the common diaphragm wall outside the foundation pit. The maximum positive bending moment of the common diaphragm wall changed little, while the negative bending moment increased greatly during construction. Overall, the foundation pit excavation had a great impact on the negative moment of the common diaphragm wall. During the foundation pit excavation process, the subway station column lifted upward, and the maximum displacement, which was located at the west end of the station near the foundation pit, gradually weakened from west to east. As the foundation pit excavation process continued, the maximum axial force of the station column increased by 10.38%, and the pressure was the largest in the middle column. As the thickness of the diaphragm wall increased, the stiffness of the foundation pit retaining structure increased. After earthwork excavation and unloading, the locations in the retaining structure with high stiffnesses could resist deformations. The whole foundation pit was offset due to the high stiffness of the foundation pit retaining structure, which increased the horizontal deformation of the existing station structure. With increasing thickness, the relative horizontal deformation of the station slab gradually increased, mainly because the difference between the depths of the old and new diaphragm walls caused the embedded soil of the two same deep foundation pits to differ. Furthermore, there were great differences in the Earth pressure behind the wall. As the depth of the diaphragm wall increased, the active Earth pressure behind the diaphragm wall increased.
Research on Precision Marketing Strategy and Personalized Recommendation Method Based on Big Data Drive
Authors: Gu Jinjiang
Published: April 2022

In view of the explosive growth of big data technology, precision marketing and personalized recommendation have also received the dividends of big data technology. The traditional extensive operation has not effectively combined the products of businesses with the needs of users, and the success rate of marketing is low, which has led to the crisis that operators may become “pipelines.” To meet the personalized needs of users and precision, marketing technology has been developed. This paper is based on big data technology and personalized recommendation algorithm theory and takes the marketing strategy of the actual telecommunications industry as an empirical research method. The experimental results verify that the analysis model based on big data has a good recommendation effect in precision marketing and personalized recommendation and confirm the advantages of the recommendation algorithm based on user collaborative filtering in personalized recommendation algorithm.
Development of Algorithms for an IoT-Based Smart Agriculture Monitoring System
Authors: Siddiquee Kazy Noor-e-Alam , Islam Md. Shabiul , Singh Ninni , Gunjan Vinit Kumar , Yong Wong Hin , Huda Mohammad Nurul , Naik D. S. Bhupal
Published: April 2022

Sensor-based agriculture monitoring systems have limited outcomes on the detection or counting of vegetables from agriculture fields due to the utilization of either conventional color transformations or machine learning-based methods. To overcome these limitations, this research is aimed at proposing an IoT-based smart agriculture monitoring system with multiple algorithms such as detection, quantification, ripeness checking, and detection of infected vegetables. This paper presents smart agriculture monitoring systems for Internet of Things (IoT) applications. The CHT has been applied to detect and quantify vegetables from the agriculture field. Using color thresholding and color segmentation techniques, defected vegetables have also been detected. A machine learning method-convolutional neural network (CNN) has been used for the development and implementation of all algorithms. A comparison between traditional methods and CNN has been simulated in MATLAB to find out the optimal method for its implementation in this agricultural monitoring system. Compared to the traditional methods, the CNN is the optimal method in this research work which performed better over the previously developed algorithms with an accuracy of more than 90%. As an example (case study), a tomato field in Chittagong, Bangladesh, was chosen where a camera-mounted mobile robot captured images from the agriculture field for which the proposed IoT-based smart monitoring system was developed. This system will benefit farmers through the digitally monitored output at an agriculture field in Bangladesh as well as in Malaysia. Since this proposed smart IoT-based system is still driven by bulky, costly, and limited powered sensors, in a future work, for the required power of sensors, this research work is aimed at the design and development of an energy harvester (hybrid) (HEH) based on ultralow power electronics circuits to generate the required power of sensors. Implementation of multiple algorithms using CNN, circular Hough transformation (CHT), color thresholding, and color segmentation methods for the detection, quantification, ripeness checking, and detection of infected crops.
Cybersecurity Challenges in Blockchain Technology: A Scoping Review
Authors: Mahmood Samreen , Chadhar Mehmood , Firmin Selena
Published: April 2022

Blockchain technology (BCT) is an emerging technology. Cybersecurity challenges in BCT are being explored to add greater value to business processes and reshape business operations. This scoping review paper was aimed at exploring the current literature’s scope and categorizing various types of cybersecurity challenges in BCT. Databases such as Elsevier, ResearchGate, IEEE, ScienceDirect, and ABI/INFORM Collection (ProQuest) were searched using a combination of terms, and after rigorous screening, 51 research studies were found relevant. Data coding was performed following a framework proposed for scoping review. After careful analysis, thirty different types of cybersecurity challenges in BCT were categorized into six standardized classes. Our results show that most of the studies disclose cybersecurity challenges in BCT generally without pointing to any specific industry sector, and to a very little extent, few papers reveal cybersecurity challenges in BCT related to specific industry sectors. Also, prior studies barely investigated the strategies to minimize cybersecurity challenges in BCT. Based on gap identification, future research avenues were proposed for scholars.
MISD-SLAM: Multimodal Semantic SLAM for Dynamic Environments
Authors: You Yingxuan , Wei Peng , Cai Jialun , Huang Weibo , Kang Risheng , Liu Hong
Published: April 2022

Simultaneous localization and mapping (SLAM) is one of the most essential technologies for mobile robots. Although great progress has been made in the field of SLAM in recent years, there are a number of challenges for SLAM in dynamic environments and high-level semantic scenes. In this paper, we propose a novel multimodal semantic SLAM system (MISD-SLAM), which removes the dynamic objects in the environments and reconstructs the static background with semantic information. MISD-SLAM builds three main processes: instance segmentation, dynamic pixels removal, and semantic 3D map construction. An instance segmentation network is used to provide semantic knowledge of surrounding environments in instance level. The ORB features located on the predefined dynamic objects are removed directly. In this way, MISD-SLAM effectively reduces the impact of dynamic objects to provide precise pose estimation. Then, combining multiview geometry constraint with

K

-means clustering algorithm, our system removes the undefined but moving pixels. Meanwhile, a 3D dense point cloud map with semantic information is reconstructed, which recovers the static background without the corruptions of dynamic objects. Finally, we evaluate MISD-SLAM by comparing to ORB-SLAM3 and the state-of-the-art dynamic SLAM systems in TUM RGB-D datasets and real-world dynamic indoor environments. The results indicate that our method significantly improves the localization accuracy and system robustness, especially in high-dynamic environments.
The Use of Artificial Intelligence Combined with Wireless Network in Piano Music Teaching
Authors: Yu Linna , Luo Zhifan
Published: April 2022

Artificial intelligence (AI) development gives a new development direction to the traditional education model. The education reform in the intelligent environment is urgent. Under this background, the theory, methods, and characteristics of intelligent music education are expounded based on traditional piano music education. AI and Internet-based smart piano education is introduced. The characteristics of smart piano and its methods of assisting music teaching are analyzed. Moreover, literature review and questionnaire are adopted based on intelligent music education and smart piano theory. With two universities A and B in Nanjing as the research object, the questionnaire is designed to investigate and analyze the related problems of smart piano-assisted piano basic teaching in detail. The results show that smart piano positively improves skill training and psychological training in piano teaching. Piano major learners believe that smart piano can obviously help beginners and people with low piano levels. However, smart piano is not as good as traditional piano for high-level learners. In actual teaching, teachers should use different strategies for different levels of learners. Regarding curriculum quality, teachers have not fully played the role of the smart piano, and the curriculum of smart piano-assisted basic piano teaching still needs improvement. Finally, corresponding countermeasures and suggestions for the development direction of smart piano in piano music education are put forward according to the current situation of the smart piano. The results can reflect the current situation of smart piano-assisted basic piano teaching, provide a reference for researchers in related industries, and promote the related development of smart piano.
An Effective Artificial Intelligence-Enabled Error Detection and Accuracy Estimation Technique for English Speech Recognition System
Authors: Han Lu , Du Xueqin , Yan Li , Yu Jing
Published: April 2022

Error detection and accuracy estimation in automated speech recognition (ASR) systems act a vital part in the design of human-computer spoken dialogue systems, as recognition error can hamper accurate systems in understanding the end user intentions. The major aim is to identify the errors in an utterance, and therefore, the dialogue manager can provide proper clarifications to the user. Therefore, the design of accurate error detection and accuracy determination techniques becomes essential in the ASR system. With this motivation, this paper presents a novel artificial intelligence-enabled accuracy estimation and error detection technique for the English speech recognition system (AIEDAE-ESRS). The goal of the AIEDAE-ESRS technique is to perform three actions such as confidence estimation, out-of-vocabulary (OOV) word identification, and error type categorization. In addition, the AIEDAE-ESRS technique performs different levels of preprocessing including sampling of input speech signal, bandpass filtering, and noise removal. Besides, a new deep neural network with hidden Markov model- (DNN-HMM-) based speech recognition technology is designed, which also aims to estimate the accuracy and error. Finally, the hyperparameters of the DNN-HMM model can be optimally chosen by the use of flower pollination algorithm (FPA) and thereby accomplished improved recognition performance. In order to demonstrate the better performance of the AIEDAE-ESRS technique, a series of simulations were conducted and the results are examined under varying aspects. English voice recognition system’s accuracy estimation and error detection were made possible using artificial intelligence (AIEDAE-ESRS). There are three steps in the AIEDAE-ESRS method: confidence estimation; identifying out-of-vocabulary words (OOV); and categorizing mistake types. The simulation results reported the enhanced performance of the AIEDAE-ESRS methodology over current advanced approaches. Our AIEDAE-ESRS methodology outperforms existing methodologies by a factor of ten. The simulation results demonstrated that the AIEDAE-ESRS methodology outperformed previous approaches in terms of efficiency. The improved experimental results indicated that the AIEDAE-ESRS technique produced superior results across a variety of measures.
The Mathematical Model of Marine Engine Room Equipment Based on Machine Learning
Authors: Zeng Ji , Jin Bowen , Zhang He , Mai Songyan , Yuan Bo , Jiang Hui , Yang Mengkai , Huang Chaochun
Published: April 2022

This study is aimed at reducing the occurrence of oil spill accidents in the engine room of ships and carries out risk prevention for the equipment of the port ships, thereby reducing pollution to the marine ecological environment. Firstly, the concepts and principles of cluster analysis and ship automatic identification system are expounded. Secondly, the data information collected by the ship’s automatic identification system (AIS) is combined with density-based cluster analysis. The accident area and extent at different stages of the ship’s engine room equipment are classified. Finally, cluster analysis is used to evaluate the risk of equipment of the port ship engine room. The results show that there are 43000 ship operation information points in port a, the average operating speed of ships is 9 kilometers, and the fastest operation speed is 16.9 kilometers. In addition, many ship routes in port a need to take risk prevention measures to minimize the impact between ships and reduce the risk of oil leakage in the engine room. The proposed cabin model can easily and quickly analyze the orientation information of the ship and classify all the data into different types according to the surrounding information points. AIS can realize the information transfer between ships and between ship and shore. Information such as the position, speed, and direction of the ship needs to be accurately known to ensure safety at sea. These data need to relate to some terminals and networks to form a maritime monitoring network. The ship AIS based on cluster analysis can cluster the areas where the ship’s speed and direction change significantly in the port area, effectively preventing accidents. Scientific risk prevention measures can effectively reduce the oil leakage risk of ship engine room equipment, improve the working efficiency of marine engines, and provide a strong foundation for the entire marine ecological environment protection.
New Subclass of Analytic Function Involving
q
-Mittag-Leffler Function in Conic Domains
Authors: Noor Saima , Razzaque Asima
Published: April 2022

In this paper, we formulate the

q

-analogus of differential operator associated with

q

-Mittag-Leffler function. By using this newly defined operator, we define a new subclass

k
−
U

S

q
,
γ

m

α
,
β

,

of analytic functions in conic domains. We investigate the number of useful properties such that structural formula, coefficient estimates, Fekete–Szego problem and subordination result. We also highlighted some known corollaries of our main results.
Fixed Point Results for Generalizedα,ψ-Contraction Mapping in Rectangularb-Metric Spaces
Authors: Mamud Mustefa Abduletif , Tola Kidane Koyas
Published: April 2022

In this paper, we introduce generalizedα,ψ-contraction mappings in the setting of rectangularb-metric spaces and established existence and uniqueness of fixed points for the mappings introduced. Our results extend and generalize related fixed point results in the existing literature. We derive some consequences and corollaries from our obtained results. Also, we provide examples in support of our main findings. Furthermore, we determined a solution to an integral equation by applying our obtained results.
Adapted to Survive: Targeting Cancer Cells with BH3 Mimetics
Authors: Montero Joan , Haq Rizwan
Published: April 2022

A hallmark of cancer is cell death evasion, underlying suboptimal responses to chemotherapy, targeted agents, and immunotherapies. The approval of the antiapoptotic BCL2 antagonist venetoclax has finally validated the potential of targeting apoptotic pathways in patients with cancer. Nevertheless, pharmacologic modulators of cell death have shown markedly varied responses in preclinical and clinical studies. Here, we review emerging concepts in the use of this class of therapies. Building on these observations, we propose that treatment-induced changes in apoptotic dependency, rather than pretreatment dependencies, will need to be recognized and targeted to realize the precise deployment of these new pharmacologic agents.

Significance:

Targeting antiapoptotic family members has proven efficacious and tolerable in some cancers, but responses are infrequent, particularly for patients with solid tumors. Biomarkers to aid patient selection have been lacking. Precision functional approaches that overcome adaptive resistance to these compounds could drive durable responses to chemotherapy, targeted therapy, and immunotherapies.
Exosomal miR-4639 and miR-210 in Plasma and Urine as Biomarkers in IgA Nephropathy
Authors: Zhao Shuchen , Sun Yangyang , Mao Qingyan , Zhou Cuixing , Chen Yimeng , Xue Dong
Published: April 2022

Background: It has been widely recognized that exosomal miRNAs can participate in the pathogenesis of different renal disorders and serve as disease biomarkers. Although kidney biopsy is still the gold standard for diagnosing and monitoring immunoglobulin A nephropathy (IgAN), it is highly required to identify new and effective noninvasive biomarkers for IgAN, the most frequently detected primary glomerulonephritis worldwide. Methods: Plasma and urinary exosomes were extracted by PEG precipitation. Size and morphological characteristics of plasma and urinary exosomes were observed by transmission electron microscopy and nanoparticle tracking analysis. The levels of plasma and urinary exosomes were revealed by Western blotting. The expressions of target miRNAs were revealed by in situ hybridization and qRT-PCR. Results: The levels of plasma and urinary exosomes were remarkably enhanced in IgAN patients compared with healthy controls (HCs). The expressions of miR-4639 and miR-210 in IgAN patients were significantly higher in contrast to the individuals with membranous nephropathy, minimal change nephrosis, diabetic nephropathy, or HC. These also played a valuable role in assessing the kidney function and the level of proteinuria. Furthermore, plasma and urinary exosomal miR-4639 expression was associated with more serious and active histological activity (mesangial hypercellularity, crescent, and C3 complement deposition). With an average follow-up of 8 months, miR-4639 and miR-210 expressions in plasma and urinary exosomes were higher in patients with progressive IgAN. Plasma exosomal miR-4639 and miR-210 were better than proteinuria (g/24 h) to estimate renal outcomes. Conclusion: Exosomal miR-4639 and miR-210 could be used as valid biomarkers to assist in diagnosis, evaluate severity, and assess disease development of IgAN.
Potensi Physalis Angulata (Ciplukan) sebagai Manajemen Kelainan pada Kulit
Authors: Kurniasih Wuriandaru , Yuniaswan Anggun
Published: April 2022

Physalis angulata adalah tanaman family Solanaceae yang telah lama digunakan sebagai obat tradisional dan telah dimanfaatkan untuk menyembuhkan berbagai macam penyakit di berbagai negara, termasuk Indonesia. Berbagai fitokimia yang dapat diisolasi dari P. angulata seperti karbohidrat, lipid, mineral dan vitamin serta metabolit sekunder yakni physalin, withangulatin, saponin, tannin dan flavonoid, dipercaya memiliki aktivitas farmakologis seperti antiinflamasi, imunomodulasi, antiproliferasi, antioksidan, antibakteri dan sebagainya. Physalis angulata juga digunakan sebagai obat herbal untuk berbagai macam kelainan kulit, seperti obat luka atau bisul maupun peradangan pada kulit. Saat ini penelitian P. angulata untuk kelainan pada kulit tengah banyak dikembangkan seperti sebagai adjuvant terapi Scleroderma, akselerasi penyembuhan luka dan dermatitis kontak iritan. Mengingat aktivitas farmakologi tanaman ini sangat luas, tanaman ini sangat berpotensi sebagai modalitas terapi untuk berbagai macam penyakit kulit lain. Selain untuk meneliti manfaat yang dikandung, diperlukan juga penelitian mengenai keamanan dan untuk menentukan bahan aktif yang bermanfaat untuk setiap kelainan pada kulit.
Neuroinflammation, Stem Cells, and Stroke
Authors: Anthony Stefan , Cabantan Dorothy , Monsour Molly , Borlongan Cesario V.
Published: April 2022

Stroke remains a significant unmet clinical need with few treatment options that have a very narrow therapeutic window, thereby causing massive mortality and morbidity in the United States and around the world. Accordingly, finding safe and effective novel treatments with a wider therapeutic window stands as an urgent need in stroke. The progressive inflammation that occurs centrally and peripherally after stroke serves as a unique therapeutic target to retard and even halt the secondary cell death. Stem cell therapy represents a potent approach that can diminish inflammation in both the stroke brain and periphery (eg, spleen), advancing a paradigm shift from a traditionally brain-focused therapy to treating stroke as a neurological disorder with a significant peripheral pathology. The purpose of this review article is to highlight the inflammation-mediated secondary cell death that plagues both brain and spleen in stroke and to evaluate the therapeutic potential of stem cell therapy in dampening these inflammatory responses.
Adaptive Ranking-Based Constraint Handling for Explicitly Constrained Black-Box Optimization
Authors: Sakamoto Naoki , Akimoto Youhei
Published: April 2022

We propose a novel constraint-handling technique for the covariance matrix adaptation evolution strategy (CMA-ES). The proposed technique is aimed at solving explicitly constrained black-box continuous optimization problems, in which the explicit constraint is a constraint whereby the computational time for the constraint violation and its (numerical) gradient are negligible compared to that for the objective function. This method is designed to realize two invariance properties: invariance to the affine transformation of the search space, and invariance to the increasing transformation of the objective and constraint functions. The CMA-ES is designed to possess these properties for handling difficulties that appear in black-box optimization problems, such as non-separability, ill-conditioning, ruggedness, and the different orders of magnitude in the objective. The proposed constraint-handling technique (CHT), known as ARCH, modifies the underlying CMA-ES only in terms of the ranking of the candidate solutions. It employs a repair operator and an adaptive ranking aggregation strategy to compute the ranking. We developed test problems to evaluate the effects of the invariance properties, and performed experiments to empirically verify the invariance of the algorithm. We compared the proposed method with other CHTs on the CEC 2006 constrained optimization benchmark suite to demonstrate its efficacy. Empirical studies reveal that ARCH is able to exploit the explicitness of the constraint functions effectively, sometimes even more efficiently than an existing box-constraint handling technique on box-constrained problems, while exhibiting the invariance properties. Moreover, ARCH overwhelmingly outperforms CHTs by not exploiting the explicit constraints in terms of the number of objective function calls.
Ritual Officials and the Rise of Confucian Ritualism in the Eleventh Century
Authors: Yu Cheung Hiu
Published: April 2022

By tracing the vicissitudes of court ritual officials and related ritual institutions in the eleventh century, this article argues that the rise of Confucian ritualism was accompanied by the marginalization of ritual officials and institutions in the central government of the Northern Song (960–1127). After the mid-eleventh century, “learning-oriented ritualists,” who acquired their knowledge of court rituals mostly through Confucian ritual Classics, succeeded the fallen ritual officials to offer new insights and perspectives on court ritual reforms. During the late eleventh century, some ritualists, most of whom were associated with the intellectual circle of the celebrated reformer Wang Anshi 王安石 (1027–1086), gradually dominated the interpretation of court rituals. Their endeavors in redefining court rituals led to Zhu Xi’s 朱熹 (1130–1200) experimental reforms of both court and social rituals in the Southern Song (1127–1279), which profoundly shaped the society and culture of late imperial China.
Language Maintenance and Shift in Highly Multilingual Ecologies
Authors: Li (李向允) Xiangyun , Vosters Rik , Xu (徐建维) Jianwei
Published: April 2022

Brussels is an officially French-Dutch bilingual city, yet in reality, it is profoundly and increasingly multilingual. Earlier research on the linguistic situation in Brussels has predominantly focused on the competing dominant languages, resulting in very limited scholarly attention to smaller language communities. This paper addresses this blind spot by exploring the language repertoires, proficiencies and practices of members of the Chinese communities. Linking insights from language ecology to the study of language maintenance and shift, and informed by the questionnaire data, we discuss how the changing sociodemographic backgrounds of the participants affect the language maintenance and shift of the whole Chinese communities. Our results do not reveal a traditional pattern of shift toward the dominant majority languages, but rather hint at a community-level shift toward more complex multilingual repertoires with an increased role for English and Mandarin, in tune with Brussels’ increasingly international and multilingual context at large.
Ethics at the Crossroads: Replies to Koopman, Livingston, and Slater
Authors: Marchetti Sarin
Published: April 2022

In this article I address a number of issues raised by Colin Koopman, Alex Livingston, and Michael Slater to my reading of James’s ethics as defended in my 2015 book having to do with, in turn, the relationship between ethics and politics, ethics and psychological types, and ethics and religion. In accounting for these charges, I vindicate and further qualify my interpretation of James as a moral therapist.
La transmission d’al-Ǧāmiʿ de Maʿmar Ibn Rāšid (m. 153/770) en al-Andalus et l’apport du manuscrit d’Ankara daté de 364/974
Authors: Jaouhari Mustapha
Published: April 2022

De par son ancienneté, le Ǧāmiʿ de Maʿmar Ibn Rāšid (m. 153/770) occupe une place cruciale dans l’histoire de la transmission des hadiths. Composé très tôt à Sanaa, il a servi de source principale aux différents recueils canoniques de l’islam sunnite. L’auteur en est un disciple de Qatāda Ibn Diʿāma (m. 118/735) et de Hammām Ibn Munabbih (m. 132/750), entre autres. Un des premiers transmetteurs d’al-Ǧāmiʿ est Abū Bakr ʿAbd al-Razzāq al-Ṣanʿānī (m. 211/826) qui l’enseignait en même temps que son recueil al-Muṣannaf, d’où la confusion entre les deux recueils. Le manuscrit d’Ankara fournit la preuve éclatante qu’il s’agit là d’un recueil autonome. Copié à Tolède, sur parchemin et daté de 364/974, ce manuscrit est aujourd’hui la plus ancienne copie connue de ce texte et, en même temps, l’un des rares manuscrits andalous du IVe/Xe siècle qui nous soient parvenus. Les nombreux actes de récitation (qirāʾa) figurant notamment dans les pages des titres de ses fascicules lui procurent une valeur supplémentaire et permettent d’en reconstituer l’histoire et identifier les personnages qui l’ont étudié et ceux qui l’ont diffusé. Le manuscrit nous renseigne sur deux siècles de transmission continue, d’abord à Tolède, puis à Huesca, ensuite à Valence, sous l’autorité de personnages célèbres qui furent tous cadis de leur ville.