bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring Saudi Physical Therapists’ Perceptions and Opinions on Their Profession: A Mixed-Method Study
Authors: Aloraini Saleh M. , Alrsheed Ghdy R.
Published: June 2022

Background and Purpose. The social standing of any occupation is often referred to as occupational prestige. Occupational prestige is often evaluated as how a particular occupation is regarded relative to other occupations by different groups in the society. Occupational prestige is a useful indicator of a profession’s marketability and desirability. As physical therapists (PTs) are essential members of the healthcare team, the aim of this study is to determine Saudi PT’s (students and graduates) perception of their occupational prestige and satisfaction with their career choice. Methods. A cross-sectional, mixed-method study was employed. Practicing PTs and PT students were recruited to fill out a self-administered questionnaire to rank nine different professions (including PT) across different dimensions. Further, participants reported on their job satisfaction and participated in a semistructured interview regarding their responses. Results. A total of 175 individuals participated in this study. The physical therapy profession was rated 6th on level of education, last (9th) on level of income and level of social standing, 5th on level of responsibility, and 3rd on level of usefulness. In the overall occupational prestige, the physical therapy profession was ranked the lowest compared to the other professions. Lastly, the data from the semistructured interviews corroborated the findings identified from the quantitative aspect of our study. Discussion. The overall results of the study indicate that the current perceived level of occupational prestige among Saudi PTs and PT students is somewhat disappointing. Participants generally viewed their profession in a low occupational prestige status, which is in contrast to previous studies conducted in other countries. While some of these results can be explained by the nature and history of the profession in Saudi Arabia, Academic institutions and policy makers should make an effort to promote the occupational prestige of the physical therapy profession.
Application of the Data Mining Model in Smart Mobile Education
Authors: Wang Gang , Ding Zuqin
Published: June 2022

In order to solve the problem that education departments urgently need intelligent and efficient information technology to deal with massive data, so as to mine valuable information for management decision-making, an overall scheme framework of education informatization is proposed. The framework takes data mining as a tool, combined with the theoretical knowledge of cloud computing, and takes the student data of a school as an example to verify the practicability of the framework system. The results are as follows: the framework clusters the students of a school. The overall level of students in cluster 1 is high, accounting for 45.07% of the total number. These kinds of students have solid basic theory, strong logical thinking ability, and excellent professional knowledge learning. The overall level of students in cluster 2 is average, accounting for 38.03% of the total number. This kind of students should pay attention to the study of professional courses and the cultivation of professional skills. The rest are students in cluster 3. These kinds of students have weak basic professional knowledge and poor thinking and logic ability. Through the accuracy before and after pruning output from the model, the accuracy before pruning is 87.32% and the accuracy after pruning is 97.37%. The noise data are eliminated in the process of pruning. The framework established in this study provides a certain decision-making basis for education and teaching and explains the feasibility and effectiveness of the application of data mining technology in educational informatization.
Raman Spectroscopy-Assisted Characterization of Nanoform MoS2 Thin Film Transistor
Authors: Saminathan Rajasekaran , Hadidi Haitham , Tharwan Mohammed , Alnujaie Ali , Khamaj Jabril A. , Venugopal Gunasekaran
Published: June 2022

In this paper, we report the simple preparation and investigation of electrical transport properties of nanoform MoS2 thin film transistor (TFT) devices. MoS2 nanoparticles were synthesized by using the hydrothermal method. The physiochemical characterizations such as UV-vis, Fourier transform infrared, X-ray diffraction, and Raman spectroscopy studies were performed. Spin-coating was used to make the thin film on which silver electrodes were made. We observed nonlinear current-voltage (I-V) characteristics; however, the symmetricity was found in the I-V curve which confirms the no formation of the Schottky barrier between thin film and electrodes. Transistor transfer characteristics reveal that the TFT device is n-doped as more drain current modulation is observed when the positive gate voltage is applied. The relationship between gate-current and gate voltage studies concludes that there is no leakage gate current in the TFT device which further confirms the good reliability of transfer characteristics of a device. The device mobility was calculated as ~10.2 cm2/Vs, and the same was explained with plausible reason supported with Raman spectra analysis.
Identification of CXCR4 Upregulation in Diffuse Large B-Cell Lymphoma Associated with Prognostic Significance and Clinicopathological Characteristics
Authors: Zhang Yi-an , Yang Xue , Yao Jiamei , Ren Yuhong , Liu Peng
Published: June 2022

Background. Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous malignant lymphoma with distinct characteristics. Patients with treatment failure after the standard immunochemotherapy have worse prognosis, which implies the necessity to uncover novel targets. The C-X-C chemokine receptor 4 (CXCR4) overexpression has been identified in several hematopoietic malignancies. However, the expression signatures and prognostic significance of CXCR4 in DLBCL associated with clinicopathological features remain unclear. Methods. Gene expression profiles of DLBCL were obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Then, a meta-analysis with an integrated bioinformatic analysis was performed to assess the relationship between CXCR4 expression and clinicopathological features of DLBCL. Finally, experimental verification including immunohistochemical (IHC) staining and real-time quantitative PCR (qPCR) was carried out using patient samples. In vitro cell line viability tests were conducted using CXCR4 inhibitor WZ811. Results. DLBCL patients with activated B-cell-like (ABC) subtype have higher expression level of CXCR4 with worse survival. Differential expressed genes in the CXCR4-upregulation group were enriched in canonical pathways associated with oncogenesis. DLBCL with CXCR4 upregulation had lower degree of CD8+ T cell infiltration. TIMER analysis demonstrated that the CXCR4 expression was positively correlated with the expression of CD5, MYC, NOTCH1, PDCD1, CD274, mTOR, FOXO1, and hnRNPA2B1 in DLBCL. IHC study in patient samples showed the positive correlation between CXCR4 and nongerminal center B-cell (non-GCB) subtype and mTOR expression. Meanwhile, quantitative polymerase chain reaction results revealed that high CXCR4 mRNA level was correlated to double-hit DLBCL. Finally, cell viability test showed that WZ811 exerted antiproliferation effect in DLBCL cell lines in a dose-dependent manner. Conclusion. CXCR4 was upregulated in ABC-DLBCL associated with worse prognosis. Our analysis predicted CXCR4 as a potential target for DLBCL treatment, which may serve as an inhibitor both on BCR signaling and nuclear export warranting further investigation in clinical trials.
Research on Animation Character Based on the Semantic Segmentation Model
Authors: Huang XiaoYu , Zhang Juan , Wu SiChao
Published: June 2022

A semantic ontology-driven hierarchical consistency segmentation algorithm was proposed to solve the segmentation inconsistency of animation character models because of the changing of poses. The mapping between semantic labels and local geometric features was extracted to form a segmentation ontology. In the process of segmentation, support vector machine (SVM) and local geometric features were used to identify the semantic labels, and segmentation was carried out according to the semantic label driving hierarchy to ensure the consistency of the segmentation levels of animation character models. Poisson equation was used to define contour lines for the equal perimeters of segmentation boundary because of the changing of poses. This optimization method made the segmentation boundary smooth and consistent under the changing of poses. In the experiment part, all kinds of animation character models under different poses were verified and analyzed, and the consistent hierarchical segmentation effect was obtained. Compared with the existing methods, the proposed segmentation ontology can solve the problem of adaptive selection of optimization parameters of different classes of models, and improve the segmentation quality. With the continuous development of deep learning, the use of image segmentation for animation, and human pose recognition will become more and more important.
Art Product Recognition Model Design and Construction of VR Model
Authors: Wu Tianyou
Published: June 2022

The artwork embodies a profound human history and carries the essence of human civilization. Its content is complex and covers a wide range. How to use advanced technology to quickly and accurately classify and retrieve is an important research topic in the field. In our study, we first according to the requirements of practical application scenarios and existing data conditions proposed an overall scheme of artwork identification and retrieval. Through the functional analysis of the software required and the comparison of various databases, we present the system architecture design and data conceptual design, and complete the system-level planning and design. Then, the crawler grabbing process is designed to obtain artwork graphic data, the artwork dataset production process and labeling status required for the target application scenario were introduced, and the category imbalance state of the target dataset was analyzed. Moreover, the database table structure design of the artwork identification and retrieval system, design and development of each functional module of the server, and the web client was introduced. Finally, according to the organization, structure, and characteristics of virtual reality system, a product design evaluation system based on virtual reality technology was constructed. A theoretical model VR-PDES was designed for the application of virtual reality technology in product design evaluation. The results of this research are of great significance for people to search for images of unknown artworks and improve the service capabilities and service levels of scenic spots.
Design and Implementation of Smart Community Big Data Dynamic Analysis Model Based on Logistic Regression Model
Authors: Jiang Hong
Published: June 2022

With the economic development, smart communities have been widely studied and applied. However, the system in this field is not perfect, and there are still a series of problems, such as high construction cost, low level of intelligence, mutual independence of different systems, difficulty in unified management, and so on. To solve the above problems, this paper proposes the smart community big data dynamic analysis model based on logistic regression model. First, this paper constructs the big data research architecture of smart community based on IOT technology, including IAAs, DAAS, PAAS, and SaaS layers and the virtual service layer of resource scheduling of spatiotemporal information cloud platform optimized by spatiotemporal law. And the IoT platform is designed to collect data to lay the foundation for research. Second, this paper is oriented to the big data application requirements with distribution and mobility as the main technical characteristics. Based on the distributed data flow, this paper designs mining operator to provide technical support for the data mining algorithm; at the same time, this paper constructs a high-dimensional random matrix model for measuring big data and then deduces its abnormal data detection theory and method to detect high-dimensional abnormal data. Finally, this paper uses logistic regression model to predict the development trend of smart community and provide guarantee for smart community service. The simulation results show the efficiency and accuracy of prediction can be improved based on logistic regression model. Furthermore, it effectively avoid repeated construction and waste of resources in the community and form a new community management model based on intelligent and information-based social management and service.
Experimental and Numerical Studies on Flowing Properties of Grouting Mortar Based on the Modified MPS Method
Authors: Aierken Ailifeila , Luo Shilin , Jiang Jianqing , Chong Linlin , Chang Jin , Zhang Rui , Zhang Xiangchao
Published: June 2022

Grouting mortar has widespread application in engineering because of the advantages of good durability, low cost, and environmental friendliness. To study the flowing properties of grouting mortar, laboratory minislump tests taking different rheological parameters of grouting mortar into consideration were conducted to obtain the flow time and flow pattern of grouting mortar. A modified MPS method (moving-particle semi-implicit method) introduced two sections of Bingham rheological, and segregation was proposed. The effects of the plastic viscosity on the flow state of mortar were studied, and the relationship between the plastic viscosity and the flowing time was established. The numerical results show that the modified MPS method can be used to predict the flow time and flow pattern of mortar in the template, and plastic viscosity has a great influence on the flow time of concrete, and with the increase of plastic viscosity, the time to flow to the specified area also increases. Moreover, the analysis of the rheological parameters can provide the basis for the design of mix ratio in the construction practice.
An Investigation on Local Shearing Mechanisms of Irregular Dentate Rock Joints Using the PFC
Authors: Huan Jiuyang , He Mingming , Zhang Zhiqiang , Hu Mengdie
Published: June 2022

Joint surfaces are widely distributed in natural rock mass, and their shear mechanical properties play an important role in determining the safety and stability of rock mass. Previous studies rarely discussed the contribution degree of different joint protrusions to resisting shear stress. In this study, seven irregular dentate joint profiles were proposed to represent the geometric morphology of natural joints. Joint samples were subjected to direct shear tests under constant normal stress using the particle flow code (PFC). First, the reliability of the research scheme was verified by routine test results. Secondly, based on the microcrack tracking module and the force chain analysis, the local failure modes of the joint sample after and during the shearing process are discussed in detail. The relationship between the shear stress and the number of microcracks was studied. Finally, based on the measuring circle function, the variation law of the mean stress at different joint protrusions during the shearing process was tracked. The maximum stress of each protrusion before the shear stress peak was introduced to quantitatively describe the contribution of local protrusions to shear stress. There was an important link between the size of the protrusion and the stress it can withstand. During the shearing process, the local shearing mechanism of the joint surface is controlled by the distribution of joint protrusions. The research results of this paper can provide a good idea for the follow-up joint surface research.
Some Generalized Fractional Integral Inequalities via Harmonic Convex Functions and Their Applications
Authors: Awan Muhammad Uzair , Akhtar Nousheen , Raïssouli Mustapha , Kashuri Artion , Javed Muhammad Zakria , Noor Muhammad Aslam
Published: June 2022

The aim of this paper is to derive from an auxiliary identity some new generalizations of fractional integral inequalities of Simpson, midpoint, and trapezoid using the class of harmonic convex functions. To show that our results are quite unifying, we discuss several new special cases. Finally, some applications regarding error estimations for the Simpson quadrature formula are presented to support our theoretical results.
Prediction of Surface Settlement Induced by Large-Diameter Shield Tunneling Based on Machine-Learning Algorithms
Authors: Li Chao , Li Jinhui , Shi Zhongqi , Li Li , Li Mingxiong , Jin Dianqi , Dong Guo
Published: June 2022

The accurate prediction of surface settlement caused by large-diameter shield tunneling is crucial for the safety of the tunnel environment. However, due to the complexity and uncertainty of the rock-machine interaction and groundwater variation, it is difficult to predict the settlement by developing traditional theoretical methods. Recently, a big number of data obtained from the Chunfeng shield tunnel in China provides the possibility to predict the settlement using machine-learning methods. In this study, the equipment parameters, the geological parameters, and the monitored settlements are used to establish the models. Three machine-learning algorithms (i.e., long-short-term memory (LSTM), random forest (RF), and gated recurrent unit (GRU)) are used to predict the surface settlement. Three indicators, mean absolute error (MAE), accuracy (ACC), and coefficient of determination (

R

2

), are selected to evaluate the prediction performance. Results demonstrated that the filtering and selection of model parameters is vitally important to the accuracy of model prediction. Among the three machine-learning algorithms, the LSTM algorithm gives the best accuracy in predicting the maximum surface settlement and can effectively predict the settlement development in different strata.
Improvement Design of Functional Modules of College English Network Teaching System Based on Decision Tree Algorithm
Authors: Li Hui
Published: June 2022

English courses are a compulsory course for non-English core courses. Studying English at university is an important part of studying at a non-English university. The purpose of a university education in English is to enhance the comprehensive language skills of students in English. In this way, they can communicate effectively in English during future work, study, and social interactions, while strengthening their ability to meet the needs of social development and international exchange. The functional improvement design of the college English network teaching system will help the system to provide technical support and services for college English teaching more effectively. It can more effectively cultivate students’ language communicative ability and autonomous learning ability. This article first improves the practical units of the education system and then adds the decision tree algorithm. It uses improved decision-making algorithms to evaluate student performance with an improved learning system. The number of leaf nodes of the improved decision tree algorithm on the three datasets is 19, 14, and 15, respectively, and the number of summary points is 27, 23, and 7, respectively.
Bilateral Adrenal Hemorrhage and Adrenal Insufficiency in the Context of Polycythemia Vera: A Case Report and Review of the Literature
Authors: Soltanmohammadi Sara , Vakhshoori Mehrbod , Sajadi Ghazaleh , Heidarpour Maryam
Published: June 2022

Background. Polycythemia vera (PV) is a myeloproliferative disorder presented with different manifestations. However, bilateral adrenal hemorrhage (BAH) and adrenal insufficiency (AI) are rare manifestations. Herein, we described a patient who suffered from BAH and AI in the context of PV. Case Presentation. A 60-year-old man with an underlying history of PV was admitted with severe abdominal pain, nausea, and loss of consciousness. Primitive computed tomography (CT) scan findings revealed bilateral adrenal masses (right: 40 

∗

 23 mm, left: 60 

∗

 35 mm) with the second scan showing quite similar results (right adrenal: 40 

∗

 29 mm, left adrenal: 48 

∗

 26 mm) suggesting BAH. The further adrenal assessment proved concurrent AI. Both adrenal masses resolved completely after 15 months. However, the patient still suffered from AI. Conclusion. BAH and AI in patients with PV should be considered rare complications requiring high clinical suspicion for early diagnosis and treatment to avoid life-threatening outcomes.
Research on Consumption Prediction of Daily Necessities Based on Combination Model and Its Influence on Upgrading of Industrial Structure
Authors: He Yongquan , Jia Lanfang
Published: June 2022

The development of big data and artificial intelligence ensures the industrial innovation of traditional commodities. Economic transformation and upgrading has become the general trend of social development. Based on the public data of the Rossmann store, a well-known German chain store, and the consumption prediction model of daily necessities based on random forest and GBRT is proposed in this paper. By combining the model to initialize residuals, not only the training speed of the model is effectively improved but also more accurate prediction is obtained. Based on the analysis of the big data, this paper puts forward the influence of daily necessities consumption forecast on the upgrading of industrial structure and constructs a value creation and transmission system for daily necessities, so as to promote the rationalization level of the consumer industrial structure and provide a reference for the upgrading of the same type of commodity industrial structure.
Photocatalytic Activity of Green Construction TiO2 Nanoparticles from Phyllanthus niruri Leaf Extract
Authors: Shimi Annin K. , Wabaidur Saikh Mohammad , Siddiqui Masoom Raza , Islam Md Ataul , Rane Kantilal Pitamber , Jeevan T. S. Arul
Published: June 2022

The present research work reports the facile and green synthesis of TiO2 nanoparticles from Phyllanthus niruri leaf extract using the coprecipitation method. The plant biomolecules were responsible for the nanoproduction and exhibited reduction and stabilization activity. The green synthesized TiO2 nanoparticles were analyzed in various characterization methods. The crystalline size (23 nm) and anatase phase of TiO2 nanoparticles were analyzed from X‐ray diffraction study. The reduction and stabilization response functional group of TiO2 nanoparticles was studied from FTIR analysis. The optical properties of TiO2 nanoparticles were constructed from the UV‐DRS technique, and their calculated bandgap is 3.16 eV. The spherical morphology and their existing materials were identified using FESEM with EDX. The catalytic activity of TiO2 nanoparticles was examined against methylene blue dye under ultraviolet and visible light irradiation. It was detected that ultraviolet irradiation showed higher photocatalytic activity than visible light irradiation. In addition, visible light irradiation provides the above 90 percentage degradation of methylene blue dye. Hence, TiO2 nanoparticles were proposed as a potential catalyst of photocatalytic dye degradation application and water remediation activities.
Construction and Empirical Study of Show Analysis Model of Enterprise Mankind Resource Management Based on Deep Learning
Authors: Yihan Ni , Hongliang Ni , Xiaomei Guo , Yihuo Jiang
Published: June 2022

Owing to the rapid expend of the global economy and the increasingly fierce competition among enterprises, scientific and modern management has been gradually adopted in the transaction processing of enterprises. Especially for the show appraisal of enterprises, the traditional appraisal has a lot of subjective influence of managers, so the traditional show appraisal methods cannot meet the need for survival and expend of enterprises. The pressure of talent demand is increasing, which makes many enterprises pay more attention to whether their own mankind resource management system supports the company’s strategic spend and can win advantages in the competition of talent structure, organizational structure, and management process. Numerous foreign enterprises use mankind resource audit to achieve this goal, but at present, there is little practice in China that enterprise show evaluation is an important basic work and core content of mankind resource management and expend. Improving the effectiveness of enterprise show evaluation is of great significance to increase the core competitiveness of enterprises and promote the sustainable expend of enterprises. Therefore, this paper designs a model based on collaborative filtering algorithm to analyze the show of mankind resource management of enterprises and has achieved good results. Compared with the original algorithm, the model designed in this paper has a 65.4% improvement in algorithm, which will greatly simplify the calculation process and improve the model processing efficiency. The numerical results show that there is an inevitable linear correlation between mankind resource management and enterprise show. This index can reflect that the accuracy of the model has been enhanced by 74.3%.
ECC-Based Authenticated Key Exchange Protocol for Fog-Based IoT Networks
Authors: Iqbal Ummer , Bhola Jyoti , Jayasudha M. , Ahmad Mohd Wazih , Neware Rahul , Yadav Arvind R. , Gelana Fraol Waldamichael
Published: June 2022

Fog computing is one of the prominent technology that bridges the gap between IoT nodes and cloud servers. For increasing the efficiency at the fog level, a fog federation can be employed. Fog federation at the fog level can be controlled by the fog coordinator. However, the information exchange between the fog coordinator and IoT nodes needs to be secured. Recently, a lightweight secure key exchange (LKSE) protocol for secure key exchange for fog federation was proposed. In this paper, the cryptanalysis of the LKSE is carried out. The cryptanalysis indicates that LKSE is vulnerable to spoofing and man in the middle attacks. To overcome the limitation of the LKSE, a design of an ECC-based secure key exchange protocol for IoT devices and fog coordinators is proposed. The security strength of the designed method has been evaluated using BAN logic and the random oracle model. Simulations on AVISPA have been performed for automatic security verification of the proposed method. A detailed security and functional comparison of the proposed scheme with LKSE have also been carried out.
Woody Species Composition, Plant Communities, and Environmental Determinants in Gennemar Dry Afromontane Forest, Southern Ethiopia
Authors: Ahmed Shemsu , Lemessa Debissa , Seyum Abera
Published: June 2022

Dry Afromontane forests in Ethiopia are vital for the conservation of plant diversity and climate change mitigation. However, these forest resources are rapidly degrading and shrinking, necessitating empirical scientific investigations to ensure their successful conservation and long-term management. As a result, this study was conducted to evaluate the composition, plant communities, and environmental determinants of woody species in the Gennemar dry Afromontane forest of southern Ethiopia. Environmental variables such as altitude, aspect, and geographical location were recorded from 46 plots of 20 × 20 m for trees and 92 subplots of 10 × 10 m for shrubs were laid along 10 transect lines. Vegetation structure, diversity, vegetation classification, importance value index (IVI) and correlation with environmental parameters were analyzed. A total of 55 woody species belonging to 51 genera and 34 families were identified. Among the species identified, Jasminum stans, Maytenus addat, and Pittosporum abyssinicum were endemic to Ethiopia. Celastraceae (with 659 individuals) was the most dominant family, followed by Cupressaceae (268 individuals) and Myrsinaceae (222 individuals). Four plant communities were identified: Syzygium guineense-Mystroxylon aethiopicum, Maytenus arbutifolia-Podocarpus falcatus, Myrsine africana-Erica arborea, and Juniperus procera-Carissa spinarum. Juniperus procera, Podocarpus falcatus, and Maytenus arbutifolia were species with the highest IVI, while Maesa lanceolata, Rhamnus prinoides, and Gnidia glauca had the lowest. The DBH class distribution shows an inverted J-shaped distribution. As DBH increases, the number of individuals decreases in the higher DBH class. The distribution of plant communities and the composition of the species depend on altitude and topographic aspects. The study found that the dry Afromontane Forest is rich in species and that it should be prioritized for conservation to protect endemic and native species. Decisive elements such as the type of species, altitude, and topographic aspects must be considered for forestry activities.
Evaluation of the Clinical Efficacy of the Treatment of Overweight and Obesity in Type 2 Diabetes Mellitus by the Telemedicine Management System Based on the Internet of Things Technology
Authors: Lin Kaisang , Zhang Wei , He Fei , Shen Jie
Published: June 2022

Objective. To explore the application value of medical intelligent electronic system under the background of Internet of Things in the clinical study of the treatment of overweight/obesity in type 2 diabetes mellitus (T2DM) with empagliflozin combined with liraglutide; 50 overweight and obese adult T2DM patients in our hospital were randomly divided into the combined group and the control group, 25 cases in each group. The control group was treated with liraglutide alone, while the combined group was treated with empagliflozin on the basis of liraglutide. Based on the Internet of Things technology, with diabetes management as the core, the functions of information collection, transmission, and storage of T2DM patients are realized. Doctors pass the diabetes management plan to T2DM patients through the platform, supervise the implementation, and finally compare the clinical efficacy of the two groups. Results. Compared with before treatment, the body mass index (BMI), fasting blood glucose (FPG), postprandial blood glucose (2hPG), glycosylated hemoglobin (HbAlc), islet beta cell secretion function index (HOMA-β), islet resistance index (HOMA-IR), total cholesterol (TC), and triglyceride (TG) in both groups decreased significantly after treatment. After combined treatment, systolic blood pressure (SBP), diastolic blood pressure (DBP), FPG, 2hPG, HbA1c, and HOMA-IR in the combined group were significantly lower than those in the control group (

P
<
0.05

). Hypoglycemia occurred in both groups, with 2 cases in the control group and 4 cases in the combined group. Conclusion. The telemedicine management system based on Internet of Things technology can improve patients’ self-management ability and provide a new choice for individualized treatment of overweight/obesity T2DM patients. The combination therapy of empagliflozin and liraglutide can effectively reduce blood sugar, weight, blood pressure, blood lipid, and hypoglycemia and effectively improve insulin resistance and secretion function of islet β cells in T2DM patients.
Optimization and Tribological Properties of Hybridized Palm Kernel Shell Ash and Nano Boron Nitride Reinforced Aluminium Matrix Composites
Authors: Lokeshwari M. , Sagar P. Vidya , Kumar K. Dilip , Thirupathy D. , Subbiah Ram , Ganeshan P. , Seikh A. H. , Mohammed S. M. A. K. , Christopher David
Published: June 2022

The tribological properties of hybridized reinforced aluminium matrix composites were optimized using Taguchi and Grey Relational Analysis in conjunction with an L16 orthogonal array. The combination of palm kernel shell ash (PKSA) (0–5 wt. %) along with nano BN reinforcements was taken in interest. Loads and speeds (500, 750, 1000, and 1250 rpm) were employed as control parameters for the experiment. Using a Taber type abrasion machine, the wear samples were made, and the wear experiments were carried out. Speed and load were more important than the percentage of reinforcements in composites when it came to evaluating wear index and loss of volume. With respect to wear index and volume loss, Taguchi‐relational Grey’s analysis identified A3B1C1 (reinforcement = 5 wt. %; load = 500 g; speed = 500 rpm) as the optimal process parameter combination, with a reinforcement of 3 wt. %, load = 500 g, and speed = 500 rpm being the second‐best option. Validation tests have revealed that the anticipated and experiment values at the optimal situations are both within the acceptable range. Performance is influenced more by speed than by load, which is influenced more by the weight percentage of composites, as demonstrated by the application of the Taguchi and Grey Relational Analysis methods.
Construction and Data Integration of College Student Management Model Based on Human-Computer Interaction Data Acquisition and Monitoring System
Authors: Wang Tingfei
Published: June 2022

The research on the management mode of students in colleges and universities is helpful in cultivating students’ autonomous learning, self-education, and self-service ability. However, there are still some deficiencies in the construction of college student management model. This paper aims to study and analyze the construction and data integration of college student management mode under the data acquisition and monitoring system based on human-computer interaction. Firstly, this paper analyzes the human-computer interaction technology. Robots participate in human activities and coexist with people, which is called human-computer interaction. Human-computer interaction technology mainly includes voice interaction, image interaction, data interaction, and action interaction. Then, the sensor data acquisition algorithm based on cooperative communication is analyzed, and finally, the management mode of students is experimentally explored. The composition of the management system of college students is realized by establishing the management subject, management object, and management environment of students. The experimental results of this paper show that, in the investigation of the student union management system, 43% of the participants chose “the system exists, but it needs to be improved,” and 31.5% of the participants chose “the system is perfect.” “The system is not perfect” accounted for 14.8%, and 89.2% of the participants believed that there was a system. Obviously, whether it is the system, the enforcement strength, or the standard level, there is still room for improvement. We can strengthen the connotation construction of the student union and improve the management function of the student union, deepen the understanding of the status and role of the student union, build a standardized evaluation system for the student union, and strengthen the internal organization of the student union.
Intertextuality between French Literature Creation and Literature Translation Based on Feature Extraction and Gram Matrix
Authors: Li Ting
Published: June 2022

In the 1980s, there was a cultural turn in translation studies. Since then, translation studies are no longer confined to the study of specific texts, but examine the texts in the context of culture and history, and study the production process of texts and the relationship between texts and related factors such as culture and history. When literary works are transplanted from one language to another, it is like moving plants and animals from one place to another. They must “adapt” and grow like individuals or nations, and they can only survive if they adapt to the new environment and change. Intertextuality is one of the important terms in contemporary literary criticism. Intertextuality is one of the seven textual features of a text (formal adaptation, semantic adaptation, intentionality, receptivity, informality, situational, and intertextuality). Gram incidence matrix is designed to count and merge feature words using feature extraction algorithm for text processing and feature extraction, so that feature words of different lengths can be extracted using fixed-length algorithm. A poststructuralist, Roland Barthes, deconstructs the traditional concept of text and extends it to the social and cultural context. The so-called intertextuality of literary creation and literary translation also incorporates cultural connotation and knowledge structure into the relationship between texts. Literary system is a system, social culture is a larger system, and literary system is a constituent factor of the social cultural system, according to the theory of multiple systems; literary creation and literary translation are factors in the literary system. The main focus of intertextuality theory is text comprehension. Bloom’s intertextuality theory, on the other hand, expounds on text creation. On the basis of a feature extraction algorithm, this paper investigates the types and techniques of intertextuality between creative text and translated text using a combination of objective description and theoretical analysis.
Application of Machine Learning to Predict Trajectory of the Center of Pressure (COP) Path of Postural Sway Using a Triaxial Inertial Sensor
Authors: Wantanajittikul Kittichai , Wiboonsuntharangkoon Chakrit , Chuatrakoon Busaba , Kongsawasdi Siriphan
Published: June 2022

Postural sway indicates controlling stability in response to standing balance perturbations and determines risk of falling. In order to assess balance and postural sway, costly laboratory equipment is required, making it impractical for clinical settings. The study aimed to develop a triaxial inertial sensor and apply machine learning (ML) algorithms for predicting trajectory of the center of pressure (COP) path of postural sway. Fifty-three healthy adults, with a mean age of 46 years, participated. The inertial sensor prototype was investigated for its concurrent validity relative to the COP path length obtained from the force platform measurement. Then, ML was applied to predict the COP path by using sensor-sway metrics as the input. The results of the study revealed that all variables from the sensor prototype demonstrated high concurrent validity against the COP path from the force platform measurement (ρ > 0.75;

p
<
0.001

). The agreement between sway metrics, derived from the sensor and ML algorithms, illustrated good to excellent agreement (ICC; 0.89–0.95) between COP paths from the sensor metrics, with respect to the force plate measurement. This study demonstrated that the inertial sensor, in comparison to the standard tool, would be an option for balance assessment since it is of low-cost, conveniently portable, and comparable to the accuracy of standard force platform measurement.
Radiomics Model Based on Enhanced Gradient Level Set Segmentation Algorithm to Predict the Prognosis of Endoscopic Treatment of Sinusitis
Authors: Li Yabing , Tao Ye
Published: June 2022

Background and objective. Nasal endoscopy is a standard method to treat sinusitis. Predicting the prognosis of nasal endoscopy can make treatment more effective. The purpose of this study is to explore the prediction of radiomics model based on an enhanced gradient level set segmentation algorithm for the effect of nasal endoscopy in the treatment of sinusitis. Methods. Computed tomography (CT) images of sinusitis in 91 patients were collected. By introducing boundary gradient information into the edge detection function, the sensitivity of the level set model to the boundary of different intensities of lesions was adjusted to obtain accurate segmentation results. After that, the segmented CT image was imported into Mazda texture analysis software for feature extraction. Three dimensionality reduction methods were used to screen the best texture features. Four analysis methods in the B11 module were used to calculate the misclassified rate (MCR). Results. The segmentation algorithm based on an enhanced gradient level set has good segmentation results for sinusitis lesions. The radiomics results show that the raw data analysis method under the Fisher dimensionality reduction method has a low MCR (25.27%). Conclusion. The enhanced gradient level set segmentation algorithm can segment sinusitis lesions accurately. The radiomics model effectively predicts the prognosis of endoscopic treatment of sinusitis.
Abstract A09: Characteristics of uveal melanoma patients with central nervous system metastases
Authors: Patel Sapna P. , Hwu Patrick , Davies Michael , Wong Michael , Tawbi Hussein , Amaria Rodabe , Diab Adi , Gombos Dan , Glitza Isabella C.
Published: June 2022

In contrast to cutaneous melanoma, central nervous system (CNS) metastasis from uveal melanoma are uncommon, occurring in less than 5% of uveal patients. There is no published literature describing the features or survival of this unique population. Here we describe the clinical characteristics and outcomes of uveal melanoma CNS metastasis patients. We performed an MD Anderson Cancer Center institutional database review from 1999–2017 for consecutive uveal melanoma patients with CNS metastasis. Excluding dural-based metastases, 19 patients were identified. Ethnic makeup was 84% White, 11% Hispanic, 5% other, and median age at diagnosis was 52.4 years. The gender distribution was 12 (63%) female and 7 (37%) male. Primary tumor location in the uveal tract was 26% choroid, 11% iridociliary, 5% chiliochoroidal, and 58% not otherwise specified. Seven of 19 (37%) patients were treated with enucleation; 63% received radiation therapy for primary uveal melanoma. Median interval from diagnosis of uveal melanoma to diagnosis of CNS metastasis was 5 years. Only 7 patients had molecular testing for mutations. Of these, all had G-alpha mutations: 4 (57%) with GNAQ, and 3 (43%) with GNA11 hotspot mutations in Q209. At the time of data cutoff, 14 of 19 (74%) patients were deceased. Additional clinical information regarding treatment for CNS metastasis, histopathologic evaluation, and overall survival will be presented at the meeting.

Citation Format: Sapna P. Patel, Patrick Hwu, Michael Davies, Michael Wong, Hussein Tawbi, Rodabe Amaria, Adi Diab, Dan Gombos, Isabella C. Glitza. Characteristics of uveal melanoma patients with central nervous system metastases [abstract]. In: Proceedings of the AACR Special Conference on Melanoma: From Biology to Target; 2019 Jan 15-18; Houston, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(19 Suppl):Abstract nr A09.
Abstract B05: Sox10 differentially regulates receptor tyrosine kinase expression in melanomas
Authors: Capparelli Claudia , Purwin Timothy , Aplin Andrew
Published: June 2022

Targeting the ErbB3-ErbB2 pathway increases the efficacy of MEK inhibitors in melanoma. Given the inter- and intratumor heterogeneity of melanoma, identifying biomarkers for cells within tumors that will respond effectively to MEK inhibitor-anti-ErbB3 cotargeting is crucial. To this end, we sought to identify transcriptional regulators of ErbB3. Several transcription factors (TFs) are predicted to bind to the promoter region of ErbB3. Using correlation analysis, SOX10 was positively correlated with ErbB3 expression in the RNA-seq data from TCGA cutaneous melanoma dataset. By contrast, an inverse correlation existed between SOX10 and other receptor tyrosine kinases, EGFR and PDGFR, which have been associated with a slow-growing phenotype and resistance to BRAF and MEK inhibitors. siRNA and CRISPR knockdown/out experiments confirmed that SOX10 positively regulates ErbB3 but negatively regulates PDGFR, suggesting plasticity between SOX10-positive and SOX10-negative populations with regard to RTK expression. Overall, this study suggests that SOX10 is a potential biomarker of responsiveness to MEK inhibitor plus ErbB3 targeting antibody in melanoma.

Citation Format: Claudia Capparelli, Timothy Purwin, Andrew Aplin. Sox10 differentially regulates receptor tyrosine kinase expression in melanomas [abstract]. In: Proceedings of the AACR Special Conference on Melanoma: From Biology to Target; 2019 Jan 15-18; Houston, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(19 Suppl):Abstract nr B05.
Abstract B25: Demographic characteristics and peripheral blood clinical laboratory variables predict irAE occurrence in patients with advanced melanoma receiving anti-PD-1 monotherapy
Authors: Bai Xue , Kim Michelle S. , Kasumova Gyulnara , Cohen Justine , Lawrence Donald , Freedman Christine , Fadden Riley , Rubin Krista , Sharova Tatyana , Flaherty Keith , Sullivan Ryan , Boland Genevieve
Published: June 2022

Background: Although immune-related adverse effects (irAEs) are commonly seen in anti-PD-1 monotherapy-treated patients, their predictive biomarkers are still lacking.

Methods: In this retrospective analysis, clinical data were collected from 141 advanced melanoma patients treated with anti-PD-1 monotherapy at Massachusetts General Hospital from Sept. 2009 to Dec. 2017. Demographic characteristics, baseline, and early-on-treatment (median 3 weeks after anti-PD-1 monotherapy initiation) routine laboratory variables were collected and correlated with occurrence of irAEs in both univariate and multivariate analyses.

Results: 80/141 (56.7%) patients developed irAEs after anti-PD-1 monotherapy initiation. Significant independent predictive variables (P < 0.05) in favor of the occurrence of irAEs included the following: with no distant metastasis (Stage M0) before treatment initiation, high baseline neutrophils, and high early-on-treatment neutrophil-to-lymphocyte ratio (NLR). High baseline monocytes, high baseline basophils, and high early-on-treatment WBCs were of borderline significance (P < 0.1) in multivariate analyses. An irAE risk scoring model (total scale: 0-6) comprising these 6 factors (all as dichotomous variables) was established (HR 1.781, 95% CI 1.450 – 2.187, P < 0.001). Risks of developing at least one irAE within 12 weeks after anti-PD-1 monotherapy initiation were 0%, 21%, 21%, 39%, 30%, and 63%; within 48 weeks were 0%, 41%, 57%, 68%, 77%, and 100%, for patients with scores of 0 to 5 (no patient scored 6 within this cohort), respectively.

Conclusions: Scoring system based on simple, easily accessible, and routinely tested biomarkers could be used to help predict the risk of irAEs occurrence in anti-PD-1 monotherapy-treated advanced melanoma patients.

Citation Format: Xue Bai, Michelle S. Kim, Gyulnara Kasumova, Justine Cohen, Donald Lawrence, Christine Freedman, Riley Fadden, Krista Rubin, Tatyana Sharova, Keith Flaherty, Ryan Sullivan, Genevieve Boland. Demographic characteristics and peripheral blood clinical laboratory variables predict irAE occurrence in patients with advanced melanoma receiving anti-PD-1 monotherapy [abstract]. In: Proceedings of the AACR Special Conference on Melanoma: From Biology to Target; 2019 Jan 15-18; Houston, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(19 Suppl):Abstract nr B25.