bluuebunny/crossref_metadata_2025 huggingface dataset:
Network Pharmacology and Molecular Docking Analysis on the Pharmacological Mechanisms of Modified Sanmiaosan in Treating Ulcerative Colitis
Authors: Wang Yong , Sun Ying , Wang Ruoran , Du Jisha , Wang Qingqing
Published: August 2022

Background. Modified Sanmiaosan is an effective cure in the treatment of ulcerative colitis, but its mechanisms of action remain unclear. This study revealed the pharmacological mechanisms of Modified Sanmiaosan acting on ulcerative colitis through a pharmacology approach. Materials and Methods. The active compounds and the targets of Modified Sanmiaosan were selected from the Traditional Chinese Medicine Systems Pharmacology database according to the absorption and metabolism. The UC-related therapeutic targets were collected from the PharmGKB database, the GeneCards database, the GADA database, and the OMIM database. The networks of “drug-component-target-disease” and “herbal-component-target” were constructed by the Cytoscape software. Protein–protein interaction network was generated by the STRING database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed by the R software. Molecular docking technology was used to identify the affinity and activity between active compounds and targets. Results. The 80 effective ingredients of MSM were collected. A total of 5180 UC-related genes and the 153 key targets of MSM and UC-related were obtained. JUN, Akt1, and MAPK1 were identified as the “hub targets” involved in the effects of Modified Sanmiaosan on ulcerative colitis. Hub targets were mainly involved in inflammatory response and oxidative stress. As the results of GO analysis, biological processes such as DNA-binding transcription and RNA polymerization may participate in the treatment process; KEGG pathway analysis showed that hub targets were mainly involved in IL-17 signal pathway and TNF signal pathway of ulcerative colitis. The high affinity and activity of the active compounds and targets were verified through molecular docking. Conclusion. These findings demonstrate the active ingredients in Modified Sanmiaosan reduce inflammatory response by TNF and IL-17 signaling pathways to treat ulcerative colitis. Anti-inflammation and immune regulation may be the main mechanism of Modified Sanmiaosan in the treatment of ulcerative colitis. This study not only provide new insights into the development of a natural therapy for the prevention and treatment of ulcerative colitis but also proves a feasible method for discovering potential activated compounds from Chinese herbs.
Application Effect of Cluster-Based Care in Patients with Hypertensive Disorders of Pregnancy and Osteoarthritis
Authors: Ye Lili , Yu Chunhua , Chen Xiaoqin , Han Yanyan
Published: August 2022

Objective. To explore the application effect of cluster-based care in patients with hypertensive disorders of pregnancy and osteoarthritis. Methods. The clinical data of 60 patients with hypertensive disorders of pregnancy and osteoarthritis in our hospital were retrospectively analyzed, among which those receiving routine care from January 2020 to December 2020 were grouped into the control group (30 patients), and those receiving cluster-based care from January 2021 to January 2022 were grouped into the research group (30 patients). Psychological status, care satisfaction, and pregnancy outcomes were compared between the two groups. Results. After intervention, self-rating anxiety scale (SAS) and self-rating depression scale (SDS) scores in the research group were lower than those in the control group (

P
<
0.05

). There was no statistical significance in the difference of the modes of delivery between the two groups (

χ

2

=
1.763

,

P
>
0.05

). Patients in the research group had a lower incidence of perinatal complications than those in the control group (

χ

2

=
5.689

,

P
<
0.05

). And the satisfaction rate of care in the research group (93.33% vs 70%) was higher than that in the control group (

χ

2

=
4.238

,

P
<
0.05

). Conclusion. Cluster-based care can reduce patients’ negative mood, increase their satisfaction, and improve the maternal and infant outcomes. This type of care offers better quality care measures for patients with pregnancy hypertension and osteoarthritis, and has a wide clinical application prospect.
A Novel Appraisal Protocol for Spatiotemporal Patterns of Rainfall by Reconnaissance the Precipitation Concentration Index (PCI) with Global Warming Context
Authors: Tehreem Zara , Ali Zulfiqar , Al-Ansari Nadhir , Niaz Rizwan , Hussain Ijaz , Sammen Saad Sh.
Published: August 2022

In global warming contexts, continuous increment in temperature triggers several environmental, economic, and ecological challenges. Its impacts have severe effects on energy, agriculture, and socioeconomic structure. Moreover, the strong correlation between temperature and dynamic changing of rainfall patterns greatly influences the natural cycles of water resources. Therefore, it is necessary to examine the spatiotemporal variation of precipitation to improve precipitation monitoring systems. Thereby, it helps to make future planning for flood control and water resource management. Considering the importance of the spatiotemporal assessment of precipitation, the current study provides a new method: regional contextual precipitation concentration index (RCPCI) to analyze spatial-temporal patterns of annual rainfall intensities by reconnaissance the precipitation concentration index (PCI) in the global warming context. The current study modifies the existing version of PCI by propagating the role of temperature as auxiliary information. Further, based on spatial and nonspatial correlation analysis, the current study compares the performance of RCPCI and PCI for 45 meteorological stations of Pakistan. Tjøstheim’s coefficient and the modified t-test are used for testing and estimating the spatial correlation between both indices. In addition, the Poisson log-normal spatial model is used to assess the spatial distribution of each rainfall pattern. Outcomes associated with the current analysis show that the proposed method is a good and efficient substitute for PCI in the global warming scenario in the presence of temperature data. Therefore, to make accurate and precise climate and precipitation mitigation policies, the proposed method may incorporate uncovering the yearly pattern of rainfall.
Assessment of English Teaching Post Competency Relying on K-Means Clustering Computing Algorithm
Authors: Meng Xihua
Published: August 2022

Post competency assessment has become an important part of modern recruitment, and teaching is one of the indispensable occupations. Assessing the competence of teachers in teaching positions has become a hot topic. This paper takes English teachers as the research object and uses K-means clustering algorithm to evaluate the competence of teachers. This paper first analyzes the references related to this research and finds suitable materials for this research and then mainly describes in detail the main point of English teaching post competency. Next, this paper uses the formula to illustrate the K-means clustering algorithm used in this paper. Finally, it uses experiments to verify the influencing factors of the four dimensions of English job competency. And the final survey results show that the influencing factors have different significant differences on the four dimensions. And the experiment proves the effectiveness and robustness of the proposed algorithm in evaluating the competence of English teaching positions. In addition, from the perspective of the composition of professional titles, it is consistent with the age structure, accounting for 63.3% of the total. Associate senior researchers are the backbone of colleges and universities. This research provides a theoretical basis and reference for measurement tools for college English teacher recruitment and selection, vocational training, performance evaluation, salary reform, and other related educational practices.
TBR-NER: Research on COVID-19 Text Information Extraction Based on Joint Learning of Topic Recognition and Named Entity Recognition
Authors: Feng Xin , Li Yingrui , Hang Zhang , Fan Zhang , Yu Qiong , Xin Ruihao
Published: August 2022

There is a centralization of the core content in the text information of the new crown epidemic notification. This paper proposes a joint learning text information extraction method: TBR-NER (topic-based recognition named entity recognition) based on topic recognition and named entity recognition to predict the labeled risk areas and epidemic trajectory information in text information. Transfer learning and data augmentation are used to solve the problem of data scarcity caused by the initial local outbreak of the epidemic, and mutual understanding is achieved by topic self-labeling without introducing additional labeled data. Taking the epidemic cases in Hebei and Jilin provinces as examples, the reliability and effectiveness of the method are verified by five types of topic recognition and 15 types of entity information extraction. The experimental results show that, compared with the four existing NER methods, this method can achieve optimality faster through the mutual learning of each task at the early stage of training. The optimal accuracy in the independent test set can be improved by more than 20%, and the minimum loss value is significantly reduced. This also proves that the joint learning algorithm (TBR-NER) mentioned in this paper performs better in such tasks. The TBR-NER model has specific sociality and applicability and can help in epidemic prediction, prevention, and control.
Diagnosing Diabetic Retinopathy in OCTA Images Based on Multilevel Information Fusion Using a Deep Learning Framework
Authors: Li Qiaoyu , Zhu Xiao-rong , Sun Guangmin , Zhang Lin , Zhu Meilong , Tian Tian , Guo Chenyu , Mazhar Sarah , Yang Jin-Kui , Li Yu
Published: August 2022

Objective. As an extension of optical coherence tomography (OCT), optical coherence tomographic angiography (OCTA) provides information on the blood flow status at the microlevel and is sensitive to changes in the fundus vessels. However, due to the distinct imaging mechanism of OCTA, existing models, which are primarily used for analyzing fundus images, do not work well on OCTA images. Effectively extracting and analyzing the information in OCTA images remains challenging. To this end, a deep learning framework that fuses multilevel information in OCTA images is proposed in this study. The effectiveness of the proposed model was demonstrated in the task of diabetic retinopathy (DR) classification. Method. First, a U-Net-based segmentation model was proposed to label the boundaries of large retinal vessels and the foveal avascular zone (FAZ) in OCTA images. Then, we designed an isolated concatenated block (ICB) structure to extract and fuse information from the original OCTA images and segmentation results at different fusion levels. Results. The experiments were conducted on 301 OCTA images. Of these images, 244 were labeled by ophthalmologists as normal images, and 57 were labeled as DR images. An accuracy of 93.1% and a mean intersection over union (mIOU) of 77.1% were achieved using the proposed large vessel and FAZ segmentation model. In the ablation experiment with 6-fold validation, the proposed deep learning framework that combines the proposed isolated and concatenated convolution process significantly improved the DR diagnosis accuracy. Moreover, inputting the merged images of the original OCTA images and segmentation results further improved the model performance. Finally, a DR diagnosis accuracy of 88.1% (

95
%
CI
±
3.6
%

) and an area under the curve (AUC) of 0.92 were achieved using our proposed classification model, which significantly outperforms the state-of-the-art classification models. As a comparison, an accuracy of 83.7 (

95
%
CI
±
1.5
%

) and AUC of 0.76 were obtained using EfficientNet. Significance. The visualization results show that the FAZ and the vascular region close to the FAZ provide more information for the model than the farther surrounding area. Furthermore, this study demonstrates that a clinically sophisticated designed deep learning model is not only able to effectively assist in the diagnosis but also help to locate new indicators for certain illnesses.
Development and Application of Sales System Software Based on Computer Network
Authors: Liu Chang
Published: August 2022

In order to solve the problem that the automobile sales management becomes more and more complicated, this paper proposes a sales system software platform based on a computer network. The automobile sales management system based on the MVVM framework, with Java as the development language and MySQL as the database, is implemented by the progressive framework Vue in the front end and developed by the Spring Boot framework in the back end. Starting with the design and implementation of the system, the technical framework, functional modules, and implementation processes used to develop the system are studied. The experimental results show that the function tests are normal, the response time of the system client is generally 1-2 seconds, the processing speed is fast, and the influence ability is good. The system improves the comprehensive management ability and promotes the rapid development of automobile industry.
Urban Cultural Industry Management System and Public Economic Based on Improved Algorithm
Authors: Xiong Mengzhi
Published: August 2022

Social reliability and sustainable financial development in metropolises have become urgent problems to be solved. Due to its solid importance and imagination, urban cultural industry management and public economy have gradually become the focus of consideration in all fields of society. Organized and coordinated improvement of the urban economy and society and imaginative undertakings have also become the focus of review at all levels of academia and government. This article aims to study and apply the improved algorithm to the urban cultural industry management system and public economic analysis. It proposed the improved algorithm and related methods, the correlation between urban cultural industry management and economy, the improved particle swarm algorithm and the SOM algorithm, and finally, applied the improved SOM algorithm to evaluate the regional economy of a city. The experimental results showed that the contribution rate of the economic evaluation level of the eight economic evaluation indicators to the economic development level of each county (district and city) in the city was different, of which, the cumulative contribution rate of the first four main components reached 83%.
Daurisoline Inhibits ESCC by Inducing G1 Cell Cycle Arrest and Activating ER Stress to Trigger Noxa-Dependent Intrinsic and CHOP-DR5-Dependent Extrinsic Apoptosis via p-eIF2α-ATF4 Axis
Authors: Yuan Shuying , Pan Yongfu , Xu Tong , Zhang Li , Chen Xihui , Wang Fengying , Liu Qian , Jia Lijun
Published: August 2022

Esophageal squamous cell carcinoma (ESCC), one of the most malignant human cancers in clinic, requires novel treatment. Daurisoline (DAS) is a component of traditional Chinese herb, which exhibits anti-cancer effects by autophagy inhibition and metastasis suppression. However, the effect and mechanism of DAS on ESCC remain unclear. Here, we found that DAS inhibited cell proliferation and colony formation in both human ESCC cell lines EC1 and ECA109. Mechanistically, DAS induced p21-/p27-dependent G1 phase cell cycle arrest and apoptosis in a dose-dependent manner. The induction of apoptosis by DAS was largely dependent on the activation of the transcription factor ATF4 and its downstream NOXA-dependent intrinsic and CHOP-DR5-dependent extrinsic apoptotic pathway. ATF4 activation induced by DAS was due to the generation of excessive reactive oxygen species (ROS) and the subsequent activation of endoplasmic reticulum (ER) stress through the p-eIF2α-ATF4 signal pathway, which can be largely abrogated by N-acetylcysteine (NAC), a scavenger of ROS. Moreover, DAS treatment significantly inhibited tumor growth and reduced tumor weight in the tumor xenograft mouse model by up-regulating key proteins related to cell cycle arrest and apoptotic pathway. Taken together, these findings identified DAS as a novel candidate for the treatment of ESCC.
Interactive Multimedia Data Coscattering Point Imaging for Low Signal-to-Noise Ratio 3D Seismic Data Processing
Authors: Fei Jianbo , Wang Yanchun
Published: August 2022

In this paper, low signal-to-noise ratio 3D seismic data are processed by the method of coscattered point imaging, and the imaging method is analyzed in combination with interactive multimedia for 3D seismic data. The reconstruction is carried out using a convex set projection algorithm based on the curvilinear wave transform. The track set is extracted from the 3D data body and transformed into the common offset distance-center point tract set to achieve the reconstruction of seismic data in the common offset distance track set domain and through comparison. It is concluded that the reconstruction effect is better in the common. The reconstruction results are better in the common offset distance track set domain. To shorten the processing time and obtain better reconstruction results, this paper proposes the idea of direct reconstruction of frequency slices. Experiments on the actual seismic three-component wavefield based on velocity-type and acceleration-type three-component geophones are carried out to reveal the signal characteristics of the actual seismic wavefield under the mining space. Due to the limitation of the construction observation space and the particularity of the actual needs of mine detection, the application of the scattered wave imaging method in the mine must be based on the corresponding detection space and detection purpose. The implementation of this thesis improves the signal-to-noise ratio, resolution, and fidelity of the 3D seismic data of the Shawan Formation, which is more conducive to the search for lithological traps. Combined with the seismic geological data, several traps were finally found and implemented, indicating that the fidelity of the resultant information is good and can meet the needs of interpretation and comprehensive research. The multiwave scattering imaging method in this paper can complete multiwave field imaging of longitudinal, transverse, and slot waves, which has the advantages of data redundancy, high superposition number, and more accurate imaging than conventional reflection wave imaging and provides field application value for ensuring mine safety production.
Pressure Transient Analysis for a Well Drilling into a Large-Size Cave in Fracture-Caved Carbonate Gas Reservoirs
Authors: Jin Jie , Li Qingyu , Lu Detang
Published: August 2022

This paper studies the influence of large-size cave on pressure transient characteristics in fracture-caved carbonate gas reservoirs (FCCGR). With the rapid increase of energy demand, the exploration and development of unconventional oil and gas becomes more and more important. In recent years, many FCCGR have been discovered in western China and contribute significantly to Chinese gas reserves. However, with the presence of large-size cave, FCCGR have complex pore structures and strong heterogeneity. Traditional pressure transient analysis models cannot describe the gas flow accurately. This paper develops a novel pressure transient analysis model for FCCGR by coupling the fluctuating pressure and minor energy loss. Based on the solutions, the typical curves are plotted to analyze the pressure transient characteristics. It is found that the flow process can be subdivided into six stages, including the following: (I) wellbore storage, (II) first transition stage, (III) cave storage, (IV) second transition stage, (V) interporosity flow, and (VI) radial flow. The findings indicate that a concave is added, and the wellbore storage occurs earlier due to the existence of cave. Then, the influences of key parameters are studied. The pressure propagation coefficient and cave volume factor influence the stages I, II, III, and IV. When pressure propagation coefficient increases, the wellbore storage becomes larger and cave storage becomes smaller. The first concave moves to upper right. When cave volume factor increases, the wellbore storage occurs earlier and the curves move left in stage I. Interporosity flow factor and storage ratio influence the location and depth of the second concave. Finally, a field gas well is interpreted by using the proposed model, which verifies the reliability and correctness of the model. The findings of this study can help to better understand the influence of large-size cave on pressure transient characteristics. In addition, it can help engineers invert the cave volume, which is of great significance for the development in FCCGR.
The Application of Practical Clothing Design Method in the Teaching of Clothing Specialty
Authors: Li Miao , Fu Rong
Published: August 2022

To improve the teaching practice effect of clothing major, this study applies the practical clothing design method to the teaching of clothing major to analyze the digital clothing design and establishes a convex quadratic conic programming model for a class of force optimization problems. Then, this study transforms the optimality condition of the problem into a new projection equation system, constructs a suitable constant coefficient matrix according to the characteristics of the equation system, and obtains an equivalent linear equation system. In addition, this study proposes a full Newton step projection algorithm to directly solve the convex quadratic conic programming. Through the results of the experimental research, it can be seen that the practical clothing design method has a good application in the teaching of clothing majors, and it can be applied in the practice of clothing teaching.
Thermal Management of the Melting Process in a Latent Heat Triplex Tube Storage System Using Different Configurations of Frustum Tubes
Authors: Tiji Mohammadreza Ebrahimnataj , Al-Azzawi Waleed Khalid , Mohammed Hayder I. , Dulaimi Anmar , Rashid Farhan Lafta , Mahdi Jasim M. , Majdi Hasan Sh. , Talebizadehsardari Pouyan , Ali Hafiz Muhammad
Published: August 2022

In this study, the energy charging mechanism is mathematically modeled to determine the impact of design modifications on the thermofluidic behavior of a phase change material (PCM) filled in a triplex tube containment geometry. The surface area of the middle tube, where the PCM is placed, is supported by single or multi‐internal frustum tubes in vertical triplex tubes to increase the performance of the heating and cooling of the system. In addition to the ordinary straight triplex tubes, three more scenarios are considered: (1) changing the middle tube to the frustum tube, (2) changing the inner tube to the frustum tube, and (3) changing both the internal and central tubes to the frustum tubes. The impact of adopting the tube designs and gap width were studied. The outcomes reveal that the heat storage rates are increased for all frustum tube systems compared to the straight tube system. According to the results, the case of a gap width of 5 mm is the optimal one among the studied cases in terms of the melting time and the heat storage rate. Employing the frustum tube configuration with a 5‐mm gap width would save the melting time by 25.6% and increase the rate of heat storage by 32.8% compared to the base case of straight tubes.
Managing Post COVID-19 Patient with Breathlessness
Authors: Wong Yen Shen , Ibrahim Muhammad Amin , Mohd Zim Mohd Arif , Abdul Rani Mohd Fauzi
Published: August 2022

Background. Chronic respiratory disease may be associated with severity of coronavirus disease 2019 (COVID-19) infection. We review a case of chronic obstructive pulmonary disease (COPD) patient who developed acute breathlessness post COVID-19 infection, also focusing on the diagnostic approach. Case. A 69-year-old gentleman with background history of COPD GOLD D and ischemic heart disease was admitted with severe COVID-19 infection. He required high-flow nasal cannula upon presentation. A computed tomography pulmonary angiography (CTPA) thorax at day 10 of illness revealed moderate organizing pneumonia (OP) with emphysematous changes, without pulmonary embolism. He received oral baricitinib and intravenous methylprednisolone for 3 days, which was then followed by tapering prednisolone starting dose of 1 mg/kg/day (60 mg/day) with reduction of 10 mg prednisolone every 3 days. COPD pharmacotherapy was optimized with early utilization of dual bronchodilators and inhaled corticosteroid was withheld. He underwent inpatient pulmonary rehabilitation and was discharged with home oxygen therapy. Unfortunately, he was re-admitted after 2 weeks with shortness of breath and fever for 3 days. Blood results revealed leucocytosis with raised C-reactive protein. A repeat CTPA showed increase reticulations and crazy paving pattern with reduction in lung volume. Multidisciplinary team discussion concluded it as interstitial pneumonia with COVID-19 OP and fibrosis progression. Prednisolone was stopped and he responded well with antibiotics. A follow-up at 3 months post COVID-19 infection showed improvement of clinical symptoms with radiological resolution of ground glass changes. Conclusion. Corticosteroid inhaler should be cautioned in this case, in view of recent pneumonia and non-elevated serum eosinophil count. These groups of patients should be closely followed up to unmask interstitial lung disease that may present prior to COVID-19 and worsen post-infection. Optimizing pre-existing medical conditions should be the paramount intervention.
High-Concurrency Big Data Precision Marketing and Advertising Recommendation under 5G Wireless Communication Network Environment
Authors: Chen Xianfeng
Published: August 2022

With the rise of 5G wireless communication networks, information technology has challenged the traditional practice of marketing. The impact of enterprise precision marketing theory on traditional marketing theory was brought by massive user data in the era of big data. With the sudden rise and rapid development of mobile Internet and its derived big data, in the fierce market competition of new media and we-media, how to provide accurate information push for users has become the primary subject of research. The design of advertising precision marketing system mainly uses 5G network as the basic tool and makes precise positioning of consumer demand through high-concurrency big data analysis system.

K

-means clustering algorithm improves the data analysis system to provide personalized demand customization and deeply excavates the segmentation of the consumer market and the real demand of consumers. The results show that the model effectively enhances its adaptability. When

S

value is between 0.01 and 0.05, the variable has a high significance, and precision marketing improves the accuracy of recommendation.
A Massage Area Positioning Algorithm for Intelligent Massage System
Authors: Zhou Liran , Feng Zhiquan , Cai Zeyuan , Yang Xiaohui , Ai Changsheng , Shao Haiyan
Published: August 2022

A growing number of studies have been conducted over the past few years on the positioning of daily massage robots. However, most methods used for research have low interactivity, and a systematic method should be designed for accurate and intelligent positioning, thus compromising usability and user experience. In this study, a massage positioning algorithm with online learning capabilities is presented. The algorithm has the following main innovations: (1) autonomous massage localization can be achieved by gaining insights into natural human-machine interaction behavior and (2) online learning of user massage habits can be achieved by integrating recursive Bayesian ideas. As revealed by the experimental results, combining natural human-computer interaction and online learning with massage positioning is capable of helping people get rid of positioning aids, reducing their psychological and cognitive load, and achieving a more desirable positioning effect. Furthermore, the results of the analysis of user evaluations further verify the effectiveness of the algorithm.
Combine and Conquer: With Type 2 Diabetes Polypharmacy Is Essential Not Only to Achieve Glycemic Control but Also to Treat the Comorbidities and Stabilize or Slow the Advancement of Diabetic Nephropathy
Authors: Bell David S. H.
Published: August 2022

The concept of polypharmacy in the type 2 diabetic patient is both historic and redundant. A combination of three or more medications usually at doses which are less than those utilized for monotherapy is efficacious not only in the therapy of hyperglycemia but also in the therapy of the comorbidities of hypertension and hyperlipidemia. In addition, multiple medications are now accepted as being necessary to reduce albuminuria and decelerate the decline in renal function in the patient with diabetic nephropathy.
The Characterization and Functional Properties of Euglena gracilis Paramylon Treated with Different Methods
Authors: Gao Liwei , Zhao Xinjie , Zhao Xiangzhong
Published: August 2022

Euglena gracilis paramylon (EGP) is a polymeric polysaccharide composed of linear β-1,3 glucan. The water insolubility of EGP severely limits its application. This work aimed to improve the functional characteristics of EGP by hydrogen peroxide (H2O2) degradation and carboxymethylated modification. The results showed that the crystallinity of EGP degraded by H2O2 and carboxymethylated modification decreased by 14% and 46%, and the thermal degradation temperature was significantly descending in a crystallinity-dependent manner. In addition, the results showed that H2O2 degradation and carboxymethylation significantly improved the adsorption capacity of EGP for oil, dyes, and metal ions, and their water solubility increased by 9% and 85%. This result will provide a valuable theoretical basis for the development and utilization of EGP.
Enabling Artificial Intelligence of Things (AIoT) Healthcare Architectures and Listing Security Issues
Authors: Pise Anil Audumbar , Almuzaini Khalid K. , Ahanger Tariq Ahamed , Farouk Ahmed , pant Kumud , Pareek Piyush Kumar , Nuagah Stephen Jeswinde
Published: August 2022

A significant study has been undertaken in the areas of health care and administration of cutting-edge artificial intelligence (AI) technologies throughout the previous decade. Healthcare professionals studied smart gadgets and other medical technologies, along with the AI-based Internet of Things (IoT) (AIoT). Connecting the two regions makes sense in terms of improving care for rural and isolated resident individuals. The healthcare industry has made tremendous strides in efficiency, affordability, and usefulness as a result of new research options and major cost reductions. This includes instructions (AIoT-based) medical advancements can be both beneficial and detrimental. While the IoT concept undoubtedly offers a number of benefits, it also poses fundamental security and privacy concerns regarding medical data. However, resource-constrained AIoT devices are vulnerable to a number of assaults, which can significantly impair their performance. Cryptographic algorithms used in the past are inadequate for safeguarding IoT-enabled networks, presenting substantial security risks. The AIoT is made up of three layers: perception, network, and application, all of which are vulnerable to security threats. These threats can be aggressive or passive in nature, and they can originate both within and outside the network. Numerous IoT security issues, including replay, sniffing, and eavesdropping, have the ability to obstruct network communication. The AIoT-H application is likely to be explored in this research article due to its potential to aid with existing and different technologies, as well as bring useful solutions to healthcare security challenges. Additionally, every day, several potential problems and inconsistencies with the AIoT-H technique have been discovered.
Simulation and Application of Urban Road Landscape Based on Geographic Information Data
Authors: Yu Shanshan
Published: August 2022

In this paper, we study and analyze the urban road landscape by integrating big data with GIS and designing a simulation system. Underwood is selected as the base model and calibrated for optimal density and capacity. The traffic flow model is optimized, and the minimum flow rate of each class of road is corrected; the traffic volume of highway and expressway in the early morning and at night is adjusted to make up for the discrepancy between the calculated flow rate of the model and the actual situation due to the unstable speed. Investigate and analyze the pollutants produced by enterprises along the road and select suitable and targeted plants to enhance the ecological protection of road landscape and optimize and improve the park environment; combine the regional culture and apply the ceramic culture to the design of road landscape vignettes; select suitable water and moisture-resistant plants for slope protection plant landscape design, to form a trinity of ecological protection, landscape road, and riverfront green space of industrial park road landscape. As a new basic geospatial infrastructure and carrier, 3D city has a unique spatiotemporal view to plan and manage the operation and maintenance information of the whole city. This part of the study takes urban planning, community management, urban publicity, and tourism management as demonstration cases and focuses on the elaboration and verification of how 3D city data and 3D urban geographic information are applied in the refined urban construction and management. Typical road measurement data are selected, and the applicability of the road traffic flow model of each level is judged by numerical analysis. An interactive road model editing method with the help of auxiliary information is proposed. With the help of auxiliary information displayed in different ways, the operation of adjusting road height in three-dimensional space is transformed into operation in a two-dimensional plane, which can effectively simplify the operation process and improve the accuracy of model editing.
Effect of Different Post Materials and Adaptability on Fracture Resistance and Fracture Mode in Human Endodontically Treated Teeth
Authors: Bhaktikamala Anutara , Chengprapakorn Wareeratn , Serichetaphongse Pravej
Published: August 2022

Objective. To investigate the effect of different post materials and adaptability on fracture resistance and fracture mode of endodontically treated teeth. Materials and Methods. Sixty extracted human mandibular premolars were selected and divided into 6 groups (n = 10) according to the restorative method after endodontic treatment: no ferrule presented and restored without fiber post (Group C), 2.0 mm ferrule presented and restored without fiber post (Group CF), restored with D.T. Light-Post (Group PDT), restored with anatomically customized D.T. Light-Post, relined with resin composite (Group ADT), restored with Hi-Rem prosthetic post (Group PHR), and restored with anatomically customized Hi-Rem prosthetic post, relined with resin composite (Group AHR). After restoring with core build-up materials, all specimens were loaded at 45° in a universal testing machine until failure. Visual inspection of all specimens for fracture modes was performed. The data were analyzed using one-way ANOVA, and the fracture mode was reviewed using the chi-square test. Results. Anatomically customized groups presented statistically significant higher fracture resistance than prefabricated groups and group C (

P
<
0.05

). Without post, group CF displayed significantly higher fracture resistance than group C (

P
<
0.05

). Group C, CF, PDT, and PHR showed some specimens with unfavorable fractures. Conclusions. Anatomically customized posts presented highest fracture resistance among all groups. There was no significant difference in fracture mode across all groups.
The Effect of Routine Management Combined with Case Management Model on Social Support, Self-Efficacy, Self-Management Ability, and Psychological Flexibility of AIDS Patients
Authors: Liu Li , Zhou Jing , Xiao Huan , Luo Yanhe , Zeng Yan , Fan Li , Zheng Chen
Published: August 2022

Objective. To explore the influence of conventional management combined with case management on social support and self-efficacy of AIDS patients. Methods. The clinical case data of 120 AIDS patients who were treated and nursed in our hospital from June 2019 to June 2021 were selected as the research objects and were divided into the control group and the observation group according to the digital table method, with 60 cases each. The control group implements routine management, and the observation group implements case-based nursing management on this basis and compares the effects of self-efficacy, self-management ability, nursing ability, social support, and psychological flexibility of the two groups of patients. Results. Before the intervention, the quality of life scores of the two groups was not statistically significant (

P
>
0.05

). After the intervention, the physical function score, pain management score, and symptom response score of the observation group were significantly higher than those of the control group, and statistics showed that the difference was statistically significant (

P
<
0.05

). Before the intervention, the self-management ability of the two groups of patients was not statistically significant (

P
>
0.05

). After the intervention, the observation group’s symptom management, emotional cognition management, social support and assistance, daily life management, disease knowledge management, and treatment compliance management were significantly higher than those of the control group. Statistics show that this difference is statistically significant (

P
<
0.05

). Before the intervention, there was no significant difference in the nursing ability and psychological flexibility between the two groups of patients (

P
>
0.05

). After the intervention, the observation group’s health knowledge level, self-care skills, self-care responsibility, self-concept, and mental flexibility (resilience, strength, optimism) indicators were higher than the control group, while the depression mood disorder score was significantly lower than the control group; statistics showed that this difference was statistically significant (

P
<
0.05

). Conclusion. Routine management combined with case-based nursing management can effectively improve the self-management ability and psychological flexibility of AIDS patients, improve patient care ability and self-efficacy, and provide certain reference value for effective management of AIDS patients.
Efficient Continuation Methods for Computing Ground States of Quasi-2D Rotating Dipolar Bose-Einstein Condensates
Authors: Jeng B.-W. , Su P.-H. , Char M.-I.
Published: August 2022

We study efficient continuation methods for computing the ground state solution of quasi-2D rotating dipolar Bose-Einstein condensates (BECs). First, the highly accurate spectral collocation method is used to discretize the governing Gross-Pitaevskii equation (GPE). Then, we modify the two-level continuation scheme for 3D dipolar BECs described in Jeng et al. (2014) to develop a single-parameter continuation method for quasi-2D rotating dipolar BECs, where the chemical potential is treated as the continuation parameter. Further, by adding the ratio of dipolar interaction strength to contact interaction strength as the second continuation parameter, we propose an efficient two-parameter continuation method which can effectively show the change of the ground-state vortex structures as the dipolar interaction strength gradually increases. Moreover, we also study linear stability analysis for the GPE. Sample numerical results on quasi-2D rotating dipolar BECs are reported.
Image Segmentation Technology Based on Attention Mechanism and ENet
Authors: Ma Ling , Hou Xiaomao , Gong Zhi
Published: August 2022

With the development of today’s society, medical technology is becoming more and more important in people’s daily diagnosis and treatment and the number of computed tomography (CT) images and MRI images is also increasing. It is difficult to meet today’s needs for segmentation and recognition of medical images by manpower alone. Therefore, the use of computer technology for automatic segmentation has received extensive attention from researchers. We design a tooth CT image segmentation method combining attention mechanism and ENet. First, dilated convolution is used with the spatial information path, with a small downsampling factor to preserve the resolution of the image. Second, an attention mechanism is added to the segmentation network based on CT image features to improve the accuracy of segmentation. Then, the designed feature fusion module obtains the segmentation result of the tooth CT image. It was verified on tooth CT image dataset published by West China Hospital, and the average intersection ratio and accuracy were used as the metric. The results show that, on the dataset of West China Hospital, Mean Intersection over Union (MIOU) and accuracy are 83.47% and 95.28%, respectively, which are 3.3% and 8.09% higher than the traditional model. Compared with the multiple watershed algorithm, the Chan–Vese segmentation algorithm, and the graph cut segmentation algorithm, our algorithm increases the calculation time by 56.52%, 91.52%, and 62.96%, respectively. It can be seen that our algorithm has obvious advantages in MIOU, accuracy, and calculation time.
Monoclonal Gammopathy of Renal Significance: Histomorphological Spectrum at a Tertiary Care Center
Authors: Barwad Adarsh , Bajaj Varun , Singh Geetika , Dinda Amit Kumar , Sahoo Ranjit Kumar , Kumar Lalit , Agarwal Sanjay Kumar
Published: August 2022

Introduction: The term monoclonal gammopathy of renal significance (MGRS) has been described to include patients with renal manifestations associated with circulating monoclonal proteins with or without a clonal lymphoproliferation (B-cell or plasma cell) and not meeting diagnostic criteria for an overt hematological malignancy. A host of MGRS-associated lesions have been described that involve various renal compartments. Our study describes the histomorphological spectrum of MGRS cases at our center in the last 5 years and description as per the classification system of the International Kidney and Monoclonal Gammopathy Research Group (IKMG). Material and Methods: Retrospective analysis was carried out of all the renal biopsies with characteristic monoclonal immunoglobulin lesions for histopathological diagnosis between years 2015 and 2020 and reviewed by two independent pathologists. Results: Most patients in the study belonged to the fifth decade, with a median age of 50 years (mean 50.14 ± 10.43) range (24–68 years) with a male preponderance. Most patients presented with proteinuria as the sole manifestation (66.6%). Many of the patients (48%) had an M spike by serum protein electrophoresis or urinary protein electrophoresis with an abnormal serum free light chain assay (60.8%). AL amyloidosis was the most common diagnosis observed on histopathological evaluation (68.7%), followed by light chain deposition disease (10.4%). Conclusion: MGRS lesions are infrequently encountered in the practice of nephropathology and pose a diagnostic challenge due to the limitation of a congruent clinical or hematological picture. A thorough histological examination with immunofluorescence and electron microscopy often precipitates in the right diagnosis and prompts timely management.
Changes in Dimensions and Functions of Crystalline Lens in High Myopia Using CASIA2 Optical Coherence Tomography
Authors: Wang Xuetong , Zhu Chengcheng , Hu Xiaojun , Liu Lu , Liu Mingming , Yuan Ying , Ke Bilian
Published: August 2022

Introduction: Crystalline lens is the major dioptric component and varies with refractive status. In this study, we aim to evaluate the changes of dimensions and functions of crystalline lens in high myopia (HM) and its correlated variables using CASIA2 swept-source optical coherence tomography. Methods: One hundred and thirty eligible eyes of myopic patients from 18 to 40 years old were enrolled and divided into low-to-moderate myopia (LMM) and HM groups according to spherical equivalent (SE). Anterior segment features, including lens thickness (LT), anterior radius of curvature (ARC), posterior radius of curvature (PRC), anterior chamber depth (ACD), and lens tilt were obtained by CASIA2. Lens power was calculated using Bennett’s formula. Sixty-seven participants were imaged at the static state and the accommodative state induced by −3 diopter (D) stimulus. Results: Compared to the LMM group, the HM group exhibited a significantly reduction in LT, ARC, and lens tilt (all p < 0.01). Each parameter correlated positively with SE (all p < 0.01). Lens power increased with LT and tilt (r = 0.42, 0.45) but decreased with ARC and axial length (AL) (r = −0.37, −0.62) among highly myopic eyes. Multivariate regression analysis revealed that lower lens power appeared to be independently associated with axial elongation in both groups (LMM: β = −1.124, p = 0.002; HM: β = −1.603, p < 0.001, respectively). Decreases in ARC and ACD were accompanied by accommodative response in each group, while PRC reduced during accommodation (p = 0.009) only in HM. Conclusions: Young adults with HM presented a thinner thickness, smaller tilt, less lens power, and higher accommodative response. Lens shape was closely associated with SE; however, AL was a meaningful indicator of lens power.
Sobre os efeitos de um exílio: Jean-François Champollion e o estudo da língua egípcia em Figeac
Authors: Cabral Jessica
Published: August 2022

O presente artigo discute as condições de produção dos estudos filológicos sobre a antiga escrita hieroglífica egípcia desenvolvidos por Jean-François Champollion (1790-1832) durante o período em que foi perseguido politicamente e exilado na sua cidade natal, Figeac, logo após a restauração monárquica de 1815 na França. Para tanto, mobiliza-se a documentação epistolar que permite mapear sua produção científica de forma complementar às suas publicações. O principal cerne do trabalho aqui é analisar como, apesar das adversidades político-sociais sofridas por Champollion do ponto de vista científico, esse período foi essencial para o avanço de suas hipóteses teóricas. Em suma, o artigo busca expandir a compreensão sobre as complexidades que envolvem as inovações científicas, dissolvendo uma imagem já consolidada de que a decifração teria sido uma descoberta despropositada e não o resultado de um longo processo de estudo e de construção do conhecimento.