bluuebunny/crossref_metadata_2025 huggingface dataset:
Application of Multiparameter Kalman Filter in Ultrasonic Water Meter
Authors: Zuo Fuqiang , Liu Yu
Published: January 2022

With the gradual development of the superior performance of the ultrasonic water meter, the use of the water meter gradually occupies most of the market due to its unique advantages. Through the analysis of the influencing factors of the ultrasonic water meter, the Kalman filter is used to analyze the influencing factors, and the differences are obtained. In this paper, combined with the application scope of the Kalman filter, it is introduced. Combined with the method of data fusion, the influencing factors of the ultrasonic water meter are analyzed. They are the flow rate, temperature, speed of sound, time difference, etc. The appropriate sensor is selected through the sensor selection method, and the corresponding data is obtained by the method of the corresponding sensor. We combine the data fusion method and use Kalman’s method to filter the data. By comparing the data before and after the processing, it is found that the data before and after the filtering of different influencing factors are small. Among them, the flow speed factor has the greatest impact on the accuracy of the ultrasonic water meter; temperature and sound velocity have little effect on the performance of the ultrasonic water meter. When designing an ultrasonic water meter, it is mainly necessary to consider the impact of flow rate and time difference on the performance of the ultrasonic water meter.
Data Transmission Reliability Analysis of Wireless Sensor Networks for Social Network Optimization
Authors: Xu Xia , Tang Jin , Xiang Hua
Published: January 2022

With the rapid development of the Internet in recent years, people are using the Internet less and less frequently. People publish and obtain information through various channels on the Internet, and online social networks have become one of the most important channels. Many nodes in social networks and frequent interactions between nodes create great difficulties for privacy protection, and some of the existing studies also have problems such as cumbersome computational steps and low efficiency. In this paper, we take the complex environment of social networks as the research background and focus on the key issues of mobile wireless sensor network reliability from the mobile wireless sensor networks that apply to large-scale, simpler information, and delay tolerance. By introducing intelligent learning methods and swarm intelligence bionic optimization algorithms, we address reliability issues such as mobile wireless sensor network fault prediction methods and topology reliability assessment methods in industrial application environments, the impact of mobile path optimization of mobile wireless sensor networks on data collection efficiency and network reliability, reliable data transmission based on data fusion methods, and intelligent fault tolerance strategies for multipath routing to ensure mobile wireless sensor networks operate energy-efficiently and reliably in complex industrial application environments.
Target Positioning and Grasping of NAO Robot Based on Monocular Stereo Vision
Authors: Chen Hongbin
Published: January 2022

With the continuous advancement of science and technology and the rapid development of robotics, it has become an inevitable trend for domestic robots to enter thousands of households. In order to solve the inconvenience problem of the elderly and people with special needs, because the elderly and other people in need may need the help of domestic robots due to inconvenient legs and feet, the research of the robot target position based on monocular stereo vision and the understanding of the robot NAO are very important. Research and experiments are carried out on the target recognition and positioning in the process of NAO robot grasping. This paper proposes a recognition algorithm corresponding to quantitative component statistical information. First, extract the area of interest that contains the purpose from the image. After that, to eliminate interference in various fields and achieve target recognition, the robot cameras have almost no common field of view and can only use one camera at the same time. Therefore, this article uses the monocular vision principle to locate the target, and the detection algorithm is based on the structure of the robot head material, establishes the relationship between the height change of the machine head and the tilt angle, and improves the monocular vision NAO robot detection algorithm. According to experiments, the accuracy of the robot at close range can be controlled below 1 cm. This article completes the robot’s grasping and transmission of the target. About 80% of the external information that humans can perceive comes from vision. In addition, there are advantages such as high efficiency and good stability.
High Frequency of Microvascular Dysfunction in US Outpatient Clinics: A Sign of High Residual Risk? Data from 7,105 Patients
Authors: Naghavi Morteza , Kleis Stanley , Tanaka Hirofumi , Yen Albert A. , Zhuang Ruoyu , Gul Ahmed , Naghavi Yasamin , Metcalfe Ralph
Published: January 2022

Previous studies have linked peripheral microvascular dysfunction measured by arterial tonometry to high residual risk in on-statin patients. Digital thermal monitoring (DTM) of microvascular function is a new and simplified technique based on fingertip temperature measurements that has been correlated with the burden of atherosclerosis and its risk factors. Here, we report analyses of DTM data from two large US registries: Registry-I (6,084 cases) and Registry-II (1,021 cases) across 49 US outpatient clinics. DTM tests were performed using a VENDYS device during a 5-minute arm-cuff reactive hyperemia. Fingertip temperature falls during cuff inflation and rebounds after deflation. Adjusted maximum temperature rebound was reported as vascular reactivity index (VRI). VRI distributions were similar in both registries, with

mean
±
SD

of

1.58
±
0.53

in Registry-I and

1.52
±
0.43

in Registry-II. In the combined dataset, only 18% had optimal VRI (≥2.0) and 82% were either poor (<1.0) or intermediate (1.0-2.0). Women had slightly higher VRI than men (

1.62
±
0.56

vs.

1.54
±
0.47

,

p
<
0.001

). VRI was inversely but mildly correlated with age (

r
=
−
0.19

,

p
<
0.001

). Suboptimal VRI was found in 72% of patients <50 years, 82% of 50-70 years, and 86% of ≥70 years. Blood pressure was not correlated with VRI. In this largest registry of peripheral microvascular function measurements, suboptimal scores were highly frequent among on-treatment patients, possibly suggesting a significant residual risk. Prospective studies are warranted to validate microvascular dysfunction as an indicator of residual risk.
Supply Chain Governance of Agricultural Products under Big Data Platform Based on Blockchain Technology
Authors: Guo Wei , Yao Kai
Published: January 2022

The present work serves to improve the stable cooperation relationship among subjects of supply chain such as enterprises, farmers, intermediary organizations, and retailers and enhance the governance and optimization of agricultural product supply chain, thus strengthening the competitiveness of China’s agricultural industry. The supply chain governance of agricultural products is taken as the research object. Initially, the stabilities of two supply chain organization modes, “company and farmer” and “company, intermediary organization and farmer,” are analyzed by static game analysis. Then, based on the above analysis and the characteristics of blockchain institutional technology, a detailed analyzation is made on the mechanism of supply chain of agricultural products governance based on blockchain technology. Finally, the functional framework of agricultural supply chain governance is designed based on the basic framework of blockchain technology, and analyzation is made on the trust mechanism and contract mechanism of agricultural supply chain governance based on blockchain technology. The research results show that problems such as information and cognitive constraints in agricultural supply chain governance cannot be completely solved only through the evolution of blockchain organizational structure and the supply of governance mechanism, and speculative behavior will still appear. Optimizing the governance of supply chain of agricultural products based on blockchain technology can realize the transformation of its governance scenario. Meanwhile, the blockchain technologies such as deintermediation, demistrust, and intelligent contract play an important role in the process of agricultural supply chain governance, which can make it change in many aspects such as organization mode, application operation, and governance mechanism. The rapid development of new generation information technologies such as blockchain, the Internet of Things, and computer technology makes it possible to comprehensively digitize economic activities such as production and transaction in the supply chain of agricultural products. The present work combines the technical logic of blockchain digital governance with the institutional logic of agricultural product supply chain governance and tries to solve the instability problems caused by imperfect organization, lack of trust, and incomplete contract in agricultural product supply chain governance with the characteristics of blockchain such as deintermediation, demistrust, and intelligent contract.
Passenger Behavior Simulation in Congested Urban Rail Transit System: A Capacity‐Limited Optimal Strategy Model for Passenger Assignment
Authors: Lu Kai , Cao Nan
Published: January 2022

Optimal strategy, one of the main transit assignment models, can better demonstrate the flexibility for passengers using routes in a transit network. According to the basic optimal strategy model, passengers can board trains based on their frequency without any capacity limitation. In the metropolitan cities such as Beijing, Shanghai, and Hong Kong, morning commuters face huge transit problems. Especially for the metro system, there is heavy rush in metro stations. Owing to the limited train capacity, some passengers cannot board the first coming train and need to wait for the next one. To better demonstrate the behavior of passengers pertaining to the limited train capacity, we consider capacity constraints for the basic optimal strategy model to represent the real situation. We have proposed a simulation‐based algorithm to solve the model and apply it to the Beijing Subway to demonstrate the feasibility of the model. The application of the proposed approach has been demonstrated using the computational results for transit networks originating from practice.
Research on Real-Time Face Key Point Detection Algorithm Based on Attention Mechanism
Authors: Gao Jiangjin , Yang Tao
Published: January 2022

The existing face detection methods were affected by the network model structure used. Most of the face recognition methods had low recognition rate of face key point features due to many parameters and large amount of calculation. In order to improve the recognition accuracy and detection speed of face key points, a real-time face key point detection algorithm based on attention mechanism was proposed in this paper. Due to the multiscale characteristics of face key point features, the deep convolution network model was adopted, the attention module was added to the VGG network structure, the feature enhancement module and feature fusion module were combined to improve the shallow feature representation ability of VGG, and the cascade attention mechanism was used to improve the deep feature representation ability. Experiments showed that the proposed algorithm not only can effectively realize face key point recognition but also has better recognition accuracy and detection speed than other similar methods. This method can provide some theoretical basis and technical support for face detection in complex environment.
Digitalization and Information Management Mechanism of Sports Events Based on Multisensor Node Cooperative Perception Model
Authors: Liu Yi , Wang Yaodong , Tan Yuntong , Ma Jie , Zhuang Yan , Zhao Xiangqian
Published: January 2022

In the process of developing major sports events, how to guide providers and users to provide and utilize the archives information resources of major sports events and realize the interaction between them is an important problem to be solved urgently in the development of major sports events and the archive service of major sports events. By analyzing the present situation of archive service of major sports events, especially the analysis of the opposite dependent subjects of service providers and users, we can see that the continuous development of archive services for major sports events will inevitably lead to constant changes in user groups and user needs, guided by the theory of information retrieval, knowledge management, and media effect. According to the service model of archive service of major sports events, the archive service model of specific sports events is constructed. In this paper, four kinds of event recommendation models are applied to the collected marathon event data for experiments. Through experimental comparison, the effectiveness of content-based recommendation algorithm technology in the event network data set is verified, and an algorithm model suitable for marathon event recommendation is obtained. Experiments show that the comprehensive event recommendation model based on term frequency–inverse document frequency (TF-IDF) text weight and Race2vec entry sequence has the best recommendation performance on marathon event data set. According to the recommendation target of the event and the characteristics of the event data type, we can choose a single or comprehensive recommendation algorithm to build a model to realize the event recommendation.
Investigating the Spatiotemporal Imbalance of Accessibility to Demand Responsive Transit (DRT) Service for People with Disabilities: Explanatory Case Study in South Korea
Authors: Son Jong-Hun , Kim Do-Gyeong , Lee Eunkyeong , Choi Hosik
Published: January 2022

This study analyzed the operation-related historical data of the call taxi service for disabled people in Seoul, South Korea. The study investigated how unevenly distributed the accessibility of disabled people to transportation is in terms of time and space. In addition, the reasons that cause imbalanced accessibility were investigated in areas with good and poor accessibility. Accessibility was defined as how quickly call taxi services for the disabled are available at specific times and locations. For the analysis, the log data for tracking the status of taxis in time and space were processed to calculate their availability, an index that reflects the dwelling time and the number of taxis available at a specific time and in a specific area. This index was divided into time and space and used as a surrogate measure to assess accessibility. The results showed that there were spatial and temporal accessibility imbalances in demand responsive transit (DRT) service. The insufficient supply during the night resulting from the current DRT operating schedule has reduced the accessibility of call taxis for the disabled, and the concentration of drivers’ breaks also affected the accessibility of service during the daytime. This suggests the need for (1) an increase in supply and (2) evenly distributed breaks for the drivers. In terms of space, the outer areas of Seoul generally were found to be more accessible than the central areas. In addition, areas near depots that serve as hubs and resting places for taxi drivers, areas with excellent medical infrastructures for people with disabilities, and areas with good traffic environments tended to have good accessibility; this suggests the need to reallocate garages and improve the traffic environments to improve accessibility.
Optimization and Simulation of an English-Assisted Reading System Based on Wireless Sensor Networks
Authors: Huang Shumei
Published: January 2022

In this paper, wireless sensor network technology is applied to an English-assisted reading system to highly simulate and restore the context and improve the performance of all aspects of the English-assisted reading system to optimize the English-assisted reading system. The product designed in this paper is based on wireless sensor network technology with Linux as the core operating system and supports POSIX (Portable Operating System Interface Standard) standard application development interface; QT is used as the component and framework of the system to support many applications. Based on player open-source multimedia audio and video technology, optimized and tailored for the hardware platform, it well supports multimedia learning and entertainment functions; this paper also adopts open-source database technology based on SQL (Structured Quevy Language) and Berkeley DB, using them as a platform for data storage and access, supporting a million-level thesaurus and high-speed, example sentence search. In this paper, we describe the user’s personalized needs by creating interest models for the user, recommending the text content, and reading order that can help with understanding through the interest models and reading articles and expanding the recommended text range by making expansions to the reading content through references and related articles to further help the user understand the text. Based on the above work, this paper implements an assisted reading system; finally, a multihop self-organizing network system is formed through a wireless sensor network to make the rigid and boring English reading easy and interesting.
Efficient Approach towards Detection and Identification of Copy Move and Image Splicing Forgeries Using Mask R-CNN with MobileNet V1
Authors: Kadam Kalyani Dhananjay , Ahirrao Swati , Kotecha Ketan
Published: January 2022

With the technological advancements of the modern era, the easy availability of image editing tools has dramatically minimized the costs, expense, and expertise needed to exploit and perpetuate persuasive visual tampering. With the aid of reputable online platforms such as Facebook, Twitter, and Instagram, manipulated images are distributed worldwide. Users of online platforms may be unaware of the existence and spread of forged images. Such images have a significant impact on society and have the potential to mislead decision-making processes in areas like health care, sports, crime investigation, and so on. In addition, altered images can be used to propagate misleading information which interferes with democratic processes (e.g., elections and government legislation) and crisis situations (e.g., pandemics and natural disasters). Therefore, there is a pressing need for effective methods for the detection and identification of forgeries. Various techniques are currently employed for the identification and detection of these forgeries. Traditional techniques depend on handcrafted or shallow-learning features. In traditional techniques, selecting features from images can be a challenging task, as the researcher has to decide which features are important and which are not. Also, if the number of features to be extracted is quite large, feature extraction using these techniques can become time-consuming and tedious. Deep learning networks have recently shown remarkable performance in extracting complicated statistical characteristics from large input size data, and these techniques efficiently learn underlying hierarchical representations. However, the deep learning networks for handling these forgeries are expensive in terms of the high number of parameters, storage, and computational cost. This research work presents Mask R-CNN with MobileNet, a lightweight model, to detect and identify copy move and image splicing forgeries. We have performed a comparative analysis of the proposed work with ResNet-101 on seven different standard datasets. Our lightweight model outperforms on COVERAGE and MICCF2000 datasets for copy move and on COLUMBIA dataset for image splicing. This research work also provides a forged percentage score for a region in an image.
River Segmentation of Remote Sensing Images Based on Composite Attention Network
Authors: Fan Zhiyong , Hou Jianmin , Zang Qiang , Chen Yunjie , Yan Fei
Published: January 2022

River segmentation of remote sensing images is of important research significance and application value for environmental monitoring, disaster warning, and agricultural planning in an area. In this study, we propose a river segmentation model in remote sensing images based on composite attention network to solve the problems of abundant river details in images and the interference of non‐river information including bridges, shadows, and roads. To improve the segmentation efficiency, a composite attention mechanism is firstly introduced in the central region of the network to obtain the global feature dependence of river information. Next, in this study, we dynamically combine binary cross‐entropy loss that is designed for pixel‐wise segmentation and the Dice coefficient loss that measures the similarity of two segmentation objects into a weighted one to optimize the training process of the proposed segmentation network. The experimental results show that compared with other semantic segmentation networks, the evaluation indexes of the proposed method are higher than those of others, and the river segmentation effect of CoANet model is significantly improved. This method can segment rivers in remote sensing images more accurately and coherently, which can meet the needs of subsequent research.
Traffic Risk Modelling and Analysis under Airport-Like Simulation Environment
Authors: Sheng Yanting , Feng Rui , Biancardo Salvatore Antonio
Published: January 2022

Traffic safety plays a crucial role in the development of autonomous vehicles which attracts significant attention in the community. It is a challenge task to ensure autonomous vehicle safety under varied traffic environment interference, especially for airport-like closed-loop conditions. To that aim, we analyze autonomous vehicle safety at typical roadway conditions and traffic state constraints (e.g., car-following state at different speed distributions) by simulating the airport-like traffic conditions. The experimental results suggest that traffic collision risk is in a positive relationship with the speed difference and distance among adjacent vehicles. More specifically, the autonomous vehicle may collide with neighbors when the time to collision (TTC) indicator is lower than 4 s, and vice versa. The research findings can help both research community and practioners obtain additional information for improving traffic safety for autonomous vehicles.
Neutrophil Extracellular Traps Facilitate A549 Cell Invasion and Migration in a Macrophage‐Maintained Inflammatory Microenvironment
Authors: Zhang Lemeng , Yi Huifang , Chen Jianhua , Li Haitao , Luo Yongzhong , Cheng Tianli , Yang Hua , Jiang Zhou , Pan Changqie
Published: January 2022

Introduction. The biological functions of neutrophil extracellular traps (NETs) in tumorigenesis have drawn an increasing amount of attention. This study explored the relationship between NETs and the inflammatory microenvironment in lung cancer cell invasion and metastasis. Methods. NETs were quantified using myeloperoxidase (MPO–DNA) and immunofluorescence staining. Cytokine levels were measured using ELISA kits. THP‐1 and A549 cells were used for in vitro experiments. Transwell and Matrigel assays were used to assess the invasion and migration abilities of the cells. Results. Neutrophil infiltration and NET formation were observed in the lung cancer tissues. Compared with healthy controls, the level of MPO–DNA complexes in lung cancer patients increased remarkably and was positively correlated with peripheral blood neutrophil counts, smoking status, and poor prognosis. Increased circulating NET levels were also positively correlated with the levels of inflammatory cytokines, including IL‐1β, IL‐6, IL‐18, and TNF‐α. Neutrophils isolated from patients with lung cancer are more prone to NET release. NETs can promote the invasion and migration ability of THP‐1 and A549 cell in coculture systems, while pretreatment with NET inhibitors can effectively reduce NET‐induced invasion and metastasis. The ability of NETs to promote invasion and metastasis is partly dependent on macrophages. Conclusion. Taken together, our study demonstrated that NETs facilitate A549 cell invasion and migration in a macrophage‐maintained inflammatory microenvironment.
Optimization of the Coupling Coefficient of the Inductive Link for Wireless Power Transfer to Biomedical Implants
Authors: Bao Jiarui , Hu Shuyan , Xie Zibin , Hu Guangxi , Lu Ye , Zheng Lirong
Published: January 2022

This work focuses on the optimization of coupling coefficient (k) of the inductive link for the wireless power transfer (WPT) system to be used in implantable medical devices (IMDs) of centimeter size. The analytic expression of k is presented. Simulations are conducted by using the high-frequency structure simulator (HFSS). Analytic results are verified with simulations. The receiving (Rx) coil is implanted in the body and set as a circular coil with a radius of 5 millimeters for reducing the risk of tissue inflammation. The inductive link under misalignment scenarios is optimized to improve k. When the distance between the transmitting (Tx) and Rx coils is fixed at 20 mm, it is found that, to maximize k, the Tx coil in a planar spiral configuration with an average radius of 20 mm is preferred, and the Rx coil in a solenoid configuration with a wire pitch of 0.7 mm is recommended. Based on these optimization results, an inductive link WPT system is proposed; the coupling coefficient k, the power transfer efficiency (PTE), and the maximum power delivered to the load (MPDL) of the system are obtained with both simulation and experiment. Different media of air, muscle, and bone separating the Tx and Rx coils are tested. For the muscle (bone) medium, PTE is 44.14% (43.07%) and MPDL is 145.38 mW (128.13 mW), respectively.
Hydrothermal Carbonization of Waste Sugarcane Bagasse for the Effective Removal of Emerging Contaminants from Aqueous Solution
Authors: Prasannamedha G. , Kumar P. Senthil
Published: January 2022

Porous carbon spheres were fabricated from sugarcane bagasse using a sustainable hydrothermal carbonization process followed by alkali impregnation inert atmosphere activation. Developed spheres were technically analysed for their chemical science, structural morphology, texture, porosity with respect to size distribution, and thermal degradation. Spheres are functionally enriched with oxygenated groups showing amorphous nature portraying as a smooth surface. After activation, intensity of functional groups is reduced due to reduction reaction by KOH thereby yielding highly rich porous carbon. The active surface area developed on spheres is 111 m2 g-1 holding pores that are mesoporous in nature. Resistance to thermal exposure using TGA showed that decomposition of hemicelluloses followed by cellulose yielded aromatized carbon-rich skeleton through thermal degradation of carboxyl and hydroxyl groups. Developed carbon was found to be effective in removing Ciprofloxacin Hydrochloride from water with maximum adsorption capacity of 110.008 mg g-1. Mechanistic removal followed pseudo-second-order kinetics along with Freundlich mode of adsorption. The presence of carboxylic and hydroxyl groups in porous carbon favoured elimination of CPF from water. The development of HTC-derived carbon helped conserving the energy thereby reducing the cost requirement.
Identification of DNA Repair-Related Genes Predicting Clinical Outcome for Thyroid Cancer
Authors: Zhang Ai-ying , Li Wei , Zhou Hai-yan , Chen Jing , Zhang Li-bin
Published: January 2022

Recent studies have demonstrated the utility and superiority of DNA repair-related genes as novel biomarkers for cancer diagnosis, prognosis, and therapy. Here, we aimed to screen the potential survival-related DNA repair-related genes in thyroid cancer (TC). TCGA datasets were utilized to analyze the differentially expressed DNA repair-related genes between TC and nontumor tissues. The K–M approach and univariate analysis were employed to screen survival-related genes. RT-PCR was employed to examine the expression of DNA repair-related genes in TC samples and matched noncancer samples. CCK-8 analyses were used to determine cellular proliferation. Herein, our team discovered that the expression of four DNA repair-related genes was remarkably upregulated in TC samples in contrast to noncancer samples. Survival assays identified 14 DNA repair-related genes. In our cohort, we observed that the expression of TAF13 and DCTN4 was distinctly elevated in TC specimens in contrast to nontumor specimens. Moreover, knockdown of TAF13 and DCTN4 was observed to inhibit the TC cellular proliferation. Overall, the upregulation of TAF13 and DCTN4 is related to decreased overall survival in TC patients. Therefore, the assessment of TAF13 and DCTN4 expression may be useful for predicting prognosis in these patients.
Numerical Modeling the Flood and Pollutant Transport Processes in Residential Areas with Different Land Use Types
Authors: Fang Shulin , Ji Yongpeng , Zhang Mingliang
Published: January 2022

Large-scale flooding causes widespread disaster, and harmful pollutant concentration in water following flood affects public safety and the environment. In this study, a numerical model for solving the 2D shallow water equations and the solute transport equation is proposed to simulate overland flood and pollutant transport caused by floods. The present model is verified by comparing the predictions with the analytical solutions and simulation results; sufficiently high computational accuracy is achieved. The model is also used to simulate flood inundation and pollution spread in the area of Hun and Taizi Lane (HTL) in China due to river dike breaches; the results show that the coupling model has excellent performance for simulating the flooding process and the temporal and spatial distribution of pollutants in urban or rural areas. We use remote sensing techniques to acquire the land coverage in the area of HTL based on Landsat TM satellites. The impacts of changed land use on mitigation of flooding waves and pollutant spread are investigated; the results indicate that the land cover changes have an obvious influence on the evolution process of flood waves and pollutant transport in the study areas, where the transport of pollutants is very dynamic during flood inundation in HTL area. Furthermore, the motion of pollutants considering anisotropic diffusion is more reasonable than that due to isotropic dispersion in simulating pollutant transport associated with the flood in urban or farmland environments.
COVID-19 Induced Brief Psychotic Disorder: A Case Report and Review of Literature
Authors: Bakre Sulaimon , Chugh Kritika , Oke Oluwaseun , Kablinger Anita
Published: January 2022

The COVID-19 pandemic has significantly impacted people around the world, with asymptomatic infection to severe diseases and death. There is an increasing incidence of mental health problems in patients diagnosed with COVID-19. There are some studies that discuss possible mechanisms responsible for psychotic disorders due to coronavirus as well as risk factors for developing psychosis in patients infected with the virus. We report the case and a review of the literature in a 29-year-old female with no past psychiatric history who was diagnosed with a brief psychotic disorder following infection with COVID-19.
Effects of Out-of-Hospital Continuous Nursing on Postoperative Breast Cancer Patients by Medical Big Data
Authors: He Peijuan , Zhang Bing , Shen Songna
Published: January 2022

This study aimed to explore the application value of the intelligent medical communication system based on the Apriori algorithm and cloud follow-up platform in out-of-hospital continuous nursing of breast cancer patients. In this study, the Apriori algorithm is optimized by Amazon Web Services (AWS) and graphics processing unit (GPU) to improve its data mining speed. At the same time, a cloud follow-up platform-based intelligent mobile medical communication system is established, which includes the log-in, my workstation, patient records, follow-up center, satisfaction management, propaganda and education center, SMS platform, and appointment management module. The subjects are divided into the control group (routine telephone follow-up, 163) and the intervention group (continuous nursing intervention, 216) according to different nursing methods. The cloud follow-up platform-based intelligent medical communication system is used to analyze patients’ compliance, quality of life before and after nursing, function limitation of affected limb, and nursing satisfaction under different nursing methods. The running time of Apriori algorithm is proportional to the data amount and inversely proportional to the number of nodes in the cluster. Compared with the control group, there are statistical differences in the proportion of complete compliance data, the proportion of poor compliance data, and the proportion of total compliance in the intervention group (

P
<
0.05

). After the intervention, the scores of the quality of life in the two groups are statistically different from those before treatment (

P
<
0.05

), and the scores of the quality of life in the intervention group were higher than those in the control group (

P
<
0.05

). The proportion of patients with limited and severely limited functional activity of the affected limb in the intervention group is significantly lower than that in the control group (

P
<
0.05

). The satisfaction rate of postoperative nursing in the intervention group is significantly higher than that in the control group (

P
<
0.001

), and the proportion of basically satisfied and dissatisfied patients in the control group was higher than that in the intervention group (

P
<
0.05

).
Application of Artificial Intelligence in an Unsupervised Algorithm for Trajectory Segmentation Based on Multiple Motion Features
Authors: Xu Wenjin , Dong Shaokang
Published: January 2022

With the development of the wireless network, location-based services (e.g., the place of interest recommendation) play a crucial role in daily life. However, the data acquired is noisy, massive, it is difficult to mine it by artificial intelligence algorithm. One of the fundamental problems of trajectory knowledge discovery is trajectory segmentation. Reasonable segmentation can reduce computing resources and improvement of storage effectiveness. In this work, we propose an unsupervised algorithm for trajectory segmentation based on multiple motion features (TS-MF). The proposed algorithm consists of two steps: segmentation and mergence. The segmentation part uses the Pearson coefficient to measure the similarity of adjacent trajectory points and extract the segmentation points from a global perspective. The merging part optimizes the minimum description length (MDL) value by merging local sub-trajectories, which can avoid excessive segmentation and improve the accuracy of trajectory segmentation. To demonstrate the effectiveness of the proposed algorithm, experiments are conducted on two real datasets. Evaluations of the algorithm’s performance in comparison with the state-of-the-art indicate the proposed method achieves the highest harmonic average of purity and coverage.
Conventional Medicinal Uses, Phytoconstituents, and Biological Activities of Euphorbia officinarum L.: A Systematic Review
Authors: Chamkhi Imane , Hnini Mohamed , Aurag Jamal
Published: January 2022

The Moroccan endemic plant Euphorbia officinarum is a traditional medicinal plant, known locally as “Daghmus.” Plants in the genus Euphorbia are well known for the chemical diversity of their diterpenoids and isoprenoid constituents, which perform many activities such as cytotoxic, antimicrobial, and anti-inflammatory activities, as well as different biological properties, that cannot be overlooked. The effect of bioactive compounds (antiviral, antidiabetic, anticancer, and antioxidant). Euphorbia officinarum is an important conventional medicine for the treatment of various conditions, including skin and ophthalmological diseases. It is also used against human pathogens (intestinal parasites). E. officinarum latex is the major part of the plant used for conventional medicine and synthesizing new bioactive compounds. The characterization and isolation of its components are necessary to exploiting and enhancing its therapeutic potential. However, to the best of our knowledge, no review is available to date. In order to have and define a research question, we adopt a strategy by considering the items of the PRISMA checklist. Therefore, this review aims to cover E. officinarum taxonomy, botanical description, distribution, conventional uses, and phytochemical compounds of this plant, including the biological activities of compounds isolated and of these semisynthesized compounds. This article provides a foundation for any further studies from this plant.
Association of lncRNA PVT1 Gene Polymorphisms with the Risk of Essential Hypertension in Chinese Population
Authors: Li Rong , Yu Xia , Chen Yang , Xiao Mulun , Zuo Meiling , Xie Yuanlin , Yang Zhousheng , Kuang Dabin
Published: January 2022

Vascular dysfunction and hyperlipidemia are essential risk factors contributing to essential hypertension (EH). The plasmacytoma variant translocation 1 (PVT1) is involved in modulating angiogenesis in tumor tissues and plays an important role in fat differentiation in the progress of obesity. Therefore, we selected two tagSNPs of PVT1 (rs10956390 and rs80177647) to investigate whether they are contributing to the risk of hypertension in Chinese patients. In total, 524 adult patients with EH and 439 matched healthy controls were enrolled for two central of China. Results. PVT1 rs10956390 and rs80177647 polymorphisms were genotyped by using TaqMan assay. PVT1 rs10956390 TT genotype was associated with a decreased risk of EH (OR = 0.561, 95% CI = 0.372‐0.846, P = 0.006), while rs80177647 TA genotype was associated with an increased risk (OR = 2.236, 95% CI = 1.515‐3.301, P < 0.001). Rs10956390 T allele was associated with lower triglyceride levels in the plasma both from healthy and EH donors. What is more, there is an association between rs10956390 polymorphism and HDL‐C level, as well as LDL‐C. Conclusion. PVT1 rs10956390 and rs80177647 polymorphisms may contribute to the risk of EH in Chinese population by regulating blood lipid levels.
Propuesta de mejoramiento del Impuesto a las personas en Chile
Authors: Borges Quintanilla Humberto A. , Valenzuela Nelson
Published: January 2022

Este articulo analiza los efectos redistributivos de los impuestos en Chile y plantea que el Impuesto Global Complementario (IGC) podría recaudar más de las regiones con mayores ingresos. Se propone aumentar el IGC, principalmente en el grupo de contribuyentes de mayores ingresos que fue beneficiado con la política de disminución de impuestos aplicada en 2014.
Entre Panamá, Pandora y otros Asteroides
Authors: Leyton Guerrero Eduardo
Published: January 2022

En términos astronómicos, la distancia que separa Panamá (Tierra) del planeta Pandora, de la película Avatar, es de 6 años luz; algo así como 5,676 1013 klms. Sin embargo, desde la perspectiva de los comprometedores documentos generados por la International Consortium of Investigative Journalists (ICIJ), conocidos como Panamá Papers el 2015 y Pandora Papers liberados el pasado 3 de octubre del 2021, en términos de contenidos, compromisos, acuerdos, responsabilidades, intenciones, principios y valores consignados en los mismos; parecieran ser que, ambos lugares idílicos y paradisiacos, efectivamente son limítrofes.
Dasatinib-Induced Colitis with Rectal Sparing in a Patient with Chronic Myeloid Leukemia (Chronic Phase) on Dasatinib as an Upfront Therapy: Case Report
Authors: Maat Zakaria , Mushtaq Kamran , Yassin Mohamed A.
Published: January 2022

Dasatinib is a BCR-ABL tyrosine kinase inhibitor which was approved in 2006 for the treatment of adults diagnosed with Philadelphia chromosome-positive (Ph+) chronic myeloid leukemia (CML) in chronic phase (CP) and accelerated (myeloid or lymphoid blast) phase and CML with resistance or intolerance to prior therapy including imatinib and in adults with Ph+ acute lymphoblastic leukemia. Common adverse reactions (>15%) in patients diagnosed with CP-CML include myelosuppression, fluid retention, and diarrhea. We report a 34-year-old Filipino female patient who received dasatinib as upfront therapy for the treatment of CP-CML who experienced chronic diarrhea for 2 months, which progressed to colitis.
Pneumatosis Intestinalis following Radiation Esophagitis during Chemoradiotherapy for Lung Cancer: A Case Report
Authors: Ito Noriaki , Masuda Takeshi , Yamaguchi Kakuhiro , Sakamoto Shinjiro , Horimasu Yasushi , Nakashima Taku , Miyamoto Shintaro , Iwamoto Hiroshi , Fujitaka Kazunori , Hamada Hironobu , Hattori Noboru
Published: January 2022

Pneumatosis intestinalis (PI) is a rare disease that forms emphysema lesions under the mucosa and serosa of the gastrointestinal tract. We present the first case of PI following radiation-induced esophagitis during chemoradiotherapy (CRT) for lung cancer. A 74-year-old man with severe chronic obstructive pulmonary disease (COPD) was treated with CRT for lung cancer. During the treatment, he presented with vomiting and abdominal distention. CT showed pneumatosis from the esophagus to the small intestine. Severe radiation-induced esophagitis was observed, and gastrointestinal endoscopy revealed a circumferential esophageal ulcer. From these observations, this case was diagnosed as PI following severe esophagitis. A nasogastric tube was inserted, and conservative treatment with fasting, fluid replacement, and antibiotic was performed. Four days after the onset of PI, CT showed marked improvement of the pneumatosis. When CRT is performed for lung cancer patients, we should not only consider esophagitis but also PI. The presence of COPD may be considered a specific factor for the development of severe esophagitis and the consequent PI in this case.
Validation of Fenoterol to Study β2-Adrenoceptor Function in the Rat Urinary Bladder
Authors: Erdogan Betül Rabia , Yesilyurt Zeynep Elif , Arioglu-Inan Ebru , Michel Martin Christian
Published: January 2022

Fenoterol is a β2-adrenoceptor (AR)-selective agonist that is commonly used to investigate relaxation responses mediated by β2-AR in smooth muscle preparations. Some data have questioned this because fenoterol had low potency in the rat urinary bladder when a muscarinic agonist was used as a pre-contraction agent and because some investigators proposed that fenoterol may act in part via β3-AR. We designed the present study to investigate whether fenoterol is a proper pharmacological tool to study β2-AR-mediated relaxation responses in the rat urinary bladder. Firstly, we have compared the effect of pre-contraction agents on fenoterol potency and found that fenoterol potency was about 1.5 log units greater against KCl than carbachol (pEC50 7.19 ± 0.66 and 5.62 ± 1.09 of KCl and of carbachol, respectively). To test the selectivity of fenoterol, we have determined the effects of the β2-AR antagonist ICI 118,551 and the β3-AR antagonist L 748,337 on relaxation responses to fenoterol. While 300 nM L 748,337 had little effect on the potency of fenoterol (pEC50 6.56 ± 0.25 and 6.33 ± 0.61 in the absence and presence of L 748,337, respectively), the relaxation curve for fenoterol was right-shifted in the presence 300 nM ICI 118,551 (pEC50 5.03 ± 0.18). Thus, we conclude that fenoterol is a proper pharmacological tool to assess β2-AR-mediated responses in the rat urinary bladder and most likely in other smooth-muscle preparations containing multiple subtypes of the β-AR.
Metastatic Prostate Cancer: Treatment Options
Authors: Achard Vérane , Putora Paul Martin , Omlin Aurelius , Zilli Thomas , Fischer Stefanie
Published: January 2022

Background: Metastatic prostate cancer (PCa) is associated with considerable diminished overall survival (OS). Standard treatment for metastatic PCa has long been androgen deprivation therapy alone, with patients initially responding to this treatment and then progressing to a castration-resistant phase. Summary: The advent of novel therapeutic agents has changed this paradigm, with high-level evidence that upfront combination therapy with either docetaxel or new hormonal agents results in improved OS for patients with metastatic hormone-sensitive PCa. In the absence of a comprehensive clinical trial investigating the comparative efficacy and safety of all agents, clinicians are responsible for choosing the most appropriate therapy in close coordination with patients. Furthermore, the same therapeutic agents are also efficient in the castration-resistant phase, leading to the issue of the best therapeutic sequence. Finally, along with systemic therapy and molecular imaging advancements, radiotherapy was investigated in the oligometastatic setting, whether it is to treat the primary tumour or metastases. Key Messages: In this complex landscape, where providers have multiple effective therapeutic options to treat metastatic PCa patients, priority must be given to determine which treatment combination and sequence is best suited to a particular patient, given his comorbidities and preferences.
Charlson Comorbidity Index: A Critical Review of Clinimetric Properties
Authors: Charlson Mary E. , Carrozzino Danilo , Guidi Jenny , Patierno Chiara
Published: January 2022

The present critical review was conducted to evaluate the clinimetric properties of the Charlson Comorbidity Index (CCI), an assessment tool designed specifically to predict long-term mortality, with regard to its reliability, concurrent validity, sensitivity, incremental and predictive validity. The original version of the CCI has been adapted for use with different sources of data, ICD-9 and ICD-10 codes. The inter-rater reliability of the CCI was found to be excellent, with extremely high agreement between self-report and medical charts. The CCI has also been shown either to have concurrent validity with a number of other prognostic scales or to result in concordant predictions. Importantly, the clinimetric sensitivity of the CCI has been demonstrated in a variety of medical conditions, with stepwise increases in the CCI associated with stepwise increases in mortality. The CCI is also characterized by the clinimetric property of incremental validity, whereby adding the CCI to other measures increases the overall predictive accuracy. It has been shown to predict long-term mortality in different clinical populations, including medical, surgical, intensive care unit (ICU), trauma, and cancer patients. It may also predict in-hospital mortality, although in some instances, such as ICU or trauma patients, the CCI did not perform as well as other instruments designed specifically for that purpose. The CCI thus appears to be clinically useful not only to provide a valid assessment of the patient’s unique clinical situation, but also to demarcate major diagnostic and prognostic differences among subgroups of patients sharing the same medical diagnosis.