bluuebunny/crossref_metadata_2025 huggingface dataset:
Design of Multichannel Multirate Signal Acquisition System Based on FPGA
Authors: Wang Keming , Wu Long , Liu Wei
Published: May 2022

With the continuous advancement of science and technology, the fields of national defense, astronomy, industry, agriculture, and so on often require real-time acquisition of voltage, current, temperature, pressure, flow, and other signals, and the real-time requirements for signal acquisition are getting higher and higher. The traditional temperature acquisition method is to use the single chip or DSP as the control core to design the temperature monitoring system. However, this method has certain defects and cannot meet many high-demand signal acquisition occasions. On the one hand, most functions of this system are realized by software, and the operation of software will occupy part of the system sampling time, thus reducing the system sampling rate; on the other hand, the logic of the system to complex peripheral circuits cannot be well controlled. And Field Programmable Gate Array (FPGA) has characteristics such as parallel processing, controllability, and processing speed; therefore, the signal acquisition system with FPGA as the control core can realize high-speed signal collection. This paper studies the signal acquisition based on FPGA. In the signal acquisition system, FPGA is the control core of the whole system, and the relevant function modules of the control system complete the signal acquisition task. The acquisition control module is mainly to control the channel selection switch and the A/D converter to work, that is, to generate the logic control signal of multichannel selection and the control sequence of A/D conversion, so as to complete the acquisition and control of the multichannel analog input signal. The FPGA-based signal acquisition control system has the characteristics of short development cycle, flexible design, low cost, and high reliability. FPGA is an ideal architecture for signal acquisition, and the FPGA-based signal acquisition technology has very broad application prospects.
Investigation on Tensile Behaviour of Different Weld Joints through Taguchi Approach
Authors: Kamal Shoaib , Parthiban V. , Puthilibai G. , Thirumal Azhagan M. , Kamal Neel , Senthil T. S. , Yishak Simon
Published: May 2022

Friction stir welding is a dependable method of joining metals and other materials. Relatively joint configuration-specific welding process parameters have not yet been tuned. This work is concerned with the Taguchi orthogonal arrays to perform an analysis of variance. In this study, FSW joint configurations of AA6262-T6 Al alloy, such as butt, lap, and T joints, were studied for optimization. An orthogonal array of welds was selected using the Taguchi method. After the welds were constructed, the ultimate tensile strength of each joint was examined for statistical optimization. The lack of parameter optimization studies for butt, lap, and T joints prompted this research to fill the void. As a result, each joint arrangement must be optimised for mechanical properties and a set of parameters must be developed.
Establishment and Analysis of a Combined Diagnostic Model of Liver Cancer with Random Forest and Artificial Neural Network
Authors: Yu Runzhi , Cao Ziyi , Huang Yiqin , Zhang Xuechun , Chen Jie
Published: May 2022

The incidence of liver cancer (hepatocellular carcinoma; HCC) is rising and with poor clinical outcome expected, a more accurate judgment of tumor tissues and adjacent nontumor tissues is necessary. The aim of this study was to construct a diagnostic model based on random forest (RF) and artificial neural network (ANN). It can be used to aid in the identification of diseased tissue such as cancerous tissue, for HCC clinical diagnosis and surgical guidance. GSE36376 and GSE121248 from Gene Expression Omnibus (GEO) were used as training sets in this investigation. R package “limma” and WGCNA were used to filter the training set for statistically significant

p
<
0.05

differential genes. To better understand the biological function and characteristics, R software was used to perform GO and KEGG enrichment analyses. To pick out and further understand the key genes, we performed PPI analysis and random forest tree analysis. Next, we built the ANN to predict training sets and validation set (GSE84402), and ROC curve was plotted to calculate area under curve (AUC). Then immune cell infiltration indicated difference of immune cell subsets between control and case groups. Finally, the survival analysis of key genes was also carried out based on data in TCGA database. Based on the expression of these 9 genes, we built the artificial neural network (ANN) and the accuracy of the final models was assessed with an ROC curve. The areas under the ROC curve were 0.984 (95% CI 0.972–0.993) in training sets. Its predictive capability was further assessed using the validation set. And the areas under the ROC curve were 0.929 (95% CI 0.786–1.000). In summary, this method effectively classifies hepatocellular carcinoma tissues and the corresponding noncancerous tissues and provides reasonable new ideas for the early diagnosis of liver cancer in the future.
Dental Undergraduates and Interns’ Awareness, Attitudes, and Perception of Radiological Protection
Authors: Abuelhia Elfatih , Alghamdi Ali , Tajaldeen Abdulrahman , Mabrouk Osama , Bakheet Adel , Alsaleem Haney , Alaraik Wejdan , MSmar Amir , Quwaihes Faisal , Alshahrani Khaled , Hlosh Yahya , Alghamdi Salem , Aljondi Rowa
Published: May 2022

Medical ionizing radiation is widely used in hospitals, in particular dental clinics, and in medical research to facilitate the diagnosis and treatment of patients. The awareness, attitude, and perception of ionizing radiation exposure among dental undergraduate students and interns in radiological investigations and dental care clinics were investigated. A cross-sectional study was conducted; 17 questions were designed online using the software “QuestionPro,” which was licensed to the University of Imam Abdulrahman Bin Faisal. Participants included senior medical dental students from Imam Abdulrahman Bin Faisal University in their third to fifth years, as well as interns from King Fahad University Hospital and private dental care clinics. A total of 855 participants viewed, 360 started the questionnaire, and 258 (72%) completed it online. Overall, knowledge was lacking; 32% of respondents incorrectly believed that magnetic resonance imaging and ultrasound used ionizing radiation, while 38% were unsure. Dental X-rays were deemed harmful by 40% (n = 104) of respondents. According to 33% (n = 85) of participants, there is no radiation scatter during an X-ray or CT scan, while 30% (n = 76) are unsure. Respondents (44%; n = 104) were unaware of the radiation dose from a chest radiograph and (45%; n = 116) overestimated the radiation dose. The effects of ionizing radiation on healthy tissue are known to more than half of the participants (54%). According to 39% of respondents, digital radiography exposes them to less radiation than traditional radiography. In terms of radiation protection and hazard, 46% said personal monitoring badges should be always worn and 58% (n = 150) said lead aprons should be used on a regular basis. 63% of the subjects had received radiation protection education, such as formal lectures, tutorials, or workshops, while 37% (n = 95) had not. 53% of the respondents were not aware of the international recommendations from the International Commission on Radiological Protection. When asked if they would follow radiation protection protocols if they opened a private dental clinical practice in the future, 50% (n = 129) said they would.
High-Precision Motion Compensation for LiDAR Based on LiDAR Odometry
Authors: Qin Peilin , Zhang Chuanwei , Ma Xiaowen , Shi Zhenghe
Published: May 2022

LiDAR plays a pivotal role in the field of unmanned driving, but in actual use, it is often accompanied by errors caused by point cloud distortion, which affects the accuracy of various downstream tasks. In this paper, we first describe the feature of point cloud and propose a new feature point selection method Soft-NMS-Select; this method can obtain uniform feature point distribution and effectively improve the result of subsequent point cloud registration. Then, the point cloud registration is completed through the screened feature points, and the odometry information is obtained. For the motion distortion generated in a sweep, the prior information of the LiDAR’s own motion is obtained by using two linear interpolations, thereby improving the effect of motion compensation. Finally, for the distortion caused by the motion of objects in the scene, Euclidean clustering is used to obtain the position and normal vector of the center point of the point cloud cluster, and the motion pose of the object is calculated according to the offset between adjacent sweeps and eliminated distortion. Essentially, our method is a general point cloud compensation method that is applicable to all uses of LiDAR. This paper inserts this method into three SLAM algorithms to illustrate the effectiveness of the method proposed in this paper. The experimental results show that this method can significantly reduce the APE of the original SLAM algorithm and improve the mapping result.
Maximum Principle for Mean-Field FBSDEs with Mixed Initial-Terminal Conditions
Authors: Li Ruijing
Published: May 2022

The present paper concerns with optimal control problems allowing for time inconsistent utility functions of mean-field FBSDEs with mixed initial-terminal conditions. Moreover, the control variable enters the diffusion coefficient, and the control domain is with nonconvexity. Via extended Ekeland’s variational principle as well as the reduction method, a general stochastic maximum principle is established in the framework of mean-field theory. Finally, a linear-quadratic example is worked out to illustrate the application of the results.
Cultural Confidence on “Art & Engineering” Construction of Product Design under “New Liberal Arts”
Authors: Xu Lijun , Gao Jun , Chen Lu , Liang Guodong , Feng Hailong
Published: May 2022

A master’s degree program in “new liberal arts” is a great opportunity to strengthen cooperation between art colleges and universities, to promote the construction of product design and digital molding majors, and to promote teaching and research on the “integration” of the theoretical foundations of engineering intelligent manufacturing. To take advantage of cooperative universities’ advantageous disciplines and professional platforms, we should construct new art and emerging interdisciplinary majors, as well as promote the construction and exploration of joint training of doctors and masters in relevant disciplines in the interdisciplinary direction of art and engineering. The foregoing approaches are intended to create a new “art and engineering” model for the establishment of a product design speciality at our university. In order to meet the requirements of “Art & Engineering” advocated by the national new engineering construction, art disciplines have their own inherent rules and characteristics. We should actively create disciplinary and professional characteristics, help universities cooperate with each other in high-quality development, and share and win together, in order to continuously achieve new academic results.
Free Vascularized Fibula Salvage of Failed CPH in Pediatric Sarcoma Patients
Authors: Pires Giovanna , Moss Whitney D. , Luo Jessica , Zhang Ruyan , Jones Kevin B , Kwok Alvin C , Agarwal Jayant P
Published: May 2022

Background. Due to extended life expectancy and recent improvements in surgical techniques, limb salvage has replaced amputation as the gold standard and is now performed in 90–95% of upper extremity malignancies. However, many of these salvage procedures are associated with significant postsurgical complications. In particular, the clavicula pro humero (CPH) procedure is associated with high rates of nonunion. We present our experience with upper extremity salvage using the free vascularized fibular flap (VFF) after failure or nonunion of the original CPH procedure in the pediatric population. Methods. Five patients under the age of 18 diagnosed with upper extremity sarcoma who underwent tumor resection with immediate CPH reconstruction complicated with nonunion, and subsequent revision with free VFF were included. Data on patient demographics, oncologic characteristics, surgical procedures, intraoperative details, postoperative complications, and time to graft union were recorded. Results. Five patients (average age = 8.4 years; range = 5–10 years at surgery date) underwent secondary limb salvage procedure with free VFF reconstruction following failed CPH reconstruction for proximal humeral osteosarcoma (n = 4) or Ewing sarcoma (n = 1). The mean follow-up was 3.7 years. Complications occurred in five patients (100%), with three patients requiring reoperation (60%). Four patients achieved graft union (average union time = 3.7 months) and successful limb reconstruction. Four patients were alive with no local recurrence of the disease. One patient did not achieve union and was lost to follow-up. Conclusion. Primary bone tumors in the pediatric population require wide surgical resection, and reconstruction often has high complication rates that can warrant further procedures. A free VFF is a viable option for upper extremity salvage after previously failed reconstructions because it provides vascularized tissue to a scarred tissue bed and allows for the replacement or augmentation of large bony defects.
Mechanical Degradation of Q345 Weathering Steel and Q345 Carbon Steel under Acid Corrosion
Authors: Yang Fan , Yuan Miao M. , Qiao Wen J. , Li Na N. , Du Bin
Published: May 2022

In this work, a mechanical degradation of weathering steel and carbon steel caused by strong acid corrosion has been studied in order to clarify the threat of industrial acid vehicle leakage to steel structure bridge. Twenty-seven specimens of Q345 weathering steel plates and Q345 carbon steel plates were immersed in a 36% hydrochloric acid solution at room temperature, with the corrosion time being 0 h, 1 h, 2 h, 4 h, 8 h, 12 h, 24 h, 48 h, and 72 h, respectively. Subsequently, the obtained specimens were subjected to a uniaxial tensile test to determine the stress-strain curves. The surface morphology was studied by the noncontact surface topography instrument DSX500. By analyzing the degree of mechanical degradation, the constitutive models of test steels under strong acid corrosion were established. The analysis of results shows that the corrosion rate of carbon steel is higher than that of weathering steel. After 72 hours of corrosion, the mass loss rate of carbon steel and weathering steel was 4.77% and 4.30%, respectively. The maximum corrosion pit depth of carbon steel was 25.52 μm higher than that of weathering steel. The constitutive models were in good agreement with the test results, and the resistance to corrosion degradation and deformation of the weathering steel was higher compared to the carbon steel. The results can serve as a guideline for designing steel constructions of improved durability.
Study on Secondary Metabolites of Endophytic Fungus, Aspergillus fumigatus, from Crocus sativus L. Guided byUHPLC-HRMS/MS-Based Molecular Network
Authors: Jiang Yu , Wu Jing , Kawagishi Hirokazu , Jiang Chunxiao , Zhou Qi , Tong Zheren , Tong Yingpeng , Wang Ping
Published: May 2022

As a traditional Chinese medicine, Crocus sativus Linn has been used for a long time in China. However, the studies on secondary metabolites of its endophytic fungi were not fully sufficient. Thus, the endophytic fungus, Aspergillus fumigatus, collected from the lateral buds of C. sativus, was here investigated. An approach combining UHPLC-HRMS/MS (ultra-high performance liquid chromatography-high resolution mass spectrometry) with molecular network was carried out to construct a molecular network of crude EtOAc extract (CEE) of A. fumigatus, in which 32 chemical compounds were annotated. On the basis of analysis results, a total of 15 known natural compounds were isolated from CEE. Among them, compounds 11 and 12 were isolated for the first time from the genus Aspergillus. Moreover, CEE and compound 7 exhibited moderate inhibitory activity against Erwinia sp. with a MIC value of 100 μg/mL. This study provided a more convenient and rapid approach to investigating the crude extract with complex components of A. fumigatus, which is of great benefit to the further study and utilization of secondary metabolites of the genus Aspergillus.
Myostatin Levels and the Risk of Myopenia and Rheumatoid Cachexia in Women with Rheumatoid Arthritis
Authors: Gonzalez-Ponce Fabiola , Gamez-Nava Jorge Ivan , Gomez-Ramirez Eli Efrain , Ramirez-Villafaña Melissa , Jacobo-Cuevas Heriberto , Rodriguez-Jimenez Norma Alejandra , Olivas-Flores Eva Maria , Esparza-Guerrero Yussef , Martelli-García Alejandro , Santiago-Garcia Aline Priscilla , Nava-Valdivia Cesar Arturo , Martinez-Hernandez Alejandra , Gonzalez-Vazquez Sergio Antonio , Celis Alfredo , Cabrera-Pivaral Carlos Enrique , Totsuka-Sutto Sylvia , Cardona-Muñoz Ernesto German , Gonzalez-Lopez Laura
Published: May 2022

Background. Myostatin is a regulator of muscle size. To date, there have been no published studies focusing on the relation between myostin levels and myopenia in rheumatoid arthritis (RA). Objective. Evaluate the value of serum myostatin as a biomarker of cachexia and low skeletal muscle mass (LSMM) in RA patients, along with whether high serum myostatin is associated to these conditions after adjusting for potential confounders. Methods. This cross-sectional study included 161 female RA patients and 72 female controls. In the RA group, we assessed several potential risk factors for LSMM and rheumatoid cachexia. Dual-energy X-ray absorptiometry was used to quantify the skeletal muscle mass index (SMMI) (considering

LSMM
≤
5.5

 kg/m2) and the presence of rheumatoid cachexia (a fat-free mass

index
≤
10

percentile and fat mass

index
≥
25

percentile of the reference population). Serum myostatin concentrations were determined by ELISA. To identify a cut-off for high serum myostatin levels, we performed ROC curve analysis. Multivariable logistic regression analysis was used to identify the risk factors for LSMM and rheumatoid cachexia. The risk was expressed as odds ratios (ORs) and their 95% confidence intervals (95% CIs). Results. Compared to the controls, the RA group had a higher proportion of LSMM and exhibited high serum myostatin levels (

p
<
0.001

). ROC curve analysis showed that a myostatin

level
≥
17

 ng/mL was the most efficient cut-off for identifying rheumatoid cachexia (sensitivity: 53%, specificity: 71%) and LSMM (sensitivity: 43%, specificity: 77%). In the multivariable logistic regression, RA with high myostatin levels (≥17 ng/mL) was found to increase the risk of cachexia (

OR
=
2.79

, 95% CI: 1.24-6.29;

p
=
0.01

) and LSMM (

OR
=
3.04

, 95% CI: 1.17-7.89;

p
=
0.02

). Conclusions. High serum myostatin levels increase the risk of LSMM and rheumatoid cachexia. We propose that high myostatin levels are useful biomarkers for the identification of patients in risk of rheumatoid cachexia and myopenia.
Effects of Patellofemoral Pain Syndrome on Changes in Dynamic Postural Stability during Landing in Adult Women
Authors: Kim Chanki , Yeom Seunghyeok , Ahn Seji , Kang Nyeonju , Park Kiwon , Jeon Kyoungkyu
Published: May 2022

Background. This study investigated the effects of lower limb movements on dynamic postural stability (DPS) during drop landing in adult women with patellofemoral pain syndrome (PFPS). Methods. Thirty-eight adult women were recruited and divided into two groups, the PFPS group and the control group. The study participants performed a single-leg drop landing from a 30 cm box, and their lower limb movements and DPS were measured. Differences between groups were examined using independent sample

t

-tests. In addition, stepwise multiple linear regression was used to examine the kinematic parameters that contribute to the DPS. Results. The PFPS group had significantly lower hip flexion, internal rotation, knee flexion, ankle external rotation, pelvic oblique, tilt, rotation, and higher hip abduction, knee valgus, and ankle plantarflexion. In terms of DPS, the PFPS group had a significantly higher anteroposterior and a lower mediolateral than that of the control group. In the control group, regression analysis revealed a controlled anteroposterior using knee flexion, while the PFPS group controlled mediolateral through ankle plantarflexion. Conclusions. Patients with PFPS experienced more shock on their knee joint during landing than patients in the control group with greater anteroposterior instability and lower mediolateral instability.
Forskolin Stimulates Estrogen Receptor (ER) α Transcriptional Activity and Protects ER from Degradation by Distinct Mechanisms
Authors: Tsai Houng-Wei , Lin Vicky Y. , Shupnik Margaret A.
Published: May 2022

Estradiol action is mediated by estrogen receptors (ERs), a and ß. Estradiol binding initiates ER-mediated transcription and ER degradation, the latter of which occurs via the ubiquitin-proteasome pathway. Inhibition of proteasome activity prevents estradiol-induced ERα degradation and transactivation. In ER-positive GH3 cells (a rat pituitary prolactinoma cell line), forskolin, acting via protein kinase A (PKA), stimulates ERα transcriptional activity without causing degradation, and proteasome inhibition does not block forskolin-stimulated transcription. Forskolin also protects liganded ERα from degradation. In the current study, we first examined ERα and ERβ transcriptional activity in ER-negative HT22 cells and found that forskolin stimulated ERα-, but not ERβ-dependent transcription, through the ligand-binding domain (LBD). We also identified four mutations (L396R, D431Y, Y542F, and K534E/M548V) on the ERα LBD that selectively obliterated the response to forskolin. In GH3 cells, transfected ERα mutants and ERβ were protected from degradation by forskolin. Ubiquitination of ERα and ERβ was increased by forskolin or estradiol. ERα ubiquitination was diminished by a mutated ubiquitin (K48R) that prevents elongation of polyubiquitin chains for targeting the proteasome. Increased ERα ubiquitination was not affected by the deletion of the A/B domain but significantly diminished in the F domain deletion mutant. Our results indicate distinct and novel mechanisms for forskolin stimulation of ERα transcriptional activity and protection from ligand-induced degradation. It also suggests a unique mechanism by which forskolin increases unliganded and liganded ERα and ERβ ubiquitination but uncouples them from proteasome-mediated degradation regardless of their transcriptional responses to forskolin.
Association between Mutation in SMARCAD1 and Basan Syndrome with Cutaneous Squamous Cell Carcinoma
Authors: Xiong Ying , Chen Ting , Yu Jia , Zhou He , Lu Baozhen , Chen Lijie , Sun Liwei , Wang Can , Li Sujun , Wu Bo
Published: May 2022

Background. Basan syndrome is a rare autosomal-dominant ectodermal dysplasia with certain clinic-pathological features caused by mutations in the SMARCAD1 gene. Currently, no skin malignancy related to Basan syndrome has been reported. This study was aimed at identifying related gene mutations in a new Chinese pedigree with Basan syndrome and discovering the possible association between Basan syndrome and cutaneous squamous cell carcinoma (cSCC). Methods. We report a case of Basan syndrome from China with family history of cSCC. The pedigree contains 28 individuals. Among them, 12 members had Basan syndrome, while 4 affected members were diagnosed with cSCC in the 1st and 2nd generations. Whole exome sequencing (WES) and Sanger sequencing were performed for 7 available individuals. The specific gene mutation on pre-mRNA splicing was also analyzed using in vitro Minigene assay. In addition, sequencing data was analyzed with bioinformatics workflow, aiming to discover the gene associated with cSCC. Results. Gene sequencing results showed a heterozygous mutation, c.378+5G>A, in the SMARCAD1 gene in all tested individuals with Basan syndrome. Minigene result implicated the specific mutation may cause splicing variations by exon skipping occurring in the targeted exons. Conclusion. To the best of our knowledge, this is the first study reported Basan syndrome with family history of cSCC. Despite in this study we cannot draw any conclusion about the association between Basan syndrome and cSCC at the genetic level, this study encourages future works to substantiate this potential but important issue.
Art Research Based on Machine Learning and Artificial Intelligence
Authors: Qiang Ran Li , Guang Li Fa , Hua Sun Yan , Maia Darchia
Published: May 2022

In this paper, machine learning and artificial intelligence are applied to art research to improve the intelligence of art research. This study concludes that the Gaussian homomorphic filter has the best processing impact in the image homomorphic filtering stage by comparing the processing effects of Gaussian homomorphic filter, Butterworth homomorphic filter, and exponential filter. Moreover, this study uses median filtering to eliminate salt and pepper noise in images and designs and implements a rapid digitization system for art works based on three-dimensional reconstruction. In addition, in order to improve the time efficiency of the system and the digital quality of art works and optimize the SIFT feature matching speed, this study proposes a relative position-based SIFT feature fast matching algorithm. Finally, this study verifies the effectiveness of the method proposed in this study through experimental research. The results show that it has a certain effect on promoting the development of art research and the application of computer technology in the art industry.
Investigation on Efficient Removal of Fluoride from Ground Water Using Activated Carbon Adsorbents
Authors: Chukka Naga Dheeraj Kumar Reddy , Gomathi Nagajothi P. , Natrayan L. , Reddy Yeddula Bharath Simha , Veeman Dhinakaran , Patil Pravin P. , Thanappan Subash
Published: May 2022

Groundwater seems to be the most significant natural source of potable water for millions of individuals. Fluoride pollution in groundwater is a big problem in Tamil Nadu’s Dharmapuri area. According to a survey done in a school in the Dharmapuri area, dental and skeletal fluoroses afflict almost 75% of school kids. There is no proven or recommended cost-effective strategy for lowering fluoride levels in the home. This study proposes cost-effective and efficient natural treatment approaches for lowering fluoride levels. In this experiment, fluorides in groundwater are eliminated to a suitable extent utilizing natural adsorbents. Neem stem charcoal (activated carbon), neem leaves powder, dry coconut husk, coconut shell charcoal (activated carbon), and rice husk powder are natural adsorbents. The adsorbents were utilized at different concentrations until the best concentration was found. The ideal concentration removes the bulk of fluoride from groundwater and delivers adequate treatment. People could adopt this cost-effective procedure because just a few components are enough. As per the Bureau of Indian Standards, the concentration should not exceed 1.5 ppm, and it should not be lesser than 1 ppm; keeping this in mind, the neem stem charcoal which has higher efficiency in removing fluoride can be used in extensive environments, but in this selected place, it reduces the concentration even below 1 ppm, which relays below the standard level. As a result, adopting these procedures helps prevent dental and skeletal fluoroses, which is common among young people.
Multifeature Fusion Human Pose Tracking Algorithm Based on Motion Image Analysis
Authors: Si Lipeng , Liu Baolong
Published: May 2022

Human pose and motion detection is an important area of computer vision research, covering the interplay of different fields such as image processing, pattern recognition, and artificial intelligence. Due to the complexity of human motion, existing 3D recognition and pose detection methods based on low-quality depth images are not very accurate and reliable. Due to the time-sensitive nature of features, a single feature cannot adapt to the dynamic changes of the scene, so it is difficult for the target tracking algorithm based on a single feature to achieve robust tracking results. If multiple features are fused and applied in the tracking algorithm, the complementarity between different features can be used to better adapt to the scene changes and achieve robust tracking results. In order to solve the problem of human pose and human motion recognition in low-quality depth images, this paper uses the Kinect somatosensory camera to obtain 20 human skeleton joint points through the Kinect skeleton tracking technology. This paper studies the typical human posture and interactive action recognition technology in daily life. On the basis of understanding the characteristics of skeletal data, this paper proposes a distance feature and angle feature model combined with human body structure. Through the experimental results, it is found that the distance feature and the angle feature value are basically not affected by the distance change. When the subjects turned 45° to the left and 45° to the right, the distance characteristics changed, which was different from the characteristic data when the subjects turned around.
Vulnerability of Agrobiodiversity and Agroforestry Settings to Climate Change in Gedeo Zone, Ethiopia
Authors: Erenso Fikadu , Andemo Azene
Published: May 2022

The study was carried out at the Gedeo zone aiming to investigate the vulnerability of agrobiodiversity and agroforestry settings to climate change in the district. Thus, the study was focused on evaluating crop diversity under different crop management practices and its distribution at the household level among different wealth classes and land use land cover change impact on agrobiodiversity and agroecosystems areas. Therefore, crop survey both from the home garden and crop field, the last 30 years’ data from five meteorological stations located in the district and the past 30 years’ Landsat satellite images at a 10-year interval within the same season was used. A total of 65 crop plant species with eleven major use categories have been recorded in the studied home gardens and crop fields. The crop plant species collected from both the home garden and crop field account for 57% and 38%, while the rest 5% were from the adjacent field. The land use and land cover map of the study area indicate that the largest part of the study area (108548.01 hectares) was covered by agroforestry, whereas the smallest portion of the district, about 975.15, 6457.41 and 12501.27 hectares of the area, was covered by bare land, cropland, and grassland, respectively. The remaining 20537.73 hectares (13.8%) of the district were covered with settlements. Crop species diversity is higher almost in the entire study site. However, crop species compositions were significantly variable among these study sites. The climatic data results indicated a reduction in average rainfall pattern in most of the stations and an increase in temperature within the employed time range.
Application of BP Neural Networks in Garment Pattern Design System
Authors: Ma Shuo , Yan Xiaoyu
Published: May 2022

With the intensification of global market competition and the continuous development of the information technology, competition in the apparel market has become increasingly fierce. The key to whether China’s garment industry can maintain its advantage in the international market competition in the future lies in whether it can promote and realize the informatization of the garment industry or not. After all, under the context of increasingly developed information technologies and growing competition in the garment market, mass customization of garments has become a future trend in the garment industry. As custom-made clothing is more in line with consumers’ individual needs in terms of style, fabric, and size, the focus of development for clothing companies is increasingly on the grasp of the fit of clothing. However, with China’s large population and the wide variety of body types, traditional hand-made garments are time-consuming and cannot meet the differentiated needs of consumers in the modern market. The design of garment samples is an important part of the industrial production of garments and is highly dependent on the skills and experience of the operators. In other words, the level of technical expertise can determine the quality and shape of a garment product to a certain extent. As a result, in order to further improve the efficiency and quality of garment sample design and to reduce the dependence on operator skills and experience, this study proposes an intelligent garment paper sample design system based on BP neural networks. The system mainly utilizes the self-learning, self-organizing, and adaptive as well as nonlinear mapping functions of artificial neural networks to design clothing samples autonomously, thus improving the design efficiency. In the era of rapid development of information technology and artificial intelligence technology, the development of intelligent garment pattern design systems with independent intellectual property rights is of great significance in promoting the prosperity of the garment industry.
Prevalence, Intensity, and Risk Factors for Helminth Infections in Pigs in Menoua, Western Highlands of Cameroon, with Some Data on Protozoa
Authors: Kouam Marc K. , Ngueguim Fabrice D.
Published: May 2022

Helminthes affect satisfactory pig farming by causing poor growth rate and infertility. The objective of this study was to investigate the occurrence of helminthes in pig production, as well as factors influencing their prevalence in Menoua, Western Highlands of Cameroon. Thus, 597 fecal samples from 100 farms of three production types (farrower, grower, and farrow-to-finish) were collected together with data on farmer and management characteristics. Samples were qualitatively and quantitatively analyzed. Eggs of eight helminthes were identified: Hyostrongylus rubidus (81.10%, 50-550 epg), Strongyloides ransomi (34.5%, 50-150 epg), Trichostrongylus sp. (28.1%, 50-650 epg), Ascaris suum (11.6%, 50-200 epg), Metastrongylus sp. (10.4%, 50-250 epg), Oesophagostomum dentatum (5.7%, 50-150 epg), Trichuris suis (4.0%, 50-150 epg), and Macracanthorhynchus hirudinaceus (0.2%, 50-50 epg). The overall prevalence was 89.3% (533 out of 597). Single infestations were 30.2%, while mixed infestations were 59.1%. A. suum, S. ransomi, and strongyles (H. rubidus, Trichostrongylus sp., Metastrongylus sp., and O. dentatum) were found in almost all age groups but the prevalence of A. suum increased with the growing age to drop in older animals. H. rubidus was found in all farm types followed by S. ransomi in farrower and farrow-to-finish farms. The other parasites were present only in farrow-to-finish farms. Coccidia parasites were also found including Isospora suis (26.30%, 50-12500 oocysts per gram of feces (opg)) and Eimeria spp. (1.40%, 100-100 opg). The risk of infestation for some parasites was lower with increasing herd size, high education level of farmers, and in wooden piggeries and semipermanent structures. The infestation risk was higher for all the investigated parasites for pigs escaping the pens. The overall significance of these parasites on growth and reproduction of the naturally infested pigs deserve assessment. Necropsy studies to confirm the worm burden are needed. Risk factors were identified, thus paving the way to design successful helminth control in pig production enterprises.
Application of an Improved TF-IDF Method in Literary Text Classification
Authors: Xiang Lin
Published: May 2022

Literature is extremely important in the advancement of human civilization. Every day, many literary texts of various genres are produced, dating back to ancient times. An urgent concern for managers in the current literary activity is how to classify and save the expanding mass of literary text data for easy access by readers. In the realm of text classification, the TF-IDF algorithm is a widely used classification algorithm. However, there are significant issues with utilizing this approach, including a lack of distribution information inside categories, a lack of distribution information between categories, and an inability to adjust to skewed datasets. It is possible to improve classification accuracy by using the TF-IDF algorithm in this paper’s application situation by exploiting the association between feature words and the quantity of texts in which they appear, while ignoring the variation in feature word distribution across categories. With the purpose of classifying the literary texts in this study, this work proposes an improved IDF method for the problem of feature words appearing several times and having diverse meanings in different fields. The meanings of feature words in distinct domains are separated to increase the trust in the TF-IDF algorithm’s output. Using the improved TF-IDF method suggested in this research with the random forest (RF) classifier, the experimental results show that the classifier has a good classification impact, which can meet the actual work needs, based on comparative experiments on feature dimension selection, feature selection algorithm, feature weight algorithm, and classifier. It has a fair amount of historical significance.
Deep Learning‐Based Computed Tomography Perfusion Imaging to Evaluate the Effectiveness and Safety of Thrombolytic Therapy for Cerebral Infarct with Unknown Time of Onset
Authors: Hu Minlei , Chen Ning , Zhou Xuyou , Wu Yanping , Ma Chao
Published: May 2022

This study was aimed to discuss the effectiveness and safety of deep learning‐based computed tomography perfusion (CTP) imaging in the thrombolytic therapy for acute cerebral infarct with unknown time of onset. A total of 100 patients with acute cerebral infarct with unknown time of onset were selected as the research objects. All patients received thrombolytic therapy. According to different image processing methods, they were divided into the algorithm group (artificial intelligence algorithm‐based image processing group) and the control group (conventional method‐based image processing group). After that, the evaluations of effectiveness and safety of thrombolytic therapy for the patients with acute cerebral infarct in the two groups were compared. The research results demonstrated that artificial intelligence algorithm‐based CTP imaging showed significant diagnostic effects and the image quality in the algorithm group was remarkably higher than that in the control group (P < 0.05). Besides, the overall image quality of algorithm group was relatively higher. The differences in the National Institute of Health stroke scale (NIHSS) scores for the two groups indicated that the thrombolytic effect on the algorithm group was superior to that on the control group. Thrombolytic therapy for the algorithm group showed therapeutic effects on neurologic impairment. The symptomatic intracranial hemorrhage rate of the algorithm group within 24 hours was lower than the hemorrhage conversion rate of the control group, and the difference between the two groups was 14%. The data differences between the two groups showed statistical significance (P < 0.05). The results demonstrated that the safety of guided thrombolytic therapy for the algorithm group was higher than that in the control group. To sum up, deep learning‐based CTP images showed the clinical application values in the diagnosis of cerebral infarct.
Research on the Selection of Factors in a Traction Fault Elevator Based on PCA and a Rough Set
Authors: Jin Xinfeng , Li Chen , Li Dongyang , Zeng Junjie , Wang Qinye
Published: May 2022

To the problem of large subjectivity in existing index screening methods, this paper uses principal component analysis and the rough set method to select faulty factors in a traction fault elevator, eliminate the unrelated and unimportant indices, and then set up 4 main indices: rated parameter, running environment, manufacturing maintenance condition, and man-machine factor; and 10 two-grade fingers, including rated load, use unit, and manufacturing unit, which constitute a traction failure elevator factor index system, provide a new train of thought and method for the research and analysis of traction fault elevators.
Hormonal Fluctuations and Periodontal Status in Postmenopausal Women
Authors: Rafiei Mehrad , Salarisedigh Somayeh , Khalili Parvin , Jamali Zahra , Sardari Farimah
Published: May 2022

Introduction. While the short-term effects of hormonal events on gingival inflammation have been well described, their long-term effects on the periodontium have received less attention. Our investigation was aimed at evaluating the correlation between hormonal fluctuations and periodontal status in postmenopausal women from the profile of the Rafsanjan Cohort Study. Material and Methods. We used the data obtained from the profile of the Rafsanjan Cohort Study (RCS) as a part of the prospective epidemiological research studies in Iran (PERSIAN). The RCS includes 10,000 participants aged 35–70 years old. Among this population, the periodontal status data of 4143 women were available. Of these 4,143, the postmenopausal women were included in the study, and those who had a history of gingival treatment during the past 6 months were excluded from the study. Finally, 928 postmenopausal women were included in the present study. Periodontal status was assessed by measuring the clinical attachment loss, pocket depth, and bleeding on probing (BOP). Univariate and multivariate regression analyses were applied using three different models. Results. The results showed that 53.2% of postmenopausal women had periodontitis. There were significant differences between the participants with and without periodontitis in brushing frequency and educational status

P
<
0.05

. After adjusting for all potential confounders, no correlation was found between hormonal fluctuations and periodontal status. Conclusion. There was no correlation between hormonal fluctuations and periodontal status.
Predicting Role of Prestroke Glycemic Variability Estimated by Glycated Albumin for Reperfusion and Prognosis after Endovascular Treatment
Authors: Lee Sang-Hwa , Mo Hee Jung , Kim Yerim , Park So Young , Kim Yeo Jin , Lee Minwoo , Sohn Jong-Hee , Kim Chulho
Published: May 2022

Introduction: Glycated hemoglobin is widely used for the diagnosis of diabetes, but it is not accurately correlated with blood glucose fluctuations. We evaluated the impact of prestroke glycemic variability, measured by glycated albumin (GA) on reperfusion rate and stroke outcomes after endovascular treatment (EVT). Methods: We consecutively collected 310 EVT-treated patients for 60 months using a multicenter registry database. Primary outcome was unsuccessful reperfusion defined by modified Thrombolysis in Cerebral Infarction grade 0 to 2a. Secondary outcomes were occurrence of early neurologic deterioration (END), symptomatic hemorrhagic transformation (SHT) and a 3-month poor outcome (modified Rankin Scale >2). GA was measured in the morning after hospital admission with overnight fasting and determined to reflect high prestroke glycemic variability (GA ≥16.0%). Results: Over the median follow-up of 60 months of 310 patients, there were 64 (20.6%) events of unsuccessful reperfusion, 66 (21.3%) of END, 21 (6.8%) of SHT, and 180 (58.1%) of 3-month poor outcome. In the higher GA group (130, 41.9%), proportion of unsuccessful reperfusion, END, SHT, and poor outcome were higher than lower GA group. The multivariate analysis showed that higher GA was associated with unsuccessful reperfusion after EVT (adjusted odds ratio 4.13; 95% confidence interval [CI], 1.93–8.85). The area under the receiver operating characteristic of GA (0.644; 95% CI: 0.634–0.740) for predicting poor outcome was better than that of glycated hemoglobin (0.586; 95% CI: 0.529–0.642, p for DeLong’s pairwise comparison = 0.005). Conclusion: GA, reflecting prestroke glycemic variability, could be a reliable parameter for predicting reperfusion rate and acute ischemic stroke outcome in this study.
Education During Pandemic: The Adoption of Learning Resource on Wifi Hub Expanded Electronic Learning in Sarangani (LR on WHEeLs) in Alabel 4 District
Authors: Castillas Glenn M.
Published: May 2022

The purpose of this study is to look into teachers' willingness to use the Learning Resources on Wi-Fi Hub for Expanded e-Learning (LR on WHEeLs) as a flexible learning option to extend the reach of e-learning to remote villages, particularly those outside of the service coverage of major telecommunications companies and internet service providers.

This study employs quantitative research, with data collected via an online survey questionnaire. Purposive sampling was also used to select respondents from Alegria National High School. The collected data was statistically analyzed using weighted mean.

The teachers' readiness on LR on WHEeLs anchored to the uses of ICT revealed the following: first, the school staff and the department as a whole provide ICT professional development. Second, ICT-based activities and materials for teaching were frequently used, and subsequently, teachers were confident in their ICT skills. This indicates that the majority of teacher-respondents had adapted to so-called 21st-century learners. However, it has been revealed that the difficulties encountered by participants in the use of LR on WHEeLs include a lack of interest on the part of teachers, a lack of benefit from using Technology in teaching and learning, and an absence of adequate content/materials. As a result, proper reinforcement must be provided to teachers through training, orientation, and seminars, as well as the provision of the support needed and materials for the use of LR on WHEeLs.
Deep Learning in Biology: 3D Representation of Online and Reality
Authors: Suprapto Purwati K. , Ardiansyah Ryan , Chaidir Diki M. , Baiq Baiq , Meylani Vita
Published: May 2022

Deep learning is required to examine biological material, particularly abstract content, either in the laboratory alone or with internet literature. This study aims to compare the effectiveness of learning through practicum versus learning through a combination of practicum (real-world data) and online literature review in terms of the ability to represent the three-dimensional (3D) model of plant tissue structure in a plant anatomy course. This study employed a quantitative approach with a quasi-experimental design in the posttest alone control group. This research used Purposive sampling to choose the research sample, which consisted of two classes of students enrolled in a plant anatomy course. ANOVA was used to analyze the data, with a significance level of 0.05. The results indicated a significant difference in learning when combined practicum was with online literature study visuospatial when practicum was used alone with a more excellent 3D model representation value in the class. Classes that combine an applied practicum with an online literature review have a grade point average of 73.61.