bluuebunny/crossref_metadata_2025 huggingface dataset:
Diagnostic Value of Spiral CT and Magnetic Resonance Imaging Scanning in Gastric Cancer and Precancerous Lesions
Authors: Zhen Yaolan , Xie Qing , Liu Lei
Published: May 2022

In order to explore the diagnostic value of spiral CT and magnetic resonance imaging scanning in gastric cancer and precancerous lesions, the author selected 56 gastric cancer patients treated in a medical center (group) as the experimental subjects, and all patients underwent MRI, multislice spiral CT scan, and enhanced CT scan two weeks before surgery; at the same time, the gastric cancer staging results of patients were diagnosed according to surgical pathology. All patients were examined under the condition of knowledge and performed breath-holding exercise before examination. The status, location, and extent of tumor lesions were evaluated. In comparison of T staging of gastric cancer patients with magnetic resonance scanning imaging and postoperative pathological examination results, among them, T staging of 3 patients did not match the results of pathological examination, the accuracy rates of T staging on magnetic resonance scanning imaging were

T
1
=
94.7
%

,

T
2
=
87.6
%

,

T
3
=
91.2
%

, and

T
4
=
94.7
%

, and the total accuracy was 92.1%. Comparison of helical CT scan imaging and postoperative pathological examination results is as follows. Among them, T staging of 8 patients did not match the results of pathological examination, 3 patients were ulcerative, 5 were protuberance, the accuracy rates of T staging in spiral CT scan imaging were

T
1
=
90.8
%

,

T
2
=
82.2
%

,

T
3
=
76.9
%

, and

T
4
=
87.6
%

, and the total accuracy was 84.5%. The total accuracy rate of imaging N staging was 77.5%, and the total accuracy rate of spiral CT scanning imaging N staging was 80.8%. The accuracy rates of M0 and M1 staging in magnetic resonance imaging were 100.0% and 96.5%, respectively, and the accuracy rates of M0 and M1 staging in spiral CT scan imaging were 96.5% and 96.5%, respectively. The accuracy rate of magnetic resonance imaging for the diagnosis of gastric cancer N staging was 77.4%, and the reason for the low accuracy rate was mainly because the enhancement effect was not obvious due to insufficient enhancement. The accuracy rate of spiral CT in diagnosing N staging of gastric cancer was 80.9%, which was mainly due to the small diameter of the middle celiac artery lymph nodes. Magnetic resonance and spiral CT scans have high value in the early diagnosis and staging of gastric cancer.
Study on the Multi‐Governance of Public Rental Housing Exit in China Based on the Evolutionary Game Theory
Authors: Tang Jing , Li Shilong
Published: May 2022

The COVID‐19 pandemic has plunged the housing affordability and living sanitary conditions of China's low‐income groups into a crisis. Public rental housing has made a significant contribution to alleviating this crisis, yet its exit problem has become more acute due to the impact of the epidemic. In order to explore how to effectively play the role of multi‐governance in public rental housing exit, this paper adopts game theory to analyze the evolution of the behavioral strategies of government departments and public rental housing tenants in public rental housing exit by combining four influencing parameters: the epidemic severity, the epidemic influence coefficient, the public participation degree, and the public reporting fairness. In response to exploring the conditions for the effective functioning of the multi‐governance model under the impact of the epidemic, the influences of parameter change on the stability of the system are analyzed. The results show that when the COVID‐19 epidemic impact coefficient is high, government departments need to reduce their own supervision costs to achieve better multi‐governance effects; when public reports are distorted, the government departments’ own supervision capabilities determine the impact of public participation on governance effects.
Decision Model of Contract‐Farming Supply Chain Considering Producer’s Fairness Concerns under Random Yield
Authors: Feng Yangang , Chen Rui , He Lin
Published: May 2022

Supply chain management is critical for addressing uncertainties caused by random demand and production yield. In this study, a random yield supply chain, in which the production process of fresh agricultural products is easily affected by factors, such as weather, soil, or plant diseases and insect pests, was considered. Therefore, the actual output is typically less than the planned output. A model in which the producer faces yield uncertainty was considered, and the influence of the producer’s fairness concerns on the planned output of the contract‐farming supply chain was considered. Methods to motivate the producer to increase planned output through reasonable contracts were investigated. The results revealed that the producer’s fairness concern considerably influences the optimal expected profit. In the case of the random output, the planned output and maximum expected profits reduce when the farmer exhibits fairness concerns. As the degree of the producer’s fairness concern increases, the planned output and expected profit gradually decrease The cost‐sharing contract can effectively encourage the producer to increase his planned output and expected utility. Finally, the results were verified numerically.
Implementation of Embedded Microprocessor in Optimal Teaching of Physical Health in the Internet Era
Authors: Liu Juan
Published: May 2022

The emergence of the online media environment has made the social environment faced by contemporary students more complicated. How to adapt to the rapid development of the network media environment, correctly grasping yourself in the complicated network world, not indulging in the network, is one of the focuses of many families and schools. As a media environment, the network has the advantages of rapid dissemination, large amount of information, strong interactivity, and rapid release. Especially through the integration with traditional media and new mobile media, it has become an important source of people’s access to massive information. It has had a profound impact. For college sports health science, how to guide students to use online sports health resources for independent learning is an important topic in the reform of college sports health education in the new era. How the university sports health science under the Internet environment can help the development goals of the healthy China in the new era becomes the theoretical problem of the in-depth study of sports health care in colleges and universities in China. This paper studies the optimization and implementation of the teaching principles of sports health in the Internet era. It integrates all the teaching principles of sports health since the reform and opening up and then produces questionnaires. The professors of the teaching of health education are the subjects of the survey. They conducted three rounds of questionnaire survey on the integrated teaching principles of 51 sports health education and analyzed the statistics of each round by mathematical statistics and logic analysis. After the logic unit consumption optimization, the microprocessor performance has been greatly improved and the critical path delay performance optimization maximum value has been increased from 4.69 to 8.24.
Some Singular Value Inequalities for Sector Matrices Involving Operator Concave Functions
Authors: Yang Chaojun
Published: May 2022

In this paper, we give some singular value inequalities for sector matrices involving operator concave function, which are generalizations of some existing results. Moreover, we present some unitarily invariant norm inequalities for sector matrices.
Infected Dentigerous Cyst of Maxillary Sinus Mimicking Intraoral Abscess in a Pediatric Patient: Management of Misdiagnosis and Inaccurate Treatment
Authors: Chybicki Damian , Popielarczyk Alicja , Markowski Wojciech , Torbicka Gaja , Janas-Naze Anna
Published: May 2022

The article presents the case of a 12-year-old male patient who was suffering from exacerbated (infected) dentigerous cyst of maxillary sinus, associated with impacted canine whose symptoms were deceptively similar to intraoral abscess. The first-aid treatment performed by general dental practitioner consisted of intraoral incision and resulted in oroantral fistula formation. Eventually, the patient’s ailments were not resolved, and we had to deal with serious local complications and difficulties. The treatment was performed under general anesthesia in one-day surgery system and included enucleation of the lesion, excision, and closure of oroantral fistula. Dislocated canine was not removed, and its subsequent eruption was observed.
Association of Probiotics with Atopic Dermatitis among Infant: A Meta-analysis of Randomized Controlled Trials
Authors: Pan Hua , Su Jingqiu
Published: May 2022

Background. Previous studies have explored the relationship between probiotics and risk of atopic dermatitis among infant; however, the results are still inconclusive. We aimed to assess the abovementioned association. Methods. PubMed, Web of Science, Embase, and China National Knowledge Infrastructure were retrieved for association between probiotics and atopic dermatitis with randomized controlled trials (RCTs) until Nov 20, 2021. The effect size was pooled by using random or fixed effect models according to the heterogeneity. Stata 12.0 was used for meta-analysis, sensitivity analysis, and bias analysis. Results. At the end of the screening article, 2575 infants were extracted from 8 trials and finally met the qualification criteria. In comparison to placebo, probiotics dramatically reduced incidence of childhood atopic dermatitis (RR=0.86, 95%CI=0.78-0.95). However, probiotics did not exhibit benefit over placebo in preventing the development of either IgE-associated infant AD (RR=0.98, 95%CI=0.79-1.22) or sensitive constitution (RR=0.93, 95%CI=0.81-1.08). From the results of sensitivity and publication bias, we found that these results were robust with little publication bias. Conclusion. During the late stages of pregnancy, women taking probiotics could lower the risk of infantile atopic dermatitis, but not for IgE-associated infant AD or sensitive constitution. The results could provide evidence for the fibrosis. Future studies are needed to confirm the results.
Some Examples of Materialist Dialectics in the Concept of Higher Mathematics
Authors: Xiaohui Zhou , Xuanze Zhao , Gang Wang , Cui Huang
Published: May 2022

Some examples of dialectics philosophy in higher mathematics are illustrated in this paper. Firstly, the principle of interconversion between quality and quantity in dialectics philosophy is quantified by the mathematical definition of the limit theory. Secondly, some natural and social phenomena imply the definition of continuous function in incremental form and it is a new explanation for the Zeno paradox. Finally, the dialectics relationship between the local change and the whole change of some variables is discussed in the differential median theorems.
Identifying the Moderating Effect of Hyperconnectivity on the Relationship between Job Demand Control Imbalance, Work-to-Family Conflict, and Health and Well-Being of Office Employees Working in the Oil and Gas Industry, Malaysia
Authors: Kanwal Noreen , Isha Ahmad Shahrul Nizam bin
Published: May 2022

There is an increasing acknowledgment of the added value obtained by integrating technological efforts to engage employees round the clock for organizational productivity. Hyperconnectivity is the demand of time for competitive advantage in businesses, but studies on its impact on the health and well-being of the employees have been neglected in academic research. Hence, in this study, we investigated the effect of hyperconnectivity on health and well-being, and in moderating the effect of work-to-family conflict and job demand control imbalance on the health and well-being of the office employees. An online questionnaire survey was used to collect data from 410 office employees working in the oil and gas industry in Malaysia. Respondents were approached through the LinkedIn forum. Statistical tests, principal component analysis, structural equation modeling, and path analysis were conducted. It is found that hyperconnectivity has a negatively insignificant effect on health and well-being. In addition, hyperconnectivity significantly strengthens the negative effect of job demand control imbalance (22%) and work-to-family conflict (24%) on health and well-being. It is concluded that hyperconnectivity decreases health and expedites other psychosocial hazards related to the health and well-being of the employees. Urgent measures should be taken to reduce unnecessary and frequent online notifications, messages, emails, and phone calls, both during and off-working hours. In this way, the effect of job demand control imbalance and work-to-family conflict can be reduced on the health and well-being of the office employees. Considering the negative consequences of hyperconnectivity, this problem should be addressed in health and safety policies in organizations. Future studies can investigate the effect of hyperconnectivity on job demands and control separately.
Serotype Distribution and Antimicrobial Resistance Profile of Haemophilus influenzae Isolated from School Children with Acute Otitis Media
Authors: Safari Dodi , Wahyono Daniel Joko , Tafroji Wisnu , Darmawan Anton Budhi , Winarti Yayah , Kusdaryanto Wahyu Dwi , Paramaiswari Wisiva Tofriska , Pramono Hendro , Pratiwi Meyta , Chamadi Muhamad Riza
Published: May 2022

Haemophilus influenzae is a Gram-negative opportunistic bacterial pathogen of the human respiratory tract. This study describes the prevalence, serotype distribution, and susceptibility profiles of H. influenzae strains isolated from the nasopharynx of school children with acute otitis media (AOM) in Banyumas Regency, Central Java, Indonesia. H. influenzae was isolated from nasopharyngeal swab specimens using chocolate agar plates supplemented with IsoVitaleX and bacitracin. Serotyping was performed using quantitative polymerase chain reaction. Antimicrobial susceptibility profiles were determined using a microdilution broth assay. H. influenzae was present in 69.7% of samples (85/122). Nontypeable H. influenzae (NHTi) was the most common serotype (95.3%), followed by H. influenzae type b (3.5%) and H. influenzae type f (1.2%). All the H. influenzae isolates were susceptible to levofloxacin, ceftriaxone, imipenem, meropenem, cefuroxime, and cefixime. Most isolates were susceptible to sparfloxacin (99%), cefepime (99%), amoxicillin/clavulanic acid 2 : 1 (99%), ampicillin/sulbactam 2 : 1 (96%), chloramphenicol (94%), tetracycline (93%), ampicillin (87%), and clarithromycin (82%). Nineteen percent of the isolates were resistant to cotrimoxazole, and 11% of the isolates were resistant to ampicillin. This study showed that H. influenzae carriage among samples was dominated by NTHi and less susceptible to cotrimoxazole.
Modeling and Analysis of HIV and Cholera Direct Transmission with Optimal Control
Authors: Cheneke Kumama Regassa , Rao Koya Purnachandra , Edessa Geremew Kenassa
Published: May 2022

In this study, a mathematical model of the human immunodeficiency virus (HIV) and cholera co infection is constructed and analyzed. The disease‐free equilibrium of the co‐infection model is both locally and globally asymptotically stable if R0 < 1 and unstable if R0 > 1. The only cholera model and only the HIV model show forward bifurcation if the corresponding reproduction numbers attain a value one. The disease‐free equilibria of only the cholera and only the HIV models is locally and globally asymptotically if R0 < 1, and the endemic equilibria of only the cholera model and only the HIV model are locally and globally asymptotically stable if the corresponding reproduction number is equal to one. The endemic equilibrium point of the HIV and cholera model is computed, and stability property is shown with numerical simulations. The computed partial derivatives (∂R0h/∂R0c > 0) show that the increase of one infection contributes to the increase of other infection. Pontryagin’s maximum principle is applied to construct Hamiltonian function, and optimal controls are computed. The optimal system is solved numerically using forward and backward sweep method of Runge Kutta’s fourth‐order methods. The numerical simulations are plotted using MATLAB.
Face Detection Method based on Lightweight Network and Weak Semantic Segmentation Attention Mechanism
Authors: Wu Xiaoyan
Published: May 2022

A face detection method based on lightweight network and weak semantic segmentation attention mechanism is proposed in this paper, aiming at the problems of low detection accuracy and slow detection speed in face detection in complex scenes. K-means++ algorithm is employed to perform clustering analysis on YOLOv4 model prior frames in this paper, and smaller size prior frames are set to capture small face information to solve the missing detection problem of small face targets in scenes. The backbone network structure is improved by introducing Mobile Net lightweight network model, to reduce the number of parameters and calculation of the model and improve the detection speed. The convolutional block attention module model with dual attention mechanism is embedded to improve the sensitivity of the model to target features, which can suppress interference information and improve the accuracy of target detection. A dynamic enhancement attachment based on weak semantic segmentation is added in front of the detector head, whose output is used as the spatial weight distribution to correct the activation area, to suppress the false detection and missed detection caused by the decrease of extraction ability evoked by the pursuit of lightweight. The experimental results on WIDEFACE dataset indicate that this method not only can detect face in real time and with high accuracy, but also has better performance than other existing methods.
Degree‐Based Molecular Descriptors and QSPR Analysis of Breast Cancer Drugs
Authors: Shanmukha M. C. , Usha A. , Praveen B. M. , Douhadji Abalo
Published: May 2022

The disease that involves abnormal cell growth and spreads through the surrounding tissues damaging other parts of the body is cancer. Breast cancer is the most common one out of many types. Women are affected by breast cancer either by hormonal changes or genetic changes that occur in DNA. As breast cancer is a life‐threatening disease, it is necessary for further studies to gear up in fighting the deadliest disease. In this work, a detailed study is made on the occurrence, symptoms, and the drugs involved in its treatment. For this purpose, the quantitative structure‐property relationship (QSPR) analysis is made using 21 drugs used in the treatment of breast cancer. The drugs considered in the study are modelled as molecular graphs using their molecular structures, and 11 topological indices are computed. The QSPR analysis is carried out for these drugs, and conclusions are drawn based on the analysis.
Deep Learning Based Dual Channel Banana Grading System Using Convolution Neural Network
Authors: S Raghavendra , Ganguli Souvik , Selvan P. Thirumarai , Nayak Mitali Madhusmita , Chaudhury Sushovan , Espina Randell U. , Ofori Isaac
Published: May 2022

Deep learning has recently been hailed as the most advanced computer vision technology for image classification. The invention of convolutional neural network (CNN) simplified the effort of feature engineering. Classification of various stages of fruit maturity using machine learning algorithms is a difficult task since it is difficult to distinguish the visual features of the fruits at different maturity stages. Fruit ripeness is critical in agriculture since it impacts the quality of the fruit. Manually determining the maturity of the fruit has various flaws, including the fact that it takes a long time, needs a lot of labor, and can lead to inconsistencies. In developing countries, agriculture is one of the most important economic sectors. Created system can be employed in the food processing business, in real-life applications where the intelligent system’s accuracy, cost, and speed will improve the production rate and allow satisfying consumer demand. With small number of image samples, the system is capable of automating assembly line related work for classifying bananas along with sufficient overall accuracy. The noninvasive method will also be used to classify other clustered fruits or horticultural crops in the future. The system can either replace or aid human operators who can focus their efforts on fruit selection. The combined merits of RGB and HSI (hyperspectral imaging) for classification of bananas were highlighted in the present study; they have possible application as a model for classification of several types of horticultural produce. The multi-input model’s quick processing time can be a useful and handy technique in the farm field during postharvest procedures. Via a combination of CNN and MLP applied to data collected using RGB and hyperspectral imaging, the multi-input model reliably recognizes bananas with an accuracy level of 98.4 percent as well as an F1-score of 0.97. The AI algorithm predicted the size (large, medium, and microscopic) and perspective (front or rear half) of banana classes with 99 percent accuracy. In comparison to previous studies that simply employed RGB imaging, the presented model revealed the value of integrating RGB imaging and HSI approaches.
Piano Information Teaching Mode Based on Deep Learning Algorithm
Authors: Wang XieHong
Published: May 2022

In order to improve the effect of piano information teaching, a piano information teaching mode based on deep learning algorithm is proposed. The teaching objectives are divided into three levels: classroom teaching objectives, curriculum objectives, and education and training objectives. A piano information classroom integrating cloud application platform, teaching platform, resource platform, learning space, and interactive classroom is built. The previous teaching mode is optimized to build an innovative teaching mode of piano information classroom. The evaluation index system of piano informatization classroom teaching quality is constructed, and the hierarchical structure model of each evaluation index is established by using the analytic hierarchy process. The hierarchical analysis method is used to establish a hierarchical structure model of each evaluation index. The judgment matrix is determined by the nine-digit scale method. After the consistency verification of the judgment matrix, the weight of the quality evaluation of piano information classroom teaching is calculated. The new mode optimizes the weight and threshold of BP neural network in deep learning algorithm by genetic algorithm (GA). The weight of each classroom teaching quality evaluation index is input into the GA-BP neural network, and the network output result is the piano information classroom teaching quality evaluation score. The test results show that the optimal number of hidden layer nodes for the BP neural network is 7, when the GA-BP neural network iterations are 95. This method can evaluate the quality of piano information classroom teaching, with high evaluation accuracy and strong practical application.
miR-196a-5p-Rich Extracellular Vesicles from Trophoblasts Induce M1 Polarization of Macrophages in Recurrent Miscarriage
Authors: Zhang Jing , Tao Yu , Cai Renfei , Wang Yao
Published: May 2022

Purpose. Numerous studies have described the presence of crosstalk between trophoblasts and macrophages and the critical role it plays in recurrent miscarriage (RM). However, the mechanism of trophoblast-derived extracellular vesicle (EV) miRNAs and their interactions with decidual macrophages in the pathogenesis of RM remains unclear. Materials and Methods. miRNA-seq was used to identify the differentially expressed miRNAs between RM patients and healthy controls. qPCR and in situ hybridization assays were performed to analyze the expression levels of miR-196a-5p in RM. THP-1 cells were treated with EVs, and qPCR and flow cytometry were performed to explore the polarization of macrophages. To explore the crosstalk between trophoblasts and macrophages, a coculture model and a series of cell function assays were performed. Results. We first demonstrated that miR-196a-5p expression was higher in the cytotrophoblasts of villous tissues and plasma EVs from RM patients. miR-196a-5p derived from trophoblasts could be transferred into macrophages via EVs to induce M1 polarization via IκBα-mediated NF-κB pathway. Moreover, we found that M1 macrophages induced by EV miR-196a-5p derived from trophoblasts conversely regulated the proliferation, migration, and apoptosis of trophoblasts via TNF-α. Conclusions. This study indicated that trophoblast-derived EV miR-196a-5p was positively associated with RM and functioned by regulating the crosstalk between trophoblasts and macrophages. These findings may attribute to identify a novel biomarker specific for RM.
New Solitons and Multishock Wave Structures for the Conformable Space Fractional Burger and Time Fractional Sharma-Tasso-Olver Models
Authors: Akter Selina , Harun-Or-Roshid  , Noor N. F. M.
Published: May 2022

This present paper studies the conformable space fractional Burgers, and the time fractional Sharma-Tasso-Olver models; both are highly important for nonlinear diffusive waves in fluid dynamics, sound waves in a viscous medium, and flow in field soils, as well as in gas and plasma dynamics. To retrieve explicit solutions of the fractional differential models, we propose an integral scheme, namely, Modified Kudryashov method. We obtain periodic, solitary, mixed periodic-soliton, and polynomial solutions through the approach. In particular, we exhibit topological kink-dark bell wave, topological kink, singular kink, bright bell, peakon solitons, and periodic shape waves to apply suitable values on parameters for both distinct models. The impact of fractionality on the wave shape and its deformation is analyzed and discussed graphically. We also investigate multishock wave’s solutions of both models and analyzed the effect of each existing parameters involved in the obtained solutions. To visualize the real characters of the solitary solutions, the graphical elucidation in 3D and 2D profiles are plotted. In computational effort and realization, it is emphasized that the proposed scheme is friendly useful, highly effective, and a powerful mathematical tool to extract exact solitary wave solutions for the differential models, as well as fractional differential models.
A Deep Learning-Based Model for Analyzing Social Public Issues
Authors: Zhu Yue
Published: May 2022

Social work services have grown in popularity in China in recent years, and in the context of the government's support of social governance innovation, social work has emerged as a powerful tool for intervening in communal public concerns. Community public problems are a focused expression of urban community contradictions and disputes. The aging and damage problems of public facilities in old building areas without property management in urban communities are affecting the lives of residents, and how social workers should intervene in the increasing public problems in communities can no longer be ignored. This article takes the behavior of social workers as the research object. By summarizing and analyzing the existing research results at home and abroad, it clarifies the importance of social workers' behavior to solve the public problems in communities. In order to analyze the group behavior of social workers, a hierarchical analysis model for group behavior identification is proposed by combining deep neural networks. The method uses moderation network migration learning to achieve the detection of temporal consistency of multiple human bodies in behavioral groups; the recognition of individual behaviors with unconstrained duration in-group behaviors is completed through the fusion of spatiotemporal feature learning; the stable and effective recognition of g is achieved through the fusion of individual behavior categories in scenes and the contextual information of interaction scenes. It is experimentally verified that the method can detect social workers' group behaviors, promote the rational solution to community public problems, and drive the development of community multibody governance.
Microbial Profile and Safety of Chicken Eggs from a Poultry Farm and Small-Scale Vendors in Hawassa, Southern Ethiopia
Authors: Damena Abraham , Mikru Abraham , Adane Million , Dobo Beyene
Published: May 2022

A freshly laid hen’s egg is devoid of microorganism, but soon after oviposition, it is contaminated by various spoilage and pathogenic microorganisms. The aim of this study was to assess the microbial profile and safety of chicken eggs in Hawassa City. A total of 60 egg samples were collected from Hawassa University Poultry Farm (HUPF) and small-scale vendors in Hawassa. The samples were analyzed for aerobic mesophilic bacterial count (AMBC), Staphylococcal count (SC), Enterobacteriaceae count (EC), total coliform count (TCC), fecal coliform count (FCC), and yeast and mold count (YMC). Moreover, the dominant mesophilic aerobic bacterial genera and common bacterial pathogens were identified by phenotypic methods. Accordingly, the mean aerobic mesophilic bacterial load of the shell surface rinsate of the egg samples ranged from 1.22 log10 CFU/ml to 9.7 log10 CFU/ml, while that of the internal contents ranged from 1.52 log CFU/ml to 9.36 log CFU/ml. The microbial load values of the egg contents were beyond the international recommended acceptable limits and suggested incipient spoilage. The mesophilic aerobic bacterial genera of the shell and internal contents of the egg samples were similarly dominated by Pseudomonas, Micrococcus, and Staphylococcus. The incidence of E. coli in shell rinsate and egg content was 10% (6 of 60) and 1.67% (1 of 60), respectively. Salmonellae were detected in shell rinsate of six egg samples (10%) and in the contents of eight samples (13.33%), all from small-scale vendors. These findings call for vigilant exercise of good agricultural and hygienic practices by primary producers and retailers.
Enhancing Orthopedic Surgery and Treatment Using Artificial Intelligence and Its Application in Health and Dietary Welfare
Authors: Rubidha Devi D. , UmaMaheswaran S. K. , Tarar Sandhya , Zamani Abu Sarwar , Gangodkar Durgaprasad , Chakkaravarthy A. Prabhu , Samori IssahAbubakari
Published: May 2022

The current decade has seen an increased usage of high-end digital technologies like machine learning in the field of health care services which enable in supporting and performing different functions with less or no human interventions. The application of machine learning tools in the orthopedic area is gaining more popularity as it can support in analyzing the issues in a more comprehensive manner, provide accurate data, support in forecasting the pattern. It enables offering critical information for taking quick decisions by the medical practitioners in order to enhance the health and dietary care service delivery. The ML tools can support in collecting patient centric data related to orthopedic surgery and also estimate the postoperative complications, level of treatment modalities to be provided, and guide the medical practitioners in taking effective clinical device decisions. The ML approach also supports in providing prediction methods of implementing the ortho surgical outcomes. Furthermore, it can also guide in making better treatment procedures, forecast the patterns, and stream the health care management services for better patient recovery. This study implements a quantitative research approach which will support in sourcing the data from the respondents who are currently working as medical practitioners, orthopedic experts, and radiologists who use ML-based models in making critical decisions related to orthopedic surgery. The researchers chose nearly 149 respondents, and the information was analysed using the IBM SPSS package for gaining critical interpretation. The major analyses cover descriptive analysis, regression analysis, and analysis of variances.
Intelligent Cost Accounting Optimization System of Building Engineering Materials Based on Ant Colony Algorithm
Authors: Ma Xue , Sohail Mishal
Published: May 2022

To save money on labour and keep track of the expenses of building engineering materials. This study provides an intelligent accounting and optimization system for building materials costs based on the ant colony algorithm. In the hardware, three relays are used to achieve open phase protection and convert the voltage signal into current signal; in the software, distinguish the material characteristics, identify the material types, use the virtual governance cost method, optimise the cost intelligent accounting mode, and design the software integration management function using integration technology and the ant colony algorithm; and in the hardware, use the virtual governance cost method. The average labour cost of the intelligent building material cost accounting and optimization system in this paper and the other three systems is 1924 (RMB 10,000), 2749 (RMB 10,000), and 2744 (RMB 10,000), respectively, demonstrating that the intelligent building material cost accounting and optimization system integrated with the ant colony algorithm has a better overall performance.
Fault‐Tolerant Resolvability of Swapped Optical Transpose Interconnection System
Authors: Hussain Iffat Fida , Afridi Sheeba , Qureshi Ahmad Mahmood , Ali Gohar , Ali Usman
Published: May 2022

Interconnection systems in computer science and information technology are mainly represented by graphs. One such instance is of swapped network simulated by the optical transpose interconnection system (OTIS). Fault tolerance has become a vital feature of optoelectronic systems. Among multiple types of faults that may take place in an interconnection system, two significant kinds are either due to malfunctioning of a node (processor in case of OG) or collapse of communication between nodes (failure of interprocessor transmission). To prevail over these faults, the unique recognition of every node is essential. In graph‐theoretic interpretation, this leads to instigating the metric dimension β(OG) and fault‐metric dimension β ′(OG) of the graph OG obtained from the interconnection system. This paper explores OTIS over base graph Pm (path graph over m vertices) for resolvability and fault‐tolerant resolvability. Furthermore, bounds for β(OG) and β′(OG) are also imparted over G = Pm.
Interactive Crossword Puzzles as an Adjunct Tool in Teaching Undergraduate Dental Students
Authors: Qutieshat Abubaker , Al-Harthy Nutayla , Singh Gurdeep , Chopra Viresh , Aouididi Rayhana , Arfaoui Rayan , Dileesh Sapna , Alsadoon Ahmed , Al-Nadhiri Omaima , Al-Busaidi Shima , Al-Rashdi Sumaiya , Alrashdan Mohammad S
Published: May 2022

Background. In the restorative dentistry module of the undergraduate dental program, dental students encounter many new terms and concepts in a short period of time. The provision of adequate learning support to reinforce key concepts can be challenging. Aim. The purpose of this study is to determine student perceptions of how effective interactive crossword puzzles are as adjunctive tools to enhance the learning of restorative dentistry. Methods. Students completed interactive crossword puzzles created by the authors, with a reward awarded to the first group of students who completed the puzzles successfully. The interactive crossword platform was programmed using the ReactJS framework and designed using Tailwind CSS. An evaluation of the student's perception of this educational method was conducted using textual feedback and Likert-scale questionnaires. Results. Students found the crossword puzzles engaging, meaningful, and successful as indicated by their favorable Likert scores and feedback. Written comments revealed student enthusiasm for and a desire to be exposed to more of these exercises. Conclusions. This work sheds light on the potential advantages of incorporating interactive crossword puzzles into the restorative dentistry course from a student’s perspective. The crossword puzzles improved students’ ability to review and reinforce concepts and terminology and proved to be meaningful and enjoyable. The web-based nature of the tool ensured good student responsiveness and engaged the entire class in an interactive, competitive setting. Application of the hint option, which offered a text of relevant reading material, helped students understand, retain more knowledge, and engage with course material more than they might have otherwise.
Computer Graphic Image Design and Visual Communication Design in the Internet of Things Scenario
Authors: Cheng Rongjie
Published: May 2022

For the problems of low-illumination reconstructed images with low resolution and long reconstruction time, an image reconstruction system based on the wavelet domain chunking compressed perception algorithm is proposed. A low-illumination image sampling model is established, and the wavelet domain chunking compression perception and information fusion processing are performed using the depth-of-field adaptive adjustment method of the image. The multiscale Retinex algorithm is used for wavelet domain chunking compressed perception and information extraction, and the information entropy feature quantity of the image is extracted. The IoT-based artificial intelligence image detection system has been formed, which effectively enhances the accuracy and timeliness of the image detection system and makes up for the deficiencies of the traditional image detection system. Simulation results show that the method is used for low-illumination image reconstruction with higher resolution, better edge perception, and shorter reconstruction time, which is more efficient for practical application.
Generative Logic of Digital Capitalism Based on Artificial Intelligence Technology
Authors: Li Zongrui
Published: May 2022

In the era of digital capitalism, machines and technology have gradually become the main body that dominates workers. Information technology is actually the digital embodiment of mass machine production. It is with the help of ICT and digital technology that digital capitalism realizes the digital transformation of the way capitalism exists and the proliferation of digital capital. The purpose of this paper is to study the generative logic of digital capitalism based on artificial intelligence technology. Compare the production, circulation, consumption of traditional commodities, and the production of digital capital, explore the nature of digital capitalism and the differentiation of digital capitalism in the era of artificial intelligence, analyze the impact of artificial intelligence on labor polarization, and the results show the high-skilled labor force in the eastern region. The ratio to the medium-skilled labor force is 0.086. Take the M enterprise in capitalism as an example, and study the application of artificial intelligence to the energy and power industry to provide value to customers through new products. The new changes in contemporary artificial intelligence capitalism solve the problems in the operation of the original business model, benefiting both customers and enterprises.
Gastrointestinal Quality of Life in Gastroesophageal Reflux Disease: A Systematic Review
Authors: Fuchs Karl-Hermann , Musial Frauke , Eypasch Ernst , Meining Alexander
Published: May 2022

Background: The Gastrointestinal Quality of Life Index (GIQLI) is a well-established instrument for the assessment of quality of life (QOL) in gastrointestinal (GI) diseases. The purpose of this literature review was to investigate QOL by means of GIQLI in patients with gastroesophageal reflux disease (GERD) prior to any interventional therapy. There are several reports on GIQLI data; however, comparisons from different countries and/or different GERD cohorts assessing the same disease have to date not been conducted. Methods: The GIQLI uses 36 items around 5 dimensions (GI symptoms [19 items], emotional dimension [5 items], physical dimension [7 items], social dimension [4 items], and therapeutic influences [1 item]). A literature search was conducted on the application of GIQLI in GERD patients prior to interventional therapy using reports in PubMed. Data on the mean GIQLI as well as index data for the 5 dimensions as originally validated were extracted from the published patient cohorts. A comparison with the normal healthy control group from the original publication of the GIQLI validation conducted by Eypasch was performed. Data are presented descriptively as GIQLI points as well as a reduction from 100% maximum possible index points (max 144 index points = highest QOL). Results: In total, 77 abstracts from studies using the GIQLI on patients with GERD were identified. After screening for content, 21 publications were considered for further analysis. Ten studies in GERD patients comprised complete calculations of all dimensions and were included in the analysis. Data from 1,682 study patients were evaluated with sample sizes ranging from 33 to 568 patients (median age of 789 females and 858 males: 51.8 years). The median overall GIQLI for the patient group was 91.7 (range 86–102.4), corresponding to 63.68% of the maximum GIQLI. The dimensions with the largest deviation from the respective maximum score were the physical dimension (55% of maximum) followed by the emotional dimension (60% of maximum). In summary, the GIQLI level in GERD cohorts was reduced to 55–75% of the maximum possible index. Conclusions: Severe GERD causes substantial reductions in the patient’s QOL. The level of GIQLI can carry between different studied GERD cohorts from different departments and countries. GIQLI can be used as an established tool to assess the patient’s condition in various dimensions.
Lymph Node Tuberculosis in Otolaryngological Practice: A Study of 68 Cases at the Sourô Sanou University Hospital of Bobo Dioulasso, Burkina Faso
Authors: Ouédraogo Richard Wend-Lasida , Amona Fructueux Modeste , Ikouebe Atonoboma Syska , Elola Abdoulaye
Published: May 2022

Introduction: Lymph node tuberculosis (LNTB) frequently affects peripheral cervical lymph node body sites. We aimed to study epidemiology and diagnostic and therapeutic characteristics of LNTB patients in ENT routine practice. Methods: We conducted a cross-sectional prospective study in the ENT and cervicofacial surgery department at the Sourô Sanou University Hospital of Bobo Dioulasso, Burkina Faso, for a period of 36 months. Results: There were 68 cases with LNTB, of which 54.4% were mostly men. The mean age and the median age were calculated at 37 ± 6.8 and 42 years, respectively. The patient’s age ranged between 3 and 81 years, and the most represented age group was from 30 to 60 years (62%). According to geographical origin, most patients (79%) originated from rural areas. In 6 cases (9%), patients reported diabetes and 12 patients were HIV positives (18%). Most clinical features leading to the ENT consultation were cervical lymph nodes (82%) and cervical scrofuloderma (18%). For the multiple locations, the lymphadenopathies involved mostly the transversal cervical chain (56%) and spinal chain (50%). Histopathology examination was the mostly diagnosed methods used in 68%. A 6-month anti-tuberculous treatment was given with a follow-up of 6 months without any relapse in 62 cases (97%). Conclusion: The frequency of 68 cases of LNTB in 3 years is underappreciated. Among all lymph node sites, transversal cervical chain and cervical spinal chain were mostly affected. Further advanced studies are recommended to determine the prevalence and contributing factors of LNTB in the study area.
Multi-Trait Genetic Analysis Reveals Clinically Interpretable Hypertension Subtypes
Authors: Vaura Felix , Kim Hyunkyung , Udler Miriam S. ,   FinnGen*, Salomaa Veikko , Lahti Leo , Niiranen Teemu
Published: May 2022

Background:

Hypertension comprises a heterogeneous range of phenotypes. We asked whether underlying genetic structure could explain a part of this heterogeneity.

Methods:

Our study sample comprised N=198 148 FinnGen participants (56% women, mean age 58 years) and N=21 168 well-phenotyped FINRISK participants (53% women, mean age 50 years). First, we identified genetic hypertension components with an unsupervised Bayesian non-negative matrix factorization algorithm using public genome-wide association data for 144 genetic hypertension variants and 16 clinical traits. For these components, we computed their (1) cross-sectional associations with clinical traits in FINRISK using linear regression and (2) longitudinal associations with incident adverse outcomes in FinnGen using Cox regression.

Results:

We observed 4 genetic hypertension components corresponding to recognizable clinical phenotypes: obesity (high body mass index), dyslipidemia (low high-density lipoprotein cholesterol and high triglycerides), hypolipidemia (low low-density lipoprotein cholesterol and low total cholesterol), and short stature. In FINRISK, all hypertension components had robust associations with their respective clinical characteristics. In FinnGen, the Obesity component was associated with increased diabetes risk (hazard ratio per 1 SD increase 1.08 [Bonferroni corrected CI, 1.05–1.10]) and the Hypolipidemia component with increased autoimmune disease risk (hazard ratio per 1 SD increase 1.05 [Bonferroni corrected CI, 1.03–1.07]). In addition, all hypertension components were related to both hypertension and cardiovascular disease.

Conclusions:

Our unsupervised analysis demonstrates that the genetic basis of hypertension can be understood as a mixture of 4 broad, clinically interpretable components capturing disease heterogeneity. These components could be used to stratify individuals into specific genetic subtypes and, therefore, to benefit personalized health care and pharmaceutical research.