bluuebunny/crossref_metadata_2025 huggingface dataset:
Bacitracin for Injection Recall: Impact on Immediate Breast Implant Surgical Outcomes
Authors: Tirrell Abigail R. , Bekeny Jenna C. , Tefera Eshetu A. , Song David H. , Fan Kenneth L.
Published: August 2022

Background. Triple-antibiotic irrigation of breast implant pockets is a mainstay of infection prophylaxis in breast reconstruction and augmentation. The recall of bacitracin for injection due to risk of anaphylaxis and nephrotoxicity in January 2020, a staple component of the irrigation solution, has raised concern for worsened postoperative sequelae. This study aimed to investigate pre- and post-recall implant-based breast surgery to analyze the impact of bacitracin in irrigation solutions on infection rates. Methods. All implant-based breast reconstruction or augmentation surgeries from January 2019 to February 2021 were retrospectively reviewed. In a regression discontinuity study design, patients were divided into pre- and post-recall groups. Patient demographics, surgical details, and outcomes including infection rates were collected. Differences in complication rates were compared between groups and with surgical and patient factors. Results. 254 implants in 143 patients met inclusion criteria for this study, with 172 implants placed before recall and 82 placed after recall. Patients in each cohort did not differ in age, BMI, smoking status, or history of breast radiation or capsular contracture (

p
>
0.05

). All breast pockets were irrigated with antibiotic solution, most commonly bacitracin, cefazolin, gentamycin, and povidone-iodine before recall (116,67.4%) and cefazolin, gentamycin, and povidone-iodine after recall (59,72.0%). There was no difference in incidence of infection (6.4% vs. 8.5%,

p
=
0.551

) or cellulitis (3.5% vs. 3.7%,

p
=
0.959

) before and after recall. Implant infection was associated with smoking history (

p
<
0.001

) and increased surgical time (

p
=
0.003

). Conclusions. Despite the recent recall of bacitracin from inclusion in breast pocket irrigation solutions, our study demonstrated no detrimental impact on immediate complication rates. This shift in irrigation protocols calls for additional investigations into optimizing antibiotic combinations in solution, as bacitracin is no longer a viable option, to improve surgical outcomes and long-term benefits.
Deep Learning Reconstruction Algorithm‐Based MRI Image Evaluation of Edaravone in the Treatment of Lower Limb Ischemia‐Reperfusion Injury
Authors: Liu Jianping , Duan Xunhong , Ye Rong , Xiao Junqi , Fang Cuifu , Liu Fengen
Published: August 2022

This research aimed to evaluate the therapeutic effect of edaravone on lower limb ischemia‐reperfusion injury by MRI images of graph patch‐based directional curvelet transform (GPBDCT), compression reconstruction algorithm. 200 patients with lower limb ischemia‐reperfusion injury after replantation of severed limb were randomly divided into the observation group (edaravone treatment) and control group (Mailuoning injection treatment), with 100 cases in each group. MRI scanning and image processing using the GPBDCT algorithm were used to evaluate the therapeutic effect of the two groups of patients. The results showed that the signal noise ratio (SNR) (22.01), relative l2 norm error (RLNE) (0.0792), and matching degree γ (0.9997) of the compression and reconstruction algorithm based on GPBDCT were superior to those of the conventional compression and reconstruction algorithm (P < 0.05). MRI examination showed that the decrease of bleeding signal after treatment in the observation group was superior to that in the control group. The levels of superoxide dismutase (SOD) (15 ± 2.02), malondialdehyde (MDA) (2.27 ± 1.02), B cell lymphoma‐2 (Bcl‐2) (8.5 ± 1.02), Bcl‐2‐associated X (Bax) (3.7 ± 0.42), and Caspase‐3 protein (35.9 ± 5.42) in the observation group before and after treatment were significantly higher than those in the control group (P < 0.05). In conclusion, the GPBDCT‐based compression reconstruction algorithm has a better effect on MRI image processing, and edaravone can better remove free radicals and alleviate apoptosis.
A Parallel DNA Algorithm for Solving the Quota Traveling Salesman Problem Based on Biocomputing Model
Authors: Wang Zhaocai , Wu Xian , Wu Tunhua
Published: August 2022

The quota traveling salesman problem (QTSP) is a variant of the traveling salesman problem (TSP), which is a classical optimization problem. In the QTSP, the salesman visits some of the

n

cities to meet a given sales quota

Q

while having minimized travel costs. In this paper, we develop a DNA algorithm based on Adleman-Lipton model to solve the quota traveling salesman problem. Its time complexity is

O

n

2

+
Q

, which is a significant improvement over previous algorithms with exponential complexity. A coding scheme of element information is pointed out, and a reasonable biological algorithm is raised by using limited conditions, whose feasibility is verified by simulation experiments. The innovation of this study is to propose a polynomial time complexity algorithm to solve the QTSP. This advantage will become more obvious as the problem scale increases compared with the algorithm of exponential computational complexity. The proposed DNA algorithm also has the significant advantages of having a large storage capacity and consuming less energy during the operation. With the maturity of DNA manipulation technology, DNA computing, as one of the parallel biological computing methods, has the potential to solve more complex NP-hard problems.
Transient Electromagnetic 1‐Dimensional Inversion Based on the Quantum Particle Swarms Optimization‐Smooth Constrained Least Squares Joint Algorithm and Its Application in Karst Exploration
Authors: Liu Xue , Pan Chunwei , Zheng Fangkun , Sun Ying , Gou Qingsong
Published: August 2022

Before the construction of the bridge bored pile in the karst area, geological conditions of the excavation area should be investigated. In order to avoid the karst caves in underground space making adverse impacts on the construction, bearing capacity, and stability of pile foundation, in this paper, we use the transient electromagnetic method to detect the karst development in the bearing layer of the pile foundation, which is different from the traditional karst survey method. To improve the interpretation accuracy of transient electromagnetic detection for karst caves, the quantum particle swarm optimization (QPSO) algorithm was combined with the smooth constrained least squares (CLS) algorithm, and the transient electromagnetic inversion based on the QPSO‐CLS joint algorithm was generated. Better inversion results were achieved by the proposed method in this study. Based on the inversion calculation results of simulation data and field test data, it is further demonstrated that the QPSO‐CLS joint algorithm has high optimization efficiency without manually setting the initial model. The interpretation results are consistent with the theoretical model and drilling logging results, which proves the adaptability of the proposed algorithm.
Using Artificial Intelligence to Predict Customer Satisfaction with E‐Payment Systems during the COVID‐19 Pandemic
Authors: Atawneh Samer H. , Hamadneh Nawaf N. , Jaber Jamil J. , Al Wadi S. , Khan Waqar A.
Published: August 2022

This study explores the impact of electronic payment systems on Saudi Arabia’s customer satisfaction during the COVID‐19 pandemic. Descriptive analytical approach of a sample of 1,025 people living in Saudi Arabia was used to answer the study questions and test its hypotheses. Then, a new hybrid fuzzy inference system (HyFIS) is proposed to predict customer satisfaction during COVID‐19 pandemic. The proposed system contemplates customer resistance (CR), access to technology (AT), privacy (PV), costs (CT), and speed of efficiency (SE) as the input variables and customer satisfaction (CS) as the output variable. Various statistical tests are utilized to determine the efficiency of input variables in the obtained data. The statistical tests are multicollinearity tests, reliability and validity, ordinal least square (OLS), fixed effect, and random development. As a result, we can determine each input variable’s direct and indirect impact on the CS. Under OLS, fixed effect, and unexpected effect, the SE, CT, PV, AT, and CR considerably impact EP. The EP has been shown to have substantial positive indirect implications. Under OLS, fixed effect, and random effect, the CT, PV, and CR are found to have a significant positive impact on CS. In addition, the AT has a substantial impact on CS in a fixed effect indirect effect. The results of HyFIS were compared to those of the adaptive network‐based fuzzy inference system (ANFIS). The results reveal that HyFIS outperforms ANFIS in predicting CS based on the error criterion.
Motion Planning and Tracking Control of Autonomous Vehicle Based on Improved

A

∗

Algorithm
Authors: Bai Yunlong , Li Gang , Li Ning
Published: August 2022

The traditional

A

∗

algorithm, applied to the motion planning of autonomous vehicles, easily causes high computational costs and excessive turning points generated in the planning path. In addition, the vehicle cannot track the path due to the unsmooth inflection point. To overcome these potential limitations, an improved

A

∗

algorithm-based motion planning algorithm and a tracking control strategy based on model predictive control theory were proposed in this work. The method of expanding the search neighborhood is adopted to improve the planning efficiency of

A

∗

algorithm. The artificial potential field method is also incorporated into the proposed

A

∗

algorithm. The resultant force generated by each potential field is further introduced into the evaluation function of

A

∗

algorithm to plan the driving path, which could be suitable for autonomous vehicles. The sharp nodes in the path are smoothed by cubic quasi-uniform B-spline curve. The tracking control strategy is designed based on model predictive control theory to realize the accurate tracking of the planned path. Typical obstacle avoidance conditions were selected for co-simulation test verification. The experimental results show that the proposed motion planning algorithm and tracking control strategy can effectively plan the obstacle avoidance path and accurately track the path in different environments.
The Design of Academic Programs Using Rough Set Association Rule Mining
Authors: Hogo Mofreh A.
Published: August 2022

Program accreditation is important for determining whether or not a program or institution meets quality standards. It helps employers to evaluate the programs and qualifications of their graduates as well as to achieve its strategic goals and its continuous improvement plans. Preparing for accreditation requires extensive effort. One of the required documents is the program’s self-study report (SSR), which includes the PEO-SO map (which allocates the program’s educational objectives (PEOs) to student learning outcomes (SOs)). It influences program structure design, performance monitoring, assessment, and continuous improvement. Professionals in each academic engineering program have designed their PEO-SO maps in accordance with their experiences. The problem with the incorrect design of map design is that the SOs are either missing altogether or cannot be assigned to the correct PEOs. The objective of this work is to use a hybrid data mining approach to design the correct PEO-SO map. The proposed hybrid approach utilizes three different data mining techniques: classification to find the similarities between PEOs, crisp association rules to find the crisp rules for the PEO-SO map, and rough set association rules to find the coarse association rules for the PEO-SO map. The work collected 200 SSRs of accredited engineering programs by the ABET-EAC. The paper presents the different phases of the work, such as data collection and preprocessing, building of three data mining models (classification, crisp association rules, and rough set association rules), and analysis of the results and comparison with related work. The validation of the obtained results by different fifty specialists (from the academic engineering field) and their recommendations were also presented. The comparison with other related works proved the success of the proposed approach to discover the correct PEO-SO maps with higher performance.
Analysis of the Stability of Reinforced Plastic Waste Treated Clay as Embankment Fill on Soft Soils
Authors: Amena Shelema
Published: August 2022

The purpose of this study is to analyze the suitability and stability of clay soil treated with plastic waste as an embankment fill. Plastic wastes are used to stabilize the locally found weak clay. The locally found weak clay soil is stabilized with plastic waste. The stability analyses of the proposed slope have been done by finite element method using geotechnical software PLAXIS 2D. The stability analyses were performed for different conditions considering the geometry of the embankment, characterization of fill material, and the strength of reinforcement. Different models were analyzed to determine the safe height, side slope, and tensile strength of geogrid required to stabilize the embankment in addition to that of unreinforced embankments. The factor of safety of each trial is taken to check the stability of the modeled embankments. Accordingly, the factor of safety increases as geogrid axial stiffness increases greater than 500 kN/m. The analysis results revealed that with increasing slope height and slope angle the factor of safety decreases. This study found that plastic waste treated clay could be used as embankment fill when reinforced with geogrid.
Effects of an Aquatic Physical Exercise Program on Ventilatory Parameters in People with Parkinson’s Disease
Authors: Yamaguchi Bruna , Iucksch Dielise Debona , Paladini Luis Henrique , Israel Vera Lúcia
Published: August 2022

Problems in the respiratory system are the main cause of death in Parkinson’s disease (PD). Ventilatory limitations can also be part of a vicious cycle involving physical-functional limitations (e.g., walking difficulties) and the patients’ perception of fatigue. The objective of this study was to analyze the effects of an aquatic physical exercise intervention program on ventilatory parameters, perception of fatigue, and gait capacity in participants with PD. This quasi-experimental study had a single group with repeated measures in four assessments, proposing an aquatic physical exercise intervention program. The inclusion criteria encompassed being in levels 1 to 4 on the Hoehn and Yahr scale and having a medical certificate for the activities. Assessments took place at 3-month intervals between them—the first period was the control, the second following the intervention, and the third period was the follow-up. The intervention had 25 biweekly sessions over 3 months. A total of 13 people (71.3 ± 5.61 years old) participated in the intervention, without significant differences in the control period. Between the intervention assessments, they had statistically significant differences in MIP, MEP, FVC, Tiffeneau index, MVV, and fatigue. The study demonstrated that the aquatic physical exercise intervention was effective for ventilatory outcomes and fatigue in people with PD.
Endurance Monitoring Method for Rock Climbers Based on Multisensor FDA Model
Authors: Dai Yibo
Published: August 2022

The quality of sports performance mainly depends on the scientific degree of sports training. The best monitoring and control of the whole process of sports training is an important guarantee for improving the scientific degree of training. For the scientific monitoring of sports training process, many scholars have carried out research from many aspects. Current research still finds that athletes still have many problems with the protection of their own physical endurance. (1) The monitoring of the sports training process by coaches and athletes is still mainly spontaneous. The monitoring of athletes has not yet formed a system. (2) At present, the monitoring of athletes is mainly carried out from a single discipline or a certain field, and there is no systematic monitoring system. (3) There are many common problems in the monitoring items of the training process in the existing research. Existing studies have relatively little content on specific characteristics. In this paper, a dynamic monitoring system for the training process of elite rock climbers is established, and a training operation mode for rock climbers is established. (1) This paper sorts out the various subsystems of the training system. The monitoring system of sports training process mainly includes target system, personnel organization system, and software and hardware system. In addition, the sports training system proposed in this paper also includes monitoring content system, implementation system, and evaluation system. The sports training process monitoring system also includes a subsystem for monitoring the development of athletic ability of athletes. We take on the training load condition monitoring subsystem; daily physical function state and psychological state monitoring subsystem; and physical and mental health monitoring subsystem. (2) In addition, this paper establishes an operation mode dominated by “scientific research leaders.” The model includes three parts: “Administrative Managers, Scientific Research Leaders, and Coaches.” (3) Finally, this paper establishes five basic guiding ideologies for the evaluation of training process monitoring results. This paper establishes three reference standards for the evaluation of monitoring indicators.
Effects of COVID-19 Pandemic on Progress Test Performance in German-Speaking Countries
Authors: Sehy Victoria , Roselló Atanet Iván , Sieg Miriam , Struzena Jana , März Maren
Published: August 2022

Background. The COVID-19 pandemic has been the source of many challenges for medical students worldwide. The authors examined short-term effects on the knowledge gain of medical students in German-speaking countries. Methods. The development of the knowledge gain of medical students during the pandemic was measured by comparing the outcomes of shared questions within Berlin Progress Test (PT) pairs. The PT is a formative test of 200 multiple choice questions at the graduate level, which provides feedback to students on knowledge and knowledge gain during their course of study. It is provided to about 11,000 students in Germany and Austria around the beginning of each semester. We analyzed three successive test pairs: PT36-PT41 (both conducted before the pandemic), PT37-PT42 (PT37 took place before the pandemic; PT42 was conducted from April 2020 onwards), and PT38-PT43 (PT38 was administered before the pandemic; PT43 started in November 2020). The authors used mixed-effect regression models and compared the absolute variations in the percentage of correct answers per subject. Results. The most recent test of each PT pair showed a higher mean score compared to the previous test in the same pair (PT36-PT41 : 2.53 (95% CI: 1.31–3.75), PT37-PT42 : 3.72 (2.57–4.88), and PT38-PT43 : 5.66 (4.63–6.69)). Analogously, an increase in the share of correct answers was observed for most medical disciplines, with Epidemiology showing the most remarkable upsurge. Conclusions. Overall, PT performance improved during the pandemic, which we take as an indication that the sudden shift to online learning did not have a negative effect on the knowledge gain of students. We consider that these results may be helpful in advancing innovative approaches to medical education.
Experimental Study on Grouting and Flow Characteristics of Rough Vertical Fractures
Authors: Li Zheng , Liu Jie , Shi Qian , Mao Kun , Li Zhao , Tang Hongyu , Wang Tianlong
Published: August 2022

It is of great engineering significance to study the seepage characteristics and flow field distribution of rough fractured rock masses for grouting to stop leakage. Through the visual fracture seepage test device we developed, the visual seepage characteristics of tension fractures under vertical angles and different stress paths of grout and water were studied. Through silica gel secondary mould turning technology, the fracture morphology is accurately reprinted; based on GIS simulation technology, the visualization of the fracture surface spatial data is realized; the actual seepage area and flow path of the fluid are measured accurately by using digital image self-recognition technology, and the variation law of the grout and water seepage area under the coupling of normal stress and water pressure is obtained. Through visualization, it is pointed out that, with the increase of normal stress, the fracture water can be divided into three stages, archipelago flow, transition flow, and groove flow, while the grout has no capillary permeability and no archipelago flow effect because of its high viscosity. The critical point of grout antiseepage is defined and calibrated by data. Based on the analysis of the cross-sectional velocity of the groove flow, it is pointed out that the relationship between the velocity on the flow path and JRC is an exponential function. The main flow path is mainly distributed in the area where the JRC is relatively small. As the normal stress increases, the first deflection point of the grout flow path appears in the maximum region of JRC (6.42); the secondary deflection point appears in the second largest region of the flow path JRC (4.53), and the fluid of deflection point has the maximum kinetic energy on the main flow path. The current study can accurately obtain the relevant parameters of vertical fracture grouting seepage characteristics and provide theoretical guidance for solving the key scientific problems in grouting engineering, such as invisible flow paths and unmeasurable velocity vectors.
[Retracted] Automatic Detection and Classification of Epileptic Seizures in Patients with Liver Cirrhosis and Overlapping Hev Infection Based on Deep Multimodal Fusion Technology
Authors: Yu Jianan , Min Rui , Yu Yun , Hu Xiaorui , Fu Xiandong , Chi Nannan
Published: August 2022

Liver cirrhosis is a clinical chronic developmental liver disease, which is caused by long‐term or repeated effects of liver dysfunction, and there are more and more cases of epileptic seizures in patients with liver cirrhosis and HEV infection. This article aims to study how to analyze epileptic seizures in patients with liver cirrhosis and overlapping HEV infection based on deep multimodal fusion technology. This article proposes a deep learning neural network algorithm based on deep multimodal fusion technology, and how to use this algorithm to automatically detect and classify epileptic seizures. The data in the experiment in this article show that the prevalence of epilepsy accounts for 1% of the world's population, about 56.7 million people, and 1 in 25 people may have an epileptic seizure at some time in their lives, and in each person’s life, the probability of seizures due to various reasons is 10%. In 2016, the proportion of males with cirrhosis reached 16%, females reached 8%, and males were 8% higher than females, which is a full double. The test results show that with the increase in patients with cirrhosis and overlapping HEV infection, the frequency of epileptic seizures is also getting higher and higher, indicating that the frequency of epileptic seizures has been increased in patients with cirrhosis and overlapping HEV infection. Therefore, it is imperative to analyze the epileptic seizures of patients with liver cirrhosis and overlapping HEV infection based on deep multimodal fusion technology.
Seismic Vulnerability Analysis of Prefabricated Concrete Frame with a Cam‐Type Response Amplifying Device of Viscous Damper
Authors: Wei Luyao , Nie Huijiao
Published: August 2022

A new type of limit response amplifying device (cam‐type response amplifying device) was proposed in order to be able to solve the shortcomings of the seismic performance of the prefabricated concrete structures and the shortcomings of the existing response amplification devices that were prone to failure under rare earthquakes. On the basis of the unit library provided by ABAQUS, the secondary development was carried out and the dynamic time history analysis was performed on the solid model of the prefabricated frame structure. We selected the displacement angle between layers as the structural damage index and used the dynamic incremental method to analyze the seismic vulnerability of the uncontrolled structure without the cam‐type response amplification device and the added damping structure. The results show that compared with the uncontrolled structure, the damping structure with a cam‐type response amplification device had a significant reduction in the probability of reaching various failure states, and the seismic performance was effectively improved. The cam‐type response amplifier had an excellent shock absorption effect under the action of all levels of the earthquake, which could effectively reduce the damage degree to the structure. Through the analysis of the vulnerability curve, it could provide the basis for the design method based on the behavior of the prefabricated concrete structures.
[Retracted] The Impact of Agricultural Land Rights Policy on the Pure Technical Efficiency of Farmers’ Agricultural Production: Evidence from the Largest Wheat Planting Environment in China
Authors: Cong Shengmei
Published: August 2022

Although the clarification of property rights for agricultural land has the potential to enhance agricultural production efficiency and support its sustainable growth, this goal may not always be met in reality. As a result, the emphasis of this study is on the elements that affect agricultural output. It also examines how the stability of land rights affects agricultural production efficiency and, most importantly, how the heterogeneity of farmers’ perspectives affects this process. Through the empirical test using the data of farmers in Henan Province, the largest wheat area in China, the results show that: (1) The farmland confirmation policy significantly promotes the improvement of the pure technical efficiency of agricultural production, a series of robustness tests, and the treatment of endogenous problems, which also confirmed the robustness of the results. (2) In the allocation of factors, agricultural investment and credit acquisition have been proved to be important influencing mechanisms, while labor and land transfer have not played a mechanistic role. (3) Heterogeneity analysis shows that the self‐service of farmers choosing to purchase agricultural machinery is more efficient than purchasing outsourcing services; The agricultural production of farmer households without hired workers has a significant technical efficiency, but the impact on farmer households with hired workers is not significant; for farmer households with agricultural insurance purchase behavior, purchase willingness, and planting and breeding advantages, the farmland ownership confirmation policy can play a more important role in promoting the pure technical efficiency of agricultural production; The promotion effect of the farmland right confirmation policy on the pure technical efficiency of agricultural output is strongest when there is a smaller level of farmers operating on a part‐time basis and when more farmers prioritize profit maximization as the production goal. Corresponding policy recommendations are made at the conclusion of the study in light of the conclusions mentioned.
Exploration of Ear Biometrics Using EfficientNet
Authors: Booysens Aimee , Viriri Serestina
Published: August 2022

Biometrics is the recognition of a human using biometric characteristics for identification, which may be physiological or behavioral. The physiological biometric features are the face, ear, iris, fingerprint, and handprint; behavioral biometrics are signatures, voice, gait pattern, and keystrokes. Numerous systems have been developed to distinguish biometric traits used in multiple applications, such as forensic investigations and security systems. With the current worldwide pandemic, facial identification has failed due to users wearing masks; however, the human ear has proven more suitable as it is visible. Therefore, the main contribution is to present the results of a CNN developed using EfficientNet. This paper presents the performance achieved in this research and shows the efficiency of EfficientNet on ear recognition. The nine variants of EfficientNets were fine-tuned and implemented on multiple publicly available ear datasets. The experiments showed that EfficientNet variant B8 achieved the best accuracy of 98.45%.
Analytical Method of Calculating Reliability Sensitivity for Space Capsule Life Support Systems
Authors: Mutar Emad Kareem
Published: August 2022

Several fields within the social and technical sciences have identified the importance of theoretical and practical research into complex systems. The sensitivity of these systems is one of the primary focuses. The capsule’s high-pressure oxygen supply system (HPOSS) prepares a complex system with complex interconnections. The reliability of HPOSS cannot be reduced to a single equivalent component or block by combining series and parallel reductions. The aim of this paper is to demonstrate the application of mathematical detection tests to HPOSS in order to assess the sensitivity of the reliability of complex systems. Using the matrix-based minimal cut methodology and the linear sensitivity model of system reliability, the critical system illustrates the suggested methodologies and their relevance to investigating the sensitivity of complex interconnected systems.
Integration of Transcriptome and Epigenome to Identify and Develop Prognostic Markers for Ovarian Cancer
Authors: Xu Can , Cao Wei
Published: August 2022

DNA methylation is a widely researched epigenetic modification. It is associated with the occurrence and development of cancer and has helped evaluate patients’ prognoses. However, most existing DNA methylation prognosis models have not simultaneously considered the changes of the downstream transcriptome. Methods. The RNA-Sequencing data and DNA methylation omics data of ovarian cancer patients were downloaded from The Cancer Genome Atlas (TCGA) database. The Consensus Cluster Plus algorithm was used to construct the methylated molecular subtypes of the ovary. Lasso regression was employed to build a multi-gene signature. An independent data set was applied to verify the prognostic value of the signature. The Gene Set Variation Analysis (GSVA) was used to carry out the enrichment analysis of the pathways linked to the gene signature. The IMvigor 210 cohort was used to explore the predictive efficacy of the gene signature for immunotherapy response. Results. We distinguished ovarian cancer samples into two subtypes with different prognosis, based on the omics data of DNA methylation. Differentially expressed genes and enrichment analysis among subtypes indicated that DNA methylation was related to fatty acid metabolism and the extracellular matrix (ECM)-receptor. Furthermore, we constructed an 8-gene signature, which proved to be efficient and stable in predicting prognostics in ovarian cancer patients with different data sets and distinctive pathological characteristics. Finally, the 8-gene signature could predict patients’ responses to immunotherapy. The polymerase chain reaction experiment was further used to verify the expression of 8 genes. Conclusion. We analyzed the prognostic value of the related genes of methylation in ovarian cancer. The 8-gene signature predicted the prognosis and immunotherapy response of ovarian cancer patients well and is expected to be valuable in clinical application.
A Case Report of Leptomeningeal Myelomatosis and Rapid Improvement with Regimen Consisting of Daratumumab, Pomalidomide, Vincristine, Procarbazine, and Dexamethasone
Authors: Kuan Jew Win , Chai Sing Ling , Rajadurai Pathmanathan , Lau Lee Gong , Uchang Joseph , Syed Husain Sharifah Noor Akmal
Published: August 2022

Central nervous system (CNS) involvement in multiple myeloma (MM) (MM-CNS) in the form of leptomeningeal myelomatosis or brain parenchyma plasmacytoma is rare, causing challenges in clinical diagnosis and treatment. We would like to report a case of leptomeningeal myelomatosis and illustrated the challeges. A 61-year-old man was diagnosed with MM with left paravertebral plasmacytoma, R-ISS II with high suspicion of double-hit MM, either biallelic aberrancy of TP53 or del(17p) and IGH aberrancy depending on the definition chosen, treated with lenalidomide-bortezomib-dexamethasone and local radiotherapy, later developed systemic relapse and progression to MM-CNS in the form of leptomeningeal myelomatosis. A modified CNS-based treatment not reported before, consisting of daratumumab, pomalidomide, vincristine, procarbazine, and dexamethasone, brought a rapid clinical improvement and warrants a further study. Incorporation of intrathecal thiotepa into the regimen would likely increase the efficacy.
Genetic Algorithm-Based Human Mental Stress Detection and Alerting in Internet of Things
Authors: Hamatta Hatem S. A. , Banerjee Kakoli , Anandaram Harishchander , Shabbir Alam Mohammad , Deva Durai C. Anand , Parvathi Devi B. , Palivela Hemant , Rajagopal R. , Yeshitla Alazar
Published: August 2022

Healthcare is one of the emerging application fields in the Internet of Things (IoT). Stress is a heightened psycho-physiological condition of the human that occurs in response to major objects or events. Stress factors are environmental elements that lead to stress. A person’s emotional well-being can be negatively impacted by long-term exposure to several stresses affecting at the same time, which can cause chronic health issues. To avoid strain problems, it is vital to recognize them in their early stages, which can only be done through regular stress monitoring. Wearable gadgets offer constant and real information collecting, which aids in experiencing an increase. An investigation of stress discovery using detecting devices and deep learning-based is implemented in this work. This proposed work investigates stress detection techniques that are utilized with detecting hardware, for example, electroencephalography (EEG), photoplethysmography (PPG), and the Galvanic skin reaction (GSR) as well as in various conditions including traveling and learning. A genetic algorithm is utilized to separate the features, and the ECNN-LSTM is utilized to classify the given information by utilizing the DEAP dataset. Before that, preprocessing strategies are proposed for eliminating artifacts in the signal. Then, the stress that is beyond the threshold value is reached the emergency/alert state; in that case, an expert who predicts the mental stress sends the report to the patient/doctor through the Internet. Finally, the performance is evaluated and compared with the traditional approaches in terms of accuracy, f1-score, precision, and recall.
[Retracted] Cell Division Cycle‐Associated Protein 3 (CDCA3) Is a Potential Biomarker for Clinical Prognosis and Immunotherapy in Pan‐Cancer
Authors: Xu Yingkun , Shen Meiying , Peng Yang , Liu Li , Tang Lingfeng , Yang Ting , Pu Dongyao , Tan Wenhao , Zhang Wenjie , Liu Shengchun
Published: August 2022

CDCA3 is an essential regulator in cell mitosis and can regulate many physiological and pathological processes in the human body by stimulating certain proteins such as cell cycle regulatory proteins, transcription factors, and signal transduction molecules. Although several studies have shown that dysregulation of CDCA3 is a common phenomenon in human cancers, no systematic pan‐cancer analysis has been performed. In this study, we comprehensively investigated the role of CDCA3 in 33 human cancer types by utilizing multiple cancer‐related databases and bioinformatics analysis tools, including TCGA, GTEx, GEPIA, TIMER, STRING, Metascape, and Cytoscape. Evidence from bioinformatics databases shows that CDCA3 is overexpressed in almost all human cancer types, and its overexpression is significantly associated with survival in patients with more than ten cancer types. CDCA3 expression positively correlates with immune cell infiltration levels in multiple human cancer types. Furthermore, the results of the GSEA analysis revealed that overexpression of CDCA3 may promote the malignant progression of cancer by activating various oncogenic signaling pathways in human cancers. In conclusion, our pan‐cancer analysis provides a comprehensive overview of the oncogenic role of CDCA3 in multiple human cancer types, suggesting that CDCA3 may serve as a potential therapeutic target and prognostic biomarker in multiple human cancer types.
Analysis of Clinical Characteristics and Risk Factors of Postoperative Recurrence and Malignant Transformation of Low-Grade Glioma
Authors: Luo Cheng , Luo Qian , Xu Yaoduan , Song Jiushan , Liu Yi , Wang Laizang , Dong Zhuoqi , Huang Wei , Yu Hualin , Li Jinghui
Published: August 2022

This research was developed to explore the clinical characteristics and related risk factors of postoperative recurrence and malignant transformation of low-grade glioma (LGG). The subjects were rolled into observation group (19 cases) and control group (51 cases) according to recurrence and malignant transformation during the follow-up period. The clinical data of the two groups were compared, and the risk factors of recurrence and malignant transformation were analyzed with the time of recurrence and malignant transformation as independent variables. The experimental results showed that the proportion of patients aged over 45 years in the observation group (63.16%) was higher than that in the control group (50.98%). The proportion of preoperative functional status score (KPS) ≥80 in the observation group (68.42%) was lower than that in the control group (78.43%). The proportion of patients with tumor over 5 cm in the control group (27.45%) was lower than that in the observation group (52.63%), and the proportion of total resection of tumor in the control group (47.06%) was higher than that in the observation group (21.05%). Furthermore, the multivariate analysis showed that preoperative KPS score, preoperative duration of disease, resection scope, postoperative treatment, oncotesticular antigen (OY-TES-1) mRNA, P53, mouse double microbody amplification gene (MDM2), vascular endothelial growth factor (VEGF), and epidermal growth factor receptor (EGFR) were independent risk factors (all

P
<
0.05

). In summary, patients with postoperative recurrence and malignant transformation had poorer physical condition and higher degree of malignancy before surgery. Preoperative KPS score, duration of disease, surgical resection scope, postoperative treatment, OY-TES-1 mRNA, P53, MDM2, VEGF, and EGFR were the risk factors.
Antibiotics Resistance Pattern of Food-Borne Bacteria Isolated from Ice Cream in Bangladesh: A Multidisciplinary Study
Authors: Sohel Md , Akter Moushumi , Hasan Md. Fahmid , Mahmud Shahin , Islam Mohammod Johirul , Islam Ashekul , Islam Khairul , Al Mamun Abdullah
Published: August 2022

Ice cream is one of the most popular food items consumed during the summer season in Bangladesh by all ages but mostly school-going students. Due to the ingredients and handling process of ice cream, it acts as a good shelter for pathogenic and nonpathogenic microorganisms. Therefore, we aimed to investigate the microbial count, prevalence, isolate and characterize multidrug-resistant bacteria in ice cream samples collected from nearby shops of schools in Tangail district, Bangladesh. Ice-cream consumer and nonconsumer students were selected by providing questionnaires. Total viable count (TVC) and total coliform count (TCC) were determined by pour plate methods, where conventional methods were performed for bacterial identification. The Kirby-Bauer disk diffusion method was used to determine the antimicrobial susceptibility of bacterial isolates. Kado and Liu method, with some modifications, was used to extract plasmid from the isolated bacteria and visualized through gel electrophoresis. The demographic characteristics showed that the degree of symptoms regarding microorganisms mediated disorders and rate of antibiotics intake in ice cream consumers were significantly higher than the nonconsumers. The range of TVC and TCC in the ice cream samples was found 0–9.9 × 109 CFU/ml and 0–900 CFU/ml, respectively. Interestingly, 93.75% of the total ice cream samples also showed fungal positive. A total of 12 different bacterial species were identified, including Proteus spp, E. coli, V.cholera, Pseudomonas spp, Shigella spp, Klebsiella spp, Aeromonas spp, V. Parahemolyticus. Salmonella paratyphi, Citrobacterspp, Plesiomonasspp, and Staphylococcus aureus. The antimicrobial susceptibility assay showed the multiple resistance frequency of these isolates to different antimicrobial drugs. All individual isolates were screened for plasmid DNA, and we found that seven strains harbored a single or more than two plasmids sized approximately between 1.9 and 140 MDa, indicating a possible connection between resistance phenotype pattern and genotype.
Quality Evaluation and Informatization Analysis of Physical Education Teaching Reform Based on Artificial Intelligence
Authors: Xu Yixiong , Huang Shuai , Li Lei
Published: August 2022

With the continuous reform of China’s education and the development of the educational environment, English will no longer be the third subject for Chinese students and physical education will replace it as the third subject. The teaching mode has also gradually changed from the traditional artificial mode to the current smart education. In the context of artificial intelligence, physical education can also apply this technology to daily teaching. After physical education becomes the third subject, it is necessary to reform the existing teaching mode and conduct quality evaluation and informatization analysis. In order to achieve this effect, we use artificial intelligence action scenes to detect students' detailed actions and identify key actions and then use computer vision system to create regression models and Bayesian formulas to give the criteria for judging the subsequent training points of the computer. Then, according to the training data of each student in the training process, the quality analysis and informatization evaluation of the teaching reform of physical education are carried out. Using the action bank algorithm as the basic algorithm of feature extraction, a template research method based on multispectral clustering is proposed to facilitate its dissemination in the computer background database. Then, through experiments to compare the before and after optimization of the algorithm, the data analysis of the resolution, time consumption, and detection error of the action bank model were carried out, and it was found that the performance was improved. Then, by means of mean shift detection method and spatiotemporal action detection method, the resolution, time consumption, and detection error of the action bank model are optimized to achieve the quality evaluation and informatization analysis of physical education teaching reform.
Adding Visual Information to Improve Multimodal Machine Translation for Low-Resource Language
Authors: Shi Xiayang , Yu Zhenqiang
Published: August 2022

Machine translation makes it easy for people to communicate across languages. Multimodal machine translation is also one of the important directions of research in machine translation, which uses feature information such as images and audio to assist translation models in obtaining higher quality target languages. However, in the vast majority of current research work has been conducted on the basis of commonly used corpora such as English, French, German, less research has been done on low-resource languages, and this has left the translation of low-resource languages relatively behind. This paper selects the English-Hindi and English-Hausa corpus, researched on low-resource language translation. The different models we use for image feature information extraction are fusion of image features with text information in the text encoding process of translation, using image features to provide additional information, and assisting the translation model for translation. Compared with text-only machine translation, the experimental results show that our method improves 3 BLEU in the English-Hindi dataset and improves 0.47 BLEU in the English-Hausa dataset. In addition, we also analyze the effect of image feature information extracted by different feature extraction models on the translation results. Different models pay different attention to each region of the image, and ResNet model is able to extract more feature information compared to VGG model, which is more effective for translation.
Application and Deconstruction of Visual Communication in Art Design Based on Linear Operator Theory
Authors: Tian Ye , Shan Huan
Published: August 2022

With the continuous development of society, information transmission can be seen everywhere, and various forms of visual communication with artistic design such as posters, periodicals, and electronic screens appear one after another. Visual communication is the effective communication of information through various visual elements. Visual communication of art design can promote the exchange of information and promote the development and progress of society. However, in the process of visual communication of artistic design, there are many problems of unclear images such as halo and inconsistent brightness, which brings bad visual experience to the information receiver. The linear operator theory has the ability to transform parameters and generalize to find the optimal solution, and the linear operator theory is applied to the visual communication of art design, which can effectively solve the problem of unclear images in traditional visual communication. This paper compares and analyzes the information entropy and mapping similarity between the visual communication of art design based on the linear operator theory and the traditional visual communication of art design by setting up an experimental group. The results showed that, among the four communication methods of art design visual communication, that is, figures, videos, animations, and movies, the mapping information entropy of art design visual communication based on linear operator theory in 6 different scenarios is 1.55 more than the traditional visual communication mode on average, and the average mapping similarity is 0.10 more. Therefore, the visual communication of artistic design based on the linear operator theory can convey more information and more accurate information and improve the effect of visual communication.