bluuebunny/crossref_metadata_2025 huggingface dataset:
Multiobjective Optimization of Airport Ferry Vehicle Scheduling during Peak Hours Based on NSGA-II
Authors: Bi Jun , Ding Cong , Xie Dongfan , Li Yanhua
Published: July 2022

Airport ferry vehicles are used to transport passengers between the far apron and terminals. During the peak hours of flight arrival or departure, the demand for ferry vehicles will increase, and improper scheduling will result in significant delays. In this study, we construct a 0–1 integer programming scheduling model for ferry vehicles with multiple objectives: minimize flight delays and vehicle travel distances and balance vehicle workloads when there is an insufficient number of ferry vehicles. To solve the multiobjective model, this study selects the second version of the nondominated sorting genetic algorithm-II as the main framework and designs a modified coding and decoding scheme to solve the constraint problem in the model. The proposed model and algorithm are verified using actual data from Kunming Changshui International Airport, China. Compared with the scheduling method of manual first come first serve, the total delay time of the proposed model is reduced by 24.52%, the transit distance by 6.63%, and the balance index by 24.05%, which helps the airport solve the problem of insufficient ferry vehicles during peak hours. Comparison results show that the proposed model has a shorter calculation time and better distribution of solution sets than three state-of-the-art multiobjective optimization algorithms: MOPSO, MOACO, and SPEA-II. This research can help airports reduce flight delays, vehicle purchases, and operation costs.
Optimal Design Method for Vessel-Bridge Collision Based on Life-Cycle Theory
Authors: Fu Tao , Wang Kai , Zhou Ye , Ren Xiaoqian , Zhu Zhixin , Li Yan , Sun Yue , Meng Lingxiao
Published: July 2022

As structures crossing waterways, bridges are obstacles to vessels. Vessel-bridge collisions are inevitable. They not only involve the safety of vessel passage but also seriously affect the safe operation of bridges. Vessel-bridge collisions cause not only huge economic losses and casualties but also severe political and environmental losses. Vessel collision safety of existing and new bridges is one of the key technical problems that engineers and bridge managers must solve. Comprehensive consideration of vessel-bridge collision risk loss and structural performance in the design stage to achieve optimal cost over the life cycle is an important aspect of bridge design. Based on the current life-cycle design theory of engineering structures, this paper proposes a theoretical framework for vessel-bridge collision optimization design based on the life cycle, which includes three parts: vessel-bridge collision probability analysis, vessel-bridge collision vulnerability analysis, and vessel-bridge collision hazard. Taking the minimum cost of the bridge structure in the design service life period as the objective function, the optimization design model and design process of vessel-bridge collision based on whole life are established, and the key problems to be solved in each part are expounded.
Synthesis and Analysis of Impregnation on Activated Carbon in Multiwalled Carbon Nanotube for Cu Adsorption from Wastewater
Authors: Natrayan L. , Arul Kumar P. V. , Dhanraj Joshuva Arockia , Kaliappan S. , Sivakumar N. S. , Patil Pravin P. , Sekar S. , Paramasivam Prabhu
Published: July 2022

Industrial wastes contain more toxins that get dissolved in the rivers and lakes, which are means of freshwater reservoirs. The contamination of freshwater leads to various issues for microorganisms and humans. This paper proposes a novel method to remove excess copper from the water. The nanotubes are used as a powder in membrane form to remove the copper from the water. The multiwalled carbon nanotube is widely used as a membrane for filtration. It contains many graphene layers of nm size that easily adsorbs the copper when the water permeates through it. Activated carbon is the earliest and most economical method that also adsorbs copper to a certain extent. This paper proposes the methods of involving the activated carbon in the multiwalled carbon nanotube to improve the adsorption capability of the copper. Here, activated carbon is impregnated on the multiwalled carbon nanotube’s defect and imperfect surface areas. It makes more adsorption sites on the surface, increasing the adsorption amount. The same method is applied to Hydroxyl functionalized multiwalled carbon nanotubes. Both the methods showed better results and increased the copper removal. The functionalized method removed 93.82% copper, whereas the nonfunctionalized method removed 80.62% copper from the water.
Real-Time Detection of Lower Limb Training Stability Function Based on Smart Wearable Sensors
Authors: Zhang Ying
Published: July 2022

The research of smart wearable sensors in limb training has great application significance. In the face of real-time detection requirements, this paper proposes a hardware solution for the stability function of lower limb training based on the theory of intelligent wearable sensors. For the specific implementation circuit of the device, considering the reliability of the system, the system implements antijamming design for the hardware circuit from three aspects: adding decoupling capacitors, optimizing layout and wiring, and rationally grounding the hardware circuit, and performs moving average filtering on the collected sensor data to remove noise, which solves the problem of sensor data precision issues. During the simulation process, by analyzing the changes of acceleration, angular velocity, and attitude angle under different lower limb training activities and different wearing positions, the characteristics of stability combined acceleration, combined angular velocity, and attitude angle were constructed, and the stability mean, variance, and attitude angle were extracted. The experimental results show that the extracted 57 feature dimensions are first reduced to 21 dimensions by the principal component analysis algorithm, and then, the optimal feature subset is selected by the encapsulation method, and the dimension is reduced to 9. The proposed multifeature fusion algorithm has higher accuracy, and the maximum has increased by 6.5%, effectively improving the accuracy of the lower limb training stability function detection algorithm.
Biogas Production from Food Waste Using Nanocatalyst
Authors: Bharathi P. , Dayana R. , Rangaraju Magesh , Varsha V. , Subathra M. , Gayathri  , Sundramurthy Venkatesa Prabhu
Published: July 2022

The food waste management has become a very important part in the modern world. In the olden days, the population was very low, so that the low waste produced was easily disposed by dumping it under the soil. However, nowadays, due to high population, amount of waste is produced high which could not be dumped due to the land pollution. To overcome this problem, the food waste must be managed or utilized properly to give zero waste. Therefore, this work focused on the production of biogas from food waste through the anaerobic digestion process using iron oxide nanoparticles. The iron oxide nanocatalyst from red mud reduced the process time for the anaerobic digestion was by 5.38% compared to the noncatalytic process. The produced biogas analysis done through GCMS analysis and calculated by comparing the both anaerobic degradation setup with and without nanocatalyst. Nanocatalyzed degradation contains 50% high amount of methane and 23.5% of total amount of biogas when compared to nonnanocatalyzed degradation.
Reselling or Agency Selling? The Optimal Pricing and Return Strategy for the Agricultural Product
Authors: Huang Guoxuan , Sun Kangtai , Zhou Tai
Published: July 2022

An increasing number of farmer cooperatives turn to sell their agricultural products through the e-commerce platform. Two sales modes are investigated: the reselling mode and the agency selling mode. In the former mode, the cooperative charges the platform a wholesale price and the platform sets the retail price and the return compensation. In the latter mode, the cooperative decides the retail price and the return compensation on his own but needs to share a proportion of his revenue to the platform. We analyze the optimal pricing and return decisions in these two modes, and the results are shown as follows: (1) In the reselling mode, the wholesale price is linearly increasing in the surviving rate, whereas both the retail price and the return compensation are independent of the surviving rate. (2) In the agency selling mode, the retail price and the return compensation are increasing in the surviving rate and decreasing in the revenue sharing proportion. (3) The retail price (demand) in the agency mode is higher (lower) than that in the reselling mode. There exists a Pareto improvement region wherein both firms prefer the agency selling mode to the reselling mode. (4) The cooperative prefers the agency mode to the reselling mode in a market with high surviving rate and low revenue sharing proportion.
[Retracted] Analysis of the Basic Characteristics and Teaching Environment and Mode of Music Appreciation Course Based on Core Literacy
Authors: Lv Hua
Published: July 2022

The main goals of a music appreciation course are to develop college students’ emotions, improve their musical abilities, and strengthen their conceptual framework. This essay primarily introduces the fundamental elements and instructional approach of a music appreciation course built on core literacy. In order to clarify the need for and orientation of basic literacy in college music appreciation teaching, as well as to understand the special value of the subject, we conducted research on the relationship between basic literacy and college music appreciation teaching. Based on this, a new detection algorithm that fuses feature fusion and AM (attention mechanism) is proposed, and visual AM is added to the algorithm based on AM features to help the agent learn the best course of action quickly. The findings indicate that this method’s cumulative normalized discount gain increases by about 0.07 and that the recommended list’s overall quality has significantly improved. The hit ranking is decreased by about 0.05 when compared to the collaborative neural network filtering method without AM.
Varied Response of EEG Rhythm to Different tDCS Protocols and Lesion Hemispheres in Stroke Subjects with Upper Limb Dysfunction
Authors: Wang Chunfang , Chen Yuanyuan , Song Peiqing , Yu Hongli , Du Jingang , Zhang Ying , Sun Changcheng
Published: July 2022

Transcranial direct current stimulation (tDCS) provides a way to modulate the cortical activity and promote motor rehabilitation following stroke. However, evidence indicates that the response to tDCS is highly variable. This study was aimed at exploring rhythmic response of Electroencephalography (EEG) to three tDCS protocols in stroke subjects. We hypothesize that tDCS protocols may interact with stoke characteristics, and electrode placement may affect cortical activity which could be reflected by the EEG rhythm. 32 subjects with unilateral stroke were recruited to a single-blinded, randomized, and controlled crossover experiment. All of the subjects underwent four tDCS protocols (anodal (atDCS), cathodal (ctDCS), and bilateral tDCS (bi-tDCS) and sham) with an interval of at least 1 week. Resting-state EEG was acquired before and after the stimulation. We tested the change of EEG spectral power after tDCS and the difference of change among four protocols using the paired-sample

t

-test and repeated measures analysis of variance. Then, we investigated the clinical factors affecting the above changes using the linear and quadratic regression model. According to the results, EEG responded to atDCS and bi-tDCS protocols on alpha and beta rhythm and subjects with a left lesion had higher response than those with the right lesion. Besides that, the change of alpha and beta power after atDCS and of beta power after bi-tDCS showed association with clinical characteristics only in subjects with the left lesion. In conclusion, the study found varied EEG response with different protocols, lesion hemispheres, and other clinical characteristics supporting the individualized cortical oscillatory effect induced by tDCS.
Prediction of Customer Demand for Hands-On Inquiry-Based Learning (HIBL) Product Based on Big Data Clustering Algorithm
Authors: Bai Xingxing
Published: July 2022

The objective was to identify previously unknown groups in a dataset using various techniques. Significant progress has been made in this field in recent years, resulting in the development of novel and promising clustering algorithms. With the constant advancement of big data technology, research on study tours has also become crucial. Clustering can unearth the potential hidden information in large datasets, thereby facilitating more efficient work. Diverse measures have been proposed to quantify similarity, including the Euclidean distance and data space density. As a result, clustering becomes a multi-objective optimization problem. Clustering algorithms are extensively utilized in data preprocessing, data classification, and big data prediction. In this study, we examine clustering methods for big data from a theoretical perspective to comprehend their correlations across a large number of datasets. In addition, we predicted customer demand for research products using fabricated metrics.
[Retracted] PLK1 Is a Potential Prognostic Factor Associated with the Tumor Microenvironment in Lung Adenocarcinoma
Authors: Wang Lina , Gao Man , Sun Dongjie , Wu Haitao , Lv Shuang , Li Yulin , Li Lisha
Published: July 2022

More than 40% of lung cancers are lung adenocarcinoma (LUAD) worldwide. However, the prognosis of LUAD is poor for the lack of effective treatment methods. Our study identified PLK1 as a novel prognosis biomarker and treatment target for LUAD. Based on the Cancer Genome Atlas (TCGA) database, differentially expressed genes (DEGs) from 551 LUAD cases were analyzed for the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. To explore the biological pathways and the tumor‐infiltrating immune cells (TICs) using gene set variation analysis (GSVA) and the CIBERSORT, as well as to analyze DEGs, a protein‐protein interaction (PPI) network and Cox regression analysis were performed. Validation of DEGs was achieved through quantitative real‐time PCR (qPCR) and immunoblotting. DEGs associated with the cell cycle were sorted out. Cell cycle scores were positively correlated with age, clinical stages, and metastasis and negatively correlated with overall survival of LUAD patients. PPI and Cox analyses showed that PLK1 could be a prognostic factor for LUAD patients. CIBERSORT analysis revealed a positive correlation between the transcription level of PLK1 and the function of CD8+ and activated memory CD4+ T cells, as well as a negative correlation with activated natural killer cells. Furthermore, PLK1 overexpression increased immune cytotoxicity, as measured by the cytolytic activity score, IFN‐ score, and IFN‐ level. There is a strong correlation between PLK1 and key features of TICs, indicating its potential as a promising prognostic biomarker for LUAD.
Phytochemical Classification of Medicinal Plants Used in the Treatment of Kidney Disease Based on Traditional Persian Medicine
Authors: Rabizadeh Fatemeh , Mirian Maryam Sadat , Doosti Rahele , Kiani-Anbouhi Roya , Eftekhari Elahe
Published: July 2022

Background and Objectives. Human beings have used natural products as one of the pharmaceutical sources to improve human health for thousands of years. Phytochemical constituents distributed in different parts of medicinal plants cause therapeutic effects on treatment of acute and chronic diseases. Over the years, traditional Persian medicine has become popular over Iran and some countries globally as a source of alternative therapies of kidney diseases and renal dysfunctions. Iranian herbal medicine consists of natural compounds with complex active ingredients that causes valuable effects. Despite performing research works on traditional Persian medicine in the treatment of kidney disorders, there is still a need to investigate on chemical components and biological molecules of medicinal plants. Methods. This review was focused on studying the various secondary metabolites in model plants of Iranian herbal medicine known as treatment of kidney diseases in traditional Persian medicine textbooks including Makhzan-ol-Advieh, The Canon of Medicine, and Taghvim al-Abdan fi Tadbir al-Ensan. Results. Secondary metabolites of 94 medical plants belonging to 42 families were reported with their scientific and family name. Conclusion. Although herbal medicines are gaining rapid popularity among people and the pharmaceutical industry, the understandings of the phytochemical and therapeutic properties of medicinal plant are important for developing effective nephroprotective medicines. Therefore, the relationship between traditional uses and biological properties should be clearly verified through further studies.
Geographical Discrimination of Ground Amazon Cocoa by Near-Infrared Spectroscopy: Influence of Sample Preparation
Authors: Negrão Ferreira Fabielle , Albuquerque Chagas-Junior Gilson Celso , Santana de Oliveira Mozaniel , Rodrigues Barbosa Jhonatas , Chaves Oliveira Marcos Enê , Santos Lopes Alessandra
Published: July 2022

This work presents the application of the NIR technique associated with exploratory analysis of spectral data by main principal components for the discrimination of Amazon cocoa ground seeds. Cocoa samples from different geographic regions of the state of Pará, Brazil (Medicilândia, Tucumã, and Tomé-Açu), were evaluated. The samples collected from each region were divided into four groups distinguished by the treatment applied to the samples, which were fermented (1-with fat and 2-fat-free) and unfermented (3-with moisture and 4-dried). Each set of samples was analyzed separately to identify the influence of moisture, fermentation, and fat on the geographical differentiation of the three regions. From the results obtained, it can be observed that it was not possible to differentiate the samples of seeds not fermented by geographic origin. However, fermentation was crucial for efficient discrimination, providing more defined clusters for each geographic region. The presence of fat in the seeds was a determinant to obtain the best model of geographic discrimination.
Quality Evaluation of Market Acacia catechu by Fingerprint-Chemical Pattern Recognition
Authors: Gao Leilei , Sun Xiaochen , Mei Meng , Wang Fang , Yang Jun , Peng Huasheng , Zhan Zhilai
Published: July 2022

Acacia catechu (L.f.) Willd, a leguminous plant, is included in the 2020 edition of the Chinese Pharmacopoeia and is mainly used to treat eczema, mouth ulcers, diarrhea, bruising, and traumatic hemorrhage. However, there are imported and domestic Acacia catechu samples available in China, and their quality and price are very different, which seriously affects the safety and stability of their clinical application. Importantly, there is no simple and effective method for identifying or classifying grades of Acacia catechu. In this study, 47 batches of commercial Acacia catechu were used for identifying or classifying grades of Acacia catechu using high performance liquid chromatography (HPLC) combined with chemometric analysis. Firstly, gradient elution was adopted with 0.05% phosphoric acid water (A)-methanol (B) as the mobile phase to establish chromatographic conditions. The HPLC chromatograms of 47 batches of Acacia catechu samples were analyzed by the “Similarity Evaluation System for Chromatographic Fingerprint of TCM” software (version 2012A). The common peaks of Acacia catechu were identified to evaluate the similarity. Based on the determination results of fingerprint chromatographic peak area, the quality of the collected Acacia catechu was evaluated by chemometric methods such as CA, PCA, and OPLS-DA. The results showed that the collected Acacia catechu samples were significantly divided into three categories. The first-class samples were all imported Acacia catechu except S9 sample, which was domestic Acacia catechu; the second-class samples were partly domestic Acacia catechu and partly imported Acacia catechu; and the third-class samples were all domestic Acacia catechu. Moreover, OPLS-DA of 47 batches of samples showed that the contents of catechin and the total contents of catechin and epicatechin could be used as key indicators for assessing the quality of Acacia catechu. The developed HPLC fingerprint and quantitative analysis method of multi-indicator components can be used for classification and quality evaluation of market Acacia catechu, which has a significant reference value for developing Acacia catechu grade quality standards.
Wisdom Homestay Tourism Recommendation Platform and Marketing Strategy Based on Multi-Information Fusion Sensor Network
Authors: Zu Enhou , Shu Ming Hung , Huang Hsiao-Chun , Hsieh Ching-Tang , Huang Jui-Chan
Published: July 2022

At present, China’s tourism market is huge, and traditional hotel accommodation is not popular with young people, and homestays are just in line with young people’s yearning. And most of the current push methods are determined by consumption on large platforms such as Ctrip, which not conforms to the recommendation method of homestays, so it aims at personalized marketing research for homestays. In this paper, the multi-information fusion sensor network is used to push B&B hotels in tourist areas to achieve B&B hotel marketing and maximize profits. Using the multi-information fusion sensor network to carry out personalized platform design, platform users can easily and quickly search for the homestay they want and can realize the automatic push function to achieve the rationality of marketing. The experimental results in this paper found that the average relative speedup increased from 1.9 to 17.7 for the execution of the scoring-oriented algorithm in the algorithm compared to a single computer. Performing the sort-oriented algorithm in the algorithm, the average relative speedup increased from 1.9 to 18.8. It can illustrate the effectiveness of the design system in this paper, and the software can carry out personalized marketing for homestays.
Proteomic Analysis Reveals Molecular Differences in the Development of Gastric Cancer
Authors: Dhondrup Rinchen , Zhang XiaoKang , Feng Xuemei , Lobsang Dhondrup , Hua Qincuo , Liu Junli , Cuo Ying , Zhuoma Sangji , Duojie Geri , Duojie Caidan Suonan , Gyal Samdrup
Published: July 2022

Gastric cancer (GC) is the 3rd leading cause of death from cancer and the 5th most common cancer worldwide. The detection rate of GC among Tibetans is significantly higher than that in Han Chinese, probably due to differences in their living habits, dietary structure, and environment. Despite such a high disease burden, the epidemiology of gastric cancer has not been studied in this population. Molecular markers are required to aid the diagnosis and treatment of GC. In this study, we collected gastric tissue samples from patients in Tibet with chronic nonatrophic gastritis (CNAG) (n = 6), chronic atrophic gastritis (CAG) (n = 7), gastric intraepithelial neoplasia (GIN) (n = 4), and GC (n = 5). The proteins in each group were analyzed using coupled label-free mass spectrometry. In addition, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, and protein interaction networks were used to analyze the differentially expressed proteins (DEPs) among groups. DEPs were quantified in comparisons of GC versus CNAG (223), GC versus GIN (100), and GIN versus CNAG (341). GO and KEGG analyses showed that the DEPs were mainly associated with immunity (GC versus CNAG) and cancer proliferation and metastasis (GC versus GIN, and GIN versus CNAG). Furthermore, the expression levels of cell proliferation and cytoskeleton-related proteins increased consistently during cancer development, such as ITGA4, DDC, and CPT1A; thus, they are potential diagnostic markers. These results obtained by proteomics analysis could improve our understanding of cancer biology in GC and provide a rich resource for data mining and discovering potential immunotherapy targets.
Luminal A Breast Cancer: How Feasible is Omitting Axillary Dissection Without Neoadjuvant Therapy
Authors: Yüksel Cemil , Aksel Bülent , Doğan Lütfi
Published: July 2022

Background. Luminal A breast cancer has a good prognosis and the criteria for adjuvant and neoadjuvant chemotherapy (NAC) are not clear. The aim of this study was to present our results of upfront surgery and long-term survival in luminal A tumors as well as the rates of protection from axillary dissection. Material and Methods. 271 Luminal A breast cancer patients who had operated at our center were evaluated retrospectively. In patients with 2 or less sentinel lymph node (SLN) positivity who did not receive neoadjuvant therapy and underwent breast-conserving surgery, axillary lymph node dissection was omitted (OAD). Axillary lymph node dissection (ALND) was performed in patients with positive SLN who did not meet these criteria (axillary dissection after sentinel/ADAS). Results. While Sentinel Lymph Node Biopsy (SLNB) was performed in 212 (77.9%) patients, SLNB + Axillary Dissection (AD) was performed in 58 (21.3%), and direct axillary dissection was performed in 1 (0.8%) patient. OAD was applied to 18 (23.6%) of the positive patients. Discussion/Conclusions. ALND rates are still strikingly high in luminal A breast cancer treatment, despite the disease’s milder clinical course. In order to avoid complications of axillary dissection, patients should be considered for NAC as much as possible. Novel neoadjuvant or other therapy options are also required.
Characterization of Chemically Treated Sisal Fiber/Polyester Composites
Authors: Adugna Ayalew Adane , Fenta Wodag Awoke
Published: July 2022

Natural fibers have the potential to replace synthetic fibers for making polymer composites due to their remarkable properties. Polyester is one of the core materiel used for textile and leather due to hydrophobic property. Sisal fibers have high strength among various naturals and can be used as the supporting material for polymers. A detailed experimental study was conducted for the extraction of sisal fiber and composite development. The fibers were treated by using 2%, 6%, and 10% NaOH concentrations within 24, 48, and 72 h soaking time. Composite was made from different sisal to polyester ratios of 20 : 80, 30 : 70, and 40 : 60 (w/w). Mechanical properties such as tensile strength and flexural strength of treated, untreated, and reinforced fibers were determined. Functional groups of both the treated and untreated sisal fibers were characterized using Fourier transform infrared spectroscopy (FTIR). The thermal stability of sisal fiber was analyzed by thermogravimetric analysis (TGA). The optimum tensile strength and bending strength of the composite were found at 44.0 MPa and 50.8 MPa for fiber with polyester ratio of 30 : 70, 6% NaOH concentration, and 48 h soaking time. It is confirmed that treated sisal fiber-reinforced polyester composites have better tensile and bending properties and lower water absorption than untreated fibers.
A Real-Time Monitoring and Warning System for Power Grids Based on Edge Computing
Authors: Li Hang , Dong Yongle , Yin Chao , Xi Jia , Bai Luwei , Hui Zhenzhen
Published: July 2022

It is very important for the safe operation of the power grid to be able to achieve real-time online monitoring, but along with the expansion of the smart grid, powerful computing power is required to achieve online monitoring, which cannot be loaded by ordinary servers. Due to the limited computing and storage resources of the server, it is difficult to fully meet the real-time requirements of online power line monitoring. Therefore, this research proposes a smart grid real-time monitoring and early warning system based on edge computing, which can reasonably allocate computing tasks according to the effective use of edge node resources. It can also collect and process information in real time, and can monitor the power grid online, which improves the fault identification efficiency of the power grid, effectively reduces the economic cost, and relieves the computing pressure of the online monitoring equipment on the cloud computing server. Meanwhile, considering the burst problem in allocation queue optimization, a multipriority allocation queue algorithm is proposed, and an improved greedy algorithm allocation model is used to solve the optimal scheduling problem between bursts. Simulation analysis shows that the scheduling scheme proposed in this paper can effectively reduce the monitoring delay of the power line monitoring system, improve the overall adaptability and compatibility of the system, meet the market demand, and facilitate promotion.
Feasibility and Application of Cluster Nursing to the Care of Patients with Acute Oncology
Authors: Song Jun , Fu Lei
Published: July 2022

Objective. To probe the utility of cluster nursing for the care of acute oncology clients. Methods. One hundred fourteen cases of acute oncology pioneers undergoing therapy in our clinic from April 2019 to February 2021 were randomly assigned into two consecutive arms, conventional care and cluster care, in accordance with the nursing modality. Complications, satisfaction, quality of survival, and negative emotions were compared across the two parties. Results. The comorbidity incidence rate of the subject matter in the research cohort was 7.02%, which was below the comorbidity rate of 17.54% in the reaction cohort (

P
<
0.05

); the percentage of satisfaction in the research cohort was 96.49%, which was higher than the satisfaction rate of 78.95% in the reaction cohort (

P
<
0.05

); aftercare, the quality of survival was significantly higher in both groups, and the SAS and SDS scores were significantly lower, with a more pronounced trend of change in the research cohort than in the reaction cohort (

P
<
0.05

). Conclusion. Bundled care for casualty oncology is of major value, with a marked reduction in the incidence of postoperative complications, high quality of survival, an excellent prognosis and negative mood, high patient morale and satisfaction and compliance with curative treatment, and good support for subsequent care.
An Enhanced RFID-Based Authentication Protocol using PUF for Vehicular Cloud Computing
Authors: Kumar Vikas , Kumar Rahul , Jangirala Srinivas , Kumari Saru , Kumar Sachin , Chen Chien-Ming
Published: July 2022

RFID (radio frequency identification) is an Internet of Things (IoT) enabling technology. All physical devices can be connected to the Internet of Things thanks to RFID. When RFID is extensively utilized and fast increasing, security and privacy concerns are unavoidable. Interception, manipulation, and replay of the wireless broadcast channel between the tag and the reader are all possible security threats. Unverified tags or readers provide untrustworthy messages. IoT requires a safe and consistent RFID authentication system. PUFs are also physical one-way functions made up of the unique nanoscopic structure of physical things and their reactivity to random occurrences. PUF includes an unclonable feature that takes advantage of physical characteristics to boost security and resistance to physical attacks. We analyze the security of the RSEAP2 authentication protocol that has been recently proposed by Safkhani et al., a hash-based protocol, and elliptic curve cryptosystem-based protocol. Our security analysis clearly shows important security pitfalls in RSEAP2 such as mutual authentication, session key agreement, and denial-of-service attack. In our proposed work, we improved their scheme and enhanced their version using physically unclonable function (PUF), which are used by the proposed protocol in tags. This research proposes a cloud-based RFID authentication technique that is both efficient and trustworthy. To decrease the RFID tag’s overhead, the suggested authentication approach not only resists the aforementioned typical assaults and preserves the tag’s privacy, but also incorporates the cloud server into the RFID system. According to simulation results, our approach is efficient. Moreover, according to our security study, our protocol can withstand a variety of attacks, including tracking, replay, and desynchronization assaults. Our scheme withstands all the 18 security features and further consumes the computation cost as 14.7088 ms which is comparable with the other schemes. Similarly, our scheme consumes the communication cost as 672 bits during the sending mode and 512 bits during the receiving mode. Overall, the performance of our proposed method is equivalent to that of related schemes and provides additional security features than existing protocols. Mutual authentication, session key generation, and ephemeral session security are all achieved. Using the real-or-random concept, we formalize the security of the proposed protocol.
Smart Teaching Design Mode based on Machine Learning and its Effect Evaluation
Authors: Su Qianqian
Published: July 2022

With the continuous progress of science and technology, the mode of smart teaching is more and more applied in the actual teaching process. Under the intelligent teaching system mode, teachers and students can jointly complete the construction of curriculum resources and classroom teaching tasks. This paper evaluates its application effect by introducing two examples of smart teaching. Among them, the evaluation effect of the academic teaching network system shows that the teaching network system based on machine learning is composed of three parts: model selection, data preparation, and modeling prediction. Moreover, it can greatly improve the prediction performance of the intelligent algorithm in the teaching mode by introducing the oversampling technology SMOTE algorithm (Synthetic Minority Oversampling Technique). To further verify the advantages of the smart teaching model, an example of social sciences teaching is introduced. The results show that the relevant predictive performance indicators in the computer engineering discipline are improved by using a combination of intelligent algorithms.
The Chinese Herbal Formula Huoxiang Zhengqi Dropping Pills Prevents Acute Intestinal Injury Induced by Heatstroke by Increasing the Expression of Claudin-3 in Rats
Authors: Li Yu-Nong , Tao Hui , Hong Jia-Hui , Xiong Ya-Lan , Pan Xi-Chun , Liu Ya , Yang Xue-Sen , Zhang Hai-Gang
Published: July 2022

Intestinal injury has been regarded as an important causative factor for systemic inflammation during heatstroke, and maintaining intestinal integrity has been a potential target for the prevention of HS. Huoxiang Zhengqi Dropping Pills (HZPD) is a modern preparation of Huoxiang Zhengqi and widely used to prevent HS. The present study aims to explore the protective effect of HZDP on intestinal injury during heatstroke and analyze its potential pharmacodynamic basis. Male rats in the control and HS groups were given normal saline, and those in the HZDP groups were given HZDP (0.23, 0.46, and 0.92 g/kg) before induction of HS. Serum contents of tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), intestinal fatty acid-binding protein (iFABP), and diamine oxidase (DAO) were determined using ELISA. Histopathology of intestinal injury was observed following H&E staining. The expression of claudin-3 was determined using western blot, immunohistochemistry, and immunofluorescence techniques. Moreover, network pharmacological tools were used to analyze the potential pharmacodynamic basis and the mechanism of HZDP. Treatment with HZDP significantly prolonged the time to reach Tc. Compared with the control group, the contents of TNF-α, IL-6, iFABP, and DAO in HS rats increased markedly. HZDP treatments reduced these levels significantly, and the effects in the middle dose group (0.46 g/kg) were most obvious. HZDP also attenuated intestinal injury and significantly reversed the decrease in claudin-3 expression. Bioinformatics analysis suggested that 35 active ingredients and 128 target genes of HZDP were screened from TCMSP and 93 target genes intersected with heatstroke target genes, which were considered potential therapeutic targets. TNF-α and IL-6 were the main inflammatory target genes of HZDP correlated with HS. These results indicated that HZDP effectively protected intestinal barrier function and prevented acute intestinal injury by increasing the expression of claudin-3 in rats, eventually improving heat resistance.
Understanding Gene Action, Combining Ability, and Heterosis to Identify Superior Aromatic Rice Hybrids Using Artificial Neural Network
Authors: Sunny Albin , Chakraborty Nihar Ranjan , Kumar Anil , Singh Bhupesh Kumar , Paul Amitava , Maman Shalma , Sebastian Anasooya , Darko Daniel Amoako
Published: July 2022

The aromatic rice represents a smaller but independent rice collection, the quality of which is considered to be highly acceptable. Farmers are interested in growing aromatic rice due to high premium market price. The prime objective of this study was to enhance genetic improvement of aromatic rice. Combining ability analysis (GCA and SCA) and gene action are studied in a set of 7 × 7 half-diallel crosses. Twenty-one hybrids along with their seven parents were assessed in randomized complete block design. Different quantitative characters were used to estimate the magnitude of heterosis. GCA and SCA significance for all traits revealed the importance of both additive and nonadditive genetic components. Several genes determine quantitative traits, with each gene having very little impacts and being easily influenced by environmental factors. Pusa Basmati-1 and Govindobhog were the best combiners among the seven parents. In terms of per se performance, heterosis, and SCA effects on seed yield per plant and important yield qualities, the crosses BM-24 Deharadun Pahari, Baskota × Tulaipanji, and Pusa Basmati-1 × Tulaipanji may be of interest. Because of its interconnected processing properties, ANN can play a critical role in this experiment. As a result, the current study was carried out to collect data and validate it using an artificial neural network (ANN) on the combining ability, gene action, and heterosis involved in the expression of diverse fragrant rice features. Using ANN, the validation of the result was done and it was found that the overall efficiency was approximately 99%.
Clinical Features and Long-Term Outcomes in Very Young Patients with Myocardial Infarction with Non-Obstructive Coronary Arteries
Authors: Juan-Salvadores Pablo , Jiménez Díaz Víctor Alfonso , Rodríguez González de Araujo Ana , Iglesia Carreño Cristina , Guitián González Alba , Veiga Garcia Cesar , Baz Alonso José Antonio , Caamaño Isorna Francisco , Iñiguez Romo Andrés
Published: July 2022

Background. The main cause of acute coronary syndrome (ACS) is coronary artery obstruction due to atherosclerotic plaque growth or thrombus formation secondary to plaque rupture or erosion. However, there is a subgroup of patients with signs and symptoms suggestive of ACS but without relevant coronary artery obstruction on coronary angiography. This population is defined as myocardial infarction with non-obstructive coronary arteries (MINOCA). The present study analyzes the clinical features and outcomes of very young patients with a diagnosis of MINOCA. Method. Nested case-control study of ≤40-year-old patients referred for coronary angiography due to clinical suspicion of ACS. Patients were divided into three groups: patients with obstructive coronary artery disease (CAD), patients diagnosed with MINOCA, and controls with non-coronary artery disease. Results. Of 19,321 coronary angiographies performed in our center in a period of 10 years, 408 (2.1%) were in patients ≤40 years old, and MINOCA was identified in 32 (21%) patients. The cardiovascular risk factors for obstructive CAD and MINOCA were very similar. The incidence of major adverse cardiovascular events (MACE) at follow-up was significantly higher in the MINOCA (HR 4.13 (95%CI 1.22–13.89) and obstructive CAD (HR 4.59 (95%CI 1.90–10.99) patients compared to controls. Cocaine use HR 14.58 (95%CI 3.08–69.02), family history of CAD HR 6.20 (95%CI 1.40–27.43), and depression HR 5.16 (95%CI 1.06–25.24) were associated with a poor outcome in the MINOCA population. Conclusion. Very young patients with MINOCA had a poor prognosis at long-term follow-up, similar to patients with obstructive CAD. Focusing efforts on secondary prevention is essential in this population.
Assessment of Physical Fitness and Health Status of Athletes Based on Intelligent Medical Treatment under Machine Learning
Authors: Tong Yunlong
Published: July 2022

Machine learning is an interdisciplinary study of how to make computer programs perform similar to human learning, and its techniques are widely used in the medical industry. The purpose of this paper is to study how to use machine learning-based intelligent medicine to analyze and study the assessment of athletes’ physique and health status and describe the machine learning algorithm. This paper puts forward the problem of intelligent medical diagnosis, which is based on machine learning, and then elaborates on the concept of machine learning and related algorithms, and designs and analyzes a case of an athlete’s physique monitoring and health status assessment system. The experimental results show that the athlete’s physical fitness monitoring and health status evaluation system can meet the needs of users. The text classification effect based on the LSTM method is slightly inferior to the SVM effect, in which the recall rate of diabetes is not more than 40%, and the recall rate of cerebral infarction is improved by 26.5% after using fuzzy matching.
A key to species of Hercinothrips, with one new species, and a neotype designation for H. trilineatus (Priesner)
Authors: GOLDARACENA ARTURO , VIERBERGEN GIJSBERTUS (BERT)
Published: July 2022

A female neotype from Transvaal, South Africa, is designated for Hercothrips trilineatus Priesner, the original type specimens from Tanzania having been destroyed in Hamburg during the 1940’s. Hercinothrips splendens sp.n. is described from both sexes taken from Aloe plants in a Netherlands greenhouse. A key is provided to the 10 known extant species of Hercinothrips.
A new species of planthopper in the genus Anchimothon (Hemiptera: Auchenorrhyncha: Derbidae) on palms from Costa Rica
Authors: BAHDER BRIAN W. , BARRANTES EDWIN A. , ECHAVARRIA MARCO A. ZUMBADO , HELMICK ERICKA E. , BARTLETT CHARLES R.
Published: July 2022

Anchimothon is a small genus of derbid planthoppers known from Mesoamerica and northern South America. Recent survey efforts in the Caribbean basin have documented many new taxa of fulgoroids from palms. During this survey, a novel taxon identified as Anchimothon was collected from palm seedlings at La Selva Biological Station in Costa Rica. Here, the novel taxon is described as A. myriei sp. n. with molecular data for the cytochrome c oxidase subunit I (COI) and18S rRNA providing support for placement of the new species in Anchimothon. An updated key is provided for the current species of Anchimothon.
Further species and range extensions of Amazonian bryozoans: chipping away at the iceberg
Authors: WOOD TIMOTHY S. , OKAMURA BETH
Published: July 2022

A bryozoan survey conducted in the Amazon Basin in the vicinities of Manaus and Santarém during the high water season (May, 2018) revealed four new species described here: Fredericella adrianoi n. sp., Plumatella divae n. sp., Plumatella hartikainenae n. sp., and Plumatella spencerjonesae n. sp. Two of these species were encountered only once, suggesting that other undescribed species are likely to occur in the area. Range extensions were determined for two additional species: Plumatella pirassununga and Timwoodiellina natans. In addition, colonies were collected for the first time for two species previously known only by their statoblasts: Plumatella siolii and Plumatella marcusi. Statoblasts of Tapajosella elongata were encountered near Manaus, but the colonies remained elusive. The discovery of new species collected during two expeditions to the Amazon Basin in different seasons and years suggests that further diversity remains undetected in this and other poorly studied regions of the world. With few exceptions, plumatellid colonies described so far from the Amazon Basin are very similar in appearance, with branches wholly attached to the substratum and body walls that are soft, colorless, and transparent.
Notes on Stibochiona nicea (Gray, 1846) from China with description of a new subspecies from Hainan Island (Lepidoptera, Nymphalidae)
Authors: LI HUA-ZHAO , LIU ZHE
Published: July 2022

New information of Stibochiona nicea is presented. Stibochiona nicea wangyukunae ssp. nov. is described from Hainan Island, S. China based on wing patterns, and S. nicea subucula is recorded from China for the first time. The adults and the male genitalia of all the three subspecies of N. nicea from China are illustrated.
Recent Issues in Politics, Preamble and Constitution of India: An Overview
Authors: Kumar Abhinav
Published: July 2022

When India is marching to celebrate seventy-five years of Independence, Indian politics has undergone several changes. India has seen one-party dominance, the Emergency period, multi-party alliances, a crisis to the Constitution and much more. Many political parties and socio-political movements have come and gone through the passage of time. Many new streams of thoughts, personalities and movements have emerged. But whatever exists now owes its existence to the legacy of the previous years. Hence, it is necessary to understand and have a general idea of politics of post-colonial India.

This article seeks to draw an overview of the political history of India since its Independence up to the current period; from the Congress System after Independence, to the Emergency period under Indira Gandhi, and finally the surge and dominance of the BJP in 2014 and 2019. Focus would be laid on major issues and debates of the respective periods: Current political issues, such as the Citizenship Amendment Act, protests over the farm laws and other issues have raised the debate on the wording of the Preamble and the rights guaranteed by the Constitution of India.
Impact of COVID-19 Pandemic on Postgraduate Psychiatry Teaching- Learning and Evaluation in India: A Nationwide Survey
Authors: Deshmukh Deepanjali , Patil Anuradha V. , Deore Rajrajeshwar , Bhise Manik C.
Published: July 2022

Background:

COVID-19 pandemic had disrupted postgraduate (PG) medical education in India. This study aimed to assess PG teaching, learning, evaluation (TLE), and innovative TLE methods used during the pandemic.

Methods:

We conducted a cross-sectional survey using Google Forms to seek anonymous responses from psychiatry teachers across India. Information about PG TLE, postings in COVID-19 care units, methods of teaching adopted in different settings, difficulties faced, and methods of evaluation used were sought in responses. Descriptive statistics methods were used for analysis.

Results:

The pandemic led to compromised TLE opportunities for the students. Posting of students and teachers in COVID-19 wards for an average of 15 months, students and teachers getting COVID-19, conversion of psychiatry wards to COVID-19 wards, and reduced number of outpatients and inpatients impaired the teaching-learning opportunities. For examination, the evaluation was done with limited standards, like using dummy patients or case vignettes. A few innovative TLE methods were also used during the pandemic.

Conclusions:

COVID-19 pandemic had led to sub-optimal PG TLE. Teachers suggested many alternative and flexible TLE methods and platforms.