bluuebunny/crossref_metadata_2025 huggingface dataset:
Prospective multicentre randomised clinical trial comparing survival rates, quality of life and nutritional status between advanced gastric cancer patients with different follow-up intensities: study protocol for the STOFOLUP trial
Authors: Eom Bang Wool , Koo Dong-Hoe , An Ji Yeong , Lee Han Hong , Kim Hyoung-Il , Hur Hoon , Yoo Moon-Won , Ryu Min-Hee , Lee Hyuk-Joon , Kim Su Mi , Park Ji-Ho , Min Jae Seok , Seo Kyung Won , Jeong Sang-Ho , Jeong Oh , Kwon Oh Kyoung , Ryu Seung Wan , Yoo Chang Hak , Bae Jae Moon , Ryu Keun Won
Published: December 2021

Introduction

Patients who underwent curative gastrectomy for gastric cancer are regularly followed-up for the early detection of recurrence and postoperative symptom management. However, there is a lack of evidence with regard to proper surveillance intervals and diagnostic tools. This study aims to evaluate whether frequent surveillance tests have a survival benefit or improve the quality of life in patients who underwent curative resection for advanced gastric cancer.

Methods and analysis

The STOFOLUP trial is an investigator-initiated, parallel-assigned, multicentre randomised controlled trial involving 16 hospitals in the Republic of Korea. Patients (n=886) diagnosed with pathological stage II or III gastric adenocarcinoma will be randomised to either the 3-month or the 6-month group at a 1:1 ratio, stratified by trial site and tumour stage. Patients allocated to the 3-month group will undergo an abdominal CT scan every 3 months postoperatively and those allocated to the 6-month group will undergo CT every 6 months. The primary endpoint is 3-year overall survival and the secondary endpoints are quality of life, as assessed using KOrean QUality of life in Stomach cancer patients Study group-40, the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 and the stomach cancer-specific module (STO22), and nutritional outcomes. Other survival data including data concerning 3-year disease-free survival, recurrence-free survival, gastric cancer-specific survival and postrecurrence survival will also be estimated. The first patient was enrolled on July 2021 and active patient enrolment is currently underway.

Ethics and dissemination

This study has been approved by the Institutional Review Board of eight of the participating hospitals (NCC 2021-0085, KBSMC2021-01-059, SMC 2021-01-140, KC21OEDE0082, 4-2021-0281, AJIRB-MED-INT-20-608, 2021-0515 and H-2102-093-1198). This study will be disseminated through peer-reviewed publications, national or international conferences.

Trial registration number

NCT04740346.
Coping in patients with pancreatic cancer: a scoping review and narrative synthesis
Authors: Ristau Patrick , Oetting-Roß Claudia , Büscher Andreas
Published: December 2021

Introduction

Pancreatic cancer is a malignant disease with one of the highest cancer-specific mortality rates. Coping with it probably differs from other malignant diseases. This scoping review was intended to explore and characterise academic literature related to the coping in patients with pancreatic cancer.

Methods

Eight databases were searched for primary and secondary studies and reviews reporting on coping with pancreatic cancer (adenocarcinoma) in adults in English or German language, regardless of publication date or study design, which were then analysed and summarised by narrative synthesis.

Results

Of 1472 publications identified, 9 articles and book contributions published from 1989 to 2020 in the USA, Europe and Australia met the inclusion criteria. The two main aspects covered were the confrontation with coping tasks, and the reciprocally associated coping with these challenges. In particular, the coping tasks revealed some pancreatic cancer-specific features, such as an increased incidence of depression and anxiety or certain digestive problems, whereas applying of coping strategies seems to be more like the coping behaviours known from the literature for other severe or cancer diseases.

Conclusions

Patients with pancreatic cancer experience various health issues and face various quality of life changes and coping tasks. Disease-specific contextual factors, usually consisting of late diagnosis at an advanced stage, rapid progression and often poor prognosis, as well as disease-specific challenges are major differences compared with other malignancies or serious illnesses. However, the coping strategies applied do not seem to differ in principle. Currently, no pancreatic cancer-specific coping model exists.
Occupational risk of SARS-CoV-2 infection and reinfection during the second pandemic surge: a cohort study
Authors: Leidi Antonio , Berner Amandine , Dumont Roxane , Dubos Richard , Koegler Flora , Piumatti Giovanni , Vuilleumier Nicolas , Kaiser Laurent , Balavoine Jean-François , Trono Didier , Pittet Didier , Chappuis François , Kherad Omar , Courvoisier Delphine Sophie , Azman Andrew S , Zaballa Maria Eugenia , Guessous Idris , Stringhini Silvia
Published: December 2021

Objectives

This cohort study including essential workers, assessed the risk and incidence of SARS-CoV-2 infection during the second surge of COVID-19 according to baseline serostatus and occupational sector.

Methods

Essential workers were selected from a seroprevalence survey cohort in Geneva, Switzerland and were linked to a state centralised registry compiling SARS-CoV-2 infections. Primary outcome was the incidence of virologically confirmed infections from serological assessment (between May and September 2020) to 25 January 2021, according to baseline antibody status and stratified by three predefined occupational groups (occupations requiring sustained physical proximity, involving brief regular contact or others).

Results

10 457 essential workers were included (occupations requiring sustained physical proximity accounted for 3057 individuals, those involving regular brief contact, 3645 and 3755 workers were classified under ‘Other essential occupations’). After a follow-up period of over 27 weeks, 5 (0.6%) seropositive and 830 (8.5%) seronegative individuals had a positive SARS-CoV-2 test, with an incidence rate of 0.2 (95% CI 0.1 to 0.6) and 3.2 (95% CI 2.9 to 3.4) cases per person-week, respectively. Incidences were similar across occupational groups. Seropositive essential workers had a 93% reduction in the hazard (HR of 0.07, 95% CI 0.03 to 0.17) of having a positive test during the follow-up with no significant between-occupational group difference.

Conclusions

A 10-fold reduction in the hazard of being virologically tested positive was observed among anti-SARS-CoV-2 seropositive essential workers regardless of their sector of occupation, confirming the seroprotective effect of a previous SARS-CoV2 exposure at least 6 months after infection.
Dietary diversity score is inversely related to the risk of polycystic ovary syndrome in Tehranian women: a case-control study
Authors: Soodi Sahel , Keshavarz Seyed Ali , Hosseini Sedighe , Abbasi Behnood
Published: December 2021

Polycystic ovary syndrome (PCOS) is the most common endocrine disorder among women of reproductive age and is affected by various dietary factors. Therefore, this study aimed to investigate the relationship between dietary diversity score (DDS) and the risk of PCOS. Our case-control study was conducted in the summer and autumn of 2019 in Taleghani and Arash hospitals in Tehran, Iran. A total of 494 participants (203 cases and 291 controls) were included in the study. Thereafter, their demographic information, dietary intake, and anthropometric and physical activity assessments were gathered. A validated semi-quantitative food frequency questionnaire was then used to calculate the DDS by scoring 5 food groups. To evaluate the risk of PCOS in association with DDS, the subjects were categorized based on the quartile cut-off points of the DDS. The mean ± SD age of the participants in both the case and control groups was 28.98 ± 5.43 and 30.15 ± 6.21 years, while mean ± SD body mass index was 25.74 ± 5.44 and 23.65 ± 3.90 kg/m2, respectively. The comparison between the case and control groups indicated that total DDS was 5.19 ± 1.19 for the cases and 5.51 ± 1.19 for the controls. The comparison of DDS in the highest versus the lowest quartiles showed a decreased risk of PCOS (p < 0.05). We demonstrated an inverse association between DDS and PCOS compared with the control group. Furthermore, a higher DDS was significantly associated with a lower risk of PCOS (odds ratio = 0.40).

Novelty: This is the first investigation on the relationship between DDS and PCOS. Results depicted an inverse relationship between DDS and PCOS.
Quasinormal modes of a massive scalar field nonminimally coupled to gravity in the spacetime of self-dual black hole
Authors: Santos J. S. , Cruz M. B. , Brito F. A.
Published: December 2021

In this work, we investigate the quasinormal modes for a massive scalar field with a nonminimal coupling with gravity in the spacetime of a loop quantum black hole, known as the self-dual black hole. In this way, we have calculated the characteristic frequencies using the 3rd order WKB approach, where we can verify a strong dependence with the mass of scalar field, the parameter of nonminimal coupling with gravity, and parameters of the loop quantum gravity. From our results, we can check that the self-dual black hole is stable under the scalar perturbations when assuming small values for the parameters. Also, such results tell us that the quasinormal modes assume different values for the cases where the mass of field is null and the nonminimal coupling assumes $$\xi =0$$

ξ
=
0

and $$\xi =1/6$$

ξ
=
1
/
6

, i.e., a possible breaking of the conformal invariance can be seen in the context of loop quantum black holes.
Neutrino interaction physics in neutrino telescopes
Authors: Katori Teppei , Yanez Juan Pablo , Yuan Tianlu
Published: December 2021

Neutrino telescopes can observe neutrino interactions starting at GeV energies by sampling a small fraction of the Cherenkov radiation produced by charged secondary particles. These experiments instrument volumes massive enough to collect substantial samples of neutrinos up to the TeV scale as well as small samples at the PeV scale. This unique ability of neutrino telescopes has been exploited to study the properties of neutrino interactions across energies that cannot be accessed with man-made beams. Here, we present the methods and results obtained by IceCube, the most mature neutrino telescope in operation, and offer a glimpse of what the future holds in this field.
Recent highlights from GENIE v3
Authors: Alvarez-Ruso Luis , Andreopoulos Costas , Ashkenazi Adi , Barry Christopher , Dennis Steve , Dytman Steve , Gallagher Hugh , Soto Alfonso Andres Garcia , Gardiner Steven , Giele Walter , Hatcher Robert , Hen Or , Jiang Libo , Kakorin Igor D. , Kuzmin Konstantin S. , Meregaglia Anselmo , Naumov Vadim A. , Papadopoulou Afroditi , Roda Marco , Syrotenko Vladyslav , Tena-Vidal Júlia , Wolcott Jeremy , Wright Natalie , Kabirnezhad Monireh , Vololoniaina Narisoa
Published: December 2021

The release of GENIE v3.0.0 was a major milestone in the long history of the GENIE project, delivering several alternative comprehensive neutrino interaction models, improved charged-lepton scattering simulations, a range of beyond the Standard Model simulation capabilities, improved experimental interfaces, expanded core framework capabilities, and advanced new frameworks for the global analysis of neutrino scattering data and tuning of neutrino interaction models. Steady progress continued following the release of GENIE v3.0.0. New tools and a large number of new physics models, comprehensive model configurations, and tunes have been made publicly available and planned for release in v3.2.0. This article highlights some of the most recent technical and physics developments in the GENIE v3 series.
Hyperspherical Variational Co-embedding for Attributed Networks
Authors: Fang Jinyuan , Liang Shangsong , Meng Zaiqiao , De Rijke Maarten
Published: December 2021

Network-based information has been widely explored and exploited in the information retrieval literature. Attributed networks, consisting of nodes, edges as well as attributes describing properties of nodes, are a basic type of network-based data, and are especially useful for many applications. Examples include user profiling in social networks and item recommendation in user-item purchase networks. Learning useful and expressive representations of entities in attributed networks can provide more effective building blocks to down-stream network-based tasks such as link prediction and attribute inference. Practically, input features of attributed networks are normalized as unit directional vectors. However, most network embedding techniques ignore thesphericalnature of inputs and focus on learning representations in a Gaussian or Euclidean space, which, we hypothesize, might lead to less effective representations. To obtain more effective representations of attributed networks, we investigate the problem of mapping an attributed network with unit normalized directional features into a non-Gaussian and non-Euclidean space. Specifically, we propose a hyperspherical variational co-embedding for attributed networks (HCAN), which is based on generalized variational auto-encoders for heterogeneous data with multiple types of entities. HCAN jointly learns latent embeddings for both nodes and attributes in a unified hyperspherical space such that the affinities between nodes and attributes can be captured effectively. We argue that this is a crucial feature in many real-world applications of attributed networks. Previous Gaussian network embedding algorithms break the assumption of uninformative prior, which leads to unstable results and poor performance. In contrast, HCAN embeds nodes and attributes as von Mises-Fisher distributions, and allows one to capture the uncertainty of the inferred representations. Experimental results on eight datasets show that HCAN yields better performance in a number of applications compared with nine state-of-the-art baselines.
On the Electrochemical Insertion of Mg2+in Na7V4(P2O7)4(PO4) and Na3V2(PO4)3 Host Materials
Authors: Dongmo Saustin , Maroni Fabio , Gauckler Cornelius , Marinaro Mario , Wohlfahrt-Mehrens Margret
Published: December 2021

Next generation energy storage technologies need to be more sustainable and cheaper. Among Post-Li chemistries, Mg batteries are emerging as a possible alternative with desirable features like abundance of Mg on the Earth’s crust and a doubled volumetric capacity with respect to the current Li metal. However, research and development of Mg-batteries is still in its infancy stage and still many hurdles are to be understood and solved. For instance, cathode materials showing high capacities, operating at high potentials and with sufficient fast kinetics need to be designed and developed. Polyanionic materials are a class of sustainable and environmentally friendly that emerged as possible Mg2+ hosts. In this work the insertion of Mg cations inside the NASICON Na3V2(PO4)3 and, for the first time, in the mixed phosphate phase Na7V4(P2O7)4(PO4), is reported, structurally and electrochemically characterized.
Lysyl oxidase regulation and protein aldehydes in the injured newborn lung
Authors: Zhong Ying , Mahoney Rose C. , Khatun Zehedina , Chen Howard H. , Nguyen Christopher T. , Caravan Peter , Roberts Jesse D.
Published: December 2021

During newborn lung injury, excessive activity of lysyl oxidases (LOXs) disrupts extracellular matrix (ECM) formation. Previous studies indicate that TGFβ activation in the O2-injured mouse pup lung increases lysyl oxidase (LOX) expression. But how TGFβ regulates this, and whether the LOXs generate excess pulmonary aldehydes are unknown. First, we determined that O2-mediated lung injury increases LOX protein expression in TGFβ-stimulated pup lung interstitial fibroblasts. This regulation appeared to be direct; this is because TGFβ treatment also increased LOX protein expression in isolated pup lung fibroblasts. Then using a fibroblast cell line, we determined that TGFβ stimulates LOX expression at a transcriptional level via Smad2/3-dependent signaling. LOX is translated as a pro-protein that requires secretion and extracellular cleavage before assuming amine oxidase activity and, in some cells, reuptake with nuclear localization. We found that pro-LOX is processed in the newborn mouse pup lung. Also, O2-mediated injury was determined to increase pro-LOX secretion and nuclear LOX immunoreactivity particularly in areas populated with interstitial fibroblasts and exhibiting malformed ECM. Then, using molecular probes, we detected increased aldehyde levels in vivo in O2-injured pup lungs, which mapped to areas of increased pro-LOX secretion in lung sections. Increased activity of LOXs plays a critical role in the aldehyde generation; an inhibitor of LOXs prevented the elevation of aldehydes in the O2-injured pup lung. These results reveal new mechanisms of TGFβ and LOX in newborn lung disease and suggest that aldehyde-reactive probes might have utility in sensing the activation of LOXs in vivo during lung injury.
Antenatal mesenchymal stromal cell extracellular vesicle treatment preserves lung development in a model of bronchopulmonary dysplasia due to chorioamnionitis
Authors: Abele Alison N. , Taglauer Elizabeth S. , Almeda Maricar , Wilson Noah , Abikoye Abigail , Seedorf Gregory J. , Mitsialis S. Alex , Kourembanas Stella , Abman Steven H.
Published: December 2021

Antenatal stressors such as chorioamnionitis (CA) increase the risk for bronchopulmonary dysplasia (BPD). Studies have shown that experimental BPD can be ameliorated by postnatal treatment with mesenchymal stromal cell-derived extracellular vesicles (MEx). However, the antenatal efficacy of MEx to prevent BPD is unknown. To determine whether antenatal MEx therapy attenuates intrauterine inflammation and preserves lung growth in a rat model of CA-induced BPD. At embryonic day ( E) 20, rat litters were treated with intra-amniotic injections of saline, endotoxin (ETX) to model chorioamnionitis, MEx, or ETX plus MEx followed by cesarean section delivery with placental harvest at E22. Placental and lung evaluations were conducted at day 0 and day 14, respectively. To assess the effects of ETX and MEx on lung growth in vitro, E15 lung explants were imaged for distal branching. Placental tissues from ETX-exposed pregnancies showed increased expression of inflammatory markers NLRP-3 and IL-1ß and altered spiral artery morphology. In addition, infant rats exposed to intrauterine ETX had reduced alveolarization and pulmonary vessel density (PVD), increased right ventricular hypertrophy (RVH), and decreased lung mechanics. Intrauterine MEx therapy of ETX-exposed pups reduced inflammatory cytokines, normalized spiral artery architecture, and preserved distal lung growth and mechanics. In vitro studies showed that MEx treatment enhanced distal lung branching and increased VEGF and SPC gene expression. Antenatal MEx treatment preserved distal lung growth and reduced intrauterine inflammation in a model of CA-induced BPD. We speculate that MEx may provide a novel therapeutic strategy to prevent BPD due to antenatal inflammation.
Prediction and enrichment analyses of the Homo sapiens-Drosophila melanogaster COPD-related orthologs: potential for modeling of human COPD genomic responses with the fruit fly
Authors: Rouka Erasmia , Gourgoulianni Natalia , Lüpold Stefan , Hatzoglou Chrissi , Gourgoulianis Konstantinos I. , Zarogiannis Sotirios G.
Published: December 2021

The significant similarities in airway epithelial cells between mammals and the fruit fly Drosophila melanogaster have rendered the latter an important model organism for studies of chronic inflammatory lung diseases. Focusing on the chronic obstructive pulmonary disease (COPD), we here mapped human gene orthologs associated with this disease in D. melanogaster to identify functionally equivalent genes for immediate, further screening with the fruit fly model. The DIOPT-DIST tool was accessed for the prediction of the COPD-associated orthologs between humans and Drosophila. Enrichment analyses with respect to pathways of the retrieved functional homologs were performed using the ToppFun and FlyMine tools, identifying 73 unique human genes as well as 438 fruit fly genes. The ToppFun analysis verified that the human gene list is associated with COPD phenotypes. Furthermore, the FlyMine investigation highlighted that the Drosophila genes are functionally connected mainly with the “ABC-family proteins mediated transport” and the “β-catenin-independent WNT signaling pathway.” These results suggest an evolutionarily conserved role toward responses to inhaled toxicants and CO2 in both species. We reason that the predicted orthologous genes should be further studied in the Drosophila models of cigarette smoke-induced COPD.
Multiweight Cross-Multimedia Logistics Optimal Path Exploration by Integrating High-Dimensional Deep Learning
Authors: Zhang Huiying , Guo Jinjin , Sun Guie
Published: December 2021

High-dimensional deep learning has been applied in all walks of life at present, among which the most representative one is the logistics path optimization combining multimedia with high-dimensional deep learning. Using multimedia logistics to explore and operate the best path can make the whole logistics industry get innovation and leap forward. How to use high-dimensional deep learning to conduct visual logistics operation management is an opportunity and a problem facing the whole logistics industry at present. The application of high-dimensional deep learning technology can help logistics enterprises improve their management level, realize intelligent decision-making, and enable accurate prediction. Starting from the total amount of logistics, regional layout, enterprise scale, and high-dimensional deep learning algorithm, this paper analyzes the current situation of China’s logistic development through multiweight analysis and explores the best path for multimedia logistics.
The Choice of Multimodal Transport Mode of Agricultural By‐Product Logistics in Land‐Sea New Corridor in Western China Based on Big Data
Authors: Chen Xing , Liu Ziyu
Published: December 2021

The “new land‐sea corridor” has brought cross‐border facilitation and increased trade financing channels. It not only has long been a road‐sea transportation corridor but also has been upgraded to a trade corridor. As one of the most inclusive cities, Chongqing, with the help of this channel, can bring more dividends and international resources to the entire western region. Through the logistics base of Singaporean‐Chongqing cooperation in multimodal transport, Chongqing can play an important role as a channel operation center and an important logistics hub. Some international shipping resources will be extended to Chongqing, letting the whole western region share the agricultural by‐products brought by Southeast Asian countries. Multimodal transport is a common mode of transport in international trade; it combines various modes of transport organically, brings into play the advantages of various modes of transport, and can reduce costs to a large extent. At present, multimodal transport is mostly used for importing and exporting goods; multimodal transport is not widely used in agricultural by‐product logistics transportation. Multimodal combination will be used in the transportation of agricultural by‐product logistics; it can avoid the shortcomings of simply using road transportation and make the logistics transportation cost of agricultural by‐products lower and management more convenient. Based on the large data, this paper considers factors such as route factors, transfer mode selection, and window meeting time in the transfer process; a mathematical model and advanced colony ant algorithm can be used to solve the transfer optimization problem of a very large fleet of agricultural by‐product logistics. This solution can provide instructions and suggestions for companies that should increase relevant scientific research.
Blood Pressure Model Based on Hybrid Feature Convolution Neural Network in Promoting Rehabilitation of Patients with Hypertensive Intracerebral Hemorrhage
Authors: Zheng Zhixia , Bai Limei , Li Shaoquan
Published: December 2021

Objective. Accurate prediction of the rise of blood pressure is essential for the hypertensive intracerebral hemorrhage. This study uses the hybrid feature convolution neural network to establish the blood pressure model instead of the traditional method of pulse waves. Methods. The pulse waves of 100 patients were collected, and the pulse wave was decomposed into three bell wave compound forms to obtain the accurate pulse wave propagation time. Then, the mixed feature convolution neural network model ABP-net was proposed, which combined the pulse wave propagation time characteristics with the pulse wave waveform characteristics automatically extracted by one-dimensional convolution to predict the arterial blood pressure. Finally, according to the prediction results, 20 patients were treated before the high blood pressure appeared (model group), and another 20 patients with a daily fixed treatment scheme were selected as the control group. Results. In 80 training sets, compared with linear regression and the random forest method, the hybrid feature convolution neural network has higher accuracy in predicting blood pressure. In 20 test sets, the blood pressure error was eliminated within 5 mmHg. The total effective rate in the model group and the control group was 95.0% and 85.0%, respectively (

P
=
0.035

). After treatment, the scores of self-care ability of daily life and limb motor function in the model group were higher than those in the control group (

P
<
0.05

). There were 8 cases (13.6%) in the model group and 17 cases (28.3%) in the control group due to the recurrence of cerebrovascular accident (

P
=
0.043

). Conclusion. Drug treatment guided by a blood pressure model based on a hybrid feature convolution neural network for patients with hypertensive cerebral hemorrhage can significantly and smoothly reduce blood pressure, promote the health recovery, and reduce the occurrence of cerebrovascular accidents.
A Blockchain-Integrated Divided-Block Sparse Matrix Transformation Differential Privacy Data Publishing Model
Authors: Hong Yiyang , Zhao Xingwen , Zhu Hui , Li Hui
Published: December 2021

With the rapid development of information technology, people benefit more and more from big data. At the same time, it becomes a great concern that how to obtain optimal outputs from big data publishing and sharing management while protecting privacy. Many researchers seek to realize differential privacy protection in massive high-dimensional datasets using the method of principal component analysis. However, these algorithms are inefficient in processing and do not take into account the different privacy protection needs of each attribute in high-dimensional datasets. To address the above problem, we design a Divided-block Sparse Matrix Transformation Differential Privacy Data Publishing Algorithm (DSMT-DP). In this algorithm, different levels of privacy budget parameters are assigned to different attributes according to the required privacy protection level of each attribute, taking into account the privacy protection needs of different levels of attributes. Meanwhile, the use of the divided-block scheme and the sparse matrix transformation scheme can improve the computational efficiency of the principal component analysis method for handling large amounts of high-dimensional sensitive data, and we demonstrate that the proposed algorithm satisfies differential privacy. Our experimental results show that the mean square error of the proposed algorithm is smaller than the traditional differential privacy algorithm with the same privacy parameters, and the computational efficiency can be improved. Further, we combine this algorithm with blockchain and propose an Efficient Privacy Data Publishing and Sharing Model based on the blockchain. Publishing and sharing private data on this model not only resist strong background knowledge attacks from adversaries outside the system but also prevent stealing and tampering of data by not-completely-honest participants inside the system.
Research on Precision Cultivation of Digital Multimedia Crop Based on Predictive Computational Intelligence Technology
Authors: Lin Yuke , Zhang Ying
Published: December 2021

With the intersection and integration of modern crop cultivation and emerging disciplines, crop cultivation management is moving from traditional modeling and standardization to quantitative and intelligent direction. Crop precision cultivation technology is to apply system science and information technology to crop cultivation and digitally design information perception of the objects and processes involved in crop cultivation, dynamic simulation, so as to realize the quantification and accuracy of crop cultivation management. With the integration and intersection of modern digital multimedia crop cultivation and emerging disciplines, digital multimedia crop cultivation tends to gradually implement the quantitative and intelligent development, replacing the traditional scale and standardization. The technology of digital multimedia crop cultivation is to use science and information technology in digital multimedia crops to achieve the quantitative and precise characteristics of digital multimedia crop cultivation. The advancement of digital multimedia crop cultivation technology has greatly improved the management and benefits of the entire agricultural industry and has played a positive role in the development of agricultural information and modernity.
Is It Possible to Earn Abnormal Return in an Inefficient Market? An Approach Based on Machine Learning in Stock Trading
Authors: Khoa Bui Thanh , Huynh Tran Trong
Published: December 2021

Risk management and stock investment decision‐making is an essential topic for investors and fund managers, especially in the context of the COVID‐19 pandemic. The problem becomes easier if the market is efficient, where stock prices fully reflect potential risk. Nevertheless, if the market is not efficient, investors may have an opportunity to find an effective investment method. Vietnam is one of the emerging markets; the efficiency is still weak. Thus, there will be an opportunity for astute investors. This study aims to test the weak‐form efficient market and provide a modern approach to investors’ decision‐making. To achieve that aim, this study uses historical data of stocks in the VN‐Index and VN30 portfolio to buy and sell within a one‐day period under the rolling window approach to test the Ho Chi Minh City Stock Exchange (HoSE) through a runs test and to perform stock trading using the support vector machine (SVM) and logistic regression. The buying/selling of stocks is guided by the forecasted outcomes (increase/decrease) of logistic regression and SVM. This study adjusted the return rate in proportion to the risks and compared it with index investments of VN‐Index and VN30 to evaluate investment efficiency. The test results dismissed the weak‐form efficient‐market hypothesis, which opens up many opportunities for short‐term traders. This study’s primary contribution is to provide a stock trading strategy for short‐term investors to maximize trading profits. Because logistic regression and SVM have proven effective trading methods, investors can use them to achieve abnormal returns.
Isolation and Identification of Infection-Causing Bacteria in Dairy Animals and Determination of Their Antibiogram
Authors: Arbab Safia , Ullah Hanif , Wang Weiwei , Li Ka , Akbar Ali , Zhang Jiyu
Published: December 2021

Pathogens are always a threat to the livestock and domestic animals due to their exposure to the contaminated environments. The study was conducted to evaluation of the prevalence of Escherichia coli, Shigella spp., Salmonella spp., and S. aureus, in farm animals (cattle and buffalos). A total of 150 (n = 150) samples were collected from cattle and buffaloes, 60 samples from cows’ and buffalo’s teats milk, 30 of water samples, and 60 of fecal samples isolates from dairy farm animals, which may act as reservoir disseminating such pathogens. Farm hygiene, management, and milking procedure were listed through a questionnaire. The most common pathogens detected in this study was E. coli 88 (58%) and S. aureus 81 (54%), followed by Salmonella spp. 32 (21%), and Shigella spp. 44 (29%), respectively. During the antibiogram studies, the results revealed that the highest number of bacterial isolates showed resistance against ampicillin 50 (56.8%), followed by ciprofloxacin 23 (26.1%) and augmentin 22 (25%) of Escherichia coli and ampicillin 49 (60.4%), cefpodoxime 23 (28.3%), and augmentin 20 (24.6%) of S. aureus. In the case of Salmonella spp., the highest resistance was showed by amoxicillin 16 (50%). In Shigella spp., the highest resistance was shown by ampicillin 16 (36.3%), followed by cefpodoxime and ceftazidime 10 (22.7%). The high frequency of isolates in this investigation with multiple antibiotic resistance ranges from 15. MARI % value of S. aureus and E. coli 15 (12.5%), followed by Salmonella and Shigella spp. ranges from 12 (10%), suggesting the presence of various antibiotic-resistant bacteria as well as highly resistant bacteria. The mean ± SD zone areas for the greater resistance are for E. coli and S. aureus, already known to be multiresistant, followed by Salmonella spp. and Shigella spp., when the zone areas are for the low resistance, and the findings determined that there was a little difference between S. aureus and E. coli.
Research on Application Adaptability of Big Data and IoT in Discipline Construction of Mechanical Engineering Specialty in Universities
Authors: Wang Chunxia , Xie Jian
Published: December 2021

With Industry 4.0 and another round of scientific and technological reform and development, industrial reform and development, the latest economic development, and the escalating complexity of the upcoming problems faced by human beings all over the world, there is an urgent need for cross-compounding between disciplines and disciplines, resulting in emerging engineering majors. In response to these situations, the article analyzes the characteristics, necessity, and main problems faced by the construction and talent cultivation of emerging engineering majors with multidisciplinary cross-composite and discusses the new initiatives of building emerging engineering majors with multidisciplinary cross-composite and innovative talent cultivation to encourage the cultivation of brave exploration and innovation, cultivate innovative talents with unique insights, and promote innovation and breakthroughs in economic, social, and scientific and technological development needs. Finally, the article takes mechanical and electronic engineering as an example to explore how the crossover and integration between several important aspects of the construction of emerging engineering majors are effectively carried out in order to provide certain reference and reference for the construction of related emerging engineering disciplines and majors.
Analytical Investigation of Noyes–Field Model for Time‐Fractional Belousov–Zhabotinsky Reaction
Authors: Alaoui Mohammed Kbiri , Fayyaz Rabia , Khan Adnan , Shah Rasool , Abdo Mohammed S.
Published: December 2021

In this article, we find the solution of time‐fractional Belousov–Zhabotinskii reaction by implementing two well‐known analytical techniques. The proposed methods are the modified form of the Adomian decomposition method and homotopy perturbation method with Yang transform. In Caputo manner, the fractional derivative is used. The solution we obtained is in the form of series which helps in investigating the analytical solution of the time‐fractional Belousov–Zhabotinskii (B‐Z) system. To verify the accuracy of the proposed methods, an illustrative example is taken, and through graphs, the solution is shown. Also, the fractional‐order and integer‐order solutions are compared with the help of graphs which are easy to understand. It has been verified that the solution obtained by using the given approaches has the desired rate of convergence to the exact solution. The proposed technique’s principal benefit is the low amount of calculations required. It can also be used to solve fractional‐order physical problems in a variety of domains.
Application of Different Modelling Methods to Arbitrate Various Hydrological Attributes Using CMORPH and TRMM Satellite Data in Upper Omo-Gibe Basin of Ethiopia
Authors: Koshuma Abera Ermias , Debebe Yegelilaw Eyesus , Dasho Defaru Katise , Lohani Tarun Kumar
Published: December 2021

Rainfall is a basic input parameter for hydrological modelling that exerts a great influence on the dependability of hydrological simulations. Limited availability of accurate and reliable precipitation data in Abelti watershed of Omo Gibe basin of Ethiopia coerces to use satellite rainfall data to design watershed management practices. The primary objective of this research is to find a better output by comparing and evaluating Climate Prediction Centre Morphing techniques (CMORPH) and Tropical Rainfall Measuring Mission (TRMM). Satellite precipitation products (SPPs) and inputs were incorporated to simulate stream flow. Sensitivity and uncertainty analysis, calibration, and validation of the model were conducted using Soil and Water Assessment Tool (SWAT), Calibration and Uncertainty Program 2012 (SWAT-CUP-2012), particularly the Sequential/Uncertainty Fitting (SUFI-2) algorithm for all rainfall inputs independently. The calibration and validation period was taken as 2003–2010 and 2011–2018, respectively. On the basis of the modelling results of SWAT and uncertainty analysis, TRRM relatively performed well than that of CMORPH. The result illustrated that the SWAT model thoroughly predicted the catchment runoff simulation for all SPPs. However, TRMM-based simulations capture the shape of the observed stream flow hydrograph, and there was slight under and overestimation of the stream flow volume simulated SPPs followed by the reduction of model performance statistics. Bias-corrected satellite rainfall-based simulations significantly improved the model performance as well as the volume of stream flow simulated. The detail study exhibited that the in situ-based simulation outperformed satellite products in terms of the objective functions in the study area.
An Application of Possibilistic Moments of Nonlinear Type of Fuzzy Numbers in Supply Chain Management
Authors: Appadoo Srimantoorao S. , Gajpal Yuvraj , Kumar Amit
Published: December 2021

The supply chain (SC) network is prone to disturbance due to various uncertainties associated with their subsystems. The COVID-19 outbreak has exposed the global vulnerability of the supply chain network. The current pandemic has severely affected almost every SC network because its members are situated at the international level. One of the reasons for SC network failure is the deterministic assumptions of different parameters. A realistic SC network model requires the use of the uncertain value of the parameters, which can be further captured by fuzzy numbers. This paper discusses the possibilistic moment of several nonlinear types of fuzzy numbers that are important for SC network modeling. We give closed-form possibilistic moments’ expression for various types of fuzzy numbers that are very similar to the moment’s properties in probability theory and stochastic process. We then illustrate the application of proposed fuzzy numbers by solving an inventory model. This paper also provides results related to the EPQ inventory model in a fuzzy possibilistic setup.
Micromedia News Dissemination Impact Assessment Integrated with Personalized Recommendation Algorithm
Authors: Guo Shaofang
Published: December 2021

The development of the Internet has completely changed the way of recommending and disseminating news content. Traditional media forms of news dissemination effectiveness evaluation methods are no longer fully suitable for the evolving needs of new media news dissemination. Therefore, it is necessary to innovate methods for evaluating the effects of new media news dissemination. This article mainly combines personalized recommendation algorithms to evaluate the effectiveness of news dissemination. Currently, popular personalized recommendation algorithms include content-based recommendation algorithms, collaborative filtering recommendation algorithms, knowledge-based recommendation algorithms, and associated recommendation algorithms. These recommendation algorithms are effective. This promotes the dissemination of news, which also recommends news content that is more relevant to user preferences for most users. In addition, the quality of news content is further evaluated through the news rating system, thereby effectively improving the quality of news content.
Synthesis and Spectral Characterisation of (E)-3-(3-(4 (Dimethylamino)Phenyl)Acrylo-yl)-4-Hydroxy-2H-Chromen-2-One and Their Antibacterial Activity and Acetylcholinesterase Inhibition
Authors: Slimani Ichraf , Hamdi Naceur , Al-Hazmy Sadeq M. , Alhagri Ibrahim A. , Ebeid El-Zeiny M. , Okba Ehab A.
Published: December 2021

A new coumarin derivative, (E)-3-(3-(4-(dimethylamino) phenyl) acrylo-yl)-4-hydroxy-2H-chromen-2-one (3), was synthesized by the condensation of 3-acetyl-4-hydroxycoumarin (1) with 4-N,N-dimethylaminobenzaldehyde (2) in the presence of piperidine in ethanol. The structure of the synthesized compound was characterized using spectroscopic data (IR and 1H NMR) and elemental analysis. The antimicrobial properties and acetylcholinesterase inhibition activity (AChEI) of coumarin 3 were investigated, with the highest observed AChEI activity providing 48.25% inhibition. The electronic absorption and emission spectra revealed that 3 exists as two, main keto-enol tautomers. The ratios of these tautomers in both protic and aprotic solvents with different polarities and dielectric constants were calculated. The fluorescence of coumarin 3 was enhanced upon increasing the medium viscosity, which was due to the resultant molecular rigidity. This criterion was further investigated using DNA, whereby 3 showed enhanced fluorescence upon its uptake in DNA grooves and was therefore tested as a novel DNA fluorescent stain.
Analysis and Recognition Based on Citrus Color Grading Model considering Computer Vision Technology
Authors: Deng Jianxun
Published: December 2021

With the continuous advancement of smart agriculture, the introduction of robots for intelligent harvesting in modern agriculture is one of the crucial methods for the picking of fruits, vegetables, and melons. In this paper, three different illuminations, including front lighting, normal lighting, and back lighting, are first applied to citrus based on the computer vision technology. Secondly, the image data of the fruits, fruit stems, and leaves of the citrus are collected. The color component distributions of citrus based on different color models are analyzed according to the corresponding characteristic values, and an exploratory data analysis process for the image data of citrus is established. In addition, 300 citrus images are selected, and the citrus fruits are segmented from the background through the simulation experiment. The results of the study indicate that the recognition rate for the maturity of citrus has exceeded 98%, which has proved the effectiveness of the method proposed in this paper.
A Basketball Technique Balance Control Technology Based on Ant Colony Algorithm
Authors: Wang Yong , Du Yongxin
Published: December 2021

Aiming at the problems of low accuracy, poor stability, and effect of balance control in the current basketball skill balance control process, a basketball skill balance control method based on ant colony algorithm is proposed. The principle and characteristics of ant colony algorithm are analyzed, the mathematical model of ant colony algorithm is established, and the implementation steps of ant colony algorithm are given. According to the balance and stability control principle of basketball skills, this paper constructs the balance and stability control model of basketball skills. By establishing the knee-ankle-foot joint analysis model and using the ant colony algorithm, the basketball movement path is constructed. Through the fitness function, select the basketball motion path nodes and update the pheromone, obtain the relationship between the internal stress and displacement of the body under different force directions, and obtain the influence law of the effective knee joint stress with the varus and internal rotation, so as to achieve the balance and stability of the basketball skills sexual control analysis. The experimental results show that the proposed method has better stability and effect of basketball technique balance control and can effectively improve the accuracy of basketball technique balance control.
An Analysis of Computer-Aided Design Software Course Teaching in Visual Communication Design Major by Integrating Grey Variable Weight Clustering Evaluation Model
Authors: Zhang Hong , Wu Chenhui
Published: December 2021

Computer-aided design software course has become a compulsory course for visual communication design specialty in many colleges and universities, but there are some problems in its development, such as boring classroom, lack of specialty, weak practice, and single assessment. Due to the inaccuracy of data in the teaching process of traditional CAD software course, this paper puts forward an innovative educational model of CAD software course in visual communication design major. Visual communication design major carries out the career planning of college students under the background of Internet +, comprehensively analyzes the employment situation of college students from the career planning introduction, on the basis of exploring the current situation of computer-aided design software course education in China, and analyzes the curriculum reform of this major students’ career planning.
Predictors and Utilization of Health Institution Services for Childbirth among Mothers in a Southern Nigerian City
Authors: Arogundade Kazeem , Sampson June , Boath Elizabeth , Akpan Ubong , Olatoregun Olaposi , Femi-Pius Oluwayemisi , Orjih Jude , Afirima Barinaadaa , Umar Nasir
Published: December 2021

Background. Poor maternal health indices, including high maternal mortality, are among Nigeria’s major public health problems. Most of these deaths can be prevented by timely access and utilization of maternity healthcare services by women. Aim/Objective. This study seeks to identify factors affecting the utilization of health facilities for the delivery of babies among mothers in Calabar, Cross River State, Nigeria. Methodology. The study was a community-based cross-sectional study. A structured questionnaire was administered to 422 women of reproductive age residents in the study area who had given birth at least once within the last five years prior to the survey using a multistage random sampling technique. Data generated were entered, coded, and analyzed using Statistical Packages for Social Sciences (SPSS version 22.0), and results were presented in tables and charts. Chi-squared tests and multiple logistic regression were used for the identification of variables associated with health facility-based delivery. Result. The mean age of respondents was 27.3 years (SD = 8.4). Fifty-two percent of the respondents utilized the health facility for delivery, 89.6% attended at least one antenatal clinic (ANC), and 18.9% completed at least 3 ANC sessions. There was a statistically significant association between health facility delivery and marital status (

P
=
0.007

), education (

P
=
0.042

), and family size (

P
=
0.002

). Older women (OR = 0.7, CI = 0.169–3.714), Christians (OR = 1.9, CI = 0.093–41.1), divorcees (OR = 3.7, CI = 0.00–0.00), and respondents who registered early (first trimester) for ANC (OR = 4.9, CI = 0.78–31.48) were found to be higher users of delivery services at the health facility. Conclusion. Community health intervention focusing on improving the knowledge and awareness of the significance of utilizing available delivery services at the healthcare facility should be developed and implemented.