bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of subanaesthetic S-ketamine on postoperative delirium and cognitive function in elderly patients undergoing non-cardiac thoracic surgery: a protocol for a randomised, double-blinded, placebo-controlled and positive-controlled, non-inferiority trial (SKED trial)
Authors: Wei Wei , Zhang Anyu , Liu Lv , Zheng Xi , Tang Chunlin , Zhou Ming , Gu Yu , Yao Yonghua
Published: August 2022

Introduction

Postoperative delirium (POD) is a common and distressing complication after thoracic surgery. S-ketamine has neuroprotective properties as a dissociative anaesthetic. Emerging literature has indicated that S-ketamine can reduce cognitive impairment in patients with depression. However, the role of S-ketamine in preventing POD remains unknown. Therefore, this study aims to evaluate the effect of intraoperative prophylactic S-ketamine compared with that of dexmedetomidine on the incidence of POD in elderly patients undergoing non-cardiac thoracic surgery.

Methods and analysis

This will be a randomised, double-blinded, placebo-controlled, positive-controlled, non-inferiority trial that enrolled patients aged 60–90 years undergoing thoracic surgery. The patients will be randomly allocated in a ratio of 1:1:1 to S-ketamine, dexmedetomidine or normal saline placebo groups using computer-generated randomisation with a block size of six. The primary outcome will be the incidence of POD within 4 days after surgery and this will be assessed using a 3-Minute Diagnostic Confusion Assessment Method two times per day. The severity and duration of POD, the incidence of emergence delirium, postoperative pain, quality of sleep, cognitive function, and the plasma concentrations of acetylcholine, brain-derived neurotrophic factor, tumour necrosis factor-α and incidence of adverse events will be evaluated as secondary outcomes.

Ethics and dissemination

Ethical approval has been obtained from the Institutional Review Board of the Cancer Hospital and the Institute of Guangzhou Medical University (ZN202119). At the end of the trial, we commit to making a public disclosure available, regardless of the outcome. The public disclosure will include a publication in an appropriate journal and an oral presentation at academic meetings.

Trial registration number

ChiCTR2100052750 (NCT05242692).
Narrative synthesis systematic review of Pakistani women’s health outcomes from primary care interventions
Authors: Rizvi Jafree Sara , Mahmood Qaisar Khalid , Sohail Malik Muhammad , Asim Muhammad , Barlow Jane
Published: August 2022

Objective

Women living in Pakistan have complex health problems including infectious and non-communicable diseases, accident and injuries, and mental health problems. While a majority of these women rely on primary healthcare services for all of their healthcare needs, there has to date been no overview of the extent of their effectiveness. The objective of this review was to (1) synthesise the available evidence regarding the effectiveness of primary care based interventions aimed at improving women’s mental and physical health and (2) identify the factors that promote effectiveness for women’s health outcomes.

Methods

Five academic databases were searched, including PubMed, BMC Medicine, Medline, CINAHL and the Cochrane Library. A search was also made of the grey literature. The quality of included studies was assessed using a standardised critical appraisal tool, and the findings summarised using a narrative synthesis.

Results

In total, 18 studies were included in the review. Eight involved evaluations of counselling interventions, three health education and awareness interventions, two social and psychosocial interventions, and five were evaluations of combination interventions. Twelve of the included studies were randomised controlled trials. Of these 14 reported significant outcomes, and 4 further interventions showed partially favourable results. However, interventions mostly targeted women’s mental or reproductive health.

Conclusions

While the evidence is limited in terms of quality and what has been evaluated, a number of interventions appear to be effective in improving outcomes for women. The three key approaches include the adoption of an active door-to-door and group-based approach; utilisation of community peers who can deliver care cost-effectively and who are more accepted in the community; and the integration of financial vouchers to support uptake in poor populations.

PROSPERO registration number

CRD42020203472.
Strengthening emergency care systems to improve patient care for ST-elevation myocardial infarction (STEMI) at a high-volume tertiary care centre in India
Authors: Gopinath Bharath , Kumar Akshay , Sah Rajesh , Bhoi Sanjeev , Jamshed Nayer , Ekka Meera , Aggarwal Praveen , Deorari Ashok , Bhargava Balram , Kappagantu Vignan
Published: August 2022

Background

ST-elevation myocardial infarction (STEMI) is a highly time-sensitive and life-threatening condition. Early recognition and timely management are challenging in a busy emergency department (ED), especially in low/middle-income countries where emergency systems are often fragmented. The aim of our quality improvement (QI) project was to increase the percentage of patients with STEMI undergoing primary percutaneous coronary intervention (PCI) with door to balloon (D2B) time of <90 min by 30% over 12 months.

Methods

As part of the first step in QI, baseline data were collected at different points in the process of care. Using process maps and fishbone analysis, delays in patient registration, ECG and communication with cardiology were identified as some bottlenecks, and change ideas were tested using plan–do–study–act cycles using point-of-care QI methodology. The majority of the change ideas focused on interventions in the ED like strengthening triage, training frontline staff, early diagnosis and quick transportation of patients.

Results

During the baseline phase, 22.22% of patients were found to have a D2B time of <90 min. We achieved an increase of 47.78% in patients receiving PCI within 90 min and hence increased to 70% at the end of the intervention phase. Data collected for 4 months after the intervention phase were found to have sustained the effort.

Conclusion

Significant improvement in the door to reperfusion time resulted from a meticulous assessment of emergency care processes by drawing process flow chart and implementation of change ideas like introduction of fast-track policy for patients with chest pain, reducing staff turnover in the triage area, formal training of staff, continuous engagement with cardiology team and by interchanging of processes which led to a reduction in time to ECG.
SWITCHING BETWEEN TWO LOSING STOCKS MAY ENABLE PARADOXICAL WIN: AN EMPIRICAL ANALYSIS
Authors: WEN TAO , LAI JOEL WEIJIA , CHEONG KANG HAO
Published: August 2022

Finding strategies to profit from the stock markets is a topic of immense interest to both institutional and retail investors. Possible methods range from machine learning, time series prediction, and network science to game theory. Game theory is a useful mathematical tool to model the relationship between agents and the stocks. In this paper, we ask an important question: Why do some (non-optimal) traders end up winning despite alternating between losing stocks? Our empirical observations reveal that by using a switching strategy abstractly derived from the switching in Parrondo’s paradox, we can demonstrate that losing stocks can be combined in a time-based switching scheme to achieve a winning outcome. This is akin to an automatic investment plan. Several stocks within a given time period are being analyzed. Our analysis may provide a descriptive explanation for why some traders end up winning despite switching between losing stocks. However, it is not the focus of this paper to provide any normative advice or support for switching between stocks.
THE BACKBONE OF THE FINANCIAL INTERACTION NETWORK USING A MAXIMUM ENTROPY DISTRIBUTION
Authors: VALLE MAURICIO A. , URBINA FELIPE
Published: August 2022

We modeled the stocks of the financial system as a set of many interacting like spins derived from binary daily returns. From the empirical observation of these returns, we used a Boltzmann machine to infer a distribution of states equivalent to a maximum entropy distribution. This model describes the interaction couplings between each stock pair in the system, which can be considered a complete network with [Formula: see text][Formula: see text]1)/2 couplings. We then engage in a coupling removal process to find a critical graph that can describe the observed states of the system with the minimum number of edges. We interpret the critical graph as the backbone of the system, and it allows us to evaluate the importance of markets in their relation to others in the system. We also found that the structure of this critical graph is highly variable over time and appears to be dependent on the level of entropy of the system.
An introduction to dirings
Authors: Biyogmam G. R. , Nganou J. B. , Tchamna S.
Published: August 2022

In this paper, we introduce the notion of diring as a generalization of rings and digroups. We treat basic properties of dirings and provide several examples. In addition, several notions of ring theory such as ideals and homomorphisms are considered in the newly introduced framework. Finally, we construct Leibniz algebra and quasi-Jordan algebra structures on non-commutative algebras by using diring operations.
A Portfolio Model of Quantitative Easing
Authors: Christensen Jens H. E. , Krogstrup Signe
Published: August 2022

This paper presents a portfolio model of asset price effects arising from central bank large-scale asset purchases, or quantitative easing (QE). Two financial frictions — segmentation of the market for central bank reserves and imperfect asset substitutability — give rise to two distinct portfolio effects. One is well known and derives from the reduced supply of the purchased assets. The other is new, runs through banks’ portfolio responses to reserves expansions, and is independent of the types of assets purchased. The results imply that central bank reserve expansions can affect long-term bond prices even in the absence of long-term bond purchases.
Pharmacogenetics of Antiplatelet Therapy
Authors: Castrichini Matteo , Luzum Jasmine A. , Pereira Naveen
Published: August 2022

Antiplatelet therapy is used in the treatment of patients with acute coronary syndromes, stroke, and those undergoing percutaneous coronary intervention. Clopidogrel is the most widely used antiplatelet P2Y12 inhibitor in clinical practice. Genetic variation in CYP2C19 may influence its enzymatic activity, resulting in individuals who are carriers of loss-of-function CYP2C19 alleles and thus have reduced active clopidogrel metabolites, high on-treatment platelet reactivity, and increased ischemic risk. Prospective studies have examined the utility of CYP2C19 genetic testing to guide antiplatelet therapy, and more recently published meta-analyses suggest that pharmacogenetics represents a key treatment strategy to individualize antiplatelet therapy. Rapid genetic tests, including bedside genotyping platforms that are validated and have high reproducibility, are available to guide selection of P2Y12 inhibitors in clinical practice. The aim of this review is to provide an overview of the background and rationale for the role of a guided antiplatelet approach to enhance patient care.
The steep uphill path leading to ex vivo gene therapy for genodermatoses
Authors: Palamenghi Michele , De Luca Michele , De Rosa Laura
Published: August 2022

Cell therapy, gene therapy, and tissue engineering have the potential to revolutionize the field of regenerative medicine. In particular, gene therapy is understood as the therapeutical correction of mutated genes by addition of a correct copy of the gene or site-specific gene modifications. Gene correction of somatic stem cells sustaining renewing tissues is critical to ensure long-term clinical success of ex vivo gene therapy. To date, remarkable clinical outcomes arose from combined ex vivo cell and gene therapy of different genetic diseases, such as immunodeficiencies and genodermatoses. Despite the efforts of researchers around the world, only a few of these advanced approaches have yet made it to routine therapy. In fact, gene therapy poses one of the greatest technical challenges in modern medicine, spanning safety and efficacy issues, regulatory constraints, registration and market access, all of which need to be addressed to make the therapy available to patients with rare disease. In this review, we survey some of the main challenges in the development of combined cell and gene therapy of genetic skin diseases.
Hypoxia-inducible factor as a bridge between healthy barrier function, wound healing, and fibrosis
Authors: Steiner Calen A. , Cartwright Ian M. , Taylor Cormac T. , Colgan Sean P.
Published: August 2022

The healthy mammalian intestine is lined by a single layer of epithelial cells. These cells provide a selectively permeable barrier to luminal contents and normally do so in an efficient and effective manner. Barrier function in the healthy mucosa is provided via several mechanisms including epithelial junctional complexes, mucus production, as well as mucosal-derived antimicrobial proteins. As tissue metabolism is central to the maintenance of homeostasis in the mucosa, intestinal [Formula: see text] levels are uniquely low due to counter-current blood flow and the presence of the microbiota, resulting in the stabilization of the transcription factor hypoxia-inducible factor (HIF). Ongoing studies have revealed that HIF molds normal intestinal metabolism and is central to the coordination of barrier regulation during both homeostasis and active disease. During acute inflammation, HIF is central to controlling the rapid restitution of the epithelium consistent with normal wound healing responses. In contrast, HIF may also contribute to the fibrostenotic response associated with chronic, nonresolving inflammation. As such, HIF may function as a double-edged sword in the overall course of the inflammatory response. Here, we review recent literature on the contribution of HIF to mucosal barrier function, wound healing, and fibrosis.
Interleukin 6 mediated activation of the mineralocorticoid receptor in the aldosterone-sensitive distal nephron
Authors: Wynne Brandi M. , Samson Trinity K. , Moyer Hayley C. , van Elst Henrieke J. , Moseley Auriel S. , Hecht Gillian , Paul Oishi , Al-Khalili Otor , Gomez-Sanchez Celso , Ko Benjamin , Eaton Douglas C. , Hoover Robert S.
Published: August 2022

Hypertension is characterized by increased sodium (Na+) reabsorption along the aldosterone-sensitive distal nephron (ASDN) as well as chronic systemic inflammation. Interleukin-6 (IL-6) is thought to be a mediator of this inflammatory process. Interestingly, increased Na+ reabsorption within the ASDN does not always correlate with increases in aldosterone (Aldo), the primary hormone that modulates Na+ reabsorption via the mineralocorticoid receptor (MR). Thus, understanding how increased ASDN Na+ reabsorption may occur independent of Aldo stimulation is critical. Here, we show that IL-6 can activate the MR by activating Rac1 and stimulating the generation of reactive oxygen species (ROS) with a consequent increase in thiazide-sensitive Na+ uptake. Using an in vitro model of the distal convoluted tubule (DCT2), mDCT15 cells, we observed nuclear translocation of eGFP-tagged MR after IL-6 treatment. To confirm the activation of downstream transcription factors, mDCT15 cells were transfected with mineralocorticoid response element (MRE)-luciferase reporter constructs; then treated with vehicle, Aldo, or IL-6. Aldosterone or IL-6 treatment increased luciferase activity that was reversed with MR antagonist cotreatment, but IL-6 treatment was reversed by Rac1 inhibition or ROS reduction. In both mDCT15 and mpkCCD cells, IL-6 increased amiloride-sensitive transepithelial Na+ current. ROS and IL-6 increased 22Na+ uptake via the thiazide-sensitive sodium chloride cotransporter (NCC). These results are the first to demonstrate that IL-6 can activate the MR resulting in MRE activation and that IL-6 increases NCC-mediated Na+ reabsorption, providing evidence for an alternative mechanism for stimulating ASDN Na+ uptake during conditions where Aldo-mediated MR stimulation may not occur.
A Real-Time UWB Location and Tracking System Based on TWR-TDOA Estimation and a Simplified MPGA Layout Optimization
Authors: Zhu Yanping , Huang Lei , Liu Jing , Cao Zhongkang , Chen Jinli , Mu Zijian
Published: August 2022

This article designs and implements a 3D moving target positioning and tracking system by using ultrawideband (UWB) technology. The result of the two-way ranging by the time difference of arrival (TWR-TDOA) positioning algorithm is adopted to result in a new resolution that is to resolve the hyperbolic equations. The proposed algorithm is applied to outdoor and indoor scenarios. To minimize the effect of the sensor layout, this article proposes a simplified multi-population genetic algorithm (MPGA) to obtain the optimum distribution of anchors, which can rapidly reduce the number of search iterations. To resolve the low stability of the TDOA algorithm in outdoor and indoor scenarios, the Kalman filter algorithm is utilized to improve the stability and positioning accuracy of this system and a good simulation effect is achieved. The test results show that the system’s positioning error is far less than that of using other methods. The whole system has a feature of high precision, high stability, low complexity, and low cost.
Core Technology Optimization of Intelligent Financial Technology Based on Collaborative Filtering Algorithm in Big Data Environment
Authors: Hou Xiaohua
Published: August 2022

With the improvement of people’s economic level, people pay more attention to financial investment. At present, the financial industry provides customers with a variety of investment services, but it has always been unable to provide targeted services for customers. Based on this, this paper studies the optimization of intelligent financial technology core technology based on collaborative filtering algorithm in the big data environment. On the basis of a simple analysis of the application of financial core technology and the research status of collaborative filtering algorithm, this paper constructs an application model of intelligent financial collaborative filtering algorithm. In view of the shortcomings of collaborative filtering algorithm, it uses user-based clustering algorithm to improve the collaborative filtering algorithm. According to the frequency of customers’ access to financial products, the attention model is established and simulated. The results show that the collaborative filtering optimization algorithm used in this paper can reduce the absolute error of recommendation and improve the accuracy.
Optimization of College English Teaching Plan under the Background of Micro-Video and Big Data
Authors: Zhou Xue
Published: August 2022

English education has gained greater popularity due to the demands of international economy as well as international politics. College English education is also a part of national English education. However, the English education mode in colleges and universities has certain defects, and it still adopts traditional English education methods to impart knowledge to college students. This limits the interest of college students in learning English. The class hours and assessment mode of English education in colleges and universities limit the time for English learning in colleges and universities, which is also one of the reasons for the disadvantages of college English. Today, with the development of information technology, college English education should consider more technological elements to improve quality of English education in colleges and universities. Micro-video technology is a kind of video with interactive and real-time characteristics, which can be free from geographical restrictions. There are also many English education videos in the micro-video technology, which has a richer background of English knowledge and local customs. This research uses micro-video technology to assist English class level in universities. This research also considers big data theory to extract relevant features in micro-video technology to improve level of college English education. The research results show that micro-video technology can improve learning interest of English students in colleges and universities. CNN and LSTM methods can better predict student grades, student performance characteristics, and teacher performance characteristics. The hybrid CNN-LSTM algorithm has higher accuracy in predicting relevant features of college English teaching compared to the single CNN method. This also shows that the micro-video technology has great temporal characteristics in English teaching. This is a friendly study for improving the quality of English teaching.
Metaheuristics Method for Classification and Prediction of Student Performance Using Machine Learning Predictors
Authors: Kamal Mustafa , Chakrabarti Sudakshina , Ramirez-Asis Edwin , Asís-López Maximiliano , Allauca-Castillo Wendy , Kumar Tribhuwan , Sanchez Domenic T. , Rahmani Abdul Wahab
Published: August 2022

Over the last few decades, there has been a gradual deterioration in higher education in all three areas: the academic setting (both staff and students), as well as research and development output (including graduates). All colleges and universities are essentially focused on improving management decision-making and educating pupils. High-quality higher education can be obtained through a variety of methods. One method is to accurately forecast pupils’ achievement in their chosen educational context. There are numerous prediction models from which to pick. While it is unclear whether there are any markers that can predict whether a kid will be an academic genius, a dropout, or an average performer, the researcher reports student achievement. This article presents a metaheuristics and machine learning-based method for the classification and prediction of student performance. Firstly, features are selected using a relief algorithm. Machine learning classifiers such as BPNN, RF, and NB are used to classify student academic performance data. BPNN is having better accuracy for classification and prediction of student academic performance.
Towards Generating Adversarial Examples on Combined Systems of Automatic Speaker Verification and Spoofing Countermeasure
Authors: Zhang Xingyu , Zhang Xiongwei , Zou Xia , Liu Haibo , Sun Meng
Published: August 2022

The security of unprotected automatic speaker verification (ASV) system is vulnerable to a variety of spoofing attacks where an attacker (adversary) disguises him/herself as a specific targeted user. It is a common practice to use spoofing countermeasure (CM) to improve the security of ASV systems so as to avoid illegal access. However, recent studies have shown that both ASV and CM systems are vulnerable to adversarial attacks. Previous researches mainly focus on adversarial attacks on a single ASV or CM system. But in practical scenarios, ASVs are typically deployed in conjunction with CM. In this paper, we investigate attacking the tandem system of ASV and CM with adversarial examples. The joint objective function is designed to restrict the generating process of adversarial examples. The joint gradient of the ASV and CM system is derived to generate adversarial examples. Fast Gradient Sign Method (FSGM) and Projected Gradient Descent (PGD) are utilized to study the vulnerability of tandem verification systems against white-box adversarial attacks. Through our attack, audio samples whose original labels are spoof or nontarget can be successfully accepted by the tandem system. Experimental results on the ASVSpoof2019 dataset show that the tandem system is vulnerable to our proposed attack.
Helicobacter pylori Thioredoxin1 May Play a Highly Pathogenic Role via the IL6/STAT3 Pathway
Authors: Guo Yanlei , Ding Shigang
Published: August 2022

Background. Recent studies have shown that CagA is considered highly pathogenic to helicobacter pylori (HP) in Western populations. However, in East Asia, CagA positive HP can be up to 90%, but not all patients will lead to gastric cancer. Our research group has found that HP thioredoxin1 (Trx1) may be a marker of high pathogenicity. Here, we investigate whether HP Trx1 exerts high pathogenicity and its internal molecular mechanism. Materials and Methods. We constructed the coculture system of high-Trx1 HP and low-Trx1 HP strains with gastric epithelial cell lines separately and detected the influence of HP strains. The cells were stained by AM/PI, and the cell’s mortality was assessed by fluorescence microscope. The cell’s supernatants or precipitates were collected to detect the expression of IL6. In addition, the cell’s precipitates were collected, and the expression of p-STAT3 was detected by western blot. Furthermore, the cell’s supernatants were collected for detecting the expression of 8-OHDG to investigate the extent of DNA damage. Results. The high-Trx1 HP can cause higher mortality of GES-1 cells compared with the low-Trx1 HP group (high-Trx1 HP (

4.53
±
0.56

) %, low-Trx1 HP (

0.39
±
0.10

) %,

P
<
0.001

). The mRNA and protein level of IL-6 in AGS and GES-1 cells were increased during HP infection, and the expression of IL-6 in the High-Trx1 HP group was much higher than the low-Trx1 HP group. Besides, the expression of p-STAT3 was higher in the HP-positive gastric mucosa. And the expression of p-STAT3 in the high-Trx1 HP group was significantly upregulated compared with the low-Trx1 HP group. Furthermore, the expression of 8-OHDG in the high-Trx1 group was much higher than the low-Trx1 group (high-Trx1 HP (

5.47
±
1.73

) ng/ml, low-Trx1 HP (

2.89
±
1.72

) ng/ml,

P
<
0.05

). Conclusion. HP Trx1 may play as a marker of high pathogenicity, and the high-Trx1 HP could mediate the pathogenic process of HP infection via the IL6/STAT3 pathway.
Intervention Algorithm of Horse Racing for Students’ Psychological Disorders Based on Big Data
Authors: Qin Meng , Gui Quanan
Published: August 2022

Horse racing is a competitive activity in which humans control horses. It is a worldwide traditional sports activity. In the history of human-horse racing, horse racing activities in various eras have been followed but also constantly innovated. According to the K-means clustering algorithm, a cluster analysis model is constructed for the model, and the algorithm model is applied to the students’ mental health counseling work. After six iterations to get the classification and six iterations of the cluster center algorithm, it was found that the mixed psychological population accounted for 50%. Horse racing can not only effectively relieve students’ psychological problems and exercise students’ willpower and thinking ability, but also promote traditional sports. Through K-means clustering algorithm research, frame design, and program design, a complete psychological disorder intervention system is established, which provides scientific, objective, and reliable data guarantee for the correct implementation of decision-making strategies. Integrating cluster analysis into the process of students’ mental health analysis makes it easier for decision-makers to understand and master all aspects of students’ information, to analyze and customize solutions for different types of students. It provides a good foundation for providing different psychotherapeutic methods for different groups of students.
Effectiveness of VR Technology Based on Artificial Intelligence and Big Data in Overcoming Psychological Barriers in Taekwondo Practical Learning
Authors: Guo Pengjv
Published: August 2022

With the rapid development of modern society, a series of emerging technologies such as big data technology, artificial intelligence technology, and cloud computing have also developed rapidly. Among them, artificial intelligence is an important part of computer bionics. It is widely used in the research and analysis of virtual reality. These technologies have effectively assisted modern classroom teaching. In Taekwondo learning, students are easy to encounter some difficult problems, including fear of competition and other psychological obstacles. This study developed a new idea to study these psychological disorders by using the combination of artificial intelligence, big data analysis, and VR technology. The experimental results show that when learners are in the virtual situation created by VR technology, their learning and interactive experiences have been greatly optimized and their learning skills have been greatly improved. They are no longer so afraid of this sport, but they also eliminate their fear of this sports competition, to achieve the ultimate goal of overcoming psychological obstacles. Experiments show that the VR teaching mode based on artificial intelligence and big data technology has its own uniqueness, which can effectively help Taekwondo players overcome the psychological obstacles they encounter in the process of actual combat, and the anxiety and fear indexes of the players decreased by 12.5% and 11.5%, respectively.
A Multi-Level Fuzzy Comprehensive Evaluation Method for Knowledge Transfer Efficiency in Innovation Cluster
Authors: Zhang Xiaoli , Xu Rui
Published: August 2022

Knowledge transfer is the essential requirement for innovation clusters to carry out collaborative innovation, and it is a necessary process for innovation clusters to realize the knowledge value enhancement. The evaluation of knowledge transfer efficiency in innovation cluster can effectively reflect the knowledge gap, environment, and whether it is effectively coordinated among members of the innovation cluster. In order to evaluate the knowledge transfer efficiency in innovation clusters more scientifically and accurately, this paper analyzes the main factors affecting the efficiency of knowledge transfer based on the characteristics of innovation clusters and establishes a multi-level comprehensive evaluation system including knowledge transfer subject features, knowledge content features, knowledge transfer environment, and knowledge transfer coordination behavior. Furthermore, a set of AHP-Entropy index weight determination method and multi-level fuzzy comprehensive evaluation method are proposed to evaluate the knowledge transfer efficiency in innovation cluster. The results of the case study show that the evaluation system and method of knowledge transfer efficiency established in this paper are effective, and they can provide valuable reference for the management of knowledge transfer activities in innovation clusters.
Olive Disease Classification Based on Vision Transformer and CNN Models
Authors: Alshammari Hamoud , Gasmi Karim , Ben Ltaifa Ibtihel , Krichen Moez , Ben Ammar Lassaad , Mahmood Mahmood A.
Published: August 2022

It has been noted that disease detection approaches based on deep learning are becoming increasingly important in artificial intelligence-based research in the field of agriculture. Studies conducted in this area are not at the level that is desirable due to the diversity of plant species and the regional characteristics of many of these species. Although numerous researchers have studied diseases on plant leaves, it is undeniable that timely diagnosis of diseases on olive leaves remains a difficult task. It is estimated that people have been cultivating olive trees for 6000 years, making it one of the most useful and profitable fruit trees in history. Symptoms that appear on infected leaves can vary from one plant to another or even between individual leaves on the same plant. Because olive groves are susceptible to a variety of pathogens, including bacterial blight, olive knot, Aculus olearius, and olive peacock spot, it has been difficult to develop an effective olive disease detection algorithm. For this reason, we developed a unique deep ensemble learning strategy that combines the convolutional neural network model with vision transformer model. The goal of this method is to detect and classify diseases that can affect olive leaves. In addition, binary and multiclassification systems based on deep convolutional models were used to categorize olive leaf disease. The results are encouraging and show how effectively CNN and vision transformer models can be used together. Our model outperformed the other models with an accuracy of about 96% for multiclass classification and 97% for binary classification, as shown by the experimental results reported in this study.
Study on the Influence of the Blasting of Preceding Tunnel on the Pre-Penetration Surrounding Rock in Succeeding Tunnel with Small Clear Distance
Authors: Bao Xiankai , Zhang Wu , Zhao Shuang , Yu Chaoyun , Lü Yongjun , Wang Shurui , Wu Ning
Published: August 2022

To study the influence of the preceding tunnel blasting on the surrounding rock in the pre-penetration area of the succeeding tunnel, combined with the actual monitoring of the Kaifeng Mountain small clear distance tunnel, the relationship between the vibration velocity and the blasting center distance was derived according to the energy attenuation law, predicted the peak velocity of particle vibration on the pre-penetration surrounding rock, came up with the conception of surrounding rock seismic wave vibration velocity ratio, obtained its change situation, and then established a numerical model to further analyze the changes in vibration velocity, plastic strain, and stress. The results show the prediction formula of peak vibration velocity obtained from theoretical analysis of vibration velocity, which can well calculate the peak vibration velocity of some unmeasurable points in tunnel engineering and provide theoretical support for actual tunnel blasting engineering. Under the same clear distance conditions, the front blasting side of surrounding rock in the pre-penetration area of the succeeding tunnel is affected by blasting vibration more than the back blasting side, and the vibration velocity decreases gradually from the arch waist⟶arch shoulder⟶arch foot⟶vault (arch bottom), and the most unfavorable section is that the blasting surface is parallel to the surrounding rock section in the pre-penetration area of the preceding tunnel. The excavation of the lower step has greater destructive force than that of the upper step; with the clear distance that gradually increases, the impact of the preceding tunnel blasting on the surrounding rock in the pre-penetration area of the succeeding tunnel becomes smaller, and D (D is the tunnel span) is the minimum safe clear distance.
Peripheral Nerve Regeneration with Acellular Nerve Allografts Seeded with Amniotic Fluid-Derived Stem Cells
Authors: Ma Xue , Elsner Eileen , Cai Jiaozhong , Smith Thomas L. , Li Zhongyu
Published: August 2022

Introduction. Tissue engineering strategies have attempted to mimic regenerating axons’ environment by adding supportive types of cells other than Schwann cell to the nerve allograft. We hypothesized that allografts can be seeded with amniotic fluid-derived stem cells (AFS) to promote nerve regeneration. Methods. ANAs with AFS cells for long-gap nerve repairs were studied using a rat model. A sciatic nerve injury was created and repaired immediately with a rat acellular nerve allograft (ANA) construct alone, an ANA construct seeded with AFS cells, or with an autograft. Walking track analysis and electrophysiology were performed to document the return of motor control at 4 months post injury. Axon morphology on the nerve segments was assessed. Results. In vivo gait analysis showed that the ANA plus AFS cell group had significantly advanced recoveries in overlap distance, paw angle degree, paw drag, stance width, axis distance, and sciatic function index (SFI) compared with ANA alone. The ANA plus AFS cell group also demonstrated greater gastrocnemius compound muscle action potential (CMAP) ratio, sciatic axon diameter, fiber diameter, myelin thickness,

G

ratio (average axonal diameter (AD)/fiber diameter (FD)), and neuromuscular junction (NMJ) numbers compared to ANA. Discussion. The allograft plus AFS cell group demonstrated significantly improved functional and histological outcomes compared to allograft group alone, showing no significant difference of the nerve regeneration from the autograft group. Thus, AFS cells may be a suitable cell source to replace Schwann cells to support and accelerate peripheral nerve regeneration following large-gap nerve injury.
Construction and Prediction of Students’ Multiattribute Social Network Based on Psychological Big Data Analysis
Authors: Zhang Na , Zou Yuanyuan
Published: August 2022

In view of the limitations of the current research on students’ single attribute psychological problems. In this paper, a multiattribute social network model was constructed based on students’ social data and psychological label data, and the improved MANE algorithm was used to solve the problem to predict students’ psychological problems. In addition, DeepWalk and Node2vec network embedding algorithms were used to embed students’ multiattribute social network, respectively, so to verify the effectiveness of the model. Finally, based on the prediction model of students’ psychological problems, this paper uses Django web framework, MySQL database, and Bootstrap framework to design a personality prediction system, including data storage, algorithm training and prediction, result display, and other modules.
The Application of Variable Fuzzy Sets Theory on the Quality Assessment of Surrounding Rocks
Authors: Shao Jian-Li , Gao Lei , Wu Qi-Hong , Gu Xin-Bao
Published: August 2022

The quality assessment of surrounding rocks has tremendous influences on engineering construction, so its investigation is significant. The uniaxial compressive strength of rocks

σ

c

, the integrity coefficients of rock mass

K

V

, the conditions of the structural plane

S

S

, the seepage amount of groundwater

W

, and the intersection angle

θ

between the axis line and structural plane are selected as the quality assessment index of surrounding rocks at first. Then, the entropy weight-variable fuzzy sets model is introduced. Second, the relative membership degree matrix about the variable fuzzy sets is established, and the weight coefficients are determined based on the entropy weight method. Finally, the fracture behavior level of surrounding rocks is determined using the mean ranking feature value. The conclusions demonstrate that the results obtained based on the variable fuzzy sets method are consistent with the current specification; its accuracy arrives at 80%. Compared with the traditional way, its assessment process has higher reliability and efficiency. So, it could provide a new alternate way to assess the risk level in civil engineering accurately.
A Multiobjective Optimization Algorithm for Building Interior Design and Spatial Structure Optimization
Authors: Ran Meng , Dong Jian
Published: August 2022

Based on the global big data environment, people have more and more requirements for the interior design and spatial structure of buildings, and the traditional design has been unable to meet people’s needs, and the importance of artificial intelligence decision-making is reasonably reflected in the process of building interior design and space structure optimization. There are a variety of algorithms for artificial intelligence decision-making, artificial neural networks, and correlation coefficient analysis methods, and expandable interior design mining methods are currently being continuously improved and evolved, and these algorithms are used to analyze each case and then screen and finally obtain the optimal results, and the proposed multiobjective optimization and constraint optimization make the research work provide a new strategy for the design development of the data age. In the case of the Library of Extremely Cold Lands, the solution set quality of the nonadaptive solution is verified, the convergence, uniformity, and extensiveness are optimized, and then the experimental process is analyzed, and finally the multiobjective conclusion that building interior design and spatial structure still needs to be further optimized for artificial intelligence decision-making is obtained.
Interest of Widefield-Optical Coherence Tomography Angiography for Diagnosis and Follow-Up of Retinal Neovascularisation in Proliferative Diabetic Retinopathy
Authors: Vofo Brice Nguedia , Galarza Pablo , Chowers Itay , Levy Jaime
Published: August 2022

Aim. The primary aim was to evaluate the use of optical coherence tomography angiography (OCTA) versus fluorescein angiography (FA) for detecting and monitoring retinal neovascularization (NV) in patients with proliferative diabetic retinopathy (PDR) receiving treatment with anti-vascular endothelial growth factor (anti-VEGF). Methods. Treatment-naïve patients with PDR, willing to begin anti-VEGF treatment without laser from 9/2018–2/2020 were included. FA and OCTA scans were obtained at baseline, and a second OCTA scan was performed after 6 months of anti-VEGF therapy. We calculated sensitivity and specificity for two masked graders with respect to identifying NV on OCTA versus FA. Using ImageJ software, we also measured the change in NV size, at baseline and 6-month follow-up. Results. Ten eyes in eight patients were included, of which three eyes in three patients received a 6-month follow-up examination. Mean age was 51.7 ± 11.2 years, and 75% of patients were male. Overall, 21 NV sites in the 10 eyes were identified both clinically and on FA. Using OCTA scans, the sensitivity and specificity for both graders were extremely high, ranging from 95.2% to 100%. At 6-month follow-up, NV size decreased by 69.8%. Conclusion. These results suggest that OCTA may provide a suitable alternative to FA for visualizing, measuring, and monitoring changes in retinal NV in patients with PDR who receive anti-VEGF therapy.
Chemical Applicability of Newly Introduced Topological Invariants and Their Relation with Polycyclic Compounds
Authors: Alghazzawi Dilshad , Raza Ali , Munir Usama , Ali Md. Shajib
Published: August 2022

In quantitative structure‐property and structure‐activity relationships studies, several graph invariants, namely, topological indices have been defined and studied due to their numerous applications in computer networks, biotechnology, and nanochemistry. Topological indices are numeric parameters that describe the biological, physical, and chemical properties depending on the structure and topology of different chemical compounds. In this article, we inaugurated some degree‐based novel indices, namely, geometric‐harmonic GHI, harmonic‐geometric (HGI), neighborhood harmonic‐geometric (NHGI), and neighborhood geometric‐harmonic (NGHI) indices and verified their chemical applicability. Furthermore, an attempt is made to calculate analytical closed formulas for different variants of silicon carbides and analyze the obtained results graphically.
Ferulic Acid Protects Endothelial Cells from Hypoxia-Induced Injury by Regulating MicroRNA-92a
Authors: Huang Yuqi , Tian Li , Liu Yan , Liu Jiangwei , Huang Jianzhao
Published: August 2022

Background & Aim. Ferulic acid (FA), the main effective ingredient in Angelica sinensis, has been widely recognized as the cause of angiogenesis and proliferation of human umbilical vein endothelial cells (HUVECs). This study is mainly aimed at investigating the effect of FA on the apoptosis of HUVECs, which may play a key role in angiogenesis. Materials and Methods. CCK-8 (cell counting kit-8), Western blotting and Annexin V-FITC/PI staining were used to detect cell viability and apoptosis after hypoxia stimulation. The level of microRNA-92 a (miR-92 a) was detected by qRT-PCR.. Then, the assays of flow cytometry and the annexin V/PI staining kit were applied to value the impact of FA on hypoxia-induced cell proliferation, cell cycle distribution, and apoptosis. Furthermore, the inhibitor and mimic of miR-92a were also administrated to explore the role of miR-92a in this process. Student’s

t

-test was used to explore the differences between two groups, while one-way analysis of variance (ANOVA) was used to explore the differences between more than two groups. Results. The results showed that hypoxia stimulation significantly inhibited HUVEC viability and proliferation, such as remarkably decreasing the expression of CDK2, CDK4, and cyclin D1 in HUVECs. The results of annexin V-FITC/PI apoptosis detection showed that hypoxia culture significantly induced HUVEC apoptosis, which indicated that hypoxia stimulation significantly inhibited viability and proliferation of HUVECs but caused cell apoptosis and the expression of miR-92a. Meanwhile, FA remarkably protected HUVECs from hypoxia-induced inhibition of viability and proliferation, as well as the enhancement of apoptosis and miR-92a expression. Furthermore, suppression of miR-92a enhanced the protective effects of FA on hypoxia-induced HUVECs, while activation of miR-92a reversed those effects. Conclusion. Our study reported that FA preserved HUVECs from hypoxia-induced injury via regulating miR-92a, which facilitated the understanding of the protective capacity of FA in hypoxia-caused HUVEC injury.
CircAGFG1 Promotes Osteosarcoma Progression and Stemness by Competing with miR-302a-3p to Upregulate the Expression of LATS2
Authors: Li Tongchun , Xing Guangjie , Lu Liangliang , Kong Xiangzhen , Guo Jinwei
Published: August 2022

This study aimed to investigate the effect of circRNA (circAGFG1) on the proliferation, migration, invasion, and cell stemness of osteosarcoma cells by targeting miR-302a to regulate LATS2. The expression of circAGFG1 in osteosarcoma cells and normal osteoblasts was detected by real-time fluorescent quantitative PCR (RT-qPCR). Cell proliferation, clone formation, and invasion were detected by CCK-8, clone formation, and cell invasion assays. In vivo tumor formation assay was used to detect the effect of circAGFG1 on tumor growth. The expression level of circAGFG1 was upregulated in osteosarcoma cells. The downregulation of circAGFG1 inhibited the proliferation, invasion, and migration of osteosarcoma cells. The overexpression of circAGFG1 enhanced the stemness of osteosarcoma cells. CircAGFG1 was specifically bound to miR-302a to regulate the expression activity of miR-302a. MiR-302a specifically bound to the 3′UTR of LATS2 and inhibited the expression of LATS2. The overexpression of miR-302a reversed the effect of circAGFG1 on the proliferation, invasion, and migration of osteosarcoma cells. CircAGFG1 regulated the expression of LATS2 by miR-302a, thereby regulating the proliferation, migration, and invasion of osteosarcoma cells.
Three-Dimensional Animation Space Design Based on Virtual Reality
Authors: Zhang Rongxue
Published: August 2022

3D animation stereo space design is to process and analyze the collected target image information on the computer and finally obtain a 3D model that can represent the corresponding structure. As a branch of computer vision, 3D animation stereo space design is an important part of realizing the key technology of environment perception. What humans see in the three-dimensional world is a two-dimensional picture. Combined with the visual mechanism and the prior information of the object, it can realize the perception of the environment and promote the convenience of life and production. Games, movies, virtual humans, and any product that uses 3D technology require 3D engine support. The 3D engine encapsulates hardware operations and graphics algorithms and can manage a large number of texture and model resources to construct complex 3D scenes. In order to facilitate the research related to virtual human, in this paper, through the research and study of graphics-related mathematical knowledge and related technologies of engine architecture, an intelligent virtual animation generation engine based on DirectX12 is realized, and three-dimensional characters are controlled through related components, and the function of each module is tested and guaranteed. Test cases were designed to test the various functions of the engine and finally showed that the design goals in the demand analysis have been completed, and a lightweight three-dimensional animation three-dimensional space model has been realized.