bluuebunny/crossref_metadata_2025 huggingface dataset:
Deer Hunting Optimization with 3D-Convolutional Neural Network for Diabetic Retinopathy Classification Model
Authors: Bapatla Sesikala , Harikiran J.
Published: September 2022

A retina disease caused by high glucose levels in the blood is called Diabetic Retinopathy (DR) and is the world’s leading cause of blindness. To avoid or delay vision degradation and loss, early diagnosis and treatment are required. As a result, the creation of an automated method for accurate DR identification is essential. For this, in this paper, a 3D-Convolution Neural Network (3D-CNN) with Deer Hunting Optimization (DHO) algorithm is proposed for detecting and classifying DR images. The proposed 3D-CNN-DHO approach includes four phases such as pre-processing, segmentation, feature extraction, and classification. The contrast of the DR image is first improved using a Contrast-Limited Adaptive Histogram Equalization (CLAHE) approach. Subsequently, the threshold-based effective segmentation is carried out. Then, the Resnet50 model is implemented to extract the features from the image. Finally, 3D-CNN-DHO-based classifier model is implemented to categorize the various DR stages. The experiments are carried out in detail and evaluated on the Messidor DR benchmark dataset. The acquired experimental result demonstrated the 3D-CNN-DHO model’s outstanding qualities by achieving optimal specificity, sensitivity, recall, precision, and accuracy.
AuraRing
Authors: Parizi Farshid Salemi , Whitmire Eric , Patel Shwetak
Published: September 2022

Wearable computing platforms, such as smartwatches and head-mounted mixed reality displays, demand new input devices for high-fidelity interaction. We present AuraRing, a wearable magnetic tracking system designed for tracking fine-grained finger movement. The hardware consists of a ring with an embedded electromagnetic transmitter coil and a wristband with multiple sensor coils. By measuring the magnetic fields at different points around the wrist, AuraRing estimates the five degree-of-freedom pose of the ring. AuraRing is trained only on simulated data and requires no runtime supervised training, ensuring user and session independence. It has a dynamic accuracy of 4.4 mm, as measured through a user evaluation with optical ground truth. The ring is completely self-contained and consumes just 2.3 mW of power.
Explainable Convolutional Neural Networks: A Taxonomy, Review, and Future Directions
Authors: Ibrahim Rami , Shafiq M. Omair
Published: September 2022

Convolutional neural networks (CNNs)
have shown promising results and have outperformed classical machine learning techniques in tasks such as image classification and object recognition. Their human-brain like structure enabled them to learn sophisticated features while passing images through their layers. However, their lack of explainability led to the demand for interpretations to justify their predictions. Research on
Explainable AI
or
XAI
has gained momentum to provide knowledge and insights into neural networks. This study summarizes the literature to gain more understanding of explainability in CNNs (i.e., Explainable Convolutional Neural Networks). We classify models that made efforts to improve the CNNs interpretation. We present and discuss taxonomies for XAI models that modify CNN architecture, simplify CNN representations, analyze feature relevance, and visualize interpretations. We review various metrics used to evaluate XAI interpretations. In addition, we discuss the applications and tasks of XAI models. This focused and extensive survey develops a perspective on this area by addressing suggestions for overcoming XAI interpretation challenges, like models’ generalization, unifying evaluation criteria, building robust models, and providing interpretations with semantic descriptions. Our taxonomy can be a reference to motivate future research in interpreting neural networks.
General and Domain-adaptive Chinese Spelling Check with Error-consistent Pretraining
Authors: Lv Qi , Cao Ziqiang , Geng Lei , Ai Chunhui , Yan Xu , Fu Guohong
Published: September 2022

The lack of label data is one of the significant bottlenecks for Chinese Spelling Check. Existing researches use the automatic generation method by exploiting unlabeled data to expand the supervised corpus. However, there is a big gap between the real input scenario and automatically generated corpus. Thus, we develop a competitive general speller ECSpell, which adopts the Error-consistent masking strategy to create data for pretraining. This error-consistency masking strategy is used to specify the error types of automatically generated sentences consistent with the real scene. The experimental result indicates that our model outperforms previous state-of-the-art models on the general benchmark.

Moreover, spellers often work within a particular domain in real life. Due to many uncommon domain terms, experiments on our built domain-specific datasets show that general models perform terribly. Inspired by the common practice of input methods, we propose to add an alterable user dictionary to handle the zero-shot domain-adaption problem. Specifically, we attach a User Dictionary guided inference module (UD) to a general token classification-based speller. Our experiments demonstrate that ECSpell
UD
, namely, ECSpell combined with UD, surpasses all the other baselines broadly, even approaching the performance on the general benchmark.

1
Survey: Exploiting Data Redundancy for Optimization of Deep Learning
Authors: Chen Jou-An , Niu Wei , Ren Bin , Wang Yanzhi , Shen Xipeng
Published: September 2022

Data redundancy is ubiquitous in the inputs and intermediate results of
Deep Neural Networks (DNN)
. It offers many significant opportunities for improving DNN performance and efficiency and has been explored in a large body of work. These studies have scattered in many venues across several years. The targets they focus on range from images to videos and texts, and the techniques they use to detect and exploit data redundancy also vary in many aspects. There is not yet a systematic examination and summary of the many efforts, making it difficult for researchers to get a comprehensive view of the prior work, the state of the art, differences and shared principles, and the areas and directions yet to explore. This article tries to fill the void. It surveys hundreds of recent papers on the topic, introduces a novel taxonomy to put the various techniques into a single categorization framework, offers a comprehensive description of the main methods used for exploiting data redundancy in improving multiple kinds of DNNs on data, and points out a set of research opportunities for future exploration.
The Biology and Evolution of Fierce Females (Moles and Hyenas)
Authors: Jiménez Rafael , Burgos Miguel , Barrionuevo Francisco J.
Published: September 2022

Talpid moles and spotted hyenas have become the paradigms of anatomical and behavioral female masculinization. Females of many mole species develop ovotestes that produce testosterone, show external genitalia that resemble that of males, and close their vaginal orifice after every estrus, and female spotted hyenas lack an external vaginal orifice and develop a pseudoscrotum and a large pseudopenis through which they urinate, mate, and give birth. We review current knowledge about several significant aspects of the biology and evolution of these females, including ( a) their specific study methods; ( b) their unique anatomical features, and how these peculiarities influence certain physiological functions; and ( c) the role that steroid hormones as well as genetic and environmental factors may have in urogenital system development, aggressive behavior, and social dominance. Nevertheless, both mole and hyena females are exceptionally efficient mothers, so their peculiar genitalia should not call into question their femininity.
Chemical Ecology of Floral Resources in Conservation Biological Control
Authors: Colazza Stefano , Peri Ezio , Cusumano Antonino
Published: September 2022

Conservation biological control aims to enhance populations of natural enemies of insect pests in crop habitats, typically by intentional provision of flowering plants as food resources. Ideally, these flowering plants should be inherently attractive to natural enemies to ensure that they are frequently visited. We review the chemical ecology of floral resources in a conservation biological control context, with a focus on insect parasitoids. We highlight the role of floral volatiles as semiochemicals that attract parasitoids to the food resources. The discovery that nectar-inhabiting microbes can be hidden players in mediating parasitoid responses to flowering plants has highlighted the complexity of the interactions between plants and parasitoids. Furthermore, because food webs in agroecosystems do not generally stop at the third trophic level, we also consider responses of hyperparasitoids to floral resources. We thus provide an overview of floral compounds as semiochemicals from a multitrophic perspective, and we focus on the remaining questions that need to be addressed to move the field forward.
Food System Resilience: Concepts, Issues, and Challenges
Authors: Zurek Monika , Ingram John , Sanderson Bellamy Angelina , Goold Conor , Lyon Christopher , Alexander Peter , Barnes Andrew , Bebber Daniel P. , Breeze Tom D. , Bruce Ann , Collins Lisa M. , Davies Jessica , Doherty Bob , Ensor Jonathan , Franco Sofia C. , Gatto Andrea , Hess Tim , Lamprinopoulou Chrysa , Liu Lingxuan , Merkle Magnus , Norton Lisa , Oliver Tom , Ollerton Jeff , Potts Simon , Reed Mark S. , Sutcliffe Chloe , Withers Paul J.A.
Published: September 2022

Food system resilience has multiple dimensions. We draw on food system and resilience concepts and review resilience framings of different communities. We present four questions to frame food system resilience (Resilience of what? Resilience to what? Resilience from whose perspective? Resilience for how long?) and three approaches to enhancing resilience (robustness, recovery, and reorientation—the three “Rs”). We focus on enhancing resilience of food system outcomes and argue this will require food system actors adapting their activities, noting that activities do not change spontaneously but in response to a change in drivers: an opportunity or a threat. However, operationalizing resilience enhancement involves normative choices and will result in decisions having to be negotiated about trade-offs among food system outcomes for different stakeholders. New approaches to including different food system actors’ perceptions and goals are needed to build food systems that are better positioned to address challenges of the future.
Molecular Monitoring of Lymphomas
Authors: Schroers-Martin Joseph G. , Alig Stefan , Garofalo Andrea , Tessoulin Benoit , Sugio Takeshi , Alizadeh Ash A.
Published: September 2022

Molecular monitoring of tumor-derived alterations has an established role in the surveillance of leukemias, and emerging nucleic acid sequencing technologies are likely to similarly transform the clinical management of lymphomas. Lymphomas are well suited for molecular surveillance due to relatively high cell-free DNA and circulating tumor DNA concentrations, high somatic mutational burden, and the existence of stereotyped variants enabling focused interrogation of recurrently altered regions. Here, we review the clinical scenarios and key technologies applicable for the molecular monitoring of lymphomas, summarizing current evidence in the literature regarding molecular subtyping and classification, evaluation of treatment response, the surveillance of active cellular therapies, and emerging clinical trial strategies.
Embracing Complexity: A Review of Negotiation Research
Authors: Boothby Erica J. , Cooney Gus , Schweitzer Maurice E.
Published: September 2022

In this review, we identify emerging trends in negotiation scholarship that embrace complexity, finding moderators of effects that were initially described as monolithic, examining the nuances of social interaction, and studying negotiation as it occurs in the real world. We also identify areas in which research is lacking and call for scholarship that offers practical advice. All told, the existing research highlights negotiation as an exciting context for examining human behavior, characterized by features such as strong emotions, an intriguing blend of cooperation and competition, the presence of fundamental issues such as power and group identity, and outcomes that deeply affect the trajectory of people's personal and professional lives.
Temperature Dependent Analysis of Mixed CNT Bundle Interconnecting using Active Shielding Technique
Authors: Kumar Ch. Praveen , Rao E. Sreenivasa , Sekhar P. Chandra
Published: September 2022

The cumulative increase of resistivity in copper due to scaling and indispensable requirements of high current densities and unprecedented switching speed are the impelling forces behind the continuous investigation towards the new wiring solution for nanometer circuits and systems. Mixed carbon nanotube bundle (MCB) interconnects are the most optimistic solution that can address the challenges faced by the conventional materials and thereby enhances the lifetime of electrical interconnects. MCB is a combination of Single walled carbon nanotubes (SWCNT’s) and Multi walled carbon nanotubes (MWCNT’s). On the basis of hierarchical modelling, various bundle structures are introduced pertaining to the placement of SWCNT’s and MWCNT’s in the bundle. The reliability of the MCB structures are investigated by calculating the propagation delay and power dissipation. The delays and peak crosstalk noise are examined from the transient analysis for all the bundle structures considered in the present study. Further to improve the data rates and performance, CNTFET based ternary logic system is encompassed for MCB interconnects. Active shielding technique is incorporated effectively for minimizing the crosstalk effects. Finally, modelling of the mixed CNT bundle is done under the influence of temperature and the temperature sensitive crosstalk noise effects are investigated for CNTFET based active shielded MCB structures. Encouragingly, it is observed that, the crosstalk effects are lessened to a greater extent for the MCB structure wherein SWCNT’s are placed at the centre and MWCNT’s at the periphery. All these analyses have been carried out at 22 nm technology node.
Near-Infrared-Light Triggered Electron Transfer from Ag2S Nanocrystals to Perylene Bisimide
Authors: Nagai Yuki , Watanabe Tadashi , Yoshioka Daisuke , Okayasu Yoshinori , Tamai Naoto , Kobayashi Yoichi
Published: September 2022

Long-wavelength light penetrates deeply in a variety of substances and can induce selective excitation in condensed phases. Therefore, photofunctional materials that are responsive to long-wavelength light are essential. Ag2S nanocrystals (NCs), which are near-infrared-light (NIR)-responsive materials, have applications as NIR phosphors and photosensitizers. However, the excited-state dynamics of Ag2S NCs combined with aromatic molecules have not been elucidated to date. In this study, we synthesized perylene bisimide-coordinated Ag2S nanocrystals (PBI-Ag2S) and investigated the excited-state dynamics by subpicosecond-to-nanosecond transient absorption spectroscopy. When PBI-Ag2S is excited using a 530 nm light, where the excited-state dynamics of the PBI moiety is mainly probed, PBI radical anions are instantaneously produced by ultrafast hole transfer from PBI to Ag2S NCs. Moreover, PBI radical anions are formed even upon excitation with a 720-nm light, where only Ag2S NCs are selectively excited. This study is important for developing novel organic-inorganic nanohybrid photofunctional materials that utilize low-energy light efficiently for applications in photoredox catalysts, optoelectronic devices, and solar cells.
Adaptation-induced plasticity in the sensory cortex
Authors: Bharmauria Vishal , Ouelhazi Afef , Lussiez Rudy , Molotchnikoff Stéphane
Published: September 2022

For medical and fundamental reasons, we need to understand adult brain plasticity at several levels: structural, physiological, and behavioral. Historically, brain plasticity has been mostly investigated by weakening or removing sensory inputs. The visual system has been extensively used because diminishing visual inputs, i.e., visual deprivation-induced plasticity, permits more tractable findings. The present review is centered on the reverse strategy, by imposing a novel stimulus, i.e., adaptation-induced plasticity. Adaptation refers to the constant (milliseconds to hours) presentation of a nonoptimal stimulus (adapter) within the receptive field (RF, spatial area that modulates neuronal firing) of the neuron under observation. We specifically focus on how adaptation impacts the tuning of visual neurons with other associated properties. After adaptation, visual cortical neurons respond robustly to the adapter (before adaptation it typically evokes feeble responses) by developing alternate tuning curves that outlast the adaptation time. Here, with dendritic structure as foundation, we synthesize a push-pull mechanism of development and acquisition of novel tuning curves following adaptation. We then explain how these changes apply at the global level across different brain regions and species with a short description of underlying neurochemical changes. Finally, we discuss physiopathological consequences and conclude with some gaps and questions that need to be addressed to further comprehend such neuroplasticity.
Efficacy of the Panax Notoginseng Ejiao Suppository in the Treatment of Patients with Ulcerative Proctitis and Its Effect on Inflammatory Response and Immune Function
Authors: Liu Yu , Sun Yingjie , Wang Xince , Wang Dongsheng , Zeng Li , Lu Qingge
Published: September 2022

Objective. To investigate the efficacy of the Panax notoginseng Ejiao suppository in patients with ulcerative proctitis and its effect on inflammatory response and immune function. Methods. This study recruited 100 patients with ulcerative proctitis who were hospitalized to our hospital’s anorectal outpatient department between May 2015 and October 2020. They were randomly separated into either a control or a study group, with 50 cases in each. The control group received the mesalazine suppository, whereas the study group received the Panax notoginseng Ejiao suppository. Outcome measures included clinical effectiveness, inflammatory response, and immunological state of patients. Results. The total efficiency in the study group was significantly higher than that in the control group (

P
=
0.019

). The Mayo score and Baron endoscopic score between the two groups were significantly decreased after treatment, with lower results in the study group (

P
<
0.05

). The inflammatory variables were dramatically reduced following therapy, with the study group doing worse. Following treatment, the number of Th 17 cells declined dramatically in both groups, while the proportion of Treg cells increased significantly, with greater alterations of Th17 cells and Treg cells observed in the study group than those in the control group (

P
<
0.05

). The Panax notoginseng Ejiao suppository resulted in significantly shorter time lapses before symptom alleviation and a lower incidence of recurrence at 6 months after treatment versus mesalazine suppository (

P
<
0.05

). Conclusion. In patients with ulcerative proctitis, the Panax notoginseng Ejiao suppository significantly improves clinical efficacy, reduces the incidence of recurrence, mitigates inflammatory response, and improves immune function.
AS-DMF: A Lightweight Malware Encrypted Traffic Detection Method Based on Active Learning and Feature Selection
Authors: Huo Yuehua , Zhao Faqi , Zhang Hangsheng , Zhuang Shangyuan , Sun Jiyan
Published: September 2022

The sharp increasing volume of encrypted traffic generated by malware brings a huge challenge to traditional payload-based malicious traffic detection methods. Solutions that based on machine learning and deep learning are becoming mainstream. However, the machine learning-based methods are limited by manual-design features, which have the problem of highly correlated multicollinearity. And both methods rely heavily on a large number of labeled samples, which needs lots of human effort. In this paper, we apply the active learning to the malicious encrypted traffic detection problem and propose AS-DMF framework. AS-DMF is a lightweight detection framework that combine the uncertainty sampling and density-based query strategy to query the informative and representative instances from the sample set and then train them in a detection (DMF) model. Moreover, we propose a feature selection mechanism which can select the meaningful features of traffic efficiently. Our comprehensive experiments on the real-word dataset indicate that AS-DMF achieves lightweighting at both feature and data levels with a high performance of 0.9460 mAcc.
Correlation between Cardiac Ultrasound Index and Cardiovascular Risk in Healthy Obese and Overweight Populations
Authors: Pan Xiaoyu , Chen Xiaoyi , Ren Lin , Li Zelin , Chen Shuchun
Published: September 2022

Objective. To investigate the correlation of obesity and overweight with cardiac ultrasound parameters and future cardiovascular risk among healthy populations. Methods. Basic clinical characteristics as well as cardiac ultrasound parameters were collected from healthy people. Firstly, all participants were divided into three groups: normal, overweight, and obese. Then the differences in cardiac ultrasound parameters between the three groups were calculated. Subsequently, those aged 35–60 years were screened to determine their cardiovascular risk according to the SCORE system. Finally, the correlation between cardiac ultrasound indices and cardiovascular risk was calculated. Results. A total of 1328 healthy participants were included, of whom 504 were normal, 580 were overweight and 244 were obese. Obesity and overweight significantly increased the aorta, left atrium, right atrium, right ventricle, the end-diastolic diameter of the left ventricle, main pulmonary artery, right ventricular outflow tract, interventricular septum, left ventricular posterior wall, and triglycerides and decreased E/A values and high-density lipoprotein-cholesterol. Ejection fraction, fractional shortening, low-density lipoprotein-cholesterol, and total cholesterol did not change between the three groups. A total of 781 participants were screened for SCORE scores. Obesity and being overweight significantly increased the incidence of future cardiovascular events, and lower E/A values were also associated with cardiovascular risk. All cardiac parameters were strongly associated with cardiovascular risk. Conclusion. Our research demonstrates that obesity and overweight can damage heart shape and function and raise the risk of future cardiovascular events in people that are healthy. Cardiovascular risk and cardiac structural and functional impairments are significantly positively correlated.
Protein Kinase N2 Reduces Hydrogen Peroxide-inducedDamage and Apoptosis in PC12 Cells by AntiOxidative Stress and Activation of the mTOR Pathway
Authors: Wang Lin , Zhang Lin
Published: September 2022

Objective. To investigate the role and mechanism of protein kinase N2 (PKN2) in hydrogen peroxide (H2O2)-induced injury of PC12 cells. Methods. PC12 cells were transfected with lentivirus to knock down or overexpress PKN2 and then were treated with 300 μM H2O2 to establish a cell model of oxidative stress injury. The cell viability of PC12 cells in each group was determined by the CCK-8 method. Biochemical assays were used to measure reactive oxygen species (ROS), malondialdehyde (MDA) levels, and superoxide dismutase (SOD) activity. Western blot was used to detect the protein expressions of PKN2, caspase-3, cleaved-caspase-3, PARP, cleaved-PARP, p-mTOR, and mTOR in PC12 cells in each group. Results. H2O2 treatment could significantly reduce PC12 cell viability and promote cell apoptosis and oxidative stress. PKN2 overexpression inhibited H2O2-induced apoptosis and oxidation damage by increasing PC12 cell viability, SOD activity, and p-mTOR protein expression, reducing intracellular ROS and MDA levels, and cleaved-caspase-3 and cleaved-PARP protein expression. Conclusion. PKN2 overexpression can alleviate H2O2-induced oxidative stress injury and apoptosis in PC12 cells by activating the mTOR pathway.
Application of Whole-Body Hyperbaric Oxygen Therapy in the Treatment of Grade III Exposed Dog Bite Wounds
Authors: Tian Chao , Yang Qiang , Bi Shu-Zhen , Li Xu-Rong , Chen Jin-Hua , Guo Yao
Published: September 2022

Objective. The aim of the study is to evaluate the therapeutic effect of hyperbaric oxygen in the treatment of grade III exposed dog bite wounds. Method. Fifty-two patients with grade III dog bite wounds who were seen in the emergency department of our hospital from 2017 to 2021 were selected for this research. The participants were randomly divided into an experimental group and a control group, with 26 patients in each group. The experimental group received hyperbaric oxygen therapy (HBOT), and the control group received routine treatment. The patients were followed up for three months after the treatment concluded. The wound healing rate, infection rate, and healing time were measured and compared. Results. The cure rate of the experimental group (96.2%) was higher than that of the control group (69.2%). The infection rate in the experimental group (3.8%) was lower than that of the control group (30.8%). The average cure time of the experimental group (9 ± 2.7) was lower than that of the control group (11 ± 3.4). The number of dressing changes in the experimental group (4 ± 3.0) was lower than that of the control group (7.5 ± 3.5), and there was a significant difference between the two groups (

P
<
0.05

). Conclusion. According to the results, HBOT of grade III dog bite wounds can promote wound healing, improve the cure, and reduce the wound infection rate. It should have a primary role in the clinical treatment of these wounds.
Modeling and Analysis Method of National Fitness Big Data for Basketball Projects Based on a Multivariate Statistical Model
Authors: Zhao Qi
Published: September 2022

How to start from the fitness needs of people and effectively improve the precision of the supply of public fitness services everyone is an important issue that needs to be solved first at the current stage. This requires us to proceed from the reality, conduct accurate research, and find a method that can match the current problem. In this paper, taking basketball projects in national fitness as an example, by introducing a proposition about the development of small basketball events, the corresponding big data modeling and analysis methods are studied. The research methods and research objectives involved in this paper are based on the relevant parameters of the multivariate statistical model. First, the article introduces the calculation principle of the multiple linear regression model. We introduce the concept of variance inflation factor involved in this principle and carry out the modeling and analysis of big data based on this variable. In order to illustrate the application effect of big data in this kind of research, this paper introduces three different big data technologies, including immune selection optimization algorithm, particle swarm optimization algorithm, and Elman neural network, to predict and analyze the variance inflation factor (VIF) corresponding to the small basketball project. The analysis results show that the Elman network exhibits certain advantages in terms of computing convergence time. And, as the number of calculation steps increases, the superiority of the Elman network is more obvious. As far as the prediction performance is concerned, the square of the correlation coefficient corresponding to the immune selection optimization algorithm is the largest and the sum of the squares of the residuals is the smallest, showing superior prediction performance.
An Efficient Method for Solving Fractional Black-Scholes Model with Index and Exponential Decay Kernels
Authors: Rashid Saima , Butt Saad Ihsan , Hammouch Zakia , Bonyah Ebenezer
Published: September 2022

The Black-Scholes equation (BSe) is fascinating in the business world for predicting the performance of financial investment valuation systems. The Caputo fractional derivative (CFD) and Caputo-Fabrizio fractional derivative operators are used in this research to analyze the BSe. The Adomian decomposition method (ADM) and the new iterative transform (NIM) approach are combined alongside the Yang transform. In addition, the convergence and uniqueness results for the aforementioned framework have been calculated. The existence and uniqueness results have been established and frequently accompanied innovative aspects of the prospective system in fixed point terminologies. To provide additional insight into such concepts, a variety of illustrations and tabulations are used. Additionally, the provided techniques regulate and modify the obtained analytical results in a really productive fashion, allowing us to modify and regulate the converging domains of the series solution in a pragmatic manner.
Role of Different Types of miRNAs in Some Cardiovascular Diseases and Therapy‐Based miRNA Strategies: A Mini Review
Authors: Fayez Safa S. , Mishlish Sami Mukhlif , Saied Hanan M. , Shaban Semaa A. , Suleiman Ahmed AbdulJabbar , Hassan Firas , Al-Saffar Ali Z. , Al-Obaidi Jameel R.
Published: September 2022

The role of microRNAs (miRNAs) in the pathogenesis of cardiovascular disease has been extensively studied. miRNAs have been highlighted as an important physiological regulator for activities like cardiac protection. miRNAs are present in the circulation, and they have been investigated as physiological markers, especially in the condition of heart failure. However, there is less compelling verification that miRNAs can outperform traditional biomarkers. However, clinical evidence is still required. In this review article, we explored the feasibility of miRNAs as diagnostic biomarkers for heart failure in a systematic study. Searching in the PubMed database to identify miRNA molecules that are differentially expressed between groups of patients with heart failure or heart disease and controls, throughout the investigation, we discovered no significant overlap in differentially expressed miRNAs. Only four miRNAs (“miR‐126,” “miR‐150‐5p,” “hsa‐miR‐233,” and “miR‐423‐5p”) were differentially expressed. Results from our review show that there is not enough evidence to support the use of miRNAs as biomarkers in clinical settings.
Association between Stigma and Pain in Patients with Temporomandibular Disorders
Authors: Zhu Rui , Zhang Li , Zheng Yun-Hao , Zhang Zi-Han , Zhang Li-Ming , Yang Hao-Lun , Yue Yuan , Xiong Xin
Published: September 2022

Objective. This study aims to explore the association between stigma and pain in patients with temporomandibular disorders (TMDs). Methods. Two hundred and twenty-five patients with TMDs were recruited, and they completed the questionnaires including the Visual Analogue Scale of Pain (VAS), Generalized Anxiety Disorder 7-Item (GAD-7), the Patient Health Questionnaire 9-item (PHQ-9), Jaw Functional Limitation Scale 8-item (JFLS-8), the Stigma Scale for Chronic Illness 8-item (SSCI-8), and other demographic and disease-related information. The total score of SSCI-8 indicated overall stigma, which could be classified into 2 subdomains, felt stigma and enacted stigma, according to their representative items, respectively. Then, the patients were divided into 2 groups in each subdomain of stigma according to their scores: stigma group (score ≥ 1) and no stigma group (score = 0). Results. Patients with overall stigma and enacted stigma presented significantly higher scores in VAS, GAD-7, PHQ-9, and JFLS-8 than those without overall stigma and those without enacted stigma, respectively. Significant differences between patients with and without felt stigma were only observed in GAD-7, PHQ-9, and JFLS-8. Patients with overall stigma and enacted stigma mainly suffered from pain-related TMDs (PTs) and combined TMDs (CTs). Overall stigma and enacted stigma rather than felt stigma were significantly associated with both PTs and CTs. Stigma, including overall stigma, enacted stigma, and felt stigma, was more associated with anxiety and depression and less related to jaw functional limitation of the patients with TMDs. Conclusion. Stigma, specifically enacted stigma, was correlated to pain in patients with TMDs. Stigma was more related to psychological problems than jaw functional limitation.
Wind Tunnel Testing and Validation of Helicopter Rotor Blades Using Additive Manufacturing
Authors: Hasan Inamul , Mukesh R. , Radha Krishnan P. , Srinath R. , Babu Dhanya Prakash , Lemma Gurmu Negash
Published: September 2022

This research paper aims to validate the aerodynamic performance of rotor blades using additive manufacturing techniques. Wind tunnel testing is a technique used to find the flow characteristics of the body. Computational fluid dynamics (CFD) techniques are used for aerodynamic analysis, and validation should be done using wind tunnel testing. In the aerodynamic testing of models, additive manufacturing techniques help in validating the results by making models easily for wind tunnels. Recent developments in additive manufacturing help in the aerodynamic testing of models in wind tunnels. The CFD analysis of helicopter rotor blades was analyzed in this research, and validation was done using additive manufacturing techniques. Computational analysis was carried out for static analysis for the forward speeds of Mach numbers 0.3, 0.4, and 0.5. The results obtained were satisfactory to the previous results and were validated with wind tunnel testing. Results proved that the error percentage was lower, and the computational analysis was valid. In this research, models were designed using the FDM technique for wind tunnel testing as it is cost-effective and easy to manufacture.
Technology Based on Interactive Theatre Performance Production and Performance Platform
Authors: Xia Xiuzheng , Tian Chen
Published: September 2022

Drama refers to a comprehensive art that realizes the purpose of narrative through language, movement, dance, music, puppets, and other forms. From the pre-Qin period⟶the Han and Wei periods⟶the Tang, Song, and Jin periods⟶the Yuan Dynasty⟶the late Yuan Ming and Qing periods⟶modern times, the art of opera has been welcomed and recognized by a vast audience since its birth, but it is difficult to inherit the art of Chinese opera. The fundamental reason is that there is no good platform for performance. It should be said that since the beginning of the performing arts, there has also been academic thinking on the practice of this artistic creation, so in the academic field of drama, there is actually drama performance science. Due to the changes of the times, Chinese drama art cannot keep up with the pace of the Internet. Therefore, this article proposed a technical research based on the interactive drama performance production and performance platform. This article mainly talks about face recognition technology and its algorithm, and applies it to theatrical performances and productions. In the following experiments, this technology is also used to create a network platform, and its user experience evaluation effect is good. The theatrical performances and productions of young people were also scored, and the final experimental results showed that: at the minimum required level, which is at least three (or more) dramatic materials in the class, scores are high at both levels. Among them, 94.4% of the classes in the first-level kindergarten and 86.1% of the classes in the second-level kindergarten meet this standard. Most of the two levels are qualified, that is to say, in the performance area, at least three people can perform at the same time, which is enough to show that theatrical performance has been passed down.
Design of Asynchronous Motor Controller Based on Controlled Lagrangians Method
Authors: Gao Yunbo , Liu Jianqiang , Li Maoqing , Tian Zhiyu , Li Cuiran
Published: September 2022

Asynchronous motor system has the characteristics of high order, strong coupling, and nonlinearity. From the dynamical model, it is the underactuated mechanical system, which means that the dimension of its input space is fewer than the degree of freedom. Following this perspective, the energy based nonlinear control technology-CL (controlled Lagrangians) method is used to solve the control problem in this paper. Based on the expected controlled energy and its derivative with respect to time, controlled Lagrangians and generalized force are constructed, and they produce the controlled equations. In order to ensure the complete matching between the controlled equation and the original equation, the gyroscopic forces containing the first-order term of velocity are innovatively introduced into the generalized force, and the matching conditions are obtained. By solving the matching conditions composed of some partial differential equations, the nonlinear smooth feedback control law can realize the global asymptotic stabilization of not only velocity but also position. Finally, the controlled energy is selected as the Lyapunov function, and the stability is proved according to the LaSalle invariant theorem. The effectiveness of the designed control law is demonstrated in the results of the simulation.
Optimal Element Allocation for RIS-Aided Physical Layer Security
Authors: Zhang Ying , Zhang Guoan , Chen Siyu , Choi Jaeho , Ho Pin-Han
Published: September 2022

In this paper, we investigate an innovative physical layer security (PLS) scheme for an uncertain reconfigurable intelligent surface- (RIS-) assisted communication system under eavesdropping attack. Specifically, in our proposed system, we consider that the uncertain RIS is known to the legitimate user while not to the eavesdropper (Eve). In this manner, the reflective elements of the uncertain RIS are adjusted to strengthen the keen signals for the legitimate user while suppressing the signals for Eve via jamming. We analyze the system by assuming legitimate and wiretap channels, respectively, where the secrecy capacity maximization problem is formulated and its exact closed-form expression is derived. Simulation results verifying the accuracy of our analysis demonstrate the validity and superiority of the uncertain RIS-assisted communication system against its counterparts.
LncRNA MDRL Mitigates Atherosclerosis through miR-361/SQSTM1/NLRP3 Signaling
Authors: You Ling , Zheng Yanjie , Yang Jing , Hou Qian , Wang Lianxia , Zhang Yan , Zhao Chunxia , Xie Ruiqin
Published: September 2022

Objective. Long non-coding RNAs (lncRNAs) play many important roles in gene regulation and disease pathogenesis. Here, we sought to determine that mitochondrial dynamic related lncRNA (MDRL) modulates NLRP3 inflammasome activation and apoptosis of vascular smooth muscle cells (VSMCs) and protects arteries against atherosclerosis. Methods. In vivo experiments, we applied LDLR knockout (LDLR-/-) mice fed the high-fat diet to investigate the effects of MDRL on atherosclerosis. In vitro experiments, we applied mouse aortic smooth muscle cells to determine the mechanism of MDRL in abrogating NLRP3 inflammasome and inhibiting cell apoptosis through miR-361/sequentosome 1 (SQSTM1) by TUNEL staining, quantitative RT-PCR, western blot, microribonucleoprotein immunoprecipitation, and luciferase reporter assay. Results. Downregulated MDRL and increased NLRP3 were observed in mouse atherosclerotic plaques, accompanied with the increase of miR-361. The results showed that MDRL overexpression significantly attenuated the burden of atherosclerotic plaque and facilitated plaque stability through inhibiting NLRP3 inflammasome activation and cell apoptosis, and vice versa. Mechanically, MDRL suppressed NLRP3 inflammasome activation and VSMC apoptosis via suppressing miR-361. Furthermore, miR-361 directly bound to the 3’UTR of SQSTM1 and inhibited its translation, subsequently activating NLRP3 inflammasome. Systematic delivery of miR-361 partly counteracted the beneficial effects of MDRL overexpression on atherosclerotic development in LDLR-/- mice. Conclusions. In summary, MDRL alleviates NLRP3 inflammasome activation and apoptosis in VSMCs through miR-361/SQSTM1/NLRP3 pathway during atherogenesis. These data indicate that MDRL and inhibition of miR-361 represent potential therapeutic targets in atherosclerosis-related diseases.
Context Aware Convolutional Neural Network for Children Caries Diagnosis on Dental Panoramic Radiographs
Authors: Zhou Xiaojie , Yu Guoxia , Yin Qiyue , Liu Yan , Zhang Zhiling , Sun Jie
Published: September 2022

The objective of this study is to improve traditional convolutional neural networks for more accurate children dental caries diagnosis on panoramic radiographs. A context aware convolutional neural network (CNN) is proposed by considering information among adjacent teeth, based on the fact that caries of teeth often affects each other due to the same growing environment. Specifically, when performing caries diagnosis on a tooth, information from its adjacent teeth will be collected and adaptively fused for final classification. Children panoramic radiographs of 210 patients with one or more caries and 94 patients without caries are utilized, among which there are a total of 6028 teeth with 3039 to be caries. The proposed context aware CNN outperforms typical CNN baseline with the accuracy, precision, recall,

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1

score, and area-under-the-curve (AUC) being 0.8272, 0.8538, 0.8770, 0.8652, and 0.9005, respectively, showing potential to improve typical CNN instead of just copying them in previous works. Specially, the proposed method performs better than two five-year attending doctors for the second primary molar caries diagnosis. Considering the results obtained, it is beneficial to promote CNN based deep learning methods for assisting dentists for caries diagnosis in hospitals.
Effectiveness and Safety of Saccharomyces Boulardii for the Treatment of Acute Gastroenteritis in the Pediatric Population: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
Authors: Fu Hongbo , Li Jinrong , Xu Xunhua , Xia Caihuai , Pan Yajuan
Published: September 2022

Objective. To explore the efficacy and safety of Saccharomyces boulardii for the treatment of acute gastroenteritis in children aged under 5. Methods. Two independent researchers retrieved literature from PubMed, OVID, Embase, ScienceDirect, and other databases, followed by extracting indicators of the primary endpoints. Cochrane Q test andI2statistics were used to evaluate interstudy heterogeneity. The relative risk (RR) and mean difference (MD) of related indicators were calculated and combined using the random- or fixed-effect model, as appropriate. Furthermore, the funnel plot and Egger’s test were used to evaluate the publication bias. A two-sidedP<0.05denoted statistical significance. Results. 10 articles were included in this meta-analysis, with a total of 1282 children having acute gastroenteritis. The use of Saccharomyces boulardii in children with acute gastroenteritis could effectively shorten diarrhea duration (MD=19.70, 95% CI: -24.87, 14.52) and reduce the length of hospital stay (MD=−0.91, 95% CI: -1.28, -0.54). Compared with the control group, the RR of continued diarrhea was significantly lower in the treatment group after 1 day treatment (RR=−0.31, 95% CI: 0.59, 0.03) and 3 days treatment (RR=0.52, 95% CI: 0.41, 0.66). In addition, treatment with Saccharomyces boulardii reduced the average number of diarrhea after 3 days of treatment by about 1.03 (MD=−1.03, 95% CI: -1.53, -0.53). There were no adverse drug reactions in both groups. Conclusion. The use of probiotic Saccharomyces boulardii can significantly improve the symptoms of diarrhea in children with acute gastroenteritis and reduce the duration of diarrhea symptoms and the time of hospitalization. Meanwhile, the RR of continued diarrhea in children after 1 and 3 days of Saccharomyces boulardii treatment and the frequency of diarrhea after 3 days of Saccharomyces boulardii treatment were decreased. It is also safe and does not increase the incidence of adverse drug reactions.
Intelligent Building Space Layout and Optimization Design Method Based on Biological Population Simulation
Authors: Wu Chunlei , Lin Yunhua
Published: September 2022

Smart buildings can store various types of data, analyze data at a faster speed, and quickly provide users with the most accurate and high-quality intelligent services through technical means. The main purpose is to meet the needs of users, to provide communication and a series of knowledge services for all professional participants, and to provide comfortable working resources and working environment for all professional participants to ensure the smooth implementation of the project and meet the construction engineering requirements. In this study, the spatial layout and optimization of intelligent buildings are carried out based on biological population simulation, and the following conclusions are drawn: (1) The emergence of multicore or multicore graphics converters reduces the cost and popularity of high-performance software platforms, and provides faster computing speeds for applications. A new platform and implementation method have been developed. Comparing marine biopopulation models relies on the i4Ocean platform. The i4Ocean platform is a computer platform for seascape information and virtual reality applications, including view management, production engine, and MVC core framework. (2) The swarm model simulates the movement of fish in a virtual ocean. Determine their behavioral changes based on determined behavioral conditions (e.g., in position, position, and velocity). As everyone in the group moves, the entire group is monitored for behavior. (3) Intelligent buildings involve many aspects of the social machine, such as building construction, which not only affects architecture, but also design. Smart construction helps improve quality, shorten production time, save resources, and control costs. It is an important part of the structural transformation of the supply side of the construction industry, and an important tool for the structural adjustment and modernization of the construction industry and greenhouses. (4) X2View is like the most popular configuration king, with integrated functions. Project software is placed on the X2View and sent to the door or touch screen for processing and monitoring. In the driver configuration interface, you can set the application frame time of the monitoring node and the real-time measurement time of the record value recording time frame.
Spatial-Temporal Characteristics Analysis of Air Pollution in Hubei Province Based on Functional Data Clustering
Authors: Chen Shiqi , Hu Mengting , Jiang Yajie , Xiong Yazhou
Published: September 2022

In recent years, China has attached great importance to ecological and environmental protection, upholding the important concept that clear waters and lush mountains are valuable assets. In order to explore the characteristics of air pollution in this area, the air quality index (AQI) is studied by clustering analysis of functional data. Firstly, the change curve of the air quality index is reduced by principal component analysis of functional data. Secondly, the basis coefficients of principal components are clustered by

K

-means. Finally, the characteristics of air pollution in Hubei Province are analyzed from the aspects of the time dimension and space dimension. The results show that 13 prefectural administrative regions in Hubei Province can be divided into four types of areas according to air quality changes, showing a trend of increasing pollution from north to south and showing a significant similar pattern in the time dimension, with significant seasonal characteristics.