bluuebunny/crossref_metadata_2025 huggingface dataset:
Simulation Analysis of Influencing Factors of fsQCA Calibration Membership
Authors: Yang Haiwen , Jiang Haifeng , Yang Yingya
Published: June 2022

Based on the analysis of the reasons, principles and classification of fuzzy set data calibration, we analyze that the fuzzy set data calibration membership is influenced by different data distribution, the crossover anchored points setting and transformation selection. Starting from the common problems existing in the current fuzzy-set qualitative comparative analysis (fsQCA) application research, this paper analyzes the possible reasons for ignoring the data calibration research, divides the relationship between the three dimensions of original data distribution, the crossover anchored points setting and calibration transformation and data calibration, and makes a visual analysis on their influence relationship through simulated data. Data distribution, crossover points anchored setting and transformation selection all have a significant impact on fsQCA calibration membership. The distribution of the original data will be a skew attribute consistent with the calibration membership. The cross combination of the high, medium and low setting of the crossover points and the selection of the calibration transformation will produce a significantly different calibration membership, and the crossover points anchored setting has a more obvious impact on the calibration membership than the selection of the calibration transformation.
Falsification-Aware Semantics for Temporal Logics and Their Inconsistency-Tolerant Subsystems: Theoretical Foundations of Falsification-Aware Model Checking
Authors: Kamide Norihiro
Published: June 2022

Model checking is well known to be a computer-aided method for verifying concurrent systems. Temporal logics and their Kripke-style semantics have been widely used in model checking. Falsification-aware Kripke-style semantics for temporal logics have been required for the theoretical basis of model checking because falsification plays a critical role in obtaining counterexample traces for the underlying object specifications in model checking. However, a useful falsification-aware Kripke-style semantics has yet to be developed for standard temporal logics. Hence, this study introduces two types of falsification-aware Kripke-style semantics for standard temporal logics that have been typically used in model checking. The equivalences among the proposed falsification-aware and standard Kripke-style semantics for standard temporal logics are proved. Furthermore, some inconsistency-tolerant subsystems of standard temporal logics are semantically obtained from the proposed falsification-aware Kripke-style semantics for standard temporal logics by deleting a characteristic condition on the labeling function of the semantics. The proposed semantic framework for standard and inconsistency-tolerant temporal logics is regarded as a unified framework for generalizing and combining the existing standard, inconsistency-tolerant, and many-valued semantic frameworks. This unified semantic framework is useful for obtaining a theoretical basis for generalized (inconsistency-tolerant) model checking, referred to here as falsification-aware model checking.
Weak dual pairs in Dirac–Jacobi geometry
Authors: Schnitzer Jonas , Tortorella Alfonso Giuseppe
Published: June 2022

Adopting the omni-Lie algebroid approach to Dirac–Jacobi structures, we propose and investigate a notion of weak dual pairs in Dirac–Jacobi geometry. Their main motivating examples arise from the theory of multiplicative precontact structures on Lie groupoids. Among other properties of weak dual pairs, we prove two main results. (1) We show that the property of fitting in a weak dual pair defines an equivalence relation for Dirac–Jacobi manifolds. So, in particular, we get the existence of self-dual pairs and this immediately leads to an alternative proof of the normal form theorem around Dirac–Jacobi transversals. (2) We prove the characteristic leaf correspondence theorem for weak dual pairs paralleling and extending analogous results for symplectic and contact dual pairs. Moreover, the same ideas of this proof apply to get a presymplectic leaf correspondence for weak dual pairs in Dirac geometry (not yet present in literature).
On a Hardy–Sobolev-type inequality and applications
Authors: Carvalho Jonison L. , Furtado Marcelo F. , Medeiros Everaldo S.
Published: June 2022

In this paper, we prove a new Friedrich-type inequality. As an application, we derive some existence and non-existence results to the quasilinear elliptic problem with Robin boundary condition [Formula: see text] where [Formula: see text] is an exterior domain such that [Formula: see text].
Time Synchronization Protocol for the KLJN Secure Key Exchange Scheme
Authors: Kish Laszlo B.
Published: June 2022

The information theoretically secure Kirchhoff-law-Johnson-noise (KLJN) key exchange scheme, similarly to quantum key distribution (QKD), is also potentially vulnerable against clock attacks, where Eve takes over the control of clock synchronization in the channel. This short note aims to introduce a time synchronization protocol scheme for Alice and Bob, which is resistant against arbitrary time delay attacks, both symmetric and asymmetric ones. We propose and explore various ways of clock synchronization for the KLJN system and propose an ultimate protocol that preserves time and hardware integrity under arbitrary attacks.
bHLHDB: A next generation database of basic helix loop helix transcription factors based on deep learning model
Authors: Öncül Ali Burak , Çelik Yüksel , Ünel Necdet Mehmet , Baloglu Mehmet Cengiz
Published: June 2022

The basic helix loop helix (bHLH) superfamily is a large and diverse protein family that plays a role in various vital functions in nearly all animals and plants. The bHLH proteins form one of the largest families of transcription factors found in plants that act as homo- or heterodimers to regulate the expression of their target genes. The bHLH transcription factor is involved in many aspects of plant development and metabolism, including photomorphogenesis, light signal transduction, secondary metabolism, and stress response. The amount of molecular data has increased dramatically with the development of high-throughput techniques and wide use of bioinformatics techniques. The most efficient way to use this information is to store and analyze the data in a well-organized manner. In this study, all members of the bHLH superfamily in the plant kingdom were used to develop and implement a relational database. We have created a database called bHLHDB (www.bhlhdb.org) for the bHLH family members on which queries can be conducted based on the family or sequences information. The Hidden Markov Model (HMM), which is frequently used by researchers for the analysis of sequences, and the BLAST query were integrated into the database. In addition, the deep learning model was developed to predict the type of TF with only the protein sequence quickly, efficiently, and with 97.54% accuracy and 97.76% precision. We created a unique and next-generation database for bHLH transcription factors and made this database available to the world of science. We believe that the database will be a valuable tool in future studies of the bHLH family.
Potassium oleate as an effective interface modifier for defect passivation in planar perovskite solar cells
Authors: Cai Fangfang , Wu Jihuai , Pan Weichun , Li Guodong , Zhu Sijia , Chen Xia , Ke Chaoran , Yang Jinhui , Lan Zhang , Lin Jianming
Published: June 2022

As a typical of the next generation photovoltaic technology, perovskite solar cells (PSCs) have attracted extensive attention in industry and academia because of their outstanding excellent performance and unprecedented growing efficiency. However, commercial applications of PSCs require further improvements in efficiency and stability, and the defects and its induced non-radiation loss become the research hotspots. Herein, potassium oleate (KOA) as an effective modifier is introduced at the interface of perovskite/spiro. The K[Formula: see text] ions of KOA can penetrate into the perovskite bulk to fill the positive charge vacancy; the-COO[Formula: see text] group of KOA can coordinate with Pb[Formula: see text] and passivate defects; the hydrophobic long chain olefins of KOA can cover on perovskite, and thus, ameliorate the environmental stability of the devices. As a result, the multi-functional KOA-modified PSC achieves an impressive efficiency of 23.22%, along with high open circuit voltage ([Formula: see text] of 1.16 V.
Decomposition dimension of Cartesian product of some graphs
Authors: Reji T. , Ruby R.
Published: June 2022

For an ordered [Formula: see text]-decomposition [Formula: see text] of a connected graph [Formula: see text], the [Formula: see text]-representation of an edge [Formula: see text] is the [Formula: see text]-tuple [Formula: see text], where [Formula: see text] represents the distance from [Formula: see text] to [Formula: see text]. A decomposition [Formula: see text] is resolving if every two distinct edges of [Formula: see text] have distinct representations. The minimum [Formula: see text] for which [Formula: see text] has a resolving [Formula: see text]-decomposition is its decomposition dimension [Formula: see text]. In this paper, decomposition dimension of Cartesian product of paths, cycles and stars is studied.
Black Holes or Objects without Event Horizon?
Authors: Verozub Leonid
Published: June 2022

This paper examines the question of whether the generally accepted interpretation of a supermassive object in M87 is the only one possible. There are grounds for this, in particular, due to the detection of a magnetic field in its vicinity. For this purpose, the stability of self-gravitating objects is investigated based on the correct definition of the energy of gravitation in the framework of the bi-metric approach to the theory. It is shown that supermassive objects can be stable configurations of a partially degenerate Fermi gas, the radius of which is less than their Schwarzschild radius.
Forward-backward Transliteration of Punjabi Gurmukhi Script Using N-gram Language Model
Authors: Goyal Kapil Dev , Abbas Muhammad Raihan , Goyal Vishal , Saleem Yasir
Published: June 2022

Transliterating the text of a language to a foreign script is called forward transliteration and transliterating the text back to the original script is called backward transliteration. In this work, we perform both forward as well as backward transliteration on Punjabi. We transliterate Punjabi person names from Gurmukhi script to English Roman script and from English Roman script back to Gurmukhi script using n-gram language model. We used more than one million parallel entities of person names in Gurmukhi and Roman script as the training corpus. We generated English to Punjabi and Punjabi to English n-grams databases from the corpus. To get better results, we tried to create as long n-grams as possible ranging from bi-gram to 30-gram. Our n-grams database contains more than 10 million n-grams, with each n-gram having multiple mappings of the other script. The most challenging part is to find the mapping for the given n-gram from the parallel name entity while creating n-grams databases. As per the orthography rules, the same combination of letters may have different pronunciation, depending upon its location in the word. Therefore, we categorized n-grams into starting, middle, and ending n-grams and used them accordingly in the transliteration process. The transliteration process works like the merge sort. We start searching the longest possible n-gram in the database and split the string recursively until the match is found. The transliterated strings are merged back to form the final output. In English to Punjabi transliteration, we achieved 96% accuracy using gold standard and 99.14% accuracy using minimum edit distance. In Punjabi to English transliteration, the result showed 96.85% and 99.35% accuracy for the gold standard and minimum edit distance, respectively.
Agrochemicals, Environment, and Human Health
Authors: Devi P. Indira , Manjula M. , Bhavani R.V.
Published: June 2022

Global consumption of agrochemicals continues to rise, despite growing evidence of their adverse effects on environmental quality and human health. The extent of increase varies across nations, by type of chemical compounds and by severity of the detrimental impacts. The differential impacts are largely attributable to the level of technology adoption and regulation as well as their enforcement and compliance. The article highlights gaps in technical, legal, and social aspects, which include the paucity of holistic and long-term ecological impact assessment frameworks and lack of consideration for the social dimensions of pesticide use in regulatory decisions. Bridging these gaps, establishing global cooperation for regulation and governance, and a regional/national-level monitoring mechanism are suggested. This, complemented with a policy shift from the current approach of productivity enhancement to augmenting agroecosystem services, would encourage sustainable and nature-positive agriculture equipped to meet the multiple challenges of food security, ecological safety, and climate resilience.
Artificial Intelligence and Machine Learning for Lead-to-Candidate Decision-Making and Beyond
Authors: McNair Douglas
Published: June 2022

The use of artificial intelligence (AI) and machine learning (ML) in pharmaceutical research and development has to date focused on research: target identification; docking-, fragment-, and motif-based generation of compound libraries; modeling of synthesis feasibility; rank-ordering likely hits according to structural and chemometric similarity to compounds having known activity and affinity to the target(s); optimizing a smaller library for synthesis and high-throughput screening; and combining evidence from screening to support hit-to-lead decisions. Applying AI/ML methods to lead optimization and lead-to-candidate (L2C) decision-making has shown slower progress, especially regarding predicting absorption, distribution, metabolism, excretion, and toxicology properties. The present review surveys reasons why this is so, reports progress that has occurred in recent years, and summarizes some of the issues that remain. Effective AI/ML tools to derisk L2C and later phases of development are important to accelerate the pharmaceutical development process, ameliorate escalating development costs, and achieve greater success rates.
Review—The Synthesis and Characterization of Recent Two-Dimensional Materials for Energy Storage Applications
Authors: Nehate Shraddha Dhanraj , Sundaresh Sreeram , Saikumar Ashwin Kumar , Sundaram Kalpathy B.
Published: June 2022

The ever-increasing energy consumption has been projected to burden renewable energy sources. It is imperative to look for high-performance clean energy storage systems to sustain future energy demands. Among all the environmentally friendly and efficient energy storage options, supercapacitors are one of the most researched devices. Supercapacitors possess excellent electrochemical properties such as high-power density, superior cyclic stability, fast charging-discharging rates, and high specific capacitance that makes them a fascinating candidate. To improve the energy storage capacity, the two-dimensional counterpart of the supercapacitors is being investigated extensively and manifested unique electrochemical properties. This article thoroughly summarizes the synthesis and characterization techniques adopted for the most recent two-dimensional supercapacitor electrode materials. We focus on the family of carbon-based materials, transition metal oxides and hydroxides, MXenes, and transition metal dichalcogenides that can be employed for clean energy storage applications. The performance of these materials is discussed and compared based on their synthesis technique.
The χ‐Boundedness of (P2 ∪ P3)‐Free Graphs
Authors: Wang Xiao , Zhang Donghan
Published: June 2022

In the early 1980s, Gyárfás introduced the concept of the χ‐bound with χ‐binding functions thereby extending the notion of perfectness. There are a number of challenging conjectures about the χ‐bound. Let χ(G), ω(G), and Δ(G) be the chromatic number, clique number, and maximum degree of a graph G, respectively. In this paper, we prove that if G is a triangle‐free and (P2 ∪ P3)‐free graph, then χ(G) ≤ 3 unless G is one of eight graphs with Δ(G) = 5 and χ(G) = 4, where the eight graphs are extended from the Grötzsch graph as a Mycielskian of a 5‐cycle graph. Moreover, we also show that χ(G) ≤ 3ω(G) if G is a {P2 ∪ P3, W4}‐free graph.
Construction of Economic Security Early Warning System Based on Cloud Computing and Data Mining
Authors: Yuan Guanghui , Xie Fei , Tan Huiling
Published: June 2022

Economic security is a core theoretical issue in economics. In modern economic conditions, the ups and downs caused by economic instability in any economic system will affect the stability of the financial market, bring huge losses to the economy, and affect the development of the whole national economy. Therefore, research on the regularity of economic security and economic fluctuations is one of the important contents to ensure economic stability and scientific development. Accurate monitoring and forecasting of economic security are an indispensable link in economic system regulation, and it is also an important reference factor for any economic organization to make decisions. This article focuses on the construction of an economic security early warning system as the main research content. It integrates cloud computing and data mining technologies and is supported by CNN-SVM algorithm and designs an early warning model that can adaptively evaluate and warn the economic security state. Experiments show that when the CNN network in the model uses ReLU activation function and SVM uses RBF function, the prediction accuracy can reach 0.98, and the prediction effect is the best. The data set is verified, and the output Q province’s 2018 economic security early warning comprehensive index is 0.893. The 2019 economic security early warning index is 0.829, which is consistent with the actual situation.
Creep Mechanical Properties of Granite under Combined Axial Compression and Water Pressure and Support Characteristics of Surrounding Rock
Authors: Li Xiaolong , Zhang Chong , He Jianhua , Deng Xingfu
Published: June 2022

Granite is a common brittle rock material in underground surrounding rock, such as Yebatan Hydropower Station. The underground cavern of Yebatan Hydropower Station has characteristics of large span, high ground stress, fault development, and abundant groundwater. Long-term stability of surrounding rock is a key factor for the project safe operation. Especially for the surrounding rock of large underground cavern, its long-term rheological stability must be considered. In this paper, taking the surrounding rock of a large underground cavern in Yebatan Hydropower Station as research object, creep mechanical test of the combined axial pressure and water pressure under normal water level and dead water level is carried out, and long-term damage mechanism of rock under different water confining pressures is revealed. Based on rock mechanical properties, calculation and analysis of surrounding rock stability under different support time are carried out, and optimal support time is also discussed.
Volumetric Evaluation of Maxillary Lateral Incisor Root Resorption due to Positional Variations of Impacted Canine
Authors: Razeghinejad Mohammed Hossein , Bardal Roghieh , Shahi Saeid , Mortezapoor Elham , Mostafavi Maryam
Published: June 2022

Introduction. The purpose of this study was to investigate the relationship of the volume of lateral incisor resorption and impacted canine features. Materials and Methods. This study consisted of CBCT images of 47 samples with unilateral impacted maxillary canine (13 males and 34 females). The volume of lateral incisors in impacted side and nonimpacted side was calculated with the Mimics 10.01 software. Canine and lateral incisor angulations were measured in panoramic reformatted images. The canine cusp tip distance from midpalatal suture was measured in axial cross-section images. Results. The difference between two sides volume was considered as the mean volume of resorption (MVR) that was statistically significant (

P
<
0.001

). MVR was not statistically significant between two sexes (

P
=
0.95

), in buccopalatal and mesiodistal positions of impacted canine, and in different angulations or distances of the impacted canine to midline (

P
>
0.05

). The concurrent effect of the canine distance to the midline and the angle of the canine with the lateral incisor on the MVR were statistically significant (

P
=
0.049

). Conclusion. The maximum rate of lateral root resorption is when the distance from the canine to the midline is less than 5 mm and the angle of the canine to the lateral incisor is 30–60 degrees.
Towards the First Multiepitope Vaccine Candidate against Neospora caninum in Mouse Model: Immunoinformatic Standpoint
Authors: Shams Morteza , Maleki Bahman , Kordi Bahareh , Majidiani Hamidreza , Nazari Naser , Irannejad Hamid , Asghari Ali
Published: June 2022

Neospora caninum is an economically significant parasite among livestock, particularly in dairy cattle herds, causing storm abortions. Vaccination seems necessary to limit the infection and its harsh consequences. This is the first steps towards developing a multiepitope vaccine candidate against N. caninum using in silico approaches. High‐ranked mouse MHC‐binding and shared linear B‐cell epitopes from six proteins (SRS2, MIC3, MIC6, GRA1, IMP‐1, and profilin) as well as IFN‐γ‐inducing epitopes (from SAG1) were predicted, screened, and connected together through appropriate linkers. Finally, RS‐09 protein (TLR4 agonist) and histidine tag were added to N‐ and C‐terminal of the vaccine sequence, yielding 486 residues in length. Physicochemical properties showed a stable (instability index: 27.23), highly soluble, antigenic (VaxiJen score: 0.9554), and nonallergenic candidate. Secondary structure of the multiepitope protein included 58.85% random coil, 20.99% extended strand, and 20.16% alpha helix. Also, the tertiary structure was predicted, and further analyses validated a stable interaction between the vaccine model and mouse TLR4 (binding score: ‐1261.6). Virtual simulation of immune profile demonstrated potently stimulated humoral (IgG+IgM) and cell‐mediated (IFN‐γ) responses upon multiepitope vaccine injection. Altogether, a potentially immunogenic vaccine candidate was developed using several N. caninum proteins, with the capability to elicit IFN‐γ upsurge and other components of cellular immunity, and can be used in prophylactic purposes against neosporosis.
Effectiveness and Safety of Nonvitamin K Oral Anticoagulants Rivaroxaban and Apixaban in Patients with Venous Thromboembolism: A Meta-Analysis of Real-World Studies
Authors: Wu Olivia , Morris Stephen , Larsen Torben Bjerregaard , Skjøth Flemming , Evans Alex , Bowrin Kevin , Wojciechowski Piotr , Margas Wojciech , Huelsebeck Maria
Published: June 2022

Background. Rivaroxaban and apixaban are the most widely used nonvitamin K oral anticoagulants (NOACs) in patients with venous thromboembolism (VTE). This meta-analysis evaluates the effectiveness and safety of both NOACs versus standard of care (SoC) in real-world practice. Methods. Real-world evidence (RWE) studies were identified through a systematic literature review conducted between January 2012 and July 2020, using Embase, MEDLINE, and the websites of cardiological, hematological, and oncological associations. Eligible RWE studies recruited adult patients with deep vein thrombosis and/or pulmonary embolism and presented a comparison between rivaroxaban and apixaban versus SoC, consisting either of vitamin K antagonists, heparins, or combinations thereof. Hazard ratios (HRs) for the comparison between NOACs and SoC were extracted from the relevant studies or estimated based on the reported binary data. The between-treatment contrasts were reported as HRs with associated 95% confidence intervals. Results. A total of 65 RWE studies were identified and considered relevant for the meta-analysis. Compared with SoC, both rivaroxaban and apixaban were associated with reduced risks of recurrent VTE and a lower rate of major bleeding events. Patients treated with rivaroxaban were at a lower risk of all-cause death compared with those receiving SoC (

HR
=
0.56

[0.39-0.80]), while evidence for apixaban from the identified studies was insufficient to demonstrate a statistically significant change in mortality (

HR
=
0.66

[0.30-1.47]). Conclusion. This analysis indicates that in real-world practice, rivaroxaban and apixaban are associated with a lower risk of recurrent VTE and major bleeding events compared with SoC. Survival benefit in patients treated with rivaroxaban was also observed.
Some Fixed-Circle Results with Different Auxiliary Functions
Authors: Kaplan Elif , Mlaiki Nabil , Taş Nihal , Haque Salma , Souayah Asma Karoui
Published: June 2022

As the generalization of the fixed-point theory, the fixed-circle problems are interesting and notable geometric constructions. In this paper, we prove that some new necessary conditions are investigated for the existence of a fixed circle of a given self-mapping in

G

-metric spaces. The well-known Braincari and Chatterjea contractive conditions are generalized for proving the uniqueness of obtained theorems. Finally, an application to parametric rectified linear unit activation functions are given to show the importance of studying the fixed-circle problem.
Uranium Recovery from Phosphates for Self-Sufficient Nuclear Power in the Eastern Mediterranean
Authors: Haidar Nassar H. S.
Published: June 2022

Production of phosphate fertilizers (PF), without uranium recovery, amounts to dispersing uranium compounds on agricultural fields. These compounds are naturally hidden in phosphate rock deposits prior to processing. Such a dispersion is a cumulative environmental damage, that may become rather catastrophic in few hundred years, under the current rates & impurities of phosphate fertilization of agricultural lands. It is also an avoidable irreversible waste of one of the world’s major energy resources. This study demonstrates quantitatively the low impact of U costs on the nuclear power generation costs, which happens, so far, to be a main reason for nonrecovery of uranium from the present PF industry. It reports on novel procedures for (i) estimating the required U feed to nuclear power plants (NPPs), (ii) pricing U as a function of its cumulative world production, and (iii) for quantifying U accumulation in phosphate fertilized lands. We also demonstrate that countries of the eastern Mediterranean can, in the long run, become collectively U partially self-sufficient, by recovering U from their phosphate resources, to power 13.2% of their entire electric energy generation contemporary needs.
Dynamic Response Analysis of Super Shallow‐Buried Rectangular Tunnel
Authors: Su Sanqing , Yin Tao , Cao Zhen , Lei Bin , Liu Zhao , Lin Wenxu , Kuang Anyuan
Published: June 2022

Relying on the project of the open‐cut municipal tunnel undercrossing Ankang Freight V yard, the train dynamic response and seismic response of ultrashallow‐buried rectangular tunnel of the lower interchange are studied, respectively, by combining the method of field measurement and numerical simulation. The results show that under the action of train vibration load, the dynamic stress response of the top plate midspan and the upper end of the side wall of the tunnel cross section directly below the rail is the most significant, and the dynamic stress response of the bottom plate is the smallest. Under the rare earthquake, the tunnel structure has large transverse deformation, in which the transverse displacement of the tunnel roof is the largest. At the same time, there is a large stress concentration at the variable section of the tunnel.
The Innovation of Blended Teaching Mode of College English in Mobile Network Environment
Authors: Ren Yanqing
Published: June 2022

With the rapid development of economic globalization, a new type of mobile learning mode has emerged. Currently, the life of contemporary college students is inseparable from cell phones and computers, and such electronic devices are considered the important medium of mobile learning in the second classroom. In the process of education reform and “Internet +” integration, the blended teaching mode relying on the mobile network environment is favored by college English teachers. Furthermore, to improve the quality of English teaching, English teachers use the flipped classroom format to fully integrate the traditional classroom with online courses. In such format, a comprehensive, diversified assessment and evaluation system is built effectively. Specifically, starting from the current situation of college English teaching, the article analyzes and researches the flipped classroom hybrid teaching mode in four aspects to provide reference values for related scholars. Considering mentioned characteristics and advantages, the necessity and feasibility of adopting mobile learning mode in the second classroom teaching of college English are analyzed in this paper. Meanwhile, the application mode of specific devices for better learning is considered for better learning.
Emotion Recognition of Online Education Learners by Convolutional Neural Networks
Authors: Ye Fulan
Published: June 2022

At present, the facial expression recognition model in video communication has problems such as weak network generalization ability and complex model structure, which leads to a large amount of computation. Firstly, the Inception architecture is adopted as a design philosophy. The Visual Geometry Group Network (VGGNet) model is improved. Multiscale kernel convolutional layers are constructed to obtain more expressive features. Secondly, the attention mechanism is integrated into a multiscale feature fusion network to form a multiattention mechanism Convolutional Neural Network (CNN) model. Novel spatial and multichannel attention models are designed. The effects of redundant information and noise are reduced. Finally, experiments are carried out on the Fer2013 dataset and the Extended Cohn-Kanade Dataset (CK+) to verify the detection accuracy of the model. The results show that the Delivered Duty Unpaid (DDU) loss can be used for facial expression recognition in complex environments. After the attention module is added, the overall recognition accuracy of the network on Fer2013 and CK+ has been improved to varying degrees. The addition of the channel attention module has a more obvious effect on the recognition accuracy compared with the spatial attention module. The addition of the attention module enables the network to increase the attention to error-prone samples. The improved network model can better extract the key features of facial expressions, enhance the feature discrimination ability, and improve the recognition accuracy of error-prone expressions. The accuracy rate of facial expression recognition with larger movements is over 98%. Facial expressions are an important way of communication between people, and online video has greatly limited this communication method. The proposed CNN model based on multiscale feature fusion will effectively solve these network limitations and have an important and positive impact on future network information exchange.
[Retracted] Meta‐Analysis of the Main Components of Nanophotodynamics Combined with Traditional Chinese Medicine in the Treatment of Tumors
Authors: Liu Ying , Li Yanwei , Wen Yulong
Published: June 2022

At present, cancer has become one of the main reasons that affect people’s life and health. With the development of nanomaterials and nanotechnology, tumor phototherapy such as photodynamic therapy, photothermal therapy, and combination therapy has been developed rapidly. Based on this, this paper proposes to take gastric cancer, esophageal cancer, liver cancer, intestinal cancer, and pancreatic cancer as the starting point and apply the methods of network meta‐analysis to comprehensively carry out the horizontal comprehensive evaluation of the efficacy and safety of traditional Chinese medicine injections. It is hoped that this article can provide high‐quality evidence‐based medicine for clinical decision‐making and promote clinical rational drug use. The purpose of this paper is to study the meta‐analysis of the main components of tumor treatment with nanophotodynamics combined with traditional Chinese medicine. The experimental results in this paper show that non‐small‐cell lung cancer has the largest number of evaluations, with 77 evaluations, accounting for 38.5% of the total frequency of tumor types. This may be related to the fact that lung cancer ranks first in the morbidity and mortality of malignant tumors. It is followed by the evaluation times of liver cancer and gastric cancer, which were 29 times and 25 times, respectively, accounting for 14.5% and 12.5% of the total frequency of tumor types. The therapeutic effect of SM‐NP light therapy group on tumor was significantly higher than that of free Ce6 light therapy group, and its destruction and killing effect on tumor tissue was greater.
Online Troll Reviewer Detection Using Deep Learning Techniques
Authors: Al-Adhaileh Mosleh Hmoud , Aldhyani Theyazn H. H. , Alghamdi Ans D.
Published: June 2022

The concentration of this paper is on detecting trolls among reviewers and users in online discussions and link distribution on social news aggregators such as Reddit. Trolls, a subset of suspicious reviewers, have been the focus of our attention. A troll reviewer is distinguished from an ordinary reviewer by the use of sentiment analysis and deep learning techniques to identify the sentiment of their troll posts. Machine learning and lexicon-based approaches can also be used for sentiment analysis. The novelty of the proposed system is that it applies a convolutional neural network integrated with a bidirectional long short-term memory (CNN–BiLSTM) model to detect troll reviewers in online discussions using a standard troll online reviewer dataset collected from the Reddit social media platform. Two experiments were carried out in our work: the first one was based on text data (sentiment analysis), and the second one was based on numerical data (10 attributes) extracted from the dataset. The CNN-BiLSTM model achieved 97% accuracy using text data and 100% accuracy using numerical data. While analyzing the results of our model, we observed that it provided better results than the compared methods.
Application Value Evaluation of Blockchain Technology in Innovation and Entrepreneurship Information Platform for College Students
Authors: Li Shixiao
Published: June 2022

The current collegiate innovation and entrepreneurship information network works in a centralized manner, and there is a centralized trust dilemma. Malicious administrators can use their own rights to achieve public and private purposes. To solve this problem, a blockchain technology based on decentralization was introduced into the innovation as well as an entrepreneurship information platform for college students. It is critical to understand how to assess the usefulness of blockchain in innovation and entrepreneurship information platforms. This research mixes it with the current popular artificial intelligence trend and offers a neural network to assess the value of blockchain technology in terms of creativity and as an entrepreneurship information platform. The contents are as follows: (1) an application value evaluation method with an improved residual neural network is proposed. First, an improved data pooling layer is constructed by using three consecutive convolutional layers in series. The approach then has a significant feature learning ability by increasing the receptive field, thanks to an atrous residual block that combines atrous convolution and the residual block. Finally, the dropout method is introduced to avoid the negative impact of overfitting. (2) An application value evaluation method based on skip connection and residual network is proposed. With the inception module, this method creates a better data pooling layer and adds residual connections. The skip connection line is built in the residual block, which improves the residual block’s learning efficiency for feature information. The ordinary convolution in the residual block with a skip connection line is replaced with atrous convolution, and an atrous residual block with a skip connection line is designed. Finally, to construct a neural network, the two designed leftover blocks are connected end-to-end.
Three-Dimensional Landscape Rendering and Landscape Spatial Distribution of Traditional Villages Based on Big Data Information System
Authors: Li Jianjian , Wei Pan
Published: June 2022

Traditional villages refer to the villages that formed earlier, are rich in traditional resources, and have various values and must be protected. This paper aims to study how to draw three-dimensional landscapes of traditional villages based on the big data information system. This paper puts forward the problem of 3D landscape rendering, which is based on big data and modeling, and then elaborates around the concept of data mining and related algorithms and designs and systematically tests 3D landscape rendering. The experimental results show that when the number of rendered patches is less than 120193 between 120193 and 242029, the system can run smoothly. It can achieve acceptable and relatively smooth operation; when it exceeds 242029, the system is obviously stuck. The design scheme of the three-dimensional landscape geographic information system of the traditional villages is reasonable and feasible, the operation is stable, and the expected research goals are achieved.
Admission Circulating Cell‐Free DNA Levels as a Prognostic Factor in Pediatric Burns
Authors: Halpern D. , Cohen A. , Sharon N. , Krieger Y. , Silberstein E. , Michael T. , Douvdevani A. , Shoham Y.
Published: June 2022

Background. Burn injuries in children are a major physical and psychological trauma, often a severe condition with long‐term consequences. Current methods of assessing the extent of burn injuries on admission are inaccurate. Circulating cell‐free DNA (cfDNA) is a potential marker of tissue damage that may be useful in burn care. Objective. To explore the use of cfDNA admission levels as a prognostic marker of pediatric burn severity and outcome. Methods. cfDNA levels of 38 pediatric burn patients (otherwise healthy) and 12 matched pediatric controls (minor elective surgery patients) admitted to our center were quantified by a direct fluorometric assay. Results. We found significantly higher admission cfDNA levels in the patient group (median 724 ng/ml, range 44‐4405), compared to the control group (median 423 ng/ml, range 206‐970, Mann–Whitney, P = 0.03) and a significant difference between cfDNA levels of partial‐thickness burns (median 590 ng/ml, range 44‐2909) and full‐thickness burns (median 2394 ng/ml, range 528‐4405, Mann–Whitney, P = 0.01). We also found significant correlations between cfDNA levels and hospitalization duration (Spearman, R = 0.42, P < 0.01) and undergoing surgical procedures (Spearman, R = 0.40, P < 0.01). PICU admission did not correlate to cfDNA levels (Spearman, R = 0.14, P = NS). Discussion. Admission cfDNA levels may be a valuable objective tool for assessing the severity of pediatric burn injuries on admission, including correlations with the length of hospitalization and surgical burden. Conclusion. Admission cfDNA levels may be a promising novel pediatric burn assessment method. Further investigation of cfDNA levels in healthy children standardized to age and larger cohorts are needed to establish cfDNA as a valuable prognostic factor for pediatric burn injury.
Design and Application of Vocal Music Teaching Management System
Authors: Sudu Langteng
Published: June 2022

This article proposes a virtual reality-based management system for vocal music instruction. Additionally, this article proposes an improved algorithm for automatic vocal main melody extraction. The pitch saliency function calculation method is improved based on the spectral characteristics of vocal music signals in order to reduce the computational complexity and time required to extract the vocal main melody. The model presented in this article has the potential to increase the recognition accuracy of the main melody model, decrease the rate of melody localization false alarms, and increase the overall accuracy of vocal main melody extraction. Additionally, this article incorporates the extraction algorithm into the management system, making it convenient for teachers to use during instruction.
Research on Recommendation of College Mental Health Teaching Materials Based on Improved Deep Learning Algorithm
Authors: Zhou Yunxia , Li Lei
Published: June 2022

In order to meet the differentiated needs of students and improve the satisfaction of college mental health textbook recommendation, a college mental health textbook recommendation scheme based on improved deep learning algorithm is proposed. Based on the analysis of the principle of deep learning data recommendation system, the data interest is calculated according to the browsing records of students on college mental health textbooks. Combine the deep learning algorithm and collaborative filtering algorithm to collect the demand data of college mental health textbooks, then use the Naive Bayesian classification method to divide the college mental health textbooks into interested and uninterested parts, and recommend the interested college mental health textbooks to the students in need. Experiments show that the longest recommendation time of the college mental health textbook recommendation scheme based on the improved deep learning algorithm proposed in this paper is 4.5 min, the highest recommended recall rate is 95.18%, the average accuracy is 97.2%, the highest content richness is 0.8, the system stability coefficient is 1.06, and the overall average praise rate is 97.79%. It has a good recommendation effect.
Construction of Nursing Quality Evaluation Index System Based on Big Data Assisted Analysis in the Context of Intelligent Medical Treatment
Authors: Wang WanLi , Li Xia , Chen JunGuo , Cui Ying
Published: June 2022

Objective. To improve and ensure the quality of nursing (QOC), scientifically and effectively improve nursing management, and improve the hospital QOC overall level and construction of nursing quality evaluation index suitable for China (NQEI) system. Method. This research is based on the fuzzy neural network (FNN) big data analysis technology, and temperature of hospital patients,blood pressure, blood sugar, blood uric acid, and other data were analyzed, assisted by health big data NQEI. With this, in smart medicine (WIT120), under the background of big data assisted analysis NQEI system and the nursing satisfaction index of patients, inpatient management index, quality of inpatient management, and quality of inpatient management, the coupling of four aspects is analyzed. Result. The results showed that, in the coupling analysis of nursing satisfaction indicators, using the big data assisted NQEI system, the comprehensive satisfaction of patients with nursing was 0.963, and the complaint rate is −0.963. In the coupling analysis of patient hospitalization management indicators, assisted by big data NQEI, the average length of stay of patients in the system is −0.982, postoperative recovery time is −0.996, and ICU time is −0.892. In the coupling analysis of patient hospitalization management quality, assisted by big data assisted NQEI, the inpatient infection of the system is −0.982, the postoperative rehabilitation time was −0.996, and the ICU time was −0.892. In the coupling analysis of patient prognosis management quality, assisted by big data assisted NQEI, the re-examination compliance rate of patients in the system is 0.997, and the medication compliance rate is 0.995, indicating that it is assisted by the big data NQEI system and has high correlation with real data. Conclusion. Through analysis, it is proved that using big data to assist the NQEI system, patients’ nursing satisfaction index, inpatient management index, inpatient management quality, and inpatient management quality are better than those using the quality control circle NQEI high system, and the results are credible. However, its clinical application is not perfect and needs further verification.
Environmental Design and Sustainable Development of Ecological Environment by Big Data Analysis and Computing: A Case Study of Tianjin
Authors: Wei Guangsen , Chen Weidong , Yang Hude , Tsai Sang-Bing
Published: June 2022

Sustainable development, as a new idea of development, has become a source of worldwide concern. Many elements, such as society, economics, resources, and the environment, have a role in the long-term evolution of the ecological environment. It is an intricate mechanism. Based on previous research, this study investigates the relationship between environmental design and the long-term evolution of the ecological environment in the new age. The following are the specifics. First, the conceptual model of ecological sustainable development is constructed, and the “low-carbon idea” environmental design approach is addressed. Then, using Tianjin as an example, an assessment method for environmental sustainable development in environmental design is constructed based on summarizing past studies. The ecological features are included in the DPSIR model, and the “low-carbon concept” environmental design method is used in Tianjin Binhai New Area. The findings show that, with the continued development of Binhai New Area, the adjustment of industrial structure, and the gradual improvement of people’s awareness of urban sustainable development, the ecological environment’s sustainability index will improve, with per capita ecological carrying capacity rising from 2019 and the per capita ecological carrying capacity of agricultural and livestock products, which are 0.09 hm2 and 0.09 hm2, respectively, rising significantly. Since 2019, the per capita ecological footprint has also declined.
Application of Big Data Technology in News Media Scene Visualization Based on Internet of Things (IoTs)
Authors: He Mengfan , Li Yangbo
Published: June 2022

The rapid development of information technology has made people quickly enter the data era, and the big data era has made visualization technology that can process and analyze data with more and more attention. At present, most of the data news visualization explorations of domestic network media remain at the level of static infographics. The Data News and Visualization Laboratory of New Media has developed a series of visual news works displayed in the form of interactive dynamic graphs. This article will discuss the application scenarios, technical architecture, and key technologies of the Internet of Things in news media through the analysis of the correlation between the Internet of Things and news media.