bluuebunny/crossref_metadata_2025 huggingface dataset:
Mercury concentration in hair collected from women in artisanal small-scale gold mining areas in Camarines Norte, Philippines
Authors: Shibata Harune , Takenaka Chisato , Murao Satoshi , Sera Koichiro
Published: August 2022

After the conclusion of the Minamata Convention on Mercury, the use of mercury (Hg) has been prohibited worldwide, except in some developing countries. The Republic of the Philippines is one of the 128 signatories of the Convention. There are many artisanal and small-scale gold mining (ASGM) operations in the Philippines that still use Hg to amalgamate gold. In order to know the direct effect of exposure to Hg on women’s hair, we performed the proton-induced X-ray emission analysis of Hg concentrations in the hair samples collected from women at risk of Hg contamination, in both ASGM and non-ASGM areas in Camarines Norte, Philippines. At the same time of the hair sampling, we also conducted interviews with the women about their lives. From the analysis results, we found that the range of Hg concentrations in the hair samples was at a safe level, with no significant difference between the ASGM and non-ASGM areas. An analysis of the effect of diet on Hg concentrations in the hair samples showed a tendency toward higher Hg concentrations in women who ate more fish. Our results through hair analysis did not show a direct effect of exposure to atmospheric Hg, but further survey of local people should be necessary to reduce the risk of Hg contamination in women even after the use of Hg in ASGM eventually comes to an end.
Barrow holographic dark energy model with GO cut-off - An alternative perspective
Authors: Nandhida Krishnan P. , Mathew Titus K.
Published: August 2022

Recently, Barrow holographic dark energy (BHDE), based on Barrow entropy, has been proposed to describe the late acceleration of the universe. Contrary to the earlier analysis of this model in the literature, we consider the BHDE with the Granda–Oliveros length as IR cut-off, as a dynamical vacuum, having a constant equation of state [Formula: see text] We have analytically solved for the Hubble parameter and studied the evolution of cosmological parameters. The model is compared with the observational data on Hubble parameter (OHD36) and Supernovae type Ia (SN Ia), the pantheon data. In the absence of interaction between the dark sectors, we found that the model predicts a [Formula: see text]CDM-like evolution of the universe with an effective cosmological constant. In this case, the model is found to satisfy the generalized second law (GSL), irrespective of the value of the Barrow index. The interaction also shows the safe validity of GSL, for the extracted value of the Barrow index, [Formula: see text]. The thermodynamic analysis of the model predicts an end de Sitter phase of maximum entropy. We performed a dynamical system analysis, which reveals that the end de Sitter phase is stable. Furthermore, we performed the Information Criterion analysis using Akaike and Bayesian Information Criterion to compare the statistical compatibility of the present model with the standard [Formula: see text]CDM model.
A COMPARATIVE ANALYSIS REPORT ON THE MULTI-WAVE FRACTIONAL HIROTA EQUATION IN NONLINEAR DISPERSIVE MEDIA
Authors: GAO XIANGJUN , FARIDI WAQAS ALI , ASJAD MUHAMMAD IMRAN , JHANGEER ADIL , ALEEM MARYAM , ALAM MOHAMMAD MAHTAB
Published: August 2022

The propagation attributes of waves and its modeling maneuvers have a significant role in maritime, coastal engineering, and ocean. In the geographical fields, waves are primary source of environmental process owed to energy conveyance on the floating structure or on the synthetic field. This study aims to investigate the new auxiliary equation method to obtain analytical solutions of the nonlinear Hirota model with fractional order. The fractional model is developed by utilizing Riemann–Liouville, [Formula: see text], and the fractional-order Atangana–Baleanu differential operator in Riemann–Liouville sense. The solitonic patterns of the nonlinear fractional Hirota equation successfully surveyed, where the exact solutions are presented by rational, trigonometric, hyperbolic, and exponential functions. The contravene of surveyed results with the substantially recognized result is executed which states the novelty of obtained results. Three dimensional as well as two-dimensional comparison is presented for a couple of Hirota model solutions which are revealed diagrammatically for appropriate parameters by using Mathematica. We strongly believe that this study will help physicists to predict some new conceptions in the field of mathematical physics.
Novel Non-Convex Regularization for Generating Double Threshold Value in Penalized Least Squares Regression
Authors: Kittisuwan Pichid , Thaiwirot Wanwisa
Published: August 2022

A lot of works in machine learning (ML) usually use components which are built by signal processing, such as wavelet and Fourier coefficients, for computations; therefore, many problems in signal processing affect ML algorithms. Consequently, we try to solve linear inverse problems in signal processing, such as the classical denoising and deconvolution problems, in this work. The penalized least squares regression (PLSR), also called as the proximity operator, of the non-convex regularization, can solve various problems in signal processing. In the classical denoising problem, the PLSR with the double threshold value is more flexible than the PLSR with the single threshold value. Therefore, we propose the novel non-convex regularization which can build the PLSR with the double threshold value. The proposed regularization is based on good properties of the minimax-concave (MC) regularization. We also present novel PLSRs of the MC and proposed regularizations where these PLSRs have closed-form solutions and the relationship to the group of considered components, also known as the multivariate case, together. We compare proposed methods with state-of-the-art methods in the classical denoising and deconvolution problems. Here, we use the majorization-minimization (MM) method for comparing the performance of regularizations in the deconvolution problem. Experimental results show that proposed methods give trustworthy results.
Modeling and Simulation of a Quantum Thermal Noise on the Qubit
Authors: Chapeau-Blondeau François
Published: August 2022

Quantum noise or decoherence is a major factor impacting the performance of quantum technologies. On the qubit, an important quantum noise, often relevant in practice, is the thermal noise or generalized amplitude damping noise, describing the interaction with a thermal bath at an arbitrary temperature. A qubit thermal noise however cannot be modeled nor directly simulated with a few elementary Pauli operators, but instead requires specific operators. Our main goal here is to construct a circuit model for simulating the thermal noise from standard elementary qubit operators. Starting from a common quantum-operation model based on Kraus operators and an associated qubit-environment model, we derive a proper Stinespring dilated representation for the thermal noise. This dilated unitary model is then decomposed in terms of simple elementary qubit operators, and converted into a circuit based on elementary quantum gates. We arrive at our targeted simulator circuit for the thermal noise, coming with built-in easy control on the noise parameters. The noise simulator is then physically implemented and tested on an IBM-Q quantum processor. The simulator represents a useful addition to existing libraries of quantum circuits for quantum processors, and it offers a new tool for investigating quantum signal and information processing having to cope with thermal noise.
Facile synthesis of porphyrin-conjugates as amphiphilic modified photosensitizer structures of m-THPP bearing carbamate, carboxylate and sulfonate linkers
Authors: Shaker Yasser M. , Omar Mohamed A. , Grover Nitika , Senge Mathias O.
Published: August 2022

5,10,15,20-Tetrakis(3-hydroxyphenyl)porphyrin (m-THPP) bearing various nitrogen and sulfur containing heterocycles, aromatic, aliphatic and alicyclic residues covalently linked to the oxygen atom of the meta-hydroxy group of the porphyrin unit were synthesized in good yields as potential photosensitizers for photodynamic therapy (PDT). These new amphiphilic conjugates were designed to use three different polar linkers (carboxylate, sulfonate, and carbamate linker units)via the reaction of m-THPP with nicotinoyl chloride hydrochloride (carboxylate linker), 5-bromothiophene-2-sulfonyl chloride (sulfonate linker), phenyl isocyanate, 3,5-bis(trifluoromethyl)phenyl isocyanate, hexyl isocyanate and cyclohexyl isocyanate (carbamate linker). The heterocycles employed are 5- and 6-membered rings with different solubility characteristics.
ACHIEVING EMPLOYMENT DIVIDEND IN THE POST-COVID-19 ERA: AN EXPLORATION FROM CHINA’S CARBON MARKET
Authors: LIU YISHUANG , HUANG JINPENG , DONG HANMIN
Published: August 2022

Under the pressure of economic uncertainty and environmental protection in the post-COVID-19 era, achieving a new round of employment dividends has become one practical choice. Using the panel data of 30 Chinese provinces from 2007 to 2019, this study estimates the employment outcomes of carbon ETS pilots based on the difference-in-differences model. The findings of this study indicate the following: (1) Carbon ETS pilots can positively increase employment scales with an average effect of 7.12%. (2) This promoting effect will become more significant in provinces with high education levels, provinces with high average wages, and eastern region provinces. But there is no obvious difference between gender. (3) This positive effect can be transferred and enhanced by market competition and energy consumption. At the crossroads of green economic recovery, it will be greatly beneficial to formulate the national carbon market development roadmap under the carbon neutrality strategy.
Humanistic communication in information centric workplaces
Authors: Ranade Nupoor , Swarts Jason
Published: August 2022

Professional writers adapt their skills to suit expanded professional roles that involve production and management of information, but preparation through mere skill-based training is problematic because that communication work is messy in ways that are not addressable through simple skills training. We must understand how skills "influence and shape the discursive activities surrounding their use" (Selber, 1994). This paper reports the results of a study of people trained in humanities disciplines like communication, English, writing studies, technical communication, etc., on how they have found means to employ their training in their workplace and keep what is humanistic about writing and communicating at the foreground of their interactions with information technologies. Instead of focusing on technology alone, this research encourages a unified approach to preparing students for the workplace.
Evaluating Recommender Systems: Survey and Framework
Authors: Zangerle Eva , Bauer Christine
Published: August 2022

The comprehensive evaluation of the performance of a recommender system is a complex endeavor: many facets need to be considered in configuring an adequate and effective evaluation setting. Such facets include, for instance, defining the specific goals of the evaluation, choosing an evaluation method, underlying data, and suitable evaluation metrics. In this article, we consolidate and systematically organize this dispersed knowledge on recommender systems evaluation. We introduce the Framework for Evaluating Recommender systems (FEVR), which we derive from the discourse on recommender systems evaluation. In FEVR, we categorize the evaluation space of recommender systems evaluation. We postulate that the comprehensive evaluation of a recommender system frequently requires considering multiple facets and perspectives in the evaluation. The FEVR framework provides a structured foundation to adopt adequate evaluation configurations that encompass this required multi-facetedness and provides the basis to advance in the field. We outline and discuss the challenges of a comprehensive evaluation of recommender systems and provide an outlook on what we need to embrace and do to move forward as a research community.
A Survey on Video Moment Localization
Authors: Liu Meng , Nie Liqiang , Wang Yunxiao , Wang Meng , Rui Yong
Published: August 2022

Video moment localization, also known as video moment retrieval, aims to search a target segment within a video described by a given natural language query. Beyond the task of temporal action localization whereby the target actions are pre-defined, video moment retrieval can query arbitrary complex activities. In this survey paper, we aim to present a comprehensive review of existing video moment localization techniques, including supervised, weakly supervised, and unsupervised ones. We also review the datasets available for video moment localization and group results of related work. In addition, we discuss promising future directions for this field, in particular large-scale datasets and interpretable video moment localization models.
The Comparison of Language Models with a Novel Text Filtering Approach for Turkish Sentiment Analysis
Authors: Guven Zekeriya Anil
Published: August 2022

Today, comments can be made on many topics on web platforms with the development of the internet. Analyzing the data of these comments is essential for companies and data scientists. There are many methods for analyzing data. Recently, language models have also been used in many studies for sentiment analysis or text classification. In this study, Turkish sentiment analysis is performed using language models on hotel and movie review datasets. The language models are chosen because they are rarely used in Turkish literature. The pre-trained BERT, ALBERT, ELECTRA, and DistilBERT models for the Turkish language are trained and tested with these datasets. In addition, a text filtering method, which removes the words that can provide the opposition sentiment in the positive or negative labeled text, is proposed for sentiment analysis. These datasets obtained by this method are also retrained with language models and the accuracy values of their models are measured. The results of this study are compared with previous studies using the same datasets. As a result of the analysis, the accuracy values obtain state-of-the-art results with language models compared to previous studies. The best performance has been achieved by training the ELECTRA language model using the proposed text filtering method.
SAGA-net
Authors: Xie Liuyue , Duan Tinglin , Shimada Kenji
Published: August 2022

In this paper, we propose a real-time shape-assisted graph attention neural network to perform local pointcloud repairment. The orderless pointclouds require an effective shape encoder to distill local and global geometric feature descriptors. Previous work has attempted to convert pointcloud representation into a voxelized shape or perform grid-transformations. While these approaches can subsequently allow common convolution operations on the structured data, they either pose additional computational cost or disrupt the local geometric information.

We present SAGA-Net, an efficient graph attention neural network framework with a prior shape inquiry protocol that effectively extracts local geometric information, locates the descriptor for the missing region and accurately reconstructs the local region in a real-time manner. Our framework has been validated on a benchmark dataset, ShapeNet.

We demonstrate that our framework can repair each partial pointcloud with accuracy surpassing other frameworks in most object categories, and improve the computational efficiency by orders of magnitude in terms of time cost.
The Evolution and Ecology of Interactions Between Ants and Honeydew-Producing Hemipteran Insects
Authors: Nelson Annika S. , Mooney Kailen A.
Published: August 2022

The interactions between ants and certain sap-feeding insects in the order Hemiptera are classic examples of food-for-protection mutualisms. In these associations, herbivorous hemipterans use a highly specialized, straw-like mouthpart to consume sap directly from plant phloem and xylem and, as a result, excrete a sugar-rich waste product called honeydew. Ant foragers use specialized adaptations to collect and share honeydew with nestmates and, in exchange, protect hemipterans against predators. The two key innovations underlying this interaction—hemipteran sap feeding and ant harvesting of honeydew—have driven the evolutionary success and ecological dominance of ants. These interactions also carry unique costs and benefits for each partner and are highly context dependent. Understanding the factors mediating this mutualism is critical, as these interactions have broader ecological consequences for the natural and agricultural ecosystems in which they are embedded.
Decoding Default Risk: A Review of Modeling Approaches, Findings, and Estimation Methods
Authors: Bakshi Gurdip , Gao Xiaohui , Zhong Zhaodong
Published: August 2022

Default risk permeates the behavior of corporate bond returns and spreads, credit default swap spreads, estimation of default probabilities, and loss in default. Pertinent to this review are salient empirical findings and implications of default process estimation from 1974 to 2021. Both structural and reduced-form models are covered. In structural models, default occurs if the value of assets falls below some threshold obligation. The reduced-form models involve assumptions about the default process combined with recovery in default. Default process estimation and measurements of default probability have improved by exploiting data on defaultable bonds, credit default swaps, tally of default realizations, and options on individual equities. Empirical investigations continue to address the relevance of stochastic asset volatility, jumps in asset values, and modeling of default boundary and firm leverage process.
An Innovative Balanced-Yielding Support Method for Tunnel in Deep Inclined Strata
Authors: Yongke Wei , Hongyan Guo , Juyi Hu , Jiaqing Liu , Limin Liu
Published: August 2022

Aiming at the problem that the uneven deformation of the tunnel surrounding rock in the deep inclined rock strata caused local instability, an innovative balanced-yielding support technology was proposed with the engineering background of the Shangping tunnel in Huafeng Mine. Based on the mechanism analysis of this technology, the specific implementing steps were proposed. It mainly included in situ stress analysis, the stress distribution of the tunnel surrounding rock with different sections, the design of the parameter of bolt-cable and yielding structure, and supporting effect evaluation. The results showed that (1) the stress concentration appeared at the top corners of the lower side and the bottom corner of the upper side of the rectangular and semicircular arched tunnel. (2) Compared with rectangle and vertical-wall semicircular arch tunnels, the trapezoidal tunnel could relieve the shearing effect of the inclined rock strata. (3) The length, prestress, spacing-row distance of the bolt, and the parameter of the yielding structure were all optimally designed to form the balanced-yielding support system. (4) In engineering application, the maximum deformations of the roof, right side and left side, were less than 80 mm. Compared with the original support system, the shallow separation of the trapezoidal tunnel supported by the balanced-yielding support system had been reduced by 147%.
Rheological Properties and Antiaging Performance of Graphene Oxide-Modified Bio-Asphalt
Authors: Qian Huaxin , Li Yimin , Ding Renhong , Han Hua , Zou Xiaolong , Zhang Yunliang , Zhu Shaofeng
Published: August 2022

To enhance the performance of bio-asphalt, an attempt was made to modify bio-asphalt using graphene oxide (GO). Two bio-asphalts were prepared and modified with different GO dosage levels of 0 to 0.08% to obtain GO-modified bio-asphalts (GOMBA). The two GOMBA were tested in the conventional properties (penetration, softening point, and ductility), high- and low-temperature rheological properties, and aging properties. The results showed that the penetration decreases and the ductility increases slightly with the increase in the dosage of GO, while the softening point increases stably to the maximum by 17.84%, and 15.99% for the two GOMBA, respectively. GO is beneficial to improve the high temperature performance and the recovery after the deformation of the GOMBA; on the contrary, it does not significantly affect the low temperature cracking resistance of those. The maximum residual penetration ratio is 10.58% and 8.84%, respectively, and the maximum residual ductility is 10.79% and 27.51%, respectively, for the two GOMBA after short-term aging. GO modification plays a role in the change of carbonyl index (CI) and sulfoxide index (SI) of the GOMBA before and after aging based on the FT-IR spectra, indicating that the GO can effectively improve the antiaging performance of bio-asphalt.
Design and Implementation of Fault Diagnosis System for Power Internet of Things Equipment Based on Neural Network
Authors: Ren Qiang
Published: August 2022

The design and application of the equipment fault diagnosis system have been improved and upgraded, allowing it to effectively detect the equipment’s operation status and promptly eliminate hidden faults, reducing the occurrence of unexpected accidents and improving the safety index of people’s lives. The purpose of this essay is to design and apply neural network (NN) fault diagnosis system model in power Internet of things (IOT) equipment and explore its accuracy and effectiveness. The BP neural network (BPNN) algorithm was used to construct model of a fault monitoring testing of the power IOT equipment. Neural network is an algorithmic mathematical model that imitates the behavioral characteristics of animal neural network and performs distributed parallel information processing. The network parameters were as follows: there were four input layer nodes, seven hidden layer nodes, and five output layer nodes, the training times were 10000, and the allowable error was 0.002. In this paper, we use the IOT to detect model of a fault monitoring testing of power equipment designed in each sample, the success rate is as high as 97.5%, and the designed network structure and network parameters are reasonable. The trained loss is less than 0.001, and the nontraining set samples may be appropriately identified. It is clear that the NN has a high application for power equipment fault diagnosis in the IOT value.
Visual Memory Neural Network for Artistic Graphic Design
Authors: Zheng Yuchuan
Published: August 2022

Artistic graphic design is the aesthetic result of the designer’s fusion of various elements, with a high degree of independence. Considering the lack of significant visual design scope and aesthetic indicators of graphic design, our research aims to build an upgraded network model that can categorize different types of artistic graphics with labels and realize the free combination of graphic solutions. We realize the scheme reorganization of artistic graphic design from the perspective of computer vision and propose the artistic graphic design method based on memory neural network. We built a computer vision environment and reconstructed the computer vision network to set up an independent deep camera vision range calculation law. Considering the artistic graphic region segmentation problem, we propose the self-attentive mechanism, which can quantitatively segment different artistic graphic regions according to temporal features, before arranging them in a sequence to obtain the graphic region feature vector. We also add the LSTM structure based on the attention mechanism to match with the self-attention features of the graphical region segmentation module and pass the matched attention feature vector to the LSTM network to extract the labeled text feature information of the graphs. To test the effectiveness of our method, we build a database of artistic graphics and set up an adaptive training process. We also compared deep learning methods of the same type, and the experimental results proved that our method outperformed other deep methods in artistic graphic design by keeping the scheme reorganization accuracy and quantitative evaluation of artistic models above 90%.
Low-Delay Opportunistic Routing with Reducing Overhead in Asynchronous Duty-Cycled Wireless Sensor Networks
Authors: Liu Fang , Zhang Zheng , Liu Yuanan
Published: August 2022

The Internet of Things (IoT) and cloud computing are well developed and applied in different services. Among these services, some of them take latency and overhead as the metrics to evaluate the quality of services. This paper introduces how an opportunistic routing (OR) protocol reduces latency and overhead when it is applied in wireless sensor network (WSN) application among lightweight devices. OR mitigates the delay problem and balances the energy consumption and delay of the nodes in WSNs. However, OR, with the nature of broadcasting, can easily cause heavy overhead such as redundant data and control packets in the forwarding process. In the current solution, the number of candidates (potential forwarders) is not limited by the dynamics of forwarding process. Also, the overhead of establishing the candidate sets is high due to global information calculation. Therefore, a low-delay OR protocol with reducing overhead which designs the dynamic candidate area (DCA) to establish candidate sets is first proposed in this paper. The main work is as follows. (a) The duty cycle of a node is adjusted according to the distance between the node and sink node in the initialized network. (b) A method to establish dynamic candidate sets is proposed based on the adaptive duty cycle. Before and during the forwarding process, the dynamic candidate area is adjusted in time. (c) According to the feature of the candidate area, the corresponding routing metric is proposed to complete the cooperative communication among candidates. Through further theoretical analysis and simulations, the results indicate that this protocol achieves better performance in terms of transmission delay, data and control overhead, and network lifetime compared to the state-of-the-art solutions.
Optimal Control Analysis of Treatment Strategies of the Dynamics of Cholera
Authors: Abubakar Sani Fakai , Ibrahim M. O.
Published: August 2022

A nine-compartment deterministic cholera model was formulated, and the model describes interactions between human, Vibrio cholerae bacteria, and the enviroment that warrant the interaction. Realities and socioeconomic burden influence spread and control mechanism of the disease. The model investigated some effective ways of hindering cholera outbreak and spread. The existence and uniqueness of solution of the system of equations that the model comprises were ascertained. The basic reproduction number

R

0

of the model was obtained using “next-generation matrix” method, and the most sensitive parameters were identified using “normalised forward sensitivity index” method. Three controls, hygiene consciousness denoted by X1, cholera vaccine X2, and cholera awareness programme X3, were chosen. Optimal control theory is applied to ascertain the level of effect of the controls in reducing susceptible, exposed, infected individuals and causative pathogen population. Pontryagin’s maximum principle is used to prove the optimal solution of the model, and the optimal system was derived and numerically solved. Simulations were made with graphs that show the effects of the controls on susceptible, exposed, infected, and Vibrio cholerae population. The findings are that simultaneous application of the three controls can be one of the fast and effective ways of controlling cholera. If two controls are to be selected, hygiene consciousness and vaccine are the best combination.
Insulin Edema Syndrome due to Rapid Glucose Correction in a Diabetic Patient
Authors: Hussien Siham M. , Imanli Hasan , Tran Dena H. , Chow Robert D. , Sood Aseem
Published: August 2022

Edema resulting from the initiation of insulin therapy or intensification of glycemic control is a rare and under-recognized complication. In this report, we present a case of a 46-year-old patient with insulin-dependent diabetes mellitus (IDDM) who avoided insulin treatment due to associated peripheral edema. Though rare, this phenomenon is typically seen in patients with elevated glucose levels who are initiated on insulin treatment, resulting in rapid correction and tight control of glucose levels. The diagnosis of insulin-induced edema is made after other causes of acute edema are ruled out. Furthermore, in this case report, we will also discuss the postulated mechanisms for the edema-causing property of insulin.
Effects of Multimodal Analgesia Combined with Auricular Point Therapy on Physical and Mental Stress and Rehabilitation Quality of Patients with Meniscus Injury during the Perioperative Period
Authors: Yao Yuanyuan , Yu Guiyang , Lu Jianbo , Han Tian , He Huizhen
Published: August 2022

Objective. To investigate the effect of multimodal analgesia combined with auricular point therapy on physical and mental stress and rehabilitation quality of patients with meniscus injury during the perioperative period. Methods. 148 patients in our hospital from October 2019 to October 2021 who were scheduled to undergo meniscus surgery were selected and grouped according to the order of file establishment, with 74 cases in each. The control group was given routine analgesia, and the observation group was given multimodal analgesia combined with auricular point therapy. The pain level (visual analogue scale (VAS)), physical and mental stress (heart rate (HR), mean arterial pressure (MAP), depression scale (PHQ-9), and anxiety scale (GAD-7)), complications, rehabilitation quality, and analgesia satisfaction were observed. Results. The VAS scores of pain in the observation group were lower than those in the control group at 6 hours before operation and at 6 hours, 24 hours, and 72 hours after operation (

P
<
0.05

). The MAP, HR, PHQ-9, and GAD-7 scores of the observation group were lower than those of the control group 6 hours before operation (

P
<
0.05

). There was no significant difference in MAP, HR, PHQ-9, and GAD-7 scores between the two groups at 6 hours and 24 hours after operation (

P
>
0.05

). The analgesic satisfaction of the observation group was better than that of the control group (

P
<
0.05

). The incidence of complications in the observation group was 8.11% compared with 12.16% in the control group, which was not statistically significant (

P
>
0.05

). The first exhaust, getting out of bed, and hospital stay in the observation group were shorter than those in the control group (

P
<
0.05

). Conclusion. Multimodal analgesia combined with auricular acupuncture therapy is effective in perioperative patients with meniscus injury. It can reduce perioperative pain, reduce physical and mental stress, and promote early postoperative recovery through a variety of analgesic mechanisms.
Stable Metabolic Control but Increased Demand for Professional Support in Children with Type 1 Diabetes in the Past Ten Years in Bern/Switzerland: A Quality Control Study
Authors: Dennig Michelle J. , Sommer Grit , Zingg Tanja , Flück Christa E. , Boettcher Claudia
Published: August 2022

Introduction. Lower HbA1c targets and increasingly complex diabetes management with substantially increasing costs dominate today’s type 1 diabetes therapy in children and adolescents. Objective. To evaluate metabolic control in children and adolescents with type 1 diabetes and assess associated factors, evaluate determinants for frequency of healthcare contacts, and compare actual with historical data. Method. This cross-sectional observational study collected data on 178 children and adolescents with type 1 diabetes treated at the University Children’s Hospital in Bern. Results. Mean HbA1c was 7.9% (63 mmol/mol), 33.1% (59/178) of children reached the target of

HbA
1
c
<
7.5

% (<59 mmol/mol), and 18.0% (32/178) had an

HbA
1
c
 
value
<
7.0

% (<53 mmol/mol). Compared to historical data, stable HbA1c levels appeared with a doubled proportion of individuals using insulin pumps. Metabolic control was worse with a longer duration of diabetes and younger age at diagnosis but better when parents came from a Western European country. Age at the consultation, use of diabetes technology and native language influenced the number of healthcare contacts. Younger patients, patients using CSII, and patients without an official Swiss language as mother tongue had more consultations with a healthcare professional than older and native language individuals. Conclusion. The metabolic targets in childhood and adolescent type 1 diabetes are still unmet despite a shift towards more technology. Our study documents a higher demand for support and supervision in specific patient groups. An investment to increase healthcare contacts could help combat the increase in total diabetes cost and significantly improve metabolic control.
Analysis of Digital Transformation of Enterprise Accounting Talents from the Perspective of Blockchain
Authors: Zhou Wenxue , Xu Ziyan , Zhou Jia , Gao Yongli
Published: August 2022

In order to improve the digital transformation effect of enterprise accounting talents, this paper combines intelligent methods to carry out the digital transformation of enterprise accounting talents from the perspective of blockchain. Moreover, this paper studies the sliding window CS-SCHT algorithm in depth. Based on the theoretical derivation of the sliding window CS-SCHT based on the gray code kernel, the algorithm is implemented on the computer platform, and the test experiment of the operation time is carried out. In addition, this paper explores the application of the sliding window CS-SCHT algorithm in adaptive filtering. The experimental results show that the adaptive filter based on the CS-SCHT algorithm can obtain a higher signal-to-noise ratio than the sliding window DFT algorithm. Finally, this paper constructs an intelligent accounting digital information processing system. The research shows that the system proposed in this paper can play an important role in the digital transformation of enterprise accounting talents from the perspective of blockchain.
Effect of Recycled Bagasse on Cracking Behavior of Clay Materials
Authors: Ma Wenlong , Liu Wenbo , Wang Yuanhang , Yang Binbin
Published: August 2022

Bagasse is the residue after juicing sugarcane, and bagasse is a recyclable biological resource that can be used in many ways. Under arid climatic conditions, the clay material shrinks and loses water. Many crisscross drying shrinkage cracks formed on the surface and inside the soil will affect the stability of the soil. In this article, the cracking characteristics of clays with different bagasse contents during the evaporation process have been studied. The cracks were extracted and calculated by digital image processing technology, and the crack characteristics of samples with different bagasse contents were studied by fractal dimension and crack entropy. The results show that when moisture content maintains 34%, the clay material forms only one main crack without bagasse, forms no crack with bagasse content of 9%, and forms a crack network with the bagasse content of 3%. Adding bagasse to the clay can advance the cracking time of the clay, and different contents of bagasse have different effects on the cracking time of the clay. Among these five experimental groups, the clay was affected the most with 3% bagasse content, while the least effect happened with 6% bagasse content. The time can be advanced when the clay crack entropy appears and increases the size of the crack entropy.
Association between Serum Total Testosterone Level and Bone Mineral Density in Middle-Aged Postmenopausal Women
Authors: Yang JinXiao , Kong Guofei , Yao Xiaocong , Zhu Zhongxin
Published: August 2022

Background. Hormone status strongly affects women’s health and quality of life. To date, studies investigating the association between total testosterone (T) level and bone mineral density (BMD) in women are limited and have yielded contradictory conclusions. The aim of our study was to examine the association between serum total T level and lumbar BMD in postmenopausal women aged 40–59 years. Methods. The study group included 1,058 women from the 2011–2016 National Health and Nutrition Examination Survey. Multiple regression analyses were used to evaluate the association between serum total T level and lumbar BMD. Results. After adjusting for covariates, there was a positive association between the serum total T level and lumbar BMD (β, 1.07; 95% confidence interval, 0.17–1.97). A non-linearity in this association was identified, with a point of inflection at 30 ng/dL. Conclusions. Serum total T level was positively associated with lumbar BMD in middle-aged postmenopausal women up to a T level >30 ng/dL. Therefore, increasing T level in women with a low serum total T level may have beneficial outcomes on bone health.
Research on the Influencing Mechanism of Data Capital on Farmers’ Income
Authors: Xiumei Xu , Xiaoxuan Zhai , Hui Wang
Published: August 2022

Based on the 2018 China Family Panel Studies data, this paper uses the OLS model, threshold regression model, and mediation effect model to analyze the influencing mechanism and degree of data capital on farmers’ income. The study found that data capital has a significant positive impact on farmers’ income, which can effectively promote farmers’ income. There is a nonlinear relationship between data capital and farmers’ income, and its marginal return increases with farmers’ human capital increasing. Social network plays a partial intermediary role between data capital and farmers’ income, that is, social network is an important channel for data capital to affect farmers’ income improvement. Based on the above conclusions, some reference suggestions are put forward.
Optimization of Voltage Dynamic Performance at Inverter Output with Machine Learning and Intelligent Virtual Impedance
Authors: Wang Lu
Published: August 2022

With the continuous improvement of industrial production and manufacturing level, all kinds of equipment are developing in the direction of refinement and precision, especially the equipment manufacturing industry such as automobile manufacturing, equipment, integrated circuits, chip manufacturing, and other semiconductor industries. An intelligent virtual resistance control strategy based on machine research is proposed for rational power distribution and cycle suppression when multiple inverters are operated in parallel in low-voltage microgrids. Based on this, the control strategy of temporary power reduction of inverters is improved to improve the parallel inverter power distribution accuracy and ensure the reliable dynamic response of the constrained current in the circuit between parallel inverters. Finally, a multi-inverter parallel system model is established to verify the correctness and effectiveness of the proposed control strategy. The voltage waveform under nonlinear load conditions is improved and high-frequency harmonics are suppressed, which has obvious advantages compared with the general virtual impedance design method.
Analysis of Financial Management and Decision-Making in Institution of Higher Learning Based on Deep Learning Algorithm
Authors: Zang Zhichao
Published: August 2022

This study creates a model of financial management and decision-making in higher education institutions and implements financial early warning and decision-making in higher education institutions based on the DL algorithm and data-driven thinking. In addition to analyzing the causes of financial risks and creating an early warning system for financial risks, this study provides prevention strategies for financial risks in institutions of higher education. Concurrently, a high-precision early-warning model of shared financial risks is established using the early-warning index data that were obtained by screening and imported into the MATLAB training DL network. The main system modules are designed simultaneously using the timing diagram and flowchart of the model, which is based on model analysis and the modeling process. This model’s main objective is to boost the effectiveness of financial management and scientific judgment in higher education institutions. Finally, it is used for experimental analysis and result research, providing an early warning of financial project budget execution progress. Compared to the traditional model’s accuracy of 12.03 percent, the experimental results demonstrate that this model’s prediction accuracy can reach 95.78%. The financial management and decision-making analysis of a higher education institution are the subjects of this study’s application of the DL algorithm. Positive results were obtained, which can serve as a starting point for future research in the field.
The Influence of Nanoparticle on Vaccine Responses against Bacterial Infection
Authors: Bagheri-Josheghani Sareh , Bakhshi Bita , Najar-peerayeh Shahin
Published: August 2022

Nowadays, nanovaccine is considered as an evolving method in the field of vaccination to induce immunity in the human body against various diseases, including bacterial or viral diseases as well as virulent tumors. Nanovaccines are more efficient than traditional vaccines since they could potentially induce both humoral and cellular immune reactions. Various studies have shown that nanoparticles with multiple compounds have been designed as delivery systems or as adjuvants for vaccines. Nanoparticles could function as a drug delivery tool, as an adjuvant to promote antigen processing, and as an immune modulator to induce immune responses. These nanoparticles generate immune responses through activating immune cells as well as through the production of antibody responses. Design engineering of nanoparticles (NPs) used to produce nanovaccines to induce immunity in the human body needs comprehensive information about the ways they interact with the component of immune system. Challenges remain due to the lack of sufficient and comprehensive information about the nanoparticles' mode of action. Several studies have described the interactions between various classes of nanoparticles and the immune system in the field of prevention of bacterial infections. The results of some studies conducted in recent years on the interaction between nanoparticles and biosystems have considerably affected the methods used to design nanoparticles for medical applications. In this review, NPs’ characteristics influencing their interplay with the immune system were discussed in vivo. The information obtained could lead to the development of strategies for rationalizing the design of nanovaccines in order to achieve optimum induction of immune response.
Research on Soft Rocks for the Construction of Roadbeds for High-Speed Railroad: Effect of Water Soaking Environment
Authors: Zhang Xiangdong , Geng Jie , Xu Yuebo , Zhou Zhongchao , Pang Shuai
Published: August 2022

The strength of the roadbed composed of soft rock decreases following water immersion. Cement slurry is mixed with a soft rock to strengthen the soft rock roadbed to address this problem. The uniaxial compressive strength was determined, and the triaxial compression tests were conducted to analyze muddy sandstones mixed with different amounts of the cement slurry of the same composition. Some of the cured samples were soaked in water, and the samples were analyzed. The results were compared with the results obtained by analyzing unsoaked samples. The MIDAS/GTS NX software was used to develop a three-dimensional finite model to simulate the settlement patterns of roadbeds developed in the presence of natural water, saturated water, and muddy sandstone reinforcements. The experimental results have been presented and discussed. (1) When the filling rate corresponding to the cement slurry is 32%, the uniaxial compressive strength of muddy sandstone containing natural water reaches 3.32 MPa, which is approximately 5 times higher than the strength of muddy sandstone devoid of cement slurry. (2) The water absorption energy of the reinforced muddy sandstone was analyzed from the perspective of saturated water content. The water plugging effect observed after the addition of the cement slurry was studied, and the equations defining uniaxial compressive strength, elastic modulus, and free saturated water content were established. (3) An increase in the content of the cement slurry admixture resulted in a change in the nature of the partial stress–strain curves generated for muddy sandstone. The curve change from strain-hardening to strain-softening type and the deformation modulus and extent of cohesion realized increased exponentially with an increase in the cement slurry filling rate. A positive linear correlation was observed between the internal friction angle and the cement slurry filling rate. (4) An increase in the cement slurry filling rate corresponding to the saturated muddy sandstone resulted in an exponential decrease in the settlement deformation value. The vertical displacement decreased to 0.3497 mm when the grouting rate reached 32% under conditions of saturation. The deformation tended to converge and stabilize, indicating that the introduction of the admixture consisting of the cement slurry could help in effectively controlling the property of settlement deformation observed in the fully weathered muddy sandstone roadbed. The results helped in the scientific evaluation of the reinforcement effect. The reported results also helped develop a theoretical basis for the development of soft foundation reinforcement.
[Retracted] Analysis of Metabonomic Characteristics after Exercise Fatigue Based on NMR
Authors: Chen YuRong , Wang Xiaoqiang
Published: August 2022

In order to better understand the changes of body metabolism of athletes before and after exercise, this paper proposes a method of metabonomics feature analysis after exercise fatigue based on NMR. This paper makes a retrospective analysis on the metabonomic characteristics of urine of middle and long distance runners after 30 minutes of a heavy load training class based on NMR. The experiment analyzes the urine of athletes by combining NMR technology and metabonomics principle. The experimental results show that the Q2 value of this experiment is greater than that of all comparisons, and r2x and r2y are 0.436 and 0.85, respectively. Conclusion. This method can effectively analyze the changes of body metabolism after athletes’ fatigue, so as to better alleviate athletes’ fatigue after exercise.
Statistical analysis of an orographic rainfall for Eight North-East region of India with special focus over Sikkim
Authors: Verma Pooja , Biswas Amrita , Chakraborty Swastika
Published: August 2022

Autoregressive integrated moving average (ARIMA) models are used to predict the rain rate for orographic rainfall over a long period of time, from 1980 to 1918. As the orographic rainfall may cause landslides and other natural disaster issues, So, this study is very important for the analysis of rainfall prediction. In this research, statistical calculations have been done based on the rainfall data for twelve regions of India (Cherrapunji, Darjeling, Dawki, Ghum, Itanagar, Kamchenjunga, Mizoram, Nagaland, Pakyong, Saser Kangri, Slot Kangri, and Tripura) from the eight states, i.e., Sikkim, Meghalaya, West Bengal, Ladakh (Union Territory of India), Arunachal Pradesh, Mizoram, Tripura, and Nagaland) with varying altitude. The model's output is assessed using several error calculations. The model's performance is represented by the fit value, which is reliable for the north-east region of India with increasing altitude. The statistical dependability of the rainfall prediction is shown by the parameters. The lowest value of root mean square error (RMSE) indicates better prediction for orographic rainfall.