bluuebunny/crossref_metadata_2025 huggingface dataset:
Vegetation restoration types affect soil bacterial community composition and diversity in degraded lands in subtropical of China
Authors: Zheng Xiangzhou , Yan Mingjuan , Lin Cheng , Guo Baoling , Ding Hong , Yu Juhua , Peng Shaoyun , Sveen Tord Ranheim , Zhang Yushu
Published: August 2021

Significant improvement of soil quality and biodiversity has been reported following vegetation restoration on the degraded lands in subtropical of China. However, so far the response of soil bacterial communities and drivers of their composition to differing vegetation restoration types are not well understood. In this study, we investigated soil physicochemical properties and bacterial communities in degraded land subjected to differing vegetation restoration types after 12 years of long‐term experiment. Restoration types included grassland, cropland, three differing plantation forests (orchard, coniferous forest, and coniferous forest with applied tillage), and control of degraded land. Bacterial community composition was examined using 16S rDNA sequencing. Result found that soil nutrient content includes soil organic carbon (SOC), total N (TN), available nitrogen (AN), available phosphorus (AP), and available potassium (AK) was improved after 12‐year restoration and the highest contents were found in cropland. However, soil pH was decreased after revegetation in the order degraded land > grassland > forestland > cropland, and the soil C/N ratio was significantly decreased in cropland. Revegetation restoration significantly increased operational taxonomic units (OTUs), ACE, and Chao1 indices by 13.67–22.81%, 16.34–25.11%, and 14.66–24.00%, with relative abundances of bacterial phyla varying between the different vegetation types. Soil physicochemical properties (e.g. pH, SOC, TN, AN, AP, and AK) showed significant correlations with the majority of the dominant phyla. When degraded land was restored to cropland, soil C/N ratio decreased which promoted the growth of Actinobacteria. Revegetation with grassland and forest increased soil nutrient content and decreased pH, resulting in shifts in bacterial phyla favoring Proteobacteria and Acidobacteria. Our observations show that restoration of degraded land will lead to differing bacterial community compositions depending on the vegetation type.
An intervention study for the prevention of vasovagal reactions and evaluating donors' experience: Analysis of donors' return for subsequent donation
Authors: Wiersum‐Osselton Johanna , Prinsze Femmeke , van den Brekel Elise , van Dongen Anne , Hermans Frank , Bokhorst Arlinke , der Kreek Tanneke Marijt‐van
Published: August 2021

Background and Objectives

The EPISoDe (Experience Success in Donation) study investigated the effect of interventions on self‐reported vasovagal reactions (VVRs) in first‐time and novice (second to fourth donation) whole blood donors aged ≤30 years, demonstrating a 23% reduction of VVR from water drinking shortly before donation in the novice donors. Because donation experience and complications affect donor retention, we analysed intervention group donors' return for subsequent donation, a predefined secondary outcome.

Materials and Methods

The interventions were as follows: 330 ml water, 500 ml water, ball squeezing before phlebotomy (placebo) and a control group. All donors received an online questionnaire about their experience within a week after donation. In the Netherlands, eligible donors are invited at least yearly depending on hospitals' needs. We analysed attendances within 421 days through return percentages and binomial logistic regression.

Results

Of the 8300 EPISoDe participants, 6538 (78.8%) returned within 421 days. Return did not differ between the two water groups, whereas odds for return were significantly higher in both water and placebo intervention donors compared to the control group (odds ratio [OR] 1.14, 95% confidence interval [CI] 1.00–1.29 and 1.22, 1.05–1.43, respectively) after adjustment for occurrence of VVR, unsuccessful collection, gender and donation history. Staff‐recorded or self‐reported VVR at index donation was associated with reduced odds for return (OR 0.47, 95% CI 0.37–0.60 and OR 0.53, 95% CI 0.46–0.61, respectively).

Conclusion

In this cohort of younger inexperienced blood donors, 78.8% returned for subsequent donation. Donors who received an active study intervention, either water or placebo, were more likely to return than control group donors.
Dosagem de silício em silico-fosfatos naturais
Authors: Cassedanne Jeannine Odette , Carvalho Hamílcar Freire de
Published: August 2021

This study describes a silicon volumetric titration in minerals silico-phosphates. Silicon is precipited as quinolin silico-molibdate and molybdenum is titsted by complexometric-accumulation method. In the range of 0,5 to 2,5 mg of silicon, a precision of about 0,5% is reached with a good reproducibility. A previous elimination of phosphates ions is necessary.
Material Mechanics and Hussein Zbib: A Tribute to His Memory
Authors: Aifantis Elias C.
Published: August 2021

A number of new trends in material mechanics and engineering science can be traced back to the PhD work of Hussein Zbib at Michigan Technological University (MTU). In particular, the topics of shear bands and plastic instabilities found a new basis and direction, prompting distinguished researchers—whom he begun interacting with during his doctoral and post-doctoral years (seeAppendix)—to turn their attention to gradient plasticity and make their own monumental contributions in this field. This article first provides a brief account of the initial attempts, I had the joy to share with him, on gradient mechanics theory and its implications to the problems of strain localization and size effects. It then continues with a brief exposition of topics that his “scientific family” has taken up in parallel with him or later on. Finally, it concludes with a sketch of ideas I discussed with him during his post-doctoral period at MTU and his tenure period as a faculty member and Chairman at Washington State University (WSU) which, unfortunately, he did not have the time to elaborate upon.
Vocal fold vibration mode changes due to cricothyroid and thyroarytenoid muscle interaction in a three-dimensional model of the canine larynx
Authors: Geng Biao , Movahhedi Mohammadreza , Xue Qian , Zheng Xudong
Published: August 2021

Using a continuum model based on magnetic resonance imaging of a canine larynx, parametric simulations of the vocal fold vibration during phonation were conducted with the cricothyroid muscle (CT) and the thyroarytenoid muscle (TA) independently activated from zero to full activation. The fundamental frequency (f0) first increased and then experienced a downward jump as TA activity gradually increased under moderate to high CT activation. Proper orthogonal decomposition analysis revealed that the vocal fold vibrations were dominated by two modes representing a lateral motion and rotational motion, respectively, and the f0 drop was associated with a switch on the order of the two modes. In another parametric set where only the vocalis was active, f0 increased monotonically with both TA and CT activity and the mode switch did not occur. The results suggested that the active stress in the TA, which causes large stress differences between the body and cover, is essential for the occurrence of the rotational mode and mode switch. Relatively greater TA activity tends to promote the rotational mode, while relatively greater CT activity tends to promote the lateral mode. The results also suggested that the vibration modes affected f0 by affecting the contribution of the TA stress to the effective stiffness. The switch in the dominant mode caused the non-monotonic change of f0.
Recurrent uterine rupture in third trimester of pregnancy
Authors: Uleanya Obiefula , McCallin Kate , Khanem Noor , Sabir Sabahat
Published: August 2021

We report a case of recurrent upper segment uterine rupture in a 31-year-old woman at 32+5/40 weeks of gestation. She had fundal uterine rupture 3 years ago in her first pregnancy at 40 weeks of gestation. There was no history of uterine malformation or prior uterine surgery. However, we noted that she had had three laparoscopic procedures for endometriosis treatment. She was scheduled to have an elective repeat caesarean section at 34+6/40 weeks of gestation in the index pregnancy. Unfortunately, she presented at 32+5/40 weeks with features of acute abdomen and signs of fetal distress. She had a category 1 caesarean section and was found to have fundal uterine rupture at the same site. She had a smooth uneventful recovery following a timely intervention and discharged home on day 5 postoperatively in a good condition with her baby girl.
Characteristics of child welfare investigations reported by healthcare professionals in Ontario: secondary analysis of a regional database
Authors: Livingston Eliza , Joh-Carnella Nicolette , Lindberg Daniel M , Vandermorris Ashley , Smith Jennifer , Kagan-Cassidy Miya , Giokas Danielle , Fallon Barbara
Published: August 2021

Objectives

This study examines the characteristics and outcomes of child welfare investigations reported by hospital-based and community-based healthcare professionals.

Methods

A sample of 7590 child maltreatment-related investigations from the Ontario Incidence Study of Reported Child Abuse and Neglect-2018, a cross-sectional study, was analysed. Bivariate analyses compared characteristics of hospital and community healthcare-reported investigations. Chi-square automatic interaction detector analyses were used to predict the most influential factors in the decision to provide a family with services following a child welfare investigation from each referral source.

Results

Community healthcare-reported investigations were more likely to have a primary concern of physical abuse while hospital-reported investigations were more likely to be focused on assessing risk of future maltreatment. Hospital-reported investigations were more likely to involve noted primary caregiver (eg, mental health issues, alcohol/drug abuse, victim of intimate partner violence (IPV)) and household risk factors. The most significant predictor of service provision following an investigation was having a caregiver who was identified as a victim of IPV in hospital-reported investigations (χ2=30.237, df=1, adj. p<0.001) and having a caregiver for whom few social supports was noted in community healthcare-reported investigations (χ2=18.892, df=1, adj. p<0.001).

Conclusion

Healthcare professionals likely interact with children who are at high risk for maltreatment. This study’s findings highlight the important role that healthcare professionals play in child maltreatment identification, which may differ across hospital-based and community-based settings and has implications for future collaborations between the healthcare and child welfare systems.
The conformal anomaly action to fourth order (4T) in $$d=4$$ in momentum space
Authors: Corianò Claudio , Maglio Matteo Maria , Theofilopoulos Dimosthenis
Published: August 2021

We elaborate on the structure of the conformal anomaly effective action up to 4-th order, in an expansion in the gravitational fluctuations (h) of the background metric, in the flat spacetime limit. For this purpose we discuss the renormalization of 4-point functions containing insertions of stress-energy tensors (4T), in conformal field theories in four spacetime dimensions with the goal of identifying the structure of the anomaly action. We focus on a separation of the correlator into its transverse/traceless and longitudinal components, applied to the trace and conservation Ward identities (WI) in momentum space. These are sufficient to identify, from their hierarchical structure, the anomaly contribution, without the need to proceed with a complete determination of all of its independent form factors. Renormalization induces sequential bilinear graviton-scalar mixings on single, double and multiple trace terms, corresponding to $$R\square ^{-1}$$

R

□

-
1

interactions of the scalar curvature, with intermediate virtual massless exchanges. These dilaton-like terms couple to the conformal anomaly, as for the chiral anomalous WIs. We show that at 4T level a new traceless component appears after renormalization. We comment on future extensions of this result to more general backgrounds, with possible applications to non local cosmologies.
Probing gluon number density with electron-dijet correlations at EIC
Authors: van Hameren A. , Kotko P. , Kutak K. , Sapeta S. , Żarów E.
Published: August 2021

We propose a novel way of studying the gluon number density (the so-called Weizsäcker–Williams gluon distribution) using the planned Electron Ion Collider. Namely, with the help of the azimuthal correlations between the total transverse momentum of the dijet system and the scattered electron, we examine an interplay between the effect of the soft gluon emissions (the Sudakov form factor) and the gluon saturation effects. The kinematic cuts are chosen such that the dijet system is produced in the forward direction in the laboratory frame, which provides an upper bound on the probed longitudinal fractions of the hadron momentum carried by scattered gluons. Further cuts enable us to use the factorization formalism that directly involves the unpolarized Weizsäcker–Williams gluon distribution. We find this observable to be very sensitive to the soft gluon emission and moderately sensitive to the gluon saturation.
Explicit solutions to nonlinear Chen–Lee–Liu equation
Authors: Akinyemi Lanre , Ullah Najib , Akbar Yasir , Hashemi Mir Sajjad , Akbulut Arzu , Rezazadeh Hadi
Published: August 2021

In this work, a generalized [Formula: see text]-expansion method has been used for solving the nonlinear Chen–Lee–Liu equation. This method is a more common, general, and powerful mathematical algorithm for finding the exact solutions of nonlinear partial differential equations (NPDEs), where [Formula: see text] follows the Jacobi elliptic equation [Formula: see text], and we let [Formula: see text] be a fourth-order polynomial. Many new exact solutions such as the hyperbolic, rational, and trigonometric solutions with different parameters in terms of the Jacobi elliptic functions are obtained. The distinct solutions obtained in this paper clearly explain the importance of some physical structures in the field of nonlinear phenomena. Also, this method deals very well with higher-order nonlinear equations in the field of science. The numerical results described in the plots were obtained by using Maple.
Geochemical and palaeomagnetic characteristics of the Vestfold Hills mafic dykes in the Prydz Bay region: implications of a Paleoproterozoic connection between East Antarctica and Proto-India
Authors: Pandit Manoj K. , Pivarunas Anthony , Meert Joseph G.
Published: August 2021

The Archean age granite gneiss basement along the Prydz Bay coastline in East Antarctica hosts north–south-, east–west-, NE–SW- and NW–SE-trending mafic dyke swarms in the Vestfold Hills region that intruded between 2420 and 1250 Ma. The orientations of dykes do not show a direct correlation with the dyke geochemistry. Instead the dykes can be broadly discriminated into high-Mg and Fe-rich tholeiites. The former type is more siliceous, large ion lithophile elements (LILEs), high field strength elements (HFSEs) and light REEs enriched crystallized from a fractionated melt with a notable crustal component or fluid enrichment through the previous subduction process. The Fe-rich tholeiites are less siliceous, have lower abundances of LILEs and REEs, that indicates derivation from an undifferentiated, primitive melt. The geochemical characteristics of both types underline a shallow level and a high degree of melting in the majority of cases, and a broadly island arc basalt (IAB) affinity. Palaeomagnetic analysis of hand samples shows directional groups consistent with geochemical groupings. The Vestfold Hills dykes show a possible linkage with the coeval mafic dykes in the Eastern Dharwar and Bastar cratons of the South Indian Block, based on the similarity in the Paleoproterozoic palaeolatitudes.
Intrarenal modulation of NF-κB activity attenuates cardiac injury in a swine model of CKD: a renal-cardio axis
Authors: Chade Alejandro R. , Engel Jason E. , Hall Michael E. , Eirin Alfonso , Bidwell Gene L.
Published: August 2021

Chronic kidney disease (CKD) is a progressive disorder with high cardiovascular morbidity and mortality. This work supports the role of inflammatory cytokines of renal origin in renal-cardio pathophysiology in CKD and that the heart may be a target. Furthermore, it supports the feasibility of a new strategy in a translational fashion, using targeted inhibition of renal NF-κB signaling to offset the development of cardiac injury in CKD.
Metabolic acidosis regulates RGS16 and G protein signaling in osteoblasts
Authors: Krieger Nancy S. , Bushinsky David A.
Published: August 2021

The results presented in this study indicate that regulation of regulator of G protein signaling 16 and G protein signaling in the osteoblast plays an important role in modulating the response of osteoblastic ovarian cancer G protein-coupled receptor 1 (OGR1) to metabolic acidosis and the subsequent stimulation of osteoclastic bone resorption. Further characterization of the regulation of OGR1 in metabolic acidosis-induced bone resorption will help in understanding bone loss in acidotic patients with chronic kidney disease.
Specialized proresolution mediators in the bladder: annexin-A1 normalizes inflammation and bladder dysfunction during bladder outlet obstruction
Authors: Hughes Francis M. , Harper Shelby N. , Nosé Brent D. , Allkanjari Armand , Zheng Michael T. , Jin Huixia , Purves J. Todd
Published: August 2021

To our knowledge, this is the first study of proinflammation-resolving pathways in the bladder, which is the basis of a new pharmacological genus-dubbed “resolution pharmacology” aimed at reducing inflammation without creating an immunocompromised state. Inflammation plays a causative or exacerbating role in numerous bladder maladies. We documented proresolution receptors in the rat bladder and the effectiveness of a specialized proresolving mediator, annexin-A1, in alleviating detrimental aspects of bladder outlet obstruction and speeding recovery after deobstruction.
Research on Risk Assessment of Science and Technology Data in Network Finance Based on Portfolio Empowerment
Authors: Zhao Qi
Published: August 2021

At present, the proposed network finance technology data risk assessment time is too long, leading to low accuracy. In order to solve the above problems, this paper puts forward the research on the risk assessment of network financial S&T data based on portfolio weighting, determines the risk index of network financial S&T data, calculates the weight of risk data in network S&T data, searches the risk data characteristic quantity in networks according to network S&T risk index, and completes the extraction of risk data. According to the risk data characteristics of network finance, a decision tree is constructed, the data entropy involved in the decision tree is calculated, the types of risk data characteristics are induced, the nodes of the decision tree are created, and the status of risk data of network finance is obtained. The state of risk data is brought into the definition of Bayesian network probability, and the risk degree of risk data is analyzed to improve the precision of risk data analysis. The experimental results show that the risk assessment of network financial S&T data based on portfolio weighting can effectively shorten the assessment time and improve the accuracy.
An Immersive Context Teaching Method for College English Based on Artificial Intelligence and Machine Learning in Virtual Reality Technology
Authors: Ma Li
Published: August 2021

With the development of language research and language teaching, people realize that grammatical competence is an important part of communicative competence. In foreign language teaching, grammar teaching is not only necessary but also the main way to achieve the goal of communicative competence. This article mainly studies the virtual reality technology college English immersive context teaching method based on artificial intelligence and machine learning. The purpose is to improve students’ English learning ability. Through the comparative teaching experiment of two classes of freshmen in a university, the experimental class conducted VR technology-based immersive virtual context teaching from the perspective of constructivism, while the control class adopted common multimedia equipment and traditional teaching methods. In the classroom, teachers occupy most of the time, students only passively receive a lot of information from teachers, they have little chance to participate in the exchange of information and express ideas in the target language, and most of the time they are “immersed” in the Chinese environment. The overall English level was also better than that of the control class, with an average score of 2.8 points higher. This shows that college English immersive context teaching combining constructivism theory and VR technology can indeed improve students’ English level.
Towards an Elastic Fog‐Computing Framework for IoT Big Data Analytics Applications
Authors: Pham Linh Manh , Nguyen Truong-Thang , Hoang Tien-Quang
Published: August 2021

IoT applications have been being moved to the cloud during the last decade in order to reduce operating costs and provide more scalable services to users. However, IoT latency‐sensitive big data streaming systems (e.g., smart home application) is not suitable with the cloud and needs another model to fit in. Fog computing, aiming at bringing computation, communication, and storage resources from “cloud to ground” closest to smart end‐devices, seems to be a complementary appropriate proposal for such type of application. Although there are various research efforts and solutions for deploying and conducting elasticity of IoT big data analytics applications on the cloud, similar work on fog computing is not many. This article firstly introduces AutoFog, a fog‐computing framework, which provides holistic deployment and an elasticity solution for fog‐based IoT big data analytics applications including a novel mechanism for elasticity provision. Secondly, the article also points out requirements that a framework of IoT big data analytics application on fog environment should support. Finally, through a realistic smart home use case, extensive experiments were conducted to validate typical aspects of our proposed framework.
[Retracted] Analysis of Sports Performance Prediction Model Based on GA‐BP Neural Network Algorithm
Authors: Wang Jinjuan
Published: August 2021

There are many factors that affect athletes’ sports performance in sports competitions. The traditional sports performance prediction method is difficult to obtain more accurate sports performance prediction results and corresponding data analysis in a short time, which is not conducive for coaches to formulate targeted and scientific training sprint plans for athletes’ problems. Therefore, based on GA‐BP neural network algorithm, this paper constructs a sports performance prediction model and carries out experiments and analysis. The experimental results show that GA‐BP neural network algorithm has a faster convergence speed than BP neural network and can achieve the expected error accuracy in a shorter time, which overcomes the problems of the BP neural network. At the same time, different from the previous models, GA‐BP neural network algorithm can get the athlete training model according to the relationship between quality training indicators and special sports training results, which can more intuitively show the advantages and disadvantages of athletes. In the final sports performance prediction results, GA‐BP neural network prediction results have higher accuracy, better stability, better prediction effect, and higher application value than BP neural network.
[Retracted] Analysis of Color Language and Aesthetic Paradigm of Print Art Based on GB‐BP Neural Network
Authors: Chen Zhiqiang , Tan Yongding
Published: August 2021

Color is the basic element of printmaking art creation and also an important medium for artists to express their emotions. In order to improve the understanding of the print by tourists, the research first carries out image analysis of different colors, summarizes the common color image adjectives in the art of publishing and painting, then optimizes BP neural network algorithm by gradient promotion (GP) algorithm, and constructs a color language analysis technology based on GP‐BP neural network review paradigm. Through this technology, the content of color expression of different types of print art works is analyzed. Then, the subjective evaluation of these print art works is carried out by questionnaire adjustment method. Finally, the subjective evaluation and network evaluation results are compared. On the three materials, the expression effect of color image adjectives such as “heavy light fast,” “modern classical,” “lively steady,” and “soft Yang Gang” is consistent (P value is greater than 0.05). The first set of print works mainly reflects the artist’s “affinity cold” emotion. The MSE values of the evaluation results are less than 0.01. That is, the color language analysis technology of print art based on GP‐BP neural network can reflect the artist’s emotion to a certain extent when analyzing the color language of the print.
[Retracted] Analysis of Feasibility Modeling of Multimode Physical Fitness Training for Long‐Distance Runners
Authors: Xia Xu
Published: August 2021

Because the traditional multimode feasibility modeling analysis method of physical fitness training for long‐distance runners has the problems of long modeling time and low modeling accuracy, a new multimode feasibility modeling analysis method for physical fitness training of long‐distance runners is proposed. The improved LLE (local linear embedding) method is used to reduce the dimensionality of the training data for the physical fitness of long‐distance runners. According to the processing results, the information theory is used to analyze the information content of the physical fitness training features of the long‐distance runners, the information entropy of each feature is calculated, and the long‐distance runners are extracted. Athlete’s physical fitness enhancement training characteristics, combined with quantitative regression analysis method to carry out the information regression analysis of the long‐distance runners’ physical fitness training multimode statistical sequence, construct the feasibility evaluation model of the long‐distance runners’ physical fitness training multimode and complete the feasibility of the long‐distance runners’ physical fitness training multimode feasibility study Mode analysis. The simulation experiment results show that the proposed method has higher accuracy and shorter modeling time for multimode feasibility modeling of physical fitness training for long‐distance runners.
Evolution Law of Gas Discharge of Carbon Monoxide in Mining Extra-Thick Coal Seam of Datong Mining Area
Authors: Ma Zhanyuan , Du Feng
Published: August 2021

In order to reveal the evolution law of gas discharge of carbon monoxide in mining an extra-thick coal seam of the Datong mining area by the numerical simulation and field monitoring test, the 8202 working face and 8309 working face in the Tongxin coal mine are chosen as the test sites. The results show that the seepage flow of carbon monoxide gas reaches

1.854
×

10

−
8

 

m

3

/
s

in the #1 fracture after the #3 key stratum in the far field breaks in the 8202 working face, the seepage flow of carbon monoxide gas reaches

1.307
×

10

−
7

 

m

3

/
s

in the #2 fracture, the seepage flow of carbon monoxide gas reaches

4.276
×

10

−
7

 

m

3

/
s

in the #3 fracture, the seepage flow of carbon monoxide gas reaches

4.192
×

10

−
7

 

m

3

/
s

in the #4 fracture, and the seepage flow of carbon monoxide gas reaches

1.623
×

10

−
7

 

m

3

/
s

in the #5 fracture. The initial caving of the #3 key stratum in the far field occurs and collapses to the gob, when the working face in the #3-5 coal seam advances to 180 m, and the voussoir beam forms in the #3 key stratum. Besides, a shower shape was formed by the seepage flow of carbon monoxide gas, and the maximum flow in the working face reaches

4.562
×

10

−
4

 

m

3

/
s

. When the 8309 working face advances from 521.2 m to 556.4 m, the air pressure at the working face gradually rises and reaches the maximum magnitude and then begins to decrease; when the working face advances to 556.4 m, the air pressure at the working face reaches the maximum magnitude of 91.35 kPa. The gas discharge disaster of carbon monoxide in mining the extra-thick coal seam of the Datong mining area is effectively controlled by the dynamic balance multipoint control technology. The research results can be treated as an important theoretical basis for the prevention and treatment for carbon monoxide discharge disaster in mining the extra-thick coal seam of the Datong mining area.
A Robust Data‐Driven Method for Multiseasonality and Heteroscedasticity in Time Series Preprocessing
Authors: Sun Bin , Ma Liyao , Shen Tao , Geng Renkang , Zhou Yuan , Tian Ye
Published: August 2021

Internet of Things (IoT) is emerging, and 5G enables much more data transport from mobile and wireless sources. The data to be transmitted is too much compared to link capacity. Labelling data and transmit only useful part of the collected data or their features is a promising solution for this challenge. Abnormal data are valuable due to the need to train models and to detect anomalies when being compared to already overflowing normal data. Labelling can be done in data sources or edges to balance the load and computing between sources, edges, and centres. However, unsupervised labelling method is still a challenge preventing to implement the above solutions. Two main problems in unsupervised labelling are long‐term dynamic multiseasonality and heteroscedasticity. This paper proposes a data‐driven method to handle modelling and heteroscedasticity problems. The method contains the following main steps. First, raw data are preprocessed and grouped. Second, main models are built for each group. Third, models are adapted back to the original measured data to get raw residuals. Fourth, raw residuals go through deheteroscedasticity and become normalized residuals. Finally, normalized residuals are used to conduct anomaly detection. The experimental results with real‐world data show that our method successfully increases receiver‐operating characteristic (AUC) by about 30%.
[Retracted] Simulation Test of Wireless Underground Sensor Network in Stadiums
Authors: Wang Dongzhi , Ming Hui
Published: August 2021

The underground sensor network is a kind of sensor network with sensor nodes buried in the soil. It is used in football fields, golf courses, and other stadiums and can effectively assist the stadium managers to maintain the turf condition. As the turf maintenance in the stadium is still in the manual state, the turf maintenance is time‐consuming and laborious. In order to improve this situation and adapt to future development needs, this paper proposes a wireless underground sensor network, designs the network architecture, and uses NS2 network simulation. The performance of the network was simulated and tested by the platform. This article first proposes a distance estimation method for sound and vibration signals based on the generalized correlation of the time difference of arrival based on the characteristics of the real signal when the event occurs. Then, for the range estimation obtained by applying this method, applying the idea of sparse signal reconstruction, a positioning algorithm based on the time difference of arrival based on the velocity function is proposed. Finally, using the above‐mentioned positioning algorithm, this paper obtains an overall fusion positioning strategy with the help of the idea of data fusion while taking into account the characteristics of the vibration source on the steel beam based on the positioning results of individual sound and vibration signals. The point of innovation lies in the development of positioning and tracking‐oriented platforms, including the development of wireless sensor network gateways and the development of sensor nodes. A network gateway based on network communication was developed to realize the connection with the Internet extranet. The results show that the wireless underground sensor network has strong usability in stadiums, and the network performance can meet the application requirements.
[Retracted] Application of Intelligent Fuzzy Decision Tree Algorithm in English Teaching Model Improvement
Authors: Li Jingjing
Published: August 2021

As the number of students in universities continues to grow, the university academic management system has a large amount of data on student performance. However, the utilization of these data is only limited to simple query and statistical work, and there is no precedent of using these data for improving English teaching mode. With the application of fuzzy theory in machine learning and artificial intelligence, the fuzzy decision tree algorithm was born by integrating fuzzy set theory with decision tree algorithm. In this paper, we propose a way to obtain the centroids of continuous attribute clustering by K‐means algorithm and combine the triangular fuzzy number to fuzzy the continuous data. In addition, this paper analyzes the influence of nearest neighbor distance on classification, introduces Gaussian weight function, gives different voting weights to the neighborhood according to the distance, and establishes a weighted K‐nearest neighbor classification algorithm. To address the problem of low classification efficiency of K‐nearest neighbor algorithm when the dataset is large, this paper further improves the algorithm and establishes the partitioned weighted K‐nearest neighbor algorithm. The classification time was shortened from 11.39 seconds to 5.22 seconds, and the classification efficiency greatly improved.
Analysis of English Performance Rating Based on Machine Learning and Optimized BP Network Technology
Authors: Liu Yuan , Dong Liangfeng
Published: August 2021

In order to improve the intelligent effect of English performance rating, this paper analyzes the English performance rating process and builds the corresponding algorithm model based on the wisdom of teaching ideas, and it combines BP spatial network technology with spatial sampling and spatial statistical algorithms to construct the system kernel algorithm. Moreover, this paper extracts students’ English answers through text recognition and compares them with the standard library. Among them, objective questions are mainly scored directly through standard answer comparison, and subjective questions compare student scores with standard answers. In addition, this paper uses a needs analysis to construct the framework of the entire English performance rating system and evaluates the practical effect of the system constructed in the paper through experimental research. According to statistical research data, the English performance rating system in this paper is known to have certain effects.
[Retracted] Biobjective UAV/UGV Collaborative Rendezvous Planning in Persistent Intelligent Task‐Based Wireless Communication
Authors: Wang Qin , Chen Hua , Tian Junwei , Wang Jia , Su Yu
Published: August 2021

This paper addresses a multiobjective Unmanned Aerial Vehicle (UAV) and Unmanned Ground Vehicle (UGVs) collaboration scheduling problem in which UAVs must be recharged periodically during a persistent task, such as wireless communication and making aerial panoramic VR video by UAV. The proposal is to introduce a UGV/UAV cooperative system in which UAVs should be recharged by UGVs periodically, and also, the UGVs have to visit their task points expect for the recharge points. The objective of the problem is to schedule and plan paths with the tradeoff of path length and makespan for UAVs and UGVs. The mathematical model which can be considered a combinatorial multiobjective optimization problem is presented firstly, and the solution of the problem is composed of presubsolution and postsubsolution. The multiobjective adaptive large neighborhood is hybrid with the Pareto local search (MOALP) to resolve the problem. The experimental result shows that the proposed algorithm outperforms the compared algorithms on the rendezvous planning problem for UAVs and UGVs working collaboratively in intelligent tasks.
New Bounds for the Randić Index of Graphs
Authors: Atapour Maryam , Jahanbani Akbar , Khoeilar Rana
Published: August 2021

The Randić index of a graph

G

is defined as the sum of weights

1
/

d

u

d

v

over all edges

u
v

of

G

, where

d

u

and

d

v

are the degrees of the vertices

u

and

v

in

G

, respectively. In this paper, we will obtain lower and upper bounds for the Randić index in terms of size, maximum degree, and minimum degree. Moreover, we obtain a generally lower and a general upper bound for the Randić index.
miR-124-3p Ameliorates Isoflurane-Induced Learning and Memory Impairment via Targeting STAT3 and Inhibiting Neuroinflammation
Authors: Liu Fenghua , Qiu Fengyu , Chen Huayong
Published: August 2021

Introduction: Substantial evidence has indicated that isoflurane leads to learning and memory impairment. This study was designed to investigate the potential role of microRNA-124-3p (miR-124-3p) in isoflurane-induced learning and memory impairment in rats. Methods: Spatial learning and memory of rats were estimated by the Morris water maze (MWM) test after the construction of isoflurane-treated models. qRT-PCR was performed to assess the expression levels of miR-124-3p. The levels of interleukin-1β, interleukin-6, and tumor necrosis factor-α in the hippocampal tissues were determined by enzyme-linked immunosorbent assay. The luciferase activity was determined by using a dual-luciferase reporter assay system. Results: The higher escape latency and lower time spent in the original quadrant were shown in isoflurane-treated rats compared with the control rats. Moreover, treatment with isoflurane could induce neuroinflammation, and miR-124-3p was poorly expressed in the hippocampal tissue of isoflurane-treated rats. Furthermore, STAT3 is a functional target of miR-124-3p, and inflammatory cytokine level was downregulated by miR-124-3p. Discussion/Conclusion: Combining the results of the current study demonstrates that miR-124-3p may have pivotal roles in improving isoflurane-induced learning and memory impairment via targeting STAT3 and inhibiting neuroinflammation.
The Potential and Limitations of Precision Oncology: Lessons Learned from Whole-Exome Sequencing in an Exceptional Response to Everolimus in Advanced Renal Cell Carcinoma
Authors: Pilling Amanda , Wee Christopher , Bar-Meir Eliezer , Dyson Gregory , Hwang Ok , Gupta Nilesh , Chitale Dhananjay , Hwang Clara
Published: August 2021

Through elucidating the genetic mechanisms of drug sensitivity, precision medicine aims to improve patient selection and response to therapy. Exceptional responders are patients that exhibit exquisite and durable responses to targeted therapy, providing a rare opportunity to identify the molecular basis of drug sensitivity. We identified an exceptional responder to everolimus, an oral inhibitor of the mammalian target of rapamycin (mTOR) pathway, in a patient with advanced renal cell carcinoma. Through whole-exome sequencing on pretreatment and metastatic tumor DNA, we identified alterations in several mTOR pathway genes, with several mutations implicated in mTOR activation. Importantly, these alterations are currently not included in commercially available next-generation sequencing panels, suggesting that precision medicine is still limited in its ability to predict responses to mTOR-targeted therapies. Further research to discover and validate predictive biomarkers of response to everolimus and other targeted therapies is urgently needed. Given the rarity of patients with exceptional responses to targeted agents, cooperative efforts to understand the molecular basis for these phenotypes are essential.
Relation of Maximum Lifetime Body Mass Index with Age at Hemodialysis Initiation and Vascular Complications in Japan
Authors: Onozaki Akira , Nagayama Daiji , Azuma Nakanobu , Sugai Keita , Shitara Etsuko , Sakai Takehiko , Masai Motoyuki , Shirai Kohji , Tatsuno Ichiro
Published: August 2021

Objective: The aim of this study was to investigate the association of the maximum lifetime body mass index (max BMI) with hemodialysis initiation and comorbidities in Japanese hemodialysis patients. Methods: In a retrospective cross-sectional study on 724 hemodialysis patients, max BMI, age at hemodialysis initiation, and comorbidities including sleep apnea syndrome, cerebro-cardiovascular diseases, and proliferative diabetic retinopathy (PDR) were analyzed. Early hemodialysis initiation was defined as age <50 years. Result: Diabetes patients showed a higher max BMI and prevalence of atherosclerotic diseases than nondiabetes patients, despite almost the same age at hemodialysis initiation. Patients with early hemodialysis initiation showed higher male ratio, prevalence of PDR, and max BMI than those with later initiation, despite almost equal prevalence of diabetes. Receiver-operating characteristic curve analysis determined a max BMI of 28.4 kg/m2 as a reliable cutoff value for predicting early hemodialysis initiation, and this parameter was identified as an independent predictor of early hemodialysis initiation using bivariate logistic regression analysis. Vitrectomy for PDR also tended to contribute independently to early hemodialysis initiation. Conclusion: A high max BMI contributed to early hemodialysis initiation independent of diabetes. Furthermore, PDR was associated with a high max BMI and early hemodialysis initiation. These results suggest that weight reduction in young chronic kidney disease patients with obesity may prevent hemodialysis and blindness.
Intrinsic motivation, career exposure, and quality of life: How do they influence the accounting students’ career choice?
Authors: Hatane Saarce Elsye , Gunawan Fenia Agustin , Pratama Stella Wulan
Published: August 2021

This study aimed to determine the factors that are considered by accounting students who choose careers as public accountants and private accountants. Three factors that became the focus of observation are intrinsic motivation, career exposure, and quality of life. Data collection in this research was organized in several public and private universities in Java. The survey was distributed online and obtained 445 valid questionnaires used to test the research model. The findings indicated that students who have more career information are more likely to choose a career as a public accountant. Besides, students who have a higher perception of the quality of life tend to choose a career as a private accountant. This study has not found significant evidence on the effect of intrinsic motivation on career choice. This study promotes accounting career institutions and universities in developing the interest of the younger generation in the accounting profession, be it public accountants or private accountants. Developing from the limitations in this study, further research can develop this accountant career research model by considering other factors, as well as observing accounting students in various demographic variations.
Optimal generation capacity mix in microgrid to meet demand
Authors: Sharma Virendra , Choubey Piyush Kumar , Kumar Amit , Gidwani Lata
Published: August 2021

This paper presents an approach for optimal generation capacity mix to fulfill future power demand using a micro-grid model which is operated in both the on-grid and off-grid modes. This is achieved using the solar photovoltaic (PV) system, fuel-cell, and battery energy storage system (BESS) with and without the grid-connected mode. Different control approaches and optimal size of the generators are presented. Proposed micro grid with solar PV system, solid oxide fuel cell (SOFC) and back scattered electron detector (BESD) is tested for different operational scenarios of loads. Comparative index of performance (CIP) is introduced to indicate effectiveness of the micro-grid operations in the off-grid mode. This is based on difference in the total harmonic distortions (THD) in both the on-grid and off-grid modes. This is established that CIP indicates that the micro-grid works efficiently in the both the on-grid and off- grid modes during the simulated events of the switching ON/OFF the loads at different test conditions. The optimal generation mix successfully met the load demand with and without grid having conventional generatio.
The gravitational search algorithm for incorporating TCSC devices into the system for optimum power flow
Authors: Wais Dunya Sh. , Majeed Wafaa S.
Published: August 2021

This paper proposes a gravitational search algorithm (GSA) to allocate the thyristor-controlled series compensator (TCSC) incorporation with the issue of reactive power management. The aim of using TCSC units in this study is to minimize active and reactive power losses. Reserve beyond the thermal border, enhance the voltage profile and increase transmission-lines flow while continuing the whole generation cost of the system a little increase compared with its single goal base case. The optimal power flow (OPF) described is a consideration for finding the best size and location of the TCSCs devices seeing techno-economic subjects for minimizing fuel cost of generation units and the costs of installing TCSCs devices. The GSA algorithm's high ability in solving the proposed multi-objective problem is tested on two 9 and 30 bus test systems. For each test system, four case studies are considered to represent both normal and emergency operating conditions. The proposed GSA method's simulation results show that GSA offers a practical and robust high-quality solution for the problem and improves system performance.
An optimal allocation of UPFC and transient stability improvement of an electrical power system: IEEE-30 buses
Authors: Razzaq Altahir Ali Abdul , Marei Marwa M.
Published: August 2021

Recently, the expansion process of electrical networks has become crucial with the development of electrical systems. One of the active solutions to progress the performance of an electrical system is the usage of flexible AC transmission system (FACTS). As a new generation of telecommunications and power electronics technology, FACTS has provided a new viewpoint to increase the bearing capacity, better control the grid, and reduce costs. The unified power flow controller had a multi-purpose unit that could command the scenario of providing or consuming the power components and maintaining the bus voltage. The study's novelty resided in presenting a modified particle swarm optimization algorithm-based software system and applied a Newton-Raphson load flow solution to get the best solutions for optimal allocation of unified power flow controllers (UPFC). This study has focused on the functions of the UPFC electrical system with corresponding effects on transient stability. MATLAB software (Simulink/code) and excel sheet were performed on IEEE 30 buses as a case study. It has been shown the effectiveness of UPFC with fast response and autonomous command on the flow of power components. The dynamic response for stability improvement for some network buses had been verified to ensure the robustness of UPFC during a sudden disturbance in electrical load. The case study results illustrate that the number of UPFC increased with load increased by (14% and 21%).