bluuebunny/crossref_metadata_2025 huggingface dataset:
Non-consumptive effects of intraguild predator Blattisocius dentriticus (Berlese) on the development and prey consumption of Neoseiulus cucumeris (Oudemans)
Authors: Gu Xinyao , Zhang Keshi , Zhang Zhi-Qiang
Published: July 2022

Predator-prey interactions are fundamental to the understanding of ecological communities. The non-consumptive effects of predators on the food web can be more prominent than direct killing. However, the non-consumptive effects in intraguild interaction have rarely been studied. This study determined the non-consumptive effects of an intraguild predator Blattisocius dentriticus on Neoseiulus cucumeris. The responses of N. cucumeris to the predation risk of B. dentriticus adult females were examined in a laboratory test. The developmental response of N. cucumeris to predation risk was sex-specific: the presence of B. dentriticus cues prolonged the immature development of N. cucumeris males and increased their consumption rates of Tyrophagus putrescentiae eggs, but did not affect the development and prey consumption of female N. cucumeris. The size at maturity of N. cucumeris was not affected by predation risk from B. dentriticus. This study demonstrated that intraguild predators can have substantial non-consumptive influence on intraguild prey.
New records of water mites from Turkey and Iran revealed by DNA barcoding, with the description of a new species (Acari, Hydrachnidia)
Authors: Pešić Vladimir , Esen Yunus , Gülle Pinar , Zawal Andrzej , Saboori Alireza , Jovanović Milica , Bańkowska Aleksandra , Smit Harry
Published: July 2022

New records of water mites from Iran and Turkey revealed by DNA barcoding are presented. DNA barcodes were recovered from 44 water mite specimens morphologically assigned to 18 species. The DNA barcoding data for the twelve species were uploaded into the BOLD database. One species of the Hygrobates longiporus-complex, H. thori Pešić & Smit sp. nov. is described as new for science and Hydrodroma persica Pešić & Saboori, 2012 is reported as new for Turkey. We propose to lower the taxonomic status of Hydrodroma golestanica to a subspecies of H. torrenticola, i.e. H. torrenticola golestanica nov. stat.
An ultrasonically actuated needle promotes the transport of nanoparticles and fluids
Authors: Perra Emanuele , Hayward Nick , Pritzker Kenneth P. H. , Nieminen Heikki J.
Published: July 2022

Non-invasive therapeutic ultrasound (US) methods, such as high-intensity focused ultrasound (HIFU), have limited access to tissue targets shadowed by bones or presence of gas. This study demonstrates that an ultrasonically actuated medical needle can be used to translate nanoparticles and fluids under the action of nonlinear phenomena, potentially overcoming some limitations of HIFU. A simulation study was first conducted to study the delivery of a tracer with an ultrasonically actuated needle (33 kHz) inside a porous medium acting as a model for soft tissue. The model was then validated experimentally in different concentrations of agarose gel showing a close match with the experimental results, when diluted soot nanoparticles (diameter < 150 nm) were employed as delivered entity. An additional simulation study demonstrated a threefold increase in the volume covered by the delivered agent in liver under a constant injection rate, when compared to without US. This method, if developed to its full potential, could serve as a cost effective way to improve safety and efficacy of drug therapies by maximizing the concentration of delivered entities within, e.g., a small lesion, while minimizing exposure outside the lesion.
Head Kinematics in Youth Ice Hockey by Player Speed and Impact Direction
Authors: Swenson Abigail G. , Schunicht Bari A. , Pritchard Nicholas S. , Miller Logan E. , Urban Jillian E. , Stitzel Joel D.
Published: July 2022

Hockey is a fast-paced sport known for body checking, or intentional collisions used to separate opponents from the puck. Exposure to these impacts is concerning, as evidence suggests head impact exposure (HIE), even if noninjurious, can cause long-term brain changes. Currently, there is limited understanding of the effect of impact direction and collision speed on HIE. Video analysis was used to determine speed and direction for 162 collisions from 13 youth athletes. These data were paired with head kinematic data collected with an instrumented mouthpiece. Relationships between peak resultant head kinematics and speeds were evaluated with linear regression. Mean athlete speeds and relative velocity between athletes ranged from 2.05 to 2.76 m/s. Mean peak resultant linear acceleration, rotational velocity, and rotational acceleration were 13.1 g, 10.5 rad/s, and 1112 rad/s2, respectively. Significant relationships between speeds and head kinematics emerged when stratified by contact characteristics. HIE also varied by direction of collision; most collisions occurred in the forward-oblique (ie, offset from center) direction; frontal collisions had the greatest magnitude peak kinematics. These findings indicate that HIE in youth hockey is influenced by speed and direction of impact. This study may inform future strategies to reduce the severity of HIE in hockey.
Do the Self-Reported Changes in Physical Activity After the Emergence of the COVID-19 Pandemic Associate With Major Depression According to Moderate to Vigorous Physical Activity Status?
Authors: Ahn Jeong Hyun , Nam Jin Young
Published: July 2022

Background: As the COVID-19 pandemic emerged, and social distancing increased, the physical activity (PA) of people decreased, which increased depression. The purpose of this study was to analyze the relationship between self-reported changes in PA with the COVID-19 pandemic and major depression according to moderate to vigorous physical activity (MVPA) status. Methods: This study included 228,457 adults and used data from the Korea Community Health Survey 2020. Multiple logistic regression analysis was performed to evaluate the relationship between self-reported changes in PA and major depression stratified by MVPA status. Results: The percentage of participants who reported decreases in PA was 39.5% in men and 44.7% in women compared with the pre-COVID-19 pandemic period. Those who reported decreases in PA after the onset of COVID-19 had major depression (men odds ratio = 1.28; 95% confidence interval, 1.15–1.43 and women odds ratio = 1.35; 95% confidence interval, 1.25–1.46). Women who were moderately or vigorously physically active had higher odds of major depression when they reported decreases in PA (odds ratio = 1.31; 95% confidence interval, 1.06–1.62). Conclusions: People who reported decreases in PA were associated with major depression compared with the pre-COVID-19 pandemic period. Based on this, the government should encourage exercise to reduce major depression and provide guidelines for PA at home or outdoors.
Bridging membrane transport models
Authors: Geise Geoffrey M.
Published: July 2022

Analysis of transport processes in swollen polymer networks bridges two classical models
Accessing justice for survivors of violence against women
Authors: Blair Graeme , Jassal Nirvikar
Published: July 2022

A police reform experiment in India shows mixed results
In Other Journals
Authors: Hines Pamela J. , Vinson Valda , Jiang Di , Osborne Ian S. , Wible Brad , Hurtley Stella M. , Grocholski Brent
Published: July 2022

Editors’ selections from the current scientific literature
Pharmacokinetics and Adverse Effects of Clofazimine in the Treatment of Pulmonary Non-Tuberculous Mycobacterial Infection
Authors: Watanabe Fumiya , Furuuchi Koji , Hanada Kazuhiko , Fujiwara Keiji , Uesugi Fumiko , Hiramatsu Miyako , Yoshiyama Takashi , Shiraishi Yuji , Kurashima Atsuyuki , Ohta Ken , Morimoto Kozo
Published: July 2022

Clofazimine (CFZ) is used to treat pulmonary non-tuberculous mycobacterial (NTM) infection; however, its pharmacokinetics remain unexplored in patients with pulmonary NTM, and the relationship between CFZ serum concentration and adverse effects has not been investigated. The objectives of this study were to characterize the pharmacokinetics of CFZ in pulmonary NTM disease treatment and to investigate the relationship between the steady-state CFZ serum concentration and adverse effects.
Cyanophycin Granule Polypeptide: a Neglected High Value-Added Biopolymer, Synthesized in Activated Sludge on a Large Scale
Authors: Zou Kui , Huang Yu , Feng Bo , Qing Taiping , Zhang Peng , Chen You-Peng
Published: July 2022

The conversion of organic pollutants into bioresources by activated sludge can reduce the carbon dioxide emission of wastewater treatment plants. Identification of new high value-added biopolymers produced by activated sludge is beneficial to recover bioresources.
Unveiling the Biosynthetic Pathway for Short Mycolic Acids in Nontuberculous Mycobacteria: Mycobacterium smegmatis MSMEG_4301 and Its Ortholog Mycobacterium abscessus MAB_1915 Are Essential for the Synthesis of α′-Mycolic Acids
Authors: Di Capua Cecilia B. , Belardinelli Juan M. , Carignano Hugo A. , Buchieri María V. , Suarez Cristian A. , Morbidoni Héctor R.
Published: July 2022

Mycobacterium abscessus
is a nontuberculous
mycobacterium
responsible for an increasing number of hard-to-treat infections due to the impervious nature of its cell envelope, a natural barrier to several antibiotics. Mycolic acids are key components of that envelope; thus, their synthesis is a valuable target for drug development.
The Greenhouse Phyllosphere Microbiome and Associations with Introduced Bumblebees and Predatory Mites
Authors: Legein Marie , Smets Wenke , Wuyts Karen , Bosmans Lien , Samson Roeland , Lebeer Sarah
Published: July 2022

Greenhouses, though highly effective agricultural environments, are characterized by reduced sources of bacterial diversity and means of dispersal compared to more natural settings. As it is known that plant health and productivity are affected by associated bacteria, improving our knowledge on the bacterial communities on greenhouse crops is key to further innovate in horticulture.
Optic chiasm, optic tract and deep white demyelination: an unusual distribution of myelin oligodendrocyte glycoprotein-associated demyelination (MOGAD), case report and review of literature
Authors: Lasrado Adeline , Chattannavar Goura , Sachdeva Virender , Kekunnaya Ramesh
Published: July 2022

A preschool girl presented with sudden-onset bilateral painless loss of vision from 2 days prior. Child’s examination showed light perception vision, sluggishly reacting pupils, otherwise normal anterior segment, healthy optic disc and retina in both eyes. MRI of brain and orbit with contrast revealed thickened left part of the optic chiasm with contrast enhancement extending proximally to bilateral optic tract and hyperintensities in the left thalamus and periventricular white mater. Considering the topographical distribution of lesions in the brain, neuromyelitis optica spectrum disorder was suspected. The child was started on intravenous methylprednisolone followed by tapering oral steroids. Serological testing was positive for myelin oligodendrocyte glycoprotein (MOG) and negative for aquaporin-4 antibodies. This case represents an unusual case of MOG associated demyelination disorder where the distribution of lesions showed chiasmal involvement along with optic tract, thalamus and deep white mater lesions.
Diagnostic delay in IPF impacts progression-free survival, quality of life and hospitalisation rates
Authors: Hoyer Nils , Prior Thomas Skovhus , Bendstrup Elisabeth , Shaker Saher Burhan
Published: July 2022

Background

The diagnosis of idiopathic pulmonary fibrosis (IPF) is often delayed up to several years. The objective of this study was to assess the impact of the diagnostic delay on progression-free survival, quality of life and hospitalisation rates.

Methods

A total of 264 incident patients with IPF were included immediately after their diagnosis and followed for up to 5 years, with regular collection of clinical data, quality-of-life questionnaires and assessment of disease progression. Hospitalisation data were extracted from electronic patient records. Analyses were performed on the entire cohort and strata according to forced vital capacity (FVC) at diagnosis.

Results

A long diagnostic delay (>1 year) was associated with worse progression-free survival compared with a short diagnostic delay (<1 year) (HR: 1.70, 95% CI: 1.18 to 2.46, p=0.004) especially in patients with mild disease at the time of diagnosis (FVC>80% predicted). Mean total scores of the St. George’s respiratory questionnaire (SGRQ), a derived IPF-specific version of the SGRQ and the chronic obstructive pulmonary disease assessment test (CAT) were consistently higher in patients with long diagnostic delays, indicating worse quality of life. Mean hospitalisation rates were higher during the first year after diagnosis (Incidence rate ratio [IRR]: 3.28, 95% CI: 1.35 to 8.55, p=0.01) and during the entire follow-up (IRR: 1.74, 95% CI: 1.01 to 3.02, p=0.04).

Conclusion

A diagnostic delay of more than 1 year negatively impacts progression-free survival, quality of life and hospitalisation rates in patients with IPF. These findings highlight the importance of an early diagnosis for proper management of IPF.

Trial registration number

NCT02755441.
British Society of Gastroenterology guidelines on the management of functional dyspepsia
Authors: Black Christopher J , Paine Peter A , Agrawal Anurag , Aziz Imran , Eugenicos Maria P , Houghton Lesley A , Hungin Pali , Overshott Ross , Vasant Dipesh H , Rudd Sheryl , Winning Richard C , Corsetti Maura , Ford Alexander C
Published: July 2022

Functional dyspepsia (FD) is a common disorder of gut–brain interaction, affecting approximately 7% of individuals in the community, with most patients managed in primary care. The last British Society of Gastroenterology (BSG) guideline for the management of dyspepsia was published in 1996. In the interim, substantial advances have been made in understanding the complex pathophysiology of FD, and there has been a considerable amount of new evidence published concerning its diagnosis and classification, with the advent of the Rome IV criteria, and management. The primary aim of this guideline, commissioned by the BSG, is to review and summarise the current evidence to inform and guide clinical practice, by providing a practical framework for evidence-based diagnosis and treatment of patients. The approach to investigating the patient presenting with dyspepsia is discussed, and efficacy of drugs in FD summarised based on evidence derived from a comprehensive search of the medical literature, which was used to inform an update of a series of pairwise and network meta-analyses. Specific recommendations have been made according to the Grading of Recommendations Assessment, Development and Evaluation system. These provide both the strength of the recommendations and the overall quality of evidence. Finally, in this guideline, we consider novel treatments that are in development, as well as highlighting areas of unmet need and priorities for future research.
A Hierarchical Processing and Completion Mechanism of Foreground Information for Person Re-Identification
Authors: Huang Jiajian , Wang Shihao
Published: July 2022

Person re-identification (Re-ID) arises in many applications such as video surveillance and intelligent security. Background clutter and distribution drift are two issues that cross-domain person Re-ID faces. In this research, we propose that the background clutter problem be solved by combining semantic segmentation technology with human attribute identification technology. To overcome the distribution drift problem, we propose employing MMD as a metric for distribution differences and processing methods based on feature properties. The results of the experiments reveal that our strategy yielded the best results.
China’s BRI: A Platform for Cultural Communications and Exchanges with Iran
Authors: Yazdani Enayatollah , Zeng Ji
Published: July 2022

The Chinese Belt and Road Initiative (BRI) is a large project aiming at improving regional cooperation through better connectivity among the countries lying on the ancient Silk Road and beyond. Since Iran is one of the countries in the BRI, the Sino-Iranian cooperation in the framework of BRI can enhance the economic, political, security, military, cultural, and diplomatic ties between the two nations. In particular, both China and Iran attach great importance to cultural exchanges based on BRI’s aims and policies which helps in deepening mutual understanding between the two nations and promoting cultural cooperation of Beijing and Tehran. Indeed, Belt and Road Initiative would greatly contribute to boosting the cultural interaction and exchanges between China and Iran.
The 21st Glossop Lecture: engineering geology and the geoscience time machine
Authors: Shilston David T.
Published: July 2022

How did the geology and geomorphology of a site become the way it is today? And what are the practical engineering geological applications of that knowledge to civil engineering and environmental projects? The answer is much more than a description of the materials logged in an excavation or a borehole, or a description of a site's geological history. It requires a mental time machine that enables us to investigate and understand the conditions, processes and materials that occur over geological time and recently (including human-induced, anthropogenic impacts). In this paper, by means of some short case study examples, I explore and describe how the application of a time machine approach is an essential tool for engineering geologists, both in the field and back at their desks. (A recording of my lecture, which I gave at the Royal Institution, London on 24 November 2021, is available on YouTube: Glossop Medal Lecture, 2021,
https://youtu.be/CAJDtSrrA4w
. The lecture is about 65 minutes long.)
On Node Localizability Identification in Barycentric Linear Localization
Authors: Ping Haodi , Wang Yongcai , Shen Xingfa , Li Deying , Chen Wenping
Published: July 2022

Determining whether nodes can be uniquely localized, called localizability detection, is a concomitant problem in network localization. Localizability detection under the traditional
Non-Linear Localization (NLL)
schema has been well explored, whereas localizability under the emerging
Barycentric coordinate-based Linear Localization (BLL)
schema has not been well investigated. Non-awareness of the node localizability in BLL may cause theoretically localizable nodes to converge to wrong locations because their locations are impacted by the wrong locations of the unlocalizable nodes through the iterative location propagation. In this article, the deficiency of existing localizability theories and algorithms in BLL is firstly investigated and then a necessary condition and a sufficient condition for BLL node localizability detection are proposed. Based on these two conditions, an efficient

Iterative Maximum Flow (IMF)

algorithm is designed to identify BLL localizable nodes, and only localizable nodes are selected to enable a
Localizability Aware Barycentric Linear Localization (LABLL)
algorithm, which can guarantee the locations of the localizable nodes converging correctly. The proposed IMF and LABLL algorithms are validated by both theoretical analysis and experimental evaluations.
Research on Multimedia Teaching and Teaching Reform Innovation of Accounting Major in Higher Vocational Colleges under the Background of Big Data and Internet of Things
Authors: Yu Haixia
Published: July 2022

Under the influence of the rapid development of the production process of computers, chips, semiconductors, and other equipment, computer software technology has also made great progress. Among them, big data and Internet of Things technologies have developed particularly rapidly, and big data and Internet of Things technologies have gradually become mainstream technologies in this era. The Internet of Everything and data prediction in its technical ideas have brought convenience to the technological innovation of various industries. Teaching innovation in colleges and universities has always pursued the integration of the latest technology into the teaching process of colleges and universities, especially higher vocational colleges that attach importance to practical application, among which are accounting majors. Because it is impossible to directly conduct experiments through equipment like engineering, but enterprises connected with higher vocational colleges have greater demand for students with a high level of practice, so the use of multimedia education teaching and teaching reform and innovation has become the focus of higher vocational colleges On the basis of analyzing the necessity of multimedia teaching of accounting major in higher vocational colleges, this paper conducts a questionnaire survey on teachers and students in 6 higher vocational colleges and analyzes the existing problems of multimedia teaching in accounting major in higher vocational colleges according to the questionnaire data. Finally, aiming at the existing problems, combined with big data and Internet of Things technology, analyze the possible teaching innovation paths that new technology can provide for accounting majors in higher vocational colleges.
Using the Logistic Map as Compared to the Cubic Map to Show the Convergence and the Relaxation of the Period–1 Fixed Point
Authors: Akwasi Anamuah Mensah Patrick , Obeng-Denteh William , Issaka Ibrahim , Baah Gyamfi Kwasi , Asamoah Joshua Kiddy K.
Published: July 2022

In this paper, we employ the logistic map and the cubic map to locate the relaxation and the convergence to the periodic fixed point of a system, specifically, the period—1 fixed point. The study has shown that the period—1 fixed point of a logistic map as a recurrence has its convergence at a transcritical bifurcation having its power-law fit with exponent

β
=
−
1

when

α
=
1

and

μ
=
0

. The cubic map shows its convergence to the fixed point at a pitchfork bifurcation decaying at a power law with exponent

β
=
−

1
/
2

α
=
1

and

μ
=
0

. However, the system shows their relaxation time at the same power law with exponents and

z
=
−
1

.
An ALBI- and Ascites-Based Model to Predict Survival for BCLC Stage B Hepatocellular Carcinoma
Authors: He Cheng , Yang Jing , Jin Zheng , Zhu Ying , Hu Wei , Zeng Lingfeng , Li Xiaocheng
Published: July 2022

Background. We aimed to develop a predictive model constituted with the ALBI grade, the ascites, and tumor burden related parameters in patients with BCLC stage B HCC. Methods. Patients diagnosed as the BCLC stage B HCC were collected from a retrospective database. Construction and validation of the predictive model were performed based on multivariate Cox regression analysis. Predictive accuracy, discrimination (c-index), and fitness performance (calibration curve) of the model were compared with the other eight models. The decision curve analysis (DCA) was used to evaluate the clinical utility. Results. A total of 1773 patients diagnosed as BCLC stage B HCC between 2007 and 2016 were included in the present study. The ALBI-AS grade, the AFP level, and the 8-and-14 grade were used for the development of a prognostic prediction model after multivariate analysis. The area under the receiver operator characteristic curve (AUROC) for overall survival at 1, 2, and 3 years predicted by the present model were 0.73, 0.69, and 0.67 in the training cohort. The concordance index (c-index) and the Aiken information criterion (AIC) were 0.68 and 6216.3, respectively. In the internal and external validation cohorts, the present model still revealed excellent predictive accuracy, discrimination, and fitness performance. Then the ALBI-AS based model was evaluated to be superior to other prognostic models with the highest AUROC, c-index, and lowest AIC values. Moreover, DCA also demonstrated that the present model was clinically beneficial. Conclusion. The ALBI-AS grade is a novel predictor of survival for patients with BCLC stage B HCC.
Online Cyber-Attack Detection in the Industrial Control System: A Deep Reinforcement Learning Approach
Authors: Liu Zhenze , Wang Chunyang , Wang Weiping
Published: July 2022

In the open network environment, industrial control systems face huge security risks and are often subject to network attacks. The existing abnormal detection methods of industrial control networks have the problem of a low intelligence degree of adaptive detection and recognition. To overcome this problem, this article makes full use of the advantages of deep reinforcement learning in decision-making and builds a learning system with continuous learning ability. Specifically, industrial control network and deep reinforcement learning characteristics are applied to design a unique reward and learning mechanism. Moreover, an industrial control anomaly detection system based on deep reinforcement learning is constructed. Finally, we verify the algorithm on the gas pipeline industrial control dataset of Mississippi State University. The experimental results show that the convergence rate of this model is significantly higher than that of traditional deep learning methods. More importantly, this model can get a higher F1 score.
Fibrosis-4 Index Is Closely Associated with Arterial Damage and Future Risk of Coronary Heart Disease in Type 2 Diabetes
Authors: Watanabe Kentaro , Takakubo Noe , Saigusa Taro , Nagasawa Akiko , Yamana Midori , Ojima Midori , Kameda Wataru , Susa Shinji , Ishizawa Kenichi , Ishihara Hisamitsu
Published: July 2022

This study evaluated the association between fibrosis-4 (FIB 4) index and arterial damage or future risk of coronary heart disease (CHD) in type 2 diabetes. The study subjects were 253 patients with type 2 diabetes. The FIB4 index, as a marker of hepatic fibrosis based on age, aspartate aminotransferase and alanine aminotransferase levels, and platelet count, was calculated for all subjects. Carotid intima-media thickness (IMT), carotid artery calcification (CAC), and aortic arch calcification (AAC) grade (0–2) were assessed as atherosclerotic variables. The Suita score was calculated as the future risk of coronary heart disease (CHD). We assessed whether the FIB4 index was associated with both atherosclerotic variables and the Suita score. FIB4 index was significantly associated with IMT (r = 0.241,

P
<
0.001

) and Suita score (r = 0.291,

P
<
0.001

). Subjects with CAC showed a significantly higher FIB4 index score compared to subjects without (1.70 ± 0.74 and 1.24 ± 0.69, respectively,

P
<
0.001

), whereas the FIB4 index was significantly elevated with a higher grade of AAC (1.24 ± 0.74, 1.56 ± 0.66, and 1.79 ± 0.71, respectively,

P
<
0.001

). Linear regression analysis adjusted for clinical characteristics indicated that the FIB4 index was positively associated with IMT, Suita score, CAC, and AAC grade (β = 0.241,

P
=
0.004

; β = 2.994,

P
<
0.001

; β = 0.139,

P
=
0.001

; and β = 0.265,

P
<
0.001

, respectively). FIB4 index is closely associated with arterial damage and future risk of CHD in type 2 diabetes.
Optimization of Hello Message Broadcasting Prediction Model for Stability Analysis
Authors: Venu Nookala , Swathi R. , Sarangi Sanjaya Kumar , Subashini V. , Arulkumar D. , Ralhan Shimpy , Debtera Baru
Published: July 2022

In mobile ad hoc networks, nodes are connected and disconnected regularly; since every mobile node travels autonomously, those nodes are dispersed not uniformly. Connection damage has straight consequences on the network characteristics. For that motivation, various techniques are quick and efficient damage of connection identification using alert packet is difficult for that time to identify next connection in a mobile network. It increases end to end delay and reduces the network lifetime. The present effective connection alteration rate- (ECAR-) based communication scheme depends on the details of neighbouring nodes to survey the connection between the connection alteration rate and the hello time gap in terms of entire transmission rate. Nevertheless, the hello time gap tracking algorithm is constructed to increase transmission rate displaying a stable choice of connection alteration rate, still although node velocity alters. It reduces end to end delay and increases the network lifetime. The hello time gap tracking algorithm is constructed in the network, and it obtains effective connection among unstable mobile nodes. Experimental output indicates that the connection alteration rate in general enhances the hello time gap. It provides the effective connection changing rate for analyzing different metrics which are network lifetime. throughput, and detection efficiency that are improved in the proposed ECAR scheme.
Digital Art Design Effectiveness Model System Based on K-Medoids Algorithm
Authors: Luo Xin
Published: July 2022

With the development of the times, figurative expressions no longer meet the creative needs of artists and the aesthetic demands of the people. In order to express art in a more profound way, the perfect use of abstract graphics plays a crucial role in the success of the work. In recent years, there has been a surge in the creation of digital art, but there is relatively little theoretical literature on the combination of abstract graphics as a visual language and digital art. In addition, research on the theoretical aspects of digital art design is also relatively weak, so it is essential to analyse the formal aesthetics and innovative applications. In fact, digital art design has a very important role to play in promoting the development of creative cultural industries. In other words, the healthy development of digital art design can influence the future prospects of a country’s creative and cultural industries. Digital art design is an integrated and complex production process and labour outcome. In addition to its human, aesthetic, and social value, digital art also has an economic value. Digital art is a new art form that combines digital technology and artistic aesthetics. As such, digital art is characterised by high technology, diverse forms, popularised art, and the advantages of high communication, interactivity, and influence, which can provide more assistance for the innovation and application of abstract graphics. Digital art is multifaceted and has an artistic expression that cannot be matched by other forms of technology. Abstract graphics, driven by digital art, are full of novelty and interest and can greatly enrich people’s emotions and senses. Abstract graphics bring the experience of digital art to its fullest potential. The combination of digital art and abstract graphics offers more innovation and possibilities for the development of art and will bring great prosperity to art communication. With the widespread use of computer and network technology, the Internet has developed rapidly. In this context, digital art, as art created in a digital way and concept, has gained widespread attention. As a result, how to integrate existing computer resources in the new environment to build a model of digital art design effectiveness will cause a direct influence on the quality of digital art design with digital content innovation as the core. At the same time, as digital art becomes more and more popular, the demand for digital talents becomes very urgent. As a result, the cultivation of high-quality digital talents has become a major concern for society. Therefore, in order to explore the success of digital art design and the cultivation of digital art talents, and to better serve the innovation of digital art, this paper proposes a digital art effectiveness model based on the K-medoids algorithm. This model can provide a deeper and more comprehensive understanding of digital art and abstract graphics and provide theoretical support for professional design creation.
Math and Science Integrated Curriculum: Pedagogical Knowledge-Based Education Framework
Authors: Al-Mutawah Masooma , Mahmoud Enaz , Thomas Ruby , Preji Nisha , Alghazo Yazan
Published: July 2022

Many researchers investigated students’ attitudes towards learning mathematics and science. Educators were trying to be more innovative in creating different teaching strategies to engage students in these subjects which they find complex or not relevant to their lives. Namely, curriculum designers were trying to find ways to make these subjects more enjoyable and meaningful for students. Many studies found that the problem could be in the way that teachers use to deliver these subjects but not in the content itself. Additionally, students cannot see the benefits of the learnt output coming out of studying several topics in science or mathematics. As educators, we realized that many skills like problem solving, investigation, critical thinking, interpretation, creativity, reasoning, and others cannot be gained easily when the knowledge is separated away of the application in real world. This study tends to give an example of how we can integrate mathematics and science curriculum in a pedagogical knowledge-based framework that enables teachers to show how beneficial and effective is this scientific knowledge in real world application, particularly by using an integrated curriculum. Knowledge and skill from 6th grade in Bahraini public schools were used to design the integrated model.
The Impact of Artificial Intelligence and Blockchain Technology on the Development of Modern Educational Technology
Authors: Chen Yan
Published: July 2022

In order to solve the problem of adding artificial intelligence and blockchain technology to education, the purpose of meeting the needs of combining artificial intelligence and blockchain technology with modern education is to make up for the lack of artificial intelligence in modern education, improve students’ interest in learning, and cultivate high-quality students. Through practice and analysis in a chemistry class in an experimental school, samples were taken from 821 students in the third grade parallel class, and 39 teachers taught students in accordance with their aptitude; finally, from the average score statistics of the first and second inspections, it can be seen that the intelligent classroom teaching of chemistry has a certain effect on improving the average score of students in parallel classes in grade three.
Malicious Code Classification Method Based on Deep Residual Network and Hybrid Attention Mechanism for Edge Security
Authors: Shao Yanli , Lu Yang , Wei Dan , Fang Jinglong , Qin Feiwei , Chen Bin
Published: July 2022

Edge computing is a feasible solution for effectively collecting and processing data in industrial Internet of Things (IIoT) systems, and edge security is an important guarantee for edge computing. Fast and accurate classification of malicious code in the whole lift cycle of edge computing is of great significance, which can effectively prevent malicious code from attacking wireless sensor networks and ensure the stable and secure transmission of data in smart devices. Considering that there is a large amount of code reuse in the same malicious code family, making their visual feature similar, many studies use visualization technology to assist malicious code classification. However, traditional malicious code visual classification schemes have the problems such as single image source, weak ability of deep-level feature extraction, and lack of attention to key image details. Therefore, an innovative malicious code visual classification method based on a deep residual network and hybrid attention mechanism for edge security is proposed in this study. Firstly, the malicious code visualization scheme integrates the bytecode file and assembly file of the malware and converts them into a four-channel RGBA image to fully represent malicious code feature information without increasing the computational complexity. Secondly, a hybrid attention mechanism is introduced into the deep residual network to construct an effective classification model, which extracts image texture features of malicious code from two dimensions of the channel and spatial to improve the classification performance. Finally, the experimental results on the BIG2015 and Malimg datasets show that the proposed scheme is feasible and effective and can be widely applied used in various malicious code classification issues, and the classification accuracy rate is relatively higher than the existing better-performing malicious code classification methods.
[Retracted] Clinical Analysis of Surgical Treatment of Senile Intertrochanteric Fracture Based on Intelligent Knowledge of Health Care
Authors: Bi Weidong , Xu Jianjie , Dong Zhihui , Wang Zhaona , Li Jiebing , Shang Yongwei , Wu Jianzhong
Published: July 2022

In order to explore the clinical application value of intelligent health care knowledge combined with closed reduction intramedullary nail fixation in elderly patients with intertrochanteric fracture of the femur, a retrospective analysis is performed on 80 elderly patients who received intertrochanteric surgery from January 2019 to January 2021. All patients were divided into study group and control group based on intelligent medical knowledge received or not. During the phase of treatment, both the two groups were treated with closed reduction and intramedullary nailing. The control group received conventional knowledge training and rehabilitation before and after the surgery, and the research group received additional intelligent medical knowledge health care. Observations of patients after bed and ground time are compared and the VAS score is used to evaluate the pain degree at 12 h, 24 h, and 48 h after surgery. Besides, the incidence of postoperative complications in the two groups is observed. From the clinical follow‐up results, it is clearly evident that intramedullary nail fixation based on medical care knowledge can effectively improve the hip function and quality of life in patients, reduce postoperative pain, and improve the prognosis of elderly patients with femoral trochanteric fracture.
The Influence of the Relative Timing between Pole and Heel Strike on Lower Limb Loading among Young and Older Naïve Pole Walkers
Authors: Di Bacco Vincenzo E. , Kiriella Jeevaka B. , Gage William H.
Published: July 2022

Current research is unclear with respect to whether pole walking (PW) reduces lower limb loading when compared to regular walking (RW). Contradictory findings in the literature may be related to the relative timing between pole and foot contact events, which were examined in the current study among naïve pole walkers. Fourteen young (4 F; 25.3 ± 5.4 years) and 8 older adults (4 F; 68.5 ± 3.2 years) performed PW and RW trials along a force plate embedded walkway at two different visits. The time difference between pole and foot contact during both the onset of ground contact and the peak force application was calculated. Several kinetic measures were calculated for the lower limbs and poles. A significant decrease during PW, compared to RW, was found for foot impulse (2.1%;

p
<
0.01

), peak vertical ground reaction force (vGRF) (3.4%;

p
<
0.01

), rate of loading (5.2%;

p
=
0.02

), and peak push-off vGRF (2.1%;

p
=
0.01

). No difference in pole loading was found between age groups and visits. No significant correlations were found between the relative timing and foot loading measures. Significant low-to-moderate negative correlations were found between peak foot and pole vGRFs (

p
=
0.04

), peak foot vGRF and pole strike impulse (

p
=
0.01

), peak foot vGRF and pole impulse (

p
=
0.02

), and peak foot push-off vGRF and pole impulse (

p
=
0.01

), suggesting that as pole loading increased, foot loading decreased. Findings suggest timing between pole and heel contact may not be related to unloading the lower limbs but may be related to other aspects of pole use since PW reduced lower limb loading.
Optimal Dispatching of New Energy Power Grid with High Penetration Rate under the Background of Big Data
Authors: Zhang Xiaohui , Wang Yanwei
Published: July 2022

After decades of development, electricity has become an important driving force for national economic construction, and countries’ dependence on electricity is also increasing. In order to solve the problems of environmental pollution and nonrenewable resources in the process of traditional energy power generation and further improve the utilization efficiency of electricity, countries have vigorously developed new energy grids. As a rapidly advancing developing country, my country has a huge demand for electricity. In addition, in recent years, my country’s new energy power generation technology has advanced by leaps and bounds, and it has become an extremely important source of electricity, which is necessary. The purpose of this study is to improve the power grid dispatching and facilitate the people through the understanding of new energy sources with high penetration rate. This paper mainly uses the experimental method, the comparison method, and the investigation method and uses the big data technology to analyze the use of new energy and the optimal dispatch of the new energy grid. The experimental data show that the load changes in each time period are within 1. Through the continuous testing and optimization of the objective function, the dispatching of the high-penetration new energy grid has initially achieved scientific overall planning. The development of this research will help to realize the optimal configuration between traditional energy power generation and new energy power generation and realize the sustainable development of new energy power generation while reducing the loss of grid connection.
Applicability of the Time Fractional Derivative Model on Fickian and Non-Fickian Transport in the Single Fracture: An Experimental Investigation
Authors: Zhang Haoming , Qian Jiazhong , Liu Yong , Xu Yi , Sun Hongguang , Chen Xuequn , Li Fulin
Published: July 2022

The understanding of solute transport in rock fractures is of great importance in many engineering fields. In this study, two groups of experiments on artificial and natural single fractures with different fracture apertures and roughness were conducted to investigate the changes of solute transport regimes. The time fractional advection–dispersion equation (tFADE) as a promising model was applied to describe the anomalous transport. The performance of the classical advection-dispersion equation (ADE) and tFADE was compared according to the fitting precision of breakthrough curves (BTCs). The responses of the fitting parameters in the tFADE to the experimental conditions were also discussed. The results indicated that the non-Fickian transport more likely occurred in the short distance transport, and the larger Peclet number (

Pe

) led to the increase of the exponent of the power-law function in the phase of concentration decline. The tFADE was superior to ADE in capturing the non-Fickian transport especially the tailing behavior. The fractional order of time

α

in the tFADE was the key parameter to describe the anomalous transport process, and its responding mechanisms of were revealed: the best-fit

α

decreased with the increase of flow velocity and the decrease of the fracture aperture. The roughness of the single fracture which leads to a complex flow field had a significant effect on the best-fit

α

. The findings of this study can help for better understanding the effectiveness and physical significance of the tFADE.
Quality Analysis of Railroad Train Shunting Operation Plan Using the Intelligent Body Model
Authors: Yu Tao
Published: July 2022

Shunting work is an important component part of railway transport production and is an important link in realizing the train marshalling plan and the train operation map, accelerating the rotation of vehicles, and completing the task of transport production. With the present, the gradual construction of passenger dedicated lines and high-speed train operation bring a new dawn to railroad transportation on the one hand, but on the other hand, high-speed train operation makes the process of train operation more complicated, and the safety hazards and uncontrollable factors of trains are higher than before. Compared with existing lines, passenger dedicated lines put forward higher requirements on the performance of train operation and dispatching system, requiring better real-time, intelligence, and interactive response characteristics of the train operation and dispatching system. The construction of passenger dedicated lines and the increase in train operation speed have put forward higher requirements for safe, on-time, and high-efficiency train operation. The train operation scheduling system is one of the cores of intelligent railroad transportation system, which is the guarantee of safe and on-time train operation. This requires the search for new control strategies to meet the requirements of high-speed train operation and multiple objectives of safety, punctuality, and comfort. Train operation scheduling is a typical distributed system. At present, there are still problems in the safety of railway shunting operations, such as disconnection in management and implementation, failure to revise some rules and regulations, frequent occurrence of obstacles in equipment and facilities, and substandard quality of operators. Therefore, it is necessary to make a systematic analysis of the current situation of railway shunting safety and propose countermeasures and measures. By studying the structure of intelligent body and multi-intelligent body theory, it decomposes the influencing factors of railroad shunting operation, designs the intelligent body model of each element, and applies it in train shunting operation to improve the quality of railroad shunting operation.
Active Learning Music Genre Classification Based on Support Vector Machine
Authors: Deng Guanghui , Ko Young Chun
Published: July 2022

The improved SVM (support vector machine) offers an active training method that provides users with the most informative sample through multiple iterations and adds it to the training package, which can significantly reduce the cost of manually labeling samples. To evaluate the classifier’s performance, 801 music samples were tested for five music types (Dance, Lyric, Jazz, Folk, and Rock). The effectiveness of the proposed SVM active training method was confirmed by two things: the convergence speed and the classification accuracy, and the number of samples to be labeled with the same accuracy. And the classification accuracy was 81%. At the expense of a little precision, both SVM active training methods drastically reduce the number of labels to be trained, and the method proposed in this paper works better. At the same time, the smaller the value, the fewer the labels that need to be labeled. This is because increasing the number of iterations allows the classifier to select the most appropriate sampling points, while the larger the set value, the smaller the number of iterations. So you can choose between the two depending on the actual situation.