bluuebunny/crossref_metadata_2025 huggingface dataset:
Building a practice-based research network for healthcare integration: a protocol paper for a mixed-method project
Authors: Peters Sanne , Chakraborty Samantha Paubrey , Barton Christopher , Sturgiss Elizabeth Ann , Mazza Danielle , De Leon - Santiago Maria , Staunton-Smith Timothy , Russell Grant
Published: June 2022

Introduction

Practice-based research networks (PBRNs) are sustained collaborations between healthcare professionals, researchers and members of the community that develop, conduct and report on research relevant to local needs. While PBRNs have traditionally been focused towards primary care practices and their patients, there has been increasing interest in how they may help facilitate healthcare integration. Yet, little is known on the ways in which PBRNs can best integrate with the broader healthcare system, in particular Advanced Health Research and Translation Centres. The overall project aim is to build a sustainable collaboration between a PBRN and an Advanced Health Research and Translation Centre to generate a research platform suitable for planning, undertaking and translating research to improve care across the healthcare continuum.

Methods and analysis

We will use a developmental evaluation design. Our iterative approach will be informed by a programme logic model and consists of: preparation work (pre-implementation assessment, literature review, community and stakeholder engagement), adaptation and building for a sustainable collaboration (strategy for recruitment and sustainment of members) and planning for network action (designing and implementing priority initiatives, monitoring and follow-up).

Ethics and dissemination

This project was approved by the Monash Health ethics committee (ERM Reference Number: 76281; Monash Health Ref: RES-21-0000-392L) and the Monash University Human Research ethics committee (Reference Number: 29786). Dissemination will take place via various channels, including relevant national and international committees and conferences, peer-reviewed journals and social media. Continuous dissemination to and communication with all participants in this project as well as other relevant stakeholders will help strengthen and sustain the network.
Identification of social innovation in health criteria in Latin America
Authors: Duque-Paz Luisa Fernanda , Castro-Arroyave Diana
Published: June 2022

Objectives

Understanding the Latin American Social Innovation in Health (SIH) approach requires a process of typifying and identifying main criteria of the approach based on the employed practices of different health initiatives implemented throughout the region. This article presents a descriptive analysis of the main criteria of SIH.

Design

To identify the theoretical and methodological developments of SIH between the years 2013 and 2018, a scoping review was conducted using a mixed approach. 80 texts in English, Spanish and Portuguese were screened through a reflexive analysis process involving intratextual and intertextual reading.

Setting and participants

The documentary research covered journals, books and higher degree theses addressing experiences or theoretical constructs developed in the Latin American region.

Primary and secondary outcome measures

The approaches identified in the studied initiatives were mutually complementary; moreover, based on the typification of the main criteria between approaches and implementation proposals, the convergences and divergences between SIH and other approaches found in the sample were identified. In most cases, the different approaches in the sample are committed to initiatives that include some degree of innovation, improve access to healthcare services and recognise in one way or another a public policy in line with the Sustainable Development Goals (SDGs).

Results

Eighteen characteristic criteria were identified, of which nine particularly differentiate SIH from other approaches conceptually and methodologically. Further work is essential to eliminate the vague delimitation between social and technological aspects of innovation.

Conclusions

The findings indicate that although the SIH concept is in construction, it is advancing down a path of recognition in the region, defining its role as an important field of study on social transformation in health and development.
Assessing use of inhalable nicotine products within complex markets: the dilemma of heated tobacco products
Authors: Miller Connor Richard , Xu Steve S , Smith Danielle M , Sutanto Edward , Goniewicz Maciej Lukasz , Quah Anne C K , Fong Geoffrey T
Published: June 2022

The introduction of electronic inhalable products, such as nicotine vaping products (NVPs) and heated tobacco products (HTPs), has further diversified the nicotine market landscape. This poses unique challenges in measuring self-reported nicotine use behaviours, which have been the hallmark of tobacco surveillance systems. This paper raises concerns of potential measurement error for electronic inhalable product use in surveys due to similarities in product design between NVPs and HTPs, as well as changing trends in cannabis administration. We identify several strategies for addressing this issue (eg, including descriptive preambles in surveys that differentiate product classes from one another; incorporating survey questions that probe beyond an initial question regarding product use). In the absence of comprehensive validation studies, caution is warranted when interpreting survey results that rely on self-reported HTP use.
An Improved Semi-supervised Variational Autoencoder with Gate Mechanism for Text Classification
Authors: Ye Haiming , Zhang Weiwen , Nie Mengna
Published: June 2022

In recent years, semi-supervised learning has been investigated to take full advantages of increasing unlabeled data. Although pretrained deep learning models are successfully adopted on a massive amount of unlabeled data, they may not be applicable in specific domains as the data is limited. In this paper, we propose a model, termed Semi-supervised Variational AutoEncoder (SVAE), which consists of Gated Convolutional Neural Networks (GCNN) as both the encoder and the decoder. Since the canonical VAE suffers from Kullback–Leibler (KL) vanishing problem, we attach a layer named Scalar after Batch Normalization (BN) to scale the output of the BN. We conduct experiments on two domain-specific datasets with a small amount of data. The results show that SVAE outperforms other alternative baselines for language modeling and semi-supervised learning studies. Especially, the results in the language modeling validate the effect of combining BN and Scalar for tackling the KL vanishing problem. Moreover, the visualization of the latent representations verifies the performance of SVAE on less data.
Global Mittag-Leffler Stability and Global Asymptotic ω-Period for Fractional-Order Cohen–Grossberg Neural Networks with Time-Varying Delays
Authors: Jiang Wangdong , Li Zhiying , Zhang Yuehong
Published: June 2022

The dynamic behaviors for fractional-order Cohen–Grossberg neural networks with time-varying delays (FCGNND) are studied in this paper. By introducing the Mittag-Leffler (ML) function, based on properties of fractional calculus, the differential mean-value theorem and Arzela–Ascoli theorem, we give some sufficient theorems to determine the boundedness, global Mittag-Leffler stability (GMLS) and global asymptotical [Formula: see text]-periodicity (GAP) for FCGNND. Finally, a numerical example is given to verify the effectiveness of the theorems.
CMOS Transistors Based First-Order Voltage-Mode All-Pass Filter with Tunable Transformation Possibility
Authors: Gupta Shiv Narain , Chaturvedi Bhartendu , Mohan Jitendra
Published: June 2022

In this paper, a novel complementary metal-oxide semiconductor (CMOS) transistors based first-order voltage-mode all-pass filter is proposed. The filter circuit employs six metal-oxide semiconductor (MOS) transistors and minimal number of passive components, i.e., a resistor and a capacitor. The core of the proposed filter is a CMOS inverting amplifier with unity gain. The proposed circuit exhibits some attractive features such as compact design, high input impedance and ability to provide non-inverting and inverting all-pass responses simultaneously. Additionally, it does not require any kind of passive element matching constraints. Furthermore, by replacing the passive resistor with an active negative channel metal-oxide semiconductor (NMOS) transistor, the proposed filter is enriched with the much-desired feature of tunability. The theoretical behavior is tested and demonstrated by carrying SPICE simulations using TSMC 0.18[Formula: see text][Formula: see text]m level-7 CMOS process parameters.
Parity functors
Authors: Nikonov Igor
Published: June 2022

A parity is a rule to assign labels to the crossings of knot diagrams in a way compatible with the Reidemeister moves. Parity functors can be viewed as parities which provide to each knot diagram its own coefficient group that contains parities of the crossings. In the paper we describe the universal oriented parity functors for free knots and for knots in a fixed surface.
Pseudorapidity window size dependence of multiplicity fluctuations in high-energy collisions with system size and beam energies
Authors: Kumar Ashwini , Devi Gauri , Singh B. K. , Ali Bushra , Ahmad Shakeel
Published: June 2022

An investigation of the critical behavior of strongly interacting quantum chromodynamics (QCD) matter has been performed by analyzing fluctuation observables on event-by-event (ebe) basis measured in high-energy collision experiments. The fluctuation analysis is performed using nuclear interactions at different target sizes and at different colliding beam energies as a function of varying width of pseudorapidity interval. For the sake of comparison, ebe multiplicity fluctuations in hadronic and heavy ion collisions (p–H, p–A and A–B) are studied within the framework of the Lund Monte Carlo-based FRITIOF model. Charged particle multiplicity and the variance of the multiplicity distribution are estimated for the interactions involving different target sizes and beam momenta, i.e., p–H, p–CNO, p–AgBr at 200 A GeV/c and [Formula: see text]O–AgBr collisions at 14.6 A, 60 A and 200 A GeV/c. Further, multiplicity fluctuations are quantified in terms of intensive quantity, the scaled variances [Formula: see text] and the strongly intensive quantity [Formula: see text] derived from the charged particle multiplicity and the width of the multiplicity distribution. Strongly intensive quantity [Formula: see text] is a quantity of great significance to extract information about short- and long-range multiplicity correlations. Furthermore, the collision centrality and centrality bin width-dependent behavior of the multiplicity fluctuation have been examined in the framework of Lund Monte Carlo-based FRITIOF model. Results based on the fluctuation analysis carried out in this study are interpreted in terms of dynamics of collision process and the possibility of related QCD phase transition.
AVERAGE TRAPPING TIME OF HONEYPOTS ON WEIGHTED RANDOM FRACTAL NETWORKS
Authors: HUANG YUKE , ZENG CHENG , ZHANG HANXIONG , XUE YUMEI
Published: June 2022

This paper studies the average trapping time of honeypots on weighted random fractal networks. We introduce three parameters: the node-weight factor [Formula: see text], the edge-weight factor [Formula: see text] and the connecting probability [Formula: see text], making our model closer to real networks. We analyze the movements of the attacker on the network, and get the explicit and asymptotic expressions of the average trapping time for different ranges of parameters.
On the characterization of constant functions through nonlocal functionals
Authors: Gobbino Massimo , Picenni Nicola
Published: June 2022

We address a classical open question by H. Brezis and R. Ignat concerning the characterization of constant functions through double integrals that involve difference quotients.

Our first result is a counterexample to the question in its full generality. This counterexample requires the construction of a function whose difference quotients avoid a sequence of intervals with endpoints that diverge to infinity. Our second result is a positive answer to the question when restricted either to functions that are bounded and approximately differentiable almost everywhere, or to functions with bounded variation.

We also present some related open problems that are motivated by our positive and negative results.
On the Steiner property for planar minimizing clusters. The isotropic case
Authors: Franceschi Valentina , Pratelli Aldo , Stefani Giorgio
Published: June 2022

We consider the isoperimetric problem for clusters in the plane with a double density, that is, perimeter and volume depend on two weights. In this paper, we consider the isotropic case, in the parallel paper [V. Franceschi, A. Pratelli and G. Stefani, On the Steiner property for planar minimizing clusters. The anisotropic case, preprint (2020)] the anisotropic case is studied. Here we prove that, in a wide generality, minimal clusters enjoy the “Steiner property”, which means that the boundaries are made by [Formula: see text] regular arcs, meeting in finitely many triple points with the [Formula: see text] property.
Restrained domination polynomial of join and corona of graphs
Authors: Velmurugan S. , Kala R.
Published: June 2022

Let [Formula: see text] be a simple graph of order [Formula: see text]. A set [Formula: see text] is said to be a restrained set if each vertex in [Formula: see text] is adjacent to a vertex in [Formula: see text]. The restrained polynomial of a graph [Formula: see text] is [Formula: see text] where [Formula: see text] is the number of restrained sets of [Formula: see text] of cardinality [Formula: see text]. A set [Formula: see text] is said to be a restrained dominating set if each vertex in [Formula: see text] is adjacent to a vertex in [Formula: see text] and to a vertex in [Formula: see text]. The restrained domination polynomial of a graph [Formula: see text] is defined by [Formula: see text] where [Formula: see text] is the number of restrained dominating sets of [Formula: see text] of cardinality [Formula: see text]. In this paper, we derive restrained domination polynomial of join and corona of any two graphs.
A locally resonant phononic crystal structure with low-frequency broad bandgap
Authors: Chen Chen , Wang Danyang , Lei Jincheng , Liu Zishun
Published: June 2022

The vibration induced by low-frequency elastic wave reduces the working accuracy of precision instruments. The locally resonant phononic crystal provides a feasible measure for low-frequency vibration isolation because of its bandgap characteristics. In this paper, a locally resonant phononic crystal structure with a broad bandgap is proposed, which consists of a periodic phononic crystal plate with double-sided steel stubs coated by rubber layers. Through finite element analysis, it can be found that the proposed structure can produce a bandgap with 355 Hz bandwidth within the range of 0–500 Hz and isolate vibration in the range of bandgap. By analyzing the local resonance modes of the proposed structure, we further propose the equivalent mass–spring model to predict its bandgap range. The predicted bandgap results from equivalent models of the proposed structure agree well with the results from the finite element analysis. These equivalent models provide an effective and simple method for bandgap optimization of the proposed phononic crystal structure.
First Light of the Integral Field Unit of GRIS on the GREGOR Solar Telescope
Authors: Dominguez-Tagle C. , Collados M. , Lopez R. , Cedillo J. J. Vaz , Esteves M. A. , Grassin O. , Vega N. , Mato A. , Quintero J. , Rodriguez H. , Regalado S. , Gonzalez F.
Published: June 2022

An Integral Field Unit (IFU) based on image slicers has been added to the GREGOR Infrared Spectrograph (GRIS). This upgrade to the instrument makes possible 2D spectropolarimetry in the near-infrared by simultaneously recording the full Stokes profiles of spectral lines (in a given spectral interval) at all the points in the field of view (FOV). It provides high-cadence spectropolarimetric observations at the instrument’s high spatial resolution and high polarization sensitivity at the GREGOR solar telescope. The IFU is ideal for observing the polarized spectrum of fast-evolving solar features at high spatial and spectral resolutions. The high observing cadence opens the possibility of time-series observations. The analysis of observations to this level of accuracy is essential for understanding the complex dynamics and interactions of solar plasma and magnetic fields. The image slicer of the IFU has eight slices of width 100[Formula: see text][Formula: see text]m, covering a total FOV of  [Formula: see text]. It was designed and built within the framework of the European projects SOLARNET and GREST, as a prototype for future instruments of the European Solar Telescope (EST) and was integrated into GRIS. After two commissioning campaigns in 2017 and 2018, the IFU was finally installed at the end of September 2018 and offered to all observers who use the telescope.
A Survey on Data-driven COVID-19 and Future Pandemic Management
Authors: Tao Yudong , Yang Chuang , Wang Tianyi , Coltey Erik , Jin Yanxiu , Liu Yinghao , Jiang Renhe , Fan Zipei , Song Xuan , Shibasaki Ryosuke , Chen Shu-Ching , Shyu Mei-Ling , Luis Steven
Published: June 2022

The COVID-19 pandemic has resulted in more than 440 million confirmed cases globally and almost 6 million reported deaths as of March 2022. Consequently, the world experienced grave repercussions to citizens’ lives, health, wellness, and the economy. In responding to such a disastrous global event, countermeasures are often implemented to slow down and limit the virus’s rapid spread. Meanwhile, disaster recovery, mitigation, and preparation measures have been taken to manage the impacts and losses of the ongoing and future pandemics. Data-driven techniques have been successfully applied to many domains and critical applications in recent years. Due to the highly interdisciplinary nature of pandemic management, researchers have proposed and developed data-driven techniques across various domains. However, a systematic and comprehensive survey of data-driven techniques for pandemic management is still missing. In this article, we review existing data analysis and visualization techniques and their applications for COVID-19 and future pandemic management with respect to four phases (namely, Response, Recovery, Mitigation, and Preparation) in disaster management. Data sources utilized in these studies and specific data acquisition and integration techniques for COVID-19 are also summarized. Furthermore, open issues and future directions for data-driven pandemic management are discussed.
New Insights into the Evolution of Massive Stars and Their Effects on Our Understanding of Early Galaxies
Authors: Eldridge Jan J. , Stanway Elizabeth R.
Published: June 2022

The observable characteristics and subsequent evolution of young stellar populations is dominated by their massive stars. As our understanding of those massive stars and the factors affecting their evolution improves, so our interpretation of distant, unresolved stellar systems can also advance. As observations increasingly probe the distant Universe, and the rare low-metallicity starbursts nearby, so the opportunity arises for these two fields to complement one another and leads to an improved conception of both stars and galaxies. Here, we review the current state of the art in modeling of massive star–dominated stellar populations and discuss their applications and implications for interpreting the distant Universe. Our principal findings include the following: ▪ Binary evolutionary pathways must be included to understand the stellar populations in early galaxies. ▪ Observations constraining the extreme ultraviolet spectrum of early galaxies are showing that current models are incomplete. The best current guess is that some form of accretion onto compact remnants is required. ▪ The evolution and fates of very massive stars, on the order of 100 M⊙ and above, may be key to fully understand aspects of early galaxies.
Ownership and Value in Childhood
Authors: Pesowski Madison L. , Nancekivell Shaylene E. , Tasimi Arber , Friedman Ori
Published: June 2022

Ownership and value go together, and understanding both is imperative for children to know how to act in socially appropriate and advantageous ways. This paper reviews how children come to think about ownership and value. We first review how children consider history, labor, and control when inferring whether objects are owned and to whom they belong. We then review how children conceive of ownership rights and how they use ownership to anticipate other people's actions, feelings, and knowledge. With value, we first touch on children's attention to physical features and norms. We then discuss how ownership impacts children's valuations of objects, stemming both from children's own status as owners and from their knowledge of previous ownership. We also review how various kinds of distinctive histories affect children's valuations. Finally, we review children's understanding of how value depends on the market forces of supply and demand.
Binocular Integration in the Primate Primary Visual Cortex
Authors: Maier A. , Cox M.A. , Westerberg J.A. , Dougherty K.
Published: June 2022

Our brains devote substantial resources to creating a singular, coherent view from the two images in our eyes. Both anatomical and functional studies have established that the underlying fusion of monocular signals into a combined binocular response starts within the first synapses downstream from our eyes. Long-standing consensus held that the two eyes’ signals remain largely segregated until they are combined by neurons in the upper layers of the primary visual cortex. However, new experimental data challenge this classic model, suggesting that there are pronounced earlier interactions between the two eyes’ streams of activation. In this article, we review the literature and detail how these findings can be functionally interpreted in context with previously established psychophysical models of binocular vision.
Boosting the Electrochemical Performance of Mn-doped CuCo2O4/CuO Heterostructures for All-Solid-State Asymmetric Battery-type Supercapacitors
Authors: Reddy G. Rajasekhara , Dillip G. R. , Manjunath G. L. , Joo S. W.
Published: June 2022

The introduction of Manganese (Mn) ions (2+ ⇋ 3+ ⇋ 4+) to transition metal oxides proved to be a potential strategy to tailor the redox behavior of these materials for energy storage. We fabricate a lower electronegative element (i.e., Mn) doped copper cobaltite and copper oxide (CuCo2O4/CuO; CCO) heterostructures electrodes through the hydrothermal synthesis route. The ensued electrodes have a more than 2-fold improvement in specific capacity (382.9 C g−1) than the undoped CCO electrode (120.8 C g−1) at 1 A g−1. The all-solid-state asymmetric supercapacitor (ASC) practical device is constructed with higher Mn-doped CCO heterostructures as the positive electrode and activated carbon (AC) as the negative electrode. With a voltage window of 1.5 V, the fabricated ASC device has a high specific energy of 52.6 Wh kg−1 and specific power of 774.3 W kg−1. The long-term cyclic stability of 92% capacity retention after 5000 cycles at the current density of 4 A g−1. Additionally, two ASC devices are series-connected that can power up a red light-emitting diode (LED) display for more than 150 s, demonstrating the device’s efficient power delivery.
Multistate Resistive Switching with Self-Rectifying Behavior and Synaptic Characteristics in a Solution-processed ZnO/PTAA Bilayer Memristor
Authors: Khan Sobia Ali , Rahmani Mehr Khalid , Khan Muhammad Umair , Kim Jungmin , Bae Jinho , Kang Moon Hee
Published: June 2022

The progress of artificial synaptic devices is vital to the realization of the consciousness of effectual bioinspired neuromorphic computing systems. In this study, we fabricated an ITO/ZnO/PTAA/Ag artificial synaptic memristor based on a low-cost solution process. The fabricated device exhibited uniform gradual bipolar resistive switching with excellent endurance and self-rectifying behavior owing to the bilayer heterojunction structure of ZnO/PTAA. The growth of the conducting filament can be efficiently controlled by modulating the current compliance and voltage during the SET process. Modification of conductance states was also observed by simulations to stimuli, which are essential for synaptic function in neuromorphic computing. Various pulse measurements were performed to mimic synaptic behaviors, including long-term potentiation, long-term depression, spike-rate-dependent plasticity, paired-pulse facilitation, and post-tetanic potentiation. Moreover, we reveal that the real device shows an approximately similar pattern recognition rate as the ideal device owing to a more uniform conductance update.
Insulin-like growth factor-I biocompartmentalization across blood, interstitial fluid and muscle, before and after 3 months of chronic resistance exercise
Authors: Sterczala Adam J. , Pierce Joseph R. , Barnes Brian R. , Urso Maria L. , Matheny Ronald W. , Scofield Dennis E. , Flanagan Shawn D. , Maresh Carl M. , Zambraski Edward J. , Kraemer William J. , Nindl Bradley C.
Published: June 2022

In the first investigation to assess resistance training’s effects on the IGF-I system in serum, interstitial fluid, and skeletal muscle, training decreased basal circulating and interstitial IGF-I but did not alter basal intramuscular IGF-I protein activity. Posttraining, acute exercise-induced interstitial IGF-I increases were strongly correlated with intramuscular IGF-I expression and signaling. These findings highlight the importance of multibiocompartment measurement when analyzing IGF-I and suggest that IGF-I’s role in hypertrophic adaptations is locally mediated.
Evaluation of Dynamic Foraminal Stenosis with Positional MRI in Patients with C6 Radiculopathy‐Mimicking Pain: A Prospective Radiologic Cohort Study
Authors: Kaya Ozcan , Sariyilmaz Kerim , Tutpinar Yildiray , Cakmak Mehmet Fevzi , Cakir Mehmet Semih , Ozkunt Okan
Published: June 2022

Objective. Patients with a C6 radiculopathy‐mimicking complaint are always in the gray zone if the diagnosis is not clear. The aim of the study is to make the diagnosis clear if the neck and shoulder pain is caused by a dynamic stenosis of the neural foramen at the C5‐C6 level. Methods. Patients with a C6 radiculopathy‐mimicking complaint were included in the study. Patients had a cervical spine magnetic resonance imaging (MRI) at the normal limits, or a minimal protrusion at the C5‐C6 level underwent a dynamic MRI procedure. We measured the foraminal area and spinal cord diameter (SCD) at the C5‐C6 level by using the PACS system ROI irregular are determination integral embedded to PACS. Inter‐ and intraobserver reliability of measurements was evaluated. Results were analyzed statistically, and a p value< 0.05 was accepted as statistically meaningful. Results. A total of 23 patients between January 2019 and June 2019 were included in the study. There were 10 men and 13 women, and the mean age was 41.3 (range 33‐53). Foraminal area decrease at C5‐C6 in extension and increase in flexion when compared with the neutral position was statistically significant (p < 0.001). Foraminal area changes between the complaint side and the opposite side was not statistically different (p > 0.05). Interobserver and intraobserver reliability of measurements were classified as in almost perfect agreement. Conclusions. Our present work presented dynamic and positional foraminal changes in MRI with radiculopathy‐mimicking patients. Soever, we did not find a difference between the clinical complaint side and the opposite side in radiculopathy‐mimicking patients. Cervical radiculopathy pain should not be attributed only to foraminal sizes. PACS embedded irregular area measurement integral allows the easy measure of a big number of patients without additional set‐up and digital work requirements.
Internet of Things-Based Crop Classification Model Using Deep Learning for Indirect Solar Drying
Authors: Sharma Brij Bhushan , Gupta Gaurav , Vaidya Pankaj , Basheer Shakila , Memon Fida Hussain , Thakur R. N.
Published: June 2022

The energy which is obtained from the sun in the form of light and heat is known as solar energy. Nowadays, technology is focused on utilization of this rich resource of energy. So many ways to harness and utilize this source of energy have already been introduced; solar drying of crops is one of its applications. Drying of crops is required to improve the quality of the crops as well as to protect crops from so many unwanted issues like moisture, pest/insect attacks, and birds/animals. Traditional methods are still used to dry the crops; drying of crops is required to preserving food product for long time. In this paper, we studied about the working mechanism of indirect solar dryers and introduced IoT-based system to control and monitor the temperature of the solar dryer as per the requirement of specific crop. To achieve the automation accurately and precisely deep learning method is also used to set the required temperature according to the requirement of the specific crop.
The Role of Medical Big Data and Artificial Intelligence in the Diagnosis of Knee Osteoarthritis with Cardiovascular and Cerebrovascular Diseases
Authors: Huan Xin , Wan Pan , Zhou Yonghuan
Published: June 2022

In this Internet era, people use more and more network data, and hospital diagnosis is even more important. The improvement of medical standards has brought about the rapid growth of medical data. How to analyze related symptoms from a large amount of data performing an analysis and accurately diagnosing its symptoms has become one of the difficult problems. This article is aimed at studying the role of medical huge amount of data and artificial intelligence in the diagnosis of knee osteoarthritis combined with cardiovascular and cerebrovascular diseases. To this end, this article proposes to improve data mining methods and proposes a comprehensive analysis of patient data in the field of artificial intelligence for intelligent diagnosis and treatment so that doctors can make accurate judgments about the symptoms of patients and designed related experiments to explore its specific effects. The experimental results in this article show that the improved data mining speed has increased by 17%, the data integrity has increased by 31%, and the proportion of valid data has also increased by 23%, which is very effective for clinical diagnosis.
A Personalized Recommendation Algorithm for Political and Ideological Courses in Colleges Using Multiple Interests of Users
Authors: Luo Li
Published: June 2022

Due to the development of social economy and the continuous growth of science and technology, the historical progress of the information age has opened up. With its mass audience, vast range, and powerful guiding technology, streaming media technology has significantly reduced the time and gap among people in various parts of the world, particularly in the field of education. However, political and ideological education classes in colleges are not sufficiently focused, and as a result, personalized recommendations and analysis of users’ various interests are not possible because of low precision, low user coverage, excessive recommendation time, and poor optimal solution capability. To fill these issues, this study provides a personalized recommendation system for political and ideological courses in colleges based on the interests of multiple users. This paper developed a framework for mining knowledge points in political and ideological course, mined knowledge points in a course using association rules, and calculated the weight of knowledge points using hierarchical tree theory. Apart from these, this paper established the user interest model to obtain the learning characteristics of learners. The experimental results show that the proposed algorithm has higher recommendation accuracy, higher user coverage, short recommendation time, and good optimization ability, which proved that it has a high application value. Based on this study, it can be argued that in modern era of education, the proposed recommendation system of political and ideological education has significant comparative importance for promoting political and ideological education in colleges.
Cooperative Hunting Strategy with a Superior Evader Based on Differential Game
Authors: Wang Chunyan , Shi Weixiang , Liang Li
Published: June 2022

This paper considers a pursuit‐evasion game with multiple pursuers and a superior evader. A novel cooperative pursuit strategy is proposed to capture a faster evader while maintaining a formation. First, the initial states including position distribution and the minimum required number of pursuers for ensuring capture are obtained based on the idea of Apollonius circle. Second, a cost function is designed, and the cooperative hunting strategy is developed using the distances between the centers of multiple Apollonius circles. Finally, numerical simulation and UAVs flying tests are provided to demonstrate the effectiveness of the proposed cooperative hunting strategy.
Effect of High-Pressure Treatment on the Quality of a Hericium erinaceus: Millet Composite Beverage
Authors: Zhou Zhiguo , Shang Xiaolan , Wang Zixin , Sun Chengxi , Zhang Lin
Published: June 2022

Hericiumerinaceus-millet (HM) composite beverage was prepared by mixing Hericium erinaceus juice and millet juice and then subjected to high-pressure processing (HPP) of 300 MPa and 600 MPa at room temperature and thermal processing (TP) of 100°C for 3 min. The differences in pH, total soluble solids, amino acid nitrogen content, total colony numbers, sensory scores, and shelf life of HPP-treated and TP-treated samples stored at 4°C, 27°C, and 37°C for 80 days and the differences in volatile substances stored at 4°C and 27°C for 30 days were studied. The results showed that there was no significant difference in total soluble solids, amino acid nitrogen, and pH when comparing HPP- and TP-treated HM beverages. The order of HM beverages’ shelf life following different treatments was as follows: TP-treated >600 MPa HPP-treated >300 MPa HPP-treated. When stored at 4°C, the shelf life of the three treatments was 63, 52, and 39 days, respectively. Compared with TP-treated beverages, HPP-treated beverages better retained their ester flavor compounds, especially ethyl acetate. Moreover, the main volatile compounds in TP-treated beverages changed more during storage than those in HPP-treated beverages. Overall, HPP-treated beverages had advantages in terms of flavor over TP-treated beverages.
Sharing of Teaching Resources for English Majors Based on Ubiquitous Learning Resource Sharing Platform and Neural Network
Authors: Zhang Lijuan
Published: June 2022

Teachers in traditional English education devote a great deal of time and effort to developing excellent English teaching courseware and other teaching materials. However, because the network’s powerful sharing capability was not fully utilized, poor resource sharing hampered the school’s overall teaching efficiency. The goal of this paper is to investigate how to use a ubiquitous learning resource sharing platform and a neural network to analyze the method of English major education resource sharing. Because the BP neural network algorithm has better classification and prediction functions, it was proposed because it can classify and predict information in the sharing of teaching resources for English majors. This allows for seamless sharing of teaching materials. According to the findings of this study, there were 562.13 million people learning English in China in 2015, accounting for 37% of the population. By 2018, 945.61 million people were learning English, accounting for 85 percent of the population. Almost every student is learning English, demonstrating the language’s importance. As a result, the importance of English instruction is clear, and the sharing of teaching resources should be prioritized.
Designing the Modern Dual-Engine Two-Speed Smart Hybrid Electric Drive Powertrain
Authors: Pattanaik Balachandra , Alagirisamy Mukil , Karthikeyan V. , Nallamothu Ramesh Babu , Samuel G. Giftson
Published: June 2022

While potential for battery-powered electric vehicles (BEVs) is increasing as the need to minimise greenhouse gas pollution and the utilization of energy production, the restricted driving range and the uninviting market price constitute BEV obstacles to reliable assessment as a conventional car. This paper suggests a double-motor multispeed direct-drive BEV drivetrain to improve average engine running performance in everyday travelling whilst raising any production or control sophistication, effectively saving minimal battery resources and production costs. The characteristics of the proposed drivetrain are first defined through quantitative and visual measurements, which divide the conventional one-engine propulsion to two with different permanent gears to optimise engine performance. Centred on dynamic powertrain modelling in Simulink, the economic change strategy and circulatory system consisting transfer control were planned and checked. Based on the simulation performance, it is stated that substantial increases in energy quality can be accomplished. Thanks to the optimised torque transfer control technique, the vehicle’s incredibly low pull is registered during the shifting phase. Finally, it can be inferred that the suggested dual-motor drivetrain is better than the conventional single-motor equivalent in terms of fuel efficiency, driving range, and expense. There is substantial increase in total machine running areas of affordable to solitary machine performance and megacity driving ages, similar to WLTC, FTP-75, and JP 10-15, with 5 to 8 percentage performance enhancement being achieved.
Successful Treatment with Antibiotics Alone for Infant Rib Osteomyelitis
Authors: Matsumoto Yasuaki , Shimozawa Katsuyoshi , Yamanaka Junko , Atsumi Yukari , Ota Tomomi , Mochizuki Shinji , Shichino Hiroyuki
Published: June 2022

Pediatric rib osteomyelitis is a rare disease occurring predominantly in the neonatal period and early childhood and accounting for about 1% of all pediatric osteomyelitis. Compared to osteomyelitis in other parts of the body, pediatric rib osteomyelitis shows few localized findings (such as redness and swelling) and often an indolent lesion as well either of which may delay diagnosis and thus make treatment more difficult. A previously healthy one-year-old girl came to our department with a chief complaint of fever lasting for three days. She was admitted to our department to investigate her fever. At the time of admission, radiographs showed decreased permeability in the left lung field; so, we started antimicrobial therapy on the assumption of pneumonia. On the second day of admission, methicillin-susceptible Staphylococcus aureus was detected in the blood culture. A further, more detailed physical examination revealed some slight left anterior chest swelling. We performed a contrast-enhanced CT scan and an MRI and diagnosed her with rib osteomyelitis complicated with a chest wall abscess. She was given intravenous cefazolin for two weeks, switched to oral cephalexin for four weeks, and then recovered completely. She was treated without surgical intervention, having showed a good response to antimicrobial therapy. Osteomyelitis of the ribs in children is reported to be more common in the lower ribs and to occur more frequently in infants. In many cases, the earliest symptoms are nonspecific, so careful examination to detect any subtle abnormalities—such as swelling or mass—is of key importance for early diagnosis in infants. Regarding treatment, most cases of hematogenous osteomyelitis resolve with antimicrobial therapy alone—although surgical intervention may be required in cases of poor response to antimicrobial therapy. Therefore, early diagnosis of rib osteomyelitis through careful physical examination may reduce the chances of requiring surgical intervention.
Restaurant Interior Design under Digital Image Processing Based on Visual Sensing Technology
Authors: Wan Yan , Cui Can , Wang Guanqiang
Published: June 2022

With the development of the social economy, people are paying more and more attention to decorative effects and the comfort and individual characteristics of decoration. To meet the increasingly high requirements of customers, many restaurants have begun to focus on the personalization of the dining environment, which is comfortable to build and focuses on the spiritual satisfaction and experience of customers during the dining process. In this study, a comprehensive analysis of digital image processing technology is performed to implement an automatic illumination system with improved performance for the restaurant interior design and embed the restaurant interior design with intelligence. The convolutional neural network (CNN) is employed in the automatic illumination system to develop the human body recognition model. After a test of its recognition accuracy, the parameters of CNN are optimized, and high recognition accuracy of 0.97 is achieved. Compared with other models, the process of training the designed model implemented in this study can finish in 40 minutes, and the performance has been well optimized. Moreover, the processing function of the model is also able to resist the interference of other external objects. The excellent automatic illuminating system can greatly improve the atmosphere as well as the service level of the restaurant at night, which can promote the modernization of the restaurant and give certain reference significance to the reform and advancement of the decoration industry.
Acute Pancreatitis in Pregnancy: A Ten-Year Noninterventional, Retrospective Cohort Experience
Authors: Haiyan Zhao , Na Peng , Jialin He , Qingjian Lv , Jianying Bai , Xiumei Bai
Published: June 2022

Background. The study is aimed at evaluating the clinical attributes, types, and risk factors associated with poor outcomes in women with acute pancreatitis (AP) during pregnancy. Methods. From 2011 to 2020, 45 antenatal mothers with AP were included in this noninterventional, retrospective study. The correlation between etiology of AP, its severity, biochemical parameters, length of stay, and treatment was analyzed. Based on the presence of organ failure and systemic complications, the severity of AP was classified according to the revised Atlantic criteria. Results. In total, 19 (42.2%), 15 (33.3%), and 11 (24.2%) patients had mild AP (MAP), moderately severe AP (MSAP), and severe AP (SAP), respectively. The major cause of AP in these patients was hypertriglyceridemia (26.6%), while only 2 (4.44%) suffered from biliary pancreatitis. The median length of stay at hospital was significantly longer in patients with SAP (

P
=
0.034

), and these patients had significantly higher triglycerides and total cholesterol levels when compared to MAP and MSAP. It was observed that levels of liver function enzymes such as alanine aminotransferase serum levels and aspartate aminotransferase serum levels were significantly higher in patients who stayed in hospital for >13 days. The presence of hypertriglyceridemia significantly increased the duration of stay (>13 days,

P
=
0.04

) and induced SAP (

P
=
0.001

). Majority of patients with SAP received blood purification than those with MAP and MSAP (

P
<
0.001

). Conclusion. Hypertriglyceridemia was associated with AP during pregnancy in our study. Early diagnosis of AP and assessment of its severity are very important for the general management of this disease.
Network Intrusion Detection Method Based on Improved CNN in Internet of Things Environment
Authors: Wang Yulin , Wang Jinheng , Jin Honglin
Published: June 2022

In view of most existing intrusion detection technologies that cannot meet the actual needs of the Internet of Things and facing the problems of poor detection effect of complex network intrusion methods, a network intrusion detection method based on deep learning algorithm in the environment of the Internet of Things is proposed. Firstly, the Internet of Things intrusion detection model is constructed based on edge computing, in which the concept of gated convolution is introduced to improve the convolution neural network model. Data passes through convolution layer, pooling, dropout, full connection, and Softmax function to realize multiclassification. Finally, the Focal Loss function is used to modulate the training ratio of positive and negative samples to solve the problem of uneven distribution of sample data. The proposed algorithm is demonstrated experimentally based on KDD99 data set. The results show that the accuracy, precision, recall, and F1 values are 92.14%, 95.97%, 90.89%, and 90.03%, which are better than other comparison algorithms. The proposed method can better meet the needs of Internet of Things intrusion detection.
Embedded Estimation Sequential Bayes Parameter Inference for the Ricker Dynamical System
Authors: Rehman Muhammad Javvad Ur , Zafar Raheel , Dilpazir Hammad , Sohail Muhammad Farhan , Khan Muhammad Arslan , Jahan Rifat
Published: June 2022

The dynamical systems are comprised of two components that change over time: the state space and the observation models. This study examines parameter inference in dynamical systems from the perspective of Bayesian inference. Inference on unknown parameters in nonlinear and non-Gaussian dynamical systems is challenging because the posterior densities corresponding to the unknown parameters do not have traceable formulations. Such a system is represented by the Ricker model, which is a traditional discrete population model in ecology and epidemiology that is used in many fields. This study, which deals with parameter inference, also known as parameter learning, is the central objective of this study. A sequential embedded estimation technique is proposed to estimate the posterior density and obtain parameter inference. The resulting algorithm is called the Augmented Sequential Markov Chain Monte Carlo (ASMCMC) procedure. Experiments are performed via simulation to illustrate the performance of the ASMCMC algorithm for observations from the Ricker dynamical system.
Evaluation of the Effect of Refined Nursing Intervention on Coronary CT Imaging Microscopy
Authors: Qian Tao
Published: June 2022

The aim is to study the benefits of using advanced medical services for coronary CT angiography. From August 2019 to August 2020, 50 patients who underwent CT angiography were selected and divided into control groups and study groups, with 25 patients in each group. The monitoring team provides basic support, and the training team provides maximum support. Experimental results showed that the positive microscopic image of the study group after the intervention was better than that of the control group, and the stress score was lower than that of the control group (

P
<
0.05

 s and

30.73
±
9.57

 min) and are short (

58.32
±
13.15

seconds and

53.17
±
11.84

minutes) between control groups, with significant differences. The significance is (

P
<
0.05

. Patient care is relevant to patients with coronary CT angiography, which has been shown to improve heart rate, reduce stress, improve microscopic imaging, and provide relevant liver function tests. It is recommended to promote the show.