bluuebunny/crossref_metadata_2025 huggingface dataset:
Project Cost Accounting Based on Internet of Things Technology
Authors: Jiang Yi
Published: February 2022

In order to improve the effect of engineering cost accounting, this paper applies the Internet of Things technology to the engineering cost accounting system, and combines the chaotic data processing method with the Internet of Things technology. Moreover, this paper uses the Internet of Things technology to construct the engineering cost accounting system, uses the Internet of Things technology to collect various data in the real-time process of the project, and builds the engineering cost accounting system based on the actual situation. In addition, this paper combines improved intelligent algorithms to improve system performance to enable the system to collect data, manage data, process data, transmit data, and output data. It can be seen from the research results that the project cost evaluation system constructed in this paper is rated above good, which is higher than the existing project cost evaluation methods. The experimental research shows that the project cost accounting system based on the Internet of Things technology proposed in this paper has a good engineering data processing effect.
Research on Wireless Network Virtualization Positioning Technology Based on Next-Generation Agile IoT Technology
Authors: Liu Baojing , Han Chenye
Published: February 2022

Wireless network virtualization (WNV) is an evolving technology that supports networking for future wireless networks and agile IoT applications that optimize wireless bandwidth, provide network protection, and increase network performance in general. However, the exponential growth and increased demand for IoT have posed considerable scalability problems, interoperability, and heterogeneity across diverse fields from intelligent cities to healthcare, urban computing, and tactile fast internet growth. In this paper, IoT-based WNV (IoT-WNV) technology has been used. The leading technologies that create a scalable and stable network, consistent with many IoT products, for effective wireless virtualization in next-generation agile IoT systems are the networking function virtualization (NFV), mobile edge computing, and software-defined networks (SDNs). The network function virtualization (NFV) feature improves network stability, while the SDN operates, optimizes, and configures network services dynamically, enabling dynamically-based network functionality and interconnectivity. This special problem involves virtualizing IoT system wireless sensor networks to speed up network resource management by analyzing data obtained from devices deployed in various applications. This technological combination will satisfy the demands of modern applications. IoT-WNV aims to improve wireless virtualization for the next-generation network by implementing human-smart technology for load balance, network management, and network security.
Surrogate Modeling with Gaussian Processes for an Inverse Problem in Polymer Dynamics
Authors: Chouhan Pankaj , Shanbhag Sachin
Published: February 2022

When rheological models of polymer blends are used for inverse modeling, they can characterize polymer mixtures from rheological observations. This requires repeated evaluation of potentially expensive rheological models. We explored surrogate models based on Gaussian processes (GP-SM) as a cheaper alternative for describing the rheology of polydisperse binary blends. We used the time-dependent diffusion double reptation (TDD-DR) model as the true model; it takes a 5-dimensional input vector specifying the binary blend as input and yields a function called the relaxation spectrum as output. We used the TDD-DR model to generate training data of different sizes [Formula: see text], via Latin hypercube sampling. The optimal values of the GP-SM hyper-parameters, assuming a separable covariance kernel, were obtained by maximum likelihood estimation. The GP-SM interpolates the training data by design and offers reasonable predictions of relaxation spectra with uncertainty estimates. In general, the accuracy of GP-SMs improves as the size of the training data [Formula: see text] increases, as does the cost for training and prediction. The optimal hyper-parameters were found to be relatively insensitive to [Formula: see text]. Finally, we considered the inverse problem of inferring the structure of the polymer blend from a synthetic dataset generated using the true model. Surprisingly, the solution to the inverse problem obtained using GP-SMs and TDD-DR was qualitatively similar. GP-SMs can be several orders of magnitude cheaper than expensive rheological models, which provides a proof-of-concept validation for using GP-SMs for inverse problems in polymer rheology.
MAIDE: Augmented Reality (AR)-facilitated Mobile System for Onboarding of Internet of Things (IoT) Devices at Ease
Authors: Zhang Huanle , Uddin Mostafa , Hao Fang , Mukherjee Sarit , Mohapatra Prasant
Published: February 2022

Having an efficient onboarding process is a pivotal step to utilize and provision the IoT devices for accessing the network infrastructure. However, the current process to onboard IoT devices is time-consuming and labor-intensive, which makes the process vulnerable to human errors and security risks. In order to have a streamlined onboarding process, we need a mechanism to reliably associate each digital identity with each physical device. We design an onboarding mechanism called
MAIDE
to fill this technical gap.
MAIDE
is an Augmented Reality (AR)-facilitated app that systematically selects multiple measurement locations, calculates measurement time for each location and guides the user through the measurement process. The app also uses an optimized voting-based algorithm to derive the device-to-ID mapping based on measurement data. This method does not require any modification to existing IoT devices or the infrastructure and can be applied to all major wireless protocols such as BLE, and WiFi. Our extensive experiments show that
MAIDE
achieves high device-to-ID mapping accuracy. For example, to distinguish two devices on a ceiling in a typical enterprise environment,
MAIDE
achieves ~95% accuracy by measuring 5 seconds of Received Signal Strength (RSS) data for each measurement location when the devices are 4 feet apart.
Toxic Relationships and Arms-Race Coevolution Revisited
Authors: Bucciarelli G.M. , Alsalek Farid , Kats L.B. , Green D.B. , Shaffer H.B.
Published: February 2022

Toxin evolution in animals is one of the most fascinating and complex subjects of scientific inquiry today. Gaining an understanding of toxins poses a multifaceted challenge given the diverse modes of acquisition, evolutionary adaptations, and abiotic components that affect toxin phenotypes. Here, we highlight some of the main genetic and ecological factors that influence toxin evolution and discuss the role of antagonistic interactions and coevolutionary dynamics in shaping the direction and extent of toxicity and resistance in animals. We focus on toxic Pacific newts (family Salamandridae, genus Taricha) as a system to investigate and better evaluate the widely distributed toxin they possess, tetrodotoxin (TTX), and the hypothesized model of arms-race coevolution with snake predators that is used to explain phenotypic patterns of newt toxicity. Finally, we propose an alternative coevolutionary model that incorporates TTX-producing bacteria and draws from an elicitor–receptor concept to explain TTX evolution and ecology.
Host Genetic Determinants of the Microbiome Across Animals: From Caenorhabditis elegans to Cattle
Authors: Ryu Erica P. , Davenport Emily R.
Published: February 2022

Animals harbor diverse communities of microbes within their gastrointestinal tracts. Phylogenetic relationship, diet, gut morphology, host physiology, and ecology all influence microbiome composition within and between animal clades. Emerging evidence points to host genetics as also playing a role in determining gut microbial composition within species. Here, we discuss recent advances in the study of microbiome heritability across a variety of animal species . Candidate gene and discovery-based studies in humans, mice, Drosophila, Caenorhabditis elegans, cattle, swine, poultry, and baboons reveal trends in the types of microbes that are heritable and the host genes and pathways involved in shaping the microbiome. Heritable gut microbes within a host species tend to be phylogenetically restricted. Host genetic variation in immune- and growth-related genes drives the abundances of these heritable bacteria within the gut. With only a small slice of the metazoan branch of the tree of life explored to date, this is an area rife with opportunities to shed light into the mechanisms governing host–microbe relationships.
Bluetongue Research at a Crossroads: Modern Genomics Tools Can Pave the Way to New Insights
Authors: Kopanke Jennifer , Carpenter Molly , Lee Justin , Reed Kirsten , Rodgers Case , Burton Mollie , Lovett Kierra , Westrich Joseph A. , McNulty Erin , McDermott Emily , Barbera Carly , Cavany Sean , Rohr Jason R. , Perkins T. Alex , Mathiason Candace K. , Stenglein Mark , Mayo Christie
Published: February 2022

Bluetongue virus (BTV) is an arthropod-borne, segmented double-stranded RNA virus that can cause severe disease in both wild and domestic ruminants. BTV evolves via several key mechanisms, including the accumulation of mutations over time and the reassortment of genome segments.Additionally, BTV must maintain fitness in two disparate hosts, the insect vector and the ruminant. The specific features of viral adaptation in each host that permit host-switching are poorly characterized. Limited field studies and experimental work have alluded to the presence of these phenomena at work, but our understanding of the factors that drive or constrain BTV's genetic diversification remains incomplete. Current research leveraging novel approaches and whole genome sequencing applications promises to improve our understanding of BTV's evolution, ultimately contributing to the development of better predictive models and management strategies to reduce future impacts of bluetongue epizootics.
Histone Variants in the Specialization of Plant Chromatin
Authors: Foroozani Maryam , Holder Dylan H. , Deal Roger B.
Published: February 2022

The basic unit of chromatin, the nucleosome, is an octamer of four core histone proteins (H2A, H2B, H3, and H4) and serves as a fundamental regulatory unit in all DNA-templated processes. The majority of nucleosome assembly occurs during DNA replication when these core histones are produced en masse to accommodate the nascent genome. In addition, there are a number of nonallelic sequence variants of H2A and H3 in particular, known as histone variants, that can be incorporated into nucleosomes in a targeted and replication-independent manner. By virtue of their sequence divergence from the replication-coupled histones, these histone variants can impart unique properties onto the nucleosomes they occupy and thereby influence transcription and epigenetic states, DNA repair, chromosome segregation, and other nuclear processes in ways that profoundly affect plant biology. In this review, we discuss the evolutionary origins of these variants in plants, their known roles in chromatin, and their impacts on plant development and stress responses. We focus on the individual and combined roles of histone variants in transcriptional regulation within euchromatic and heterochromatic genome regions. Finally, we highlight gaps in our understanding of plant variants at the molecular, cellular, and organismal levels, and we propose new directions for study in the field of plant histone variants.
Immigrant Organizations
Authors: Bloemraad Irene , Chaudhary Ali R. , Gleeson Shannon
Published: February 2022

We call for incorporating organizations into migration scholarship, and for considering immigrants in organizational research. By centering immigrant organizations (IOs) as a unit of analysis, migration scholars can reconsider whether and how IOs affect well-being, integration, political voice, identities, globalization, and development. Migration scholars must learn from scholars of organizations, but organization scholars must in turn question assumptions of nativity and citizenship in their research. Doing so illuminates the unique challenges—and, at times, opportunities—faced by IOs, especially regarding inequities tied to legal status and stigmatization. We further argue that cross-national and transnational analyses of IOs help unpack organizational embeddedness—that is, the ways in which contexts at the local, national, binational, and geopolitical levels generate opportunities and constraints. Studying IOs raises critical questions of civic inequality and organizational stigma but also highlights IOs’ potential to give voice to and effect positive change for migrant communities.
The Role of Doubt in Conceiving Research: Reflections from a Career Shaped by a Dissertation
Authors: Presser Stanley
Published: February 2022

The doctoral dissertation often shapes the career that follows it, influencing both opportunities encountered and research conducted. This article describes the ways this has been true for me and then argues that, given the dissertation's importance, graduate programs do not focus sufficiently on strategies for conceiving research. As a result, many students flounder at the dissertation proposal stage. Drawing on the role of doubt in my career and in science more generally, I propose changes in doctoral programs to reduce the problem.
The Effects of Perceived Stigma on the Concealment of Disease and Satisfaction with Life in Patients with Epilepsy: An Example in Eastern Turkey
Authors: Turan Gülcan Bahçecioğlu , Özer Zülfünaz , Özden Beyan
Published: February 2022

Background. Stigma and exclusion are common features of epilepsy in both developed and developing countries, and they cause a significant burden associated with the condition. At the same time, although it varies from country to country depending on cultural differences and economic conditions, having epilepsy causes significant social consequences. Objective. This study was conducted to examine the effects of perceived stigma on the concealment of disease and satisfaction with life in patients with epilepsy living in the east of Turkey. Methods. This cross-sectional and descriptive study was carried out with 150 patients who met the study criteria and who agreed to participate in the study between March and July 2021 in a university hospital in Elazığ, east of Turkey. The data were collected using a personal information form, an Epilepsy Stigma Scale (ESS), a Concealment of Epilepsy Scale (CES), and a Satisfaction with Life Scale (SWLS). Results. The total mean ESS score of the patients was 40.7 ± 9.04, the total CES mean score was 57.19 ± 12.57, and the total SWLS mean score was 6.68 ± 2.86. When the regression coefficients were examined, it was found that the ESS variable had a positive and significant effect on the CES, while the ESS and the CES had a negative and significant effect on satisfaction with life (

p
<
0.001

). Conclusion. It was found that the patients had high levels of perceived stigma and concealment of epilepsy and low satisfaction with life levels. It was also found that the patients concealed their disease for fear of stigma, which negatively affected their satisfaction with life.
Relationship between Religious Coping, Pain Severity, and Childbirth Self-Efficacy in Iranian Primipara Women
Authors: Sotudeh Tahereh , Hasanpoor-Azghady Seyedeh Batool , Amiri-Farahani Leila
Published: February 2022

Background. One of the important goals of midwifery support and care is to control labor pain and increase the ability to cope with pain. The use of religious coping may be effective in counteracting the stressors of labor, especially labor pain, as well as increasing the self-efficacy of labor. This study was conducted to determine the relationship between religious coping, pain severity, and childbirth self-efficacy in Iranian primipara women. Materials and Methods. This cross-sectional study was performed on 200 Iranian primiparous women referred to eight health centers in the capital of Hormozgan Province who were intending to have a normal vaginal delivery (NVD) in the Persian Gulf and Sharifi Hospitals. The sampling was multistage. Data were collected by demographic and fertility questionnaires, the Iranian Religious Coping Scale, the Childbirth Self-Efficacy Inventory, and the Visual Analog Scale for pain measurement. Results. Among the dimensions of religious coping, benevolent reappraisal had a significant direct relationship with pain severity, and negative religious coping had a significant inverse relationship with pain severity. In the case of childbirth self-efficacy subscales, the results showed dimensions of religious practices, benevolent reappraisal, and active religious coping had a significant direct relationship with outcome expectancy, and negative religious coping had a significant indirect relationship with outcome expectancy. Also, there was a significant direct relationship between religious practices and efficacy expectancy and a significant inverse relationship between negative and passive religious coping and efficacy expectancy. Conclusion. With increasing some dimensions of positive religious coping, the severity of labor pain and childbirth self-efficacy increases, and with increasing dimensions of negative and passive religious coping, childbirth self-efficacy decreases. These correlations were weak in all the mentioned results.
Novel MAGT1 Mutation Found in the First Chinese XMEN in Hong Kong
Authors: Au Elaine Yuen Ling , Tung Edmund Kwok Kwan , Ip Ricky Wai Ki , Li Philip Hei
Published: February 2022

The availability of next-generation sequencing (NGS) helps to resolve many of the diagnostic odysseys. Common variable immunodeficiency disease (CVID) is an entity encompassing a heterogenous group of conditions with hypogammaglobulinemia, and it is a diagnosis of exclusion. In recent years, with the advances of molecular diagnostics, more and more patients have been reclassified with more defined entities after their genetic causes were found. Here, we reported a young man, who was managed as CVID since childhood, presenting with recurrent infection, hypogammaglobulinemia, and immune thrombocytopenia (ITP). Finally, more than a decade after initial presentation, gene panel testing revealed a novel mutation in the MAGT1 gene. Collectively, the genetic findings and clinical presentations confirm the diagnosis of X-linked immunodeficiency with magnesium defect and Epstein–Barr virus infection and neoplasia (XMEN). MAGT1 is an evolutionarily conserved, magnesium-specific transporter expressed in all mammalian cells that plays an essential role in magnesium homeostasis. MAGT1 also acts as an accessory protein for STT3B, as catalytic subunits of the oligosaccharyltransferase protein complex, which carries out glycan chain transfer to proteins in the endoplasmic reticulum during N-glycosylation. Glycans play an essential role in the stability, maturation, and localization in glycoproteins that are important in our immune cells’ function. Mutation of the gene resulted in a rare X-linked recessive condition XMEN. The disease has complete penetrance but variable expressivity. It is mainly associated with immunodeficiency, immunodysregulation, and predisposition to EBV-associated lymphoproliferation. Extraimmune manifestations have also been reported in some patient cohorts, including hepatic and neurological abnormalities. Overall, the presentation varies among patients and overlaps with other clinical entities, in which diagnosis is challenging. Before the era of NGS, traditional workup hinges heavily on phenotype studies, followed by single-gene sequencing. The diagnostic yield is low, and a significant delay in diagnosis is common. This case illustrated the importance of early consideration of molecular studies in complex immunological cases without obvious secondary causes as an integral part of patient management.
A Step-by-Step Equivalent Microprediction Method for the Mechanical Properties of Composite Solid Propellants considering Dewetting Damage
Authors: Cui Huiru , Lv Xuan , Xu Yurong , Zhong Zhiwen , Zhou Zixiang , Ma Weili
Published: February 2022

Reliable prediction of the macromechanical properties of composite solid propellants in the microscale can accelerate the development of propellants with high mechanical properties. According to the characteristics of the composition ratio of a four-component hydroxyl-terminated polybutadiene (HTPB) propellant with the component ammonium perchlorate (AP), hydroxyl-terminated polybutadiene, aluminum powder (AL), and cyclotrimethylenetrinitramine (or RDX for short), an improved random delivery algorithm was developed to separately model filler particles with the different sizes. A step-by-step equivalent representative volume element (RVE) model was generated to reflect the microstructures of the propellant. The isotropy and uniformity of the RVE model were also tested using a two-point probability function. The Park-Paulino-Roesler (PPR) cohesive model was introduced to simulate the particle debonding (or dewetting) in solid propellant. The stress-strain curves of the propellant were obtained by the macroscopic test with the extension rate 200 mm/min at different temperatures. Based on these experimental data, the 8 characteristic parameters suitable for the microinterface of the propellant were obtained by using an inversion optimization method. A microscale finite element prediction model of the propellant considering dewetting damage was constructed to study the evolution process of the microdamage of the propellant. The predicted stress-strain curves of the propellant under different loading conditions were in good agreement with the test results.
Management of Acute Pancreatitis: Conservative Treatment and Step-Up Invasive Approaches—Evidence-Based Guidance for Clinicians
Authors: Giakoumakis Michail I. , Gkionis Ioannis G. , Marinis Anastasios I. , Flamourakis Mathaios E. , Spiridakis Konstantinos G. , Tsagkataki Eleni S. , Kaloeidi Eleni I. , Strehle Andreas F. , Bachlitzanakis Emmanouil N. , Christodoulakis Manousos S.
Published: February 2022

Although acute pancreatitis is one of the most common conditions that physicians face in daily practice, different approaches are still being followed. Given that in 20–30% of cases, acute pancreatitis progresses to the severe form with single- or multiorgan failure and is often associated with admission to the intensive care unit, proper management is important. This article is aimed at emphasizing the importance of proper conservative treatment of acute pancreatitis and at focusing on intervention criteria in case of complications, analyzing additionally the step-up endoscopic and surgical approaches. The most common mistakes in conservative treatment include inadequate initial fluid resuscitation, abuse in the administration of antibiotics, insufficient analgesia, avoidance of oral feeding, and inappropriate use of imaging techniques. Moreover, the timing and indications for endoscopic retrograde cholangiopancreatography and cholecystectomy are crucial. Furthermore, in case of unsatisfying response to conservative treatment, which mainly happens during necrotic pancreatitis, early intervention is not indicated and a minimally invasive approach must be adopted firstly, 4 weeks after the onset of the disease, and before any surgical intervention. Each medical procedure has specific indications and must be used in the appropriate occasion. As a result, clinical doctors must be familiar both with the intervention criteria and the indications of each method. The proper management of acute pancreatitis is essential and life-saving. That is valid both for the conservative treatment and for the invasive approaches.
Integrated Planning of MV/LV Distribution Systems with DG Using Single Solution-Based Metaheuristics with a Novel Neighborhood Search Method Based on the Zbus Matrix
Authors: Valencia Alejandro , Hincapie Ricardo A. , Gallego Ramon A.
Published: February 2022

This paper presents a new methodology for the optimal integrated planning of medium- and low-voltage distribution systems, considering the location and sizing of distributed generation. The integrated problem is formulated as a mixed-integer nonlinear model and, to solve it, two well-known optimization algorithms (simulated annealing and iterated local search) are used. The intensification and diversification processes are usually the bottleneck of metaheuristic techniques for solving complex problems. To overcome such complexity, a new neighborhood search method based on the Zbus matrix (NSZM) is proposed, to explore the solution space more efficiently and effectively for both algorithms. The proposed methodology is validated and tested on a real distribution system taken from the literature. The results obtained are better than those reported in the literature. To verify the efficiency of the new NSZM method, the Wilcoxon signed ranks test is used to measure the performance behavior of the NSZM method in the two optimization algorithms used. The numerical results demonstrate that the NSZM method enhances both algorithms equally.
Research on Grid Monitoring Algorithm of Educational Resources Based on Economic Structure Transformation
Authors: Wang Meihui , Liu Jia
Published: February 2022

In order to overcome the problems of the traditional educational resource grid monitoring algorithm, such as high signal noise, high data acquisition time, and high monitoring error rate, an educational resource grid monitoring algorithm based on the transformation of economic structure was proposed. This paper analyzes the structure of educational resource grid and constructs the monitoring structure of educational resource grid by using hierarchical tree structure model. With the support of this architecture, information sensors and data collection detectors are used to collect relevant data, and convolutional neural networks are used to denoise the collected data. According to the processed data, the educational resource grid under the transformation of economic structure is monitored to obtain relevant monitoring results. Experimental results show that the maximum value and minimum value of signal noise are 15 dB and 9 dB, respectively, the data acquisition time is always lower than 0.3 s, and the monitoring error rate is always below 4%, which has high practical application value.
The Heuristic Algorithm Optimization of Home Care Path Based on the Internet of Things Realizes Connected Medical Care
Authors: Zhang Jinfeng , Li Xin , Zhao Yu
Published: February 2022

Optimize the scheduling problem of family nursing staff according to the actual needs of the customers, combined with the psychological behavior characteristics of the participants, and use the path heuristic algorithm on home nursing service institutions, full-time nursing staff, and nursing customers. Taking this as the maximization of the three subjects as the ultimate goal of home caregiver optimization and scheduling, a path heuristic-based heuristic optimization and scheduling method (path heuristic algorithm, PHA). The effectiveness of this method is analyzed through examples, and finally, according to the experimental analysis results of the distribution, dominance, and convergence of the proposed PHA algorithm, the home caregiver optimization and scheduling method proposed in this paper can provide a more long-term scheduling method for enterprise companies.
Risen Alive: The Lazarus Phenomenon
Authors: Gaba Waqar Haider , El Hag Shahad Abobakar , Bashir Shaima Mustafa
Published: February 2022

The Lazarus phenomenon described as delayed return of spontaneous circulation (ROSC) after cessation of CPR is rare, though underreported. We present the case of a 25-year-old woman who visited our hospital for persistent vomiting and weight loss for the last six months following bariatric surgery. On the 16th day of admission, the patient experienced cardiac arrest (code blue). The patient underwent 73 min of continuous cardiopulmonary resuscitation (CPR); however, no responses were observed, which led to an announcement of death. Fifty minutes later, the family members noticed subtle eye movements that necessitated resumption of the advanced cardiac life support protocol and resuscitation. The patient survived; however, she developed significant neurological deficits secondary to prolonged anoxic brain injury. She was discharged after a ten-week stay in the hospital but did not achieve full neurologic, cognitive, and motor recovery. Patients should be observed and monitored after the cessation of CPR before confirming death.
Efficacy and Safety of Temozolomide Combined with Radiotherapy in the Treatment of Malignant Glioma
Authors: Wei Shoufeng , Li Junde
Published: February 2022

MG is a clinical common intracranial tumor, with the characteristics of strong invasion. In our study, we aim to explore the efficacy and safety of temozolomide combined with radiotherapy in the treatment of malignant glioma (MG) and its influence on postoperative complications and survival rate of patients. 120 MG patients admitted to our hospital (January 2019–January 2020) were chosen as the research objects and were randomly divided into group A (n = 60) and group B (n = 60). All patients were treated with radiotherapy, and patients in group A were additionally treated with temozolomide. The clinical efficacy, quality of life, incidence of adverse reactions, incidence of postoperative complications, survival rates, and average survival time of the two groups were compared. The objective remission rate (ORR), disease control rate (DCR), survival rates after one year and two years of follow-up, and the number of patients with improved quality of life in group A were markedly higher compared with group B

P
<
0.05

. The incidence of postoperative complications in group A was remarkably lower compared with group B

P
<
0.05

. The average survival time of group A was dramatically longer compared with group B

P
<
0.001

. There was no significant difference in the incidence of adverse reactions between the two groups

P
>
0.05

, and no new adverse reactions occurred in the patients. Temozolomide combined with radiotherapy can effectively improve the quality of life, treatment effect, and survival rate of MG patients, with a lower incidence of postoperative complications and better tolerance. Our finding indicates that temozolomide combined with radiotherapy has a high clinical application value. In addition, it indicates that this treatment method should be promoted in practice.
Current Understanding of the Neural Circuitry in the Comorbidity of Chronic Pain and Anxiety
Authors: Chen Teng , Wang Jing , Wang Yan-Qing , Chu Yu-Xia
Published: February 2022

Chronic pain patients often develop mental disorders, and anxiety disorders are common. We hypothesize that the comorbid anxiety results from an imbalance between the reward and antireward system due to persistent pain, which leads to the dysfunction of the pain and anxiety regulatory system. In this review, we will focus on changes in neuroplasticity, especially in neural circuits, during chronic pain and anxiety as observed in animal studies. Several neural circuits within specific regions of the brain, including the nucleus accumbens, lateral habenular, parabrachial nucleus, medial septum, anterior cingulate cortex, amygdala, hippocampus, medial prefrontal cortex, and bed nucleus of the stria terminalis, will be discussed based on novel findings after chemogenetic or optogenetic manipulation. We believe that these animal studies provide novel insights into human conditions and can guide clinical practice.
A New V-Net Convolutional Neural Network Based on Four-Dimensional Hyperchaotic System for Medical Image Encryption
Authors: Wang Xiaowei , Yin Shoulin , Shafiq Muhammad , Laghari Asif Ali , Karim Shahid , Cheikhrouhou Omar , Alhakami Wajdi , Hamam Habib
Published: February 2022

In the transmission of medical images, if the image is not processed, it is very likely to leak data and personal privacy, resulting in unpredictable consequences. Traditional encryption algorithms have limited ability to deal with complex data. The chaotic system is characterized by randomness and ergodicity, which has advantages over traditional encryption algorithms in image encryption processing. A novel V-net convolutional neural network (CNN) based on four-dimensional hyperchaotic system for medical image encryption is presented in this study. Firstly, the plaintext medical images are processed into 4D hyperchaotic sequence images, including image segmentation, chaotic system processing, and pseudorandom sequence generation. Then, V-net CNN is used to train chaotic sequences to eliminate the periodicity of chaotic sequences. Finally, the chaotic sequence image is diffused to change the raw image pixel to realize the encryption processing. Simulation test analysis demonstrates that the proposed algorithm has better effect, robustness, and plaintext sensitivity.
Evaluation of Lightning Prediction by an Electrification and Discharge Model in Long-Term Forecasting Experiments
Authors: Xu Liangtao , Chen Shuang , Yao Wen
Published: February 2022

Over nearly three rainy seasons of lightning activity in North China, numerical prediction experiments were carried out using the Weather Research and Forecasting model coupled with electrification and discharge schemes (WRF-Electric). The numerical forecast results were evaluated using the neighborhood-based equitable threat score (ETS) and fraction skill score (FSS) verification methods based on nationwide observational lightning data. An algorithm was used to generate the coverage of the total flash (intracloud and cloud-to-ground flashes) by fitting the cloud-to-ground flash data. The numerical results showed that the region of lightning activity could be well predicted by the mesoscale WRF-Electric model, particularly during a 6–12-hour forecasting period. The average ETS score of the 6–12-hour forecasting period was 0.34 for a 20 km neighborhood radius. The predictive skill of the model varied not only monthly but also diurnally. The model showed better forecasting skills during the main rainy season (June–July–August) and at 14 : 00–20 : 00 local time. The predictability of the model was enhanced with increasing thunderstorm scale. On the other hand, the coverage of predicted lightning activity was relatively concentrated, and the lightning flash density was higher than the observations. The main discrepancies in the model prediction were related to the design of the discharge parameterization. Thus, in discharge parameterization, the initial threshold for lightning should be modified according to the model resolution, while the magnitude of the neutralization charge in a single discharge should be referenced to the observational results.
Fast Implementation of Multiplication on Polynomial Rings
Authors: Wang Boyu , Gao Haiying , Yang Fan
Published: February 2022

Multiplication on polynomial rings has been widely used in public-key cryptographic schemes based on ideal lattices. It is an important module that significantly affects the efficiency of the schemes. Improved Preprocess-then-NTT (IPtNTT) is an algorithm which can fast realize multiplication on polynomial rings. Compared with the Number Theoretic Transform (NTT), the IPtNTT weakens the parameter restriction of lattice-based public-key cryptographic schemes. By optimizing the IPtNTT with the AVX2 instruction set, we reduce the clock cycles consumed by multiplication on polynomial rings to 15%–22%. According to the experimental results, we give specific suggestions on using AVX2 optimized IPtNTT to realize multiplication on polynomial rings with different parameters chosen in lattice-based public-key cryptosystems.
High-Temperature Rheology Characteristics of Hard Petroleum Asphalt Used in China
Authors: Li Bo , Wang Binghui , Zhang Xijun , Lin Xixiong , Zhang Yan
Published: February 2022

Hard petroleum asphalt, which is a high modulus asphalt binder material, is used for improving asphalt pavement rutting distress. This property is attributed to the good high-temperature rheological characteristics of hard petroleum asphalt. The study investigates the performance of hard petroleum asphalt and Styrene-Butadiene-Styrene polymer modified asphalt (SBSPMA) based on three aspects: asphalt oil source, asphalt grade, and aging degree. The short-term and long-term aging of four hard petroleum asphalts and SBSPMA of comparative samples were measured using the rolling thin film oven test (RTFOT) and the pressure aging test (PAV). Firstly, the viscosity-temperature curve of hard petroleum asphalt was obtained using the Brookfield viscosity test at different temperatures combined with the improved REFUTAS formula. The complex shear modulus (

G

∗

), phase angle (δ), and rutting factor (

G

∗

/

sin
 
 
δ

) of each asphalt sample were then measured by the dynamic shear rheometer test (DSR). Furthermore, the temperature sensitivity of each asphalt sample was calculated using the complex modulus index method (GTS). The compaction and paving temperature ranges of each asphalt were then confirmed. The results showed that the high-temperature rheological characteristics of hard petroleum asphalt were similar to those of SBSPMA. The temperature sensitivity of hard petroleum asphalt was basically the same as that of SBSPMA, while the influence of aging on the

G

∗

of hard petroleum asphalt was greater than that of SBSPMA. In addition, the hard petroleum asphalt construction temperature was lower than that of SBSPMA.
Towards Optimal Resources Allocation in Cloud Manufacturing: New Task Decomposition Strategy and Service Composition Model
Authors: Fang Zhou , Wu Qilin , Guan Dashuai
Published: February 2022

Service composition optimization is one of the core issues in cloud manufacturing research. However, all current studies of service composition in cloud manufacturing assume that tasks have been decomposed into subtasks, so they can be directly mapped to existing services. However, due to the complexity, diversity, and multilevel of services in cloud manufacturing, services have different granularity. Therefore, the matching between tasks and services does not always occur at the lowest level. For solving the problem of discontinuity between task decomposition and service composition, this paper considers the characteristics of existing services in the cloud pool and proposes a task decomposition strategy based on task/service matching on the basis of refining the description model of tasks and services. Then, for the decomposed subtask set, the E-CARGO model is used to model the optimal composition process of services, and CPLEX is used to solve the model. Practical cases show that the proposed task decomposition strategy can solve the problem of discontinuity between task decomposition and service composition without relying on more expert systems. In addition, the proposed service composition model is more flexible, can easily model more variable factors, and CPLEX can solve the model more quickly and stably.
Assessment of Accessory Canals and Foramina in the Mandibular Arch Using Cone‐Beam Computed Tomography and a New Classification for Mandibular Accessory Canals
Authors: Muley Pooja , Kale Lata , Choudhary Sneha , Aldhuwayhi Sami , Thakare Amar , Mallineni Sreekanth Kumar
Published: February 2022

Objectives. The objectives of the study include the following: (i) to assess the presence of accessory canals and foramina in the body of the mandible using cone‐beam computed tomography (CBCT), (ii) to evaluate the location, number, diameter, and length of accessory canals in the body of the mandible, and (iii) to propose a new classification for mandibular accessory canals based on the location. Methods. A total of 50 (25 males and 25 females) CBCT scans were analyzed in three anatomical planes and three‐dimensional (3D) reconstructions for the exact number, location, diameter, and accessory length canals and accessory foramina in the body of the mandible. The statistical analysis used was an independent t‐test. Results. Out of 50 CBCT scans, a total of 243 accessory canals and 245 accessory foramina were found. About 53% of accessory canals and foramina were found in males, while 47% were observed in females; 89% were evident in the anterior region, and only 11% were in the posterior region. The majority (64%) of the medial lingual canals had a diameter greater than or equal to 1 mm, while only 32% of accessory canals had a diameter of less than 1 mm (p < 0.05). The mean length of median lingual canals in females was 1.2910 ± 0.2582 mm and 2.6438 ± 0.5288 mm in male subjects. Mandibular accessory canals are classified broadly into anterior and posterior accessory canals, which have further subdivisions. Conclusion. CBCT plays a dynamic role in determining the mandible location of various neurovascular structures, including accessory canals and foramina. Female subjects were observed with more accessory canals and foramina and more common in the anterior region than in the posterior region.
Analytical Simulation of Heat and Mass Transmission in Casson Fluid Flow across a Stretching Surface
Authors: Khan Kashif Ali , Jamil Faizan , Ali Javaid , Khan Ilyas , Ahmed Nauman , Andualem Mulugeta , Rafiq Muhammad
Published: February 2022

This research presents a review of an analytical simulation of heat and mass transmission features of steady, non-Newtonian Casson fluid motion across a permeable medium through a stretching surface. The effects of heat production and thermal emission are put into discussion. Mathematically, the governing model is manipulated by a series of nonlinear partial equations, which are then modified into ordinary differential equations with the assistance of appropriate conversion. Analytical results for such equations are then achieved by invoking the notable technique of the homotopy analysis method (HAM), and its solution sounds good while achieving the convergence guaranteed in the convergence table. Some achievements have been made. The consequence of raising the value of the Casson parameter is comprehended to be putting down the velocity field while increasing the temperature field. Also, the concentration field falls with an increase in the Schmidt number, while it rises with an enhancement in the Soret number. The electric parameter due to Lorentz’s force is capable of accelerating the temperature of the fluid but downsizing the velocity.
Late Stent Thrombosis in a Patient with Endovascular Aortic Repair for Blunt Thoracic Aortic Injury
Authors: Chiu Michael H. , Kaitoukov Youri , Roze des Ordons Amanda
Published: February 2022

Blunt thoracic aortic injury (BTAI) is associated with high mortality and morbidity. Thoracic endovascular aortic repair has become the recommended treatment modality given improved short-term results compared to open repair. We present a case of a 19-year-old male who presented with acute paralysis and multiorgan dysfunction from acute TEVAR thrombosis. Systemic thrombolysis, catheter-directed thrombolysis followed by aspiration thrombectomy, and angioplasty were initially successful in restoring perfusion. However, he developed progressive multiorgan failure related to prompt reocclusion within 48 hours. This case is the first to describe thrombolysis and angioplasty as a management strategy for acute TEVAR thrombosis. We also review the literature surrounding this uncommon complication.
Research on Emotion Recognition of EEG Signal Based on Convolutional Neural Networks and High-Order Cross-Analysis
Authors: Fan Chengcheng , Liu Xiang , Gu Xuelin , Zhou Liang , Li Xiaoou
Published: February 2022

Emotion recognition means the automatic identification of a human’s emotional state by obtaining his/her physiological or nonphysiological signals. The EEG-based method is an effective mechanism, which is commonly used for the recognition of emotions in real environments. In this paper, the convolutional neural network is used to classify the EEG signal into three and four emotional states under the DEAP dataset, which is defined as a Database for Emotion Analysis using physiological signals. For this purpose, a high-order cross-feature sample is extracted to recognize the emotional state with a single channel. A seven-layer convolutional neural network is used to classify the 32-channel EEG signal, and the average accuracy of four and three emotional states is 65% and 58.62%. The single-channel high-order cross-sample is classified with convolutional neural networks, and the average accuracy of four emotional states is 43.5%. Among all the channels related to emotion recognition, the F4 channel gets the best classification accuracy of 44.25%, and the average accuracy of the even number channel is higher than the odd number channel. The proposed method provides a basis for the real-time application of EEG-based emotion recognition.
Question Answering System Based on Knowledge Graph in Traditional Chinese Medicine Diagnosis and Treatment of Viral Hepatitis B
Authors: Yin Yating , Zhang Lei , Wang Yiguo , Wang Mingqiang , Zhang Qiming , Li Guo-zheng
Published: February 2022

This article uses the real medical records and web pages of Chinese medicine diagnosis and treatment of hepatitis B to extract structured medical knowledge, and obtains a total of 8,563 entities, 96,896 relationships, 32 entity types, and 40 relationship types. The structured data was stored in the Neo4j graph structure database, and a knowledge graph of Chinese medical diagnosis and treatment of hepatitis B was constructed. The knowledge map is used as a structured data source to provide high‐quality knowledge information for the medical question and answer system based on hepatitis B disease. Applying the deep learning method to the question identification and knowledge response of the question answering system makes the hepatitis B medical intelligent question answering system has important research and application significance. The question‐and‐answer system takes aim at hepatitis B, a public health problem in the world and leverages the advantages of traditional Chinese medicine for diagnosis and treatment. It provides a reference for doctors’ disease diagnosis, treatment, and patient self‐care. Its value is important for the treatment of hepatitis B disease.