bluuebunny/crossref_metadata_2025 huggingface dataset:
Uncovering the high prevalence of bacterial burden in surgical site wounds with point‐of‐care fluorescence imaging
Authors: Sandy‐Hodgetts Kylie , Andersen Charles A. , Al‐Jalodi Omar , Serena Laura , Teimouri Christina , Serena Thomas E.
Published: December 2021

Detection of bacterial burden within or near surgical wounds is critical to reducing the occurrence of surgical site infection (SSI). A distinct lack of reliable methods to identify postoperative bioburden has forced reliance on clinical signs and symptoms of infection (CSS). As a result, infection management has been reactive, rather than proactive. Fluorescence imaging of bacterial burden (FL) is positioned to potentially flip that paradigm. This post hoc analysis evaluated 58 imaged and biopsied surgical site wounds from the multi‐centre fluorescence imaging assessment and guidance clinical trial. Diagnostic accuracy measures of CSS and FL were evaluated. A reader study investigated the impact of advanced image interpretation experience on imaging sensitivity. Forty‐four of fifty‐eight surgical site wounds (75.8%) had bacterial loads >104 CFU/g (median = 3.11 × 105 CFU/g); however, only 3 of 44 were CSS positive (sensitivity of 6.8%). FL improved sensitivity of bacterial detection by 5.7‐fold compared with CSS alone (P = .0005). Sensitivity improved by 11.3‐fold over CSS among clinicians highly experienced with FL interpretation (P < .0001). Surgical sites that reach the stage of referral to a wound specialist frequently harbour asymptomatic high bacterial loads that delay healing and increase infection risk. Advanced imaging of pathological bacterial burden improves surgical site monitoring and may reduce the rate of SSIs.
A convolutional neural network‐based comparative study for pepper seed classification: Analysis of selected deep features with support vector machine
Authors: Sabanci Kadir , Aslan Muhammet Fatih , Ropelewska Ewa , Unlersen Muhammed Fahri
Published: December 2021

The seeds of high quality are very important for the cultivation of the pepper. The required cultivation practices and growing conditions may be affected by the cultivar. Also, the productivity and properties of pepper depend on the cultivar. The selection of appropriate seed cultivars may be necessary for the breeding programs. The cultivar differentiation of pepper seeds may be tested by the human eye. However, small sizes and visual similarities make it difficult to distinguish between seed cultivars. Computer vision and artificial intelligence can provide high cultivar discrimination accuracy and the procedures are objective and fast. This study aimed to classify pepper seeds belonging to different cultivars with convolutional neural network (CNN) models. The seeds were obtained from green, orange, red, and yellow pepper cultivars. A flatbed scanner was used to acquire the pepper seed images. After the image acquisition, the procedure applied was preprocessing of the images, data augmentation using different techniques and then deep learning‐based classification. Two approaches have been proposed for classification. In the first approach, CNN models (ResNet18 and ResNet50) were trained for pepper seeds. In the second approach, different from the first, the features of pretrained CNN models were fused, and feature selection was applied to the fused features. Classification using all features and selected features was performed with the support vector machine (SVM) with different kernel functions (Linear, Quadratic, Cubic, Gaussian). The accuracies in the first approximation were 98.05% and 97.07% for ResNet50 and ResNet18, respectively. In the second approach, CNN‐SVM‐Cubic achieved up to 99.02% accuracy with the selected features.

Practical applications

In precision agriculture, it is very important that the seeds be of the same type for the purification and standardization of the crop culture. Performing this classification manually with human assistance will result in subjective, slow, and low standard outcomes. To overcome such problems, classification supported by artificial intelligence and machine vision systems emerges as an important tool. In this study, a highly successful classification system is presented according to the visual characteristics of pepper seeds. The proposed models can be preferred in practice for identifying pepper seeds and detecting falsification or ensuring their reliability. It will prevent mixing of different pepper seeds with different attributes for processing.
Reply to: Comment on: “Optimal exercise parameters of tai chi for balance performance in older adults: A meta‐analysis”
Authors: Zheng Guohua , Wang Lecong
Published: December 2021

This letter comments on the letter by Xin Tian
Human capital acquisition as a signaling device in promotion competition
Authors: Cohen Chen , Zax Ori
Published: December 2021

We analyze an economy in which workers compete over promotion to one of a fixed number of high‐paying jobs. Hence, the probability of obtaining a promotion to such a job is a function of the worker's own ability and level of schooling as well as her/his rival's. In such an economy, a new reason for acquiring human capital emerges, obtaining an edge over potential rivals for desirable jobs. We discuss the implications of this new incentive to acquire human capital and show that low‐ability workers overinvest while high‐ability workers underinvest in schooling.
Digital connectivity for work after hours: Its curvilinear relationship with employee job performance
Authors: Ren Shuang , Hu Jia , Tang Guiyao , Chadee Doren
Published: December 2021

Using digital technologies for work‐related matters during nonwork time is an increasingly common behavior in contemporary workplaces. Despite the prevalence of digital connectivity (DCON) in today's organizations, its implications for employee job performance remain under‐specified. Drawing on conservation of resources (COR) theory and the “too‐much‐of‐a‐good‐thing” (TMGT) meta‐theoretical principle, we theorize that DCON has an inverted U‐shaped relationship with employee job performance through the mediation of social capital development (SCD) and emotional exhaustion (EE). The results of two studies with different designs support our theoretical expectations. Specifically, we found that increases in DCON associate with higher SCD, lower EE, and higher job performance up to an inflexion point, after which more DCON has detrimental effects. The theoretical and practical implications of the findings are fully discussed.
Mitigation of vanillic acid‐promoted faba bean Fusarium wilt by faba bean–wheat intercropping
Authors: Zheng Yiran , Guo Yuting , Lv Jiaxing , Dong Kun , Dong Yan
Published: December 2021

Long‐term continuous monocropping of faba beans increases the incidence of faba bean wilt, while faba bean–wheat intercropping can effectively control it. This study aimed to understand the underlying mechanism of faba bean–wheat intercropping for the control of Fusarium oxysporum and vanillic acid (VA)‐promoted occurrence of faba bean wilt. The occurrence of faba bean wilt was investigated among the monocropped and intercropped plants of faba beans in a field experiment. The contents and types of phenolic acids were examined in the rhizosphere soil. Monocropped and intercropped faba beans were examined under the dual stress of F. oxysporum and different concentrations of VA (0, 50, 100, 200 mg/L) to understand the alleviating mechanism of faba bean–wheat intercropping. Exogenous addition of high concentrations of VA significantly inhibited the growth and reproduction of F. oxysporum, but under the dual stress of F. oxysporum and different concentrations of VA, it significantly inhibited the defence enzymes of faba bean roots, stems, and leaves, and rhizosphere soil enzymes. Interestingly, faba bean–wheat intercropping alleviated VA stress and thereby the incidence and disease index of faba bean Fusarium wilt by improving plant resistance and soil enzyme activity. The dual stress of F. oxysporum and VA promotes the occurrence of Fusarium wilt by damaging the defence system of the faba bean root system and rhizosphere soil environment. However, faba bean–wheat intercropping effectively alleviates the autotoxicity of VA by improving the physiological and biochemical resistance of faba beans and soil enzyme activities, and thus controls the occurrence of Fusarium wilt.
Teaching about death and dying—A national mixed‐methods survey of palliative care education provision in Swedish undergraduate nursing programmes
Authors: Hagelin Carina Lundh , Melin‐Johansson Christina , Ek Kristina , Henoch Ingela , Österlind Jane , Browall Maria
Published: December 2021

Background

In coming decades, the number of people affected by illnesses who need palliative care will rise worldwide. Registered Nurses are in a central position in providing this care, and education is one of the necessary components for meeting coming requirements. However, there is a lack of knowledge about palliative care in undergraduate nursing education curricula, including the extent of the education provided and the related pedagogical methods.

Aim

The aim was to investigate the extent, content and pedagogical methods used and to explore lecturers’ experiences of being responsible for teaching and learning about palliative care for undergraduate nursing students on nursing programmes at Swedish universities.

Setting

All 24 universities responsible for providing undergraduate nursing education in Sweden participated.

Participants

One lecturer with in‐depth knowledge about palliative care or end‐of‐life care education participated in the quantitative (n = 24) and qualitative (n = 22) parts of the study.

Method

A mixed‐method research study with an explorative design was used. Descriptive statistics were used to analyse quantitative data, and content analysis for qualitative, with both also analysed integratively.

Results

Few undergraduate nursing programmes included a specific course about palliative care in their curricula, however, all universities incorporated education about palliative care in some way. Most of the palliative care education was theoretical, and lecturers used a variety of pedagogical strategies and their own professional and personal experience to support students to understand the palliative care approach. Topics such as life and death were difficult to both learn and teach about.

Conclusions

There is a need for substantial education about palliative care. Lecturers strive on their own to develop students’ understanding and increase the extent of palliative care education with innovative teaching strategies, but must compete with other topics. Palliative care teaching must be prioritised, not only by the universities, but also by the national authority.
The role of markets on resource conflicts*
Authors: Dickson Alex , MacKenzie Ian A. , Sekeris Petros G.
Published: December 2021

We develop a generalized theory of resource conflict. We demonstrate that the existence of a resource curse (or blessing) relies on two fundamental elements: (i) market conditions; and (ii) the production technology or agents’ preferences, depending on the context under study. When resource prices are treated as exogenous, we obtain the conventional result: an increase in the value of the resource rent, due to an increase in its price or its availability (or lower opportunity cost of appropriation), increases conflict. However, when the price of the contestable resource is endogenously determined (i.e., in local markets) or if markets do not exist, we find that the relationship between conflict intensity and resource abundance depends on the production technology or on agents’ preferences: conflict can increase when the contestable resource becomes scarcer. Therefore, our paper identifies a fundamental transmission mechanism in resource conflicts.
The novel HLA‐DRB1*12:02:11 allele identified by next‐generation sequencing in a Chinese bone marrow donor
Authors: He Yi Zhen , Fu Rui , Zhang Wei , He Ji , Zhu Faming
Published: December 2021

HLA‐DRB1*12:02:11 differs from HLA‐DRB1*12:02:01:01 by a single nucleotide substitution at position 579 T > G.
Electricity Usage Monitoring Based On Internet of Things
Authors: Ahmad Mohd Ridzuan , Hashim Hishamuddin
Published: December 2021

Electricity monitoring systems have long been used in industrial scenarios such as process scheduling and distribution. This monitoring system needs to be developed for domestic use such as in homes and shops. In recent times, the electricity demand has increased in households with the use of different appliances. The advent of technologies such as the Internet of Things (IoT) has made real-time data acquisition and analysis possible. This project is designed to control and monitor household electricity consumption via smartphones using the ESP8266 Wi-Fi module as a communication protocol and the Blynk application as a private server. The used wifi module provides notification through the Blynk application. The system uses an Arduino Mega2560 microcontroller to control all devices in this project. For monitoring the energy usage, a current sensor type Split Core Current Transformer (SCT013) was used. From the experimental results, it is confirmed that the system is capable of monitoring the whole house’s electrical usage easily. With this system in place, end-users are provided with proper awareness and able to plan their home’s electrical consumption pattern effectively.
Physiological aspects of cardiopulmonary dysanapsis on exercise in adults born preterm
Authors: Duke Joseph W. , Lewandowski Adam J. , Abman Steven H. , Lovering Andrew T.
Published: December 2021

Progressive improvements in perinatal care and respiratory management of preterm infants have resulted in increased survival of newborns of extremely low gestational age over the past few decades. However, the incidence of bronchopulmonary dysplasia, the chronic lung disease after preterm birth, has not changed. Studies of the long‐term follow‐up of adults born preterm have shown persistent abnormalities of respiratory, cardiovascular and cardiopulmonary function, possibly leading to a lower exercise capacity. The underlying causes of these abnormalities are incompletely known, but we hypothesize that dysanapsis, i.e. discordant growth and development, in the respiratory and cardiovascular systems is a central structural feature that leads to a lower exercise capacity in young adults born preterm than those born at term. We discuss how the hypothesized system dysanapsis underscores the observed respiratory, cardiovascular and cardiopulmonary limitations. Specifically, adults born preterm have: (1) normal lung volumes but smaller airways, which causes expiratory airflow limitation and abnormal respiratory mechanics but without impacts on pulmonary gas exchange efficiency; (2) normal total cardiac size but smaller cardiac chambers; and (3) in some cases, evidence of pulmonary hypertension, particularly during exercise, suggesting a reduced pulmonary vascular capacity despite reduced cardiac output. We speculate that these underlying developmental abnormalities may accelerate the normal age‐associated decline in exercise capacity, via an accelerated decline in respiratory, cardiovascular and cardiopulmonary function. Finally, we suggest areas of future research, especially the need for longitudinal and interventional studies from infancy into adulthood to better understand how preterm birth alters exercise capacity across the lifespan.

image
Atomic-scale growth, imaging, spectroscopy, and electronic transport properties of metal-oxide films and interfaces
Authors: Ohsawa Takeo
Published: December 2021

Metal-oxide thin films and interfaces exhibit numerous fascinating electronic transport properties that are not found in conventional semiconductor materials. There has been much interest in engineering them to improve their functionalities, and an improved fundamental understanding of the phenomena that occur in oxide films and heterostructures is critical. In this review, an innovative approach to strontium titanate and zinc oxide-based heterostructures using state-of-the-art scanning tunneling microscopy and photoemission spectroscopy systems, as well as electrical measurements are presented. The results show that atomic-scale bottom-up processes with greater care provide excellent opportunities for improving material properties and classifying complicated conductivity.
An effect of extra compactified dimensions of space in the molecule $$\hbox {NO}_{{2}}$$
Authors: Weber Hans-Georg
Published: December 2021

The theory of large extra compactified dimensions of space (ADD-model) predicts that gravity may become strong in a compactification space of the size of a molecule and may affect the vibrational motion of a molecule. In triatomic molecules like $$\hbox {NO}_{{2}}$$

NO
2

nuclear dynamics is strongly coupled to electronic dynamics at the intersection of electronic states (conical intersection). We discuss experimental results on $$\hbox {NO}_{{2}}$$

NO
2

which reveal that the collision-free molecule optically excited into a symmetric stretch vibration mode of an electronic state with conical intersection undergoes an irreversible non-radiative transition into an asymmetric stretch vibration mode in combination with a change of the electronic state. We suggest ascribing this irreversible non-radiative transition to a gravitational perturbation on the vibrational motion in $$\hbox {NO}_{{2}}$$

NO
2

. This gravitational perturbation deactivates the upper state of the optical transition. The width of the absorption line is given by the characteristic time of the gravitational perturbation and not by the radiative lifetime of the excited molecular state.

Graphical abstract
Therapeutic Effects of Shikonin on Skin Diseases: A Review
Authors: Mu Zhenzhen , Guo Jinrong , Zhang Dongxia , Xu Yuanyuan , Zhou Mingming , Guo Yimeng , Hou Yuzhu , Gao Xinghua , Han Xiuping , Geng Long
Published: December 2021

Shikonin is one of the primary active components extracted from the dried root ofZicao (Lithospermum erythrorhizon, Onosma paniculata, or Arnebia euchroma), a traditional Chinese herbal medicine. Shikonin is known to not only exert anti-proliferative, anti-inflammatory, and anti-angiogenic activities, but also play a crucial role in triggering the production of reactive oxygen species, suppressing the release of exosomes, and inducing apoptosis. Increasing evidence suggests that shikonin has a protective effect against skin diseases, including psoriasis, melanoma, and hypertrophic scars. In order to evaluate the application potential of shikonin in the treatment of skin diseases, this review is the first of its kind to provide comprehensive and up-to-date information regarding the uses of shikonin and its derivatives on skin diseases and its underlying mechanisms. In this review, we have focused on the signaling pathways and cellular targets involved in the anti-dermatosis effects of shikonin to bridge the gaps in the literature, thereby providing scientific support for the research and development of new drugs from a traditional medicinal plant.
Inhibiting TGF-β 1-Mediated Cellular Processes as an Effective Strategy for the Treatment of Pulmonary Fibrosis with Chinese Herbal Medicines
Authors: Wang Jing , Zhao Xingtao , Feng Wuwen , Li Yunxia , Peng Cheng
Published: December 2021

Pulmonary fibrosis (PF) is a chronic and irreversible interstitial lung disease that even threatens the lives of some patients infected with COVID-19. PF is a multicellular pathological process, including the initial injuries of epithelial cells, recruitment of inflammatory cells, epithelial-mesenchymal transition, activation and differentiation of fibroblasts, etc. TGF-[Formula: see text]1 acts as a key effect factor that participates in these cellular processes of PF. Recently, much attention was paid to inhibiting TGF-[Formula: see text]1 mediated cell processes in the treatment of PF with Chinese herbal medicines (CHM), an important part of traditional Chinese medicine. Here, this review first summarized the effects of TGF-[Formula: see text]1 in different cellular processes of PF. Then, this review summarized the recent research on CHM (compounds, multi-components, single medicines and prescriptions) to directly and/or indirectly inhibit TGF-[Formula: see text]1 signaling (TLRs, PPARs, micrRNA, etc.) in PF. Most of the research focused on CHM natural compounds, including but not limited to alkaloids, flavonoids, phenols and terpenes. After review, the research perspectives of CHM on TGF-[Formula: see text]1 inhibition in PF were further discussed. This review hopes that revealing the inhibiting effects of CHM on TGF-[Formula: see text]1-mediated cellular processes of PF can promote CHM to be better understood and utilized, thus transforming the therapeutic activities of CHM into practice.
Brain-computer Interaction Enabled AAC for Visual Interactive Paradigm
Authors: Liu Yaming , Zhou Zihan , Wang Aihong , Samuel R. Dinesh Jackson , Kumar Priyanmalarvizhi
Published: December 2021

The brain-computer interface (BCI) has recently provided a potential means for individuals with the least movement to control a computer utilizing their brain waves, with no motor output needed. Augmentative and alternative communication (AAC) is generally utilized by individuals with severe physical and speech disabilities and is one of the primary application fields for BCI technologies. The main objective of this study is to examine students’ brain parameters such as attention, concentration, and the energy of several brain waves using Augmentative and Alternative Communication-based Visual Interactive Paradigm (AAC-VIP) based on BCI in education systems. Particular emphasis is placed on integrating AAC into daily school life to foster every student’s access to and participation in the education curriculum. The effectiveness of the support plans has been assessed via behavioral observations and team interviews. The experimental findings demonstrate that the proposed model allows the completion of communication, with the highest interaction rate of 97.66%. It can be utilized in the classrooms to enhance the educative way of people with intellectual disabilities.
Deep Learning-based Mental Health Monitoring Scheme for College Students Using Convolutional Neural Network
Authors: Du Chao , Liu Chang , Balamurugan P. , Selvaraj P.
Published: December 2021

Artificial intelligence (AI) in healthcare has recently been promising using deep neural networks. It is indeed even been in clinical trials more and more, with positive outcomes. Deep learning is the process of using algorithms to train a neural network model using huge quantities of data to learn how to execute a given task and then make an accurate classification or prediction. Apart from physical health monitoring, such deep learning models can be used for the mental health evaluation of individuals. This study thus designs a deep learning-based mental health monitoring scheme (DL-MHMS) for college students. This model uses the most efficient convolutional neural network (CNN) to classify the mental health status as positive, negative, and normal using the EEG signals collected from college students. The simulation analysis achieves the highest classification accuracy and F1 scores of 97.54% and 98.35%, less sleeping disorder rate of 21.19%, low depression level of 18.11%, reduced suicide attention level of 28.14%, increasing personality development ratio of 97.52%, enhance self-esteem ratio of 98.42%, compared to existing models.
Beam dynamics design of HIAF RFQ
Authors: Wang Chao , Dou Weiping , Wang Zhijun , Tao Yue , Chen Weilong , Feng Chi , Liu Shuhui , He Yuan , Qin Yuanshuai , Qi Xin , Wang Wangsheng , Jia Yongzhi , Yuan Chenzhang , Li Lu
Published: December 2021

The high-intensity heavy ion accelerator facility is a next-generation advanced heavy-ion accelerator facility built by the Institute of Modern Physics, Chinese Academy of Sciences. The RFQ is designed to provide a continuous wave beam and 2[Formula: see text]mA pulse beam with high-quality longitudinal beam distribution for the injection linear accelerator. Two different designs of aiming to suppress the longitudinal emittance were studied, and the optimized scheme which composed of a three-harmonic pre-buncher and an RFQ accelerator with small longitudinal acceptance was chosen. More emphasis is put on the section between pre-buncher and RFQ, where the space charge effect becomes severe with bunched beam. The optimal design and the analysis are presented in this paper.
A NOVEL VARIATIONAL PERSPECTIVE TO FRACTAL WAVE EQUATIONS WITH VARIABLE COEFFICIENTS
Authors: HAN XUE-FENG , WANG KANG-LE
Published: December 2021

This paper aims at establishing two different types of wave models with unsmooth boundaries by the fractal calculus, and their fractal variational principles are successfully designed by employing the fractal semi-inverse transform method. A new approximate technology is proposed to solve the two fractal models based on the variational principle and fractal two-scale transform method. Finally, two numerical examples show that the proposed method is efficient and accurate, which can be extended to solve different types of fractal models.
LIFE STRESS, SOCIAL SUPPORT, AND DEPRESSION LEVELS IN MID- AND OLDER-AGED INDIVIDUALS EXPERIENCING BEREAVEMENT OF A SPOUSE IN TAIWAN
Authors: LI YANG-TZU , TSENG HUA-YUAN , HSIAO KAO-MING , CHEUNG JOHNSON CHUN-SING , TSUI MING SUM
Published: December 2021

This research aimed to explore life stress, available social support, and depression levels in mid- and older-aged individuals experiencing the bereavement of a spouse. We excluded subjects who were remarried, living with companions, divorced but not remarried, separated, or never married, resulting in a final sample of 1,231 subjects. Analyses indicated that a significant level of stress related to health, finances, and family relationships was associated with higher levels of life stress and depression. Individuals with family and friends who were less willing to listen or who cared less tended to suffer from more severe symptoms of depression.
ADOLESCENT DRUG REHABILITATION SERVICE MODELS IN HONG KONG: FROM THE PERSPECTIVE OF FRONTLINE SOCIAL WORKERS
Authors: TIN BEN KA-CHUNG , CHEUNG JOHNSON CHUN-SING
Published: December 2021

This study aimed to contribute to an exploratory categorization of different adolescent drug rehabilitation service models in Hong Kong. In-depth interviews were conducted with local social workers working in the medical model setting, integrated model setting, and social model setting. There was a trend that hybrid models were used by the drug rehabilitation service providers and a shift to postmodernism was found in the current service settings.
Birecognition of prime graphs, and minimal prime graphs
Authors: Belkhechine Houmem , Ben Salha Cherifa , Ille Pierre
Published: December 2021

Given a graph [Formula: see text], a subset [Formula: see text] of [Formula: see text] is a module of [Formula: see text] if for each [Formula: see text], [Formula: see text] is adjacent to all the elements of [Formula: see text] or to none of them. For instance, [Formula: see text], [Formula: see text] and [Formula: see text] ([Formula: see text]) are the trivial modules of [Formula: see text]. A graph [Formula: see text] is prime if [Formula: see text] and all its modules are trivial.

Given a prime graph [Formula: see text], consider [Formula: see text] such that [Formula: see text] is prime. Given a graph [Formula: see text] such that [Formula: see text] and [Formula: see text], [Formula: see text] and [Formula: see text] are [Formula: see text]-similar if for each [Formula: see text], [Formula: see text] and [Formula: see text] are both prime or not. The graph [Formula: see text] is said to be [Formula: see text]-birecognizable if every graph, [Formula: see text]-similar to [Formula: see text], is prime. We study the graphs [Formula: see text] that are not [Formula: see text]-birecognizable, where [Formula: see text] such that [Formula: see text] is prime, by using the following notion of a minimal prime graph. Given a prime graph [Formula: see text], consider [Formula: see text] such that [Formula: see text] is prime. Given [Formula: see text], [Formula: see text] is [Formula: see text]-minimal if for each [Formula: see text] such that [Formula: see text], [Formula: see text] is not prime.
2-Point set domination in separable graphs
Authors: Gupta Purnima , Jain Deepti
Published: December 2021

In a graph [Formula: see text], a set [Formula: see text] is a [Formula: see text]-point set dominating set (in short 2-psd set) of [Formula: see text] if for every subset [Formula: see text] there exists a nonempty subset [Formula: see text] containing at most two vertices such that the induced subgraph [Formula: see text] is connected in [Formula: see text]. The [Formula: see text]-point set domination number of [Formula: see text], denoted by [Formula: see text], is the minimum cardinality of a 2-psd set of [Formula: see text]. The main focus of this paper is to find the value of [Formula: see text] for a separable graph and thereafter computing [Formula: see text] for some well-known classes of separable graphs. Further we classify the set of all 2-psd sets of a separable graph into six disjoint classes and study the existence of minimum 2-psd sets in each class.
Impact of media coverage on a fractional-order SIR epidemic model
Authors: Maji Chandan
Published: December 2021

In this work, we formulated and analyzed a fractional-order epidemic model of infectious disease (such as SARS, 2019-nCoV and COVID-19) concerning media effect. The model is based on classical susceptible-infected-recovered (SIR) model. Basic properties regarding positivity, boundedness and non-negative solutions are discussed. Basic reproduction number [Formula: see text] of the system has been calculated using next-generation matrix method and it is seen that the disease-free equilibrium is locally as well as globally asymptotically stable if [Formula: see text], otherwise unstable. The existence of endemic equilibrium point is established using the Lambert W function. The condition for global stability has been derived. Numerical simulation suggests that fractional order and media have a large effect on our system dynamics. When media impact is stronger enough, our fractional-order system stabilizes the oscillation.
Thermodynamic Evaluation of a Direct Expansion Ground-Sourced Heat Pump with Horizontal Ground Heat Exchangers Using Advanced Exergy Analysis
Authors: Zarei Abdolazim , Ameri Mehran , Ghazizade-Ahsaee Hossein
Published: December 2021

This paper deals with the advanced exergetic analysis of a horizontal direct-expansion ground sourced CO2 heat pump operating in a transcritical cycle. The cycle is thermodynamically modeled in Engineering Equation Solver (EES) considering the pressure drops in both high and low temperature heat exchangers, and the system is to provide a fixed heating load. Conventional exergy analysis orderly suggests a compressor, expansion valve, gas cooler and ground heat exchanger to be considered for system improvement, while tracing exergy destruction of all components in detail demonstrates true improvement potential of each and all components and the system as a whole and offers a different order. Advanced exergy analysis points out that the compressor is directly and indirectly responsible for 56% of the overall exergy destruction generated in the cycle, confirming the detrimental role of this component in the system. The second influential component is recognized to be a ground heat exchanger accounting for 20% exergy destruction of the compressor as well as submitting 89% avoidability in its own exergy destruction, and expansion valve proves to be the last option for system improvement according to this analysis.
Approaches for FPGA Design Assurance
Authors: Cahill Eli , Hutchings Brad , Goeders Jeffrey
Published: December 2021

Field-Programmable Gate Arrays (FPGAs) are widely used for custom hardware implementations, including in many security-sensitive industries, such as defense, communications, transportation, medical, and more. Compiling source hardware descriptions to FPGA bitstreams requires the use of complex computer-aided design (CAD) tools. These tools are typically proprietary and closed-source, and it is not possible to easily determine that the produced bitstream is equivalent to the source design.

In this work, we present various FPGA design flows that leverage pre-synthesizing or pre-implementing parts of the design, combined with open-source synthesis tools, bitstream-to-netlist tools, and commercial equivalence-checking tools, to verify that a produced hardware design is equivalent to the designer’s source design.

We evaluate these different design flows on several benchmark circuits and demonstrate that they are effective at detecting malicious modifications made to the design during compilation. We compare our proposed design flows with baseline commercial design flows and measure the overheads to area and runtime.
Research into Teachers’ (Dis)Respect for Learners: A Cross-Cultural Study of English Language Teachers’ and Learners’ Perceptions
Authors: Mostafaei Alaei Mahnaz , Forough Ameri Amirhamid
Published: December 2021

A safe learning context begins with teachers-students respectful interaction. This qualitative study drawing on the premises of grounded theory (GT) examined native and nonnative English language teachers’ and learners’ (n = 114) perceptions of teachers’ (dis)respect for learners. Content analysis of focus groups and online interviews revealed three overarching themes: (1) teachers’ interpersonal characteristics, (2) teachers’ insightfulness, and (3) teachers’ occupational attributes. Overall, 14 subthemes emerged. An important finding was that politeness, learners’ self-esteem, and care were the most recurrent subthemes, respectively, raised by all four groups of nonnative teachers (NNTs), nonnative learners (NNLs), native teachers (NTs), and native learners (NLs). Moreover, politeness, care, learners’ self-esteem, dedication, and interest were the five culture-general components of teachers’ (dis)respect for learners because they were mentioned by both natives and nonnatives. Conversely, other subthemes could be considered as culture-specific components because they were raised by either natives (fairness, encouragement, appreciativeness, kindness, punctuality, and learners’ freedom) or nonnatives (helpfulness, patience, and learners’ individuality). Furthermore, the three above-mentioned themes were common to all participants. Therefore, given this diversity within universality, we proposed a cross-cultural model of teachers’ (dis)respect. The pedagogical implications are discussed.
A New Fault Diagnosis Model for Circuits in Railway Vehicle Based on the Principal Component Analysis and the Belief Rule Base
Authors: Wu Hao , Zhang Bangcheng , Gao Zhi , Chen Siyu , Bu Qianying
Published: December 2021

Circuits are considered an important part of railway vehicles, and circuit fault diagnosis in the railway vehicle is also a research hotspot. In view of the nonlinearity and diversity of track circuit components, as well as the diversity and similarity of fault phenomena, in this paper, a new fault diagnosis model for circuits based on the principal component analysis (PCA) and the belief rule base (BRB) is proposed, which overcomes the shortcomings of the circuit fault diagnosis method based on data, model, and knowledge. In the proposed model, to simplify the model and improve the accuracy, PCA is used to reduce the dimension of the key fault features, and varimax rotation is used to deduce the fault features. BRB is used to combine qualitative knowledge and quantitative data effectively, and evidential reasoning (ER) algorithm is used to carry out the inference of knowledge. The initial parameters of the model are optimized, and the optimal precondition attributes, rule weights, and belief degree parameters are obtained to improve the accuracy. Through the training and testing of the model, the experimental results show that the method can accurately diagnose the fault of the driver controller potentiometer in the railway vehicle. Compared with other methods, the model shows high accuracy.
Study on PD-L1 Expression in NSCLC Patients and Related Influencing Factors in the Real World
Authors: Zhu Yefei , Lin Shuangxiang , Wang Yueping , Shen Bingxiao , Lin Ling , Wang Liangxing , He Susu
Published: December 2021

PD-L1 is one of the current biomarkers for immune checkpoint inhibitor (ICI) therapy in patients with non-small-cell lung cancer. However, the expression of PD-L1 in the real world and its related influencing factors remain unclear. We want to observe the expression of PD-L1 in the real world and study the related influencing factors through the collection and analysis of clinical data. R software (version 4.0) was used to perform data analysis and the “corplot” package for correlation analysis. A total of 296 individuals (mean [SD] age, 67 [9] years; 23%female) were assessed. According to the expression amount of PD-L1, the cohort was divided into low nonexpression group (

PD
‐
L
1
<
1
%

, 26.7%), low-expression group (

1
%
≤
PD
‐
L
1
<
50
%

, 49.3%), and high-expression group (

PD
‐
L
1
≥
50
%

, 23.5%). Age, gender, underlying diseases, smoking status, and PD-L1 expression level were not statistically significant. We found that the expression of PD-L1 was correlated with serum albumin (

P
<
0.05

) and pathological type (

P
<
0.05

) and had a negative correlation with EGFR mutation but did not correlate with gender, age, smoking status, combined with underlying diseases, tumor stage, whether it was initially treated or not, sampling site, specimen type, specimen storage time, R-IFN, CD4, CD8, NLR, CRP, and LDH. The present findings indicated that serum albumin, pathological type, and EGFR mutations are associated with PD-L1 expression in patients with NSCLC, which may provide a new basis for individualized immunotherapy and need further study to confirm. The results of this study help to further reveal the actual expression of PD-L1 in non-small-cell lung cancer patients with real events.
Design of Higher Education System Based on Artificial Intelligence Technology
Authors: Li Jun , Li Jiye , Yang Yazhi , Ren Zhaoxu
Published: December 2021

In order to solve the problems of low security and response efficiency and slow running speed of the current designed higher education system, a higher education system based on artificial intelligence technology is designed. Firstly, according to the characteristics of artificial intelligence technology, intelligent teaching system, agent technology, and data mining technology are introduced in detail. Then it analyzes the overall and detailed functional requirements of the system and adaptively generates knowledge content and teaching mode suitable for students’ ability and personality by using intelligent reasoning ability and the collection and analysis of students’ personality characteristics. Through data mining of intelligent teaching system, the decision tree about curriculum is obtained, and the students’ cognitive ability is calculated. Based on the theory of cognitive science, using the “double master” teaching mode, combined with agent technology and intelligent teaching system, the system function is divided into six modules. Through the design of database structure and data table, the design of higher education system based on artificial intelligence technology is realized. The experimental results show that the proposed method has high security and response efficiency, fast running speed, and good teaching effect.
Downregulated Expression of miRNA-130a-5p Aggravates Hepatoma Progression via Targeting PTP4A2
Authors: Shi Longqing , Wang Fengbo , Zhang Yue , Yang Yue , Qu Zheng , Sun Donglin
Published: December 2021

Background. Hepatoma is a leading cause of death worldwide, with high metastasis and recurrence rates. The aberrant expression of miRNA-130a-5p is involved in the development and progression of various cancers. However, there are no studies investigating the role of miRNA-130a-5p in hepatoma. The present study is aimed at clarifying the functional role of miRNA-130a-5p in hepatoma progression. Methods. The expression levels of miRNA-130a-5p in hepatoma tissues and cell lines were detected by qRT-PCR assays. Bioinformatic analysis, gain-/loss-of-function experiments, and luciferase activity assays were conducted to verify whether miRNA-130a-5p is targeted by protein tyrosine phosphatase 4A2 (PTP4A2). The functions of miRNA-130a-5p and PTP4A2 in hepatoma were determined by cell proliferation assays. Results. The expression of miRNA-130a-5p was downregulated in hepatoma tissues and was related to poor prognosis. However, the expression level of PTP4A2 was contradictory to that of miRNA-130a-5p, and PTP4A2 upregulation could aggravate hepatoma progression. The ectopic overexpression of PTP4A2 promoted hepatoma cell proliferation in vitro, which could be reversed by miRNA-130a-5p. Conclusions. Our study implies that miRNA-130a-5p, which is downregulated in hepatoma tissues, can suppress hepatoma cell proliferation via targeting PTP4A2.
A Decision Support System for Power Components Based on Improved YOLOv4-Tiny
Authors: Tian Yangyang , Mao Wandeng , Yuan Shaoguang , Wan Diming , Chen Yuanhui
Published: December 2021

The traditional image object detection algorithm applied in power inspection cannot effectively position power components, and the accuracy of recognition is low in scenes with some interference. In this research, we proposed a data-driven power detection method based on the improved YOLOv4-tiny model, which combined the ResNet-D module and the adjusted Res-CBAM to the backbone network of the existing YOLOv4-tiny module. We replaced the CSPOSANet module in the YOLOv4-tiny backbone network with the ResNet-D module to reduce the FLOPS required by the model. At the same time, the adjusted Res-CBAM whose feature fusion ways were replaced with stacking in the channels was combined as an auxiliary classifier. Finally, the features of five different receptive scales were used for prediction, and the display of the results was optimized by merging the prediction boxes. In the experiment, 57134 images collected on the power inspection line were processed and labeled, and the default anchor boxes were re-clustered, and the speed and accuracy of the model were evaluated by video and validation set of 3459 images. Processing multiple pictures and videos collected from the power inspection projects, we re-clustered the default anchor box and tested the speed and accuracy of the model. The results show that compared with the original YOLOv4-tiny model, the accuracy of our method that can position objects under occlusion and complex lighting conditions is guaranteed while the detection speed is about 13% faster.
Modular Irregular Labeling on Double-Star and Friendship Graphs
Authors: Sugeng K. A. , Barack Z. Z. , Hinding N. , Simanjuntak R.
Published: December 2021

A modular irregular graph is a graph that admits a modular irregular labeling. A modular irregular labeling of a graph

G

of order

n

is a mapping of the set of edges of the graph to

1,2
,
…
,
k

such that the weights of all vertices are different. The vertex weight is the sum of its incident edge labels, and all vertex weights are calculated with the sum modulo

n

. The modular irregularity strength is the minimum largest edge label such that a modular irregular labeling can be done. In this paper, we construct a modular irregular labeling of two classes of graphs that are biregular; in this case, the regular double-star graph and friendship graph classes are chosen. Since the modular irregularity strength of the friendship graph also holds the minimal irregularity strength, then the labeling is also an irregular labeling with the same strength as the modular case.
Building a Discourse‐Argument Hybrid System for Vietnamese Why‐Question Answering
Authors: Nguyen Chinh Trong , Nguyen Dang Tuan
Published: December 2021

Recently, many deep learning models have archived high results in question answering task with overall F1scores above 0.88 on SQuAD datasets. However, many of these models have quite low F1scores on why‐questions. These F1scores range from 0.57 to 0.7 on SQuAD v1.1 development set. This means these models are more appropriate to the extraction of answers for factoid questions than for why‐questions. Why‐questions are asked when explanations are needed. These explanations are possibly arguments or simply subjective opinions. Therefore, we propose an approach to finding the answer for why‐question using discourse analysis and natural language inference. In our approach, natural language inference is applied to identify implicit arguments at sentence level. It is also applied in sentence similarity calculation. Discourse analysis is applied to identify the explicit arguments and the opinions at sentence level in documents. The results from these two methods are the answer candidates to be selected as the final answer for each why‐question. We also implement a system with our approach. Our system can provide an answer for a why‐question and a document as in reading comprehension test. We test our system with a Vietnamese translated test set which contains all why‐questions of SQuAD v1.1 development set. The test results show that our system cannot beat a deep learning model in F1score; however, our system can answer more questions (answer rate of 77.0%) than the deep learning model (answer rate of 61.0%).
Evaluation Algorithm of Ecological Energy-Saving Effect of Green Buildings Based on Gray Correlation Degree
Authors: Wang Chongyu
Published: December 2021

The environmental protection attribute and energy-saving level of green buildings cannot be described by the traditional evaluation model. In order to solve the above problems, a new ecological energy-saving effect evaluation algorithm of green buildings based on gray correlation degree is designed. Based on the framework of building energy-saving index system, the environmental protection evaluation standards are divided and the results are used to screen the energy-saving indexes, so as to complete the establishment of green building ecological energy-saving index system and standards. Then, the evaluation set is established, and the evaluation scale of each layer of indicators is accurately located according to the weight value of each index. On this basis, the membership matrix is constructed. By calculating the index weight and determining the fuzzy synthesis operator, the rating process of the algorithm is improved and the analysis of the evaluation algorithm of environmental protection and energy conservation indicators of green building materials based on gray correlation degree is realized. The experimental results show that the designed algorithm has good stability of the fitting curve, can save energy, and has low cost.
On the Properties of the New Generalized Pareto Distribution and Its Applications
Authors: Salahuddin Najma , Khalil Alamgir , Mashwani Wali Khan , Alrajhi Sharifah , Al-Marzouki Sanaa , Shah Kamal
Published: December 2021

In this paper, a new generalization of the Generalized Pareto distribution is proposed using the generator suggested in [1], named as Khalil Extended Generalized Pareto (KEGP) distribution. Various shapes of the suggested model and important mathematical properties are investigated that includes moments, quantile function, moment-generating function, measures of entropy, and order statistics. Parametric estimation of the model is discussed using the technique of maximum likelihood. A simulation study is performed for the assessment of the maximum likelihood estimates in terms of their bias and mean squared error using simulated sample estimates. The practical applications are illustrated via two real data sets from survival and reliability theory. The suggested model provided better fits than the other considered models.