scholarly journals Recent advances in immunoassays and biosensors for mycotoxins detection in feedstuffs and foods

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Runxian Li ◽  
Yang Wen ◽  
Fenglai Wang ◽  
Pingli He
Keyword(s):  
Signal Transduction ◽  
Rapid Detection ◽  
Recent Progress ◽  
Future Trend ◽  
Detection Methods ◽  
Sensor Technology ◽  
Future Research ◽  
Advanced Material ◽  
Different Types ◽  
Detection Strategies

AbstractMycotoxins are secondary metabolites produced by fungus. Many mycotoxin species are highly toxic and are frequently found in cereals and feedstuffs. So, powerful detection methods are vital and effective ways to prevent feed contamination. Traditional detection methods can no longer meet the needs of massive, real-time, simple, and fast mycotoxin monitoring. Rapid detection methods based on advanced material and sensor technology are the future trend. In this review, we highlight recent progress of mycotoxin rapid detection strategies in feedstuffs and foods, especially for simultaneous multiplex mycotoxin determination. Immunoassays, biosensors, and the prominent roles of nanomaterials are introduced. The principles of different types of recognition and signal transduction are explained, and the merits and pitfalls of these methods are compared. Furthermore, limitations and challenges of existing rapid sensing strategies and perspectives of future research are discussed.

scholarly journals Overview of Rapid Detection Methods for Salmonella in Foods: Progress and Challenges

Foods ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 2402
Author(s):  
Minglu Wang ◽  
Yilun Zhang ◽  
Fangyuan Tian ◽  
Xiaoyu Liu ◽  
Shuyuan Du ◽  
...  
Keyword(s):  
Signal Transduction ◽  
Rapid Detection ◽  
Food Production ◽  
Detection Methods ◽  
Consumer Health ◽  
High Prevalence ◽  
Transduction Mechanisms ◽  
Recognition Elements ◽  
New Perspective ◽  
Shed Light

Salmonella contamination in food production and processing is a serious threat to consumer health. More and more rapid detection methods have been proposed to compensate for the inefficiency of traditional bacterial cultures to suppress the high prevalence of Salmonella more efficiently. The contamination of Salmonella in foods can be identified by recognition elements and screened using rapid detection methods with different measurable signals (optical, electrical, etc.). Therefore, the different signal transduction mechanisms and Salmonella recognition elements are the key of the sensitivity, accuracy and specificity for the rapid detection methods. In this review, the bioreceptors for Salmonella were firstly summarized and described, then the current promising Salmonella rapid detection methods in foodstuffs with different signal transduction were objectively summarized and evaluated. Moreover, the challenges faced by these methods in practical monitoring and the development prospect were also emphasized to shed light on a new perspective for the Salmonella rapid detection methods applications.

scholarly journals Methods of Detecting Insufficient Effort Responding: Comparisons and Practical Recommendations

2019 ◽  
Vol 80 (2) ◽  
pp. 312-345 ◽  
Author(s):  
Maxwell Hong ◽  
Jeffrey T. Steedle ◽  
Ying Cheng
Keyword(s):  
Psychometric Properties ◽  
Detection Methods ◽  
Future Research ◽  
Validity And Reliability ◽  
Multiple Sources ◽  
Research Directions ◽  
Different Types ◽  
Future Research Directions ◽  
Biased Responding ◽  
Practical Recommendations

Insufficient effort responding (IER) affects many forms of assessment in both educational and psychological contexts. Much research has examined different types of IER, IER’s impact on the psychometric properties of test scores, and preprocessing procedures used to detect IER. However, there is a gap in the literature in terms of practical advice for applied researchers and psychometricians when evaluating multiple sources of IER evidence, including the best strategy or combination of strategies when preprocessing data. In this study, we demonstrate how the use of different IER detection methods may affect psychometric properties such as predictive validity and reliability. Moreover, we evaluate how different data cleansing procedures can detect different types of IER. We provide evidence via simulation studies and applied analysis using the ACT’s Engage assessment as a motivating example. Based on the findings of the study, we provide recommendations and future research directions for those who suspect their data may contain responses reflecting careless, random, or biased responding.

Overview of Subsynchronous Oscillation in Grid-connected Wind Farm

2020 ◽  
Vol 13 (7) ◽  
pp. 969-979
Author(s):  
Xu Pei-Zhen ◽  
Lu Yong-Geng ◽  
Cao Xi-Min
Keyword(s):  
Power Systems ◽  
Wind Turbine ◽  
Large Scale ◽  
Wind Farm ◽  
Wind Farms ◽  
Induction Generator ◽  
Future Research ◽  
Stable Operation ◽  
Subsynchronous Oscillation ◽  
Different Types

Background: Over the past few years, the subsynchronous oscillation (SSO) caused by the grid-connected wind farm had a bad influence on the stable operation of the system and has now become a bottleneck factor restricting the efficient utilization of wind power. How to mitigate and suppress the phenomenon of SSO of wind farms has become the focus of power system research. Methods: This paper first analyzes the SSO of different types of wind turbines, including squirrelcage induction generator based wind turbine (SCIG-WT), permanent magnet synchronous generator- based wind turbine (PMSG-WT), and doubly-fed induction generator based wind turbine (DFIG-WT). Then, the mechanisms of different types of SSO are proposed with the aim to better understand SSO in large-scale wind integrated power systems, and the main analytical methods suitable for studying the SSO of wind farms are summarized. Results: On the basis of results, using additional damping control suppression methods to solve SSO caused by the flexible power transmission devices and the wind turbine converter is recommended. Conclusion: The current development direction of the SSO of large-scale wind farm grid-connected systems is summarized and the current challenges and recommendations for future research and development are discussed.

Antecedents and Consequences of Gossip in Work Groups

2019 ◽  
pp. 416-434
Author(s):  
Bianca Beersma ◽  
Gerben A. van Kleef ◽  
Maria T. M. Dijkstra
Keyword(s):  
Social Order ◽  
Information Exchange ◽  
Work Groups ◽  
Psychological Theory ◽  
Future Research ◽  
Group Norms ◽  
Group Effectiveness ◽  
Interpersonal Aggression ◽  
Different Types ◽  
Antecedents And Consequences

This chapter provides an overview of the antecedents and consequences of gossip in work groups. First, the chapter reviews the different motives for gossip in work groups (i.e., bonding, entertainment, emotional venting, information exchange, maintenance of group norms/social order, and interpersonal aggression) and links each motive to psychological theory. Second, the chapter reviews the different types of influence that gossip can have on various indicators of group effectiveness. Reflecting on the motives underlying gossip in work groups, as well as on its outcomes, it argues that future research should start integrating the diverse insights provided by earlier research on both gossip motives and outcomes, and it provides a number of suggestions for doing so.

scholarly journals Advantages and potential challenges of data management in e-maintenance

2019 ◽  
Vol 25 (3) ◽  
pp. 378-396 ◽  
Author(s):  
Arian Razmi-Farooji ◽  
Hanna Kropsu-Vehkaperä ◽  
Janne Härkönen ◽  
Harri Haapasalo
Keyword(s):  
Data Management ◽  
Design Methodology ◽  
Management Practices ◽  
Future Research ◽  
Conceptual Approach ◽  
Content Type ◽  
Different Types ◽  
Maintenance Systems ◽  
Industry Leader ◽  
Practical Implications

Purpose The purpose of this paper is twofold: first, to understand data management challenges in e-maintenance systems from a holistically viewpoint through summarizing the earlier scattered research in the field, and second, to present a conceptual approach for addressing these challenges in practice. Design/methodology/approach The study is realized as a combination of a literature review and by the means of analyzing the practices on an industry leader in manufacturing and maintenance services. Findings This research provides a general understanding over data management challenges in e-maintenance and summarizes their associated proposed solutions. In addition, this paper lists and exemplifies different types and sources of data which can be collected in e-maintenance, across different organizational levels. Analyzing the data management practices of an e-maintenance industry leader provides a conceptual approach to address identified challenges in practice. Research limitations/implications Since this paper is based on studying the practices of a single company, it might be limited to generalize the results. Future research topics can focus on each of mentioned data management challenges and also validate the applicability of presented model in other companies and industries. Practical implications Understanding the e-maintenance-related challenges helps maintenance managers and other involved stakeholders in e-maintenance systems to better solve the challenges. Originality/value The so-far literature on e-maintenance has been studied with narrow focus to data and data management in e-maintenance appears as one of the less studied topics in the literature. This research paper contributes to e-maintenance by highlighting the deficiencies of the discussion surrounding the perspectives of data management in e-maintenance by studying all common data management challenges and listing different types of data which need to be acquired in e-maintenance systems.

scholarly journals Advances in Forest Robotics: A State-of-the-Art Survey

Robotics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 53
Author(s):  
Luiz F. P. Oliveira ◽  
António P. Moreira ◽  
Manuel F. Silva
Keyword(s):  
Future Research ◽  
Navigation Systems ◽  
Public And Private ◽  
Environmental Preservation ◽  
The Public ◽  
Forest Exploitation ◽  
Different Types ◽  
Scientific Papers ◽  
Great Relevance ◽  
Robotic Applications

The development of robotic systems to operate in forest environments is of great relevance for the public and private sectors. In this sense, this article reviews several scientific papers, research projects and commercial products related to robotic applications for environmental preservation, monitoring, wildfire firefighting, inventory operations, planting, pruning and harvesting. After conducting critical analysis, the main characteristics observed were: (a) the locomotion system is directly affected by the type of environmental monitoring to be performed; (b) different reasons for pruning result in different locomotion and cutting systems; (c) each type of forest, in each season and each type of soil can directly interfere with the navigation technique used; and (d) the integration of the concept of swarm of robots with robots of different types of locomotion systems (land, air or sea) can compensate for the time of executing tasks in unstructured environments. Two major areas are proposed for future research works: Internet of Things (IoT)-based smart forest and navigation systems. It is expected that, with the various characteristics exposed in this paper, the current robotic forest systems will be improved, so that forest exploitation becomes more efficient and sustainable.

Development of an antigen-ELISA and a colloidal gold–based immunochromatographic strip based on monoclonal antibodies for detection of avian influenza A(H5) viruses

2021 ◽  
pp. 104063872110275
Author(s):  
Yixin Xiao ◽  
Fan Yang ◽  
Fumin Liu ◽  
Linfang Cheng ◽  
Hangping Yao ◽  
...  
Keyword(s):  
Avian Influenza ◽  
Disease Virus ◽  
Colloidal Gold ◽  
Rapid Detection ◽  
Influenza A ◽  
Field Investigation ◽  
Cross Reactivity ◽  
Detection Methods ◽  
Immunochromatographic Strip ◽  
Antigen Elisa

Avian influenza A(H5) viruses (avian IAVs) pose a major threat to the economy and public health. We developed an antigen-ELISA (ag-ELISA) and a colloidal gold–based immunochromatographic strip for the rapid detection of avian A(H5) viruses. Both detection methods displayed no cross-reactivity with other viruses (e.g., other avian IAVs, infectious bursal disease virus, Newcastle disease virus, infectious bronchitis virus, avian paramyxovirus). The ag-ELISA was sensitive down to 0.5 hemagglutinin (HA) units/100 µL of avian A(H5) viruses and 7.5 ng/mL of purified H5 HA proteins. The immunochromatographic strip was sensitive down to 1 HA unit/100 µL of avian A(H5) viruses. Both detection methods exhibited good reproducibility with CVs < 10%. For 200 random poultry samples, the sensitivity and specificity of the ag-ELISA were 92.6% and 98.8%, respectively, and for test strips were 88.9% and 98.3%, respectively. Both detection methods displayed high specificity, sensitivity, and stability, making them suitable for rapid detection and field investigation of avian A(H5) viruses.

scholarly journals Recent Progress of Fluxgate Magnetic Sensors: Basic Research and Application

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1500
Author(s):  
Songrui Wei ◽  
Xiaoqi Liao ◽  
Han Zhang ◽  
Jianhua Pang ◽  
Yan Zhou
Keyword(s):  
Recent Progress ◽  
Electronic Devices ◽  
Basic Research ◽  
Research Direction ◽  
Magnetic Sensor ◽  
Magnetic Sensors ◽  
Future Research ◽  
Calibration Methods ◽  
Wearable Electronic ◽  
Wearable Electronic Devices

Fluxgate magnetic sensors are especially important in detecting weak magnetic fields. The mechanism of a fluxgate magnetic sensor is based on Faraday’s law of electromagnetic induction. The structure of a fluxgate magnetic sensor mainly consists of excitation windings, core and sensing windings, similar to the structure of a transformer. To date, they have been applied to many fields such as geophysics and astro-observations, wearable electronic devices and non-destructive testing. In this review, we report the recent progress in both the basic research and applications of fluxgate magnetic sensors, especially in the past two years. Regarding the basic research, we focus on the progress in lowering the noise, better calibration methods and increasing the sensitivity. Concerning applications, we introduce recent work about fluxgate magnetometers on spacecraft, unmanned aerial vehicles, wearable electronic devices and defect detection in coiled tubing. Based on the above work, we hope that we can have a clearer prospect about the future research direction of fluxgate magnetic sensor.

scholarly journals A Survey on Deep Learning Based Methods and Datasets for Monocular 3D Object Detection

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 517
Author(s):  
Seong-heum Kim ◽  
Youngbae Hwang
Keyword(s):  
Deep Learning ◽  
Object Detection ◽  
Low Cost ◽  
Detection Methods ◽  
Future Research ◽  
3D Object ◽  
Practical Applications ◽  
Depth Sensors ◽  
Significant Research ◽  
3D Object Detection

Owing to recent advancements in deep learning methods and relevant databases, it is becoming increasingly easier to recognize 3D objects using only RGB images from single viewpoints. This study investigates the major breakthroughs and current progress in deep learning-based monocular 3D object detection. For relatively low-cost data acquisition systems without depth sensors or cameras at multiple viewpoints, we first consider existing databases with 2D RGB photos and their relevant attributes. Based on this simple sensor modality for practical applications, deep learning-based monocular 3D object detection methods that overcome significant research challenges are categorized and summarized. We present the key concepts and detailed descriptions of representative single-stage and multiple-stage detection solutions. In addition, we discuss the effectiveness of the detection models on their baseline benchmarks. Finally, we explore several directions for future research on monocular 3D object detection.

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