scholarly journals Infrared light sensors permit rapid recording of wingbeat frequency and bioacoustic species identification of mosquitoes

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Dongmin Kim ◽  
Terry J. DeBriere ◽  
Satish Cherukumalli ◽  
Gregory S. White ◽  
Nathan D. Burkett-Cadena
Keyword(s):  
Optical Sensors ◽  
Mosquito Species ◽  
Infrared Light ◽  
Identification System ◽  
Automated Identification ◽  
Vector Surveillance ◽  
Wingbeat Frequency ◽  
Simple Method ◽  
Species Overlap ◽  
Vector Borne

AbstractRecognition and classification of mosquitoes is a critical component of vector-borne disease management. Vector surveillance, based on wingbeat frequency and other parameters, is becoming increasingly important in the development of automated identification systems, but inconsistent data quality and results frequently emerge from different techniques and data processing methods which have not been standardized on wingbeat collection of numerous species. We developed a simple method to detect and record mosquito wingbeat by multi-dimensional optical sensors and collected 21,825 wingbeat files from 29 North American mosquito species. In pairwise comparisons, wingbeat frequency of twenty six species overlapped with at least one other species. No significant differences were observed in wingbeat frequencies between and within individuals of Culex quinquefasciatus over time. This work demonstrates the potential utility of quantifying mosquito wingbeat frequency by infrared light sensors as a component of an automated mosquito identification system. Due to species overlap, wingbeat frequency will need to integrate with other parameters to accurately delineate species in support of efficient mosquito surveillance, an important component of disease intervention.

scholarly journals The Role of Mosquito Surveillance in Monitoring Arboviral Infections in Croatia

2020 ◽  
Vol 39 (1) ◽  
pp. 15-22
Author(s):  
Nataša Janev Holcer ◽  
Krunoslav Capak ◽  
Tatjana Vilibić-Čavlek ◽  
Pavle Jeličić ◽  
Lovro Bucić
Keyword(s):  
Public Health ◽  
Detection System ◽  
Mosquito Species ◽  
National Level ◽  
Virus Detection ◽  
Monitoring And Evaluation ◽  
Legal Framework ◽  
Vector Surveillance ◽  
Vector Borne Diseases ◽  
Vector Borne

In accordance with the noticed growing trend in the number of vector-borne disease cases, the extent of public health significance of this problem is also increasing. However, the strengthening of capacities for suppression of these outbreaks is present. With the aim of protecting population from arbovirus infections, there is a need for continuous monitoring and evaluation of risk factors related to vectors and vector borne diseases and human health, for which data is acquired through monitoring programs. In order to address these issues, several activities must be integrated and taken into consideration: vector surveillance, entomological activity, early detection system, preventive measures, counter-epidemic measures and virus detection in vectors, reservoirs or infected animals. There is a legal framework regarding mosquito monitoring on a local, as well as national level. Additionally, at the initiative of the Croatian Institute of Public Health, invasive mosquito species monitoring is being implemented and continuously conducted since 2016.

scholarly journals Increased Adult Aedes aegypti and Culex quinquefasciatus (Diptera: Culicidae) Abundance in a Dengue Transmission Hotspot, Compared to a Coldspot, within Kaohsiung City, Taiwan

Insects ◽  
2018 ◽  
Vol 9 (3) ◽  
pp. 98 ◽  
Author(s):  
Ka-Chon Ng ◽  
Luis Chaves ◽  
Kun-Hsien Tsai ◽  
Ting-Wu Chuang
Keyword(s):  
Aedes Aegypti ◽  
Culex Quinquefasciatus ◽  
Disease Transmission ◽  
Mosquito Species ◽  
Comparative Approach ◽  
Vector Surveillance ◽  
Mosquito Abundance ◽  
Dengue Transmission ◽  
Vector Borne ◽  
Kaohsiung City

The assumption that vector abundance differences might drive spatial and temporal heterogeneities in vector-borne disease transmission is common, though data supporting it is scarce. Here, we present data from two common mosquito species Aedes aegypti (Linnaeus) and Culex quinquefasciatus Say, biweekly sampled as adults, from March 2016 through December 2017, with BG-sentinel traps in two neighboring districts of Kaohsiung City (KC), Taiwan. One district has historically been a dengue transmission hotspot (Sanmin), and the other a coldspot (Nanzih). We collected a total 41,027 mosquitoes, and we found that average mosquito abundance (mean ± S.D.) was higher in Sanmin (Ae. aegypti: 9.03 ± 1.46; Cx. quinquefasciatus: 142.57 ± 14.38) than Nanzih (Ae. aegypti: 6.21 ± 0.47; Cx. quinquefasciatus: 63.37 ± 8.71) during the study period. In both districts, Ae. aegypti and Cx. quinquefasciatus population dynamics were sensitive to changes in temperature, the most platykurtic environmental variable at KC during the study period, a pattern predicted by Schmalhausen’s law, which states that organisms are more sensitive to small changes in environmental variables whose average value is more uncertain than its extremes. Our results also suggest that differences in Ae. aegypti abundance might be responsible for spatial differences in dengue transmission at KC. Our comparative approach, where we also observed a significant increment in the abundance of Cx. quinquefasciatus in the dengue transmission hotspot, suggests this area might be more likely to experience outbreaks of other vector borne diseases and should become a primary focus for vector surveillance and control.

The Scientific Basis for the Prevention of Zooanthroponoze Vector-Borne Diseases Spread by Parasitic Arthropods of the Center of the East European Plain

2020 ◽  
Vol 14 (1) ◽  
pp. 81-88
Author(s):  
Fedor I. Vasilevich ◽  
Anna M. Nikanorova
Keyword(s):  
Mathematical Models ◽  
Culex Pipiens ◽  
Preventive Measures ◽  
Mosquito Species ◽  
Natural Habitat ◽  
Piperonyl Butoxide ◽  
East European Plain ◽  
Vector Borne Diseases ◽  
Vector Borne ◽  
Kaluga Region

The purpose of the research is development of preventive measures against zooanthroponoze vector-borne diseases spread by parasitic arthropods in the Kaluga Region. Materials and methods. The subject of the research was Ixodidae, mosquitoes, and small mammals inhabiting the Kaluga Region. The census of parasitic arthropods was carried out on the territory of all districts of the Kaluga Region and the city of Kaluga. Open natural habitat and human settlements were investigated. Weather conditions from 2013 to 2018 were also taken into account. For the purposes of the study, we used standard methods for capturing and counting arthropods and mouse-like rodents. In order to obtain mathematical models of small mammal populations, a full factorial experiment was conducted using the collected statistical data. In-process testing of the drug based on s-fenvalerate and piperonyl butoxide were carried out under the conditions of the agricultural collective farm “Niva” of the Kozelsky District, the Kaluga Region, and LLC “Angus Center of Genetics” of the Babyninsky District, the Kaluga Region. Results and discussion. In the Kaluga Region, two species of ixodic ticks are found, namely, Ixodes ricinus and Dermacentor reticulatus, which have two activity peaks. Mosquito may have 3-4 generations in a year in the Kaluga region. The most common mosquito species in the Kaluga Region are Aedes communis, Ae. (Och.) togoi and Ae. (Och.) diantaeus, Culex pipiens Culex Linnaeus, 1758 (Diptera, Culicidae) (Culex pipiens): Cx. pipiens f. pipiens L. (non-autogenic form) and Cx. p. f. molestus Fors. (autogenic form), which interbreed, and reproductively isolated in the Region. The developed mathematical models make it possible to quantify the risks of outbreaks of zooanthroponoze vector-borne diseases without the cost of field research, and allow for rational, timely and effective preventive measures. Medications based on s-fenvalerate and piperonyl butoxide and based on cyfluthrin showed high insecto-acaricidal efficacy and safety.

scholarly journals Marine Network Protocols and Security Risks

2021 ◽  
Vol 1 (2) ◽  
pp. 239-251
Author(s):  
Ky Tran ◽  
Sid Keene ◽  
Erik Fretheim ◽  
Michail Tsikerdekis
Keyword(s):  
Network Protocols ◽  
Network Protocol ◽  
Identification System ◽  
Automated Identification ◽  
Security Risks ◽  
Domain Specific ◽  
Protocol Security ◽  
Challenges And Opportunities

Marine network protocols are domain-specific network protocols that aim to incorporate particular features within the specialized marine context that devices are implemented in. Devices implemented in such vessels involve critical equipment; however, limited research exists for marine network protocol security. In this paper, we provide an analysis of several marine network protocols used in today’s vessels and provide a classification of attack risks. Several protocols involve known security limitations, such as Automated Identification System (AIS) and National Marine Electronic Association (NMEA) 0183, while newer protocols, such as OneNet provide more security hardiness. We further identify several challenges and opportunities for future implementations of such protocols.

scholarly journals Listerial meningitis: Atypical strain and misidentification by the automated identification system (Vitek2)

2019 ◽  
Vol 75 (1) ◽  
pp. 99-101
Author(s):  
Gurpreet Singh Bhalla ◽  
Mahadevan Kumar ◽  
Pooja Mahajan ◽  
Kavita Sahai
Keyword(s):  
Identification System ◽  
Automated Identification

scholarly journals Development and Validation of a Three-Dimensional Printed Multifunctional Trap for Surveillance of Mosquitoes

2021 ◽  
Vol 37 (2) ◽  
pp. 68-75
Author(s):  
Drew David Reinbold-Wasson ◽  
Michael Hay Reiskind
Keyword(s):  
Mosquito Species ◽  
Three Dimensional ◽  
Cost Effective ◽  
Disease Monitoring ◽  
Life History Stage ◽  
Mosquito Trap ◽  
Host Seeking ◽  
Vector Borne ◽  
Development And Validation ◽  
Better Than

ABSTRACT An essential component of vector-borne disease monitoring programs is mosquito surveillance. Surveillance efforts employ various collection traps depending on mosquito species and targeted life-history stage, i.e., eggs, larvae, host-seeking, resting, or gravid adults. Surveillance activities often use commercial traps, sometimes modified to accept specific mosquito species attractants. The advent of widely available and affordable 3D printing technology allows the construction of novel trap designs and components. The study goal was to develop and assess a cost-effective, multipurpose, 6-volt mosquito trap integrating features of both host-seeking and gravid mosquito traps to collect undamaged live specimens: a multifunctional mosquito trap (MMT). We tested the MMT in comparison to commercial traps, targeting gravid Aedes albopictus, host-seeking Ae. albopictus, and total number of host-seeking mosquitos regardless of species. Field evaluations found the MMT performed as well as or better than comparable commercial traps. This project demonstrates an easy to construct, inexpensive, and versatile mosquito trap, potentially useful for surveying multiple mosquito species and other hematophagous insects by varying attractants into the MMT.

scholarly journals Design and Implementation of an Efficient Rose Leaf Disease Detection using K-Nearest Neighbours

2020 ◽  
Vol 9 (3) ◽  
pp. 21-27
Keyword(s):  
Plant Disease ◽  
Spot Size ◽  
Extraction Process ◽  
Disease Classification ◽  
Identification System ◽  
Automated Identification ◽  
Accurate Identification ◽  
Leaf Disease ◽  
Key Factor ◽  
Agriculture Products

Plants are prone to different diseases caused by multiple reasons like environmental conditions, light, bacteria, and fungus. These diseases always have some physical characteristics on the leaves, stems, and fruit, such as changes in natural appearance, spot, size, etc. Due to similar patterns, distinguishing and identifying category of plant disease is the most challenging task. Therefore, efficient and flawless mechanisms should be discovered earlier so that accurate identification and prevention can be performed to avoid several losses of the entire plant. Therefore, an automated identification system can be a key factor in preventing loss in the cultivation and maintaining high quality of agriculture products. This paper introduces modeling of rose plant leaf disease classification technique using feature extraction process and supervised learning mechanism. The outcome of the proposed study justifies the scope of the proposed system in terms of accuracy towards the classification of different kind of rose plant disease.

scholarly journals Real-Time Maritime Traffic Anomaly Detection Based on Sensors and History Data Embedding

Sensors ◽  
2019 ◽  
Vol 19 (17) ◽  
pp. 3782 ◽  
Author(s):  
Julius Venskus ◽  
Povilas Treigys ◽  
Jolita Bernatavičienė ◽  
Gintautas Tamulevičius ◽  
Viktor Medvedev
Keyword(s):  
Neural Network ◽  
Data Processing ◽  
Processing Time ◽  
Heavy Traffic ◽  
Sensor Data ◽  
Identification System ◽  
Automated Identification ◽  
Maritime Traffic ◽  
Abnormal Movements ◽  
The Neural Network

The automated identification system of vessel movements receives a huge amount of multivariate, heterogeneous sensor data, which should be analyzed to make a proper and timely decision on vessel movements. The large number of vessels makes it difficult and time-consuming to detect abnormalities, thus rapid response algorithms should be developed for a decision support system to identify abnormal movements of vessels in areas of heavy traffic. This paper extends the previous study on a self-organizing map application for processing of sensor stream data received by the maritime automated identification system. The more data about the vessel’s movement is registered and submitted to the algorithm, the higher the accuracy of the algorithm should be. However, the task cannot be guaranteed without using an effective retraining strategy with respect to precision and data processing time. In addition, retraining ensures the integration of the latest vessel movement data, which reflects the actual conditions and context. With a view to maintaining the quality of the results of the algorithm, data batching strategies for the neural network retraining to detect anomalies in streaming maritime traffic data were investigated. The effectiveness of strategies in terms of modeling precision and the data processing time were estimated on real sensor data. The obtained results show that the neural network retraining time can be shortened by half while the sensitivity and precision only change slightly.

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