Journal articles: 'Odor vector'

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Yan, Luchun, Chuandong Wu, and Jiemin Liu. "Visual Analysis of Odor Interaction Based on Support Vector Regression Method." Sensors 20, no. 6 (March 19, 2020): 1707. http://dx.doi.org/10.3390/s20061707.

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The complex odor interaction between odorants makes it difficult to predict the odor intensity of their mixtures. The analysis method is currently one of the factors limiting our understanding of the odor interaction laws. We used a support vector regression algorithm to establish odor intensity prediction models for binary esters, aldehydes, and aromatic hydrocarbon mixtures, respectively. The prediction accuracy to both training samples and test samples demonstrated the high prediction capacity of the support vector regression model. Then the optimized model was used to generate extra odor data by predicting the odor intensity of more simulated samples with various mixing ratios and concentration levels. Based on these olfactory measured and model predicted data, the odor interaction was analyzed in the form of contour maps. This intuitive method showed more details about the odor interaction pattern in the binary mixture. We found that that the antagonism effect was commonly observed in these binary mixtures and the interaction degree was more intense when the components’ mixing ratio was close. Meanwhile, the odor intensity level of the odor mixture barely influenced the interaction degree. The machine learning algorithms were considered promising tools in odor researches.

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Aleixandre, Manuel, Kaoru Nakazawa, and Takamichi Nakamoto. "Optimization of Modulation Methods for Solenoid Valves to Realize an Odor Generation System." Sensors 19, no. 18 (September 17, 2019): 4009. http://dx.doi.org/10.3390/s19184009.

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An artificial olfactory system coupled with an odor generation system is herein reported. The artificial olfactory system is composed of four chemical sensors consisting of quartz crystal microbalances (QCMs) coated with room temperature ionic liquids (RTILs). The sensors are interrogated by four vector network analyzers, which are used to measure the series resonant frequency and motional resistance. The odor generation system can generate eight different odors and mix them in any composition. Solenoid valves are used to switch the path and control the concentration of the different odors before blending. Two algorithms to control the solenoid valves, delta-sigma modulator, and simple pulse width modulation (PWM) are studied, optimized, and compared. Finally, the uncertainty of the odor generating system is calculated.

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Yamanaka, Takao, Nitikarn Nimsuk, and Takamichi Nakamoto. "Concurrent Recording and Regeneration of Visual and Olfactory Information Using Odor Sensor." Presence: Teleoperators and Virtual Environments 16, no. 3 (June 1, 2007): 307–17. http://dx.doi.org/10.1162/pres.16.3.307.

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In this paper, a method of concurrent recording and regeneration of visual and olfactory information is presented using electronic nose technology. To accomplish this objective, the sensor response patterns of odors in the atmosphere were measured using QCM (quartz crystal microbalance) odor sensors with partially overlapping specificities. Then the odors were identified from the response patterns using LVQ (learning vector quantization), a pattern classification algorithm of neural networks with supervised learning. Visual information, presented as a movie, was captured using a digital video camera; concurrently, odors using odor sensor responses were paired to the video. The recorded visual and olfactory information was evaluated by sensory tests to investigate the effectiveness of the proposed system. As a result, it was found that the olfactory information recorded using the proposed method was appropriate for odor regeneration associated with the movie.

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Chai, Hwa Chia, and Kek Heng Chua. "The Potential Use of Volatile Biomarkers for Malaria Diagnosis." Diagnostics 11, no. 12 (November 30, 2021): 2244. http://dx.doi.org/10.3390/diagnostics11122244.

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Pathogens may change the odor and odor-related biting behavior of the vector and host to enhance pathogen transmission. In recent years, volatile biomarker investigations have emerged to identify odors that are differentially and specifically released by pathogens and plants, or the pathogen-infected or even cancer patients. Several studies have reported odors or volatile biomarkers specifically detected from the breath and skin of malaria-infected individuals. This review will discuss the potential use of these odors or volatile biomarkers for the diagnosis of malaria. This approach not only allows for the non-invasive mean of sample collection but also opens up the opportunity to develop a biosensor for malaria diagnosis in low-resource settings.

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Robinson, Ailie, Annette O. Busula, Mirjam A. Voets, Khalid B. Beshir, John C. Caulfield, Stephen J. Powers, Niels O. Verhulst, et al. "Plasmodium-associated changes in human odor attract mosquitoes." Proceedings of the National Academy of Sciences 115, no. 18 (April 16, 2018): E4209—E4218. http://dx.doi.org/10.1073/pnas.1721610115.

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Malaria parasites (Plasmodium) can change the attractiveness of their vertebrate hosts to Anopheles vectors, leading to a greater number of vector–host contacts and increased transmission. Indeed, naturally Plasmodium-infected children have been shown to attract more mosquitoes than parasite-free children. Here, we demonstrate Plasmodium-induced increases in the attractiveness of skin odor in Kenyan children and reveal quantitative differences in the production of specific odor components in infected vs. parasite-free individuals. We found the aldehydes heptanal, octanal, and nonanal to be produced in greater amounts by infected individuals and detected by mosquito antennae. In behavioral experiments, we demonstrated that these, and other, Plasmodium-induced aldehydes enhanced the attractiveness of a synthetic odor blend mimicking “healthy” human odor. Heptanal alone increased the attractiveness of “parasite-free” natural human odor. Should the increased production of these aldehydes by Plasmodium-infected humans lead to increased mosquito biting in a natural setting, this would likely affect the transmission of malaria.

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Ogawa, Keishiro, Katsufumi Inoue, Michifumi Yoshioka, and Hidekazu Yanagimoto. "Odor Detecting Algorithm with Boundary Compensation Support Vector Machine." IEEJ Transactions on Electronics, Information and Systems 135, no. 7 (2015): 920–26. http://dx.doi.org/10.1541/ieejeiss.135.920.

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Husni, Nyayu Latifah, Siti Nurmaini, Irsyadi Yani, and Ade Silvia. "Intelligent Sensing Using Metal Oxide Semiconductor Based-on Support Vector Machine for Odor Classification." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 6 (December 1, 2018): 4133. http://dx.doi.org/10.11591/ijece.v8i6.pp4133-4147.

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Classifying odor in real experiment presents some challenges, especially the uncertainty of the odor concentration and dispersion that can lead to a difficulty in obtaining an accurate datasets. In this study, to enhance the accuracy, datasets arrangement based on MOS sensors parameters using SVM approach for odor classification is proposed. The sensors are tested to determine the sensors' time response, sensors' peak duration, sensors' sensitivity, and sensors' stability when applied to the various sources at different range. Three sources were used in experimental test, namely: ethanol, methanol, and acetone. The gas sensors characteristics are analyzed in open sampling method to see the sensors' performance in real situation. These performances are considered as the base of choosing the position in collecting the datasets. The sensors in dynamic experiment have average of precision of 93.8-97.0%, the accuracy 93.3-96.7%, and the recall 93.3-96.7%. This values indicates that the collected datasets can support the SVM in improving the intelligent sensing when conducting odor classification work.

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Mweresa, Collins K., W. R. Mukabana, J. J. A. van Loon, M. Dicke, and W. Takken. "Use of semiochemicals for surveillance and control of hematophagous insects." Chemoecology 30, no. 6 (June 23, 2020): 277–86. http://dx.doi.org/10.1007/s00049-020-00317-1.

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Abstract Reliance on broad-spectrum insecticides and chemotherapeutic agents to control hematophagous insect vectors, and their related diseases is threatened by increasing insecticide and drug resistance, respectively. Thus, development of novel, alternative, complementary and effective technologies for surveillance and control of such insects is strongly encouraged. Semiochemicals are increasingly developed for monitoring and intervention of insect crop pests, but this has not been adequately addressed for hematophagous insects of medical and veterinary importance. This review provides an insight in the application of semiochemicals for control of hematophagous insects. Here, we provide specific information regarding the isolation and identification of semiochemical compounds, optimization approaches, detection, perception and discrimination by the insect olfactory system. Navigation of insects along wind-borne odor plumes is discussed and methods of odor application in field situations are reviewed. Finally, we discuss prospects and future challenges for the application of semiochemical-based tools with emphasis on mosquitoes. The acquired knowledge can guide development of more effective components of integrated vector management, safeguard against emerging resistance of insects to existing insecticides and reduce the burden of vector-borne diseases.

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Mayer, Christoph J., Andreas Vilcinskas, and Jürgen Gross. "Phytopathogen Lures Its Insect Vector by Altering Host Plant Odor." Journal of Chemical Ecology 34, no. 8 (July 4, 2008): 1045–49. http://dx.doi.org/10.1007/s10886-008-9516-1.

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Choi, Sang-Il, and Gu-Min Jeong. "A Discriminant Distance Based Composite Vector Selection Method for Odor Classification." Sensors 14, no. 4 (April 17, 2014): 6938–51. http://dx.doi.org/10.3390/s140406938.

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Jiang, Wei, and Daqi Gao. "Five Typical Stenches Detection Using an Electronic Nose." Sensors 20, no. 9 (April 29, 2020): 2514. http://dx.doi.org/10.3390/s20092514.

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This paper deals with the classification of stenches, which can stimulate olfactory organs to discomfort people and pollute the environment. In China, the triangle odor bag method, which only depends on the state of the panelist, is widely used in determining odor concentration. In this paper, we propose a stenches detection system composed of an electronic nose and machine learning algorithms to discriminate five typical stenches. These five chemicals producing stenches are 2-phenylethyl alcohol, isovaleric acid, methylcyclopentanone, γ-undecalactone, and 2-methylindole. We will use random forest, support vector machines, backpropagation neural network, principal components analysis (PCA), and linear discriminant analysis (LDA) in this paper. The result shows that LDA (support vector machine (SVM)) has better performance in detecting the stenches considered in this paper.

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Hawaria, Dawit, Dante Santiago, and Delnesaw Yewhalaw. "Efficient attractants and simple odor-baited sticky trap for surveillance of Anopheles arabiensis Patton mosquito in Ethiopia." Journal of Infection in Developing Countries 10, no. 01 (January 31, 2016): 82–89. http://dx.doi.org/10.3855/jidc.6841.

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Introduction: Many efforts have been made to ease the burden of malaria through vector control, among whichis the development of odor-baited traps and evaluation of efficient attractants that could replace host odor. However, most traps and evaluated attractants are expensive, which poor communities cannot afford. This study was conductedwith the aim to devise asimple and affordable odor-baited trap and to investigate effective but affordable attractants for trapping Anopheles arabiensis. Methodology: First, an odor-baited sticky trap was developed; next, an experimental study with randomized design was conducted to evaluate the efficacy of selected attractants for trapping Anopheles arabiensis using the designed trap from June to August 2014. Laboratory strain Anopheles arabiensis were obtainedfrom the Adama Malaria Research and Training Center Insectary. Wild Anopheline mosquito larvae were collected from a temporary breeding site, reared in Asendabo Vector Biology Laboratory, and tested. Results: A simple odor-baited sticky trap was designed. Selected attractants were tested for attracting efficiency using the designed trap. Among the evaluated attractants, cow urine, which was kept for four days, attracted significantly more wild population and laboratory strains of the Anopheles arabiensisthan a worn sock alone and the combination of cow urine and a worn sock. Conclusions: Although further comparison studies with other standard traps are needed, the designed trap in conjunction with efficient attractant is shown to be effective for mosquito surveillance. Of the tested attractants, cow urine was anefficient attractant both for the wild population and the laboratory strain of Anohpeles arabiensis.

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Zhang, Wenli, Fengchun Tian, An Song, Zhenzhen Zhao, Youwen Hu, and Anyan Jiang. "Continuous wide spectrum odor sensing for electronic nose system." Sensor Review 38, no. 2 (March 19, 2018): 223–30. http://dx.doi.org/10.1108/sr-04-2017-0067.

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Purpose This paper aims to propose an odor sensing system based on wide spectrum for e-nose, based on comprehensive analysis on the merits and drawbacks of current e-nose. Design/methodology/approach The wide spectral light is used as the sensing medium in the e-nose system based on continuous wide spectrum (CWS) odor sensing, and the sensing response of each sensing element is the change of light intensity distribution. Findings Experimental results not only verify the feasibility and effectiveness of the proposed system but also show the effectiveness of least square support vector machine (LSSVM) in eliminating system errors. Practical implications Theoretical model of the system was constructed, and experimental tests were carried out by using NO2 and SO2. System errors in the test data were eliminated using the LSSVM, and the preprocessed data were classified by euclidean distance to centroids (EDC), k-nearest neighbor (KNN), support vector machine (SVM), LSSVM, respectively. Originality/value The system not only has the advantages of current e-nose but also realizes expansion of sensing array by means of light source and the spectrometer with their wide spectrum, high resolution characteristics which improve the detection accuracy and realize real-time detection.

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Wang, G., A. F. Carey, J. R. Carlson, and L. J. Zwiebel. "Molecular basis of odor coding in the malaria vector mosquito Anopheles gambiae." Proceedings of the National Academy of Sciences 107, no. 9 (February 16, 2010): 4418–23. http://dx.doi.org/10.1073/pnas.0913392107.

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Galán, Roberto Fdez, Silke Sachse, C. Giovanni Galizia, and Andreas V. M. Herz. "Odor-Driven Attractor Dynamics in the Antennal Lobe Allow for Simple and Rapid Olfactory Pattern Classification." Neural Computation 16, no. 5 (May 1, 2004): 999–1012. http://dx.doi.org/10.1162/089976604773135078.

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The antennal lobe plays a central role for odor processing in insects, as demonstrated by electrophysiological and imaging experiments. Here we analyze the detailed temporal evolution of glomerular activity patterns in the antennal lobe of honeybees. We represent these spatiotemporal patterns as trajectories in a multidimensional space, where each dimension accounts for the activity of one glomerulus. Our data show that the trajectories reach odor-specific steady states (attractors) that correspond to stable activity patterns at about 1 second after stimulus onset. As revealed by a detailed mathematical investigation, the trajectories are characterized by different phases: response onset, steady-state plateau, response offset, and periods of spontaneous activity. An analysis based on support-vector machines quantifies the odor specificity of the attractors and the optimal time needed for odor discrimination. The results support the hypothesis of a spatial olfactory code in the antennal lobe and suggest a perceptron-like readout mechanism that is biologically implemented in a downstream network, such as the mushroom body.

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Yan, Luchun, Jiemin Liu, and Di Fang. "Use of a Modified Vector Model for Odor Intensity Prediction of Odorant Mixtures." Sensors 15, no. 3 (March 9, 2015): 5697–709. http://dx.doi.org/10.3390/s150305697.

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Lu, Tan, Yu Tong Qiu, Guirong Wang, Jae Young Kwon, Michael Rutzler, Hyung-Wook Kwon, R. Jason Pitts, et al. "Odor Coding in the Maxillary Palp of the Malaria Vector Mosquito Anopheles gambiae." Current Biology 17, no. 18 (September 2007): 1533–44. http://dx.doi.org/10.1016/j.cub.2007.07.062.

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Liu, Taoping, Wentian Zhang, Peter McLean, Maiken Ueland, Shari L. Forbes, and Steven W. Su. "Electronic Nose-Based Odor Classification using Genetic Algorithms and Fuzzy Support Vector Machines." International Journal of Fuzzy Systems 20, no. 4 (January 17, 2018): 1309–20. http://dx.doi.org/10.1007/s40815-018-0449-8.

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Nimsuk, Nitikarn. "Application of Electronic Nose for Classification of Fish Sauces Using Transient Responses and Learning Vector Quantization Algorithm." Advanced Materials Research 931-932 (May 2014): 1582–86. http://dx.doi.org/10.4028/www.scientific.net/amr.931-932.1582.

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Fish sauce is one of the signature condiments in various cuisines in many countries. In this paper, fish sauces are successfully classified into groups depending on their quality indicated by the level of total nitrogen content. We introduce an electronic nose technology together with a neural network algorithm to the classification of fish sauces. The transient responses are used as features for the creation of pattern vectors for odor samples. The result of principal component analysis shows well-separated patterns of fish sauce. Furthermore, we also apply the learning vector quantization method for the classification. As a result, we obtain high accuracy of more than 90% in the classification of fish sauce based on the level of total nitrogen content.

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Liu, Huixiang, Qing Li, Bin Yan, Lei Zhang, and Yu Gu. "Bionic Electronic Nose Based on MOS Sensors Array and Machine Learning Algorithms Used for Wine Properties Detection." Sensors 19, no. 1 (December 22, 2018): 45. http://dx.doi.org/10.3390/s19010045.

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In this study, a portable electronic nose (E-nose) prototype is developed using metal oxide semiconductor (MOS) sensors to detect odors of different wines. Odor detection facilitates the distinction of wines with different properties, including areas of production, vintage years, fermentation processes, and varietals. Four popular machine learning algorithms—extreme gradient boosting (XGBoost), random forest (RF), support vector machine (SVM), and backpropagation neural network (BPNN)—were used to build identification models for different classification tasks. Experimental results show that BPNN achieved the best performance, with accuracies of 94% and 92.5% in identifying production areas and varietals, respectively; and SVM achieved the best performance in identifying vintages and fermentation processes, with accuracies of 67.3% and 60.5%, respectively. Results demonstrate the effectiveness of the developed E-nose, which could be used to distinguish different wines based on their properties following selection of an optimal algorithm.

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Eilerts, Diane, Morgen VanderGiessen, Elizabeth Bose, Kyera Broxton, and Clément Vinauger. "Odor-Specific Daily Rhythms in the Olfactory Sensitivity and Behavior of Aedes aegypti Mosquitoes." Insects 9, no. 4 (October 23, 2018): 147. http://dx.doi.org/10.3390/insects9040147.

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Many biological processes and behaviors in mosquitoes display rhythmic patterns, allowing for fine tuning to cyclic environmental conditions. In mosquitoes, vector-host interactions are primarily mediated by olfactory signals. Previous studies have established that, in the malaria vector Anopheles gambiae, rhythmic expression of odorant binding proteins and takeout proteins in the antenna resulted in a corresponding rhythm in olfactory sensitivity to relevant host odors. However, it remained unclear how rhythms observed in olfactory sensitivity affect or explain rhythms in behavioral output, which ultimately impacts disease transmission. In order to address this knowledge gap, we quantified and compared patterns in locomotor activity, olfactory sensitivity, and olfactory behaviors in adult female Aedes aegypti mosquitoes. Here, we demonstrate an odorant-specific modulation of olfactory sensitivity in Ae. aegypti, decoupled from rhythms in olfactory behavior. Additionally, behavioral assays performed herein represent the first evidence of a time-dependence of the olfactory activation of behavior in Ae. aegypti mosquitoes. Results suggest that olfactory behavior of Aedes mosquitoes is modulated at both the peripheral (antenna) and central levels. As such, this work serves as a foundation for future studies aimed at further understanding the neural and molecular mechanisms underlying behavioral plasticity.

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Seol, Daun, Daeil Jang, Kyungjoon Cha, Jin-Woo Oh, and Hoeil Chung. "Use of Multiple Bacteriophage-Based Structural Color Sensors to Improve Accuracy for Discrimination of Geographical Origins of Agricultural Products." Sensors 21, no. 3 (February 2, 2021): 986. http://dx.doi.org/10.3390/s21030986.

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A single M13 bacteriophage color sensor was previously utilized for discriminating the geographical origins of agricultural products (garlic, onion, and perilla). The resulting discrimination accuracy was acceptable, ranging from 88.6% to 94.0%. To improve the accuracy further, the use of three separate M13 bacteriophage color sensors containing different amino acid residues providing unique individual color changes (Wild sensor: glutamic acid (E)-glycine (G)-aspartic acid (D), WHW sensor: tryptophan (W)-histidine (H)-tryptophan (W), 4E sensor: four repeating glutamic acids (E)) was proposed. This study was driven by the possibility of enhancing sample discrimination by combining mutually characteristic and complimentary RGB signals obtained from each color sensor, which resulted from dissimilar interactions of sample odors with the employed color sensors. When each color sensor was used individually, the discrimination accuracy based on support vector machine (SVM) ranged from 91.8–94.0%, 88.6–90.3%, and 89.8–92.1% for garlic, onion, and perilla samples, respectively. Accuracy improved to 98.0%, 97.5%, and 97.1%, respectively, by integrating all of the RGB signals acquired from the three color sensors. Therefore, the proposed strategy was effective for improving sample discriminability. To further examine the dissimilar responses of each color sensor to odor molecules, typical odor components in the samples (allyl disulfide, allyl methyl disulfide, and perillaldehyde) were measured using each color sensor, and differences in RGB signals were analyzed.

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Na Songkhla, Sawit, and Takamichi Nakamoto. "Interpretation of Quartz Crystal Microbalance Behavior with Viscous Film Using a Mason Equivalent Circuit." Chemosensors 9, no. 1 (January 2, 2021): 9. http://dx.doi.org/10.3390/chemosensors9010009.

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In odor sensing based on Quartz Crystal Microbalances (QCMs), the sensing film is crucial for both sensor sensitivity and selectivity. The typical response of the QCM due to sorption is a negative frequency shift. However, in some cases, the sorption causes a positive frequency shift, and then, Sauerbrey’s equation and Kanazawa’s equation cannot be applied to this situation. We model the QCM response with a Mason equivalent circuit. The model approximates a single layer of a uniform viscous coating on the QCM. The simulation of the equation circuit shows the possibility of the positive frequency change when the sorption occurs, which is the situation we find in some of the odor sensing applications. We measured the QCM frequency and resistance using the Vector Network Analyzer (VNWA). The QCMs were coated with glycerol, PEG2000, and PEG20M. To simulate odor exposure, a microdispenser was used to deposit the water. A positive frequency shift was observed in the case of PEG2000, and a negative frequency change was obtained for PEG20M. These results can be explained by the Mason equivalent circuit, with the assumption that when the film is exposed to water, its thickness increases and its viscosity decreases.

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SAKURABA, Yuichi, Junichi IDE, Takamichi NAKAMOTO, and Toyosaka MORIIZUMI. "Selection of Odor Adsorption Films for Sensory Quantity Evaluation and Estimation Using Fuzzy Learning Vector Quantization." Transactions of the Society of Instrument and Control Engineers 31, no. 3 (1995): 357–63. http://dx.doi.org/10.9746/sicetr1965.31.357.

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Gaurav, Kumar, Ajay Kumar, and Ram Dayal. "Veco-Taxis as a Novel Engineered Algorithm for Odor Source Localization." International Journal of Ambient Computing and Intelligence 11, no. 2 (April 2020): 1–29. http://dx.doi.org/10.4018/ijaci.2020040101.

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Algorithms with limited intelligence are unable to localize an odor source in an indoor environment with weak or no airflow. Stage wise solutions to odor source localization has been provided with a novel engineered algorithm called veco-taxis for plume traversal. It finds turn angles by calculating concentration gradients using vector algebra-based search algorithms. Levy walk is used in the plume finding phase. The concept of last chemical detection points (LCDPs) has been adopted for source declaration. The success rate of implemented algorithms is quantified using minimum and maximum move lengths—a key parameter—during source localization. A unified success and performance index (SPI) of the search algorithm is presented for the first time. SPI uncovers implicit parameters accountable for success in locating source and considers a qualitative performance. Higher SPIs are observed when the move length in plume finding is minimum and kept smaller than the plume traversal move length by some factor. It has been also demonstrated through simulations that veco-taxis is superior to the E. coli algorithm.

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Liang, Wei, Li Na Zhang, Xiao Wei Li, and Yan Di Zuo. "Research of Electronic Nose Pattern Recognition Algorithm Based on SVM." Applied Mechanics and Materials 220-223 (November 2012): 2244–47. http://dx.doi.org/10.4028/www.scientific.net/amm.220-223.2244.

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In order to improve the recognition rate of the electronic nose system for small samples, an electronic nose pattern recognition algorithm based on support vector machine (SVM) is proposed in this paper. Identification experiments for three kinds of wine with similar odor were carried out. The sensor arrays are optimized by means of principal component analysis (PCA) method first. Then, make comparing experiment using different algorithms for different number of training samples of wine. The related results show that PCA-SVM based pattern recognition algorithms has high recognition accuracy, stronger classification capability, and has potential advantages in small sample classification and recognition experiments.

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Avrunin, Oleg, Yana Nosova, Sergii Zlepko, Ibrahim Younouss Abdelhamid, and Nataliia Shushliapina. "ASSESSMENT OF THE DIAGNOSTIC VALUE OF THE METHOD OF COMPUTER OLFACTOMETRY." Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska 9, no. 3 (September 26, 2019): 18–21. http://dx.doi.org/10.35784/iapgos.236.

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Olfactory studies can be a criterion for evaluating rhinosurgical intervention, and olfactory impairment may indicate respiratory impairment. Therefore, the urgent task is to develop an integrated approach to determining respiratory and olfactory disorders. A structural scheme was developed for the method of objective diagnosis of respiratory and olfactory disorders, taking into account the measu, rement of both the aerodynamic parameters of nasal breathing and the calculation of energy characteristics, which are used to determine olfactory sensitivity. The diagnostic significance of the proposed method of analyzing rhinofolipometry data with regard to additional parameters was assessed - it is necessary to take into account the time and power of breathing when the threshold of sensation of the odorivector is at the transition point of the airflow mode to the turbulent quadratic. It has been established that it is advisable to use the energy criteria of nasal breathing, pneumatic power and energy of nasal breathing under the action of the corresponding odor vector for the assessment of respiratory impaired olfactory. To assess the respiratory impairment of olfactory, it is necessary to use the method in which an odor vector is installed in the air path of the rhinomanometer, and the patient is asked to perform breathing maneuvers with a consistent increase in respiration rate while fixing the time at which olfactory sensitivity is achieved and then determining the respiratory energy characteristics. A statistical processing of diagnostic results was carried out, which confirms the adequacy of the model of independent statistical verification and makes it possible to use this method for the functional diagnosis of respiratory-olfactory disorders and testing of respiratory-olfactory sensitivity. The probability index of the error of the second kind is 0.17.

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Chen, Cheng-Hsuan, Kuo-Kai Shyu, Cheng-Kai Lu, Chi-Wen Jao, and Po-Lei Lee. "Classification of Prefrontal Cortex Activity Based on Functional Near-Infrared Spectroscopy Data upon Olfactory Stimulation." Brain Sciences 11, no. 6 (May 26, 2021): 701. http://dx.doi.org/10.3390/brainsci11060701.

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The sense of smell is one of the most important organs in humans, and olfactory imaging can detect signals in the anterior orbital frontal lobe. This study assessed olfactory stimuli using support vector machines (SVMs) with signals from functional near-infrared spectroscopy (fNIRS) data obtained from the prefrontal cortex. These data included odor stimuli and air state, which triggered the hemodynamic response function (HRF), determined from variations in oxyhemoglobin (oxyHb) and deoxyhemoglobin (deoxyHb) levels; photoplethysmography (PPG) of two wavelengths (raw optical red and near-infrared data); and the ratios of data from two optical datasets. We adopted three SVM kernel functions (i.e., linear, quadratic, and cubic) to analyze signals and compare their performance with the HRF and PPG signals. The results revealed that oxyHb yielded the most efficient single-signal data with a quadratic kernel function, and a combination of HRF and PPG signals yielded the most efficient multi-signal data with the cubic function. Our results revealed superior SVM analysis of HRFs for classifying odor and air status using fNIRS data during olfaction in humans. Furthermore, the olfactory stimulation can be accurately classified by using quadratic and cubic kernel functions in SVM, even for an individual participant data set.

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Zhang, Yang, Lei Zhang, Yabin Ma, Jinsen Guan, Zhaoxia Liu, and Jihui Liu. "Research on dairy products detection based on machine learning algorithm." MATEC Web of Conferences 355 (2022): 03008. http://dx.doi.org/10.1051/matecconf/202235503008.

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In this study, an electronic nose model composed of seven kinds of metal oxide semiconductor sensors was developed to distinguish the milk source (the dairy farm to which milk belongs), estimate the content of milk fat and protein in milk, to identify the authenticity and evaluate the quality of milk. The developed electronic nose is a low-cost and non-destructive testing equipment. (1) For the identification of milk sources, this paper uses the method of combining the electronic nose odor characteristics of milk and the component characteristics to distinguish different milk sources, and uses Principal Component Analysis (PCA) and Linear Discriminant Analysis , LDA) for dimensionality reduction analysis, and finally use three machine learning algorithms such as Logistic Regression (LR), Support Vector Machine (SVM) and Random Forest (RF) to build a milk source (cow farm) Identify the model and evaluate and compare the classification effects. The experimental results prove that the classification effect of the SVM-LDA model based on the electronic nose odor characteristics is better than other single feature models, and the accuracy of the test set reaches 91.5%. The RF-LDA and SVM-LDA models based on the fusion feature of the two have the best effect Set accuracy rate is as high as 96%. (2) The three algorithms, Gradient Boosting Decision Tree (GBDT), Extreme Gradient Boosting (XGBoost) and Random Forest (RF), are used to construct the electronic nose odor data for milk fat rate and protein rate. The method of estimating the model, the results show that the RF model has the best estimation performance( R2 =0.9399 for milk fat; R2=0.9301for milk protein). And it prove that the method proposed in this study can improve the estimation accuracy of milk fat and protein, which provides a technical basis for predicting the quality of dairy products.

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Chen, Sicong. "piRNAs in the Olfactory Bulb Related to Fear Conditioning can Migrate from the Brain to the Germline." Scientific and Social Research 3, no. 5 (November 5, 2021): 132–36. http://dx.doi.org/10.36922/ssr.v3i5.1233.

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Small RNAs have been shown to be crucial in the mechanisms of transgenerational memory. Precisely, piRNAs have previously been thought to only exist in the germline and are related to transgenerational memory. To determine if the offspring inherits memory due to piRNA transmission, we conducted odor fear-conditioning tests and identified a piRNA that increased in abundance. That piRNA is thought to be involved in memory formation of the fear-conditioning test. We then used a virus vector to manipulate a single nucleotide of that piRNA sequence to see if it can migrate from the olfactory bulb to the germline. The data should theoretically indicate whether the mutant piRNA has migrated from the olfactory bulb to the germline of the mice.

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Weng, Xiaohui, Cheng Kong, Hongyang Jin, Dongxue Chen, Chunguang Li, Yinwu Li, Lili Ren, Yingkui Xiao, and Zhiyong Chang. "Detection of Volatile Organic Compounds (VOCs) in Livestock Houses Based on Electronic Nose." Applied Sciences 11, no. 5 (March 6, 2021): 2337. http://dx.doi.org/10.3390/app11052337.

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The composition of volatile organic compounds (VOCs) in large-scale livestock farms is complex, which seriously affects the health of livestock and is difficult to evaluate. In order to quickly analyze the pollution degree of VOCs in livestock farms, electronic nose technology was used in this study to detect and analyze the gases in pig and chicken houses, respectively. Firstly, the gas chromatography–mass spectrometry (GC–MS) and electronic nose were used to analyze the VOCs in the pig and chicken houses at different time and locations. The types and relative contents of VOCs were obtained from different livestock farms by GC–MS analysis. The sensor array response of the electronic nose showed similar results. In addition, linear discriminant analysis (LDA), K nearest neighbor (KNN) and support vector machine (SVM) analyses were performed on the electrical signal that was generated by the sensors of electronic nose, respectively. Finally, the classification rate of different odor sources in livestock farms was the highest (>85%), which indicates that SVM is a more effective method suitable for volatile gases recognition in livestock farms. The results have shown that the developed electronic nose sensor is a promising and feasible instrument for characterizing volatile odors in livestock farms.

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Diallo, Souleymane, Mohd Shahbaaz, JohnMark O. Makwatta, Jackson M. Muema, Daniel Masiga, Alan Christofells, and Merid N. Getahun. "Antennal Enriched Odorant Binding Proteins Are Required for Odor Communication in Glossina f. fuscipes." Biomolecules 11, no. 4 (April 8, 2021): 541. http://dx.doi.org/10.3390/biom11040541.

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Olfaction is orchestrated at different stages and involves various proteins at each step. For example, odorant-binding proteins (OBPs) are soluble proteins found in sensillum lymph that might encounter odorants before reaching the odorant receptors. In tsetse flies, the function of OBPs in olfaction is less understood. Here, we investigated the role of OBPs in Glossina fuscipes fuscipes olfaction, the main vector of sleeping sickness, using multidisciplinary approaches. Our tissue expression study demonstrated that GffLush was conserved in legs and antenna in both sexes, whereas GffObp44 and GffObp69 were expressed in the legs but absent in the antenna. GffObp99 was absent in the female antenna but expressed in the male antenna. Short odorant exposure induced a fast alteration in the transcription of OBP genes. Furthermore, we successfully silenced a specific OBP expressed in the antenna via dsRNAi feeding to decipher its function. We found that silencing OBPs that interact with 1-octen-3-ol significantly abolished flies’ attraction to 1-octen-3-ol, a known attractant for tsetse fly. However, OBPs that demonstrated a weak interaction with 1-octen-3-ol did not affect the behavioral response, even though it was successfully silenced. Thus, OBPs’ selective interaction with ligands, their expression in the antenna and their significant impact on behavior when silenced demonstrated their direct involvement in olfaction.

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Xiao, Zuobing, Pan Xiang, Jiancai Zhu, Quan Zhu, Ying Liu, and Yunwei Niu. "Evaluation of the Perceptual Interaction among Sulfur Compounds in Mango by Feller’s Additive Model, Odor Activity Value, and Vector Model." Journal of Agricultural and Food Chemistry 67, no. 32 (July 29, 2019): 8926–37. http://dx.doi.org/10.1021/acs.jafc.9b03156.

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Nik Ab Rahim, Nik Nor Rahimah, Jamal Othman, Norlida Hanim Mohd Salleh, and Norshamliza Chamhuri. "A Non-Market Valuation Approach to Environmental Cost-Benefit Analysis for Sanitary Landfill Project Appraisal." Sustainability 13, no. 14 (July 10, 2021): 7718. http://dx.doi.org/10.3390/su13147718.

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Extensive non-engineered landfilling practice in developing countries has raised environmental concerns, but operating a sanitary landfill appears infeasible due to financial incapability. This study aims to determine the feasibility of a sanitary landfill project by including its environmental values into the project appraisal while simultaneously applying three policy-relevant methods—non-market valuation, benefits transfer, and cost-benefit analysis—in two study areas in Peninsular Malaysia. The non-market valuation study used choice modeling, a questionnaire-based technique, to elicit willingness to pay among 624 households toward the environmental attributes of the sanitary landfill. Their responses resulted in the monetary values of the environmental attributes by referring to implicit prices of leachate discharge, bad odor, disease vector and view. The implicit prices of bad odor (RM2.29 per month) and view (RM3.59 per month) in the two study areas were transferable and used as a proxy of additional solid waste disposal payment in environmental cost-benefit analysis. Positive net present value offers empirical evidence of the feasibility of the sanitary landfill project. The findings show that the inclusion of environmental values in project appraisals increases the chances of implementing sanitary landfills, providing a new approach to address the environmental concerns in developing countries. Future research should consider the external costs along with the external benefits to allow for a comprehensive comparison between environmental values in environmental cost-benefit analysis.

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Bahk, Young Yil, Hojong Jun, Seo Hye Park, Haneul Jung, Seung Jegal, Myung-Deok Kim-Jeon, Jong Yul Roh, et al. "Surveillance of Chigger Mite Vectors for Tsutsugamushi Disease in the Hwaseong Area, Gyeonggi-do, Republic of Korea, 2015." Korean Journal of Parasitology 58, no. 3 (June 26, 2020): 301–8. http://dx.doi.org/10.3347/kjp.2020.58.3.301.

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Owing to global climate change, the global resurgence of vector-borne infectious diseases and their potential to inflict widespread casualties among human populations has emerged as a pivotal burden on public health systems. Tsutsugamushi disease (scrub typhus) in the Republic of Korea is steadily increasing and was designated as a legal communicable disease in 1994. The disease is a mite-borne acute febrile disease most commonly contracted from October to December. In this study, we tried to determine the prevalence of tsutsugamushi disease transmitted by chigger mites living on rodents and investigated their target vector diversity, abundance, and distribution to enable the mapping of hotspots for this disease in 2015. A total of 5 species belonging to 4 genera (109 mites): Leptotrombidium scutellare 60.6%, L. pallidum 28.4% Neotrombicula tamiyai 9.2%, Euschoengastia koreaensis/0.9%), and Neoschoengastia asakawa 0.9% were collected using chigger mite collecting traps mimicking human skin odor and sticky chigger traps from April to November 2015. Chigger mites causing tsutsugamushi disease in wild rodents were also collected in Hwaseong for the zoonotic surveillance of the vector. A total of 77 rodents belonging to 3 genera: Apodemus agrarius (93.5%), Crocidura lasiura (5.2%), and Micromys minutus (1.3%) were collected in April, October, and November 2015. The most common mite was L. pallidum (46.9%), followed by L. scutellare (18.6%), and L. orientale (18.0%). However, any of the chigger mite pools collected from rodent hosts was tested positive for Orientia tsutsugamushi, the pathogen of tsutsugamushi disease, in this survey.

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Cahyana, Budi Tri, and Arhamsyah Arhamsyah. "PEMANFAATAN HASIL HUTAN BUKAN KAYU SEBAGAI BAHAN INSEKTISIDA ALAMI." Jurnal Riset Industri Hasil Hutan 4, no. 2 (December 31, 2012): 31. http://dx.doi.org/10.24111/jrihh.v4i2.1206.

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Non-timber forest products (NTFPs) such as the root of Akar Wangi (Vetiveria zizainoides), Durian’s bark (Durio zibethinus Murr), Jaringau (Acorus Calamus L.), Liligundi (Vitex trifolia), Gemor bark (Alseodaphne spp.), and Neem seeds (Azadirachta indica A. Juss.) have good potential as a natural insecticide. They can be used for anti-mosquito materials that can be prevent the development of vector-borne Dengue Haemorrhagic Fever (DHF). Disruptive effects of the plants to the insects come from the odor which produces from the plant. Judging from the compounds that contained in non-timber forest products (NTFPs), beside used as anti-mosquito repellent, it can also used as other pests repellant such as bugs, termites, ants, etc. The end product also can be diversed as insect repellent burns, topical / lotion, spray, and others.Keywords : akar wangi, durian bark, jariangau, liligundi, gemor bark, mimba, natural insecticide

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Kessy, Stella T., Ladslaus L. Mnyone, Bruno A. Nyundo, and Issa N. Lyimo. "Passive Outdoor Host Seeking Device (POHD): Designing and Evaluation against Outdoor Biting Malaria Vectors." Scientific World Journal 2020 (July 1, 2020): 1–15. http://dx.doi.org/10.1155/2020/4801068.

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Odor-baited devices are increasingly needed to compliment long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) for control of residual malaria transmission. However, the odor-baited devices developed so far are bulky, dependent on the source of electricity and carbon dioxide (CO2), and they are logistically unsuitable for scaling up in surveillance and control of malaria vectors. We designed a passive and portable outdoor host seeking device (POHD) and preliminarily evaluated suitable components against Anopheles arabiensis that maintains residual malaria transmission. Experiments were conducted using semifield reared An. arabiensis within the semifield system at Ifakara Health Institute (IHI) in southeastern Tanzania. These mosquitoes were exposed to Suna traps® baited with BG lures or source of light and augmented with carbon dioxide (CO2) in view of identifying best attractants necessary to improve attractiveness of designed POHD. Two Suna traps® were hanged at the corner but outside the experimental hut in a diagonal line and rotated between four corners to control for the effect of position and wind direction on mosquito catches. Furthermore, mosquitoes were also exposed to either a bendiocarb-treated or bendiocarb-untreated POHD baited with Mbita blend, Ifakara blend, and worn socks and augmented with warmth (i.e., 1.5 liter bottle of warm water) inside an experimental hut or a screened rectangular box. This study demonstrated that mosquitoes were more strongly attracted to Suna trap® baited with BG lures and CO2 relative to those traps baited with a source of light and CO2. The POHD baited with synthetic blends attracted and killed greater proportion of An. arabiensis compared with POHD baited with worn socks. Efficacy of the POHD was unaffected by source of warmth, and it was reduced by about 50% when the device was tested inside a screened rectangular box relative to closed experimental hut. Overall, this study demonstrates that the POHD baited with synthetic blends (Mbita and Ifakara blends) and bendiocarb can effectively attract and kill outdoor biting malaria vector species. Such POHD baited with synthetic blends may require the source of CO2 to enhance attractiveness to mosquitoes. Further trials are, therefore, ongoing to evaluate attractiveness of improved design of POHD baited with slow-release formulation of synthetic blends and sustainable source of CO2 to malaria vectors under semifield and natural environments.

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Santana, Isis Bugia, Franco Henrique Andrade Leite, and Manoelito Coelho Santos Junior. "Identification of Lutzomyia longipalpis Odorant Binding Protein Modulators by Comparative Modeling, Hierarchical Virtual Screening, and Molecular Dynamics." Journal of Chemistry 2018 (September 24, 2018): 1–10. http://dx.doi.org/10.1155/2018/4173479.

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Visceral leishmaniasis (VL) is the second most important vector-borne disease in the world. It is transmitted by Lutzomyia longipalpis in America; therefore, controlling the vector is essential to prevent the disease, especially using traps with chemical attractants. It is known that odorant binding proteins (OBPs) act at the first odor selection level, so in silico methodology was used to identify putative vector chemical modulators based on OBPs on known ligand structures. Therefore, 3D structures of L. longipalpis OBP were predicted through different comparative modeling methods. The best model was subjected to molecular dynamics studies. Then, a hierarchical virtual screening approach filtered OBP modulator-like compounds from ZINC12 biogenic database based in global chemical space, using principal components from ChemGPS-NP server. Such compounds then were evaluated and ranked according to their affinity with the OBP orthosteric site by molecular docking in DOCK 6.7. The compounds were scored by Grid Score function and top five ranked poses had their intermolecular complex interactions analyzed in PLIP server. Most ligands in the top of the rank were lysophospholipids, which could potentially interact with the OBP hydrophobic pocket through Phe72, Tyr76, Ile79, Ala87, Lys88, Asp92, Phe61, Leu75, Trp113, His120, and Phe122 residues and H-bonding with His120 and Phe122. Next, compounds in the top of the rank were evaluated by 50 ns MD and the results showed that the phosphate group of these compounds could set a salt bridge with His110. Additionally, Tyr76, Ala87, Met91, Trp113, and Phe122 were important to hydrophobic interactions with the ligand. These results highlight the importance of accurate assessments such as MD studies in order to analyze the docking results in the identification of new odorant modulators.

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Amos, Brogan A., Scott A. Ritchie, and Ring T. Cardé. "Attraction Versus Capture II: Efficiency of the BG-Sentinel Trap Under Semifield Conditions and Characterizing Response Behaviors of Male Aedes aegypti (Diptera: Culicidae)." Journal of Medical Entomology 57, no. 5 (May 4, 2020): 1539–49. http://dx.doi.org/10.1093/jme/tjaa065.

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Abstract Aedes aegypti (L.) is an important vector of viruses causing dengue, Zika, chikungunya, and yellow fever and as such presents a serious threat to public health in tropical regions. Control programs involving ‘rear and release’ of modified male Ae. aegypti are underway and require effective trapping methods for surveillance of both the released insects and the impacted wild mosquito population. The BG-Sentinel trap (BGS) is widely used in Ae. aegypti surveillance but its level of efficiency, that is, what proportion of the mosquitoes encountering the trap are captured, is unknown. This is especially true for male mosquitoes, the behavior of which is incompletely understood. We tested the efficiency of two versions of the BGS for capturing male Ae. aegypti under semifield conditions with and without CO2 and a human skin odor mimic lure and with these baits combined. A navy-blue BGS trap emitting CO2 and a human skin odor mimic captured 18% of the released male Ae. aegypti, with a capture efficiency of 9 % (of the total encounters with the trap). Male Ae. aegypti had multiple encounters with the BGS that did not result in capture; they crossed over the trap entrance without being captured or landed on the sides of the trap. Swarming behavior around the BGS was also recorded, even when only a visual cue was present. Understanding male Ae. aegypti behaviors during an encounter with the BGS can inform improvement of trap design and therefore capture efficiency for surveillance in control programs.

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Amos, Brogan A., Kyran M. Staunton, Scott A. Ritchie, and Ring T. Cardé. "Attraction Versus Capture: Efficiency of BG-Sentinel Trap Under Semi-Field Conditions and Characterizing Response Behaviors for Female Aedes aegypti (Diptera: Culicidae)." Journal of Medical Entomology 57, no. 3 (January 16, 2020): 884–92. http://dx.doi.org/10.1093/jme/tjz243.

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Abstract Aedes aegypti (L.) is an important vector of viruses causing dengue, Zika, chikungunya, and yellow fever and as such is a threat to public health worldwide. Effective trapping methods are essential for surveillance of both the mosquito species and disease presence. The BG-Sentinel (BGS) is a widely used to trap Ae. aegypti but little is known of its efficiency, i.e., what proportion of the mosquitoes encountering the trap are captured. The first version of the BGS trap was predominantly white, and the current version is mostly navy blue. While this trap is often deployed without any olfactory lure, it can also be deployed with CO2 and/or a human skin odor mimic lure to increase capture rates. We tested the efficiency of capturing Ae. aegypti under semi-field conditions for the original white version without lures as well the blue version with and without various lure combinations. None of the configurations tested here captured 100% of the mosquitoes that encountered the trap. A navy-blue trap emitting CO2 and a skin odor mimic produced the highest capture (14% of the total insects in the semi-field cage), but its capture efficiency was just 5% (of mosquitoes encountering the trap). Mosquitoes often had multiple encounters with a trap that did not result in capture; they crossed over the trap entrance without being captured or landed on the sides of the trap. Understanding these behaviors and the factors that induce them has the potential to suggest improvement in trap design and therefore capture efficiency.

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Xiao, Zuobing, Pan Xiang, Jiancai Zhu, Quan Zhu, Ying Liu, and Yunwei Niu. "Correction to Evaluation of the Perceptual Interaction among Sulfur Compounds in Mango by Feller’s Additive Model, Odor Activity Value, and Vector Model." Journal of Agricultural and Food Chemistry 67, no. 39 (September 20, 2019): 10995. http://dx.doi.org/10.1021/acs.jafc.9b05794.

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Miazzi, Fabio, Carolin Hoyer, Silke Sachse, Markus Knaden, Dieter Wicher, Bill S. Hansson, and Sofia Lavista-Llanos. "Optimization of Insect Odorant Receptor Trafficking and Functional Expression Via Transient Transfection in HEK293 Cells." Chemical Senses 44, no. 9 (August 31, 2019): 673–82. http://dx.doi.org/10.1093/chemse/bjz062.

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Abstract Insect odorant receptors (ORs) show a limited functional expression in various heterologous expression systems including insect and mammalian cells. This may be in part due to the absence of key components driving the release of these proteins from the endoplasmic reticulum and directing them to the plasma membrane. In order to mitigate this problem, we took advantage of small export signals within the human HCN1 and Rhodopsin that have been shown to promote protein release from the endoplasmic reticulum and the trafficking of post-Golgi vesicles, respectively. Moreover, we designed a new vector based on a bidirectional expression cassette to drive the functional expression of the insect odorant receptor coreceptor (Orco) and an odor-binding OR, simultaneously. We show that this new method can be used to reliably express insect ORs in HEK293 cells via transient transfection and that is highly suitable for downstream applications using automated and high-throughput imaging platforms.

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Cárdenas-Talero, José Luis, Jorge Antonio Silva-Leal, Andrea Pérez-Vidal, and Patricia Torres-Lozada. "The Influence of Municipal Wastewater Treatment Technologies on the Biological Stabilization of Sewage Sludge: A Systematic Review." Sustainability 14, no. 10 (May 13, 2022): 5910. http://dx.doi.org/10.3390/su14105910.

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Various wastewater treatment technologies are available today and biological processes are predominantly used in these technologies. Increasing wastewater treatment systems produces large amounts of sewage sludge with variable quantities and qualities, which must be properly managed. Anaerobic and aerobic digestion and composting are major strategies to treat this sludge. The main indicators of biological stabilization are volatile fatty acids (VFAs), volatile solids (VS), the carbon/nitrogen (C/N) ratio, humic substances (HS), the total organic carbon (TOC), the carbon dioxide (CO2) evolution rate, the specific oxygen uptake rate (SOUR), and the Dewar test; however, different criteria exist for the same indicators. Although there is no consensus for defining the stability of sewage sludge (biosolids) in the research and regulations reviewed, controlling the biological degradation, vector attraction, and odor determines the biological stabilization of sewage sludge. Because pollutants and pathogens are not completely removed in biological stabilization processes, further treatments to improve the quality of biosolids and to ensure their safe use should be explored.

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Huang, Yixu, Iyll-Joon Doh, and Euiwon Bae. "Design and Validation of a Portable Machine Learning-Based Electronic Nose." Sensors 21, no. 11 (June 7, 2021): 3923. http://dx.doi.org/10.3390/s21113923.

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Volatile organic compounds (VOCs) are chemicals emitted by various groups, such as foods, bacteria, and plants. While there are specific pathways and biological features significantly related to such VOCs, detection of these is achieved mostly by human odor testing or high-end methods such as gas chromatography–mass spectrometry that can analyze the gaseous component. However, odor characterization can be quite helpful in the rapid classification of some samples in sufficient concentrations. Lower-cost metal-oxide gas sensors have the potential to allow the same type of detection with less training required. Here, we report a portable, battery-powered electronic nose system that utilizes multiple metal-oxide gas sensors and machine learning algorithms to detect and classify VOCs. An in-house circuit was designed with ten metal-oxide sensors and voltage dividers; an STM32 microcontroller was used for data acquisition with 12-bit analog-to-digital conversion. For classification of target samples, a supervised machine learning algorithm such as support vector machine (SVM) was applied to classify the VOCs based on the measurement results. The coefficient of variation (standard deviation divided by mean) of 8 of the 10 sensors stayed below 10%, indicating the excellent repeatability of these sensors. As a proof of concept, four different types of wine samples and three different oil samples were classified, and the training model reported 100% and 98% accuracy based on the confusion matrix analysis, respectively. When the trained model was challenged against new sets of data, sensitivity and specificity of 98.5% and 98.6% were achieved for the wine test and 96.3% and 93.3% for the oil test, respectively, when the SVM classifier was used. These results suggest that the metal-oxide sensors are suitable for usage in food authentication applications.

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Abramson, Charles I., Joseph Frasca, Ryan Fehr, Enrique Sulbaran Romero, Eliecer Lizano, and Elis Aldana. "Psychology of Learning: A New Approach to Study Behavior of Rhodnius Prolixus Stal under Laboratory Conditions." Psychological Reports 97, no. 3 (December 2005): 721–31. http://dx.doi.org/10.2466/pr0.97.3.721-731.

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Conditioning methodologies associated with the psychology of learning are suggested as a new strategy to investigate behavior of the assassin bug Rhodnius prolixus, which is the main vector of Chagas disease in Venezuela. Chagas disease is the fourth leading cause of death in Latin America, as it causes severe chronic illness and approximately 43,000 deaths per year. To illustrate this strategy, two preliminary experiments are reported. In the first, Pavlovian conditioning was examined by pairing an olfactory conditioned stimulus with a temperature unconditioned stimulus. A temperature of 42°C elicits a complex behavioral sequence in R. prolixus consisting of proboscis extension and crawling. Over the course of 12 training trials, this behavioral sequence was not elicited by an olfactory conditioned stimulus. In the second experiment, a latent inhibition paradigm was used to pre-expose R. prolixus to an olfactory conditioned stimulus before pairing the odor with temperature. Over the course of training, an effect of pre-exposure was found. Suggestions for research are discussed and potential conditioned and unconditioned stimuli identified.

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Menda, Gil, Joshua H. Uhr, Robert A. Wyttenbach, Françoise M. Vermeylen, David M. Smith, Laura C. Harrington, and Ronald R. Hoy. "Associative learning in the dengue vector mosquito,Aedes aegypti: avoidance of a previously attractive odor or surface color that is paired with an aversive stimulus." Journal of Experimental Biology 216, no. 2 (September 20, 2012): 218–23. http://dx.doi.org/10.1242/jeb.074898.

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Tizard, Ian, and Loren Skow. "The olfactory system: the remote-sensing arm of the immune system." Animal Health Research Reviews 22, no. 1 (April 30, 2021): 14–25. http://dx.doi.org/10.1017/s1466252320000262.

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AbstractOdors may be pleasant or unpleasant and in practice, pleasant odors are attractive while unpleasant odors are repellent. However, an odor that is noxious to one species may be attractive to another. Plants, predators, and pathogens may enhance their transmission by manipulating these signals. This may be especially significant when odors attract arthropod disease vectors. Odor detection may also be important in small prey species for evasion of macropredators such as large carnivores. Conversely, pleasant odors may identify family members, parents, or sexual partners. They may also generate signals of good health or fitness and contribute to the process of mate selection. In this review, we seek to integrate these odor-driven processes into a coherent pattern of behaviors that serve to complement the innate and adaptive immune systems. It may be considered the ‘behavioral immune system’.

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Adib, Hooman, Nazanin Kazerooni, Alireza Falsafi, Mohammad Amin Adhami, Mehdi Dehghan, and Abbas Golnari. "Prediction of sulfur content in propane and butane after gas purification on a treatment unit." Oil & Gas Science and Technology – Revue d’IFP Energies nouvelles 73 (2018): 70. http://dx.doi.org/10.2516/ogst/2018021.

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The acidic compounds such as Mercaptans, H2S and COS are commonly present in the liquid LPG streams in the south Pars gas processing plant. Sulfur contaminants not only lead to odor problems but can form objectionable oxides on combustion and cause environmental pollution. In present study, Support Vector Machine (SVM) is employed to develop an intelligent model to predict the sulfur content of propane and butane products of Liquefied Petroleum Gas (LPG) treatment unit of south Pars gas processing plant of Assaluyeh/Iran. A set of seven input/output plant data each consisting of 365 data has been used to train, optimize, and test the model. Model development that consists of training, optimization and test was performed using randomly selected 70%, 15%, and 15% of available data respectively. Test results from the SVM developed model showed good compliance with operating plant data. Squared correlation coefficients for developed models are 0.97 and 0.99 for propane and butane sulfur content, respectively. According to the results of the present case study, SVM could be regarded as a reliable accurate approach for modeling the sulfur content of LPG treatment unit of a natural gas processing plant.

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Rumengan, Antonius P. "UJI LARVASIDA NYAMUK (Aedes aegypti) DARI ASCIDIAN (Didemnum molle)." JURNAL PERIKANAN DAN KELAUTAN TROPIS 6, no. 2 (August 30, 2010): 83. http://dx.doi.org/10.35800/jpkt.6.2.2010.166.

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Dengue haemorrhagie fever is one of the disease which caused by dengue virus. It spreads out by mosquito Aedes aegypti as the vector. To date, people use abate as the larvacidal. Yet it causes the negative effects, such as bad odor, rustiness of the water container and resistency either to the larvae or to the living environment if continue using it. The objective of the research was to examine the larvacidal activity of Didemnum molle extract against A. aegypti larvae. The sample was extracted with methanol to give methanolic extract which was further partitioned with ethyl acetate, hexane, and chloroform to yield three fractions of ethyl acetate, hexane, and chloroform. Methanolic extract and the three fractions were tested against the A. aegypti larvae instar III for several concentrations. Abate and tap water were used as controls. The result exhibited that Didemnum molle extracts contain or produce larvacidae substances against A. aegypti larvae. They are approved by the data of methanolic extract and the 3 fractions which are more powerful than abate, particularly hexane. However it still needs to be purified to obtain single active compound.

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Han, Lu, Jingyi Zhu, Xia Fan, Chong Zhang, Kang Tu, Jing Peng, Jiahong Wang, and Leiqing Pan. "Rapid Non-Destructive Quantification of Eugenol in Curdlan Biofilms by Electronic Nose Combined with Gas Chromatography-Mass Spectrometry." Sensors 20, no. 16 (August 9, 2020): 4441. http://dx.doi.org/10.3390/s20164441.

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Eugenol is hepatotoxic and potentially hazardous to human health. This paper reports on a rapid non-destructive quantitative method for the determination of eugenol concentration in curdlan (CD) biofilms by electronic nose (E-nose) combined with gas chromatography-mass spectrometry (GC-MS). Different concentrations of eugenol were added to the film-forming solution to form a series of biofilms by casting method, and the actual eugenol concentration in the biofilm was determined. Analysis of the odor collected on the biofilms was carried out by GC-MS and an E-nose. The E-nose data was subjected to principal component analysis (PCA) and linear discriminant analysis (LDA) in order to establish a discriminant model for determining eugenol concentrations in the biofilms. Further analyses involving the application of all sensors and featured sensors, the prediction model-based partial least squares (PLS) and support vector machines (SVM) were carried out to determine eugenol concentration in the CD biofilms. The results showed that the optimal prediction model for eugenol concentration was obtained by PLS at R2p of 0.952 using 10 sensors. The study described a rapid, non-destructive detection and quantitative method for determining eugenol concentration in bio-based packaging materials.

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Journal articles on the topic 'Odor vector'

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