Relevant bibliographies by topics / Odor

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
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Academic literature on the topic 'Odor'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 August 2024

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Journal articles on the topic "Odor"

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Bo, Weichen, Yuandong Yu, Ran He, Dongya Qin, Xin Zheng, Yue Wang, Botian Ding, and Guizhao Liang. "Insight into the Structure–Odor Relationship of Molecules: A Computational Study Based on Deep Learning." Foods 11, no. 14 (July 9, 2022): 2033. http://dx.doi.org/10.3390/foods11142033.

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Molecules with pleasant odors, unacceptable odors, and even serious toxicity are closely related to human social life. It is impractical to identify the odors of molecules in large quantities (particularly hazardous odors) using experimental methods. Computer-aided methods have currently attracted increasing attention for the prediction of molecular odors. Here, through models based on multilayer perceptron (MLP) and physicochemical descriptors (MLP-Des), MLP and molecular fingerprint, and convolutional neural network (CNN), we conduct the two-class prediction of odor/no odor, fruity/no odor, floral/no odor, and woody/no odor, and the multi-class prediction of fruity/flowery/woody/no odor on our newly refined molecular odor datasets. We show that three kinds of predictors can robustly predict molecular odors. The MLP-Des model not only exhibits the best prediction results (the AUC values are 0.99 and 0.86 for the two- and multi-classification models, respectively) but can also well reflect the characteristics of the structure–odor relationship of molecules. The CNN model takes 2D molecular images as input and can automatically extract the structural features related to molecular odors. The proposed models are of great help for the prediction of molecular odorants, understanding the underlying relationship between chemical structure and odor perception, and the discovery of new odorous and/or hazardous molecules.
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Patel, Muktiben M., Nigam D. Patel, Angela Rekhi, and Alan R. Hirsch. "163 Treatment of Odor-Induced Anxiogenesis With Odor-Induced Anxiolysis." CNS Spectrums 23, no. 1 (February 2018): 99. http://dx.doi.org/10.1017/s1092852918000548.

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AbstractStudy ObjectiveTo understand the effects of odor on anxiety.IntroductionReduction of odor-induced anxiety through a presentation of an odor has not heretofore been described.MethodCase report: A 69-year-old right-handed male with a five year history of generalized anxiety disorder, presented with a one and a half month history of hypersensitivity to odors of multiple synthetic chemicals manifest by the perception that these odors were more intense and unpleasant inducing nausea, abdominal cramping, coughing, a need to “get away from the smell”, and panic with intense anxiety. These symptoms would occur whenever he was exposed to these smells, 20 to 25 times a day, and would persist for 10 to 15 minutes after the exposure. When odors induced the above symptoms, exposure to the aroma of cinnamon immediately alleviated these symptoms. He now continues using cinnamon odor whenever the odor induced anxiety and associated symptoms arise. This remedy has been effective over the course of treatment, for almost two years.ResultsAbnormalities on examination: Three per second titubation. Archimedean Spiral Test: Saw tooth pattern with macrographia. Anxious, circumstantial, overly inclusive. Unable to determine how to put on shoe covers. Impaired voluntary upward gave, but intact vertical doll’s eyes. Left torticollis. Bilateral finger to nose dysmetria. Low amplitude, high frequency tremor on extension of both upper extremities. Areflexic. Olfactory Testing: hyposmic. MRI of brain with and without infusion: mild generalized volume loss.ConclusionsThere are myriad mechanisms whereby odor may have reduced the odor-induced anxiety. Since aroma induced anxiogeneis is usually confined to a specific odor, it does not preclude other odors from acting in an anxiolytic manner. The combination of exposure simultaneously of anxiolytic and anxiogenic odors may have acted to increase the threshold of the anxiety producing odor, inhibiting perception of the anxiogenic odor and thus precipitation of anxiety. The two odors could have combined in an additive fashion, changing the olfactory characteristics of the anxiety provoking odor such that it no longer was perceived as the same odor and thus no anxiety. The anxiolytic/anxiogenic odor mixture could have overwhelmed the anxiogenic odor, thus creating the perception of only anxiolytic odor. On a central basis, the anxiolysis and anxiogenesis may have been induced to occur coincidently with anxiolysis superseding anxiogenesis. Alternatively, the odors may have acted as a distractor, changing the focus of attention from anxiogenic odor to a different odor which does not have the same anxiety provoking effect. Maybe because the patient already has demonstrated a heightened odor emotion linkage, he may be more susceptible to any other odor emotion effects. Trial of odors in those with odor induced anxiety warrants consideration.Funding AcknowledgementsNo funding.
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Bian, Yuge, Haoning Gong, and I. H. (Mel) Suffet. "The Use of the Odor Profile Method with an “Odor Patrol” Panel to Evaluate an Odor Impacted Site near a Landfill." Atmosphere 12, no. 4 (April 9, 2021): 472. http://dx.doi.org/10.3390/atmos12040472.

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A third-party-trained “Odor Patrol” program was conducted at a school that is about a one-mile distance from a landfill to clarify the odor nuisance problems from the landfill. Every 20 min from 6 to 9 a.m. on school days, the “Odor Profile Method” (OPM) was used with the landfill odor wheel to identify the odor type and intensity of each odor type. This study showed that an Odor Patrol using the OPM can accurately define odor nuisance changes over time and can be used as a method to confirm changes of odor nuisances in a field study. The Odor Patrol only found 13 data inputs of the 1000 data inputs (1.3%) for the 100-day odor monitoring with a landfill odor or trash odor that could cause odor complaints. The Odor Patrol data and the Odor Complaint data compared well. The OPM by an “Odor Patrol” could determine the contribution of the nuisance odors from 6 to 9 a.m. at the school site, about one mile away from the landfill. The study demonstrated a novel approach for odor monitoring by using the Odor Profile Method with an Odor Patrol. The OPM not only confirmed the mitigation of a landfill odor problem, but it also determined odor character, odor intensity, odor frequency and odor duration during this study period. “Landfill gas” was determined to be primarily a rotten vegetable odor with a secondary sewery/fecal odor of lower intensity, and “trash odors” were primarily a rancid and sweet odor with a secondary sewery/fecal and/or rotten vegetable odor of lower intensities generated from trash reaching the landfill. The order of intensity observed from high to low was: Trash odor (Rancid–Sweet) > Rotten vegetable > Sewery/Fecal > Rancid. Thus, trash odor is the major problematic odor from the landfill site. Quality assurance methods were used to remove local odors from the evaluation.
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Burlingame, G. A. "A practical framework using odor survey data to prioritize nuisance odors." Water Science and Technology 59, no. 3 (February 1, 2009): 595–602. http://dx.doi.org/10.2166/wst.2009.872.

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There are three main questions that need to be answered to address nuisance odors at the fenceline of a wastewater treatment plant: What odors are occurring at the fenceline of the plant? What processes within the plant give rise to these odors? What priority should we assign to mitigation of the nuisance odors? The prioritization is based on three factors that make odors a nuisance: strength or intensity of the odor when it is detected; quality or description of the odor; persistence or occurrence of the odor at the fenceline. Since fenceline odors vary according to: wind direction; wind speed; atmospheric stability and obstructions (buildings, trees, roadways), this study conducted odor surveys at the fenceline of a wastewater plant between April and November for 20 surveys. The data were used to develop a practical framework in three steps: summarize fenceline (residential vs non-residential) odor survey data; use odor type category and average odor strength to determine the annoyance factor; use annoyance factor and fenceline occurrence to determine the priority rating for nuisance odors to be mitigated.
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Öberg, Christina, Maria Larsson, and Lars Bäckman. "Differential sex effects in olfactory functioning: The role of verbal processing." Journal of the International Neuropsychological Society 8, no. 5 (July 2002): 691–98. http://dx.doi.org/10.1017/s1355617702801424.

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AbstractWe investigated sex difference across a number of olfactory tasks. Thirty-six men and 35 women ranging in age from 19 to 36 years were assessed in 6 different tasks: absolute sensitivity for n-butanol, intensity discrimination, quality discrimination, episodic recognition memory for familiar and unfamiliar odors, and odor identification. No sex differences were observed in the tasks tapping primarily sensory acuity (i.e., odor sensitivity, intensity discrimination, and quality discrimination) or in episodic memory for unfamiliar odors. By contrast, women outperformed men in the tasks involving verbal processing (i.e., memory for familiar odors and odor identification). Interestingly, controlling for odor naming ability resulted in that the observed sex difference in episodic odor memory for familiar odors disappeared. This outcome suggests that women's superiority in episodic odor memory is largely mediated by their higher proficiency in odor identification.
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Cho, Hyeon-Jun, and Su-Chul Yoon. "Occurrence of Designated Odor Substances in Wastewater Treatment Plant and Industrial Estate." Journal of Korean Society of Environmental Engineers 46, no. 3 (March 31, 2024): 73–80. http://dx.doi.org/10.4491/ksee.2024.46.3.73.

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Objectives : Odor emissions pose a challenge due to the diversity of odor-producing substances, their various sources, and the complex interactions between different compounds. Moreover, people's perception of odor intensity can vary based on their living environment and psychological state, making it difficult to effectively manage and develop mitigation measures for odors, in contrast to other air pollutants. To address this issue, this study focuses on two prominent sources of residential odors, namely wastewater treatment plant and industrial estate.Methods : Through on-site data collection, the study aims to investigate the characteristics of odor emissions and analyze seasonal trends in odor generation. Ultimately, the study seeks to assess the substances contributing to odors in wastewater treatment plant and industrial estate through odor contribution analysis.Results and Discussion : The research findings reveal that wastewater treatment plants predominantly emit high concentrations of fatty acid substances such as Propionic acid, iso-Valeric acid, and n-Valeric acid. In contrast, industrial estates release a variety of odor-causing substances, including Toluene, Xylene, Butyraldehyde, Trimethylamine, and iso-Valeraldehyde.Conclusion Significant differences are observed both in terms of odor concentration and odor contribution. These disparities are attributed to the specific characteristics of wastewater treatment plants and industrial processes that induce odors. Nevertheless, in both types of facilities, Trimethylamine is identified as a major contributor to odors.
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Tamura, Kaori, and Tsuyoshi Okamoto. "Odor descriptive ratings can predict some odor-color associations in different color features of hue or lightness." PeerJ 11 (April 20, 2023): e15251. http://dx.doi.org/10.7717/peerj.15251.

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Background Olfactory information can be associated with color information. Researchers have investigated the role of descriptive ratings of odors on odor-color associations. Research into these associations should also focus on the differences in odor types. We aimed to identify the odor descriptive ratings that can predict odor-color corresponding formation, and predict features of the associated colors from the ratings taking into consideration the differences in the odor types. Methods We assessed 13 types of odors and their associated colors in participants with a Japanese cultural background. The associated colors from odors in the CIE L*a*b* space were subjectively evaluated to prevent the priming effect from selecting color patches. We analyzed the data using Bayesian multilevel modeling, which included the random effects of each odor, for investigating the effect of descriptive ratings on associated colors. We investigated the effects of five descriptive ratings, namely Edibility, Arousal, Familiarity, Pleasantness, and Strength on the associated colors. Results The Bayesian multilevel model indicated that the odor description of Edibility was related to the reddish hues of associated colors in three odors. Edibility was related to the yellow hues of colors in the remaining five odors. The Arousal description was related to the yellowish hues in two odors. The Strength of the tested odors was generally related to the color lightness. The present analysis could contribute in investigating the influence of the olfactory descriptive rating that anticipates the associated color for each odor.
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Schoenbaum, G., and H. Eichenbaum. "Information coding in the rodent prefrontal cortex. I. Single-neuron activity in orbitofrontal cortex compared with that in pyriform cortex." Journal of Neurophysiology 74, no. 2 (August 1, 1995): 733–50. http://dx.doi.org/10.1152/jn.1995.74.2.733.

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1. Extracellular spike activity was recorded from 1,942 single neurons in orbitofrontal cortex (OF) and 591 single neurons in pyriform cortex (PIR) over multiple sessions in rats performing an eight-odor discrimination task in which the stimulus sequence contained predictable associations between particular odor pairs. Neural firing patterns were examined in relation to task events in the current trial and variables associated with current sensory processing, events of recent past trials, and long-term associations involving the odor cues. 2. Overall, 34% of single neurons in OF and 30% of single neurons in PIR fired selectively during one or more salient trial events including trial initiation, odor sampling, performance of the discriminative response, and water consumption. The activity of other cells recorded in OF (13%) and PIR (10%) was suppressed for the duration of each trial. Although the proportion of some cell types differed between the two areas, the firing patterns of OF and PIR neurons were qualitatively indistinguishable. 3. Firing during odor sampling and the discriminative response was influenced by the identity of the current odor. Some cells fired selectively to a single odor, but most cells were coarsely tuned such that they fired to several of the eight odors to differing degrees consistent with previous reports. Considerable odor coding was observed in both OF and PIR. 4. Firing during trial initiation and odor sampling was also influenced by the identity and reward association of the odor presented in the immediately preceding trial. The influence of past odor identity and valence was observed in both OF and PIR. 5. Firing during trial events was also influenced by the acquired associations between odors and their assigned reward contingencies and between pairs of odors involved in predictive relationships. The reward valence of the current odor significantly influenced firing during odor sampling and the discriminative response; some cells responded preferentially to rewarded odors and others to nonrewarded odors. Firing during trial initiation and odor sampling reflected whether or not the odor in the current trial had been predicted by the odor in the preceding trial. In addition, firing during odor sampling reflected the expectation of reward in the following trial that could be inferred from the predictable associations between odors. Each of these properties was observed in both OF and PIR. 6. The findings in OF were consistent with the view that prefrontal subdivisions mediate the temporal organization of complex behaviors within specific informational domains. OF appears to be concerned with the specific domain of olfaction.(ABSTRACT TRUNCATED AT 400 WORDS)
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Carmona-Escutia, Rosa Pilar, Edith Ponce-Alquicira, María Dolores García-Parra, Socorro Josefina Villanueva-Rodríguez, and Héctor B. Escalona-Buendía. "Changes in the Sensory Odor Profile during Chorizo Maturation and Their Relationship with Volatile Compound Patterns by Partial Least Square Regression (PLS)." Foods 12, no. 5 (February 22, 2023): 932. http://dx.doi.org/10.3390/foods12050932.

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Odor is one of the most important attributes to determine the overall acceptance of a product. The aim of this investigation is to evaluate the changes in the odor profile and the volatile compounds during thirty-three days of ripening to obtain the pattern of volatile compounds necessary to integrate the odor profile of chorizo (fermented sausage), using Partial Least Squares (PLS). The chili and pork meat odors were predominant during the first five days, vinegar and fermented odors at days twelve and nineteen days, and finally a rancid odor predominated at the end. Only the vinegar, rancid, and fermented odors could be predicted with a good fit model, with the R2 coefficient above 0.5, using linear PLS, and the pork meat odor using logarithmic PLS. Each group of volatile compounds interacted in different ways; esters had a positive influence on the vinegar and rancid odors, but a negative on the fermented odor. Some volatile compounds contributed to more than one odor, such as hexanal, ethanol, and ethyl octanoate. This work allowed us to understand the pattern of volatile compounds required to generate some of the specific odors of chorizo; further studies are required to explore the effect of other food components on these patterns of odors.
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Bhalla, Mukul, Kim M. Marcus, and John M. Cornwell. "ODOR Recognition and Identification: Effect of Labels over Time." Psychological Reports 86, no. 2 (April 2000): 565–74. http://dx.doi.org/10.2466/pr0.2000.86.2.565.

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The effect of labels on recognition and identification of odors over time was assessed. 30 men and 30 women were presented 20 odors; half of the participants were also told a name for the odor as a label. Five min. and 60 min. later, all participants were given 20 odors (10 from the original set, 10 new) and asked whether each odor was new or old (odor recognition). The group given labels was also asked to recall the label provided (odor identification). Analysis indicated a significant effect of time on recognition. Significantly more odors were recognized at 5 min. than 60 min. The effect of label was also significant, with recognition being better for the Label condition than the No-Label condition. As for odor identification, women identified more labels than did men. Overall, odor recognition was better with labels soon after exposure, and the women were better at remembering the labels than the men.
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Dissertations / Theses on the topic "Odor"

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So, Tak-wing. "Odour nuisance from restaurants and its control /." [Hong Kong] : University of Hong Kong, 1993. http://sunzi.lib.hku.hk/hkuto/record.jsp?B13498563.

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Murali, Sathish kumar. "Odor sensitivity in CD-1 mice for "green" odors." Thesis, Linköpings universitet, Molekylär genetik, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-68956.

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―Green‖ odors comprise a group of eight structurally related aliphatic alkenals and alkenols which are characteristic for the odor of a wide variety of plant materials. Using an automated olfactometer, the olfactory detection thresholds for ―green‖ odors were determined in six CD-1 mice and compared with that of spider monkeys and human subjects. Detection threshold values for alcoholic ‖green‖ odors (cis-3-hexen-1-ol, trans-3-hexen-1-ol, trans-2-hexen-1-ol and 1-hexanol) ranged from 8.1 x 109 to 8.1 x 1011 molecules/cm3 and for aldehydic ‖green‖ odors (cis-3-hexenal, trans-3-hexenal, trans-2-hexenal and n-hexanal) , from 8.1 x 107 to 8.1 x 1011 molecules/ cm3 . Detection threshold values of ―green‖ odor with double bond ranged from 8.1 x 107 to 8.1 x 1011 molecules/cm3 and for ―green‖ odor without double bond ranged from 8.1 x 108 to 8.1 x 1011 molecules/cm3. Detection threshold value of cis- configured ―green‖ odors ranged from 8.1 x 108 to 8.1 x 1011 molecules/ cm3 and for trans- configured ―green‖ odors threshold value ranged from 8.1 x 107 to 8.1 x 1011 molecules/ cm3. Trans-2-hexenal with a double bond at C-2 position in its molecular structure yielded the lowest detection threshold value when compared the other ―green‖ odors (8.1 x 107 to 8.1 x 109 molecules /cm3) which shows not only the presence of double bond plays a major role in detection but the position of the double bond present. A comparison between the present data and data from the other species showed that CD-1 mice displayed lower detection thresholds for all ‖green‖ odors than human subjects and spider monkeys except for the cis-3-hexen-1-ol odor. These findings suggest that the differences in the threshold values between ―green‖ odors are due to the difference in the molecular structure like the presence of double bond and the position of double bond.
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Vilalai, Sirapong. "Statistical odor prediction models for supporting biosolids odor management." College Park, Md.: University of Maryland, 2008. http://hdl.handle.net/1903/8805.

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Thesis (Ph. D.) -- University of Maryland, College Park, 2008.
Thesis research directed by: Dept. of Civil and Environmental Engineering Engineering. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
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Willander, Johan. "Autobiographical odor memory." Doctoral thesis, Stockholm : Department of Psychology, Stockholm University, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-7172.

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Legha, Prem. "Molecular structure and odor mixture perception." Thesis, View thesis, 2004. http://handle.uws.edu.au:8081/1959.7/549.

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The sense of smell is a primal sense for humans as well as animals.In everyday life the smells encountered are composed of dozens, even hundreds of odors; few arise from a single odorant. Enormous numbers of odors occur due to the vast variation in the concentration, size and structure of odorant molecules that makes olfaction differ from simpler visual or auditory dimensions. Accordingly, little is known about the ways in which changes in molecular structure and concentration of individual odorants change odor quality. Also, currently not much is understood about synergism/antagonism, how one odorant masks or suppresses another in mixtures and there is no method for predicting which odor will be suppressed. The two main objectives of this thesis were to determine whether a part of a molecular structure rather than the whole structure plays a key role in odor quality and whether a key part of a molecule can be used to choose antagonists for that odorant. For this study three classes of musks and two potential antagonists were used. The results of the study are discussed in some detail. It is concluded that future studies of the importance of molecular structure in mixture interactions require substantially more information on the relation between structure and odor quality to allow systematic studies to be developed. In summary the two hypotheses investigated were not supported by the results. Importantly, however, they do support the view that it is likely that odor quality is dependent on the whole structure of an odorant not a single feature.
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Arshamian, Artin. "Olfactory Cognition : The Case of Olfactory Imagery." Doctoral thesis, Stockholms universitet, Psykologiska institutionen, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-88413.

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The capacity to form olfactory images has received less attention than the formation of visual and auditory images. The evidence in favor of such ability is also inconsistent. This thesis explored some of the characteristics of olfactory imagery through three empirical studies. Study I investigated the effects of blocking spontaneous sniffing during olfactory imagery. The results indicated that the prevention of spontaneous sniffing reduced olfactory but not visual imagery capacity. Study II studied the relation between olfactory awareness (as indexed by olfactory dreams, olfactory imagery, and olfactory interest) and olfactory functions (i.e., odor threshold, episodic odor memory, and odor identification). The main findings were that compared to low, high olfactory awareness was associated with better episodic odor memory and identification, but not with higher olfactory sensitivity. Study III investigated the neural correlates of odor evoked autobiographical memories (OEAMs) as (a) a function of cue modality (i.e., odors and their verbal referents), and (b) a function of memory remoteness. The results from Study III showed that OEAMs activated regions generally associated with autobiographical memory. In addition, verbally cued OEAMs were associated with activity linked to olfactory imagery. Odor cues activated the limbic and temporal polar regions more than verbal cues; a result that may explain the phenomenological differences found between the cued memories. Moreover, OEAMs from the first decade of life were associated with higher activity in the secondary olfactory cortex, whereas memories from young adulthood were related to areas linked to semantic memory processing. Taken together these studies favor the notion of a human capacity to form olfactory images.
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Schreiner, Linda [Verfasser]. "Characterization of conifer wood regarding its odor-active constituents, their structure-odor relationships, and the influence of wood odors on humans / Linda Schreiner." München : Verlag Dr. Hut, 2020. http://d-nb.info/1220568031/34.

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Norton, Jenny Lynn. "Efficacy of Odor Scavengers in Reducing Odor Compounds in Water, Milk, and Soymilk." Thesis, Virginia Tech, 2003. http://hdl.handle.net/10919/45094.

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Odor detection thresholds of hexanal, 2-heptenal, 2-pentanone, and 2,4-nonadienal were determined in spring water, high temperature short time (HTST) 2% fat milk, and extended shelf life soymilk. The efficacy of odor scavenger's beta-cyclodextrin, D-sorbitol, and nylon 6 in removing these odors was also determined. The odor thresholds of the different odor and media combinations were as follows: hexanal in spring water, milk, and soymilk were 585, 339, and 536 ppb respectively; 2-heptenal in spring water, milk, and soymilk were 2,092, 2,322, and 3,184 ppb respectively; 2-pentanone in spring water, milk and soymilk were 24,925, 29,255 and 33,271 ppb respectively; and 2,4-nonadienal in spring water, milk, and soymilk were 164, 326, and 243 ppb respectively. These amounts reference the initial spiked concentration that was added directly to the media. Both hexanal and 2,4-nonadienal had lower thresholds than 2-heptenal and 2-pentanone in all of the media. The odor detection thresholds of 2-heptenal, 2-pentanone, and 2,4-nonadienal did show a significant difference between soymilk and water, but not for milk. The efficacy of the odor scavengers were determined by use of solid phase micro-extraction gas chromatography (SPME-GC) and sensory evaluation. Hexanal, 2-heptenal, 2-pentanone, and 2,4-nonadienal were spiked at 1,000, 3,000, 30,000, and 300 ppb respectively in all three media. Beta-cyclodextrin, D-sorbitol, and nylon 6 were added at a level of 0.1% w/v and 1.0% w/v. In all of the media, beta-cyclodextrin was found to significantly reduce hexanal, 2-pentanone, 2-heptenal, and 2,4-nonadienal at both 0.1% w/v and 1.0% w/v. Nylon 6 was not found beneficial.
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LocPort, Jamie Kendra. "THE NOSE KNOWS WHICH WAY THE ODOR FLOWS: SPATIAL ORIENTATION IN ODOR-GUIDED NAVIGATION." Case Western Reserve University School of Graduate Studies / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=case1522781434619908.

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Mašek, Pavel. "Odor intensity learning in Drosophila." [S.l.] : [s.n.], 2005. http://deposit.ddb.de/cgi-bin/dokserv?idn=979681405.

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Books on the topic "Odor"

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L, Cross Frank, ed. Odor control: Including hazardous/toxic odors. Lancaster: Technomic Pub. Co., 1989.

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Dravnieks, Andrew. Atlas of odor character profiles. Philadelphia, PA: ASTM, 1985.

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Manfred, Rothe. Introduction to aroma research. Dordrecht, Netherlands: Kluwer Academic Publishers, 1988.

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(Korea), Kungnip Hwanʼgyŏng Yŏnʼguwŏn, ed. So kyumo yŏngse saŏpchang akchʻwi kwalli pangan surip yŏnʼgu. [Inchʻŏn Kwangyŏksi]: Kungnip Hwanʼgyŏng Yŏnʼguwŏn, 2004.

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Inaba, Masumi, and Yoshikata Inaba. Human Body Odor. Tokyo: Springer Japan, 1992. http://dx.doi.org/10.1007/978-4-431-66908-1.

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Sinisgalli, Leonardo. L' odor moro. Cava dei Tirreni: Avagliano, 1990.

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Inaba, Masumi. Human body odor: Etiology, treatment, and related factors. Tokyo: Springer-Verlag, 1992.

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Force, Swine Odor Task, and North Carolina Agricultural Research Service., eds. Options for managing odor: A report from the Swine Odor Task Force. [Raleigh, N.C.]: North Carolina Agricultural Research Service, North Carolina State University, 1995.

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Buettner, Andrea, ed. Springer Handbook of Odor. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-26932-0.

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Heffernan, Michael. The odor of sanctity. Cliffs of Moher, County Clare, Ireland: Salmon Poetry, 2008.

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Book chapters on the topic "Odor"

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Patel, Himanshu K. "Odor." In Biological and Medical Physics, Biomedical Engineering, 85–113. New Delhi: Springer India, 2013. http://dx.doi.org/10.1007/978-81-322-1548-6_4.

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Bährle-Rapp, Marina. "Odor." In Springer Lexikon Kosmetik und Körperpflege, 384. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-71095-0_7094.

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Gooch, Jan W. "Odor." In Encyclopedic Dictionary of Polymers, 500. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-6247-8_8104.

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Lyman, Bernard. "Odor." In A Psychology of Food, 69–84. Dordrecht: Springer Netherlands, 1989. http://dx.doi.org/10.1007/978-94-011-7033-8_7.

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Capinera, John L., Marjorie A. Hoy, Paul W. Paré, Mohamed A. Farag, John T. Trumble, Murray B. Isman, Byron J. Adams, et al. "Nest Odor." In Encyclopedia of Entomology, 2596. Dordrecht: Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-6359-6_2193.

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Sterer, Nir, and Mel Rosenberg. "Odor Perception." In Breath Odors, 29–33. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-44731-1_4.

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Hannon, Bruce, and Matthias Ruth. "Odor Sensing." In Modeling Dynamic Biological Systems, 133–35. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05615-9_15.

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Heppner, John B., David B. Richman, Steven E. Naranjo, Dale Habeck, Christopher Asaro, Jean-Luc Boevé, Johann Baumgärtner, et al. "Species Odor." In Encyclopedia of Entomology, 3484. Dordrecht: Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-6359-6_4298.

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Gabrys, Beata, John L. Capinera, Jesusa C. Legaspi, Benjamin C. Legaspi, Lewis S. Long, John L. Capinera, Jamie Ellis, et al. "Colony Odor." In Encyclopedia of Entomology, 1008. Dordrecht: Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-6359-6_768.

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Brunner, Calvin R. "Odor Emissions." In Hazardous Air Emissions from Incineration, 66–76. Boston, MA: Springer US, 1985. http://dx.doi.org/10.1007/978-1-4613-2539-0_7.

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Conference papers on the topic "Odor"

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Nailos, Mary Ann, Dan Stein, Lawrence T. Nielsen, and Anna Iwasinska. "Analysis and Identification of Off-Odor Compounds in Electronic Systems." In ISTFA 2006. ASM International, 2006. http://dx.doi.org/10.31399/asm.cp.istfa2006p0020.

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Abstract The detection and identification of substances that give rise to aromas and off-odors is often a difficult task. Perception of odors is very subjective and odor detection thresholds vary from person to person. The identification of trace levels of compounds responsible for perceived odors is difficult using conventional analytical tools. This paper will focus on a novel method for sampling and analyzing aromatic volatile compounds using an analytical system specifically designed for odor analysis.
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Gu, Huaxi, Jiang Xu, and Zheng Wang. "ODOR." In the 6th IEEE/ACM/IFIP international conference. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1450135.1450181.

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Smith, Jake. "Odor Monitoring and Mitigation at the Hennepin County Waste to Energy Facility." In 15th Annual North American Waste-to-Energy Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/nawtec15-003.

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Hennepin Energy Recovery Center (HERC) is a waste to energy facility owned by Hennepin County and operated by Covanta Energy. HERC has been in operation since 1989. The facility burns 365,000 tons of residential and commercial solid waste per year and generates about 34 mega-watts of electricity that is sold to Xcel Energy. HERC is located on the north side of downtown Minneapolis in the Historic Warehouse District, a neighborhood that is changing from industrial to a more commercial/residential mix with loft conversions and construction of new condominiums. The Minnesota Twins baseball team is also siting a new stadium in the parking lot immediately southeast of the facility. The potential for odors from the tipping floor of the facility affecting the neighborhood has become more of a concern due to the changes in the neighborhood. In March 2004 the County began an odor study. This included developing baseline information on odors from HERC and from the surrounding community by conducting daily odor monitoring at select points on the facility property and throughout the community: • Determining how far odors from HERC migrate into the community. • Quantifying detected odors using a Nasal Ranger. • Determining the factors that contribute to these odors. • Developing a method of controlling these odors. • Continued monitoring to determine the impact of mitigation methods. Odors detected were characterized as garbage odors, garbage-related odors, and neighborhood odors. Baseline data showed that while garbage odors from HERC were mostly undetectable beyond the perimeter of the property, there was room for improvement in decreasing the presence and intensity of these odors. The tipping hall was designed to operate under negative pressure to control odors, however the entrance and exit doors were always open and a negative pressure could not be maintained.
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Guoliang Qu, IKE Edeogu, and John J.R Feddes. "Odor Index: an Integration of Odor Parameters." In 2008 Providence, Rhode Island, June 29 - July 2, 2008. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2008. http://dx.doi.org/10.13031/2013.25161.

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Lei, Menglong, and Chengyu Li. "A Balance Between Odor Intensity and Odor Perception Range in Odor-Guided Flapping Flight." In ASME 2022 Fluids Engineering Division Summer Meeting. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/fedsm2022-85407.

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Abstract Insects rely on their olfactory system to forage, prey, and mate. They can sense odorant plumes emitted from sources of their interests with their bilateral odorant antennae, and track down odor sources using their highly efficient flapping-wing mechanism. The odor-tracking process typically consists of two distinct behaviors: surging upwind at higher velocity and zigzagging crosswind at lower velocity. Despite extensive numerical and experimental studies on odor guided flight in insects, we have limited understandings on the effects of flight velocity on odor plume structure and its associated odor perception. In this study, a fully coupled three-way numerical solver is developed, which solves the 3D Navier-Stokes equations coupled with equations of motion for the passive flapping wings, and the odorant convection-diffusion equation. This numerical solver is applied to resolve the unsteady flow field and the odor plume transport for a fruit fly model at different flight velocities in terms of reduced frequency. Our results show that the odor plume structure and intensity are strong related to reduced frequency. At smaller reduced frequency (larger forward velocity), odor plume is pushed up during downstroke and draw back during upstroke. At larger reduced frequency (smaller forward velocity), the flapping wings induce a shield-like air flow around the antennae which may greatly increase the odor sampling range. Our finding may explain why flight velocity is important in odor guided flight.
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Takamizawa, Tadashi, Kazuki Miyagi, Hitoshi Miyauchi, Masahiro Imahashi, Kenshi Hayashi, and Perena Gouma. "Discrimination of Body Odor Using Odor Sieving Sensor System." In OLFACTION AND ELECTRONIC NOSE: PROCEEDINGS OF THE 14TH INTERNATIONAL SYMPOSIUM ON OLFACTION AND ELECTRONIC NOSE. AIP, 2011. http://dx.doi.org/10.1063/1.3626366.

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Zemba, Stephen G. "Do Odors at a Waste Management Facility Indicate a Risk to Health?" In 20th Annual North American Waste-to-Energy Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/nawtec20-7038.

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Odor control is a frequent issue at facilities that process municipal solid waste. Even waste-to-energy facilities, which are typically operated under “negative pressure,” may be less than 100% effective at preventing the occasional release of odorous emissions. When odors travel off-property to nearby residents and businesses, the tangible exposure often elicits concerns about the specific chemicals responsible for the odor and the potential for the emissions to affect public health. However, because the gaseous compounds that may lead to objectionable off-site odors are generally different than those that might result in adverse health effects, conditions of odor and risk are not as closely linked as is sometimes assumed. While odors can be assessed through personal observations, the assessment of risk requires detailed knowledge of the composition of the emitted gases. The gas produced from the aerobic decay of municipal solid waste contains a different mix of chemicals that are not as well characterized than gas produced from the anaerobic decay of waste in a landfill (which has been analyzed by the U.S. EPA and others). Air samples were recently collected from the tipping floor of a waste-to-energy facility, analyzed for chemical composition, and evaluated for their potential to lead to off-site health risks. The composition of the gas was found to be similar to published data from other MSW handling facilities, and includes both basic hydrocarbons and some EPA-designated Hazardous Air Pollutants. Thirty-two different volatile organic compounds were detected. Ethanol was found to be the most prevalent compound, almost two orders of magnitude greater in concentration than other chemicals. Additional compounds identified in the gas samples include (in order of abundance) methyl ethyl ketone, acetone, sec-butanol, isopentane, acetaldehyde, butane, isopropyl alcohol, limonene, and 1-propanol. A case-specific atmospheric dispersion of the gases was modeled to predict off-site concentrations much smaller than levels known to cause adverse health effects. Based on odor characteristics of the gas, generically extrapolating the study to other settings suggests that short-term odorous conditions due to MSW management facilities (waste-to-energy facilities, transfer stations, etc.) do not typically correspond to significant long-term health risks.
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Varshney, Kush R., and Lav R. Varshney. "Active odor cancellation." In 2014 IEEE Statistical Signal Processing Workshop (SSP). IEEE, 2014. http://dx.doi.org/10.1109/ssp.2014.6884566.

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Obrist, Marianna, Alexandre N. Tuch, and Kasper Hornbaek. "Opportunities for odor." In CHI '14: CHI Conference on Human Factors in Computing Systems. New York, NY, USA: ACM, 2014. http://dx.doi.org/10.1145/2556288.2557008.

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Kovačević, Dorotea, Dajana Kupres, Fran Šepat, and Maja Brozović. "Exploring odor associations based on packaging visual elements." In 11th International Symposium on Graphic Engineering and Design. University of Novi Sad, Faculty of technical sciences, Department of graphic engineering and design, 2022. http://dx.doi.org/10.24867/grid-2022-p57.

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Previous studies have shown that packaging design can influence people’s expectations regarding product attributes. This study explored the role of packaging visual design in presenting a nonvisual attribute (i.e. odor) by investigating consumers’ responses to various graphic designs displayed on perfume packaging. Particularly, the aim was to examine how different visual elements (such as patterns, photographs and illustrations) influence product choices, preferences and odor associations. 136 people participated in the study, with approximately equal numbers of males and females. They were presented with 10 packaging samples. The samples were of the same shape and size but with different visual elements. The results of the experiment confirmed that participants associated highly recognizable objects with their specific odors. For example, a lemon pattern was paired with a fresh smell, and an image of a rose was paired with a floral smell. On the other hand, when packaging presented odor-neutral objects, the participants’ responses were not uniform. The design which was associated with the largest range of smells was the one with a photograph of a human body, which was paired with three different perfume types (namely, floral, woody and oriental). When data were split by gender, the results suggested that men had a preference for regular and sharp visual shapes. Another relevant finding is that perception of perfume packaging can be influenced by age. Young participants mostly preferred abstract visual shapes for perfume presentations. The results of the choice task indicated that young participants were more sensitive to variations in design than mature participants. Furthermore, they associated most of the packaging designs with more than one type of smell. The findings can be useful for successful perfume packaging design, especially when young consumers are the main target audience.
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Reports on the topic "Odor"

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Simon, Alison G., Lauryn E. DeGreeff, Kimberly Peranich, Howard Holness, and Kenneth G. Furton. Canine Generalization to Molecularly Similar Odors and Odor Mixtures. Fort Belvoir, VA: Defense Technical Information Center, June 2018. http://dx.doi.org/10.21236/ad1056109.

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W.T. McKean. Low Odor, High Yield Kraft Pulping. Office of Scientific and Technical Information (OSTI), December 2000. http://dx.doi.org/10.2172/809123.

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Atema, Jelle. Odor Plume Tracing: Lobster Inspired Algorithms. Fort Belvoir, VA: Defense Technical Information Center, September 2001. http://dx.doi.org/10.21236/ada415619.

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Schmeisser, Elmar, Kimberly A. Pollard, and Tomasz Letowski. Olfaction Warfare: Odor as Sword and Shield. Fort Belvoir, VA: Defense Technical Information Center, March 2013. http://dx.doi.org/10.21236/ada577342.

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Beauchamp, Gary. Odor Signals of Immune Activation and CNS Inflammation. Fort Belvoir, VA: Defense Technical Information Center, December 2014. http://dx.doi.org/10.21236/ada612446.

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Abdul-Bari, Mohammed, and Rachel McQueen. Comparison of Odor Intensity between Nylon and Polyester. Ames: Iowa State University, Digital Repository, November 2016. http://dx.doi.org/10.31274/itaa_proceedings-180814-1575.

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Koseff, Jeffrey R. Hydrodynamic Interactions Between Olfactory Appendages and Odor Plumes. Fort Belvoir, VA: Defense Technical Information Center, April 2000. http://dx.doi.org/10.21236/ada375850.

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Beauchamp, Gary. Odor Signals of Immune Activation and CNS Inflammation. Fort Belvoir, VA: Defense Technical Information Center, October 2013. http://dx.doi.org/10.21236/ada596566.

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Willis, Mark A. Biologically-Inspired Search Algorithms for Locating Unseen Odor Sources. Fort Belvoir, VA: Defense Technical Information Center, May 2002. http://dx.doi.org/10.21236/ada402125.

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Kowton, Jennifer, and Rachel McQueen. The Perception of Odor in Textiles: An Exploratory Study. Ames: Iowa State University, Digital Repository, November 2016. http://dx.doi.org/10.31274/itaa_proceedings-180814-1393.

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