Science Talks最新文献

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Remote sensing applications for managing a large-scale restoration dynamics project throughout the City of Gold Coast conservation estate

Science Talks

Pub Date : 2025-01-31 DOI: 10.1016/j.sctalk.2025.100429

Jean-Marc Hero , Luke Shoo , Michael Duncan , Darren Roche , Jesse Kenny , Howard Taylor , Tim Robson , Sanjeev Kumar Srivastava , Josh Veitch-Michaelis

The City of Gold Coast established a program to restore native forests throughout the conservation estate (∼13,789 ha) utilizing constructed (CNR), assisted (ANR), and unassisted natural regeneration (UNR). Each year the city maintains over 4000 Ha of restoration works. The program is supported by an environmental decision support tool (oRestore) for the smart allocation of restoration funds over space and time (see [1] for details). We introduce the Restoration Dynamics Project, a quantitative evidence-based evaluation of the success of restoration actions undertaken between 2005 and 2022. Based on 17 restoration work areas (historically pasture dominated by exotic grasses, and open eucalypt forest vegetation (preclearing Regional Ecosystem 12.11.3), we compared optical and LiDAR vegetation metrics with field BioCondition assessments. UNR is suppressed by the presence of weed species that dominate cleared areas, resulting in low BioCondition. Unassisted, weeds can persist for decades, and intervention (ANR) is required for the recovery of native vegetation. CNR (tree-planting) provides canopy cover, however, lacks species diversity in the shrub layer. Assisted NR (controlling invasive species) is optimal for maximizing biodiversity in open eucalypt forests. LiDAR analytics can be a surrogate for BioCondition however field surveys are needed to determine non-native plant cover.

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引用次数: 0

3MT Competition (EUSIPCO2024): A peek into the black box: Insights into the functionality of complex-valued neural networks for multichannel speech enhancement

Science Talks

Pub Date : 2025-01-30 DOI: 10.1016/j.sctalk.2025.100430

Annika Briegleb

Artificial neural networks (ANNs) have become an important part of signal processing research. While ANNs outperform model-based signal processing methods in many applications, their internal processing often remains unclear. In this thesis, a framework for analyzing the signal processing performed by ANN-based filters for multichannel speech enhancement is proposed. By designing specific training and test scenarios that allow to associate each time frame with certain information, e.g., spatial cues, and using low-cost analysis tools such as clustering, interpretable information can be extracted from the hidden features of the ANN. The proposed framework allows to assess whether and where spatial information is represented inside the ANN, answering the question whether these ANNs exploit spatial cues in addition to spectral information. Furthermore, the impact of the choice of training target on the functionality and interpretability of the ANN is considered. By applying the proposed analysis tools to two conceptually different speech enhancement frameworks, it is shown that the amount of spatial information extracted inside the ANN varies depending on the training target and the test scenario. The insights from this thesis help to assess the signal processing capabilities of ANNs and allow to make informed decisions when configuring, training, and deploying ANNs.

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引用次数: 0

Erratum regarding missing Ethical Statements and Participant's Consents in previously published articles

Science Talks

Pub Date : 2025-01-30 DOI: 10.1016/j.sctalk.2025.100428

引用次数: 0

It tastes sweeter when melted: Exploring the impact of food temperature on tongue temperature and perceived sweetness/vanilla

Science Talks

Pub Date : 2025-01-27 DOI: 10.1016/j.sctalk.2025.100424

Hannah McNeill , Rebecca Ford , Ian Fisk , Margaret Thibodeau , Gloria Liu , Marion Doyennette , Qian Yang

The relationship between perceived sweetness intensity and temperature of food is complex. Previous research on the effect of temperature on sweetness perception primarily focused on single solutions. This study aimed to address the gap by using an infrared camera to measure tongue surface temperature, explore tongue temperature ranges, the relationship between sweet/flavour and tongue temperature at different serving temperatures during real food consumption. Participants (n = 22) consumed custard served at warm (59.1 ± 0.8 °C), ambient (24 ± 0.6 °C), chilled (4.6 ± 0.5 °C), and frozen (−2.7 ± 0.3) temperatures. An infrared camera was used to capture participant tongue surface temperature. Sweetness and vanilla intensity were recorded using a modified General Labelled Magnitude Scale. This study demonstrated that infrared imaging could effectively capture tongue surface temperature. Results revealed tongue surface temperature recovered to baseline more efficiently after cooling than warming. A weak positive correlation was found between tongue surface temperature, perceived sweetness (r = 0.234, p-value = 0.002) and vanilla intensity (r = 0.226, p-value = 0.003). Perceived sweetness intensity was significantly higher for warm custard (tongue = 37.3 °C, sweetness = 20.5) than frozen custard (tongue = 27.1 °C, sweetness = 13.3). This suggests that temperature changes on the tongue during food consumption could significantly contribute to the perceived intensity of sweetness. The findings provide valuable insights to food industries interested in sugar reduction.

{"title":"It tastes sweeter when melted: Exploring the impact of food temperature on tongue temperature and perceived sweetness/vanilla","authors":"Hannah McNeill , Rebecca Ford , Ian Fisk , Margaret Thibodeau , Gloria Liu , Marion Doyennette , Qian Yang","doi":"10.1016/j.sctalk.2025.100424","DOIUrl":"10.1016/j.sctalk.2025.100424","url":null,"abstract":"<div><div>The relationship between perceived sweetness intensity and temperature of food is complex. Previous research on the effect of temperature on sweetness perception primarily focused on single solutions. This study aimed to address the gap by using an infrared camera to measure tongue surface temperature, explore tongue temperature ranges, the relationship between sweet/flavour and tongue temperature at different serving temperatures during real food consumption. Participants (<em>n</em> = 22) consumed custard served at warm (59.1 ± 0.8 °C), ambient (24 ± 0.6 °C), chilled (4.6 ± 0.5 °C), and frozen (−2.7 ± 0.3) temperatures. An infrared camera was used to capture participant tongue surface temperature. Sweetness and vanilla intensity were recorded using a modified General Labelled Magnitude Scale. This study demonstrated that infrared imaging could effectively capture tongue surface temperature. Results revealed tongue surface temperature recovered to baseline more efficiently after cooling than warming. A weak positive correlation was found between tongue surface temperature, perceived sweetness (<em>r</em> = 0.234, <em>p</em>-value = 0.002) and vanilla intensity (<em>r</em> = 0.226, p-value = 0.003). Perceived sweetness intensity was significantly higher for warm custard (tongue = 37.3 °C, sweetness = 20.5) than frozen custard (tongue = 27.1 °C, sweetness = 13.3). This suggests that temperature changes on the tongue during food consumption could significantly contribute to the perceived intensity of sweetness. The findings provide valuable insights to food industries interested in sugar reduction.</div></div>","PeriodicalId":101148,"journal":{"name":"Science Talks","volume":"13 ","pages":"Article 100424"},"PeriodicalIF":0.0,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143348796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Learning context invariant representations for EEG data

Science Talks

Pub Date : 2025-01-27 DOI: 10.1016/j.sctalk.2025.100422

Thibault de Surrel

The goal of Brain-Computer Interfaces is to translate a user's brain activity into commands. To achieve this, the subject is equipped with sensors on their scalp that each record the electrical signals from a certain area of their brain using Electroencephalography (EEG). This EEG is a multivariate 0me series that contains very high-dimensional informa0on about brain activity. Unfortunately, EEGs are subject to a lot of variability, making it difficult to build a universal BCI. The goal of my PhD is to understand and tackle these variabilities. The most used representation of an EEG is its covariance matrix. As these matrices are symmetric positive definite (SPD), they live on a manifold that can be endowed with a Riemannian structure. This structure helps us better understand the intrinsic connections between the different SPD matrices in play. In my research, I am trying to build a probabilistic framework on the manifold of SPD matrices. The goal is to define and study a probability distribution that takes into account the Riemannian geometry of SPD matrices. Then, I could model a set of SPD matrices using this probability distribution and better understand how variabilities affect the covariance matrices derived from a BCI experiment.

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引用次数: 0

Magnetic Resonance Spectroscopy (MRS) transforming multiple sclerosis (MS) diagnosis

Science Talks

Pub Date : 2025-01-27 DOI: 10.1016/j.sctalk.2025.100427

Landoline Bonnin , Pascal Bourdon , Carole Guillevin , Remy Guillevin , Clement Giraud , Christine Fernandez-Maloigne

Anna is one of the 1.8 million people worldwide with multiple sclerosis who live with the uncertainty of disease progression every day [1]. Traditional Magnetic Resonance Imaging scans every six months reveal brain lesions but can't predict how the disease will progress [2]. A new technology, Magnetic Resonance Spectroscopy (MRS), shows promise in predicting disease progression by revealing cerebral metabolism and neurophysiological changes [3]. However, current MRS measurement methods vary between medical centers, affecting reliability [[4], [5], [6]]. Standardizing these measurements using Physics-Informed Neural Networks (PINNs), which are more reliable than traditional neural networks because they are based on the physics of spectra, could ensure accurate, comparable results worldwide [[7], [8], [9]]. This would reassure doctors and patients like Anna, and potentially improve their quality of life by enabling earlier and more precise treatment.

{"title":"Magnetic Resonance Spectroscopy (MRS) transforming multiple sclerosis (MS) diagnosis","authors":"Landoline Bonnin , Pascal Bourdon , Carole Guillevin , Remy Guillevin , Clement Giraud , Christine Fernandez-Maloigne","doi":"10.1016/j.sctalk.2025.100427","DOIUrl":"10.1016/j.sctalk.2025.100427","url":null,"abstract":"<div><div>Anna is one of the 1.8 million people worldwide with multiple sclerosis who live with the uncertainty of disease progression every day [<span><span>1</span></span>]. Traditional Magnetic Resonance Imaging scans every six months reveal brain lesions but can't predict how the disease will progress [<span><span>2</span></span>]. A new technology, Magnetic Resonance Spectroscopy (MRS), shows promise in predicting disease progression by revealing cerebral metabolism and neurophysiological changes [<span><span>3</span></span>]. However, current MRS measurement methods vary between medical centers, affecting reliability [<span><span>[4]</span></span>, <span><span>[5]</span></span>, <span><span>[6]</span></span>]. Standardizing these measurements using Physics-Informed Neural Networks (PINNs), which are more reliable than traditional neural networks because they are based on the physics of spectra, could ensure accurate, comparable results worldwide [<span><span>[7]</span></span>, <span><span>[8]</span></span>, <span><span>[9]</span></span>]. This would reassure doctors and patients like Anna, and potentially improve their quality of life by enabling earlier and more precise treatment.</div></div>","PeriodicalId":101148,"journal":{"name":"Science Talks","volume":"13 ","pages":"Article 100427"},"PeriodicalIF":0.0,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143204332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Flavourful insights into the saltiness perception of samphire

Science Talks

Pub Date : 2025-01-23 DOI: 10.1016/j.sctalk.2025.100425

Saumya Sood, Lisa Methven, Qiaofen Cheng

Samphire has been used as a salt substitute in cooked foods. However, the mechanism of its saltiness perception has not been fully understood. This study aimed to investigate whether saltiness could be induced either as a direct contribution from the volatiles within samphire or through involvement in Maillard reaction during cooking.

Odour profiling of samphire extracts revealed aromas such as seaweed, grassy green and tomato vine, relating to around 80 volatile compounds. However, these volatiles did not significantly enhance saltiness. Samphire extracts were incorporated into nachos at an equivalent sodium content to a control (with added NaCl) to investigate its contribution to saltiness perception through Maillard reaction. Sensory profiling revealed that samphire nachos were significantly saltier than control, alongside stronger umami taste and a distinctive green vegetable flavour. The Strecker aldehydes and the pyrazines were substantially and significantly higher in the samphire nachos than these in control. Pyrazines like 2,6-dimethylpyrazine, 2,3-dimethylpyrazine and 2-ethyl-5-methylpyrazines have previously been reported associated with enhancing salty taste. In conclusion, these Maillard derived compounds resulting from samphire addition may contribute to the increased saltiness of samphire nachos, supporting samphire extracts to be used as a combined salt substitute and flavour enhancer in heat-treated food products.

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引用次数: 0

Determining sensory drivers of complex metadescriptors through regression modelling

Science Talks

Pub Date : 2025-01-23 DOI: 10.1016/j.sctalk.2025.100423

Emily Fisher , Charles Diako , Rebecca Shingleton , Sidsel Jensen , Joanne Hort

In sensory science, terms such as creaminess often lack precise definitions due to their multi-modal nature. Least absolute shrinkage and selection operator (LASSO), a regression technique known for automatic predictor selection, and partial least squares regression, which handles multicollinearity, were compared for their ability to accurately identify the underlying sensory attributes driving creaminess perception.

Twenty-eight sensory attributes were selected after discussions with milk consumers. Thirty-two milk samples were chosen to represent these attributes, spanning a wide range of creaminess. Quantitative descriptive analysis, with trained panellists, and a consumer study (n = 117 New Zealand milk drinkers) assessed the sensory attributes and creaminess ratings, respectively. LASSO and PLSR were compared for their predictive ability and attributes retained using sensory attributes (trained panel) as predictors and creaminess ratings (consumers) as the response variable.

LASSO identified four key sensory attributes with a good model fit (R² = 0.951), while PLSR suggested thirteen (R² = 0.933). LASSO is effective in uncovering pertinent attributes within a complex sensory experience enabling cost-effective research. PLSR offers a comprehensive model for extensive product development. This research provides an alternative approach for determining pertinent attributes in complex metadesciptors. Resulting models offer clearer targets for product development, thus increased commercial gains.

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引用次数: 0

Smart natural technology & maintenance of sustainable aquatic environment: A study during lockdown

Science Talks

Pub Date : 2025-01-23 DOI: 10.1016/j.sctalk.2025.100426

Sucharita Bhattacharyya , Anwesh Bhowmick

Natural climatic changes and human activities affect environmental balance influencing various global ecosystems including the aquatic one. Here the Gangetic ecosystem of India with Dolphin is focused. The Ganges is India's longest river and its lifeline contributing immensely to the country's overall GDP. Again, it is home to many animals including the Dolphin, recognized to be a reliable health indicator with its hydrodynamic body system which works efficiently by the smart natural technique of echolocation and desquamation. However, industrial effluents, agricultural runoffs, discharge of untreated wastewater along with sedimentation produce gross negative effects on the Gangetic environment. These directly pollute the river, disrupt its regular flow, and obstruct the normal activities of the Dolphin, thus destroying its habitat which ultimately reduces the population and affects the river's bio-diversity balance. Country-wide lockdown during the COVID-19 Pandemic temporarily stops all human interventions. The net outcome is the rejuvenation of the water quality confirmed by the reappearance of the Dolphins after several years along its various stretches. So how the identified steps should be practiced to maintain the Gangetic ecosystem, while maintaining the country's economic growth, has been considered as the greatest challenge here.

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引用次数: 0

Towards the next generation of trustable, efficient and sustainable text-to-audio generative models

Science Talks

Pub Date : 2025-01-17 DOI: 10.1016/j.sctalk.2025.100419

Francesca Ronchini

Text-to-Audio (TTA) models are deep learning generative systems that generate audio samples from textual descriptions given as input to the models. The goal of this research is to leverage the opportunities of TTA models and advance them to address key challenges. Regarding opportunities, we proposed studies to investigate how these models can be easily integrated into music production practices as user-friendly sketching tools for audio samples, democratizing access to music creation without the need for sample libraries or instruments. They also offer significant potential for research and innovation. Deep learning models require large amounts of data to achieve good performance, but gathering data can be challenging. We demonstrated that by generating desired audio content through natural language, these models provide valuable training data for audio applications where data are not always massively available. However, several important challenges arise with these models, such as the rightful attribution of copyrighted data, the generation of deepfake content, and energy consumption, as shown in our studies. Through this comprehensive investigation, we aim to advance text-to-audio generative models by aligning their development with the needs of end users and society. Achieving this requires combining machine learning techniques with principles of ethics, sustainability, and trustworthiness.

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引用次数: 0

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