Science Talks最新文献

The increase in diseases and outbreaks triggered by pathogenic microorganisms of various kinds of bacteria has increased interest in the development of the use of natural materials as antibacterial agents. Natural materials that contain antibacterial substances can be found in essential oils. Plants that contain essential oils are very abundant in this world, especially clove oil. Clove oil has a high content of eugenol, which makes it have strong antibacterial properties. Therefore, many developments have been carried out in various fields related to clove oil, both in the medical field as an anti-inflammatory and analgesic, as well as in the food field as a food preservative and antibacterial food packaging. This study aims to present a comprehensive analysis map of publications related to the advantages of clove oil as an antibacterial bibliometrically using VOSviewer software. Such as research trends, emerging keywords, collaboration between researchers, and contributions from various countries. Using the query: ((TITLE-ABS-KEY(clove oil) AND TITLE-ABS-KEY(antibacterial))), 697 related literatures published in the period 1944–2024 were analyzed. From the data obtained, it was found that there was an increasing trend of publications although it was not significant and fluctuating. Overall, this research can be used to facilitate the author in identifying research gaps and become a strong basis for compiling a comprehensive and informative literature review for further research directions in the future of this research topic.

It is well known that perception of food and drink is a temporal phenomenon. And it is under this premise that several temporal methods have been developed in the past 50 years trying to capture, describe and quantify these sensory changes occurring during food tasting.

More than one hand is needed to count the amount of multi-attribute temporal methods which have been developed since 1994, when the Progressive Profile was first published. From one bite to a whole portion, these methods have been used to evaluate product qualities, consumer behavior and food oral processing, among other challenges. But sometimes it seems that methods are developed faster than they can be validated.

In this presentation 363 research articles (from 1991 to 2022) using temporal descriptive methods were analyzed according to a previously validated protocol. A quantitative and qualitative synthesis of the results allowed the identification of trends in how methods were developed, refined, and disseminated. Some critical research gaps in establishing the validity and reliability of the methods were identified and discussed. Results suggest the need for general guidelines on how to implement the method, analyze and interpret data, and report the results.

Hop water is advertised as an alcohol-free and zero-calorie beer alternative or a more “natural” flavored seltzer alternative. This study investigates whether experiential or contextual factors influence consumers to perceive hop water as more beer-like or seltzer-like. 43 regular seltzer-drinkers, 41 regular beer-drinkers, 45 regular drinkers of both, and 68 who regularly drink neither tasted three commercially-available hop waters inside one of three drinking contexts (apartment garden, office breakroom, or outdoor bar) simulated in an immersive room using sound and 360° video projection. They described their overall perceptions, similar products, and potential drivers of liking or disliking. In order to quantify the beer-likeness and seltzer-likeness of descriptions, we identified sensory terms associated with beer or seltzer using a Correspondence Analysis of descriptions of typical beers, seltzers, and other drink categories from 518 online survey responses. Tokenized responses from the immersive tasting were projected into this space and the highest-contributing terms determined. In the bar, participants more often compared drinks to beer. In the breakroom, participants focused on carbonation. Regular beer-drinkers described the products with less beer-like vocabulary. These findings suggest perceptual assimilation with context-based expectations and perceptual contrast with more familiar products, especially for products in-between well-known categories.

Obtaining detailed information regarding the surrounding environment of a host vehicle is crucial for the operation of autonomous driving and advanced driver assistance systems (ADAS). This necessitates radar systems equipped with high-resolution capabilities in range, Doppler, azimuth, and elevation. Terahertz (THz) frequency band radar systems offer the potential for nearly-optical resolution while being compact and lightweight. Nevertheless, the frequency-selective range-dependent attenuation of the THz propagation channel poses challenges to implementing automotive radars operating within this frequency band. The computational complexity of estimating the parameters of the THz channel adds to the challenge. Hence, automotive radar systems often adopt a simplified flat channel model for THz radar range estimation.

This study delves into the implications of this assumption on THz radar range performance estimation through the misspecified Crame'r-Rao bound (MCRB). Simulations are conducted to assess the ability of the proposed approach in evaluating the impact of frequency-selective misspecification on radar range estimation accuracy and detection range.

This study compared the probability of influenza A virus (IAV) ribonucleic acid (RNA) detection between selected individual and population-based samples in breeding herds. A 3500-sow breeding herd was sampled for matched sets (n = 57) of family oral fluids (FOF), udder wipes, sow nasal wipes, individual piglet nasal wipes, and drinker wipes and tested by reverse transcription real-time polymerase chain reaction (RT-rtPCR) for IAV RNA detection. Overall, 57.9% (33/57) of FOF samples, 49.1% (28/57) of udder wipes, 28.1% (16/57) of sow nasal wipes, 15.8% (9/57) of drinker wipes and 66.6% (38/57) of the individual piglet nasal wipes tested positive for IAV RNA. FOF had a kappa value of 0.81, a near-perfect agreement compared to individual piglet nasal wipes. Udder wipes revealed a kappa value of 0.65, a substantial agreement with individual piglet nasal wipes. The other sample types had a fair agreement with individual piglet nasal wipes (kappa values <0.28). These results validate FOF as an efficient alternative population-based sample type for IAV surveillance in the breeding herd. The proportion of positive piglets within litter by room A had 91% positivity (20/22), room B had 70% (17/24), and room C had 9% (1/11) positivity. The findings also highlight the importance of testing different farrowing rooms in the same breeding herd to strengthen IAV surveillance.

Semi-supervised learning (SSL) is a commonly used technique when annotated data is scarce but unlabeled data is easily available. In recent years, SSL has seen a large boost in the computer vision domain and methods such as FixMatch were successfully adapted to audio classification tasks. However, there still remains a gap between SSL methods and the fully supervised baselines, which were trained with all labels available. In this work, we first investigate the quality of the pseudo-labels, i.e., generated labels for unlabeled data, for musical instrument family classification and acoustic scene classification. Based on these insights, we propose and evaluate a novel extension of FixMatch that quantifies and considers the uncertainty of the pseudo-labels. Additionally, we highlight the problematic tradeoff between pseudo-label quality and quantity. Our results show that Monte-Carlo Dropout combined with temperature scaling improved the pseudo-label accuracy from 78.4% to 86.7% for instrument family and from 87.9% to 89.9% for acoustic scene classification. Even though the accuracy on the test sets improved from 71.0% to 72.1% and from 69.2% to 70.8%, respectively, there is still a gap to the fully supervised baseline leaving room for future work.

Accurate estimation of epidemic outbreak risks at any given time horizon, and in any national province of interest for COVID-19 (novel coronavirus disease, SARS-COV-2), a contagious disease, is of practical importance. This study proposes novel bio and health system's spatiotemporal reliability method, applicable to multi-regional national health systems. This approach enables accurate estimation of future epidemic outbreak risks, suitable for multiregional biological systems. Daily numbers of recorded patients in two different countries were chosen for this study. This study aimed to benchmark state-of-the-art reliability method, by extracting necessary health system information from nationally observed patient numbers, while taking into account national territorial mapping. Proper confidence bands have been estimated for predicted probability levels. Suggested multivariate reliability methodology may be used for various public health applications, based on available in situ clinical survey data. This study analyzed epidemiological dynamics, based on total numbers of nationally daily-recorded patients. It is recommended to study the percentage of infected patients, with respect to the local population tested. The suggested spatiotemporal methodology being general and well suitable for the latter task.

The Reserve Bank of India (RBI) has been cautious about “private virtual currencies” like Bitcoin and Ethereum because of the challenges they pose for regulation and security [16]. However, there's been a recent change in trend with the introduction of the Digital Rupee, a RBI backed digital currency [17]. This Digitalized version of rupee aims to induce the advantages of cryptocurrencies and side by side making sure the stability of legal tender.

The Digital Rupee aims to revolutionize Indian payment system by reducing all sorts of dependency on physical cash and promoting digital transactions [20]. This change from offline to online currency can possibly reduce the costs related with printing, storing, and transporting physical currency [5]. Moreover, it has the potential to extend financial services to unbanked societies by the option of accessible digital wallets [13].

However, like two sides of a coin, these benefits also have some challenges. Cybersecurity threats, privacy issues, and the need for robust technology and legal frameworks has to be addressed for the Digital Rupee to succeed. Overcoming these problems is imperative so that all citizens of India can access this technology.

Overall, the Digital Rupee signifies a major step forward for India's financial system. By fostering financial inclusion, improving efficiency, and combatting illicit activities, there is a possibility that the digital rupee can improve the financial landscape of India.

The development of membrane separation in industrial currently widely utilized, especially for electrodialysis membrane. Electrodialysis is becoming increasingly popular since it is an electrically driven membrane technology that mainly uses an ion exchange process. In this study, research trends of electrodialysis worldwide is presented, using a bibliometric study of publications from 1993 to 2023. The Scopus database found 1642 publications related to electrodialysis. The paper identifies several aspects of research assessment based on bibliometric analysis, including the trend, the most influential country, co-authorship, keyword term, publication metrics by Scimago Journal & Country Rank (SJR), and a comparison of each university using QS World University Rankings. China is the most prolific contributor in this area, with 439 publications. With 158 publications overall, 2022 has also shown the greatest number of electrodialysis publications. The two universities with the most publications are Université Laval in Canada and the University of Science and Technology of China, each with 66. Based on their QS World University Rankings performance assessment, both of them are suggested for advanced study, notably in the field of electrodialysis research. As a result, it is predicted that these bibliometrics will be useful for future advancements in the study of electrodialysis.

The fast pace of emerging product categories highlights the importance of ensuring that category labels meet consumer expectations, but the effect of category labels on consumer perception is not well understood. To examine the impact of category expectations on liking, 384 consumers were assigned one of four conditions where they were told they were drinking either milk (broad condition), plant-based milk (intermediate condition), almond milk (specific condition), or given no information (control group). All groups were given six almond milks and asked to rate their liking on a 9-point hedonic scale. Consumers in the broad, intermediate, and specific conditions were also asked to rate category fit on a 9-point Likert scale. Category label significantly impacted overall liking, with the specific condition having significantly higher liking than the control, followed by the intermediate and then the broad condition. External preference mapping showed that the sensory drivers of liking were constant across the four conditions, but the sensory drivers of category fit changed depending on the condition. Our results suggest that increased specificity in category labels can increase product liking, underscoring the importance of sensory evaluation for understanding the link between category labels and consumer perception.