A study on the consumer's perception of front-of-pack nutrition labeling

The goal of this research is to investigate the present situation for front of pack labeling in Korea and the perception of consumers for the new system of labeling, front of pack labeling, based on the consumer survey. We investigated the number of processed foods with front of pack labeling in one retailer in Youngin-si. And we also surveyed 1,019 participants nationwide whose ages were from 20 to 49; the knowledge of nutrition labeling, the knowledge of 'front of pack labeling', and the opinion about the labeling system. The data were analyzed using SAS statistics program. The results were as follows: 13.4% of processed foods had front of pack labeling, and 16.8% of the consumers always checked the nutrition labeling, while 32.7% of the consumers seldom checked it. In addition, 44.3% of the consumers think that 'front of pack labeling' is necessary, and 58.3% of the consumers think it is important to show the percentage of daily value as a way of 'front of pack labeling'. However, 32% of the consumer think the possibility of 'front of pack labeling' is slim. Meanwhile, 58.3% of the consumers think that it is important to have the color difference according to contents. The number of favorite nutrients in the front of pack was four or five. It seems that the recognition of current nutrition labeling has the influence on the willingness of using the future 'front of pack labeling'. Along with our study, the policy for 'front of pack labeling' has to be updated and improved constantly since 'front of pack labeling' helps consumer understand nutrition facts

Hierarchical Joint Graph Learning and Multivariate Time Series Forecasting

Multivariate time series is prevalent in many scientific and industrial domains. Modeling multivariate signals is challenging due to their long-range temporal dependencies and intricate interactions--both direct and indirect. To confront these complexities, we introduce a method of representing multivariate signals as nodes in a graph with edges indicating interdependency between them. Specifically, we leverage graph neural networks (GNN) and attention mechanisms to efficiently learn the underlying relationships within the time series data. Moreover, we suggest employing hierarchical signal decompositions running over the graphs to capture multiple spatial dependencies. The effectiveness of our proposed model is evaluated across various real-world benchmark datasets designed for long-term forecasting tasks. The results consistently showcase the superiority of our model, achieving an average 23\% reduction in mean squared error (MSE) compared to existing models.Comment: Temporal Graph Learning Workshop @ NeurIPS 2023, New Orleans, United State

Can We Utilize Pre-trained Language Models within Causal Discovery Algorithms?

Scaling laws have allowed Pre-trained Language Models (PLMs) into the field of causal reasoning. Causal reasoning of PLM relies solely on text-based descriptions, in contrast to causal discovery which aims to determine the causal relationships between variables utilizing data. Recently, there has been current research regarding a method that mimics causal discovery by aggregating the outcomes of repetitive causal reasoning, achieved through specifically designed prompts. It highlights the usefulness of PLMs in discovering cause and effect, which is often limited by a lack of data, especially when dealing with multiple variables. Conversely, the characteristics of PLMs which are that PLMs do not analyze data and they are highly dependent on prompt design leads to a crucial limitation for directly using PLMs in causal discovery. Accordingly, PLM-based causal reasoning deeply depends on the prompt design and carries out the risk of overconfidence and false predictions in determining causal relationships. In this paper, we empirically demonstrate the aforementioned limitations of PLM-based causal reasoning through experiments on physics-inspired synthetic data. Then, we propose a new framework that integrates prior knowledge obtained from PLM with a causal discovery algorithm. This is accomplished by initializing an adjacency matrix for causal discovery and incorporating regularization using prior knowledge. Our proposed framework not only demonstrates improved performance through the integration of PLM and causal discovery but also suggests how to leverage PLM-extracted prior knowledge with existing causal discovery algorithms

Fate of Iprobenfos and Tricyclazole at Paddy Cultivation Environment

Objectives This study aimed to identify the fate of iprobenfos and tricyclazole in the soil and paddy water during the rice cultivation process and to identify their exposure pathways into surface water. Methods Both iprobenfos and tricyclazole were sprayed onto two sample sites following the pesticide safety usage guidelines. Residues in the samples. Soil, paddy water, and drainage water samples were collected for 28 days after post-application. Residues were subsequently analyzed using LC-MS/MS. Results and Discussion The fate of the two pesticides, iprobenfos and tricyclazole, in the rice cultivation environment was influenced by factors such as soil half-life, Koc, water solubility, formulation, and precipitation patterns. Initial concentrations of iprobenfos and tricyclazole in the paddy field near the drainage were 5,774 μg/L and 307 μg/L, respectively, while concentrations in the drain water were 1,850 μg/L and 182 μg/L. Four days after application, the residual concentrations of iprobenfos and tricyclazole in both paddy and drain water ranged from N.D. (Not Detected) to 5.6 μg/L and N.D. to 56 μg/L, respectively, indicating a rapid decline. During the experimental period, the average concentration reduction ratios in drain water near the drainage compared to the drain water were higher for tricyclazole (90%) than for iprobenfos (52%). Conclusion The soil and water half-life of tricyclazole exceeded that of iprobenfos, leading to a slower rate of concentration reduction. The lower Koc value for tricyclazole suggests enhanced soil desorption due to rainfall, increasing its concentration in paddy fields. The presence of iprobenfos and tricyclazole in surface water is likely due to dispersion during pesticide application. While concentrations diminish owing to the dilution effect when water moves from paddy fields to surface water, it's posited that runoff could affect nearby stream water within seven days post-application

The Role of Light and Circadian Clock in Regulation of Leaf Senescence

Leaf senescence is an integrated response of the cells to develop age information and various environmental signals. Thus, some of the genes involved in the response to environmental changes are expected to regulate leaf senescence. Light acts not only as the primary source of energy for photosynthesis but also as an essential environmental cue that directly control plant growth and development including leaf senescence. The molecular mechanisms linking light signaling to leaf senescence have recently emerged, exploring the role of Phytochrome-Interacting Factors (PIFs) as a central player leading to diverse senescence responses, senescence-promoting gene regulatory networks (GRNs) involving PIFs, and structural features of transcription modules in GRNs. The circadian clock is an endogenous time-keeping system for the adaptation of organisms to changing environmental signals and coordinates developmental events throughout the life of the plant. Circadian rhythms can be reset by environmental signals, such as light-dark or temperature cycles, to match the environmental cycle. Research advances have led to the discovery of the role of core clock components as senescence regulators and their underlying signaling pathways, as well as the age-dependent shortening of the circadian clock period. These discoveries highlight the close relationship between the circadian system and leaf senescence. Key issues remain to be elucidated, including the effect of light on leaf senescence in relation to the circadian clock, and the identification of key molecules linking aging, light, and the circadian clock, and integration mechanisms of various senescence-affecting signals at the multi-regulation levels in dynamics point of view.1

INVESTIGATION ON EFFECTS OF ENLARGED PIPE RUPTURE SIZE AND AIR PENETRATION TIMING IN REALSCALE EXPERIMENT OF SIPHON BREAKER

To ensure the safety of research reactors, the water level must be maintained above the required height. When a pipe ruptures, the siphon phenomenon causes continuous loss of coolant until the hydraulic head is removed. To protect the reactor core from this kind of accident, a siphon breaker has been suggested as a passive safety device. This study mainly focused on two variables: the size of the pipe rupture and the timing of air entrainment. In this study, the size of the pipe rupture was increased to the guillotine break case. There was a region in which a larger pipe rupture did not need a larger siphon breaker, and the water flow rate was related to the size of the pipe rupture and affected the residual water quantity. The timing of air entrainment was predicted to influence residual water level. However, the residual water level was not affected by the timing of air entrainment. The experimental cases, which showed the characteristic of partical sweep-out mode in the separation of siphon breaking phenomenon [2], showed almost same trend of physical properties.ungraded1111Ysciescopu

Therapeutic Potential of Ursonic Acid: Comparison with Ursolic Acid

Plants have been used as drugs to treat human disease for centuries. Ursonic acid (UNA) is a naturally occurring pentacyclic triterpenoid extracted from certain medicinal herbs such as Ziziphus jujuba. Since the pharmacological effects and associated mechanisms of UNA are not well-known, in this work, we attempt to introduce the therapeutic potential of UNA with a comparison to ursolic acid (ULA), a well-known secondary metabolite, for beneficial effects. UNA has a keto group at the C-3 position, which may provide a critical difference for the varied biological activities between UNA and ULA. Several studies previously showed that UNA exerts pharmaceutical effects similar to, or stronger than, ULA, with UNA significantly decreasing the survival and proliferation of various types of cancer cells. UNA has potential to exert inhibitory effects in parasitic protozoa that cause several tropical diseases. UNA also exerts other potential effects, including antihyperglycemic, anti-inflammatory, antiviral, and antioxidant activities. Of note, a recent study highlighted the suppressive potential of UNA against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Molecular modifications of UNA may enhance bioavailability, which is crucial for in vivo and clinical studies. In conclusion, UNA has promising potential to be developed in anticancer and antiprotozoan pharmaceuticals. In-depth investigations may increase the possibility of UNA being developed as a novel reagent for chemotherapy

Novel cell balancing applied near-field coupling and Serial–Parallel Circuit configuration

This paper proposes a near-field cell balancing method to be applied to batteries of higher capacity and power. This method involves a wireless power transfer to balance battery cells, which produces higher efficiency than conventional passive approaches, and faster equalization than active approaches. Cell balancing is a crucial function of the battery management system (BMS) that maintains the balance of charge and discharge between cells of individual batteries. Furthermore, this method is designed to meet the increasing demand for faster cell balancing associated with high-capacity and high-power batteries. We selected a serial–parallel configuration to minimize the technical concern for isolation, or energy transfer to unselected cells. Experiments were conducted with two battery cells, and voltage equalization accelerated by 51% when the proposed cell balancing approach was applied

Iterative C−H Functionalization Leading to Multiple Amidations of Anilides

Polyaminobenzenes were synthesized by the ruthenium-catalyzed iterative C−H amidation of anilides using dioxazolones as an amino source. This strategy could be implemented by the sequential activation of C−H bonds of formerly generated compounds by cascade chelation assistance of newly installed amide groups. Computational studies provided a rationale. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinhei118191sciescopu