Browsing by Author "Wang T"
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- Item3D Printing of Textured Soft Hybrid Meat Analogues(MDPI (Basel, Switzerland), 2022-02-06) Wang T; Kaur L; Furuhata Y; Aoyama H; Singh J; Mirade PSMeat analogue is a food product mainly made of plant proteins. It is considered to be a sustainable food and has gained a lot of interest in recent years. Hybrid meat is a next generation meat analogue prepared by the co-processing of both plant and animal protein ingredients at different ratios and is considered to be nutritionally superior to the currently available plant-only meat analogues. Three-dimensional (3D) printing technology is becoming increasingly popular in food processing. Three-dimensional food printing involves the modification of food structures, which leads to the creation of soft food. Currently, there is no available research on 3D printing of meat analogues. This study was carried out to create plant and animal protein-based formulations for 3D printing of hybrid meat analogues with soft textures. Pea protein isolate (PPI) and chicken mince were selected as the main plant protein and meat sources, respectively, for 3D printing tests. Then, rheology and forward extrusion tests were carried out on these selected samples to obtain a basic understanding of their potential printability. Afterwards, extrusion-based 3D printing was conducted to print a 3D chicken nugget shape. The addition of 20% chicken mince paste to PPI based paste achieved better printability and fibre structure.
- ItemDisentangling the effects of temperature and reactive minerals on soil carbon stocks across a thermal gradient in a temperate native forest ecosystem(Springer Nature, 2024-03) Siregar IH; Camps-Arbestain M; Kereszturi G; Palmer A; Kirschbaum MUF; Wang T; Weintraub-Lef SREffects of global warming on soil organic carbon (C) can be investigated by comparing sites experiencing different temperatures. However, observations can be affected by covariance of temperature with other environmental properties. Here, we studied a thermal gradient in forest soils derived from volcanic materials on Mount Taranaki (New Zealand) to disentangle the effects of temperature and reactive minerals on soil organic C quantity and composition. We collected soils at four depths and four elevations with mean annual temperatures ranging from 7.3 to 10.5 °C. Soil C stocks were not significantly different across sites (average 162 MgC ha−1 to 85 cm depth, P >.05). Neither aluminium (Al)-complexed C, nor mineral-associated C changed significantly (P >.05) with temperature. The molecular characterisation of soil organic matter showed that plant-derived C declined with increasing temperature, while microbial-processed C increased. Accompanying these changes, soil short-range order (SRO) constituents (including allophane) generally increased with temperature. Results from structural equation modelling revealed that, although a warmer temperature tended to accelerate soil organic C decomposition as inferred from molecular fingerprints, it also exerted a positive effect on soil total C presumably by enhancing plant C input. Despite a close linkage between mineral-associated C and soil organic C, the increased abundance of reactive minerals at 30–85 cm depth with temperature did not increase soil organic C concentration at that depth. We therefore propose that fresh C inputs, rather than reactive minerals, mediate soil C responses to temperature across the thermal gradient of volcanic soils under humid-temperate climatic conditions
- ItemEvolutionary Game and Simulation of Green Housing Market Subject Behavior in China.(John Wiley and Sons, 2022-04-05) Qian Y; Yu M; Wang T; Yuan R; Feng Z; Zhao X; Fu HIn China, driven by the national "3060" double carbon targets (i.e., reaching peak carbon emissions by 2030 and carbon neutrality by 2060), green housing has become one of the major fields to reduce carbon emissions, facilitating the achievement of the double carbon targets. Promoting the growth of green housing is an important way for the real estate industry to achieve low-carbon transformation and improve the quality of housing. Meanwhile, the construction industry also can benefit from green housing to achieve its energy conservation and emission reduction targets. Therefore, it is critical to boost and maintain the sustainable growth of the green housing market in China. However, the literature has not focused attention on the market behavior of the green housing market in China. This study proposes a tripartite evolutionary game model to investigate the subject behavior of the green housing market in China. This model consists of three major subjects in a green housing market: developers, consumers, and governments. Based on this model, this study analyzes the stability of the strategy options for each stakeholder and identifies the stable conditions of strategy portfolios to reach the equilibrium points of the game system. The validity of the proposed tripartite evolutionary game model is tested through the simulation of the impacts from various factors on system evolution. According to the impacts of factors and the stable conditions of strategies, this paper puts forward relevant policy suggestions for the healthy and sustainable growth of China's green housing market.
- ItemForecasting Eruptions at Poorly Known Volcanoes Using Analogs and Multivariate Renewal Processes(John Wiley and Sons, Inc on behalf of the American Geophysical Union, 2022-06-28) Wang T; Bebbington M; Cronin S; Carman JForecasting future destructive eruptions from re-awakening volcanoes remains a challenge, mainly due to a lack of previous event data. This sparks a search for similar volcanoes to provide additional information, especially those with better compiled and understood event records. However, we show that some of the most obviously geologically comparable volcanoes have differing statistical occurrence patterns. Using such matches produces large forecasting uncertainties. We created a statistical tool to identify and test the compatibility of potential analogue volcanoes based on repose-time characteristics from world-wide datasets. Selecting analogue volcanoes with compatible behavior for factors being forecast, such as repose time, significantly reduces forecasting uncertainties. Applying this tool to Tongariro volcano (NZ), there is a 5% probability for a Volcanic Explosivity Index (VEI) ≥ 3 explosive eruption in the next 50 years. Using pre-historic geological records of a smaller available set of analogs, we forecast a 1% probability of a VEI ≥ 4 eruption in the next 50 years.
- ItemHigher temperature accelerates carbon cycling in a temperate montane forest without decreasing soil carbon stocks(Elsevier B.V., 2024-11-09) Siregar IH; Camps-Arbestain M; Wang T; Kirschbaum MUF; Kereszturi G; Palmer AGlobal warming is expected to accelerate the cycling of soil organic carbon (SOC) and the assimilation of new carbon, but the net effect of those counteracting accelerations and their ultimate effects on SOC are still uncertain. This hinders the prediction of long-term changes in biospheric carbon stocks and SOC-climate feedbacks. Here, we studied the long-term effect of temperature on carbon cycling across a 3.2 °C altitudinal temperature gradient in a temperate forest ecosystem in New Zealand. Across the gradient, soil respiration rates increased with increasing temperature from 9.0 to 10.4 tC ha−1 yr−1, but SOC stocks down to 85 cm depth also tended to increase, from 154 to 176 tC ha−1, albeit non-significantly (P = 0.06). This system was able to maintain higher soil respiration rates at higher temperatures without reducing SOC because the higher respiration rates were sustained by higher litterfall rates. Aboveground litterfall increased from 1.8 to 2.4 tC ha−1 yr−1 and estimated belowground C inputs increased from 7.2 to 8.0 tC ha−1 yr−1 along the temperature gradient. These higher fluxes were associated with significantly (P < 0.05) increased biomass at higher temperatures. As a direct measure of the effect of temperature on carbon cycling processes, we also calculated the turnover rate of forest litter which increased about 1.4-fold across the temperature gradient. This study demonstrates that higher temperatures along the thermal gradient increased plant carbon inputs through enhanced gross primary production, which counteracted SOC losses through temperature-enhanced soil respiration. These results suggest that temperature sensitivities of both plant carbon inputs and SOC losses must be considered for predicting SOC-climate feedbacks.
- ItemLifestyle and incident dementia: A COSMIC individual participant data meta-analysis(Wiley Periodicals LLC on behalf of Alzheimer's Association, 2024-06-16) Van Asbroeck S; Köhler S; van Boxtel MPJ; Lipnicki DM; Crawford JD; Castro-Costa E; Lima-Costa MF; Blay SL; Shifu X; Wang T; Yue L; Lipton RB; Katz MJ; Derby CA; Guerchet M; Preux P-M; Mbelesso P; Norton J; Ritchie K; Skoog I; Najar J; Sterner TR; Scarmeas N; Yannakoulia M; Dardiotis T; Rolandi E; Davin A; Rossi M; Gureje O; Ojagbemi A; Bello T; Kim KW; Han JW; Oh DJ; Trompet S; Gussekloo J; Riedel-Heller SG; Röhr S; Pabst A; Shahar S; Rivan NFM; Singh DKA; Jacobsen E; Ganguli M; Hughes T; Haan M; Aiello AE; Ding D; Zhao Q; Xiao Z; Narazaki K; Chen T; Chen S; Ng TP; Gwee X; Gao Q; Brodaty H; Trollor J; Kochan N; Lobo A; Santabárbara J; Gracia-Garcia P; Sachdev PS; Deckers K; for Cohort Studies of Memory in an International Consortium (COSMIC)INTRODUCTION: The LIfestyle for BRAin Health (LIBRA) index yields a dementia risk score based on modifiable lifestyle factors and is validated in Western samples. We investigated whether the association between LIBRA scores and incident dementia is moderated by geographical location or sociodemographic characteristics. METHODS: We combined data from 21 prospective cohorts across six continents (N = 31,680) and conducted cohort-specific Cox proportional hazard regression analyses in a two-step individual participant data meta-analysis. RESULTS: A one-standard-deviation increase in LIBRA score was associated with a 21% higher risk for dementia. The association was stronger for Asian cohorts compared to European cohorts, and for individuals aged ≤75 years (vs older), though only within the first 5 years of follow-up. No interactions with sex, education, or socioeconomic position were observed. DISCUSSION: Modifiable risk and protective factors appear relevant for dementia risk reduction across diverse geographical and sociodemographic groups. HIGHLIGHTS: - A two-step individual participant data meta-analysis was conducted. - This was done at a global scale using data from 21 ethno-regionally diverse cohorts. - The association between a modifiable dementia risk score and dementia was examined. - The association was modified by geographical region and age at baseline. - Yet, modifiable dementia risk and protective factors appear relevant in all investigated groups and regions.
- ItemManipulating the alpha level cannot cure significance testing – comments on "Redefine statistical significance"(PeerJ Preprints, 2017-11-14) Trafimov D; Amrhein V; Areshenkoff CN; Barrera - Causil C; Beh EJ; Bilgiç Y; Bono R; Bradley MT; Briggs WM; Cepeda - Freyre HA; Chaigneau SE; Ciocca DR; Correa JC; Cousineau D; de Boer MR; Dhar SS; Dolgov I; Gómez - Benito J; Grendar M; Grice J; Guerrero - Gimenez ME; Gutiérrez A; Huedo - Medina TB; Jaffe K; Janyan A; Karimnezhad A; Korner - Nievergelt F; Kosugi K; Lachmair M; Ledesma R; Limongi R; Liuzza MT; Lombardo R; Marks M; Meinlschmidt G; Nalborczyk L; Nguyen HT; Ospina R; Perezgonzalez JD; Pfister R; Rahona JJ; Rodríguez - Medina DA; Romão X; Ruiz - Fernández S; Suarez I; Tegethoff M; Tejo M; van de Schoot R; Vankov I; Velasco - Forero S; Wang T; Yamada Y; Zoppino FCM; Marmolejo - Ramos FWe argue that depending on p-values to reject null hypotheses, including a recent call for changing the canonical alpha level for statistical significance from .05 to .005, is deleterious for the finding of new discoveries and the progress of science. Given that blanket and variable criterion levels both are problematic, it is sensible to dispense with significance testing altogether. There are alternatives that address study design and determining sample sizes much more directly than significance testing does; but none of the statistical tools should replace significance testing as the new magic method giving clear-cut mechanical answers. Inference should not be based on single studies at all, but on cumulative evidence from multiple independent studies. When evaluating the strength of the evidence, we should consider, for example, auxiliary assumptions, the strength of the experimental design, or implications for applications. To boil all this down to a binary decision based on a p-value threshold of .05, .01, .005, or anything else, is not acceptable.
- ItemPhysico-chemical and Textural Properties of 3D Printed Plant-based and Hybrid Soft Meat Analogs(Springer Science+Business Media, LLC, part of Springer Nature, 2023-06) Wang T; Kaur L; Beniwal AS; Furuhata Y; Aoyama H; Singh JThis study investigated the physico-chemical and textural properties of 3D-printed pea protein-only and pea protein-chicken-based hybrid meat analogs. Both pea protein isolate (PPI)-only and hybrid cooked meat analogs had a similar moisture content of approximately 70%, which was similar to that of chicken mince. However, the protein content increased significantly with the amount of chicken in the hybrid paste undergoing 3D printing and cooking. Significant differences were observed in the hardness values of the non-printed cooked pastes and the 3D printed cooked counterparts, suggesting that the 3D printing process reduces the hardness of the samples and is a suitable method to produce a soft meal, and has significant potential in elderly health care. Scanning electron microscopy (SEM) revealed that adding chicken to the plant protein matrix led to better fiber formation. PPI itself was not able to form any fibers merely by 3D printing and cooking in boiling water. Protein-protein interactions were also studied through the protein solubility test, which indicated that hydrogen bonding was the major bonding that contributed to the structure formation in cooked printed meat analogs. In addition, disulfide bonding was correlated with improved fibrous structures, as observed through SEM.
- ItemTFGNet: Frequency-guided saliency detection for complex scenes(Elsevier B.V., 2025-01-08) Wang Y; Wang R; Liu J; Xu R; Wang T; Hou F; Liu B; Lei NSalient object detection (SOD) with accurate boundaries in complex and chaotic natural or social scenes remains a significant challenge. Many edge-aware or/and two-branch models rely on exchanging global and local information between multistage features, which can propagate errors and lead to incorrect predictions. To address this issue, this work explores the fundamental problems in current U-Net architecture-based SOD models from the perspective of image spatial frequency decomposition and synthesis. A concise and efficient Frequency-Guided Network (TFGNet) is proposed that simultaneously learns the boundary details (high-spatial frequency) and inner regions (low-spatial frequency) of salient regions in two separate branches. Each branch utilizes a Multiscale Frequency Feature Enhancement (FFE) module to learn pixel-wise frequency features and a Transformer-based decoder to learn mask-wise frequency features, improving a comprehensive understanding of salient regions. TFGNet eliminates the need to exchange global and local features at intermediate layers of the two branches, thereby reducing interference from erroneous information. A hybrid loss function is also proposed to combine BCE, IoU, and Histogram dissimilarity to ensure pixel accuracy, structural integrity, and frequency distribution consistency between ground truth and predicted saliency maps. Comprehensive evaluations have been conducted on five widely used SOD datasets and one underwater SOD dataset, demonstrating the superior performance of TFGNet compared to state-of-the-art methods. The codes and results are available at https://github.com/yiwangtz/TFGNet.
- ItemWBNet: Weakly-supervised salient object detection via scribble and pseudo-background priors(Elsevier Ltd, 2024-10) Wang Y; Wang R; He X; Lin C; Wang T; Jia Q; Fan XWeakly supervised salient object detection (WSOD) methods endeavor to boost sparse labels to get more salient cues in various ways. Among them, an effective approach is using pseudo labels from multiple unsupervised self-learning methods, but inaccurate and inconsistent pseudo labels could ultimately lead to detection performance degradation. To tackle this problem, we develop a new multi-source WSOD framework, WBNet, that can effectively utilize pseudo-background (non-salient region) labels combined with scribble labels to obtain more accurate salient features. We first design a comprehensive salient pseudo-mask generator from multiple self-learning features. Then, we pioneer the exploration of generating salient pseudo-labels via point-prompted and box-prompted Segment Anything Models (SAM). Then, WBNet leverages a pixel-level Feature Aggregation Module (FAM), a mask-level Transformer-decoder (TFD), and an auxiliary Boundary Prediction Module (EPM) with a hybrid loss function to handle complex saliency detection tasks. Comprehensively evaluated with state-of-the-art methods on five widely used datasets, the proposed method significantly improves saliency detection performance. The code and results are publicly available at https://github.com/yiwangtz/WBNet.
