Discussion on the Relevance of Old Low-lying Land Reclamation and Soil Liquefaction

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchive

The Capability of Canna edulis Ker Starch as Carboxymethyl Cellulose Replacement on Yogurt Drink During Cold Storage

The decreasing of yogurt drink quality will occur during storage. Stabilizer that usually used for maintaining the yogurt quality is a chemical compound namely carboxymethyl cellulose (CMC). Canna (Canna edulis Ker) potentially used as a natural stabilizer, which is a local Indonesian tuber with high starch content and antioxidative properties. The purpose of this study is to investigate the capability of Canna starch to replace the used of CMC based on the physicochemical and antioxidant activity of yogurt drink during cold storage. The complete randomized factorial design will be used with two factor. The first factor was Canna starch/CMC levels divided into 5 groups, T0 (0.2%CMC) as a control, T1 (0.15% CMC + 0.025% canna), T2 (0.1% CMC + 0.05% canna), T3 (0.05% CMC + 0.075% canna), and T4 (0.1% Canna), respectively. The second factor was the storage time of yogurt drink divided into four groups, 1, 7, 14 and 21 days, to determine the quality change during stored in the refrigerator at 4°C. Data obtained from the results of subsequent studies analyzed by GLM (General Linear Model) and followed by Duncan's multiple range test (DMRT). This study resulted that Canna starch has the capability as a natural stabilizer for producing functional yogurt drink with potential health benefits related to the high antioxidant activity. The combination of 0.1% CMC and 0.05% Canna starch addition on yogurt drink manufacture showed the best physicochemical qualit

Variation of the Fine-Structure Constant from the de Sitter Invariant Special Relativity

There are obvious discrepancies among various experimental constraints on the variation of the fine-structure constant, $\alpha$. We attempt to discuss the issue in the framework of de Sitter invariant Special Relativity (${\cal SR}_{c,R}$) and to present a possible solution to the disagreement. In addition, on the basis of the observational data and the discussions presented in this Letter, we derive a rough theoretical estimate of the radius of the Universe.Comment: 8 pages, no figure

Non-Additive Effects on Decomposition from Mixing Litter of the Invasive Mikania micrantha H.B.K. with Native Plants

A common hypothesis to explain the effect of litter mixing is based on the difference in litter N content between mixed species. Although many studies have shown that litter of invasive non-native plants typically has higher N content than that of native plants in the communities they invade, there has been surprisingly little study of mixing effects during plant invasions. We address this question in south China where Mikania micrantha H.B.K., a non-native vine, with high litter N content, has invaded many forested ecosystems. We were specifically interested in whether this invader accelerated decomposition and how the strength of the litter mixing effect changes with the degree of invasion and over time during litter decomposition. Using litterbags, we evaluated the effect of mixing litter of M. micrantha with the litter of 7 native resident plants, at 3 ratios: M1 (1:4, = exotic:native litter), M2 (1:1) and M3 (4:1, = exotic:native litter) over three incubation periods. We compared mixed litter with unmixed litter of the native species to identify if a non-additive effect of mixing litter existed. We found that there were positive significant non-additive effects of litter mixing on both mass loss and nutrient release. These effects changed with native species identity, mixture ratio and decay times. Overall the greatest accelerations of mixture decay and N release tended to be in the highest degree of invasion (mix ratio M3) and during the middle and final measured stages of decomposition. Contrary to expectations, the initial difference in litter N did not explain species differences in the effect of mixing but overall it appears that invasion by M. micrantha is accelerating the decomposition of native species litter. This effect on a fundamental ecosystem process could contribute to higher rates of nutrient turnover in invaded ecosystems. © 2013 Chen et al

Spatial and temporal characteristics of carbon emission and sequestration of terrestrial ecosystems and their driving factors in mainland China—a case study of 352 prefectural administrative districts

IntroductionGlobal climate change, increase in human activities, and prominence of ecological issues have led to uneven quantitative and spatial distributions of carbon emission and sequestration of terrestrial ecosystems. Such uneven distributions can lead to more negative impacts on the natural environment and human living conditions.MethodsTherefore, based on the carbon neutralization policy, we conducted geographically weighted regression (GWR) modeling in this study using panel data from 352 Chinese prefectural administrative districts in 2000, 2005, 2010, and 2017 to analyze and determine the impact factors and their spatial distribution for carbon emission and sequestration of terrestrial ecosystems.ResultsOur results showed that total population (TP), per capita gross domestic product (GDP) (PCG), proportion of secondary industry output (PSIO), scale of urban built-up area (SUB), green space proportion in city areas (GSP), normalized difference vegetation index (NDVI), and temperature (TEM) are factors driving carbon sequestration and carbon emission. The spatial distribution of these driving factors in mainland China is: (1) TP showed a negative correlation to carbon emission in most areas, while it exhibited a positive correlation to carbon sequestration in the southern, southwestern, and western parts of northwest China; however, in all other areas, TP showed a negative correlation with carbon sequestration; (2) PCG was positively correlated to carbon emission in most areas of China and to carbon sequestration in southwest, south, central, and northeast China; however, PCG demonstrated a negative correlation to carbon sequestration in the remaining areas; (3) PSIO and SUB presented a positive correlation to carbon emission and a negative correlation to carbon sequestration in most areas; (3) In contrast, GSP showed a negative correlation to carbon emission and a positive correlation to carbon sequestration in most areas; (5)NDVI showed a negative correlation to carbon emission and carbon sequestration in most areas toward the east of the “Heihe-Tengchong Line”; NDVI was positively correlated to both carbon emission and sequestration toward the west of this line; (6)TEM was positively correlated to carbon emission and sequestration in most parts of China.DiscussionBased on these results, we further divided the Chinese cities into 6 groups: (1) Groups 1, 2, 3, and 6 are areas where carbon emission and sequestration are governed by both socioeconomic and natural ecological factors. The major driving factors of carbon emission and carbon sequestration in group 1 are PSIO, GSP, and NDVI; the driving factors of group 2 are SUB and NDVI. Meanwhile, carbon emission and sequestration in group 3 are governed by PCG, GSP, and NDVI; for group 6, carbon emission and sequestration are controlled by PCG, SUB, GSP, and NDVI; (2) Group 4 represents areas where carbon emission and sequestration are majorly impacted by PCG and SUB, thereby rendering socioeconomic factors as the major driving forces. Group 5 represents areas where carbon emission and sequestration are sensitive to the natural environment, with GSP and NDVI being the driving factors. Considering the uneven distribution of carbon sequestration and emission and the diverse driving factors in different areas of China, we provided guidance for future environmental policies aimed at reducing the uneven distribution of carbon sequestration and emission in different areas to achieve carbon neutralization

Towards Better Query Classification with Multi-Expert Knowledge Condensation in JD Ads Search

Search query classification, as an effective way to understand user intents, is of great importance in real-world online ads systems. To ensure a lower latency, a shallow model (e.g. FastText) is widely used for efficient online inference. However, the representation ability of the FastText model is insufficient, resulting in poor classification performance, especially on some low-frequency queries and tailed categories. Using a deeper and more complex model (e.g. BERT) is an effective solution, but it will cause a higher online inference latency and more expensive computing costs. Thus, how to juggle both inference efficiency and classification performance is obviously of great practical importance. To overcome this challenge, in this paper, we propose knowledge condensation (KC), a simple yet effective knowledge distillation framework to boost the classification performance of the online FastText model under strict low latency constraints. Specifically, we propose to train an offline BERT model to retrieve more potentially relevant data. Benefiting from its powerful semantic representation, more relevant labels not exposed in the historical data will be added into the training set for better FastText model training. Moreover, a novel distribution-diverse multi-expert learning strategy is proposed to further improve the mining ability of relevant data. By training multiple BERT models from different data distributions, it can respectively perform better at high, middle, and low-frequency search queries. The model ensemble from multi-distribution makes its retrieval ability more powerful. We have deployed two versions of this framework in JD search, and both offline experiments and online A/B testing from multiple datasets have validated the effectiveness of the proposed approach