Chemical composition of Chinese palm fruit and chemical properties of the oil extracts

The proximate composition, mineral concentration of fleshy mesocarp, palm meat (PM) and palm kernel (PK) of oil palm fruit (Elaeis guineensis S.L.Dura) produced in Hainan, China were investigated. The fatty acid composition, chemical properties and minor constituents of palm oil (PO) and palm kernel oil (PKO) were also studied. The crude fat of PM and PK were 68.09±3.57% and 49.36±2.61%, respectively. The PM and PK were found to be good sources of minerals. The acid value (AV) and free fatty acid (FFA) of PO extracted from fresh PM were much higher. If the fresh PM were heated at 100ºC for 30 min, the AV and % FFA could be reduced to 4.62±0.04 mgKOH/g and 2.72±0.002%, respectively. The major fatty acid of PO was palmitic acid 39.93±1.66% and that of PKO was lauric acid 48.01±0.69%. Tocopherol isomer (α-, (β+γ)- and δ-) contents in PO were 68.8±1.84, 22.8±0.54 and 11.8±0.12 mg/kg, respectively. The β-carotene content in PO was 901.5±11.95 mg/kg. The content of sterols in PO and PKO were 880.0±5.23 and 858.0±4.37 mg/kg, respectively. PO and PKO exhibited good chemical properties and could be used as edible oils and for industrial applications. There are almost no data about Chinese palm fruit now and this study systematically researched on it, which can provide useful information for Chinese oil palm industry.Key words: Chemical composition, palm fruit, palm oil, palm kernel oil, chemical properties

Supply chain quality management: an investigation in the Chinese construction industry

Recently, in China, the issue of poor quality construction has drawn much public attention. This problem is related not only to poor quality control on the part of the construction firm, but also to the use of inadequate materials and inexperienced subcontractors, that is, to poor quality assurance in the construction supply chain. The purpose of this article is to examine supply chain quality management (SCQM) in the construction industry. Using a case-study approach, this research focuses on a Chinese medium-sized private enterprise in order to determine the most efficient way to conduct a high-quality project when collaborating with material suppliers and subcontractors. To this end, we replicate and extend the SCQM practices to help develop a more refined SCQM conceptual model relevant to the construction industry. Based on the different perspectives of managers and engineers, two frameworks are presented to illustrate (1) the correlation between SCQM and purchasing function (PF), and (2) how to work with material suppliers and subcontractors; the proposed models also show how these aspects will influence and control the quality of projects. Although constrained by the limitations inherent in case-study methodology, this article consolidates the work in one particular area of supply chain management. It also succeeds in meeting two core challenges, namely to explicate the interaction between SCQM and PF, and to provide guidance to construction firms on how to deal with SCQM issues with material suppliers and subcontractors

Towards Neural Mixture Recommender for Long Range Dependent User Sequences

Understanding temporal dynamics has proved to be highly valuable for accurate recommendation. Sequential recommenders have been successful in modeling the dynamics of users and items over time. However, while different model architectures excel at capturing various temporal ranges or dynamics, distinct application contexts require adapting to diverse behaviors. In this paper we examine how to build a model that can make use of different temporal ranges and dynamics depending on the request context. We begin with the analysis of an anonymized Youtube dataset comprising millions of user sequences. We quantify the degree of long-range dependence in these sequences and demonstrate that both short-term and long-term dependent behavioral patterns co-exist. We then propose a neural Multi-temporal-range Mixture Model (M3) as a tailored solution to deal with both short-term and long-term dependencies. Our approach employs a mixture of models, each with a different temporal range. These models are combined by a learned gating mechanism capable of exerting different model combinations given different contextual information. In empirical evaluations on a public dataset and our own anonymized YouTube dataset, M3 consistently outperforms state-of-the-art sequential recommendation methods.Comment: Accepted at WWW 201

Propionate Protects Haloperidol-Induced Neurite Lesions Mediated by Neuropeptide Y

Haloperidol is a commonly used antipsychotic drug for treating schizophrenia. Clinical imaging studies have found that haloperidol can cause volume loss of human brain tissue, which is supported by animal studies showing that haloperidol reduces the number of synaptic spines. The mechanism remains unknown. Gut microbiota metabolites, short chain fatty acids including propionate, are reported to have neuroprotective effect and influence gene expression. This study aims to investigate the effect and mechanism of propionate in the protection of neurite lesion induced by haloperidol. This study showed that 10 μM haloperidol (clinical relevant dose) impaired neurite length in human blastoma SH-SY5Y cells, which were confirmed by using primary mouse striatal spiny neurons. We found that haloperidol impaired neurite length were accompanied by a decreased neuropeptide Y (NPY) expression, but no effect on GSK3β signaling. Importantly, this project research found that propionate was capable of protecting against haloperidol-induced neurite lesions and preventing NPY reduction. To confirm this finding, we used specific siRNAs targeting NPY which blocked the protective effect of propionate on haloperidol-induced neurite lesions. Furthermore, since NPY is regulated by the nuclear transcription factor CREB, we measured pCREB that was decreased by haloperidol and was normalized by propionate. Therefore, propionate has a protective effect against pCREB-NPY mediated haloperidol-induced neurite lesions

Seasonal patterns of canopy photosynthesis captured by remotely sensed sun-induced fluorescence and vegetation indexes in mid-to-high latitude forests : a cross-platform comparison

© The Author(s), 2018. This is the author's version of the work and is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Science of The Total Environment 644 (2018): 439-451, doi:10.1016/j.scitotenv.2018.06.269.Characterized by the noticeable seasonal patterns of photosynthesis, mid-to-high latitude forests are sensitive to climate change and crucial for understanding the global carbon cycle. To monitor the seasonal cycle of the canopy photosynthesis from space, several remote sensing based indexes, such as normalized difference vegetation index (NDVI), enhanced vegetation index (EVI) and leaf area index (LAI), have been implemented within the past decades. Recently, satellite-derived sun-induced fluorescence (SIF) has shown great potentials of providing retrievals that are more related to photosynthesis process. However, the potentials of different canopy measurements have not been thoroughly assessed in the context of recent advances of new satellites and proposals of improved indexes. Here, we present a cross-site intercomparison of one emerging remote sensing based index of phenological index (PI) and two SIF datasets against the conventional indexes of NDVI, EVI and LAI to capture the seasonal cycles of canopy photosynthesis. NDVI, EVI, LAI and PI were calculated from Moderate Resolution Imaging Spectroradiometer (MODIS) measurements, while SIF were evaluated from Global Ozone Monitoring Experiment-2 (GOME-2) and Orbiting Carbon Observatory-2 (OCO-2) observations. Results indicated that GOME-2 SIF was highly correlated with gross primary productivity (GPP) and absorbed photosynthetically active radiation (APAR) during the growing seasons. Key phenological metrics captured by SIF from GOME-2 and OCO-2 matched closely with photosynthesis phenology as inferred by GPP. However, the applications of OCO-2 SIF for phenological studies may be limited only for a small range of sites (at site-level) due to a limited spatial sampling. Among the MODIS estimations, PI and NDVI provided most reliable predictions of start of growing seasons, while no indexes accurately captured the end of growing seasons.This work was supported by the Chinese Arctic and Antarctic Administration, National Natural Science Foundation of China (Grant Nos. 41676176 and 41676182), the Chinese Polar Environment Comprehensive Investigation, Assessment Program (Grant No. 312231103). This work was also supported by the Fundamental Research Funds for the 440 Central Universities2020-07-1

Armeniacae semen amarum: a review on its botany, phytochemistry, pharmacology, clinical application, toxicology and pharmacokinetics

Armeniacae semen amarum—seeds of Prunus armeniaca L. (Rosaceae) (ASA), also known as Kuxingren in Chinese, is a traditional Chinese herbal drug commonly used for lung disease and intestinal disorders. It has long been used to treat coughs and asthma, as well as to lubricate the colon and reduce constipation. ASA refers to the dried ripe seed of diverse species of Rosaceae and contains a variety of phytochemical components, including glycosides, organic acids, amino acids, flavonoids, terpenes, phytosterols, phenylpropanoids, and other components. Extensive data shows that ASA exhibits various pharmacological activities, such as anticancer activity, anti-oxidation, antimicrobial activity, anti-inflammation, protection of cardiovascular, neural, respiratory and digestive systems, antidiabetic effects, and protection of the liver and kidney, and other activities. In clinical practice, ASA can be used as a single drug or in combination with other traditional Chinese medicines, forming ASA-containing formulas, to treat various afflictions. However, it is important to consider the potential adverse reactions and pharmacokinetic properties of ASA during its clinical use. Overall, with various bioactive components, diversified pharmacological actions and potent efficacies, ASA is a promising drug that merits in-depth study on its functional mechanisms to facilitate its clinical application