A detection problem: Sensitivity and uncertainty analysis of a land surface temperature approach to detecting dynamics of water use by groundwater-dependent vegetation

Sustainable management of groundwater-dependent vegetation (GDV) requires the accurate identification of GDVs, characterisation of their water use dynamics and an understanding of associated errors. This paper presents sensitivity and uncertainty analyses of one GDV mapping method which uses temperature differences between time-series of modelled and observed land surface temperature (LST) to detect groundwater use by vegetation in a subtropical woodland. Uncertainty in modelled LST was quantified using the Jacobian method with error variances obtained from literature. Groundwater use was inferred where modelled and observed LST were significantly different using a Student's t-test. Modelled LST was most sensitive to low-range wind speeds (<1.5 m s⁻¹), low-range vegetation height (<=0.5 m), and low-range leaf area index (<=0.5 m² m⁻²), limiting the detectability of groundwater use by vegetation under such conditions. The model-data approach was well-suited to detection of GDV because model-data errors were lowest for climatic conditions conducive to groundwater use.     

Fast intrusion detection based on a non-negative matrix factorization model

In this paper, we present an efficient fast anomaly intrusion detection model incorporating a large amount of data from various data sources. A novel method based on non-negative matrix factorization (NMF) is presented to profile program and user behaviors of a computer system. A large amount of high-dimensional data is collected in our experiments and divided into smaller data blocks by a specific scheme. The system call data is divided into blocks by processes, while command data is divided into consecutive blocks with a fixed length. The frequencies of individual elements in each block of data are computed and placed column by column as data vectors to construct a matrix representation. NMF is employed to reduce the high-dimensional data vectors and anomaly detection can be realized as a very simple classifier in low dimensions. Experimental results show that the model presented in this paper is promising in terms of detection accuracy, computation efficiency and implementation for fast intrusion detection.     

Ultraviolet Photoluminescence of Carbon Nanospheres and its Surface Plasmon‐Induced Enhancement

Ultraviolet (UV) light can be used in versatile applications ranging from photoelectronic devices to biomedical imaging. In the development of new UV light sources, in this study, stable UV emission at ≈350 nm is unprecedentedly obtained from carbon nanospheres (CNSs). The origin of the UV fluorescence is comprehensively investigated via various characterization methods, including Raman and Fourier transform infrared analyses, with comparison to the visible emission of carbon nanodots. Based on the density functional calculations, the UV fluorescence is assigned to the carbon nanostructures bonded to bridging O atoms and dangling –OH groups. Moreover, a twofold enhancement in the UV emission is acquired for Au‐carbon core‐shell nanospheres (Au‐CNSs). This remarkable modification of the UV emission is primarily ascribed to charge transfer between the CNSs and the Au surface.     

Enhanced CO2/N2 selectivity in amidoxime-modified porous carbon

In this work, we examine the use of the amidoxime functional group grafted onto a hierarchical porous carbon framework for the selective capture and removal of carbon dioxide from combustion streams. Measured CO₂/N₂ ideal selectivity values for the amidoxime-grafted carbon were significantly higher than the pristine porous carbon with improvements of 65%. Though the overall CO₂ capacity decreased slightly for the activated carbon from 4.97 mmol g⁻¹ to 4.24 mmol g⁻¹ after surface modification due to a reduction in the total surface area, the isosteric heats of adsorption increased after amidoxime incorporation indicating an increased interaction of CO₂ with the sorbent. Total capacity was reproducible and stable after multiple adsorption/desorption cycles with no loss of capacity suggesting that modification with the amidoxime group is a potential method to enhance carbon capture.     

Emerging functional nanomaterials for the detection of food contaminants

Along with the progress in nanoscience, a variety of advanced functional nanomaterials were constructed to develop effective and innovative analytical techniques for food safety surveillance. In this review, we summarized the advanced analytical methods that have been developed based upon advanced functional nanomaterials, including plasmonic nanomaterial-based colorimetric methods, fluorescent nanomaterial-based fluorescent methods, advanced functional material-based molecular imprinting technology, advanced functional material-based chromatographic methods, plasmonic nanomaterial-based surface enhanced Raman scattering technology, and advanced functional material-based electrochemical methods. This review provides a progressive roadmap for further development of portable, rapid, and in situ detection technology to promote food safety surveillance from bench to market and eventually reduce the gap between research in the laboratory and industrial applications.     

Chinese red pepper (Zanthoxylum bungeanum Maxim.) leaf extract as natural antioxidants in salted silver carp (Hypophthalmichthys molitrix) in dorsal and ventral muscles during processing

Chinese red pepper (Zanthoxylum bungeanum Maxim.) leaf (ZML) extract contains high amounts of phenolic compounds possessing high total antioxidant capacity and hydroxyl, 1, 1-dipheny-2-picrylhydrazyl (DPPH) free radical scavenging activity. ZML extract was investigated as a natural antioxidant for the lipid stability of salted silver carp (Hypophthalmichthys molitrix) throughout salting and drying. Both dorsal and ventral muscles were examined for differences in moisture content, salt content, total lipid content, and degree of lipid oxidation. The hexanal content, Thiobarbituric acid reactive substances (TBARS) value, and lipoxygenase (LOX) activity in the ventral muscle were significantly higher than those of the dorsal muscle (p < 0.05). In the treatments with ZML extract, the hexanal content, the TBARS value, and the LOX activity were significantly lower (p < 0.05) during processing both in the dorsal and ventral muscles. The sensory qualities of processed salted fish could be improved with the amount of 0.030% extract in the dorsal muscle and 0.045% extract in the ventral muscle. These results showed that ZML extract can be a source of natural antioxidants and used as a food additive.     

间接竞争化学发光酶免疫法检测动物源食品中的 呋喃西林代谢物

目的建立动物源食品中呋喃西林代谢物间接竞争化学发光酶免疫检测方法。方法采用活化酯法将衍生后的呋喃西林代谢物半抗原与卵清蛋白(ovalbumin,OVA)偶联成为包被原;其次,对化学发光液体系、包被原和单克隆抗体的最优稀释倍数及其他反应条件进行优化;最后对该法的灵敏度、特异性、精密度及准确度进行评价。结果化学发光液A液为8 mmol/L对碘苯酚溶液和10 mmol/L鲁米诺溶液(1:1,V:V)混合,B液为每10 m L三(羟甲基)氨基甲烷(Tris)-盐酸缓冲液加5μL 30%H_2O_2溶液,A液与B液临用前体积比1:1混匀;最优反应条件是包被原和单抗稀释倍数均为800,封闭液为1%脱脂乳,竞争时间30 min,酶标二抗孵育60 min;该法的线性方程为Y=-0.4654X+0.3768(r~2=0.993),线性范围为0.123~2.398 ng/m L,IC50为0.544 ng/m L,批内和批间变异系数分别为1.9%~4.1%和2.8%~5.3%,空白鸡肉样品添加回收率为89.6%~98.0%。结论该检测方法简单快速,可用于实验室或现场动物源食品中呋喃西林代谢物的筛查。     

酶法制备花生粕醒酒多肽

为更合理有效地利用花生粕资源,制备具有醒酒作用的花生粕多肽,本实验以Alcalase AF 2.4L蛋白酶酶法制备花生粕醒酒肽,经分级分离后,通过体外和动物实验验证其醒酒效果。结果表明,花生粕醒酒肽制备最佳工艺条件为：酶解时间3 h、酶解温度35 ℃、pH 9.5及料液比1∶30（m/V）。该条件下乙醇脱氢酶（alcoholdehydrogenase,ADH）激活率及多肽得率均较高。经分级分离后,分子质量在1 000～3 000 D的多肽对ADH激活作用最强,激活率为30.47%。G25凝胶色谱分析表明,花生粕多肽中小于3 000 D的多肽占89.55%,ADH激活率为29.25%。动物实验证明,花生粕多肽对小鼠有显著的防醉醒酒作用。小鼠血液乙醇含量测定结果表明,高剂量的花生粕多肽在60～90 min内能显著降低小鼠血液中的乙醇含量。     

多维灰聚类分析在熟肉制品安全风险评估中的应用

以某省2011年餐饮服务食品安全抽检数据为基础,采用灰理论对当年餐饮服务环节熟肉制品的食品安全风险程度做出多维灰聚类评估。评估结果显示抽检中不合格样品大多属于低风险类,可以得出当年熟肉制品的食品安全状况属于安全可控状态。该法更加明确了食品安全风险的等级,加强了监管餐饮环节食品安全的有效性,也为今后评估食品安全风险等级提供了一种新的研究方法。