Evaluating the Effectiveness of Margin Parameter when Learning Knowledge Embedding Representation for Domain-specific Multi-relational Categorized Data

Learning knowledge representation is an increasingly important technology that supports a variety of machine learning related applications. However, the choice of hyperparameters is seldom justified and usually relies on exhaustive search. Understanding the effect of hyperparameter combinations on embedding quality is crucial to avoid the inefficient process and enhance practicality of vector representation methods. We evaluate the effects of distinct values for the margin parameter focused on translational embedding representation models for multi-relational categorized data. We assess the margin influence regarding the quality of embedding models by contrasting traditional link prediction task accuracy against a classification task. The findings provide evidence that lower values of margin are not rigorous enough to help with the learning process, whereas larger values produce much noise pushing the entities beyond to the surface of the hyperspace, thus requiring constant regularization. Finally, the correlation between link prediction and classification accuracy shows traditional validation protocol for embedding models is a weak metric to represent the quality of embedding representation

Making ways for 'better education': Placing the Shenzhen-Hong Kong mobility industry

Tens of thousands of children living on Mainland China cross the border between Shenzhen and Hong Kong for a ‘better education’ every day. A well-oiled industry is in place to manage, facilitate and control this education mobility field. It involves schools, diverse businesses and non-governmental organisations that, in articulation with the Chinese and Hong Kong states, stimulate and regulate the movement of people, materialities, ideas and practices. Drawing on our fieldwork and media analysis, this paper unpacks the transurban mobility industry to illustrate the role of the various players and how they work in conjunction to facilitate cross-border schooling, especially among the very young children. We map out and visualise with photos the workings of the schools, buses, escorts, tutoring centres, day care and boarding houses. We show how the mobility industry, intersecting with other business networks and mobility systems, links Shenzhen and Hong Kong, taking and making places in these cities, especially in the border region. Our paper illustrates the role of this mobility industry in the making of the political-economy and socio-culture of the border area, which constantly connects, divides and redefines the two cities and regions it bridges. We end with some reflections on the implications of the recent political challenges and COVID-19 pandemic on this cross-border education mobility system

Effect of fulvic acids on lead-induced oxidative stress to metal sensitive Vicia faba L. plant

Lead (Pb) is a ubiquitous environmental pollutant capable to induce various morphological, physiological, and biochemical functions in plants. Only few publications focus on the influence of Pb speciation both on its phytoavailability and phytotoxicity. Therefore, Pb toxicity (in terms of lipid peroxidation, hydrogen peroxide induction, and photosynthetic pigments contents) was studied in Vicia faba plants in relation with Pb uptake and speciation. V. faba seedlings were exposed to Pb supplied as Pb(NO3)2 or complexed by two fulvic acids (FAs), i.e. Suwannee River fulvic acid (SRFA) and Elliott Soil fulvic acid (ESFA), for 1, 12, and 24 h under controlled hydroponic conditions. For both FAs, Pb uptake and translocation by Vicia faba increased at low level (5 mg l−1), whereas decreased at high level of application (25 mg l−1). Despite the increased Pb uptake with FAs at low concentrations, there was no influence on the Pb toxicity to the plants. However, at high concentrations, FAs reduced Pb toxicity by reducing its uptake. These results highlighted the role of the dilution factor for FAs reactivity in relation with structure; SRFA was more effective than ESFA in reducing Pb uptake and alleviating Pb toxicity to V. faba due to comparatively strong binding affinity for the heavy metal

Identification of sulfation sites of metabolites and prediction of the compounds’ biological effects

Characterizing the biological effects of metabolic transformations (or biotransformation) is one of the key steps in developing safe and effective pharmaceuticals. Sulfate conjugation, one of the major phase II biotransformations, is the focus of this study. While this biotransformation typically facilitates excretion of metabolites by making the compounds more water soluble, sulfation may also lead to bioactivation, producing carcinogenic products. The end result, excretion or bioactivation, depends on the structural features of the sulfation sites, so obtaining the structure of the sulfated metabolites is critically important. We describe herein a very simple, high-throughput procedure for using mass spectrometry to identify the structure—and thus the biological fate—of sulfated metabolites. We have chemically synthesized and analyzed libraries of compounds representing all the biologically relevant types of sulfation products, and using the mass spectral data, the structural features present in these analytes can be reliably determined, with a 97% success rate. This work represents the first example of a high-throughput analysis that can identify the structure of sulfated metabolites and predict their biological effects

Phytoscreening and phytoextraction of heavy metals at Danish polluted sites using willow and poplar trees

The main purpose of this study was to determine typical concentrations of heavy metals (HM) in wood from willows and poplars, in order to test the feasibility of phytoscreening and phytoextraction of HM. Samples were taken from one strongly, one moderately, and one slightly polluted site and from three reference sites. Wood from both tree species had similar background concentrations at 0.5 mg kg(−1) for cadmium (Cd), 1.6 mg kg(−1) for copper (Cu), 0.3 mg kg(−1) for nickel (Ni), and 25 mg kg(−1) for zinc (Zn). Concentrations of chromium (Cr) and lead (Pb) were below or close to detection limit. Concentrations in wood from the highly polluted site were significantly elevated, compared to references, in particular for willow. The conclusion from these results is that tree coring could be used successfully to identify strongly heavy metal-polluted soil for Cd, Cu, Ni, Zn, and that willow trees were superior to poplars, except when screening for Ni. Phytoextraction of HMs was quantified from measured concentration in wood at the most polluted site. Extraction efficiencies were best for willows and Cd, but below 0.5 % over 10 years, and below 1 ‰ in 10 years for all other HMs. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11356-013-2085-z) contains supplementary material, which is available to authorized users

Behavior and Impact of Zirconium in the Soil–Plant System: Plant Uptake and Phytotoxicity

Because of the large number of sites they pollute, toxic metals that contaminate terrestrial ecosystems are increasingly of environmental and sanitary concern (Uzu et al. 2010, 2011; Shahid et al. 2011a, b, 2012a). Among such metals is zirconium (Zr), which has the atomic number 40 and is a transition metal that resembles titanium in physical and chemical properties (Zaccone et al. 2008). Zr is widely used in many chemical industry processes and in nuclear reactors (Sandoval et al. 2011; Kamal et al. 2011), owing to its useful properties like hardness, corrosion-resistance and permeable to neutrons (Mushtaq 2012). Hence, the recent increased use of Zr by industry, and the occurrence of the Chernobyl and Fukashima catastrophe have enhanced environmental levels in soil and waters (Yirchenko and Agapkina 1993; Mosulishvili et al. 1994 ; Kruglov et al. 1996)