The composition and microbial quality of pre-packed dates purchased in Greater Glasgow

Composition and microbiological contamination was measured in samples of pre-packed dates purchased from a number of stores and retail outlets in Greater Glasgow. The sugar content of dried pitted dates was c . 74%, about 10% more than reported on those packs where nutritional information was given. Potentially pathogenic bacteria like Escherichia coli, Staphylococcus aureus and Bacillus cereus were identified in some of the samples together with lactic acid bacteria, yeasts and moulds, Aspergillus flavus and A. parasiticus . Fresh dates were the most heavily contaminated of all samples, probably owing to the high moisture content.     

Use of chemical variation and predation as plant defenses byEncelia farinosa against a specialist herbivore

Larvae of the monophagous herbivore,Trirhabda geminata, selectively eat particular plants and plant parts of its natural host,Encelia farinosa. Measurements of leaf damage and larval positions on branches through time support this observation. Time-lapse movie photography revealed that larvae are sufficiently mobile to search most of a plant in a 48-hr period and that aggregations were the result of larval activity and not directly the result of oviposition. Experiments withT. geminata larvae on artificial diets containing a range of natural concentrations of chemical extracts fromE. farinosa leaves showed that the larvae grew significantly slower and had a lower overall survivorship at the high concentration. Combining the results of all choice tests, larvae appeared unable to distinguish between high- and low-concentration agar diets. Considered individually, larval preferences for natural production concentrations changed as the season progressed. Early-season larvae preferred low-concentration leaves, while late-season larvae preferred high-concentrations. Measurements of chemical and nitrogen content of leaves selected by larvae in the field confirmed this pattern. Percent parasitism in field-collected larvae increased with season as the larval population decreased. This combination of slowed growth and increasing parasitism and predation is a putative defense strategy ofEncelia farinosa to prevent adaptation by a specialist herbivore to the total range of compounds elaborated.     

Energy Metabolites as Biomarkers in Ischemic and Dilated Cardiomyopathy

With more than 25 million people affected, heart failure (HF) is a global threat. As energy production pathways are known to play a pivotal role in HF, we sought here to identify key metabolic changes in ischemic- and non-ischemic HF by using a multi-OMICS approach. Serum metabolites and mRNAseq and epigenetic DNA methylation profiles were analyzed from blood and left ventricular heart biopsy specimens of the same individuals. In total we collected serum from n = 82 patients with Dilated Cardiomyopathy (DCM) and n = 51 controls in the screening stage. We identified several metabolites involved in glycolysis and citric acid cycle to be elevated up to 5.7-fold in DCM (p = 1.7 × 10⁻⁶). Interestingly, cardiac mRNA and epigenetic changes of genes encoding rate-limiting enzymes of these pathways could also be found and validated in our second stage of metabolite assessment in n = 52 DCM, n = 39 ischemic HF and n = 57 controls. In conclusion, we identified a new set of metabolomic biomarkers for HF. We were able to identify underlying biological cascades that potentially represent suitable intervention targets.     

Torrefied agro-industrial residue as filler in natural rubber compounds

This study explored the feasibility of using torrefied biomass as a reinforcing filler in natural rubber compounds. Carbon black was then replaced with the torrefied biomass in elastomer formulations for concentrations varying from 0% to 100% (60 parts per hundred rubber or phr total). Their influence on the curing process, dynamic properties, and mechanical properties was investigated. Results were compared with the properties of vulcanizates containing solely carbon black fillers. Time to cure (t₉₀) for compounds with torrefied biomass fillers increased, while filler-filler interactions (ΔG') decreased, compared to carbon black controls. At low strains, the tan δ values of the torrefied fillers vulcanizates were similar to the controls. Incorporation of torrefied biomass into natural rubber decreased compound tensile strength and modulus but increased elongation. Replacement with torrefied fillers resulted in a weaker filler network in the matrix. Still, results showed that moderate substitution concentrations (~20 phr) could be feasible for some natural rubber applications.     

Neural Machine Translation by Fusing Key Information of Text

When the Transformer proposed by Google in 2017, it was first used for machine translation tasks and achieved the state of the art at that time. Although the current neural machine translation model can generate high quality translation results, there are still mistranslations and omissions in the translation of key information of long sentences. On the other hand, the most important part in traditional translation tasks is the translation of key information. In the translation results, as long as the key information is translated accurately and completely, even if other parts of the results are translated incorrect, the final translation results’ quality can still be guaranteed. In order to solve the problem of mistranslation and missed translation effectively, and improve the accuracy and completeness of long sentence translation in machine translation, this paper proposes a key information fused neural machine translation model based on Transformer. The model proposed in this paper extracts the keywords of the source language text separately as the input of the encoder. After the same encoding as the source language text, it is fused with the output of the source language text encoded by the encoder, then the key information is processed and input into the decoder. With incorporating keyword information from the source language sentence, the model’s performance in the task of translating long sentences is very reliable. In order to verify the effectiveness of the method of fusion of key information proposed in this paper, a series of experiments were carried out on the verification set. The experimental results show that the Bilingual Evaluation Understudy (BLEU) score of the model proposed in this paper on the Workshop on Machine Translation (WMT) 2017 test dataset is higher than the BLEU score of Transformer proposed by Google on the WMT2017 test dataset. The experimental results show the advantages of the model proposed in this paper.     

Effects of firm and IT characteristics on the value of e-commerce initiatives: An inductive theoretical framework

We explore the theoretical foundations on how firm and IT characteristics explain the market value variations in e-commerce initiatives by examining the announcements of 946 e-commerce initiatives in the public media. Our approach combines the Event study methodology and Decision tree induction to examine the main and interaction effects of IT and firm characteristics on Cumulative Abnormal Returns (CAR). In particular, we generate complex interaction models that can guide e-commerce investment decisions so managers can know, for example, which combination of IT and firm characteristics are more likely to be viewed positively by investors. The selected study variables as well as explanation of the proposed framework are informed by innovation, resource-based view, transaction cost economics and complementarity theories. We have inductively developed a set of propositions that can be deductively tested to assess the validity of our proposed theoretical framework. Hence our study provides an initial roadmap for theory development on e-commerce and CAR.