Blue Light Improves Photosynthetic Performance during Healing and Acclimatization of Grafted Watermelon Seedlings

To investigate the importance of light on healing and acclimatization, in the present study, grafted watermelon seedlings were exposed to darkness (D) or light, provided by blue (B), red (R), a mixture of R (68%) and B (RB), or white (W; 35% B, 49% intermediate spectra, 16% R) LEDs for 12 days. Survival ratio, root and shoot growth, soluble carbohydrate content, photosynthetic pigments content, and photosynthetic performance were evaluated. Seedling survival was not only strongly limited in D but the survived seedlings had an inferior shoot and root development, reduced chlorophyll content, and attenuated photosynthetic efficiency. RB-exposed seedlings had a less-developed root system. R-exposed seedlings showed leaf epinasty, and had the smallest leaf area, reduced chlorophyll content, and suppressed photosynthetic apparatus performance. The R-exposed seedlings contained the highest amount of soluble carbohydrate and together with D-exposed seedlings the lowest amount of chlorophyll in their scions. B-exposed seedlings showed the highest chlorophyll content and improved overall PSII photosynthetic functioning. W-exposed seedling had the largest leaf area, and closely resembled the photosynthetic properties of RB-exposed seedlings. We assume that, during healing of grafted seedlings monochromatic R light should be avoided. Instead, W and monochromatic B light may be willingly adopted due to their promoting effect on shoot, pigments content, and photosynthetic efficiency.     

Sign boundary and hand articulation feature recognition in Sign Language videos

Machine Translation - In this paper we present a recommendation system for (semi-)automatic annotation of sign language videos exploiting deep learning techniques, which handle handshape...     

Editorial: Security and Privacy Protection for Mobile Applications and Platforms

Mobile Networks and Applications -     

Semi-supervised online structure learning for composite event recognition

Online structure learning approaches, such as those stemming from statistical relational learning, enable the discovery of complex relations in noisy data streams. However, these methods assume the existence of fully-labelled training data, which is unrealistic for most real-world applications. We present a novel approach for completing the supervision of a semi-supervised structure learning task. We incorporate graph-cut minimisation, a technique that derives labels for unlabelled data, based on their distance to their labelled counterparts. In order to adapt graph-cut minimisation to first order logic, we employ a suitable structural distance for measuring the distance between sets of logical atoms. The labelling process is achieved online (single-pass) by means of a caching mechanism and the Hoeffding bound, a statistical tool to approximate globally-optimal decisions from locally-optimal ones. We evaluate our approach on the task of composite event recognition by using a benchmark dataset for human activity recognition, as well as a real dataset for maritime monitoring. The evaluation suggests that our approach can effectively complete the missing labels and eventually, improve the accuracy of the underlying structure learning system.

     

A Systematic Review and Meta-Analysis of Pharmacogenetic Studies in Patients with Chronic Kidney Disease

Chronic kidney disease (CKD) is an important global public health problem due to its high prevalence and morbidity. Although the treatment of nephrology patients has changed considerably, ineffectiveness and side effects of medications represent a major issue. In an effort to elucidate the contribution of genetic variants located in several genes in the response to treatment of patients with CKD, we performed a systematic review and meta-analysis of all available pharmacogenetics studies. The association between genotype distribution and response to medication was examined using the dominant, recessive, and additive inheritance models. Subgroup analysis based on ethnicity was also performed. In total, 29 studies were included in the meta-analysis, which examined the association of 11 genes (16 polymorphisms) with the response to treatment regarding CKD. Among the 29 studies, 18 studies included patients with renal transplantation, 8 involved patients with nephrotic syndrome, and 3 studies included patients with lupus nephritis. The present meta-analysis provides strong evidence for the contribution of variants harbored in the ABCB1, IL-10, ITPA, MIF, and TNF genes that creates some genetic predisposition that reduces effectiveness or is associated with adverse events of medications used in CKD.