Frequency-interleaved SDM transmission over multicore fiber for next generation short-reach optical interconnect systems

Space division multiplexing (SDM) technique is proposed to overcome the bandwidth density drives of short-reach optical transmission systems by utilizing 8-core multicore fiber (MCF). Intercore crosstalk (XT) and higher order modulation format are the most challenging impairments of SDM based optical interconnect (OI) systems. To satisfy the exponential growth of the Internet traffic a frequency interleaving scheme is applied to short-reach MCF OI transmission systems. The negative effects of spectral overlap and intercore XT is reduced by shifting channel frequencies between adjacent cores. To exploit the full potential of SDM power efficient binary phase shift keying (BPSK) modulation format and digital signal processing such as multiple input multiple output (MIMO) equalization are used

Towards Enriching Genomic Resources in Legumes

Food legumes, mainly comprising dry beans, dry peas, soybean, chickpea, pigeonpea, groundnut, greengram, blackgram, cowpea, lentil and lathyrus, have considerable area under cultivation globally and these are important constituents of cereal-based vegetarian diets. Keeping in view their tremendous importance for diversification and intensification of contemporary agriculture, systematic efforts towards their genetic improvement have been undertaken with classical breeding tools, lately complemented by the use of genomic tools. These genomic tools provide comprehensive information on genes involved in biochemical pathways leading upto nutritional compounds and can be used to understand the genetics of traits of interest and consequently, helping in marker assisted breeding. During the last two decades powerful genetic and genomic tools such as establishment of genetic and physical maps, expressed sequence tags, bioinformatic tools, genome-wide sequence data, genomic and metabolomic platforms, etc. have been developed for many legume species. These efforts have led to development of large scale molecular markers, identification of various marker trait associations, construction of genetic and linkage maps, expressed sequence tags database, partial or whole genome sequences, physical and molecular maps, DNA chips and bacterial artificial chromosome (BAC) libraries. After the genome sequencing of three model species, Medicago, Lotus and Glycine, draft genome sequences have recently been made available in agronomically important food legumes, pigeonpea and chickpea while similar efforts are underway in groundnut and greengram. The new generation sequencing (NGS) and genotyping platforms such as 454/FLX sequencing and Illumina GoldenGate/Solexa have revolutionized plant genomic research as these generate millions of ESTs per run. With the increased amount of genomic resources, there are now tremendous opportunities to integrate these with the genetic resources for their widespread use in routine legume improvement programmes by integrating them with conventional breeding tools. As a result, the genomics assisted breeding (GAB) can now be successfully used in legume improvement and development of improved genotypes having improved agronomic and quality traits and resistance to biotic and abiotic stresses. This chapter discusses the developments made in development of legume genomics and their role in overall improvement of food legumes

Colocalization of different neurotransmitter transporters on synaptic vesicles is sparse except for VGLUT1 and ZnT3

Vesicular transporters (VTs) define the type of neurotransmitter that synaptic vesicles (SVs) store and release. While certain mammalian neurons release multiple transmitters, it is not clear whether the release occurs from the same or distinct vesicle pools at the synapse. Using quantitative single-vesicle imaging, we show that a vast majority of SVs in the rodent brain contain only one type of VT, indicating specificity for a single neurotransmitter. Interestingly, SVs containing dual transporters are highly diverse (27 types) but small in proportion (2% of all SVs), excluding the largest pool that carries VGLUT1 and ZnT3 (34%). Using VGLUT1-ZnT3 SVs, we demonstrate that the transporter colocalization influences the SV content and synaptic quantal size. Thus, the presence of diverse transporters on the same vesicle is bona fide, and depending on the VT types, this may act to regulate neurotransmitter type, content, and release in space and time

Consequences of concurrent Ascaridia galli and Escherichia coli infections in chickens

Three experiments were carried out to examine the consequences of concurrent infections with Ascaridia galli and Escherichia coli in chickens raised for table egg production. Characteristic pathological lesions including airsacculitis, peritonitis and/or polyserositis were seen in all groups infected with E. coli. Furthermore, a trend for increased mortality rates was observed in groups infected with both organisms which, however, could not be confirmed statistically. The mean worm burden was significantly lower in combined infection groups compared to groups infected only with A. galli. It was also shown that combined infections of E. coli and A. galli had an added significant negative impact on weight gain

Novel role for the transient receptor potential channel TRPM2 in prostate cancer cell proliferation

We have identified a novel function for a member of the transient receptor potential (TRP) protein super-family, TRPM2, in prostate cancer cell proliferation. TRPM2 encodes a non-selective cation-permeable ion channel. We found that selectively knocking down TRPM2 with the small interfering RNA technique inhibited the growth of prostate cancer cells but not of non-cancerous cells. The subcellular localization of this protein is also remarkably different between cancerous and non-cancerous cells. In BPH-1 (benign), TRPM2 protein is homogenously located near the plasma membrane and in the cytoplasm, whereas in the cancerous cells (PC-3 and DU-145), a significant amount of the TRPM2 protein is located in the nuclei in a clustered pattern. Furthermore, we have found that TRPM2 inhibited nuclear ADP-ribosylation in prostate cancer cells. However, TRPM2 knockdown-induced inhibition of proliferation is independent of the activity of poly(ADP-ribose) polymerases. We conclude that TRPM2 is essential for prostate cancer cell proliferation and may be a potential target for the selective treatment of prostate cancer

A novel TOPSIS–CBR goal programming approach to sustainable healthcare treatment

Cancer is one of the most common diseases worldwide and its treatment is a complex and time-consuming process. Specifically, prostate cancer as the most common cancer among male population has received the attentions of many researchers. Oncologists and medical physicists usually rely on their past experience and expertise to prescribe the dose plan for cancer treatment. The main objective of dose planning process is to deliver high dose to the cancerous cells and simultaneously minimize the side effects of the treatment. In this article, a novel TOPSIS case based reasoning goal-programming approach has been proposed to optimize the dose plan for prostate cancer treatment. Firstly, a hybrid retrieval process TOPSIS–CBR [technique for order preference by similarity to ideal solution (TOPSIS) and case based reasoning (CBR)] is used to capture the expertise and experience of oncologists. Thereafter, the dose plans of retrieved cases are adjusted using goal-programming mathematical model. This approach will not only help oncologists to make a better trade-off between different conflicting decision making criteria but will also deliver a high dose to the cancerous cells with minimal and necessary effect on surrounding organs at risk. The efficacy of proposed method is tested on a real data set collected from Nottingham City Hospital using leave-one-out strategy. In most of the cases treatment plans generated by the proposed method is coherent with the dose plan prescribed by an experienced oncologist or even better. Developed decision support system can assist both new and experienced oncologists in the treatment planning process

Social media and sensemaking patterns in new product development: demystifying the customer sentiment

Artificial intelligence by principle is developed to assist but also support decision making processes. In our study, we explore how information retrieved from social media can assist decision-making processes for new product development (NPD). We focus on consumers’ emotions that are expressed through social media and analyse the variations of their sentiments in all the stages of NPD. We collect data from Twitter that reveal consumers’ appreciation of aspects of the design of a newly launched model of an innovative automotive company. We adopt the sensemaking approach coupled with the use of fuzzy logic for text mining. This combinatory methodological approach enables us to retrieve consensus from the data and to explore the variations of sentiments of the customers about the product and define the polarity of these emotions for each of the NPD stages. The analysis identifies sensemaking patterns in Twitter data and explains the NPD process and the associated steps where the social interactions from customers can have an iterative role. We conclude the paper by outlining an agenda for future research in the NPD process and the role of the customer opinion through sensemaking mechanisms