Modelling, analysis, and acceleration of a printed circuit board fabrication process

Product design and fabrication constitute an important business activity in any manufacturing firm. Designing an optimized product fabrication process is an important problem in itself and is of significant practical and research interest. In this paper, we look into a printed circuit board (PCB) fabrication process and investigate ways in which the fabrication cycle time can be minimized. Single class queueing networks constitute the modelling framework for our study. The model developed in this paper and the analysis experiments carried out are based on extensive data collected on a PCB fabrication company located in Bangalore, India. This is a representative PCB fabrication company involving multiple, concurrent fabrication works with contention for human/technical resources. Our model seeks to capture faithfully the flow of the fabrication process in this company and such other organisations, using queueing networks. Using the model developed, we explore how the cycle times can be reduced using input control, load balancing, and variability reduction. The model presented is sufficiently generic and conceptual; its scope extends beyond that of a PCB fabrication organization

Derivation of an eigenvalue probability density function relating to the Poincare disk

A result of Zyczkowski and Sommers [J.Phys.A, 33, 2045--2057 (2000)] gives the eigenvalue probability density function for the top N x N sub-block of a Haar distributed matrix from U(N+n). In the case n \ge N, we rederive this result, starting from knowledge of the distribution of the sub-blocks, introducing the Schur decomposition, and integrating over all variables except the eigenvalues. The integration is done by identifying a recursive structure which reduces the dimension. This approach is inspired by an analogous approach which has been recently applied to determine the eigenvalue probability density function for random matrices A^{-1} B, where A and B are random matrices with entries standard complex normals. We relate the eigenvalue distribution of the sub-blocks to a many body quantum state, and to the one-component plasma, on the pseudosphere.Comment: 11 pages; To appear in J.Phys

Antifungal potential of Azotobacter species and its metabolites against Fusarium verticillioides and biodegradation of fumonisin

Abstract Aims In the study, seven Plant Growth Promoting Rhizobacteria (PGPR) Azotobacter species were screened against three strains of Fusarium verticillioides to test its antifungal activity. Azotobacter strains were tested for the degradation of fumonisin produced by F. verticillioides. Secondary metabolites were isolated and characterized from the Azotobacter strains for the first time. Methods and Results Potential seven Azotobacter species antifungal activity was tested following the dual culture assay against three strains of Fusarium verticillioides namely FVM-42, FVM-86 and MTCC156 estimating the substantial zone of inhibition. Azotobacter species AZT-31 and AZT-50 strains significantly inhibited the growth of F. verticillioides recording drastic growth enhancement of maize under in-vitro conditions by calculating the infection incidence, vigour index and germination percentage. As confirmation, dereplication studies were conducted for the reconfirmation of Azotobacter strains by isolating from rhizoplane. Azotobacter strains played a key role in the degradation of fumonisin produced by F. verticillioides reporting 98% degradation at 2Â h of incubation with the pathogen. Furthermore, in the study first time, we have tried to isolate and characterize the secondary metabolites from the Azotobacter strains exhibiting six compounds from the species AZT-31 (2) and AZT-50 (4). Preliminary in-vitro experiments were carried out using the compounds extracted to check the reduction of infection incidence (90%) and increase in germination percentage upto 50 to 70% when compared to the test pathogen. Conclusion Azotobacter strains referred as PGPR on influencing the growth of plant by producing certain substances that act as stimulators on inhibiting the growth of the pathogen. Significance and Impact of the study The future perspective would be the production of an active combination of carboxamide compound and Azotobacter species for preventively controlling the phytopathogenic fungi of plants and crops and also towards the treatment of seeds

Broad ligament cystic lymphangioma: A case report

This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Novel insights into the cardio-protective effects of FGF21 in lean and obese rat hearts

Aims: Fibroblast growth factor 21 (FGF21) is a hepatic metabolic regulator with pleotropic actions. Its plasma concentrations are increased in obesity and diabetes; states associated with an increased incidence of cardiovascular disease. We therefore investigated the direct effect of FGF21 on cardio-protection in obese and lean hearts in response to ischemia. Methods and Results: FGF21, FGF21-receptor 1 (FGFR1) and beta-Klotho (βKlotho) were expressed in rodent, human hearts and primary rat cardiomyocytes. Cardiac FGF21 was expressed and secreted (real time RT-PCR/western blot and ELISA) in an autocrine-paracrine manner, in response to obesity and hypoxia, involving FGFR1-βKlotho components. Cardiac-FGF21 expression and secretion were increased in response to global ischemia. In contrast βKlotho was reduced in obese hearts. In isolated adult rat cardiomyocytes, FGF21 activated PI3K/Akt (phosphatidylinositol 3-kinase/Akt), ERK1/2(extracellular signal-regulated kinase) and AMPK (AMP-activated protein kinase) pathways. In Langendorff perfused rat [adult male wild-type wistar] hearts, FGF21 administration induced significant cardio-protection and restoration of function following global ischemia. Inhibition of PI3K/Akt, AMPK, ERK1/2 and ROR-α (retinoic-acid receptor alpha) pathway led to significant decrease of FGF21 induced cardio-protection and restoration of cardiac function in response to global ischemia. More importantly, this cardio-protective response induced by FGF21 was reduced in obesity, although the cardiac expression profiles and circulating FGF21 levels were increased. Conclusion: In an ex vivo Langendorff system, we show that FGF21 induced cardiac protection and restoration of cardiac function involving autocrine-paracrine pathways, with reduced effect in obesity. Collectively, our findings provide novel insights into FGF21-induced cardiac effects in obesity and ischemia

Comparative and temporal transcriptome analysis of peste des petits ruminants virus infected goat peripheral blood mononuclear cells

Peste des petits ruminanats virus (PPRV), a morbillivirus causes an acute, highly contagious disease – peste des petits ruminants (PPR), affecting goats and sheep. Sungri/96 vaccine strain is widely used for mass vaccination programs in India against PPR and is considered the most potent vaccine providing long-term immunity. However, occurrence of outbreaks due to emerging PPR viruses may be a challenge. In this study, the temporal dynamics of immune response in goat peripheral blood mononuclear cells (PBMCs) infected with Sungri/96 vaccine virus was investigated by transcriptome analysis. Infected goat PBMCs at 48 h and 120 h post infection revealed 2540 and 2000 differentially expressed genes (DEGs), respectively, on comparison with respective controls. Comparison of the infected samples revealed 1416 DEGs to be altered across time points. Functional analysis of DEGs reflected enrichment of TLR signaling pathways, innate immune response, inflammatory response, positive regulation of signal transduction and cytokine production. The upregulation of innate immune genes during early phase (between 2-5 days) viz. interferon regulatory factors (IRFs), tripartite motifs (TRIM) and several interferon stimulated genes (ISGs) in infected PBMCs and interactome analysis indicated induction of broad-spectrum anti-viral state. Several Transcription factors – IRF3, FOXO3 and SP1 that govern immune regulatory pathways were identified to co-regulate the DEGs. The results from this study, highlighted the involvement of both innate and adaptive immune systems with the enrichment of complement cascade observed at 120 h p.i., suggestive of a link between innate and adaptive immune response. Based on the transcriptome analysis and qRT-PCR validation, an in vitro mechanism for the induction of ISGs by IRFs in an interferon independent manner to trigger a robust immune response was predicted in PPRV infection

DRAMMS: deformable registration via attribute matching and mutual-saliency weighting

A general-purpose deformable registration algorithm referred to as ”DRAMMS” is presented in this paper. DRAMMS adds to the literature of registration methods that bridge between the traditional voxel-wise methods and landmark/feature-based methods. In particular, DRAMMS extracts Gabor attributes at each voxel and selects the optimal components, so that they form a highly distinctive morphological signature reflecting the anatomical context around each voxel in a multi-scale and multi-resolution fashion. Compared with intensity or mutual-information based methods, the high-dimensional optimal Gabor attributes render different anatomical regions relatively distinctively identifiable and therefore help establish more accurate and reliable correspondence. Moreover, the optimal Gabor attribute vector is constructed in a way that generalizes well, i.e., it can be applied to different registration tasks, regardless of the image contents under registration. A second characteristic of DRAMMS is that it is based on a cost function that weights different voxel pairs according to a metric referred to as ”mutual-saliency”, which reflects the uniqueness (reliability) of anatomical correspondences implied by the tentative transformation. As a result, image voxels do not contribute equally to the optimization process, as in most voxel-wise methods, or in a binary selection fashion, as in most landmark/feature-based methods. Instead, they contribute according to a continuously-valued mutual-saliency map, which is dynamically updated during the algorithm’s evolution. The general applicability and accuracy of DRAMMS are demonstrated by experiments in simulated images, inter-subject images, single-/multi-modality images, and longitudinal images, from human and mouse brains, breast, heart, and prostate

Ophthalmic Complications of Dengue

A case series suggests that the spectrum of complications in dengue infection is widening

The usefulness of arbekacin compared to vancomycin

The bacteriological efficacy response (improved, arbekacin vs. vancomycin; 71.2% vs. 79.5%) and clinical efficacy response (improved, arbekacin vs. vancomycin; 65.3% vs. 76.1%) were not statistically different between the two groups. The complication rate was significantly higher in the vancomycin group (32.9%) compared to the arbekacin group (15.1%) (p = 0.019). Arbekacin was not inferior to vancomycin, and it could be a good alternative drug for vancomycin in methicillin-resistant Staphylococcus aureus (MRSA) treatment

Enhancing Video Recommendation Using Multimedia Content

Video recordings are complex media types. When we watch a movie, we can effortlessly register a lot of details conveyed to us (by the author) through different multimedia channels, in particular, the audio and visual modalities. To date, majority of movie recommender systems use collaborative filtering (CF) models or content-based filtering (CBF) relying on metadata (e.g., editorial such as genre or wisdom of the crowd such as user-generated tags) at their core since they are human-generated and are assumed to cover the 'content semantics' of movies by a great degree. The information obtained from multimedia content and learning from muli-modal sources (e.g., audio, visual and metadata) on the other hand, offers the possibility of uncovering relationships between modalities and obtaining an in-depth understanding of natural phenomena occurring in a video. These discerning characteristics of heterogeneous feature sets meet users' differing information needs. In the context of this Ph.D. thesis [9], which is briefly summarized in the current extended abstract, approaches to automated extraction of multimedia information from videos and their integration with video recommender systems have been elaborated, implemented, and analyzed. Variety of tasks related to movie recommendation using multimedia content have been studied. The results of this thesis can motivate the fact that recommender system research can benefit from knowledge in multimedia signal processing and machine learning established over the last decades for solving various recommendation tasks