Perancangan Promosi Produk Kosmetik Salsa

Salsa merupakan salah satu Perusahaan Indonesia yang bertempat di Jawa Timur, Surabaya danbergerak di bidang kecantikan dengan memproduksi berbagai macam kosmetik untuk memenuhi kebutuhanwanita akan produk kecantikan. Namun, meskipun telah lama berdiri, hingga kini Salsa masih belum terlaludikenal di kalangan masyarakat sehingga mengakibatkan adanya kesulitan dalam hal penjualan. Promosi yangkurang gencar juga merupakan salah satu faktor yang memperngaruhi terjadinya masalah di atas. Oleh karenaitu, untuk membantu Salsa menghadapi permasalahannya maka dibutuhkan sebuah perancangan promosi yangtepat guna meningkatkan brand awareness masyarakat akan keberadaan Salsa

Melanophore migration and survival during zebrafish adult pigment stripe development require the immunoglobulin superfamily adhesion molecule Igsf11.

The zebrafish adult pigment pattern has emerged as a useful model for understanding the development and evolution of adult form as well as pattern-forming mechanisms more generally. In this species, a series of horizontal melanophore stripes arises during the larval-to-adult transformation, but the genetic and cellular bases for stripe formation remain largely unknown. Here, we show that the seurat mutant phenotype, consisting of an irregular spotted pattern, arises from lesions in the gene encoding Immunoglobulin superfamily member 11 (Igsf11). We find that Igsf11 is expressed by melanophores and their precursors, and we demonstrate by cell transplantation and genetic rescue that igsf11 functions autonomously to this lineage in promoting adult stripe development. Further analyses of cell behaviors in vitro, in vivo, and in explant cultures ex vivo demonstrate that Igsf11 mediates adhesive interactions and that mutants for igsf11 exhibit defects in both the migration and survival of melanophores and their precursors. These findings identify the first in vivo requirements for igsf11 as well as the first instance of an immunoglobulin superfamily member functioning in pigment cell development and patterning. Our results provide new insights into adult pigment pattern morphogenesis and how cellular interactions mediate pattern formation

Post-Embryonic Nerve-Associated Precursors to Adult Pigment Cells: Genetic Requirements and Dynamics of Morphogenesis and Differentiation

The pigment cells of vertebrates serve a variety of functions and generate a stunning variety of patterns. These cells are also implicated in human pathologies including melanoma. Whereas the events of pigment cell development have been studied extensively in the embryo, much less is known about morphogenesis and differentiation of these cells during post-embryonic stages. Previous studies of zebrafish revealed genetically distinct populations of embryonic and adult melanophores, the ectotherm homologue of amniote melanocytes. Here, we use molecular markers, vital labeling, time-lapse imaging, mutational analyses, and transgenesis to identify peripheral nerves as a niche for precursors to adult melanophores that subsequently migrate to the skin to form the adult pigment pattern. We further identify genetic requirements for establishing, maintaining, and recruiting precursors to the adult melanophore lineage and demonstrate novel compensatory behaviors during pattern regulation in mutant backgrounds. Finally, we show that distinct populations of latent precursors having differential regenerative capabilities persist into the adult. These findings provide a foundation for future studies of post-embryonic pigment cell precursors in development, evolution, and neoplasia

A Realism Metric for Generated LiDAR Point Clouds

A considerable amount of research is concerned with the generation of realistic sensor data. LiDAR point clouds are generated by complex simulations or learned generative models. The generated data is usually exploited to enable or improve downstream perception algorithms. Two major questions arise from these procedures: First, how to evaluate the realism of the generated data? Second, does more realistic data also lead to better perception performance? This paper addresses both questions and presents a novel metric to quantify the realism of LiDAR point clouds. Relevant features are learned from real-world and synthetic point clouds by training on a proxy classification task. In a series of experiments, we demonstrate the application of our metric to determine the realism of generated LiDAR data and compare the realism estimation of our metric to the performance of a segmentation model. We confirm that our metric provides an indication for the downstream segmentation performance

Hypergraph models of biological networks to identify genes critical to pathogenic viral response

BACKGROUND: Representing biological networks as graphs is a powerful approach to reveal underlying patterns, signatures, and critical components from high-throughput biomolecular data. However, graphs do not natively capture the multi-way relationships present among genes and proteins in biological systems. Hypergraphs are generalizations of graphs that naturally model multi-way relationships and have shown promise in modeling systems such as protein complexes and metabolic reactions. In this paper we seek to understand how hypergraphs can more faithfully identify, and potentially predict, important genes based on complex relationships inferred from genomic expression data sets. RESULTS: We compiled a novel data set of transcriptional host response to pathogenic viral infections and formulated relationships between genes as a hypergraph where hyperedges represent significantly perturbed genes, and vertices represent individual biological samples with specific experimental conditions. We find that hypergraph betweenness centrality is a superior method for identification of genes important to viral response when compared with graph centrality. CONCLUSIONS: Our results demonstrate the utility of using hypergraphs to represent complex biological systems and highlight central important responses in common to a variety of highly pathogenic viruses

Prevalence of non-aureus Staphylococcus species causing intramammary infections in Canadian dairy herds

Non-aureus staphylococci (NAS), the microorganisms most frequently isolated from bovine milk worldwide, are a heterogeneous group of numerous species. To establish their importance as a group, the distribution of individual species needs to be determined. In the present study, NAS intramammary infection (IMI) was defined as a milk sample containing ≥1,000 cfu/mL in pure or mixed culture that was obtained from a cohort of cows assembled by the Canadian Bovine Mastitis Research Network. Overall, 6,213 (6.3%) of 98,233 quarter-milk samples from 5,149 cows and 20,305 udder quarters were associated with an NAS IMI. Of the 6,213 phenotypically identified NAS isolates, 5,509 (89%) were stored by the Canadian Bovine Mastitis Research Network Mastitis Pathogen Collection and characterized using partial sequencing of the rpoB housekeeping gene, confirming 5,434 isolates as NAS. Prevalence of each NAS species IMI was estimated using Bayesian models, with presence of a specific NAS species as the outcome. Overall quarter-level NAS IMI prevalence was 26%. The most prevalent species causing IMI were Staphylococcus chromogenes (13%), Staphylococcus simulans (4%), Staphylococcus haemolyticus (3%), Staphylococcus xylosus (2%), and Staphylococcus epidermidis (1%). The prevalence of NAS IMI as a group was highest in first-parity heifers and was evenly distributed throughout cows in parities ≥2. The IMI prevalence of some species such as S. chromogenes, S. simulans, and S. epidermidis differed among parities. Overall prevalence of NAS IMI was 35% at calving, decreased over the next 10 d, and then gradually increased until the end of lactation. The prevalence of S. chromogenes, Staphylococcus gallinarum, Staphylococcus cohnii, and Staphylococcus capitis was highest at calving, whereas the prevalence of S. chromogenes, S. haemolyticus, S. xylosus, and S. cohnii increased during lactation. Although the overall prevalence of NAS IMI was similar across barn types, the prevalence of S. simulans, S. xylosus, S. cohnii, Staphylococcus saprophyticus, S. capitis, and Staphylococcus arlettae IMI was higher in tie-stall barns; the prevalence of S. epidermidis IMI was lowest; and the prevalence of S. chromogenes and Staphylococcus sciuri IMI was highest in bedded-pack barns. Staphylococcus simulans, S. epidermidis, S. xylosus, and S. cohnii IMI were more prevalent in herds with intermediate to high bulk milk somatic cell count (BMSCC) and S. haemolyticus IMI was more prevalent in herds with high BMSCC, whereas other common NAS species IMI were equally prevalent in all 3 BMSCC categories. Distribution of NAS species IMI differed among the 4 regions of Canada. In conclusion, distribution differed considerably among NAS species IMI; therefore, accurate identification (species level) is essential for studying NAS epidemiology