Suppliers of luxury fashion fabrics in France have historically been working in fierce competitive ways. Usually family-owned businesses, they are working for the same clients, be it in fast fashion, premium fashion or luxury (including Haute-Couture). Calais lace-makers are no exception. However, what could have been described as same emulation in the past turns out to be a weakness in the XXIst century, with booming foreign competition from developing countries. Up to now, they’ve been unable to join their forces to collaborate on projects such as big orders from fashion brands. Created in 1952, the Dentelle de Calais® label can be used by the lace manufacturers using Leavers machines, and active members to the French Federation of Lace and Embroidment (which is the IP owner of the label). This encompasses the places of Calais (traditionally manufacturing lace for undergarments) and of Caudry (more focused on clothes). Caudresian lace has become famous as a proud supplier for the Duchess of Cambridge’s wedding dress or for the awarded costumes in The Great Gatsby. However, it appears that the label is currently dying, being unequally used by the various lace-makers and retailers / brand owners of clothes or undergarments. In January 2014, a repositioning of the label has been initiated. We’ve been asked to do it and decided to use action research to complete this task. The ultimate objective was to give a new identity to the label and DNA to the brand, which could be used by any lace-maker using Leavers machines in a way enhancing his own brand equity. In short, we aim at crafting an ingredient branding strategy. The present action research, on top of solving the client’s issues, aimed at enhancing knowledge on several key topics. First, we wanted to understand better information processes in a cluster that is bi-located, and with internal “fights”. Then, another objective was to grasp the various points that are at stake when clustering happens in-between non-aligned partners. More specifically, we wanted to uncover how decisions happened, and stimulate new ways for decision-making optimization. A last objective was to reflect upon ingredient collective-branding strategic developments, as most literature on branding concerns individual brands and not collective ones. As these become a major trend in these days, we believe academic research has a great role to play. Our research is a first step in this direction. To do this, various data collection and analysis methods have been used: • Interviews with all types stakeholders (fashion designers, purchasers, marketers, journalists, students in fashion or business schools, etc.), to understand their present vision of lace fabric in general and whether they would or would not use it (including in their sales argument). Then similar discussion on Calais lace is conducted. Open-coding and axial coding are then done to identify the values associated with lace and Calais lace, for each stakeholder-category. • Semiotic analysis of the label, to understand the Ethics and Aesthetics of this collective brand. This includes content and discourse analyses, visual (iconic and plastic) analysis of the communication tools including the logo, etc. The current label positioning is presented thanks to the greimasian semiotic square . • Non-participant observation and non-directed interviews with all lace-makers to get each one’s perspective on the label. Open coding and axial coding (Strauss & Corbin) are used to identify the relevant categories and sub-categories underlying the dicsourses. • Lexical analysis of all verbatims will help identify the proper jargon to reconcile stakeholders and manufacturers. • Market analysis on the various relevant markets: Middle East, Europe and Asia. • Structural semiotics are used to wrap-up findings and craft a new brand identity (Greimas’ semiotic square and narrative scheme). More than a simple action, this ingredient-branding collective action will help foster a collective conscience around the preservation of an endangered manufacturing sector of activity, paving the way for a future industrial cluster. Besides the managerial outcomes, this project aimed at (1) Understanding better information processes in a cluster that is bi-located, and with internal “fights”; (2) Grasping the various points that are at stake when clustering happens in-between non-aligned partners, esp. in terms of decision-making processes; and (3) Reflecting upon ingredient collective-branding strategic developments. Our paper presents all these points, providing practical and theoretical insights for the luxury community in general.

Cryopreservation of boar semen is continually researched in reproductive technologies and genetic resource banking in breed conservation. For evaluating the boar semen quality, sperm motility (MOT) is an important parameter because the movement of spermatozoa indicates active metabolism, membrane integrity and fertilizing capacity. Various researches have been trying to improve the quality of semen post-thawed in boar. Recently, polymorphism (g.358A>T) of cluster-of-differentiation antigen 9 (CD9) gene reported to be significant association with MOT. Also, CD9 gene was expressed in the male germ line stem cells is crucial for sperm-egg fusion, and was therefore selected as candidate gene for boar semen. This study was conducted to evaluate the pig SNP (g.358A>T) of CD9 gene as a positional controlling for semen parameters of post-thawed boar semen. To results, the g.358A>T SNP of the CD9 gene was significantly associated with the traits such as MOT, curve linear velocity, straight line velocity, average path velocity and amplitude of lateral head displacement. Particularly, the g.358A>T SNP significantly has the highest association with MOT and animals with AA genotype (p<0.001). Therefore, we suggest that the g.358A>T in the intron 6 region of the porcine CD9 may be used as a molecular marker for Duroc boar Post-thawed semen quality, although its functional effect was not defined yet.

The dredge gear is dragged along the bottom of the sea to catch targeted edible bottom dwelling species. Species composition and ecological index of the catches of dredge were estimated around Gangneung coastal fishing ground by dredge with different mesh size and tooth space from July to December 2013. Eight different types of dredge including four different tooth space (24.7 mm, 29.9 mm, 34.9 mm, 40.1 mm) and four different mesh size(15.5 mm, 32.7 mm, 51.1 mm, 060.0 mm) were used in the experiment. During the experiment, total catches were collected 31 species as sipunculida 1 species, mollusca 13 species, annelida 3 species, arthropoda 8 species, echinodermata 4 species and others 2 species. The dominant genus were mollusca and echinodermata while the dominant species were Megangulus venulosus, Pseudocardium sachalinensis, Schaphechinus brevis. The richness index was ranged 1.29-1.72, evenness index was 0.6-0.65 and diversity index was 1.65-1.83 according to the tooth space and mesh size of dredge. Richness index, diversity index were high at tooth space 34.9 mm dredge and ecological index showed decreasing tendency with the increasing of mesh size of dredge. Cluster and MDS analysis, based on a Bray-Curtis and similarity matrix of fourth root transformed data of number of species and wet weight, showed division into four different groups as four different tooth space (Group A), four different mesh size Group B (51.1 mm, 60.0 mm), Group C (32.7 mm) and Group D (15.5 mm).

Seasonal variations in species composition of catches were explored using seasonal samples caught by shrimp beam trawl in the Geum river estuary in 2011. During the study period, total catches were collected 91 species as fish 47 species, crustacean 28 species, mollusca 4 species, gastropoda 5 species, shellfish 3 species and others 4 species. The dominant species were Exopalaemon carinicauda, Eriocheir leptognathus, Palaemon gravieri, Mugil cephalus, Acanthogobius hasta, Cynoglossus joyneri, Pennahia argentata and Coilia nasus. The amount of species in spring and summer was higher than in autumn. The diversity index (H') was 0.43~0.96, evenness index (EI) was 0.14~0.25, and richness index (RI) was 1.54~4.25. Using cluster analysis 91 species were divided into 4 groups. Group I appeared mainly in spring and summer. Group II appeared only in summer. Group III appeared in winter and spring, and Group IV in spring and autumn.

The astrophysical parameters of four unstudied open star cluster candidates; Ivanov 2, 7, 9, and Harvard 9; are estimated for the first time using the PPMXL database. The stellar density distributions and color-magnitude diagrams for each cluster are used to determine the geometrical structure (cluster center, limited radius, core and tidal radii, the distances from the Sun, from the Galactic center and from the Galactic plane). Also, the main photometric parameters (age, distance modulus, color excesses, membership, total mass, relaxation time, luminosity and mass functions) are estimated.