A Path of Stories Wrapped Around Itself: A translation and aesthetic reading of Guillermo Meneses’ short story “La Mano Junto al Muro”

Senior Project submitted to The Division of Languages and Literature of Bard College

The detection of wound infection by ion mobility chemical analysis

Surgical site infection represents a large burden of care in the National Health Service. Current methods for diagnosis include a subjective clinical assessment and wound swab culture that may take several days to return a result. Both techniques are potentially unreliable and result in delays in using targeted antibiotics. Volatile organic compounds (VOCs) are produced by micro-organisms such as those present in an infected wound. This study describes the use of a device to differentiate VOCs produced by an infected wound vs. colonised wound. Malodourous wound dressings were collected from patients, these were a mix of post-operative wounds and vascular leg ulcers. Wound microbiology swabs were taken and antibiotics commenced as clinically appropriate. A control group of soiled, but not malodorous wound dressings were collected from patients who had a split skin graft (SSG) donor site. The analyser used was a G.A.S. GC-IMS. The results from the samples had a sensitivity of 100% and a specificity of 88%, with a positive predictive value of 90%. An area under the curve (AUC) of 91% demonstrates an excellent ability to discriminate those with an infected wound from those without. VOC detection using GC-IMS has the potential to serve as a diagnostic tool for the differentiation of infected and non-infected wounds and facilitate the treatment of wound infections that is cost effective, non-invasive, acceptable to patients, portable, and reliable

Working planning in packing houses of flowers mixed farms to increase the yield

The study deals with performance improvement in flowers mixed farms.  The farm under investigation is located in the central part of Israel and grows three types of green ornamentals: Pittosporum, Aralia and Aspidistra.  The farm consists of 8 hectares and employs 7 workers.  The annual yield of the farm in 2009 was 3.5 million branches.  The study investigates the working processes of the packing house.  A computer model and work planning management tool was developed using MATLAB.  The model inputs are: flower type and quantity, due date and sales price.  The output is a work schedule.  Results show an improvement of processing time by: 47% for Pittosporum, 19% - 45% for Aralia, and 23% - 54% for Aspidistra

Productivity Optimization of Screen House Layout Design

The study investigated the optimization of the screen house design to improve the growth productivity of green ornamentals. It focused on the labor-intensive handling operations in order to minimize the time invested in these operations and to maximize the total revenue. The research was performed during 2006–2007 in two modern farms in the central part of Israel. The farms contained 7 and 11 ha of Pitosporum and Aralia screen houses. The various stages of harvesting on each farm were subjected to work studies and time measurements, and a computer simulation model was developed with the ARENA 7™ to find an improved screen house layout. The main goal was to determine the time per stem and hourly output per worker as functions of length of row, distance between rows, distance between plants, work pace, and number of workers. Results show that for the examined cultivars and the present working methods, the best outcome was reached when the row length was the shortest of those examined. There was a decrease of 35% in output when row length increased from 24 to 200 m. Simulation results showed that the best length of a screen house was 24 m. Furthermore, the best width of the screen house was determined as a function of the number of workers and their work pace. In addition, the optimal location of the cart used to transfer the crops to the packaging house was determined

Les Forêts Aléatoires en Apprentissage Semi-Supervisé (Co-forest) pour la segmentation des images rétiniennes

Nous proposons une approche qui permet la reconnaissance automatique des régions Disques et Cups pour la mesure du rapport CDR (Cup/Disc Ratio) par apprentissage semi-supervisé. Une étude comparative de plusieurs techniques est proposée. Le principe repose sur une croissance de région en classifiant les pixels voisins à partir des pixels d'intérêt de l'image par apprentissage semi-supervisé. Les points d'intérêt sont détectés par l'algorithme Fuzzy C-means (FCM)

A novel hyaluronic acid hydrogel as an extracellular matrix to improve graft survival in autologous adipose tissue transfer

Introduction Adipose tissue transfer is used for correcting breast defects after cancer surgery and reconstruction after trauma or congenital defects. Graft survival can be as poor as 15%. Modified hyaluronic acid (HA) hydrogels can be used to suspend adipocytes to aid survival. The study aims were to synthesise a HA hydrogel with robust mechanical properties to support injection, and to assess adipocyte viability with HA hydrogel in vitro and in vivo. Methods A HA hydrogel with cross-linked aldehyde and hydrazine groups allowing self-healing around cells was engineered, with rheology and degradation properties characterised. Per2-dLuc 3T3-L1 murine pre-adipocytes expressing luciferase, CAG-luc-eGFP murine and human adipocytes were grown under, on, and encapsulated within HA hydrogel, with cell survival and gene expression investigated. A murine animal model underwent subcutaneous injection of primary murine adipocytes mixed with HA hydrogel, with cell survival and gene expression of mature adipocyte markers investigated. Results HA hydrogel can be degraded by tissue hyaluronidases in 4-5 days. Self-healing occurred in 30 minutes and is robust enough to resist deformation forces. Per2-dLuc 3T3-L1 and CAG-luc-eGFP murine adipocytes were encapsulated within HA hydrogel and showed a <15% reduction in photon emission compared to control. Mature adipocyte markers gene expression levels in HA hydrogel encapsulated murine and human cells were similar to those of control (no HA hydrogel) cells. Primary murine adipocytes injected subcutaneously with HA hydrogel in wild type mice showed no difference in survival at higher gel volumes compared to control. Gene expression markers of differentiation in injected primary adipocytes mixed with HA hydrogel showed no difference compared to control cells. Conclusion The novel engineered HA hydrogel has suitable mechanical characteristics for injection and can support adipocyte survival in vitro and in vivo. A human pilot trial may be the next step in development of the novel HA hydrogel

Statistical Comparisons of the Top 10 Algorithms in Data Mining for Classification Task

This work is builds on the study of the 10 top data mining algorithms identified by the IEEE International Conference on Data Mining (ICDM) community in December 2006. We address the same study, but with the application of statistical tests to establish, a more appropriate and justified ranking classifier for classification tasks. Current studies and practices on theoretical and empirical comparison of several methods, approaches, advocated tests that are more appropriate. Thereby, recent studies recommend a set of simple and robust non-parametric tests for statistical comparisons classifiers. In this paper, we propose to perform non-parametric statistical tests by the Friedman test with post-hoc tests corresponding to the comparison of several classifiers on multiple data sets. The tests provide a better judge for the relevance of these algorithms

On-line counting of pests in a greenhouse using computer vision

International audienceThis article is concerned with the on-line counting of some harmful insects in videos in the framework of in situ video-surveillance that aims at the early detection of pest attacks in greenhouse crops. The challenges mainly concern the tiny resolution and color contrast of the insects of interest in the videos, the outdoor issues and the quasi-real time constraints. Thus, we propose a complete video-processing chain that can cope with such challenges quite satisfactorily while yielding an acceptable performance. The system has been validated off-line against many recorded videos for the whiteflie species (one potential harmful pest species)

On-line video recognition and counting of harmful insects

International audienceThis article is concerned with on-line counting of harmful insects of certain species in videos in the framework of in situ video-surveillance that aims at the early detection of prominent pest attacks in greenhouse crops. The video-processing challenges that need to be coped with concern mainly the low spatial resolution and color contrast of the objects of interest in the videos, the outdoor issues and the video-processing which needs to be done in quasi-real time. Thus, we propose an approach which makes use of a pattern recognition algorithm to extract the locations of the harmful insects of interest in a video, which we combine with some videoprocessing algorithms in order to achieve an on-line video-surveillance solution. The system has been validated off-line on the whiteflie species (one potential harmful insect) and has shown acceptable performance in terms of accuracy versus computational time