Vision based referee sign language recognition system for the RoboCup MSL league

In RoboCup Middle Size league (MSL) the main referee uses assisting technology, controlled by a second referee, to support him, in particular for conveying referee decisions for robot players with the help of a wireless communication system. In this paper a vision-based system is introduced, able to interpret dynamic and static gestures of the referee, thus eliminating the need for a second one. The referee's gestures are interpreted by the system and sent directly to the Referee Box, which sends the proper commands to the robots. The system is divided into four modules: a real time hand tracking and feature extraction, a SVM (Support Vector Machine) for static hand posture identification, an HMM (Hidden Markov Model) for dynamic unistroke hand gesture recognition, and a FSM (Finite State Machine) to control the various system states transitions. The experimental results showed that the system works very reliably, being able to recognize the combination of gestures and hand postures in real-time. For the hand posture recognition, with the SVM model trained with the selected features, an accuracy of 98,2% was achieved. Also, the system has many advantages over the current implemented one, like avoiding the necessity of a second referee, working on noisy environments, working on wireless jammed situations. This system is easy to implement and train and may be an inexpensive solution

Re: Response to Request for Relevant Information on Bisphenol A Dear Ms. Oshita,

Authoritative Bodies Mechanism: Bisphenol-A). The Polycarbonate/BPA Global Group consists of the leading global manufacturers of bisphenol A and polycarbonate plastic, which for many years have supported and conducted scientific research to understand whether bisphenol A has the potential to cause health or environmental effects and to support scientifically sound public policy. As indicated by the signatures at the end of the attachment, the comments were prepare

Vision-based portuguese sign language recognition system

Vision-based hand gesture recognition is an area of active current research in computer vision and machine learning. Being a natural way of human interaction, it is an area where many researchers are working on, with the goal of making human computer interaction (HCI) easier and natural, without the need for any extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them, for example, to convey information. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. Hand gestures are a powerful human communication modality with lots of potential applications and in this context we have sign language recognition, the communication method of deaf people. Sign lan- guages are not standard and universal and the grammars differ from country to coun- try. In this paper, a real-time system able to interpret the Portuguese Sign Language is presented and described. Experiments showed that the system was able to reliably recognize the vowels in real-time, with an accuracy of 99.4% with one dataset of fea- tures and an accuracy of 99.6% with a second dataset of features. Although the im- plemented solution was only trained to recognize the vowels, it is easily extended to recognize the rest of the alphabet, being a solid foundation for the development of any vision-based sign language recognition user interface system

Disease-specific survival for limited-stage small-cell lung cancer affected by statistical method of assessment

BACKGROUND: In general, prognosis and impact of prognostic/predictive factors are assessed with Kaplan-Meier plots and/or the Cox proportional hazard model. There might be substantive differences from the results using these models for the same patients, if different statistical methods were used, for example, Boag log-normal (cure-rate model), or log-normal survival analysis. METHODS: Cohort of 244 limited-stage small-cell lung cancer patients, were accrued between 1981 and 1998, and followed to the end of 2005. The endpoint was death with or from lung cancer, for disease-specific survival (DSS). DSS at 1-, 3- and 5-years, with 95% confidence limits, are reported for all patients using the Boag, Kaplan-Meier, Cox, and log-normal survival analysis methods. Factors with significant effects on DSS were identified with step-wise forward multivariate Cox and log-normal survival analyses. Then, DSS was ascertained for patients with specific characteristics defined by these factors. RESULTS: The median follow-up of those alive was 9.5 years. The lack of events after 1966 days precluded comparison after 5 years. DSS assessed by the four methods in the full cohort differed by 0–2% at 1 year, 0–12% at 3 years, and 0–1% at 5 years. Log-normal survival analysis indicated DSS of 38% at 3 years, 10–12% higher than with other methods; univariate 95% confidence limits were non-overlapping. Surgical resection, hemoglobin level, lymph node involvement, and superior vena cava (SVC) obstruction significantly impacted DSS. DSS assessed by the Cox and log-normal survival analysis methods for four clinical risk groups differed by 1–6% at 1 year, 15–26% at 3 years, and 0–12% at 5 years; multivariate 95% confidence limits were overlapping in all instances. CONCLUSION: Surgical resection, hemoglobin level, lymph node involvement, and superior vena cava (SVC) obstruction all significantly impacted DSS. Apparent DSS for patients was influenced by the statistical methods of assessment. This would be clinically relevant in the development or improvement of clinical management strategies

Adult bone marrow stromal cell-based tissue-engineered aggrecan exhibits ultrastructure and nanomechanical properties superior to native cartilage

Objective: To quantify the structural characteristics and nanomechanical properties of aggrecan produced by adult bone marrow stromal cells (BMSCs) in peptide hydrogel scaffolds and compare to aggrecan from adult articular cartilage. Design: Adult equine BMSCs were encapsulated in 3D-peptide hydrogels and cultured for 21 days with TGF-β1 to induce chondrogenic differentiation. BMSC-aggrecan was extracted and compared with aggrecan from age-matched adult equine articular cartilage. Single molecules of aggrecan were visualized by atomic force microcopy-based imaging and aggrecan nanomechanical stiffness was quantified by high resolution force microscopy. Population-averaged measures of aggrecan hydrodynamic size, core protein structures and CS sulfation compositions were determined by size-exclusion chromatography, Western analysis, and fluorescence-assisted carbohydrate electrophoresis (FACE). Results: BMSC-aggrecan was primarily full-length while cartilage-aggrecan had many fragments. Single molecule measurements showed that core protein and GAG chains of BMSC-aggrecan were markedly longer than those of cartilage-aggrecan. Comparing full-length aggrecan of both species, BMSC-aggrecan had longer GAG chains, while the core protein trace lengths were similar. FACE analysis detected a ∼1:1 ratio of chondroitin-4-sulfate to chondroitin-6-sulfate in BMSC-GAG, a phenotype consistent with aggrecan from skeletally-immature cartilage. The nanomechanical stiffness of BMSC-aggrecan was demonstrably greater than that of cartilage-aggrecan at the same total sGAG (fixed charge) density. Conclusions: The higher proportion of full-length monomers, longer GAG chains and greater stiffness of the BMSC-aggrecan makes it biomechanically superior to adult cartilage-aggrecan. Aggrecan stiffness was not solely dependent on fixed charge density, but also on GAG molecular ultrastructure. These results support the use of adult BMSCs for cell-based cartilage repair.National Institutes of Health (U.S.) (NIH grant EB003805)National Institutes of Health (U.S.) (Grant AR33236)National Science Foundation (U.S.) (NSF grant NIRT-0403903)National Science Foundation (U.S.) (CMMI-0758651)National Institutes of Health (U.S.) (NIH Molecular, Cell, and Tissue Biomechanics Training Grant)Massachusetts Institute of Technology (Whitaker Health Science Fund Fellowship

Bcl-2 and β1-integrin predict survival in a tissue microarray of small cell lung cancer.

INTRODUCTION: Survival in small cell lung cancer (SCLC) is limited by the development of chemoresistance. Factors associated with chemoresistance in vitro have been difficult to validate in vivo. Both Bcl-2 and β(1)-integrin have been identified as in vitro chemoresistance factors in SCLC but their importance in patients remains uncertain. Tissue microarrays (TMAs) are useful to validate biomarkers but no large TMA exists for SCLC. We designed an SCLC TMA to study potential biomarkers of prognosis and then used it to clarify the role of both Bcl-2 and β(1)-integrin in SCLC. METHODS: A TMA was constructed consisting of 184 cases of SCLC and stained for expression of Bcl-2 and β(1)-integrin. The slides were scored and the role of the proteins in survival was determined using Cox regression analysis. A meta-analysis of the role of Bcl-2 expression in SCLC prognosis was performed based on published results. RESULTS: Both proteins were expressed at high levels in the SCLC cases. For Bcl-2 (n=140), the hazard ratio for death if the staining was weak in intensity was 0.55 (0.33-0.94, P=0.03) and for β(1)-integrin (n=151) was 0.60 (0.39-0.92, P=0.02). The meta-analysis showed an overall hazard ratio for low expression of Bcl-2 of 0.91(0.74-1.09). CONCLUSIONS: Both Bcl-2 and β(1)-integrin are independent prognostic factors in SCLC in this cohort although further validation is required to confirm their importance. A TMA of SCLC cases is feasible but challenging and an important tool for biomarker validation

The First Result of Global Commissioning of the ATLAS Endcap Muon Trigger System in ATLAS Cavern

We report on the ATLAS commissioning run from the view point of the Thin Gap Chamber (TGC), which is the ATLAS end cap muon trigger detector. All the TGC sectors with on-detector electronics are going to be installed to the ATLAS cavern by the end of September 2007. To integrate all sub-detectors before the physics run starting from early 2008, the global commissioning run together with other sub-detectors has been performed from June 2007. We have evaluated the performance of the complete trigger chain of the TGC electronics and provide the trigger signal using cosmic-ray to the sub-systems in the global run environment