Quality metrics for sensor images

Methods are needed for evaluating the quality of augmented visual displays (AVID). Computational quality metrics will help summarize, interpolate, and extrapolate the results of human performance tests with displays. The FLM Vision group at NASA Ames has been developing computational models of visual processing and using them to develop computational metrics for similar problems. For example, display modeling systems use metrics for comparing proposed displays, halftoning optimizing methods use metrics to evaluate the difference between the halftone and the original, and image compression methods minimize the predicted visibility of compression artifacts. The visual discrimination models take as input two arbitrary images A and B and compute an estimate of the probability that a human observer will report that A is different from B. If A is an image that one desires to display and B is the actual displayed image, such an estimate can be regarded as an image quality metric reflecting how well B approximates A. There are additional complexities associated with the problem of evaluating the quality of radar and IR enhanced displays for AVID tasks. One important problem is the question of whether intruding obstacles are detectable in such displays. Although the discrimination model can handle detection situations by making B the original image A plus the intrusion, this detection model makes the inappropriate assumption that the observer knows where the intrusion will be. Effects of signal uncertainty need to be added to our models. A pilot needs to make decisions rapidly. The models need to predict not just the probability of a correct decision, but the probability of a correct decision by the time the decision needs to be made. That is, the models need to predict latency as well as accuracy. Luce and Green have generated models for auditory detection latencies. Similar models are needed for visual detection. Most image quality models are designed for static imagery. Watson has been developing a general spatial-temporal vision model to optimize video compression techniques. These models need to be adapted and calibrated for AVID applications

Signaling of Human Frizzled Receptors to the Mating Pathway in Yeast

Frizzled receptors have seven membrane-spanning helices and are considered as atypical G protein-coupled receptors (GPCRs). The mating response of the yeast Saccharomyces cerevisiae is mediated by a GPCR signaling system and this model organism has been used extensively in the past to study mammalian GPCR function. We show here that human Frizzled receptors (Fz1 and Fz2) can be properly targeted to the yeast plasma membrane, and that they stimulate the yeast mating pathway in the absence of added Wnt ligands, as evidenced by cell cycle arrest in G1 and reporter gene expression dependent on the mating pathway-activated FUS1 gene. Introducing intracellular portions of Frizzled receptors into the Ste2p backbone resulted in the generation of constitutively active receptor chimeras that retained mating factor responsiveness. Introducing intracellular portions of Ste2p into the Frizzled receptor backbone was found to strongly enhance mating pathway activation as compared to the native Frizzleds, likely by facilitating interaction with the yeast Gα protein Gpa1p. Furthermore, we show reversibility of the highly penetrant G1-phase arrests exerted by the receptor chimeras by deletion of the mating pathway effector FAR1. Our data demonstrate that Frizzled receptors can functionally replace mating factor receptors in yeast and offer an experimental system to study modulators of Frizzled receptors

Enablers to implement sustainable initiatives in agri-food supply chains

yesDue to rapid agricultural industrialization, increased global food demand, and, increasing concerns related to food quality and safety, the concepts of sustainability and supply chain transparency are becoming critically important to the agriculture and agri-food sector. The new focus on sustainability performance objectives emphasizes the effective utilization and consumption of natural resources to balance ecological, economic and societal aspects of agri-food businesses. The management of sustainability adds a new demand on business managers who often have small profits and receive stringent requirements from large powerful customers and retailers. In this paper, we recognize and analyze the key enablers in implementing sustainable initiatives for Agri-Food Supply Chains (A-FSCs). Ten important sustainability driven enablers were considered from a rigorous literature review and phase of expert consultation. The identified enablers were then analyzed using a combined Interpretive Structural Modeling (ISM) - fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL) based framework. The ISM approach enabled an appreciation of the contextual relationships among the enablers and to classify the enablers based on their driving and dependence potential. The fuzzy DEMATEL technique supported the determination of the influential and influenced enablers and also to categorize them into cause and effect groups. An empirical case study, drawn from a vegetable and fruit retail supply chain in India, is used to focus and test the applicability of the proposed research framework. The paper facilitates professional management practice and researchers to uncover and explore the enablers for the real execution of sustainability oriented initiatives in the agri-food business sector

Advances in the treatment of prolactinomas

Prolactinomas account for approximately 40% of all pituitary adenomas and are an important cause of hypogonadism and infertility. The ultimate goal of therapy for prolactinomas is restoration or achievement of eugonadism through the normalization of hyperprolactinemia and control of tumor mass. Medical therapy with dopamine agonists is highly effective in the majority of cases and represents the mainstay of therapy. Recent data indicating successful withdrawal of these agents in a subset of patients challenge the previously held concept that medical therapy is a lifelong requirement. Complicated situations, such as those encountered in resistance to dopamine agonists, pregnancy, and giant or malignant prolactinomas, may require multimodal therapy involving surgery, radiotherapy, or both. Progress in elucidating the mechanisms underlying the pathogenesis of prolactinomas may enable future development of novel molecular therapies for treatment-resistant cases. This review provides a critical analysis of the efficacy and safety of the various modes of therapy available for the treatment of patients with prolactinomas with an emphasis on challenging situations, a discussion of the data regarding withdrawal of medical therapy, and a foreshadowing of novel approaches to therapy that may become available in the future

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field

The power of monitoring: optimizing survey designs to detect occupancy changes in a rare amphibian population

Biodiversity conservation requires reliable species assessments and rigorously designed surveys. However, determining the survey effort required to reliably detect population change can be challenging for rare, cryptic and elusive species. We used a tropical bromeliad-dwelling frog as a model system to explore a cost-effective sampling design that optimizes the chances of detecting a population decline. Relatively few sampling visits were needed to estimate occupancy and detectability with good precision, and to detect a 30% change in occupancy with 80% power. Detectability was influenced by observer expertise, which therefore also had an effect on the sampling design – less experienced observers require more sampling visits to detect the species. Even when the sampling design provides precise parameter estimates, only moderate to large changes in occupancy will be detected with reliable power. Detecting a population change of 15% or less requires a large number of sites to be surveyed, which might be unachievable for range-restricted species occurring at relatively few sites. Unless there is high initial occupancy, rare and cryptic species will be particularly challenging when it comes to detecting small population changes. This may be a particular issue for long-term monitoring of amphibians which often display low detectability and wide natural fluctuations