Attraction of Apple Maggot Flies (Diptera: Tephritidae) to Synthetic Fruit Volatile Compounds and Food Attractants in Michigan Apple Orchards

The apple maggot, Rhagoletis pomonella (Walsh), is a serious pest of apples in the United States, requiring reliable monitoring and control programs. Various synthetic apple volatile lures with and without protein hydrolysate, ammonium acetate, or ammonium carbonate were evaluated from 1998-2000 for their attractiveness to R. pomonella adults with red sticky-sphere (9 cm diam.) monitoring traps. A blend consisting of butyl butanoate (10%), propyl hexano- ate (4%), butyl hexanoate (37%), hexyl butanoate (44%), and pentyl hexanoate (5%) was the most effective lure tested for attracting both sexes of R. pomonella adults during all three field seasons. The addition of protein hydrolysate or ammonium compounds to spheres baited with a commercial attractant (BioLure) consisting of plastic dispensers containing butyl hexanoate, did not significantly increase apple maggot fly captures. Spheres baited with the blend or with butyl hexanoate in polyethylene vials and spheres baited with BioLure dispensers were highly selective in capturing R. pomonella flies relative to non-target insects. However, spheres baited with ammonium compounds with or without synthetic apple lures were non-selective with respect to apple maggot captures. Protein hydrolysate alone was ineffective for monitoring R. pomonella flies. We provide further evidence that baiting red-sticky sphere traps with the volatile blend without ammonium bait additives creates a highly effective and selective device for capturing apple maggot flies. The blend could be an important addition to current monitoring and control programs for apple maggot flies in Michigan orchards and other important apple growing regions

El sistema de cierre asistido al vacío en el tratamiento del pie diabético avanzado

Deep diabetic foot lesions pose an enormous therapeutic problem. The purpose of this study was to present the experience of the use of vacuum assisted closure (VAC) in the treatment of advanced and complicated diabetic foot lesions. MATERIAL AND METHODS: Five cases of advanced diabetic foot that were treated with VAC were prospectively studied. Three patients were diagnosed with renal failure, including one with renal transplant, who were receiving immunosuppression therapy. Four patients had undergone local foot surgery. The foot lesions were classified as grade 3 or 4 according to the Wagner classification. In all patients extensive debridement was performed that resulted in open minor amputations in four cases and resection of the metatarsophalangeal joint in one case. The VAC was applied during the same procedure. The median follow-up period of the patients was 9 months. RESULTS: Foot salvage was achieved in all cases. The median number of changes of VAC was 16 within median period of 8 weeks. Half of the changes were performed as an outpatient procedure. There were no major complications or clinical signs of infection observed. In one case before treatment with VAC began, angioplasty of the iliac artery and superficial femoral artery was performed. Other interventions carried out after the treatment was started were, two distal revascularizations and two partial transmetatarsal amputations. CONCLUSIONS: VAC appears to be very useful in the treatment of advanced diabetic foot lesion

Computable Bayesian Compression for Uniformly Discretizable Statistical Models

Supplementing Vovk and V'yugin's `if' statement, we show that Bayesian compression provides the best enumerable compression for parameter-typical data if and only if the parameter is Martin-L\"of random with respect to the prior. The result is derived for uniformly discretizable statistical models, introduced here. They feature the crucial property that given a~discretized parameter, we can compute how much data is needed to learn its value with little uncertainty. Exponential families and certain nonparametric models are shown to be uniformly discretizable

A general definition of conditional information and its application to ergodic decomposition

We discuss a simple definition of conditional mutual information (CMI) for fields and $\sigma$-fields. The new definition is applicable also in nonregular cases, unlike the well-known but more restricted definition of CMI by Dobrushin. Certain properties of the two notions of CMI and their equivalence for countably generated $\sigma$-fields are established. We also consider an application, which concerns the ergodic decomposition of mutual information for stationary processes. In this case, CMI is tightly linked, via additivity of information, with entropy defined as self-information. Thus we reconsider the latter concept in some detail

A general definition of conditional information and its application to ergodic decomposition

We discuss a~simple definition of conditional mutual information (CMI) for fields and $\sigma$-fields. The new definition is applicable also in nonregular cases, unlike the well-known but more restricted definition of CMI by Dobrushin. Certain properties of the two notions of CMI and their equivalence for countably generated $\sigma$-fields are established. We also consider an application, which concerns the ergodic decomposition of mutual information for stationary processes. In this case, CMI is tightly linked, via additivity of information, with entropy defined as self-information. Thus we reconsider the latter concept in some detail

On the Vocabulary of Grammar-Based Codes and the Logical Consistency of Texts

The article presents a new interpretation for Zipf's law in natural language which relies on two areas of information theory. We reformulate the problem of grammar-based compression and investigate properties of strongly nonergodic stationary processes. The motivation for the joint discussion is to prove a proposition with a simple informal statement: If an $n$-letter long text describes $n^\beta$ independent facts in a random but consistent way then the text contains at least $n^\beta/\log n$ different words. In the formal statement, two specific postulates are adopted. Firstly, the words are understood as the nonterminal symbols of the shortest grammar-based encoding of the text. Secondly, the texts are assumed to be emitted by a nonergodic source, with the described facts being binary IID variables that are asymptotically predictable in a shift-invariant way. The proof of the formal proposition applies several new tools. These are: a construction of universal grammar-based codes for which the differences of code lengths can be bounded easily, ergodic decomposition theorems for mutual information between the past and future of a stationary process, and a lemma that bounds differences of a sublinear function. The linguistic relevance of presented modeling assumptions, theorems, definitions, and examples is discussed in parallel.While searching for concrete processes to which our proposition can be applied, we introduce several instances of strongly nonergodic processes. In particular, we define the subclass of accessible description processes, which formalizes the notion of texts that describe facts in a self-contained way

Evaluation of semiochemical based push-pull strategy for population suppression of ambrosia beetle vectors of laurel wilt disease in avocado.

Ambrosia beetles (Coleoptera: Curculionidae: Scolytinae and Platypodinae) bore into tree xylem to complete their life cycle, feeding on symbiotic fungi. Ambrosia beetles are a threat to avocado where they have been found to vector a symbiotic fungus, Raffaelea lauricola, the causal agent of the laurel wilt disease. We assessed the repellency of methyl salicylate and verbenone to two putative laurel wilt vectors in avocado, Xyleborus volvulus (Fabricius) and Xyleborus bispinatus (Eichhoff), under laboratory conditions. Then, we tested the same two chemicals released from SPLAT flowable matrix with and without low-dose ethanol dispensers for manipulation of ambrosia beetle populations occurring in commercial avocado. The potential active space of repellents was assessed by quantifying beetle catch on traps placed 'close' (~5-10 cm) and 'far' (~1-1.5 m) away from repellent dispensers. Ambrosia beetles collected on traps associated with all in-field treatments were identified to species to assess beetle diversity and community variation. Xyleborus volvulus was not repelled by methyl salicylate (MeSA) or verbenone in laboratory assays, while X. bispinatus was repelled by MeSA but not verbenone. Ambrosia beetle trap catches were reduced in the field more when plots were treated with verbenone dispensers (SPLAT) co-deployed with low-dose ethanol dispensers than when treated with verbenone alone. Beetle diversity was highest on traps deployed with low-dose ethanol lures. The repellent treatments and ethanol lures significantly altered the species composition of beetles captured in experiment plots. Our results indicate that verbenone co-deployed with ethanol lures holds potential for manipulating ambrosia beetle vectors via push-pull management in avocado. This tactic could discourage immigration and/or population establishment of ambrosia beetles in commercial avocado and function as an additional tool for management programs of laurel wilt

Optimal Hedging with the Vector Autoregressive Model

__Abstract__ We derive the optimal hedging ratios for a portfolio of assets driven by a Cointegrated Vector Autoregressive model with general cointegration rank. Our hedge is optimal in the sense of minimum variance portfolio. We consider a model that allows for the hedges to be cointegrated with the hedged asset and among themselves. We nd that the minimum variance hedge for assets driven by the CVAR, depends strongly on the portfolio holding period. The hedge is dened as a function of correlation and cointegration parameters. For short holding periods the correlation impact is predominant. For long horizons, the hedge ratio should overweight the cointegration parameters rather then short-run correlation information. In the innite horizon, the hedge ratios shall be equal to the cointegrating vector. The hedge ratios for any intermediate portfolio holding period should be based on the weighted average of correlation and cointegration parameters. The results are general and can be applied for any portfolio of assets that can be modeled by the CVAR of any rank and order