Logistic regression for simulating damage occurrence on a fruit grading line

Many factors influence the incidence of mechanical damage in fruit handled on a grading line. This makes it difficult to address damage estimation from an analytical point of view. During fruit transfer from one element of a grading line to another, damage occurs as a combined effect of machinery roughness and the intrinsic susceptibility of fruit. This paper describes a method to estimate bruise probability by means of logistic regression, using data yielded by specific laboratory tests. Model accuracy was measured via the statistical significance of its parameters and its classification ability. The prediction model was then linked to a simulation model through which impacts and load levels, similar to those of real grading lines, could be generated. The simulation output sample size was determined to yield reliable estimations. The process makes it possible to derive a suitable line design and the type of fruit that should be handled to maintain bruise levels within European Union (EU) Standards. A real example with peaches was carried out with the aid of the software implementation SIMLIN®, developed by the authors and registered by Madrid Technical University. This kind of tool has been demanded by inter-professional associations and grading lines designers in recent year

The ν=5/2\nu=5/2 Fractional Quantum Hall State in the Presence of Alloy Disorder

We report quantitative measurements of the impact of alloy disorder on the $\nu=5/2$ fractional quantum Hall state. Alloy disorder is controlled by the aluminum content $x$ in the Al$_x$Ga$_{1-x}$As channel of a quantum well. We find that the $\nu=5/2$ state is suppressed with alloy scattering. To our surprise, in samples with alloy disorder the $\nu=5/2$ state appears at significantly reduced mobilities when compared to samples in which alloy disorder is not the dominant scattering mechanism. Our results highlight the distinct roles of the different types of disorder present in these samples, such as the short-range alloy and the long-range Coulomb disorder

Readmissions and the quality of care in patients hospitalized with heart failure

Objectives. Clinical practice guidelines based on the results of randomized clinical trials recommend that patients with heart failure due to left ventricular systolic dysfunction (LVSD) be treated with angiotensin-converting enzyme inhibitors (ACEI) at doses shown to reduce mortality and readmission. This study examined the relationship between ACEI use at discharge and readmission among patients with heart failure due to LVSD. Methods and results. Data were abstracted from the medical records of 2943 randomly selected patients hospitalized for heart failure in 50 hospitals. The outcome of interest was the number of readmissions occurring up to 21 months after discharge. Six-hundred and eleven patients were eligible for analysis. Compared with patients discharged at a recommended ACEI dose, patients not prescribed an ACEI at discharge had an adjusted rate ratio of readmission (RR) of 1.74 [95% confidence interval (CI) 1.22-2.48], while patients prescribed an ACEI at less than a recommended dose had an RR of 1.24 (95% CI 0.91-1.69) (P = 0.005 for the trend). Conclusion. Our results show that ACEI use at discharge in patients with LVSD is associated with decreased rate of readmission. These findings suggest that compliance with the ACEI prescribing recommendations listed in clinical practice guidelines for patients with heart failure due to LVSD confers benefi

How does firm innovativeness enable supply chain resilience?:The moderating role of supply uncertainty and interdependence

Despite its potential benefits in a wide range of circumstances, firm innovativeness received scant attention in relation to managing the various risks and uncertainties in the global business environment. Likewise, there is still a limited understanding of firms’ supply chain resilience (SCR) and its related antecedents in the strategic management literature. This research focuses on exploring the relationship between firm innovativeness and SCR in an attempt to facilitate bridging the gap between two important research streams and shed some light on the contingent value of firm innovativeness against disruptions and adversities. The moderating role of supply uncertainty and interdependence in the focal relationship was also hypothesised and tested. Findings suggest that firm innovativeness is positively associated with firm SCR, and supply uncertainty negatively moderates this relationship but interdependence does not. We argue that this could be due to the dual nature of interdependence in supply networks

A Re-analysis of Caries Rates in a Preventive Trial using Poisson Regression Models

The analysis of caries incidence in clinical trials has several challenging features: (1) The distribution of the number of caries onsets per patient is skewed, with the majority of patients having few or no cavities; (2) the number of surfaces at risk varies (i) over time and (ii) between patients, due to eruption and exfoliation patterns, dental diseases, and treatments ; (3) surfaces within a patient differ in their caries susceptibility, and (4) caries onsets within a patient are correlated due to shared host factors. Recent statistical developments in the area of correlated data analyses permit incorporation of some of these characteristics into the analyses. With Poisson regression models, the expected number of caries onsets can be related to the number of surfaces at risk, the time they have been at risk, and surface- and subject-specific explanatory variables. The parameter estimated in these models is an epidemiological measure of disease occurrence: the disease incidence rate (caries rate) or the rate of change from healthy (sound) to diseased (carious). Differences and ratios of these rates provide standard epidemiological measures of excess risk. To illustrate, Poisson regression models were used for exploratory analyses of the Ylivieska xylitol study.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/67228/2/10.1177_00220345940730021401.pd

Standard survey methods for estimating colony losses and explanatory risk factors in Apis mellifera

This chapter addresses survey methodology and questionnaire design for the collection of data pertaining to estimation of honey bee colony loss rates and identification of risk factors for colony loss. Sources of error in surveys are described. Advantages and disadvantages of different random and non-random sampling strategies and different modes of data collection are presented to enable the researcher to make an informed choice. We discuss survey and questionnaire methodology in some detail, for the purpose of raising awareness of issues to be considered during the survey design stage in order to minimise error and bias in the results. Aspects of survey design are illustrated using surveys in Scotland. Part of a standardized questionnaire is given as a further example, developed by the COLOSS working group for Monitoring and Diagnosis. Approaches to data analysis are described, focussing on estimation of loss rates. Dutch monitoring data from 2012 were used for an example of a statistical analysis with the public domain R software. We demonstrate the estimation of the overall proportion of losses and corresponding confidence interval using a quasi-binomial model to account for extra-binomial variation. We also illustrate generalized linear model fitting when incorporating a single risk factor, and derivation of relevant confidence intervals

Legacy of logging roads in the Congo Basin: how persistent are the scars in forest cover?

Logging roads in the Congo Basin are often associated with forest degradation through fragmentation and access for other land uses. However, in concessions managed for timber production, secondary roads are usually closed after exploitation and are expected to disappear subsequently. Little is known about the effectiveness of this prescription and the factors affecting vegetation recovery rate on abandoned logging roads. In a novel approach we assessed logging roads as temporary elements in the forest landscape that vary in persistence depending on environmental conditions. We analyzed road persistence during the period 1986–2013 in adjacent parts of Cameroon, Central African Republic and Republic of Congo. Three successive phases of road recovery were identified on LANDSAT images: open roads with bare soil, roads in the process of revegetation after abandonment and disappeared roads no longer distinguishable from the surrounding forest. Field based inventories confirmed significant differences between all three categories in density and richness of woody species and cover of dominant herbs. We used dead-end road segments, built for timber exploitation, as sampling units. Only 6% of them were identified as being re-opened. Survival analyses showed median persistence of four years for open roads before changing to the revegetating state and 20 years for revegetating roads before disappearance. Persistence of revegetating roads was 25% longer on geologically poor substrates which might result from slower forest recovery in areas with lower levels of soil nutrient content. We highlight the contrast amongst forests growing on different types of substrate in their potential for ecosystem recovery over time after roads have been abandoned. Forest management plans need to take these constraints into account. Logging activities should be concentrated on the existing road network and sites of low soil resource levels should be spared from business-as-usual exploitation. (Résumé d'auteur

Shock absorbing reception surfaces for collecting fruit during the mechanical harvesting of citrus

Damage to fresh citrus caused by impact of fruits onto collecting surfaces has restricted the adoption of mechanical harvesting. Two different experiments were carried out: investigating free-falling citrus and investigating the shock absorbing capacity of various surfaces. In free-falling experiment damage to mandarin, orange and lemon was studied. Three collecting surfaces were studied: a concrete floor, an elevated canvas provided with a frame and wheels, and a concrete floor covered with a shock absorbing canvases. Three dropping heights were used. In the shock absorbing experiment, an electronic sphere and a triaxial accelerometer were used to measure the shock capacity of seven receiving surfaces: earth, earth covered with a shock absorbing canvas, earth covered with weeds, earth covered with a mulch and an elevated canvas provided with a frame and wheels. The elevated canvases had a higher shock absorbing capacity compared to the other surfaces (260 m s−2 maximum acceleration compared with 1753 m s−2 to 2772 m s−2). Weeds, mulch and the shock absorbing canvases showed significantly higher shock absorbing capacity than the bare earth. Also, the shock absorbing canvas covering the concrete floor reduce impact and fruit damage (1866 m s−2 maximum acceleration compared to 2477 m s−2). Citrus damage susceptibility during harvest depended on variety. Weeds, mulch and shock absorbing canvases were shown to reduce impact when they cover earth during the mechanical harvesting of citrus. Elevated canvases could be used as collection systems for the mechanical harvesting of fresh citrus.This study was funded by the Ministerio de Ciencia e Innovacion (research project RTA2009-00118-C02-02) and FEDER. The authors are most grateful to the following collaborators: Maria del Mar Lopez Quevedo, Montano Perez, Juan Jose Pena and Angel Perez.Ortiz Sánchez, MC.; Blasco, J.; Balasch Parisi, S.; Torregrosa Mira, A. (2011). Shock absorbing reception surfaces for collecting fruit during the mechanical harvesting of citrus. Biosystems Engineering. 110(1):2-9. https://doi.org/10.1016/j.biosystemseng.2011.05.006S29110

Predicting Remaining Useful Life with Similarity-Based Priors

Prognostics is the area of research that is concerned with predicting the remaining useful life of machines and machine parts. The remaining useful life is the time during which a machine or part can be used, before it must be replaced or repaired. To create accurate predictions, predictive techniques must take external data into account on the operating conditions of the part and events that occurred during its lifetime. However, such data is often not available. Similarity-based techniques can help in such cases. They are based on the hypothesis that if a curve developed similarly to other curves up to a point, it will probably continue to do so. This paper presents a novel technique for similarity-based remaining useful life prediction. In particular, it combines Bayesian updating with priors that are based on similarity estimation. The paper shows that this technique outperforms other techniques on long-term predictions by a large margin, although other techniques still perform better on short-term predictions.</p