Elastic stresses and plastic deformations in 'Santa Clara' tomato fruits caused by package dependent compression

The objective of this work was to study the fruit compression behavior aiming to develop new tomato packages. Deformations caused by compression forces were observed inside packages and in individual 'Santa Clara' tomato fruit. The forces applied by a transparent acrylic lever to the fruit surface caused pericarp deformation and the flattened area was proportional to the force magnitude. The deformation was associated to the reduction in the gas volume (Vg), caused by expulsion of the air from the loculus cavity and reduction in the intercellular air volume of the pericarp. As ripening advanced, smaller fractions of the Vg reduced by the compressive force were restored after the stress was relieved. The lack of complete Vg restoration was an indication of permanent plastic deformations of the stressed cells. Vg regeneration (elastic recovery) was larger in green fruits than in the red ones. The ratio between the applied force and the flattened area (flattening pressure), which depends on cell turgidity, decreased during ripening. Fruit movements associated with its depth in the container were observed during storage in a transparent glass container (495 x 355 x 220 mm). The downward movement of the fruits was larger in the top layers because these movements seem to be driven by a summation of the deformation of many fruits in all layers.

Protéinurie orthostatique et phénomène de compression de la veine rénale gauche (nutcracker syndrome) [Orthostatic proteinuria and compression of the left renal vein (nutcracker syndrome)]

INTRODUCTION: The pathogenic mechanism of orthostatic proteinuria has not yet been clearly established. OBSERVATION: In a tall, thin, 21 year-old man, isolated proteinuria was discovered during an urological control conducted one year after a bilateral orchidopexy following left testicular torsion. Proteinuria was orthostatic. Doppler examination of the kidney revealed an entrapment of the left renal vein (nutcracker phenomenon-NCP). COMMENTS: An NCP was diagnosed in a young patient presenting with orthostatic proteinuria. By provoking modifications in intraglomerular haemodynamics, the NCP may, in nearly half of the cases, be at the origin of orthostatic proteinuria. Doppler examination is the diagnostic method of choice in the screening for NCP.

Trigeminal neuralgia related to megadolichobasilar artery compression: a prospective series of twenty-nine patients treated with gamma knife surgery, with more than one year of follow-up.

BACKGROUND: Trigeminal neuralgia (TN) secondary to megadolichobasilar artery (MBA) compression is considerably difficult to manage surgically. OBJECTIVE: This study aims to evaluate the safety/efficacy of Gamma Knife surgery (GKS) in this special group of patients. METHODS: Between July 1992 and November 2010, 29 patients with >1 year of follow-up presenting with MBA compression were treated with GKS at Timone University Hospital. Radiosurgery was performed using a Gamma Knife (model B, C or Perfexion). A single 4-mm isocenter was positioned in the cisternal portion of the trigeminal nerve at a median distance of 9.1 mm (range: 6-18.2 mm) from the emergence. RESULTS: The median follow-up period was 46.1 months (range: 12.9-157.9 months). Initially, all patients (100%) were pain free; the average time to complete pain relief was 13.5 days (range: 0-240 days). Their actuarial probability of remaining pain free without medication at 0.5, 1 and 2 years was 93.1, 79.3 and 75.7%, respectively, and remained stable until 13 years after treatment. The actuarial probability of hypoesthesia onset at 6 months was 4.3%; at 1 year it reached 13% and remained stable until 13 years after treatment. CONCLUSIONS: GKS proved to be reasonably safe and effective on a long-term basis as a first- and/or second-line surgical treatment for TN due to MBA compression.

Ensemble methods for environmental data modelling with support vector regression

This paper investigates the use of ensemble of predictors in order to improve the performance of spatial prediction methods. Support vector regression (SVR), a popular method from the field of statistical machine learning, is used. Several instances of SVR are combined using different data sampling schemes (bagging and boosting). Bagging shows good performance, and proves to be more computationally efficient than training a single SVR model while reducing error. Boosting, however, does not improve results on this specific problem.

Nanoparticles in SiH4-Ar plasma: Modelling and comparison with experimental data

Experimental and theoretical investigations for growth of silicon nanoparticles (4 to 14 nm) in radio frequency discharge were carried out. Growth processes were performed with gas mixtures of SiH4 and Ar in a plasma chemical reactor at low pressure. A distinctive feature of presented kinetic model of generation and growth of nanoparticles (compared to our earlier model) is its ability to investigate small"critical" dimensions of clusters, determining the rate of particle production and taking into account the influence of SiH2 and Si2Hm dimer radicals. The experiments in the present study were extended to high pressure (≥20 Pa) and discharge power (≥40 W). Model calculations were compared to experimental measurements, investigating the dimension of silicon nanoparticles as a function of time, discharge power, gas mixture, total pressure, and gas flow.

Modelling Bone Mineral Density in Swiss Breast Cancer Patients Treated with Letrozole, Tamoxifen and Sequences of Letrozole and Tamoxifen in the BIG 1-98 Study (SAKK 21/07).

Background: Bone health is a concern when treating early stage breast cancer patients with adjuvant aromatase inhibitors. Early detection of patients (pts) at risk of osteoporosis and fractures may be helpful for starting preventive therapies and selecting the most appropriate endocrine therapy schedule. We present statistical models describing the evolution of lumbar and hip bone mineral density (BMD) in pts treated with tamoxifen (T), letrozole (L) and sequences of T and L. Methods: Available dual-energy x-ray absorptiometry exams (DXA) of pts treated in trial BIG 1-98 were retrospectively collected from Swiss centers. Treatment arms: A) T for 5 years, B) L for 5 years, C) 2 years of T followed by 3 years of L and, D) 2 years of L followed by 3 years of T. Pts without DXA were used as a control for detecting selection biases. Patients randomized to arm A were subsequently allowed an unplanned switch from T to L. Allowing for variations between DXA machines and centres, two repeated measures models, using a covariance structure that allow for different times between DXA, were used to estimate changes in hip and lumbar BMD (g/cm2) from trial randomization. Prospectively defined covariates, considered as fixed effects in the multivariable models in an intention to treat analysis, at the time of trial randomization were: age, height, weight, hysterectomy, race, known osteoporosis, tobacco use, prior bone fracture, prior hormone replacement therapy (HRT), bisphosphonate use and previous neo-/adjuvant chemotherapy (ChT). Similarly, the T-scores for lumbar and hip BMD measurements were modeled using a per-protocol approach (allowing for treatment switch in arm A), specifically studying the effect of each therapy upon T-score percentage. Results: A total of 247 out of 546 pts had between 1 and 5 DXA; a total of 576 DXA were collected. Number of DXA measurements per arm were; arm A 133, B 137, C 141 and D 135. The median follow-up time was 5.8 years. Significant factors positively correlated with lumbar and hip BMD in the multivariate analysis were weight, previous HRT use, neo-/adjuvant ChT, hysterectomy and height. Significant negatively correlated factors in the models were osteoporosis, treatment arm (B/C/D vs. A), time since endocrine therapy start, age and smoking (current vs. never).Modeling the T-score percentage, differences from T to L were -4.199% (p = 0.036) and -4.907% (p = 0.025) for the hip and lumbar measurements respectively, before any treatment switch occurred. Conclusions: Our statistical models describe the lumbar and hip BMD evolution for pts treated with L and/or T. The results of both localisations confirm that, contrary to expectation, the sequential schedules do not seem less detrimental for the BMD than L monotherapy. The estimated difference in BMD T-score percent is at least 4% from T to L.

Objectives and motivations of small-scale forest owners : theoretical modelling and qualitative assessment

Abstract

Stem straightness and compression wood in a 22-year-old stand of container-grown Scots pine trees

Abstract

Modelling ecological niches with support vector machines

1. The ecological niche is a fundamental biological concept. Modelling species' niches is central to numerous ecological applications, including predicting species invasions, identifying reservoirs for disease, nature reserve design and forecasting the effects of anthropogenic and natural climate change on species' ranges. 2. A computational analogue of Hutchinson's ecological niche concept (the multidimensional hyperspace of species' environmental requirements) is the support of the distribution of environments in which the species persist. Recently developed machine-learning algorithms can estimate the support of such high-dimensional distributions. We show how support vector machines can be used to map ecological niches using only observations of species presence to train distribution models for 106 species of woody plants and trees in a montane environment using up to nine environmental covariates. 3. We compared the accuracy of three methods that differ in their approaches to reducing model complexity. We tested models with independent observations of both species presence and species absence. We found that the simplest procedure, which uses all available variables and no pre-processing to reduce correlation, was best overall. Ecological niche models based on support vector machines are theoretically superior to models that rely on simulating pseudo-absence data and are comparable in empirical tests. 4. Synthesis and applications. Accurate species distribution models are crucial for effective environmental planning, management and conservation, and for unravelling the role of the environment in human health and welfare. Models based on distribution estimation rather than classification overcome theoretical and practical obstacles that pervade species distribution modelling. In particular, ecological niche models based on machine-learning algorithms for estimating the support of a statistical distribution provide a promising new approach to identifying species' potential distributions and to project changes in these distributions as a result of climate change, land use and landscape alteration.

A new spin on a compositionalist predictive modelling framework for conservation planning: a tropical case study in Ecuador

Knowledge about spatial biodiversity patterns is a basic criterion for reserve network design. Although herbarium collections hold large quantities of information, the data are often scattered and cannot supply complete spatial coverage. Alternatively, herbarium data can be used to fit species distribution models and their predictions can be used to provide complete spatial coverage and derive species richness maps. Here, we build on previous effort to propose an improved compositionalist framework for using species distribution models to better inform conservation management. We illustrate the approach with models fitted with six different methods and combined using an ensemble approach for 408 plant species in a tropical and megadiverse country (Ecuador). As a complementary view to the traditional richness hotspots methodology, consisting of a simple stacking of species distribution maps, the compositionalist modelling approach used here combines separate predictions for different pools of species to identify areas of alternative suitability for conservation. Our results show that the compositionalist approach better captures the established protected areas than the traditional richness hotspots strategies and allows the identification of areas in Ecuador that would optimally complement the current protection network. Further studies should aim at refining the approach with more groups and additional species information.