Graphical Analysis of Spatio-Temporal Patterns in Forage Quality

Due to the highly structured topography in Switzerland, crop growth conditions vary within short distances. Differences in altitude are one of the major causes for climatic variation resulting in significant spatio-temporal effects on forage quality in terms of nutrient content and feeding value, particularly in grassland dominated regions. It is one of the goals of the Swiss feed database to support queries that visualize and quantify the temporal and spatial influence on feed quality

Interpreting vision and language generative models with semantic visual priors

When applied to Image-to-text models, explainability methods have two challenges. First, they often provide token-by-token explanations namely, they compute a visual explanation for each token of the generated sequence. This makes explanations expensive to compute and unable to comprehensively explain the model's output. Second, for models with visual inputs, explainability methods such as SHAP typically consider superpixels as features. Since superpixels do not correspond to semantically meaningful regions of an image, this makes explanations harder to interpret. We develop a framework based on SHAP, that allows for generating comprehensive, meaningful explanations leveraging the meaning representation of the output sequence as a whole. Moreover, by exploiting semantic priors in the visual backbone, we extract an arbitrary number of features that allow the efficient computation of Shapley values on large-scale models, generating at the same time highly meaningful visual explanations. We demonstrate that our method generates semantically more expressive explanations than traditional methods at a lower compute cost and that it can be generalized to a large family of vision-language models

A simulation code to assist designing space missions of the Airwatch type

The design of an Airwatch type space mission can greatly benefit from a flexible simulation code for establishing the values of the main parameters of the experiment. We present here a code written for this purpose. The cosmic ray primary spectrum at very high energies, the atmosphere modelling, the fluorescence yield, the photon propagation and the detector response are taken into account in order to optimize the fundamental design parameters of the experiment, namely orbit height, field of view, mirror radius, number of pixels of the focal plane, threshold of photo-detection. The optimization criterion will be to maximize counting rates versus mission cost, which imposes limits both on weight and power consumption. Preliminary results on signals with changing energy and zenith angle of incident particles are shown

Critical sets of nonlinear Sturm-Liouville operators of Ambrosetti-Prodi type

The critical set C of the operator F:H^2_D([0,pi]) -> L^2([0,pi]) defined by F(u)=-u''+f(u) is studied. Here X:=H^2_D([0,pi]) stands for the set of functions that satisfy the Dirichlet boundary conditions and whose derivatives are in L^2([0,pi]). For generic nonlinearities f, C=\cup C_k decomposes into manifolds of codimension 1 in X. If f''0, the set C_j is shown to be non-empty if, and only if, -j^2 (the j-th eigenvalue of u -> u'') is in the range of f'. The critical components C_k are (topological) hyperplanes.Comment: 6 pages, no figure

Interpreting Vision and Language Generative Models with Semantic Visual Priors

When applied to Image-to-text models, interpretability methods often provide token-by-token explanations namely, they compute a visual explanation for each token of the generated sequence. Those explanations are expensive to compute and unable to comprehensively explain the model's output. Therefore, these models often require some sort of approximation that eventually leads to misleading explanations. We develop a framework based on SHAP, that allows for generating comprehensive, meaningful explanations leveraging the meaning representation of the output sequence as a whole. Moreover, by exploiting semantic priors in the visual backbone, we extract an arbitrary number of features that allows the efficient computation of Shapley values on large-scale models, generating at the same time highly meaningful visual explanations. We demonstrate that our method generates semantically more expressive explanations than traditional methods at a lower compute cost and that it can be generalized over other explainability methods

Girdling, gibberellic acid, and forchlorfenuron: effects on yield, quality, and metabolic profile of table grape cv. Italia

Among the various vineyard treatments adopted in recent years for table-grape cultivation, there has been a significant use of plant growth regulators (PGRs) and girdling to increase berry size and yield. In particular, an increase in the application of forchlorfenuron (CPPU) and gibberellic acid (GA3) for many seeded and seedless table-grape cultivars has been registered in several countries. In this two-year study, girdling at berry set, gibberellic acid (10 mg/L) applied at berry diameter of 10 to 11 mm, and forchlorfenuron (9.75 mg/L) applied at berry diameter of 11 to 12 mm were investigated to verify their effects on berry size, yield, and chemical and metabolic characteristics of Italia grapes. In general, at harvest all treatments significantly increased berry diameter, length, and weight and consequent cluster weight and yield/vine compared to an untreated control. The treatments showed significant differences for the colorimetric parameters, in particular a higher value of hue for berries treated with GA3 and CPPU, thus shifting the skin color from yellow toward yellow-green. Metabolomic study carried out by nuclear magnetic resonance spectroscopy combined with principal component analysis indicated that metabolic profile depends on the year and, in each year, the effect of treatments consisted of a slight variation of amino acid content. Treatments effects were more pronounced in the year characterized by a cooler summer

The Cosmic-Ray Proton and Helium Spectra measured with the CAPRICE98 balloon experiment

A new measurement of the primary cosmic-ray proton and helium fluxes from 3 to 350 GeV was carried out by the balloon-borne CAPRICE experiment in 1998. This experimental setup combines different detector techniques and has excellent particle discrimination capabilities allowing clear particle identification. Our experiment has the capability to determine accurately detector selection efficiencies and systematic errors associated with them. Furthermore, it can check for the first time the energy determined by the magnet spectrometer by using the Cherenkov angle measured by the RICH detector well above 20 GeV/n. The analysis of the primary proton and helium components is described here and the results are compared with other recent measurements using other magnet spectrometers. The observed energy spectra at the top of the atmosphere can be represented by (1.27+-0.09)x10^4 E^(-2.75+-0.02) particles (m^2 GeV sr s)^-1, where E is the kinetic energy, for protons between 20 and 350 GeV and (4.8+-0.8)x10^2 E^(-2.67+-0.06) particles (m^2 GeV nucleon^-1 sr s)^-1, where E is the kinetic energy per nucleon, for helium nuclei between 15 and 150 GeV nucleon^-1.Comment: To be published on Astroparticle Physics (44 pages, 13 figures, 5 tables

Interpreting Vision and Language Generative Models with Semantic Visual Priors

When applied to Image-to-text models, explainability methods have two challenges. First, they often provide token-by-token explanations namely, they compute a visual explanation for each token of the generated sequence. This makes explanations expensive to compute and unable to comprehensively explain the model's output. Second, for models with visual inputs, explainability methods such as SHAP typically consider superpixels as features. Since superpixels do not correspond to semantically meaningful regions of an image, this makes explanations harder to interpret. We develop a framework based on SHAP, that allows for generating comprehensive, meaningful explanations leveraging the meaning representation of the output sequence as a whole. Moreover, by exploiting semantic priors in the visual backbone, we extract an arbitrary number of features that allows the efficient computation of Shapley values on large-scale models, generating at the same time highly meaningful visual explanations. We demonstrate that our method generates semantically more expressive explanations than traditional methods at a lower compute cost and that it can be generalized to a large family of vision-language models

VALSE: A Task-independent benchmark for Vision and Language models centered on linguistic phenomena

We propose VALSE (Vision And Language Structured Evaluation), a novel benchmark designed for testing general-purpose pretrained vision and language (V&L) models for their visio-linguistic grounding capabilities on specific linguistic phenomena. VALSE offers a suite of six tests covering various linguistic constructs. Solving these requires models to ground linguistic phenomena in the visual modality, allowing more fine-grained evaluations than hitherto possible. We build VALSE using methods that support the construction of valid foils, and report results from evaluating five widely-used V&L models. Our experiments suggest that current models have considerable difficulty addressing most phenomena. Hence, we expect VALSE to serve as an important benchmark to measure future progress of pretrained V&L models from a linguistic perspective, complementing the canonical task-centred V&L evaluations

Two years of flight of the Pamela experiment: results and perspectives

PAMELA is a satellite borne experiment designed to study with great accuracy cosmic rays of galactic, solar, and trapped nature in a wide energy range (protons: 80 MeV-700 GeV, electrons 50 MeV-400 GeV). Main objective is the study of the antimatter component: antiprotons (80 MeV-190 GeV), positrons (50 MeV-270 GeV) and search for antinuclei with a precision of the order of $10^{-8}$). The experiment, housed on board the Russian Resurs-DK1 satellite, was launched on June, $15^{th}$ 2006 in a $350\times 600 km$ orbit with an inclination of 70 degrees. In this work we describe the scientific objectives and the performance of PAMELA in its first two years of operation. Data on protons of trapped, secondary and galactic nature - as well as measurements of the December $13^{th}$ 2006 Solar Particle Event - are also provided.Comment: To appear on J. Phys. Soc. Jpn. as part of the proceedings of the International Workshop on Advances in Cosmic Ray Science March, 17-19, 2008 Waseda University, Shinjuku, Tokyo, Japa