A note on optimal capital stock and financing constraints

There is a robust literature on the relationship between financing constraints and real investment. Little has been said on the relationship between financing constraints and capital stock in the long run. This note focuses on this last issue. To keep the model tractable, we assume that the firm employs a single input, and this input is used as collateral. We get three main results. Firstly, we show that the optimal capital stock chosen by a firm is affected by financing constraints even when they are slack at the current time. Secondly, we show that the net present value of the potentially constrained firm is always smaller than the one of the never constrained firm. Finally, we find that in the presence of latent financing constraints the firm does not limit itself to reducing its investment when the upper limit is reached. What it actually does is to lower its long run optimal capital stock, amplifying the effects of constraints in the long run

KERNEL FEATURE CROSS-CORRELATION FOR UNSUPERVISED QUANTIFICATION OF DAMAGE FROM WINDTHROW IN FORESTS

In this study estimation of tree damage from a windthrow event using feature detection on RGB high resolution imagery is assessed. An accurate quantitative assessment of the damage in terms of volume is important and can be done by ground sampling, which is notably expensive and time-consuming, or by manual interpretation and analyses of aerial images. This latter manual method also requires an expert operator investing time to manually detect damaged trees and apply relation functions between measures and volume which are also error-prone. In the proposed method RGB images with 0.2 m ground sample distance are analysed using an adaptive template matching method. Ten images corresponding to ten separate study areas are tested. A 13 7 13 pixels kernel with a simplified lin ear-feature representation of a cylinder is applied at different rotation angles (from 0\ub0 to 170\ub0 at 10\ub0 steps). The higher values of the normalized cross-correlation (NCC) of all angles are recorded for each pixel for each image. Several features are tested: percentiles (75, 80, 85, 90, 95, 99, max) and sum and number of pixels with NCC above 0.55. Three regression methods are tested, multiple regression (mr), support vector machines (SVM) with linear kernel and random forests. The first two methods gave the best results. The ground-truth was acquired by ground sampling, and total volumes of damaged trees are estimated for each of the 10 areas. Damaged volumes in the ten areas range from 3c1.8 7 102 m3 to 3c1.2 7 104 m3. Regression results show that smv regression method over the sum gives an R-squared of 0.92, a mean of absolute errors (MAE) of 255 m3 and a relative absolute error (RAE) of 34% using leave-one-out cross validation from the 10 observations. These initial results are encouraging and support further investigations on more finely tuned kernel template metrics to define an unsupervised image analysis process to automatically assess forest damage from windthrow

One-loop soft theorems via dual superconformal symmetry

This work was supported by the Science and Technology Facilities Council Consolidated Grant ST/L000415/1 String theory, gauge theory & dualit

wall to wall spatial prediction of growing stock volume based on italian national forest inventory plots and remotely sensed data

Abstract Spatial predictions of forest variables are required for supporting modern national and sub-national forest planning strategies, especially in the framework of a climate change scenario. Nowadays methods for constructing wall-to-wall maps and calculating small-area estimates of forest parameters are becoming essential components of most advanced National Forest Inventory (NFI) programs. Such methods are based on the assumption of a relationship between the forest variables and predictor variables that are available for the entire forest area. Many commonly used predictors are based on data obtained from active or passive remote sensing technologies. Italy has almost 40% of its land area covered by forests. Because of the great diversity of Italian forests with respect to composition, structure and management and underlying climatic, morphological and soil conditions, a relevant question is whether methods successfully used in less complex temperate and boreal forests may be applied successfully at country level in Italy. For a study area of more than 48,657 km2 in central Italy of which 43% is covered by forest, the study presents the results of a test regarding wall-to-wall, spatially explicit estimation of forest growing stock volume (GSV) based on field measurement of 1350 plots during the last Italian NFI. For the same area, we used potential predictor variables that are available across the whole of Italy: cloud-free mosaics of multispectral optical satellite imagery (Landsat 5 TM), microwave sensor data (JAXA PALSAR), a canopy height model (CHM) from satellite LiDAR, and auxiliary variables from climate, temperature and precipitation maps, soil maps, and a digital terrain model. Two non-parametric (random forests and k-NN) and two parametric (multiple linear regression and geographically weighted regression) prediction methods were tested to produce wall-to-wall map of growing stock volume at 23-m resolution. Pixel level predictions were used to produce small-area, province-level model-assisted estimates. The performances of all the methods were compared in terms of percent root mean-square error using a leave-one-out procedure and an independent dataset was used for validation. Results were comparable to those available for other ecological regions using similar predictors, but random forests produced the most accurate results with a pixel level R2 = 0.69 and RMSE% = 37.2% against the independent validation dataset. Model-assisted estimates were more precise than the original design-based estimates provided by the NFI

Measuring costs of community mental health care in Italy: A prevalence-based study

AbstractBackground:Information on individual mental healthcare costs and utilization patterns in Italy is scant. We analysed the use and the annual costs of community mental health services (MHS) in an Italian local health authority (LHA). Our aims are to compare the characteristics of patients in the top decile of costs with those of the remaining 90%, and to investigate the demographic and clinical determinants of costs.Methods:This retrospective study is based on administrative data of adult patients with at least one contact with MHS in 2013. Costs of services were estimated using a microcosting method. We defined as high cost (HC) those patients whose community mental health services costs place them in the top decile of the cost distribution. The predictors of costs were investigated using multiple linear regression.Results:The overall costs borne for 7601 patients were 17 million €, with HC accounting for 87% of costs and 73% of services. Compared with the rest of the patients, HC were younger, more likely to be male, to have a diagnosis of psychosis, and longer and more intensive MHS utilization. In multiple linear regression, younger age, longer duration of contact with MHS, psychosis, bipolar disorder, personality disorder, depression, dementia and Italian citizenship accounted for 20.7% of cost variance.Conclusion:Direct mental health costs are concentrated among a small fraction of patients who receive intensive socio-rehabilitation in community services. One limitation includes the unavailability of hospital costs. Our methodology is replicable and useful for national and cross-national benchmarking

Coherent amplitudon generation in K_0.3MoO_3 through ultrafast inter-band quasi particle decay

The charge density wave system K_0.3MoO_3 has been studied using variable energy pump-probe spectroscopy, ellipsometry, and inelastic light scattering. The observed transient reflectivity response exhibits quite a complex behavior, containing contributions due to quasi particle excitations, coherent amplitudons and phonons, and heating effects. The generation of coherent amplitudons is discussed in terms of relaxation of photo-excited quasi particles, and is found to be resonant with the interband plasmon frequency. Two additional coherent excitations observed in the transients are assigned to zone-folding modes of the charge density wave state

Sentinel-2 time series analysis for monitoring multi-taxon biodiversity in mountain beech forests

Biodiversity monitoring represents a major challenge to supporting proper forest ecosystem management and biodiversity conservation. The latter is indeed shifting in recent years from single-species to multi-taxon approaches. However, multi-taxonomic studies are quite rare due to the effort required for performing field surveys. In this context, remote sensing is a powerful tool, continuously providing consistent and open access data at a different range of spatial and temporal scales. In particular, the Sentinel-2 (S2) mission has great potential to produce reliable proxies for biological diversity. In beech forests of two Italian National Parks, we sampled the beetle fauna, breeding birds, and epiphytic lichens. First, we calculated Shannon's entropy and Simpson's diversity. Then, to produce variables for biodiversity assessment, we exploited S2 data acquired in the 4 years 2017-2021. S2 images were used to construct spectral bands and photosynthetic indices time series, from which 91 harmonic metrics were derived. For each taxon and multi-taxon community, we assessed the correlation with S2 harmonic metrics, biodiversity indices, and forest structural variables. Then, to assess the potential of the harmonic metrics in predicting species diversity in terms of Shannon's and Simpson's biodiversity indices, we also fit a random forests model between each diversity index and the best 10 harmonic metrics (in terms of absolute correlation, that is, the magnitude of the correlation) for each taxon. The models' performance was evaluated via the relative root mean squared error (RMSE%). Overall, 241 beetle, 27 bird, and 59 lichen species were recorded. The diversity indices were higher for the multi-taxon community than for the single taxa. They were generally higher in the CVDA site than in GSML, except for the bird community. The highest correlation values between S2 data and biodiversity indices were recorded in CVDA for multi-taxon and beetle communities (| r| = 0.52 and 0.38, respectively), and in GSML for lichen and beetle communities (| r| = 0.34 and 0.26, respectively). RMSE% ranged between 2.53 and 9.99, and between 8.1 and 16.8 for the Simpson and Shannon index, respectively. The most important variables are phase and RMSE of red-Edge bands for bird and lichen communities, while RMSE and time of tassel cap and from EVI indices for beetles and multi-taxon diversity. Our results demonstrate that S2 data can be used for identifying potential biodiversity hotspots, showing that the herein presented harmonic metrics are informative for several taxa inhabiting wood, giving concrete support to cost-effective biodiversity monitoring and nature-based forest management in complex mountain systems

Effective actions, Wilson lines and the IR/UV mixing in noncommutative supersymmetric gauge theories

We study IR/UV mixing effects in noncommutative supersymmetric Yang-Mills theories with gauge group U(N) using background field perturbation theory. We compute three- and four-point functions of background fields, and show that the IR/UV mixed contributions to these correlators can be reproduced from an explicitly gauge-invariant effective action, which is expressed in terms of open Wilson lines.Comment: 23 pages, 8 figures. v2: new section and references added, effective action expressed only in terms of open Wilson lines operator

CUGC for hyperornithinemia-hyperammonemia-homocitrullinuria (HHH) syndrome

From 1999 to date, 50 affecting function variants have been identified and associated to HHH syndrome [1–5]. As it is not available in the literature a complete up-to-date list of disease-causing variants for SLC25A15 gene, we included this information as a Supplementary Excel sheet (See Supplementary Material File #1): this list was created by using LOVD and ClinVar databases and liked to the relevant literature reference. Reported variants consist of: 29 missense variants, 4 frameshift, 11 nonsense, 2 splicing, 2 small deletion, 1 in frame insertion, 1 gross deletion