Developing a decomposable measure of profit efficiency using DEA

In for-profit organizations efficiency measurement with reference to the potential for profit augmentation is particularly important as is its decomposition into technical, and allocative components. Different profit efficiency approaches can be found in the literature to measure and decompose overall profit efficiency. In this paper, we highlight some problems within existing approaches and propose a new measure of profit efficiency based on a geometric mean of input/output adjustments needed for maximizing profits. Overall profit efficiency is calculated through this efficiency measure and is decomposed into its technical and allocative components. Technical efficiency is calculated based on a non-oriented geometric distance function (GDF) that is able to incorporate all the sources of inefficiency, while allocative efficiency is retrieved residually. We also define a measure of profitability efficiency which complements profit efficiency in that it makes it possible to retrieve the scale efficiency of a unit as a component of its profitability efficiency. In addition, the measure of profitability efficiency allows for a dual profitability interpretation of the GDF measure of technical efficiency. The concepts introduced in the paper are illustrated using a numerical example

Falling Pitch Imitating Doppler Shift Facilitates Detection of Visual Motion in The Extreme-Periphery

Previous studies demonstrated that concurrent auditory stimuli can bias visual motion perception in the periphery more than in the fovea (e.g., Takeshima & Gyoba, 2013), and auditory becomes crucial when reliability of vision is reduced (e.g., Schmiedchen et al., 2012). We investigated if auditory affects detecting extreme-peripheral visual motion from behind, which is possibly one of the most salient situations since visual ambiguity is very high and detecting such motion can be ecologically critical to survive. In the experiment, a sequence of three 204 ms dots (255 ms SOA) was presented in the extreme-periphery (individually set by the largest eccentricity with 75% detection); each dot was presented at 3 adjacent locations with 2° distance so as to have apparent motion forward, or at the same location. As auditory stimuli, we employed concurrent beep with falling pitch, which roughly imitated Doppler pitch shift for passing-by object. We employed concurrent beep with rising pitch as a control, in addition to another no sound control. The results showed the concurrent beep with falling pitch increased the hit rate for motion detection, relative to that with no sound and rising pitch beep. Underlying mechanism was discussed with signal detection analysis

A unique spinodal region in asymmetric nuclear matter

Asymmetric nuclear matter at sub-saturation densities is shown to present only one type of instabilities. The associated order parameter is dominated by the isoscalar density and so the transition is of liquid-gas type. The instability goes in the direction of a restoration of the isospin symmetry leading to a fractionation phenomenon. These conclusions are model independent since they can be related to the general form of the asymmetry energy. They are illustrated using density functional approaches.Comment: 4 pages, 5 figures, to appear in Phys. Rev.

Extracting non-linear integrate-and-fire models from experimental data using dynamic I–V curves

The dynamic I–V curve method was recently introduced for the efficient experimental generation of reduced neuron models. The method extracts the response properties of a neuron while it is subject to a naturalistic stimulus that mimics in vivo-like fluctuating synaptic drive. The resulting history-dependent, transmembrane current is then projected onto a one-dimensional current–voltage relation that provides the basis for a tractable non-linear integrate-and-fire model. An attractive feature of the method is that it can be used in spike-triggered mode to quantify the distinct patterns of post-spike refractoriness seen in different classes of cortical neuron. The method is first illustrated using a conductance-based model and is then applied experimentally to generate reduced models of cortical layer-5 pyramidal cells and interneurons, in injected-current and injected- conductance protocols. The resulting low-dimensional neuron models—of the refractory exponential integrate-and-fire type—provide highly accurate predictions for spike-times. The method therefore provides a useful tool for the construction of tractable models and rapid experimental classification of cortical neurons

Thalamic Network Oscillations Synchronize Ontogenetic Columns in the Newborn Rat Barrel Cortex

Neocortical areas are organized in columns, which form the basic structural and functional modules of intracortical information processing. Using voltage-sensitive dye imaging and simultaneous multi-channel extracellular recordings in the barrel cortex of newborn rats in vivo, we found that spontaneously occurring and whisker stimulation-induced gamma bursts followed by longer lasting spindle bursts were topographically organized in functional cortical columns already at the day of birth. Gamma bursts synchronized a cortical network of 300-400 µm in diameter and were coherent with gamma activity recorded simultaneously in the thalamic ventral posterior medial (VPM) nucleus. Cortical gamma bursts could be elicited by focal electrical stimulation of the VPM. Whisker stimulation-induced spindle and gamma bursts and the majority of spontaneously occurring events were profoundly reduced by the local inactivation of the VPM, indicating that the thalamus is important to generate these activity patterns. Furthermore, inactivation of the barrel cortex with lidocaine reduced the gamma activity in the thalamus, suggesting that a cortico-thalamic feedback loop modulates this early thalamic network activit

How do banks assess entrepreneurial competence? The role of voluntary information disclosure

This research adds to the literature on relationship lending in the small business context by discussing the roles of entrepreneurial competence and voluntarily disclosed information as determinants of credit access. More specifically, we propose that the loan manager’s evaluation of the information voluntarily disclosed by the entrepreneur is an important complement to publicly available financial data and soft information collected through observation and third parties in framing the loan manager’s perception of the entrepreneur’s competence. Further, we argue that banks charge lower interest rates if the loan manager perceives the entrepreneur to be competent. Econometric analysis based on 433 bank-firm relationships supports these hypothesised relationships. The results imply that entrepreneurs need to communicate their competence effectively to loan managers, and that banks should utilise their loan managers’ personal evaluations as inputs to lending decisions

Collateral Quality and Loan Default Risk: The Case of Vietnam

In the transition economy of Vietnam, financial market is dominated by banking sector but commercial banks heavily rely on collateral-based lending. While the relationship between collateral and implied credit risk is still in debate, this paper provides additional empirical evidence regarding the heterogeneous effects and transmission channels of collateral characteristics on loan delinquency. Applying instrumental variable probit analysis on a unique dataset of 2295 internal loan accounts in Vietnam, we find the significantly negative impact of collateral quality on the probability of default of consumer loans, supporting the dominance of borrower selection and risk-shifting over lender selection effects. The finding implies that high-quality collateral not only signals more credible borrower but also fosters good behavior in using loan, enabling bank to mitigate adverse selection and moral hazard problems

Quantifying Irrigated Winter Wheat LAI in Argentina Using Multiple Sentinel-1 Incidence Angles

Synthetic aperture radar (SAR) data provides an appealing opportunity for all-weather day or night Earth surface monitoring. The European constellation Sentinel-1 (S1) consisting of S1-A and S1-B satellites offers a suitable revisit time and spatial resolution for the observation of croplands from space. The C-band radar backscatter is sensitive to vegetation structure changes and phenology as well as soil moisture and roughness. It also varies depending on the local incidence angle (LIA) of the SAR acquisition’s geometry. The LIA backscatter dependency could therefore be exploited to improve the retrieval of the crop biophysical variables. The availability of S1 radar time-series data at distinct observation angles holds the feasibility to retrieve leaf area index (LAI) evolution considering spatiotemporal coverage of intensively cultivated areas. Accordingly, this research presents a workflow merging multi-date S1 smoothed data acquired at distinct LIA with a Gaussian processes regression (GPR) and a cross-validation (CV) strategy to estimate cropland LAI of irrigated winter wheat. The GPR-S1-LAI model was tested against in situ data of the 2020 winter wheat campaign in the irrigated valley of Colorador river, South of Buenos Aires Province, Argentina. We achieved adequate validation results for LAI with R2CV = 0.67 and RMSECV = 0.88 m2 m−2. The trained model was further applied to a series of S1 stacked images, generating temporal LAI maps that well reflect the crop growth cycle. The robustness of the retrieval workflow is supported by the associated uncertainties along with the obtained maps. We found that processing S1 smoothed imagery with distinct acquisition geometries permits accurate radar-based LAI modeling throughout large irrigated areas and in consequence can support agricultural management practices in cloud-prone agri-environments.EEA Hilario AscasubiFil: Caballero, Gabriel. Technological University of Uruguay (UTEC). Agri-Environmental Engineering; UruguayFil: Caballero, Gabriel. University of Valencia. Image Processing Laboratory (IPL); EspañaFil: Pezzola, Alejandro. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Hilario Ascasubi; ArgentinaFil: Winschel, Cristina Ines. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Hilario Ascasubi; ArgentinaFil: Casella, Alejandra. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; ArgentinaFil: Sanchez Angonova, Paolo Andres. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Hilario Ascasubi; ArgentinaFil: Orden, Luciano. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Hilario Ascasubi; ArgentinaFil: Orden, Luciano. Universidad Miguel Hernández. Centro de Investigación e Innovación Agroalimentaria y Agroambiental. GIAAMA Reseach Group; EspañaFil: Berger, Katja. University of Valencia. Image Processing Laboratory (IPL); EspañaFil: Berger, Katja. Mantle Labs GmbH; AustriaFil: Verrelst, Jochem. University of Valencia. Image Processing Laboratory (IPL); EspañaFil: Delegido, Jesús. Universidad de Valencia. Image Processing Laboratory (IPL); Españ