Crossed spin-1/2 Heisenberg chains as a quantum impurity problem

Using equivalencies between different models we reduce the model of two spin-1/2 Heisenberg chains crossed at one point to the model of free fermions. The spin-spin correlation function is calculated by summing the perturbation series in the interchain coupling. The result reveals a power law decay with a nonuniversal exponent.Comment: 3 pages, the background information is adde

Correlation functions for the Z-invariant Ising model

The correlation functions of the Z-invariant Ising model are calculated explicitly using the Vertex Operators language developed by the Kyoto school.Comment: Latex Document, minor change and new Reference adde

Soil properties zoning of agricultural fields based on a climate-driven spatial clustering of remote sensing time series data

The identification of zones within an agricultural field that respond differently to environmental factors and agronomic management is a key requirement for the adoption of more precise and sustainable agricultural practices. Several approaches based on spatial clustering methods applied to different data sources, e.g. yield maps, proximal sensors and soil surveys, have been proposed in the last decades. The current availability of a huge amount of free remote sensing data allows to apply these approaches to agricultural areas where ground or proximal data are not available. However, in order to provide useful agronomic management information, it is essential that the zoning obtained by clustering is linked to the underlying spatial variability of soil properties. In this work we explore the hypothesis that the response of crop vigor to temporal climate variability, assessed by remote sensing data time series, selected to correspond to specific growth phases and seasonal climate patterns, provides indications on the variability of soil properties within agricultural fields, for both herbaceous and tree crops. NDVI time-series for 38 years (1984–2021) were obtained for fourteen non-irrigated herbaceous and tree crop fields in Central Italy, from multispectral satellites data (Landsat 5/7/8, Sentinel 2). The Standardized Precipitation-Evapotranspiration Index (SPEI) was used to classify time series into three climatic classes (dry/ normal/wet) for five different periods of the growth season, covering the main phenological phases. K-means clustering was used to identify patterns of crop growth from climatically classified image sets, as well as for all the bulked images for comparison (bulk clustering). Clustering results were compared with soil maps obtained from spatialized ground data, for soil texture (clay, silt and sand), soil organic matter and available soil water (ASW). The agreement between the different clustering results and soil maps was assessed by the Adjusted Rand Index. Agreement with soil maps varied depending on the field, the phenological phase considered and the soil property considered. Climate driven clustering from long, late growth season periods best matched soil properties, both for herbaceous and tree crops, despite being based on a limited number of images. The clustering from images spanning a longer growth period for dry years systematically outpaced the bulk clustering for silt, sand and ASW, while the clustering for normal climatic conditions was the best for organic matter. The performance of the matching between clustering and soil maps increased with soil variability significantly more (P < 0.05) than in the bulk clustering (mean slopes respectively 0.468 ± 0.167; 0.113 ± 0.270). The integration of the SPEI climatic index into the clustering procedure systematically improved the identification of zones with homogeneous soil properties, highlighting that a greater attention should be posed to the climate-crop-field interactions when using remotely sensed image

Managing digital transformation: The view from the top

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Managing digital transformation: The view from the top

Digital Transformation is upending businesses everywhere. While there is ample research on this topic, there is a clear gap when it comes to understanding the changing talent management role of senior executives in digital transformation processes and the demands of individual employees. This article relies on 23 in-depth interviews with senior managers who are leading all or some of the digital transformation efforts of their respective organizations. Our research, using a grounded theory approach, identifies four key activities (and 37 sub-activities or themes) stemming from the new managerial needs and talent management practices arising from DT processes. We branded these key activities “Drive business change”, “Master fluid & loose organizational structures”, “Master Talent Complexity”, and “Prioritize learning”. This paper aims to provide an overview into the thinking and managerial practices of senior executives in a digital transformation context and complements the limited number of studies that examine the intersection between managerial actions and digital transformation. It also provides a conceptual framework that captures the key managerial demands arising from digital transformation processes and identifies key actions made by senior executives as part of these processes, which can be leveraged by both scholars and practitioners alike

Transgenic‐based solutions for citrus disease management in Argentina

Citrus is a major fruit crop with economic importance worldwide, with citriculture historically threatened at times by a diverse array of pathogens. As a leading producer and exporter, Argentina has been dealing with endemic and quarantine diseases of citrus by implementing conventional management strategies. In recent decades, the pursuit of pathogen-resistant transgenic citrus has been explored in the country as part of a long-term and sustainable disease management strategy. Successful genetically modified organisms (GMOs) were created locally, engineered to resist viruses and bacteria for the control of tristeza, psorosis, canker, and huanglongbing diseases of citrus. Although the Argentine regulatory system accommodated these developments, there were also difficulties that demand further recognition and analysis. In the present work, we describe four major diseases affecting Argentine citriculture and a series of GMO-oriented strategies for their management. We explore the methodologies behind these strategies, including transgenic-based approaches, the current state of regulations, and what further actions may be taken to ensure continuing protection for citriculture.Fil: de Francesco, Agustina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Biotecnología y Biología Molecular. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Biotecnología y Biología Molecular; ArgentinaFil: Sendín, Lorena Noelia. Instituto Nacional de Tecnología Agropecuaria; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Gómez, Rocio Liliana. Instituto Nacional de Tecnología Agropecuaria; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Reyes Martinez, Carina Andrea. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Biotecnología y Biología Molecular. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Biotecnología y Biología Molecular; Argentin

Malaria early warnings based on seasonal climate forecasts from multi-model ensembles

The control of epidemic malaria is a priority for the international health community and specific targets for the early detection and effective control of epidemics have been agreed. Interannual climate variability is an important determinant of epidemics in parts of Africa where climate drives both mosquito vector dynamics and parasite development rates. Hence, skilful seasonal climate forecasts may provide early warning of changes of risk in epidemic-prone regions. Here we discuss the development of a system to forecast probabilities of anomalously high and low malaria incidence with dynamically based, seasonal-timescale, multi-model ensemble predictions of climate, using leading global coupled ocean–atmosphere climate models developed in Europe. This forecast system is successfully applied to the prediction of malaria risk in Botswana, where links between malaria and climate variability are well established, adding up to four months lead time over malaria warnings issued with observed precipitation and having a comparably high level of probabilistic prediction skill. In years in which the forecast probability distribution is different from that of climatology, malaria decision-makers can use this information for improved resource allocation

The STRIP instrument of the Large Scale Polarization Explorer: microwave eyes to map the Galactic polarized foregrounds

In this paper we discuss the latest developments of the STRIP instrument of the "Large Scale Polarization Explorer" (LSPE) experiment. LSPE is a novel project that combines ground-based (STRIP) and balloon-borne (SWIPE) polarization measurements of the microwave sky on large angular scales to attempt a detection of the "B-modes" of the Cosmic Microwave Background polarization. STRIP will observe approximately 25% of the Northern sky from the "Observatorio del Teide" in Tenerife, using an array of forty-nine coherent polarimeters at 43 GHz, coupled to a 1.5 m fully rotating crossed-Dragone telescope. A second frequency channel with six-elements at 95 GHz will be exploited as an atmospheric monitor. At present, most of the hardware of the STRIP instrument has been developed and tested at sub-system level. System-level characterization, starting in July 2018, will lead STRIP to be shipped and installed at the observation site within the end of the year. The on-site verification and calibration of the whole instrument will prepare STRIP for a 2-years campaign for the observation of the CMB polarization.Comment: 17 pages, 15 figures, proceedings of the SPIE Astronomical Telescopes + Instrumentation conference "Millimeter, Submillimeter, and Far-Infrared Detectors and Instrumentation for Astronomy IX", on June 15th, 2018, Austin (TX