A Machine Learning Approach for Prediction of Hospital Bed Availability

Las camas de internación constituyen un recurso escaso en las instituciones hospitalarias, los datos, en cambio, no. En el presente trabajo se argumenta que, haciendo uso de técnicas de aprendizaje automático, puede sacarse provecho del enorme volumen de data disponible en los sistemas de información de hospitales y sanatorios para construir soluciones de analytics que potencien la eficiente utilización de las camas de internación mediante la mejora del proceso de toma de decisiones. Con el objetivo de poner a prueba esta hipótesis, se trabajó en conjunto con una de las instituciones hospitalarias más importantes de la ciudad de Buenos Aires. El foco del trabajo estuvo puesto en la construcción de un modelo de aprendizaje automático que pudiera predecir la probabilidad de que un paciente sea dado de alta en las próximas veinticuatro horas, en función de su historia clínica, datos demográficos y algunos otros factorales ambientales. Para lograrlo se aplicaron técnicas de ingeniería de datos y aprendizaje supervisado, en el contexto de un problema de clasificación. Se experimentó con diferentes algoritmos así como formas de abordar la representación de atributos para sacar el máximo provecho de la data disponible. Como resultado, se obtuvo un modelo con un rendimiento prometedor que alcanza un puntaje de 0.84 de área bajo la curva ROC y ha demostrado generalizar muy bien en datos desconocidos. Dicho modelo fue la base sobre la cual se montó una herramienta de pronóstico de altas. Esta solución permite obtener tres predicciones, con diferentes niveles de incertidumbre asociada, de las altas esperadas en el Sanatorio para la fecha especificada. Los "niveles de confianza" reportados fueron obtenidos mediante un ejercicio de simulación sobre la data histórica que permitió comparar el pronóstico de la herramienta con el escenario observado en la realidad. El equipo de gestión de operaciones del hospital en cuestión ha hecho explícito su interés en la solución propuesta, ya que evalúan que el modelo tiene un enorme potencial para facilitar el proceso de planificación de camas y, de esta manera, ayudar a mejorar la eficiencia operacional del sanatorio.Hospital beds are a scarce resource for healthcare facilities, data is not. In this thesis, we argue that machine learning techniques could take advantage of the abundant amount of data available at hospitals information systems inorder to build analytics solutions that could propel the efficiet utilization of beds by improving the management decission making process. In order to test this hypothesis we have worked together with one of the most relevant medical institutions in Buenos Aires. The focus of our work has been placed in building a machine learning model that could predict the probability of a certain patient being discharged during the following twenty four hours, based on his medical records as well as his demographic data and some environmental factors. To this aim, data engineering and supervised learning techniques have been applied in the context of a classification task. We have experimented with different algorithms as well as feature representation approaches to make the most out of the data at hand. As a result, a model with a promising performance of 0.84 AUC-ROC score was obtained, and its results have demonstrated to generalize quite well on unseen data. This model was the base on top of which a discharges forecaster tool was developed. This solution is able to return three different predictions of the hospital discharges for a specified date with different "confidence levels" associated, thus providing management with a risk-informed prediction of hospital beds availaibility. The "confidence" reported for each of the forecasts was obtained using a simulation approach for historic data where we were able to contrast the forecast output with the actual scenario. The hospital management team has made explicit its interest in the solution, as they assess it has an enourmous potential for facilitating the bed planning process and by doing so improving the hospital operational efficiency

Determinants of Conflict Minerals Disclosure

This paper examines conflict minerals disclosure (CMD) as mandated by the Dodd–Frank Act. We rely on a thorough content analysis conducted by the Responsible Sourcing Network on a sample of 122 firms that filed CMDs with the US Securities and Exchange Commission in 2015. We document that firms with long‐term oriented incentives, a greater number of board meetings, strong corporate governance systems and inclusion in a sustainability index are associated with higher levels of CMD. Our results suggest that in the presence of enforcement leniency, both internal and external firm‐specific factors affect strategic (non‐)compliance with a mandatory social disclosure regime. We provide implications for supply chain managers, corporate reporters and policy‐makers involved in the adoption of responsible sourcing strategies. © 2018 The Authors. Business Strategy and The Environment published by ERP Environment and John Wiley & Sons Lt

Temporal shifts of Bois Noir phytoplasma types infecting grapevine in South Tyrol (Northern Italy)

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Targeting kinases with anilinopyrimidines: Discovery of N-phenyl-N'-[4-(pyrimidin-4-ylamino)phenyl]urea derivatives as selective inhibitors of class III receptor tyrosine kinase subfamily

Kinase inhibitors are attractive drugs/drug candidates for the treatment of cancer. The most recent literature has highlighted the importance of multi target kinase inhibitors, although a correct balance between specificity and non-specificity is required. In this view, the discovery of multityrosine kinase inhibitors with subfamily selectivity is a challenging goal. Herein we present the synthesis and the preliminary kinase profiling of a set of novel 4-anilinopyrimidines. Among the synthesized compounds, the N-phenyl-N\u2019-[4-(pyrimidin-4-ylamino)phenyl]urea derivatives selectively targeted some members of class III receptor tyrosine kinase family. Starting from the structure of hit compound 19 we synthesized a further compound with an improved affinity toward the class III receptor tyrosine kinase members and endowed with a promising antitumor activity both in vitro and in vivo in a murine solid tumor model. Molecular modeling simulations were used in order to rationalize the behavior of the title compounds

Infection rates of natural psyllid populations with ‘Candidatus Phytoplasma mali’ in South Tyrol (Northern Italy)

Apple proliferation is a severe disease of apple trees spreading in many European apple growing areas. It is caused by ‘Candidatus Phytoplasma mali’ that was shown to be transmitted through infected grafting material, via natural root grafts and by sap-sucking insects. Two psyllid species, Cacopsylla picta and C. melanoneura, that are recognised as the vectors of the disease, occur in orchards of South Tyrol (Northern Italy). The aim of this study was to assess the infection rates of natural populations of these insect species with ‘Ca. P. mali’. Two additional psyllid species (C. mali and Trioza urticae), which are frequent in some apple orchards of South Tyrol, were also investigated. A total of 801 specimens from 18 orchards was analysed using a real-time PCR procedure. While no specimen of T. urticae was found to be infected with ‘Ca. P. mali’, the mean infection rate of C. melanoneura and C. mali was below 1 %. The highest infection rate was found for C. picta, with a mean value of 11 % and peaking at 33%. Based on these results, it can be concluded that C. picta plays the major role as the vector of apple proliferation in South Tyrol. Keywords: apple proliferation, Cacopsylla mali, Cacopsylla melanoneura, Cacopsylla picta, pathogen transmission, Trioza urtica

Energy absorption capability of nanomodified glass/epoxy laminates

Abstract The impact response of standard and clay-modified vacuum-infused glass/epoxy laminates was investigated. The activity was oriented to evaluate the enhancements in the energy absorption capability of the laminates due to the nanomodification. Nanomodification was achieved by using Cloisite 30B nanoclays by Southern Clay. Low velocity impact tests were carried out on flat samples of about 4 mm thicknessby a drop-weight tower. The results clearly indicate that the nanomodified laminates have a greater capability to absorb the impact energy (with up to 30% increases in dissipated energy) with respect to the standard laminates, also in combination with a decrease of the peak impact force (from 10 to 15%). In some ways, this behaviour can be partly justified by the larger damage exhibited by nanomodified laminates, with projected damage areas more than double the damage areas of standard panels, for the same impact energy

On the Dynamics of a Heavy Symmetric Ball that Rolls Without Sliding on a Uniformly Rotating Surface of Revolution

We study the class of nonholonomic mechanical systems formed by a heavy symmetric ball that rolls without sliding on a surface of revolution, which is either at rest or rotates about its (vertical) figure axis with uniform angular velocity Omega. The first studies of these systems go back over a century, but a comprehensive understanding of their dynamics is still missing. The system has an SO(3) x SO(2) symmetry and reduces to four dimensions. We extend in various directions, particularly from the case Omega = 0 to the case Omega not equal 0, a number of previous results and give new results. In particular, we prove that the reduced system is Hamiltonizable even if Omega not equal 0 and, exploiting the recently introduced "moving energy," we give sufficient conditions on the profile of the surface that ensure the periodicity of the reduced dynamics and hence the quasiperiodicity of the unreduced dynamics on tori of dimension up to three. Furthermore, we determine all the equilibria of the reduced system, which are classified in three distinct families, and determine their stability properties. In addition to this, we give a new form of the equations of motion of nonholonomic systems in quasi-velocities which, at variance from the well-known Hamel equations, use any set of quasi-velocities and explicitly contain the reaction forces

Resolving vertical and east-west horizontal motion from differential interferometric synthetic aperture radar : The L'Aquila earthquake

Analysis of surface coseismic displacement has already been obtained for the 6 April 2009 L'Aquila (central Italy) earthquake from differential interferometric synthetic aperture radar (DInSAR) data. Working jointly on ascending and descending DInSAR data makes for a step forward with respect to published preliminary estimates: we process data in order to retrieve a continuous displacement pattern, both in the vertical and horizontal directions, the latter being limited to the eastward component because of the low sensibility of the SAR images used to resolve northward motion. Our analysis provides new insights on the horizontal component of displacement, obtaining a clear picture of eastward displacement patterns over the epicentral area. This result is noteworthy, as until now little information has been available on horizontal displacement following normal-fault events in the central Apennines (Umbria-Marche, 1997, and L'Aquila, 2009), given the lack of dense GPS networks, the only available source of horizontal displacement data in this area. Inverted fault characteristics from such data also show noteworthy differences compared to previous studies, localizing the Paganica fault as the causative fault for the earthquake

Comparative Molecular Genetic Analysis of Apple Genotypes Maintained in Germplasm Collections

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Development of multifunctional anticancer agents: design, synthesis and evaluation of hybrid compounds containing kinase inhibitor moieties

Cancer is a complex and a multiple-genes involved disease; for this reason it can not be treated or cured with a single drug modulating the biological function of a single target. The innovation related to multi-targeted drugs, combining the activity of different cancer progression relevant targets, became a burgeoning research topic. Drugs that act on multiple targets can enhance efficacy and reduce chemo-resistance that causes disease relapse and metastasis and remains the main obstacle to cancer therapy. One of the main target nowadays are tyrosine kinases (TKs); since most protein kinases stimulate cell growth and proliferation, cell survival and migration, they can, if overexpressed, amplified or constitutively active, assume oncogenic properties. Other ideal biological targets are enzymes as histone deacetylases (HDAC) and mitochondrial functions. Herein we present the development and the preliminary evaluation of new Abl/HDAC inhibitors bearing the pyrido-pyrimidine main scaffold; the functionalization of the most active compounds with metal ions (i.e. Zn2+, Cu2+ and Fe3+); the development of novel multi-kinase inhibitors bearing the 4-anilinopyrimidine scaffold; the development of novel cKIT/wtRET/V804MRET inhibitors bearing the 4-anilinopyridine scaffold. Besides, the development of multi-kinase inhibitors endowed with antifibrotic properties as well as novel topoisomerase inhibitors are reported