Load Balancing a Cluster of Web Servers using Distributed Packet Rewriting

In this paper, we propose and evaluate an implementation of a prototype scalable web server. The prototype consists of a load-balanced cluster of hosts that collectively accept and service TCP connections. The host IP addresses are advertised using the Round Robin DNS technique, allowing any host to receive requests from any client. Once a client attempts to establish a TCP connection with one of the hosts, a decision is made as to whether or not the connection should be redirected to a different host---namely, the host with the lowest number of established connections. We use the low-overhead Distributed Packet Rewriting (DPR) technique to redirect TCP connections. In our prototype, each host keeps information about connections in hash tables and linked lists. Every time a packet arrives, it is examined to see if it has to be redirected or not. Load information is maintained using periodic broadcasts amongst the cluster hosts.National Science Foundation (CCR-9706685); Microsof

Propuesta preliminar de ordenamiento territorial para el tratamiento de la margen del Río Salado, partido de Roque Pérez

La asistencia técnica del LINTA al Municipio de Roque Pérez se orienta al desarrollo de una Propuesta Preliminar de Ordenamiento Territorial para el tratamiento y equipamiento de la margen del río Salado -en la extensión correspondiente al tramo ubicado entre la Ruta Nacional 205 y las vías del ferrocarril- en el marco de las Obras Complementarias de dragado y ampliación del río. El objeto de la asistencia es generar un insumo básico para la elaboración de un Plan Particularizado y la readecuación normativa para el sector. El plan de actividades tiene como propósito articular instrumentos de planificación (diagnóstico, intervención y gestión) que se desarrollan en etapas con plazos diferentes; en este sentido, un Plan Particularizado para el sector en línea con la readecuación del Plan de Ordenamiento Territorial implica etapas de mediano y largo plazo que esta propuesta no incorpora, aunque promueve su abordaje en etapas posteriores a definir. En esta instancia, de etapa inicial se define como alcance del plan de trabajo la propuesta preliminar de lineamientos para el ordenamiento territorial del sector, que incluye dos productos: i) formulación de directrices para el ordenamiento territorial; ii) plano con propuesta de delimitación de áreas para el emplazamiento de equipamientos recreativo y la readecuación de la zonificación de usos del suelo. La misma implica dos abordajes articulados con alcances diferentesConvenio Comisión de Investigaciones Científicas de la provincia de Buenos Aires – Municipalidad de Roque Pére

El proyecto de paisaje y el plan particularizado como instrumentos de gestión territorial en la ribera del Río Salado

Dentro del campo multidisciplinar de actuación en el cual se desenvuelve el Laboratorio de Investigaciones del Territorio y el Ambiente (LINTA-CIC), se comunican las posibilidades de asistencia técnica en materia de planificación territorial municipal. A modo de ejemplo se presenta una propuesta de intervención paisajística y de readecuación de la normativa de usos del suelo y ordenamiento territorial en un municipio del interior de la provincia. El caso de vinculación entre el LINTA y el Municipio de Roque Pérez es representativo de la articulación de un diagnóstico territorial, el desarrollo un proyecto de creación y puesta en valor del espacio público y recreativo, la identificación de instrumentos de intervención, y la asistencia para el fortalecimiento de las capacidades municipales orientadas a conducir los procesos de planificación a nivel local. En el marco de las obras complementarias de dragado del río Salado, esta asistencia técnica tuvo por objetivo desarrollar una propuesta de ordenamiento territorial para el tratamiento y equipamiento de la margen sur, generándose los insumos básicos para la elaboración Plan Particularizado para el sector orientado a redefinir el perfil de crecimiento urbano. A partir de la agenda municipal se creó una mesa técnica y se definió una metodología estructurada en tres etapas. El resultado incluyó la elaboración de lineamientos para el ordenamiento territorial, el proyecto de paisaje con la propuesta de delimitación de áreas para el emplazamiento de equipamientos recreativo, el establecimiento de criterios mínimos para la zonificación de usos del suelo y la evaluación de modelos de gestión para desarrollar el plan.Síntesis de trabajo elaborado en el marco de asistencia técnica, convenio CIC y Municipio de Roque Pére

Generative Fractional Diffusion Models

We generalize the continuous time framework for score-based generative models from an underlying Brownian motion (BM) to an approximation of fractional Brownian motion (FBM). We derive a continuous reparameterization trick and the reverse time model by representing FBM as a stochastic integral over a family of Ornstein-Uhlenbeck processes to define generative fractional diffusion models (GFDM) with driving noise converging to a non-Markovian process of infinite quadratic variation. The Hurst index $H\in(0,1)$ of FBM enables control of the roughness of the distribution transforming path. To the best of our knowledge, this is the first attempt to build a generative model upon a stochastic process with infinite quadratic variation

DiffInfinite: Large Mask-Image Synthesis via Parallel Random Patch Diffusion in Histopathology

We present DiffInfinite, a hierarchical diffusion model that generates arbitrarily large histological images while preserving long-range correlation structural information. Our approach first generates synthetic segmentation masks, subsequently used as conditions for the high-fidelity generative diffusion process. The proposed sampling method can be scaled up to any desired image size while only requiring small patches for fast training. Moreover, it can be parallelized more efficiently than previous large-content generation methods while avoiding tiling artefacts. The training leverages classifier-free guidance to augment a small, sparsely annotated dataset with unlabelled data. Our method alleviates unique challenges in histopathological imaging practice: large-scale information, costly manual annotation, and protective data handling. The biological plausibility of DiffInfinite data is validated in a survey by ten experienced pathologists as well as a downstream segmentation task. Furthermore, the model scores strongly on anti-copying metrics which is beneficial for the protection of patient data

Data Models for Dataset Drift Controls in Machine Learning With Images

Camera images are ubiquitous in machine learning research. They also play a central role in the delivery of important services spanning medicine and environmental surveying. However, the application of machine learning models in these domains has been limited because of robustness concerns. A primary failure mode are performance drops due to differences between the training and deployment data. While there are methods to prospectively validate the robustness of machine learning models to such dataset drifts, existing approaches do not account for explicit models of the primary object of interest: the data. This makes it difficult to create physically faithful drift test cases or to provide specifications of data models that should be avoided when deploying a machine learning model. In this study, we demonstrate how these shortcomings can be overcome by pairing machine learning robustness validation with physical optics. We examine the role raw sensor data and differentiable data models can play in controlling performance risks related to image dataset drift. The findings are distilled into three applications. First, drift synthesis enables the controlled generation of physically faithful drift test cases. The experiments presented here show that the average decrease in model performance is ten to four times less severe than under post-hoc augmentation testing. Second, the gradient connection between task and data models allows for drift forensics that can be used to specify performance-sensitive data models which should be avoided during deployment of a machine learning model. Third, drift adjustment opens up the possibility for processing adjustments in the face of drift. This can lead to speed up and stabilization of classifier training at a margin of up to 20% in validation accuracy. A guide to access the open code and datasets is available at https://github.com/aiaudit-org/raw2logit.Comment: LO and MA contributed equall

Safety of standardised treatments for haematologic malignancies as regards to testicular endocrine function in children and teenagers

Study question: Does standardised treatments used in children and adolescents with haematologic malignancies, including acute lymphoblastic (ALL) or myeloid leukaemia (AML) and non-Hodgkin lymphoma (NHL), affect endocrine function of the developing testes? Summary answer: Therapy of haematologic malignancies do not provoke an overt damage of Sertoli and Leydig cell populations, as revealed by normal levels of anti-Müllerian hormone (AMH) and testosterone, but a mild primary testicular dysfunction may be observed, compensated by moderate gonadotropin elevation, during pubertal development. What is known already: Evidence exists on the deleterious effect that chemotherapy and radiotherapy have on germ cells, and some attention has been given to the effects on Leydig and Sertoli cells of the adult gonads, but information is virtually non-existent on the effects of oncologic treatment on testicular somatic cell components during childhood and adolescence. Study design, size, duration: A retrospective, analytical, observational study included 97 boys with haematological malignancies followed at two tertiary paediatric public hospitals in Buenos Aires, Argentina, between 2002 and 2015. Participants/materials, setting, methods: Clinical records of males aged 1-18 years, referred with the diagnoses of ALL, AML or NHL for the assessment of gonadal function, were eligible. We assessed serum levels of AMH and FSH as biomarkers of Sertoli cell endocrine function and testosterone and LH as biomarkers of Leydig cell function. Main results and the role of chance: All hormone levels were normal in the large majority of patients until early pubertal development. From Tanner stage G3 onwards, while serum AMH and testosterone kept within the normal ranges, gonadotropins reached mildly to moderately elevated values in up to 35.9% of the cases, indicating a compensated Sertoli and/or Leydig cell dysfunction, which generally did not require hormone replacement therapy. Limitations, reasons for caution: Serum inhibin B determination and semen analysis were not available for most patients; therefore, we could not conclude on potential fertility impairment or identify whether primary Sertoli cell dysfunction resulted in secondary depleted spermatogenesis or whether primary germ cell damage impacted Sertoli cell function. Wider implications of the findings: The regimens used in the treatment of boys and adolescents with ALL, AML or NHL in the past two decades seem relatively safe for endocrine testicular function; nonetheless, a mild primary testicular endocrine dysfunction may be observed, usually compensated by slightly elevated gonadotropin secretion by the pituitary in adolescents, and not requiring hormone replacement therapy. No clinically relevant risk factor, such as severity of the disease or treatment protocol, could be identified in association with the compensated endocrine dysfunction. Study funding/competing interest(s): This work was partially funded by grants PIP 11220130100687 of Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) and PICT 2016-0993 of Fondo para la Investigación Científica y Tecnológica (FONCYT), Argentina. R.A.R., R.P.G. and P.B. have received honoraria from CONICET (Argentina) for technology services using the AMH ELISA. L.A.A. is part-time employee of CSL Behring Argentina. The other authors have no conflicts of interest to disclose.Fil: Grinspon, Romina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones Endocrinológicas "Dr. César Bergada". Gobierno de la Ciudad de Buenos Aires. Centro de Investigaciones Endocrinológicas "Dr. César Bergada". Fundación de Endocrinología Infantil. Centro de Investigaciones Endocrinológicas "Dr. César Bergada"; Argentina. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutiérrez"; ArgentinaFil: Arozarena, María. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutiérrez"; ArgentinaFil: Prada, Silvina. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutiérrez"; ArgentinaFil: Bargman, Graciela. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños Pedro Elizalde (ex Casa Cuna); ArgentinaFil: Sanzone, María. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones Endocrinológicas "Dr. César Bergada". Gobierno de la Ciudad de Buenos Aires. Centro de Investigaciones Endocrinológicas "Dr. César Bergada". Fundación de Endocrinología Infantil. Centro de Investigaciones Endocrinológicas "Dr. César Bergada"; Argentina. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutiérrez"; ArgentinaFil: Morales Bazurto, Marjorie. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones Endocrinológicas "Dr. César Bergada". Gobierno de la Ciudad de Buenos Aires. Centro de Investigaciones Endocrinológicas "Dr. César Bergada". Fundación de Endocrinología Infantil. Centro de Investigaciones Endocrinológicas "Dr. César Bergada"; Argentina. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutiérrez"; ArgentinaFil: Gutiérrez, Marcela. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutiérrez"; ArgentinaFil: Bedecarras, Patricia Gladys. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutiérrez"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones Endocrinológicas "Dr. César Bergada". Gobierno de la Ciudad de Buenos Aires. Centro de Investigaciones Endocrinológicas "Dr. César Bergada". Fundación de Endocrinología Infantil. Centro de Investigaciones Endocrinológicas "Dr. César Bergada"; ArgentinaFil: Kannemann, Ana. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños Pedro Elizalde (ex Casa Cuna); ArgentinaFil: Elena, Graciela O.. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños Pedro Elizalde (ex Casa Cuna); ArgentinaFil: Gottlieb, Silvia Elisa. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutiérrez"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones Endocrinológicas "Dr. César Bergada". Gobierno de la Ciudad de Buenos Aires. Centro de Investigaciones Endocrinológicas "Dr. César Bergada". Fundación de Endocrinología Infantil. Centro de Investigaciones Endocrinológicas "Dr. César Bergada"; ArgentinaFil: Berenstein, Ariel José. Gobierno de la Ciudad de Buenos Aires. Instituto Multidisciplinario de Investigaciones en Patologías Pediátricas. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto Multidisciplinario de Investigaciones en Patologías Pediátricas; ArgentinaFil: Ropelato, Maria Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones Endocrinológicas "Dr. César Bergada". Gobierno de la Ciudad de Buenos Aires. Centro de Investigaciones Endocrinológicas "Dr. César Bergada". Fundación de Endocrinología Infantil. Centro de Investigaciones Endocrinológicas "Dr. César Bergada"; Argentina. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutiérrez"; ArgentinaFil: Bergadá, Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones Endocrinológicas "Dr. César Bergada". Gobierno de la Ciudad de Buenos Aires. Centro de Investigaciones Endocrinológicas "Dr. César Bergada". Fundación de Endocrinología Infantil. Centro de Investigaciones Endocrinológicas "Dr. César Bergada"; Argentina. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutiérrez"; ArgentinaFil: Aversa, Luis A.. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutiérrez"; ArgentinaFil: Rey, Rodolfo Alberto. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutiérrez"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones Endocrinológicas "Dr. César Bergada". Gobierno de la Ciudad de Buenos Aires. Centro de Investigaciones Endocrinológicas "Dr. César Bergada". Fundación de Endocrinología Infantil. Centro de Investigaciones Endocrinológicas "Dr. César Bergada"; Argentin

Data models for dataset drift controls in machine learning with optical images

Camera images are ubiquitous in machine learning research. They also play a central role in the delivery of important public services spanning medicine or environmental surveying. However, the application of machine learning models in these domains has been limited because of robustness concerns. A primary failure mode are performance drops due to differences between the training and deployment data. While there are methods to prospectively validate the robustness of machine learning models to such dataset drifts, existing approaches do not account for explicit models of machine learning’s primary object of interest: the data. This limits our ability to study and understand the relationship between data generation and downstream machine learning model performance in a physically accurate manner. In this study, we demonstrate how to overcome this limitation by pairing traditional machine learning with physical optics to obtain explicit and differentiable data models. We demonstrate how such data models can be constructed for image data and used to control downstream machine learning model performance related to dataset drift. The findings are distilled into three applications. First, drift synthesis enables the controlled generation of physically faithful drift test cases to power model selection and targeted generalization. Second, the gradient connection between machine learning task model and data model allows advanced, precise tolerancing of task model sensitivity to changes in the data generation. These drift forensics can be used to precisely specify the acceptable data environments in which a task model may be run. Third, drift optimization opens up the possibility to create drifts that can help the task model learn better faster, effectively optimizing the data generating process itself to support the downstream machine vision task. This is an interesting upgrade to existing imaging pipelines which traditionally have been optimized to be consumed by human users but not machine learning models. The data models require access to raw sensor images as commonly processed at scale in industry domains such as microscopy, biomedicine, autonomous vehicles or remote sensing. Alongside the data model code we release two datasets to the public that we collected as part of this work. In total, the two datasets, Raw-Microscopy and Raw-Drone, comprise 1,488 scientifically calibrated reference raw sensor measurements, 8,928 raw intensity variations as well as 17,856 images processed through twelve data models with different configurations. A guide to access the open code and datasets is available at https://github.com/aiaudit-org/raw2logit