Synovial cysts of the temporomandibular joint: an immunohistochemical characterization and literature review.

Synovial cysts of the temporomandibular joint (TMJ) are very rare, and to date, only 12 cases of a synovial cyst in the TMJ region have been reported in the literature. In this paper, we present the clinicopathological and immunohistochemical characteristics of one such lesion affecting a 48-year-old woman, presented with a mass in the left preauricular region.We describe the usefulness of immunohistochemical analysis for recognizing the synovial lining, which allowed for clear differentiation between ganglion and synovial cysts. Immunohistochemical analyses can be used to diagnose synovial cysts with certainty; however, using at least two markers is advisable to distinguish the two existing synovial cell subtypes. Our findings indicate that synovial cysts of TMJ possess an internal lining dominated by type B (fibroblast-like) synoviocytes

Measuring and Querying Process Performance in Supply Chains: An Approach for Mining Big-Data Cloud Storages

AbstractSurvival in today's global environment means continuously improving processes, identifying and eliminating inefficiencies wherever they occur. With so many companies operating as part or all of complex distributed supply chain, gathering, collating and analyzing the necessary data to identify such improvement opportunities is extremely complex and costly. Although few solutions exist to correlate the data, it continues to be generated in vast quantities, rendering the use of highly scalable, cloud-based solutions for process analysis a necessity. In this paper we present an overview of an analytical framework for business activity monitoring and analysis, which has been realized using extremely scalable, cloud-based technologies. It provides a low-latency solution for entire supply chains or individual nodes in such chains to query process data stores in order to deliver business insight. A custom query language has been implemented which allows business analysts to design custom queries on processes and activities based on a standard set of process metrics. Ongoing developments are focused on testing and improving the scalability and latency of the system, as well as extending the query engine to increase its flexibility and performance

Business process improvement by means of Big Data based Decision Support Systems: a case study on Call Centers

Big Data is a rapidly evolving and maturing field which places significant data storage and processing power at our disposal. To take advantage of this power, we need to create new means of collecting and processing large volumes of data at high speed. Meanwhile, as companies and organizations, such as health services, realize the importance and value of joined-up thinking across supply chains and healthcare pathways, for example, this creates a demand for a new type of approach to Business Activity Monitoring and Management. This new approach requires Big Data solutions to cope with the volume and speed of transactions across global supply chains. In this paper we describe a methodology and framework to leverage Big Data and Analytics to deliver a Decision Support framework to support Business Process Improvement, using near real-time process analytics in a decision-support environment. The system supports the capture and analysis of hierarchical process data, allowing analysis to take place at different organizational and process levels. Individual business units can perform their own process monitoring. An event-correlation mechanism is built into the system, allowing the monitoring of individual process instances or paths

A Big-Data based and process-oriented decision support system for traffic management

Data analysis and monitoring of road networks in terms of reliability and performance are valuable but hard to achieve, especially when the analytical information has to be available to decision makers on time. The gathering and analysis of the observable facts can be used to infer knowledge about traffic congestion over time and gain insights into the roads safety. However, the continuous monitoring of live traffic information produces a vast amount of data that makes it difficult for business intelligence (BI) tools to generate metrics and key performance indicators (KPI) in nearly real-time. In order to overcome these limitations, we propose the application of a big-data based and process-centric approach that integrates with operational traffic information systems to give insights into the road network's efficiency. This paper demonstrates how the adoption of an existent process-oriented DSS solution with big-data support can be leveraged to monitor and analyse live traffic data on an acceptable response time basis.publishedVersio

Habilidades da teoria da mente e compreensão de verbos metacognitivos em crianças com desenvolvimento normativo

El aprendizaje de habilidades de la teoría de la mente (ToM) se considera fundamental para garantizar un buen desempeño adaptativo en el contexto social dado que permite a las personas atribuir estados mentales a sí mismas y a otras, y así poder predecir el comportamiento de los demás. El objetivo del presente estudio consistió en analizar el desempeño en las tareas de ToM y en la comprensión de verbos mentalistas contextualizados en historias en niños con desarrollo normativo. Se utilizó una muestra de 41 niños con edades comprendidas entre 3 y 5 años con una metodología descriptiva. Los resultados muestran que el nivel 3 de ToM fue el que obtuvo menores niveles de logro. En relación con la prueba que evaluaba la comprensión de verbos mentalistas, los resultados más bajos se obtuvieron en aquella que hacía referencia al verbo saber. Los resultados encontrados sugieren que se aprenden primero verbos mentales referidos a deseos antes que a creencias, así como que los niveles de información defendidos por el modelo de ToM de Howlin et al. (1999) no parecerían estar secuenciados en niveles de complejidad.Agencia Nacional de Investigación e Innovació

Use of twitter data for waste minimisation in beef supply chain

Approximately one third of the food produced is discarded or lost, which accounts for 1.3 billion tons per annum. The waste is being generated throughout the supply chain viz. farmers, wholesalers/processors, logistics, retailers and consumers. The majority of waste occurs at the interface of retailers and consumers. Many global retailers are making efforts to extract intelligence from customer’s complaints left at retail store to backtrack their supply chain to mitigate the waste. However, majority of the customers don’t leave the complaints in the store because of various reasons like inconvenience, lack of time, distance, ignorance etc. In current digital world, consumers are active on social media and express their sentiments, thoughts, and opinions about a particular product freely. For example, on an average, 45,000 tweets are tweeted daily related to beef products to express their likes and dislikes. These tweets are large in volume, scattered and unstructured in nature. In this study, twitter data is utilised to develop waste minimization strategies by backtracking the supply chain. The execution process of proposed framework is demonstrated for beef supply chain. The proposed model is generic enough and can be applied to other domains as well

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

Procesos de aplicación conceptual y práctico de la normatividad tributaria en contextos investigativos procedimentales tributarios para el fortalecimiento de las competencias disciplinares y profesionales

La presente investigación planteó como objetivo realizar las memorias con las temáticas investigativas que se desarrollaron en el Seminario de Investigación Aplicada, con el fin de actualizar en los participantes y fortalecer sus conocimientos específicos en materia tributaria con base en los temas investigativos dispuestos y orientados por cada docente desde su inicio, elaboración, construcción y presentación ante los docentes evaluadores. Los trabajos cumplen su fin primordial con es fortalecer con los desarrollos temático de cada módulo visto en el SIA sus capacidades y competencias profesionales especialmente en el contexto tributario, en cumplimiento al requerimiento para otorgar al título de Especialistas en Gerencia Tributaria. Luego las memorias compiladas son el resultado de los trabajos presentados y evaluados oportunamente por cada docente comprometido con la calidad en cuanto a las temáticas investigativas, calidad de los contenidos, talleres teóricos prácticos, elementos metodológicos y de más lineamentos institucionales y del programa. La importancia de las memorias radica en su contenido el cual desglosa definiciones, conceptos, desarrollos teóricos prácticos, constituyéndose en un ejemplar de consulta investigativa en áreas de conocimiento fiscal y tributario en el marco de la Ley 1819 de 2016 y sus decretos reglamentarios, en síntesis al interior encontraremos fundamentos teóricos prácticos, procedimentales y resolutivos de casos especiales de Gravamen a los Movimientos Financieros, Monotributo, Renta Personas Naturales, Renta Personas Jurídicas, Procedimiento Tributario, Impuestos Distritales, Normas internacionales de Información Financiera Pymes, entre otros temas