Design of pixel-level ADCs for energy-sensitive hybrid pixel detectors

Single-photon counting hybrid pixel detectors have shown\ud to be a valid alternative to other types of X-ray imaging\ud devices due to their high sensitivity, low noise, linear behavior\ud and wide dynamic range. One important advantage of these\ud devices is the fact that detector and readout electronics are\ud manufactured separately. This allows the use of industrial\ud state-of-the-art CMOS processes to make the readout\ud electronics, combined with a free choice of detector material\ud (high resistivity Silicon, GaAs or other). By measuring not\ud only the number of X-ray photons but also their energies (or\ud wavelengths), the information content of the image increases,\ud given the same X-ray dose. We have studied several\ud possibilities of adding energy sensitivity to the single photon\ud counting capability of hybrid pixel detectors, by means of\ud pixel-level analog-to-digital converters. We show the results of\ud simulating different kinds of analog-to-digital converters in\ud terms of power, area and speed

Implantation of 3D-Printed Patient-Specific Aneurysm Models into Cadaveric Specimens: A New Training Paradigm to Allow for Improvements in Cerebrovascular Surgery and Research.

AimTo evaluate the feasibility of implanting 3D-printed brain aneurysm model in human cadavers and to assess their utility in neurosurgical research, complex case management/planning, and operative training.MethodsTwo 3D-printed aneurysm models, basilar apex and middle cerebral artery, were generated and implanted in four cadaveric specimens. The aneurysms were implanted at the same anatomical region as the modeled patient. Pterional and orbitozygomatic approaches were done on each specimen. The aneurysm implant, manipulation capabilities, and surgical clipping were evaluated.ResultsThe 3D aneurysm models were successfully implanted to the cadaveric specimens' arterial circulation in all cases. The features of the neck in terms of flexibility and its relationship with other arterial branches allowed for the practice of surgical maneuvering characteristic to aneurysm clipping. Furthermore, the relationship of the aneurysm dome with the surrounding structures allowed for better understanding of the aneurysmal local mass effect. Noticeably, all of these observations were done in a realistic environment provided by our customized embalming model for neurosurgical simulation.Conclusion3D aneurysms models implanted in cadaveric specimens may represent an untapped training method for replicating clip technique; for practicing certain approaches to aneurysms specific to a particular patient; and for improving neurosurgical research

Estudio de utilización de antivirales de acción directa en el tratamiento de la hepatitis

Objetivos: El objetivo es analizar el tratamiento con los nuevos antivirales de acción directa frente al virus de la hepatitis C en un hospital general de nivel medio. Metodología: Estudio observacional, descriptivo, retrospectivo en el que se incluyeron pacientes diagnosticados con Hepatitis C crónica que iniciaron tratamiento con antivirales de acción directa en el periodo comprendido entre el 1 de abril y el 31 de octubre de 2015. Se recogieron variables clínicas, tratamientos y se comprobaron posibles interacciones con la medicación habitual, trabajándo posteriormente con los datos obtenidos en Excel. Resultados y discusión: E 26% de los 131 pacientes presentaba coinfección con VIH. El genotipo predominante fue el 1 (74,04%), seguido por genotipo 3 (12,21%). El 67,93% presentaban fibrosis F4 y 19,84% F3, siendo el grupo prioritario de tratamiento un 87,77%. El 6,87% F2 con manifestaciones extrahepáticas y un 5,36% F0-F1, personal sanitario o mujeres con deseo de embarazo. Un 56,48% eran pacientes Naïve, 32,06% Biterapia, 8,40% Triterapia y 3,06% IFN. En un 74,8% de pacientes se eligió la primera opción de tratamiento, siendo por interacciones con el tratamiento concomitante del paciente el principal motivo de no elección ( 58% de los casos), afectando principalmente a la combinación Ombitasvir/ Paritaprevir/ Ritonavir más Dasabuvir (74,04%), provocadas por el tratamiento antrirretroviral en un 36% de los casos. Un 64,88% de pacientes recibieron tratamiento durante 12 semanas, un 32,83% durante 24 semanas y un 2,29% durante 8 semanas. No se notificaron abandonos ni reacciones adversas, habiendo concluido el tratamiento un 64,88% de pacientes. Conclusiones: El genotipo 1 es el principal causante de infección (74,04%), siendo el genotipo 3 la segunda causa. Un 74,8% de pacientes recibió la primera opción de tratamiento, eligiéndose otras opciones por interacciones con la medicación habitual del paciente en la mayoría de los casos (58%), con la terapia antirretroviral (36%), por lo que este grupo debe continuar siendo especialmente vigilado

Municipal awareness as a tool for enhancing citizen satisfaction in municipal councils of Malaysia

This research study critically analysed the existing literatures on municipal awareness relevancy of LAs service delivery for the purpose of enhancing citizen satisfaction. The purpose of the study is the investigation of citizen satisfaction level of municipal services; analysis of the existing literatures on relationship between municipal awareness and citizen satisfaction. The Material and methods were carried out using secondary data and were meticulously and critically analysed to come up with reliable results. The study shows the relevancy of the public awareness, citizen satisfaction and municipal council performance in Malaysia. It is evidence in the research that citizen consent is importance before municipal services should be provided in the local community. The research study highlighted many discrepancies in many literatures related to the existing research study, evidence based analysis were carried out to buttress importance and significance of the related study to the research work. The literatures were reviewed to ascertain the current happening in the area of local government service delivery. The study shows that many municipal councils in Malaysia provide adequate and satisfactory services to their citizens’. The study also revealed that municipal council plays important role on citizen awareness of municipal service delivery. The study concludes that municipal service delivery can be enhanced through citizen awareness campaign, to sensitize the local community on various aspects of service delivery including maintenance of the facilities provided. The study also concludes that LAs lack of awareness section affects their performance in service delivery process. The study recommends that LAs need to consults the citizen for their needs and wants; awareness campaign need to be regularly carried out to maintain cordial relationship between LAs and their citizen; it is also recommended that municipal services should be delivered the needed services by the local inhabitants’ after duly consultatio

Acquisition of business intelligence from human experience in route planning

This is an Accepted Manuscript of an article published by Taylor & Francis Group in Enterprise Information Systems on 2015, available online at:http://www.tandfonline.com/10.1080/17517575.2012.759279The logistic sector raises a number of highly challenging problems. Probably one of the most important ones is the shipping planning, i.e., plan the routes that the shippers have to follow to deliver the goods. In this paper we present an AI-based solution that has been designed to help a logistic company to improve its routes planning process. In order to achieve this goal, the solution uses the knowledge acquired by the company drivers to propose optimized routes. Hence, the proposed solution gathers the experience of the drivers, processes it and optimizes the delivery process. The solution uses Data Mining to extract knowledge from the company information systems and prepares it for analysis with a Case-Based Reasoning (CBR) algorithm. The CBR obtains critical business intelligence knowledge from the drivers experience that is needed by the planner. The design of the routes is done by a Genetic Algorithm (GA) that, given the processed information, optimizes the routes following several objectives, such as minimize the distance or time. Experimentation shows that the proposed approach is able to find routes that improve, in average, the routes made by the human experts.This work has been partially supported by the SpanishMinistry of Science and Innovation under the projects ABANT (TIN 2010-19872) and by Jobssy.com company under Project FUAM-076913

Changes in co-existence mechanisms along a long-term soil chronosequence revealed by functional trait diversity

1. Functional trait diversity can reveal mechanisms of species co-existence in plant communities. Few studies have tested whether functional diversity for foliar traits related to resource use strategy increases or decreases with declining soil phosphorus (P) in forest communities. 2. We quantified tree basal area and four foliar functional traits (i.e. nitrogen (N), phosphorus (P), thickness and tissue density) for all woody species along the c. 120 kyr Franz Josef soil chronosequence in cool temperate rainforest, where strong shifts occur in light and soil nutrient availability (i.e. total soil P declines from 805 to 100 mg g–1). We combined the abundance and trait data in functional diversity indices to quantify trait convergence and divergence, in an effort to determine whether mechanisms of co-existence change with soil fertility. 3. Relationships between species trait means and total soil N and P were examined using multiple regression, with and without weighting of species abundances. We used Rao’s quadratic entropy to quantify functional diversity at the plot scale, then compared this with random expectation, using a null model that randomizes abundances across species within plots. Taxonomic diversity was measured using Simpson’s Diversity. Relationships between functional and taxonomic diversity and total soil P were examined using jackknife linear regression. 4. Leaf N and P declined and leaf thickness and density increased monotonically with declining total soil P along the sequence; these relationships were unaffected by abundance-weighting of species in the analyses. Inclusion of total soil N did not improve predictions of trait means. All measures of diversity calculated from presence/absence data were unrelated to total soil N and P. There was no evidence for a relationship between Rao values using quantitative abundances and total soil P. However, there was a strongly positive relationship between Rao, expressed relative to random expectation, and total soil P, indicating trait convergence of dominant species as soil P declined. 5. Synthesis: Our results demonstrate that at high fertility dominant species differ in resource use strategy, but as soil fertility declines over the long-term, dominant species increasingly converge on a resource-retentive strategy. This suggests that differentiation in resource use strategy is required for co-existence at high fertility but not in low fertility ecosystems

Combining social-based data mining techniques to extract collective trends from twitter

Social Networks have become an important environment for Collective Trends extraction. The interactions amongst users provide information of their preferences and relationships. This information can be used to measure the influence of ideas, or opinions, and how they are spread within the Network. Currently, one of the most relevant and popular Social Networks is Twitter. This Social Network was created to share comments and opinions. The information provided by users is especially useful in different fields and research areas such as marketing. This data is presented as short text strings containing different ideas expressed by real people. With this representation, different Data Mining techniques (such as classification or clustering) will be used for knowledge extraction to distinguish the meaning of the opinions. Complex Network techniques are also helpful to discover influential actors and study the information propagation inside the Social Network. This work is focused on how clustering and classification techniques can be combined to extract collective knowledge from Twitter. In an initial phase, clustering techniques are applied to extract the main topics from the user opinions. Later, the collective knowledge extracted is used to relabel the dataset according to the clusters obtained to improve the classification results. Finally, these results are compared against a dataset which has been manually labelled by human experts to analyse the accuracy of the proposed method.The preparation of this manuscript has been supported by the Spanish Ministry of Science and Innovation under the following projects: TIN2010-19872 and ECO2011-30105 (National Plan for Research, Development and Innovation), as well as the Multidisciplinary Project of Universidad Autónoma de Madrid (CEMU2012-034). The authors thank Ana M. Díaz-Martín and Mercedes Rozano for the manual classification of the Tweets