Abstract
A system for the identification of pollen grains in bright-field microscopic images is presented in this work. The system is based on segmentation of raw images and binary classification for 3 types of pollen grain. The segmentation method developed tackles a major difficulty of the problem: the existence of clustered pollen grains in the initial binary images. Two different SVM classification kernels are compared to identify the 3 pollen types. The method presented in this paper is able to provide a good estimate of the number of pollen grains of Olea Europea (relative error of 1.3%) in microscopic images. For the two others pollen types tested (Corylus and Quercus), the results were not as good (relative errors of 14.5% and 20.3%, respectively).

Abstract
Purpose The purpose of this study is to contribute to the existing knowledge about the process of achieving Lean Manufacturing (LM) success. Design/methodology/approach This study uses interpretive structural modeling and captures the opinions of a group of LM experts from a world-class Japanese automobile manufacturer, to map the interrelationships among potential determinants of LM success. This study further uses the data from a survey of 122 leading automobile part manufacturers by performing structural equation modeling to empirically test the research model proposed. Findings Management support and commitment, financial resources availability, information technology competence for LM, human resources management, production process simplicity, supportive culture and supply chain-wide integration are the key determinants that directly or indirectly determine the level of achievement of LM success. Research limitations/implications The determinants of LM success as experienced by Asian automobile manufacturers might be different from determinants of LM success as experienced by Western automobile manufacturers. An interesting direction for future research would be to capture the experts' inputs from Western automobile manufacturers to complement the findings of this study. Practical implications The practical contribution of this study lays in the development of linkages among various LM success determinants. Utility of the proposed interpretive structural modeling and structural equation modeling methodologies imposing order, direction and significance of the relationships among elements of LM success assumes considerable value to the decision-makers and LM practitioners. Originality/value Building on opinions of a group of LM experts and a case study of leading auto part manufacturers, the present study strives to model the success of LM, a topic that has received little attention to date.

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Abstract
Concurrent linearizable access to shared objects can be prohibitively expensive in a high contention workload. Many applications apply ad-hoc techniques to eliminate the need for synchronous atomic updates, which may result in non-linearizable implementations. We propose a new model which leverages such patterns for concurrent access to objects in a shared memory system. In this model, each thread maintains different views on the shared object: a thread-local view and a global view. As the thread-local view is not shared, it can be updated without incurring synchronization costs. These local updates become visible to other threads only after the thread-local view is merged with the global view. This enables better performance at the expense of linearizability. We discuss the design of several datatypes and evaluate their performance and scalability compared to linearizable implementations.

Abstract
Tuberculosis is one of the major public health concerns. This highly contagious disease affects more than 10.4 million people, being a leading cause of morbidity by infection. Tuberculosis is diagnosed at the point-of-care by the Ziehl-Neelsen sputum smear microscopy test. Ziehl-Neelsen is laborious, prone to human error and infection risk, with a limit of detection of 10(4) cells/mL. In resource-poor nations, a more practical test, with lower detection limit, is paramount. This work uses a magnetoresistive biosensor to detect BCG bacteria for tuberculosis diagnosis. Herein we report: i) nanoparticle assembly method and specificity for tuberculosis detection; ii) demonstration of proportionality between BCG cell concentration and magnetoresistive voltage signal; application of multiplicative signal correction for systematic effects removal; iv) investigation of calibration effectiveness using chemometrics methods; and v) comparison with state-of-the-art point-of-care tuberculosis biosensors. Results present a clear correspondence between voltage signal and cell concentration. Multiplicative signal correction removes baseline shifts within and between biochip sensors, allowing accurate and precise voltage signal between different biochips. The corrected signal was used for multivariate regression models, which significantly decreased the calibration standard error from 0.50 to 0.03 log(10) (cells/mL). Results show that Ziehl-Neelsen detection limits and below are achievable with the magnetoresistive biochip, when pre-processing and chemometrics are used.

Abstract

Social economy has assumed a role of growing importance in these last decades, being seen by several entities and political agents as one of the pillars in a new sustainable economic model. Volunteer programs are multiplying, and greater coordination between the various involved actors is essential to guarantee that society's help reaches the people who need them. In this sense, a digital donation platform based exclusively on open source technologies has been proposed and developed, which simplifies the process of donation of goods to a set of causes created by social solidarity institutions. The application permits anonymous donations and allows the monitoring of the status of each donation by the donors. Additionally, usability was considered as a key element in the design of the application