Efficacy and tolerability of two single-day regimens of triclabendazole for fascioliasis in Peruvian children

Abstract:INTRODUCTION:The therapeutic scheme of triclabendazole (TCBZ), the recommended anthelmintic against Fasciola hepatica , involves 10mg/kg of body weight administered in a single dose; however, clinical trials in children are scarce. We evaluated the efficacy and tolerability of 2 schemes of TCBZ.METHODS: Eighty-four Peruvian children with F. hepatica eggs in their stools were allocated into 2 groups: 44 received 2 dosages of 7.5mg/kg each with a 12-h interval (Group I), and 40 received a single 10-mg/kg dose (Group II). Evaluation of efficacy was based on the presence of eggs in stools, and tolerability was based on the presence of symptoms and signs post-treatment.RESULTS: A parasitological cure was obtained in 100% of individuals from Group I and 95% of individuals from Group II. The most common adverse event was biliary colic.CONCLUSIONS: The tested scheme was efficacious and tolerable, and it might be an optimal scheme in the region. To the best of our knowledge, this represents the largest series of children treated with TCBZ in a non-hospital setting.

Single-tube nested PCR assay with in-house DNA extraction for Mycobacterium tuberculosis detection in blood and urine

Abstract: INTRODUCTION : Molecular analyses are auxiliary tools for detecting Koch's bacilli in clinical specimens from patients with suspected tuberculosis (TB). However, there are still no efficient diagnostic tests that combine high sensitivity and specificity and yield rapid results in the detection of TB. This study evaluated single-tube nested polymerase chain reaction (STNPCR) as a molecular diagnostic test with low risk of cross contamination for detecting Mycobacterium tuberculosis in clinical samples. METHODS: Mycobacterium tuberculosis deoxyribonucleic acid (DNA) was detected in blood and urine samples by STNPCR followed by agarose gel electrophoresis. In this system, reaction tubes were not opened between the two stages of PCR (simple and nested). RESULTS: STNPCR demonstrated good accuracy in clinical samples with no cross contamination between microtubes. Sensitivity in blood and urine, analyzed in parallel, was 35%-62% for pulmonary and 41%-72% for extrapulmonary TB. The specificity of STNPCR was 100% in most analyses, depending on the type of clinical sample (blood or urine) and clinical form of disease (pulmonary or extrapulmonary). CONCLUSIONS: STNPCR was effective in detecting TB, especially the extrapulmonary form for which sensitivity was higher, and had the advantage of less invasive sample collection from patients for whom a spontaneous sputum sample was unavailable. With low risk of cross contamination, the STNPCR can be used as an adjunct to conventional methods for diagnosing TB.

Nonsmall cell lung cancer: evaluation of 737 consecutive patients in a single institution

OBJECTIVE: To analyze surgical and pathological parameters and outcome and prognostic factors of patients with nonsmall cell lung cancer (NSCLC) who were admitted to a single institution, as well as to correlate these findings to the current staging system. METHOD: Seven hundred and thirty seven patients were diagnosed with NSCLC and admitted to Hospital do Cancer A. C. Camargo from 1990 to 2000. All patients were included in a continuous prospective database, and their data was analyzed. Following staging, a multidisciplinary team decision on adequate management was established. Variables included in this analysis were age, gender, histology, Karnofsky index, weight loss, clinical stage, surgical stage, chemotherapy, radiotherapy, and survival rates. RESULTS: 75.5% of patients were males. The distribution of histologic type was squamous cell carcinoma 51.8%, adenocarcinoma 43.1%, and undifferentiated large cell carcinoma 5.1%. Most patients (73%) presented significant weight loss and a Karnofsky index of 80%. Clinical staging was IA 3.8%, IB 9.2%, IIA 1.4%, IIB 8.1%, IIIA 20.9%, IIIB 22.4%, IV 30.9%. Complete tumor resection was performed in 24.6% of all patients. Surgical stage distribution was IA 25.3%, IB 1.4%, IIB 17.1%, IIIA 16.1%, IIIB 20.3%, IV 11.5%. Chemotherapy and radiotherapy were considered therapeutic options in 43% and 72%, respectively. The overall 5-year survival rate of nonsmall cell lung cancer patients in our study was 28%. Median survival was 18.9 months. CONCLUSIONS: Patients with NSCLC who were admitted to our institution presented with histopathologic and clinical characteristics that were similar to previously published series in cancer hospitals. The best prognosis was associated with complete tumor resection with lymph node dissection, which is only achievable in earlier clinical stages.

The impact of the Board of Director's composition on companies performance

The impact of the Board of Directors’ composition on companies’ performance This paper studies the impact that the board of directors’ composition has on companies’ performance in the Italian market. The research has been carried out by using a sample of 10 Italian companies, across different market sectors, over a period of 10 years (2005-2014). The characteristics of the BoD taken into consideration are the following: board size, board diversity (% of female directors), board independence and CEO duality. Results from the sample data collected concluded that these factors have a statistically significant impact on the performance of the companies that have been analysed.

Scaling In-Memory databases on multicores

Current computer systems have evolved from featuring only a single processing unit and limited RAM, in the order of kilobytes or few megabytes, to include several multicore processors, o↵ering in the order of several tens of concurrent execution contexts, and have main memory in the order of several tens to hundreds of gigabytes. This allows to keep all data of many applications in the main memory, leading to the development of inmemory databases. Compared to disk-backed databases, in-memory databases (IMDBs) are expected to provide better performance by incurring in less I/O overhead. In this dissertation, we present a scalability study of two general purpose IMDBs on multicore systems. The results show that current general purpose IMDBs do not scale on multicores, due to contention among threads running concurrent transactions. In this work, we explore di↵erent direction to overcome the scalability issues of IMDBs in multicores, while enforcing strong isolation semantics. First, we present a solution that requires no modification to either database systems or to the applications, called MacroDB. MacroDB replicates the database among several engines, using a master-slave replication scheme, where update transactions execute on the master, while read-only transactions execute on slaves. This reduces contention, allowing MacroDB to o↵er scalable performance under read-only workloads, while updateintensive workloads su↵er from performance loss, when compared to the standalone engine. Second, we delve into the database engine and identify the concurrency control mechanism used by the storage sub-component as a scalability bottleneck. We then propose a new locking scheme that allows the removal of such mechanisms from the storage sub-component. This modification o↵ers performance improvement under all workloads, when compared to the standalone engine, while scalability is limited to read-only workloads. Next we addressed the scalability limitations for update-intensive workloads, and propose the reduction of locking granularity from the table level to the attribute level. This further improved performance for intensive and moderate update workloads, at a slight cost for read-only workloads. Scalability is limited to intensive-read and read-only workloads. Finally, we investigate the impact applications have on the performance of database systems, by studying how operation order inside transactions influences the database performance. We then propose a Read before Write (RbW) interaction pattern, under which transaction perform all read operations before executing write operations. The RbW pattern allowed TPC-C to achieve scalable performance on our modified engine for all workloads. Additionally, the RbW pattern allowed our modified engine to achieve scalable performance on multicores, almost up to the total number of cores, while enforcing strong isolation.

Targeting Heme with Single Domain Antibodies

Heme, i.e. iron (Fe) protoporphyrin IX, functions as a prosthetic group in a variety of hemoproteins that participate in vital biologic functions essential to sustain life. Heme is a highly reactive molecule, participating in redox reactions, and presumably for this reason it must be sequestered within the heme pockets of hemoproteins, controlling its reactivity. However, under biological stress conditions, hemoproteins can release their prosthetic groups, generating “free heme”, which binds loosely to proteins or to other molecules and presumably acquires unfettered redox activity. Moreover, a growing body of evidence supports the notion that “free heme” can act in a vasoactive, pro-inflammatory and cytotoxic manner when released from a subset of these hemoproteins, such as extracellular hemoglobin, generated during hemolytic conditions. (...)

On-board electric vehicle battery charger with enhanced V2H operation mode

This paper proposes an on-board Electric Vehicle (EV) battery charger with enhanced Vehicle-to-Home (V2H) operation mode. For such purpose was adapted an on-board bidirectional battery charger prototype to allow the Grid-to-Vehicle (G2V), Vehicle-to-Grid (V2G) and V2H operation modes. Along the paper are presented the hardware topology and the control algorithms of this battery charger. The idea underlying to this paper is the operation of the on-board bidirectional battery charger as an energy backup system when occurs a power outages. For detecting the power outage were compared two strategies, one based on the half-cycle rms calculation of the power grid voltage, and another in the determination of the rms value based in a Kalman filter. The experimental results were obtained considering the on-board EV battery charger under the G2V, V2G, and V2H operation modes. The results show that the power outage detection is faster using a Kalman filter, up to 90% than the other strategy. This also enables a faster transition between operation modes when a power outage occurs.

EMM-ARM Retrospective and current developments

FCT PhD grant SFRH/BD/80682/2011; FCT research project VisCoDyn EXPL/ECM-EST/1323/2013

Hand gesture recognition for human computer interaction : a comparative study of different image features

Hand gesture recognition for human computer interaction, being a natural way of human computer interaction, is an area of active research in computer vision and machine learning. This is an area with many different possible applications, giving users a simpler and more natural way to communicate with robots/systems interfaces, without the need for extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them to convey information or for device control. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. In this study we try to identify hand features that, isolated, respond better in various situations in human-computer interaction. The extracted features are used to train a set of classifiers with the help of RapidMiner in order to find the best learner. A dataset with our own gesture vocabulary consisted of 10 gestures, recorded from 20 users was created for later processing. Experimental results show that the radial signature and the centroid distance are the features that when used separately obtain better results, with an accuracy of 91% and 90,1% respectively obtained with a Neural Network classifier. These to methods have also the advantage of being simple in terms of computational complexity, which make them good candidates for real-time hand gesture recognition.

Hand gesture recognition system based in computer vision and machine learning

"Lecture notes in computational vision and biomechanics series, ISSN 2212-9391, vol. 19"

Generic system for human-computer gesture interaction: applications on sign language recognition and robotic soccer refereeing

Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for human-computer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of visionbased interaction systems could be the same for all applications and thus facilitate the implementation. For hand posture recognition, a SVM (Support Vector Machine) model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM (Hidden Markov Model) model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications. To validate the proposed framework two applications were implemented. The first one is a real-time system able to interpret the Portuguese Sign Language. The second one is an online system able to help a robotic soccer game referee judge a game in real time.

Generic system for human-computer gesture interaction

Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for humancomputer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of vision-based interaction systems can be the same for all applications and thus facilitate the implementation. In order to test the proposed solutions, three prototypes were implemented. For hand posture recognition, a SVM model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications.

Dynamic group formation in mobile computer supported collaborative learning environment

Forming suitable learning groups is one of the factors that determine the efficiency of collaborative learning activities. However, only a few studies were carried out to address this problem in the mobile learning environments. In this paper, we propose a new approach for an automatic, customized, and dynamic group formation in Mobile Computer Supported Collaborative Learning (MCSCL) contexts. The proposed solution is based on the combination of three types of grouping criteria: learner’s personal characteristics, learner’s behaviours, and context information. The instructors can freely select the type, the number, and the weight of grouping criteria, together with other settings such as the number, the size, and the type of learning groups (homogeneous or heterogeneous). Apart from a grouping mechanism, the proposed approach represents a flexible tool to control each learner, and to manage the learning processes from the beginning to the end of collaborative learning activities. In order to evaluate the quality of the implemented group formation algorithm, we compare its Average Intra-cluster Distance (AID) with the one of a random group formation method. The results show a higher effectiveness of the proposed algorithm in forming homogenous and heterogeneous groups compared to the random method.

An immunity based configuration for multilayer single featured biometric authentication algorithms

Immune systems have been used in the last years to inspire approaches for several computational problems. This paper focus on behavioural biometric authentication algorithms’ accuracy enhancement by using them more than once and with different thresholds in order to first simulate the protection provided by the skin and then look for known outside entities, like lymphocytes do. The paper describes the principles that support the application of this approach to Keystroke Dynamics, an authentication biometric technology that decides on the legitimacy of a user based on his typing pattern captured on he enters the username and/or the password and, as a proof of concept, the accuracy levels of one keystroke dynamics algorithm when applied to five legitimate users of a system both in the traditional and in the immune inspired approaches are calculated and the obtained results are compared.