Impact of a training course on the quality of malaria diagnosis by microscopy in Angola

Background: In Angola, malaria is an endemic disease having a major impact on the economy. The WHO recommends testing for all suspected malaria cases, to avoid the presumptive treatment of this disease. In malaria endemic regions laboratory technicians must be very comfortable with microscopy, the golden standard for malaria diagnosis, to avoid the incorrect diagnosis. The improper use of medication promotes drug resistance and undesirable side effects. The present study aims to assess the impact of a three-day refresher course on the knowledge of technicians, quality of blood smears preparation and accuracy of microscopy malaria diagnosis, using qPCR as reference method. Methods: This study was implemented in laboratories from three hospitals in different provinces of Angola: Bengo, Benguela and Luanda. In each laboratory samples were collected before and after the training course (slide with thin and thick blood smears, a dried blood spot and a form). The impact of the intervention was evaluated through a written test, the quality of slide preparation and the performance of microscopy. Results: It was found a significant increase on the written test median score, from 52.5% to 65.0%. A total of 973 slides were analysed to evaluate the quality of thick and thin blood smears. Considering all laboratories there was a significant increase in quality of thick and thin blood smears. To determine the performance of microscopy using qPCR as the reference method we used 1,028 samples. Benguela presented the highest values for specificity, 92.9% and 98.8% pre and post-course, respectively and for sensitivity the best pre-course was Benguela (75.9%) and post-course Luanda (75.0%). However, no significant increase in sensitivity and specificity after the training course was registered in any laboratory analysed. Discussion: The findings of this study support the need of continuous refresher training for microscopists and other laboratory staff. The laboratories should have a quality control programme to supervise the diagnosis and also to assess the periodicity of new training. However, other variables needed to be considered to have a correct malaria diagnosis, such as adequate equipment and reagents for staining and visualization, good working conditions, motivated and qualified personnel.

Detection and diagnosis solutions for fault-tolerant VSI

This paper presents solutions for fault detection and diagnosis of two-level, three phase voltage-source inverter (VSI) topologies with IGBT devices. The proposed solutions combine redundant standby VSI structures and contactors (or relays) to improve the fault-tolerant capabilities of power electronics in applications with safety requirements. The suitable combination of these elements gives the inverter the ability to maintain energy processing in the occurrence of several failure modes, including short-circuit in IGBT devices, thus extending its reliability and availability. A survey of previously developed fault-tolerant VSI structures and several aspects of failure modes, detection and isolation mechanisms within VSI is first discussed. Hardware solutions for the protection of power semiconductors with fault detection and diagnosis mechanisms are then proposed to provide conditions to isolate and replace damaged power devices (or branches) in real time. Experimental results from a prototype are included to validate the proposed solutions.

Intimate partner violence after the diagnosis of sexually transmitted diseases

OBJECTIVE To assess the prevalence and factors associated with intimate partner violence after the diagnosis of sexually transmitted diseases.METHODS This cross-sectional study was conducted in Fortaleza, CE, Northeastern Brazil, in 2012 and involved 221 individuals (40.3% male and 59.7% female) attended to at reference health care units for the treatment of sexually transmitted diseases. Data were collected using a questionnaire applied during interviews with each participant. A multivariate analysis with a logistic regression model was conducted using the stepwise technique. Only the variables with a p value < 0.05 were included in the adjusted analysis. The odds ratio (OR) with 95% confidence interval (CI) was used as the measure of effect.RESULTS A total of 30.3% of the participants reported experiencing some type of violence (27.6%, psychological; 5.9%, physical; and 7.2%, sexual) after the diagnosis of sexually transmitted disease. In the multivariate analysis adjusted to assess intimate partner violence after the revelation of the diagnosis of sexually transmitted diseases, the following variables remained statistically significant: extramarital relations (OR = 3.72; 95%CI 1.91;7.26; p = 0.000), alcohol consumption by the partner (OR = 2.16; 95%CI 1.08;4.33; p = 0.026), history of violence prior to diagnosis (OR = 2.87; 95%CI 1.44;5.69; p = 0.003), and fear of disclosing the diagnosis to the partner (OR = 2.66; 95%CI 1.32;5.32; p = 0.006).CONCLUSIONS Individuals who had extramarital relations, experienced violence prior to the diagnosis of sexually transmitted disease, feared disclosing the diagnosis to the partner, and those whose partner consumed alcohol had an increased likelihood of suffering violence. The high prevalence of intimate partner violence suggests that this population is vulnerable and therefore intervention efforts should be directed to them. Referral health care services for the treatment of sexually transmitted diseases can be strategic places to identify and prevent intimate partner violence.

A hybrid genetic algorithm for the multi-mode resource-constrained project scheduling

A construction project is a group of discernible tasks or activities that are conduct-ed in a coordinated effort to accomplish one or more objectives. Construction projects re-quire varying levels of cost, time and other resources. To plan and schedule a construction project, activities must be defined sufficiently. The level of detail determines the number of activities contained within the project plan and schedule. So, finding feasible schedules which efficiently use scarce resources is a challenging task within project management. In this context, the well-known Resource Constrained Project Scheduling Problem (RCPSP) has been studied during the last decades. In the RCPSP the activities of a project have to be scheduled such that the makespan of the project is minimized. So, the technological precedence constraints have to be observed as well as limitations of the renewable resources required to accomplish the activities. Once started, an activity may not be interrupted. This problem has been extended to a more realistic model, the multi-mode resource con-strained project scheduling problem (MRCPSP), where each activity can be performed in one out of several modes. Each mode of an activity represents an alternative way of combining different levels of resource requirements with a related duration. Each renewable resource has a limited availability for the entire project such as manpower and machines. This paper presents a hybrid genetic algorithm for the multi-mode resource-constrained pro-ject scheduling problem, in which multiple execution modes are available for each of the ac-tivities of the project. The objective function is the minimization of the construction project completion time. To solve the problem, is applied a two-level genetic algorithm, which makes use of two separate levels and extend the parameterized schedule generation scheme. It is evaluated the quality of the schedules and presents detailed comparative computational re-sults for the MRCPSP, which reveal that this approach is a competitive algorithm.

Physiotherapy and Duchenne muscular dystrophy

Duchenne muscular dystrophy (DMD) is a severe, progressive disease first described by Meryon in 1852 and later by Guillaume Duchene. It is the most common and severe form of childhood muscular dystrophy, affecting 1 in 3500 live male births. Is caused by an X—linked recessive genetic disorder resulting in a deficiency of the dystrophin protein, responsible for linking contractile proteins to the sarcolemma. Diagnosis is not always easy and the first symptoms are often related to weakness and difficulty or delay in acquiring the ability to perform simple activities. Progressive weakness leads to the use of compensatory strategies in order to maintain the ability to walk and perform other activities. Respiratory muscles are also affected and the complications resulting from its impairments are frequently the cause of early death of these patients. The advances in DMD management has increased life expectancy of these children with the need for adequate care in adulthood. DMD manifestations include muscle weakness, contractures, respiratory and cardiac complications. Some authors also refer that one-third of patients have difficulties with learning and delayed global development because the gene that encodes dystrophyn expresses various dystrophin isoforms that are found in Schwann and Purkinje celis in the brain. Body functions and structure impairments like muscle weakness, contractures and reduced range of motion lead to limitations in activities, i.e., impairments affect the performance of tasks by the individual. In a physiotherapist’s point of view analysing these limitations is mandatory because physiotherapy’s final purpose is to restore or preserve the ability to perform ADL and to improve quality of life.

A genetic algorithm for the resource constrained multi-project scheduling problem

This paper presents a genetic algorithm for the resource constrained multi-project scheduling problem. The chromosome representation of the problem is based on random keys. The schedules are constructed using a heuristic that builds parameterized active schedules based on priorities, delay times, and release dates defined by the genetic algorithm. The approach is tested on a set of randomly generated problems. The computational results validate the effectiveness of the proposed algorithm.

Fatty liver automatic diagnosis from ultrasound images

In this paper an automatic classification algorithm is proposed for the diagnosis of the liver steatosis, also known as, fatty liver, from ultrasound images. The features, automatically extracted from the ultrasound images used by the classifier, are basically the ones used by the physicians in the diagnosis of the disease based on visual inspection of the ultrasound images. The main novelty of the method is the utilization of the speckle noise that corrupts the ultrasound images to compute textural features of the liver parenchyma relevant for the diagnosis. The algorithm uses the Bayesian framework to compute a noiseless image, containing anatomic and echogenic information of the liver and a second image containing only the speckle noise used to compute the textural features. The classification results, with the Bayes classifier using manually classified data as ground truth show that the automatic classifier reaches an accuracy of 95% and a 100% of sensitivity.

Genetic diversity and epidemiology of antimicrobial resistant Streptococcus pneumoniae isolates

Dissertation presented to obtain a Ph.D. degree in Biology, speciality in Microbiology, by Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Optimal location of supports in beam structures using genetic algorithms

Real structures can be thought as an assembly of components, as for instances plates, shells and beams. This later type of component is very commonly found in structures like frames which can involve a significant degree of complexity or as a reinforcement element of plates or shells. To obtain the desired mechanical behavior of these components or to improve their operating conditions when rehabilitating structures, one of the eventual parameters to consider for that purpose, when possible, is the location of the supports. In the present work, a beam-type structure is considered, and for a set of cases concerning different number and types of supports, as well as different load cases, the authors optimize the location of the supports in order to obtain minimum values of the maximum transverse deflection. The optimization processes are carried out using genetic algorithms. The results obtained, clearly show a good performance of the approach proposed. © 2014 IEEE.

A genetic algorithm for project scheduling with multi-modes and renewable resources

This paper presents a genetic algorithm-based approach for project scheduling with multi-modes and renewable resources. In this problem activities of the project may be executed in more than one operating mode and renewable resource constraints are imposed. The objective function is the minimization of the project completion time. The idea of this approach is integrating a genetic algorithm with a schedule generation scheme. This study also proposes applying a local search procedure trying to yield a better solution when the genetic algorithm and the schedule generation scheme obtain a solution. The experimental results show that this algorithm is an effective method for solving this problem.

Application of genetic algorithms in the design of an electrical potential of fractional order

Fractional calculus (FC) is currently being applied in many areas of science and technology. In fact, this mathematical concept helps the researches to have a deeper insight about several phenomena that integer order models overlook. Genetic algorithms (GA) are an important tool to solve optimization problems that occur in engineering. This methodology applies the concepts that describe biological evolution to obtain optimal solution in many different applications. In this line of thought, in this work we use the FC and the GA concepts to implement the electrical fractional order potential. The performance of the GA scheme, and the convergence of the resulting approximation, are analyzed. The results are analyzed for different number of charges and several fractional orders.

Population health diagnosis with an ecohealth approach

OBJECTIVE To analyze the characteristics of health diagnosis according to the ecohealth approach in rural and urban communities in Mexico.METHODS Health diagnosis were conducted in La Nopalera, from December 2007 to October 2008, and in Atlihuayan, from December 2010 to October 2011. The research was based on three principles of the ecohealth approach: transdisciplinarity, community participation, gender and equity. To collect information, a joint methodology and several techniques were used to stimulate the participation of inhabitants. The diagnostic exercise was carried out in five phases that went from collecting information to prioritization of problems.RESULTS The constitution of the transdisciplinary team, as well as the participation of the population and the principle of gender/equity were differentials between the communities. In the rural community, the active participation of inhabitants and authorities was achieved and the principles of transdisciplinarity and gender/equity were incorporated.CONCLUSIONS With all the difficulties that entails the boost in participation, the incorporation of gender/equity and transdisciplinarity in health diagnosis allowed a holistic public health approach closer to the needs of the population.

Project scheduling under multiple resources constraints using a genetic algorithm

The resource constrained project scheduling problem (RCPSP) is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. During the last couple of years many heuristic procedures have been developed for this problem, but still these procedures often fail in finding near-optimal solutions. This paper proposes a genetic algorithm for the resource constrained project scheduling problem. The chromosome representation of the problem is based on random keys. The schedule is constructed using a heuristic priority rule in which the priorities and delay times of the activities are defined by the genetic algorithm. The approach was tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm.

Project scheduling using a competitive genetic algorithm

- The resource constrained project scheduling problem (RCPSP) is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. During the last couple of years many heuristic procedures have been developed for this problem, but still these procedures often fail in finding near-optimal solutions. This paper proposes a genetic algorithm for the resource constrained project scheduling problem. The chromosome representation of the problem is based on random keys. The schedule is constructed using a heuristic priority rule in which the priorities and delay times of the activities are defined by the genetic algorithm. The approach was tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm

Optimal tuning of fractional controllers using genetic algorithms

This study addresses the optimization of fractional algorithms for the discrete-time control of linear and non-linear systems. The paper starts by analyzing the fundamentals of fractional control systems and genetic algorithms. In a second phase the paper evaluates the problem in an optimization perspective. The results demonstrate the feasibility of the evolutionary strategy and the adaptability to distinct types of systems.