Progress in tuberculosis vaccine development and host-directed therapies-a state of the art review

Tuberculosis continues to kill 1.4 million people annually. During the past 5 years, an alarming increase in the number of patients with multidrug-resistant tuberculosis and extensively drug-resistant tuberculosis has been noted, particularly in eastern Europe, Asia, and southern Africa. Treatment outcomes with available treatment regimens for drug-resistant tuberculosis are poor. Although substantial progress in drug development for tuberculosis has been made, scientific progress towards development of interventions for prevention and improvement of drug treatment outcomes have lagged behind. Innovative interventions are therefore needed to combat the growing pandemic of multidrug-resistant and extensively drug-resistant tuberculosis. Novel adjunct treatments are needed to accomplish improved cure rates for multidrug-resistant and extensively drug-resistant tuberculosis. A novel, safe, widely applicable, and more effective vaccine against tuberculosis is also desperately sought to achieve disease control. The quest to develop a universally protective vaccine for tuberculosis continues. So far, research and development of tuberculosis vaccines has resulted in almost 20 candidates at different stages of the clinical trial pipeline. Host-directed therapies are now being developed to refocus the anti-Mycobacterium tuberculosis-directed immune responses towards the host; a strategy that could be especially beneficial for patients with multidrug-resistant tuberculosis or extensively drug-resistant tuberculosis. As we are running short of canonical tuberculosis drugs, more attention should be given to host-directed preventive and therapeutic intervention measures.

A coupled discriminative dictionary and transformation learning approach with applications to cross domain matching

Cross domain and cross-modal matching has many applications in the field of computer vision and pattern recognition. A few examples are heterogeneous face recognition, cross view action recognition, etc. This is a very challenging task since the data in two domains can differ significantly. In this work, we propose a coupled dictionary and transformation learning approach that models the relationship between the data in both domains. The approach learns a pair of transformation matrices that map the data in the two domains in such a manner that they share common sparse representations with respect to their own dictionaries in the transformed space. The dictionaries for the two domains are learnt in a coupled manner with an additional discriminative term to ensure improved recognition performance. The dictionaries and the transformation matrices are jointly updated in an iterative manner. The applicability of the proposed approach is illustrated by evaluating its performance on different challenging tasks: face recognition across pose, illumination and resolution, heterogeneous face recognition and cross view action recognition. Extensive experiments on five datasets namely, CMU-PIE, Multi-PIE, ChokePoint, HFB and IXMAS datasets and comparisons with several state-of-the-art approaches show the effectiveness of the proposed approach. (C) 2015 Elsevier B.V. All rights reserved.

Fully 3D refraction correction dosimetry system

The irradiation of selective regions in a polymer gel dosimeter results in an increase in optical density and refractive index (RI) at those regions. An optical tomography-based dosimeter depends on rayline path through the dosimeter to estimate and reconstruct the dose distribution. The refraction of light passing through a dose region results in artefacts in the reconstructed images. These refraction errors are dependant on the scanning geometry and collection optics. We developed a fully 3D image reconstruction algorithm, algebraic reconstruction technique-refraction correction (ART-rc) that corrects for the refractive index mismatches present in a gel dosimeter scanner not only at the boundary, but also for any rayline refraction due to multiple dose regions inside the dosimeter. In this study, simulation and experimental studies have been carried out to reconstruct a 3D dose volume using 2D CCD measurements taken for various views. The study also focuses on the effectiveness of using different refractive-index matching media surrounding the gel dosimeter. Since the optical density is assumed to be low for a dosimeter, the filtered backprojection is routinely used for reconstruction. We carry out the reconstructions using conventional algebraic reconstruction (ART) and refractive index corrected ART (ART-rc) algorithms. The reconstructions based on FDK algorithm for cone-beam tomography has also been carried out for comparison. Line scanners and point detectors, are used to obtain reconstructions plane by plane. The rays passing through dose region with a RI mismatch does not reach the detector in the same plane depending on the angle of incidence and RI. In the fully 3D scanning setup using 2D array detectors, light rays that undergo refraction are still collected and hence can still be accounted for in the reconstruction algorithm. It is found that, for the central region of the dosimeter, the usable radius using ART-rc algorithm with water as RI matched medium is 71.8%, an increase of 6.4% compared to that achieved using conventional ART algorithm. Smaller diameter dosimeters are scanned with dry air scanning by using a wide-angle lens that collects refracted light. The images reconstructed using cone beam geometry is seen to deteriorate in some planes as those regions are not scanned. Refraction correction is important and needs to be taken in to consideration to achieve quantitatively accurate dose reconstructions. Refraction modeling is crucial in array based scanners as it is not possible to identify refracted rays in the sinogram space.

A coupled discriminative dictionary and transformation learning approach with applications to cross domain matching

Cross domain and cross-modal matching has many applications in the field of computer vision and pattern recognition. A few examples are heterogeneous face recognition, cross view action recognition, etc. This is a very challenging task since the data in two domains can differ significantly. In this work, we propose a coupled dictionary and transformation learning approach that models the relationship between the data in both domains. The approach learns a pair of transformation matrices that map the data in the two domains in such a manner that they share common sparse representations with respect to their own dictionaries in the transformed space. The dictionaries for the two domains are learnt in a coupled manner with an additional discriminative term to ensure improved recognition performance. The dictionaries and the transformation matrices are jointly updated in an iterative manner. The applicability of the proposed approach is illustrated by evaluating its performance on different challenging tasks: face recognition across pose, illumination and resolution, heterogeneous face recognition and cross view action recognition. Extensive experiments on five datasets namely, CMU-PIE, Multi-PIE, ChokePoint, HFB and IXMAS datasets and comparisons with several state-of-the-art approaches show the effectiveness of the proposed approach. (C) 2015 Elsevier B.V. All rights reserved.

Evaluación financiera de la explotación apícola El Jobo, en el municipio de San Ramón, departamento de Matagalpa (Período Julio 1999 - Junio 2000)

El Presente trabajo se llevó a cabo en la finca El Jobo en los Apiarios Propiedad de CODAPI, la finca se ubica en el Municipio de San Ramón, carretera Pancasan, Matlguas en las coordenadas 12" 55' Latitud Norte y 85" 55' Longitud Oeste con una altura de 640 msnm y una Temperatura de 20- 26" C. El clima existente se clasifica de Trópico semi húmedo con bosque perenne y una flora útil para la Apicultura. La época seca se presenta de Febrero a mayo y un periodo lluvioso de Junio - Enero, con una precipitación de 2000 - 2400 mm /ano. Para el levantamiento de la información se realizó un estudio de casos con entrevistas semi - estructuradas, a lo largo del ciclo apícola 1999-2000, con visitas quincenales, que permitieron conocer el manejo de los apiarios, producción de miel y los costos de producción. El análisis de la información permitió evaluar el calendario apícola, los costos de producción divididos en mano de obra, insumos, servicios; así como determinar parámetros productivos como kilogramos de miel por ciclo, por apiario, por colmena. Se calcularon además la relación beneficio costo, margen bruto por apiario, margen bruto por colmena y margen bruto por dial hombre. Los resultados indicaron que la estrategia de producción principal de este ciclo fue la producción de colonias, aprovechando la flor amarilla, miel que no tiene demanda en el mercado internacional, no obstante permitió salvar el ciclo. Una vez realizada la evaluación financiera se pudo determinar que la relación beneficio - costo de este ciclo apícola fue de 0.88. Entre los factores que influyeron en estos resultados se pueden mencionar: La falta de capacitación en el manejo gerencial, administrativo y financiero del apiario. Factores climatológicos como fuertes vientos durante la época seca deshidrataron la flora. La no realización de un calendario apícola después del Huracán Mitch que dejó desvastada la flora de la zona norte del País, lo cual incidió de forma significativa en la producción de miel al momento de la trashumancia. Afecto J también el problema zoo-sanitario del acaro varroa a partir de 1999, aumentando los costos de producción de la empresa. De los costos de producción el 43.70 % correspondió a insumos, el27.7% a servicios, el7.37% a mano de obra y un 22.8% a las amortizaciones; La reproducción de miel que se obtuvo fue de 438 Kg. en el ciclo apícola en tres cosechas, 48 Kg. en agosto, 112 Kg. en Noviembre y 278 Kg. en abril del2000, lo que refleja 109. 7 Kg. de miel/ apiario/ ciclo y 5.2 Kg. de miel/ colmena / apiario / ciclo. De los ingresos que se obtuvieron en este ciclo el 71. 67 % corresponde a la venta de cámaras de crías y el 28.33 % a la venta de miel. El margen bruto 1 apiario 1 ciclo fue de C$ 1429.75, el margen bruto 1 colmena de C$ 68.9 y el margen bruto / día/ hombre fue de C$ 62.84, lo que muestra parámetros económicos deficientes para mantener las operaciones en la explotación y el margen neto de C$ -6 339 .38.