Yield mapping, soil fertility and tree gaps in an orange orchard

The current high competition on Citrus industry demands from growers new management technologies for superior efficiency and sustainability. In this context, precision agriculture (PA) has developed techniques based on yield mapping and management systems that recognize field spatial variability, which contribute to increase profitability of commercial crops. Because spatial variability is often not perceived the orange orchards are still managed as uniform and adoption of PA technology on citrus farms is low. Thus, the objective of the present study was to characterize the spatial variability of three factors: fruit yield, soil fertility and occurrence of plant gaps caused by either citrus blight or huanglongbing (HLB) in a commercial Valencia orchard in Brotas, São Paulo State, Brazil. Data from volume, geographic coordinates and representative area of the bags used on harvest were recorded to generate yield points that were then interpolated to produce the yield map. Soil chemical characteristics were studied by analyzing samples collected along planting rows and inter-rows in 24 points distributed in the field. A map of density of tree gaps was produced by georeferencing individual gaps and later by counting the number of gaps within 500 m² cells. Data were submitted to statistical and geostatistical analyses. A t test was used to compare means of soil chemical characteristics between sampling regions. High variation on yield and density of tree gaps was observed from the maps. It was also demonstrated overlapping regions of high density of plant absence and low fruit yield. Soil fertility varied depending on the sampling region in the orchard. The spatial variability found on yield, soil fertility and on disease occurrence demonstrated the importance to adopt site specific nutrient management and disease control as tools to guarantee efficiency of fruit production.

Trace element monitoring in the ICU: quality and economic impact of a change in sampling practice.

BACKGROUND & AIMS: Trace elements (TE) are involved in the immune and antioxidant defences which are of particular importance during critical illness. Determining plasma TE levels is costly. The present quality control study aimed at assessing the economic impact of a computer reminded blood sampling versus a risk guided on-demand monitoring of plasma concentrations of selenium, copper, and zinc. METHODS: Retrospective analysis of 2 cohorts of patients admitted during 6 months periods in 2006 and 2009 to the ICU of a University hospital. INCLUSION CRITERIA: to receive intravenous micronutrient supplements and/or to have a TE sampling during ICU stay. The TE samplings were triggered by computerized reminder in 2006 versus guided by nutritionists in 2009. RESULTS: During the 2 periods 636 patients met the inclusion criteria out of 2406 consecutive admissions, representing 29.7% and 24.9% respectively of the periods' admissions. The 2009 patients had higher SAPS2 scores (p = 0.02) and lower BMI compared to 2006 (p = 0.007). The number of laboratory determinations was drastically reduced in 2009, particularly during the first week, despite the higher severity of the cohort, resulting in à 55% cost reduction. CONCLUSIONS: The monitoring of TE concentrations guided by a nutritionist resulted in a reduction of the sampling frequency, and targeting on the sickest high risk patients, requiring a nutritional prescription adaptation. This control leads to cost reduction compared to an automated sampling prescription.

Detection of Clinically Significant Prostate Cancer Using Magnetic Resonance Imaging-Ultrasound Fusion Targeted Biopsy: A Systematic Review.

CONTEXT: The current standard for diagnosing prostate cancer in men at risk relies on a transrectal ultrasound-guided biopsy test that is blind to the location of the cancer. To increase the accuracy of this diagnostic pathway, a software-based magnetic resonance imaging-ultrasound (MRI-US) fusion targeted biopsy approach has been proposed. OBJECTIVE: Our main objective was to compare the detection rate of clinically significant prostate cancer with software-based MRI-US fusion targeted biopsy against standard biopsy. The two strategies were also compared in terms of detection of all cancers, sampling utility and efficiency, and rate of serious adverse events. The outcomes of different targeted approaches were also compared. EVIDENCE ACQUISITION: We performed a systematic review of PubMed/Medline, Embase (via Ovid), and Cochrane Review databases in December 2013 following the Preferred Reported Items for Systematic reviews and Meta-analysis statement. The risk of bias was evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. EVIDENCE SYNTHESIS: Fourteen papers reporting the outcomes of 15 studies (n=2293; range: 13-582) were included. We found that MRI-US fusion targeted biopsies detect more clinically significant cancers (median: 33.3% vs 23.6%; range: 13.2-50% vs 4.8-52%) using fewer cores (median: 9.2 vs 37.1) compared with standard biopsy techniques, respectively. Some studies showed a lower detection rate of all cancer (median: 50.5% vs 43.4%; range: 23.7-82.1% vs 14.3-59%). MRI-US fusion targeted biopsy was able to detect some clinically significant cancers that would have been missed by using only standard biopsy (median: 9.1%; range: 5-16.2%). It was not possible to determine which of the two biopsy approaches led most to serious adverse events because standard and targeted biopsies were performed in the same session. Software-based MRI-US fusion targeted biopsy detected more clinically significant disease than visual targeted biopsy in the only study reporting on this outcome (20.3% vs 15.1%). CONCLUSIONS: Software-based MRI-US fusion targeted biopsy seems to detect more clinically significant cancers deploying fewer cores than standard biopsy. Because there was significant study heterogeneity in patient inclusion, definition of significant cancer, and the protocol used to conduct the standard biopsy, these findings need to be confirmed by further large multicentre validating studies. PATIENT SUMMARY: We compared the ability of standard biopsy to diagnose prostate cancer against a novel approach using software to overlay the images from magnetic resonance imaging and ultrasound to guide biopsies towards the suspicious areas of the prostate. We found consistent findings showing the superiority of this novel targeted approach, although further high-quality evidence is needed to change current practice.

SEM evidence for existence of an apical disc on the scolex of Clestobothrium crassiceps (Rudolphi, 1819): comparative results of various fixation techniques

The scolex of the bothriocephalidean cestode Clestobothrium crassiceps was studied by means of scanning electron microscopy (SEM). The comparative results of various fixation procedures and techniques are presented. The scolex of C. crassiceps is oval to globular and exhibits two deep bothria which appear in the form of two lobes separated by a longitudinal groove. At the apex of the scolex, resembling a beret, an apical disc is present (oval, flattened and with a sinuous edge). Our results are compared with those previously reported in other species of Clestobothrium. This study represents the first report which highlights the presence of an apical disc in the scolex of C. crassiceps. It describes the effects of different procedures applied to our material during preparation and a comparative analysis results obtained using these various methods.

SEM evidence for existence of an apical disc on the scolex of Clestobothrium crassiceps (Rudolphi, 1819): comparative results of various fixation techniques

The scolex of the bothriocephalidean cestode Clestobothrium crassiceps was studied by means of scanning electron microscopy (SEM). The comparative results of various fixation procedures and techniques are presented. The scolex of C. crassiceps is oval to globular and exhibits two deep bothria which appear in the form of two lobes separated by a longitudinal groove. At the apex of the scolex, resembling a beret, an apical disc is present (oval, flattened and with a sinuous edge). Our results are compared with those previously reported in other species of Clestobothrium. This study represents the first report which highlights the presence of an apical disc in the scolex of C. crassiceps. It describes the effects of different procedures applied to our material during preparation and a comparative analysis results obtained using these various methods.

Development of cardiovascular magnetic resonance imaging techniques for improved characterization of atherosclerotic disease

Atherosclerosis is a chronic cardiovascular disease that involves the thicken¬ing of the artery walls as well as the formation of plaques (lesions) causing the narrowing of the lumens, in vessels such as the aorta, the coronary and the carotid arteries. Magnetic resonance imaging (MRI) is a promising modality for the assessment of atherosclerosis, as it is a non-invasive and patient-friendly procedure that does not use ionizing radiation. MRI offers high soft tissue con¬trast already without the need of intravenous contrast media; while modifica¬tion of the MR pulse sequences allows for further adjustment of the contrast for specific diagnostic needs. As such, MRI can create angiographic images of the vessel lumens to assess stenoses at the late stage of the disease, as well as blood flow-suppressed images for the early investigation of the vessel wall and the characterization of the atherosclerotic plaques. However, despite the great technical progress that occurred over the past two decades, MRI is intrinsically a low sensitive technique and some limitations still exist in terms of accuracy and performance. A major challenge for coronary artery imaging is respiratory motion. State- of-the-art diaphragmatic navigators rely on an indirect measure of motion, per¬form a ID correction, and have long and unpredictable scan time. In response, self-navigation (SM) strategies have recently been introduced that offer 100% scan efficiency and increased ease of use. SN detects respiratory motion di¬rectly from the image data obtained at the level of the heart, and retrospectively corrects the same data before final image reconstruction. Thus, SN holds po-tential for multi-dimensional motion compensation. To this regard, this thesis presents novel SN methods that estimate 2D and 3D motion parameters from aliased sub-images that are obtained from the same raw data composing the final image. Combination of all corrected sub-images produces a final image with reduced motion artifacts for the visualization of the coronaries. The first study (section 2.2, 2D Self-Navigation with Compressed Sensing) consists of a method for 2D translational motion compensation. Here, the use of com- pressed sensing (CS) reconstruction is proposed and investigated to support motion detection by reducing aliasing artifacts. In healthy human subjects, CS demonstrated an improvement in motion detection accuracy with simula¬tions on in vivo data, while improved coronary artery visualization was demon¬strated on in vivo free-breathing acquisitions. However, the motion of the heart induced by respiration has been shown to occur in three dimensions and to be more complex than a simple translation. Therefore, the second study (section 2.3,3D Self-Navigation) consists of a method for 3D affine motion correction rather than 2D only. Here, different techniques were adopted to reduce background signal contribution in respiratory motion tracking, as this can be adversely affected by the static tissue that surrounds the heart. The proposed method demonstrated to improve conspicuity and vi¬sualization of coronary arteries in healthy and cardiovascular disease patient cohorts in comparison to a conventional ID SN method. In the third study (section 2.4, 3D Self-Navigation with Compressed Sensing), the same tracking methods were used to obtain sub-images sorted according to the respiratory position. Then, instead of motion correction, a compressed sensing reconstruction was performed on all sorted sub-image data. This process ex¬ploits the consistency of the sorted data to reduce aliasing artifacts such that the sub-image corresponding to the end-expiratory phase can directly be used to visualize the coronaries. In a healthy volunteer cohort, this strategy improved conspicuity and visualization of the coronary arteries when compared to a con¬ventional ID SN method. For the visualization of the vessel wall and atherosclerotic plaques, the state- of-the-art dual inversion recovery (DIR) technique is able to suppress the signal coming from flowing blood and provide positive wall-lumen contrast. How¬ever, optimal contrast may be difficult to obtain and is subject to RR variability. Furthermore, DIR imaging is time-inefficient and multislice acquisitions may lead to prolonged scanning times. In response and as a fourth study of this thesis (chapter 3, Vessel Wall MRI of the Carotid Arteries), a phase-sensitive DIR method has been implemented and tested in the carotid arteries of a healthy volunteer cohort. By exploiting the phase information of images acquired after DIR, the proposed phase-sensitive method enhances wall-lumen contrast while widens the window of opportunity for image acquisition. As a result, a 3-fold increase in volumetric coverage is obtained at no extra cost in scanning time, while image quality is improved. In conclusion, this thesis presented novel methods to address some of the main challenges for MRI of atherosclerosis: the suppression of motion and flow artifacts for improved visualization of vessel lumens, walls and plaques. Such methods showed to significantly improve image quality in human healthy sub¬jects, as well as scan efficiency and ease-of-use of MRI. Extensive validation is now warranted in patient populations to ascertain their diagnostic perfor¬mance. Eventually, these methods may bring the use of atherosclerosis MRI closer to the clinical practice. Résumé L'athérosclérose est une maladie cardiovasculaire chronique qui implique le épaississement de la paroi des artères, ainsi que la formation de plaques (lé¬sions) provoquant le rétrécissement des lumières, dans des vaisseaux tels que l'aorte, les coronaires et les artères carotides. L'imagerie par résonance magné¬tique (IRM) est une modalité prometteuse pour l'évaluation de l'athérosclérose, car il s'agit d'une procédure non-invasive et conviviale pour les patients, qui n'utilise pas des rayonnements ionisants. L'IRM offre un contraste des tissus mous très élevé sans avoir besoin de médias de contraste intraveineux, tan¬dis que la modification des séquences d'impulsions de RM permet en outre le réglage du contraste pour des besoins diagnostiques spécifiques. À ce titre, l'IRM peut créer des images angiographiques des lumières des vaisseaux pour évaluer les sténoses à la fin du stade de la maladie, ainsi que des images avec suppression du flux sanguin pour une première enquête des parois des vais¬seaux et une caractérisation des plaques d'athérosclérose. Cependant, malgré les grands progrès techniques qui ont eu lieu au cours des deux dernières dé¬cennies, l'IRM est une technique peu sensible et certaines limitations existent encore en termes de précision et de performance. Un des principaux défis pour l'imagerie de l'artère coronaire est le mou¬vement respiratoire. Les navigateurs diaphragmatiques de pointe comptent sur une mesure indirecte de mouvement, effectuent une correction 1D, et ont un temps d'acquisition long et imprévisible. En réponse, les stratégies d'auto- navigation (self-navigation: SN) ont été introduites récemment et offrent 100% d'efficacité d'acquisition et une meilleure facilité d'utilisation. Les SN détectent le mouvement respiratoire directement à partir des données brutes de l'image obtenue au niveau du coeur, et rétrospectivement corrigent ces mêmes données avant la reconstruction finale de l'image. Ainsi, les SN détiennent un poten¬tiel pour une compensation multidimensionnelle du mouvement. A cet égard, cette thèse présente de nouvelles méthodes SN qui estiment les paramètres de mouvement 2D et 3D à partir de sous-images qui sont obtenues à partir des mêmes données brutes qui composent l'image finale. La combinaison de toutes les sous-images corrigées produit une image finale pour la visualisation des coronaires ou les artefacts du mouvement sont réduits. La première étude (section 2.2,2D Self-Navigation with Compressed Sensing) traite d'une méthode pour une compensation 2D de mouvement de translation. Ici, on étudie l'utilisation de la reconstruction d'acquisition comprimée (compressed sensing: CS) pour soutenir la détection de mouvement en réduisant les artefacts de sous-échantillonnage. Chez des sujets humains sains, CS a démontré une amélioration de la précision de la détection de mouvement avec des simula¬tions sur des données in vivo, tandis que la visualisation de l'artère coronaire sur des acquisitions de respiration libre in vivo a aussi été améliorée. Pourtant, le mouvement du coeur induite par la respiration se produit en trois dimensions et il est plus complexe qu'un simple déplacement. Par conséquent, la deuxième étude (section 2.3, 3D Self-Navigation) traite d'une méthode de cor¬rection du mouvement 3D plutôt que 2D uniquement. Ici, différentes tech¬niques ont été adoptées pour réduire la contribution du signal du fond dans le suivi de mouvement respiratoire, qui peut être influencé négativement par le tissu statique qui entoure le coeur. La méthode proposée a démontré une amélioration, par rapport à la procédure classique SN de correction 1D, de la visualisation des artères coronaires dans le groupe de sujets sains et des pa¬tients avec maladies cardio-vasculaires. Dans la troisième étude (section 2.4,3D Self-Navigation with Compressed Sensing), les mêmes méthodes de suivi ont été utilisées pour obtenir des sous-images triées selon la position respiratoire. Au lieu de la correction du mouvement, une reconstruction de CS a été réalisée sur toutes les sous-images triées. Cette procédure exploite la cohérence des données pour réduire les artefacts de sous- échantillonnage de telle sorte que la sous-image correspondant à la phase de fin d'expiration peut directement être utilisée pour visualiser les coronaires. Dans un échantillon de volontaires en bonne santé, cette stratégie a amélioré la netteté et la visualisation des artères coronaires par rapport à une méthode classique SN ID. Pour la visualisation des parois des vaisseaux et de plaques d'athérosclérose, la technique de pointe avec double récupération d'inversion (DIR) est capa¬ble de supprimer le signal provenant du sang et de fournir un contraste posi¬tif entre la paroi et la lumière. Pourtant, il est difficile d'obtenir un contraste optimal car cela est soumis à la variabilité du rythme cardiaque. Par ailleurs, l'imagerie DIR est inefficace du point de vue du temps et les acquisitions "mul- tislice" peuvent conduire à des temps de scan prolongés. En réponse à ce prob¬lème et comme quatrième étude de cette thèse (chapitre 3, Vessel Wall MRI of the Carotid Arteries), une méthode de DIR phase-sensitive a été implémenté et testé

Source separation techniques applied to linear prediction

The prediction filters are well known models for signal estimation, in communications, control and many others areas. The classical method for deriving linear prediction coding (LPC) filters is often based on the minimization of a mean square error (MSE). Consequently, second order statistics are only required, but the estimation is only optimal if the residue is independent and identically distributed (iid) Gaussian. In this paper, we derive the ML estimate of the prediction filter. Relationships with robust estimation of auto-regressive (AR) processes, with blind deconvolution and with source separation based on mutual information minimization are then detailed. The algorithm, based on the minimization of a high-order statistics criterion, uses on-line estimation of the residue statistics. Experimental results emphasize on the interest of this approach.

On cumulant techniques in speech processing

This paper analyzes applications of cumulant analysis in speech processing. A special focus is made on different second-order statistics. A dominant role is played by an integral representation for cumulants by means of integrals involving cyclic products of kernels.