On the Rovibrational Partition Function of Molecular Hydrogen at High Temperatures

We report a comparative study of the vibrational and rovibrational partition functions using several quantum and classical statistical mechanics approaches. The calculations refer to H2, but the conclusions are anticipated to be valid also for larger systems

Targeted vagus nerve stimulation for rehabilitation after stroke

No abstract available

Intravesical Protrusion of the Prostate as a Predictive Method of Bladder Outlet Obstruction

Objective. Pressure-flow study is the gold standard for diagnosis of bladder outlet obstruction (BOO) A prospective study was carried out to compare urodynamic evaluation and measurement of intravesical protrusion of the prostate for diagnosing BOO Materials and Methods Patients presenting with lower urinary tract symptoms (LUTS) associated with benign prostatic hyperplasia and suspected BOO were prospectively evaluated through conventional urodynamics and classified according to the bladder outlet obstruction index (BOO!). They also underwent abdominal ultrasound measurement of the intravesical prostatic protrusion (IPP) and prostatic volume. The I PP was classified into three stages grade I under 5 mm; grade 11, between 5 and 10 mm, and grade III over 10 mm Results Forty-two patients, mean age 64.8 +/- 8.5 years were enrolled Transabdominal ultrasound determined a mean prostatic volume of 45 +/- 3 2 mL. Achieved IPP's values were the following: grade I - 12 (28.5%), grade II - 5 - (12%) and grade III - 25 (59.5%). The results of prostate volume differed significantly between obstructed and non-obstructed men (p = 0.033) and for IPP among obstructed, inconclusive and non-obstructed men (p = 0 016). For IPP, the area under ROC curve was 0.758 (95% confidence interval - 0.601 to 0 876), and the cutoff point to indicate BOO was 5 mm with 95 % sensitivity (75 1 - 99 2) and 50% specificity (28.2 - 71 8). Conclusion IPP and prostatic volume measured through abdominal ultrasound are noninvasive and accessible methods that significantly correlate to urinary BOO, and are useful in the diagnosis of male urinary obstructive problems.34562763

As novas tecnologias e a rotura do processo pedagógico

info:eu-repo/semantics/publishedVersio

Toward Improving Safety in Neurosurgery with an Active Handheld Instrument

Microsurgical procedures, such as petroclival meningioma resection, require careful surgical actions in order to remove tumor tissue, while avoiding brain and vessel damaging. Such procedures are currently performed under microscope magnification. Robotic tools are emerging in order to filter surgeons’ unintended movements and prevent tools from entering forbidden regions such as vascular structures. The present work investigates the use of a handheld robotic tool (Micron) to automate vessel avoidance in microsurgery. In particular, we focused on vessel segmentation, implementing a deep-learning-based segmentation strategy in microscopy images, and its integration with a feature-based passive 3D reconstruction algorithm to obtain accurate and robust vessel position. We then implemented a virtual-fixture-based strategy to control the handheld robotic tool and perform vessel avoidance. Clay vascular phantoms, lying on a background obtained from microscopy images recorded during petroclival meningioma surgery, were used for testing the segmentation and control algorithms. When testing the segmentation algorithm on 100 different phantom images, a median Dice similarity coefficient equal to 0.96 was achieved. A set of 25 Micron trials of 80 s in duration, each involving the interaction of Micron with a different vascular phantom, were recorded, with a safety distance equal to 2 mm, which was comparable to the median vessel diameter. Micron’s tip entered the forbidden region 24% of the time when the control algorithm was active. However, the median penetration depth was 16.9 μm, which was two orders of magnitude lower than median vessel diameter. Results suggest the system can assist surgeons in performing safe vessel avoidance during neurosurgical procedures

Lem benchmark database for tropical agricultural remote sensing application.

Abstract: The monitoring of agricultural activities at a regular basis is crucial to assure that the food production meets the world population demands, which is increasing yearly. Such information can be derived from remote sensing data. In spite of topic?s relevance, not enough efforts have been invested to exploit modern pattern recognition and machine learning methods for agricultural land-cover mapping from multi-temporal, multi-sensor earth observation data. Furthermore, only a small proportion of the works published on this topic relates to tropical/subtropical regions, where crop dynamics is more complicated and difficult to model than in temperate regions. A major hindrance has been the lack of accurate public databases for the comparison of different classification methods. In this context, the aim of the present paper is to share a multi-temporal and multi-sensor benchmark database that can be used by the remote sensing community for agricultural land-cover mapping. Information about crops in situ was collected in Luís Eduardo Magalhães (LEM) municipality, which is an important Brazilian agricultural area, to create field reference data including information about first and second crop harvests. Moreover, a series of remote sensing images was acquired and pre-processed, from both active and passive orbital sensors (Sentinel-1, Sentinel-2/MSI, Landsat-8/OLI), correspondent to the LEM area, along the development of the main annual crops. In this paper, we describe the LEM database (crop field boundaries, land use reference data and pre-processed images) and present the results of an experiment conducted using the Sentinel-1 and Sentinel-2 data