Augmented Reality Simulation Modules for EVD Placement Training and Planning Aids

When a novice neurosurgeon performs a psychomotor surgical task (e.g., tool navigation into brain structures), a potential risk of damaging healthy tissues and eloquent brain structures is unavoidable. When novices make multiple hits, thus a set of undesirable trajectories is created, and resulting in the potential for surgical complications. Thus, it is important that novices not only aim for a high-level of surgical mastery but also receive deliberate training in common neurosurgical procedures and underlying tasks. Surgical simulators have emerged as an adequate candidate as effective method to teach novices in safe and free-error training environments. The design of neurosurgical simulators requires a comprehensive approach to development and. In that in mind, we demonstrate a detailed case study in which two Augmented Reality (AR) training simulation modules were designed and implemented through the adoption of Model-driven Engineering. User performance evaluation is a key aspect of the surgical simulation validity. Many AR surgical simulators become obsolete; either they are not sufficient to support enough surgical scenarios, or they were validated according to subjective assessments that did not meet every need. Accordingly, we demonstrate the feasibility of the AR simulation modules through two user studies, objectively measuring novices’ performance based on quantitative metrics. Neurosurgical simulators are prone to perceptual distance underestimation. Few investigations were conducted for improving user depth perception in head-mounted display-based AR systems with perceptual motion cues. Consequently, we report our investigation’s results about whether or not head motion and perception motion cues had an influence on users’ performance

Does NICU Intervention Improve Survivability in Consanguineous Trisomy 13?

Patau Syndrome is a fatal autosomal trisomy ,usually seen because of Meiotic nondisjunction due to maternal advanced age. It is observed at a higher frequency in non-consanguineous union.Trisomy has a prevalence of : 2,000– : 29,000 in newborns. ,Also known as Patau Syndrome, it is a rare and lethal autosomal trisomy 3 with a survivability of only 7- 0 days.Only an estimated 9% to 4% of live births survive beyond year of life and are associated with mosaicism. Severity of associated malformations also plays a key role in prognosis and survival.It presents with a wide array of dysmorphic features including microphthalmia, cutis aplasia, polydactyly, cleft lip, cleft palate, various congenital heart disease, omphalocele, holoprosencephaly and urogenital abnormalities. There is an intense discussion as to whether timely NICU interventions do play a role in improving mortality in the neonate and long term better prognosis and survivability as a result , especially in VLBW(Very Low Birth Weight) infants. There is a higher reporting frequency of Trisomy’s in non-consanguineous marriages one example of which is Down Syndrome. Currently diagnosis is based on increasing maternal age, sonographic findings, serum markers and amniocentesis followed in many cases by pregnancy termination as in the West. Risk increases with increasing maternal age with an average of age of 3 years

Evaluation patterns and algorithm for cancer identifications using dynamic clustering

The domain of knowledge discovery and deep data extraction is quite prominent and used in assorted domains including engineering, mathematics and even in medical diagnosis. A number of benchmark datasets are available in which huge research work is going on with the enormous aspects of genomics that is associated with the medical data analytics. In this research manuscript, the work presents the evaluation patterns and the approaches which are used for the cancer identification with the use of dynamic clustering and deep data analytics. The work is having the elements with the medical datasets and their key features by which the training of data in the data mining algorithm can be integrated and then the overall predictions can be done on assorted parameters

Carbon assimilation and phytoplankton growth rates across the trophic spectrum: an application of the chlorophyll labelling technique

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Carbon assimilation and phytoplankton growth rates across the trophic spectrum: an application of the chlorophyll labelling technique

The chlorophyll labelling technique has been acknowledged to be a useful method for measuring phytoplankton growth rates while avoiding some of the problems involved in calculating growth rates derived from the 14C fixation rates. The results presented here are of experiments comparing phytoplankton growth rates during the summer season in three subalpine Italian lakes: Lago Maggiore, the second largest lake in Italy, and two smaller lakes, Lake Mergozzo and Lake Varese, both included in the Lago Maggiore drainage basin. The three lakes have different morphometric, physico-chemical and biological features. The first goal was to compare two different methods of estimating phytoplankton growth rates starting from 14C assimilation. The second goal of our experiments was to test the hypothesis that growth rates can be quite different across the trophic spectrum, due to the ecophysiological and morphological features of the phytoplankton assemblages. In particular, algal cell size should decrease from eutrophic to oligotrophic systems and growth rates should follow the opposite trend, as they are inversely scaled to the cell size. Two basic conclusions can be drawn. The first is that, in spite of some drawbacks still affecting the use of the chlorophyll labelling technique, this appears to be one of the most promising methods for estimating the growth rates of phytoplankton in situ. The second conclusion is that this method, coupled with information on some algal morphological parameters, can provide useful indications about the functional properties of phytoplankton assemblages living in diverse lacustrine environments

Redox Regulation of Heart Regeneration: An Evolutionary Tradeoff

Heart failure is a costly and deadly disease, affecting over 23 million patients worldwide, half of which die within 5 years of diagnosis. The pathophysiological basis of heart failure is the inability of the adult heart to regenerate lost or damaged myocardium. Although limited myocyte turnover does occur in the adult heart, it is insufficient for restoration of contractile function1-6. In contrast to lower vertebrates which can regenerate their myocardium through cardiomyocyte proliferation,7-13, adult mammalian heart cardiomyogenesis very limited1-5. Studies in the late 90s elegantly demonstrated that mammalian cardiomyocytes continue to divide for a few days after birth 14-16, only to undergo permanent cell cycle arrest shortly thereafter. Recently, we demonstrated that resection of up to 15% of the apex of the left ventricle of postnatal day 1 (P1) mice results in complete regeneration within 21 days following injury, without significant fibrosis and cardiac dysfunction17. Moreover, we described a similar regenerative response following ischemic myocardial infarction 18. This response was well characterized by robust cardiomyocyte proliferation, with gradual restoration of normal cardiac morphology and function. In addition to the histological evidence of proliferating myocytes, genetic fate-mapping studies confirmed that the majority of newly formed cardiomyocytes are derived from proliferation of preexisting cardiomyocytes17. Intriguingly, this regenerative capacity is lost by P7, after which injury results in the cardiomyocyte hypertrophy and scar-formation, which coincides with binucleation and cell cycle exit of cardiomyocytes 14, 19. An important approach to understanding the loss of regenerative ability of the mammalian heart is to first consider why, and not only how, this happens. The regenerative ability of the early postnatal heart following resection or ischemic infarction involves regeneration of the lost myocardium and vasculature with restoration of normal myocardial thickness and architecture, and long-term functional recovery. Why would the heart permanently forego such a remarkable regenerative program shortly after birth? The answer may lie in within the fundamental principal of evolutionary tradeoff

Acceptance rates and beliefs toward COVID-19 vaccination among the general population of Pakistan: A cross-sectional survey

Developing countries like Pakistan have previously suffered from barriers to acceptance of vaccination by the public because of financial and belief barriers. This study aims to explore these beliefs and highlight concerns regarding vaccine hesitancy in the general population of Pakistan since they are a hindrance to an effective coronavirus disease-19 (COVID-19) immunization in the country. A cross-sectional study was performed involving 1,778 participants from all four provinces of Pakistan. Results from the study showed more than half of the participants to be unsure of the safety (50%) and efficacy (51%) of the vaccine, whereas 42% were concerned about the side effects of the vaccine. About 72% of the respondents planned to get vaccinated, whereas 28% refused to do so. Internationally made imported vaccines were more trusted by the participants. Forty-four percent of the participants agreed to receive the vaccine upon recommendation from a physician. Lastly, participants who believed in the efficacy of the polio vaccination also considered the COVID-19 vaccine to be safe and effective

Wavelet Neural Networks for Speed Control of BLDC Motor

In the recent years, researchers have sophisticated the synthesis of neural networks depending on the wavelet functions to build the wavelet neural networks (WNNs), where the wavelet function is utilized in the hidden layer as a sigmoid function instead of conventional sigmoid function that is utilized in artificial neural network. The WNN inherits the features of the wavelet function and the neural network (NN), such as self-learning, self-adapting, time-frequency location, robustness, and nonlinearity. Besides, the wavelet function theory guarantees that the WNN can simulate the nonlinear system precisely and rapidly. In this chapter, the WNN is used with PID controller to make a developed controller named WNN-PID controller. This controller will be utilized to control the speed of Brushless DC (BLDC) motor to get preferable performance than the traditional controller techniques. Besides, the particle swarm optimization (PSO) algorithm is utilized to optimize the parameters of the WNN-PID controller. The modification for this method of the WNN such as the recurrent wavelet neural network (RWNN) was included in this chapter. Simulation results for all the above methods are given and compared