The Next Generation of High-Speed Dynamic Stability Wind Tunnel Testing (Invited)

Throughout industry, accurate measurement and modeling of dynamic derivative data at high-speed conditions has been an ongoing challenge. The expansion of flight envelopes and non-conventional vehicle design has greatly increased the demand for accurate prediction and modeling of vehicle dynamic behavior. With these issues in mind, NASA Langley Research Center (LaRC) embarked on the development and shakedown of a high-speed dynamic stability test technique that addresses the longstanding problem of accurately measuring dynamic derivatives outside the low-speed regime. The new test technique was built upon legacy technology, replacing an antiquated forced oscillation system, and greatly expanding the capabilities beyond classic forced oscillation testing at both low and high speeds. The modern system is capable of providing a snapshot of dynamic behavior over a periodic cycle for varying frequencies, not just a damping derivative term at a single frequency

Space Launch System Liftoff and Transition Aerodynamic Characterization in the NASA Langley 14- by 22-Foot Subsonic Wind Tunnel

A 1.75% scale force and moment model of the Space Launch System was tested in the NASA Langley Research Center 14- by 22-Foot Subsonic Wind Tunnel to quantify the aerodynamic forces that will be experienced by the launch vehicle during its liftoff and transition to ascent flight. The test consisted of two parts: the first was dedicated to measuring forces and moments for the entire range of angles of attack (0deg to 90deg) and roll angles (0 deg. to 360 deg.). The second was designed to measure the aerodynamic effects of the liftoff tower on the launch vehicle for ground winds from all azimuthal directions (0 deg. to 360 deg.), and vehicle liftoff height ratios from 0 to 0.94. This wind tunnel model also included a set of 154 surface static pressure ports. Details on the experimental setup, and results from both parts of testing are presented, along with a description of how the wind tunnel data was analyzed and post-processed in order to develop an aerodynamic database. Finally, lessons learned from experiencing significant dynamics in the mid-range angles of attack due to steady asymmetric vortex shedding are presented

Preceding rule induction with instance reduction methods

A new prepruning technique for rule induction is presented which applies instance reduction before rule induction. An empirical evaluation records the predictive accuracy and size of rule-sets generated from 24 datasets from the UCI Machine Learning Repository. Three instance reduction algorithms (Edited Nearest Neighbour, AllKnn and DROP5) are compared. Each one is used to reduce the size of the training set, prior to inducing a set of rules using Clark and Boswell's modification of CN2. A hybrid instance reduction algorithm (comprised of AllKnn and DROP5) is also tested. For most of the datasets, pruning the training set using ENN, AllKnn or the hybrid significantly reduces the number of rules generated by CN2, without adversely affecting the predictive performance. The hybrid achieves the highest average predictive accuracy

Empirical Evaluation of the Difficulty of Finding a Good Value of k for the Nearest Neighbor

As an analysis of the classification accuracy bound for the Nearest Neighbor technique, in this work we have studied if it is possible to find a good value of the parmeter k for each example according to their attribute values. Or at least, if there is a pattern for the parameter k in the original search space. We have carried out different approaches based onthe Nearest Neighbor technique and calculated the prediction accuracy for a group of databases from the UCI repository. Based on the experimental results of our study, we can state that, in general, it is not possible to know a priori a specific value of k to correctly classify an unseen example

Space Launch System Ascent Static Aerodynamic Database Development

This paper describes the wind tunnel testing work and data analysis required to characterize the static aerodynamic environment of NASA's Space Launch System (SLS) ascent portion of flight. Scaled models of the SLS have been tested in transonic and supersonic wind tunnels to gather the high fidelity data that is used to build aerodynamic databases. A detailed description of the wind tunnel test that was conducted to produce the latest version of the database is presented, and a representative set of aerodynamic data is shown. The wind tunnel data quality remains very high, however some concerns with wall interference effects through transonic Mach numbers are also discussed. Post-processing and analysis of the wind tunnel dataset are crucial for the development of a formal ascent aerodynamics database

On Optimizing Locally Linear Nearest Neighbour Reconstructions Using Prototype Reduction Schemes

This paper concerns the use of Prototype Reduction Schemes (PRS) to optimize the computations involved in typical k-Nearest Neighbor (k-NN) rules. These rules have been successfully used for decades in statistical Pattern Recognition (PR) applications, and have numerous applications because of their known error bounds. For a given data point of unknown identity, the k-NN possesses the phenomenon that it combines the information about the samples from a priori target classes (values) of selected neighbors to, for example, predict the target class of the tested sample. Recently, an implementation of the k-NN, named as the Locally Linear Reconstruction (LLR) [11], has been proposed. The salient feature of the latter is that by invoking a quadratic optimization process, it is capable of systematically setting model parameters, such as the number of neighbors (specified by the parameter, k) and the weights. However, the LLR takes more time than other conventional methods when it has to be applied to classification tasks. To overcome this problem, we propose a strategy of using a PRS to efficiently compute the optimization problem. In this paper, we demonstrate, first of all, that by completely discarding the points not included by the PRS, we can obtain a reduced set of sample points, using which, in turn, the quadratic optimization problem can be computed far more expediently. The values of the corresponding indices are comparable to those obtained with the original training set (i.e., the one which considers all the data points) even though the computations required to obtain the prototypes and the corresponding classification accuracies are noticeably less. The proposed method has been tested on artificial and real-life data sets, and the results obtained are very promising, and has potential in PR applications

Human Lifespan: To Live and Outlive 100 Years?

Starenje populacije je dominantno demografsko obilježje razvijenih zemalja. Stogodišnjaci su selekcionirana skupina i samo jedna od 7.000 do 10.000 osoba dosegne tu dob. Čimbenici dugovječnosti vjerojatno su brojni i uključuju gensko predodređenje (lokus na 4. kromosomu), zdrav okoliš i zdrave životne navike (prehrana s malo kalorija), redovita tjelesna i psihička aktivnost, kao i dostupnost te učinkovitost zdravstvene zaštite s primjenom geroprofi lakse. Stogodišnjaci se adaptiraju na novi život i na gubitak tjelesnih funkcija koji bivaju postupno sve izraženiji kako se dob povisuje. Granice ljudskog života produžuju se - do sada najstarija poznata osoba doživjela je 128 godina. Pojedina zemljopisna područja bilježe izrazito veći broj stogodišnjaka. Navedene su i neke dugovječne osobe s više od 100 godina u svijetu i na području Republike Hrvatske i nekih susjednih zemalja. Iako se uglavnom smatra da se granica trajanja života čovjeka ne može produžiti iznad 120 godina, za sada je ipak teško predvidjeti gdje su njezine granice.Aged population dominates in developed countries. Centenarians are a select group, and only one in 7,000 to 10,000 reach that age. Factors of longevity are numerous and include genetic predisposition (a locus on chromosome 4), environment, healthy lifestyle (hypocaloric diet, regular physical and mental exercise), accessible health services, and effi cient health protection at old age. Centenarians are well adapted to the new life and compensate for the loss of functions with age. The limits of human life are extended, so that nowadays the oldest person has reached the age of 128. Some geographic areas are characterised by higher numbers of centenarians. This article mentions a few individuals who outlived 100 years in the world, Croatia, and neighbouring countries. Although some argue that the limits of human life cannot be extended over the age of 120 years, for now we cannot predict the actual limits of human life

α-Tocopheryl succinate and TRAIL selectively synergise in induction of apoptosis in human malignant mesothelioma cells

Malignant mesothelioma (MM) is a fatal type of neoplasia with poor therapeutic prognosis, largely due to resistance to apoptosis. We investigated the apoptotic effect of alpha-tocopheryl succinate (alpha-TOS), a strong proapoptotic agent, in combination with the immunological apoptogen TNF-related apoptosis-inducing ligand (TRAIL) on both MM and nonmalignant mesothelial cells, since MM cells show low susceptibility to the clinically intriguing TRAIL. All MM cell lines tested were sensitive to alpha-TOS-induced apoptosis, and exerted high sensitivity to TRAIL in the presence of subapoptotic doses of the vitamin E analogue. Neither TRAIL or alpha-TOS alone or in combination caused apoptosis in nonmalignant mesothelial cells. Isobologram analysis of the cytotoxicity assays revealed a synergistic interaction between the two agents in MM cells and their antagonistic effect in nonmalignant mesothelial cells. TRAIL-induced apoptosis and its augmentation by alpha-TOS were inhibited by the caspase-8 inhibitor Z-IETD-FMK and the pan-caspase inhibitor Z-VAD-FMK. Activation of caspase-8 was required to induce apoptosis, which was amplified by alpha-TOS via cytochrome c release following Bid cleavage, with ensuing activation of caspase-9. Enhancement of TRAIL-induced apoptosis in MM cells by alpha-TOS was also associated with upregulation of the TRAIL cognate death receptors DR4 and DR5. Our results show that alpha-TOS and TRAIL act in synergism to kill MM cells via mitochondrial pathway, and are nontoxic to nonmalignant mesothelial cells. These findings are indicative of a novel strategy for treatment of thus far fatal MM

Generic pregabalin : current situation and implications for health authorities, generics and biosimilars manufacturers in the future

The manufacturer of pregabalin has a second use patent covering prescribing for neuropathic pain: its principal indication. The manufacturer has threatened legal action in the UK if generic pregabalin rather than Lyrica is prescribed for this indication. No problems exist for practitioners who prescribe pregabalin for epilepsy or generalized anxiety disorder. This has serious implications for health authorities. In Germany, however, generics could be legally prescribed for any approved indication once one indication loses its patent. We aim to establish the current situation with pregabalin among principally European countries. Personnel from 33 regional and national health authorities mainly from Europe, and nine from universities across Europe working as advisers to health authorities or with insight into their activities, were surveyed regarding four specific questions via email to shed light on the current situation with Lyrica and pregabalin in their country. The information collated from each country was subsequently checked for accuracy with each co-author by email and face-to-face contact and collated into five tables. The scenarios ranged from extending the patent life of Lyrica (e.g. France), endorsing the prescribing of Lyrica for neuropathic pain (e.g. Catalonia and South Korea), and current prescribing of pregabablin for all indications (e.g. Serbia and Germany). Little activity has taken place in European countries in which generic pregabalin is not yet reimbursed. The availability of generic pregabalin has prompted a number of different activities to be undertaken among the 33 countries and regions surveyed. The situation in Serbia and the historic situation in Germany provide examples of ways to maximize savings once a product loses its patent for at least one indication

Big-Data Science in Porous Materials: Materials Genomics and Machine Learning

By combining metal nodes with organic linkers we can potentially synthesize millions of possible metal organic frameworks (MOFs). At present, we have libraries of over ten thousand synthesized materials and millions of in-silico predicted materials. The fact that we have so many materials opens many exciting avenues to tailor make a material that is optimal for a given application. However, from an experimental and computational point of view we simply have too many materials to screen using brute-force techniques. In this review, we show that having so many materials allows us to use big-data methods as a powerful technique to study these materials and to discover complex correlations. The first part of the review gives an introduction to the principles of big-data science. We emphasize the importance of data collection, methods to augment small data sets, how to select appropriate training sets. An important part of this review are the different approaches that are used to represent these materials in feature space. The review also includes a general overview of the different ML techniques, but as most applications in porous materials use supervised ML our review is focused on the different approaches for supervised ML. In particular, we review the different method to optimize the ML process and how to quantify the performance of the different methods. In the second part, we review how the different approaches of ML have been applied to porous materials. In particular, we discuss applications in the field of gas storage and separation, the stability of these materials, their electronic properties, and their synthesis. The range of topics illustrates the large variety of topics that can be studied with big-data science. Given the increasing interest of the scientific community in ML, we expect this list to rapidly expand in the coming years.Comment: Editorial changes (typos fixed, minor adjustments to figures