A numerical methodology for the multi-objective optimization of the DI Diesel engine combustion

DI Diesel engine are widely used both for industrial and automotive applications due to their durability and fuel economy. Nonetheless, increasing environmental concerns force that type of engine to comply with increasingly demanding emission limits, so that, it has become mandatory to develop a robust design methodology of the DI Diesel combustion system focused on reduction of soot and NOx simultaneously while maintaining a reasonable fuel economy. In recent years, genetic algorithms and CFD three-dimensional combustion simulations have been successfully applied to that kind of problem. However, combining GAs optimization with actual CFD three-dimensional combustion simulations can be too onerous since a large number of calculations is usually needed for the genetic algorithm to converge, resulting in a high computational cost and, thus, limiting the suitability of this method for industrial processes. In order to make the optimization process less time-consuming, CFD simulations can be more conveniently used to generate a training set for the learning process of an artificial neural network which, once correctly trained, can be used to forecast the engine outputs as a function of the design parameters during a GA optimization performing a so-called virtual optimization. In the current work, a numerical methodology for the multi-objective virtual optimization of the combustion of an automotive DI Diesel engine, which relies on artificial neural networks and genetic algorithms, was developed.

Study of the genes involved in Naphthenic acids (NAs) degradation by Rhodococcus spp.

Naphthenic acids (NAs) are an important group of organic pollutants mainly found in hydrocarbon deposits. Although these compounds are toxic, recalcitrant, and persistent in the environment, we are just learning the diversity of microbial communities involved in NAs- degradation and the mechanisms by which NAs are biodegraded. Studies have shown that naphthenic acids are susceptible to biodegradation, which decreases their concentration and reduces toxicity. Nevertheless, little is still known about their biodegradability. The present PhD Thesis’s work is aimed to study the biodegradation of simple model NAs using bacteria strains belonging to the Rhodococcus genus. In particular, Rh. sp. BCP1 and Rh. opacus R7 were able to utilize NAs such as cyclohexane carboxylic acid and cyclopentane carboxylic acid as the sole carbon and energy sources, even at concentrations up to 1000 mg/L. The presence of either substituents or longer carboxylic acid chains attached to the cyclohexane ring negatively affected the growth by pure bacterial cultures. Moreover, BCP1 and R7 cells incubated in the presence of CHCA or CPCA show a general increase of saturated and methyl-substituted fatty acids in their membrane, while the cis-mono-unsaturated ones decrease, as compared to glucose-grown cells. The observed lipid molecules modification during the growth in the presence of NAs is suggested as a possible mechanism to decrease the fluidity of the cell membrane to counteract NAs toxicity. In order to further evaluate this toxic effect on cell features, the morphological changes of BCP1 and R7 cells were also assessed through Transmission Electron Microscopy (TEM), revealing interesting ultrastructural changes. The induction of putative genes, and the construction of a random transposon mutagenesis library were also carried out to reveal the mechanisms by which these Rhodococcus strains can degrade toxic compounds such as NAs.

Inhibition of the kynurenine-NAD+ pathway leads to energy failure and exacerbates apoptosis in pneumococcal meningitis

Pneumococcal meningitis causes neurological sequelae, including learning and memory deficits in up to half of the survivors. In both humans and in animal models of the disease, there is apoptotic cell death in the hippocampus, a brain region involved in learning and memory function. We previously demonstrated that in an infant rat model of pneumococcal meningitis, there is activation of the kynurenine (KYN) pathway in the hippocampus, and that there was a positive correlation between the concentration of 3-hydroxykynurenine and the extent of hippocampal apoptosis. To clarify the role of the KYN pathway in the pathogenesis of hippocampal apoptosis in pneumococcal meningitis, we specifically inhibited 2 key enzymes of the KYN pathway and assessed hippocampal apoptosis, KYN pathway metabolites, and nicotinamide adenine dinucleotide (NAD) concentrations by high-performance liquid chromatography. Pharmacological inhibition of kynurenine 3-hydroxylase and kynureninase led to decreased cellular NAD levels and increased apoptosis in the hippocampus. The cerebrospinal fluid levels of tumor necrosis factor and interleukin-1? and -? were not affected. Our data suggest that activation of the KYN pathway in pneumococcal meningitis is neuroprotective by compensating for an increased NAD demand caused by infection and inflammation;this mechanism may prevent energy failure and apoptosis in the hippocampus.

Synaptic regulation of spike firing in interneurons of the striatum in vivo

The striatum, the major input nucleus of the basal ganglia, is numerically dominated by a single class of principal neurons, the GABAergic spiny projection neuron (SPN) that has been extensively studied both in vitro and in vivo. Much less is known about the sparsely distributed interneurons, principally the cholinergic interneuron (CIN) and the GABAergic fast-spiking interneuron (FSI). Here, we summarize results from two recent studies on these interneurons where we used in vivo intracellular recording techniques in urethane-anaesthetized rats (Schulz et al., J Neurosci 31[31], 2011; J Physiol, in press). Interneurons were identified by their characteristic responses to intracellular current steps and spike waveforms. Spontaneous spiking contained a high proportion (~45%) of short inter-spike intervals (ISI) of <30 ms in FSIs, but virtually none in CINs. Spiking patterns in CINs covered a broad spectrum ranging from regular tonic spiking to phasic activity despite very similar unimodal membrane potential distributions across neurons. In general, phasic spiking activity occurred in phase with the slow ECoG waves, whereas CINs exhibiting tonic regular spiking were little affected by afferent network activity. In contrast, FSIs exhibited transitions between Down and Up states very similar to SPNs. Compared to SPNs, the FSI Up state membrane potential was noisier and power spectra exhibited significantly larger power at frequencies in the gamma range (55-95 Hz). Cortical-evoked inputs had faster dynamics in FSIs than SPNs and the membrane potential preceding spontaneous spike discharge exhibited short and steep trajectories, suggesting that fast input components controlled spike output in FSIs. Intrinsic resonance mechanisms may have further enhanced the sensitivity of FSIs to fast oscillatory inputs. Induction of an activated ECoG state by local ejection of bicuculline into the superior colliculus, resulted in increased spike frequency in both interneuron classes without changing the overall distribution of ISIs. This manipulation also made CINs responsive to a light flashed into the contralateral eye. Typically, the response consisted of an excitation at short latency followed by a pause in spike firing, via an underlying depolarization-hyperpolarization membrane sequence. These results highlight the differential sensitivity of striatal interneurons to afferent synaptic signals and support a model where CINs modulate the striatal network in response to salient sensory bottom-up signals, while FSIs serve gating of top-down signals from the cortex during action selection and reward-related learning.

The Effects of Altered Prenatal Melatonin Signaling on Adult Behavior and Hippocampal Gene Expression of the Male Rat: A Circadioneuroendocrine-Axis Hypothesis of Psychopathology

Disturbances in melatonin - the neurohormone that signals environmental darkness as part of the circadian circuit of mammals - have been implicated in various psychopathologies in humans. At present, experimental evidence linking prenatal melatonin signaling to adult physiology, behavior, and gene expression is lacking. We hypothesized that administration of melatonin (5 mg/kg) or the melatonin receptor antagonist luzindole (5 mg/kg) to rats in utero would permanently alter the circadian circuit to produce differential growth, adult behavior, and hippocampal gene expressionin the male rat. Prenatal treatment was found to increase growth in melatonin-treated animals. In addition, subjects exposed to melatonin prenatally displayed increased rearing in the open field test and an increased right turn preference in the elevated plusmaze. Rats administered luzindole prenatally, however, displayed greater freezing and grooming behavior in the open field test and improved learning in the Morris water maze. Analysis of relative adult hippocampal gene expression with RT-PCR revealed increasedexpression of brain-derived neurotrophic factor (BDNF) with a trend toward increased expression of melatonin 1A (MEL1A) receptors in melatonin-exposed animals whereas overall prenatal treatment had a significant effect on microtubule-associated protein 2(MAP2) expression. Our data support the conclusion that the manipulation of maternal melatonin levels alters brain development and leads to physiological and behavioral abnormalities in adult offspring. We designate the term circadioneuroendocrine (CNE)axis and propose the CNE-axis hypothesis of psychopathology.

Metabolomics reveals attenuation of the SLC6A20 kidney transporter in nonhuman primate and mouse models of type 2 diabetes mellitus

To enhance understanding of the metabolic indicators of type 2 diabetes mellitus (T2DM) disease pathogenesis and progression, the urinary metabolomes of well characterized rhesus macaques (normal or spontaneously and naturally diabetic) were examined. High-resolution ultra-performance liquid chromatography coupled with the accurate mass determination of time-of-flight mass spectrometry was used to analyze spot urine samples from normal (n = 10) and T2DM (n = 11) male monkeys. The machine-learning algorithm random forests classified urine samples as either from normal or T2DM monkeys. The metabolites important for developing the classifier were further examined for their biological significance. Random forests models had a misclassification error of less than 5%. Metabolites were identified based on accurate masses (<10 ppm) and confirmed by tandem mass spectrometry of authentic compounds. Urinary compounds significantly increased (p < 0.05) in the T2DM when compared with the normal group included glycine betaine (9-fold), citric acid (2.8-fold), kynurenic acid (1.8-fold), glucose (68-fold), and pipecolic acid (6.5-fold). When compared with the conventional definition of T2DM, the metabolites were also useful in defining the T2DM condition, and the urinary elevations in glycine betaine and pipecolic acid (as well as proline) indicated defective re-absorption in the kidney proximal tubules by SLC6A20, a Na(+)-dependent transporter. The mRNA levels of SLC6A20 were significantly reduced in the kidneys of monkeys with T2DM. These observations were validated in the db/db mouse model of T2DM. This study provides convincing evidence of the power of metabolomics for identifying functional changes at many levels in the omics pipeline.

Spike-based decision learning of nash equilibria in two-player games

Humans and animals face decision tasks in an uncertain multi-agent environment where an agent's strategy may change in time due to the co-adaptation of others strategies. The neuronal substrate and the computational algorithms underlying such adaptive decision making, however, is largely unknown. We propose a population coding model of spiking neurons with a policy gradient procedure that successfully acquires optimal strategies for classical game-theoretical tasks. The suggested population reinforcement learning reproduces data from human behavioral experiments for the blackjack and the inspector game. It performs optimally according to a pure (deterministic) and mixed (stochastic) Nash equilibrium, respectively. In contrast, temporal-difference(TD)-learning, covariance-learning, and basic reinforcement learning fail to perform optimally for the stochastic strategy. Spike-based population reinforcement learning, shown to follow the stochastic reward gradient, is therefore a viable candidate to explain automated decision learning of a Nash equilibrium in two-player games.

The Clearing Storm: A Re-Assessment of the Climate for Collaboration between Academic and Student Affairs

There is increasing recognition among those in higher education that it is no longer adequate to train students in a specific field or industry. Instead, the push is more towards producing well-rounded students. In order to do so, all of a university’s resources must come together and the climate on campus must be one that supportscollaboration. This report is a re-examination of the climate for collaboration on the campus of a private liberal arts university in the Mid-Atlantic region of the United States. It is a follow up to a similar investigation conducted on the same campus by Victor Arcelus(2008) five years earlier. In the interim, the university had re-configured its organizational structure, combining separate academic and student affairs divisions into a single unit overseen by the Provost. Additionally, the university had experienced turnover in several key leadership positions, including those of the President and the chief academic and student affairs officers. The purpose of this investigation, therefore, was to gauge the immediate impact of these changes on conditions for collaboration, which when present, advance student learning and development. Through interviews with six men and women, information was collected on the perceived climate for collaboration between academic and student affairs personnel.Analysis of the interview transcripts revealed that, depending on the position of the interviewee within the university, conditions on campus were seen as either improved or largely unchanged as a result of the transition in leadership and the structural merger of the two divisions.

AAC&U's Integrative Liberal Learning and the CAS Standards: Advising for a 21st Century Liberal Education

The Association of American Colleges and Universities presented and promoted integrative liberal learning as a collaborative goal that all institutions of higher education must strive to achieve. The similarities between the goals of integrative liberal learning and the Standards for Academic Advising by the Council for the Advancement of Standards in Higher Education are discussed with emphasis placed on the critical role that academic advising plays in support of an integrative liberal learning education, and in turn, future success for all students.

Sentinel lymph node procedure leads to upstaging of patients with resectable colon cancer: results of the Swiss prospective, multicenter study sentinel lymph node procedure in colon cancer

The value of the sentinel lymph node (SLN) procedure in colon cancer patients remains a matter of debate. The objective of this prospective, multicenter trial was 3-fold: to determine the identification rate and accuracy of the SLN procedure in patients with resectable colon cancer; to evaluate the learning curve of the SLN procedure; and to assess the extent of upstaging due to the SLN procedure.

Effects of instructional changes on student learning of electrochemistry in an IB chemistry course

This study investigated the effectiveness of incorporating several new instructional strategies into an International Baccalaureate (IB) chemistry course in terms of how they supported high school seniors’ understanding of electrochemistry. The three new methods used were (a) providing opportunities for visualization of particle movement by student manipulation of physical models and interactive computer simulations, (b) explicitly addressing common misconceptions identified in the literature, and (c) teaching an algorithmic, step-wise approach for determining the products of an aqueous solution electrolysis. Changes in student understanding were assessed through test scores on both internally and externally administered exams over a two-year period. It was found that visualization practice and explicit misconception instruction improved student understanding, but the effect was more apparent in the short-term. The data suggested that instruction time spent on algorithm practice was insufficient to cause significant test score improvement. There was, however, a substantial increase in the percentage of the experimental group students who chose to answer an optional electrochemistry-related external exam question, indicating an increase in student confidence. Implications for future instruction are discussed.

Virtual reality ultrasound imaging of the normal and abnormal fetal central nervous system

OBJECTIVES: In fetal ultrasound imaging, teaching and experience are of paramount importance to improve prenatal detection rates of fetal abnormalities. Yet both aspects depend on exposure to normal and, in particular, abnormal 'specimens'. We aimed to generate a number of simple virtual reality (VR) objects of the fetal central nervous system for use as educational tools. METHODS: We applied a recently proposed algorithm for the generation of fetal VR object movies to the normal and abnormal fetal brain and spine. Interactive VR object movies were generated from ultrasound volume data from normal fetuses and fetuses with typical brain or spine anomalies. Pathognomonic still images from all object movies were selected and annotated to enable recognition of these features in the object movies. RESULTS: Forty-six virtual reality object movies from 22 fetuses (two with normal and 20 with abnormal brains) were generated in an interactive display format (QuickTime) and key images were annotated. The resulting .mov files are available for download from the website of this journal. CONCLUSIONS: VR object movies can be generated from educational ultrasound volume datasets, and may prove useful for teaching and learning normal and abnormal fetal anatomy.

Education and Ideologies of the Knowledge Economy: Europe and the Politics of Emulation

The Austrian philosopher Ludwig Wittgenstein famously proposed a style of philosophy that was directed against certain pictures [bild] that tacitly direct our language and forms of life. His aim was to show the fly the way out of the fly bottle and to fight against the bewitchment of our intelligence by means of language: “A picture held us captive. And we could not get outside it, for it lay in our language and language seemed to repeat it to us inexorably” (Wittgenstein 1953, 115). In this context Wittgenstein is talking of philosophical pictures, deep metaphors that have structured our language but he does also use the term picture in other contexts (see Owen 2003, 83). I want to appeal to Wittgenstein in my use of the term ideology to refer to the way in which powerful underlying metaphors in neoclassical economics have a strong rhetorical and constitutive force at the level of public policy. Indeed, I am specifically speaking of the notion of ‘the performative’ in Wittgenstein and Austin. The notion of the knowledge economy has a prehistory in Hayek (1937; 1945) who founded the economics of knowledge in the 1930s, in Machlup (1962; 1970), who mapped the emerging employment shift to the US service economy in the early 1960s, and to sociologists Bell (1973) and Touraine (1974) who began to tease out the consequences of these changes for social structure in the post-industrial society in the early 1970s. The term has been taken up since by economists, sociologists, futurists and policy experts recently to explain the transition to the so-called ‘new economy’. It is not just a matter of noting these discursive strands in the genealogy of the ‘knowledge economy’ and related or cognate terms. We can also make a number of observations on the basis of this brief analysis. First, there has been a succession of terms like ‘postindustrial economy’, ‘information economy’, ‘knowledge economy’, ‘learning economy’, each with a set of related concepts emphasising its social, political, management or educational aspects. Often these literatures are not cross-threading and tend to focus on only one aspect of phenomena leading to classic dichotomies such as that between economy and society, knowledge and information. Second, these terms and their family concepts are discursive, historical and ideological products in the sense that they create their own meanings and often lead to constitutive effects at the level of policy. Third, while there is some empirical evidence to support claims concerning these terms, at the level of public policy these claims are empirically underdetermined and contain an integrating, visionary or futures component, which necessarily remains untested and is, perhaps, in principle untestable.