Pore structure and column efficiency of silica monoliths in high performance liquid chromatography (HPLC)

Five different methods were critically examined to characterize the pore structure of the silica monoliths. The mesopore characterization was performed using: a) the classical BJH method of nitrogen sorption data, which showed overestimated values in the mesopore distribution and was improved by using the NLDFT method, b) the ISEC method implementing the PPM and PNM models, which were especially developed for monolithic silicas, that contrary to the particulate supports, demonstrate the two inflection points in the ISEC curve, enabling the calculation of pore connectivity, a measure for the mass transfer kinetics in the mesopore network, c) the mercury porosimetry using a new recommended mercury contact angle values. rnThe results of the characterization of mesopores of monolithic silica columns by the three methods indicated that all methods were useful with respect to the pore size distribution by volume, but only the ISEC method with implemented PPM and PNM models gave the average pore size and distribution based on the number average and the pore connectivity values.rnThe characterization of the flow-through pore was performed by two different methods: a) the mercury porosimetry, which was used not only for average flow-through pore value estimation, but also the assessment of entrapment. It was found that the mass transfer from the flow-through pores to mesopores was not hindered in case of small sized flow-through pores with a narrow distribution, b) the liquid penetration where the average flow-through pore values were obtained via existing equations and improved by the additional methods developed according to Hagen-Poiseuille rules. The result was that not the flow-through pore size influences the column bock pressure, but the surface area to volume ratio of silica skeleton is most decisive. Thus the monolith with lowest ratio values will be the most permeable. rnThe flow-through pore characterization results obtained by mercury porosimetry and liquid permeability were compared with the ones from imaging and image analysis. All named methods enable a reliable characterization of the flow-through pore diameters for the monolithic silica columns, but special care should be taken about the chosen theoretical model.rnThe measured pore characterization parameters were then linked with the mass transfer properties of monolithic silica columns. As indicated by the ISEC results, no restrictions in mass transfer resistance were noticed in mesopores due to their high connectivity. The mercury porosimetry results also gave evidence that no restrictions occur for mass transfer from flow-through pores to mesopores in the small scaled silica monoliths with narrow distribution. rnThe prediction of the optimum regimes of the pore structural parameters for the given target parameters in HPLC separations was performed. It was found that a low mass transfer resistance in the mesopore volume is achieved when the nominal diameter of the number average size distribution of the mesopores is appr. an order of magnitude larger that the molecular radius of the analyte. The effective diffusion coefficient of an analyte molecule in the mesopore volume is strongly dependent on the value of the nominal pore diameter of the number averaged pore size distribution. The mesopore size has to be adapted to the molecular size of the analyte, in particular for peptides and proteins. rnThe study on flow-through pores of silica monoliths demonstrated that the surface to volume of the skeletons ratio and external porosity are decisive for the column efficiency. The latter is independent from the flow-through pore diameter. The flow-through pore characteristics by direct and indirect approaches were assessed and theoretical column efficiency curves were derived. The study showed that next to the surface to volume ratio, the total porosity and its distribution of the flow-through pores and mesopores have a substantial effect on the column plate number, especially as the extent of adsorption increases. The column efficiency is increasing with decreasing flow through pore diameter, decreasing with external porosity, and increasing with total porosity. Though this tendency has a limit due to heterogeneity of the studied monolithic samples. We found that the maximum efficiency of the studied monolithic research columns could be reached at a skeleton diameter of ~ 0.5 µm. Furthermore when the intention is to maximize the column efficiency, more homogeneous monoliths should be prepared.rn

Export Supply Chain Organization and Food Safety and Quality Standards: a case study of the Moroccan Fruit and Vegetable Sector

Agri-food supply chains extend beyond national boundaries, partially facilitated by a policy environment that encourages more liberal international trade. Rising concentration within the downstream sector has driven a shift towards “buyer-driven” global value chains (GVCs) extending internationally with global sourcing and the emergence of multinational key economic players that compete with increase emphasis on product quality attributes. Agri-food systems are thus increasingly governed by a range of inter-related public and private standards, both of which are becoming a priori mandatory, especially in supply chains for high-value and quality-differentiated agri-food products and tend to strongly affect upstream agricultural practices, firms’ internal organization and strategic behaviour and to shape the food chain organization. Notably, increasing attention has been given to the impact of SPS measures on agri-food trade and notably on developing countries’ export performance. Food and agricultural trade is the vital link in the mutual dependency of the global trade system and developing countries. Hence, developing countries derive a substantial portion of their income from food and agricultural trade. In Morocco, fruit and vegetable (especially fresh) are the primary agricultural export. Because of the labor intensity, this sector (especially citrus and tomato) is particularly important in terms of income and employment generation, especially for the female laborers hired in the farms and packing houses. Hence, the emergence of agricultural and agrifood product safety issues and the subsequent tightening of market requirements have challenged mutual gains due to the lack of technical and financial capacities of most developing countries.

Fabrication, Electrical Characterization and Simulation of Thin Film Solar Cells: CdTe and CIGS Materials

CdTe and Cu(In,Ga)Se2 (CIGS) thin film solar cells are fabricated, electrically characterized and modelled in this thesis. We start from the fabrication of CdTe thin film devices where the R.F. magnetron sputtering system is used to deposit the CdS/CdTe based solar cells. The chlorine post-growth treatment is modified in order to uniformly cover the cell surface and reduce the probability of pinholes and shunting pathways creation which, in turn, reduces the series resistance. The deionized water etching is proposed, for the first time, as the simplest solution to optimize the effect of shunt resistance, stability and metal-semiconductor inter-diffusion at the back contact. In continue, oxygen incorporation is proposed while CdTe layer deposition. This technique has been rarely examined through R.F sputtering deposition of such devices. The above experiments are characterized electrically and optically by current-voltage characterization, scanning electron microscopy, x-ray diffraction and optical spectroscopy. Furthermore, for the first time, the degradation rate of CdTe devices over time is numerically simulated through AMPS and SCAPS simulators. It is proposed that the instability of electrical parameters is coupled with the material properties and external stresses (bias, temperature and illumination). Then, CIGS materials are simulated and characterized by several techniques such as surface photovoltage spectroscopy is used (as a novel idea) to extract the band gap of graded band gap CIGS layers, surface or bulk defect states. The surface roughness is scanned by atomic force microscopy on nanometre scale to obtain the surface topography of the film. The modified equivalent circuits are proposed and the band gap graded profiles are simulated by AMPS simulator and several graded profiles are examined in order to optimize their thickness, grading strength and electrical parameters. Furthermore, the transport mechanisms and Auger generation phenomenon are modelled in CIGS devices.

Structured antibody surfaces for bio-recognition and a label-free detection of bacteria

Antibody microarrays are of great research interest because of their potential application as biosensors for high-throughput protein and pathogen screening technologies. In this active area, there is still a need for novel structures and assemblies providing insight in binding interactions such as spherical and annulus-shaped protein structures, e.g. for the utilization of curved surfaces for the enhanced protein-protein interactions and detection of antigens. Therefore, the goal of the presented work was to establish a new technique for the label-free detection of bio-molecules and bacteria on topographically structured surfaces, suitable for antibody binding.rnIn the first part of the presented thesis, the fabrication of monolayers of inverse opals with 10 μm diameter and the immobilization of antibodies on their interior surface is described. For this purpose, several established methods for the linking of antibodies to glass, including Schiff bases, EDC/S-NHS chemistry and the biotin-streptavidin affinity system, were tested. The employed methods included immunofluorescence and image analysis by phase contrast microscopy. It could be shown that these methods were not successful in terms of antibody immobilization and adjacent bacteria binding. Hence, a method based on the application of an active-ester-silane was introduced. It showed promising results but also the need for further analysis. Especially the search for alternative antibodies addressing other antigens on the exterior of bacteria will be sought-after in the future.rnAs a consequence of the ability to control antibody-functionalized surfaces, a new technique employing colloidal templating to yield large scale (~cm2) 2D arrays of antibodies against E. coli K12, eGFP and human integrin αvβ3 on a versatile useful glass surface is presented. The antibodies were swept to reside around the templating microspheres during solution drying, and physisorbed on the glass. After removing the microspheres, the formation of annuli-shaped antibody structures was observed. The preserved antibody structure and functionality is shown by binding the specific antigens and secondary antibodies. The improved detection of specific bacteria from a crude solution compared to conventional “flat” antibody surfaces and the setting up of an integrin-binding platform for targeted recognition and surface interactions of eukaryotic cells is demonstrated. The structures were investigated by atomic force, confocal and fluorescence microscopy. Operational parameters like drying time, temperature, humidity and surfactants were optimized to obtain a stable antibody structure.

Vulnerability and robustness indices against blackouts in power grids

In this dissertation some novel indices for vulnerability and robustness assessment of power grids are presented. Such indices are mainly defined from the structure of transmission power grids, and with the aim of Blackout (BO) prevention and mitigation. Numerical experiments showing how they could be used alone or in coordination with pre-existing ones to reduce the effects of BOs are discussed. These indices are introduced inside 3 different sujects: The first subject is for taking a look into economical aspects of grids’ operation and their effects in BO propagation. Basically, simulations support that: the determination to operate the grid in the most profitable way could produce an increase in the size or frequency of BOs. Conversely, some uneconomical ways of supplying energy are shown to be less affected by BO phenomena. In the second subject new topological indices are devised to address the question of "which are the best buses to place distributed generation?". The combined use of two indices, is shown as a promising alternative for extracting grid’s significant features regarding robustness against BOs and distributed generation. For this purpose, a new index based on outage shift factors is used along with a previously defined electric centrality index. The third subject is on Static Robustness Analysis of electric networks, from a purely structural point of view. A pair of existing topological indices, (namely degree index and clustering coefficient), are combined to show how degradation of the network structure can be accelerated. Blackout simulations were carried out using the DC Power Flow Method and models of transmission networks from the USA and Europe.

The role of bifidobacteria in newborn health and the intestinal microbial balance

Gut microbial acquisition during the early stage of life is an extremely important event since it affects the health status of the host. In this contest the healthy properties of the genus Bifidobacterium have a central function in newborns. The aim of this thesis was to explore the dynamics of the gut microbial colonization in newborns and to suggest possible strategies to maintain or restore a correct balance of gut bacterial population in infants. The first step of this work was to review the most recent studies on the use of probiotics and prebiotics in infants. Secondly, in order to prevent or treat intestinal disorders that may affect newborns, the capability of selected Bifidobacterium strains to reduce the amount of Enterobacteriaceae and against the infant pathogen Streptococcus agalactiae was evaluated in vitro. Furthermore, the ability of several commercial fibers to stimulate selectively the growth of bifidobacterial strains was checked. Finally, the gut microbial composition in the early stage of life in response to the intrapartum antibiotic prophylaxis (IAP) against group B Streptococcus was studied using q-PCR, DGGE and next generation sequencing. The results globally showed that Bifidobacterium breve B632 strain is the best candidate for the use in a synbiotic product coupled to a mixture of two selected prebiotic fibers (galactooligosaccharides and fructooligosaccharides) for gastrointestinal disorders in infants. Moreover, the early gut microbial composition was affected by IAP treatment with infants showing lower counts of Bifidobacterium spp. and Bacteroides spp. coupled to a decrement of biodiversity of bacteria, compared to control infants. These studies have shown that IAP could affect the early intestinal balance in infants and they have paved the way to the definition of new strategies alternative to antibiotic treatment to control GBS infection in pregnant women.

Detrimental effects of exuberant and restrained immune responses against the central nervous system in the context of multiple sclerosis and glioblastoma multiforme

Glioblastoma multiforme (GBM) is the most common and most aggressive astrocytic tumor of the central nervous system (CNS) in adults. The standard treatment consisting of surgery, followed by a combinatorial radio- and chemotherapy, is only palliative and prolongs patient median survival to 12 to 15 months. The tumor subpopulation of stem cell-like glioma-initiating cells (GICs) shows resistance against radiation as well as chemotherapy, and has been suggested to be responsible for relapses of more aggressive tumors after therapy. The efficacy of immunotherapies, which exploit the immune system to specifically recognize and eliminate malignant cells, is limited due to strong immunosuppressive activities of the GICs and the generation of a specialized protective microenvironment. The molecular mechanisms underlying the therapy resistance of GICs are largely unknown. rnThe first aim of this study was to identify immune evasion mechanisms in GICs triggered by radiation. A model was used in which patient-derived GICs were treated in vitro with fractionated ionizing radiation (2.5 Gy in 7 consecutive passages) to select for a more radio-resistant phenotype. In the model cell line 1080, this selection process resulted in increased proliferative but diminished migratory capacities in comparison to untreated control GICs. Furthermore, radio-selected GICs downregulated various proteins involved in antigen processing and presentation, resulting in decreased expression of MHC class I molecules on the cellular surface and diminished recognition potential by cytotoxic CD8+ T cells. Thus, sub-lethal fractionated radiation can promote immune evasion and hamper the success of adjuvant immunotherapy. Among several immune-associated proteins, interferon-induced transmembrane protein 3 (IFITM3) was found to be upregulated in radio-selected GICs. While high expression of IFITM3 was associated with a worse overall survival of GBM patients (TCGA database) and increased proliferation and migration of differentiated glioma cell lines, a strong contribution of IFITM3 to proliferation in vitro as well as tumor growth and invasiveness in a xenograft model could not be observed. rnMultiple sclerosis (MS) is the most common autoimmune disease of the CNS in young adults of the Western World, which leads to progressive disability in genetically susceptible individuals, possibly triggered by environmental factors. It is assumed that self-reactive, myelin-specific T helper cell 1 (Th1) and Th17 cells, which have escaped the control mechanisms of the immune system, are critical in the pathogenesis of the human disease and its animal model experimental autoimmune encephalomyelitis (EAE). It was observed that in vitro differentiated interleukin 17 (IL-17) producing Th17 cells co-expressed the Th1-phenotypic cytokine Interferon-gamma (IFN-γ) in combination with the two respective lineage-associated transcription factors RORγt and T-bet after re-isolation from the CNS of diseased mice. Pathogenic molecular mechanisms that render a CD4+ T cell encephalitogenic have scarcely been investigated up to date. rnIn the second part of the thesis, whole transcriptional changes occurring in in vitro differentiated Th17 cells in the course of EAE were analyzed. Evaluation of signaling networks revealed an overrepresentation of genes involved in communication between the innate and adaptive immune system and metabolic alterations including cholesterol biosynthesis. The transcription factors Cebpa, Fos, Klf4, Nfatc1 and Spi1, associated with thymocyte development and naïve T cells were upregulated in encephalitogenic CNS-isolated CD4+ T cells, proposing a contribution to T cell plasticity. Correlation of the murine T-cell gene expression dataset to putative MS risk genes, which were selected based on their proximity (± 500 kb; ensembl database, release 75) to the MS risk single nucleotide polymorphisms (SNPs) proposed by the most recent multiple sclerosis GWAS in 2011, revealed that 67.3% of the MS risk genes were differentially expressed in EAE. Expression patterns of Bach2, Il2ra, Irf8, Mertk, Odf3b, Plek, Rgs1, Slc30a7, and Thada were confirmed in independent experiments, suggesting a contribution to T cell pathogenicity. Functional analysis of Nfatc1 revealed that Nfatc1-deficient CD4+ T cells were restrained in their ability to induce clinical signs of EAE. Nfatc1-deficiency allowed proper T cell activation, but diminished their potential to fully differentiate into Th17 cells and to express high amounts of lineage cytokines. As the inducible Nfatc1/αA transcript is distinct from the other family members, it could represent an interesting target for therapeutic intervention in MS.rn

Measurement of LSP-induced residual stresses and fatigue life on thin-walled aluminium alloys specimens

This thesis work encloses activities carried out in the Laser Center of the Polytechnic University of Madrid and the laboratories of the University of Bologna in Forlì. This thesis focuses on the superficial mechanical treatment for metallic materials called Laser Shock Peening (LSP). This process is a surface enhancement treatment which induces a significant layer of beneficial compressive residual stresses underneath the surface of metal components in order to improve the detrimental effects of the crack growth behavior rate in it. The innovation aspect of this work is the LSP application to specimens with extremely low thickness. In particular, after a bibliographic study and comparison with the main treatments used for the same purposes, this work analyzes the physics of the operation of a laser, its interaction with the surface of the material and the generation of the surface residual stresses which are fundamentals to obtain the LSP benefits. In particular this thesis work regards the application of this treatment to some Al2024-T351 specimens with low thickness. Among the improvements that can be obtained performing this operation, the most important in the aeronautic field is the fatigue life improvement of the treated components. As demonstrated in this work, a well-done LSP treatment can slow down the progress of the defects in the material that could lead to sudden failure of the structure. A part of this thesis is the simulation of this phenomenon using the program AFGROW, with which have been analyzed different geometric configurations of the treatment, verifying which was better for large panels of typical aeronautical interest. The core of the LSP process are the residual stresses that are induced on the material by the interaction with the laser light, these can be simulated with the finite elements but it is essential to verify and measure them experimentally. In the thesis are introduced the main methods for the detection of those stresses, they can be mechanical or by diffraction. In particular, will be described the principles and the detailed realization method of the Hole Drilling measure and an introduction of the X-ray Diffraction; then will be presented the results I obtained with both techniques. In addition to these two measurement techniques will also be introduced Neutron Diffraction method. The last part refers to the experimental tests of the fatigue life of the specimens, with a detailed description of the apparatus and the procedure used from the initial specimen preparation to the fatigue test with the press. Then the obtained results are exposed and discussed.

A new information fusion method for land-use classification using high resolution satellite imagery

Satellite image classification involves designing and developing efficient image classifiers. With satellite image data and image analysis methods multiplying rapidly, selecting the right mix of data sources and data analysis approaches has become critical to the generation of quality land-use maps. In this study, a new postprocessing information fusion algorithm for the extraction and representation of land-use information based on high-resolution satellite imagery is presented. This approach can produce land-use maps with sharp interregional boundaries and homogeneous regions. The proposed approach is conducted in five steps. First, a GIS layer - ATKIS data - was used to generate two coarse homogeneous regions, i.e. urban and rural areas. Second, a thematic (class) map was generated by use of a hybrid spectral classifier combining Gaussian Maximum Likelihood algorithm (GML) and ISODATA classifier. Third, a probabilistic relaxation algorithm was performed on the thematic map, resulting in a smoothed thematic map. Fourth, edge detection and edge thinning techniques were used to generate a contour map with pixel-width interclass boundaries. Fifth, the contour map was superimposed on the thematic map by use of a region-growing algorithm with the contour map and the smoothed thematic map as two constraints. For the operation of the proposed method, a software package is developed using programming language C. This software package comprises the GML algorithm, a probabilistic relaxation algorithm, TBL edge detector, an edge thresholding algorithm, a fast parallel thinning algorithm, and a region-growing information fusion algorithm. The county of Landau of the State Rheinland-Pfalz, Germany was selected as a test site. The high-resolution IRS-1C imagery was used as the principal input data.

Deep learning for computer vision: a comparison between convolutional neural networks and hierarchical temporal memories on object recognition tasks

In recent years, Deep Learning techniques have shown to perform well on a large variety of problems both in Computer Vision and Natural Language Processing, reaching and often surpassing the state of the art on many tasks. The rise of deep learning is also revolutionizing the entire field of Machine Learning and Pattern Recognition pushing forward the concepts of automatic feature extraction and unsupervised learning in general. However, despite the strong success both in science and business, deep learning has its own limitations. It is often questioned if such techniques are only some kind of brute-force statistical approaches and if they can only work in the context of High Performance Computing with tons of data. Another important question is whether they are really biologically inspired, as claimed in certain cases, and if they can scale well in terms of "intelligence". The dissertation is focused on trying to answer these key questions in the context of Computer Vision and, in particular, Object Recognition, a task that has been heavily revolutionized by recent advances in the field. Practically speaking, these answers are based on an exhaustive comparison between two, very different, deep learning techniques on the aforementioned task: Convolutional Neural Network (CNN) and Hierarchical Temporal memory (HTM). They stand for two different approaches and points of view within the big hat of deep learning and are the best choices to understand and point out strengths and weaknesses of each of them. CNN is considered one of the most classic and powerful supervised methods used today in machine learning and pattern recognition, especially in object recognition. CNNs are well received and accepted by the scientific community and are already deployed in large corporation like Google and Facebook for solving face recognition and image auto-tagging problems. HTM, on the other hand, is known as a new emerging paradigm and a new meanly-unsupervised method, that is more biologically inspired. It tries to gain more insights from the computational neuroscience community in order to incorporate concepts like time, context and attention during the learning process which are typical of the human brain. In the end, the thesis is supposed to prove that in certain cases, with a lower quantity of data, HTM can outperform CNN.

Considerations for prenatal counselling of patients with cardiac rhabdomyomas based on their cardiac and neurologic outcomes

Cardiac rhabdomyomas are benign cardiac tumours with few cardiac complications, but with a known association to tuberous sclerosis that affects the neurologic outcome of the patients. We have analysed the long-term cardiac and neurological outcomes of patients with cardiac rhabdomyomas in order to allow comprehensive prenatal counselling, basing our findings on the records of all patients seen prenatally and postnatally with an echocardiographic diagnosis of cardiac rhabdomyoma encountered from August, 1982, to September, 2007. We analysed factors such as the number and the location of the tumours to establish their association with a diagnosis of tuberous sclerosis, predicting the cardiac and neurologic outcomes for the patients.Cardiac complications include arrhythmias, obstruction of the ventricular outflow tracts, and secondary cardiogenic shock. Arrhythmias were encountered most often during the neonatal period, with supraventricular tachycardia being the commonest rhythm disturbance identified. No specific dimension or location of the cardiac rhabdomyomas predicted the disturbances of rhythm.The importance of the diagnosis of tuberous sclerosis is exemplified by the neurodevelopmental complications, with four-fifths of the patients showing epilepsy, and two-thirds having delayed development. The presence of multiple cardiac tumours suggested a higher risk of being affected by tuberous sclerosis. The tumours generally regress after birth, and cardiac-related problems are rare after the perinatal period. Tuberous sclerosis and the associated neurodevelopmental complications dominate the clinical picture, and should form an important aspect of the prenatal counselling of parents.

Role of complement and perspectives for intervention in ischemia-reperfusion damage

Reperfusion of an organ following prolonged ischemia instigates the pro-inflammatory and pro-coagulant response of ischemia / reperfusion (IR) injury. IR injury is a wide-spread pathology, observed in many clinically relevant situations, including myocardial infarction, stroke, organ transplantation, sepsis and shock, and cardiovascular surgery on cardiopulmonary bypass. Activation of the classical, alternative, and lectin complement pathways and the generation of the anaphylatoxins C3a and C5a lead to recruitment of polymorphonuclear leukocytes, generation of radical oxygen species, up-regulation of adhesion molecules on the endothelium and platelets, and induction of cytokine release. Generalized or pathway-specific complement inhibition using protein-based drugs or low-molecular-weight inhibitors has been shown to significantly reduce tissue injury and improve outcome in numerous in-vitro, ex-vivo, and in-vivo models. Despite the obvious benefits in experimental research, only few complement inhibitors, including C1-esterase inhibitor, anti-C5 antibody, and soluble complement receptor 1, have made it into clinical trials of IR injury. The results are mixed, and the next objectives should be to combine knowledge and experience obtained in the past from animal models and channel future work to translate this into clinical trials in surgical and interventional reperfusion therapy as well as organ transplantation.

Drug antigenicity, immunogenicity, and costimulatory signaling: evidence for formation of a functional antigen through immune cell metabolism

Recognition of drugs by immune cells is usually explained by the hapten model, which states that endogenous metabolites bind irreversibly to protein to stimulate immune cells. Synthetic metabolites interact directly with protein-generating antigenic determinants for T cells; however, experimental evidence relating intracellular metabolism in immune cells and the generation of physiologically relevant Ags to functional immune responses is lacking. The aim of this study was to develop an integrated approach using animal and human experimental systems to characterize sulfamethoxazole (SMX) metabolism-derived antigenic protein adduct formation in immune cells and define the relationship among adduct formation, cell death, costimulatory signaling, and stimulation of a T cell response. Formation of SMX-derived adducts in APCs was dose and time dependent, detectable at nontoxic concentrations, and dependent on drug-metabolizing enzyme activity. Adduct formation above a threshold induced necrotic cell death, dendritic cell costimulatory molecule expression, and cytokine secretion. APCs cultured with SMX for 16 h, the time needed for drug metabolism, stimulated T cells from sensitized mice and lymphocytes and T cell clones from allergic patients. Enzyme inhibition decreased SMX-derived protein adduct formation and the T cell response. Dendritic cells cultured with SMX and adoptively transferred to recipient mice initiated an immune response; however, T cells were stimulated with adducts derived from SMX metabolism in APCs, not the parent drug. This study shows that APCs metabolize SMX; subsequent protein binding generates a functional T cell Ag. Adduct formation above a threshold stimulates cell death, which provides a maturation signal for dendritic cells.

Increasing Utilization of US Electric Grids via Smart Technologies: Integration of Load Management, Real Time Pricing, Renewables, EVs and Smart Grid Sensors

Electric power grids throughout the world suffer from serious inefficiencies associated with under-utilization due to demand patterns, engineering design and load following approaches in use today. These grids consume much of the world’s energy and represent a large carbon footprint. From material utilization perspectives significant hardware is manufactured and installed for this infrastructure often to be used at less than 20-40% of its operational capacity for most of its lifetime. These inefficiencies lead engineers to require additional grid support and conventional generation capacity additions when renewable technologies (such as solar and wind) and electric vehicles are to be added to the utility demand/supply mix. Using actual data from the PJM [PJM 2009] the work shows that consumer load management, real time price signals, sensors and intelligent demand/supply control offer a compelling path forward to increase the efficient utilization and carbon footprint reduction of the world’s grids. Underutilization factors from many distribution companies indicate that distribution feeders are often operated at only 70-80% of their peak capacity for a few hours per year, and on average are loaded to less than 30-40% of their capability. By creating strong societal connections between consumers and energy providers technology can radically change this situation. Intelligent deployment of smart sensors, smart electric vehicles, consumer-based load management technology very high saturations of intermittent renewable energy supplies can be effectively controlled and dispatched to increase the levels of utilization of existing utility distribution, substation, transmission, and generation equipment. The strengthening of these technology, society and consumer relationships requires rapid dissemination of knowledge (real time prices, costs & benefit sharing, demand response requirements) in order to incentivize behaviors that can increase the effective use of technological equipment that represents one of the largest capital assets modern society has created.

When that tune runs through your head: A PET investigation of auditory imagery for familiar melodies

The present study used positron emission tomography (PET) to examine the cerebral activity pattern associated with auditory imagery forfamiliar tunes. Subjects either imagined the continuation of nonverbaltunes cued by their first few notes, listened to a short sequence of notesas a control task, or listened and then reimagined that short sequence. Subtraction of the activation in the control task from that in the real-tune imagery task revealed primarily right-sided activation in frontal and superior temporal regions, plus supplementary motor area(SMA). Isolating retrieval of the real tunes by subtracting activation in the reimagine task from that in the real-tune imagery task revealedactivation primarily in right frontal areas and right superior temporal gyrus. Subtraction of activation in the control condition from that in the reimagine condition, intended to capture imagery of unfamiliarsequences, revealed activation in SMA, plus some left frontal regions. We conclude that areas of right auditory association cortex, together with right and left frontal cortices, are implicated in imagery for familiartunes, in accord with previous behavioral, lesion and PET data. Retrieval from musical semantic memory is mediated by structures in the right frontal lobe, in contrast to results from previous studies implicating left frontal areas for all semantic retrieval. The SMA seems to be involved specifically in image generation, implicating a motor code in this process.